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Jiang Y, Ping J, Lu H, Zhang H, Liu M, Li Y, Zhou G. Associations between high-altitude adaptation and risk of cardiovascular diseases: a bidirectional Mendelian randomization study. Mol Genet Genomics 2023; 298:1007-1021. [PMID: 37233799 DOI: 10.1007/s00438-023-02035-z] [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: 02/07/2023] [Accepted: 05/15/2023] [Indexed: 05/27/2023]
Abstract
High-altitude adaptation (HAA) was reported to be significantly associated with reduced risks for multiple cardiovascular diseases (CVDs). However, the causality and direction of the associations are largely uncharacterized. We aimed to examine the potential causal relationships between HAA and six types of CVD, including coronary artery disease (CAD), cerebral aneurysm, ischemic stroke, peripheral artery disease, arrhythmia and atrial fibrillation. We obtained the summary data from largest available genome-wide association study of HAA and six types of CVD. Two-sample bidirectional Mendelian randomization (MR) analyses were performed to infer the causality between them. In the sensitivity analyses, MR-Egger regression analyses and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global analyses were used to assess the pleiotropic effects; Cochran's Q tests were used to test the heterogeneity by inverse variance-weighted (IVW) and MR-Egger methods; and the leave-one-out analyses were used to examine whether some single nucleotide polymorphisms (SNPs) could influence the results independently. The MR main analyses showed that the genetically instrumented HAA was significantly causally associated with the reduced risks of CAD (odds ratio [OR] = 0.029; 95% confidence interval [CI] = 0.004-0.234; P = 8.64 × 10-4). In contrast, there was no statistically significant relationship between CVDs and HAA. Our findings provide evidence for the causal effects of HAA on the reduced risks of CAD. However, there is no causality of CVDs on HAA. These findings might be helpful in developing the prevention and intervention strategies for CAD.
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Affiliation(s)
- Yuqing Jiang
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing City, Jiangsu Province, 211166, People's Republic of China
| | - Jie Ping
- Department of Genetics and Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing, 100850, People's Republic of China
| | - Hao Lu
- Department of Genetics and Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing, 100850, People's Republic of China
| | - Haoxiang Zhang
- The No. 954 Hospital of PLA, Shannan City, 856100, People's Republic of China
| | - Mengyu Liu
- Department of Genetics and Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing, 100850, People's Republic of China
| | - Yuanfeng Li
- Department of Genetics and Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing, 100850, People's Republic of China.
| | - Gangqiao Zhou
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing City, Jiangsu Province, 211166, People's Republic of China.
- Department of Genetics and Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing, 100850, People's Republic of China.
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Surakka I, Wu KH, Hornsby W, Wolford BN, Shen F, Zhou W, Huffman JE, Pandit A, Hu Y, Brumpton B, Skogholt AH, Gabrielsen ME, Walters RG, Hveem K, Kooperberg C, Zöllner S, Wilson PW, Sutton NR, Daly MJ, Neale BM, Willer CJ. Multi-ancestry meta-analysis identifies 5 novel loci for ischemic stroke and reveals heterogeneity of effects between sexes and ancestries. CELL GENOMICS 2023; 3:100345. [PMID: 37601974 PMCID: PMC10435368 DOI: 10.1016/j.xgen.2023.100345] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 10/18/2022] [Accepted: 05/26/2023] [Indexed: 08/22/2023]
Abstract
Stroke is the second leading cause of death and disability worldwide. Stroke prevalence varies by sex and ancestry, possibly due to genetic heterogeneity between subgroups. We performed a genome-wide meta-analysis of 16 biobanks across multiple ancestries to study the genetics of ischemic stroke (60,176 cases, 1,310,725 controls) as part of the Global Biobank Meta-analysis Initiative (GBMI) and further combined the results with previously published MegaStroke. Five novel loci for ischemic stroke (LAMC1, CALCRL, PLSCR1, CDKN1A, and SWAP70) were identified after replication in four additional datasets. One previously reported locus showed significant ancestry heterogeneity (ABO), and one showed significant sex heterogeneity (ALDH2). The ALDH2 association was male specific (males p = 1.67e-24, females p = 0.126) and was additionally observed only in the East Asian ancestry (male) samples. These findings emphasize the need for more diverse datasets with large sample sizes to further understand the genetic predisposition of stroke in different ancestry and sex groups.
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Affiliation(s)
- Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Kuan-Han Wu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Whitney Hornsby
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Brooke N. Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Fred Shen
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jennifer E. Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Anita Pandit
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Maiken E. Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Robin G. Walters
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - The TOPMed Stroke Working Group
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Million Veteran Program (MVP)
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sebastian Zöllner
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Peter W.F. Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Nadia R. Sutton
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Cristen J. Willer
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - on behalf of the Global Biobank Meta-analysis Initiative (GBMI)
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
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103
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Teng Y, Huang DQ, Li RX, Yi C, Zhan YQ. Association Between Telomere Length and Risk of Lung Cancer in an Asian Population: A Mendelian Randomization Study. World J Oncol 2023; 14:277-284. [PMID: 37560336 PMCID: PMC10409562 DOI: 10.14740/wjon1624] [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: 05/19/2023] [Accepted: 07/19/2023] [Indexed: 08/11/2023] Open
Abstract
BACKGROUND Several traditional observational studies and Mendelian randomization (MR) studies have indicated an association between leukocyte telomere length (LTL) and the risk of lung cancer in the European population. However, the results in the Asian population are still unclear. The objective was to reveal the genetic causal association between LTL and the risk of lung cancer in the Asian population. METHODS We conducted a two-sample MR analysis using summary statistics. Instrumental variables (IVs) were obtained from the genome-wide association studies (GWAS) of LTL (n = 23,096) and lung cancer (n = 212,453) of Asian ancestry. We applied the random-effects inverse-variance weighted (IVW) model as the main method. As well, several other models were performed as complementary methods to assess the impact of potential MR assumption violations, including MR-Egger regression, weighted median, and weighted mode models. RESULTS We included eight single-nucleotide polymorphisms (SNPs) as IVs for LTL and found that LTL was significantly associated with the risk of lung cancer in the IVW model (odds ratio (OR): 1.60; 95% confidence interval (CI): 1.31 - 1.97; P = 5.96 × 10-6), which was in line with the results in the weighted median and weighted mode models. However, the relationship was not statistically significant in the MR-Egger regression model (OR: 1.44; 95% CI: 0.92 - 2.26; P = 0.160). Sensitivity analyses indicated the robustness of the results. CONCLUSIONS This two-sample MR study confirmed that longer telomere length significantly increased the risk of lung cancer in the Asian population, which was in accord with findings in the Western population.
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Affiliation(s)
- Yi Teng
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- These authors contributed equally to this work
| | - Dan Qi Huang
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- These authors contributed equally to this work
| | - Rui Xi Li
- Department of Hepatobiliary and Pancreatic Surgery, The Eighth Affiliated Hospital, Sun Yat-Sen University, China
- These authors contributed equally to this work
| | - Chao Yi
- Guangming Center for Disease Control and Prevention, Shenzhen, China
| | - Yi Qiang Zhan
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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104
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Shen S, Li Z, Jiang Y, Duan W, Li H, Du S, Esteller M, Shen H, Hu Z, Zhao Y, Christiani DC, Chen F. A Large-Scale Exome-Wide Association Study Identifies Novel Germline Mutations in Lung Cancer. Am J Respir Crit Care Med 2023; 208:280-289. [PMID: 37167549 PMCID: PMC10395715 DOI: 10.1164/rccm.202212-2199oc] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 05/11/2023] [Indexed: 05/13/2023] Open
Abstract
Rationale: Genome-wide association studies have identified common variants of lung cancer. However, the contribution of rare exome-wide variants, especially protein-coding variants, to cancers remains largely unexplored. Objectives: To evaluate the role of human exomes in genetic predisposition to lung cancer. Methods: We performed exome-wide association studies to detect the association of exomes with lung cancer in 30,312 patients and 652,902 control subjects. A scalable and accurate implementation of a generalized mixed model was used to detect the association signals for loss-of-function, missense, and synonymous variants and gene-level sets. Furthermore, we performed association and Bayesian colocalization analyses to evaluate their relationships with intermediate exposures. Measurements and Main Results: We systematically analyzed 216,739 single-nucleotide variants in the human exome. The loss-of-function variants exhibited the most notable effects on lung cancer risk. We identified four novel variants, including two missense variants (rs202197044TET3 [Pmeta (P values of meta-analysis) = 3.60 × 10-8] and rs202187871POT1 [Pmeta = 2.21 × 10-8]) and two synonymous variants (rs7447927TMEM173 [Pmeta = 1.32 × 10-9] and rs140624366ATRN [Pmeta = 2.97 × 10-9]). rs202197044TET3 was significantly associated with emphysema (odds ratio, 3.55; Pfdr = 0.015), whereas rs7447927POT1 was strongly associated with telomere length (β = 1.08; Pfdr (FDR corrected P value) = 3.76 × 10-53). Functional evidence of expression of quantitative trait loci, splicing quantitative trait loci, and isoform expression was found for the four novel genes. Gene-level association tests identified several novel genes, including POT1 (protection of telomeres 1), RTEL1, BSG, and ZNF232. Conclusions: Our findings provide insights into the genetic architecture of human exomes and their role in lung cancer predisposition.
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Affiliation(s)
- Sipeng Shen
- Department of Biostatistics and
- Jiangsu Key Lab of Cancer Biomarkers, Prevention, and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine
- China International Cooperation Center of Environment and Human Health
| | | | | | - Weiwei Duan
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, and
| | | | - Sha Du
- Department of Biostatistics and
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain
- Centro de Investigacion Biomedica en Red Cancer, Madrid, Spain
- Institucio Catalana de Recerca i Estudis Avançats, Barcelona, Spain
- Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health
- Jiangsu Key Lab of Cancer Biomarkers, Prevention, and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health
- Jiangsu Key Lab of Cancer Biomarkers, Prevention, and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine
| | - Yang Zhao
- Department of Biostatistics and
- Key Laboratory of Biomedical Big Data, Nanjing Medical University, Nanjing, China
| | - David C. Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts; and
- Pulmonary and Critical Care Division, Massachusetts General Hospital, Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Feng Chen
- Department of Biostatistics and
- Jiangsu Key Lab of Cancer Biomarkers, Prevention, and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine
- China International Cooperation Center of Environment and Human Health
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105
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Cao J, Wang Z, Zhu M, Huang Y, Jin Z, Xiong Z. Low-density lipoprotein cholesterol and risk of hepatocellular carcinoma: a Mendelian randomization and mediation analysis. Lipids Health Dis 2023; 22:110. [PMID: 37525197 PMCID: PMC10388495 DOI: 10.1186/s12944-023-01877-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 07/21/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND A previous study demonstrated that low-density lipoprotein cholesterol (LDL-C) is associated with hepatocellular carcinoma (HCC); however, the causality between them has not been proven due to conflicting research results and the interference of confounders. This study utilized Mendelian randomization (MR) to investigate the causal relationship between LDL-C and HCC and identify the mediating factors. METHODS LDL-C, HCC, and coronary artery disease (CAD) genome-wide association study (GWAS) data were obtained from a public database. To investigate causality, inverse variance weighting (IVW) was the main analysis approach. MR‒Egger, simple mode, weighted median (WM), and weighted mode were employed as supplementary analytic methods. In addition, horizontal pleiotropy and heterogeneity were tested. To evaluate the stability of the MR results, a "leave-one-out" approach was used. Multivariate MR (MVMR) was utilized to correct the confounders that might affect causality, and mediation analysis was used to investigate the potential mediating effects. Finally, we used HCC risk to infer the reverse causality with LDL-C level. RESULTS Random effects IVW results were (LDL-C-HCC: odds ratio (OR) = 0.703, 95% confidence interval (CI) = [0.508, 0.973], P = 0.034; CAD-HCC: OR = 0.722, 95% CI = [0.645, 0.808], P = 1.50 × 10-8; LDL-C-CAD: OR = 2.103, 95% CI = [1.862, 2.376], P = 5.65 × 10-33), demonstrating a causal link between LDL-C levels and a lower risk of HCC. Through MVMR, after mutual correction, the causal effect of LDL-C and CAD on HCC remained significant (P < 0.05). Through mediation analysis, it was proven that CAD mediated the causative connection between LDL-C and HCC, and the proportion of mediating effect on HCC was 58.52%. Reverse MR showed that HCC could affect LDL-C levels with a negative correlation (ORIVW = 0.979, 95% CI = [0.961, 0.997], P = 0.025). CONCLUSION This MR study confirmed the causal effect between LDL-C levels and HCC risk, with CAD playing a mediating role. It may provide a new view on HCC occurrence and development mechanisms, as well as new metabolic intervention targets for treatment.
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Affiliation(s)
- Jiali Cao
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430077, China
| | - Ziwen Wang
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430077, China
| | - Mengpei Zhu
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430077, China
| | - Yumei Huang
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430077, China
| | - Ze Jin
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430077, China
| | - Zhifan Xiong
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430077, China.
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De Lillo A, Wendt FR, Pathak GA, Polimanti R. Characterizing the polygenic architecture of complex traits in populations of East Asian and European descent. Hum Genomics 2023; 17:67. [PMID: 37475089 PMCID: PMC10360343 DOI: 10.1186/s40246-023-00514-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 07/14/2023] [Indexed: 07/22/2023] Open
Abstract
To investigate the polygenicity of complex traits in populations of East Asian (EAS) and European (EUR) descents, we leveraged genome-wide data from Biobank Japan, UK Biobank, and FinnGen cohorts. Specifically, we analyzed up to 215 outcomes related to 18 health domains, assessing their polygenic architecture via descriptive statistics, such as the proportion of susceptibility SNPs per trait (πc). While we did not observe EAS-EUR differences in the overall distribution of polygenicity parameters across the phenotypes investigated, there were ancestry-specific patterns in the polygenicity differences between health domains. In EAS, pairwise comparisons across health domains showed enrichment for πc differences related to hematological and metabolic traits (hematological fold-enrichment = 4.45, p = 2.15 × 10-7; metabolic fold-enrichment = 4.05, p = 4.01 × 10-6). For both categories, the proportion of susceptibility SNPs was lower than that observed for several other health domains (EAS-hematological median πc = 0.15%, EAS-metabolic median πc = 0.18%) with the strongest πc difference with respect to respiratory traits (EAS-respiratory median πc = 0.50%; hematological-p = 2.26 × 10-3; metabolic-p = 3.48 × 10-3). In EUR, pairwise comparisons showed multiple πc differences related to the endocrine category (fold-enrichment = 5.83, p = 4.76 × 10-6), where these traits showed a low proportion of susceptibility SNPs (EUR-endocrine median πc = 0.01%) with the strongest difference with respect to psychiatric phenotypes (EUR-psychiatric median πc = 0.50%; p = 1.19 × 10-4). Simulating sample sizes of 1,000,000 and 5,000,000 individuals, we also showed that ancestry-specific polygenicity patterns translate into differences across health domains in the genetic variance explained by susceptibility SNPs projected to be genome-wide significant (e.g., EAS hematological-neoplasm p = 2.18 × 10-4; EUR endocrine-gastrointestinal p = 6.80 × 10-4). These findings highlight that traits related to the same health domains may present ancestry-specific variability in their polygenicity.
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Affiliation(s)
- Antonella De Lillo
- Department of Psychiatry, Yale University School of Medicine, 60 Temple, Suite 7A, New Haven, CT, 06510, USA
- Department of Biology, University of Rome "Tor Vergata", Rome, Italy
| | - Frank R Wendt
- Department of Psychiatry, Yale University School of Medicine, 60 Temple, Suite 7A, New Haven, CT, 06510, USA
- Department of Anthropology, University of Toronto, Mississauga, ON, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Gita A Pathak
- Department of Psychiatry, Yale University School of Medicine, 60 Temple, Suite 7A, New Haven, CT, 06510, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale University School of Medicine, 60 Temple, Suite 7A, New Haven, CT, 06510, USA.
- VA CT Healthcare Center, West Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
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Koike Y, Takahata M, Nakajima M, Otomo N, Suetsugu H, Liu X, Endo T, Imagama S, Kobayashi K, Kaito T, Kato S, Kawaguchi Y, Kanayama M, Sakai H, Tsuji T, Miyamoto T, Inose H, Yoshii T, Kashii M, Nakashima H, Ando K, Taniguchi Y, Takeuchi K, Ito S, Tomizuka K, Hikino K, Iwasaki Y, Kamatani Y, Maeda S, Nakajima H, Mori K, Seichi A, Fujibayashi S, Kanchiku T, Watanabe K, Tanaka T, Kida K, Kobayashi S, Takahashi M, Yamada K, Takuwa H, Lu HF, Niida S, Ozaki K, Momozawa Y, Yamazaki M, Okawa A, Matsumoto M, Iwasaki N, Terao C, Ikegawa S. Genetic insights into ossification of the posterior longitudinal ligament of the spine. eLife 2023; 12:e86514. [PMID: 37461309 DOI: 10.7554/elife.86514] [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: 01/30/2023] [Accepted: 05/22/2023] [Indexed: 07/20/2023] Open
Abstract
Ossification of the posterior longitudinal ligament of the spine (OPLL) is an intractable disease leading to severe neurological deficits. Its etiology and pathogenesis are primarily unknown. The relationship between OPLL and comorbidities, especially type 2 diabetes (T2D) and high body mass index (BMI), has been the focus of attention; however, no trait has been proven to have a causal relationship. We conducted a meta-analysis of genome-wide association studies (GWASs) using 22,016 Japanese individuals and identified 14 significant loci, 8 of which were previously unreported. We then conducted a gene-based association analysis and a transcriptome-wide Mendelian randomization approach and identified three candidate genes for each. Partitioning heritability enrichment analyses observed significant enrichment of the polygenic signals in the active enhancers of the connective/bone cell group, especially H3K27ac in chondrogenic differentiation cells, as well as the immune/hematopoietic cell group. Single-cell RNA sequencing of Achilles tendon cells from a mouse Achilles tendon ossification model confirmed the expression of genes in GWAS and post-GWAS analyses in mesenchymal and immune cells. Genetic correlations with 96 complex traits showed positive correlations with T2D and BMI and a negative correlation with cerebral aneurysm. Mendelian randomization analysis demonstrated a significant causal effect of increased BMI and high bone mineral density on OPLL. We evaluated the clinical images in detail and classified OPLL into cervical, thoracic, and the other types. GWAS subanalyses identified subtype-specific signals. A polygenic risk score for BMI demonstrated that the effect of BMI was particularly strong in thoracic OPLL. Our study provides genetic insight into the etiology and pathogenesis of OPLL and is expected to serve as a basis for future treatment development.
