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Habib S. Team players in the pathogenesis of metabolic dysfunctions-associated steatotic liver disease: The basis of development of pharmacotherapy. World J Gastrointest Pathophysiol 2024; 15:93606. [DOI: 10.4291/wjgp.v15.i4.93606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 05/14/2024] [Accepted: 07/23/2024] [Indexed: 08/22/2024] Open
Abstract
Nutrient metabolism is regulated by several factors. Social determinants of health with or without genetics are the primary regulator of metabolism, and an unhealthy lifestyle affects all modulators and mediators, leading to the adaptation and finally to the exhaustion of cellular functions. Hepatic steatosis is defined by presence of fat in more than 5% of hepatocytes. In hepatocytes, fat is stored as triglycerides in lipid droplet. Hepatic steatosis results from a combination of multiple intracellular processes. In a healthy individual nutrient metabolism is regulated at several steps. It ranges from the selection of nutrients in a grocery store to the last step of consumption of ATP as an energy or as a building block of a cell as structural component. Several hormones, peptides, and genes have been described that participate in nutrient metabolism. Several enzymes participate in each nutrient metabolism as described above from ingestion to generation of ATP. As of now several publications have revealed very intricate regulation of nutrient metabolism, where most of the regulatory factors are tied to each other bidirectionally, making it difficult to comprehend chronological sequence of events. Insulin hormone is the primary regulator of all nutrients’ metabolism both in prandial and fasting states. Insulin exerts its effects directly and indirectly on enzymes involved in the three main cellular function processes; metabolic, inflammation and repair, and cell growth and regeneration. Final regulators that control the enzymatic functions through stimulation or suppression of a cell are nuclear receptors in especially farnesoid X receptor and peroxisome proliferator-activated receptor/RXR ligands, adiponectin, leptin, and adiponutrin. Insulin hormone has direct effect on these final modulators. Whereas blood glucose level, serum lipids, incretin hormones, bile acids in conjunction with microbiota are intermediary modulators which are controlled by lifestyle. The purpose of this review is to overview the key players in the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD) that help us understand the disease natural course, risk stratification, role of lifestyle and pharmacotherapy in each individual patient with MASLD to achieve personalized care and target the practice of precision medicine. PubMed and Google Scholar databases were used to identify publication related to metabolism of carbohydrate and fat in states of health and disease states; MASLD, cardiovascular disease and cancer. More than 1000 publications including original research and review papers were reviewed.
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Affiliation(s)
- Shahid Habib
- Department of Hepatology, Liver Institute PLLC, Tucson, AZ 85712, United States
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2
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Giraudi PJ, Pascut D, Banfi C, Ghilardi S, Tiribelli C, Bondesan A, Caroli D, Minocci A, Sartorio A. Serum proteome signatures associated with liver steatosis in adolescents with obesity. J Endocrinol Invest 2024:10.1007/s40618-024-02419-x. [PMID: 39017916 DOI: 10.1007/s40618-024-02419-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 06/19/2024] [Indexed: 07/18/2024]
Abstract
PURPOSE Childhood obesity, a pressing global health issue, significantly increases the risk of metabolic complications, including metabolic dysfunction associated with steatotic liver disease (MASLD). Accurate non-invasive tests for early detection and screening of steatosis are crucial. In this study, we explored the serum proteome, identifying proteins as potential biomarkers for inclusion in non-invasive steatosis diagnosis tests. METHODS Fifty-nine obese adolescents underwent ultrasonography to assess steatosis. Serum samples were collected and analyzed by targeted proteomics with the Proximity Extension Assay technology. Clinical and biochemical parameters were evaluated, and correlations among them, the individuated markers, and steatosis were performed. Receiver operating characteristic (ROC) curves were used to determine the steatosis diagnostic performance of the identified candidates, the fatty liver index (FLI), and their combination in a logistic regression model. RESULTS Significant differences were observed between subjects with and without steatosis in various clinical and biochemical parameters. Gender-related differences in the serum proteome were also noted. Five circulating proteins, including Cathepsin O (CTSO), Cadherin 2 (CDH2), and Prolyl endopeptidase (FAP), were identified as biomarkers for steatosis. CDH2, CTSO, Leukocyte Immunoglobulin Like Receptor A5 (LILRA5), BMI, waist circumference, HOMA-IR, and FLI, among others, significantly correlated with the steatosis degree. CDH2, FAP, and LDL combined in a logit model achieved a diagnostic performance with an AUC of 0.91 (95% CI 0.75-0.97, 100% sensitivity, 84% specificity). CONCLUSIONS CDH2 and FAP combined with other clinical parameters, represent useful tools for accurate diagnosis of fatty liver, emphasizing the importance of integrating novel markers into diagnostic algorithms for MASLD.
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Affiliation(s)
- P J Giraudi
- Metabolic Liver Disease Unit, Fondazione Italiana Fegato-ONLUS, Trieste, Italy.
| | - D Pascut
- Liver Cancer Unit, Fondazione Italiana Fegato-ONLUS, Trieste, Italy
| | - C Banfi
- Unit of Functional Proteomics, Metabolomics, and Network Analysis, Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - S Ghilardi
- Unit of Functional Proteomics, Metabolomics, and Network Analysis, Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - C Tiribelli
- Metabolic Liver Disease Unit, Fondazione Italiana Fegato-ONLUS, Trieste, Italy
- Liver Cancer Unit, Fondazione Italiana Fegato-ONLUS, Trieste, Italy
| | - A Bondesan
- Istituto Auxologico Italiano IRCCS, Experimental Laboratory for Auxo-endocrinological Research, Piancavallo-Verbania, Italy
| | - D Caroli
- Istituto Auxologico Italiano IRCCS, Experimental Laboratory for Auxo-endocrinological Research, Piancavallo-Verbania, Italy
| | - A Minocci
- Division of Metabolic Diseases, Istituto Auxologico Italiano IRCCS, Piancavallo-Verbania, Italy
| | - A Sartorio
- Istituto Auxologico Italiano IRCCS, Experimental Laboratory for Auxo-endocrinological Research, Piancavallo-Verbania, Italy
- Istituto Auxologico Italiano IRCCS, Experimental Laboratory for Auxo-endocrinological Research, Milan, Italy
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Venkatesh SS, Ganjgahi H, Palmer DS, Coley K, Linchangco GV, Hui Q, Wilson P, Ho YL, Cho K, Arumäe K, Wittemans LBL, Nellåker C, Vainik U, Sun YV, Holmes C, Lindgren CM, Nicholson G. Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records. Nat Commun 2024; 15:5801. [PMID: 38987242 PMCID: PMC11237142 DOI: 10.1038/s41467-024-49998-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 06/25/2024] [Indexed: 07/12/2024] Open
Abstract
Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.
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Affiliation(s)
- Samvida S Venkatesh
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Habib Ganjgahi
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Kayesha Coley
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Gregorio V Linchangco
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Peter Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kadri Arumäe
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
| | - Laura B L Wittemans
- Novo Nordisk Research Centre Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Christoffer Nellåker
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Uku Vainik
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
- Department of Neurology and Neurosurgery, Faculty of Medicine and Health Sciences, University of McGill, Montreal, Canada
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Chris Holmes
- Department of Statistics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, Oxford, UK
- The Alan Turing Institute, London, UK
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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Chen J, Hu J, Guo X, Yang Y, Qin D, Tang X, Huang Z, Wang F, Hu D, Peng D, Yu B. Apolipoprotein O modulates cholesterol metabolism via NRF2/CYB5R3 independent of LDL receptor. Cell Death Dis 2024; 15:389. [PMID: 38830896 PMCID: PMC11148037 DOI: 10.1038/s41419-024-06778-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 05/22/2024] [Accepted: 05/24/2024] [Indexed: 06/05/2024]
Abstract
Apolipoprotein O (APOO) plays a critical intracellular role in regulating lipid metabolism. Here, we investigated the roles of APOO in metabolism and atherogenesis in mice. Hepatic APOO expression was increased in response to hyperlipidemia but was inhibited after simvastatin treatment. Using a novel APOO global knockout (Apoo-/-) model, it was found that APOO depletion aggravated diet-induced obesity and elevated plasma cholesterol levels. Upon crossing with low-density lipoprotein receptor (LDLR) and apolipoprotein E (APOE) knockout hyperlipidemic mouse models, Apoo-/- Apoe-/- and Apoo-/- Ldlr-/- mice exhibited elevated plasma cholesterol levels, with more severe atherosclerotic lesions than littermate controls. This indicated the effects of APOO on cholesterol metabolism independent of LDLR and APOE. Moreover, APOO deficiency reduced cholesterol excretion through bile and feces while decreasing phospholipid unsaturation by inhibiting NRF2 and CYB5R3. Restoration of CYB5R3 expression in vivo by adeno-associated virus (AAV) injection reversed the reduced degree of phospholipid unsaturation while decreasing blood cholesterol levels. This represents the first in vivo experimental validation of the role of APOO in plasma cholesterol metabolism independent of LDLR and elucidates a previously unrecognized cholesterol metabolism pathway involving NRF2/CYB5R3. APOO may be a metabolic regulator of total-body cholesterol homeostasis and a target for atherosclerosis management. Apolipoprotein O (APOO) regulates plasma cholesterol levels and atherosclerosis through a pathway involving CYB5R3 that regulates biliary and fecal cholesterol excretion, independently of the LDL receptor. In addition, down-regulation of APOO may lead to impaired mitochondrial function, which in turn aggravates diet-induced obesity and fat accumulation.
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Affiliation(s)
- Jin Chen
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Jiarui Hu
- Department of Spine Surgery, The Second Xiangya Hospital, Central South University, NO.139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Xin Guo
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Yang Yang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Donglu Qin
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Xiaoyu Tang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Zhijie Huang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Fengjiao Wang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Die Hu
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Daoquan Peng
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Bilian Yu
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Research Institute of Blood Lipid and Atherosclerosis, Central South University, No.139 Middle Renmin Road, Changsha, 410011, Hunan, China.
- Hunan Key Laboratory of Cardiometabolic Medicine, No. 139 Middle Renmin Road, Changsha, 410011, Hunan, China.
- FuRong Laboratory, Changsha, 410078, Hunan, China.
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Habib S. Metabolic dysfunction-associated steatotic liver disease heterogeneity: Need of subtyping. World J Gastrointest Pathophysiol 2024; 15:92791. [PMID: 38845820 PMCID: PMC11151879 DOI: 10.4291/wjgp.v15.i2.92791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/04/2024] [Accepted: 04/24/2024] [Indexed: 05/23/2024] Open
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a widespread global disease with significant health burden. Unhealthy lifestyle, obesity, diabetes mellitus (DM), insulin resistance, and genetics have been implicated in the pathogenesis of MASLD. A significant degree of heterogeneity exists among each of above-mentioned risk factors. Heterogeneity of these risk factors translates into the heterogeneity of MASLD. On the other hand, MASLD can itself lead to insulin resistance and DM. Such heterogeneity makes it difficult to assess the natural course of an individual with MASLD in clinical practice. At present MASLD is considered as one disease despite the variability of etiopathogenic processes, and we lack the consensus definitions of unique subtypes of MASLD. In this review, pathogenic processes of MASLD are discussed and a need of subtyping is recommended.
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Affiliation(s)
- Shahid Habib
- Department of Hepatology, Liver Institute PLLC, Tucson, AZ 85716, United States
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MacCarthy G, Pazoki R. Using Machine Learning to Evaluate the Value of Genetic Liabilities in the Classification of Hypertension within the UK Biobank. J Clin Med 2024; 13:2955. [PMID: 38792496 PMCID: PMC11122671 DOI: 10.3390/jcm13102955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/01/2024] [Accepted: 05/07/2024] [Indexed: 05/26/2024] Open
Abstract
Background and Objective: Hypertension increases the risk of cardiovascular diseases (CVD) such as stroke, heart attack, heart failure, and kidney disease, contributing to global disease burden and premature mortality. Previous studies have utilized statistical and machine learning techniques to develop hypertension prediction models. Only a few have included genetic liabilities and evaluated their predictive values. This study aimed to develop an effective hypertension classification model and investigate the potential influence of genetic liability for multiple risk factors linked to CVD on hypertension risk using the random forest and the neural network. Materials and Methods: The study involved 244,718 European participants, who were divided into training and testing sets. Genetic liabilities were constructed using genetic variants associated with CVD risk factors obtained from genome-wide association studies (GWAS). Various combinations of machine learning models before and after feature selection were tested to develop the best classification model. The models were evaluated using area under the curve (AUC), calibration, and net reclassification improvement in the testing set. Results: The models without genetic liabilities achieved AUCs of 0.70 and 0.72 using the random forest and the neural network methods, respectively. Adding genetic liabilities improved the AUC for the random forest but not for the neural network. The best classification model was achieved when feature selection and classification were performed using random forest (AUC = 0.71, Spiegelhalter z score = 0.10, p-value = 0.92, calibration slope = 0.99). This model included genetic liabilities for total cholesterol and low-density lipoprotein (LDL). Conclusions: The study highlighted that incorporating genetic liabilities for lipids in a machine learning model may provide incremental value for hypertension classification beyond baseline characteristics.
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Affiliation(s)
- Gideon MacCarthy
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London UB8 3PH, UK
| | - Raha Pazoki
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London UB8 3PH, UK
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary’s Campus, Norfolk Place, Imperial College London, London W2 1PG, UK
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Zhou J, Zhu D, Xu Y, Chen C, Wang K. Genetically predicted gut microbiota mediate the association between plasma lipidomics and primary sclerosing cholangitis. BMC Gastroenterol 2024; 24:158. [PMID: 38720308 PMCID: PMC11080140 DOI: 10.1186/s12876-024-03246-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 04/29/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Primary sclerosing cholangitis (PSC) is a complex disease with pathogenic mechanisms that remain to be elucidated. Previous observational studies with small sample sizes have reported associations between PSC, dyslipidemia, and gut microbiota dysbiosis. However, the causality of these associations is uncertain, and there has been no systematic analysis to date. METHODS The datasets comprise data on PSC, 179 lipid species, and 412 gut microbiota species. PSC data (n = 14,890) were sourced from the International PSC Study Group, while the dataset pertaining to plasma lipidomics originated from a study involving 7174 Finnish individuals. Data on gut microbiota species were derived from the Dutch Microbiome Project study, which conducted a genome-wide association study involving 7738 participants. Furthermore, we employed a two-step Mendelian randomization (MR) analysis to quantify the proportion of the effect of gut microbiota-mediated lipidomics on PSC. RESULTS Following a rigorous screening process, our MR analysis revealed a causal relationship between higher levels of gene-predicted Phosphatidylcholine (O-16:1_18:1) (PC O-16:1_18:1) and an increased risk of developing PSC (inverse variance-weighted method, odds ratio (OR) 1.30, 95% confidence interval (CI) 1.03-1.63). There is insufficient evidence to suggest that gene-predicted PSC impacts the levels of PC O-16:1_18:1 (OR 1.01, 95% CI 0.98-1.05). When incorporating gut microbiota data into the analysis, we found that Eubacterium rectale-mediated genetic prediction explains 17.59% of the variance in PC O-16:1_18:1 levels. CONCLUSION Our study revealed a causal association between PC O-16:1_18:1 levels and PSC, with a minor portion of the effect mediated by Eubacterium rectale. This study aims to further explore the pathogenesis of PSC and identify promising therapeutic targets. For patients with PSC who lack effective treatment options, the results are encouraging.
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Affiliation(s)
- Jie Zhou
- Department of General Surgery, Wujin Hospital Affiliated with Jiangsu University, No. 2, Yongning North Road, Changzhou, 213003, Jiangsu Province, China
- Department of General Surgery, The Wujin Clinical college of Xuzhou Medical University, Changzhou, 213003, China
| | - Dagang Zhu
- Department of General Surgery, Wujin Hospital Affiliated with Jiangsu University, No. 2, Yongning North Road, Changzhou, 213003, Jiangsu Province, China.
- Department of General Surgery, The Wujin Clinical college of Xuzhou Medical University, Changzhou, 213003, China.
| | - Yixin Xu
- Department of General Surgery, Wujin Hospital Affiliated with Jiangsu University, No. 2, Yongning North Road, Changzhou, 213003, Jiangsu Province, China
- Department of General Surgery, The Wujin Clinical college of Xuzhou Medical University, Changzhou, 213003, China
| | - Chao Chen
- Department of General Surgery, Wujin Hospital Affiliated with Jiangsu University, No. 2, Yongning North Road, Changzhou, 213003, Jiangsu Province, China
- Department of General Surgery, The Wujin Clinical college of Xuzhou Medical University, Changzhou, 213003, China
| | - Kun Wang
- Department of General Surgery, Wujin Hospital Affiliated with Jiangsu University, No. 2, Yongning North Road, Changzhou, 213003, Jiangsu Province, China
- Department of General Surgery, The Wujin Clinical college of Xuzhou Medical University, Changzhou, 213003, China
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Zhong Y, Yang Y, Xu Y, Qian B, Huang S, Long Q, Qi Z, He X, Zhang Y, Li L, Hai W, Wang X, Zhao Q, Ye X. Design of a Zn-based nanozyme injectable multifunctional hydrogel with ROS scavenging activity for myocardial infarction therapy. Acta Biomater 2024; 177:62-76. [PMID: 38237713 DOI: 10.1016/j.actbio.2024.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 12/21/2023] [Accepted: 01/11/2024] [Indexed: 02/03/2024]
Abstract
The existing strategies for myocardial infarction therapy mainly focus on reinstating myocardial blood supply, often disregarding the intrinsic and intricate microenvironment created by elevated levels of reactive oxygen species (ROS) that accompanies myocardial infarction. This microenvironment entails cardiomyocytes apoptosis, substantial vascular cell death, excessive inflammatory infiltration and fibrosis. In such situation, the present study introduces a zinc-based nanozyme injectable multifunctional hydrogel, crafted from ZIF-8, to counteract ROS effects after myocardial infarction. The hydrogel exhibits both superoxide dismutase (SOD)-like and catalase (CAT)-like enzymatic activities, proficiently eliminating surplus ROS in the infarcted region and interrupting ROS-driven inflammatory cascades. Furthermore, the hydrogel's exceptional immunomodulatory ability spurs a notable transformation of macrophages into the M2 phenotype, effectively neutralizing inflammatory factors and indirectly fostering vascularization in the infarcted region. For high ROS and demanding for zinc of the infarcted microenvironment, the gradual release of zinc ions as the hydrogel degrades further enhances the bioactive and catalytic performance of the nanozymes, synergistically promoting cardiac function post myocardial infarction. In conclusion, this system of deploying catalytic nanomaterials within bioactive matrices for ROS-related ailment therapy not only establishes a robust foundation for biomedical material development, but also promises a holistic approach towards addressing myocardial infarction complexities. STATEMENT OF SIGNIFICANCE: Myocardial infarction remains the leading cause of death worldwide. However, the existing strategies for myocardial infarction therapy mainly focus on reinstating myocardial blood supply. These therapies often ignore the intrinsic and intricate microenvironment created by elevated levels of reactive oxygen species (ROS). Hence, we designed an injectable Zn-Based nanozyme hydrogel with ROS scavenging activity for myocardial infarction therapy. ALG-(ZIF-8) can significantly reduce ROS in the infarcted area and alleviate the ensuing pathological process. ALG-(ZIF-8) gradually releases zinc ions to participate in the repair process and improves cardiac function. Overall, this multifunctional hydrogel equipped with ZIF-8 makes full use of the characteristics of clearing ROS and slowly releasing zinc ions, and we are the first to test the therapeutic efficacy of Zinc-MOFs crosslinked-alginate hydrogel for myocardial infarction.
