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Qiao J, Wu Y, Zhang S, Xu Y, Zhang J, Zeng P, Wang T. Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes. BMC Genomics 2023; 24:324. [PMID: 37312035 DOI: 10.1186/s12864-023-09425-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 06/01/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear. RESULTS By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection. CONCLUSIONS Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.
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Affiliation(s)
- Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuxuan Wu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yue Xu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jinhui Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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302
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Kononov S, Azarova I, Klyosova E, Bykanova M, Churnosov M, Solodilova M, Polonikov A. Lipid-Associated GWAS Loci Predict Antiatherogenic Effects of Rosuvastatin in Patients with Coronary Artery Disease. Genes (Basel) 2023; 14:1259. [PMID: 37372439 PMCID: PMC10298211 DOI: 10.3390/genes14061259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/07/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
We have shown that lipid-associated loci discovered by genome-wide association studies (GWAS) have pleiotropic effects on lipid metabolism, carotid intima-media thickness (CIMT), and CAD risk. Here, we investigated the impact of lipid-associated GWAS loci on the efficacy of rosuvastatin therapy in terms of changes in plasma lipid levels and CIMT. The study comprised 116 CAD patients with hypercholesterolemia. CIMT, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) were measured at baseline and after 6 and 12 months of follow-up, respectively. Genotyping of fifteen lipid-associated GWAS loci was performed by the MassArray-4 System. Linear regression analysis adjusted for sex, age, body mass index, and rosuvastatin dose was used to estimate the phenotypic effects of polymorphisms, and p-values were calculated through adaptive permutation tests by the PLINK software, v1.9. Over one-year rosuvastatin therapy, a decrease in CIMT was linked to rs1689800, rs4846914, rs12328675, rs55730499, rs9987289, rs11220463, rs16942887, and rs881844 polymorphisms (Pperm < 0.05). TC change was associated with rs55730499, rs11220463, and rs6065906; LDL-C change was linked to the rs55730499, rs1689800, and rs16942887 polymorphisms; and TG change was linked to polymorphisms rs838880 and rs1883025 (Pperm < 0.05). In conclusion, polymorphisms rs1689800, rs55730499, rs11220463, and rs16942887 were found to be predictive markers for multiple antiatherogenic effects of rosuvastatin in CAD patients.
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Affiliation(s)
- Stanislav Kononov
- Department of Internal Medicine No. 2, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
| | - Iuliia Azarova
- Department of Biological Chemistry, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
| | - Elena Klyosova
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
| | - Marina Bykanova
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
- Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State University, 85 Pobedy Street, 308015 Belgorod, Russia
| | - Maria Solodilova
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
| | - Alexey Polonikov
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
- Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
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303
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Giontella A, Zagkos L, Geybels M, Larsson SC, Tzoulaki I, Mantzoros CS, Andersen B, Gill D, Cronjé HT. Renoprotective effects of genetically proxied fibroblast growth factor 21: Mendelian randomization, proteome-wide and metabolome-wide association study. Metabolism 2023:155616. [PMID: 37302695 DOI: 10.1016/j.metabol.2023.155616] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/04/2023] [Accepted: 06/02/2023] [Indexed: 06/13/2023]
Abstract
BACKGROUND Fibroblast growth factor 21 (FGF21) has demonstrated efficacy for reducing liver fat and reversing non-alcoholic steatohepatitis in phase 2 clinical trials. It is also postulated to have anti-fibrotic effects and therefore may be amenable to repurposing for the prevention and treatment of chronic kidney disease (CKD). METHODS We leverage a missense genetic variant, rs739320 in the FGF21 gene, that associates with magnetic resonance imaging-derived liver fat as a clinically validated and biologically plausible instrumental variable for studying the effects of FGF21 analogs. Performing Mendelian randomization, we ascertain associations between instrumented FGF21 and kidney phenotypes, cardiometabolic disease risk factors, as well as the circulating proteome (Somalogic, 4907 aptamers) and metabolome (Nightingale platform, 249 metabolites). RESULTS We report consistent renoprotective associations of genetically proxied FGF21 effect, including higher glomerular filtration rates (p = 1.9 × 10-4), higher urinary sodium excretion (p = 5.1 × 10-11), and lower urine albumin-creatinine ratio (p = 3.6 × 10-5). These favorable effects translated to lower CKD risk (odds ratio per rs739320 C-allele, 0.96; 95%CI, 0.94-0.98; p = 3.2 × 10-4). Genetically proxied FGF21 effect was also associated with lower fasting insulin, waist-to-hip ratio, blood pressure (systolic and diastolic BP, p < 1.0 × 10-07) and blood lipid (low-density lipoprotein cholesterol, triglycerides and apolipoprotein B, p < 6.5 × 10-24) profiles. The latter associations are replicated in our metabolome-wide association study. Proteomic perturbations associated with genetically predicted FGF21 effect were consistent with fibrosis reduction. CONCLUSION This study highlights the pleiotropic effects of genetically proxied FGF21 and supports a re-purposing opportunity for the treatment and prevention of kidney disease specifically. Further work is required to triangulate these findings, towards possible clinical development of FGF21 towards the treatment and prevention of kidney disease.
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Affiliation(s)
- Alice Giontella
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Loukas Zagkos
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | | | - Susanna C Larsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Division of Systems Biology, Biomedical Research Foundation of the Academy of Athens, Athens. Greece
| | - Christos S Mantzoros
- Department of Medicine, Boston VA Healthcare System and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | | | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Chief Scientific Advisor Office, Research and Early Development, Novo Nordisk, Copenhagen, Denmark.
| | - Héléne T Cronjé
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark.
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304
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Udler MS. Dynamic measures of insulin action identify genetic determinants of dysglycemia. Nat Genet 2023:10.1038/s41588-023-01346-6. [PMID: 37291195 DOI: 10.1038/s41588-023-01346-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Affiliation(s)
- Miriam S Udler
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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305
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Zhang Y, Li Y, Dai X, Lin H, Ma L. Type 2 diabetes has a protective causal association with thoracic aortic aneurysm: a Mendelian randomization study. Diabetol Metab Syndr 2023; 15:120. [PMID: 37280690 DOI: 10.1186/s13098-023-01101-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/31/2023] [Indexed: 06/08/2023] Open
Abstract
BACKGROUND Observational studies have reported an inverse association of type 2 diabetes (T2D) with thoracic aortic aneurysm (TAA). However, the causality of the association has not been established yet. The present study aims to clarify the causal relationship between T2D and TAA via a Mendelian randomization (MR) approach. METHODS Causality of associations were assessed using a two-sample MR framework. Genome-wide association study (GWAS) summary statistics were obtained for T2D, glycated hemoglobin (HbA1c), fasting glucose (FG) and fasting insulin (FI) as exposures, and TAA, ascending aortic diameter (AAoD) and descending aortic diameter (DAoD) as outcomes. Four different methods (inverse variance weighted [IVW], weight median, MR-Egger and MR-PRESSO) were used to calculate causal estimates. Heterogeneity and horizontal pleiotropy were assessed using Cochran Q test and MR-Egger regression intercept, respectively. RESULTS Genetically predicted T2D was inversely associated with the risk of TAA (OR: 0.931, 95% CI 0.870 to 0.997, p = 0.040, IVW method) and AAoD (Beta: -0.065, 95%CI -0.099 to - 0.031, p = 1.7e-04, IVW method), but not with DAoD (p > 0.05). Genetically predicted FG level was inversely associated with AAoD (Beta: -0.273, 95% CI -0.396 to -0.150, p = 1.41e-05, IVW method) and DAoD (Beta: -0.166, 95% CI -0.281 to -0.051, p = 0.005, IVW method), but not with TAA (p > 0.05). The effect of genetically predicted HbA1c and FI on TAA, AAoD and DAoD did not reach statistical significance (p > 0.05). CONCLUSIONS Genetic predisposition to T2D decreases the risk of TAA. Genetically predicted T2D is inversely associated with AAoD, but not with DAoD. Genetically predicted FG level was inversely associated with AAoD and DAoD.
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Affiliation(s)
- Yiran Zhang
- Department of Cardiovascular Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China
| | - Yongxin Li
- School of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xiaoyi Dai
- Department of Cardiovascular Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China
| | - Haokai Lin
- Department of Cardiovascular Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China
| | - Liang Ma
- Department of Cardiovascular Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
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306
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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: 0.5] [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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307
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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: 18] [Impact Index Per Article: 9.0] [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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308
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Ford BE, Chachra SS, Rodgers K, Moonira T, Al-Oanzi ZH, Anstee QM, Reeves HL, Schattenberg JM, Fairclough RJ, Smith DM, Tiniakos D, Agius L. The GCKR-P446L gene variant predisposes to raised blood cholesterol and lower blood glucose in the P446L mouse-a model for GCKR rs1260326. Mol Metab 2023; 72:101722. [PMID: 37031802 PMCID: PMC10182400 DOI: 10.1016/j.molmet.2023.101722] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 03/28/2023] [Accepted: 04/04/2023] [Indexed: 04/11/2023] Open
Abstract
OBJECTIVES The Glucokinase Regulatory Protein GKRP, encoded by GCKR, enables acute regulation of liver glucokinase to support metabolic demand. The common human GCKR rs1260326:Pro446 > Leu variant within a large linkage disequilibrium region associates with pleiotropic traits including lower Type 2 diabetes risk and raised blood triglycerides and cholesterol. Whether the GCKR-P446 > L substitution is causal to the raised lipids is unknown. We determined whether mouse GKRP phenocopies the human GKRP:P446 > L substitution and studied a GKRP:P446L knockin mouse to identify physiological consequences to P446 > L. METHODS GKRP-deficient hepatocytes were transfected with adenoviral vectors for human or mouse GKRP:446 P or 446 L for cellular comprehensive analysis including transcriptomics consequent to P446 > L. Physiological traits in the diet-challenged P446L mouse were compared with pleiotropic associations at the human rs1260326 locus. Transcriptomics was compared in P446L mouse liver with hepatocytes overexpressing glucokinase or GKRP:446 P/L. RESULTS 1. P446 > L substitution in mouse or human GKRP similarly compromises protein expressivity of GKRP:446 L, nuclear sequestration of glucokinase and counter-regulation of gene expression. 2. The P446L knockin mouse has lower liver glucokinase and GKRP protein similar to human liver homozygous for rs1260326-446 L. 3. The diet-challenged P446L mouse has lower blood glucose, raised blood cholesterol and altered hepatic cholesterol homeostasis consistent with relative glucokinase-to-GKRP excess, but not raised blood triglycerides. CONCLUSIONS Mouse GKRP phenocopies the human GKRP:P446 > L substitution despite the higher affinity for glucokinase of human GKRP. The diet-challenged P446L mouse replicates several traits found in association with the rs1260326 locus on chromosome 2 including raised blood cholesterol, lower blood glucose and lower liver glucokinase and GKRP protein but not raised blood triglycerides.
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Affiliation(s)
- Brian E Ford
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Shruti S Chachra
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Katrina Rodgers
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Tabassum Moonira
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Ziad H Al-Oanzi
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK; Jouf University, Clinical Laboratory Science, Sakaka, Saudi Arabia
| | - Quentin M Anstee
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK; Newcastle NIHR Biomedical Research Center, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Helen L Reeves
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK; Newcastle NIHR Biomedical Research Center, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Jörn M Schattenberg
- Metabolic Liver Research Programm, Department of Medicine, University Hospital Mainz, Mainz, Germany
| | - Rebecca J Fairclough
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - David M Smith
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dina Tiniakos
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK; Newcastle NIHR Biomedical Research Center, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK; Dept of Pathology, Aretaieion Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Loranne Agius
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK.
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Williamson A, Norris DM, Yin X, Broadaway KA, Moxley AH, Vadlamudi S, Wilson EP, Jackson AU, Ahuja V, Andersen MK, Arzumanyan Z, Bonnycastle LL, Bornstein SR, Bretschneider MP, Buchanan TA, Chang YC, Chuang LM, Chung RH, Clausen TD, Damm P, Delgado GE, de Mello VD, Dupuis J, Dwivedi OP, Erdos MR, Fernandes Silva L, Frayling TM, Gieger C, Goodarzi MO, Guo X, Gustafsson S, Hakaste L, Hammar U, Hatem G, Herrmann S, Højlund K, Horn K, Hsueh WA, Hung YJ, Hwu CM, Jonsson A, Kårhus LL, Kleber ME, Kovacs P, Lakka TA, Lauzon M, Lee IT, Lindgren CM, Lindström J, Linneberg A, Liu CT, Luan J, Aly DM, Mathiesen E, Moissl AP, Morris AP, Narisu N, Perakakis N, Peters A, Prasad RB, Rodionov RN, Roll K, Rundsten CF, Sarnowski C, Savonen K, Scholz M, Sharma S, Stinson SE, Suleman S, Tan J, Taylor KD, Uusitupa M, Vistisen D, Witte DR, Walther R, Wu P, Xiang AH, Zethelius B, Ahlqvist E, Bergman RN, Chen YDI, Collins FS, Fall T, Florez JC, Fritsche A, Grallert H, Groop L, Hansen T, Koistinen HA, Komulainen P, Laakso M, Lind L, Loeffler M, März W, Meigs JB, Raffel LJ, Rauramaa R, Rotter JI, Schwarz PEH, Stumvoll M, et alWilliamson A, Norris DM, Yin X, Broadaway KA, Moxley AH, Vadlamudi S, Wilson EP, Jackson AU, Ahuja V, Andersen MK, Arzumanyan Z, Bonnycastle LL, Bornstein SR, Bretschneider MP, Buchanan TA, Chang YC, Chuang LM, Chung RH, Clausen TD, Damm P, Delgado GE, de Mello VD, Dupuis J, Dwivedi OP, Erdos MR, Fernandes Silva L, Frayling TM, Gieger C, Goodarzi MO, Guo X, Gustafsson S, Hakaste L, Hammar U, Hatem G, Herrmann S, Højlund K, Horn K, Hsueh WA, Hung YJ, Hwu CM, Jonsson A, Kårhus LL, Kleber ME, Kovacs P, Lakka TA, Lauzon M, Lee IT, Lindgren CM, Lindström J, Linneberg A, Liu CT, Luan J, Aly DM, Mathiesen E, Moissl AP, Morris AP, Narisu N, Perakakis N, Peters A, Prasad RB, Rodionov RN, Roll K, Rundsten CF, Sarnowski C, Savonen K, Scholz M, Sharma S, Stinson SE, Suleman S, Tan J, Taylor KD, Uusitupa M, Vistisen D, Witte DR, Walther R, Wu P, Xiang AH, Zethelius B, Ahlqvist E, Bergman RN, Chen YDI, Collins FS, Fall T, Florez JC, Fritsche A, Grallert H, Groop L, Hansen T, Koistinen HA, Komulainen P, Laakso M, Lind L, Loeffler M, März W, Meigs JB, Raffel LJ, Rauramaa R, Rotter JI, Schwarz PEH, Stumvoll M, Sundström J, Tönjes A, Tuomi T, Tuomilehto J, Wagner R, Barroso I, Walker M, Grarup N, Boehnke M, Wareham NJ, Mohlke KL, Wheeler E, O'Rahilly S, Fazakerley DJ, Langenberg C. Genome-wide association study and functional characterization identifies candidate genes for insulin-stimulated glucose uptake. Nat Genet 2023; 55:973-983. [PMID: 37291194 PMCID: PMC7614755 DOI: 10.1038/s41588-023-01408-9] [Show More Authors] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 04/26/2023] [Indexed: 06/10/2023]
Abstract
Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in >55,000 participants from three ancestry groups. We identified ten new loci (P < 5 × 10-8) not previously associated with postchallenge insulin resistance, eight of which were shown to share their genetic architecture with type 2 diabetes in colocalization analyses. We investigated candidate genes at a subset of associated loci in cultured cells and identified nine candidate genes newly implicated in the expression or trafficking of GLUT4, the key glucose transporter in postprandial glucose uptake in muscle and fat. By focusing on postprandial insulin resistance, we highlighted the mechanisms of action at type 2 diabetes loci that are not adequately captured by studies of fasting glycemic traits.