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Affiliation(s)
- Yoshinao Koike
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Masahiko Takahata
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Masahiro Nakajima
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
| | - Nao Otomo
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
| | - Hiroyuki Suetsugu
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopaedic Surgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Tsutomu Endo
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Shiro Imagama
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuyoshi Kobayashi
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Takashi Kaito
- Department of Orthopaedic Surgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Satoshi Kato
- Department of Orthopaedic Surgery, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | | | - Masahiro Kanayama
- Department of Orthopedics, Hakodate Central General Hospital, Hakodate, Japan
| | - Hiroaki Sakai
- Department of Orthopaedic Surgery, Spinal Injuries Center, Iizuka, Japan
| | - Takashi Tsuji
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
- Department of Spine and Spinal Cord Surgery, Fujita Health University, Toyoake, Japan
| | - Takeshi Miyamoto
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
- Department of Orthopedic Surgery, Kumamoto University, Kumamoto, Japan
| | - Hiroyuki Inose
- Department of Orthopaedic Surgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Toshitaka Yoshii
- Department of Orthopaedic Surgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masafumi Kashii
- Department of Orthopaedic Surgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Hiroaki Nakashima
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kei Ando
- Department of Orthopedics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yuki Taniguchi
- Department of Orthopaedic Surgery, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kazuhiro Takeuchi
- Department of Orthopaedic Surgery, National Okayama Medical Center, Okayama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Yusuke Iwasaki
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Shingo Maeda
- Department of Bone and Joint Medicine, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan
| | - Hideaki Nakajima
- Department of Orthopaedics and Rehabilitation Medicine, Faculty of Medical Sciences, University of Fukui, Fukui, Japan
| | - Kanji Mori
- Department of Orthopaedic Surgery, Shiga University of Medical Science, Otsu, Japan
| | - Atsushi Seichi
- Department of Orthopedics, Jichi Medical University, Shimotsuke, Japan
| | - Shunsuke Fujibayashi
- Department of Orthopaedic Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tsukasa Kanchiku
- Department of Orthopedic Surgery, Yamaguchi University Graduate School of Medicine, Ube, Japan
| | - Kei Watanabe
- Department of Orthopaedic Surgery, Niigata University Medical and Dental General Hospital, Nankoku, Japan
| | - Toshihiro Tanaka
- Department of Orthopaedic Surgery, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Kazunobu Kida
- Department of Orthopaedic Surgery, Kochi Medical School, Nankoku, Japan
| | - Sho Kobayashi
- Department of Orthopaedic Surgery, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Masahito Takahashi
- Department of Orthopaedic Surgery, Kyorin University School of Medicine, Tokyo, Japan
| | - Kei Yamada
- Department of Orthopaedic Surgery, Kurume University School of Medicine, Obu, Japan
| | - Hiroshi Takuwa
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
| | - Hsing-Fang Lu
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Million-Person Precision Medicine Initiative, China Medical University Hospital, Taichung, Taiwan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Masashi Yamazaki
- Department of Orthopaedic Surgery, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Atsushi Okawa
- Department of Orthopaedic Surgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Morio Matsumoto
- Department of Orthopedic Surgery, Keio University School of Medicine, Nagoya, Japan
| | - Norimasa Iwasaki
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
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108
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Nahon P, Trépo E. Reply to: "Genetic factors in the clinical predictive model for hepatocellular carcinoma: Evidence from genetic association analyses". J Hepatol 2023; 79:e35-e37. [PMID: 36822477 DOI: 10.1016/j.jhep.2023.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 02/15/2023] [Indexed: 02/25/2023]
Affiliation(s)
- Pierre Nahon
- APHP, Liver Unit, Bobigny; Université Sorbonne Paris Nord, F-93000 Bobigny, France; Inserm, UMR-1138 "Functional Genomics of Solid Tumors", Centre de Recherche des Cordeliers, Université de Paris, Paris, France.
| | - Eric Trépo
- Department of Gastroenterology, Hepatopancreatology, and Digestive Oncology, Hôpital Universitaire de Bruxelles, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Experimental Gastroenterology, Université Libre de Bruxelles, Brussels, Belgium
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109
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Chen L, Fan Z, Zhao Y, Yang H, Lv G. Genetic factors in the clinical predictive model for hepatocellular carcinoma: Evidence from genetic association analyses. J Hepatol 2023; 79:e33-e35. [PMID: 36608772 DOI: 10.1016/j.jhep.2022.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 01/04/2023]
Affiliation(s)
- Lanlan Chen
- Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China
| | - Zhongqi Fan
- Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China
| | - Yuexuan Zhao
- Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China
| | - Hongqun Yang
- Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China
| | - Guoyue Lv
- Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China.
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110
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Gu Y, Yan C, Wang T, Hu B, Zhu M, Jin G. Construction and evaluation of the functional polygenic risk score for gastric cancer in a prospective cohort of the European population. Chin Med J (Engl) 2023:00029330-990000000-00640. [PMID: 37394533 DOI: 10.1097/cm9.0000000000002716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Indexed: 07/04/2023] Open
Abstract
BACKGROUND A polygenic risk score (PRS) derived from 112 single-nucleotide polymorphisms (SNPs) for gastric cancer has been reported in Chinese populations (PRS-112). However, its performance in other populations is unknown. A functional PRS (fPRS) using functional SNPs (fSNPs) may improve the generalizability of the PRS across populations with distinct ethnicities. METHODS We performed functional annotations on SNPs in strong linkage disequilibrium (LD) with the 112 previously reported SNPs to identify fSNPs that affect protein-coding or transcriptional regulation. Subsequently, we constructed an fPRS based on the fSNPs by using the LDpred2-infinitesimal model and then analyzed the performance of the PRS-112 and fPRS in the risk prediction of gastric cancer in 457,521 European participants of the UK Biobank cohort. Finally, the performance of the fPRS in combination with lifestyle factors were evaluated in predicting the risk of gastric cancer. RESULTS During 4,582,045 person-years of follow-up with a total of 623 incident gastric cancer cases, we found no significant association between the PRS-112 and gastric cancer risk in the European population (hazard ratio [HR] = 1.00 [95% confidence interval (CI) 0.93-1.09], P = 0.846). We identified 125 fSNPs, including seven deleterious protein-coding SNPs and 118 regulatory non-coding SNPs, and used them to constructed the fPRS-125. Our result showed that the fPRS-125 was significantly associated with gastric cancer risk (HR = 1.11 [95% CI, 1.03-1.20], P = 0.009). Compared to participants with a low fPRS-125 (bottom quintile), those with a high fPRS-125 (top quintile) had a higher risk of incident gastric cancer (HR = 1.43 [95% CI, 1.12-1.84], P = 0.005). Moreover, we observed that participants with both an unfavorable lifestyle and a high genetic risk had the highest risk of incident gastric cancer (HR = 4.99 [95% CI, 1.55-16.10], P = 0.007) compared to those with both a favorable lifestyle and a low genetic risk. CONCLUSION These results indicate that the fPRS-125 derived from fSNPs may act as an indicator to measure the genetic risk of gastric cancer in the European population.
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Affiliation(s)
- Yuanliang Gu
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing, Jiangsu 210009, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Tianpei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Beiping Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, Jiangsu 210009, China
| | - Guangfu Jin
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing, Jiangsu 210009, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, Jiangsu 210009, China
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111
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Lu Z, Zhang H, Yang Y, Zhao H. Sex differences of the shared genetic landscapes between type 2 diabetes and peripheral artery disease in East Asians and Europeans. Hum Genet 2023:10.1007/s00439-023-02573-x. [PMID: 37341850 DOI: 10.1007/s00439-023-02573-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 05/12/2023] [Indexed: 06/22/2023]
Abstract
Type 2 diabetes (T2D) is a critical risk factor for peripheral artery disease (PAD). However, the sex differences in genetic basis, causality, and underlying mechanisms of the two diseases are still unclear. Using sex-stratified and ethnic-based GWAS summary, we explored the genetic correlation and causal relationship between T2D and PAD in both ethnicities and sexes by linkage disequilibrium score regression, LAVA and six Mendelian Randomization approaches. We observed stronger genetic correlations between T2D and PAD in females than males in East Asians and Europeans. East Asian females exhibit higher causal effects of T2D on PAD than males. The gene-level analysis found KCNJ11 and ANK1 genes associated with the cross-trait of T2D and PAD in both sexes. Our study provides genetic evidence for the sex difference of genetic correlations and causal relationships between PAD and T2D, indicating the importance of using sex-specific strategies for monitoring PAD in T2D patients.
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Affiliation(s)
- Zhiya Lu
- Department of Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China
| | - Haoyang Zhang
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China
| | - Yuanhao Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Huiying Zhao
- Department of Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China.
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112
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Yu L, Liu W, Zhou M, Yang S, Tan Q, Fan L, Wang B, Chen W. Long-term effect of styrene and ethylbenzene exposure on fasting plasma glucose: A gene-environment interaction study. JOURNAL OF HAZARDOUS MATERIALS 2023; 452:131346. [PMID: 37030230 DOI: 10.1016/j.jhazmat.2023.131346] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/16/2023] [Accepted: 04/01/2023] [Indexed: 05/03/2023]
Abstract
Styrene and ethylbenzene (S/EB) are hazardous pollutants that have attracted worldwide concern. In this prospective cohort study, S/EB exposure biomarker (the sum of mandelic acid and phenylglyoxylic acid [MA+PGA]) and fasting plasma glucose (FPG) were repeatedly measured three times. The polygenic risk score (PRS) based on 137 single nucleotide polymorphisms for type 2 diabetes mellitus (T2DM) was calculated to evaluate cumulative genetic effect. In repeated-measures cross-sectional analyses, MA+PGA (β [95% confidence interval]: 0.106 [0.022, 0.189]) and PRS (0.111 [0.047, 0.176]) were significantly related to FPG. For long-term effect assessment, participants with sustained high MA+PGA or with high PRS had 0.021 (95% CI: -0.398, 0.441) or 0.465 (0.064, 0.866) mmol/L increase in FPG, respectively, over 3 years follow-up, and had 0.256 (0.017, 0.494) or 0.265 (0.004, 0.527) mmol/L increase in FPG, respectively, over 6 years follow-up. We further detected a significant interaction effect between MA+PGA and PRS on FPG change, compared with participants with sustained low MA+PGA and low PRS, those with sustained high MA+PGA and high PRS had 0.778 (0.319, 1.258) mmol/L increase in FPG (P for interaction=0.028) over 6 years follow-up. Our study provides the first evidence that long-term exposure to S/EB potentially increases FPG, which might be aggravated by genetic susceptibility.
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Affiliation(s)
- Linling Yu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Wei Liu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shijie Yang
- Hubei Provincial Center for Disease Control and Prevention, Wuhan, China
| | - Qiyou Tan
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Lieyang Fan
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Bin Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
| | - Weihong Chen
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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113
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Kosugi S, Kamatani Y, Harada K, Tomizuka K, Momozawa Y, Morisaki T, Terao C. Detection of trait-associated structural variations using short-read sequencing. CELL GENOMICS 2023; 3:100328. [PMID: 37388916 PMCID: PMC10300613 DOI: 10.1016/j.xgen.2023.100328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 02/17/2023] [Accepted: 04/25/2023] [Indexed: 07/01/2023]
Abstract
Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.
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Affiliation(s)
- Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba 277-8562, Japan
| | - Katsutoshi Harada
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa 230-0045, Japan
| | - Takayuki Morisaki
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, 4-6-1, Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan
| | | | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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114
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Lorincz-Comi N, Yang Y, Li G, Zhu X. MRBEE: A novel bias-corrected multivariable Mendelian Randomization method. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.10.523480. [PMID: 37066391 PMCID: PMC10103949 DOI: 10.1101/2023.01.10.523480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Mendelian randomization (MR) is an instrumental variable approach used to infer causal relationships between exposures and outcomes and can apply to summary data from genome-wide association studies (GWAS). Since GWAS summary statistics are subject to estimation errors, most existing MR approaches suffer from measurement error bias, whose scale and direction are influenced by weak instrumental variables and GWAS sample overlap, respectively. We introduce MRBEE (MR using Bias-corrected Estimating Equation), a novel multivariable MR method capable of simultaneously removing measurement error bias and identifying horizontal pleiotropy. In simulations, we showed that MRBEE is capable of effectively removing measurement error bias in the presence of weak instrumental variables and sample overlap. In two independent real data analyses, we discovered that the causal effect of BMI on coronary artery disease risk is entirely mediated by blood pressure, and that existing MR methods may underestimate the causal effect of cannabis use disorder on schizophrenia risk compared to MRBEE. MRBEE possesses significant potential for advancing genetic research by providing a valuable tool to study causality between multiple risk factors and disease outcomes, particularly as a large number of GWAS summary statistics become publicly available.
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Affiliation(s)
- Noah Lorincz-Comi
- Department of Population and Quantitative Health Sciences, School of Medicine
- Case Western Reserve University, Cleveland, OH 44106, USA June 12, 2023
| | - Yihe Yang
- Department of Population and Quantitative Health Sciences, School of Medicine
- Case Western Reserve University, Cleveland, OH 44106, USA June 12, 2023
| | - Gen Li
- Department of Population and Quantitative Health Sciences, School of Medicine
- Case Western Reserve University, Cleveland, OH 44106, USA June 12, 2023
| | - Xiaofeng Zhu
- This work was supported by grant HG011052 (to X.Z.) from the National Human Genome Research Institute (NHGRI), USA.
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Jee YH, Ho WK, Park S, Easton DF, Teo SH, Jung KJ, Kraft P. Polygenic risk scores for prediction of breast cancer in Korean women. Int J Epidemiol 2023; 52:796-805. [PMID: 36343017 PMCID: PMC10244045 DOI: 10.1093/ije/dyac206] [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: 11/21/2021] [Accepted: 10/31/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Polygenic risk scores (PRSs) for breast cancer, developed using European and Asian genome-wide association studies (GWAS), have been shown to have good discrimination in Asian women. However, prospective calibration of absolute risk prediction models, based on a PRS or PRS combined with lifestyle, clinical and environmental factors, in Asian women is limited. METHODS We consider several PRSs trained using European and/or Asian GWAS. For each PRS, we evaluate the discrimination and calibration of three absolute risk models among 41 031 women from the Korean Cancer Prevention Study (KCPS)-II Biobank: (i) a model using incidence, mortality and risk factor distributions (reference inputs) among US women and European relative risks; (ii) a recalibrated model, using Korean reference but European relative risks; and (iii) a fully Korean-based model using Korean reference and relative risk estimates from KCPS. RESULTS All Asian and European PRS improved discrimination over lifestyle, clinical and environmental (Qx) factors in Korean women. US-based absolute risk models overestimated the risks for women aged ≥50 years, and this overestimation was larger for models that only included PRS (expected-to-observed ratio E/O = 1.2 for women <50, E/O = 2.7 for women ≥50). Recalibrated and Korean-based risk models had better calibration in the large, although the risk in the highest decile was consistently overestimated. Absolute risk projections suggest that risk-reducing lifestyle changes would lead to larger absolute risk reductions among women at higher PRS. CONCLUSIONS Absolute risk models incorporating PRS trained in European and Asian GWAS and population-appropriate average age-specific incidences may be useful for risk-stratified interventions in Korean women.