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Affiliation(s)
- Yiming Zhong
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Yi Yang
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Yuze Xu
- College of Chemistry and Materials Science, Shanghai Normal University, Shanghai, 200234, China
| | - Bei Qian
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Shixing Huang
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Qiang Long
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Zhaoxi Qi
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Xiaojun He
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Yecen Zhang
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Lihui Li
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Wangxi Hai
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Xinming Wang
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.
| | - Qiang Zhao
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.
| | - Xiaofeng Ye
- Department of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.
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Senftleber NK, Andersen MK, Jørsboe E, Stæger FF, Nøhr AK, Garcia-Erill G, Meisner J, Santander CG, Balboa RF, Gilly A, Bjerregaard P, Larsen CVL, Grarup N, Jørgensen ME, Zeggini E, Moltke I, Hansen T, Albrechtsen A. GWAS of lipids in Greenlanders finds association signals shared with Europeans and reveals an independent PCSK9 association signal. Eur J Hum Genet 2024; 32:215-223. [PMID: 37903942 PMCID: PMC10853193 DOI: 10.1038/s41431-023-01485-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 09/14/2023] [Accepted: 10/11/2023] [Indexed: 11/01/2023] Open
Abstract
Perturbation of lipid homoeostasis is a major risk factor for cardiovascular disease (CVD), the leading cause of death worldwide. We aimed to identify genetic variants affecting lipid levels, and thereby risk of CVD, in Greenlanders. Genome-wide association studies (GWAS) of six blood lipids, triglycerides, LDL-cholesterol, HDL-cholesterol, total cholesterol, as well as apolipoproteins A1 and B, were performed in up to 4473 Greenlanders. For genome-wide significant variants, we also tested for associations with additional traits, including CVD events. We identified 11 genome-wide significant loci associated with lipid traits. Most of these loci were already known in Europeans, however, we found a potential causal variant near PCSK9 (rs12117661), which was independent of the known PCSK9 loss-of-function variant (rs11491147). rs12117661 was associated with lower LDL-cholesterol (βSD(SE) = -0.22 (0.03), p = 6.5 × 10-12) and total cholesterol (-0.17 (0.03), p = 1.1 × 10-8) in the Greenlandic study population. Similar associations were observed in Europeans from the UK Biobank, where the variant was also associated with a lower risk of CVD outcomes. Moreover, rs12117661 was a top eQTL for PCSK9 across tissues in European data from the GTEx portal, and was located in a predicted regulatory element, supporting a possible causal impact on PCSK9 expression. Combined, the 11 GWAS signals explained up to 16.3% of the variance of the lipid traits. This suggests that the genetic architecture of lipid levels in Greenlanders is different from Europeans, with fewer variants explaining the variance.
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Affiliation(s)
- Ninna Karsbæk Senftleber
- Clinical Research, Copenhagen University Hospital-Steno Diabetes Center Copenhagen, Herlev, Denmark
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Mette K Andersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Emil Jørsboe
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Frederik Filip Stæger
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Anne Krogh Nøhr
- Center for Clinical Data Science, Department of Clinical Medicine, Aalborg University and Research, Education, and Innovation, Aalborg University Hospital, Aalborg, Denmark
| | - Genis Garcia-Erill
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jonas Meisner
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Cindy G Santander
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Renzo F Balboa
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Arthur Gilly
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Peter Bjerregaard
- Centre for Public Health in Greenland, National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | - Christina Viskum Lytken Larsen
- Centre for Public Health in Greenland, National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
- Greenland Center for Health Research, Institute for Health and Nature, University of Greenland, Nuuk, Greenland
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marit Eika Jørgensen
- Clinical Research, Copenhagen University Hospital-Steno Diabetes Center Copenhagen, Herlev, Denmark
- Centre for Public Health in Greenland, National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
- Steno Diabetes Center Greenland, Nuuk, Greenland
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Ida Moltke
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Anders Albrechtsen
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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10
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Putluru S, Pandi C, Kannan B, Priyadharsini VJ, Arumugam P. Increased Expression of LIPC Is Associated With the Clinicopathological Features and Development of Head and Neck Squamous Cell Carcinoma. Cureus 2023; 15:e50202. [PMID: 38192945 PMCID: PMC10772308 DOI: 10.7759/cureus.50202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 12/05/2023] [Indexed: 01/10/2024] Open
Abstract
Introduction Lipase C hepatic type (LIPC) is a member of the lipase family and plays a role in tumor development. However, its specific role in head and neck squamous cell carcinoma (HNSCC) is not well understood. Objective This study aims to investigate LIPC gene expression in HNSCC and elucidate its potential role in the context of the disease. Methods LIPC expression was analyzed using the Cancer Genome Atlas-HNSCC (TCGA-HNSCC) dataset. Real-time polymerase chain reaction (qPCR) was used to validate LIPC expression in oral squamous cell carcinoma (OSCC) tissue samples, which is the most common type of HNSCC. The LIPC was assessed to find out if there is a link with HNSCC clinicopathological features, prognosis, and tumor infiltration. Functional pathways associated with the LIPC network were also examined. Results LIPC expression was found to be elevated in both HNSCC and OSCC tissues. The heightened expression of LIPC correlated with various clinicopathological features and influenced the prognosis of HNSCC patients. The LIPC gene demonstrated connections with several oncogenic genes and proteins, participating in lipid catabolic processes and other pathways. These findings suggest that LIPC expression may play a role in the pathogenesis of HNSCC. Conclusion Our study affirms that LIPC expression is linked to the development of HNSCC, suggesting its potential utility as a biomarker or therapeutic target for the disease. However, further functional studies are imperative to validate and expand upon these findings.
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Affiliation(s)
- Sahith Putluru
- Molecular Biology Lab, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Chandra Pandi
- Centre for Cellular and Molecular Research, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Balachander Kannan
- Centre for Cellular and Molecular Research, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Vijayashree J Priyadharsini
- Centre for Cellular and Molecular Research, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Paramasivam Arumugam
- Centre for Cellular and Molecular Research, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
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11
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Junna N, Ruotsalainen S, Ripatti P, FinnGen, Ripatti S, Widén E. Novel Finnish-enriched variants causing severe hypercholesterolemia and their clinical impact on coronary artery disease. Atherosclerosis 2023; 386:117327. [PMID: 37848354 DOI: 10.1016/j.atherosclerosis.2023.117327] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 09/29/2023] [Accepted: 10/03/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND AND AIMS Severe hypercholesterolemia (LDL-cholesterol ≥ 5 mmol/l) is a major risk factor for coronary artery disease (CAD). The etiology incudes both genetic and nongenetic factors, but persons carrying mutations in known hypercholesterolemia-associated genes are at significantly higher CAD risk than non-carriers. Yet, a significant proportion of mutation carriers remains undetected while the assessment of genetic candidate variants in clinical practice is challenging. METHODS To address these challenges, we set out to test the utility of a practical approach to leverage data from a large reference cohort, the FinnGen Study encompassing 356,082 persons with extensive longitudinal health record information, to aid the clinical evaluation of single genetic candidate genes variants detected by exome sequence analysis in a target population of 351 persons with severe hypercholesterolemia. RESULTS We identified 23 rare missense mutations in known hypercholesterolemia genes, 3 of which were previously described mutations (LDLR Pro309Lysfs, LDLR Arg595Gln and APOB Arg3527Gln). Subsequent in silico and clinical assessment of the remaining 20 variants pinpointed two likely hypercholesterolemia-associated variants in LDLR (Arg574Leu and Glu626Lys) and one in LDLRAP1 (Arg151Trp). Heterozygous carriers of the novel LDLR and LDLRAP1 variants received statin treatment more often than non-carriers (OR 2.1, p = 1.8e-6 and OR 1.4, p = 0.001) and untreated carriers had higher risk for ischemic heart disease (OR 2.0, p = 0.03 and OR 1.8, p = 0.008). CONCLUSIONS Our data elucidate the wide spectrum of genetic variants impacting hypercholesterolemia and demonstrate the utility of a large reference population to assess the heterogeneous impact of candidate gene variants on cardiovascular disease risk.
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Affiliation(s)
- Nella Junna
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290, Helsinki, Finland
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290, Helsinki, Finland
| | - Pietari Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290, Helsinki, Finland
| | - FinnGen
- Institute for Molecular Medicine Finland, FIMM, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290, Helsinki, Finland; Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Clinicum, University of Helsinki, Helsinki, Finland
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290, Helsinki, Finland.
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12
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Lin S, Shen R, Huang J, Liu Y, Li H, Xu Q. Identification of genomic-wide genetic links between cutaneous melanoma and obesity-related physical traits via cFDR. Genes Genomics 2023; 45:1549-1562. [PMID: 37768517 DOI: 10.1007/s13258-023-01446-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023]
Abstract
BACKGROUND Both epidemiological and clinical studies have suggested the comorbidity between cutaneous melanoma (CM) and obesity-related physical traits. However, it remains unclear about their shared genetic architecture. OBJECTIVE To determine the shared genetic architecture between CM and obesity-related physical traits through conditional false discovery rate (cFDR) analysis. METHOD Quantile-quantile plots were firstly built to assess the pleiotropic enrichment of shared single nucleotide polymorphisms between CM and each trait. Then, cFDR and conjunctional cFDR (ccFDR) were used to identify the shared risk loci between CM and each trait. Moreover, the functional evaluation of shared risk genes was carried out through analyses of expression quantitative trait loci (eQTL), Kyoto Encyclopedia of Genes and Genomes and gene ontology, respectively. Finally, single-cell sequence analysis was performed to locate the expression of eQTL-mapped genes in tissues. RESULTS Successive pleiotropic enrichment was found between CM and 5 obesity-related traits or height. 24 shared risk loci were identified between CM and 13 traits except appendicular lean mass using ccFDR analysis, with 17 novel and 4 validated loci. The functions of ccFDR-identified and eQTL-mapped genes were revealed to be mainly involved in cellular senescence, proliferation, meiotic nuclear division, cell cycle, and the metabolism of lipid, cholesterol and glucose. Single-cell sequence analysis showed that keratinocytes contribute to the occurrence and aggressiveness of CM through secreting paracrine cytokines. CONCLUSION Our findings demonstrate the significant genetic correlation between CM and obesity-related physical traits, which may provide a novel genetical basis for the pathogenesis and treatment of CM.
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Affiliation(s)
- Shen Lin
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Runnan Shen
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Jingqian Huang
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yanhan Liu
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Hongpeng Li
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Qingfang Xu
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
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13
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Sun NA, Wang YU, Chu J, Han Q, Shen Y. Bayesian Approaches in Exploring Gene-environment and Gene-gene Interactions: A Comprehensive Review. Cancer Genomics Proteomics 2023; 20:669-678. [PMID: 38035701 PMCID: PMC10687732 DOI: 10.21873/cgp.20414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 12/02/2023] Open
Abstract
Rapid advancements in high-throughput biological techniques have facilitated the generation of high-dimensional omics datasets, which have provided a solid foundation for precision medicine and prognosis prediction. Nonetheless, the problem of missing heritability persists. To solve this problem, it is essential to explain the genetic structure of disease incidence risk and prognosis by incorporating interactions. The development of the Bayesian theory has provided new approaches for developing models for interaction identification and estimation. Several Bayesian models have been developed to improve the accuracy of model and identify the main effect, gene-environment (G×E) and gene-gene (G×G) interactions. Studies based on single-nucleotide polymorphisms (SNPs) are significant for the exploration of rare and common variants. Models based on the effect heredity principle and group-based models are relatively flexible and do not require strict constraints when dealing with the hierarchical structure between the main effect and interactions (M-I). These models have a good interpretability of biological mechanisms. Machine learning-based Bayesian approaches are highly competitive in improving prediction accuracy. These models provide insights into the mechanisms underlying the occurrence and progression of complex diseases, identify more reliable biomarkers, and develop higher predictive accuracy. In this paper, we provide a comprehensive review of these Bayesian approaches.
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Affiliation(s)
- N A Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, P.R. China
| | - Y U Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, P.R. China
| | - Jiadong Chu
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, P.R. China
| | - Qiang Han
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, P.R. China
| | - Yueping Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, P.R. China
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14
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Guo Y, Chung W, Shan Z, Zhu Z, Costenbader KH, Liang L. Genome-Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases. J Am Heart Assoc 2023; 12:e030211. [PMID: 37947095 PMCID: PMC10727280 DOI: 10.1161/jaha.123.030211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 10/16/2023] [Indexed: 11/12/2023]
Abstract
Background Patients with rheumatoid arthritis (RA) have a 2- to 10-fold increased risk of cardiovascular disease (CVD), but the biological mechanisms and existence of causality underlying such associations remain to be investigated. We aimed to investigate the genetic associations and underlying mechanisms between RA and CVD by leveraging large-scale genomic data and genetic cross-trait analytic approaches. Methods and Results Within UK Biobank data, we examined the genetic correlation, shared genetics, and potential causality between RA (Ncases=6754, Ncontrols=452 384) and cardiovascular diseases (CVD, Ncases=44 238, Ncontrols=414 900) using linkage disequilibrium score regression, cross-trait meta-analysis, and Mendelian randomization. We observed significant genetic correlations of RA with myocardial infarction (rg:0.40 [95% CI, 0.24-0.56), angina (rg:0.42 [95% CI, 0.28-0.56]), coronary heart diseases (rg:0.41 [95% CI, 0.27-0.55]), and CVD (rg:0.43 [95% CI, 0.29-0.57]) after correcting for multiple testing (P<0.05/5). When stratified by frequent use of analgesics, we found increased genetic correlation between RA and CVD among participants without aspirin usage (rg:0.54 [95% CI, 0.30-0.78] for angina; Pvalue=6.69×10-6) and among participants with paracetamol usage (rg:0.75 [95% CI, 0.20-1.29] for myocardial infarction; Pvalue=8.90×10-3), whereas others remained similar. Cross-trait meta-analysis identified 9 independent shared loci between RA and CVD, including PTPN22 at chr1p13.2, BCL2L11 at chr2q13, and CCR3 at chr3p21.31 (Psingle trait<1×10-3 and Pmeta<5×10-8), highlighting potential shared pathogenesis including accelerating atherosclerosis, upregulating oxidative stress, and vascular permeability. Finally, Mendelian randomization estimates showed limited evidence of causality between RA and CVD. Conclusions Our results supported shared genetic pathogenesis rather than causality in explaining the observed association between RA and CVD. The identified shared genetic factors provided insights into potential novel therapeutic target for RA-CVD comorbidities.
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Affiliation(s)
- Yanjun Guo
- Department of Occupational and Environmental Health, School of Public HealthTongji Medical College, Huazhong University of Science and TechnologyWuhanChina
- Program in Genetic Epidemiology and Statistical Genetics, Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMAUSA
- Division of Preventive MedicineBrigham and Women’s HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Wonil Chung
- Program in Genetic Epidemiology and Statistical Genetics, Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMAUSA
- Department of Statistics and Actuarial ScienceSoongsil UniversitySeoulKorea
| | - Zhilei Shan
- Department of NutritionHarvard T.H. Chan School of Public HealthBostonMA
| | - Zhaozhong Zhu
- Program in Genetic Epidemiology and Statistical Genetics, Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMAUSA
| | - Karen H. Costenbader
- Division of Preventive MedicineBrigham and Women’s HospitalBostonMA
- Division of Rheumatology, Inflammation and Immunity, Department of MedicineBrigham and Women’s HospitalBostonMA
| | - Liming Liang
- Program in Genetic Epidemiology and Statistical Genetics, Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMAUSA
- Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonMA
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15
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Staley JR, Giannakopoulou O, Holdsworth G, Armstrong M. Genetic data do not provide evidence that lower sclerostin is associated with increased risk of atherosclerosis: comment on the article by Zheng et al. Arthritis Rheumatol 2023. [PMID: 37942677 DOI: 10.1002/art.42751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 10/30/2023] [Indexed: 11/10/2023]
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16
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Ottensmann L, Tabassum R, Ruotsalainen SE, Gerl MJ, Klose C, Widén E, Simons K, Ripatti S, Pirinen M. Genome-wide association analysis of plasma lipidome identifies 495 genetic associations. Nat Commun 2023; 14:6934. [PMID: 37907536 PMCID: PMC10618167 DOI: 10.1038/s41467-023-42532-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 10/13/2023] [Indexed: 11/02/2023] Open
Abstract
The human plasma lipidome captures risk for cardiometabolic diseases. To discover new lipid-associated variants and understand the link between lipid species and cardiometabolic disorders, we perform univariate and multivariate genome-wide analyses of 179 lipid species in 7174 Finnish individuals. We fine-map the associated loci, prioritize genes, and examine their disease links in 377,277 FinnGen participants. We identify 495 genome-trait associations in 56 genetic loci including 8 novel loci, with a considerable boost provided by the multivariate analysis. For 26 loci, fine-mapping identifies variants with a high causal probability, including 14 coding variants indicating likely causal genes. A phenome-wide analysis across 953 disease endpoints reveals disease associations for 40 lipid loci. For 11 coronary artery disease risk variants, we detect strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and lipid species beyond the standard lipids.
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Affiliation(s)
- Linda Ottensmann
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Rubina Tabassum
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | | | - Elisabeth Widén
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Samuli Ripatti
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
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17
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Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YDI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SL, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJ, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O'Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WHH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, Peloso GM. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study. Am J Hum Genet 2023; 110:1704-1717. [PMID: 37802043 PMCID: PMC10577076 DOI: 10.1016/j.ajhg.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 10/08/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.