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Affiliation(s)
- Alice Williamson
- MRC Epidemiology Unit Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Metabolic Research Laboratories Wellcome Trust-MRC Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Dougall M Norris
- Metabolic Research Laboratories Wellcome Trust-MRC Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Xianyong Yin
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Anne H Moxley
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | | | - Emma P Wilson
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Anne U Jackson
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Vasudha Ahuja
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Mette K Andersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Zorayr Arzumanyan
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lori L Bonnycastle
- Center for Precision Health Research National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stefan R Bornstein
- Department of Internal Medicine III, Metabolic and Vascular Medicine, Medical Faculty Carl Gustav Carus, Dresden, Germany
- Helmholtz Zentrum München Paul Langerhans Institute Dresden (PLID), University Hospital and Faculty of Medicine TU Dresden, Dresden, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Maxi P Bretschneider
- Department of Internal Medicine III, Metabolic and Vascular Medicine, Medical Faculty Carl Gustav Carus, Dresden, Germany
- Helmholtz Zentrum München Paul Langerhans Institute Dresden (PLID), University Hospital and Faculty of Medicine TU Dresden, Dresden, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Thomas A Buchanan
- Department of Medicine, Division of Endocrinology and Diabetes, Keck School of Medicine USC, Los Angeles, CA, USA
| | - Yi-Cheng Chang
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University, Taipei City, Taiwan
- Internal Medicine, National Taiwan University Hospital, Taipei City, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Lee-Ming Chuang
- Department of Internal Medicine, Division of Endocrinology and Metabolism, National Taiwan University Hospital, Taipei City, Taiwan
| | - Ren-Hua Chung
- Institute of Population Health Sciences, National Health Research Institutes, Toufen, Taiwan
| | - Tine D Clausen
- Department of Gynecology and Obstetrics, Nordsjaellands Hospital, Hillerød, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Damm
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Pregnant Women with Diabetes, Rigshospitalet, Copenhagen, Denmark
- Department of Obstetrics, Rigshospitalet, Copenhagen, Denmark
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Vanessa D de Mello
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Quebec, Canada
| | - Om P Dwivedi
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Michael R Erdos
- Center for Precision Health Research National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | | | - Christian Gieger
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Mark O Goodarzi
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Xiuqing Guo
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Liisa Hakaste
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Ulf Hammar
- Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, Sweden
| | - Gad Hatem
- Clinical Sciences Malmö, Genomics, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Sandra Herrmann
- Helmholtz Zentrum München Paul Langerhans Institute Dresden (PLID), University Hospital and Faculty of Medicine TU Dresden, Dresden, Germany
- Department of Internal Medicine III, Prevention and Care of Diabetes, Medical Faculty Carl Gustav Carus, Dresden, Germany
| | - Kurt Højlund
- Steno Diabetes Center Odense, Odense University Hospital, Odense, Denmark
| | - Katrin Horn
- Medical Faculty Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, Medical Faculty, Leipzig, Germany
| | - Willa A Hsueh
- Internal Medicine, Endocrinology, Diabetes and Metabolism, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Yi-Jen Hung
- Institute of Preventive Medicine, National Defense Medical Center, New Taipei City, Taiwan
| | - Chii-Min Hwu
- Department of Medicine Section of Endocrinology and Metabolism, Taipei Veterans General Hospital, Taipei City, Taiwan
| | - Anna Jonsson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Line L Kårhus
- Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Marcus E Kleber
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Peter Kovacs
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Timo A Lakka
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Marie Lauzon
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - I-Te Lee
- Department of Internal Medicine Division of Endocrinology and Metabolism, Taichung Veterans General Hospital, Taichung City, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei City, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung City, Taiwan
| | - Cecilia M Lindgren
- Big Data Institute Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Wellcome Trust Centre Human Genetics, University of Oxford, Oxford, UK
- Broad Institute, Cambridge, MA, USA
| | | | - Allan Linneberg
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Dina Mansour Aly
- Clinical Sciences Malmö, Genomics, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Elisabeth Mathiesen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Pregnant Women with Diabetes, Rigshospitalet, Copenhagen, Denmark
- Department of Endocrinology Rigshospitalet, Copenhagen, Denmark
| | - Angela P Moissl
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Institute of Nutritional Sciences, Friedrich-Schiller-University, Jena, Germany
- Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena, Jena, Germany
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Narisu Narisu
- Center for Precision Health Research National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nikolaos Perakakis
- Department of Internal Medicine III, Metabolic and Vascular Medicine, Medical Faculty Carl Gustav Carus, Dresden, Germany
- Helmholtz Zentrum München Paul Langerhans Institute Dresden (PLID), University Hospital and Faculty of Medicine TU Dresden, Dresden, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Annette Peters
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Rashmi B Prasad
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Clinical Sciences Malmö, Genomics, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Roman N Rodionov
- Department of Internal Medicine III, University Center for Vascular Medicine, Medical Faculty Carl Gustav Carus, Dresden, Germany
- College of Medicine and Public Health, Flinders University and Flinders Medical Centre, Adelaide, Australia
| | - Kathryn Roll
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Carsten F Rundsten
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Chloé Sarnowski
- Department of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center, Houston, TX, USA
| | - Kai Savonen
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Markus Scholz
- Medical Faculty Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, Medical Faculty, Leipzig, Germany
| | - Sapna Sharma
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Food Chemistry and Molecular and Sensory Science, Technical University of Munich, Freising-Weihenstephan, München, Germany
| | - Sara E Stinson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sufyan Suleman
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jingyi Tan
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Matti Uusitupa
- Department of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Dorte Vistisen
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Daniel R Witte
- Steno Diabetes Center Aarhus, Aarhus, Denmark
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Romy Walther
- Helmholtz Zentrum München Paul Langerhans Institute Dresden (PLID), University Hospital and Faculty of Medicine TU Dresden, Dresden, Germany
- Department of Internal Medicine III, Pathobiochemistry, Medical Faculty Carl Gustav Carus, Dresden, Germany
| | - Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Anny H Xiang
- Research and Evaluation, Division of Biostatistics, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Björn Zethelius
- Department of Public Health and Caring Sciences, Geriatrics, Uppsala University, Uppsala, Sweden
| | - Emma Ahlqvist
- Clinical Sciences Malmö, Genomics, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Richard N Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Yii-Der Ida Chen
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Francis S Collins
- Center for Precision Health Research National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, Sweden
| | - Jose C Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Andreas Fritsche
- Department of Internal Medicine IV, University Hospital Tübingen, Tübingen, Germany
| | - Harald Grallert
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Leif Groop
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Clinical Sciences Malmö, Genomics, Diabetes and Endocrinology, Lund University, Lund, Sweden
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Heikki A Koistinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Pirjo Komulainen
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Lars Lind
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Markus Loeffler
- Medical Faculty Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, Medical Faculty, Leipzig, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim, Germany
| | - James B Meigs
- Department of Internal Medicine IV, University Hospital Tübingen, Tübingen, Germany
- Clinical Sciences Malmö, Genomics, Diabetes and Endocrinology, Lund University, Lund, Sweden
- Department of Medicine Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Leslie J Raffel
- Department of Pediatrics, Genetic and Genomic Medicine, University of California, Irvine, CA, USA
| | - Rainer Rauramaa
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Peter E H Schwarz
- Helmholtz Zentrum München Paul Langerhans Institute Dresden (PLID), University Hospital and Faculty of Medicine TU Dresden, Dresden, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
- Department of Internal Medicine III, Prevention and Care of Diabetes, Medical Faculty Carl Gustav Carus, Dresden, Germany
| | - Michael Stumvoll
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Johan Sundström
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Anke Tönjes
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Jaakko Tuomilehto
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Robert Wagner
- Department of Internal Medicine IV, University Hospital Tübingen, Tübingen, Germany
| | - Inês Barroso
- Exeter Centre of Excellence for Diabetes Research (EXCEED), Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Mark Walker
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael Boehnke
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas J Wareham
- MRC Epidemiology Unit Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
| | - Eleanor Wheeler
- MRC Epidemiology Unit Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
| | - Stephen O'Rahilly
- Metabolic Research Laboratories Wellcome Trust-MRC Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK.
| | - Daniel J Fazakerley
- Metabolic Research Laboratories Wellcome Trust-MRC Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK.
| | - Claudia Langenberg
- MRC Epidemiology Unit Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
- Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin, Berlin, Germany.
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK.
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310
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Huang W, Wang Z, Zou C, Liu Y, Pan Y, Lu J, Zhou K, Jiao F, Zhong S, Jiang G. Effects of metabolic factors in mediating the relationship between Type 2 diabetes and depression in East Asian populations: A two-step, two-sample Mendelian randomization study. J Affect Disord 2023; 335:120-128. [PMID: 37150218 DOI: 10.1016/j.jad.2023.04.114] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 04/13/2023] [Accepted: 04/29/2023] [Indexed: 05/09/2023]
Abstract
BACKGROUND Observational studies suggested a close link between type 2 diabetes (T2D), metabolic factors and depression, while the causal relationships remained poorly understood. OBJECTIVE To determine the causality between T2D and depression, and to investigate the roles of metabolic factors in mediating the relationship between T2D and depression in East Asians. METHODS Using summary statistics from the largest and most up-to-date genome-wide association studies of depression (12,588 cases and 85,914 controls) and T2D (36,614 cases and 155,150 controls) among East Asians, two-step and two-sample MR analyses were performed to estimate the causal mediation effects of metabolic factors including lipids profiles, blood pressure (BP) and fasting insulin (FI) on the relationship between T2D and depression. RESULTS Genetically predicted T2D was significantly associated with depression (OR [95 % CI]:1.06 [1.01, 1.11], P = 0.043), but not vice versa. T2D was causally associated with lower levels of HDL-C and higher levels of LDL-C, triglycerides (TG), BP and FI. Furthermore, the causal effects of T2D on depression were significantly mediated by LDL-C (β [95 % CI]: -0.003 [-0.005, -0.001], P = 0.007), and suggestively mediated by TG (0.001 [0.001, 0.003], P = 0.049) and FI (0.006 [0.001, 0.012], P = 0.049). LIMITATIONS First, depression was defined by several methods, like symptom questionnaires or self-completed surveys. Second, two-sample MR approach is unable to detect the non-linear causal relationships. Third, independent data sets were not available for replication of our findings. CONCLUSION T2D was causally associated with the risk of depression, and LDL-C, TG, and FI were potential causal mediators of the effect of T2D on depression. Understanding the causality among T2D, metabolic factors and depression is crucial for identifying potential targets for early intervention.
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Affiliation(s)
- Wenyu Huang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Zhenqian Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Chenfeng Zou
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yang Liu
- College of Life Sciences, the University of Chinese Academy of Sciences, Beijing, China
| | - Ying Pan
- Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Jiawen Lu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Kaixin Zhou
- Big Data Research Center, Fifth Hospital of Chongqing, Chongqing, China
| | - Feng Jiao
- Guangzhou Centre for Applied Mathematics, Guangzhou University, Guangzhou, China.
| | - Shao Zhong
- Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China.
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311
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Cronjé HT, Mi MY, Austin TR, Biggs ML, Siscovick DS, Lemaitre RN, Psaty BM, Tracy RP, Djoussé L, Kizer JR, Ix JH, Rao P, Robbins JM, Barber JL, Sarzynski MA, Clish CB, Bouchard C, Mukamal KJ, Gerszten RE, Jensen MK. Plasma Proteomic Risk Markers of Incident Type 2 Diabetes Reflect Physiologically Distinct Components of Glucose-Insulin Homeostasis. Diabetes 2023; 72:666-673. [PMID: 36749929 PMCID: PMC10130486 DOI: 10.2337/db22-0628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 02/02/2023] [Indexed: 02/09/2023]
Abstract
High-throughput proteomics allows researchers to simultaneously explore the roles of thousands of biomarkers in the pathophysiology of diabetes. We conducted proteomic association studies of incident type 2 diabetes and physiologic responses to an intravenous glucose tolerance test (IVGTT) to identify novel protein contributors to glucose homeostasis and diabetes risk. We tested 4,776 SomaScan proteins measured in relation to 18-year incident diabetes risk in participants from the Cardiovascular Health Study (N = 2,631) and IVGTT-derived measures in participants from the HERITAGE Family Study (N = 752). We characterize 51 proteins that were associated with longitudinal diabetes risk, using their respective 39, 9, and 8 concurrent associations with insulin sensitivity index (SI), acute insulin response to glucose (AIRG), and glucose effectiveness (SG). Twelve of the 51 diabetes associations appear to be novel, including β-glucuronidase, which was associated with increased diabetes risk and lower SG, suggesting an alternative pathway to insulin for glucose disposal; and plexin-B2, which also was associated with increased diabetes risk, but with lower AIRG, and not with SI, indicating a mechanism related instead to pancreatic dysfunction. Other novel protein associations included alcohol dehydrogenase-1C, fructose-bisphosphate aldolase-B, sorbitol dehydrogenase with elevated type 2 diabetes risk, and a leucine-rich repeat containing protein-15 and myocilin with decreased risk. ARTICLE HIGHLIGHTS Plasma proteins are associated with the risk of incident diabetes in older adults independent of various demographic, lifestyle, and biochemical risk factors. These same proteins are associated with subtle differences in measures of glucose homeostasis earlier in life. Proteins that are associated with lower insulin sensitivity in individuals without diabetes tend to be associated with appropriate compensatory mechanisms, such as a stronger acute insulin response or higher glucose effectiveness. Proteins that are associated with future diabetes risk, but not with insulin insensitivity, tend to be associated with lower glucose effectiveness and/or impaired acute insulin response.
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Affiliation(s)
- Héléne T. Cronjé
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Michael Y. Mi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Thomas R. Austin
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Mary L. Biggs
- Department of Biostatistics, University of Washington, Seattle, WA
| | | | - Rozenn N. Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, Health Systems and Population Health, University of Washington, Seattle, WA
| | - Russell P. Tracy
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT
| | - Luc Djoussé
- Division of Aging, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Jorge R. Kizer
- Cardiology Section San Francisco Veterans Affairs Health Care System, San Francisco, CA
- Department of Medicine, Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Joachim H. Ix
- Division of Nephrology-Hypertension, University of California, San Diego, La Jolla, CA
| | - Prashant Rao
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Jeremy M. Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Jacob L. Barber
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - Mark A. Sarzynski
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | | | | | - Kenneth J. Mukamal
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Majken K. Jensen
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
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312
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Glunk V, Laber S, Sinnott-Armstrong N, Sobreira DR, Strobel SM, Batista TM, Kubitz P, Moud BN, Ebert H, Huang Y, Brandl B, Garbo G, Honecker J, Stirling DR, Abdennur N, Calabuig-Navarro V, Skurk T, Ocvirk S, Stemmer K, Cimini BA, Carpenter AE, Dankel SN, Lindgren CM, Hauner H, Nobrega MA, Claussnitzer M. A non-coding variant linked to metabolic obesity with normal weight affects actin remodelling in subcutaneous adipocytes. Nat Metab 2023; 5:861-879. [PMID: 37253881 PMCID: PMC11533588 DOI: 10.1038/s42255-023-00807-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 04/12/2023] [Indexed: 06/01/2023]
Abstract
Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders.
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Affiliation(s)
- Viktoria Glunk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Samantha Laber
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Nasa Sinnott-Armstrong
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
- Herbold Computational Biology Program, Publich Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Debora R Sobreira
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Sophie M Strobel
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Thiago M Batista
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Phil Kubitz
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bahareh Nemati Moud
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Hannah Ebert
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Yi Huang
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Beate Brandl
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Garrett Garbo
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Julius Honecker
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - David R Stirling
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nezar Abdennur
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Virtu Calabuig-Navarro
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Thomas Skurk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Soeren Ocvirk
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Intestinal Microbiology Research Group, Department of Molecular Toxicology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Kerstin Stemmer
- Molecular Cell Biology, Institute for Theoretical Medicine, University of Augsburg, Augsburg, Germany
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anne E Carpenter
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Simon N Dankel
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Cecilia M Lindgren
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Hans Hauner
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Marcelo A Nobrega
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA.
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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313
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Risal S, Li C, Luo Q, Fornes R, Lu H, Eriksson G, Manti M, Ohlsson C, Lindgren E, Crisosto N, Maliqueo M, Echiburú B, Recabarren S, Petermann TS, Benrick A, Brusselaers N, Qiao J, Deng Q, Stener-Victorin E. Transgenerational transmission of reproductive and metabolic dysfunction in the male progeny of polycystic ovary syndrome. Cell Rep Med 2023; 4:101035. [PMID: 37148878 DOI: 10.1016/j.xcrm.2023.101035] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 11/27/2022] [Accepted: 04/11/2023] [Indexed: 05/08/2023]
Abstract
The transgenerational maternal effects of polycystic ovary syndrome (PCOS) in female progeny are being revealed. As there is evidence that a male equivalent of PCOS may exists, we ask whether sons born to mothers with PCOS (PCOS-sons) transmit reproductive and metabolic phenotypes to their male progeny. Here, in a register-based cohort and a clinical case-control study, we find that PCOS-sons are more often obese and dyslipidemic. Our prenatal androgenized PCOS-like mouse model with or without diet-induced obesity confirmed that reproductive and metabolic dysfunctions in first-generation (F1) male offspring are passed down to F3. Sequencing of F1-F3 sperm reveals distinct differentially expressed (DE) small non-coding RNAs (sncRNAs) across generations in each lineage. Notably, common targets between transgenerational DEsncRNAs in mouse sperm and in PCOS-sons serum indicate similar effects of maternal hyperandrogenism, strengthening the translational relevance and highlighting a previously underappreciated risk of transmission of reproductive and metabolic dysfunction via the male germline.
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Affiliation(s)
- Sanjiv Risal
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Congru Li
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China
| | - Qing Luo
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Romina Fornes
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Haojiang Lu
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Gustaw Eriksson
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Maria Manti
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Drug Treatment, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Eva Lindgren
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Nicolas Crisosto
- Endocrinology and Metabolism Laboratory, West Division, School of Medicine, University of Chile, Carlos Schachtebeck 299, Interior Quinta Normal, Santiago, Chile; Endocrinology Unit, Department of Medicine, Clínica Alemana de Santiago, Faculty of Medicine, Clinica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - Manuel Maliqueo
- Endocrinology and Metabolism Laboratory, West Division, School of Medicine, University of Chile, Carlos Schachtebeck 299, Interior Quinta Normal, Santiago, Chile
| | - Barbara Echiburú
- Endocrinology and Metabolism Laboratory, West Division, School of Medicine, University of Chile, Carlos Schachtebeck 299, Interior Quinta Normal, Santiago, Chile
| | - Sergio Recabarren
- Laboratory of Animal Physiology and Endocrinology, Faculty of Veterinary Sciences, University of Concepción, Chillán, Chile
| | - Teresa Sir Petermann
- Endocrinology and Metabolism Laboratory, West Division, School of Medicine, University of Chile, Carlos Schachtebeck 299, Interior Quinta Normal, Santiago, Chile
| | - Anna Benrick
- Department of Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; School of Health Sciences, University of Skövde, Skövde, Sweden
| | - Nele Brusselaers
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden; Global Health Institute, Antwerp University, Antwerp, Belgium
| | - Jie Qiao
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China
| | - Qiaolin Deng
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden.