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Affiliation(s)
- Yon Ho Jee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Weang-Kee Ho
- School of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
| | - Sohee Park
- Department of Biostatistics, Yonsei University Graduate School of Public Health, Seoul, Republic of Korea
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Soo-Hwang Teo
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
- Sime Darby Medical Centre, Subang Jaya, Selangor, Malaysia
| | - Keum Ji Jung
- Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea
- Nuffield Department Population Health, University of Oxford, Oxford, UK
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Smith JL, Tcheandjieu C, Dikilitas O, Lyer K, Miyazawa K, Hilliard A, Lynch J, Rotter JI, Chen YDI, Sheu WHH, Chang KM, Kanoni S, Tsao P, Ito K, Kosel M, Clarke SL, Schaid DJ, Assimes TL, Kullo IJ. A Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.02.23290896. [PMID: 37609230 PMCID: PMC10441485 DOI: 10.1101/2023.06.02.23290896] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Background Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (PRSCHD) for 5 genetic ancestry groups. Methods We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSP+T) and continuous shrinkage priors (PRSCSx) applied on summary statistics from the largest multi-ancestry genome-wide meta-analysis for CHD to date, including 1.1 million participants from 5 continental populations. Following training and optimization of PRSCHD in the Million Veteran Program, we evaluated predictive performance of the best performing PRSCHD in 176,988 individuals across 9 cohorts of diverse genetic ancestry. Results Multi-ancestry PRSP+T outperformed ancestry specific PRSP+T across a range of tuning values. In training stage, for all ancestry groups, PRSCSx performed better than PRSP+T and multi-ancestry PRS outperformed ancestry-specific PRS. In independent validation cohorts, the selected multi-ancestry PRSP+T demonstrated the strongest association with CHD in individuals of South Asian (SAS) and European (EUR) ancestry (OR per 1SD[95% CI]; 2.75[2.41-3.14], 1.65[1.59-1.72]), followed by East Asian (EAS) (1.56[1.50-1.61]), Hispanic/Latino (HIS) (1.38[1.24-1.54]), and weakest in African (AFR) ancestry (1.16[1.11-1.21]). The selected multi-ancestry PRSCSx showed stronger associacion with CHD in comparison within each ancestry group where the association was strongest in SAS (2.67[2.38-3.00]) and EUR (1.65[1.59-1.71]), progressively decreasing in EAS (1.59[1.54-1.64]), HIS (1.51[1.35-1.69]), and lowest in AFR (1.20[1.15-1.26]). Conclusions Utilizing diverse summary statistics from a large multi-ancestry genome-wide meta-analysis led to improved performance of PRSCHD in most ancestry groups compared to single-ancestry methods. Improvement of predictive performance was limited, specifically in AFR and HIS, despite use of one of the largest and most diverse set of training and validation cohorts to date. This highlights the need for larger GWAS datasets of AFR and HIS individuals to enhance performance of PRSCHD.
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Affiliation(s)
- Johanna L Smith
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Catherine Tcheandjieu
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Kruthika Lyer
- Stanford University School of Medicine, Palo Alto, CA, USA
| | - Kazuo Miyazawa
- Riken Ctr. for Integrative Medical Sciences, Yokohama City, Japan
| | - Austin Hilliard
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford University School of Medicine, Palo Alto, CA, USA
| | - Julie Lynch
- Salt Lake City VA Met CTR., Salt Lake City, UT, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institutes, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Kyong-Mi Chang
- Corporal Michael J Crescenz VA Medical Ctr. Philadelphia, PA, USA
| | | | - Phil Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford University, Stanford, CA, USA
| | - Kaoru Ito
- Riken Ctr. for Integrative Medical Sciences, Yokohama City, Japan
| | - Matthew Kosel
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Shoa L Clarke
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford University, Stanford, CA, USA
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
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Au Yeung SL, Borges MC, Wong THT, Lawlor DA, Schooling CM. Evaluating the role of non-alcoholic fatty liver disease in cardiovascular diseases and type 2 diabetes: a Mendelian randomization study in Europeans and East Asians. Int J Epidemiol 2023; 52:921-931. [PMID: 36367831 PMCID: PMC10244054 DOI: 10.1093/ije/dyac212] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 10/21/2022] [Indexed: 11/13/2023] Open
Abstract
BACKGROUND Whether non-alcoholic fatty liver disease (NAFLD) causes cardiovascular disease (CVD) and type 2 diabetes (T2D) is unclear and possible differences between ethnicities have not been thoroughly explored. We used Mendelian randomization (MR) to assess the role of NAFLD in CVD and T2D risk in Europeans and East Asians. METHODS We conducted a MR study using genetic predictors of alanine aminotransferase (ALT), liability to NAFLD, aspartate transaminase (AST), liver magnetic resonance imaging corrected T1 and proton density fat fraction and combined them with genome-wide association studies (GWAS) summary statistics of CVD, T2D and glycaemic traits (sample size ranging from 14 400 to 977 320). Inverse-variance weighted analysis was used to assess the effect of NAFLD in these outcomes, with sensitivity analyses and replication in FinnGen. We conducted analyses in East Asians using ethnicity-specific genetic predictors of ALT and AST, and the respective outcome GWAS summary statistics. RESULTS In Europeans, higher ALT was associated with higher T2D risk (odds ratio: 1.77 per standard deviation, 95% CI 1.5 to 2.08), with similar results for other exposures, across sensitivity analyses and in FinnGen. Although NAFLD proxies were related to higher coronary artery disease (CAD) and stroke risk, sensitivity analyses suggested possible bias by horizontal pleiotropy. In East Asians, higher ALT was possibly associated with higher T2D risk, and ALT and AST were inversely associated with CAD. CONCLUSIONS NAFLD likely increases the risk of T2D in Europeans and East Asians. Potential differential effects on CAD between Europeans and East Asians require further investigation.
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Affiliation(s)
- Shiu Lun Au Yeung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tommy Hon Ting Wong
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - C Mary Schooling
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- School of Public Health and Health Policy, City University of New York, New York, USA
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De Lillo A, Wendt FR, Pathak GA, Polimanti R. Characterizing the polygenic architecture of complex traits in populations of East Asian and European descent. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.25.23290542. [PMID: 37398225 PMCID: PMC10312887 DOI: 10.1101/2023.05.25.23290542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
To investigate the polygenicity of complex traits in populations of East Asian (EAS) and European (EUR) descents, we leveraged genome-wide data from Biobank Japan, UK Biobank, and FinnGen cohorts. Specifically, we analyzed up to 215 outcomes related to 18 health domains, assessing their polygenic architecture via descriptive statistics, such as the proportion of susceptibility SNPs per trait (π c ). While we did not observe EAS-EUR differences in the overall distribution of polygenicity parameters across the phenotypes investigated, there were ancestry-specific patterns in the polygenicity differences between health domains. In EAS, pairwise comparisons across health domains showed enrichment for π c differences related to hematological and metabolic traits (hematological fold-enrichment=4.45, p=2.15×10 -7 ; metabolic fold-enrichment=4.05, p=4.01×10 -6 ). For both categories, the proportion of susceptibility SNPs was lower than that observed for several other health domains (EAS-hematological median π c =0.15%, EAS-metabolic median π c =0.18%) with the strongest π c difference with respect to respiratory traits (EAS-respiratory median π c =0.50%; Hematological-p=2.26×10 -3 ; Metabolic-p=3.48×10 -3 ). In EUR, pairwise comparisons showed multiple π c differences related to the endocrine category (fold-enrichment=5.83, p=4.76×10 -6 ), where these traits showed a low proportion of susceptibility SNPs (EUR-endocrine median π c =0.01%) with the strongest difference with respect to psychiatric phenotypes (EUR-psychiatric median π c =0.50%; p=1.19×10 -4 ). Simulating sample sizes of 1,000,000 and 5,000,000 individuals, we also showed that ancestry-specific polygenicity patterns translate into differences across health domains in the genetic variance explained by susceptibility SNPs projected to be genome-wide significant (e.g., EAS hematological-neoplasm p=2.18×10 -4 ; EUR endocrine-gastrointestinal p=6.80×10 -4 ). These findings highlight that traits related to the same health domains may present ancestry-specific variability in their polygenicity.
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Tam CH, Lim CK, Luk AO, Shi M, Man Cheung H, Ng AC, Lee HM, Lau ES, Fan B, Jiang G, Kong AP, Ozaki R, Chow EY, Lee KF, Siu SC, Hui G, Tsang CC, Lau KP, Leung JY, Cheung EY, Tsang MW, Kam G, Lau IT, Li JK, Yeung VT, Lau E, Lo S, Fung S, Cheng YL, Chow CC, Fan X, Chan TF, Yip KY, Lok S, Yu W, Tsui SK, Lan HY, Szeto CC, Tang NL, Tomlinson B, Huang Y, Jenkins AJ, Keech A, So WY, Chan JC, Ma RC. Identification of a Common Variant for Coronary Heart Disease at PDE1A Contributes to Individualized Treatment Goals and Risk Stratification of Cardiovascular Complications in Chinese Patients With Type 2 Diabetes. Diabetes Care 2023; 46:1271-1281. [PMID: 37125963 PMCID: PMC10234754 DOI: 10.2337/dc22-2331] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/28/2023] [Indexed: 05/02/2023]
Abstract
OBJECTIVE In this study we aim to unravel genetic determinants of coronary heart disease (CHD) in type 2 diabetes (T2D) and explore their applications. RESEARCH DESIGN AND METHODS We performed a two-stage genome-wide association study for CHD in Chinese patients with T2D (3,596 case and 8,898 control subjects), followed by replications in European patients with T2D (764 case and 4,276 control subjects) and general populations (n = 51,442-547,261). Each identified variant was examined for its association with a wide range of phenotypes and its interactions with glycemic, blood pressure (BP), and lipid controls in incident cardiovascular diseases. RESULTS We identified a novel variant (rs10171703) for CHD (odds ratio 1.21 [95% CI 1.13-1.30]; P = 2.4 × 10-8) and BP (β ± SE 0.130 ± 0.017; P = 4.1 × 10-14) at PDE1A in Chinese T2D patients but found only a modest association with CHD in general populations. This variant modulated the effects of BP goal attainment (130/80 mmHg) on CHD (Pinteraction = 0.0155) and myocardial infarction (MI) (Pinteraction = 5.1 × 10-4). Patients with CC genotype of rs10171703 had >40% reduction in either cardiovascular events in response to BP control (2.9 × 10-8 < P < 3.6 × 10-5), those with CT genotype had no difference (0.0726 < P < 0.2614), and those with TT genotype had a threefold increase in MI risk (P = 6.7 × 10-3). CONCLUSIONS We discovered a novel CHD- and BP-related variant at PDE1A that interacted with BP goal attainment with divergent effects on CHD risk in Chinese patients with T2D. Incorporating this information may facilitate individualized treatment strategies for precision care in diabetes, only when our findings are validated.
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Affiliation(s)
- Claudia H.T. Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Cadmon K.P. Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Andrea O.Y. Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Mai Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Hoi Man Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Alex C.W. Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
| | - Heung-man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Eric S.H. Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Alice P.S. Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
| | - Elaine Y.K. Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Ka Fai Lee
- Department of Medicine and Geriatrics, Kwong Wah Hospital, Hong Kong
| | | | - Grace Hui
- Diabetes Centre, Tung Wah Eastern Hospital, Hong Kong
| | - Chiu Chi Tsang
- Diabetes and Education Centre, Alice Ho Miu Ling Nethersole Hospital, Hong Kong
| | | | - Jenny Y.Y. Leung
- Department of Medicine and Geriatrics, Ruttonjee Hospital, Hong Kong
| | - Elaine Y.N. Cheung
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong
| | - Man Wo Tsang
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong
| | - Grace Kam
- Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong
| | | | - June K.Y. Li
- Department of Medicine, Yan Chai Hospital, Hong Kong
| | - Vincent T.F. Yeung
- Centre for Diabetes Education and Management, Our Lady of Maryknoll Hospital, Hong Kong
| | - Emmy Lau
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Hong Kong
| | - Stanley Lo
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Hong Kong
| | - Samuel Fung
- Department of Medicine and Geriatrics, Princess Margaret Hospital, Hong Kong
| | - Yuk Lun Cheng
- Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, Hong Kong
| | - Chun Chung Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
| | - Xiaodan Fan
- Department of Statistics, The Chinese University of Hong Kong, Hong Kong
| | - Ting Fung Chan
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Kevin Y.L. Yip
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong
| | - Si Lok
- Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Canada
| | - Weichuan Yu
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong
| | - Stephen K.W. Tsui
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Hui-yao Lan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Cheuk Chun Szeto
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
| | - Nelson L.S. Tang
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
- Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong
| | - Brian Tomlinson
- Faculty of Medicine, Macau University of Science and Technology, Macau
| | - Yu Huang
- Department of Biomedical Sciences, The City University of Hong Kong, Hong Kong
| | - Alicia J. Jenkins
- NHMRC Clinical Trials Centre, University of Sydney, Sydney, Australia
| | - Anthony Keech
- NHMRC Clinical Trials Centre, University of Sydney, Sydney, Australia
| | - Wing-yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
| | - Juliana C.N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
| | - Ronald C.W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong
- CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong
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Liu Z, Song L, Chen J, Zhou Y, Wang Y, Tang L, Li Y. Causal associations between chronic hepatitis B and COVID-19 in East Asian populations. Virol J 2023; 20:109. [PMID: 37264390 DOI: 10.1186/s12985-023-02081-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/25/2023] [Indexed: 06/03/2023] Open
Abstract
BACKGROUND The relationship between chronic hepatitis B (CHB) and Coronavirus disease 2019 (COVID-19) has been inconsistent in traditional observational studies. METHODS We explored the total causal and direct causal associations between CHB and the three COVID-19 outcomes using univariate and multivariate Mendelian randomization (MR) analyses, respectively. Genome-wide association study datasets for CHB and COVID-19 were obtained from the Japan Biobank and the COVID-19 Host Genetics Initiative, respectively. RESULTS Univariate MR analysis showed that CHB increased the risk of SARS-CoV-2 infection (OR = 1.04, 95% CI 1.01-1.07, P = 3.39E-03), hospitalized COVID-19 (OR = 1.10, 95% CI 1.06-1.13, P = 7.31E-08), and severe COVID-19 (OR = 1.16, 95%CI 1.08-1.26, P = 1.43E-04). A series of subsequent sensitivity analyses ensured the stability and reliability of these results. In multivariable MR analyses adjusting for type 2 diabetes, body mass index, basophil count, and smoking, genetically related CHB is still positively associated with increased risk of SARS-CoV-2 infection (OR = 1.06, 95% CI 1.02-1.11, P = 1.44E-03) and hospitalized COVID-19 (OR = 1.12, 95% CI 1.07-1.16, P = 5.13E-07). However, the causal link between CHB and severe COVID-19 was attenuated after adjustment for the above variables. In addition, the MR analysis did not support the causal effect of COVID-19 on CHB. CONCLUSIONS This study provides evidence that CHB increases COVID-19 susceptibility and severity among individuals of East Asian ancestry.
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Affiliation(s)
- Zhenguo Liu
- State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China
| | - Linnan Song
- State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China
| | - Junling Chen
- State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China
| | - Yongjun Zhou
- State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China
| | - Yuhao Wang
- State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China
| | - Libo Tang
- State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China.
| | - Yongyin Li
- State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China.
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Tan Q, Yang S, Wang B, Wang M, Yu L, Liang R, Liu W, Song J, Guo Y, Zhou M, Chen W. Gene-environment interaction in long-term effects of polychlorinated biphenyls exposure on glucose homeostasis and type 2 diabetes: The modifying effects of genetic risk and lifestyle. JOURNAL OF HAZARDOUS MATERIALS 2023; 457:131757. [PMID: 37276697 DOI: 10.1016/j.jhazmat.2023.131757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 06/07/2023]
Abstract
The longitudinal relationships of polychlorinated biphenyls (PCBs) exposure with glucose homeostasis and type 2 diabetes (T2D) risk among Chinese population have not been assessed, and interactions of PCB exposure with genetic susceptibility and lifestyle are unclear. In this prospective cohort study, fasting plasma glucose (FPG) and insulin (FPI) and seven serum indicator-PCBs were measured for each participant. We constructed polygenic risk score (PRS) of T2D and healthy lifestyle score. Each 1-unit increment of ln-transformed PCB-118 was related with a 0.141 mmol/L, 11.410 pmol/L, 0.661, and 74.5% increase in FPG, FPI, homeostasis model assessment of insulin resistance, and incident T2D risk over 6 years, respectively. Each 1-unit increment in T2D-PRS was related with a 0.169 mmol/L elevation of FPG and 65.5% elevation of incident T2D risk during 6 years. Compared with participants who had low T2D-PRS and low PCB-118, participants with high T2D-PRS and high PCB-118 showed a significant increase in FPG (0.162 mmol/L; P for interaction <0.001) and incident T2D risk [hazard ratio (HR)= 2.222]. Participants with low PCB-118, low PRS, and healthy lifestyle had the lowest incident T2D risk (HR=0.232). Our findings highlighted the significance of reducing PCB exposure and improvement in lifestyle for T2D prevention and management, especially for individuals with higher genetic risk of T2D.
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Affiliation(s)
- Qiyou Tan
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, Hubei, China
| | - Bin Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Mengyi Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Linling Yu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Ruyi Liang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Wei Liu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Jiahao Song
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Yanjun Guo
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
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122
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Pan GQ, Jiao Y, Meng GX, Dong ZR, Li T. The relationship between the serum lipid profile and hepatocellular carcinoma in east Asian population: A mendelian randomization study. Heliyon 2023; 9:e17126. [PMID: 37484252 PMCID: PMC10361312 DOI: 10.1016/j.heliyon.2023.e17126] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 06/07/2023] [Accepted: 06/08/2023] [Indexed: 07/25/2023] Open
Abstract
Background Although several studies have found that the serum lipid profile may be correlated with hepatocellular carcinoma (HCC), the causal relationships between the serum lipid profile and HCC have not been determined due to potential confounder. Here, Mendelian randomization (MR) analysis was performed to identify the relationship between the serum lipid profile and HCC in the East Asian population. Method Our study made a MR analysis with the validation of two data sets. We obtained genome-wide association study (GWAS) data related to the serum lipid profile from Asian Genetic Epidemiology Network (AGEN). Then, the data from a recent large GWAS of the East Asian ancestry in Japan (BioBank Japan, BBJ) were extracted. Summary-level statistical data for HCC were obtained from a large GWAS of the East Asian ancestry in Japan. Univariable MR analysis were performed to identify whether the genetic evidence of serum lipid profile was significantly associated with HCC risk. Multivariable MR analysis was conducted to estimate the independent effects of exposures on HCC. Results Univariable and multivariable MR analyses indicated that the serum lipid profile was not a risk factor for HCC incidence in either data set based on the East Asian population. Multivariable MR analysis revealed that the hazard ratios of the probability of HCC in AGEN were 1.134 (95% confidence interval (CI), 0.903-1.424) for TG, 1.010 (95% CI: 0.824-1.237) for HDL-C, 0.974 (95% CI: 0.746-1.271) for TC, 0.918 (95% CI: 0.734-1.147) for LDL-C, while the results in BBJ were also non-significant: 1.111 (95% CI: 0.869-1.419) for TG, 0.957 (95% CI: 0.790-1.158) for HDL-C, 0.917 (95% CI: 0.643-1.308) for TC, 0.932 (95% CI: 0.699-1.243) for LDL-C. Conclusion Our MR study with the validation of two data sets found no strong evidence to support causal associations between the serum lipid profile and HCC risk.