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Affiliation(s)
- Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jacob A Holdcraft
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donna K Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, SC, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian E Cade
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jenna C Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Susan K Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | | | - Richard A Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA; Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hildalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon Lr Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Tanika N Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Changwei Li
- Tulane University Translational Science Institute, New Orleans, LA, USA; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Don Lloyd-Jone
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | - Michael C Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Lisa W Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L Minster
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA, USA; Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Take Naseri
- Naseri & Associates Public Health Consultancy Firm and Family Health Clinic, Apia, Samoa; International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | - Wayne H-H Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute (NHRI), Miaoli County, Taiwan
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama, Birmingham, AL, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
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18
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Naber A, Demus D, Slieker R, Nicolardi S, Beulens JWJ, Elders PJM, Lieverse AG, Sijbrands EJG, 't Hart LM, Wuhrer M, van Hoek M. Apolipoprotein-CIII O-Glycosylation, a Link between GALNT2 and Plasma Lipids. Int J Mol Sci 2023; 24:14844. [PMID: 37834292 PMCID: PMC10573541 DOI: 10.3390/ijms241914844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/29/2023] [Accepted: 09/30/2023] [Indexed: 10/15/2023] Open
Abstract
Apolipoprotein-CIII (apo-CIII) is involved in triglyceride-rich lipoprotein metabolism and linked to beta-cell damage, insulin resistance, and cardiovascular disease. Apo-CIII exists in four main proteoforms: non-glycosylated (apo-CIII0a), and glycosylated apo-CIII with zero, one, or two sialic acids (apo-CIII0c, apo-CIII1 and apo-CIII2). Our objective is to determine how apo-CIII glycosylation affects lipid traits and type 2 diabetes prevalence, and to investigate the genetic basis of these relations with a genome-wide association study (GWAS) on apo-CIII glycosylation. We conducted GWAS on the four apo-CIII proteoforms in the DiaGene study in people with and without type 2 diabetes (n = 2318). We investigated the relations of the identified genetic loci and apo-CIII glycosylation with lipids and type 2 diabetes. The associations of the genetic variants with lipids were replicated in the Diabetes Care System (n = 5409). Rs4846913-A, in the GALNT2-gene, was associated with decreased apo-CIII0a. This variant was associated with increased high-density lipoprotein cholesterol and decreased triglycerides, while high apo-CIII0a was associated with raised high-density lipoprotein-cholesterol and triglycerides. Rs67086575-G, located in the IFT172-gene, was associated with decreased apo-CIII2 and with hypertriglyceridemia. In line, apo-CIII2 was associated with low triglycerides. On a genome-wide scale, we confirmed that the GALNT2-gene plays a major role i O-glycosylation of apolipoprotein-CIII, with subsequent associations with lipid parameters. We newly identified the IFT172/NRBP1 region, in the literature previously associated with hypertriglyceridemia, as involved in apolipoprotein-CIII sialylation and hypertriglyceridemia. These results link genomics, glycosylation, and lipid metabolism, and represent a key step towards unravelling the importance of O-glycosylation in health and disease.
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Affiliation(s)
- Annemieke Naber
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Daniel Demus
- Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Roderick Slieker
- Department of Cell and Chemical Biology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, Location Vrije Universiteit Amsterdam, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Simone Nicolardi
- Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Joline W J Beulens
- Department of Epidemiology and Data Science, Amsterdam UMC, Location Vrije Universiteit Amsterdam, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam Cardiovascular Sciences, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands
| | - Petra J M Elders
- Department of General Practice, Amsterdam Public Health Institute, Amsterdam UMC, Location VUmc, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Aloysius G Lieverse
- Department of Internal Medicine, Maxima Medical Center, P.O. Box 90052, 5600 PD Eindhoven, The Netherlands
| | - Eric J G Sijbrands
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Leen M 't Hart
- Department of Cell and Chemical Biology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, Location Vrije Universiteit Amsterdam, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam Cardiovascular Sciences, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Department of Biomedical Data Science, Section Molecular Epidemiology, Leiden University Medical Center, Postal Zone S5-P, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Mandy van Hoek
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
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19
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Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North K, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.10.555215. [PMID: 37745480 PMCID: PMC10515765 DOI: 10.1101/2023.09.10.555215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
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Affiliation(s)
- Min-Zhi Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | - Sheila M. Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Xihao Li
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Erin Buth
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Fei Fei Wang
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Regina Manansala
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO) WHO Collaborating Centre, University of Antwerp, Antwerp, BE
| | | | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130024, China
| | - Linda M. Polfus
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, 90033, USA
| | - Shabnam Salimi
- Department of Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Lisa R. Yanek
- Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, 1830 E Monument St Rm 8024, Baltimore, MD, 21287, USA
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, 200 Jeanette Lancaster Way, Charlottesville, VA, 22903, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA, 90502, USA
| | - Braxton D. Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Joshua P. Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98101, USA
| | - Katherine A. Pratte
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Edwin K. Silverman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kari North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rasika A. Mathias
- Department of Medicine, Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Cir JHAAC Room 3B53, Baltimore, MD, 21287, USA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - Biqi Wang
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Arnita F. Norwood
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, H3A 1G1, Canada
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Emelia J. Benjamin
- Department of Medicine, Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, 01702, USA
| | - Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98105, USA
| | - Russell P. Bowler
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Paul L. Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
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20
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Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YDI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SLR, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJF, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O’Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WHH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, Peloso GM. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291966. [PMID: 37425772 PMCID: PMC10327287 DOI: 10.1101/2023.06.28.23291966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.
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Affiliation(s)
- Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology & Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jacob A. Holdcraft
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donna K. Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA
- Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, SC, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian E. Cade
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jenna C. Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Susan K. Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James S. Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health at Houston, Houston, TX, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | | | - Richard A. Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hildalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon LR. Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Tanika N. Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G. Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Don Lloyd-Jone
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth JF. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | - Michael C. Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Lisa W. Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A. Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L. Minster
- Department of Human Genetics and Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E. Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne M. Murabito
- Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | | | - Jeffrey R. O’Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Michael H. Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | | | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama, Birmingham, AL, USA
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R. Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | | | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
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21
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Wei Q, Chen L, Zhou Y, Wang H. An adaptive test based on principal components for detecting multiple phenotype associations using GWAS summary data. Genetica 2023; 151:97-104. [PMID: 36656460 DOI: 10.1007/s10709-023-00179-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 01/11/2023] [Indexed: 01/20/2023]
Abstract
Extensive evidence from genome-wide association studies (GWAS) has shown that jointly analyzing multiple phenotypes can improve the power of the association test compared to the traditional single variant versus single trait approach. Here we propose an adaptive test based on principal components (ATPC) that is powerful and efficient for discovering the association between a single variant and multiple traits. Our method only needs GWAS summary statistics that are often available. We first estimate the trait correlation matrix by LD score regression. Then, based on the correlation matrix, we construct a series of test statistics that contain different numbers of principal components. The ultimate test statistic combines the P values of these principal component-based statistics by using the aggregated Cauchy association test. The analytical P-value of the test statistic can be computed quickly without the permutation process, which is the notable feature of our proposed method. The extensive simulation studies demonstrate that ATPC can control the type I error rates and have powerful and robust performance compared to several existing tests in a wide range of simulation settings. The analysis of the lipids GWAS summary data from the Global Lipids Genetics Consortium shows that ATPC identifies 230 new SNPs that are missed by the original single trait association analysis. By searching the GWAS Catalog, some SNPs and mapped genes identified by ATPC are reported to be associated with lipid traits. Through further analysis for GWAS results, we also find some Gene Ontology terms and biological pathways related to lipids.
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Affiliation(s)
- Qianran Wei
- Department of Statistics, School of Mathematical Sciences, Heilongjiang University, Harbin, 150080, China
| | - Lili Chen
- Department of Statistics, School of Mathematical Sciences, Heilongjiang University, Harbin, 150080, China.
| | - Yajing Zhou
- Department of Statistics, School of Mathematical Sciences, Heilongjiang University, Harbin, 150080, China
| | - Huiyi Wang
- Department of Statistics, School of Mathematical Sciences, Heilongjiang University, Harbin, 150080, China
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22
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Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods. Sci Rep 2023; 13:3078. [PMID: 36813803 PMCID: PMC9947228 DOI: 10.1038/s41598-023-30168-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 02/16/2023] [Indexed: 02/24/2023] Open
Abstract
Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30-45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value < 0.01) lipidome-genotype relations. Genotype biclusters in these 93 relations contained 5977 SNPs across 3164 genes. Twenty nine of the 93 relations contained genotype biclusters with more than 50% unique SNPs and participants, thus representing most distinct subgroups. We identified 30 significantly enriched biological processes among the SNPs involved in 21 of these 29 most distinct genotype-lipidome subgroups through which the identified genetic variants can influence and regulate plasma lipid related metabolism and profiles. This study identified 29 distinct genotype-lipidome subgroups in the studied Finnish population that may have distinct disease trajectories and therefore could be useful in precision medicine research.
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23
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Helkkula P, Hassan S, Saarentaus E, Vartiainen E, Ruotsalainen S, Leinonen JT, Palotie A, Karjalainen J, Kurki M, Ripatti S, Tukiainen T. Genome-wide association study of varicose veins identifies a protective missense variant in GJD3 enriched in the Finnish population. Commun Biol 2023; 6:71. [PMID: 36653477 PMCID: PMC9849365 DOI: 10.1038/s42003-022-04285-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 11/21/2022] [Indexed: 01/19/2023] Open
Abstract
Varicose veins is the most common manifestation of chronic venous disease that displays female-biased incidence. To identify protein-inactivating variants that could guide identification of drug target genes for varicose veins and genetic evidence for the disease prevalence difference between the sexes, we conducted a genome-wide association study of varicose veins in Finns using the FinnGen dataset with 17,027 cases and 190,028 controls. We identified 50 associated genetic loci (P < 5.0 × 10-8) of which 29 were novel including one near ERG with female-specificity (rs2836405-G, OR[95% CI] = 1.09[1.05-1.13], P = 3.1 × 10-8). These also include two X-chromosomal (ARHGAP6 and SRPX) and two autosomal novel loci (TGFB2 and GJD3) with protein-coding lead variants enriched above 56-fold in Finns over non-Finnish non-Estonian Europeans. A low-frequency missense variant in GJD3 (p.Pro59Thr) is exclusively associated with a lower risk for varicose veins (OR = 0.62 [0.55-0.70], P = 1.0 × 10-14) in a phenome-wide scan of the FinnGen data. The absence of observed pleiotropy and its membership of the connexin gene family underlines GJD3 as a potential connexin-modulating therapeutic strategy for varicose veins. Our results provide insights into varicose veins etiopathology and highlight the power of isolated populations, including Finns, to discover genetic variants that inform therapeutic development.
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Grants
- MC_PC_17228 Medical Research Council
- Academy of Finland (Suomen Akatemia)
- Sydäntutkimussäätiö (Finnish Foundation for Cardiovascular Research)
- Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), Sigrid Juselius Foundation (S.Ri. and T.T.), University of Helsinki HiLIFE Fellow and Grand Challenge grants (S.Ri.), University of Helsinki three-year research project grant (T.T.), FIMM-EMBL PhD program doctoral funding (S.H.), Nylands Nation, University of Helsinki (P.H.) The FinnGen project is funded by two grants from Business Finland (HUS 4685/31/2016 and UH 4386/31/2016) and the following industry partners: AbbVie Inc., AstraZeneca UK Ltd, Biogen MA Inc., Bristol Myers Squibb (and Celgene Corporation & Celgene International II Sàrl), Genentech Inc., Merck Sharp & Dohme Corp, Pfizer Inc., GlaxoSmithKline Intellectual Property Development Ltd., Sanofi US Services Inc., Maze Therapeutics Inc., Janssen Biotech Inc, Novartis AG, and Boehringer Ingelheim. Following biobanks are acknowledged for delivering biobank samples to FinnGen: Auria Biobank (www.auria.fi/biopankki), THL Biobank (www.thl.fi/biobank), Helsinki Biobank (www.helsinginbiopankki.fi), Biobank Borealis of Northern Finland (https://www.ppshp.fi/Tutkimus-ja-opetus/Biopankki/Pages/Biobank-Borealis-briefly-in-English.aspx), Finnish Clinical Biobank Tampere (www.tays.fi/en-US/Research_and_development/Finnish_Clinical_Biobank_Tampere), Biobank of Eastern Finland (www.ita-suomenbiopankki.fi/en), Central Finland Biobank (www.ksshp.fi/fi-FI/Potilaalle/Biopankki), Finnish Red Cross Blood Service Biobank (www.veripalvelu.fi/verenluovutus/biopankkitoiminta) and Terveystalo Biobank (www.terveystalo.com/fi/Yritystietoa/Terveystalo-Biopankki/Biopankki/).
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Affiliation(s)
- Pyry Helkkula
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Shabbeer Hassan
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Elmo Saarentaus
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Emilia Vartiainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jaakko T Leinonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Mitja Kurki
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
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24
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Venkatesh SS, Ganjgahi H, Palmer DS, Coley K, Wittemans LBL, Nellaker C, Holmes C, Lindgren CM, Nicholson G. The genetic architecture of changes in adiposity during adulthood. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.09.23284364. [PMID: 36711652 PMCID: PMC9882550 DOI: 10.1101/2023.01.09.23284364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 1.5 million primary-care health records in over 177,000 individuals in UK Biobank to study the genetic architecture of weight-change. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (a missense variant in APOE). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI, and higher in women than in men. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology driving quantitative trait values in adulthood.
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Affiliation(s)
- Samvida S. Venkatesh
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, UK
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
| | | | - Duncan S. Palmer
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
- Nuffield Department of Women’s and Reproductive Health, Medical Sciences Division, University of Oxford, UK
| | - Kayesha Coley
- Department of Population Health Sciences, University of Leicester, UK
| | - Laura B. L. Wittemans
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
- Nuffield Department of Women’s and Reproductive Health, Medical Sciences Division, University of Oxford, UK
| | - Christoffer Nellaker
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
- Nuffield Department of Women’s and Reproductive Health, Medical Sciences Division, University of Oxford, UK
| | - Chris Holmes
- Department of Statistics, University of Oxford, UK
- Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, UK
- The Alan Turing Institute, London, UK
| | - Cecilia M. Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, UK
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
- Nuffield Department of Women’s and Reproductive Health, Medical Sciences Division, University of Oxford, UK
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
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25
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Kurki MI, Karjalainen J, Palta P, Sipilä TP, Kristiansson K, Donner KM, Reeve MP, Laivuori H, Aavikko M, Kaunisto MA, Loukola A, Lahtela E, Mattsson H, Laiho P, Della Briotta Parolo P, Lehisto AA, Kanai M, Mars N, Rämö J, Kiiskinen T, Heyne HO, Veerapen K, Rüeger S, Lemmelä S, Zhou W, Ruotsalainen S, Pärn K, Hiekkalinna T, Koskelainen S, Paajanen T, Llorens V, Gracia-Tabuenca J, Siirtola H, Reis K, Elnahas AG, Sun B, Foley CN, Aalto-Setälä K, Alasoo K, Arvas M, Auro K, Biswas S, Bizaki-Vallaskangas A, Carpen O, Chen CY, Dada OA, Ding Z, Ehm MG, Eklund K, Färkkilä M, Finucane H, Ganna A, Ghazal A, Graham RR, Green EM, Hakanen A, Hautalahti M, Hedman ÅK, Hiltunen M, Hinttala R, Hovatta I, Hu X, Huertas-Vazquez A, Huilaja L, Hunkapiller J, Jacob H, Jensen JN, Joensuu H, John S, Julkunen V, Jung M, Junttila J, Kaarniranta K, Kähönen M, Kajanne R, Kallio L, Kälviäinen R, Kaprio J, Kerimov N, Kettunen J, Kilpeläinen E, Kilpi T, Klinger K, Kosma VM, Kuopio T, Kurra V, Laisk T, Laukkanen J, Lawless N, Liu A, Longerich S, Mägi R, Mäkelä J, Mäkitie A, Malarstig A, Mannermaa A, Maranville J, Matakidou A, Meretoja T, Mozaffari SV, Niemi MEK, Niemi M, Niiranen T, O Donnell CJ, Obeidat ME, Okafo G, Ollila HM, Palomäki A, Palotie T, Partanen J, Paul DS, Pelkonen M, Pendergrass RK, Petrovski S, Pitkäranta A, Platt A, Pulford D, Punkka E, Pussinen P, Raghavan N, Rahimov F, Rajpal D, Renaud NA, Riley-Gillis B, Rodosthenous R, Saarentaus E, Salminen A, Salminen E, Salomaa V, Schleutker J, Serpi R, Shen HY, Siegel R, Silander K, Siltanen S, Soini S, Soininen H, Sul JH, Tachmazidou I, Tasanen K, Tienari P, Toppila-Salmi S, Tukiainen T, Tuomi T, Turunen JA, Ulirsch JC, Vaura F, Virolainen P, Waring J, Waterworth D, Yang R, Nelis M, Reigo A, Metspalu A, Milani L, Esko T, Fox C, Havulinna AS, Perola M, Ripatti S, Jalanko A, Laitinen T, Mäkelä TP, Plenge R, McCarthy M, Runz H, Daly MJ, Palotie A. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 2023; 613:508-518. [PMID: 36653562 PMCID: PMC9849126 DOI: 10.1038/s41586-022-05473-8] [Citation(s) in RCA: 873] [Impact Index Per Article: 873.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 10/21/2022] [Indexed: 01/20/2023]
Abstract
Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10-11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.
