1
|
Heianza Y, Zhou T, Wang X, Furtado JD, Appel LJ, Sacks FM, Qi L. MTNR1B genotype and effects of carbohydrate quantity and dietary glycaemic index on glycaemic response to an oral glucose load: the OmniCarb trial. Diabetologia 2024; 67:506-515. [PMID: 38052941 DOI: 10.1007/s00125-023-06056-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 11/02/2023] [Indexed: 12/07/2023]
Abstract
AIMS/HYPOTHESIS A type 2 diabetes-risk-increasing variant, MTNR1B (melatonin receptor 1B) rs10830963, regulates the circadian function and may influence the variability in metabolic responses to dietary carbohydrates. We investigated whether the effects of carbohydrate quantity and dietary glycaemic index (GI) on glycaemic response during OGTTs varied by the risk G allele of MTNR1B-rs10830963. METHODS This study included participants (n=150) of a randomised crossover-controlled feeding trial of four diets with high/low GI levels and high/low carbohydrate content for 5 weeks. The MTNR1B-rs10830963 (C/G) variant was genotyped. Glucose response during 2 h OGTT was measured at baseline and the end of each diet intervention. RESULTS Among the four study diets, carrying the risk G allele (CG/GG vs CC genotype) of MTNR1B-rs10830963 was associated with the largest AUC of glucose during 2 h OGTT after consuming a high-carbohydrate/high-GI diet (β 134.32 [SE 45.69] mmol/l × min; p=0.004). The risk G-allele carriers showed greater increment of glucose during 0-60 min (β 1.26 [0.47] mmol/l; p=0.008) or 0-90 min (β 1.10 [0.50] mmol/l; p=0.028) after the high-carbohydrate/high-GI diet intervention, but not after consuming the other three diets. At high carbohydrate content, reducing GI levels decreased 60 min post-OGTT glucose (mean -0.67 [95% CI: -1.18, -0.17] mmol/l) and the increment of glucose during 0-60 min (mean -1.00 [95% CI: -1.67, -0.33] mmol/l) and 0-90 min, particularly in the risk G-allele carriers (pinteraction <0.05 for all). CONCLUSIONS/INTERPRETATION Our study shows that carrying the risk G allele of MTNR1B-rs10830963 is associated with greater glycaemic responses after consuming a diet with high carbohydrates and high GI levels. Reducing GI in a high-carbohydrate diet may decrease post-OGTT glucose concentrations among the risk G-allele carriers.
Collapse
Affiliation(s)
- Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
| | - Tao Zhou
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
- Department of Epidemiology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Xuan Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Jeremy D Furtado
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Biogen Epidemiology, Cambridge, MA, USA
| | - Lawrence J Appel
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Frank M Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| |
Collapse
|
2
|
Wang F, Yu J, Lin L, Lin D, Chen K, Quan H. A genome-wide association study identifies 25(OH)D3-associated genetic variants in the prediabetic Chinese population. Endocrine 2024:10.1007/s12020-024-03694-7. [PMID: 38291318 DOI: 10.1007/s12020-024-03694-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/10/2024] [Indexed: 02/01/2024]
Abstract
OBJECTIVES Diabetes mellitus has been a significant public health problem, associated with high rates of morbidity, disability, and mortality. Prediabetes is a crucial period for preventing and managing diabetes. 25(OH)D3 is an important risk factor for prediabetes. However, there is limited genetic knowledge of 25(OH)D3 in the Chinese population. This study was designed to identify genetic variants associated with 25(OH)D3 and explore the potential pathogenesis of prediabetes. METHODS In this study, 451 individuals with prediabetes were recruited to determine the genetic variants associated with 25(OH)D3 through a genome-wide association study (GWAS). Gene mapping and overrepresentation analysis (ORA) were further performed to explore the candidate genes and their biological mechanisms. RESULTS In this study, we identified two independent significant loci (rs9457733 and rs11243373, p < 5 × 10-6 and r2 < 0.6) and 37 candidate genes associated with 25(OH)D3 in prediabetes. Furthermore, the ORA analysis revealed that two genes in the gene sets, SLC22A1 and SLC22A3, were found to be significantly enriched in monoamine transmembrane transporter activity and quaternary ammonium group transmembrane transporter activity, as determined by WebGestalt and g:Profiler (padj < 0.05). CONCLUSION The identification of potential genes associated with 25(OH)D3 provides a foundation for a better understanding of the pathogenesis, diagnosis, and treatment of prediabetes.
Collapse
Affiliation(s)
- Fei Wang
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Jingwen Yu
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Leweihua Lin
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Danhong Lin
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Kaining Chen
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Huibiao Quan
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China.
| |
Collapse
|
3
|
Hong HG, Gouveia MH, Ogwang MD, Kerchan P, Reynolds SJ, Tenge CN, Were PA, Kuremu RT, Wekesa WN, Masalu N, Kawira E, Kinyera T, Wang X, Zhou J, Leal TP, Otim I, Legason ID, Nabalende H, Dhudha H, Mumia M, Baker FS, Okusolubo T, Ayers LW, Bhatia K, Goedert JJ, Woo J, Manning M, Cole N, Luo W, Hicks B, Chagaluka G, Johnston WT, Mutalima N, Borgstein E, Liomba GN, Kamiza S, Mkandawire N, Mitambo C, Molyneux EM, Newton R, Hutchinson A, Yeager M, Adeyemo AA, Thein SL, Rotimi CN, Chanock SJ, Prokunina-Olsson L, Mbulaiteye SM. Sickle cell allele HBB-rs334(T) is associated with decreased risk of childhood Burkitt lymphoma in East Africa. Am J Hematol 2024; 99:113-123. [PMID: 38009642 PMCID: PMC10872868 DOI: 10.1002/ajh.27149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 09/30/2023] [Accepted: 10/23/2023] [Indexed: 11/29/2023]
Abstract
Burkitt lymphoma (BL) is an aggressive B-cell lymphoma that significantly contributes to childhood cancer burden in sub-Saharan Africa. Plasmodium falciparum, which causes malaria, is geographically associated with BL, but the evidence remains insufficient for causal inference. Inference could be strengthened by demonstrating that mendelian genes known to protect against malaria-such as the sickle cell trait variant, HBB-rs334(T)-also protect against BL. We investigated this hypothesis among 800 BL cases and 3845 controls in four East African countries using genome-scan data to detect polymorphisms in 22 genes known to affect malaria risk. We fit generalized linear mixed models to estimate odds ratios (OR) and 95% confidence intervals (95% CI), controlling for age, sex, country, and ancestry. The ORs of the loci with BL and P. falciparum infection among controls were correlated (Spearman's ρ = 0.37, p = .039). HBB-rs334(T) was associated with lower P. falciparum infection risk among controls (OR = 0.752, 95% CI 0.628-0.9; p = .00189) and BL risk (OR = 0.687, 95% CI 0.533-0.885; p = .0037). ABO-rs8176703(T) was associated with decreased risk of BL (OR = 0.591, 95% CI 0.379-0.992; p = .00271), but not of P. falciparum infection. Our results increase support for the etiological correlation between P. falciparum and BL risk.
Collapse
Affiliation(s)
- Hyokyoung G. Hong
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| | - Mateus H. Gouveia
- Center for Research on Genomics & Global Health, NHGRI, National Institutes of Health, Bethesda, MD, USA
| | - Martin D. Ogwang
- EMBLEM Study, St. Mary’s Hospital, Lacor, Gulu, Uganda
- EMBLEM Study, African Field Epidemiology Network, Kampala, Uganda
| | - Patrick Kerchan
- EMBLEM Study, African Field Epidemiology Network, Kampala, Uganda
- EMBLEM Study, Kuluva Hospital, Arua, Uganda
| | - Steven J. Reynolds
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | | | - Pamela A. Were
- EMBLEM Study, Academic Model Providing Access To Healthcare (AMPATH), Eldoret, Kenya
| | - Robert T. Kuremu
- EMBLEM Study, Moi University College of Health Sciences, Eldoret, Kenya
| | - Walter N. Wekesa
- EMBLEM Study, Moi University College of Health Sciences, Eldoret, Kenya
| | | | - Esther Kawira
- EMBLEM Study, Shirati Health, Education, and Development Foundation, Shirati, Tanzania
| | - Tobias Kinyera
- EMBLEM Study, St. Mary’s Hospital, Lacor, Gulu, Uganda
- EMBLEM Study, African Field Epidemiology Network, Kampala, Uganda
| | - Xunde Wang
- Sickle Cell Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USAs
| | - Jiefu Zhou
- Department of Statistics and Probability, Michigan State University, MI, USA
| | - Thiago Peixoto Leal
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Isaac Otim
- EMBLEM Study, St. Mary’s Hospital, Lacor, Gulu, Uganda
- EMBLEM Study, African Field Epidemiology Network, Kampala, Uganda
| | - Ismail D. Legason
- EMBLEM Study, African Field Epidemiology Network, Kampala, Uganda
- EMBLEM Study, Kuluva Hospital, Arua, Uganda
| | - Hadijah Nabalende
- EMBLEM Study, St. Mary’s Hospital, Lacor, Gulu, Uganda
- EMBLEM Study, African Field Epidemiology Network, Kampala, Uganda
| | - Herry Dhudha
- EMBLEM Study, Bugando Medical Center, Mwanza, Tanzania
| | - Mediatrix Mumia
- EMBLEM Study, Academic Model Providing Access To Healthcare (AMPATH), Eldoret, Kenya
| | - Francine S. Baker
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| | - Temiloluwa Okusolubo
- Sickle Cell Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USAs
| | - Leona W. Ayers
- Department of Pathology, The Ohio State University, Columbus, OH, USA
| | - Kishor Bhatia
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| | - James J Goedert
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| | - Joshua Woo
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| | - Michelle Manning
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Nathan Cole
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Wen Luo
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Belynda Hicks
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - George Chagaluka
- Departments of Pediatrics and Surgery, College of Medicine, University of Malawi, Blantyre, Malawi
| | - W Thomas Johnston
- Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, UK
| | - Nora Mutalima
- Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, UK
- Cancer Epidemiology Unit, University of Oxford, Oxford, UK
| | - Eric Borgstein
- Departments of Pediatrics and Surgery, College of Medicine, University of Malawi, Blantyre, Malawi
| | - George N. Liomba
- Departments of Pediatrics and Surgery, College of Medicine, University of Malawi, Blantyre, Malawi
| | - Steve Kamiza
- Departments of Pediatrics and Surgery, College of Medicine, University of Malawi, Blantyre, Malawi
| | - Nyengo Mkandawire
- Departments of Pediatrics and Surgery, College of Medicine, University of Malawi, Blantyre, Malawi
| | | | - Elizabeth M. Molyneux
- Departments of Pediatrics and Surgery, College of Medicine, University of Malawi, Blantyre, Malawi
| | - Robert Newton
- Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, UK
| | - Amy Hutchinson
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Meredith Yeager
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Adebowale A. Adeyemo
- Center for Research on Genomics & Global Health, NHGRI, National Institutes of Health, Bethesda, MD, USA
| | - Swee Lay Thein
- Sickle Cell Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USAs
| | - Charles N. Rotimi
- Center for Research on Genomics & Global Health, NHGRI, National Institutes of Health, Bethesda, MD, USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| | - Ludmila Prokunina-Olsson
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| | - Sam M. Mbulaiteye
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, USA
| |
Collapse
|
4
|
Ouidir M, Chatterjee S, Wu J, Tekola-Ayele F. Genomic study of maternal lipid traits in early pregnancy concurs with four known adult lipid loci. J Clin Lipidol 2023; 17:168-180. [PMID: 36443208 PMCID: PMC9974591 DOI: 10.1016/j.jacl.2022.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 10/10/2022] [Accepted: 10/18/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Blood lipids during pregnancy are associated with cardiovascular diseases and adverse pregnancy outcomes. Genome-wide association studies (GWAS) in predominantly male European ancestry populations have identified genetic loci associated with blood lipid levels. However, the genetic architecture of blood lipids in pregnant women remains poorly understood. OBJECTIVE Our goal was to identify genetic loci associated with blood lipid levels among pregnant women from diverse ancestry groups and to evaluate whether previously known lipid loci in predominantly European adults are transferable to pregnant women. METHODS The trans-ancestry GWAS were conducted on serum levels of total cholesterol, high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL) and triglycerides during first trimester among pregnant women from four population groups (608 European-, 623 African-, 552 Hispanic- and 235 East Asian-Americans) recruited in the NICHD Fetal Growth Studies cohort. The four GWAS summary statistics were combined using trans-ancestry meta-analysis approaches that account for genetic heterogeneity among populations. RESULTS Loci in CELSR2 and APOE were genome-wide significantly associated (p-value < 5×10-8) with total cholesterol and LDL levels. Loci near CETP and ABCA1 approached genome-wide significant association with HDL (p-value = 2.97×10-7 and 9.71×10-8, respectively). Less than 20% of previously known adult lipid loci were transferable to pregnant women. CONCLUSION This trans-ancestry GWAS meta-analysis in pregnant women identified associations that concur with four known adult lipid loci. Limited replication of known lipid-loci from predominantly European study populations to pregnant women underlines the need for genomic studies of lipids in ancestrally diverse pregnant women. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, NCT00912132.