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Affiliation(s)
- Guo-Qiang Pan
- Department of General Surgery, Qilu Hospital, Shandong University, Jinan, China
| | - Yan Jiao
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Guang-Xiao Meng
- Department of General Surgery, Qilu Hospital, Shandong University, Jinan, China
| | - Zhao-Ru Dong
- Department of General Surgery, Qilu Hospital, Shandong University, Jinan, China
| | - Tao Li
- Department of General Surgery, Qilu Hospital, Shandong University, Jinan, China
- Department of Hepatobiliary Surgery, The Second Hospital of Shandong University, Jinan, 250012, China
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123
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Fetter T, de Graaf DM, Claus I, Wenzel J. Aberrant inflammasome activation as a driving force of human autoimmune skin disease. Front Immunol 2023; 14:1190388. [PMID: 37325658 PMCID: PMC10266227 DOI: 10.3389/fimmu.2023.1190388] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/09/2023] [Indexed: 06/17/2023] Open
Abstract
Autoimmune skin diseases are understood as conditions in which the adaptive immune system with autoantigen-specific T cells and autoantibody-producing B cells reacting against self-tissues plays a crucial pathogenic role. However, there is increasing evidence that inflammasomes, which are large multiprotein complexes that were first described 20 years ago, contribute to autoimmune disease progression. The inflammasome and its contribution to the bioactivation of interleukins IL-1β and IL-18 play an essential role in combating foreign pathogens or tissue damage, but may also act as a pathogenic driver of myriad chronic inflammatory diseases when dysfunctionally regulated. Inflammasomes containing the NOD-like receptor family members NLRP1 and NLRP3 as well as the AIM2-like receptor family member AIM2 have been increasingly investigated in inflammatory skin conditions. In addition to autoinflammatory diseases, which are often associated with skin involvement, the aberrant activation of the inflammasome has also been implied in autoimmune diseases that can either affect the skin besides other organs such as systemic lupus erythematosus and systemic sclerosis or are isolated to the skin in humans. The latter include, among others, the T-cell mediated disorders vitiligo, alopecia areata, lichen planus and cutaneous lupus erythematosus as well as the autoantibody-driven blistering skin disease bullous pemphigoid. Some diseases are characterized by both autoinflammatory and autoimmune responses such as the chronic inflammatory skin disease psoriasis. Further insights into inflammasome dysregulation and associated pathways as well as their role in forming adaptive immune responses in human autoimmune skin pathology could potentially offer a new field of therapeutic options in the future.
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Affiliation(s)
- Tanja Fetter
- Department of Dermatology and Allergy, University Hospital Bonn, Bonn, Germany
| | | | - Isabelle Claus
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Joerg Wenzel
- Department of Dermatology and Allergy, University Hospital Bonn, Bonn, Germany
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124
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Hess T, Maj C, Gehlen J, Borisov O, Haas SL, Gockel I, Vieth M, Piessen G, Alakus H, Vashist Y, Pereira C, Knapp M, Schüller V, Quaas A, Grabsch HI, Trautmann J, Malecka-Wojciesko E, Mokrowiecka A, Speller J, Mayr A, Schröder J, Hillmer AM, Heider D, Lordick F, Pérez-Aísa Á, Campo R, Espinel J, Geijo F, Thomson C, Bujanda L, Sopeña F, Lanas Á, Pellisé M, Pauligk C, Goetze TO, Zelck C, Reingruber J, Hassanin E, Elbe P, Alsabeah S, Lindblad M, Nilsson M, Kreuser N, Thieme R, Tavano F, Pastorino R, Arzani D, Persiani R, Jung JO, Nienhüser H, Ott K, Schumann RR, Kumpf O, Burock S, Arndt V, Jakubowska A, Ławniczak M, Moreno V, Martín V, Kogevinas M, Pollán M, Dąbrowska J, Salas A, Cussenot O, Boland-Auge A, Daian D, Deleuze JF, Salvi E, Teder-Laving M, Tomasello G, Ratti M, Senti C, De Re V, Steffan A, Hölscher AH, Messerle K, Bruns CJ, Sīviņš A, Bogdanova I, Skieceviciene J, Arstikyte J, Moehler M, Lang H, Grimminger PP, Kruschewski M, Vassos N, Schildberg C, Lingohr P, Ridwelski K, Lippert H, Fricker N, Krawitz P, Hoffmann P, Nöthen MM, Veits L, Izbicki JR, Mostowska A, Martinón-Torres F, Cusi D, Adolfsson R, Cancel-Tassin G, Höblinger A, Rodermann E, Ludwig M, Keller G, Metspalu A, Brenner H, Heller J, Neef M, Schepke M, Dumoulin FL, Hamann L, Cannizzaro R, Ghidini M, Plaßmann D, Geppert M, Malfertheiner P, Gehlen O, Skoczylas T, Majewski M, Lubiński J, Palmieri O, Boccia S, Latiano A, Aragones N, Schmidt T, Dinis-Ribeiro M, Medeiros R, Al-Batran SE, Leja M, Kupcinskas J, García-González MA, Venerito M, Schumacher J. Dissecting the genetic heterogeneity of gastric cancer. EBioMedicine 2023; 92:104616. [PMID: 37209533 DOI: 10.1016/j.ebiom.2023.104616] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 04/28/2023] [Accepted: 04/30/2023] [Indexed: 05/22/2023] Open
Abstract
BACKGROUND Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett's oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture. METHODS We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO. FINDINGS Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level. INTERPRETATION Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO. FUNDING German Research Foundation (DFG).
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Affiliation(s)
- Timo Hess
- Institute of Human Genetics, University of Marburg, Marburg, Germany; Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Carlo Maj
- Institute of Human Genetics, University of Marburg, Marburg, Germany; Medical Faculty, Institute for Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany
| | - Jan Gehlen
- Institute of Human Genetics, University of Marburg, Marburg, Germany
| | - Oleg Borisov
- Medical Faculty, Institute for Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany
| | - Stephan L Haas
- Department of Upper GI Diseases, Karolinska Institutet, Karolinska University Hospital and Unit of Gastroenterology and Rheumatology, Stockholm, Sweden
| | - Ines Gockel
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital Leipzig, Leipzig, Germany
| | - Michael Vieth
- Institute for Pathology, Friedrich-Alexander-University Erlangen-Nuernberg, Klinikum Bayreuth, Bayreuth, Germany
| | - Guillaume Piessen
- Department of Digestive and Oncological Surgery, Claude Huriez Hospital, CHU Lille, Lille, France
| | - Hakan Alakus
- Department of General, Visceral, Cancer and Transplant Surgery, University of Cologne, Cologne, Germany
| | - Yogesh Vashist
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany; Organ Transplant Center of Excellence, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
| | - Carina Pereira
- Molecular Oncology and Viral Pathology Group, IPO Porto Research Center (CI-IPOP), Portuguese Institute of Oncology of Porto (IPO Porto), Porto 4200-072, Portugal; Porto Comprehensive Cancer Center & RISE @ CI-IPO, University of Porto, Porto 4200-450, Portugal
| | - Michael Knapp
- Medical Faculty, Institute of Medical Biometrics, Informatics and Epidemiology (IMBIE), University of Bonn, Bonn, Germany
| | - Vitalia Schüller
- Institute of Human Genetics, University of Marburg, Marburg, Germany
| | - Alexander Quaas
- Medical Faculty, Institute of Pathology, University Hospital Cologne, University of Cologne, Germany
| | - Heike I Grabsch
- Department of Pathology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands; Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, United Kingdom
| | - Jessica Trautmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | | | - Anna Mokrowiecka
- Department of Digestive Tract Diseases, Medical University of Lodz, Lodz, Poland
| | - Jan Speller
- Medical Faculty, Institute of Medical Biometrics, Informatics and Epidemiology (IMBIE), University of Bonn, Bonn, Germany
| | - Andreas Mayr
- Medical Faculty, Institute of Medical Biometrics, Informatics and Epidemiology (IMBIE), University of Bonn, Bonn, Germany
| | - Julia Schröder
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Axel M Hillmer
- Medical Faculty, Institute of Pathology, University Hospital Cologne, University of Cologne, Germany
| | - Dominik Heider
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany
| | - Florian Lordick
- University Cancer Center Leipzig, Leipzig University Medical Center, Leipzig, Germany
| | | | - Rafael Campo
- Department of Gastroenterology, Hospital Parc Tauli, Sabadell, Spain
| | - Jesús Espinel
- Department of Gastroenterology, Complejo Hospitalario, León, Spain
| | - Fernando Geijo
- Department of Gastroenterology, Hospital Clínico Universitario, Salamanca, Spain
| | - Concha Thomson
- Department of Gastroenterology, Hospital Obispo Polanco, Teruel, Spain
| | - Luis Bujanda
- CIBER de Enfermedades Hepáticas y Digestivas (CIBERehd), Spain; Department of Gastroenterology, Hospital Donostia/Instituto Biodonostia, Universidad del País Vasco (UPV/EHU), San Sebastián, Spain
| | - Federico Sopeña
- CIBER de Enfermedades Hepáticas y Digestivas (CIBERehd), Spain; Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain; Department of Gastroenterology, Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain
| | - Ángel Lanas
- CIBER de Enfermedades Hepáticas y Digestivas (CIBERehd), Spain; Department of Gastroenterology, Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain; Instituto Aragonés de Ciencias de la Salud (IACS), Zaragoza, Spain
| | - María Pellisé
- CIBER de Enfermedades Hepáticas y Digestivas (CIBERehd), Spain; Department of Gastroenterology, Hospital Clinic of Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Claudia Pauligk
- Krankenhaus Nordwest, University Cancer Center, Frankfurt, Germany; Institut für Klinische Krebsforschung IKF GmbH am Krankenhaus Nordwest, Frankfurt, Germany
| | - Thorsten Oliver Goetze
- Krankenhaus Nordwest, University Cancer Center, Frankfurt, Germany; Institut für Klinische Krebsforschung IKF GmbH am Krankenhaus Nordwest, Frankfurt, Germany
| | - Carolin Zelck
- Institute of Human Genetics, University of Marburg, Marburg, Germany
| | - Julian Reingruber
- Institute of Human Genetics, University of Marburg, Marburg, Germany
| | - Emadeldin Hassanin
- Medical Faculty, Institute for Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany
| | - Peter Elbe
- Department of Upper GI Diseases, Karolinska Institutet, Karolinska University Hospital and Unit of Gastroenterology and Rheumatology, Stockholm, Sweden
| | - Sandra Alsabeah
- Department of Upper GI Diseases, Karolinska Institutet, Karolinska University Hospital and Unit of Gastroenterology and Rheumatology, Stockholm, Sweden
| | - Mats Lindblad
- Division of Surgery, Department of Upper GI Diseases, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden; Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Magnus Nilsson
- Division of Surgery, Department of Upper GI Diseases, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden; Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Nicole Kreuser
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital Leipzig, Leipzig, Germany
| | - René Thieme
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital Leipzig, Leipzig, Germany
| | - Francesca Tavano
- Gastroenterology Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Roberta Pastorino
- Department of Woman and Child Health and Public Health - Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy
| | - Dario Arzani
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
| | - Roberto Persiani
- Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy; Dipartimento di Scienze Mediche e Chirurgiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy
| | - Jin-On Jung
- Department of General, Visceral, Cancer and Transplant Surgery, University of Cologne, Cologne, Germany; Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Henrik Nienhüser
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Katja Ott
- Department of Surgery, RoMed Klinikum Rosenheim, Rosenheim, Germany
| | - Ralf R Schumann
- Institute of Microbiology, Infectious Diseases and Immunology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Oliver Kumpf
- Department of Anaesthesiology and Operative Intensive Care Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Susen Burock
- Charité Comprehensive Cancer Center, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University in Szczecin, Poland; Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University in Szczecin, Poland
| | - Małgorzta Ławniczak
- Department of Gastroenterology, Pomeranian Medical University in Szczecin, Poland
| | - Victor Moreno
- Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), Hospital Duran I Reynals, Barcelona, Spain; Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Faculty of Medicine, Department of Clinical Sciences, University of Barcelona, Barcelona, Spain
| | - Vicente Martín
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública e CIBERESP), Spain; The Research Group in Gene - Environment and Health Interactions (GIIGAS)/Institute of Biomedicine (IBIOMED), Universidad de Leon, Leon, Spain; Faculty of Health Sciences, Department of Biomedical Sciences, Area of Preventive Medicine and Public Health, Universidad de Leon, Leon, Spain
| | - Manolis Kogevinas
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública e CIBERESP), Spain; ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Campus Del Mar, Barcelona, Spain; IMIM (Hospital Del Mar Medical Research Institute), Barcelona, Spain
| | - Marina Pollán
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública e CIBERESP), Spain; Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
| | - Justyna Dąbrowska
- Department of Biochemistry and Molecular Biology, Poznan University of Medical Sciences, Poland
| | - Antonio Salas
- Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela, Santiago de Compostela, Spain; GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain
| | - Olivier Cussenot
- CeRePP, Paris, France; GRC n°5 Predictive Onco-Urology, Tenon Hospital, Sorbonne University, Paris, France
| | - Anne Boland-Auge
- Centre National de Recherche en Génomique Humaine, CEA, University Paris-Saclay, Evry, France
| | - Delphine Daian
- Centre National de Recherche en Génomique Humaine, CEA, University Paris-Saclay, Evry, France
| | - Jean-Francois Deleuze
- Centre National de Recherche en Génomique Humaine, CEA, University Paris-Saclay, Evry, France
| | - Erika Salvi
- Neuroalgology Unit Fondazione IRCCS, Instituto Neurologico 'Carlo Besta' Milan, Milan, Italy
| | - Maris Teder-Laving
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Gianluca Tomasello
- Medical Oncology Unit, ASST of Cremona, Cremona, Italy; Medical Oncology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Chiara Senti
- Medical Oncology Unit, ASST of Cremona, Cremona, Italy; Department of Medical Oncology, Institut Jules Bordet - Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Valli De Re
- Unit of Immunopathologia e Biomarcatori Oncologici/Bio-proteomics Facility, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy
| | - Agostino Steffan
- Unit of Immunopathologia e Biomarcatori Oncologici, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy
| | - Arnulf H Hölscher
- Department of General, Visceral, Cancer and Transplant Surgery, University of Cologne, Cologne, Germany
| | - Katharina Messerle
- Department of General, Visceral, Cancer and Transplant Surgery, University of Cologne, Cologne, Germany
| | | | - Armands Sīviņš
- Institute of Clinical and Preventive Medicine, University of Latvia, Riga East University Hospital, Riga, Latvia
| | - Inga Bogdanova
- Institute of Clinical and Preventive Medicine, University of Latvia, Riga East University Hospital, Riga, Latvia
| | - Jurgita Skieceviciene
- Gastroenterology Department and Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Justina Arstikyte
- Gastroenterology Department and Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Markus Moehler
- Department of Medicine I, University Medical Center of Johannes Gutenberg University Mainz, Mainz, Germany
| | - Hauke Lang
- Department of General, Visceral and Transplant Surgery, University Medical Center, University of Mainz, Mainz, Germany
| | - Peter P Grimminger
- Department of General, Visceral and Transplant Surgery, University Medical Center, University of Mainz, Mainz, Germany
| | - Martin Kruschewski
- Department of General and Visceral Surgery, Klinikum Frankfurt (Oder), Germany
| | - Nikolaos Vassos
- Division of Surgical Oncology and Thoracic Surgery, Department of Surgery, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany
| | - Claus Schildberg
- Department of General Surgery, Brandenburg Medical School Theodor Fontane, University Hospital Brandenburg, Brandenburg, Germany
| | - Philipp Lingohr
- Department of General, Visceral, Thoracic and Vascular Surgery, University Hospital Bonn, Bonn, Germany
| | - Karsten Ridwelski
- Department of General and Visceral Surgery, Klinikum Magdeburg GmbH, Magdeburg, Germany
| | - Hans Lippert
- Institute of Quality Assurance in Operative Medicine, Otto-von-Guericke University Hospital, Magdeburg, Germany
| | - Nadine Fricker
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Peter Krawitz
- Medical Faculty, Institute for Genomic Statistics and Bioinformatics, University of Bonn, Bonn, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Lothar Veits
- Institute for Pathology, Friedrich-Alexander-University Erlangen-Nuernberg, Klinikum Bayreuth, Bayreuth, Germany
| | - Jakob R Izbicki
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Adrianna Mostowska
- Department of Biochemistry and Molecular Biology, Poznan University of Medical Sciences, Poland
| | - Federico Martinón-Torres
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain; Department of Pediatrics, Translational Pediatrics and Infectious Diseases Section, Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Spain; Genetics, Vaccines, Infectious Diseases and Pediatrics Research Group GENVIP, Instituto de Investigación Sanitaria de Santiago (IDIS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Daniele Cusi
- Institute of Biomedical Technologies, National Research Council of Italy, Milan, Italy; Bio4Dreams-Business, Nursery for Life Sciences, Milan, Italy
| | - Rolf Adolfsson
- Department of Clinical Sciences, Umeå University, Umeå, Sweden
| | - Geraldine Cancel-Tassin
- CeRePP, Paris, France; GRC n°5 Predictive Onco-Urology, Tenon Hospital, Sorbonne University, Paris, France
| | - Aksana Höblinger
- Department of Internal Medicine I, Community Hospital Mittelrhein, Koblenz, Germany
| | - Ernst Rodermann
- Association of Medical Practices in Hematology and Internal Oncology, Troisdorf, Germany
| | - Monika Ludwig
- Association for Oncological Studies (Gefos), Dortmund, Germany
| | - Gisela Keller
- Institute of Pathology, Technical University of Munich, Munich, Germany
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Joerg Heller
- Department of Gastroenterology, Marienhaus Hospital Ahrweiler, Ahrweiler, Germany
| | - Markus Neef
- Department of Gastroenterology, Helios Hospital Siegburg, Siegburg, Germany
| | - Michael Schepke
- Department of Gastroenterology, Helios Hospital Siegburg, Siegburg, Germany
| | | | - Lutz Hamann