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Affiliation(s)
- Mitja I Kurki
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Priit Palta
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Timo P Sipilä
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | - Kati M Donner
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Mary P Reeve
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Department of Obstetrics and Gynecology, Tampere University Hospital, Tampere, Finland.,Faculty of Medicine and Health Technology, Center for Child, Adolescent and Maternal Health, University of Tampere, Tampere, Finland
| | - Mervi Aavikko
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Mari A Kaunisto
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Anu Loukola
- Helsinki Biobank, University of Helsinki and Hospital District of Helsinki and Uusimaa, Helsinki, Finland
| | - Elisa Lahtela
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Hannele Mattsson
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Päivi Laiho
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Pietro Della Briotta Parolo
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Arto A Lehisto
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Masahiro Kanai
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Nina Mars
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Joel Rämö
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tuomo Kiiskinen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Henrike O Heyne
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Digital Health Center, Hasso Plattner Institute for Digital Engineering, University of Potsdam Potsdam, Potsdam, Germany.,Hasso Plattner Institute for Digital Health at Mount Sinai, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kumar Veerapen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Sina Rüeger
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Susanna Lemmelä
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Kalle Pärn
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tero Hiekkalinna
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Sami Koskelainen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Teemu Paajanen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Vincent Llorens
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Javier Gracia-Tabuenca
- TAUCHI Research Center, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Harri Siirtola
- TAUCHI Research Center, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Kadri Reis
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Benjamin Sun
- Translational Biology, Research and Development, Biogen, Cambridge, MA, USA.,BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Christopher N Foley
- Optima Partners, Edinburgh, UK.,MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | | | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Mikko Arvas
- Finnish Red Cross Blood Service, Helsinki, Finland
| | | | | | | | - Olli Carpen
- Helsinki Biobank, University of Helsinki and Hospital District of Helsinki and Uusimaa, Helsinki, Finland
| | | | - Oluwaseun A Dada
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Zhihao Ding
- Boehringer Ingelheim, Ingelheim am Rhein, Germany
| | | | - Kari Eklund
- Division of Rheumatology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland.,Orton Orthopedic Hospital, Helsinki, Finland
| | - Martti Färkkilä
- Abdominal Center, Helsinki University Hospital, Helsinki University, Helsinki, Finland
| | - Hilary Finucane
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Andrea Ganna
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Awaisa Ghazal
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | | | - Antti Hakanen
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | | | - Åsa K Hedman
- Pfizer, New York, NY, USA.,Department of Medicine, Karolinska Institute, Solna, Sweden
| | - Mikko Hiltunen
- Clinical Biobank Tampere, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Reetta Hinttala
- Medical Research Center Oulu and PEDEGO Research Unit, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Oulu University Hospital, Oulu, Finland
| | - Iiris Hovatta
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | | | - Laura Huilaja
- PEDEGO Research Unit, University of Oulu, Oulu, Finland.,Department of Dermatology and Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | | | | | | | - Heikki Joensuu
- Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | | | - Valtteri Julkunen
- Neuro Center, Neurology, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland
| | - Marc Jung
- Boehringer Ingelheim, Ingelheim am Rhein, Germany
| | - Juhani Junttila
- Northern Finland Biobank Borealis, University of Oulu, Northern Ostrobothnia Hospital District, Oulu, Finland
| | - Kai Kaarniranta
- Department of Ophthalmology, Kuopio University Hospital, Kuopio, Finland.,Department of Ophthalmology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Mika Kähönen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Risto Kajanne
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Lila Kallio
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | - Reetta Kälviäinen
- Epilepsy Center, Kuopio University Hospital, Kuopio, Finland.,Department of Neurology, University of Eastern Finland, Kuopio, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | | | - Nurlan Kerimov
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Johannes Kettunen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Computational Medicine, Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Elina Kilpeläinen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Terhi Kilpi
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | | | - Veli-Matti Kosma
- Biobank of Eastern Finland, University of Eastern Finland, Kuopio, Finland.,Kuopio University Hospital, Kuopio, Finland
| | - Teijo Kuopio
- Central Finland Biobank, Central Finland Health Care District, Jyväskylä, Finland
| | - Venla Kurra
- Department of Clinical Genetics, Tampere University Hospital, Tampere, Finland.,Department of Clinical Genetics, Faculty of Medicine and Health Technology, Tampere, Finland
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jari Laukkanen
- Central Finland Biobank, Central Finland Health Care District, Jyväskylä, Finland.,Department of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | | | - Aoxing Liu
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Antti Mäkitie
- Department of Otorhinolaryngology-Head and Neck Surgery, University of Helsinki, Helsinki, Finland.,Helsinki University Hospital, Helsinki, Finland
| | - Anders Malarstig
- Pfizer, Cambridge, MA, USA.,Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna, Sweden
| | - Arto Mannermaa
- Biobank of Eastern Finland, University of Eastern Finland, Kuopio, Finland.,Kuopio University Hospital, Kuopio, Finland
| | | | - Athena Matakidou
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Tuomo Meretoja
- Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | | | - Mari E K Niemi
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Marianna Niemi
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,TAUCHI Research Center & Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Teemu Niiranen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,Turku University Hospital and University of Turku, Turku, Finland
| | | | - Ma En Obeidat
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - George Okafo
- Boehringer Ingelheim, Ingelheim am Rhein, Germany
| | - Hanna M Ollila
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Antti Palomäki
- Turku University Hospital and University of Turku, Turku, Finland
| | - Tuula Palotie
- Department of Oral and Maxillofacial Diseases, Helsinki University Hospital, Helsinki, Finland.,Department of Oral and Maxillofacial Diseases, University of Helsinki, Helsinki, Finland
| | - Jukka Partanen
- Finnish Red Cross Blood Service, Helsinki, Finland.,Finnish Hematological Biobank, Helsinki, Finland
| | - Dirk S Paul
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Margit Pelkonen
- Department of Pulmonary Diseases, Kuopio University Hospital, Kuopio, Finland
| | | | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Anne Pitkäranta
- Department of Otorhinolaryngology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Adam Platt
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | | | - Eero Punkka
- Helsinki Biobank, University of Helsinki and Hospital District of Helsinki and Uusimaa, Helsinki, Finland
| | - Pirkko Pussinen
- Department of Oral and Maxillofacial Diseases, University of Helsinki, Helsinki, Finland
| | | | | | - Deepak Rajpal
- Translational Sciences, Sanofi R&D, Framingham, MA, USA
| | - Nicole A Renaud
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | | | - Rodosthenis Rodosthenous
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Elmo Saarentaus
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Aino Salminen
- Department of Oral and Maxillofacial Diseases, University of Helsinki, Helsinki, Finland
| | - Eveliina Salminen
- Helsinki University Hospital, Helsinki, Finland.,Department of Clinical Genetics, HUSLAB, HUS Diagnostic Center, University of Helsinki, Helsinki, Finland
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Johanna Schleutker
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | - Raisa Serpi
- Northern Finland Biobank Borealis, University of Oulu, Northern Ostrobothnia Hospital District, Oulu, Finland
| | - Huei-Yi Shen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Richard Siegel
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Kaisa Silander
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Sanna Siltanen
- Finnish Clinical Biobank Tampere, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Sirpa Soini
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Hilkka Soininen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | | | - Ioanna Tachmazidou
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Kaisa Tasanen
- PEDEGO Research Unit, University of Oulu, Oulu, Finland.,Department of Dermatology and Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Pentti Tienari
- Department of Neurology, Helsinki University Hospital, Helsinki, Finland.,Translational Immunology, Research Programs Unit, University of Helsinki, Helsinki, Finland
| | - Sanna Toppila-Salmi
- Department of Allergy, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Abdominal Center, Endocrinology, Helsinki University Hospital, Helsinki, Finland.,Folkhalsan Research Center, Helsinki, Finland.,Research Program of Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland
| | - Joni A Turunen
- Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Eye Genetics Group, Folkhälsan Research Center, Helsinki, Finland
| | - Jacob C Ulirsch
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Felix Vaura
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,University of Turku, Turku, Finland
| | - Petri Virolainen
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | | | | | | | - Mari Nelis
- Genomics Core Facility, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anu Reigo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Anu Jalanko
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tarja Laitinen
- Finnish Clinical Biobank Tampere, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Tomi P Mäkelä
- Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | | | | | - Mark J Daly
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland. .,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA. .,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA. .,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
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26
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Kanoni S, Graham SE, Wang Y, Surakka I, Ramdas S, Zhu X, Clarke SL, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJM, Wu KHH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Yousri NA, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Hwu CM, Hung YJ, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, Matteo F, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Ruotsalainen SE, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Vazquez-Moreno M, Feitosa MF, Wojczynski MK, Wang Z, Preuss MH, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Tsao NL, Verma A, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Demirkan A, Leonard HL, Marten J, Frank M, Schmidt B, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Nongmaithem SS, Bayyana S, Stringham HM, Irvin MR, Oldmeadow C, Kim HN, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Chen S, Liu F, Yang J, Kentistou KA, Banas B, Nardone GG, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki AE, Hofer E, Lin M, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, van der Laan SW, Chitrala KN, Weiss S, Bentley AR, Doumatey AP, Adeyemo AA, Lee JY, Petersen ERB, Nielsen AA, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin SY, Wang JS, Couture C, Lyytikäinen LP, Nikus K, Cuellar-Partida G, Vestergaard H, Hidalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, Li X, Liang J, Tang H, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Chen Z, Li L, Kawaguchi T, Thiery J, Bis JC, Launer LJ, Li H, Nalls MA, Raitakari OT, Ichihara S, Wild SH, Nelson CP, Campbell H, Jäger S, Nabika T, Al-Mulla F, Niinikoski H, Braund PS, Kolcic I, Kovacs P, Giardoglou T, Katsuya T, de Kleijn D, de Borst GJ, Kim EK, Adams HHH, Ikram MA, Zhu X, Asselbergs FW, Kraaijeveld AO, Beulens JWJ, Shu XO, Rallidis LS, Pedersen O, Hansen T, Mitchell P, Hewitt AW, Kähönen M, Pérusse L, Bouchard C, Tönjes A, Chen YDI, Pennell CE, Mori TA, Lieb W, Franke A, Ohlsson C, Mellström D, Cho YS, Lee H, Yuan JM, Koh WP, Rhee SY, Woo JT, Heid IM, Stark KJ, Zimmermann ME, Völzke H, Homuth G, Evans MK, Zonderman AB, Polasek O, Pasterkamp G, Hoefer IE, Redline S, Pahkala K, Oldehinkel AJ, Snieder H, Biino G, Schmidt R, Schmidt H, Bandinelli S, Dedoussis G, Thanaraj TA, Kardia SLR, Peyser PA, Kato N, Schulze MB, Girotto G, Böger CA, Jung B, Joshi PK, Bennett DA, De Jager PL, Lu X, Mamakou V, Brown M, Caulfield MJ, Munroe PB, Guo X, Ciullo M, Jonas JB, Samani NJ, Kaprio J, Pajukanta P, Tusié-Luna T, Aguilar-Salinas CA, Adair LS, Bechayda SA, de Silva HJ, Wickremasinghe AR, Krauss RM, Wu JY, Zheng W, Hollander AI, Bharadwaj D, Correa A, Wilson JG, Lind L, Heng CK, Nelson AE, Golightly YM, Wilson JF, Penninx B, Kim HL, Attia J, Scott RJ, Rao DC, Arnett DK, Hunt SC, Walker M, Koistinen HA, Chandak GR, Mercader JM, Costanzo MC, Jang D, Burtt NP, Villalpando CG, Orozco L, Fornage M, Tai ES, van Dam RM, Lehtimäki T, Chaturvedi N, Yokota M, Liu J, Reilly DF, McKnight AJ, Kee F, Jöckel KH, McCarthy MI, Palmer CNA, Vitart V, Hayward C, Simonsick E, van Duijn CM, Jin ZB, Qu J, Hishigaki H, Lin X, März W, Gudnason V, Tardif JC, Lettre G, Hart LM', Elders PJM, Damrauer SM, Kumari M, Kivimaki M, van der Harst P, Spector TD, Loos RJF, Province MA, Parra EJ, Cruz M, Psaty BM, Brandslund I, Pramstaller PP, Rotimi CN, Christensen K, Ripatti S, Widén E, Hakonarson H, Grant SFA, Kiemeney LALM, de Graaf J, Loeffler M, Kronenberg F, Gu D, Erdmann J, Schunkert H, Franks PW, Linneberg A, Jukema JW, Khera AV, Männikkö M, Jarvelin MR, Kutalik Z, Francesco C, Mook-Kanamori DO, van Dijk KW, Watkins H, Strachan DP, Grarup N, Sever P, Poulter N, Chuang LM, Rotter JI, Dantoft TM, Karpe F, Neville MJ, Timpson NJ, Cheng CY, Wong TY, Khor CC, Li H, Sabanayagam C, Peters A, Gieger C, Hattersley AT, Pedersen NL, Magnusson PKE, Boomsma DI, Willemsen AHM, Cupples LA, van Meurs JBJ, Ghanbari M, Gordon-Larsen P, Huang W, Kim YJ, Tabara Y, Wareham NJ, Langenberg C, Zeggini E, Kuusisto J, Laakso M, Ingelsson E, Abecasis G, Chambers JC, Kooner JS, de Vries PS, Morrison AC, Hazelhurst S, Ramsay M, North KE, Daviglus M, Kraft P, Martin NG, Whitfield JB, Abbas S, Saleheen D, Walters RG, Holmes MV, Black C, Smith BH, Baras A, Justice AE, Buring JE, Ridker PM, Chasman DI, Kooperberg C, Tamiya G, Yamamoto M, van Heel DA, Trembath RC, Wei WQ, Jarvik GP, Namjou B, Hayes MG, Ritchie MD, Jousilahti P, Salomaa V, Hveem K, Åsvold BO, Kubo M, Kamatani Y, Okada Y, Murakami Y, Kim BJ, Thorsteinsdottir U, Stefansson K, Zhang J, Chen YE, Ho YL, Lynch JA, Rader DJ, Tsao PS, Chang KM, Cho K, O'Donnell CJ, Gaziano JM, Wilson PWF, Frayling TM, Hirschhorn JN, Kathiresan S, Mohlke KL, Sun YV, Morris AP, Boehnke M, Brown CD, Natarajan P, Deloukas P, Willer CJ, Assimes TL, Peloso GM. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis. Genome Biol 2022; 23:268. [PMID: 36575460 PMCID: PMC9793579 DOI: 10.1186/s13059-022-02837-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 12/06/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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Affiliation(s)
- Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Shweta Ramdas
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xiang Zhu
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Shoa L Clarke
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Konain Fatima Bhatti
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Sailaja Vedantam
- Boston Children's Hospital, EndocrinologyBoston, MA, 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Adam E Locke
- McDonnell Genome Institute and Department of Medicine, Washington University, St. Louis, MO, 63108, USA
| | - Eirini Marouli
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Greg J M Zajac
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kuan-Han H Wu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Ioanna Ntalla
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Derek Klarin
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Zeyuan Wang
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Chao Xue
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | | | - Anna Helgadottir
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Sæmundargötu 2, Reykjavik, 102, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik, 101, Iceland
| | - Mi Yeong Hwang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Sohee Han
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Saori Sakaue
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masahiro Kanai
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Ben M Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Humaira Rasheed
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Yogasudha Veturi
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Jennifer Allen Pacheco
- Center for Genetic Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60618, USA
| | - Elisabeth A Rosenthal
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA
| | - Todd Lingren
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - QiPing Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine and the Gonda Vascular Center, Mayo Clinic, Rochester, MN, USA
| | - Akira Narita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | - Jun Takayama
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | | | - Karen A Hunt
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Bhavi Trivedi
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Jeffrey Haessler
- Fred Hutchinson Cancer Center, Division of Public Health Sciences, Seattle, WA, 9810, USA
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
| | - Yuki Bradford
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Jason E Miller
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
- Usher Institute, The University of Edinburgh, Nine, Edinburgh Bioquarter, 9 Little France Road, Edinburgh, EH16 4UX, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | - George Hindy
- Department of Population Medicine, Qatar University College of Medicine, QU Health, Doha, Qatar
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Constance Turman
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Hongyan Huang
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Dhriti Sengupta
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, School of Public Health, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Ketian Yu
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ellen M Schmidt
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Anita Pandit
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Xianyong Yin
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Jing-Hua Zhao
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Hye-Mi Jang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Achilleas Pitsillides
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK
| | - Yingji Ji
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK
| | - Zishan Gao
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Simon Haworth
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Bristol Dental School, University of Bristol, Lower Maudlin Street, Bristol, BS1 2LY, UK
| | - Noha A Yousri
- Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar
- Department of Computer and Systems Engineering, Alexandria University, Alexandria, Egypt
| | - Ruth E Mitchell
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
| | - Mette Aadahl
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anne A Bjerregaard
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22903, USA
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yi-Jen Hung
- Institute of Preventive Medicine, National Defense Medical Center, Postbox 90048~700, Sanhsia Dist, New Taipei City, 237101, Taiwan
| | - Helen R Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Julia Ramirez
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- Aragon Institute of Engineering Research, University of Zaragoza and Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales Y Nanomedicina, Spain
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Line L Kårhus
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Maria Sabater-Lleal
- Unit of Genomics of Complex Diseases, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Pala Mauro
- Istituto Di Ricerca Genetica E Biomedica, Consiglio Nazionale Delle Ricerche, Rome, Italy
| | - Floris Matteo
- Istituto Di Ricerca Genetica E Biomedica, Consiglio Nazionale Delle Ricerche, Rome, Italy
- Dipartimento Di Scienze Biomediche, Università Degli Studi Di Sassari, Sardinia, Italy
| | - Aaron F McDaid
- University Center for Primary Care and Public Health, University of Lausanne, Rte de Berne 113, 1010, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Dept of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, UK
| | - Line T Møllehave
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Matthias Munz
- Institute for Cardiogenetics, University of Lübeck, DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, University Heart Center Lübeck, Lübeck and Charité - University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin and Berlin Institute of Health, Institute for Dental and Craniofacial Sciences, Department of Periodontology and Synoptic Dentistry, Berlin, Germany
| | - Lingyao Zeng
- Deutsches Herzzentrum München, Klinik Für Herz- Und Kreislauferkrankungen, Technische Universität München, Munich, Germany
- Deutsches Zentrum Für Herz-Kreislauf-Forschung (DZHK) E.V., Partner Site Munich Heart Alliance, Munich, Germany
| | - Jianfeng Huang
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Bin Yang
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Alaitz Poveda
- Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Azra Kurbasic
- Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck, Austria
- German Chronic Kidney Disease Study, Berlin, Germany
| | - Lukas Forer
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck, Austria
- German Chronic Kidney Disease Study, Berlin, Germany
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107, Leipzig, Germany
- LIFE Research Centre for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Straße 27, 04103, Leipzig, Germany
| | - Tessel E Galesloot
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | | | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - EWarwick Daw
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Joseph M Zmuda
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jonathan S Mitchell
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Via Galvani 31, 39100, Bolzano, Italy
| | - Christian Fuchsberger
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Via Galvani 31, 39100, Bolzano, Italy
| | - Henry Christensen
- Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, 98101, USA
| | - Miguel Vazquez-Moreno
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
- NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, SE1 9RT, UK
| | - Paraskevi Christofidou
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jan W Benjamins
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jorgen Engmann
- Institute of Cardiovascular Sciences, University College London, Gower Street, London, WC1E 6BT, UK
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, UK
| | - Noah L Tsao
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Roderick C Slieker
- Amsterdam UMC, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, 1081HV, the Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands
| | - Ken Sin Lo
- Montreal Heart Institute, Université de Montréal, 5000 Belanger Street, Montreal, PQ, H1T1C8, Canada
| | - Nuno R Zilhao
- Icelandic Heart Association, 201, Kopavogur, Iceland
| | - Phuong Le
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, L5L 1C6, Canada
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, 68167, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim GmbH, 68163, Mannheim, Germany
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, 68167, Mannheim, Germany
| | - Shaofeng Huo
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Daisuke D Ikeda
- Biomedical Technology Research Center, Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd, Tokushima, Japan
| | - Hiroyuki Iha
- Biomedical Technology Research Center, Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd, Tokushima, Japan
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, 310024, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, Zhejiang, China
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jun Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Ayşe Demirkan
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Section of Statistical Multi-Omics, Department of Clinical and Experimental Research, University of Surrey, Guildford, Surrey, UK
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute On Aging, NIH, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Jonathan Marten
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
| | - Mirjam Frank
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Laura J Smyth
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
| | - Marisa Cañadas-Garre
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research: Pfizer-University of Granada-Andalusian Regional Government, Granada, Spain
- Hematology Department, Hospital Universitario Virgen de Las Nieves, Granada, Spain
- Instituto de Investigación Biosanitaria de Granada (Ibs.GRANADA), Granada, Spain
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, 461-8673, Japan
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
| | - Rui Xia
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Alicia Huerta-Chagoya
- CONACYT, Instituto Nacional de Ciencias Médicas Y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Departamento de Medicina Genómica Y Toxicología Ambiental, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Coyoacán, 04510, Mexico City, Mexico
| | | | - Valeriya Lyssenko
- Lund University Diabetes Center, Lund University, Malmö, Sweden