Collapse
Affiliation(s)
- Marion Ouidir
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Suvo Chatterjee
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Jing Wu
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
| |
Collapse
|
5
|
Parcha V, Heindl B, Kalra R, Bress A, Rao S, Pandey A, Gower B, Irvin MR, McDonald MLN, Li P, Arora G, Arora P. Genetic European Ancestry and Incident Diabetes in Black Individuals: Insights From the SPRINT Trial. Circ Genom Precis Med 2022; 15:e003468. [PMID: 35089798 PMCID: PMC8847245 DOI: 10.1161/circgen.121.003468] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Black individuals have high incident diabetes risk, despite having paradoxically lower triglyceride and higher HDL (high-density lipoprotein) cholesterol levels. The basis of this is poorly understood. We evaluated the participants of SPRINT (Systolic Blood Pressure Intervention Trial) to assess the association of estimated European genetic ancestry with the risk of incident diabetes in self-identified Black individuals. METHODS Self-identified non-Hispanic Black SPRINT participants free of diabetes at baseline were included. Black participants were stratified into tertiles (T1-T3) of European ancestry proportions estimated using 106 biallelic ancestry informative genetic markers. The multivariable-adjusted association of European ancestry proportion with indices of baseline metabolic syndrome (ie, fasting plasma glucose, triglycerides, HDL cholesterol, body mass index, and blood pressure) was assessed. Multivariable-adjusted Cox regression determined the risk of incident diabetes (fasting plasma glucose ≥126 mg/dL or self-reported diabetes treatment) across tertiles of European ancestry proportion. RESULTS Among 2466 Black SPRINT participants, a higher European ancestry proportion was independently associated with higher baseline triglyceride and lower HDL cholesterol levels (P<0.001 for both). European ancestry proportion was not associated with baseline fasting plasma glucose, body mass index, and blood pressure (P>0.05). Compared with the first tertile, those in the second (hazard ratio, 0.64 [95% CI, 0.45-0.90]) and third tertiles (hazard ratio, 0.61 [95% CI, 0.44-0.89]) of the European ancestry proportion had a lower risk of incident diabetes. A 5% point higher European ancestry was associated with a 29% lower risk of incident diabetes (hazard ratio, 0.71 [95% CI, 0.55-0.93]). There was no evidence of a differential association between the European ancestry proportion tertiles and incident diabetes between those randomized to intensive versus standard blood pressure treatment. CONCLUSIONS The higher risk of incident diabetes in Black individuals may have genetic determinants in addition to adverse social factors. Further research may help understand the interplay between biological and social determinants of cardiometabolic health in Black individuals. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01206062.
Collapse
Affiliation(s)
- Vibhu Parcha
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Brittain Heindl
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rajat Kalra
- Cardiovascular Division, University of Minnesota, Minneapolis, MN, USA
| | - Adam Bress
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Shreya Rao
- Division of Cardiology, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ambarish Pandey
- Division of Cardiology, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Barbara Gower
- Department of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Merry-Lynn N. McDonald
- Division of Pulmonary, Allergy, and Critical Care, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Peng Li
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Garima Arora
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Pankaj Arora
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA
- Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL, USA
| |
Collapse
|
6
|
Patel R, Parmar N, Pramanik Palit S, Rathwa N, Ramachandran AV, Begum R. Diabetes mellitus and melatonin: Where are we? Biochimie 2022; 202:2-14. [PMID: 35007648 DOI: 10.1016/j.biochi.2022.01.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/07/2021] [Accepted: 01/04/2022] [Indexed: 12/24/2022]
Abstract
Diabetes mellitus (DM) and diabetes-related complications are amongst the leading causes of mortality worldwide. The international diabetes federation (IDF) has estimated 592 million people to suffer from DM by 2035. Hence, finding a novel biomolecule that can effectively aid diabetes management is vital, as other existing drugs have numerous side effects. Melatonin, a pineal hormone having antioxidative and anti-inflammatory properties, has been implicated in circadian dysrhythmia-linked DM. Reduced levels of melatonin and a functional link between melatonin and insulin are implicated in the pathogenesis of type 2 diabetes (T2D) Additionally, genomic studies revealed that rare variants in melatonin receptor 1b (MTNR1B) are also associated with impaired glucose tolerance and increased risk of T2D. Moreover, exogenous melatonin treatment in cell lines, rodent models, and diabetic patients has shown a potent effect in alleviating diabetes and other related complications. This highlights the role of melatonin in glucose homeostasis. However, there are also contradictory reports on the effects of melatonin supplementation. Thus, it is essential to explore if melatonin can be taken from bench to bedside for diabetes management. This review summarizes the therapeutic potential of melatonin in various diabetic models and whether it can be considered a safe drug for managing diabetic complications and diabetic manifestations like oxidative stress, inflammation, ER stress, mitochondrial dysfunction, metabolic dysregulation, etc.
Collapse
Affiliation(s)
- Roma Patel
- Department of Biochemistry, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390 002, Gujarat, India
| | - Nishant Parmar
- Department of Biochemistry, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390 002, Gujarat, India
| | - Sayantani Pramanik Palit
- Department of Biochemistry, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390 002, Gujarat, India
| | - Nirali Rathwa
- Department of Biochemistry, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390 002, Gujarat, India
| | - A V Ramachandran
- Division of Life Science, School of Sciences, Navrachana University, Vadodara, 391 410, Gujarat, India
| | - Rasheedunnisa Begum
- Department of Biochemistry, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, 390 002, Gujarat, India.
| |
Collapse
|
7
|
Lin L, Fang T, Lin L, Ou Q, Zhang H, Chen K, Quan H. Genetic Variants Relate to Fasting Plasma Glucose, 2-Hour Postprandial Glucose, Glycosylated Hemoglobin, and BMI in Prediabetes. Front Endocrinol (Lausanne) 2022; 13:778069. [PMID: 35299963 PMCID: PMC8923657 DOI: 10.3389/fendo.2022.778069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 02/01/2022] [Indexed: 12/30/2022] Open
Abstract
Diabetes mellitus (DM) is a chronic disease that seriously threatens human health. Prediabetes is a stage in the progression of DM. The level of clinical indicators including fasting plasma glucose (FPG), 2-h postprandial glucose (2hPG), and glycosylated hemoglobin (HbA1C) are the diagnostic markers of diabetes. In this genome-wide association study (GWAS), we aimed to investigate the association of genetic variants with these phenotypes in Hainan prediabetes. In this study, we recruited 451 prediabetes patients from the residents aged ≥18 years who participated in the National Diabetes Prevalence Survey of the Chinese Medical Association in 2017. The GWAS of FPG, 2hPG, HbA1C, and body mass index (BMI) in prediabetes was analyzed with a linear model using an additive genetic model with adjustment for age and sex. We identified that rs13052524 in MRPS6 and rs62212118 in SLC5A3 were associated with 2hPG in Hainan prediabetes (p = 4.35 × 10-6, p = 4.05 × 10-6, respectively). Another six variants in the four genes (LINC01648, MATN1, CRAT37, and SLCO3A1) were related to HbA1C. Moreover, rs11142842, rs1891298, rs1891299, and rs11142843 in TRPM3/TMEM2 and rs78432036 in MLYCD/OSGIN1 were correlated to BMI (all p < 5 × 10-6). This study is the first to determine the genome-wide association of FPG, 2hPG, and HbA1C, which emphasizes the importance of in-depth understanding of the phenotypes of high-value susceptibility gene markers in the diagnosis of prediabetes.
Collapse
|
8
|
Shaw DM, Polikowsky HP, Pruett DG, Chen HH, Petty LE, Viljoen KZ, Beilby JM, Jones RM, Kraft SJ, Below JE. Phenome risk classification enables phenotypic imputation and gene discovery in developmental stuttering. Am J Hum Genet 2021; 108:2271-2283. [PMID: 34861174 PMCID: PMC8715184 DOI: 10.1016/j.ajhg.2021.11.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 10/27/2021] [Indexed: 11/30/2022] Open
Abstract
Developmental stuttering is a speech disorder characterized by disruption in the forward movement of speech. This disruption includes part-word and single-syllable repetitions, prolongations, and involuntary tension that blocks syllables and words, and the disorder has a life-time prevalence of 6-12%. Within Vanderbilt's electronic health record (EHR)-linked biorepository (BioVU), only 142 individuals out of 92,762 participants (0.15%) are identified with diagnostic ICD9/10 codes, suggesting a large portion of people who stutter do not have a record of diagnosis within the EHR. To identify individuals affected by stuttering within our EHR, we built a PheCode-driven Gini impurity-based classification and regression tree model, PheML, by using comorbidities enriched in individuals affected by stuttering as predicting features and imputing stuttering status as the outcome variable. Applying PheML in BioVU identified 9,239 genotyped affected individuals (a clinical prevalence of ∼10%) for downstream genetic analysis. Ancestry-stratified GWAS of PheML-imputed affected individuals and matched control individuals identified rs12613255, a variant near CYRIA on chromosome 2 (B = 0.323; p value = 1.31 × 10-8) in European-ancestry analysis and rs7837758 (B = 0.518; p value = 5.07 × 10-8), an intronic variant found within the ZMAT4 gene on chromosome 8, in African-ancestry analysis. Polygenic-risk prediction and concordance analysis in an independent clinically ascertained sample of developmental stuttering cases validate our GWAS findings in PheML-imputed affected and control individuals and demonstrate the clinical relevance of our population-based analysis for stuttering risk.
Collapse
Affiliation(s)
- Douglas M Shaw
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Hannah P Polikowsky
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Dillon G Pruett
- Hearing and Speech Sciences, Vanderbilt University, Nashville, TN 37203, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Kathryn Z Viljoen
- Curtin School of Allied Health, Curtin University, Perth 6845, Australia
| | - Janet M Beilby
- Curtin School of Allied Health, Curtin University, Perth 6845, Australia
| | - Robin M Jones
- Hearing and Speech Sciences, Vanderbilt University, Nashville, TN 37203, USA
| | - Shelly Jo Kraft
- Communication Sciences and Disorders, Wayne State University, Detroit, MI 48202, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
| |
Collapse
|
9
|
Jung SY, Sobel EM, Pellegrini M, Yu H, Papp JC. Synergistic Effects of Genetic Variants of Glucose Homeostasis and Lifelong Exposures to Cigarette Smoking, Female Hormones, and Dietary Fat Intake on Primary Colorectal Cancer Development in African and Hispanic/Latino American Women. Front Oncol 2021; 11:760243. [PMID: 34692549 PMCID: PMC8529283 DOI: 10.3389/fonc.2021.760243] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 09/22/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Disparities in cancer genomic science exist among racial/ethnic minorities. Particularly, African American (AA) and Hispanic/Latino American (HA) women, the 2 largest minorities, are underrepresented in genetic/genome-wide studies for cancers and their risk factors. We conducted on AA and HA postmenopausal women a genomic study for insulin resistance (IR), the main biologic mechanism underlying colorectal cancer (CRC) carcinogenesis owing to obesity. METHODS With 780 genome-wide IR-specific single-nucleotide polymorphisms (SNPs) among 4,692 AA and 1,986 HA women, we constructed a CRC-risk prediction model. Along with these SNPs, we incorporated CRC-associated lifestyles in the model of each group and detected the topmost influential genetic and lifestyle factors. Further, we estimated the attributable risk of the topmost risk factors shared by the groups to explore potential factors that differentiate CRC risk between these groups. RESULTS In both groups, we detected IR-SNPs in PCSK1 (in AA) and IFT172, GCKR, and NRBP1 (in HA) and risk lifestyles, including long lifetime exposures to cigarette smoking and endogenous female hormones and daily intake of polyunsaturated fatty acids (PFA), as the topmost predictive variables for CRC risk. Combinations of those top genetic- and lifestyle-markers synergistically increased CRC risk. Of those risk factors, dietary PFA intake and long lifetime exposure to female hormones may play a key role in mediating racial disparity of CRC incidence between AA and HA women. CONCLUSIONS Our results may improve CRC risk prediction performance in those medically/scientifically underrepresented groups and lead to the development of genetically informed interventions for cancer prevention and therapeutic effort, thus contributing to reduced cancer disparities in those minority subpopulations.
Collapse
Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California, Los Angeles, Los Angeles, CA, United States
| | - Eric M. Sobel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, Life Sciences Division, University of California, Los Angeles, Los Angeles, CA, United States
| | - Herbert Yu
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, United States
| | - Jeanette C. Papp
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| |
Collapse
|
10
|
Meeks KAC, Bentley AR, Gouveia MH, Chen G, Zhou J, Lei L, Adeyemo AA, Doumatey AP, Rotimi CN. Genome-wide analyses of multiple obesity-related cytokines and hormones informs biology of cardiometabolic traits. Genome Med 2021; 13:156. [PMID: 34620218 PMCID: PMC8499470 DOI: 10.1186/s13073-021-00971-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/16/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND A complex set of perturbations occur in cytokines and hormones in the etiopathogenesis of obesity and related cardiometabolic conditions such as type 2 diabetes (T2D). Evidence for the genetic regulation of these cytokines and hormones is limited, particularly in African-ancestry populations. In order to improve our understanding of the biology of cardiometabolic traits, we investigated the genetic architecture of a large panel of obesity- related cytokines and hormones among Africans with replication analyses in African Americans. METHODS We performed genome-wide association studies (GWAS) in 4432 continental Africans, enrolled from Ghana, Kenya, and Nigeria as part of the Africa America Diabetes Mellitus (AADM) study, for 13 obesity-related cytokines and hormones, including adipsin, glucose-dependent insulinotropic peptide (GIP), glucagon-like peptide-1 (GLP-1), interleukin-1 receptor antagonist (IL1-RA), interleukin-6 (IL-6), interleukin-10 (IL-10), leptin, plasminogen activator inhibitor-1 (PAI-1), resistin, visfatin, insulin, glucagon, and ghrelin. Exact and local replication analyses were conducted in African Americans (n = 7990). The effects of sex, body mass index (BMI), and T2D on results were investigated through stratified analyses. RESULTS GWAS identified 39 significant (P value < 5 × 10-8) loci across all 13 traits. Notably, 14 loci were African-ancestry specific. In this first GWAS for adipsin and ghrelin, we detected 13 and 4 genome-wide significant loci respectively. Stratified analyses by sex, BMI, and T2D showed a strong effect of these variables on detected loci. Eight novel loci were successfully replicated: adipsin (3), GIP (1), GLP-1 (1), and insulin (3). Annotation of these loci revealed promising links between these adipocytokines and cardiometabolic outcomes as illustrated by rs201751833 for adipsin and blood pressure and locus rs759790 for insulin level and T2D in lean individuals. CONCLUSIONS Our study identified genetic variants underlying variation in multiple adipocytokines, including the first loci for adipsin and ghrelin. We identified population differences in variants associated with adipocytokines and highlight the importance of stratification for discovery of loci. The high number of African-specific loci detected emphasizes the need for GWAS in African-ancestry populations, as these loci could not have been detected in other populations. Overall, our work contributes to the understanding of the biology linking adipocytokines to cardiometabolic traits.
Collapse
Affiliation(s)
- Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Lin Lei
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA.