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314
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Gersing S, Cagiada M, Gebbia M, Gjesing AP, Coté AG, Seesankar G, Li R, Tabet D, Weile J, Stein A, Gloyn AL, Hansen T, Roth FP, Lindorff-Larsen K, Hartmann-Petersen R. A comprehensive map of human glucokinase variant activity. Genome Biol 2023; 24:97. [PMID: 37101203 PMCID: PMC10131484 DOI: 10.1186/s13059-023-02935-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 04/10/2023] [Indexed: 04/28/2023] Open
Abstract
BACKGROUND Glucokinase (GCK) regulates insulin secretion to maintain appropriate blood glucose levels. Sequence variants can alter GCK activity to cause hyperinsulinemic hypoglycemia or hyperglycemia associated with GCK-maturity-onset diabetes of the young (GCK-MODY), collectively affecting up to 10 million people worldwide. Patients with GCK-MODY are frequently misdiagnosed and treated unnecessarily. Genetic testing can prevent this but is hampered by the challenge of interpreting novel missense variants. RESULT Here, we exploit a multiplexed yeast complementation assay to measure both hyper- and hypoactive GCK variation, capturing 97% of all possible missense and nonsense variants. Activity scores correlate with in vitro catalytic efficiency, fasting glucose levels in carriers of GCK variants and with evolutionary conservation. Hypoactive variants are concentrated at buried positions, near the active site, and at a region of known importance for GCK conformational dynamics. Some hyperactive variants shift the conformational equilibrium towards the active state through a relative destabilization of the inactive conformation. CONCLUSION Our comprehensive assessment of GCK variant activity promises to facilitate variant interpretation and diagnosis, expand our mechanistic understanding of hyperactive variants, and inform development of therapeutics targeting GCK.
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Affiliation(s)
- Sarah Gersing
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Matteo Cagiada
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Marinella Gebbia
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada
| | - Anette P Gjesing
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Atina G Coté
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada
| | - Gireesh Seesankar
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada
| | - Roujia Li
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, M5T 3A1, Canada
| | - Daniel Tabet
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, M5T 3A1, Canada
| | - Jochen Weile
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, M5T 3A1, Canada
| | - Amelie Stein
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Anna L Gloyn
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Frederick P Roth
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada.
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, M5G 1X5, Canada.
- Department of Computer Science, University of Toronto, Toronto, ON, M5T 3A1, Canada.
| | - Kresten Lindorff-Larsen
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
| | - Rasmus Hartmann-Petersen
- The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
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315
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Ivanova T, Churnosova M, Abramova M, Plotnikov D, Ponomarenko I, Reshetnikov E, Aristova I, Sorokina I, Churnosov M. Sex-Specific Features of the Correlation between GWAS-Noticeable Polymorphisms and Hypertension in Europeans of Russia. Int J Mol Sci 2023; 24:ijms24097799. [PMID: 37175507 PMCID: PMC10178435 DOI: 10.3390/ijms24097799] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 04/13/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
The aim of the study was directed at studying the sex-specific features of the correlation between genome-wide association studies (GWAS)-noticeable polymorphisms and hypertension (HTN). In two groups of European subjects of Russia (n = 1405 in total), such as men (n = 821 in total: n = 564 HTN, n = 257 control) and women (n = 584 in total: n = 375 HTN, n = 209 control), the distribution of ten specially selected polymorphisms (they have confirmed associations of GWAS level with blood pressure (BP) parameters and/or HTN in Europeans) has been considered. The list of studied loci was as follows: (PLCE1) rs932764 A > G, (AC026703.1) rs1173771 G > A, (CERS5) rs7302981 G > A, (HFE) rs1799945 C > G, (OBFC1) rs4387287 C > A, (BAG6) rs805303 G > A, (RGL3) rs167479 T > G, (ARHGAP42) rs633185 C > G, (TBX2) rs8068318 T > C, and (ATP2B1) rs2681472 A > G. The contribution of individual loci and their inter-locus interactions to the HTN susceptibility with bioinformatic interpretation of associative links was evaluated separately in men's and women's cohorts. The men-women differences in involvement in the disease of the BP/HTN-associated GWAS SNPs were detected. Among women, the HTN risk has been associated with HFE rs1799945 C > G (genotype GG was risky; ORGG = 11.15 ppermGG = 0.014) and inter-locus interactions of all 10 examined SNPs as part of 26 intergenic interactions models. In men, the polymorphism BAG6 rs805303 G > A (genotype AA was protective; ORAA = 0.30 ppermAA = 0.0008) and inter-SNPs interactions of eight loci in only seven models have been founded as HTN-correlated. HTN-linked loci and strongly linked SNPs were characterized by pronounced polyvector functionality in both men and women, but at the same time, signaling pathways of HTN-linked genes/SNPs in women and men were similar and were represented mainly by immune mechanisms. As a result, the present study has demonstrated a more pronounced contribution of BP/HTN-associated GWAS SNPs to the HTN susceptibility (due to weightier intergenic interactions) in European women than in men.
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Affiliation(s)
- Tatiana Ivanova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Abramova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Denis Plotnikov
- Genetic Epidemiology Lab, Kazan State Medical University, 420012 Kazan, Russia
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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316
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Majara L, Kalungi A, Koen N, Tsuo K, Wang Y, Gupta R, Nkambule LL, Zar H, Stein DJ, Kinyanda E, Atkinson EG, Martin AR. Low and differential polygenic score generalizability among African populations due largely to genetic diversity. HGG ADVANCES 2023; 4:100184. [PMID: 36873096 PMCID: PMC9982687 DOI: 10.1016/j.xhgg.2023.100184] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 02/04/2023] [Indexed: 02/15/2023] Open
Abstract
African populations are vastly underrepresented in genetic studies but have the most genetic variation and face wide-ranging environmental exposures globally. Because systematic evaluations of genetic prediction had not yet been conducted in ancestries that span African diversity, we calculated polygenic risk scores (PRSs) in simulations across Africa and in empirical data from South Africa, Uganda, and the United Kingdom to better understand the generalizability of genetic studies. PRS accuracy improves with ancestry-matched discovery cohorts more than from ancestry-mismatched studies. Within ancestrally and ethnically diverse South African individuals, we find that PRS accuracy is low for all traits but varies across groups. Differences in African ancestries contribute more to variability in PRS accuracy than other large cohort differences considered between individuals in the United Kingdom versus Uganda. We computed PRS in African ancestry populations using existing European-only versus ancestrally diverse genetic studies; the increased diversity produced the largest accuracy gains for hemoglobin concentration and white blood cell count, reflecting large-effect ancestry-enriched variants in genes known to influence sickle cell anemia and the allergic response, respectively. Differences in PRS accuracy across African ancestries originating from diverse regions are as large as across out-of-Africa continental ancestries, requiring commensurate nuance.
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Affiliation(s)
- Lerato Majara
- Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER), Harvard T.H. Chan School of Public Health, Department of Epidemiology, Boston, MA, USA
- MRC Human Genetics Research Unit, Division of Human Genetics, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Observatory 7925, South Africa
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Allan Kalungi
- Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER), Harvard T.H. Chan School of Public Health, Department of Epidemiology, Boston, MA, USA
- Department of Psychiatry, College of Health Sciences, Makerere University, Kampala, Uganda
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Mental Health Project, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) & London School of Hygiene and Tropical Medicine (LSHTM), Uganda Research Unit, Entebbe, Uganda
| | - Nastassja Koen
- Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER), Harvard T.H. Chan School of Public Health, Department of Epidemiology, Boston, MA, USA
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Cape Town, South Africa
| | - Kristin Tsuo
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Rahul Gupta
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Lethukuthula L. Nkambule
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Heather Zar
- Department of Paediatrics and Child Health, Red Cross Children’s Hospital and Medical Research Council Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - Dan J. Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Cape Town, South Africa
| | - Eugene Kinyanda
- Mental Health Project, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) & London School of Hygiene and Tropical Medicine (LSHTM), Uganda Research Unit, Entebbe, Uganda
| | - Elizabeth G. Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Alicia R. Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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317
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Saadullah Khani N, Cotic M, Wang B, Abidoph R, Mills G, Richards-Belle A, Perry BI, Khandaker GM, Bramon E. Schizophrenia and cardiometabolic abnormalities: A Mendelian randomization study. Front Genet 2023; 14:1150458. [PMID: 37091807 PMCID: PMC10115959 DOI: 10.3389/fgene.2023.1150458] [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: 01/24/2023] [Accepted: 03/29/2023] [Indexed: 04/08/2023] Open
Abstract
Background: Individuals with a diagnosis of schizophrenia are known to be at high risk of premature mortality due to poor physical health, especially cardiovascular disease, diabetes, and obesity. The reasons for these physical health outcomes within this patient population are complex. Despite well-documented cardiometabolic adverse effects of certain antipsychotic drugs and lifestyle factors, schizophrenia may have an independent effect. Aims: To investigate if there is evidence that schizophrenia is causally related to cardiometabolic traits (blood lipids, anthropometric traits, glycaemic traits, blood pressure) and vice versa using bi-directional two-sample Mendelian randomization (MR) analysis. Methods: We used 185 genetic variants associated with schizophrenia from the latest Psychiatric Genomics Consortium GWAS (n = 130,644) in the forward analysis (schizophrenia to cardiometabolic traits) and genetic variants associated with the cardiometabolic traits from various consortia in the reverse analysis (cardiometabolic traits to schizophrenia), both at genome-wide significance (5 × 10-8). The primary method was inverse-variance weighted MR, supported by supplementary methods such as MR-Egger, as well as median and mode-based methods. Results: In the forward analysis, schizophrenia was associated with slightly higher low-density lipoprotein (LDL) cholesterol levels (0.013 SD change in LDL per log odds increase in schizophrenia risk, 95% CI, 0.001-0.024 SD; p = 0.027) and total cholesterol levels (0.013 SD change in total cholesterol per log odds increase in schizophrenia risk, 95% CI, 0.002-0.025 SD; p = 0.023). However, these associations did not survive multiple testing corrections. There was no evidence of a causal effect of cardiometabolic traits on schizophrenia in the reverse analysis. Discussion: Dyslipidemia and obesity in schizophrenia patients are unlikely to be driven primarily by schizophrenia itself. Therefore, lifestyle, diet, antipsychotic drugs side effects, as well as shared mechanisms for metabolic dysfunction and schizophrenia such as low-grade systemic inflammation could be possible reasons for the apparent increased risk of metabolic disease in people with schizophrenia. Further research is needed to examine the shared immune mechanism hypothesis.
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Affiliation(s)
- Noushin Saadullah Khani
- Division of Psychiatry, Mental Health Neuroscience Department, University College London, London, United Kingdom
| | - Marius Cotic
- Division of Psychiatry, Mental Health Neuroscience Department, University College London, London, United Kingdom
- Department of Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Baihan Wang
- Division of Psychiatry, Mental Health Neuroscience Department, University College London, London, United Kingdom
| | - Rosemary Abidoph
- Division of Psychiatry, Mental Health Neuroscience Department, University College London, London, United Kingdom
- Camden and Islington NHS Foundation Trust, London, United Kingdom
| | - Georgina Mills
- Division of Psychiatry, Mental Health Neuroscience Department, University College London, London, United Kingdom
| | - Alvin Richards-Belle
- Division of Psychiatry, Mental Health Neuroscience Department, University College London, London, United Kingdom
- Division of Psychiatry, Epidemiology and Applied Clinical Research Department, University College London, London, United Kingdom
| | - Benjamin I. Perry
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Golam M. Khandaker
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- NIHR Bristol Biomedical Research Centre, Bristol, United Kingdom
- Avon and Wiltshire Mental Health Partnership NHS Trust, Bristol, United Kingdom
| | - Elvira Bramon
- Division of Psychiatry, Mental Health Neuroscience Department, University College London, London, United Kingdom
- Camden and Islington NHS Foundation Trust, London, United Kingdom
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318
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Mastracci TL, Apte M, Amundadottir LT, Alvarsson A, Artandi S, Bellin MD, Bernal-Mizrachi E, Caicedo A, Campbell-Thompson M, Cruz-Monserrate Z, El Ouaamari A, Gaulton KJ, Geisz A, Goodarzi MO, Hara M, Hull-Meichle RL, Kleger A, Klein AP, Kopp JL, Kulkarni RN, Muzumdar MD, Naren AP, Oakes SA, Olesen SS, Phelps EA, Powers AC, Stabler CL, Tirkes T, Whitcomb DC, Yadav D, Yong J, Zaghloul NA, Pandol SJ, Sander M. Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings. Diabetes 2023; 72:433-448. [PMID: 36940317 PMCID: PMC10033248 DOI: 10.2337/db22-0942] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 12/29/2022] [Indexed: 03/22/2023]
Abstract
The Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report provides a summary of the proceedings from the workshop. The goals of the workshop were to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into six major theme areas, including 1) pancreas anatomy and physiology, 2) diabetes in the setting of exocrine disease, 3) metabolic influences on the exocrine pancreas, 4) genetic drivers of pancreatic diseases, 5) tools for integrated pancreatic analysis, and 6) implications of exocrine-endocrine cross talk. For each theme, multiple presentations were followed by panel discussions on specific topics relevant to each area of research; these are summarized here. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.
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Affiliation(s)
- Teresa L. Mastracci
- Department of Biology, Indiana University–Purdue University Indianapolis, Indianapolis, IN
| | - Minoti Apte
- Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
| | | | - Alexandra Alvarsson
- Diabetes, Obesity, and Metabolism Institute, Mount Sinai Hospital, New York, NY
| | - Steven Artandi
- Department of Internal Medicine, Stanford University, Stanford, CA
| | - Melena D. Bellin
- Departments of Pediatrics and Surgery, University of Minnesota Medical School, Minneapolis, MN
| | - Ernesto Bernal-Mizrachi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL
| | - Alejandro Caicedo
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL
| | - Martha Campbell-Thompson
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
| | - Zobeida Cruz-Monserrate
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH
| | | | - Kyle J. Gaulton
- Department of Pediatrics, University of California San Diego, La Jolla, CA
| | - Andrea Geisz
- Department of Molecular and Cell Biology, Boston University Henry M. Goldman School of Dental Medicine, Boston, MA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Manami Hara
- Department of Medicine, The University of Chicago, Chicago, IL
| | - Rebecca L. Hull-Meichle
- Department of Medicine, Division of Metabolism, Endocrinology, and Nutrition, University of Washington, Seattle, WA
| | - Alexander Kleger
- Institute of Molecular Oncology and Stem Cell Biology, Ulm University, Ulm, Germany
| | - Alison P. Klein
- Department of Pathology and Medicine, Johns Hopkins School of Medicine, Baltimore MD
| | - Janel L. Kopp
- Department of Cellular & Physiological Sciences, The University of British Columbia, Vancouver, Canada
| | | | - Mandar D. Muzumdar
- Departments of Genetics and Internal Medicine (Oncology), Yale University School of Medicine, New Haven, CT
| | | | - Scott A. Oakes
- Department of Pathology, The University of Chicago, Chicago, IL
| | - Søren S. Olesen
- Department of Gastroenterology and Hepatology, Aalborg University Hospital, Aalborg, Denmark
| | - Edward A. Phelps
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL
| | - Alvin C. Powers
- Department of Medicine, Division of Diabetes, Endocrinology, and Metabolism, Vanderbilt University Medical Center, Nashville, TN
| | - Cherie L. Stabler
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL
| | - Temel Tirkes
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN
| | | | - Dhiraj Yadav
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Jing Yong
- Degenerative Diseases Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Norann A. Zaghloul
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - Stephen J. Pandol
- Department of Gastroenterology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Maike Sander
- Department of Pediatrics and Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA
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Kong L, Ye C, Wang Y, Zheng J, Zhao Z, Li M, Xu Y, Lu J, Chen Y, Xu M, Wang W, Ning G, Bi Y, Wang T. Causal effect of lower birthweight on non-alcoholic fatty liver disease and mediating roles of insulin resistance and metabolites. Liver Int 2023; 43:829-839. [PMID: 36719063 DOI: 10.1111/liv.15532] [Citation(s) in RCA: 6] [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: 11/11/2022] [Revised: 12/29/2022] [Accepted: 01/28/2023] [Indexed: 02/01/2023]
Abstract
BACKGROUND & AIMS The causal association of lower birthweight with non-alcoholic fatty liver disease (NAFLD) and the mediating pathways remain unclear. We aimed to investigate the causal, independent association of lower birthweight with NAFLD and identify potential metabolic mediators and their mediation effects in this association. METHODS We performed two-step, two-sample Mendelian randomization (MR) using genome-wide association study (GWAS) summary statistics for birthweight from the Early Growth Genetics Consortium of 298 142 Europeans, NAFLD from a GWAS meta-analysis of 8434 NAFLD cases and 770 180 controls of Europeans, and 25 candidate mediators from corresponding reliable GWASs. RESULTS Genetically determined each 1-SD lower birthweight was associated with a 45% (95% CI: 1.25-1.69) increased risk of NAFLD, and this causal association persisted after adjusting for childhood obesity or adult adiposity traits in multivariable MR. Two-step MR identified 6 of 25 candidate mediators partially mediate the effect of lower birthweight on NAFLD, including fasting insulin (proportion mediated: 22.05%), leucine (17.29%), isoleucine (13.55%), valine (11.37%), alanine (10.01%) and monounsaturated fatty acids (MUFA; 7.23%). Bidirectional MR suggested a unidirectional effect of insulin resistance on isoleucine, leucine and valine and a unidirectional effect of alanine on insulin resistance. CONCLUSIONS This MR study elucidated the causal impact of lower birthweight on subsequent risk of NAFLD, independently of later-life adiposity and identified mediators including insulin resistance, branched-chain amino acids, alanine and MUFA in this association pathway. Our findings shed light on the pathogenesis of NAFLD and imply additional targets for prevention and intervention of NAFLD attributed to low birthweight.