- Center for Diabetes Research, University of Bergen, Bergen, Norway
| | | | - Swati Bayyana
- Genomic Research On Complex Diseases (GRC Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- Academy of Scientific and Innovative Research (AcSIR), New Delhi, India
| | - Heather M Stringham
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Marguerite R Irvin
- Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Han-Na Kim
- Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Korea
- Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul, 06355, Korea
| | - Seungho Ryu
- Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 04514, Korea
- Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Korea
| | - Paul R H J Timmers
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Liubov Arbeeva
- Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, USA
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Duke-NUS Medical School, Health Services and Systems Research, Singapore, 169857, Singapore
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, Anschutz Medical Campus, University of Colorado, Denver, Aurora, CO, 80045, USA
| | - Gauri Prasad
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Centre, Ghaziabad, Uttar Pradesh, India
| | - Laura Lorés-Motta
- Departments of Ophthalmology and Human Genetics, Radboud University Nijmegen Medical Center, Philips Van Leydenlaan 15, Nijmegen, 6525 EX, the Netherlands
| | - Marc Pauper
- Departments of Ophthalmology and Human Genetics, Radboud University Nijmegen Medical Center, Philips Van Leydenlaan 15, Nijmegen, 6525 EX, the Netherlands
| | - Jirong Long
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Elizabeth Theusch
- Department of Pediatrics, University of California San Francisco, Oakland, CA, 94609, USA
| | - Fumihiko Takeuchi
- National Center for Global Health and Medicine, Tokyo, 1628655, Japan
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
- Department of Biostatistics and Epidemiology, University of Massachusetts-Amherst, Amherst, MA, 01003, USA
| | - Anu Loukola
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Sailalitha Bollepalli
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Sophie C Warner
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 17 Hougou Lane, Chong Wen Men, Beijing, 100005, China
| | - Wen B Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 1 Dong Jiao Min Xiang, Beijing, 100730, Dong Cheng District, China
| | - Teresa Nutile
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso" - CNR, Naples, Italy
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso" - CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - Yun Ju Sung
- Division of Biostatistics, Washington University, St. Louis, MO, 63110, USA
| | - Shufeng Chen
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Jingyun Yang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Bernhard Banas
- Dept of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | | | - Karina Meidtner
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jennifer A Smith
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Prashantha Hebbar
- Department of Genetics and Bioinformatics, Dasman Diabetes Institute, Kuwait City, Kuwait
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
- Department of Clinical Epidemiology, Institute of Health Informatics, University College London, London, UK
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Maoxuan Lin
- Massachusetts General Hospital Cancer Center, Charlestown, MA, 02129, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
| | - Simona Vaccargiu
- Institute of Genetic and Biomedical Research, National Research Council of Italy, UOS of Sassari, Sassari, Italy
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, the Netherlands
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Brian E Cade
- Sleep Medicine and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Kumaraswamy Naidu Chitrala
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIH, Baltimore, MD, 20892-9205, USA
- Department of Engineering Technology, University of Houston-Sugarland, Houston, TX, USA
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University of Greifswald and University Medicine Greifswald, Greifswald, Germany
| | - Amy R Bentley
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Ayo P Doumatey
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Adebowale A Adeyemo
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Jong Young Lee
- , Oneomics. Co. Ltd. 2F, Soonchunhyang Mirai Medical Center 173, Buheuyng-Ro, Bucheon-Si Gyeonggi-Do, 14585, Korea
| | - Eva R B Petersen
- Department of Clinical Biochemistry and Immunology, Hospital of Southern Jutland, Kresten Philipsens Vej 15, 6200, Aabenraa, Denmark
| | - Aneta A Nielsen
- Department of Clinical Biochemistry, Lillebaelt Hospital, Kolding, Denmark
| | - Hyeok Sun Choi
- Department of Biomedical Science, Hallym University, Chuncheon, 24252, Gangwon-Do, Korea
| | - Maria Nethander
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sandra Freitag-Wolf
- Institute of Medical Informatics and Statistics, Kiel University, Kiel, Germany
| | - Lorraine Southam
- Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Nigel W Rayner
- Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Carol A Wang
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, 2308, Australia
| | - Shih-Yi Lin
- Center for Geriatrics and Gerontology, Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Jun-Sing Wang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | | | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, 33521, Tampere, Finland
- Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Gabriel Cuellar-Partida
- University of Queensland Diamantina Institute, Translational Research Institute, Kent St, Woolloongabba, Brisbane, QLD, 4102, Australia
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Bornholms Hospital, Rønne, Denmark
| | - Bertha Hidalgo
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Olga Giannakopoulou
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Qiuyin Cai
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Morgan O Obura
- Amsterdam UMC, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, 1081HV, the Netherlands
| | - Jessica van Setten
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Xiaoyin Li
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Jingjing Liang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine Stanford, Palo Alto, CA, 94305, USA
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jae Hun Shin
- Department of Biomedical Science, Hallym University, Chuncheon, 24252, Gangwon-Do, Korea
| | - Rebecca D Jackson
- Division of Endocrinology, Ohio State University, Columbus, OH, 43210, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98195, USA
| | - Lisa Warsinger Martin
- School of Medicine and Health Sciences, George Washington University, Washington, DC, 20037, USA
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Joachim Thiery
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107, Leipzig, Germany
- Institute for Laboratory Medicine, University Hospital Leipzig, Paul-List-Strasse 13/15, 04103, Leipzig, Germany
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, 98101, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIH, Baltimore, MD, 20892-9205, USA
| | - Huaixing Li
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Sahoko Ichihara
- Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, 329-0498, Japan
| | - Sarah H Wild
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Susanne Jäger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, 6938501, Japan
| | - Fahd Al-Mulla
- Department of Genetics and Bioinformatics, Dasman Diabetes Institute, Kuwait City, Kuwait
| | - Harri Niinikoski
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Physiology, University of Turku, Turku, Finland
| | - Peter S Braund
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ivana Kolcic
- University of Split School of Medicine, Šoltanska 2, HR-21000, Split, Croatia
| | - Peter Kovacs
- University of Leipzig Medical Center, Liebigstr. 18, 04103, Medical Department III - Endocrinology, Nephrology, RheumatologyLeipzig, Germany
| | - Tota Giardoglou
- Department of Nutrition-Dietetics, Harokopio University, Eleftheriou Venizelou, 17676, Athens, Greece
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, 5650871, Japan
- Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine, Suita, 5650871, Japan
| | - Dominique de Kleijn
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Gert J de Borst
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Eung Kweon Kim
- Corneal Dystrophy Research Institute, Yonsei University College of Medicine, Saevit Eye Hospital, SeoulIlsan, 03722, Korea
| | - Hieab H H Adams
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Dept of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Folkert W Asselbergs
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Adriaan O Kraaijeveld
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Joline W J Beulens
- Amsterdam UMC, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, 1081HV, the Netherlands
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, 3584CG, Utrecht, the Netherlands
| | - Xiao-Ou Shu
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Loukianos S Rallidis
- Second Department of Cardiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Paul Mitchell
- Center for Vision Research, Department of Ophthalmology and The Westmead Institute, University of Sydney, Hawkesbury Rd, Sydney, NSW, 2145, Australia
| | - Alex W Hewitt
- School of Medicine, Menzies Institute for Medical Research, University of Tasmania, Liverpool St, Hobart, TAS, 7000, Australia
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC, 3002, Australia
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Louis Pérusse
- Department of Kinesiology, Université Laval, Québec, Canada
- Centre Nutrition, Santé Et Société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Québec, Canada
| | - Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Anke Tönjes
- University of Leipzig Medical Center, Liebigstr. 18, 04103, Medical Department III - Endocrinology, Nephrology, RheumatologyLeipzig, Germany
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Craig E Pennell
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, 2308, Australia
| | - Trevor A Mori
- Discipline of Internal Medicine, Medical School, The University of Western Australia, Perth, WA, Australia
| | - Wolfgang Lieb
- Institute of Epidemiology, Kiel University, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Dan Mellström
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, 24252, Gangwon-Do, Korea
| | - Hyejin Lee
- Department of Internal Medicine, EwhaWomans University School of Medicine, Seoul, Korea
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15232, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15232, USA
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117545, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, 117609, Singapore
| | - Sang Youl Rhee
- Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, 02447, Korea
| | - Jeong-Taek Woo
- Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, 02447, Korea
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Martina E Zimmermann
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University of Greifswald and University Medicine Greifswald, Greifswald, Germany
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute On Aging Intramural Research Program, NIH Biomedical Research Center, NIH 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Science, National Institute On Aging Intramural Research Program, NIH Biomedical Research Center, NIH 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Ozren Polasek
- University of Split School of Medicine, Šoltanska 2, HR-21000, Split, Croatia
- Algebra University College, Ilica 242, Zagreb, Croatia
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Imo E Hoefer
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Susan Redline
- Sleep Medicine and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Physical Activity and Health, Paavo Nurmi Centre, Sports and Exercise Medicine Unit, University of Turku, Turku, Finland
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, the Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, the Netherlands
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Pavia, Italy
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Helena Schmidt
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, Graz, Austria
| | | | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Norihiro Kato
- National Center for Global Health and Medicine, Tokyo, 1628655, Japan
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Giorgia Girotto
- Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Strada Di Fiume 447, 34149, Trieste, Italy
| | - Carsten A Böger
- Dept of Nephrology, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology, , Traunstein Hospital, Diabetology, RheumatologyTraunstein, Germany
- KfH Kidney Center Traunstein, Traunstein, Germany
| | - Bettina Jung
- Dept of Nephrology, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology, , Traunstein Hospital, Diabetology, RheumatologyTraunstein, Germany
- KfH Kidney Center Traunstein, Traunstein, Germany
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Philip L De Jager
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Neurology, Center for Translational and Systems Neuroimmunology, Columbia University Medical Center, New York, NY, USA
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Vasiliki Mamakou
- Medical School, National and Kapodistrian University Athens, 75 M. Assias Street, 115 27, Athens, Greece
- Dromokaiteio Psychiatric Hospital, 124 61, Athens, Greece
| | - Morris Brown
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Mark J Caulfield
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Marina Ciullo
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso" - CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - Jost B Jonas
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 17 Hougou Lane, Chong Wen Men, Beijing, 100005, China
- Department of Ophthalmology, Medical Faculty Mannheim, Heidelberg University, Kutzerufer 1, 68167, Mannheim, Germany
- Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
- Privatpraxis Prof Jonas Und Dr Panda-Jonas, Heidelberg, Germany
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
| | - Teresa Tusié-Luna
- Unidad de Biología Molecular Y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/ Instituto Nacional de Ciencias Médicas Y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Carlos A Aguilar-Salinas
- Departamento de Endocrinología Y Metabolismo, Instituto Nacional de Ciencias Médicas Y Nutrición Salvador Zubirán, 14080, Mexico, Mexico
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, 27516, USA
| | - Sonny Augustin Bechayda
- USC-Office of Population Studies Foundation, University of San Carlos, 6000, Cebu City, Philippines
- Department of Anthropology, Sociology, and History, University of San Carlos, 6000, Cebu City, Philippines
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, 11010, Sri Lanka
| | - Ananda R Wickremasinghe
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Ragama, 11010, Sri Lanka
| | - Ronald M Krauss
- Children's Hospital Oakland Research Institute, Oakland, CA, 94609, USA
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Wei Zheng
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Anneke Iden Hollander
- Departments of Ophthalmology and Human Genetics, Radboud University Nijmegen Medical Center, Philips Van Leydenlaan 15, Nijmegen, 6525 EX, the Netherlands
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Centre, Ghaziabad, Uttar Pradesh, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore and Khoo Teck Puat - National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Amanda E Nelson
- Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Yvonne M Golightly
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, USA
- Injury Prevention Research Center, University of North Carolina, Chapel Hill, NC, USA
- Division of Physical Therapy, University of North Carolina, Chapel Hill, NC, USA
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Brenda Penninx
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Hyung-Lae Kim
- Department of Biochemistry, College of Medicine, Ewha Womans University, Seoul, 07804, Korea
| | - John Attia
- Hunter Medical Research Institute, Newcastle, Australia
- Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia
| | - Rodney J Scott
- Hunter Medical Research Institute, Newcastle, Australia
- Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia
| | - D C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, USA
| | - Donna K Arnett
- Office of the Provost, University of South Carolina, Columbia, SC, USA
| | - Steven C Hunt
- Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar
- Department of Internal Medicine, University of Utah, Salt Lake City, Utah, 84132, USA
| | - Mark Walker
- Institute of Cellular Medicine (Diabetes), The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Heikki A Koistinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Medicine, Helsinki University Hospital, University of Helsinki, Haartmaninkatu 4, P.O.Box 340, 00029, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Biomedicum 2U, Tukholmankatu 8, 00290, Helsinki, Finland
| | - Giriraj R Chandak
- Academy of Scientific and Innovative Research (AcSIR), New Delhi, India
- JSS Academy of Higher Education and Research, Mysuru, India
| | - Josep M Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Maria C Costanzo
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dongkeun Jang
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Noël P Burtt
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Lorena Orozco
- Laboratorio de Inmunogenómica Y Enfermedades Metabólicas, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - EShyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, 119228, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | | | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Dermot F Reilly
- Genetics, Merck Sharp & Dohme Corp., Kenilworth, NJ, 07033, USA
| | - Amy Jayne McKnight
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
| | - Frank Kee
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Colin N A Palmer
- Population Health and Genomics, University of Dundee, Ninwells Hospital and Medical School, Dundee, DD1 9SY, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
| | - Eleanor Simonsick
- Intramural Research Program, National Institute On Aging, 3001 S. Hanover St., Baltimore, MD, 21225, USA
| | - Cornelia M van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Zi-Bing Jin
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key Laboratory, Beijing, 100730, China
- The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Jia Qu
- The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Haretsugu Hishigaki
- Biomedical Technology Research Center, Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd, Tokushima, Japan
| | - Xu Lin
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, 68167, Mannheim, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim and Augsburg, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Jean-Claude Tardif
- Montreal Heart Institute, Université de Montréal, 5000 Belanger Street, Montreal, PQ, H1T1C8, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Université de Montréal, 5000 Belanger Street, Montreal, PQ, H1T1C8, Canada
| | - Leen M 't Hart
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, Amsterdam, 1081HV, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam Cardiovascular Sciences, Amsterdam, 1081HV, the Netherlands
| | - Petra J M Elders
- Department of General Practice, Amsterdam UMC, Amsterdam, 1081HV, the Netherlands
- Amsterdam Public Health Research Institute, Health Behaviours and Chronic Diseases, Amsterdam, 1081HV, the Netherlands
| | - Scott M Damrauer
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
| | - Meena Kumari
- Institute of Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, UK
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Ruth J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, L5L 1C6, Canada
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, 98101, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ivan Brandslund
- Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Peter P Pramstaller
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Via Galvani 31, 39100, Bolzano, Italy
| | - Charles N Rotimi
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Kaare Christensen
- Danish Aging Research Center, University of Southern Denmark, Odense C, Denmark
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
- Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Struan F A Grant
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Lambertus A L M Kiemeney
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Jacqueline de Graaf
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107, Leipzig, Germany
- LIFE Research Centre for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Straße 27, 04103, Leipzig, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck, Austria
- German Chronic Kidney Disease Study, Berlin, Germany
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
- School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, and University Heart Center Lübeck, Lübeck, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik Für Herz- Und Kreislauferkrankungen, Technische Universität München, Munich, Germany
- Deutsches Zentrum Für Herz-Kreislauf-Forschung (DZHK) E.V., Partner Site Munich Heart Alliance, Munich, Germany
| | - Paul W Franks
- Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Minna Männikkö
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter of Oulu, University of Oulu, Oulu, Finland
| | - Zoltan Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Rte de Berne 113, 1010, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Cucca Francesco
- Institute for Genetic and Biomedical Research, Italian National Council of Research (IRGB CNR), Cagliari, Italy
- University of Sassari, Sassari, Italy
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Hugh Watkins
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, SW17 0RE, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Sever
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
| | - Neil Poulter
- School of Public Health, Imperial College London, London, W12 7RH, UK
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei, Taiwan
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Thomas M Dantoft
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Fredrik Karpe
- OCDEM, University of Oxford, Churchill Hospital, Oxford, OX3 7LE, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Matt J Neville
- OCDEM, University of Oxford, Churchill Hospital, Oxford, OX3 7LE, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Ching-Yu Cheng
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Tien-Yin Wong
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Hengtong Li
- Data Science, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
| | - Charumathi Sabanayagam
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Deutsches Zentrum Für Herz-Kreislauf-Forschung (DZHK) E.V., Partner Site Munich Heart Alliance, Munich, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Andrew T Hattersley
- Medical School, University of Exeter, University of Exeter, Exeter, EX2 5DW, UK
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
| | - Allegonda H M Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
| | - LAdrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, 27516, USA
| | - Wei Huang
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, China
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin, Berlin, Germany
| | - Eleftheria Zeggini
- Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts Der Isar, TUM School of Medicine, Munich, Germany
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, 94305, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, 94305, USA
| | - Goncalo Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- School of Public Health, Imperial College London, London, W12 7RH, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, School of Public Health, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, School of Public Health, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois College of Medicine, Chicago, IL, USA
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD, 4006, Australia
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD, 4006, Australia
| | - Shahid Abbas
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
- Faisalabad Institute of Cardiology, Faislabad, Pakistan
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK
| | - Michael V Holmes
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals, Oxford, UK
| | - Corri Black
- Aberdeen Centre for Health Data Science,1:042 Polwarth Building School of Medicine, Medical Science and Nutrition University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - Aris Baras
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Anne E Justice
- Department of Population Health Sciences, Geisinger Health, Danville, PA, 17822, USA
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Charles Kooperberg
- Fred Hutchinson Cancer Center, Division of Public Health Sciences, Seattle, WA, 9810, USA
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | - David A van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Richard C Trembath
- School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Washington, USA
| | - Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA
| | - M Geoffrey Hayes
- Center for Genetic Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60618, USA
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60618, USA
- Department of Anthropology, Northwestern University, Evanston, IL, 60208, USA
| | - Marylyn D Ritchie
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Public Health and Nursing, HUNT Research Centre, NTNU, Norwegian University of Science and Technology, 7600, Levanger, Norway
- Department of Research, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Public Health and Nursing, HUNT Research Centre, NTNU, Norwegian University of Science and Technology, 7600, Levanger, Norway
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Bong-Jo Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
- Faculty of Medicine, University of Iceland, Sæmundargötu 2, Reykjavik, 102, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
| | - Jifeng Zhang
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - YEugene Chen
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- University of Massachusetts, Boston, MA, USA
| | - Daniel J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Philip S Tsao
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - John M Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Peter W F Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK
| | - Joel N Hirschhorn
- Boston Children's Hospital, EndocrinologyBoston, MA, 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Departments of Pediatrics and Genetics, Harvard Medical School, Boston, MA, USA
| | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Christopher D Brown
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.
| | - Themistocles L Assimes
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA.