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA.
| |
Collapse
|
11
|
Jung SY. Genetic Signatures of Glucose Homeostasis: Synergistic Interplay With Long-Term Exposure to Cigarette Smoking in Development of Primary Colorectal Cancer Among African American Women. Clin Transl Gastroenterol 2021; 12:e00412. [PMID: 34608882 PMCID: PMC8500576 DOI: 10.14309/ctg.0000000000000412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 08/22/2021] [Indexed: 11/17/2022] Open
Abstract
INTRODUCTION Insulin resistance (IR)/glucose intolerance is a critical biologic mechanism for the development of colorectal cancer (CRC) in postmenopausal women. Whereas IR and excessive adiposity are more prevalent in African American (AA) women than in White women, AA women are underrepresented in genome-wide studies for systemic regulation of IR and the association with CRC risk. METHODS With 780 genome-wide IR single-nucleotide polymorphisms (SNPs) among 4,692 AA women, we tested for a causal inference between genetically elevated IR and CRC risk. Furthermore, by incorporating CRC-associated lifestyle factors, we established a prediction model on the basis of gene-environment interactions to generate risk profiles for CRC with the most influential genetic and lifestyle factors. RESUTLS In the pooled Mendelian randomization analysis, the genetically elevated IR was associated with 9 times increased risk of CRC, but with lack of analytic power. By addressing the variation of individual SNPs in CRC in the prediction model, we detected 4 fasting glucose-specific SNPs in GCK, PCSK1, and MTNR1B and 4 lifestyles, including smoking, aging, prolonged lifetime exposure to endogenous estrogen, and high fat intake, as the most predictive markers of CRC risk. Our joint test for those risk genotypes and lifestyles with smoking revealed the synergistically increased CRC risk, more substantially in women with longer-term exposure to cigarette smoking. DISCUSSION Our findings may improve CRC prediction ability among medically underrepresented AA women and highlight genetically informed preventive interventions (e.g., smoking cessation; CRC screening to longer-term smokers) for those women at high risk with risk genotypes and behavioral patterns.
Collapse
Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, School of Nursing, University of California, Los Angeles, Los Angeles, California, USA; and
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, California, USA.
| |
Collapse
|
12
|
Bentley AR, Chen G, Doumatey AP, Shriner D, Meeks KAC, Gouveia MH, Ekoru K, Zhou J, Adeyemo A, Rotimi CN. GWAS in Africans identifies novel lipids loci and demonstrates heterogenous association within Africa. Hum Mol Genet 2021; 30:2205-2214. [PMID: 34196372 DOI: 10.1093/hmg/ddab174] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 01/11/2023] Open
Abstract
Serum lipids are biomarkers of cardiometabolic disease risk, and understanding genomic factors contributing to their distribution is of interest. Studies of lipids in Africans are rare, though it is expected that such studies could identify novel loci. We conducted a GWAS of 4317 Africans enrolled from Nigeria, Ghana, and Kenya. We evaluated linear mixed models of high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), total cholesterol (CHOL), triglycerides (TG), and TG/HDLC. Replication was attempted in 9542 African Americans (AA). In our main analysis, we identified 28 novel associations in Africans. Of the 18 of these that could be tested in AA, three associations replicated (GPNMB-TG, ENPP1-TG, and SMARCA4-LDLC). Five additional novel loci were discovered upon meta-analysis with AA (rs138282551-TG, PGBD5-HDLC, CD80-TG/HDLC, SLC44A1-CHOL, and TLL2-CHOL). Analyses considering only those with predominantly West African ancestry (Nigeria, Ghana, and AA) yielded new insights: ORC5-LDLC and chr20:60973327-CHOL. Among our novel findings are some loci with known connections to lipids pathways. For instance, rs147706369 (TLL2) alters a regulatory motif for sterol regulatory element-binding proteins (SREBPs), a family of transcription factors that control the expression of a range of enzymes involved in cholesterol, fatty acid, and triglyceride synthesis, and rs115749422 (SMARCA4), an independent association near the known LDLR locus that is rare or absent in populations without African ancestry. These findings demonstrate the utility of conducting genomic analyses in Africans for discovering novel loci and provide some preliminary evidence for caution against treating 'African ancestry' as a monolithic category.
Collapse
Affiliation(s)
- Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Kenneth Ekoru
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| |
Collapse
|
13
|
Fischer C, Wilken-Schmitz A, Hernandez-Olmos V, Proschak E, Stark H, Fleming I, Weigert A, Thurn M, Hofmann M, Werner ER, Geisslinger G, Niederberger E, Watschinger K, Tegeder I. AGMO Inhibitor Reduces 3T3-L1 Adipogenesis. Cells 2021; 10:1081. [PMID: 34062826 DOI: 10.3390/cells10051081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 04/20/2021] [Accepted: 04/28/2021] [Indexed: 12/20/2022] Open
Abstract
Alkylglycerol monooxygenase (AGMO) is a tetrahydrobiopterin (BH4)-dependent enzyme with major expression in the liver and white adipose tissue that cleaves alkyl ether glycerolipids. The present study describes the disclosure and biological characterization of a candidate compound (Cp6), which inhibits AGMO with an IC50 of 30–100 µM and 5–20-fold preference of AGMO relative to other BH4-dependent enzymes, i.e., phenylalanine-hydroxylase and nitric oxide synthase. The viability and metabolic activity of mouse 3T3-L1 fibroblasts, HepG2 human hepatocytes and mouse RAW264.7 macrophages were not affected up to 10-fold of the IC50. However, Cp6 reversibly inhibited the differentiation of 3T3-L1 cells towards adipocytes, in which AGMO expression was upregulated upon differentiation. Cp6 reduced the accumulation of lipid droplets in adipocytes upon differentiation and in HepG2 cells exposed to free fatty acids. Cp6 also inhibited IL-4-driven differentiation of RAW264.7 macrophages towards M2-like macrophages, which serve as adipocyte progenitors in adipose tissue. Collectively, the data suggest that pharmacologic AGMO inhibition may affect lipid storage.
Collapse
|
14
|
Gouveia MH, Bentley AR, Leonard H, Meeks KAC, Ekoru K, Chen G, Nalls MA, Simonsick EM, Tarazona-Santos E, Lima-Costa MF, Adeyemo A, Shriner D, Rotimi CN. Trans-ethnic meta-analysis identifies new loci associated with longitudinal blood pressure traits. Sci Rep 2021; 11:4075. [PMID: 33603002 PMCID: PMC7893038 DOI: 10.1038/s41598-021-83450-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 01/25/2021] [Indexed: 01/09/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified thousands of genetic loci associated with cross-sectional blood pressure (BP) traits; however, GWAS based on longitudinal BP have been underexplored. We performed ethnic-specific and trans-ethnic GWAS meta-analysis using longitudinal and cross-sectional BP data of 33,720 individuals from five cohorts in the US and one in Brazil. In addition to identifying several known loci, we identified thirteen novel loci with nine based on longitudinal and four on cross-sectional BP traits. Most of the novel loci were ethnic- or study-specific, with the majority identified in African Americans (AA). Four of these discoveries showed additional evidence of association in independent datasets, including an intergenic variant (rs4060030, p = 7.3 × 10–9) with reported regulatory function. We observed a high correlation between the meta-analysis results for baseline and longitudinal average BP (rho = 0.48). BP trajectory results were more correlated with those of average BP (rho = 0.35) than baseline BP(rho = 0.18). Heritability estimates trended higher for longitudinal traits than for cross-sectional traits, providing evidence for different genetic architectures. Furthermore, the longitudinal data identified up to 20% more BP known associations than did cross-sectional data. Our analyses of longitudinal BP data in diverse ethnic groups identified novel BP loci associated with BP trajectory, indicating a need for further longitudinal GWAS on BP and other age-related traits.
Collapse
Affiliation(s)
- Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Hampton Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA.,Data Tecnica International, Glen Echo, MD, 20812, USA
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Kenneth Ekoru
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA.,Data Tecnica International, Glen Echo, MD, 20812, USA
| | - Eleanor M Simonsick
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Eduardo Tarazona-Santos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil
| | | | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA. .,Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Building 12A/Room 4047, Bethesda, MD, 20814, USA.
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA. .,Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Building 12A/Room 4047, Bethesda, MD, 20814, USA.
| |
Collapse
|
15
|
Zahedi AS, Akbarzadeh M, Sedaghati-Khayat B, Seyedhamzehzadeh A, Daneshpour MS. GCKR common functional polymorphisms are associated with metabolic syndrome and its components: a 10-year retrospective cohort study in Iranian adults. Diabetol Metab Syndr 2021; 13:20. [PMID: 33602293 PMCID: PMC7890822 DOI: 10.1186/s13098-021-00637-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 02/08/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Previous studies reported that common functional variants (rs780093, rs780094, and rs1260326) in the glucokinase regulator gene (GCKR) were associated with metabolic syndrome despite the simultaneous association with the favorable and unfavorable metabolic syndrome components. We decided to evaluate these findings in a cohort study with a large sample size of Iranian adult subjects, to our knowledge for the first time. We investigated the association of the GCKR variants with incident MetS in mean follow-up times for nearly 10 years. METHODS Analysis of this retrospective cohort study was performed among 5666 participants of the Tehran Cardiometabolic Genetics Study (TCGS) at 19-88 years at baseline. Linear and logistic regression analyses were used to investigate the metabolic syndrome (JIS criteria) association and its components with rs780093, rs780094, and rs1260326 in an additive genetic model. Cox regression was carried out to peruse variants' association with the incidence of metabolic syndrome in the TCGS cohort study. RESULTS In the current study, we have consistently replicated the association of the GCKR SNPs with higher triglyceride and lower fasting blood sugar levels (p < 0.05) in Iranian adults. The CT genotype of the variants was associated with lower HDL-C levels. The proportional Cox adjusted model regression resulted that TT carriers of rs780094, rs780093, and rs1260326 were associated with 20%, 23%, and 21% excess risk metabolic syndrome incidence, respectively (p < 0.05). CONCLUSIONS Elevated triglyceride levels had the strongest association with GCKR selected variants among the metabolic syndrome components. Despite the association of these variants with decreased fasting blood sugar levels, T alleles of the variants were associated with metabolic syndrome incidence; so whether individuals are T allele carriers of the common functional variants, they have a risk factor for the future incidence of metabolic syndrome.
Collapse
Affiliation(s)
- Asiyeh Sadat Zahedi
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Mahdi Akbarzadeh
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Bahareh Sedaghati-Khayat
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Atefeh Seyedhamzehzadeh
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Maryam S. Daneshpour
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| |
Collapse
|
16
|
Sorlí JV, Barragán R, Coltell O, Portolés O, Pascual EC, Ortega-Azorín C, González JI, Estruch R, Saiz C, Pérez-Fidalgo A, Ordovas JM, Corella D. Chronological Age Interacts with the Circadian Melatonin Receptor 1B Gene Variation, Determining Fasting Glucose Concentrations in Mediterranean Populations. Additional Analyses on Type-2 Diabetes Risk. Nutrients 2020; 12:nu12113323. [PMID: 33138317 PMCID: PMC7692445 DOI: 10.3390/nu12113323] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 10/21/2020] [Accepted: 10/24/2020] [Indexed: 12/25/2022] Open
Abstract
Gene-age interactions have not been systematically investigated on metabolic phenotypes and this modulation will be key for a better understanding of the temporal regulation in nutrigenomics. Taking into account that aging is typically associated with both impairment of the circadian system and a decrease in melatonin secretion, we focused on the melatonin receptor 1B (MTNR1B)-rs10830963 C>G variant that has been associated with fasting glucose concentrations, gestational diabetes, and type-2 diabetes. Therefore, our main aim was to investigate whether the association between the MTNR1B-rs10830963 polymorphism and fasting glucose is age dependent. Our secondary aims were to analyze the polymorphism association with type-2 diabetes and explore the gene-pregnancies interactions on the later type-2 diabetes risk. Three Mediterranean cohorts (n = 2823) were analyzed. First, a cross-sectional study in the discovery cohort consisting of 1378 participants (aged 18 to 80 years; mean age 41 years) from the general population was carried out. To validate and extend the results, two replication cohorts consisting of elderly individuals were studied. In the discovery cohort, we observed a strong gene-age interaction (p = 0.001), determining fasting glucose in such a way that the increasing effect of the risk G-allele was much greater in young (p = 5.9 × 10-10) than in elderly participants (p = 0.805). Consistently, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose concentrations in the two replication cohorts (mean age over 65 years) did not reach statistical significance (p > 0.05 for both). However, in the elderly cohorts, significant associations between the polymorphism and type-2 diabetes at baseline were found. Moreover, in one of the cohorts, we obtained a statistically significant interaction between the MTNR1B polymorphism and the number of pregnancies, retrospectively assessed, on the type-2 diabetes risk. In conclusion, the association of the MTNR1B-rs10830963 polymorphism with fasting glucose is age-dependent, having a greater effect in younger people. However, in elderly subjects, associations of the polymorphism with type-2 diabetes were observed and our exploratory analysis suggested a modulatory effect of the number of past pregnancies on the future type-2 diabetes genetic risk.
Collapse
Affiliation(s)
- Jose V. Sorlí
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Rocío Barragán
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Department of Medicine, Sleep Center of Excellence, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Oscar Coltell
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Department of Computer Languages and Systems, Universitat Jaume I, 12071 Castellón, Spain
| | - Olga Portolés
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Eva C. Pascual
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
| | - Carolina Ortega-Azorín
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - José I. González
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Ramon Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Department of Internal Medicine, Hospital Clinic, Institut d’Investigació Biomèdica August Pi i Sunyer (IDIBAPS), University of Barcelona, Villarroel, 170, 08036 Barcelona, Spain
| | - Carmen Saiz
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
| | - Alejandro Pérez-Fidalgo
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Cáncer, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jose M. Ordovas
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, USA;
- Precision Nutrition and Obesity Program, IMDEA Alimentación, 28049 Madrid, Spain
| | - Dolores Corella
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain; (J.V.S.); (R.B.); (O.P.); (E.C.P.); (C.O.-A.); (J.I.G.); (C.S.); (A.P.-F.)
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (O.C.); (R.E.)