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Affiliation(s)
- Lijie Kong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chaojie Ye
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiying Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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320
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Wong WJ, Emdin C, Bick AG, Zekavat SM, Niroula A, Pirruccello JP, Dichtel L, Griffin G, Uddin MM, Gibson CJ, Kovalcik V, Lin AE, McConkey ME, Vromman A, Sellar RS, Kim PG, Agrawal M, Weinstock J, Long MT, Yu B, Banerjee R, Nicholls RC, Dennis A, Kelly M, Loh PR, McCarroll S, Boerwinkle E, Vasan RS, Jaiswal S, Johnson AD, Chung RT, Corey K, Levy D, Ballantyne C, Ebert BL, Natarajan P. Clonal haematopoiesis and risk of chronic liver disease. Nature 2023; 616:747-754. [PMID: 37046084 PMCID: PMC10405350 DOI: 10.1038/s41586-023-05857-4] [Citation(s) in RCA: 93] [Impact Index Per Article: 46.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 02/16/2023] [Indexed: 04/14/2023]
Abstract
Chronic liver disease is a major public health burden worldwide1. Although different aetiologies and mechanisms of liver injury exist, progression of chronic liver disease follows a common pathway of liver inflammation, injury and fibrosis2. Here we examined the association between clonal haematopoiesis of indeterminate potential (CHIP) and chronic liver disease in 214,563 individuals from 4 independent cohorts with whole-exome sequencing data (Framingham Heart Study, Atherosclerosis Risk in Communities Study, UK Biobank and Mass General Brigham Biobank). CHIP was associated with an increased risk of prevalent and incident chronic liver disease (odds ratio = 2.01, 95% confidence interval (95% CI) [1.46, 2.79]; P < 0.001). Individuals with CHIP were more likely to demonstrate liver inflammation and fibrosis detectable by magnetic resonance imaging compared to those without CHIP (odds ratio = 1.74, 95% CI [1.16, 2.60]; P = 0.007). To assess potential causality, Mendelian randomization analyses showed that genetic predisposition to CHIP was associated with a greater risk of chronic liver disease (odds ratio = 2.37, 95% CI [1.57, 3.6]; P < 0.001). In a dietary model of non-alcoholic steatohepatitis, mice transplanted with Tet2-deficient haematopoietic cells demonstrated more severe liver inflammation and fibrosis. These effects were mediated by the NLRP3 inflammasome and increased levels of expression of downstream inflammatory cytokines in Tet2-deficient macrophages. In summary, clonal haematopoiesis is associated with an elevated risk of liver inflammation and chronic liver disease progression through an aberrant inflammatory response.
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Affiliation(s)
- Waihay J Wong
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Connor Emdin
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Alexander G Bick
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Seyedeh M Zekavat
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Yale University School of Medicine, New Haven, CT, USA
- Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Abhishek Niroula
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Department of Laboratory Medicine, Lund University, Lund, Sweden
| | - James P Pirruccello
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - Laura Dichtel
- Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gabriel Griffin
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Department of Pathology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Md Mesbah Uddin
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Christopher J Gibson
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Veronica Kovalcik
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Amy E Lin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Marie E McConkey
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Amelie Vromman
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Rob S Sellar
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Haematology, UCL Cancer Institute, London, UK
| | - Peter G Kim
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Mridul Agrawal
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Joshua Weinstock
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Michelle T Long
- Section of Gastroenterology, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | | | | | | | - Po-Ru Loh
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Steve McCarroll
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Ramachandran S Vasan
- The University of Texas School of Public Health San Antonio, San Antonio, TX, USA
- Framingham Heart Study of the NHLBI and Boston University School of Medicine, Framingham, MA, USA
- The University of Texas Health Science Center, San Antonio, TX, USA
| | - Siddhartha Jaiswal
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Andrew D Johnson
- Population Sciences Branch, National Heart, Lung, and Blood Institute, Framingham, MA, USA
| | - Raymond T Chung
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Liver Center, Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kathleen Corey
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Liver Center, Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Daniel Levy
- Framingham Heart Study of the NHLBI and Boston University School of Medicine, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Christie Ballantyne
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Benjamin L Ebert
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Howard Hughes Medical Institute, Dana-Farber Cancer Institute, Boston, MA, USA.
| | - Pradeep Natarajan
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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321
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Chen J, Yuan S, Fu T, Ruan X, Qiao J, Wang X, Li X, Gill D, Burgess S, Giovannucci EL, Larsson SC. Gastrointestinal Consequences of Type 2 Diabetes Mellitus and Impaired Glycemic Homeostasis: A Mendelian Randomization Study. Diabetes Care 2023; 46:828-835. [PMID: 36800530 PMCID: PMC10091506 DOI: 10.2337/dc22-1385] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 01/17/2023] [Indexed: 02/19/2023]
Abstract
OBJECTIVE We conducted a Mendelian randomization (MR) study to examine the associations of type 2 diabetes and glycemic traits with gastrointestinal diseases (GDs). RESEARCH DESIGN AND METHODS Uncorrelated genetic variants associated with type 2 diabetes (n = 231), fasting insulin (n = 38), fasting glucose (n = 71), and hemoglobin A1c (n = 75) at the genome-wide significance were selected as instrument variables. Genetic associations with 23 common GDs were obtained from the FinnGen and UK Biobank studies and other large consortia. RESULTS Genetic liability to type 2 diabetes was associated with the risk of 12 GDs. Per 1-unit increase in the log-transformed odds ratio (OR) of type 2 diabetes, the OR was 1.06 (95% CI, 1.03-1.09) for gastroesophageal reflux disease, 1.12 (95% CI, 1.07-1.17) for gastric ulcer, 1.11 (95% CI, 1.03-1.20) for acute gastritis, 1.07 (95% CI, 1.01-1.13) for chronic gastritis, 1.08 (95% CI, 1.03-1.12) for irritable bowel syndrome, 1.04 (95% CI, 1.01-1.07) for diverticular disease, 1.08 (95% CI, 1.02-1.14) for acute pancreatitis, 1.09 (95% CI, 1.05-1.12) for cholelithiasis, 1.09 (95% CI, 1.05-1.13) for cholelithiasis with cholecystitis, 1.29 (95% CI, 1.17-1.43) for nonalcoholic fatty liver disease, 1.12 (95% CI, 1.03-1.21) for liver cirrhosis, and 0.93 (95% CI, 0.89-0.97) for ulcerative colitis. Genetically predicted higher levels of fasting insulin and glucose were associated with six and one GDs, respectively. CONCLUSIONS Associations were found between genetic liability to type 2 diabetes and an increased risk of a broad range of GDs, highlighting the importance of GD prevention in patients with type 2 diabetes.
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Affiliation(s)
- Jie Chen
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Tian Fu
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xixian Ruan
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jie Qiao
- Department of Endocrinology and Metabolism, the Second Affiliated Hospital of ZheJiang University School of Medicine, Hangzhou, China
| | - Xiaoyan Wang
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xue Li
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, U.K
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, U.K
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, U.K
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K
| | - Edward L. Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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322
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Mina T, Yew YW, Ng HK, Sadhu N, Wansaicheong G, Dalan R, Low DYW, Lam BCC, Riboli E, Lee ES, Ngeow J, Elliott P, Griva K, Loh M, Lee J, Chambers J. Adiposity impacts cognitive function in Asian populations: an epidemiological and Mendelian Randomization study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 33:100710. [PMID: 36851942 PMCID: PMC9957736 DOI: 10.1016/j.lanwpc.2023.100710] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/19/2023] [Accepted: 01/26/2023] [Indexed: 02/15/2023]
Abstract
Background Obesity and related metabolic disturbances including diabetes, hypertension and hyperlipidemia predict future cognitive decline. Asia has a high prevalence of both obesity and metabolic disease, potentially amplifying the future burden of dementia in the region. We aimed to investigate the impact of adiposity and metabolic risk on cognitive function in Asian populations, using an epidemiological analysis and a two-sample Mendelian Randomization (MR) study. Methods The Health for Life in Singapore (HELIOS) Study is a population-based cohort of South-East-Asian men and women in Singapore, aged 30-84 years. We analyzed 8769 participants with metabolic and cognitive data collected between 2018 and 2021. Whole-body fat mass was quantified with Dual X-Ray Absorptiometry (DEXA). Cognition was assessed using a computerized cognitive battery. An index of general cognition ' g ' was derived through factor analysis. We tested the relationship of fat mass indices and metabolic measures with ' g ' using regression approaches. We then performed inverse-variance-weighted MR of adiposity and metabolic risk factors on ' g ', using summary statistics for genome-wide association studies of BMI, visceral adipose tissue (VAT), waist-hip-ratio (WHR), blood pressure, HDL cholesterol, triglycerides, fasting glucose, HbA1c, and general cognition. Findings Participants were 58.9% female, and aged 51.4 (11.3) years. In univariate analysis, all 29 adiposity and metabolic measures assessed were associated with ' g ' at P < 0.05. In multivariable analyses, reduced ' g ' was consistently associated with increased visceral fat mass index and lower HDL cholesterol (P < 0.001), but not with blood pressure, triglycerides, or glycemic indices. The reduction in ' g ' associated with 1SD higher visceral fat, or 1SD lower HDL cholesterol, was equivalent to a 0.7 and 0.9-year increase in chronological age respectively (P < 0.001). Inverse variance MR analyses showed that reduced ' g ' is associated with genetically determined elevation of VAT, BMI and WHR (all P < 0.001). In contrast, MR did not support a causal role for blood pressure, lipid, or glycemic indices on cognition. Interpretation We show an independent relationship between adiposity and cognition in a multi-ethnic Asian population. MR analyses suggest that both visceral adiposity and raised BMI are likely to be causally linked to cognition. Our findings have important implications for preservation of cognitive health, including further motivation for action to reverse the rising burden of obesity in the Asia-Pacific region. Funding The Nanyang Technological University-the Lee Kong Chian School of Medicine, National Healthcare Group, National Medical Research Council, Ministry of Education, Singapore.
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Affiliation(s)
- Theresia Mina
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Yik Weng Yew
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,National Skin Centre, Research Division, 1 Mandalay Rd, 308205, Singapore
| | - Hong Kiat Ng
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Nilanjana Sadhu
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Gervais Wansaicheong
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Diagnostic Radiology, Tan Tock Seng Hospital (TTSH), 11 Jalan Tan Tock Seng, 308433, Singapore
| | - Rinkoo Dalan
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Endocrinology, TTSH, Singapore
| | - Dorrain Yan Wen Low
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Benjamin Chih Chiang Lam
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Khoo Teck Puat Hospital, Integrated Care for Obesity & Diabetes, 90 Yishun Central, 768828, Singapore
| | - Elio Riboli
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, 152 Medical School, St Mary's Campus, London, W2 1NY, United Kingdom
| | - Eng Sing Lee
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Clinical Research Unit, National Healthcare Group Polyclinic, 3 Fusionopolis Link, Nexus@one-north, #05-10, 138543, Singapore
| | - Joanne Ngeow
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Division of Medical Oncology, National Cancer Centre, 11 Hospital Drive, 169610, Singapore
| | - Paul Elliott
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, 152 Medical School, St Mary's Campus, London, W2 1NY, United Kingdom
| | - Konstadina Griva
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore
| | - Marie Loh
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,National Skin Centre, Research Division, 1 Mandalay Rd, 308205, Singapore
| | - Jimmy Lee
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Research Division, Institute of Mental Health, 539747, Singapore
| | - John Chambers
- Nanyang Technological University Lee Kong Chian School of Medicine, Level 18 Clinical Sciences Building, 11 Mandalay Road, 308232, Singapore.,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, 152 Medical School, St Mary's Campus, London, W2 1NY, United Kingdom
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323
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Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Rayner NW, Bocher O, Arruda ALDSV, Sonehara K, Namba S, Lee SSK, Preuss MH, Petty LE, Schroeder P, Vanderwerff B, Kals M, Bragg F, Lin K, Guo X, Zhang W, Yao J, Kim YJ, Graff M, Takeuchi F, Nano J, Lamri A, Nakatochi M, Moon S, Scott RA, Cook JP, Lee JJ, Pan I, Taliun D, Parra EJ, Chai JF, Bielak LF, Tabara Y, Hai Y, Thorleifsson G, Grarup N, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Kwak SH, Long J, Sun M, Tong L, Chen WM, Nongmaithem SS, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen CH, Raffield LM, Prins BP, Nicolas A, Yanek LR, Chen G, Brody JA, Kabagambe E, An P, Xiang AH, Choi HS, Cade BE, Tan J, Broadaway KA, Williamson A, Kamali Z, Cui J, Adair LS, Adeyemo A, Aguilar-Salinas CA, Ahluwalia TS, Anand SS, Bertoni A, Bork-Jensen J, Brandslund I, Buchanan TA, Burant CF, Butterworth AS, Canouil M, Chan JCN, Chang LC, Chee ML, Chen J, Chen SH, Chen YT, Chen Z, Chuang LM, Cushman M, Danesh J, Das SK, de Silva HJ, et alSuzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Rayner NW, Bocher O, Arruda ALDSV, Sonehara K, Namba S, Lee SSK, Preuss MH, Petty LE, Schroeder P, Vanderwerff B, Kals M, Bragg F, Lin K, Guo X, Zhang W, Yao J, Kim YJ, Graff M, Takeuchi F, Nano J, Lamri A, Nakatochi M, Moon S, Scott RA, Cook JP, Lee JJ, Pan I, Taliun D, Parra EJ, Chai JF, Bielak LF, Tabara Y, Hai Y, Thorleifsson G, Grarup N, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Kwak SH, Long J, Sun M, Tong L, Chen WM, Nongmaithem SS, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen CH, Raffield LM, Prins BP, Nicolas A, Yanek LR, Chen G, Brody JA, Kabagambe E, An P, Xiang AH, Choi HS, Cade BE, Tan J, Broadaway KA, Williamson A, Kamali Z, Cui J, Adair LS, Adeyemo A, Aguilar-Salinas CA, Ahluwalia TS, Anand SS, Bertoni A, Bork-Jensen J, Brandslund I, Buchanan TA, Burant CF, Butterworth AS, Canouil M, Chan JCN, Chang LC, Chee ML, Chen J, Chen SH, Chen YT, Chen Z, Chuang LM, Cushman M, Danesh J, Das SK, de Silva HJ, Dedoussis G, Dimitrov L, Doumatey AP, Du S, Duan Q, Eckardt KU, Emery LS, Evans DS, Evans MK, Fischer K, Floyd JS, Ford I, Franco OH, Frayling TM, Freedman BI, Genter P, Gerstein HC, Giedraitis V, González-Villalpando C, González-Villalpando ME, Gordon-Larsen P, Gross M, Guare LA, Hackinger S, Han S, Hattersley AT, Herder C, Horikoshi M, Howard AG, Hsueh W, Huang M, Huang W, Hung YJ, Hwang MY, Hwu CM, Ichihara S, Ikram MA, Ingelsson M, Islam MT, Isono M, Jang HM, Jasmine F, Jiang G, Jonas JB, Jørgensen T, Kandeel FR, Kasturiratne A, Katsuya T, Kaur V, Kawaguchi T, Keaton JM, Kho AN, Khor CC, Kibriya MG, Kim DH, Kronenberg F, Kuusisto J, Läll K, Lange LA, Lee KM, Lee MS, Lee NR, Leong A, Li L, Li Y, Li-Gao R, Lithgart S, Lindgren CM, Linneberg A, Liu CT, Liu J, Locke AE, Louie T, Luan J, Luk AO, Luo X, Lv J, Lynch JA, Lyssenko V, Maeda S, Mamakou V, Mansuri SR, Matsuda K, Meitinger T, Metspalu A, Mo H, Morris AD, Nadler JL, Nalls MA, Nayak U, Ntalla I, Okada Y, Orozco L, Patel SR, Patil S, Pei P, Pereira MA, Peters A, Pirie FJ, Polikowsky HG, Porneala B, Prasad G, Rasmussen-Torvik LJ, Reiner AP, Roden M, Rohde R, Roll K, Sabanayagam C, Sandow K, Sankareswaran A, Sattar N, Schönherr S, Shahriar M, Shen B, Shi J, Shin DM, Shojima N, Smith JA, So WY, Stančáková A, Steinthorsdottir V, Stilp AM, Strauch K, Taylor KD, Thorand B, Thorsteinsdottir U, Tomlinson B, Tran TC, Tsai FJ, Tuomilehto J, Tusie-Luna T, Udler MS, Valladares-Salgado A, van Dam RM, van Klinken JB, Varma R, Wacher-Rodarte N, Wheeler E, Wickremasinghe AR, van Dijk KW, Witte DR, Yajnik CS, Yamamoto K, Yamamoto K, Yoon K, Yu C, Yuan JM, Yusuf S, Zawistowski M, Zhang L, Zheng W, VA Million Veteran Program, AMED GRIFIN Diabetes Initiative Japan, Biobank Japan Project, Penn Medicine BioBank, Regeneron Genetics Center, eMERGE Consortium, International Consortium for Blood Pressure (ICBP), Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), Raffel LJ, Igase M, Ipp E, Redline S, Cho YS, Lind L, Province MA, Fornage M, Hanis CL, Ingelsson E, Zonderman AB, Psaty BM, Wang YX, Rotimi CN, Becker DM, Matsuda F, Liu Y, Yokota M, Kardia SLR, Peyser PA, Pankow JS, Engert JC, Bonnefond A, Froguel P, Wilson JG, Sheu WHH, Wu JY, Hayes MG, Ma RCW, Wong TY, Mook-Kanamori DO, Tuomi T, Chandak GR, Collins FS, Bharadwaj D, Paré G, Sale MM, Ahsan H, Motala AA, Shu XO, Park KS, Jukema JW, Cruz M, Chen YDI, Rich SS, McKean-Cowdin R, Grallert H, Cheng CY, Ghanbari M, Tai ES, Dupuis J, Kato N, Laakso M, Köttgen A, Koh WP, Bowden DW, Palmer CNA, Kooner JS, Kooperberg C, Liu S, North KE, Saleheen D, Hansen T, Pedersen O, Wareham NJ, Lee J, Kim BJ, Millwood IY, Walters RG, Stefansson K, Goodarzi MO, Mohlke KL, Langenberg C, Haiman CA, Loos RJF, Florez JC, Rader DJ, Ritchie MD, Zöllner S, Mägi R, Denny JC, Yamauchi T, Kadowaki T, Chambers JC, Ng MCY, Sim X, Below JE, Tsao PS, Chang KM, McCarthy MI, Meigs JB, Mahajan A, Spracklen CN, Mercader JM, Boehnke M, Rotter JI, Vujkovic M, Voight BF, Morris AP, Zeggini E. Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.31.23287839. [PMID: 37034649 PMCID: PMC10081410 DOI: 10.1101/2023.03.31.23287839] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.