- Institute of Microbiology, Infectious Diseases and Immunology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Renato Cannizzaro
- Unit of Oncological Gastroenterology, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Michele Ghidini
- Medical Oncology Unit, ASST of Cremona, Cremona, Italy; Medical Oncology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | | | - Peter Malfertheiner
- Department of Gastroenterology, Hepatology and Infectious Diseases, Otto-von-Guericke University Hospital, Magdeburg, Germany; Department of Internal Medicine II, Hospital of the Ludwig Maximilians University of Munich, Munich, Germany
| | - Olivier Gehlen
- Department of Surgical Oncology, Centre Hospitalier Lyon-sud, Lyon, France
| | - Tomasz Skoczylas
- 2nd Department of General Surgery, Medical University of Lublin, Lublin, Poland
| | - Marek Majewski
- 2nd Department of General Surgery, Medical University of Lublin, Lublin, Poland
| | - Jan Lubiński
- Department of Genetics and Pathology, Pomeranian Medical University in Szczecin, Poland
| | - Orazio Palmieri
- Gastroenterology Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Stefania Boccia
- Department of Woman and Child Health and Public Health - Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy; Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Roma, Italy
| | - Anna Latiano
- Gastroenterology Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Nuria Aragones
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública e CIBERESP), Spain; Epidemiology Section, Public Health Division, Department of Health of Madrid, Madrid, Spain
| | - Thomas Schmidt
- Department of General, Visceral, Cancer and Transplant Surgery, University of Cologne, Cologne, Germany; Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Mário Dinis-Ribeiro
- Porto Comprehensive Cancer Center & RISE @ CI-IPO, University of Porto, Porto 4200-450, Portugal; Gastroenterology Department, Portuguese Institute of Oncology of Porto, Porto 4200-072, Portugal
| | - Rui Medeiros
- Molecular Oncology and Viral Pathology Group, IPO Porto Research Center (CI-IPOP), Portuguese Institute of Oncology of Porto (IPO Porto), Porto 4200-072, Portugal; Research Department of the Portuguese League Against Cancer-North (LPCC-NRNorte), Porto 4200-177, Portugal
| | - Salah-Eddin Al-Batran
- Krankenhaus Nordwest, University Cancer Center, Frankfurt, Germany; Institut für Klinische Krebsforschung IKF GmbH am Krankenhaus Nordwest, Frankfurt, Germany
| | - Mārcis Leja
- Institute of Clinical and Preventive Medicine, University of Latvia, Riga East University Hospital, Riga, Latvia; Digestive Diseases Centre GASTRO, Riga, Latvia
| | - Juozas Kupcinskas
- Gastroenterology Department and Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - María A García-González
- CIBER de Enfermedades Hepáticas y Digestivas (CIBERehd), Spain; Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain; Instituto Aragonés de Ciencias de la Salud (IACS), Zaragoza, Spain
| | - Marino Venerito
- Department of Gastroenterology, Hepatology and Infectious Diseases, Otto-von-Guericke University Hospital, Magdeburg, Germany
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Kojima S, Koyama S, Ka M, Saito Y, Parrish EH, Endo M, Takata S, Mizukoshi M, Hikino K, Takeda A, Gelinas AF, Heaton SM, Koide R, Kamada AJ, Noguchi M, Hamada M, Kamatani Y, Murakawa Y, Ishigaki K, Nakamura Y, Ito K, Terao C, Momozawa Y, Parrish NF. Mobile element variation contributes to population-specific genome diversification, gene regulation and disease risk. Nat Genet 2023:10.1038/s41588-023-01390-2. [PMID: 37169872 DOI: 10.1038/s41588-023-01390-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 04/04/2023] [Indexed: 05/13/2023]
Abstract
Mobile genetic elements (MEs) are heritable mutagens that recursively generate structural variants (SVs). ME variants (MEVs) are difficult to genotype and integrate in statistical genetics, obscuring their impact on genome diversification and traits. We developed a tool that accurately genotypes MEVs using short-read whole-genome sequencing (WGS) and applied it to global human populations. We find unexpected population-specific MEV differences, including an Alu insertion distribution distinguishing Japanese from other populations. Integrating MEVs with expression quantitative trait loci (eQTL) maps shows that MEV classes regulate tissue-specific gene expression by shared mechanisms, including creating or attenuating enhancers and recruiting post-transcriptional regulators, supporting class-wide interpretability. MEVs more often associate with gene expression changes than SNVs, thus plausibly impacting traits. Performing genome-wide association study (GWAS) with MEVs pinpoints potential causes of disease risk, including a LINE-1 insertion associated with keloid and fasciitis. This work implicates MEVs as drivers of human divergence and disease risk.
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Affiliation(s)
- Shohei Kojima
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan.
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Mirei Ka
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
- Next-Generation Precision Medicine Development, Integrative Genomics Laboratory, Graduate School of Medicine, Department of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Yuka Saito
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
- Graduate School of Medical Life Science, Yokohama City University, Yokohama, Japan
| | - Erica H Parrish
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Mikiko Endo
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sadaaki Takata
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Misaki Mizukoshi
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Atsushi Takeda
- Graduate School of Advanced Science and Engineering, Waseda University, Tokyo, Japan
- Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan
| | - Asami F Gelinas
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Steven M Heaton
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Rie Koide
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Anselmo J Kamada
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
- Paleovirology Lab, Department of Biology, University of Oxford, Oxford, UK
| | - Michiya Noguchi
- Cell Engineering Division, BioResource Research Center, RIKEN, Tsukuba, Japan
| | - Michiaki Hamada
- Graduate School of Advanced Science and Engineering, Waseda University, Tokyo, Japan
- Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yasuhiro Murakawa
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy
| | - Kazuyoshi Ishigaki
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yukio Nakamura
- Cell Engineering Division, BioResource Research Center, RIKEN, Tsukuba, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Nicholas F Parrish
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan.
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Liu J, Wang L, Cui X, Shen Q, Wu D, Yang M, Dong Y, Liu Y, Chen H, Yang Z, Liu Y, Zhu M, Ma H, Jin G, Qian Y. Polygenic Risk Score, Lifestyles, and Type 2 Diabetes Risk: A Prospective Chinese Cohort Study. Nutrients 2023; 15:2144. [PMID: 37432247 DOI: 10.3390/nu15092144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 04/28/2023] [Accepted: 04/28/2023] [Indexed: 07/12/2023] Open
Abstract
The aim of this study was to generate a polygenic risk score (PRS) for type 2 diabetes (T2D) and test whether it could be used in identifying high-risk individuals for lifestyle intervention in a Chinese cohort. We genotyped 80 genetic variants among 5024 participants without non-communicable diseases at baseline in the Wuxi Non-Communicable Diseases cohort (Wuxi NCDs cohort). During the follow-up period of 14 years, 440 cases of T2D were newly diagnosed. Using Cox regression, we found that the PRS of 46 SNPs identified by the East Asians was relevant to the future T2D. Participants with a high PRS (top quintile) had a two-fold higher risk of T2D than the bottom quintile (hazard ratio: 2.06, 95% confidence interval: 1.42-2.97). Lifestyle factors were considered, including cigarette smoking, alcohol consumption, physical exercise, diet, body mass index (BMI), and waist circumference (WC). Among high-PRS individuals, the 10-year incidence of T2D slumped from 6.77% to 3.28% for participants having ideal lifestyles (4-6 healthy lifestyle factors) compared with poor lifestyles (0-2 healthy lifestyle factors). When integrating the high PRS, the 10-year T2D risk of low-clinical-risk individuals exceeded that of high-clinical-risk individuals with a low PRS (3.34% vs. 2.91%). These findings suggest that the PRS of 46 SNPs could be used in identifying high-risk individuals and improve the risk stratification defined by traditional clinical risk factors for T2D. Healthy lifestyles can reduce the risk of a high PRS, which indicates the potential utility in early screening and precise prevention.
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Affiliation(s)
- Jia Liu
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Lu Wang
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Xuan Cui
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Qian Shen
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Dun Wu
- College of Arts and Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Man Yang
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Yunqiu Dong
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Yongchao Liu
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Hai Chen
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Zhijie Yang
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Yaqi Liu
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
| | - Meng Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Hongxia Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Guangfu Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yun Qian
- Department of Chronic Non-Communicable Disease Control, The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University (Wuxi Center for Disease Control and Prevention), Wuxi 214023, China
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Wong D, Auguste G, Cardenas CLL, Turner AW, Chen Y, Song Y, Ma L, Perry RN, Aherrahrou R, Kuppusamy M, Yang C, Mosquera JV, Dube CJ, Khan MD, Palmore M, Kalra JK, Kavousi M, Peyser PA, Matic L, Hedin U, Manichaikul A, Sonkusare SK, Civelek M, Kovacic JC, Björkegren JL, Malhotra R, Miller CL. FHL5 Controls Vascular Disease-Associated Gene Programs in Smooth Muscle Cells. Circ Res 2023; 132:1144-1161. [PMID: 37017084 PMCID: PMC10147587 DOI: 10.1161/circresaha.122.321692] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 03/21/2023] [Indexed: 04/06/2023]
Abstract
BACKGROUND Genome-wide association studies have identified hundreds of loci associated with common vascular diseases, such as coronary artery disease, myocardial infarction, and hypertension. However, the lack of mechanistic insights for many GWAS loci limits their translation into the clinic. Among these loci with unknown functions is UFL1-four-and-a-half LIM (LIN-11, Isl-1, MEC-3) domain 5 (FHL5; chr6q16.1), which reached genome-wide significance in a recent coronary artery disease/ myocardial infarction GWAS meta-analysis. UFL1-FHL5 is also associated with several vascular diseases, consistent with the widespread pleiotropy observed for GWAS loci. METHODS We apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and ex vivo analysis of human coronary artery tissues to implicate FHL5 as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments in coronary artery smooth muscle cells. RESULTS We prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through expression quantitative trait locus colocalization methods. FHL5 gene expression was enriched in the smooth muscle cells and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating smooth muscle cell contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream coronary artery disease/myocardial infarction loci, such as FOXL1 and FN1 that have roles in vascular remodeling. CONCLUSIONS Taken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling gene programs. These transacting mechanisms may explain a portion of the heritable risk for complex vascular diseases.
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Affiliation(s)
- Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Christian L. Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Adam W. Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yixuan Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yipei Song
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - R. Noah Perry
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Redouane Aherrahrou
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Maniselvan Kuppusamy
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Chaojie Yang
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jose Verdezoto Mosquera
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Collin J. Dube
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, Virginia, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Meredith Palmore
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jaspreet K. Kalra
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, The Netherlands
| | | | - Ljubica Matic
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ulf Hedin
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ani Manichaikul
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Swapnil K. Sonkusare
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Australia
| | - Johan L.M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Huddinge, Sweden
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Clint L. Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
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128
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Xu YC, Wang JX, Chu YR, Qian H, Wang HY, Wang F. Diseases of the musculoskeletal system and connective tissue and risk of breast cancer: Mendelian randomization study in European and East Asian populations. Front Oncol 2023; 13:1170119. [PMID: 37182186 PMCID: PMC10169740 DOI: 10.3389/fonc.2023.1170119] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 04/10/2023] [Indexed: 05/16/2023] Open
Abstract
Objective Associations between diseases of the musculoskeletal system and connective tissue (MSCTD) and breast cancer (BC) have not been elucidated completely. The purpose of this study was to investigate the associations of MSCTD, rheumatoid arthritis (RA), Sjogren syndrome (SS), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), dermatomyositis (DM), polymyositis (PM), osteoarthritis (OA) of hip or knee, and ankylosing spondylitis (AS) with BC in European populations and East Asian populations using Mendelian randomized (MR) analysis. Methods The genetic instruments linked to MSCTD, RA, SS, SLE, SSc, DM, PM, OA, and AS were chosen from the EBI database of complete genome-wide association studies (GWAS) summary data and the FinnGen consortium. The associations of genetic variants with BC were extracted from the Breast Cancer Association Consortium (BCAC). Two Sample MR was performed using summary data from GWAS, principally using the inverse variant weighted (IVW) method. Heterogeneity, pleiotropy, and sensitivity analyses were performed to evaluate the robustness of the results by weighted median, MR Egger, simple mode, weighted mode, and leave-one-out analysis. Results In the European population, causal relationships between RA and BC (OR=1.04, 95%CI: 1.01-1.07, P=0.023), AS and BC (OR=1.21, 95%CI: 1.06-1.36, P=0.013) were confirmed. IVW analysis showed DM (OR=0.98, 95%CI: 0.96-0.99, P=0.026) and PM (OR=0.98, 95%CI: 0.97-0.99, P=0.002) were associated with slightly decreased risks of estrogen receptor (ER)+ BC, and MSCTD was associated with an increased risk of ER- BC (OR=1.85, 95%CI: 1.27-2.44, P=0.039). There was no causal relationship between SLE, SS, SSc, OA, and BC, neither ER+ BC nor ER- BC. However, in the East Asian population, IVW analysis showed that RA (OR=0.94, 95%CI: 0.89-0.99, P=0.0096) and SLE (OR=0.95, 95%CI: 0.92-0.99, P=0.0058) was associated with decreased risks of BC. Conclusions This study suggests that causal relationships between patients with MSCTD and BC in the European population are different from those in the East Asian population, patients with RA and AS in the European population have an increased risk of BC, patients with MSCTD have increased risk of ER- BC in the European population, while patients with RA and SLE in the East Asian population have decreased risk of BC.
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Affiliation(s)
- Yue-chen Xu
- Department of Radiotherapy, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jian-xiong Wang
- Department of Rheumatology and Immunology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yi-ran Chu
- Department of Rheumatology and Immunology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Han Qian
- Department of Radiotherapy, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Hong-yan Wang
- Department of Radiotherapy, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Fan Wang
- Department of Radiotherapy, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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Wang H, Li Y, Cao W, Zhang J, Cao M, Meng X, Liu D, Wang Y. Leveraging IgG N-glycosylation to infer the causality between T2D and hypertension. Diabetol Metab Syndr 2023; 15:80. [PMID: 37095539 PMCID: PMC10127371 DOI: 10.1186/s13098-023-01053-6] [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: 01/11/2023] [Accepted: 04/07/2023] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Observational studies demonstrated a bidirectional association between type 2 diabetes (T2D) and hypertension, whereas Mendelian randomization (MR) analyses supported the causality from T2D to hypertension but not causal from hypertension to T2D. We previously found that IgG N-glycosylation is associated with both T2D and hypertension, and thus IgG N-glycosylation might link the causality between them. METHODS We carried out a genome-wide association study (GWAS) to identify IgG N-glycosylation-quantitative-trait loci (QTLs) integrating GWAS for T2D and hypertension and then performed bidirectional univariable and multivariable MR analyses to infer the causal association among them. The inverse-variance-weighted (IVW) analysis was performed as the primary analysis, followed by some sensitivity analyses to explore the stability of the results. RESULTS Six putatively causal IgG N-glycans for T2D and four for hypertension were identified in the IVW method. Genetically predicted T2D increased the risk of hypertension (odds ratio [OR] = 1.177, 95% confidence interval (95% CI) = 1.037-1.338, P = 0.012) and vice versa (OR = 1.391, 95% CI = 1.081-1.790, P = 0.010). Multivariable MR showed that T2D remained at risk effect with hypertension ([OR] = 1.229, 95% CI = 1.140-1.325, P = 7.817 × 10-8) after conditioning on T2D-related IgG-glycans. Conversely, hypertension was associated with higher T2D risk (OR = 1.287, 95% CI = 1.107-1.497, P = 0.001) after adjusting for related IgG-glycans. No evidence of horizontal pleiotropy was observed, as MR‒Egger regression provided P values for intercept > 0.05. CONCLUSION Our study validated the mutual causality between T2D and hypertension from the perspective of IgG N-glycosylation, further validating the "common soil" hypothesis underlying the pathogenesis of T2D and hypertension.