- Correspondence: ; Tel.: +34-96-386-4800
| |
Collapse
|
17
|
Joseph JJ, Zhou X, Zilbermint M, Stratakis CA, Faucz FR, Lodish MB, Berthon A, Wilson JG, Hsueh WA, Golden SH, Lin S. The Association of ARMC5 with the Renin-Angiotensin-Aldosterone System, Blood Pressure, and Glycemia in African Americans. J Clin Endocrinol Metab 2020; 105:5841631. [PMID: 32436940 PMCID: PMC7308077 DOI: 10.1210/clinem/dgaa290] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 05/18/2020] [Indexed: 12/31/2022]
Abstract
CONTEXT Armadillo repeat containing 5 (ARMC5) on chromosome 16 is an adrenal gland tumor suppressor gene associated with primary aldosteronism, especially among African Americans (AAs). We examined the association of ARMC5 variants with aldosterone, plasma renin activity (PRA), blood pressure, glucose, and glycosylated hemoglobin A1c (HbA1c) in community-dwelling AAs. METHODS The Jackson Heart Study is a prospective cardiovascular cohort study in AAs with baseline data collection from 2000 to 2004. Kernel machine method was used to perform a single joint test to analyze for an overall association between the phenotypes of interest (aldosterone, PRA, systolic and diastolic blood pressure [SBP, DBP], glucose, and HbA1c) and the ARMC5 single nucleotide variants (SNVs) adjusted for age, sex, BMI, and medications; followed by Baysian Lasso methodology to identify sets of SNVs in terms of associated haplotypes with specific phenotypes. RESULTS Among 3223 participants (62% female; mean age 55.6 (SD ± 12.8) years), the average SBP and DBP were 127 and 76 mmHg, respectively. The average fasting plasma glucose and HbA1c were 101 mg/dL and 6.0%, respectively. ARMC5 variants were associated with all 6 phenotypes. Haplotype TCGCC (ch16:31476015-31476093) was negatively associated, whereas haplotype CCCCTTGCG (ch16:31477195-31477460) was positively associated with SBP, DBP, and glucose. Haplotypes GGACG (ch16:31477790-31478013) and ACGCG (ch16:31477834-31478113) were negatively associated with aldosterone and positively associated with HbA1c and glucose, respectively. Haplotype GCGCGAGC (ch16:31471193-ch16:31473597(rs114871627) was positively associated with PRA and negatively associated with HbA1c. CONCLUSIONS ARMC5 variants are associated with aldosterone, PRA, blood pressure, fasting glucose, and HbA1c in community-dwelling AAs, suggesting that germline mutations in ARMC5 may underlie cardiometabolic disease in AAs.
Collapse
Affiliation(s)
- Joshua J Joseph
- The Ohio State University, Columbus, Ohio
- Correspondence and Reprint Requests: Joshua J. Joseph, MD, Department of Medicine, The Ohio State University Wexner Medical Center, 566 McCampbell Hall, 1581 Dodd Drive, Columbus, OH 43210; Phone: 614-346-8878; Fax: 614-366-0345;
| | | | - Mihail Zilbermint
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Section on Endocrinology and Genetics, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
- Johns Hopkins Community Physicians at Suburban Hospital, Bethesda, Maryland
| | - Constantine A Stratakis
- Section on Endocrinology and Genetics, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Fabio R Faucz
- Section on Endocrinology and Genetics, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Maya B Lodish
- Division of Pediatric Endocrinology and Diabetes, University of California, San Francisco, San Francisco, California
| | - Annabel Berthon
- Institut Cochin, Centre National de la Recherche Scientifique (CNRS), INSERM, Université Paris Descartes, Paris, France
| | - James G Wilson
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
- Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Sherita H Golden
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Shili Lin
- The Ohio State University, Columbus, Ohio
| |
Collapse
|
18
|
Jia Y, Shen Y, Shi X, Gu X, Zhang P, Liu Y, Zhu A, Jiang L. MTNR1B gene on susceptibility to gestational diabetes mellitus: a two-stage hospital-based study in Southern China. Mol Genet Genomics 2020; 295:1369-1378. [PMID: 32656703 DOI: 10.1007/s00438-020-01706-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 07/01/2020] [Indexed: 02/07/2023]
Abstract
Large-scale studies on genetic risk loci for melatonin receptor 1B (MTNR1B) gene and GDM risk have not been well generalized to the Chinese population. In this study, we performed two-stage case-control study: 1.429 pregnant women: 753 GDM/676 controls in the Southern Chinese population by genotyping 5 SNPs (rs10830963, rs1387153, rs2166706, rs1447352, and rs4753426) in MTNR1B. Genotypes were determined using the Sequenom MassARRAY platform and TaqMan allelic discrimination assay. Interactions between genetic variants and age/BMI as predictors of GDM risk were evaluated under the logistic regression model. In the first stage, the SNP rs10830963 was discovered to be potentially related to GDM risk (additive model: OR = 1.27, 95%CI = 1.05-1.55, P = 0.025), which was further confirmed in the second stage with a similar effect (additive model: OR = 1.53, 95%CI = 1.19-1.98, P = 0.005). In the combined stage, the G allele of rs10830963 was potentially associated with GDM risk (additive model: OR = 1.36, 95%CI = 1.17-1.59, P < 0.001; dominant model: OR = 1.45, 95%CI = 1.15-1.83, P = 0.005). The rs10830963 interacted with age and BMI to contribute to GDM risk in the combined participants. And, the similar interactive effects for the other four SNPs also exist. These findings offer the potential to improve our understanding of the etiology of GDM, and particularly of biological mechanisms.
Collapse
Affiliation(s)
- Yulong Jia
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, Nantong, Jiangsu, China
| | - Yi Shen
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, Nantong, Jiangsu, China
| | - Xiuying Shi
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, Nantong, Jiangsu, China
| | - Xuefeng Gu
- Shanghai Key Laboratory for Molecular Imaging, University of Medicine and Health Sciences, Shanghai, People's Republic of China
| | - Peng Zhang
- School of Clinical Medicine, University of Medicine and Health Sciences, Shanghai, People's Republic of China
| | - Yuanlin Liu
- Department of Obstetrics and Gynecology, Nantong University Affiliated Hospital, Nantong, Jiangsu, China
| | - Aiyong Zhu
- School of Nursing and Health Management, University of Medicine and Health Sciences, Shanghai, People's Republic of China
| | - Liying Jiang
- Shanghai Key Laboratory for Molecular Imaging, University of Medicine and Health Sciences, Shanghai, People's Republic of China. .,Jiading District Central Hospital, Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China.
| |
Collapse
|
19
|
Shen Y, Jia Y, Li Y, Gu X, Wan G, Zhang P, Zhang Y, Jiang L. Genetic determinants of gestational diabetes mellitus: a case-control study in two independent populations. Acta Diabetol 2020; 57:843-852. [PMID: 32114639 DOI: 10.1007/s00592-020-01485-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 01/17/2020] [Indexed: 01/25/2023]
Abstract
BACKGROUND Genetic risk score (GRS) is more informative to identify the complicated associations between variants of genes and disease. Considering similar pathogenesis and shared genetic predispositions between gestational diabetes mellitus (GDM) and type 2 diabetes/obesity, we conducted this study to explore whether the GRS model integrating variants related to type 2 diabetes/obesity is also associated with GDM risk. METHODS A population-based case-control study that included 1429 subjects was conducted to investigate the association between the GRS model and GDM risk, which were analyzed employing stratified logistic regression analysis with the adjustment for age, BMI, parity and family history of diabetes. RESULTS We have screened 23 SNPs and further filtered six SNPs that were significantly associated with the risk of GDM: four risk SNPs (MTNR1B: rs10830963, rs1387153, rs2166706; MC4R: rs2229616) and two protective SNPs (MTNR1B: rs1447352 and rs4753426). The GRS model with a higher score indicated a higher genetic predisposition to develop GDM, especially in the highest quartile of GRS (all P < 0.001) and the strata of advanced maternal age (all P < 0.001) and obesity (all P = 0.005). CONCLUSION In this study, six SNPs were explored and further identified to be associated with GDM risk, which suggested GRSs including these polymorphisms might participate in facilitating GDM risk. These findings offer the potential to improve our understanding of the etiology of GDM.
Collapse
Affiliation(s)
- Yi Shen
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, Nantong, Jiangsu Province, People's Republic of China
| | - Yulong Jia
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, Nantong, Jiangsu Province, People's Republic of China
| | - Yuandong Li
- School of Management, Xuzhou Medical University, Xuzhou, Jiangsu Province, People's Republic of China
| | - Xuefeng Gu
- Shanghai Key Laboratory for Molecular Imaging, University of Medicine and Health Sciences, Shanghai, People's Republic of China
| | - Guoqing Wan
- Shanghai Key Laboratory for Molecular Imaging, University of Medicine and Health Sciences, Shanghai, People's Republic of China
| | - Peng Zhang
- School of Clinical Medicine, University of Medicine and Health Sciences, Shanghai, People's Republic of China
| | - Yafeng Zhang
- Affiliated Hospital of Nantong University, Nantong University, Nantong, Jiangsu Province, People's Republic of China.
| | - Liying Jiang
- Shanghai Key Laboratory for Molecular Imaging, University of Medicine and Health Sciences, Shanghai, People's Republic of China.
| |
Collapse
|
20
|
Wang T, Wang XT, Lai R, Ling HW, Zhang F, Lu Q, Lv DM, Yin XX. MTNR1B Gene Polymorphisms Are Associated With the Therapeutic Responses to Repaglinide in Chinese Patients With Type 2 Diabetes Mellitus. Front Pharmacol 2019; 10:1318. [PMID: 31787898 PMCID: PMC6855210 DOI: 10.3389/fphar.2019.01318] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 10/15/2019] [Indexed: 12/14/2022] Open
Abstract
The objective of this study was to investigate whether MTNR1B gene variants influence repaglinide response in Chinese patients with newly diagnosed type 2 diabetes mellitus (T2DM). A total of 300 patients with T2DM and 200 control subjects were enrolled to identify MTNR1B rs10830963 and rs1387153 genotypes by real-time polymerase chain reaction (PCR), with subsequent high-resolution melting (HRM) analysis. Ninety-five patients with newly diagnosed T2DM were randomly selected to undergo 8 weeks of repaglinide treatment (3 mg/day). After 8-week repaglinide monotherapy, patients with at least one G allele of MTNR1B rs10830963 showed a smaller decrease in fasting plasma glucose (FPG) (P = 0.031) and a smaller increase in homeostasis model assessment for beta cell function (HOMA-B) (P = 0.002) levels than those with the CC genotype did. The T allele carriers at rs1387153 exhibited a smaller decrease in FPG (P = 0.007) and smaller increases in postprandial serum insulin (PINS) (P = 0.016) and HOMA-B (P < 0.001) levels compared to individuals with the CC genotype. These data suggest that the MTNR1B rs10830963 and rs1387153 polymorphisms are associated with repaglinide monotherapy efficacy in Chinese patients with T2DM.
Collapse
Affiliation(s)
- Tao Wang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.,Department of Pharmacy, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Xiao-Tong Wang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Ran Lai
- Department of Pharmacy, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Hong-Wei Ling
- Department of Endocrinology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Fan Zhang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Qian Lu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Dong-Mei Lv
- Department of Pharmacy, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Xiao-Xing Yin
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| |
Collapse
|
21
|
Adeyemo AA, Zaghloul NA, Chen G, Doumatey AP, Leitch CC, Hostelley TL, Nesmith JE, Zhou J, Bentley AR, Shriner D, Fasanmade O, Okafor G, Eghan B Jr, Agyenim-Boateng K, Chandrasekharappa S, Adeleye J, Balogun W, Owusu S, Amoah A, Acheampong J, Johnson T, Oli J, Adebamowo C, Collins F, Dunston G, Rotimi CN; South Africa Zulu Type 2 Diabetes Case-Control Study. ZRANB3 is an African-specific type 2 diabetes locus associated with beta-cell mass and insulin response. Nat Commun 2019; 10:3195. [PMID: 31324766 DOI: 10.1038/s41467-019-10967-7] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 06/11/2019] [Indexed: 12/13/2022] Open
Abstract
Genome analysis of diverse human populations has contributed to the identification of novel genomic loci for diseases of major clinical and public health impact. Here, we report a genome-wide analysis of type 2 diabetes (T2D) in sub-Saharan Africans, an understudied ancestral group. We analyze ~18 million autosomal SNPs in 5,231 individuals from Nigeria, Ghana and Kenya. We identify a previously-unreported genome-wide significant locus: ZRANB3 (Zinc Finger RANBP2-Type Containing 3, lead SNP p = 2.831 × 10−9). Knockdown or genomic knockout of the zebrafish ortholog results in reduction in pancreatic β-cell number which we demonstrate to be due to increased apoptosis in islets. siRNA transfection of murine Zranb3 in MIN6 β-cells results in impaired insulin secretion in response to high glucose, implicating Zranb3 in β-cell functional response to high glucose conditions. We also show transferability in our study of 32 established T2D loci. Our findings advance understanding of the genetics of T2D in non-European ancestry populations. Type 2 diabetes (T2D) is prevalent in populations worldwide, however, mostly studied in European and mixed-ancestry populations. Here, the authors perform a genome-wide association study for T2D in over 5,000 sub-Saharan Africans and identify a locus, ZRANB3, that is specific for this population.
Collapse
|
22
|
Abstract
Despite considerable advances in the past few years, obesity and type 2 diabetes mellitus (T2DM) remain two major challenges for public health systems globally. In the past 9 years, genome-wide association studies (GWAS) have established a major role for genetic variation within the MTNR1B locus in regulating fasting plasma levels of glucose and in affecting the risk of T2DM. This discovery generated a major interest in the melatonergic system, in particular the melatonin MT2 receptor (which is encoded by MTNR1B). In this Review, we discuss the effect of melatonin and its receptors on glucose homeostasis, obesity and T2DM. Preclinical and clinical post-GWAS evidence of frequent and rare variants of the MTNR1B locus confirmed its importance in regulating glucose homeostasis and T2DM risk with minor effects on obesity. However, these studies did not solve the question of whether melatonin is beneficial or detrimental, an issue that will be discussed in the context of the peculiarities of the melatonergic system. Melatonin receptors might have therapeutic potential as they belong to the highly druggable G protein-coupled receptor superfamily. Clarifying the precise role of melatonin and its receptors on glucose homeostasis is urgent, as melatonin is widely used for other indications, either as a prescribed medication or as a supplement without medical prescription, in many countries in Europe and in the USA.
Collapse
Affiliation(s)
- Angeliki Karamitri
- Inserm, U1016, Institut Cochin, Paris, France
- CNRS UMR 8104, Paris, France
- Université Paris Descartes, Université Sorbonne Paris Cité, Paris, France
| | - Ralf Jockers
- Inserm, U1016, Institut Cochin, Paris, France.
- CNRS UMR 8104, Paris, France.