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Affiliation(s)
- Ken Suzuki
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Konstantinos Hatzikotoulas
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Henry J. Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Xianyong Yin
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing City, China
| | - Kim M. Lorenz
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ravi Mandla
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alicia Huerta-Chagoya
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Nigel W. Rayner
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ozvan Bocher
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ana Luiza de S. V. Arruda
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Simon S. K. Lee
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael H. Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lauren E. Petty
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip Schroeder
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brett Vanderwerff
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fiona Bragg
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hosptial, London NorthWest Healthcare NHS Trust, Middlesex, UK
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sanghoon Moon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - James P. Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Jung-Jin Lee
- Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian Pan
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
| | - Daniel Taliun
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto at Mississsauga, Mississauga, ON, Canada
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tamar Sofer
- Department of Biostatistics, Harvard University, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard University, Boston, MA, USA
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Chloé Sarnowski
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Darryl Nousome
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Soo-Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Meng Sun
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Lin Tong
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Suraj S. Nongmaithem
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Victor J. Y. Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Claudia H. T. Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Yoonjung Yoonie Joo
- Institute of Data Science, Korea University, Seoul, South Korea
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bram Peter Prins
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Aude Nicolas
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Lisa R. Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Edmond Kabagambe
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Academics, Ochsner Health, New Orleans, LA, USA
| | - Ping An
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Anny H. Xiang
- Department of Research and Evaluation, Division of Biostatistics Research, Kaiser Permanente of Southern California, Pasadena, CA, USA
| | - Hyeok Sun Choi
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Brian E. Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - K. Alaine Broadaway
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alice Williamson
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Metabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Jinrui Cui
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Linda S. Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carlos A. Aguilar-Salinas
- Unidad de Investigación en Enfermedades Metabólicas and Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Tarunveer S. Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Sonia S. Anand
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Alain Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivan Brandslund
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
- Department of Clinical Biochemistry, Vejle Hospital, Vejle, Denmark
| | - Thomas A. Buchanan
- Department of Medicine, Division of Endocrinology and Diabetes, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Charles F. Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Adam S. Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Mickaël Canouil
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Li-Ching Chang
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ji Chen
- Exeter Centre of Excellence in Diabetes (ExCEeD), Exeter Medical School, University of Exeter, Exeter, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Shyh-Huei Chen
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Lee-Ming Chuang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Mary Cushman
- Department of Medicine, University of Vermont, Colchester, VT, USA
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Swapan K. Das
- Section on Endocrinology and Metabolism, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - H. Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shufa Du
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Leslie S. Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Michele K. Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fischer
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - James S. Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Oscar H. Franco
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Pauline Genter
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Hertzel C. Gerstein
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Maria Elena González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lindsay A. Guare
- Genomics and Computational Biology Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sophie Hackinger
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Sohee Han
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | | | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Dusseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Annie-Green Howard
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Willa Hsueh
- Department of Internal Medicine, Diabetes and Metabolism Research Center, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Mengna Huang
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan Branch, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Mi Yeong Hwang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Sahoko Ichihara
- Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, Japan
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | | | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hye-Mi Jang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Farzana Jasmine
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Guozhi Jiang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Jost B. Jonas
- Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
| | - Torben Jørgensen
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - Fouad R. Kandeel
- Department of Clinical Diabetes, Endocrinology and Metabolism, Department of Translational Research and Cellular Therapeutics, City of Hope, Duarte, CA, USA
| | | | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Varinderpal Kaur
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Jacob M. Keaton
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Abel N. Kho
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Muhammad G. Kibriya
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Duk-Hwan Kim
- Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, South Korea
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Leslie A. Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Kyung Min Lee
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Myung-Shik Lee
- Severance Biomedical Science Institute and Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Nanette R. Lee
- USC-Office of Population Studies Foundation Inc., University of San Carlos, Cebu City, Philippines
| | - Aaron Leong
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Symen Lithgart
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Cecilia M. Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Big Data Institute, Li Ka Shing Centre For Health Information and Discovery, University of Oxford, Oxford, UK
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Adam E. Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St Louis, MO, USA
- Present address: Regeneron Genetics Center, Tarrytown, NY, USA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jian’an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andrea O. Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Xi Luo
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Julie A. Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway
| | - Shiro Maeda
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Vasiliki Mamakou
- Dromokaiteio Psychiatric Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Sohail Rafik Mansuri
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Koichi Matsuda
- Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Huan Mo
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew D. Morris
- The Usher Institute to the Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Jerry L. Nadler
- Department of Medicine and Pharmacology, New York Medical College, Valhalla, NY, USA
| | - Michael A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Glen Echo, MD, USA
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Uma Nayak
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Sanjay R. Patel
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Snehal Patil
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Mark A Pereira
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilians Universität München, Munich, Germany
| | - Fraser J. Pirie
- Department of Diabetes and Endocrinology, Nelson R Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Hannah G. Polikowsky
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Campus, Ghaziabad, India
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Michael Roden
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Dusseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Katheryn Roll
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Kevin Sandow
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alagu Sankareswaran
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Mohammad Shahriar
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Botong Shen
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Dong Mun Shin
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | | | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Chair of Genetic Epidemiology, Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig Maximilians Universität München, Munich, Germany
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Brian Tomlinson
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
| | - Tam C. Tran
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Fuu-Jen Tsai
- Department of Medical Genetics and Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Jaakko Tuomilehto
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland, Finnish Institute for Health and Welfare, Helsinki, Finland
- National School of Public Health, Madrid, Spain
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Teresa Tusie-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Departamento de Medicina Genómica y Toxiología Ambiental, Instituto de Investigaciones Biomédicas, UNAM, Mexico City, Mexico
| | - Miriam S. Udler
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Adan Valladares-Salgado
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Rob M. van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jan B. van Klinken
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Chemistry, Laboratory of Genetic Metabolic Disease, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Rohit Varma
- Southern California Eye Institute, CHA Hollywood Presbyterian Hospital, Los Angeles, CA, USA
| | - Niels Wacher-Rodarte
- Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Ko Willems van Dijk
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniel R. Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Chittaranjan S. Yajnik
- Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | - Ken Yamamoto
- Department of Medical Biochemistry, Kurume University School of Medicine, Kurume, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Liang Zhang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | | | | | | | | | | | | | - Leslie J Raffel
- Department of Pediatrics, Division of Genetic and Genomic Medicine, UCI Irvine School of Medicine, Irvine, CA, USA
| | - Michiya Igase
- Department of Anti-Aging Medicine, Ehime University Graduate School of Medicine, Ehime, Japan
| | - Eli Ipp
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Michael A. Province
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Craig L. Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, US
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Alan B. Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ya-Xing Wang
- Beijing Institute of Ophthalmology, Ophthalmology and Visual Sciences Key Laboratory, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Diane M. Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - James C. Engert
- Department of Medicine, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Amélie Bonnefond
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Philippe Froguel
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Wayne H. H. Sheu
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - M. Geoffrey Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Anthropology, Northwestern University, Evanston, IL, USA
| | - Ronald C. W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Dennis O. Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tiinamaija Tuomi
- Department of Endocrinology, Helsinki University Hospital, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Lund University Diabetes Centre, Malmö, Sweden
| | - Giriraj R. Chandak
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Francis S. Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Michèle M. Sale
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Deceased
| | - Habibul Ahsan
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Ayesha A. Motala
- Department of Diabetes and Endocrinology, Nelson R Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kyong-Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Roberta McKean-Cowdin
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Josee Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Woon-Puay Koh
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Colin N. A. Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, University of Dundee, Dundee, UK
| | - Jaspal S. Kooner
- Department of Cardiology, Ealing Hosptial, London NorthWest Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | | | - Simin Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
- Department of Medicine, Brown University Alpert School of Medicine, Providence, RI, USA
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Danish Saleheen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas J. Wareham
- The Usher Institute to the Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Juyoung Lee
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Bong-Jo Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Iona Y. Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Robin G. Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kari Stefansson
- deCODE Genetics, Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Mark O. Goodarzi
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité Universitätsmedizin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Jose C. Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daniel J. Rader
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Translational Medicine and Therapeutics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D. Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Center for Precision Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sebastian Zöllner
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Joshua C. Denny
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Toranomon Hospital, Tokyo, Japan
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hosptial, London NorthWest Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Maggie C. Y. Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jennifer E. Below
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip S. Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyong-Mi Chang
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mark I. McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hosptial, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Present address: Genentech, South San Francisco, CA, USA
| | - James B. Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Present address: Genentech, South San Francisco, CA, USA
| | - Cassandra N. Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Josep M. Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marijana Vujkovic
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Epidemiology, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F. Voight
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Andrew P. Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- TUM School of Medicine, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany
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Bayer S, Reik A, von Hesler L, Hauner H, Holzapfel C. Association between Genotype and the Glycemic Response to an Oral Glucose Tolerance Test: A Systematic Review. Nutrients 2023; 15:nu15071695. [PMID: 37049537 PMCID: PMC10096950 DOI: 10.3390/nu15071695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/21/2023] [Accepted: 03/22/2023] [Indexed: 04/03/2023] Open
Abstract
The inter-individual variability of metabolic response to foods may be partly due to genetic variation. This systematic review aims to assess the associations between genetic variants and glucose response to an oral glucose tolerance test (OGTT). Three databases (PubMed, Web of Science, Embase) were searched for keywords in the field of genetics, OGTT, and metabolic response (PROSPERO: CRD42021231203). Inclusion criteria were available data on single nucleotide polymorphisms (SNPs) and glucose area under the curve (gAUC) in a healthy study cohort. In total, 33,219 records were identified, of which 139 reports met the inclusion criteria. This narrative synthesis focused on 49 reports describing gene loci for which several reports were available. An association between SNPs and the gAUC was described for 13 gene loci with 53 different SNPs. Three gene loci were mostly investigated: transcription factor 7 like 2 (TCF7L2), peroxisome proliferator-activated receptor gamma (PPARγ), and potassium inwardly rectifying channel subfamily J member 11 (KCNJ11). In most reports, the associations were not significant or single findings were not replicated. No robust evidence for an association between SNPs and gAUC after an OGTT in healthy persons was found across the identified studies. Future studies should investigate the effect of polygenic risk scores on postprandial glucose levels.
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Affiliation(s)
- Sandra Bayer
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
| | - Anna Reik
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
| | - Lena von Hesler
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
| | - Hans Hauner
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
- Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany
| | - Christina Holzapfel
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
- Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, 36037 Fulda, Germany
- Correspondence:
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325
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Lin Z, Huang J, Xie S, Zheng Z, Tang K, Li S, Chen R. The Association Between Insulin Use and Asthma: An Epidemiological Observational Analysis and Mendelian Randomization Study. Lung 2023; 201:189-199. [PMID: 36971839 DOI: 10.1007/s00408-023-00611-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 03/09/2023] [Indexed: 03/29/2023]
Abstract
BACKGROUND Asthma is a common respiratory disease caused by genetic and environmental factors, but the contribution of insulin use to the risk of asthma remains unclear. This study aimed to investigate the association between insulin use and asthma in a large population-based cohort, and further explore their causal relationship by Mendelian randomization (MR) analysis. METHODS An epidemiological study including 85,887 participants from the National Health and Nutrition Examination Survey (NHANES) 2001-2018 was performed to evaluate the association between insulin use and asthma. Based on the inverse-variance weighted approach, MR analysis were conducted to estimate the causal effect of insulin use on asthma from the UKB and FinnGen datasets, respectively. RESULTS In the NHANES cohort, we found that insulin use was associated with an increased risk of asthma [odd ratio (OR) 1.38; 95% CI 1.16-1.64; p < 0.001]. For the MR analysis, we found a causal relationship between insulin use and a higher risk of asthma in both Finn (OR 1.10; p < 0.001) and UK Biobank cohorts (OR 1.18; p < 0.001). Meanwhile, there was no causal association between diabetes and asthma. After multivariable adjustment for diabetes in UKB cohort, the insulin use remained significantly associated with an increased risk of asthma (OR 1.17, p < 0.001). CONCLUSIONS An association between insulin use and an increased risk of asthma was found via the real-world data from the NHANES. In addition, the current study identified a causal effect and provided a genetic evidence of insulin use and asthma. More studies are needed to elucidate the mechanisms underlying the association between insulin use and asthma.
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Affiliation(s)
- Zikai Lin
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
- Nanshan School of Medical, Guangzhou Medical University, Guangzhou, China
| | - Junfeng Huang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Shuojia Xie
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
- Nanshan School of Medical, Guangzhou Medical University, Guangzhou, China
| | - Ziwen Zheng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Kailun Tang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
- Department of Allergy and Clinical Immunology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Clinical Medical College of Henan University, Kaifeng, China
| | - Shiyue Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China.
| | - Ruchong Chen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China.
- Department of Allergy and Clinical Immunology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
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326
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Mao X, Mao S, Sun H, Huang F, Wang Y, Zhang D, Wang Q, Li Z, Zou W, Liao Z. Causal associations between modifiable risk factors and pancreatitis: A comprehensive Mendelian randomization study. Front Immunol 2023; 14:1091780. [PMID: 36999014 PMCID: PMC10043332 DOI: 10.3389/fimmu.2023.1091780] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/03/2023] [Indexed: 03/15/2023] Open
Abstract
BackgroundThe pathogenesis of pancreatitis involves diverse environmental risk factors, some of which have not yet been clearly elucidated. This study systematically investigated the causal effects of genetically predicted modifiable risk factors on pancreatitis using the Mendelian randomization (MR) approach.MethodsGenetic variants associated with 30 exposure factors were obtained from genome-wide association studies. Summary-level statistical data for acute pancreatitis (AP), chronic pancreatitis (CP), alcohol-induced AP (AAP) and alcohol-induced CP (ACP) were obtained from FinnGen consortia. Univariable and multivariable MR analyses were performed to identify causal risk factors for pancreatitis.ResultsGenetic predisposition to smoking (OR = 1.314, P = 0.021), cholelithiasis (OR = 1.365, P = 1.307E-19) and inflammatory bowel disease (IBD) (OR = 1.063, P = 0.008) as well as higher triglycerides (OR = 1.189, P = 0.016), body mass index (BMI) (OR = 1.335, P = 3.077E-04), whole body fat mass (OR = 1.291, P = 0.004) and waist circumference (OR = 1.466, P = 0.011) were associated with increased risk of AP. The effect of obesity traits on AP was attenuated after correcting for cholelithiasis. Genetically-driven smoking (OR = 1.595, P = 0.005), alcohol consumption (OR = 3.142, P = 0.020), cholelithiasis (OR = 1.180, P = 0.001), autoimmune diseases (OR = 1.123, P = 0.008), IBD (OR = 1.066, P = 0.042), type 2 diabetes (OR = 1.121, P = 0.029), and higher serum calcium (OR = 1.933, P = 0.018), triglycerides (OR = 1.222, P = 0.021) and waist-to-hip ratio (OR = 1.632, P = 0.023) increased the risk of CP. Cholelithiasis, triglycerides and the waist-to-hip ratio remained significant predictors in the multivariable MR. Genetically predicted alcohol drinking was associated with increased risk of AAP (OR = 15.045, P = 0.001) and ACP (OR = 6.042, P = 0.014). After adjustment of alcohol drinking, genetic liability to IBD had a similar significant causal effect on AAP (OR = 1.137, P = 0.049), while testosterone (OR = 0.270, P = 0.002) a triglyceride (OR = 1.610, P = 0.001) and hip circumference (OR = 0.648, P = 0.040) were significantly associated with ACP. Genetically predicted higher education and household income levels could lower the risk of pancreatitis.ConclusionsThis MR study provides evidence of complex causal associations between modifiable risk factors and pancreatitis. These findings provide new insights into potential therapeutic and prevention strategies.
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Affiliation(s)
- Xiaotong Mao
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
| | - Shenghan Mao
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
| | - Hongxin Sun
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
| | - Fuquan Huang
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
| | - Yuanchen Wang
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
| | - Deyu Zhang
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
| | - Qiwen Wang
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
| | - Zhaoshen Li
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
| | - Wenbin Zou
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
- *Correspondence: Zhuan Liao, ; Wenbin Zou,
| | - Zhuan Liao
- Department of Gastroenterology, Changhai Hospital, Navy Medical University, Shanghai, China
- Shanghai Institute of Pancreatic Diseases, Shanghai, China
- *Correspondence: Zhuan Liao, ; Wenbin Zou,
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327
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Mendelian Randomization Analysis Provides Insights into the Pathogenesis of Serum Levels of Branched-Chain Amino Acids in Cardiovascular Disease. Metabolites 2023; 13:metabo13030403. [PMID: 36984843 PMCID: PMC10059809 DOI: 10.3390/metabo13030403] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/03/2023] [Accepted: 03/06/2023] [Indexed: 03/11/2023] Open
Abstract
Several observational studies have indicated an association between high serum levels of branched-chain amino acids (BCAAs) and an increased risk of cardiovascular disease (CVD). To assess whether theses associations reflect causality, we carried out two-sample Mendelian randomization (MR). Single-nucleotide polymorphisms (SNPs) associated with BCAA were evaluated in 10 studies, including 24,925 participants. The association between SNPs and coronary artery disease (CAD) were assessed using summary estimates from the CARDIoGRAMplusC4D consortium. Further MR analysis of BCAAs and seven CVD outcomes was performed. The BCAA-raising gene functions were also analyzed. MR analyses revealed a risk-increasing causal relationship between serum BCAA concentrations and CAD (odds ratio 1.08; 95% confidence interval (CI) 1.02–1.14), which was partly mediated by blood pressure and type 2 diabetes. BCAA also demonstrated a causal relationship with ischemic CVD events induced by plaque rupture and thrombosis (false discovery rate <0.05). Two BCAA-raising genes (MRL33 and CBLN1) were preferentially associated with myocardial infarction risk in the presence of atherosclerosis (p < 0.003). Functional analysis of the BCAA-raising genes suggested the causal involvement of two pathophysiological pathways, including glucose metabolism (PPM1K and TRMT61A) related to plaque progression, and the newly discovered neuroendocrine disorders regulating blood pressure (MRPL33, CBLN1, and C2orf16) related to plaque rupture and thrombosis. This comprehensive MR analysis provided insights into the potential causal mechanisms linking BCAA with CVD risk and suggested targeting neuroendocrine disorders as a potential strategy for the prevention of CVD. These results warrant further studies to elucidate the mechanisms underlying these reported causal associations.