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Affiliation(s)
- Haotian Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Yuan Li
- Lianyungang Maternal and Child Health Hospital, Lianyungang, 222062, Jiangsu, China
| | - Weijie Cao
- Centre for Precision Medicine, Edith Cowan University, Perth, 60127, Australia
| | - Jie Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Mingyang Cao
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China
| | - Di Liu
- Centre for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, University Town, Nanshan District, Shenzhen, 518055, Guangdong, China.
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China.
- Centre for Precision Medicine, Edith Cowan University, Perth, 60127, Australia.
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Shimada M, Yoshihara K, Tanigawa T, Nomura H, Hamanishi J, Fujiwara S, Tanabe H, Kajiyama H, Mandai M, Aoki D, Enomoto T, Okamoto A. An attempt to establish real-world databases of poly(ADP-ribose) polymerase inhibitors for advanced or recurrent epithelial ovarian cancer: the Japanese Gynecologic Oncology Group. J Gynecol Oncol 2023; 34:e62. [PMID: 37116954 PMCID: PMC10157342 DOI: 10.3802/jgo.2023.34.e62] [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: 03/20/2023] [Accepted: 04/16/2023] [Indexed: 04/30/2023] Open
Abstract
The development of new treatments for gynecological malignancies has been conducted mainly through collaborative international phase III trials led by the United States and Europe. The survival outcomes of many gynecological malignancies have greatly improved as a result. Recent large-scale genome-wide association studies have revealed that drug efficacy and adverse event profiles are not always uniform. Thus, it is important to validate new treatment options in each country to safely and efficiently provide newly developed treatment options to patients with gynecological malignancies. The Japanese Gynecologic Oncology Group (JGOG) is conducting 5 cohort studies (JGOG 3026, 3027, 3028, 3030, and 3031) to establish real-world data (RWD) of poly(ADP-ribose) polymerase (PARP) inhibitor use in patients with advanced or recurrent epithelial ovarian cancer. The RWD constructed will be used to provide newly developed PARP inhibitors for women with advanced or recurrent ovarian cancer in a safer and more efficient manner as well as to develop further treatment options. In 2022, The JGOG, Korean Gynecologic Oncology Group, Chinese Gynecologic Cancer Society, and Taiwanese Gynecologic Oncology Group established the East Asian Gynecologic Oncology Trial Group to collaborate with East Asian countries in clinical research on gynecologic malignancies and disseminate new knowledge on gynecologic malignancies from Asia. The JGOG will conduct a collaborative integrated analysis of the RWD generated from Asian countries and disseminate real-world clinical knowledge regarding new treatment options that have been clinically implemented.
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Affiliation(s)
- Muneaki Shimada
- Department of Obstetrics and Gynecology, Tohoku University School of Medicine, Sendai, Japan
- Tohoku University Advanced Research Center for Innovations in Next-Generation Medicine, Sendai, Japan.
| | - Kosuke Yoshihara
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Chuo, Japan
| | - Terumi Tanigawa
- Department of Gynecology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Hiroyuki Nomura
- Department of Obstetrics and Gynecology, School of Medicine, Fujita Health University, Toyoake, Japan
| | - Junzo Hamanishi
- Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Satoe Fujiwara
- Department of Obstetrics and Gynecology, Osaka Medical and Pharmaceutical University, Takatsuki, Japan
| | - Hiroshi Tanabe
- Department of Gynecology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Hiroaki Kajiyama
- Department of Obstetrics and Gynecology, Nagoya University Graduate School of Medicine, Showa-ku, Japan
| | - Masaki Mandai
- Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Daisuke Aoki
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo, Japan
| | - Takayuki Enomoto
- Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Chuo, Japan
| | - Aikou Okamoto
- Department of Obstetrics and Gynecology, Jikei University School of Medicine, Tokyo, Japan
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Yun H, Lim JE, Lee EY. Genetic Risk Score for Prediction of Coronary Heart Disease in the Korean Genome and Epidemiology Study. Rev Cardiovasc Med 2023; 24:102. [PMID: 39076255 PMCID: PMC11273040 DOI: 10.31083/j.rcm2404102] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 01/25/2023] [Accepted: 02/08/2023] [Indexed: 07/31/2024] Open
Abstract
Background Using a genetic risk score (GRS) to predict coronary heart disease (CHD) may detect disease earlier. The current study aims to assess whether GRS is associated with CHD incidence and whether it is clinically useful for improving prediction using traditional risk factors (TRFs) as well as family history. Methods Data from a total of 48,941 participants in the Korean Genome and Epidemiology Study were analyzed in the current study. The weighted GRS was constructed using 55 single-nucleotide polymorphisms based on published genome-wide association studies. The association of GRS with incident CHD was analyzed using Cox proportional hazard model. Discrimination and reclassification were assessed to demonstrate the clinical utility of GRS. The analyses were performed separately by sex. Results After adjusting for family history and TRFs, GRS was significantly associated with CHD incidence in men; compared to the low GRS group, men in the high GRS group had a 2.07-fold increased risk of CHD (95% confidence interval [CI]: 1.51-2.85). In men, the combination of TRFs, family history, and GRS had better performance than TRFs alone (C statistics for TRF-only model, 0.66, 95% CI, 0.64-0.69; C statistics for combination model, 0.68, 95% CI, 0.65-0.71; category-free reclassification index, 15%). In women, however, there was no significant association between GRS and CHD and no improvement between models. Conclusions GRS was associated with CHD incidence and contributed to a small improvement of CHD prediction in men. The potential clinical use of GRS may not outweigh the value of family history.
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Affiliation(s)
- Hyunok Yun
- Department of Nursing, Catholic Kkottongnae University, 28211 Cheongju, Republic of Korea
| | - Ji Eun Lim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, 02447 Seoul, Republic of Korea
| | - Eun Young Lee
- Department of Nursing, Catholic Kkottongnae University, 28211 Cheongju, Republic of Korea
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Bai H, Song M, Lei S, Jiao L, Hu X, Wu T, Song J, Liu T, Peng W, Zhao Z, Meng Z, Ying B. Genome-wide association study of tuberculosis in the western Chinese Han and Tibetan population. MedComm (Beijing) 2023; 4:e250. [PMID: 37009413 PMCID: PMC10050958 DOI: 10.1002/mco2.250] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 02/16/2023] [Accepted: 03/03/2023] [Indexed: 03/31/2023] Open
Abstract
Tuberculosis (TB) remains a serious global public health threat. Accumulated evidence has demonstrated that human susceptibility to TB has a strong genetic basis. And different susceptibility single nucleotide polymorphisms (SNP) have been reported in different studies. To gain greater insight into the host susceptibility to TB, we perform a two-stage genome-wide association study to identify the susceptible loci of TB. In the discovery stage, 3116 (1532 TB patients and 1584 healthy controls) and 439 (211 TB patients and 228 healthy controls) individuals were genome-wide genotyped from a western Chinese Han and Tibetan population, respectively. Based on the additive genetic model, we discovered 14 and three independent loci that had potential associations with TB susceptibility in the Chinese Han and Tibetan populations, respectively (p < 1 × 10-5). Furthermore, we conducted an imputation-based meta-analysis on another two East Asia cohorts to replicate our findings. We identified one independent locus harbored by the human leukocyte antigen (HLA) class II genes that was genome-wide significantly associated with TB (lead SNP rs111875628 with a p-value of 2.20 × 10-9). Our findings suggest a novel mechanism of the interaction with the HLA class II genes and reinforce the importance of the HLA class II alleles in response to TB.
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Affiliation(s)
- Hao Bai
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Mengyuan Song
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Shikun Lei
- State Key Laboratory of Biotherapy and Cancer CenterWest China HospitalSichuan UniversityChengduP. R. China
| | - Lin Jiao
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Xuejiao Hu
- Division of Laboratory MedicineGuangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhouP. R. China
| | - Tao Wu
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Jiajia Song
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Tangyuheng Liu
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Wu Peng
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Zhenzhen Zhao
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Zirui Meng
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
| | - Binwu Ying
- Department of Laboratory MedicineWest China HospitalSichuan UniversityChengduP. R. China
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Marenholz I, Arnau-Soler A, Rosillo-Salazar OD, Lee YA. New insights from genetic studies of eczema. MED GENET-BERLIN 2023; 35:33-45. [PMID: 38835414 PMCID: PMC10842541 DOI: 10.1515/medgen-2023-2010] [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: 06/06/2024]
Abstract
Genome-wide association studies (GWAS) provided fundamental insight into the genetic determinants of complex allergic diseases. For eczema, 58 susceptibility loci were reported. Protein-changing variants were associated with eczema at genome-wide significance at 12 loci. The majority of risk variants were, however, located in non-coding, regulatory regions of the genome. Prioritized target genes were enriched in pathways of the immune response and of epithelial barrier function. Interestingly, a large overlap in the genetic architecture underlying different allergic diseases was identified pointing to common pathomechanisms for eczema, asthma, hay fever, and food allergy. Here, we review the most recent findings from GWAS for eczema including the role of rare variants and genetic heterogeneity in ethnically diverse populations. In addition, we provide an overview of genes underlying Mendelian disorders featuring eczematous skin inflammation.
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Affiliation(s)
- Ingo Marenholz
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Robert-Rössle-Str. 10 13125 Berlin Germany
| | - Aleix Arnau-Soler
- Max Delbrück Center for Molecular Medicine in Robert-Rössle-Str. 10 13125 Berlin Germany
| | - Oscar Daniel Rosillo-Salazar
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Robert-Rössle-Str. 10 13125 Berlin Germany
| | - Young-Ae Lee
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Robert-Rössle-Str. 10 13125 Berlin Germany
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Deng Y, Huang J, Wong MCS. Association between serum uric acid and prostate cancer risk in East Asian populations: a Mendelian randomization study. Eur J Nutr 2023; 62:1323-1329. [PMID: 36542132 DOI: 10.1007/s00394-022-03076-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE Previous observational studies showed that serum uric acid (SUA) was associated with prostate cancer, but the causal relationship is unclear. This study aimed to explore the potential causal association between SUA and prostate cancer risk using Mendelian randomization (MR) analyses in the East Asian populations. METHODS Publicly available summary-level genome-wide association studies (GWAS) data on SUA were obtained from a genome-wide meta-analysis of three Japanese cohorts (121,745 subjects). The GWAS data on prostate cancer were derived from Biobank Japan (109,347 subjects with 5,408 cases and 103,939 controls). A total of 34 SUA-related single-nucleotide polymorphisms (SNPs) (P value < 5 × 10-8) were identified as instrumental variables. The inverse variance weighted method was used as the primary method to compute the odds ratios (ORs) and 95% confidence intervals (95% CIs) for per standard deviation increase in SUA. MR Egger, weighted median, and weighted mode were also applied to test the robustness of the results. RESULTS Genetically predicted SUA was positively associated with prostate cancer risk using inverse variance weighted (OR = 1.12; 95% CI 1.00-1.26; P = 0.043). The positive association was robust when MR Egger (OR = 1.16; 95% CI 1.01-1.34; P = 0.048), weighted median (OR = 1.18; 95% CI 1.03-1.36; P = 0.018), and weighted mode (OR = 1.14; 95% CI 1.01-1.29; P = 0.041) were used. CONCLUSION There were potential causal associations between higher genetically predicted SUA levels and increased prostate cancer risk. Further, MR studies with more valid SNPs and more cancer cases are needed. Validation of the findings is also recommended.
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Affiliation(s)
- Yunyang Deng
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, the Chinese University of Hong Kong, Hong Kong SAR, 999077, China
| | - Junjie Huang
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, the Chinese University of Hong Kong, Hong Kong SAR, 999077, China
| | - Martin Chi Sang Wong
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, the Chinese University of Hong Kong, Hong Kong SAR, 999077, China.
- School of Public Health, the Chinese Academy of Medical Sciences and the Peking Union Medical College, Beijing, 100000, China.
- School of Public Health, Peking University, Beijing, 100000, China.
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Liu X, Zou L, Nie C, Qin Y, Tong X, Wang J, Yang H, Xu X, Jin X, Xiao L, Zhang T, Min J, Zeng Y, Jia H, Hou Y. Mendelian randomization analyses reveal causal relationships between the human microbiome and longevity. Sci Rep 2023; 13:5127. [PMID: 36991009 PMCID: PMC10052271 DOI: 10.1038/s41598-023-31115-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 03/07/2023] [Indexed: 03/31/2023] Open
Abstract
Although recent studies have revealed the association between the human microbiome especially gut microbiota and longevity, their causality remains unclear. Here, we assess the causal relationships between the human microbiome (gut and oral microbiota) and longevity, by leveraging bidirectional two-sample Mendelian randomization (MR) analyses based on genome-wide association studies (GWAS) summary statistics of the gut and oral microbiome from the 4D-SZ cohort and longevity from the CLHLS cohort. We found that some disease-protected gut microbiota such as Coriobacteriaceae and Oxalobacter as well as the probiotic Lactobacillus amylovorus were related to increased odds of longevity, whereas the other gut microbiota such as colorectal cancer pathogen Fusobacterium nucleatum, Coprococcus, Streptococcus, Lactobacillus, and Neisseria were negatively associated with longevity. The reverse MR analysis further revealed genetically longevous individuals tended to have higher abundances of Prevotella and Paraprevotella but lower abundances of Bacteroides and Fusobacterium species. Few overlaps of gut microbiota-longevity interactions were identified across different populations. We also identified abundant links between the oral microbiome and longevity. The additional analysis suggested that centenarians genetically had a lower gut microbial diversity, but no difference in oral microbiota. Our findings strongly implicate these bacteria to play a role in human longevity and underscore the relocation of commensal microbes among different body sites that would need to be monitored for long and healthy life.
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Affiliation(s)
- Xiaomin Liu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Chao Nie
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Xin Tong
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen, 518083, China
- James D. Watson Institute of Genome Sciences, Hangzhou, 310058, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, 518083, China
- James D. Watson Institute of Genome Sciences, Hangzhou, 310058, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Tao Zhang
- BGI-Shenzhen, Shenzhen, 518083, China
- Department of Biology, University of Copenhagen, Universitetsparken 13, 2100, Copenhagen, Denmark
| | - Junxia Min
- School of Medicine, The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University, Hangzhou, China.
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Raissun Institute for Advanced Studies, Peking University, Beijing, China.
| | - Huijue Jia
- Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Shanghai, China.
| | - Yong Hou
- BGI-Shenzhen, Shenzhen, 518083, China.
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Wu TW, Chou CL, Cheng CF, Lu SX, Wu YJ, Wang LY. Associations of genetic markers of diabetes mellitus with carotid atherosclerosis: a community-based case-control study. Cardiovasc Diabetol 2023; 22:51. [PMID: 36894991 PMCID: PMC9999522 DOI: 10.1186/s12933-023-01787-7] [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] [Received: 01/06/2023] [Accepted: 03/01/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND Diabetes mellitus (DM) is a well-established determinant of atherosclerosis and cardiovascular diseases (CVD). Recently, genome-wide association studies (GWAS) identified several single nucleotide polymorphism (SNP) significantly correlated with DM. The study aimed to explore the relationships of the top significant DM SNPs with carotid atherosclerosis (CA). METHODS We used a case-control design and randomly selected 309 cases and 439 controls with and without, respectively, carotid plaque (CP) from a community-based cohort. Eight recent GWAS on DM in East Asians reported hundreds of SNPs with genome-wide significance. The study used the top significant DM SNPs, with a p-value < 10-16, as the candidate genetic markers of CA. The independent effects of these DM SNPs on CA were assessed by multivariable logistic regression analyses to control the effects of conventional cardio-metabolic risk factors. RESULTS Multivariable analyses showed that, 9 SNPs, including rs4712524, rs1150777, rs10842993, rs2858980, rs9583907, rs1077476, rs7180016, rs4383154, and rs9937354, showed promising associations with the presence of carotid plaque (CP). Among them, rs9937354, rs10842993, rs7180016, and rs4383154 showed significantly independent effects. The means (SD) of the 9-locus genetic risk score (9-GRS) of CP-positive and -negative subjects were 9.19 (1.53) and 8.62 (1.63), respectively (p < 0.001). The corresponding values of 4-locus GRS (4-GRS) were 4.02 (0.81) and. 3.78 (0.92), respectively (p < 0.001). The multivariable-adjusted odds ratio of having CP for per 1.0 increase in 9-GRS and 4-GRS were 1.30 (95% CI 1.18-1.44; p = 4.7 × 10-7) and 1.47 (95% CI 1.74-9.40; p = 6.1 × 10-5), respectively. The means of multi-locus GRSs of DM patients were similar to those of CP-positive subjects and higher than those of CP-negative or DM-negative subjects. CONCLUSIONS We identified 9 DM SNPs showing promising associations with CP. The multi-locus GRSs may be used as biomarkers for the identification and prediction of high-risks subjects for atherosclerosis and atherosclerotic diseases. Future studies on these specific SNPs and their associated genes may provide valuable information for the preventions of DM and atherosclerosis.