- Université Paris Descartes, Université Sorbonne Paris Cité, Paris, France.
| |
Collapse
|
23
|
Huang Q, Du J, Merriman C, Gong Z. Genetic, Functional, and Immunological Study of ZnT8 in Diabetes. Int J Endocrinol 2019; 2019:1524905. [PMID: 30936916 PMCID: PMC6413397 DOI: 10.1155/2019/1524905] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 11/14/2018] [Accepted: 12/05/2018] [Indexed: 12/11/2022] Open
Abstract
Zinc level in the body is finely regulated to maintain cellular function. Dysregulation of zinc metabolism may induce a variety of diseases, e.g., diabetes. Zinc participates in insulin synthesis, storage, and secretion by functioning as a "cellular second messenger" in the insulin signaling pathway and glucose homeostasis. The highest zinc concentration is in the pancreas islets. Zinc accumulation in cell granules is manipulated by ZnT8, a zinc transporter expressed predominately in pancreatic α and β cells. A common ZnT8 gene (SLC30A8) polymorphism increases the risk of type 2 diabetes mellitus (T2DM), and rare mutations may present protective effects. In type 1 diabetes mellitus (T1DM), autoantibodies show specificity for binding two variants of ZnT8 (R or W at amino acid 325) dictated by a polymorphism in SLC30A8. In this review, we summarize the structure, feature, functions, and polymorphisms of ZnT8 along with its association with diabetes and explore future study directions.
Collapse
Affiliation(s)
- Qiong Huang
- Department of Pharmacy, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China
| | - Jie Du
- Department of Pharmacy, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China
| | - Chengfeng Merriman
- Department of Physiology, Johns Hopkins School of Medicine, 725 North Wolfe Street, Baltimore, MD 21205, USA
| | - Zhicheng Gong
- Department of Pharmacy, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China
| |
Collapse
|
24
|
Liu J, Wang L, Qian Y, Dai J, Shen C, Jin G, Hu Z, Shen H. Association of 48 type 2 diabetes susceptibility loci with fasting plasma glucose and lipid levels in Chinese Hans. Diabetes Res Clin Pract 2018. [PMID: 29518490 DOI: 10.1016/j.diabres.2018.02.039] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
AIM Dozens of susceptibility loci have been identified by type 2 diabetes (T2D) genome wide association study (GWAS) in Europeans. In our previous studies, we systematically evaluated the association of 48 susceptibility loci with T2D risk in Chinese Hans. Because dyslipidemia and hyperglycemia are implicated in the pathogenic process of T2D, we further evaluated whether these 48 single nucleotide polymorphisms (SNPs) were related to fasting plasma glucose (FPG) or lipid levels in Chinese Hans. METHODS The 48 SNPs were genotyped by using the Taqman OpenArray Genotyping System and iPLEX Sequenom MassARRAY platform. Multiple linear regression was used to assess the relationship between genetic variants and FPG and lipid levels among 3281 non-diabetic, healthy Chinese Hans. RESULTS After adjusting for age, gender, body mass index (BMI), smoking status and drinking status, the T allele of rs13266634 in the SLC30A8 gene was significantly associated with decreased glucose level (β = -0.0119, P = 8.05 × 10-5), whereas the T allele of rs896854 in the TP53INP1 gene was associated with increased triglyceride (TG) level (β = 0.0342, P = 9.61 × 10-4) and decreased high-density lipoprotein cholesterol (HDL-C) level (β = -0.015, P = 3.24 × 10-3) after Bonferroni correction. We also conducted a meta-analysis consisted of 11 studies and confirmed that SNP rs896854 in the TP53INP1 gene was associated with T2D risk. CONCLUSION Our findings indicated that SNP rs13266634 in SLC30A8 was associated with glucose level and SNP rs896854 in TP53INP1 was associated with lipid level.
Collapse
Affiliation(s)
- Jia Liu
- Department of Health Promotion & Chronic Non-Communicable Disease Control, Wuxi Center for Disease Control and Prevention, Wuxi, Jiangsu, China
| | - Lu Wang
- Department of Health Promotion & Chronic Non-Communicable Disease Control, Wuxi Center for Disease Control and Prevention, Wuxi, Jiangsu, China
| | - Yun Qian
- Department of Health Promotion & Chronic Non-Communicable Disease Control, Wuxi Center for Disease Control and Prevention, Wuxi, Jiangsu, China.
| | - Juncheng Dai
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Guangfu Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhibin Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| |
Collapse
|
25
|
Benson MD, Khor CC, Gage PJ, Lehmann OJ. A targeted approach to genome-wide studies reveals new genetic associations with central corneal thickness. Mol Vis 2017; 23:952-962. [PMID: 29296075 PMCID: PMC5741379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 12/13/2017] [Indexed: 11/24/2022] Open
Abstract
PURPOSE To evaluate the ability of a targeted genome-wide association study (GWAS) to identify genes associated with central corneal thickness (CCT). METHODS A targeted GWAS was used to investigate whether ten candidate genes with known roles in corneal development were associated with CCT in two Singaporean populations. The single nucleotide polymorphisms (SNPs) within a 500 kb interval encompassing each candidate were analyzed, and in light of the resulting data, members of the Wnt pathway were subsequently screened using similar methodology. RESULTS Variants within the 500 kb interval encompassing three candidate genes, DKK1 (rs1896368, p=1.32×10-3), DKK2 (rs17510449, p=7.34×10-4), and FOXO1 (rs7326616, p=1.56×10-4 and rs4943785, p=1.19×10-3), were statistically significantly associated with CCT in the Singapore Indian population. DKK2 was statistically significantly associated with CCT in a separate Singapore Malaysian population (rs10015200, p=2.26×10-3). Analysis of Wnt signaling pathway genes in each population demonstrated that TCF7L2 (rs3814573, p=1.18×10-3), RYK (rs6763231, p=1.12×10-3 and rs4854785, p=1.11×10-3), and FZD8 (rs640827, p=5.17×10-4) were statistically significantly associated with CCT. CONCLUSIONS The targeted GWAS identified four genes (DKK1, DKK2, RYK, and FZD8) with novel associations with CCT and confirmed known associations with two genes, FOXO1 and TCF7L2. All six participate in the Wnt pathway, supporting a broader role for Wnt signaling in regulating the thickness of the cornea. In parallel, this study demonstrated that a hypothesis-driven candidate gene approach can identify associations in existing GWAS data sets.
Collapse
Affiliation(s)
- Matthew D. Benson
- Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Canada
| | | | - Philip J. Gage
- Department of Ophthalmology and Visual Science, Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI
| | - Ordan J. Lehmann
- Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Canada,Department of Medical Genetics, University of Alberta, Edmonton, Canada
| |
Collapse
|
26
|
Huang X, Fang S, Yang H, Gao J, He M, Ke S, Zhao Y, Chen C, Huang L. Evaluating the contribution of gut microbiome to the variance of porcine serum glucose and lipid concentration. Sci Rep 2017; 7:14928. [PMID: 29097803 DOI: 10.1038/s41598-017-15044-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 10/19/2017] [Indexed: 02/07/2023] Open
Abstract
Serum glucose and lipids are important indicators for host metabolic condition. Interaction of host and gut microbes regulates the metabolism process. However, how much the gut microbiome contributes to the variance of serum glucose and lipids is largely unknown. Here we carried out a 16S rRNA gene based association study between cecum microbiome and the concentration of serum glucose and lipids in 240 Chinese Erhualian pigs. We identified tens of bacterial taxa associated with serum glucose and lipids. The butyrate-producing bacteria were significantly associated with serum glucose level. The pathogenic bacteria belonging to Proteobacteria and Fusobacteria showed significant associations with increased serum lipid levels, while the bacteria Lactobacillus and Bacilli had negative correlations with serum lipids. Cross-validation analysis revealed that 23.8% variation of serum glucose and 1.6%~6.0% variations of serum lipids were explained by gut microbiome. Furthermore, predicted function capacities related to nutrition intake, transport and carbohydrate metabolism were significantly associated with serum glucose level, while the pathways related to antioxidant metabolism and bile synthesis tended to be associated with serum lipid level. The results provide meaningful information to get insight into the effect of gut microbiome on serum glucose and lipid levels in pigs.
Collapse
|
27
|
Abstract
PURPOSE OF REVIEW Type 2 diabetes (T2D) is a complex genetic metabolic disorder. T2D heritability has been estimated around 40-70%. In the last decade, exponential progress has been made in identifying T2D genetic determinants, through genome-wide association studies (GWAS). Among single-nucleotide polymorphisms mostly associated with T2D risk, rs10830963 is located in the MTNR1B gene, encoding one of the two receptors of melatonin, a neurohormone involved in circadian rhythms. Subsequent studies aiming to disentangle the role of MTNR1B in T2D pathophysiology led to controversies. In this review, we will tackle them and will try to give some directions to get a better view of MTNR1B contribution to T2D pathophysiology. RECENT FINDINGS Recent studies either based on genetic/genomic analyses, clinical/epidemiology data, functional analyses at rs10830963 locus, insulin secretion assays in response to melatonin (involving or not MTNR1B) or animal model analyses have led to strong controversies at each level of interpretation. We discuss possible caveats in these studies and present ways to go beyond these issues, towards a better understanding of T2D molecular mechanisms, keeping in mind that melatonin is a versatile hormone and regulates many functions via its primary role in the body clock.
Collapse
Affiliation(s)
- Amélie Bonnefond
- CNRS UMR 8199. European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Pôle Recherche-1er - 1er étage Aile Ouest, 1 place de Verdun, 59045, Lille Cedex, France.
| | - Philippe Froguel
- CNRS UMR 8199. European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Pôle Recherche-1er - 1er étage Aile Ouest, 1 place de Verdun, 59045, Lille Cedex, France
- Genomics of Common Disease, Imperial College London, London, W12 0NN, UK
| |
Collapse
|
28
|
Wheeler E, Marenne G, Barroso I. Genetic aetiology of glycaemic traits: approaches and insights. Hum Mol Genet 2017; 26:R172-R184. [PMID: 28977447 PMCID: PMC5886471 DOI: 10.1093/hmg/ddx293] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 07/18/2017] [Accepted: 07/21/2017] [Indexed: 12/17/2022] Open
Abstract
Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.
Collapse
Affiliation(s)
- Eleanor Wheeler
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Gaëlle Marenne
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Inês Barroso
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK
| |
Collapse
|
29
|
Stanfill A, Simpson C, Sherwood P, Poloyac S, Crago E, Kim H, Conley Y. A pilot study on the impact of dopamine, serotonin, and brain-derived neurotrophic factor genotype on long-term functional outcomes after subarachnoid hemorrhage. SAGE Open Med 2017; 5:2050312117726725. [PMID: 28894586 PMCID: PMC5582657 DOI: 10.1177/2050312117726725] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 07/23/2017] [Indexed: 12/01/2022] Open
Abstract
Objectives: Many that survive an aneurysmal subarachnoid hemorrhage experience lasting physical disability, which might be improved by medications with effects on the dopaminergic, serotonergic, and brain-derived neurotrophic factor neurotransmitter systems. But it is not clear which patients are most likely to benefit from these therapies. The purpose of this pilot study was to explore the relationship of genetic polymorphisms in these pathways with 12-month functional outcomes after aneurysmal subarachnoid hemorrhage. Methods: Subjects were recruited at the time of admission as a part of a larger parent study. Genotypes were generated using the Affymetrix genome-wide human single-nucleotide polymorphism array 6.0. Those within dopaminergic, serotonergic, and brain-derived neurotrophic factor pathways were analyzed for associations with functional outcomes at 12 months post aneurysmal subarachnoid hemorrhage using the Glasgow Outcome Scale and the Modified Rankin Scale. Results: The 154 subjects were 55.8 ± 11.3 years old and 74% female; they had Fisher scores of 2.95 ± 0.67, Hunt/Hess scores of 2.66 ± 1.13, and admission Glasgow Coma Scale scores of 12.52 ± 3.79. Single-nucleotide polymorphisms in the serotonin receptor genes 1B and 1E and dopamine receptor D2 were associated with greater disability (odds ratio: 3.88–3.25, confidence interval: 1.01–14.77), while single-nucleotide polymorphisms in the serotonin receptor genes 2A and 2C and dopamine receptor D5 conferred a risk of poor recovery (odds ratio: 3.31–2.32, confidence interval: 1.00–10.80). Single-nucleotide polymorphisms within the same serotonin genes, and within the dopamine receptor gene D2, were associated with greater recovery after aneurysmal subarachnoid hemorrhage (odds ratio: 0.17–0.34, confidence interval: 0.05–0.89). Conclusions: These data demonstrate that there may be an association between genetic factors and functional outcomes post stroke.