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328
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Dybjer E, Kumar A, Nägga K, Engström G, Mattsson-Carlgren N, Nilsson PM, Melander O, Hansson O. Polygenic risk of type 2 diabetes is associated with incident vascular dementia: a prospective cohort study. Brain Commun 2023; 5:fcad054. [PMID: 37091584 PMCID: PMC10118265 DOI: 10.1093/braincomms/fcad054] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/28/2022] [Accepted: 03/02/2023] [Indexed: 03/09/2023] Open
Abstract
Type 2 diabetes and dementia are associated, but it is unclear whether the two diseases have common genetic risk markers that could partly explain their association. It is also unclear whether the association between the two diseases is of a causal nature. Furthermore, few studies on diabetes and dementia have validated dementia end-points with high diagnostic precision. We tested associations between polygenic risk scores for type 2 diabetes, fasting glucose, fasting insulin and haemoglobin A1c as exposure variables and dementia as outcome variables in 29 139 adults (mean age 55) followed for 20-23 years. Dementia diagnoses were validated by physicians through data from medical records, neuroimaging and biomarkers in cerebrospinal fluid. The dementia end-points included all-cause dementia, mixed dementia, Alzheimer's disease and vascular dementia. We also tested causal associations between type 2 diabetes and dementia through two-sample Mendelian randomization analyses. Seven different polygenic risk scores including single-nucleotide polymorphisms with different significance thresholds for type 2 diabetes were tested. A polygenic risk score including 4891 single-nucleotide polymorphisms with a P-value of <5e-04 showed the strongest association with different outcomes, including all-cause dementia (hazard ratio 1.11; Bonferroni corrected P = 3.6e-03), mixed dementia (hazard ratio 1.18; Bonferroni corrected P = 3.3e-04) and vascular dementia cases (hazard ratio 1.28; Bonferroni corrected P = 9.6e-05). The associations were stronger for non-carriers of the Alzheimer's disease risk gene APOE ε4. There was, however, no significant association between polygenic risk scores for type 2 diabetes and Alzheimer's disease. Furthermore, two-sample Mendelian randomization analyses could not confirm a causal link between genetic risk markers of type 2 diabetes and dementia outcomes. In conclusion, polygenic risk of type 2 diabetes is associated with an increased risk of dementia, in particular vascular dementia. The findings imply that certain people with type 2 diabetes may, due to their genetic background, be more prone to develop diabetes-associated dementia. This knowledge could in the future lead to targeted preventive strategies in clinical practice.
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Affiliation(s)
- Elin Dybjer
- Department of Clinical Sciences Malmö, Lund University, Jan Waldenströms gata 35, SE-21428 Malmö, Sweden
| | - Atul Kumar
- MultiPark: Multidisciplinary Research focused on Parkinson's disease, Lund University, Box 117, SE-22100 Lund, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Skånes universitetssjukhus, VE Minnessjukdomar, SE-20502 Malmö, Sweden
| | - Katarina Nägga
- Department of Clinical Sciences Malmö, Lund University, Jan Waldenströms gata 35, SE-21428 Malmö, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Skånes universitetssjukhus, VE Minnessjukdomar, SE-20502 Malmö, Sweden
- Department of Acute Internal Medicine and Geriatrics, Linköping University, SE-58183 Linköping, Sweden
| | - Gunnar Engström
- Department of Clinical Sciences Malmö, Lund University, Jan Waldenströms gata 35, SE-21428 Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- MultiPark: Multidisciplinary Research focused on Parkinson's disease, Lund University, Box 117, SE-22100 Lund, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Skånes universitetssjukhus, VE Minnessjukdomar, SE-20502 Malmö, Sweden
- Brain Injury After Cardiac Arrest Research Group, Lund University, Box 117, SE-22100 Lund, Sweden
- WCMM – Wallenberg Centre for Molecular Medicine, Lund University, Sölvegatan 19, BMC D11, SE-22184 Lund, Sweden
| | - Peter M Nilsson
- Department of Clinical Sciences Malmö, Lund University, Jan Waldenströms gata 35, SE-21428 Malmö, Sweden
- EpiHealth: Epidemiology for Health Strategic Research Area, Lund University, SUS Malmö, Jan Waldenströms gata 35, SE-20502 Malmö, Sweden
| | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University, Jan Waldenströms gata 35, SE-21428 Malmö, Sweden
- EpiHealth: Epidemiology for Health Strategic Research Area, Lund University, SUS Malmö, Jan Waldenströms gata 35, SE-20502 Malmö, Sweden
- Department of Emergency and Internal Medicine, Skåne University Hospital, SE-20502 Malmö, Sweden
- EXODIAB: Excellence in Diabetes Research in Sweden, Lund University, Box 117, SE-22100 Lund, Sweden
| | - Oskar Hansson
- MultiPark: Multidisciplinary Research focused on Parkinson's disease, Lund University, Box 117, SE-22100 Lund, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Skånes universitetssjukhus, VE Minnessjukdomar, SE-20502 Malmö, Sweden
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329
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Azarova I, Polonikov A, Klyosova E. Molecular Genetics of Abnormal Redox Homeostasis in Type 2 Diabetes Mellitus. Int J Mol Sci 2023; 24:4738. [PMID: 36902173 PMCID: PMC10003739 DOI: 10.3390/ijms24054738] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 03/05/2023] Open
Abstract
Numerous studies have shown that oxidative stress resulting from an imbalance between the production of free radicals and their neutralization by antioxidant enzymes is one of the major pathological disorders underlying the development and progression of type 2 diabetes (T2D). The present review summarizes the current state of the art advances in understanding the role of abnormal redox homeostasis in the molecular mechanisms of T2D and provides comprehensive information on the characteristics and biological functions of antioxidant and oxidative enzymes, as well as discusses genetic studies conducted so far in order to investigate the contribution of polymorphisms in genes encoding redox state-regulating enzymes to the disease pathogenesis.
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Affiliation(s)
- Iuliia Azarova
- Department of Biological Chemistry, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
| | - Alexey Polonikov
- Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
| | - Elena Klyosova
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
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330
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Saadh MJ, Pal RS, Arias-Gonzáles JL, Orosco Gavilán JC, JC D, Mohany M, Al-Rejaie SS, Bahrami A, Kadham MJ, Amin AH, Georgia H. A Mendelian Randomization Analysis Investigates Causal Associations between Inflammatory Bowel Diseases and Variable Risk Factors. Nutrients 2023; 15:1202. [PMID: 36904201 PMCID: PMC10005338 DOI: 10.3390/nu15051202] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 02/25/2023] [Accepted: 02/26/2023] [Indexed: 03/06/2023] Open
Abstract
The question of whether variable risk factors and various nutrients are causally related to inflammatory bowel diseases (IBDs) has remained unanswered so far. Thus, this study investigated whether genetically predicted risk factors and nutrients play a function in the occurrence of inflammatory bowel diseases, including ulcerative colitis (UC), non-infective colitis (NIC), and Crohn's disease (CD), using Mendelian randomization (MR) analysis. Utilizing the data of genome-wide association studies (GWASs) with 37 exposure factors, we ran Mendelian randomization analyses based on up to 458,109 participants. Univariable and multivariable MR analyses were conducted to determine causal risk factors for IBD diseases. Genetic predisposition to smoking and appendectomy as well as vegetable and fruit intake, breastfeeding, n-3 PUFAs, n-6 PUFAs, vitamin D, total cholesterol, whole-body fat mass, and physical activity were related to the risk of UC (p < 0.05). The effect of lifestyle behaviors on UC was attenuated after correcting for appendectomy. Genetically driven smoking, alcohol consumption, appendectomy, tonsillectomy, blood calcium, tea intake, autoimmune diseases, type 2 diabetes, cesarean delivery, vitamin D deficiency, and antibiotic exposure increased the risk of CD (p < 0.05), while vegetable and fruit intake, breastfeeding, physical activity, blood zinc, and n-3 PUFAs decreased the risk of CD (p < 0.05). Appendectomy, antibiotics, physical activity, blood zinc, n-3 PUFAs, and vegetable fruit intake remained significant predictors in multivariable MR (p < 0.05). Besides smoking, breastfeeding, alcoholic drinks, vegetable and fruit intake, vitamin D, appendectomy, and n-3 PUFAs were associated with NIC (p < 0.05). Smoking, alcoholic drinks, vegetable and fruit intake, vitamin D, appendectomy, and n-3 PUFAs remained significant predictors in multivariable MR (p < 0.05). Our results provide new and comprehensive evidence demonstrating that there are approving causal effects of various risk factors on IBDs. These findings also supply some suggestions for the treatment and prevention of these diseases.
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Affiliation(s)
- Mohamed J. Saadh
- Faculty of Pharmacy, Middle East University, Amman 11831, Jordan;
- Applied Science Research Center, Applied Science Private University, Amman 11152, Jordan
| | - Rashmi Saxena Pal
- School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 144001, Punjab, India;
| | - José Luis Arias-Gonzáles
- Department of Social Sciences, Faculty of Social Studies, Pontifical University of Peru, San Miguel 15088, Peru;
| | | | - Darshan JC
- Department of Pharmacy Practice, Yenepoya Pharmacy College & Research Centre, Yenepoya Deemed to Be University, Mangalore 575018, Karnataka, India;
| | - Mohamed Mohany
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 55760, Riyadh 1145, Saudi Arabia; (M.M.); (S.S.A.-R.)
| | - Salim S. Al-Rejaie
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 55760, Riyadh 1145, Saudi Arabia; (M.M.); (S.S.A.-R.)
| | - Abolfazl Bahrami
- Biomedical Center for Systems Biology Science Munich, Ludwig Maximilians University, 80333 Munich, Germany
| | | | - Ali H. Amin
- Zoology Department, Faculty of Science, Mansoura University, Mansoura 35516, Egypt;
| | - Hrosti Georgia
- Institute of Immunology, Hannover Medical School, 30625 Hannover, Germany
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331
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 2306] [Impact Index Per Article: 1153.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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332
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Liu D, Gao X, Pan XF, Zhou T, Zhu C, Li F, Fan JG, Targher G, Zhao J. The hepato-ovarian axis: genetic evidence for a causal association between non-alcoholic fatty liver disease and polycystic ovary syndrome. BMC Med 2023; 21:62. [PMID: 36800955 PMCID: PMC9940436 DOI: 10.1186/s12916-023-02775-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 02/09/2023] [Indexed: 02/21/2023] Open
Abstract
BACKGROUND Recent studies found associations between non-alcoholic fatty liver disease (NAFLD) and polycystic ovary syndrome (PCOS), but the causal nature of this association is still uncertain. METHODS We performed a bidirectional two-sample Mendelian randomization (MR) analysis to test for the causal association between NAFLD and PCOS using data from a large-scale biopsy-confirmed NAFLD genome-wide association study (GWAS) (1483 cases and 17,781 controls) and PCOS GWAS (10,074 cases and 103,164 controls) in European ancestries. Data from glycemic-related traits GWAS (in up to 200,622 individuals) and sex hormones GWAS (in 189,473 women) in the UK Biobank (UKB) were used in the MR mediation analysis to assess potential mediating roles of these molecules in the causal pathway between NAFLD and PCOS. Replication analysis was conducted using two independent datasets from NAFLD and PCOS GWASs in the UKB and a meta-analysis of data from FinnGen and the Estonian Biobank, respectively. A linkage disequilibrium score regression was conducted to assess genetic correlations between NAFLD, PCOS, glycemic-related traits, and sex hormones using full summary statistics. RESULTS Individuals with higher genetic liability to NAFLD were more likely to develop PCOS (OR per one-unit log odds increase in NAFLD: 1.10, 95% CI: 1.02-1.18; P = 0.013). Indirect causal effects of NAFLD on PCOS via fasting insulin only (OR: 1.02, 95% CI: 1.01-1.03; P = 0.004) and further a suggestive indirect causal effect via fasting insulin in concert with androgen levels were revealed in MR mediation analyses. However, the conditional F statistics of NAFLD and fasting insulin were less than 10, suggesting likely weak instrument bias in the MVMR and MR mediation analyses. CONCLUSIONS Our study suggests that genetically predicted NAFLD was associated with a higher risk of developing PCOS but less evidence for vice versa. Fasting insulin and sex hormones might mediate the link between NAFLD and PCOS.
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Affiliation(s)
- Dong Liu
- Ministry of Education and Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No.1665, Kongjiang Road, Yangpu District, Shanghai, 200092, China
| | - Xue Gao
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Xiong-Fei Pan
- Ministry of Education Key Laboratory of Birth Defects and Related Diseases in Women and Children, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
- Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan, China
| | - Tao Zhou
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Cairong Zhu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fei Li
- Ministry of Education and Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No.1665, Kongjiang Road, Yangpu District, Shanghai, 200092, China
- Department of Developmental and Behavioral Pediatric & Child Primary Care, Brain and Behavioral Research Unit of Shanghai Institute for Pediatric Research, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Maternal and Child Health, School of Public Health, Shanghai Jiao Tong University, Shanghai, China
| | - Jian-Gao Fan
- Department of Gastroenterology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Lab of Pediatric Gastroenterology and Nutrition, Shanghai, China
| | - Giovanni Targher
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Verona, Verona, Italy
| | - Jian Zhao
- Ministry of Education and Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No.1665, Kongjiang Road, Yangpu District, Shanghai, 200092, China.
- Department of Maternal and Child Health, School of Public Health, Shanghai Jiao Tong University, Shanghai, China.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
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Shi Q, Wang Q, Wang Z, Lu J, Wang R. Systemic inflammatory regulators and proliferative diabetic retinopathy: A bidirectional Mendelian randomization study. Front Immunol 2023; 14:1088778. [PMID: 36845092 PMCID: PMC9950638 DOI: 10.3389/fimmu.2023.1088778] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 02/01/2023] [Indexed: 02/12/2023] Open
Abstract
Background Increasing evidence shows that systemic inflammation is an embedded mechanism of proliferative diabetic retinopathy (PDR). However, the specific systemic inflammatory factors involved in this process remained obscure. The study aimed to identify the upstream and downstream systemic regulators of PDR by using Mendelian randomization (MR) analyses. Methods We performed a bidirectional two-sample MR analysis implementing the results from genome-wide association studies for 41 serum cytokines from 8,293 Finnish individuals, and PDR from FinnGen consortium (2,025 cases vs. 284,826 controls) and eight cohorts of European ancestry (398 cases vs. 2,848 controls), respectively. The inverse-variance-weighted method was adopted as the main MR method, and four additional MR methods (MR-Egger, weighted-median, MR-pleiotropy residual sum and outlier (MR-PRESSO), and MR-Steiger filtering methods) were used for the sensitivity analyses. Results from FinnGen and eight cohorts were pooled into a meta-analysis. Results Our results showed that genetically predicted higher stem cell growth factor-β (SCGFb) and interleukin-8 were positively associated with an elevated risk of PDR, with a combined effect of one standard deviation (SD) increase in SCGFb and interleukin-8 causing 11.8% [95% confidence interval (CI): 0.6%, 24.2%]) and 21.4% [95% CI: 3.8%, 41.9%]) higher risk of PDR, respectively. In contrast, genetically predisposition to PDR showed a positive association with the increased levels of growth-regulated oncogene-α (GROa), stromal cell-derived factor-1 alpha (SDF1a), monocyte chemotactic protein-3 (MCP3), granulocyte colony-stimulating factor (GCSF), interleukin-12p70, and interleukin-2 receptor subunit alpha (IL-2ra). Conclusions Our MR study identified two upstream regulators and six downstream effectors of PDR, providing opportunities for new therapeutic exploitation of PDR onset. Nonetheless, these nominal associations of systemic inflammatory regulators and PDR require validation in larger cohorts.
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Affiliation(s)
- Qiqin Shi
- Department of Ophthalmology, Ningbo Hangzhou Bay Hospital, Ningbo, Zhejiang, China
| | - Qiangsheng Wang
- Department of Haematology, Ningbo Hangzhou Bay Hospital, Ningbo, Zhejiang, China
| | - Zhenqian Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Jiawen Lu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Ruobing Wang
- Department of Ophthalmology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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Cryo-EM structure supports a role of AQP7 as a junction protein. Nat Commun 2023; 14:600. [PMID: 36737436 PMCID: PMC9898259 DOI: 10.1038/s41467-023-36272-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 01/23/2023] [Indexed: 02/05/2023] Open
Abstract
Aquaglyceroporin 7 (AQP7) facilitates glycerol flux across the plasma membrane with a critical physiological role linked to metabolism, obesity, and associated diseases. Here, we present the single-particle cryo-EM structure of AQP7 determined at 2.55 Å resolution adopting two adhering tetramers, stabilized by extracellularly exposed loops, in a configuration like that of the well-characterized interaction of AQP0 tetramers. The central pore, in-between the four monomers, displays well-defined densities restricted by two leucine filters. Gas chromatography mass spectrometry (GC/MS) results show that the AQP7 sample contains glycerol 3-phosphate (Gro3P), which is compatible with the identified features in the central pore. AQP7 is shown to be highly expressed in human pancreatic α- and β- cells suggesting that the identified AQP7 octamer assembly, in addition to its function as glycerol channel, may serve as junction proteins within the endocrine pancreas.