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Affiliation(s)
- Tzu-Wei Wu
- Department of Medicine, MacKay Medical College, No. 46, Sec. 3, Zhongzheng Road, Sanzhi District, New Taipei City, Taiwan
| | - Chao-Liang Chou
- Department of Medicine, MacKay Medical College, No. 46, Sec. 3, Zhongzheng Road, Sanzhi District, New Taipei City, Taiwan.,Department of Neurology, MacKay Memorial Hospital, New Taipei City, Taiwan
| | - Chun-Fang Cheng
- Tamsui Health Station, Department of Health, New Taipei City Government, New Taipei City, Taiwan
| | - Shu-Xin Lu
- Department of Neurology, MacKay Memorial Hospital, New Taipei City, Taiwan
| | - Yih-Jer Wu
- Department of Medicine, MacKay Medical College, No. 46, Sec. 3, Zhongzheng Road, Sanzhi District, New Taipei City, Taiwan. .,Institute of Biomedical Sciences, MacKay Medical College, New Taipei City, Taiwan. .,Cardiovascular Center, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan. .,Department of Medical Research, MacKay Memorial Hospital, Taipei, Taiwan.
| | - Li-Yu Wang
- Department of Medicine, MacKay Medical College, No. 46, Sec. 3, Zhongzheng Road, Sanzhi District, New Taipei City, Taiwan.
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Deng Y, Huang J, Wong MCS. Associations of alcohol and coffee with colorectal cancer risk in East Asian populations: a Mendelian randomization study. Eur J Nutr 2023; 62:749-756. [PMID: 36239790 DOI: 10.1007/s00394-022-03002-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 09/07/2022] [Indexed: 11/26/2022]
Abstract
PURPOSE Previous observational studies have shown that alcohol and coffee were associated with colorectal cancer (CRC) risk, but the causal relationships have not been adequately explored. This study aimed to assess the potential causal associations of alcohol and coffee with CRC risk using Mendelian randomization (MR) analyses in an East Asian population. METHODS Publicly available summary-level genome-wide association studies data on ever/never alcohol drinker (n = 165,084), alcohol consumption (n = 58,610), coffee consumption (n = 152,634), and CRC (7062 cases and 195,745 controls) were obtained from the BioBank Japan (BBJ). Single-nucleotide polymorphisms (SNPs) that were significantly related to the exposures were identified as instrumental variables. Five, two, and six SNPs were used for ever/never alcohol drinkers, alcohol consumption, and coffee consumption, respectively. The inverse variance weighted method was used as the main MR method to calculate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of CRC risk per one-unit change in exposures. RESULTS Genetically predicted ever/never alcohol drinkers (OR: 1.08; 95% CI 1.06, 1.11; P < 0.001) and alcohol consumption (OR: 1.39; 95% CI 1.21, 1.60; P < 0.001) were positively associated with CRC risk. Conversely, genetically predicted coffee consumption was inversely related to CRC risk, with an OR (95% CI) of 0.80 (0.64, 0.99) (P = 0.037). CONCLUSION Genetically predicted alcohol use and consumption were risk factors for CRC while genetically predicted coffee consumption was a protective factor. Our findings highlight the effectiveness of keeping healthy dietary habits to prevent CRC. Further studies with more valid SNPs and CRC cases are needed. Validation of our findings is also recommended.
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Affiliation(s)
- Yunyang Deng
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, 999077, China
| | - Junjie Huang
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, 999077, China
| | - Martin Chi Sang Wong
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, 999077, China.
- School of Public Health, The Chinese Academy of Medical Sciences and the Peking Union Medical College, Beijing, 100000, China.
- School of Public Health, Peking University, Beijing, 100000, China.
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138
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Xie Y, Acosta JN, Ye Y, Demarais ZS, Conlon CJ, Chen M, Zhao H, Falcone GJ. Whole-Exome Sequencing Analyses Support a Role of Vitamin D Metabolism in Ischemic Stroke. Stroke 2023; 54:800-809. [PMID: 36762557 PMCID: PMC10467223 DOI: 10.1161/strokeaha.122.040883] [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: 08/10/2022] [Accepted: 12/22/2022] [Indexed: 02/11/2023]
Abstract
BACKGROUND Ischemic stroke (IS) is a highly heritable trait, and genome-wide association studies have identified several commonly occurring susceptibility risk loci for this condition. However, there are limited data on the contribution of rare genetic variation to IS. METHODS We conducted an exome-wide study using whole-exome sequencing data from 152 058 UK Biobank participants, including 1777 IS cases. We performed single-variant analyses for rare variants and gene-based analyses for loss-of-function and deleterious missense rare variants. We validated these results through (1) gene-based testing using summary statistics from MEGASTROKE-a genome-wide association study of IS that included 67 162 IS cases and 454 450 controls, (2) gene-based testing using individual-level data from 1706 IS survivors, including 142 recurrent IS cases, enrolled in the VISP trial (Vitamin Intervention for Stroke Prevention); and (3) gene-based testing against neuroimaging phenotypes related to cerebrovascular disease using summary-level data from 42 310 UK Biobank participants with available magnetic resonance imaging data. RESULTS In single-variant association analyses, none of the evaluated variants were associated with IS at genome-wide significance levels (P<5×10-8). In the gene-based analysis focused on loss-of-function and deleterious missense variants, rare genetic variation at CYP2R1 was significantly associated with IS risk (P=2.6×10-6), exceeding the Bonferroni-corrected threshold for 16 074 tests (P<3.1×10-6). Validations analyses indicated that CYP2R1 was associated with IS risk in MEGASTROKE (gene-based test, P=0.003), with IS recurrence in the VISP trial (gene-based test, P=0.001) and with neuroimaging traits (white matter hyperintensity, mean diffusivity, and fractional anisotropy) in the UK Biobank neuroimaging study (all gene-based tests, P<0.05). CONCLUSIONS Because CYP2R1 plays an important role in vitamin D metabolism and existing observational evidence suggests an association between vitamin D levels and cerebrovascular disease, our results support a role of this pathway in the occurrence of IS.
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Affiliation(s)
- Yuhan Xie
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Julián N. Acosta
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Yixuan Ye
- Program of Computational Biology and Bioinformatics, Yale School of Medicine, New Haven, CT, USA
| | - Zachariah S. Demarais
- Frank H. Netter M.D. School of Medicine, Quinnipiac University, North Haven, CT, USA
| | - Carolyn J. Conlon
- Frank H. Netter M.D. School of Medicine, Quinnipiac University, North Haven, CT, USA
| | - Ming Chen
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Program of Computational Biology and Bioinformatics, Yale School of Medicine, New Haven, CT, USA
| | - Guido J. Falcone
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
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139
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Han Y, Byun J, Zhu C, Sun R, Roh JY, Cordell HJ, Lee HS, Shaw VR, Kang SW, Razjouyan J, Cooley MA, Hassan MM, Siminovitch KA, Folseraas T, Ellinghaus D, Bergquist A, Rushbrook SM, Franke A, Karlsen TH, Lazaridis KN, McGlynn KA, Roberts LR, Amos CI. Multitrait genome-wide analyses identify new susceptibility loci and candidate drugs to primary sclerosing cholangitis. Nat Commun 2023; 14:1069. [PMID: 36828809 PMCID: PMC9958016 DOI: 10.1038/s41467-023-36678-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 02/10/2023] [Indexed: 02/26/2023] Open
Abstract
Primary sclerosing cholangitis (PSC) is a rare autoimmune bile duct disease that is strongly associated with immune-mediated disorders. In this study, we implemented multitrait joint analyses to genome-wide association summary statistics of PSC and numerous clinical and epidemiological traits to estimate the genetic contribution of each trait and genetic correlations between traits and to identify new lead PSC risk-associated loci. We identified seven new loci that have not been previously reported and one new independent lead variant in the previously reported locus. Functional annotation and fine-mapping nominated several potential susceptibility genes such as MANBA and IRF5. Network-based in silico drug efficacy screening provided candidate agents for further study of pharmacological effect in PSC.
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Affiliation(s)
- Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Catherine Zhu
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Ryan Sun
- Department of Biostatistics, University of Texas, M.D. Anderson Cancer Center, Houston, TX, USA
| | - Julia Y Roh
- Department of Pharmacy, Ochsner Health, New Orleans, LA, USA
| | - Heather J Cordell
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Hyun-Sung Lee
- David J. Sugarbaker Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Vikram R Shaw
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Sung Wook Kang
- David J. Sugarbaker Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Javad Razjouyan
- VA HSR&D, Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Big Data Scientist Training Enhancement Program (BD-STEP), VA Office of Research and Development, Washington, DC, USA
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- VA Quality Scholars Coordinating Center, IQuESt, Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Matthew A Cooley
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, USA
| | - Manal M Hassan
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Katherine A Siminovitch
- Departments of Medicine, Immunology and Medical Sciences, University of Toronto, Toronto, Ontario, Canada
- Mount Sinai Hospital, Lunenfeld-Tanenbaum Research Institute and Toronto General Research Institute, Toronto, Ontario, Canada
| | - Trine Folseraas
- Norwegian PSC Research Center, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Annika Bergquist
- Department of Medicine Huddinge, Unit of Gastroenterology and Rheumatology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Simon M Rushbrook
- Department of Gastroenterology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
- Norwich Medical School, University of East Anglia, Norfolk, United Kingdom
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Tom H Karlsen
- Oslo University Hospital Rikshospitalet and University of Oslo, Oslo, Norway
| | - Konstantinos N Lazaridis
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Katherine A McGlynn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Lewis R Roberts
- Oslo University Hospital Rikshospitalet and University of Oslo, Oslo, Norway
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
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140
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Zhao B, Li Y, Fan Z, Wu Z, Shu J, Yang X, Yang Y, Wang X, Li B, Wang X, Copana C, Yang Y, Lin J, Li Y, Stein JL, O'Brien JM, Li T, Zhu H. Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.16.23286035. [PMID: 36824893 PMCID: PMC9949187 DOI: 10.1101/2023.02.16.23286035] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yilin Yang
- Department of Computer and Information Science and Electrical and Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT 06511, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joan M. O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Diseases, PA, 19104, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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141
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Genetic Susceptibility to Hepatocellular Carcinoma in Patients with Chronic Hepatitis Virus Infection. Viruses 2023; 15:v15020559. [PMID: 36851773 PMCID: PMC9964813 DOI: 10.3390/v15020559] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/13/2023] [Accepted: 02/14/2023] [Indexed: 02/22/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths globally. The risk factors for HCC include chronic hepatitis B and C virus infections, excessive alcohol consumption, obesity, metabolic disease, and aflatoxin exposure. In addition to these viral and environmental risk factors, individual genetic predisposition is a major determinant of HCC risk. Familial clustering of HCC has been observed, and a hereditary factor likely contributes to the risk of HCC development. The familial aggregation may depend on a shared environment and genetic background as well as the interactions of environmental and genetic factors. Genome-wide association studies (GWASs) are one of the most practical tools for mapping the patterns of inheritance for the most common form of genomic variation, single nucleotide polymorphisms. This approach is practical for investigating genetic variants across the human genome, which is affected by thousands of common genetic variants that do not follow Mendelian inheritance. This review article summarizes the academic knowledge of GWAS-identified genetic loci and their association with HCC. We summarize the GWASs in accordance with various chronic hepatitis virus infection statuses. This genetic profiling could be used to identify candidate biomarkers to refine HCC screening and management by enabling individual risk-based personalization and stratification. A more comprehensive understanding of the genetic mechanisms underlying individual predisposition to HCC may lead to improvements in the prevention and early diagnosis of HCC and the development of effective treatment strategies.
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142
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Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility. Nat Commun 2023; 14:896. [PMID: 36797296 PMCID: PMC9935862 DOI: 10.1038/s41467-023-36491-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 02/03/2023] [Indexed: 02/18/2023] Open
Abstract
Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery.
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143
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Yang Y, Knol MJ, Wang R, Mishra A, Liu D, Luciano M, Teumer A, Armstrong N, Bis JC, Jhun MA, Li S, Adams HHH, Aziz NA, Bastin ME, Bourgey M, Brody JA, Frenzel S, Gottesman RF, Hosten N, Hou L, Kardia SLR, Lohner V, Marquis P, Maniega SM, Satizabal CL, Sorond FA, Valdés Hernández MC, van Duijn CM, Vernooij MW, Wittfeld K, Yang Q, Zhao W, Boerwinkle E, Levy D, Deary IJ, Jiang J, Mather KA, Mosley TH, Psaty BM, Sachdev PS, Smith JA, Sotoodehnia N, DeCarli CS, Breteler MMB, Ikram MA, Grabe HJ, Wardlaw J, Longstreth WT, Launer LJ, Seshadri S, Debette S, Fornage M. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI. Brain 2023; 146:492-506. [PMID: 35943854 PMCID: PMC9924914 DOI: 10.1093/brain/awac290] [Citation(s) in RCA: 11] [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: 02/18/2022] [Revised: 06/23/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.
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Affiliation(s)
- Yunju Yang
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX 77030, USA
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Aniket Mishra
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
| | - Dan Liu
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Michelle Luciano
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, 15-269, Poland
| | - Nicola Armstrong
- Mathematics and Statistics, Curtin University, 6845 Perth, Australia
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Min A Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Hieab H H Adams
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Nasir Ahmad Aziz
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, 53127 Bonn, Germany
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Mathieu Bourgey
- Canadian Centre for Computational Genomics, McGill University, Montréal, Quebec, Canada H3A 0G1
- Department for Human Genetics, McGill University Genome Centre, McGill University, Montréal, Quebec, Canada H3A 0G1
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
| | - Rebecca F Gottesman
- Stroke Branch, National Institutes of Neurological Disorders and Stroke, Bethesda, MD 20814, USA
| | - Norbert Hosten
- Department of Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Valerie Lohner
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Pascale Marquis
- Canadian Centre for Computational Genomics, McGill University, Montréal, Quebec, Canada H3A 0G1
- Department for Human Genetics, McGill University Genome Centre, McGill University, Montréal, Quebec, Canada H3A 0G1
| | - Susana Muñoz Maniega
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases and Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX 78229, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
| | - Farzaneh A Sorond
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Maria C Valdés Hernández
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Nuffield Department of Population Health, Oxford University, Oxford, OX3 7LF, UK
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Rostock, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA 01701, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
- Neuroscience Research Australia, Sydney, NSW 2031, Australia
| | - Thomas H Mosley
- The Memory Impairment Neurodegenerative Dementia (MIND) Research Center, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
- Department of Epidemiology, University of Washington, Seattle, WA 98104, USA
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, University of New South Wales, Randwick, NSW 2031, Australia
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Charles S DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA 95816, USA
| | - Monique M B Breteler
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, 53127 Bonn, Germany
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Rostock, Germany
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - W T Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA 98104, USA
- Department of Neurology, University of Washington, Seattle, WA 98104, USA
| | - Lenore J Launer
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases and Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX 78229, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
| | - Stephanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
- CHU de Bordeaux, Department of Neurology, F-33000 Bordeaux, France
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX 77030, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science at Houston, Houston, TX 77030, USA
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Aherrahrou R, Lue D, Perry RN, Aberra YT, Khan MD, Soh JY, Örd T, Singha P, Yang Q, Gilani H, Benavente ED, Wong D, Hinkle J, Ma L, Sheynkman GM, den Ruijter HM, Miller CL, Björkegren JLM, Kaikkonen MU, Civelek M. Genetic Regulation of SMC Gene Expression and Splicing Predict Causal CAD Genes. Circ Res 2023; 132:323-338. [PMID: 36597873 PMCID: PMC9898186 DOI: 10.1161/circresaha.122.321586] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 12/20/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies have identified over 175 loci associated with CAD. The majority of these loci are in noncoding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we aimed to identify the subset of the CAD loci associated with the regulation of transcription in distinct SMC phenotypes. METHODS We measured gene expression in SMCs isolated from the ascending aortas of 151 heart transplant donors of various genetic ancestries in quiescent or proliferative conditions and calculated the association of their expression and splicing with ~6.3 million imputed single-nucleotide polymorphism markers across the genome. RESULTS We identified 4910 expression and 4412 splicing quantitative trait loci (sQTLs) representing regions of the genome associated with transcript abundance and splicing. A total of 3660 expression quantitative trait loci (eQTLs) had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 eQTLs were SMC-specific and sex-biased, respectively. We made these results available for public query on a user-friendly website. To identify the effector transcript(s) regulated by CAD loci, we used 4 distinct colocalization approaches. We identified 84 eQTL and 164 sQTL that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. One CAD locus colocalized with a sex-specific eQTL (TERF2IP), and another locus colocalized with SMC-specific eQTL (ALKBH8). The most significantly associated CAD locus, 9p21, was an sQTL for the long noncoding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs. CONCLUSIONS Collectively, our results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.