Collapse
Affiliation(s)
- Ansley Stanfill
- Acute and Tertiary Care, College of Nursing, The University of Tennessee Health Science Center, Memphis, TN, USA
- Health Promotion & Development, School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Genetics, Genomics and Informatics, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN, USA
- Ansley Stanfill, Acute and Tertiary Care, College of Nursing, The University of Tennessee Health Science Center, 71 Manassas St #425, Memphis, TN 38163, USA.
| | - Claire Simpson
- Department of Genetics, Genomics and Informatics, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Paula Sherwood
- Acute & Tertiary Care, School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA
| | - Samuel Poloyac
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Elizabeth Crago
- Acute & Tertiary Care, School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA
| | - Hyungsuk Kim
- National Institute of Nursing Research, National Institutes of Health, Bethesda, MD, USA
| | - Yvette Conley
- Health Promotion & Development, School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| |
Collapse
|
30
|
Shi Y, Li Y, Wang J, Wang C, Fan J, Zhao J, Yin L, Liu X, Zhang D, Li L. Meta-analyses of the association of G6PC2 allele variants with elevated fasting glucose and type 2 diabetes. PLoS One 2017; 12:e0181232. [PMID: 28704540 DOI: 10.1371/journal.pone.0181232] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 06/28/2017] [Indexed: 12/19/2022] Open
Abstract
Objective To collectively evaluate the association of glucose-6-phosphatase catalytic unit 2 (G6PC2) allele variants with elevated fasting glucose (FG) and type 2 diabetes (T2D). Design Meta-analysis Data sources PubMed, Web of Knowledge and Embase databases. Study selection Full text articles of studies that identified an association of G6PC2 with T2D and elevated FG. Patient involvement There was no T2D patient involvement in the analyses on the association of FG with G6PC2, there were T2D patients and non-diabetes patient involvement in the analyses on the association of T2D with G6PC2. Statistical analysis Random-effects meta-analyses were used to calculate the pool effect sizes. I2 metric and H2 tests were used to calculate the heterogeneity. Begg's funnel plot and Egger’s linear regression test were done to assess publication bias. Results Of the 423 studies identified, 21 were eligible and included. Data on three loci (rs560887, rs16856187 and rs573225) were available. The G allele at rs560887 in three ethnicities, the C allele at rs16856187 and the A allele at rs573225 all had a positive association with elevated FG. Per increment of G allele at rs560887 and A allele at rs573225 resulted in a FG 0.070 mmol/l and 0.075 mmol/l higher (ß (95% CI) = 0.070 (0.060, 0.079), p = 4.635e-50 and 0.075 (0.065, 0.085), p = 5.856e-48, respectively). With regard to the relationship of rs16856187 and FG, an increase of 0.152 (95% CI: 0.034–0.270; p = 0.011) and 0.317 (95% CI: 0.193–0.442, p = 6.046e-07) was found in the standardized mean difference (SMD) of FG for the AC and CC genotypes, respectively, when compared with the AA reference genotype. However, the G-allele of rs560887 in Caucasians under the additive model and the C-allele of rs16856187 under the allele and dominant models were associated with a decreased risk of T2D (OR (95% CI) = 0.964 (0.947, 0.981), p = 0.570e-4; OR (95% CI) = 0.892 (0.832, 0.956), p = 0.001; and OR (95% CI) = 0.923(0.892, 0.955), p = 5.301e-6, respectively). Conclusions Our meta-analyses demonstrate that all three allele variants of G6PC2 (rs560887, rs16856187 and rs573225) are associated with elevated FG, with two variants (rs560887 in the Caucasians subgroup and rs16856187 under the allele and dominant model) being associated with T2D as well. Further studies utilizing larger sample sizes and different ethnic populations are needed to extend and confirm these findings.
Collapse
|
31
|
Chen G, Zhang Z, Adebamowo SN, Liu G, Adeyemo A, Zhou Y, Doumatey AP, Wang C, Zhou J, Yan W, Shriner D, Tekola-Ayele F, Bentley AR, Jiang C, Rotimi CN. Common and rare exonic MUC5B variants associated with type 2 diabetes in Han Chinese. PLoS One 2017; 12:e0173784. [PMID: 28346466 PMCID: PMC5367689 DOI: 10.1371/journal.pone.0173784] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 02/27/2017] [Indexed: 12/17/2022] Open
Abstract
Genome-wide association studies have identified over one hundred common genetic risk variants associated with type 2 diabetes (T2D). However, most of the heritability of T2D has not been accounted for. In this study, we investigated the contribution of rare and common variants to T2D susceptibility by analyzing exome array data in 1,908 Han Chinese genotyped with Affymetrix Axiom® Exome Genotyping Arrays. Based on the joint common and rare variants analysis of 57,704 autosomal SNPs within 12,244 genes using Sequence Kernel Association Tests (SKAT), we identified significant associations between T2D and 25 variants (9 rare and 16 common) in MUC5B, p-value 1.01×10−14. This finding was replicated (p = 0.0463) in an independent sample that included 10,401 unrelated individuals. Sixty-six of 1,553 possible haplotypes based on 25 SNPs within MUC5B showed significant association with T2D (Bonferroni corrected p values < 3.2×10−5). The expression level of MUC5B is significantly higher in pancreatic tissues of persons with T2D compared to those without T2D (p-value = 5×10−5). Our findings suggest that dysregulated MUC5B expression may be involved in the pathogenesis of T2D. As a strong candidate gene for T2D, MUC5B may play an important role in the mechanisms underlying T2D etiology and its complications.
Collapse
Affiliation(s)
- Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (CNR); (GC)
| | | | - Sally N. Adebamowo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Yanxun Zhou
- Suizhou Central Hospital, Suizhou, Hubei, China
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Fasil Tekola-Ayele
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (CNR); (GC)
| |
Collapse
|
32
|
Chidambaram M, Liju S, Saboo B, Sathyavani K, Viswanathan V, Pankratz N, Gross M, Mohan V, Radha V. Replication of genome-wide association signals in Asian Indians with early-onset type 2 diabetes. Acta Diabetol 2016; 53:915-923. [PMID: 27488727 DOI: 10.1007/s00592-016-0889-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 07/12/2016] [Indexed: 01/22/2023]
Abstract
AIMS To evaluate the association of 87 genetic variants previously associated with type 2 diabetes mellitus (T2DM) in genome-wide association studies of populations of European ancestry in an Asian Indian population with early-onset type 2 diabetes mellitus (EOT2DM). METHODS The study groups comprised of 877 type 2 diabetes individuals, 436 individuals with EOT2DM (age at diagnosis below 35 years), 441 individuals with older T2DM (diagnosis at 35 years or greater) and controls with normal glucose tolerance (NGT) (n = 400 younger than 35 years; n = 438 older than 35 years). The participants were genotyped for 87 SNPs from 44 genes and 27 intergenic loci. Associations were tested using logistic regression. RESULTS All the variants in TCF7L2 and CDKN2A/2B showed study-wide significance (p < 1.4 × 10-4) with T2DM, but only rs7903146, rs12243326, rs12255372 of TCF7L2 and rs7020996 of CDKN2A/2B showed study-wide significance (p < 1.4 × 10-4) with EOT2DM in this population. In addition, an intergenic SNP on chromosome 1 (rs10493685) was also shown to be study-wide significant (p = 7.1 × 10-6). Several additional SNPs previously associated with T2DM reached borderline significance in this study, but may have been limited by relatively low sample numbers. Various other SNPs of T2DM were not associated with EOT2DM. CONCLUSIONS Some of the variants in TCF7L2 and CDKN2A/2B associated with T2DM are associated with EOT2DM as well. An intergenic SNP on chromosome 1p31 showed association only with early-onset T2DM in this Asian Indian population. The lack of association with many other SNPs of T2DM may be a reflection of the lack of power of the study, sample size, differences in the frequencies of genetic polymorphisms in different ethnic groups, effect sizes, as well as ancestral differences in pattern of LD between the genetic variants involved in early- and late-onset T2DM.
Collapse
Affiliation(s)
- Manickam Chidambaram
- Madras Diabetes Research Foundation, 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
- Division of Cardiovascular Research, Sidra Medical and Research Center, Doha, Qatar
| | - Samuel Liju
- Madras Diabetes Research Foundation, 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Banshi Saboo
- Diabetologist and Endocrine and Metabolic Physician at Diabetes Care and Hormone Clinic, Ahmedabad, Gujarat, India
| | - Kumpatla Sathyavani
- M.V. Hospital for Diabetes and Prof. M. Viswanathan Diabetes Research Centre, Chennai, Tamil Nadu, India
| | - Vijay Viswanathan
- M.V. Hospital for Diabetes and Prof. M. Viswanathan Diabetes Research Centre, Chennai, Tamil Nadu, India
| | - Nathan Pankratz
- Department of Laboratory Medicine Pathology, Medical School University of Minnesota, Minneapolis, MN, USA
| | - Myron Gross
- Department of Laboratory Medicine Pathology, Medical School University of Minnesota, Minneapolis, MN, USA
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation, 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
- Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases Prevention and Control, IDF Centre of Education, Chennai, India
| | - Venkatesan Radha
- Madras Diabetes Research Foundation, 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India.
| |
Collapse
|
33
|
Langlois C, Abadi A, Peralta-Romero J, Alyass A, Suarez F, Gomez-Zamudio J, Burguete-Garcia AI, Yazdi FT, Cruz M, Meyre D. Evaluating the transferability of 15 European-derived fasting plasma glucose SNPs in Mexican children and adolescents. Sci Rep 2016; 6:36202. [PMID: 27782183 PMCID: PMC5080582 DOI: 10.1038/srep36202] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 10/12/2016] [Indexed: 12/15/2022] Open
Abstract
Genome wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with fasting plasma glucose (FPG) in adult European populations. The contribution of these SNPs to FPG in non-Europeans and children is unclear. We studied the association of 15 GWAS SNPs and a genotype score (GS) with FPG and 7 metabolic traits in 1,421 Mexican children and adolescents from Mexico City. Genotyping of the 15 SNPs was performed using TaqMan Open Array. We used multivariate linear regression models adjusted for age, sex, body mass index standard deviation score, and recruitment center. We identified significant associations between 3 SNPs (G6PC2 (rs560887), GCKR (rs1260326), MTNR1B (rs10830963)), the GS and FPG level. The FPG risk alleles of 11 out of the 15 SNPs (73.3%) displayed significant or non-significant beta values for FPG directionally consistent with those reported in adult European GWAS. The risk allele frequencies for 11 of 15 (73.3%) SNPs differed significantly in Mexican children and adolescents compared to European adults from the 1000G Project, but no significant enrichment in FPG risk alleles was observed in the Mexican population. Our data support a partial transferability of European GWAS FPG association signals in children and adolescents from the admixed Mexican population.
Collapse
Affiliation(s)
- Christine Langlois
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Arkan Abadi
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Jesus Peralta-Romero
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Akram Alyass
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Fernando Suarez
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Jaime Gomez-Zamudio
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Ana I Burguete-Garcia
- Centro de investigación sobre enfermedades infecciosas. Instituto Nacional de Salud Pública. Cuernavaca, Morelos, Mexico
| | - Fereshteh T Yazdi
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| |
Collapse
|
34
|
Tin A, Balakrishnan P, Beaty TH, Boerwinkle E, Hoogeveen RC, Young JH, Kao WHL. GCKR and PPP1R3B identified as genome-wide significant loci for plasma lactate: the Atherosclerosis Risk in Communities (ARIC) study. Diabet Med 2016; 33:968-75. [PMID: 26433129 PMCID: PMC4819009 DOI: 10.1111/dme.12971] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/28/2015] [Indexed: 12/22/2022]
Abstract
AIM To investigate the genetic influence of circulating lactate level, a marker of oxidative capacity associated with diabetes. METHODS We conducted a genome-wide association study of log-transformed plasma lactate levels in 6901 European-American participants in the Atherosclerosis Risk in Communities study. For regions that achieved genome-wide significance in European-American participants, we conducted candidate region analysis in African-American subjects and tested for interaction between metformin use and the index single nucleotide polymorphisms for plasma lactate in European-American subjects. RESULTS The genome-wide association study in European-American subjects identified two genome-wide significant loci, GCKR (rs1260326, T allele β=0.08; P=1.8×10(-47) ) and PPP1R3B/LOC157273 (rs9987289, A allele β=0.06; P=1.6×10(-9) ). The index single nucleotide polymorphisms in these two loci explain 3.3% of the variance in log-transformed plasma lactate levels among the European-American subjects. In the African-American subjects, based on a region-significant threshold, the index single nucleotide polymorphism at GCKR was associated with plasma lactate but that at PPP1R3B/LOC157273 was not. Metformin use appeared to strengthen the association between the index single nucleotide polymorphism at PPP1R3B/LOC157273 and plasma lactate in European-American subjects (P for interaction=0.01). CONCLUSIONS We identified GCKR and PPP1R3B/LOC157273 as two genome-wide significant loci of plasma lactate. Both loci are associated with other diabetes-related phenotypes. These findings increase our understanding of the genetic control of lactate metabolism.
Collapse
Affiliation(s)
- A Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - P Balakrishnan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - T H Beaty
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - E Boerwinkle
- Human Genetics Center, University of Texas School of Public Health, Houston, TX, USA
| | - R C Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- Center for Cardiovascular Disease Prevention, Methodist DeBakey Heart and Vascular Center, Houston, TX, USA
| | - J H Young
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Medicine, The Johns Hopkins University, School of Medicine, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - W H L Kao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| |
Collapse
|
35
|
Ali S, Nafis S, Kalaiarasan P, Rai E, Sharma S, Bamezai RN. Understanding Genetic Heterogeneity in Type 2 Diabetes by Delineating Physiological Phenotypes: SIRT1 and its Gene Network in Impaired Insulin Secretion. Rev Diabet Stud 2016; 13:17-34. [PMID: 27563694 DOI: 10.1900/rds.2016.13.17] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Type 2 diabetes (T2D) is a chronic metabolic disease which shows an exponential increase in all parts of the world. However, the disease is controllable by early detection and modified lifestyle. A series of factors have been associated with the pathogenesis of diabetes, and genes are considered to play a critical role. The individual risk of developing T2D is determined by an altered genetic background of the en-zymes involved in several metabolism-related biological mechanisms, including glucose homeostasis, insulin metab-olism, the glucose and ion transporters involved in glucose uptake, transcription factors, signaling intermediates of insulin signaling pathways, insulin production and secretion, pancreatic tissue development, and apoptosis. However, many candidate genes have shown heterogeneity of associations with the disease in different populations. A possible approach to resolving this complexity and under-standing genetic heterogeneity is to delineate the physiological phenotypes one by one as studying them in combination may cause discrepancies in association studies. A systems biology approach involving regulatory proteins, transcription factors, and microRNAs is one way to understand and identify key factors in complex diseases such as T2D. Our earlier studies have screened more than 100 single nucleotide polymorphisms (SNPs) belonging to more than 60 globally known T2D candidate genes in the Indian population. We observed that genes invariably involved in the activity of pancreatic β-cells provide susceptibility to type 2 diabetes (T2D). Encouraged by these results, we attempted to delineate in this review one of the commonest physiological phenotypes in T2D, namely impaired insulin secretion, as the cause of hyperglycemia. This review is also intended to explain the genetic basis of the pathophysiology of insulin secretion in the context of variations in the SIRT1 gene, a major switch that modulates insulin secretion, and a set of other genes such as HHEX, PGC-α, TCF7L2, UCP2, and ND3 which were found to be in association with T2D. The review aims to look at the genotypic and transcriptional regulatory relationships with the disease phenotype.