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335
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Broadaway KA, Yin X, Williamson A, Parsons VA, Wilson EP, Moxley AH, Vadlamudi S, Varshney A, Jackson AU, Ahuja V, Bornstein SR, Corbin LJ, Delgado GE, Dwivedi OP, Fernandes Silva L, Frayling TM, Grallert H, Gustafsson S, Hakaste L, Hammar U, Herder C, Herrmann S, Højlund K, Hughes DA, Kleber ME, Lindgren CM, Liu CT, Luan J, Malmberg A, Moissl AP, Morris AP, Perakakis N, Peters A, Petrie JR, Roden M, Schwarz PEH, Sharma S, Silveira A, Strawbridge RJ, Tuomi T, Wood AR, Wu P, Zethelius B, Baldassarre D, Eriksson JG, Fall T, Florez JC, Fritsche A, Gigante B, Hamsten A, Kajantie E, Laakso M, Lahti J, Lawlor DA, Lind L, März W, Meigs JB, Sundström J, Timpson NJ, Wagner R, Walker M, Wareham NJ, Watkins H, Barroso I, O'Rahilly S, Grarup N, Parker SC, Boehnke M, Langenberg C, Wheeler E, Mohlke KL. Loci for insulin processing and secretion provide insight into type 2 diabetes risk. Am J Hum Genet 2023; 110:284-299. [PMID: 36693378 PMCID: PMC9943750 DOI: 10.1016/j.ajhg.2023.01.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 01/03/2023] [Indexed: 01/25/2023] Open
Abstract
Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p value < 5 × 10-8), which validated 12 previously reported loci for proinsulin and ten additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher rather than lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait locus (eQTL) data, suggesting candidate genes, including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms that may predispose one to disease.
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Affiliation(s)
- K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Xianyong Yin
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA; Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Alice Williamson
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Victoria A Parsons
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Emma P Wilson
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Anne H Moxley
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | | | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Anne U Jackson
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Vasudha Ahuja
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Stefan R Bornstein
- Department of Internal Medicine, Metabolic and Vascular Medicine, MedicCal Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Laura J Corbin
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Om P Dwivedi
- University of Helsinki, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland
| | | | | | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Stefan Gustafsson
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Liisa Hakaste
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Ulf Hammar
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Christian Herder
- German Center for Diabetes Research, Neuherberg, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sandra Herrmann
- Department of Internal Medicine, Prevention and Care of Diabetes, Medical Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany
| | | | - David A Hughes
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus E Kleber
- Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany; SYNLAB MVZ Humangenetik Mannheim, Mannheim, BW, Germany
| | - Cecilia M Lindgren
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Nuffield Department of Population Health, University of Oxford, Oxford, UK; Wellcome Trust Centre Human Genetics, University of Oxford, Oxford, UK; Broad Institute, Cambridge, MA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Anni Malmberg
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Angela P Moissl
- Institute of Nutritional Sciences, Friedrich-Schiller-University, Jena, Germany; Competence Cluster for Nutrition and Cardiovascular Health, Halle-Jena-Leipzig, Germany; Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Nikolaos Perakakis
- Department of Internal Medicine, Metabolic and Vascular Medicine, MedicCal Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - John R Petrie
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Peter E H Schwarz
- Department of Internal Medicine, Prevention and Care of Diabetes, Medical Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Sapna Sharma
- German Center for Diabetes Research, Neuherberg, Germany; Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Chair of Food Chemistry and Molecular Sensory Science, Technische Universität München, Freising, Germany
| | - Angela Silveira
- Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden; Oxford Biomedical Research Centre, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Rona J Strawbridge
- Institute of Health and Wellbeing, Mental Health and Wellbeing, University of Glasgow, Glasgow, UK; Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland; Abdominal Center, Endocrinology, Helsinki University Hospital, Helsinki, Finland
| | - Andrew R Wood
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Björn Zethelius
- Department of Geriatrics, Uppsala University, Uppsala, Sweden
| | - Damiano Baldassarre
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy; Cardiovascular Prevention Area, Centro Cardiologico Monzino I.R.C.C.S., Milan, Italy
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Folkhälsan Research Centre, Helsinki, Finland; Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jose C Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Andreas Fritsche
- Department of Internal Medicine, Diabetology, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Bruna Gigante
- Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Anders Hamsten
- Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Eero Kajantie
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland; PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland; Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway; Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Deborah A Lawlor
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Lars Lind
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Winfried März
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim, BW, Germany; Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany
| | - James B Meigs
- Department of Medicine, Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Johan Sundström
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Robert Wagner
- Department of Internal Medicine, Diabetology, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Mark Walker
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; Health Data Research UK, Gibbs Building, London, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Inês Barroso
- Exeter Centre of Excellence for Diabetes Research, Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Stephen O'Rahilly
- MRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stephen Cj Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Michael Boehnke
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA; Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany; Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
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Juan-Mateu J, Bajew S, Miret-Cuesta M, Íñiguez LP, Lopez-Pascual A, Bonnal S, Atla G, Bonàs-Guarch S, Ferrer J, Valcárcel J, Irimia M. Pancreatic microexons regulate islet function and glucose homeostasis. Nat Metab 2023; 5:219-236. [PMID: 36759540 DOI: 10.1038/s42255-022-00734-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 12/21/2022] [Indexed: 02/11/2023]
Abstract
Pancreatic islets control glucose homeostasis by the balanced secretion of insulin and other hormones, and their abnormal function causes diabetes or hypoglycaemia. Here we uncover a conserved programme of alternative microexons included in mRNAs of islet cells, particularly in genes involved in vesicle transport and exocytosis. Islet microexons (IsletMICs) are regulated by the RNA binding protein SRRM3 and represent a subset of the larger neural programme that are particularly sensitive to SRRM3 levels. Both SRRM3 and IsletMICs are induced by elevated glucose levels, and depletion of SRRM3 in human and rat beta cell lines and mouse islets, or repression of particular IsletMICs using antisense oligonucleotides, leads to inappropriate insulin secretion. Consistently, mice harbouring mutations in Srrm3 display defects in islet cell identity and function, leading to hyperinsulinaemic hypoglycaemia. Importantly, human genetic variants that influence SRRM3 expression and IsletMIC inclusion in islets are associated with fasting glucose variation and type 2 diabetes risk. Taken together, our data identify a conserved microexon programme that regulates glucose homeostasis.
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Affiliation(s)
- Jonàs Juan-Mateu
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
| | - Simon Bajew
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Marta Miret-Cuesta
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Luis P Íñiguez
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Amaya Lopez-Pascual
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Sophie Bonnal
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Goutham Atla
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Sílvia Bonàs-Guarch
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Jorge Ferrer
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Juan Valcárcel
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
- ICREA, Barcelona, Spain.
| | - Manuel Irimia
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
- ICREA, Barcelona, Spain.
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337
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Garfield V, Salzmann A, Burgess S, Chaturvedi N. A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach. Diabetes 2023; 72:175-183. [PMID: 36669000 PMCID: PMC7614590 DOI: 10.2337/db22-0110] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 10/24/2022] [Indexed: 01/21/2023]
Abstract
In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.
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Affiliation(s)
- Victoria Garfield
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
| | - Antoine Salzmann
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, MRC Biostatistics Unit, University of Cambridge, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
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338
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Cook TW, Wilstermann AM, Mitchell JT, Arnold NE, Rajasekaran S, Bupp CP, Prokop JW. Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics. Biomolecules 2023; 13:257. [PMID: 36830626 PMCID: PMC9953665 DOI: 10.3390/biom13020257] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/20/2023] [Accepted: 01/26/2023] [Indexed: 01/31/2023] Open
Abstract
Insulin is amongst the human genome's most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (INS) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The INS gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the INS transcripts that might influence the readthrough fusion transcript INS-IGF2. This INS-IGF2 transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS-IGF2 results in a loss of the stop codon. INS transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3'UTR alternatively spliced INS transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements.
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Affiliation(s)
- Taylor W. Cook
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | | | - Jackson T. Mitchell
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | - Nicholas E. Arnold
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | - Surender Rajasekaran
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Office of Research, Corewell Health, Grand Rapids, MI 49503, USA
| | - Caleb P. Bupp
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Division of Medical Genetics, Corewell Health, Grand Rapids, MI 49503, USA
| | - Jeremy W. Prokop
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
- Office of Research, Corewell Health, Grand Rapids, MI 49503, USA
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Qiao Z, Sidorenko J, Revez JA, Xue A, Lu X, Pärna K, Snieder H, Visscher PM, Wray NR, Yengo L. Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose. Nat Commun 2023; 14:451. [PMID: 36707517 PMCID: PMC9883484 DOI: 10.1038/s41467-023-36013-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 01/12/2023] [Indexed: 01/29/2023] Open
Abstract
The genetic regulation of post-prandial glucose levels is poorly understood. Here, we characterise the genetic architecture of blood glucose variably measured within 0 and 24 h of fasting in 368,000 European ancestry participants of the UK Biobank. We found a near-linear increase in the heritability of non-fasting glucose levels over time, which plateaus to its fasting state value after 5 h post meal (h2 = 11%; standard error: 1%). The genetic correlation between different fasting times is > 0.77, suggesting that the genetic control of glucose is largely constant across fasting durations. Accounting for heritability differences between fasting times leads to a ~16% improvement in the discovery of genetic variants associated with glucose. Newly detected variants improve the prediction of fasting glucose and type 2 diabetes in independent samples. Finally, we meta-analysed summary statistics from genome-wide association studies of random and fasting glucose (N = 518,615) and identified 156 independent SNPs explaining 3% of fasting glucose variance. Altogether, our study demonstrates the utility of random glucose measures to improve the discovery of genetic variants associated with glucose homeostasis, even in fasting conditions.
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Affiliation(s)
- Zhen Qiao
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Julia Sidorenko
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Joana A Revez
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Angli Xue
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Xueling Lu
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Laboratory of Environmental Medicine and Developmental Toxicology, Shantou University Medical College, Guangdong, China
| | - Katri Pärna
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
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340
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Pei Y, Risal S, Jiang H, Lu H, Lindgren E, Stener-Victorin E, Deng Q. Transcriptomic survey of key reproductive and metabolic tissues in mouse models of polycystic ovary syndrome. Commun Biol 2023; 6:69. [PMID: 36653487 PMCID: PMC9849269 DOI: 10.1038/s42003-022-04362-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 12/09/2022] [Indexed: 01/19/2023] Open
Abstract
Excessive androgen production and obesity are key to polycystic ovary syndrome (PCOS) pathogenesis. Prenatal androgenized (PNA), peripubertal androgenized, and overexpression of nerve growth factor in theca cells (17NF) are commonly used PCOS-like mouse models and diet-induced maternal obesity model is often included for comparsion. To reveal the molecular features of these models, we have performed transcriptome survey of the hypothalamus, adipose tissue, ovary and metaphase II (MII) oocytes. The largest number of differentially expressed genes (DEGs) is found in the ovaries of 17NF and in the adipose tissues of peripubertal androgenized models. In contrast, hypothalamus is most affected in PNA and maternal obesity models suggesting fetal programming effects. The Ms4a6e gene, membrane-spanning 4-domains subfamily A member 6E, a DEG identified in the adipose tissue in all mouse models is also differently expressed in adipose tissue of women with PCOS, highlighting a conserved disease function. Our comprehensive transcriptomic profiling of key target tissues involved in PCOS pathology highlights the effects of developmental windows for androgen exposure and maternal obesity, and provides unique resource to investigate molecular mechanisms underlying PCOS pathogenesis.
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Affiliation(s)
- Yu Pei
- grid.4714.60000 0004 1937 0626Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Center for molecular medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Sanjiv Risal
- grid.4714.60000 0004 1937 0626Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Hong Jiang
- grid.4714.60000 0004 1937 0626Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Haojiang Lu
- grid.4714.60000 0004 1937 0626Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Eva Lindgren
- grid.4714.60000 0004 1937 0626Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Elisabet Stener-Victorin
- grid.4714.60000 0004 1937 0626Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Qiaolin Deng
- grid.4714.60000 0004 1937 0626Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Center for molecular medicine, Karolinska University Hospital, Stockholm, Sweden
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341
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Wang K, Yang F, Liu X, Lin X, Yin H, Tang Q, Jiang L, Yao K. Appraising the Effects of Metabolic Traits on the Risk of Glaucoma: A Mendelian Randomization Study. Metabolites 2023; 13:109. [PMID: 36677034 PMCID: PMC9867384 DOI: 10.3390/metabo13010109] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/24/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Metabolic traits are associated with the risk of developing glaucoma in observational studies. To assess whether theses associations reflect causality, we conducted a Mendelian randomization (MR) study. Our study included up to 20,906 glaucoma cases and 438,188 controls. Genetic instruments associated with the concerned 11 exposures at the genome-wide significance level were selected from corresponding genome-wide association studies. Summary-level data for glaucoma were obtained from the UK Biobank, the GERA study, and the FinnGen consortium. Univariable and multivariable MR analyses were conducted separately in two populations. Our results showed that higher genetic liability to type 2 diabetes (T2D) was causally and independently associated with an increased risk of glaucoma (odds ratio [OR], 1.11; 95% confidence interval [CI], 1.06-1.16; p = 4.4 × 10-6). The association for T2D persisted after multivariable adjustment. In addition, higher genetically predicted systolic blood pressure (SBP), fasting glucose (FG), and HbA1c, were also suggestively associated with glaucoma risk. The OR was 1.08 (95% CI, 1.01-1.16; p = 0.035) for SBP, 1.24 (95% CI, 1.05-1.47; p = 0.011) for FG, and 1.28 (95% CI, 1.01-1.61; p = 0.039) for HbA1c. No evidence was observed to support the causal effects of body mass index and blood lipids for glaucoma. This study suggests a causal role for diabetes, as well as possible roles for higher SBP, FG, and HbA1c in the development of glaucoma. Further validation is needed to assess the potential of these risk factors as pharmacological targets for glaucoma prevention.
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Affiliation(s)
- Kai Wang
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
| | - Fangkun Yang
- Department of Cardiology, Ningbo First Hospital, Ningbo 315010, China
| | - Xin Liu
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
| | - Xueqi Lin
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
| | - Houfa Yin
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
| | - Qiaomei Tang
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
| | - Li Jiang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou 311121, China
| | - Ke Yao
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
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342
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Jasper EA, Hellwege JN, Piekos JA, Jones SH, Hartmann KE, Mautz B, Aronoff DM, Edwards TL, Edwards DRV. Genetically-predicted placental gene expression is associated with birthweight and adult body mass index. Sci Rep 2023; 13:322. [PMID: 36609580 PMCID: PMC9822919 DOI: 10.1038/s41598-022-26572-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 12/16/2022] [Indexed: 01/09/2023] Open
Abstract
The placenta is critical to human growth and development and has been implicated in health outcomes. Understanding the mechanisms through which the placenta influences perinatal and later-life outcomes requires further investigation. We evaluated the relationships between birthweight and adult body mass index (BMI) and genetically-predicted gene expression in human placenta. Birthweight genome-wide association summary statistics were obtained from the Early Growth Genetics Consortium (N = 298,142). Adult BMI summary statistics were obtained from the GIANT consortium (N = 681,275). We used S-PrediXcan to evaluate associations between the outcomes and predicted gene expression in placental tissue and, to identify genes where placental expression was exclusively associated with the outcomes, compared to 48 other tissues (GTEx v7). We identified 24 genes where predicted placental expression was significantly associated with birthweight, 15 of which were not associated with birthweight in any other tissue. One of these genes has been previously linked to birthweight. Analyses identified 182 genes where placental expression was associated with adult BMI, 110 were not associated with BMI in any other tissue. Eleven genes that had placental gene expression levels exclusively associated with BMI have been previously associated with BMI. Expression of a single gene, PAX4, was associated with both outcomes exclusively in the placenta. Inter-individual variation of gene expression in placental tissue may contribute to observed variation in birthweight and adult BMI, supporting developmental origins hypothesis.
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Affiliation(s)
- Elizabeth A Jasper
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA.
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Jacklyn N Hellwege
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Epidemiology Center, Vanderbilt University, Nashville, TN, USA
| | | | - Sarah H Jones
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Katherine E Hartmann
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Epidemiology Center, Vanderbilt University, Nashville, TN, USA
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Brian Mautz
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Epidemiology Center, Vanderbilt University, Nashville, TN, USA
- Population Analytics, Analytics and Insights, Data Sciences, Janssen Research & Development, Spring House, PA, USA
| | - David M Aronoff
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Todd L Edwards
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Digna R Velez Edwards
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA.