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Affiliation(s)
- Rédouane Aherrahrou
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Dillon Lue
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - R Noah Perry
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Yonathan Tamrat Aberra
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Joon Yuhl Soh
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
| | - Tiit Örd
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Prosanta Singha
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Qianyi Yang
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Huda Gilani
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ernest Diez Benavente
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, The Netherlands
| | - Doris Wong
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jameson Hinkle
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, United States of America
| | - Gloria M Sheynkman
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Cancer Center, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, The Netherlands
| | - Clint L Miller
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Johan LM Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, United States of America
- Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, United States of America
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Minna U Kaikkonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America
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Ohbe H, Hachiya T, Yamaji T, Nakano S, Miyamoto Y, Sutoh Y, Otsuka-Yamasaki Y, Shimizu A, Yasunaga H, Sawada N, Inoue M, Tsugane S, Iwasaki M. Development and validation of genome-wide polygenic risk scores for predicting breast cancer incidence in Japanese females: a population-based case-cohort study. Breast Cancer Res Treat 2023; 197:661-671. [PMID: 36538246 DOI: 10.1007/s10549-022-06843-6] [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: 09/28/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE This study aimed to develop an ancestry-specific polygenic risk scores (PRSs) for the prediction of breast cancer events in Japanese females and validate it in a longitudinal cohort study. METHODS Using publicly available summary statistics of female breast cancer genome-wide association study (GWAS) of Japanese and European ancestries, we, respectively, developed 31 candidate genome-wide PRSs using pruning and thresholding (P + T) and LDpred methods with varying parameters. Among the candidate PRS models, the best model was selected using a case-cohort dataset (63 breast cancer cases and 2213 sub-cohorts of Japanese females during a median follow-up of 11.9 years) according to the maximal predictive ability by Harrell's C-statistics. The best-performing PRS for each derivation GWAS was evaluated in another independent case-cohort dataset (260 breast cancer cases and 7845 sub-cohorts of Japanese females during a median follow-up of 16.9 years). RESULTS For the best PRS model involving 46,861 single nucleotide polymorphisms (SNPs; P + T method with PT = 0.05 and R2 = 0.2) derived from Japanese-ancestry GWAS, the Harrell's C-statistic was 0.598 ± 0.018 in the evaluation dataset. The age-adjusted hazard ratio for breast cancer in females with the highest PRS quintile compared with those in the lowest PRS quintile was 2.47 (95% confidence intervals, 1.64-3.70). The PRS constructed using Japanese-ancestry GWAS demonstrated better predictive performance for breast cancer in Japanese females than that using European-ancestry GWAS (Harrell's C-statistics 0.598 versus 0.586). CONCLUSION This study developed a breast cancer PRS for Japanese females and demonstrated the usefulness of the PRS for breast cancer risk stratification.
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Affiliation(s)
- Hiroyuki Ohbe
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan.
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
| | - Shiori Nakano
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yoshihisa Miyamoto
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan
| | - Yayoi Otsuka-Yamasaki
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan
| | - Hideo Yasunaga
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Norie Sawada
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Manami Inoue
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.,Division of Prevention, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Shoichiro Tsugane
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.,National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.,Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
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146
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Buch S, Innes H, Lutz PL, Nischalke HD, Marquardt JU, Fischer J, Weiss KH, Rosendahl J, Marot A, Krawczyk M, Casper M, Lammert F, Eyer F, Vogel A, Marhenke S, von Felden J, Sharma R, Atkinson SR, McQuillin A, Nattermann J, Schafmayer C, Franke A, Strassburg C, Rietschel M, Altmann H, Sulk S, Thangapandi VR, Brosch M, Lackner C, Stauber RE, Canbay A, Link A, Reiberger T, Mandorfer M, Semmler G, Scheiner B, Datz C, Romeo S, Ginanni Corradini S, Irving WL, Morling JR, Guha IN, Barnes E, Ansari MA, Quistrebert J, Valenti L, Müller SA, Morgan MY, Dufour JF, Trebicka J, Berg T, Deltenre P, Mueller S, Hampe J, Stickel F. Genetic variation in TERT modifies the risk of hepatocellular carcinoma in alcohol-related cirrhosis: results from a genome-wide case-control study. Gut 2023; 72:381-391. [PMID: 35788059 PMCID: PMC9872243 DOI: 10.1136/gutjnl-2022-327196] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 06/23/2022] [Indexed: 01/28/2023]
Abstract
OBJECTIVE Hepatocellular carcinoma (HCC) often develops in patients with alcohol-related cirrhosis at an annual risk of up to 2.5%. Some host genetic risk factors have been identified but do not account for the majority of the variance in occurrence. This study aimed to identify novel susceptibility loci for the development of HCC in people with alcohol related cirrhosis. DESIGN Patients with alcohol-related cirrhosis and HCC (cases: n=1214) and controls without HCC (n=1866), recruited from Germany, Austria, Switzerland, Italy and the UK, were included in a two-stage genome-wide association study using a case-control design. A validation cohort of 1520 people misusing alcohol but with no evidence of liver disease was included to control for possible association effects with alcohol misuse. Genotyping was performed using the InfiniumGlobal Screening Array (V.24v2, Illumina) and the OmniExpress Array (V.24v1-0a, Illumina). RESULTS Associations with variants rs738409 in PNPLA3 and rs58542926 in TM6SF2 previously associated with an increased risk of HCC in patients with alcohol-related cirrhosis were confirmed at genome-wide significance. A novel locus rs2242652(A) in TERT (telomerase reverse transcriptase) was also associated with a decreased risk of HCC, in the combined meta-analysis, at genome-wide significance (p=6.41×10-9, OR=0.61 (95% CI 0.52 to 0.70). This protective association remained significant after correction for sex, age, body mass index and type 2 diabetes (p=7.94×10-5, OR=0.63 (95% CI 0.50 to 0.79). Carriage of rs2242652(A) in TERT was associated with an increased leucocyte telomere length (p=2.12×10-44). CONCLUSION This study identifies rs2242652 in TERT as a novel protective factor for HCC in patients with alcohol-related cirrhosis.
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Affiliation(s)
- Stephan Buch
- Department of Medicine I, Dresden University Hospital, Dresden, Germany
- Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Hamish Innes
- School of Health and Life Sciences, Glasgow Caledonian University School of Health and Life Sciences, Glasgow, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | | | | | - Jens U Marquardt
- Department of Medicine I, University of Luebeck Human Medicine, Lubeck, Germany
| | - Janett Fischer
- Department of Gastroenterology and Rheumatology, Section Hepatology, Leipzig University, Leipzig, Germany
| | - Karl Heinz Weiss
- Department of Internal Medicine, Krankenhaus Salem, Heidelberg, Germany
| | - Jonas Rosendahl
- Department of Gastroenterology, University Hospital Halle, Halle, Germany
| | - Astrid Marot
- Division of Gastroenterology and Hepatology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
- Department of Gastroenterology and Hepatology, CHU UCL Namur, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Marcin Krawczyk
- Department of Medicine II, Saarland University Medical Center, Saarland University, Saarbrucken, Germany
- Laboratory of Metabolic Liver Diseases, Department of General, Transplant and Liver Surgery, Centre for Preclinical Research, Medical University of Warsaw, Warszawa, Poland
| | - Markus Casper
- Department of Medicine II, Saarland University Medical Center, Saarland University, Saarbrucken, Germany
| | - Frank Lammert
- Department of Medicine II, Saarland University Medical Center, Saarland University, Saarbrucken, Germany
| | - Florian Eyer
- Department of Clinical Toxicology, Klinikum Rechts der Isar, Technical University of Munich, Munchen, Germany
| | - Arndt Vogel
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
| | - Silke Marhenke
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
| | - Johann von Felden
- Department of Internal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Rohini Sharma
- Hammersmith Hospital Campus, Imperial College, London, UK
| | | | - Andrew McQuillin
- Molecular Psychiatry Laboratory, University College London, London, UK
| | - Jacob Nattermann
- Department of Internal Medicine I, University of Bonn, Bonn, Germany
| | - Clemens Schafmayer
- Department of General Surgery, Rostock University Medical Center, Rostock, Germany
| | - Andre Franke
- Institute for Clinical Molecular Biology, Kiel University, Kiel, Germany
| | | | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Heidi Altmann
- Department of Medicine I, University Hospital Dresden, Dresden, Germany
| | - Stefan Sulk
- Department of Medicine I, University Hospital Dresden, Dresden, Germany
| | - Veera Raghavan Thangapandi
- Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany
- Department of Medicine I, University Hospital Dresden, Dresden, Germany
| | - Mario Brosch
- Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany
- Department of Medicine I, University Hospital Dresden, Dresden, Germany
| | | | - Rudolf E Stauber
- Department of Internal Medicine, University of Graz, Graz, Austria
| | - Ali Canbay
- Department of Internal Medicine, Ruhr-Universitat Bochum, Bochum, Germany
| | - Alexander Link
- Department of Gastroenterology, Hepatology and Infectious Diseases, Otto von Guericke Universitat Magdeburg, Magdeburg, Germany
| | - Thomas Reiberger
- Division of Gastroenterology & Hepatology, Department of Internal Medicine III, Medical University of Vienna, Wien, Austria
| | - Mattias Mandorfer
- Division of Gastroenterology & Hepatology, Department of Internal Medicine III, Medical University of Vienna, Wien, Austria
| | - Georg Semmler
- Division of Gastroenterology & Hepatology, Department of Internal Medicine III, Medical University of Vienna, Wien, Austria
| | - Bernhard Scheiner
- Division of Gastroenterology & Hepatology, Department of Internal Medicine III, Medical University of Vienna, Wien, Austria
| | - Christian Datz
- Department of Internal Medicine, General Hospital Oberndorf, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Stefano Romeo
- Department of Molecular and Clinical Medicine, University of Gothenburg, Institute of Medicine, Sahlgrenska Academy, Wallenberg Laboratory, Gothenburg, Sweden
- Clinical Nutrition Unit, Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Stefano Ginanni Corradini
- Division of Gastroenterology, Department of Translational and Precision Medicine, University of Rome La Sapienza, Rome, Italy
| | | | - Joanne R Morling
- Division of Epidemiology and Public Health, University of Nottingham, Nottingham, UK
| | - Indra Neil Guha
- Nottingham Digestive Diseases NIHR Biomedical Research Unit, University Hospital, Nottingham, UK
| | - Eleanor Barnes
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - M Azim Ansari
- Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine and the Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Jocelyn Quistrebert
- Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine and the Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Luca Valenti
- Internal Medicine and Metabolic Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Sascha A Müller
- Department of Surgery, Hirslanden Klinik Beau-Site, Bern, Switzerland
| | - Marsha Yvonne Morgan
- Division of Medicine, Royal Free Campus, UCL Institute for Liver and Digestive Health, London, UK
| | | | - Jonel Trebicka
- Gastroenterology, Hepatology, Endocrinology and Clinical Infectiology, University of Münster, Münster, Germany
| | - Thomas Berg
- Division of Hepatology, Department of Medicine II, Leipzig University Medical Center, Leipzig University, Leipzig, Germany
| | - Pierre Deltenre
- Division of Gastroenterology and Hepatology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
- Department of Gastroenterology and Hepatology, CHU UCL Namur, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Sebastian Mueller
- Salem Medical Center, Department of Gastroenterology and Hepatology, University of Heidelberg, Heidelberg, Germany
| | - Jochen Hampe
- Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany
- Department of Medicine I, University Hospital Dresden, Dresden, Germany
| | - Felix Stickel
- Department of Gatroenterology and Hepatology, University of Zürich, Zürich, Switzerland
- Hirslanden Klinik Beau-Site, Bern, Switzerland
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147
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Lorincz-Comi N, Yang Y, Li G, Zhu X. MRBEE: A novel bias-corrected multivariable Mendelian Randomization method. RESEARCH SQUARE 2023:rs.3.rs-2464632. [PMID: 36778480 PMCID: PMC9915796 DOI: 10.21203/rs.3.rs-2464632/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Mendelian Randomization (MR) has been widely applied to infer causality of exposures on outcomes in the genome wide association (GWAS) era. Existing approaches are often subject to biases from multiple sources including weak instruments, sample overlap, and measurement error. We introduce MRBEE, a computationally efficient multivariable MR method that can correct for all known biases simultaneously, which is demonstrated in theory, simulations, and real data analysis. In comparison, all existing MR methods are biased. In two independent real data analyses, we observed that the causal effect of BMI on coronary artery disease risk is completely mediated by blood pressure, and that existing MR methods drastically underestimate the causal effect of cannabis use disorder on schizophrenia risk compared to MRBEE. We demonstrate that MRBEE can be a useful tool in studying causality between multiple risk factors and a disease outcome, especially as more GWAS summary statistics are being made publicly available.
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Affiliation(s)
- Noah Lorincz-Comi
- Department of Population and Quantitative Health Sciences, Case Western Reserve University
| | - Yihe Yang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University
| | - Gen Li
- Department of Population and Quantitative Health Sciences, Case Western Reserve University
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University
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148
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Salim F, Mizutani S, Zolfo M, Yamada T. Recent advances of machine learning applications in human gut microbiota study: from observational analysis toward causal inference and clinical intervention. Curr Opin Biotechnol 2023; 79:102884. [PMID: 36623442 DOI: 10.1016/j.copbio.2022.102884] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 02/24/2022] [Accepted: 12/09/2022] [Indexed: 01/08/2023]
Abstract
Statistical methods, especially machine learning, learning(ML), are pivotal for the analyses of large data generated by multiomics human gut microbiota study. These analyses lead to the discovery of microbe-disease associations. Furthermore, recent efforts for more data transparency and accessible analytical tools improved data availability and study reproducibility. Our recent accumulated knowledge on microbe-disease associations brings light to the next questions: what is the role of microbes in disease progression and how can we apply our knowledge of microbiome in clinical settings? Here, we introduce recent studies that implemented ML to answer the questions of causal inference and clinical translation.
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Affiliation(s)
- Felix Salim
- School of Life Science and Technology, Tokyo Institute of Technology
| | - Sayaka Mizutani
- School of Life Science and Technology, Tokyo Institute of Technology; Japan Society for the Promotion of Science
| | - Moreno Zolfo
- School of Life Science and Technology, Tokyo Institute of Technology
| | - Takuji Yamada
- School of Life Science and Technology, Tokyo Institute of Technology; Metagen, Inc.; Metagen Therapeutics, Inc.; digzyme, Inc..
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149
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Sliz E, Tyrmi JS, Rahmioglu N, Zondervan KT, Becker CM, Uimari O, Kettunen J. Evidence of a causal effect of genetic tendency to gain muscle mass on uterine leiomyomata. Nat Commun 2023; 14:542. [PMID: 36726022 PMCID: PMC9892568 DOI: 10.1038/s41467-023-35974-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 01/10/2023] [Indexed: 02/03/2023] Open
Abstract
Uterine leiomyomata (UL) are the most common tumours of the female genital tract and the primary cause of surgical removal of the uterus. Genetic factors contribute to UL susceptibility. To add understanding to the heritable genetic risk factors, we conduct a genome-wide association study (GWAS) of UL in up to 426,558 European women from FinnGen and a previous UL meta-GWAS. In addition to the 50 known UL loci, we identify 22 loci that have not been associated with UL in prior studies. UL-associated loci harbour genes enriched for development, growth, and cellular senescence. Of particular interest are the smooth muscle cell differentiation and proliferation-regulating genes functioning on the myocardin-cyclin dependent kinase inhibitor 1 A pathway. Our results further suggest that genetic predisposition to increased fat-free mass may be causally related to higher UL risk, underscoring the involvement of altered muscle tissue biology in UL pathophysiology. Overall, our findings add to the understanding of the genetic pathways underlying UL, which may aid in developing novel therapeutics.
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Affiliation(s)
- Eeva Sliz
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
- Biocenter Oulu, Oulu, Finland.
| | - Jaakko S Tyrmi
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu, Finland
| | - Nilufer Rahmioglu
- Oxford Endometriosis CaRe Centre, Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Krina T Zondervan
- Oxford Endometriosis CaRe Centre, Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Christian M Becker
- Oxford Endometriosis CaRe Centre, Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
| | - Outi Uimari
- Department of Obstetrics and Gynecology, Oulu University Hospital, Oulu, Finland
- PEDEGO Research Unit, University of Oulu and Oulu University Hospital, Oulu, Finland
- Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Johannes Kettunen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu, Finland
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Tsai MC, Hsu CH, Chu SK, Roy-Gagnon MH, Lin SH. Genome-wide association study of age at menarche in the Taiwan Biobank suggests NOL4 as a novel associated gene. J Hum Genet 2023; 68:339-345. [PMID: 36710296 DOI: 10.1038/s10038-023-01124-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 01/15/2023] [Accepted: 01/17/2023] [Indexed: 01/31/2023]
Abstract
Sexual maturation is a complex physiological process that involves multiple variables, such as genetic and environmental factors. Among females, age at menarche (AM) is a critical milestone for sexual maturation. This study aimed to identify genetic markers of AM using nationwide population cohort data in Taiwan. Females with self-reported AM between 10 and 16 years (N = 39,827) were eligible for the final analysis. To identify genetic signals related to AM, we conducted a genome-wide association study using a linear regression model and split-half meta-analysis method to verify our findings. The Functional Mapping and Annotation web-based platform was used for positional mapping and gene-based and gene-set analyses. The meta-analysis identified four significant loci, i.e., LIN28B (pooled P = 1.39 × 10-21), NOL4 (pooled P = 8.94 × 10-9), GPR45 (pooled P = 4.19 × 10-11), and LOC105373831 (pooled P = 4.37 × 10-8), that were associated with AM. MAGMA gene-based analysis revealed that LIN28B (P = 1.13 × 10-8), NOL4 (P = 2.27 × 10-7), RXRG (P = 4.34 × 10-7), ETV5 (P = 1.75 × 10-6), and HACE1 (P = 1.82 × 10-6) were significantly associated with AM, while the gene-set analysis identified a significantly enriched pathway involving mTOR signaling complex (FDR corrected P = 1.28 × 10-2). The results replicated evidence for several genetic markers associated with AM in the Taiwanese female population. Our analysis identified a novel locus (rs7239368) in NOL4 associated with AM (β = 0.051 ± 0.009 years, pooled P = 8.94 × 10-9), whereas additional research is needed to validate its molecular role in sexual maturation.
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Affiliation(s)
- Meng-Che Tsai
- Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.,Department of Genomic Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.,Department of Medical Humanities and Social Medicine, Collage of Medicine, National Cheng Kung University, Tainan, Taiwan.,Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Chih-Hui Hsu
- Biostatistics Consulting Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Shih-Kai Chu
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.,Clinical Research Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | | | - Sheng-Hsiang Lin
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan. .,Biostatistics Consulting Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan. .,Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
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