Collapse
Affiliation(s)
- Shafat Ali
- National Centre of Applied Human Genetics, School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, India
| | - Shazia Nafis
- National Centre of Applied Human Genetics, School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, India
| | - Ponnusamy Kalaiarasan
- National Centre of Applied Human Genetics, School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, India
| | - Ekta Rai
- Human Genetics Research Group, Department of Biotechnology, Shri Mata Vaishno Devi University, Katra, 182320, India
| | - Swarkar Sharma
- Human Genetics Research Group, Department of Biotechnology, Shri Mata Vaishno Devi University, Katra, 182320, India
| | - Rameshwar N Bamezai
- National Centre of Applied Human Genetics, School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, India
| |
Collapse
|
36
|
Adeyemo AA, Tekola-Ayele F, Doumatey AP, Bentley AR, Chen G, Huang H, Zhou J, Shriner D, Fasanmade O, Okafor G, Eghan B, Agyenim-Boateng K, Adeleye J, Balogun W, Elkahloun A, Chandrasekharappa S, Owusu S, Amoah A, Acheampong J, Johnson T, Oli J, Adebamowo C, Collins F, Dunston G, Rotimi CN. Evaluation of Genome Wide Association Study Associated Type 2 Diabetes Susceptibility Loci in Sub Saharan Africans. Front Genet 2015; 6:335. [PMID: 26635871 PMCID: PMC4656823 DOI: 10.3389/fgene.2015.00335] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 11/09/2015] [Indexed: 01/31/2023] Open
Abstract
Genome wide association studies (GWAS) for type 2 diabetes (T2D) undertaken in European and Asian ancestry populations have yielded dozens of robustly associated loci. However, the genomics of T2D remains largely understudied in sub-Saharan Africa (SSA), where rates of T2D are increasing dramatically and where the environmental background is quite different than in these previous studies. Here, we evaluate 106 reported T2D GWAS loci in continental Africans. We tested each of these SNPs, and SNPs in linkage disequilibrium (LD) with these index SNPs, for an association with T2D in order to assess transferability and to fine map the loci leveraging the generally reduced LD of African genomes. The study included 1775 unrelated Africans (1035 T2D cases, 740 controls; mean age 54 years; 59% female) enrolled in Nigeria, Ghana, and Kenya as part of the Africa America Diabetes Mellitus (AADM) study. All samples were genotyped on the Affymetrix Axiom PanAFR SNP array. Forty-one of the tested loci showed transferability to this African sample (p < 0.05, same direction of effect), 11 at the exact reported SNP and 30 others at SNPs in LD with the reported SNP (after adjustment for the number of tested SNPs). TCF7L2 SNP rs7903146 was the most significant locus in this study (p = 1.61 × 10−8). Most of the loci that showed transferability were successfully fine-mapped, i.e., localized to smaller haplotypes than in the original reports. The findings indicate that the genetic architecture of T2D in SSA is characterized by several risk loci shared with non-African ancestral populations and that data from African populations may facilitate fine mapping of risk loci. The study provides an important resource for meta-analysis of African ancestry populations and transferability of novel loci.
Collapse
Affiliation(s)
- Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - Fasil Tekola-Ayele
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - Hanxia Huang
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | | | - Godfrey Okafor
- Department of Medicine, University of Nigeria Teaching Hospital Enugu, Nigeria
| | - Benjamin Eghan
- Department of Medicine, University of Science and Technology Kumasi, Ghana
| | | | - Jokotade Adeleye
- Department of Medicine, College of Medicine, University of Ibadan Ibadan, Nigeria
| | - Williams Balogun
- Department of Medicine, College of Medicine, University of Ibadan Ibadan, Nigeria
| | - Abdel Elkahloun
- National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | | | - Samuel Owusu
- Department of Medicine and Therapeutics, University of Ghana Medical School Accra, Ghana
| | - Albert Amoah
- Department of Medicine and Therapeutics, University of Ghana Medical School Accra, Ghana
| | - Joseph Acheampong
- Department of Medicine, University of Science and Technology Kumasi, Ghana
| | - Thomas Johnson
- Department of Medicine, University of Lagos Lagos, Nigeria
| | - Johnnie Oli
- Department of Medicine, University of Nigeria Teaching Hospital Enugu, Nigeria
| | - Clement Adebamowo
- Institute of Human Virology, School of Medicine, University of Maryland Baltimore, MD, USA
| | | | - Georgia Dunston
- National Human Genome Center at Howard University Washington, DC, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| |
Collapse
|
37
|
Abstract
Type 2 diabetes (T2D) is a global health problem showing substantial ethnic disparity in disease prevalence. African Americans have one of the highest prevalence of T2D in the USA but little is known about their genetic risks. This review summarizes the findings of genetic regions and loci associated with T2D and related glycemic traits using linkage, admixture, and association approaches in populations of African ancestry. In particular, findings from genome-wide association and exome chip studies suggest the presence of both ancestry-specific and shared loci for T2D and glycemic traits. Among the European-identified loci that are transferable to individuals of African ancestry, allelic heterogeneity as well as differential linkage disequilibrium and risk allele frequencies pose challenges and opportunities for fine mapping and identification of causal variant(s) by trans-ancestry meta-analysis. More genetic research is needed in African ancestry populations including the next-generation sequencing to improve the understanding of genetic architecture of T2D.
Collapse
Affiliation(s)
- Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA,
| |
Collapse
|
38
|
Iyengar SK, Sedor JR, Freedman BI, Kao WHL, Kretzler M, Keller BJ, Abboud HE, Adler SG, Best LG, Bowden DW, Burlock A, Chen YDI, Cole SA, Comeau ME, Curtis JM, Divers J, Drechsler C, Duggirala R, Elston RC, Guo X, Huang H, Hoffmann MM, Howard BV, Ipp E, Kimmel PL, Klag MJ, Knowler WC, Kohn OF, Leak TS, Leehey DJ, Li M, Malhotra A, März W, Nair V, Nelson RG, Nicholas SB, O’Brien SJ, Pahl MV, Parekh RS, Pezzolesi MG, Rasooly RS, Rotimi CN, Rotter JI, Schelling JR, Seldin MF, Shah VO, Smiles AM, Smith MW, Taylor KD, Thameem F, Thornley-Brown DP, Truitt BJ, Wanner C, Weil EJ, Winkler CA, Zager PG, Igo RP, Hanson RL, Langefeld CD. Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND). PLoS Genet 2015; 11:e1005352. [PMID: 26305897 PMCID: PMC4549309 DOI: 10.1371/journal.pgen.1005352] [Citation(s) in RCA: 93] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Accepted: 06/10/2015] [Indexed: 11/28/2022] Open
Abstract
Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD. Type 2 diabetes is the most common cause of severe kidney disease worldwide and diabetic kidney disease (DKD) associates with premature death. Individuals of non-European ancestry have the highest burden of type 2 DKD; hence understanding the causes of DKD remains critical to reducing health disparities. Family studies demonstrate that genes regulate the onset and progression of DKD; however, identifying these genes has proven to be challenging. The Family Investigation of Diabetes and Nephropathy consortium (FIND) recruited a large multi-ethnic collection of individuals with type 2 diabetes with and without kidney disease in order to detect genes associated with DKD. FIND discovered and replicated a DKD-associated genetic locus on human chromosome 6q25.2 (rs955333) between the SCAF8 and CNKSR genes. Findings were supported by significantly different expression of genes in this region from kidney tissue of subjects with, versus without DKD. The present findings identify a novel kidney disease susceptibility locus in individuals with type 2 diabetes which is consistent across subjects of differing ancestries. In addition, FIND results provide a rich catalogue of genetic variation in DKD patients for future research on the genetic architecture regulating this common and devastating disease.
Collapse
Affiliation(s)
- Sudha K. Iyengar
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail: (SKI); (JRS); (BIF)
| | - John R. Sedor
- Departments of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
- Departments of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail: (SKI); (JRS); (BIF)
| | - Barry I. Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- * E-mail: (SKI); (JRS); (BIF)
| | - W. H. Linda Kao
- Department of Epidemiology and Medicine, John Hopkins University, Baltimore, Maryland, United States of America
| | - Matthias Kretzler
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Benjamin J. Keller
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Hanna E. Abboud
- Department of Medicine/Nephrology, The University of Texas Health Science Center, San Antonio, Texas, United States of America
| | - Sharon G. Adler
- Department of Medicine, Division of Nephrology and Hypertension, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Lyle G. Best
- Missouri Breaks Industries Research, Timber Lake, South Dakota, United States of America
| | - Donald W. Bowden
- Department of Biochemistry, Center for Human Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Allison Burlock
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Shelley A. Cole
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Mary E. Comeau
- Center for Public Health Genomics and Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, United States of America
| | - Jeffrey M. Curtis
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Jasmin Divers
- Center for Public Health Genomics and Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, United States of America
| | - Christiane Drechsler
- University Hospital Würzburg, Renal Division and Comprehensive Heart Failure Center, Würzburg, Germany
| | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Robert C. Elston
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Huateng Huang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America
| | | | - Barbara V. Howard
- MedStar Health Research Institute, Hyattsville, Maryland, United States of America
| | - Eli Ipp
- Department of Medicine, Section of Diabetes and Metabolism, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Paul L. Kimmel
- Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States of America
| | - Michael J. Klag
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - William C. Knowler
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Orly F. Kohn
- Department of Medicine, University of Chicago Medicine, Chicago, Illinois, United States of America
| | - Tennille S. Leak
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - David J. Leehey
- Department of Medicine, Loyola School of Medicine, Maywood, Illinois, United States of America
| | - Man Li
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Alka Malhotra
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Winfried März
- Heidelberg University and Synlab Academy, University of Graz, Graz, Austria
| | - Viji Nair
- Department of Internal Medicine/Nephrology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Robert G. Nelson
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Susanne B. Nicholas
- Department of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Stephen J. O’Brien
- Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg, Russia, and Oceanographic Center, Nova Southeastern University, Ft. Lauderdale, Florida, United States of America
| | - Madeleine V. Pahl
- Department of Medicine, University of California, Irvine, Irvine, California, United States of America
| | - Rulan S. Parekh
- Departments of Paediatrics and Medicine, Hospital for Sick Children, University Health Network and the University of Toronto, Toronto, Ontario, Canada
| | - Marcus G. Pezzolesi
- Department of Medicine, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Rebekah S. Rasooly
- National Institute of Diabetes and Digestive Disease, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, Bethesda, Maryland, United States of America
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Jeffrey R. Schelling
- Departments of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Michael F. Seldin
- Department of Biochemistry and Molecular Medicine, UC Davis School of Medicine, Davis, California, United States of America
| | - Vallabh O. Shah
- Department of Biochemistry & Molecular Biology, University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Adam M. Smiles
- Joslin Diabetes Center, Section on Genetics and Epidemiology, Boston, Massachusetts, United States of America
| | - Michael W. Smith
- National Human Genome Research Institute, Rockville, Maryland, United States of America
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Farook Thameem
- Department of Medicine, The University of Texas Health Science Center, San Antonio, Texas, United States of America
| | | | - Barbara J. Truitt
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Christoph Wanner
- Department of Medicine, Division of Nephrology, University Hospital Würzburg, Würzburg, Germany
| | - E. Jennifer Weil
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Cheryl A. Winkler
- Center for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America
| | - Philip G. Zager
- Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Robert P. Igo
- Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Robert L. Hanson
- National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona, United States of America
| | - Carl D. Langefeld
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | | |
Collapse
|
39
|
Zheng C, Dalla Man C, Cobelli C, Groop L, Zhao H, Bale AE, Shaw M, Duran E, Pierpont B, Caprio S, Santoro N. A common variant in the MTNR1b gene is associated with increased risk of impaired fasting glucose (IFG) in youth with obesity. Obesity (Silver Spring) 2015; 23:1022-9. [PMID: 25919927 PMCID: PMC4414047 DOI: 10.1002/oby.21030] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Accepted: 12/21/2014] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To explore the role of MTNR1B rs10830963 and G6PC2 rs560887 variants in the pathogenesis of impaired fasting glucose (IFG) in obese adolescents. METHODS A total of 346 Caucasians, 218 African-Americans, and 217 Hispanics obese children and adolescents underwent an oral glucose tolerance test (OGTT) and 518 underwent the evaluation of insulin secretion by the oral minimal model (OMM). Also, 274 subjects underwent a second OGTT after 3.0 ± 2.1 years. RESULTS The MTNR1B rs10830963 variant was associated with higher fasting glucose levels and lower dynamic beta-cell response in Caucasians and Hispanics (P < 0.05) and conferred an increased risk of showing IFG to Caucasians (P = 0.05), African-Americans (P = 0.0066), and Hispanics (P = 0.024). Despite the association between the G6PC2 rs560887 and higher fasting glucose levels (P < 0.05), there was no association between this variant and IFG at baseline or at follow-up (all P > 0.10). CONCLUSIONS It has been shown for the first time in obese youth that the MTNR1B variant is associated with an increased risk of IFG.
Collapse
Affiliation(s)
- Chao Zheng
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
- Department of Endocrinology, The 2 Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Leif Groop
- Department of Clinical Sciences/Diabetes & Endocrinology and Lund University Diabetes Centre, Lund University, University Hospital, Malmoe, Malmoe, Sweden
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT
| | - Allen E Bale
- Department of Genetics, Yale University School of Medicine, New Haven, CT
| | - Melissa Shaw
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Elvira Duran
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Bridget Pierpont
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Sonia Caprio
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Nicola Santoro
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| |
Collapse
|
40
|
Daya M, van der Merwe L, van Helden PD, Möller M, Hoal EG. Investigating the Role of Gene-Gene Interactions in TB Susceptibility. PLoS One 2015; 10:e0123970. [PMID: 25919455 PMCID: PMC4412713 DOI: 10.1371/journal.pone.0123970] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2014] [Accepted: 02/24/2015] [Indexed: 11/22/2022] Open
Abstract
Tuberculosis (TB) is the second leading cause of mortality from infectious disease worldwide. One of the factors involved in developing disease is the genetics of the host, yet the field of TB susceptibility genetics has not yielded the answers that were expected. A commonly posited explanation for the missing heritability of complex disease is gene-gene interactions, also referred to as epistasis. In this study we investigate the role of gene-gene interactions in genetic susceptibility to TB using a cohort recruited from a high TB incidence community from Cape Town, South Africa. Our discovery data set incorporates genotypes from a large a number of candidate gene studies as well as genome-wide data. After limiting our search space to pairs of putative TB susceptibility genes, as well as pairs of genes that have been curated in online databases as potential interactors, we use statistical modelling to identify pairs of interacting SNPs. We attempt to validate the top models identified in our discovery data set using an independent genome-wide TB case-control data set from The Gambia. A number of models were successfully validated, indicating that interplay between the NRG1 - NRG3, GRIK1 - GRIK3 and IL23R - ATG4C gene pairs may modify susceptibility to TB. Gene pairs involved in the NF-κB pathway were also identified in the discovery data set (SFTPD - NOD2, ISG15 - TLR8 and NLRC5 - IL12RB1), but could not be tested in the Gambian study group due to lack of overlapping data.