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27
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Aragam KG, Jiang T, Goel A, Kanoni S, Wolford BN, Atri DS, Weeks EM, Wang M, Hindy G, Zhou W, Grace C, Roselli C, Marston NA, Kamanu FK, Surakka I, Venegas LM, Sherliker P, Koyama S, Ishigaki K, Åsvold BO, Brown MR, Brumpton B, de Vries PS, Giannakopoulou O, Giardoglou P, Gudbjartsson DF, Güldener U, Haider SMI, Helgadottir A, Ibrahim M, Kastrati A, Kessler T, Kyriakou T, Konopka T, Li L, Ma L, Meitinger T, Mucha S, Munz M, Murgia F, Nielsen JB, Nöthen MM, Pang S, Reinberger T, Schnitzler G, Smedley D, Thorleifsson G, von Scheidt M, Ulirsch JC, Arnar DO, Burtt NP, Costanzo MC, Flannick J, Ito K, Jang DK, Kamatani Y, Khera AV, Komuro I, Kullo IJ, Lotta LA, Nelson CP, Roberts R, Thorgeirsson G, Thorsteinsdottir U, Webb TR, Baras A, Björkegren JLM, Boerwinkle E, Dedoussis G, Holm H, Hveem K, Melander O, Morrison AC, Orho-Melander M, Rallidis LS, Ruusalepp A, Sabatine MS, Stefansson K, Zalloua P, Ellinor PT, Farrall M, Danesh J, Ruff CT, Finucane HK, Hopewell JC, Clarke R, Gupta RM, Erdmann J, Samani NJ, Schunkert H, Watkins H, Willer CJ, Deloukas P, Kathiresan S, Butterworth AS. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants. Nat Genet 2022; 54:1803-1815. [PMID: 36474045 PMCID: PMC9729111 DOI: 10.1038/s41588-022-01233-6] [Citation(s) in RCA: 167] [Impact Index Per Article: 83.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 10/17/2022] [Indexed: 12/12/2022]
Abstract
The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.
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Affiliation(s)
- Krishna G Aragam
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA. .,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. .,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Tao Jiang
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Anuj Goel
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Brooke N Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Deepak S Atri
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Divisions of Cardiovascular Medicine and Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elle M Weeks
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Minxian Wang
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - George Hindy
- Department of Population Medicine, Qatar University College of Medicine, Doha, Qatar
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christopher Grace
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Carolina Roselli
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nicholas A Marston
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Frederick K Kamanu
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Loreto Muñoz Venegas
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Paul Sherliker
- Medical Research Council Population Health Research Unit, CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Bjørn O Åsvold
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway.,Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ben Brumpton
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Olga Giannakopoulou
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Panagiota Giardoglou
- Department of Nutrition-Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Ulrich Güldener
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Syed M Ijlal Haider
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | | | - Maysson Ibrahim
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Adnan Kastrati
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Thorsten Kessler
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | | | - Tomasz Konopka
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Ling Li
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Lijiang Ma
- Department of Genetics and Genomic Science, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Meitinger
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany.,Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.,Klinikum Rechts der Isar, Institute of Human Genetics, Technical University of Munich, Munich, Germany
| | - Sören Mucha
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Matthias Munz
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Federico Murgia
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Jonas B Nielsen
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA.,Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Markus M Nöthen
- School of Medicine and University Hospital Bonn, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Shichao Pang
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Tobias Reinberger
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Gavin Schnitzler
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Damian Smedley
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | - Moritz von Scheidt
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Jacob C Ulirsch
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | | | | | - David O Arnar
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Department of Internal Medicine, Division of Cardiology, Landspitali-National University Hospital of Iceland, Hringbraut, Reykjavik, Iceland
| | - Noël P Burtt
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maria C Costanzo
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jason Flannick
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Dong-Keun Jang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Amit V Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Issei Komuro
- Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Luca A Lotta
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Christopher P Nelson
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Glenfield Hospital, Leicester, UK
| | - Robert Roberts
- Cardiovascular Genomics and Genetics, University of Arizona College of Medicin, Phoenix, AZ, USA
| | - Gudmundur Thorgeirsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Department of Internal Medicine, Division of Cardiology, Landspitali-National University Hospital of Iceland, Hringbraut, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Thomas R Webb
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Glenfield Hospital, Leicester, UK
| | - Aris Baras
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Integrated Cardio Metabolic Centre, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden.,Clinical Gene Networks AB, Stockholm, Sweden
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - George Dedoussis
- Department of Nutrition-Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Kristian Hveem
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.,HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Olle Melander
- Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Loukianos S Rallidis
- Second Department of Cardiology, Medical School, National and Kapodistrian University of Athens, University General Hospital Attikon, Athens, Greece
| | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital and Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Marc S Sabatine
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Pierre Zalloua
- Harvard T.H.Chan School of Public Health, Boston, MA, USA.,College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, UAE
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Martin Farrall
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,National Institute for Health and Care Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge, UK.,The National Institute for Health and Care Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK.,Human Genetics, Wellcome Sanger Institute, Saffron Walden, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.,British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK
| | - Christian T Ruff
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Hilary K Finucane
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jemma C Hopewell
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Robert Clarke
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Rajat M Gupta
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Divisions of Cardiovascular Medicine and Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.,German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Nilesh J Samani
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Heribert Schunkert
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany.,German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Hugh Watkins
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.,Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA.,Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | | | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. .,National Institute for Health and Care Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge, UK. .,The National Institute for Health and Care Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK. .,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK. .,British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK.
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28
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Pansa CC, Molica LR, Moraes KCM. Non-alcoholic fatty liver disease establishment and progression: genetics and epigenetics as relevant modulators of the pathology. Scand J Gastroenterol 2022; 58:521-533. [PMID: 36426638 DOI: 10.1080/00365521.2022.2148835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) results from metabolic dysfunctions that affect more than one-third of the world population. Over the last decades, scientific investigations have clarified many details on the pathology establishment and development; however, effective therapeutics approaches are still evasive. In addition, studies demonstrated that NAFLD establishment and progression are related to several etiologies. Recently, genetics and epigenetics backgrounds have emerged as relevant elements to the pathology onset, and, hence, deserve deep investigation to clarify molecular details on NAFLD signaling, which may be correlated with population behavior. Thus, to minimize the global problem, public health and public policies should take advantage of studies on NAFLD over the next following decades. METHODS In this context, we have performed a selective literature review focusing on biochemistry of lipid metabolism, genetics, epigenetics, and the ethnicity as strong elements that drive NAFLD establishment. RESULTS Considering the etiological agents that acts on NAFLD development and progression, the genetics and the epigenetics emerged as relevant factors. Genetics acts as a powerful element in the establishment and progression of the NAFLD. Over the last decades, details concerning genes and their polymorphisms, as well as epigenetics, have been considered relevant elements in the systems biology of diseases, and their effects on NAFLD should be considered in-depth, as well as the ethnicity, clarifying whether people are susceptible to liver diseases. Moreover, the endemicity and social problems of hepatic disfunction are far to be solved, which require a combined effort of various sectors of society. CONCLUSION Hence, the elements presented and discussed in this short review demonstrated their relevance to the physiological control of NAFLD, opening perspectives for research to develop new strategy to treat fatty liver diseases.
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Affiliation(s)
- Camila Cristiane Pansa
- Departamento de Biologia Geral e Aplicada, Cellular Signalling and Gene Expression Laboratory, Universidade Estadual Paulista "Júlio de Mesquita Filho", Instituto de Biociências, Rio Claro, Brazil
| | - Letícia Ramos Molica
- Departamento de Biologia Geral e Aplicada, Cellular Signalling and Gene Expression Laboratory, Universidade Estadual Paulista "Júlio de Mesquita Filho", Instituto de Biociências, Rio Claro, Brazil
| | - Karen C M Moraes
- Departamento de Biologia Geral e Aplicada, Cellular Signalling and Gene Expression Laboratory, Universidade Estadual Paulista "Júlio de Mesquita Filho", Instituto de Biociências, Rio Claro, Brazil
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29
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Ahangari M, Kirkpatrick R, Nguyen TH, Gillespie N, Kendler KS, Bacanu SA, Webb BT, Verrelli BC, Riley BP. Examining the source of increased bipolar disorder and major depressive disorder common risk variation burden in multiplex schizophrenia families. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:106. [PMID: 36434002 PMCID: PMC9700852 DOI: 10.1038/s41537-022-00317-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/03/2022] [Indexed: 11/27/2022]
Abstract
Psychotic and affective disorders often aggregate in the relatives of probands with schizophrenia, and genetic studies show substantial genetic correlation among schizophrenia, bipolar disorder, and major depressive disorder. In this study, we examined the polygenic risk burden of bipolar disorder and major depressive disorder in 257 multiplex schizophrenia families (N = 1005) from the Irish Study of High-Density Multiplex Schizophrenia Families versus 2205 ancestry-matched controls. Our results indicate that members of multiplex schizophrenia families have an increased polygenic risk for bipolar disorder and major depressive disorder compared to population controls. However, this observation is largely attributable to the part of the genetic risk that bipolar disorder or major depressive disorder share with schizophrenia due to genetic correlation, rather than the affective portion of the genetic risk unique to them. These findings suggest that a complete interpretation of cross-disorder polygenic risks in multiplex families requires an assessment of the relative contribution of shared versus unique genetic factors to account for genetic correlations across psychiatric disorders.
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Affiliation(s)
- Mohammad Ahangari
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
- Integrative Life Sciences PhD Program, Virginia Commonwealth University, Richmond, VA, USA.
| | - Robert Kirkpatrick
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Tan-Hoang Nguyen
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Nathan Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Silviu-Alin Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Bradley T Webb
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, USA
| | - Brian C Verrelli
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA, USA
| | - Brien P Riley
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
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30
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Lamri A, De Paoli M, De Souza R, Werstuck G, Anand S, Pigeyre M. Insight into genetic, biological, and environmental determinants of sexual-dimorphism in type 2 diabetes and glucose-related traits. Front Cardiovasc Med 2022; 9:964743. [PMID: 36505380 PMCID: PMC9729955 DOI: 10.3389/fcvm.2022.964743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 10/21/2022] [Indexed: 11/25/2022] Open
Abstract
There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.
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Affiliation(s)
- Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Population Health Research Institute (PHRI), Hamilton, ON, Canada
| | - Monica De Paoli
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Thrombosis and Atherosclerosis Research Institute (TaARI), Hamilton, ON, Canada
| | - Russell De Souza
- Population Health Research Institute (PHRI), Hamilton, ON, Canada,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Geoff Werstuck
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Thrombosis and Atherosclerosis Research Institute (TaARI), Hamilton, ON, Canada
| | - Sonia Anand
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Population Health Research Institute (PHRI), Hamilton, ON, Canada,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Marie Pigeyre
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Population Health Research Institute (PHRI), Hamilton, ON, Canada,*Correspondence: Marie Pigeyre
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31
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Sandholm N, Hotakainen R, Haukka JK, Jansson Sigfrids F, Dahlström EH, Antikainen AA, Valo E, Syreeni A, Kilpeläinen E, Kytölä A, Palotie A, Harjutsalo V, Forsblom C, Groop PH. Whole-exome sequencing identifies novel protein-altering variants associated with serum apolipoprotein and lipid concentrations. Genome Med 2022; 14:132. [PMID: 36419110 PMCID: PMC9685920 DOI: 10.1186/s13073-022-01135-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/04/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Dyslipidemia is a major risk factor for cardiovascular disease, and diabetes impacts the lipid metabolism through multiple pathways. In addition to the standard lipid measurements, apolipoprotein concentrations provide added awareness of the burden of circulating lipoproteins. While common genetic variants modestly affect the serum lipid concentrations, rare genetic mutations can cause monogenic forms of hypercholesterolemia and other genetic disorders of lipid metabolism. We aimed to identify low-frequency protein-altering variants (PAVs) affecting lipoprotein and lipid traits. METHODS We analyzed whole-exome (WES) and whole-genome sequencing (WGS) data of 481 and 474 individuals with type 1 diabetes, respectively. The phenotypic data consisted of 79 serum lipid and apolipoprotein phenotypes obtained with clinical laboratory measurements and nuclear magnetic resonance spectroscopy. RESULTS The single-variant analysis identified an association between the LIPC p.Thr405Met (rs113298164) and serum apolipoprotein A1 concentrations (p=7.8×10-8). The burden of PAVs was significantly associated with lipid phenotypes in LIPC, RBM47, TRMT5, GTF3C5, MARCHF10, and RYR3 (p<2.9×10-6). The RBM47 gene is required for apolipoprotein B post-translational modifications, and in our data, the association between RBM47 and apolipoprotein C-III concentrations was due to a rare 21 base pair p.Ala496-Ala502 deletion; in replication, the burden of rare deleterious variants in RBM47 was associated with lower triglyceride concentrations in WES of >170,000 individuals from multiple ancestries (p=0.0013). Two PAVs in GTF3C5 were highly enriched in the Finnish population and associated with cardiovascular phenotypes in the general population. In the previously known APOB gene, we identified novel associations at two protein-truncating variants resulting in lower serum non-HDL cholesterol (p=4.8×10-4), apolipoprotein B (p=5.6×10-4), and LDL cholesterol (p=9.5×10-4) concentrations. CONCLUSIONS We identified lipid and apolipoprotein-associated variants in the previously known LIPC and APOB genes, as well as PAVs in GTF3C5 associated with LDLC, and in RBM47 associated with apolipoprotein C-III concentrations, implicated as an independent CVD risk factor. Identification of rare loss-of-function variants has previously revealed genes that can be targeted to prevent CVD, such as the LDL cholesterol-lowering loss-of-function variants in the PCSK9 gene. Thus, this study suggests novel putative therapeutic targets for the prevention of CVD.
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Affiliation(s)
- Niina Sandholm
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ronja Hotakainen
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jani K. Haukka
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Fanny Jansson Sigfrids
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Emma H. Dahlström
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anni A. Antikainen
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Erkka Valo
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anna Syreeni
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Elina Kilpeläinen
- grid.7737.40000 0004 0410 2071Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Anastasia Kytölä
- grid.7737.40000 0004 0410 2071Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Aarno Palotie
- grid.7737.40000 0004 0410 2071Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland ,grid.32224.350000 0004 0386 9924Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA ,grid.66859.340000 0004 0546 1623The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Valma Harjutsalo
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Carol Forsblom
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Per-Henrik Groop
- grid.428673.c0000 0004 0409 6302Folkhälsan Research Center, Biomedicum Helsinki, Haartmaninkatu 8, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland ,grid.7737.40000 0004 0410 2071Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland ,grid.1002.30000 0004 1936 7857Department of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria Australia
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Selvaraj MS, Li X, Li Z, Pampana A, Zhang DY, Park J, Aslibekyan S, Bis JC, Brody JA, Cade BE, Chuang LM, Chung RH, Curran JE, de Las Fuentes L, de Vries PS, Duggirala R, Freedman BI, Graff M, Guo X, Heard-Costa N, Hidalgo B, Hwu CM, Irvin MR, Kelly TN, Kral BG, Lange L, Li X, Lisa M, Lubitz SA, Manichaikul AW, Michael P, Montasser ME, Morrison AC, Naseri T, O'Connell JR, Palmer ND, Peyser PA, Reupena MS, Smith JA, Sun X, Taylor KD, Tracy RP, Tsai MY, Wang Z, Wang Y, Bao W, Wilkins JT, Yanek LR, Zhao W, Arnett DK, Blangero J, Boerwinkle E, Bowden DW, Chen YDI, Correa A, Cupples LA, Dutcher SK, Ellinor PT, Fornage M, Gabriel S, Germer S, Gibbs R, He J, Kaplan RC, Kardia SLR, Kim R, Kooperberg C, Loos RJF, Viaud-Martinez KA, Mathias RA, McGarvey ST, Mitchell BD, Nickerson D, North KE, Psaty BM, Redline S, Reiner AP, Vasan RS, Rich SS, Willer C, Rotter JI, Rader DJ, Lin X, Peloso GM, Natarajan P. Whole genome sequence analysis of blood lipid levels in >66,000 individuals. Nat Commun 2022; 13:5995. [PMID: 36220816 PMCID: PMC9553944 DOI: 10.1038/s41467-022-33510-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 09/21/2022] [Indexed: 01/05/2023] Open
Abstract
Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.
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Affiliation(s)
- Margaret Sunitha Selvaraj
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Akhil Pampana
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA
| | - David Y Zhang
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Joseph Park
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Brian E Cade
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Ren-Hua Chung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, 350, Taiwan
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, 78520, USA
| | - Lisa de Las Fuentes
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, 78520, USA
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Mariaelisa Graff
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Nancy Heard-Costa
- Department of Neurology, Boston university School of Medicine, Boston, MA, USA
| | - Bertha Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, 70112, USA
- Tulane University Translational Science Institute, New Orleans, LA, 70112, USA
| | - Brian G Kral
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Martin Lisa
- Department of Medicine, George Washington University, Washingron, DC, USA
| | - Steven A Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, 02124, USA
| | - Ani W Manichaikul
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Preuss Michael
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - May E Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Take Naseri
- Ministry of Health, Government of Samoa, Samoa, USA
| | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | | | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Xiao Sun
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, 70112, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Russell P Tracy
- Departments of Pathology & Laboratory Medicine and Biochemistry, Larner College of Medicine at the University of Vermont, Colchester, VT, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minneosta, Minneapolis, MN, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Wei Bao
- Institute of Public Health, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230026, China
| | - John T Wilkins
- Department of Medicine (Cardiology) and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Donna K Arnett
- Dean's Office, University of Kentucky College of Public Health, Lexington, KY, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, 78520, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Yii-Der Ida Chen
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Adolfo Correa
- Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Susan K Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, 02124, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, 7722, USA
| | | | - Soren Germer
- New York Genome Center, New York, NY, 10013, USA
| | - Richard Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, 77030, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, 70112, USA
- Tulane University Translational Science Institute, New Orleans, LA, 70112, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | | | - Rasika A Mathias
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Stephen T McGarvey
- Department of Epidemiology, International Health Institute, Brown University, Providence, RI, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Deborah Nickerson
- University of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA
| | - Kari E North
- Department of Epidemiology, UNC Chapel Hill, Chapel Hill, NC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Ramachandran S Vasan
- Sections of Preventive medicine and Epidemiology, Cardiovascular medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Stephen S Rich
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Cristen Willer
- University of Michigan, Internal Medicine, Ann Arbor, MI, 48109, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Daniel J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Statistics, Harvard University, Cambridge, MA, 02138, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA.
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA.
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA.
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Dean M, Moitra K, Allikmets R. The human ATP-binding cassette (ABC) transporter superfamily. Hum Mutat 2022; 43:1162-1182. [PMID: 35642569 PMCID: PMC9357071 DOI: 10.1002/humu.24418] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 05/26/2022] [Accepted: 05/27/2022] [Indexed: 11/12/2022]
Abstract
The ATP-binding cassette (ABC) transporter superfamily comprises membrane proteins that efflux various substrates across extra- and intracellular membranes. Mutations in ABC genes cause 21 human disorders or phenotypes with Mendelian inheritance, including cystic fibrosis, adrenoleukodystrophy, retinal degeneration, cholesterol, and bile transport defects. To provide tools to study the function of human ABC transporters we compiled data from multiple genomics databases. We analyzed ABC gene conservation within human populations and across vertebrates and surveyed phenotypes of ABC gene mutations in mice. Most mouse ABC gene disruption mutations have a phenotype that mimics human disease, indicating they are applicable models. Interestingly, several ABCA family genes, whose human function is unknown, have cholesterol level phenotypes in the mouse. Genome-wide association studies confirm and extend ABC traits and suggest several new functions to investigate. Whole-exome sequencing of tumors from diverse cancer types demonstrates that mutations in ABC genes are not common in cancer, but specific genes are overexpressed in select tumor types. Finally, an analysis of the frequency of loss-of-function mutations demonstrates that many human ABC genes are essential with a low level of variants, while others have a higher level of genetic diversity.