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
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343
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Kharb S, Joshi A. Multi-omics and machine learning for the prevention and management of female reproductive health. Front Endocrinol (Lausanne) 2023; 14:1081667. [PMID: 36909346 PMCID: PMC9996332 DOI: 10.3389/fendo.2023.1081667] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 02/06/2023] [Indexed: 02/25/2023] Open
Abstract
Females typically carry most of the burden of reproduction in mammals. In humans, this burden is exacerbated further, as the evolutionary advantage of a large and complex human brain came at a great cost of women's reproductive health. Pregnancy thus became a highly demanding phase in a woman's life cycle both physically and emotionally and therefore needs monitoring to assure an optimal outcome. Moreover, an increasing societal trend towards reproductive complications partly due to the increasing maternal age and global obesity pandemic demands closer monitoring of female reproductive health. This review first provides an overview of female reproductive biology and further explores utilization of large-scale data analysis and -omics techniques (genomics, transcriptomics, proteomics, and metabolomics) towards diagnosis, prognosis, and management of female reproductive disorders. In addition, we explore machine learning approaches for predictive models towards prevention and management. Furthermore, mobile apps and wearable devices provide a promise of continuous monitoring of health. These complementary technologies can be combined towards monitoring female (fertility-related) health and detection of any early complications to provide intervention solutions. In summary, technological advances (e.g., omics and wearables) have shown a promise towards diagnosis, prognosis, and management of female reproductive disorders. Systematic integration of these technologies is needed urgently in female reproductive healthcare to be further implemented in the national healthcare systems for societal benefit.
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Affiliation(s)
- Simmi Kharb
- Department of Biochemistry, Postgraduate Institute of Medical Sciences, Rohtak, Haryana, India
- *Correspondence: Simmi Kharb, ; Anagha Joshi,
| | - Anagha Joshi
- Computational Biology Unit (CBU), Department of Clinical Science, University of Bergen, Bergen, Norway
- *Correspondence: Simmi Kharb, ; Anagha Joshi,
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Hong-Le T, Crouse WL, Keele GR, Holl K, Seshie O, Tschannen M, Craddock A, Das SK, Szalanczy AM, McDonald B, Grzybowski M, Klotz J, Sharma NK, Geurts AM, Key CCC, Hawkins G, Valdar W, Mott R, Solberg Woods LC. Genetic Mapping of Multiple Traits Identifies Novel Genes for Adiposity, Lipids, and Insulin Secretory Capacity in Outbred Rats. Diabetes 2023; 72:135-148. [PMID: 36219827 PMCID: PMC9797320 DOI: 10.2337/db22-0252] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 10/04/2022] [Indexed: 01/21/2023]
Abstract
Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity.
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Affiliation(s)
- Thu Hong-Le
- Genetics Institute, University College London, London, U.K
| | - Wesley L. Crouse
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | - Katie Holl
- Medical College of Wisconsin, Milwaukee, WI
| | - Osborne Seshie
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | | | - Ann Craddock
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Swapan K. Das
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Alexandria M. Szalanczy
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Bailey McDonald
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | | | | | - Neeraj K. Sharma
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | | | - Chia-Chi Chuang Key
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Gregory Hawkins
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC
| | - William Valdar
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Richard Mott
- Genetics Institute, University College London, London, U.K
| | - Leah C. Solberg Woods
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
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345
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Wang Z, Zhu M, Huang Y, Cao J, Xiong Z. High blood pressure mediated the effect of fasting insulin level on nonalcoholic fatty liver disease risk: A Mendelian randomization study. Digit Health 2023; 9:20552076231216682. [PMID: 38025107 PMCID: PMC10666686 DOI: 10.1177/20552076231216682] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2023] [Indexed: 12/01/2023] Open
Abstract
Objective The interactions between fasting insulin levels, high blood pressure and nonalcoholic fatty liver disease (NAFLD) are still unclear. We examined the causal mechanisms between these three cardiometabolic traits using Mendelian randomization (MR) approach by utilizing genetic instruments. Methods Three different genome-wide association studies resources of European ancestry were utilized for the present study. Two-sample MRs were used to assess causal effects between fasting insulin levels, high blood pressure and NAFLD. Multivariate MR was used to calculate the mediating effect. The inverse variance-weighted method was used as the main analysis method. Results Our study confirmed a causal effect of fasting insulin levels (IVW-OR = 9.54, P = 0.001) and high blood pressure (IVW-OR = 3.926, P = 0.005) on NAFLD risk. And fasting insulin level was positively casually associated with high blood pressure risk (IVW-OR = 1.170, P < 0.001). However, the impact of high blood pressure on fasting insulin levels was still uncertain because of the presence of horizontal pleiotropy. Reverse MR showed NAFLD had a positive correlation with fasting insulin levels (IVW-OR = 1.010, P < 0.001) and a negative causal effect on high blood pressure risk (IVW-OR = 0.997, P = 0.037). Combined the multivariate MR result revealed high blood pressure partially mediated the contribution of fasting insulin level to NAFLD risk (proportion mediated: 9.091%). Conclusions Our study suggests there is a bidirectional causal relationship between fasting insulin levels and NAFLD. High blood pressure seems to play a mediating role in the development of NAFLD caused by changes in fasting insulin levels. However, it is uncertain whether high blood pressure is a mediator between NAFLD and the risk of fasting insulin level.
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Affiliation(s)
- Ziwen Wang
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Mengpei Zhu
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yumei Huang
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiali Cao
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhifan Xiong
- Department of Gastroenterology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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346
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Nguyen A, Khafagy R, Hashemy H, Kuo KHM, Roshandel D, Paterson AD, Dash S. Investigating the association between fasting insulin, erythrocytosis and HbA1c through Mendelian randomization and observational analyses. Front Endocrinol (Lausanne) 2023; 14:1146099. [PMID: 37008938 PMCID: PMC10064082 DOI: 10.3389/fendo.2023.1146099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 02/28/2023] [Indexed: 03/19/2023] Open
Abstract
BACKGROUND Insulin resistance (IR) with associated compensatory hyperinsulinemia (HI) are early abnormalities in the etiology of prediabetes (preT2D) and type 2 diabetes (T2D). IR and HI also associate with increased erythrocytosis. Hemoglobin A1c (HbA1c) is commonly used to diagnose and monitor preT2D and T2D, but can be influenced by erythrocytosis independent of glycemia. METHODS We undertook bidirectional Mendelian randomization (MR) in individuals of European ancestry to investigate potential causal associations between increased fasting insulin adjusted for BMI (FI), erythrocytosis and its non-glycemic impact on HbA1c. We investigated the association between the triglyceride-glucose index (TGI), a surrogate measure of IR and HI, and glycation gap (difference between measured HbA1c and predicted HbA1c derived from linear regression of fasting glucose) in people with normoglycemia and preT2D. RESULTS Inverse variance weighted MR (IVWMR) suggested that increased FI increases hemoglobin (Hb, b=0.54 ± 0.09, p=2.7 x 10-10), red cell count (RCC, b=0.54 ± 0.12, p=5.38x10-6) and reticulocyte (RETIC, b=0.70 ± 0.15, p=2.18x10-6). Multivariable MR indicated that increased FI did not impact HbA1c (b=0.23 ± 0.16, p=0.162) but reduced HbA1c after adjustment for T2D (b=0.31 ± 0.13, p=0.016). Increased Hb (b=0.03 ± 0.01, p=0.02), RCC (b=0.02 ± 0.01, p=0.04) and RETIC (b=0.03 ± 0.01, p=0.002) might modestly increase FI. In the observational cohort, increased TGI associated with decreased glycation gap, (i.e., measured HbA1c was lower than expected based on fasting glucose, (b=-0.09 ± 0.009, p<0.0001)) in people with preT2D but not in those with normoglycemia (b=0.02 ± 0.007, p<0.0001). CONCLUSIONS MR suggests increased FI increases erythrocytosis and might potentially decrease HbA1c by non-glycemic effects. Increased TGI, a surrogate measure of increased FI, associates with lower-than-expected HbA1c in people with preT2D. These findings merit confirmatory studies to evaluate their clinical significance.
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Affiliation(s)
- Anthony Nguyen
- Department of Medicine, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Rana Khafagy
- Department of Medicine, University Health Network, University of Toronto, Toronto, ON, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, Canada
- Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Habiba Hashemy
- Department of Medicine, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Kevin H. M. Kuo
- Division of Medical Oncology and Haematology, Department of Medicine, University Health Network, Toronto, ON, Canada
- Division of Haematology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Delnaz Roshandel
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, Canada
| | - Andrew D. Paterson
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, Canada
- Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Satya Dash
- Department of Medicine, University Health Network, University of Toronto, Toronto, ON, Canada
- *Correspondence: Satya Dash,
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347
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Zhao X, Ding R, Su C, Yue R. Sleep traits, fat accumulation, and glycemic traits in relation to gastroesophageal reflux disease: A Mendelian randomization study. Front Nutr 2023; 10:1106769. [PMID: 36895273 PMCID: PMC9988956 DOI: 10.3389/fnut.2023.1106769] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 02/02/2023] [Indexed: 02/25/2023] Open
Abstract
Background Sleep traits, fat accumulation, and glycemic traits are associated with gastroesophageal reflux disease (GERD) in observational studies. However, whether their associations are causal remains unknown. We performed a Mendelian randomization (MR) study to determine these causal relationships. Methods Independent genetic variants associated with insomnia, sleep duration, short sleep duration, body fat percentage, visceral adipose tissue (VAT) mass, type 2 diabetes, fasting glucose, and fasting insulin at the genome-wide significance level were selected as instrumental variables. Summary-level data for GERD were derived from a genome-wide association meta-analysis including 78,707 cases and 288,734 controls of European descent. Inverse variance weighted (IVW) was used for the main analysis, with weighted median and MR-Egger as complements to IVW. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis to estimate the stability of the results. Results The MR study showed the causal relationships of genetically predicted insomnia (odds ratio [OR] = 1.306, 95% confidence interval [CI] 1.261 to 1.352; p = 2.24 × 10-51), short sleep duration (OR = 1.304, 95% CI: 1.147 to 1.483, p = 4.83 × 10-5), body fat percentage (OR = 1.793, 95% CI 1.496 to 2.149; p = 2.68 × 10-10), and visceral adipose tissue (OR = 2.090, 95% CI 1.963 to 2.225; p = 4.42 × 10-117) with the risk of GERD. There was little evidence for causal associations between genetically predicted glycemic traits and GERD. In multivariable analyses, genetically predicted VAT accumulation, insomnia, and decreased sleep duration were associated with an increased risk of GERD. Conclusion This study suggests the possible roles of insomnia, short sleep, body fat percentage, and visceral adiposity in the development of GERD.
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Affiliation(s)
- Xiaoyan Zhao
- Clinical Medical School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.,Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Rui Ding
- Clinical Medical School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Chengguo Su
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Rensong Yue
- Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Li J, Yang M, Luo P, Wang G, Dong B, Xu P. Type 2 diabetes and glycemic traits are not causal factors of delirium: A two-sample mendelian randomization analysis. Front Genet 2023; 14:1087878. [PMID: 36896238 PMCID: PMC9988945 DOI: 10.3389/fgene.2023.1087878] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/20/2023] [Indexed: 02/23/2023] Open
Abstract
This study aims to explore the genetic causal association between type 2 diabetes (T2D) and glycemic traits (fasting glucose [FG], fasting insulin [FI], and glycated hemoglobin [HbA1c]) on delirium using Mendelian randomization (MR). Genome-wide association studies (GWAS) summary data for T2D and glycemic traits were obtained from the IEU OpenGWAS database. GWAS summary data for delirium were obtained from the FinnGen Consortium. All the participants were of European ancestry. In addition, we used T2D, FG, FI, and HbA1c as exposures and delirium as outcomes. A random-effects variance-weighted model (IVW), MR Egger, weighted median, simple mode, and weighted mode were used to perform MR analysis. In addition, MR-IVW and MR-Egger analyses were used to detect heterogeneity in the MR results. Horizontal pleiotropy was detected using MR-Egger regression and MR pleiotropy residual sum and outliers (MR-PRESSO). MR-PRESSO was also used to assess outlier single nucleotide polymorphisms (SNPs). The "leave one out" analysis was used to investigate whether the MR analysis results were influenced by a single SNP and evaluate the robustness of the results. In this study, we conducted a two-sample MR analysis, and there was no evidence of a genetic causal association between T2D and glycemic traits (T2D, FG, FI, and HbA1c) on delirium (all p > 0.05). The MR-IVW and MR-Egger tests showed no heterogeneity in our MR results (all p values >0.05). In addition, The MR-Egger and MR-PRESSO tests showed no horizontal pleiotropy in our MR results (all p > 0.05). The MR-PRESSO results also showed that there were no outliers during the MR analysis. In addition, the "leave one out" test did not find that the SNPs included in the analysis could affect the stability of the MR results. Therefore, our study did not support the causal effects of T2D and glycemic traits (FG, FI, and HbA1c) on delirium risk.
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Affiliation(s)
- Jing Li
- Department of Anesthesiology, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Mingyi Yang
- Department of Joint Surgery, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Pan Luo
- Department of Joint Surgery, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Gang Wang
- Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Buhuai Dong
- Department of Anesthesiology, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Peng Xu
- Department of Joint Surgery, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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He Q, Wang W, Li H, Xiong Y, Tao C, Ma L, You C. Genetic Insights into the Risk of Metabolic Syndrome and Its Components on Dementia: A Mendelian Randomization. J Alzheimers Dis 2023; 96:725-743. [PMID: 37840498 PMCID: PMC10657705 DOI: 10.3233/jad-230623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/04/2023] [Indexed: 10/17/2023]
Abstract
BACKGROUND The role of metabolic syndrome (MetS) on dementia is disputed. OBJECTIVE We conducted a Mendelian randomization to clarify whether the genetically predicted MetS and its components are casually associated with the risk of different dementia types. METHODS The genetic predictors of MetS and its five components (waist circumference, hypertension, fasting blood glucose, triglycerides, and high-density lipoprotein cholesterol [HDL-C]) come from comprehensive public genome-wide association studies (GWAS). Different dementia types are collected from the GWAS in the European population. Inverse variance weighting is utilized as the main method, complemented by several sensitivity approaches to verify the robustness of the results. RESULTS Genetically predicted MetS and its five components are not causally associated with the increasing risk of dementia (all p > 0.05). In addition, no significant association between MetS and its components and Alzheimer's disease, vascular dementia, frontotemporal dementia, dementia with Lewy bodies, and dementia due to Parkinson's disease (all p > 0.05), except the association between HDL-C and dementia with Lewy bodies. HDL-C may play a protective role in dementia with Lewy bodies (OR: 0.81, 95% CI: 0.72-0.92, p = 0.0010). CONCLUSIONS From the perspective of genetic variants, our study provides novel evidence that MetS and its components are not associated with different dementia types.
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Affiliation(s)
- Qiang He
- Department of Neurosurgery, West China Hospital, Sichuan University, Wuhou District, Chengdu, Sichuan, China
| | - Wenjing Wang
- Department of Pharmacy, Institute of Metabolic Diseases and Pharmacotherapy, West China Hospital, Sichuan University, Wuhou District, Chengdu, China
| | - Hao Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, Beijing, China
| | - Yang Xiong
- Department of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Chuanyuan Tao
- Department of Neurosurgery, West China Hospital, Sichuan University, Wuhou District, Chengdu, Sichuan, China
| | - Lu Ma
- Department of Neurosurgery, West China Hospital, Sichuan University, Wuhou District, Chengdu, Sichuan, China
| | - Chao You
- Department of Neurosurgery, West China Hospital, Sichuan University, Wuhou District, Chengdu, Sichuan, China
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Au Yeung SL, Wong THT, He B, Luo S, Kwok KO. Does ACE2 mediate the detrimental effect of exposures related to COVID-19 risk: A Mendelian randomization investigation. J Med Virol 2023; 95:e28205. [PMID: 36217700 PMCID: PMC9874514 DOI: 10.1002/jmv.28205] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/22/2022] [Accepted: 10/06/2022] [Indexed: 01/27/2023]
Abstract
OBJECTIVES Adiposity, smoking, and lower socioeconomic position (SEP) increase COVID-19 risk while the association of vitamin D, blood pressure, and glycemic traits in COVID-19 risk were less clear. Whether angiotensin-converting enzyme 2 (ACE2), the key receptor for SARS-CoV-2, mediates these associations has not been investigated. We conducted a Mendelian randomization study to assess the role of these exposures in COVID-19 and mediation by ACE2. METHODS We extracted genetic variants strongly related to various exposures (vitamin D, blood pressure, glycemic traits, smoking, adiposity, and educational attainment [SEP proxy]), and ACE2 cis-variants from genome-wide association studies (GWAS, n ranged from 28 204 to 3 037 499) and applied them to GWAS summary statistics of ACE2 (n = 28 204) and COVID-19 (severe, hospitalized, and susceptibility, n ≤ 2 942 817). We used inverse variance weighted as the main analyses, with MR-Egger and weighted median as sensitivity analyses. Mediation analyses were performed based on product of coefficient method. RESULTS Higher adiposity, lifetime smoking index, and lower educational attainment were consistently associated with higher risk of COVID-19 phenotypes while there was no strong evidence for an association of other exposures in COVID-19 risk. ACE2 partially mediates the detrimental effects of body mass index (ranged from 4.3% to 8.2%), waist-to-hip ratio (ranged from 11.2% to 16.8%), and lower educational attainment (ranged from 4.0% to 7.5%) in COVID-19 phenotypes while ACE2 did not mediate the detrimental effect of smoking. CONCLUSIONS We provided genetic evidence that reducing ACE2 could partly lower COVID-19 risk amongst people who were overweight/obese or of lower SEP.
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Affiliation(s)
- Shiu Lun Au Yeung
- School of Public Health, LKS Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Tommy Hon Ting Wong
- School of Public Health, LKS Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Baoting He
- School of Public Health, LKS Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Shan Luo
- School of Public Health, LKS Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Kin On Kwok
- Jockey Club School of Public Health and Primary Care, Faculty of MedicineChinese University of Hong KongHong Kong Special Administrative RegionChina,Stanley Ho Centre for Emerging Infectious DiseasesThe Chinese University of Hong KongHong Kong Special Administrative RegionChina,Hong Kong Institute of Asia‐Pacific StudiesThe Chinese University of Hong KongHong Kong Special Administrative RegionChina
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