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Affiliation(s)
- Michael Dean
- Laboratory of Translational Genomics, National Cancer Institute, Gaithersburg, Maryland 21702
| | | | - Rando Allikmets
- Department of Ophthalmology, Columbia University, New York, New York, 10032
- Department of Pathology & Cell Biology, Columbia University, New York, New York, 10032
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Exploring Lead loci shared between schizophrenia and Cardiometabolic traits. BMC Genomics 2022; 23:617. [PMID: 36008755 PMCID: PMC9414090 DOI: 10.1186/s12864-022-08766-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 07/13/2022] [Indexed: 11/10/2022] Open
Abstract
Individuals with schizophrenia (SCZ) have, on average, a 10- to 20-year shorter expected life span than the rest of the population, primarily due to cardiovascular disease comorbidity. Genome-wide association studies (GWAS) have previously been used to separately identify common variants in SCZ and cardiometabolic traits. However, genetic variants jointly influencing both traits remain to be fully characterised. To assess overlaps (if any) between the genetic architecture of SCZ and cardiometabolic traits, we used conditional false discovery rate (FDR) and local genetic correlation statistical framework analyses. A conjunctional FDR was used to identify shared genetic traits between SCZ and cardiometabolic risk factors. We identified 144 genetic variants which were shared between SCZ and body mass index (BMI), and 15 variants shared between SCZ and triglycerides (TG). Furthermore, we discovered four novel single nucleotide polymorphisms (SNPs) (rs3865350, rs9860913, rs13307 and rs9614186) and four proximate genes (DERL2, SNX4, LY75 and EFCAB6) which were shared by SCZ and BMI. We observed that the novel genetic variant rs13307 and the most proximate gene LY75 exerted potential effects on SCZ and BMI comorbidity. Also, we observed a mixture of concordant and opposite direction associations with shared genetic variants. We demonstrated a moderate to high genetic overlap between SCZ and cardiometabolic traits associated with a pattern of bidirectional associations. Our data suggested a complex interplay between metabolism-related gene pathways in SCZ pathophysiology.
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Nutrigenetic Interaction of Spontaneously Hypertensive Rat Chromosome 20 Segment and High-Sucrose Diet Sensitizes to Metabolic Syndrome. Nutrients 2022; 14:nu14163428. [PMID: 36014934 PMCID: PMC9416443 DOI: 10.3390/nu14163428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/17/2022] [Accepted: 08/19/2022] [Indexed: 11/16/2022] Open
Abstract
Several corresponding regions of human and mammalian genomes have been shown to affect sensitivity to the manifestation of metabolic syndrome via nutrigenetic interactions. In this study, we assessed the effect of sucrose administration in a newly established congenic strain BN.SHR20, in which a limited segment of rat chromosome 20 from a metabolic syndrome model, spontaneously hypertensive rat (SHR), was introgressed into Brown Norway (BN) genomic background. We mapped the extent of the differential segment and compared the genomic sequences of BN vs. SHR within the segment in silico. The differential segment of SHR origin in BN.SHR20 spans about 9 Mb of the telomeric portion of the short arm of chromosome 20. We identified non-synonymous mutations e.g., in ApoM, Notch4, Slc39a7, Smim29 genes and other variations in or near genes associated with metabolic syndrome in human genome-wide association studies. Male rats of BN and BN.SHR20 strains were fed a standard diet for 18 weeks (control groups) or 16 weeks of standard diet followed by 14 days of high-sucrose diet (HSD). We assessed the morphometric and metabolic profiles of all groups. Adiposity significantly increased only in BN.SHR20 after HSD. Fasting glycemia and the glucose levels during the oral glucose tolerance test were higher in BN.SHR20 than in BN groups, while insulin levels were comparable. The fasting levels of triacylglycerols were the highest in sucrose-fed BN.SHR20, both compared to the sucrose-fed BN and the control BN.SHR20. The non-esterified fatty acids and total cholesterol concentrations were higher in BN.SHR20 compared to their respective BN groups, and the HSD elicited an increase in non-esterified fatty acids only in BN.SHR20. In a new genetically defined model, we have isolated a limited genomic region involved in nutrigenetic sensitization to sucrose-induced metabolic disturbances.
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Yeh KH, Wan HL, Teng MS, Chou HH, Hsu LA, Ko YL. Genetic Variants at the APOE Locus Predict Cardiometabolic Traits and Metabolic Syndrome: A Taiwan Biobank Study. Genes (Basel) 2022; 13:genes13081366. [PMID: 36011277 PMCID: PMC9407549 DOI: 10.3390/genes13081366] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 07/20/2022] [Accepted: 07/26/2022] [Indexed: 12/10/2022] Open
Abstract
Several apolipoprotein genes are located at the APOE locus on chromosome 19q13.32. This study explored the genetic determinants of cardiometabolic traits and metabolic syndrome at the APOE locus in a Taiwanese population. A total of 81,387 Taiwan Biobank (TWB) participants were enrolled to undergo genotype−phenotype analysis using data from the Axiom Genome-Wide CHB arrays. Regional association analysis with conditional analysis revealed lead single-nucleotide variations (SNVs) at the APOE locus: APOE rs7412 and rs429358 for total, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) cholesterol levels; CLPTM1 rs3786505 and rs11672748 for LDL and HDL cholesterol levels; and APOC1 rs438811 and APOE-APOC1 rs439401 for serum triglyceride levels. Genotype−phenotype association analysis revealed a significant association of rs429358 and rs438811 with metabolic syndrome and of rs7412, rs438811, and rs439401 with serum albumin levels (p < 0.0015). Stepwise regression analysis indicated that CLPTM1 variants were independently associated with LDL and HDL cholesterol levels (p = 3.10 × 10−15 for rs3786505 and p = 1.48 × 10−15 for rs11672748, respectively). APOE rs429358 and APOC1 rs438811 were also independently associated with metabolic syndrome (p = 2.29 × 10−14) and serum albumin levels (p = 3.80 × 10−6), respectively. In conclusion, in addition to APOE variants, CLPTM1 is a novel candidate locus for LDL and HDL cholesterol levels at the APOE gene region in Taiwan. Our data also indicated that APOE and APOC1 variants were independently associated with metabolic syndrome and serum albumin levels, respectively. These results revealed the crucial role of genetic variants at the APOE locus in predicting cardiometabolic traits and metabolic syndrome.
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Affiliation(s)
- Kuan-Hung Yeh
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan; (K.-H.Y.); (H.-H.C.)
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
| | - Hsiang-Lin Wan
- Division of Hematology/Oncology, Department of Internal Medicine, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan;
| | - Ming-Sheng Teng
- Department of Research, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan;
| | - Hsin-Hua Chou
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan; (K.-H.Y.); (H.-H.C.)
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
| | - Lung-An Hsu
- The First Cardiovascular Division, Department of Internal Medicine, Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Taoyuan 33305, Taiwan;
| | - Yu-Lin Ko
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan; (K.-H.Y.); (H.-H.C.)
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
- Department of Research, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan;
- Correspondence: ; Tel.: +886-2-6628-9779 (ext. 5355); Fax: +886-2-6628-9009
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Tang F, Duan C, Li R, Zhang H, Mo X. Identification of RNA modification-associated single nucleotide polymorphisms in genomic loci for low-density lipoprotein cholesterol concentrations. Pharmacogenomics 2022; 23:655-665. [PMID: 35880552 DOI: 10.2217/pgs-2022-0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Introduction: Genome-wide association studies have identified approximately 1000 lipid-associated loci, but functional variants are less known. Materials & methods: The authors identified RNA modification-related single nucleotide polymorphisms (RNAm-SNPs) in summary data from a genome-wide association study. By applying Mendelian randomization analysis, the authors identified gene expression levels involved in the regulation of RNAm-SNPs on low-density lipoprotein cholesterol (LDL-C) levels. Results: The authors identified 391 RNAm-SNPs that were significantly associated with LDL-C levels. RNAm-SNPs in NPC1L1, LDLR, APOB, MYLIP, LDLRAP1 and ABCA6 were identified. The RNAm-SNPs were associated with gene expression. The expression levels of 112 genes were associated with LDL-C levels, and some of them (e.g., APOB, SMARCA4 and SH2B3) were associated with coronary artery disease. Conclusion: This study identified many RNAm-SNPs in LDL-C loci and elucidated the relationship among the SNPs, gene expression and LDL-C.
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Affiliation(s)
- Fan Tang
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive & Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, China
| | - Chengcheng Duan
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive & Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, China
| | - Ru Li
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive & Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, China
| | - Huan Zhang
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive & Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, China
| | - Xingbo Mo
- Department of Epidemiology, Jiangsu Key Laboratory of Preventive & Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, China.,Center for Genetic Epidemiology & Genomics, School of Public Health, Medical College of Soochow University, China
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Ahangari M, Gentry AE, Nguyen TH, Kirkpatrick R, Verrelli BC, Bacanu SA, Kendler KS, Webb BT, Riley BP. Evaluating the role of common risk variation in the recurrence risk of schizophrenia in multiplex schizophrenia families. Transl Psychiatry 2022; 12:291. [PMID: 35864105 PMCID: PMC9304393 DOI: 10.1038/s41398-022-02060-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/05/2022] [Indexed: 12/13/2022] Open
Abstract
Multiplex families have higher recurrence risk of schizophrenia compared to the families of sporadic cases, but the source of this increased recurrence risk is unknown. We used schizophrenia genome-wide association study data (N = 156,509) to construct polygenic risk scores (PRS) in 1005 individuals from 257 multiplex schizophrenia families, 2114 ancestry-matched sporadic cases, and 2205 population controls, to evaluate whether increased PRS can explain the higher recurrence risk of schizophrenia in multiplex families compared to ancestry-matched sporadic cases. Using mixed-effects logistic regression with family structure modeled as a random effect, we show that SCZ PRS in familial cases does not differ significantly from sporadic cases either with, or without family history (FH) of psychotic disorders (All sporadic cases p = 0.90, FH+ cases p = 0.88, FH- cases p = 0.82). These results indicate that increased burden of common schizophrenia risk variation as indexed by current SCZ PRS, is unlikely to account for the higher recurrence risk of schizophrenia in multiplex families. In the absence of elevated PRS, segregation of rare risk variation or environmental influences unique to the families may explain the increased familial recurrence risk. These findings also further validate a genetically influenced psychosis spectrum, as shown by a continuous increase of common SCZ risk variation burden from unaffected relatives to schizophrenia cases in multiplex families. Finally, these results suggest that common risk variation loading are unlikely to be predictive of schizophrenia recurrence risk in the families of index probands, and additional components of genetic risk must be identified and included in order to improve recurrence risk prediction.
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Affiliation(s)
- Mohammad Ahangari
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Integrative Life Sciences PhD Program, Virginia Commonwealth University, Richmond, VA USA
| | - Amanda E. Gentry
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA
| | | | - Tan-Hoang Nguyen
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Robert Kirkpatrick
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Brian C. Verrelli
- grid.224260.00000 0004 0458 8737Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA USA
| | - Silviu-Alin Bacanu
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Kenneth S. Kendler
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA USA
| | - Bradley T. Webb
- grid.505215.6GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI, Richmond, VA USA
| | - Brien P. Riley
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA USA
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Wingo AP, Vattathil SM, Liu J, Fan W, Cutler DJ, Levey AI, Schneider JA, Bennett DA, Wingo TS. LDL cholesterol is associated with higher AD neuropathology burden independent of APOE. J Neurol Neurosurg Psychiatry 2022; 93:jnnp-2021-328164. [PMID: 35772923 PMCID: PMC9380478 DOI: 10.1136/jnnp-2021-328164] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 06/07/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE APOE is a strong risk factor for Alzheimer's disease (AD) and associated with higher low-density lipoprotein cholesterol (LDL-C) levels. Moreover, LDL-C is associated with the development of clinically ascertained AD; however, whether this association is present with the underlying neuropathological manifestations of AD or whether it is independent of the effect of APOE is unknown and is the focus of this paper. METHODS Individuals in the Religious Orders Study/Memory and Ageing Project cohorts with longitudinal measures of blood lipids and detailed autopsies were studied. We modelled the relationship between blood lipids and 12 age-related brain pathologies using a linear mixed model adjusted for potential confounding factors and stratified by APOE genotype with overall significance determined by meta-analysis. Blood lipids considered were LDL-C, high-density lipoprotein cholesterol and triglycerides. Brain pathologies included AD pathology measured by silver staining (Braak stage, a modified Consortium to Establish a Registry for Alzheimer's Disease [CERAD] score and global AD pathology) and immunohistochemistry (beta-amyloid and neurofibrillary tangles) as well as cerebral microinfarct, cerebral macroinfarct, cerebral amyloid angiopathy, cerebral atherosclerosis, hippocampal sclerosis, TDP-43 cytoplasmic inclusions and Lewy bodies. RESULTS 559 participants (69.1% female) had complete data for analysis. They were followed for a median of 7 years and a median of 3 years prior to dementia onset. LDL-C was associated with all measures of AD neuropathology (neurofibrillary tangles, beta-amyloid, Braak stage, modified CERAD score and global AD pathology) and cerebral amyloid angiopathy independent of APOE after adjusting for age, sex, cholesterol-lowering medication use, body mass index, smoking and education at false discovery rate (FDR) p-value <0.05. CONCLUSIONS These findings implicate LDL-C in the pathophysiology of AD independent of APOE and suggest LDL-C is a modifiable risk factor for AD.
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Affiliation(s)
- Aliza P Wingo
- Division of Mental Health, Atlanta VA Medical Center, Decatur, Georgia, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Selina M Vattathil
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Jiaqi Liu
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Wen Fan
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David J Cutler
- Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Allan I Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
- Goizueta Alzheimer's Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Julie A Schneider
- Departments of Pathology and Neurological Science, Rush Alzheimer's Disease Center, Rush University, Chicago, Illinois, USA
- Rush Alzheimer's Disease Center, Rush University, Chicago, Illinois, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University, Chicago, Illinois, USA
| | - Thomas S Wingo
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
- Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
- Goizueta Alzheimer's Disease Center, Emory University School of Medicine, Atlanta, GA, USA
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An LDLR missense variant poses high risk of familial hypercholesterolemia in 30% of Greenlanders and offers potential of early cardiovascular disease intervention. HGG ADVANCES 2022; 3:100118. [PMID: 36267056 PMCID: PMC9577620 DOI: 10.1016/j.xhgg.2022.100118] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/11/2022] [Indexed: 11/25/2022] Open
Abstract
The common Arctic-specific LDLR p.G137S variant was recently shown to be associated with elevated lipid levels. Motivated by this, we aimed to investigate the effect of p.G137S on metabolic health and cardiovascular disease risk among Greenlanders to quantify its impact on the population. In a population-based Greenlandic cohort (n = 5,063), we tested for associations between the p.G137S variant and metabolic health traits as well as cardiovascular disease risk based on registry data. In addition, we explored the variant’s impact on plasma NMR measured lipoprotein concentration and composition in another Greenlandic cohort (n = 1,629); 29.5% of the individuals in the cohort carried at least one copy of the p.G137S risk allele. Furthermore, 25.4% of the heterozygous and 54.7% of the homozygous carriers had high levels (>4.9 mmol/L) of serum LDL cholesterol, which is above the diagnostic level for familial hypercholesterolemia (FH). Moreover, p.G137S was associated with an overall atherosclerotic lipid profile, and increased risk of ischemic heart disease (HR [95% CI], 1.51 [1.18–1.92], p = 0.00096), peripheral artery disease (1.69 [1.01–2.82], p = 0.046), and coronary operations (1.78 [1.21–2.62], p = 0.0035). Due to its high frequency and large effect sizes, p.G137S has a marked population-level impact, increasing the risk of FH and cardiovascular disease for up to 30% of the Greenlandic population. Thus, p.G137S is a potential marker for early intervention in Arctic populations.
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Gene-lifestyle interactions in the genomics of human complex traits. Eur J Hum Genet 2022; 30:730-739. [PMID: 35314805 PMCID: PMC9178041 DOI: 10.1038/s41431-022-01045-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 12/22/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Abstract
The role and biological significance of gene-environment interactions in human traits and diseases remain poorly understood. To address these questions, the CHARGE Gene-Lifestyle Interactions Working Group conducted series of genome-wide interaction studies (GWIS) involving up to 610,475 individuals across four ancestries for three lipids and four blood pressure traits, while accounting for interaction effects with drinking and smoking exposures. Here we used GWIS summary statistics from these studies to decipher potential differences in genetic associations and G×E interactions across phenotype-exposure-ancestry combinations, and to derive insights on the potential mechanistic underlying G×E through in-silico functional analyses. Our analyses show first that interaction effects likely contribute to the commonly reported ancestry-specific genetic effect in complex traits, and second, that some phenotype-exposures pairs are more likely to benefit from a greater detection power when accounting for interactions. It also highlighted modest correlation between marginal and interaction effects, providing material for future methodological development and biological discussions. We also estimated contributions to phenotypic variance, including in particular the genetic heritability conditional on the exposure, and heritability partitioned across a range of functional annotations and cell types. In these analyses, we found multiple instances of potential heterogeneity of functional partitions between exposed and unexposed individuals, providing new evidence for likely exposure-specific genetic pathways. Finally, along this work, we identified potential biases in methods used to jointly meta-analyze genetic and interaction effects. We performed simulations to characterize these limitations and to provide the community with guidelines for future G×E studies.
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Jurado-Camacho PA, Cid-Soto MA, Barajas-Olmos F, García-Ortíz H, Baca-Peynado P, Martínez-Hernández A, Centeno-Cruz F, Contreras-Cubas C, González-Villalpando ME, Saldaña-Álvarez Y, Salas-Martinez G, Mendoza-Caamal EC, González-Villalpando C, Córdova EJ, Orozco L. Exome Sequencing Data Analysis and a Case-Control Study in Mexican Population Reveals Lipid Trait Associations of New and Known Genetic Variants in Dyslipidemia-Associated Loci. Front Genet 2022; 13:807381. [PMID: 35669185 PMCID: PMC9164108 DOI: 10.3389/fgene.2022.807381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Plasma lipid levels are a major risk factor for cardiovascular diseases. Although international efforts have identified a group of loci associated with the risk of dyslipidemia, Latin American populations have been underrepresented in these studies.Objective: To know the genetic variation occurring in lipid-related loci in the Mexican population and its association with dyslipidemia.Methods: We searched for single-nucleotide variants in 177 lipid candidate genes using previously published exome sequencing data from 2838 Mexican individuals belonging to three different cohorts. With the extracted variants, we performed a case-control study. Logistic regression and quantitative trait analyses were implemented in PLINK software. We used an LD pruning using a 50-kb sliding window size, a 5-kb window step size and a r2 threshold of 0.1.Results: Among the 34251 biallelic variants identified in our sample population, 33% showed low frequency. For case-control study, we selected 2521 variants based on a minor allele frequency ≥1% in all datasets. We found 19 variants in 9 genes significantly associated with at least one lipid trait, with the most significant associations found in the APOA1/C3/A4/A5-ZPR1-BUD13 gene cluster on chromosome 11. Notably, all 11 variants associated with hypertriglyceridemia were within this cluster; whereas variants associated with hypercholesterolemia were located at chromosome 2 and 19, and for low high density lipoprotein cholesterol were in chromosomes 9, 11, and 19. No significant associated variants were found for low density lipoprotein. We found several novel variants associated with different lipemic traits: rs3825041 in BUD13 with hypertriglyceridemia, rs7252453 in CILP2 with decreased risk to hypercholesterolemia and rs11076176 in CETP with increased risk to low high density lipoprotein cholesterol.Conclusions: We identified novel variants in lipid-regulation candidate genes in the Mexican population, an underrepresented population in genomic studies, demonstrating the necessity of more genomic studies on multi-ethnic populations to gain a deeper understanding of the genetic structure of the lipemic traits.
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Affiliation(s)
- Pedro A. Jurado-Camacho
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
- Posgraduate in Biomedical Sciences, National Autonomous University of Mexico, Mexico City, Mexico
| | - Miguel A. Cid-Soto
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Francisco Barajas-Olmos
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Humberto García-Ortíz
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Paulina Baca-Peynado
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
- Posgraduate in Biomedical Sciences, National Autonomous University of Mexico, Mexico City, Mexico
| | - Angélica Martínez-Hernández
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Federico Centeno-Cruz
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Cecilia Contreras-Cubas
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | - María Elena González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigación en Diabetes y Riesgo Cardiovascular, Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | - Yolanda Saldaña-Álvarez
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Guadalupe Salas-Martinez
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
| | | | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigación en Diabetes y Riesgo Cardiovascular, Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | - Emilio J. Córdova
- Oncogenomics Consortium Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
- *Correspondence: Emilio J. Córdova, ; Lorena Orozco,
| | - Lorena Orozco
- Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
- *Correspondence: Emilio J. Córdova, ; Lorena Orozco,
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Lipoprotein(a) beyond the kringle IV repeat polymorphism: The complexity of genetic variation in the LPA gene. Atherosclerosis 2022; 349:17-35. [PMID: 35606073 PMCID: PMC7613587 DOI: 10.1016/j.atherosclerosis.2022.04.003] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 02/23/2022] [Accepted: 04/01/2022] [Indexed: 12/24/2022]
Abstract
High lipoprotein(a) [Lp(a)] concentrations are one of the most important genetically determined risk factors for cardiovascular disease. Lp(a) concentrations are an enigmatic trait largely controlled by one single gene (LPA) that contains a complex interplay of several genetic elements with many surprising effects discussed in this review. A hypervariable coding copy number variation (the kringle IV type-2 repeat, KIV-2) generates >40 apolipoprotein(a) protein isoforms and determines the median Lp(a) concentrations. Carriers of small isoforms with up to 22 kringle IV domains have median Lp(a) concentrations up to 5 times higher than those with large isoforms (>22 kringle IV domains). The effect of the apo(a) isoforms are, however, modified by many functional single nucleotide polymorphisms (SNPs) distributed over the complete range of allele frequencies (<0.1% to >20%) with very pronounced effects on Lp(a) concentrations. A complex interaction is present between the apo (a) isoforms and LPA SNPs, with isoforms partially masking the effect of functional SNPs and, vice versa, SNPs lowering the Lp(a) concentrations of affected isoforms. This picture is further complicated by SNP-SNP interactions, a poorly understood role of other polymorphisms such as short tandem repeats and linkage structures that are poorly captured by common R2 values. A further layer of complexity derives from recent findings that several functional SNPs are located in the KIV-2 repeat and are thus not accessible to conventional sequencing and genotyping technologies. A critical impact of the ancestry on correlation structures and baseline Lp(a) values becomes increasingly evident. This review provides a comprehensive overview on the complex genetic architecture of the Lp(a) concentrations in plasma, a field that has made tremendous progress with the introduction of new technologies. Understanding the genetics of Lp(a) might be a key to many mysteries of Lp(a) and booster new ideas on the metabolism of Lp(a) and possible interventional targets.
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An Amish founder population reveals rare-population genetic determinants of the human lipidome. Commun Biol 2022; 5:334. [PMID: 35393526 PMCID: PMC8989972 DOI: 10.1038/s42003-022-03291-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 03/17/2022] [Indexed: 12/02/2022] Open
Abstract
Identifying the genetic determinants of inter-individual variation in lipid species (lipidome) may provide deeper understanding and additional insight into the mechanistic effect of complex lipidomic pathways in CVD risk and progression beyond simple traditional lipids. Previous studies have been largely population based and thus only powered to discover associations with common genetic variants. Founder populations represent a powerful resource to accelerate discovery of previously unknown biology associated with rare population alleles that have risen to higher frequency due to genetic drift. We performed a genome-wide association scan of 355 lipid species in 650 individuals from the Amish founder population including 127 lipid species not previously tested. To the best of our knowledge, we report for the first time the lipid species associated with two rare-population but Amish-enriched lipid variants: APOB_rs5742904 and APOC3_rs76353203. We also identified novel associations for 3 rare-population Amish-enriched loci with several sphingolipids and with proposed potential functional/causal variant in each locus including GLTPD2_rs536055318, CERS5_rs771033566, and AKNA_rs531892793. We replicated 7 previously known common loci including novel associations with two sterols: androstenediol with UGT locus and estriol with SLC22A8/A24 locus. Our results show the double power of founder populations and detailed lipidome to discover novel trait-associated variants. A GWAS of 355 lipid species in the Old Order Amish founder population reveals associations between Amish-enriched loci and several sphingolipids.
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Weissbrod O, Kanai M, Shi H, Gazal S, Peyrot WJ, Khera AV, Okada Y, Martin AR, Finucane HK, Price AL. Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores. Nat Genet 2022; 54:450-458. [PMID: 35393596 PMCID: PMC9009299 DOI: 10.1038/s41588-022-01036-9] [Citation(s) in RCA: 108] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 02/25/2022] [Indexed: 01/25/2023]
Abstract
Polygenic risk scores suffer reduced accuracy in non-European populations, exacerbating health disparities. We propose PolyPred, a method that improves cross-population polygenic risk scores by combining two predictors: a new predictor that leverages functionally informed fine-mapping to estimate causal effects (instead of tagging effects), addressing linkage disequilibrium differences, and BOLT-LMM, a published predictor. When a large training sample is available in the non-European target population, we propose PolyPred+, which further incorporates the non-European training data. We applied PolyPred to 49 diseases/traits in four UK Biobank populations using UK Biobank British training data, and observed relative improvements versus BOLT-LMM ranging from +7% in south Asians to +32% in Africans, consistent with simulations. We applied PolyPred+ to 23 diseases/traits in UK Biobank east Asians using both UK Biobank British and Biobank Japan training data, and observed improvements of +24% versus BOLT-LMM and +12% versus PolyPred. Summary statistics-based analogs of PolyPred and PolyPred+ attained similar improvements.
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Affiliation(s)
- Omer Weissbrod
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA.
| | - Masahiro Kanai
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Huwenbo Shi
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA
- OMNI Bioinformatics, San Francisco, CA, USA
| | - Steven Gazal
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Wouter J Peyrot
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Amit V Khera
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Hilary K Finucane
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alkes L Price
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Chemello K, Blom DJ, Marais AD, Lambert G, Blanchard V. Genetic and Mechanistic Insights into the Modulation of Circulating Lipoprotein (a) Concentration by Apolipoprotein E Isoforms. Curr Atheroscler Rep 2022; 24:399-405. [PMID: 35355214 DOI: 10.1007/s11883-022-01016-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/04/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE OF REVIEW Lipoprotein (a) [Lp(a)] is a highly atherogenic lipoprotein species. A unique feature of Lp(a) is the strong genetic determination of its concentration. The LPA gene is responsible for up to 90% of the variance in Lp(a), but other genes also have an impact. RECENT FINDINGS Genome-wide associations studies indicate that the APOE gene, encoding apolipoprotein E (apoE), is the second most important locus modulating Lp(a) concentrations. Population studies clearly show that carriers of the apoE2 variant (ε2) display reduced Lp(a) levels, the lowest concentrations being observed in ε2/ε2 homozygotes. This genotype can lead predisposed adults to develop dysbetalipoproteinemia, a lipid disorder characterized by sharp elevations in cholesterol and triglycerides. However, dysbetalipoproteinemia does not significantly modulate circulating Lp(a). Mechanistically, apoE appears to impair the production but not the catabolism of Lp(a). These observations underline the complexity of Lp(a) metabolism and provide key insights into the pathways governing Lp(a) synthesis and secretion.
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Affiliation(s)
- Kévin Chemello
- Laboratoire Inserm, UMR 1188 DéTROI, Université de La Réunion, 2 Rue Maxime Rivière, 97490, Sainte Clotilde, France
| | - Dirk J Blom
- Division of Lipidology and Cape Heart Institute, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - A David Marais
- Division of Chemical Pathology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Gilles Lambert
- Laboratoire Inserm, UMR 1188 DéTROI, Université de La Réunion, 2 Rue Maxime Rivière, 97490, Sainte Clotilde, France.
| | - Valentin Blanchard
- Laboratoire Inserm, UMR 1188 DéTROI, Université de La Réunion, 2 Rue Maxime Rivière, 97490, Sainte Clotilde, France.,Departments of Medicine, Centre for Heart Lung Innovation, Providence Healthcare Research Institute, St. Paul's Hospital, University of British Columbia, Vancouver, Canada
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47
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Metz S, Krarup NT, Bryrup T, Støy J, Andersson EA, Christoffersen C, Neville MJ, Christiansen MR, Jonsson AE, Witte DR, Kampmann U, Nielsen LB, Jørgensen NR, Karpe F, Grarup N, Pedersen O, Kilpeläinen TO, Hansen T. The Arg82Cys polymorphism of the protein nepmucin implies a role in HDL metabolism. J Endocr Soc 2022; 6:bvac034. [PMID: 35382499 PMCID: PMC8974852 DOI: 10.1210/jendso/bvac034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Indexed: 12/02/2022] Open
Abstract
Context Blood lipid levels are linked to the risk of cardiovascular disease and regulated by genetic factors. A low-frequency polymorphism Arg82Cys (rs72836561) in the membrane protein nepmucin, encoded by CD300LG, is associated with lower fasting concentration of high-density lipoprotein cholesterol (HDLc) and higher fasting triglycerides. However, whether the variant is linked to postprandial lipids and glycemic status remains elusive. Objective Here, we augment the genetic effect of Arg82Cys on fasting plasma concentrations of HDL subclasses, postprandial lipemia after a standardized high-fat meal, and glycemic status to further untangle its role in HDL metabolism. Methods We elucidated fasting associations with HDL subclasses in a population-based cohort study (Oxford BioBank, OBB), including 4522 healthy men and women. We investigated fasting and postprandial consequences on HDL metabolism in recall-by-genotype (RbG) studies (fasting: 20 carrier/20 noncarrier; postprandial: 7 carrier/17 noncarrier), and shed light on the synergistic interaction with glycemic status. Results A lower fasting plasma concentration of cholesterol in large HDL particles was found in healthy male carriers of the Cys82 polymorphism compared to noncarriers, both in the OBB (P = .004) and RbG studies (P = .005). In addition, the Cys82 polymorphism was associated with low fasting plasma concentrations of ApoA1 (P = .008) in the OBB cohort. On the contrary, we did not find differences in postprandial lipemia or 2-hour plasma glucose levels. Conclusion Taken together, our results indicate an association between the Arg82Cys variant and a lower concentration of HDL particles and HDLc, especially in larger HDL subclasses, suggesting a link between nepmucin and HDLc metabolism or maturation.
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Affiliation(s)
- Sophia Metz
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nikolaj T Krarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Aalborg University Hospital, Department of Cardiology, Aalborg, Denmark
| | - Thomas Bryrup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Julie Støy
- Aarhus University Hospital, Steno Diabetes Center Aarhus, Aarhus, Denmark
| | - Ehm A Andersson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christina Christoffersen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matt J Neville
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Malene R Christiansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anna E Jonsson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Daniel R Witte
- Department of Public Health, Section of Epidemiology, Aarhus University, Denmark
| | - Ulla Kampmann
- Aarhus University Hospital, Steno Diabetes Center Aarhus, Aarhus, Denmark
| | - Lars B Nielsen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Faculty of Health, Aarhus University, Aarhus, Denmark
| | - Niklas R Jørgensen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen Denmark
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health, University of Southern Denmark, Odense, Denmark
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Li X, Yung G, Zhou H, Sun R, Li Z, Hou K, Zhang MJ, Liu Y, Arapoglou T, Wang C, Ionita-Laza I, Lin X. A multi-dimensional integrative scoring framework for predicting functional variants in the human genome. Am J Hum Genet 2022; 109:446-456. [PMID: 35216679 PMCID: PMC8948160 DOI: 10.1016/j.ajhg.2022.01.017] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 01/26/2022] [Indexed: 12/26/2022] Open
Abstract
Attempts to identify and prioritize functional DNA elements in coding and non-coding regions, particularly through use of in silico functional annotation data, continue to increase in popularity. However, specific functional roles can vary widely from one variant to another, making it challenging to summarize different aspects of variant function with a one-dimensional rating. Here we propose multi-dimensional annotation-class integrative estimation (MACIE), an unsupervised multivariate mixed-model framework capable of integrating annotations of diverse origin to assess multi-dimensional functional roles for both coding and non-coding variants. Unlike existing one-dimensional scoring methods, MACIE views variant functionality as a composite attribute encompassing multiple characteristics and estimates the joint posterior functional probabilities of each genomic position. This estimate offers more comprehensive and interpretable information in the presence of multiple aspects of functionality. Applied to a variety of independent coding and non-coding datasets, MACIE demonstrates powerful and robust performance in discriminating between functional and non-functional variants. We also show an application of MACIE to fine-mapping and heritability enrichment analysis by using the lipids GWAS summary statistics data from the European Network for Genetic and Genomic Epidemiology Consortium.
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Affiliation(s)
- Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Godwin Yung
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Methods, Collaboration and Outreach Group, Genentech/Roche, South San Francisco, CA 94080, USA
| | - Hufeng Zhou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Ryan Sun
- Department of Biostatistics, University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Kangcheng Hou
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Martin Jinye Zhang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Yaowu Liu
- School of Statistics, Southwestern University of Finance and Economics, Chengdu, Sichuan, China
| | - Theodore Arapoglou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Chen Wang
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Iuliana Ionita-Laza
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY 10032, USA.
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Statistics, Harvard University, Cambridge, MA, 02138, USA.
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49
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Pfisterer SG, Brock I, Kanerva K, Hlushchenko I, Paavolainen L, Ripatti P, Islam MM, Kyttälä A, Di Taranto MD, Scotto di Frega A, Fortunato G, Kuusisto J, Horvath P, Ripatti S, Laakso M, Ikonen E. Multiparametric platform for profiling lipid trafficking in human leukocytes. CELL REPORTS METHODS 2022; 2:100166. [PMID: 35474963 PMCID: PMC9017167 DOI: 10.1016/j.crmeth.2022.100166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/26/2021] [Accepted: 01/18/2022] [Indexed: 11/25/2022]
Abstract
Systematic insight into cellular dysfunction can improve understanding of disease etiology, risk assessment, and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validate this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrate lipid storage data into another readout parameter, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlates positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explains hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking and has broad possible applications in dissecting the cellular basis of metabolic disorders.
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Affiliation(s)
- Simon G. Pfisterer
- Department of Anatomy, Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland
| | - Ivonne Brock
- Department of Anatomy, Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland
- Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Kristiina Kanerva
- Department of Anatomy, Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland
- Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Iryna Hlushchenko
- Department of Anatomy, Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland
| | - Lassi Paavolainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Pietari Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Mohammad Majharul Islam
- Department of Anatomy, Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland
| | - Aija Kyttälä
- Finnish Institute for Health and Welfare (THL), THL Biobank, Helsinki, Finland
| | - Maria D. Di Taranto
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Napoli, Italy
- CEINGE Biotecnologie Avanzate scarl Naples, Napoli, Italy
| | | | - Giuliana Fortunato
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Napoli, Italy
- CEINGE Biotecnologie Avanzate scarl Naples, Napoli, Italy
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Peter Horvath
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Biological Research Center, Szeged, Hungary
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Elina Ikonen
- Department of Anatomy, Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland
- Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
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50
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Wang T, Qiao J, Zhang S, Wei Y, Zeng P. Simultaneous test and estimation of total genetic effect in eQTL integrative analysis through mixed models. Brief Bioinform 2022; 23:6535679. [PMID: 35212359 DOI: 10.1093/bib/bbac038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 01/22/2022] [Accepted: 02/07/2021] [Indexed: 11/14/2022] Open
Abstract
Integration of expression quantitative trait loci (eQTL) into genome-wide association studies (GWASs) is a promising manner to reveal functional roles of associated single-nucleotide polymorphisms (SNPs) in complex phenotypes and has become an active research field in post-GWAS era. However, how to efficiently incorporate eQTL mapping study into GWAS for prioritization of causal genes remains elusive. We herein proposed a novel method termed as Mixed transcriptome-wide association studies (TWAS) and mediated Variance estimation (MTV) by modeling the effects of cis-SNPs of a gene as a function of eQTL. MTV formulates the integrative method and TWAS within a unified framework via mixed models and therefore includes many prior methods/tests as special cases. We further justified MTV from another two statistical perspectives of mediation analysis and two-stage Mendelian randomization. Relative to existing methods, MTV is superior for pronounced features including the processing of direct effects of cis-SNPs on phenotypes, the powerful likelihood ratio test for assessment of joint effects of cis-SNPs and genetically regulated gene expression (GReX), two useful quantities to measure relative genetic contributions of GReX and cis-SNPs to phenotypic variance, and the computationally efferent parameter expansion expectation maximum algorithm. With extensive simulations, we identified that MTV correctly controlled the type I error in joint evaluation of the total genetic effect and proved more powerful to discover true association signals across various scenarios compared to existing methods. We finally applied MTV to 41 complex traits/diseases available from three GWASs and discovered many new associated genes that had otherwise been missed by existing methods. We also revealed that a small but substantial fraction of phenotypic variation was mediated by GReX. Overall, MTV constructs a robust and realistic modeling foundation for integrative omics analysis and has the advantage of offering more attractive biological interpretations of GWAS results.
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Affiliation(s)
- Ting Wang
- Department of Biostatistics at Xuzhou Medical University, China
| | - Jiahao Qiao
- Department of Biostatistics at Xuzhou Medical University, China
| | - Shuo Zhang
- Department of Biostatistics at Xuzhou Medical University, China
| | - Yongyue Wei
- Department of Biostatistics at Nanjing Medical University, China
| | - Ping Zeng
- Department of Biostatistics, Center for Medical Statistics and Data Analysis and Key Laboratory of Human Genetics and Environmental Medicine at Xuzhou Medical University, China
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