Collapse
Affiliation(s)
- Michelle Daya
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Lize van der Merwe
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Paul D. van Helden
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Marlo Möller
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Eileen G. Hoal
- SA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| |
Collapse
|
41
|
Sobota RS, Shriner D, Kodaman N, Goodloe R, Zheng W, Gao YT, Edwards TL, Amos CI, Williams SM. Addressing population-specific multiple testing burdens in genetic association studies. Ann Hum Genet 2015; 79:136-47. [PMID: 25644736 DOI: 10.1111/ahg.12095] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 10/06/2014] [Indexed: 01/06/2023]
Abstract
The number of effectively independent tests performed in genome-wide association studies (GWAS) varies by population, making a universal P-value threshold inappropriate. We estimated the number of independent SNPs in Phase 3 HapMap samples by: (1) the LD-pruning function in PLINK, and (2) an autocorrelation-based approach. Autocorrelation was also used to estimate the number of independent SNPs in whole genome sequences from 1000 Genomes. Both approaches yielded consistent estimates of numbers of independent SNPs, which were used to calculate new population-specific thresholds for genome-wide significance. African populations had the most stringent thresholds (1.49 × 10(-7) for YRI at r(2) = 0.3), East Asian populations the least (3.75 × 10(-7) for JPT at r(2) = 0.3). We also assessed how using population-specific significance thresholds compared to using a single multiple testing threshold at the conventional 5 × 10(-8) cutoff. Applied to a previously published GWAS of melanoma in Caucasians, our approach identified two additional genes, both previously associated with the phenotype. In a Chinese breast cancer GWAS, our approach identified 48 additional genes, 19 of which were in or near genes previously associated with the phenotype. We conclude that the conventional genome-wide significance threshold generates an excess of Type 2 errors, particularly in GWAS performed on more recently founded populations.
Collapse
Affiliation(s)
- Rafal S Sobota
- Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, Tennessee; Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire
| | | | | | | | | | | | | | | | | |
Collapse
|
42
|
Simpson CL, Wojciechowski R, Oexle K, Murgia F, Portas L, Li X, Verhoeven VJM, Vitart V, Schache M, Hosseini SM, Hysi PG, Raffel LJ, Cotch MF, Chew E, Klein BEK, Klein R, Wong TY, van Duijn CM, Mitchell P, Saw SM, Fossarello M, Wang JJ, Polašek O, Campbell H, Rudan I, Oostra BA, Uitterlinden AG, Hofman A, Rivadeneira F, Amin N, Karssen LC, Vingerling JR, Döring A, Bettecken T, Bencic G, Gieger C, Wichmann HE, Wilson JF, Venturini C, Fleck B, Cumberland PM, Rahi JS, Hammond CJ, Hayward C, Wright AF, Paterson AD, Baird PN, Klaver CCW, Rotter JI, Pirastu M, Meitinger T, Bailey-Wilson JE, Stambolian D. Genome-wide meta-analysis of myopia and hyperopia provides evidence for replication of 11 loci. PLoS One 2014; 9:e107110. [PMID: 25233373 PMCID: PMC4169415 DOI: 10.1371/journal.pone.0107110] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Accepted: 08/12/2014] [Indexed: 01/01/2023] Open
Abstract
Refractive error (RE) is a complex, multifactorial disorder characterized by a mismatch between the optical power of the eye and its axial length that causes object images to be focused off the retina. The two major subtypes of RE are myopia (nearsightedness) and hyperopia (farsightedness), which represent opposite ends of the distribution of the quantitative measure of spherical refraction. We performed a fixed effects meta-analysis of genome-wide association results of myopia and hyperopia from 9 studies of European-derived populations: AREDS, KORA, FES, OGP-Talana, MESA, RSI, RSII, RSIII and ERF. One genome-wide significant region was observed for myopia, corresponding to a previously identified myopia locus on 8q12 (p = 1.25×10−8), which has been reported by Kiefer et al. as significantly associated with myopia age at onset and Verhoeven et al. as significantly associated to mean spherical-equivalent (MSE) refractive error. We observed two genome-wide significant associations with hyperopia. These regions overlapped with loci on 15q14 (minimum p value = 9.11×10−11) and 8q12 (minimum p value 1.82×10−11) previously reported for MSE and myopia age at onset. We also used an intermarker linkage- disequilibrium-based method for calculating the effective number of tests in targeted regional replication analyses. We analyzed myopia (which represents the closest phenotype in our data to the one used by Kiefer et al.) and showed replication of 10 additional loci associated with myopia previously reported by Kiefer et al. This is the first replication of these loci using myopia as the trait under analysis. “Replication-level” association was also seen between hyperopia and 12 of Kiefer et al.'s published loci. For the loci that show evidence of association to both myopia and hyperopia, the estimated effect of the risk alleles were in opposite directions for the two traits. This suggests that these loci are important contributors to variation of refractive error across the distribution.
Collapse
Affiliation(s)
- Claire L. Simpson
- National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Robert Wojciechowski
- National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland, United States of America
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Konrad Oexle
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | - Federico Murgia
- Institute of Population Genetics, National Research Council of Italy, Sassari, Italy
| | - Laura Portas
- Institute of Population Genetics, National Research Council of Italy, Sassari, Italy
| | - Xiaohui Li
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Virginie J. M. Verhoeven
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Veronique Vitart
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, United Kingdom
| | - Maria Schache
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - S. Mohsen Hosseini
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada, and DCCT/EDIC Research Group, The Diabetes Control and Complications Trial and Follow-up Study, The Biostatistics Center, The George Washington University, Rockville, Maryland, United States of America
| | - Pirro G. Hysi
- Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Hospital, London, United Kingdom
| | - Leslie J. Raffel
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Mary Frances Cotch
- Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Emily Chew
- Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Barbara E. K. Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Tien Yin Wong
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Singapore Eye Research Institute, National University of Singapore, Singapore, Singapore
| | | | - Paul Mitchell
- Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, Australia
| | - Seang Mei Saw
- Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Maurizio Fossarello
- Dipartimento di Scienze Chirurgiche, Clinica Oculistica Universita' degli studi di Cagliari, Cagliari, Italy
| | - Jie Jin Wang
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, Australia
| | - DCCT/EDIC Research Group
- The Diabetes Control and Complications Trial and Follow-up Study, The Biostatistics Center, The George Washington University, Rockville, Maryland, United States of America
| | - Ozren Polašek
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, the Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, the Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, the Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, the Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Lennart C. Karssen
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Johannes R. Vingerling
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Angela Döring
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Thomas Bettecken
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Goran Bencic
- Department of Ophthalmology, Hospital “Sestre Milosrdnice”, Zagreb, Croatia
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - H.-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Cristina Venturini
- Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Hospital, London, United Kingdom
| | - Brian Fleck
- Princess Alexandra Eye Pavilion, Edinburgh, United Kingdom
| | - Phillippa M. Cumberland
- MRC Centre of Epidemiology for Child Health, Institute of Child Health, University College London, London, United Kingdom
| | - Jugnoo S. Rahi
- MRC Centre of Epidemiology for Child Health, Institute of Child Health, University College London, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Ulverscroft Vision Research Group, Institute of Child Health, University College London, London, United Kingdom
| | - Chris J. Hammond
- Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Hospital, London, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, United Kingdom
| | - Alan F. Wright
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew D. Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada, and DCCT/EDIC Research Group, The Diabetes Control and Complications Trial and Follow-up Study, The Biostatistics Center, The George Washington University, Rockville, Maryland, United States of America
| | - Paul N. Baird
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Caroline C. W. Klaver
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Mario Pirastu
- Institute of Population Genetics, National Research Council of Italy, Sassari, Italy
| | - Thomas Meitinger
- Institute of Human Genetics, Technische Universität München, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Joan E. Bailey-Wilson
- National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland, United States of America
- * E-mail:
| | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| |
Collapse
|
43
|
Ng MCY, Shriner D, Chen BH, Li J, Chen WM, Guo X, Liu J, Bielinski SJ, Yanek LR, Nalls MA, Comeau ME, Rasmussen-Torvik LJ, Jensen RA, Evans DS, Sun YV, An P, Patel SR, Lu Y, Long J, Armstrong LL, Wagenknecht L, Yang L, Snively BM, Palmer ND, Mudgal P, Langefeld CD, Keene KL, Freedman BI, Mychaleckyj JC, Nayak U, Raffel LJ, Goodarzi MO, Chen YDI, Taylor HA, Correa A, Sims M, Couper D, Pankow JS, Boerwinkle E, Adeyemo A, Doumatey A, Chen G, Mathias RA, Vaidya D, Singleton AB, Zonderman AB, Igo RP, Sedor JR, Kabagambe EK, Siscovick DS, McKnight B, Rice K, Liu Y, Hsueh WC, Zhao W, Bielak LF, Kraja A, Province MA, Bottinger EP, Gottesman O, Cai Q, Zheng W, Blot WJ, Lowe WL, Pacheco JA, Crawford DC, Grundberg E, Rich SS, Hayes MG, Shu XO, Loos RJF, Borecki IB, Peyser PA, Cummings SR, Psaty BM, Fornage M, Iyengar SK, Evans MK, Becker DM, Kao WHL, Wilson JG, Rotter JI, Sale MM, Liu S, Rotimi CN, Bowden DW. Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes. PLoS Genet 2014; 10:e1004517. [PMID: 25102180 PMCID: PMC4125087 DOI: 10.1371/journal.pgen.1004517] [Citation(s) in RCA: 150] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Accepted: 06/05/2014] [Indexed: 12/11/2022] Open
Abstract
Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15×10−94<P<5×10−8, odds ratio (OR) = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2×10−23 < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies. Despite the higher prevalence of type 2 diabetes (T2D) in African Americans than in Europeans, recent genome-wide association studies (GWAS) were examined primarily in individuals of European ancestry. In this study, we performed meta-analysis of 17 GWAS in 8,284 cases and 15,543 controls to explore the genetic architecture of T2D in African Americans. Following replication in additional 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry, we identified two novel and three previous reported T2D loci reaching genome-wide significance. We also examined 158 loci previously reported to be associated with T2D or regulating glucose homeostasis. While 56% of these loci were shared between African Americans and the other populations, the strongest associations in African Americans are often found in nearby single nucleotide polymorphisms (SNPs) instead of the original SNPs reported in other populations due to differential genetic architecture across populations. Our results highlight the importance of performing genetic studies in non-European populations to fine map the causal genetic variants.
Collapse
Affiliation(s)
- Maggie C. Y. Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Brian H. Chen
- Program on Genomics and Nutrition, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
- Center for Metabolic Disease Prevention, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
| | - Jiang Li
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Jiankang Liu
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Suzette J. Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Lisa R. Yanek
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Michael A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Mary E. Comeau
- Center for Public Health Genomics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Richard A. Jensen
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Daniel S. Evans
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, United States of America
| | - Yan V. Sun
- Department of Epidemiology and Biomedical Informatics, Emory University, Atlanta, Georgia, United States of America
| | - Ping An
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Sanjay R. Patel
- Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Loren L. Armstrong
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Lynne Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Lingyao Yang
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Beverly M. Snively
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nicholette D. Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Poorva Mudgal
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Carl D. Langefeld
- Center for Public Health Genomics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Keith L. Keene
- Department of Biology, Center for Health Disparities, East Carolina University, Greenville, North Carolina, United States of America
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Josyf C. Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Uma Nayak
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Leslie J. Raffel
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Mark O. Goodarzi
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Y-D Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Herman A. Taylor
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
- Jackson State University, Tougaloo College, Jackson, Mississippi, United States of America
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - David Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Ayo Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Rasika A. Mathias
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Division of Allergy and Clinical Immunology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Dhananjay Vaidya
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Andrew B. Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Alan B. Zonderman
- Laboratory of Personality and Cognition, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Robert P. Igo
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - John R. Sedor
- Department of Medicine, Case Western Reserve University, MetroHealth System campus, Cleveland, Ohio, United States of America
- Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | | | - Edmond K. Kabagambe
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - David S. Siscovick
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - Barbara McKnight
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Kenneth Rice
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Wen-Chi Hsueh
- Department of Medicine, University of California, San Francisco, California, United States of America
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Aldi Kraja
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Michael A. Province
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Erwin P. Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Omri Gottesman
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee; International Epidemiology Institute, Rockville, Maryland, United States of America
| | - William L. Lowe
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Jennifer A. Pacheco
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Dana C. Crawford
- Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
| | | | | | - Elin Grundberg
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | | | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - M. Geoffrey Hayes
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Ingrid B. Borecki
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Steven R. Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, United States of America
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Department of Health Services, University of Washington, Seattle, Washington, United States of America
| | - Myriam Fornage
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Sudha K. Iyengar
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Michele K. Evans
- Health Disparities Unit, National Institute on Aging, National Institutes of Health, Baltimore Maryland, United States of America
| | - Diane M. Becker
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - W. H. Linda Kao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Michèle M. Sale
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Medicine, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Simin Liu
- Program on Genomics and Nutrition, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
- Department of Epidemiology, University of California Los Angeles, Los Angeles, California, United States of America
- Departments of Epidemiology and Medicine, Brown University, Providence, Rhode Island, United States of America
- * E-mail: (SL); (CNR); (DWB)
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
- * E-mail: (SL); (CNR); (DWB)
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- * E-mail: (SL); (CNR); (DWB)
| | | |
Collapse
|
44
|
Piccolo RS, Pearce N, Araujo AB, McKinlay JB. The contribution of biogeographical ancestry and socioeconomic status to racial/ethnic disparities in type 2 diabetes mellitus: results from the Boston Area Community Health Survey. Ann Epidemiol 2014; 24:648-54, 654.e1. [PMID: 25088753 DOI: 10.1016/j.annepidem.2014.06.098] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2013] [Revised: 06/17/2014] [Accepted: 06/19/2014] [Indexed: 11/23/2022]
Abstract
PURPOSE Racial/ethnic disparities in the incidence of type 2 diabetes mellitus (T2DM) are well documented, and many researchers have proposed that biogeographical ancestry (BGA) may play a role in these disparities. However, studies examining the role of BGA on T2DM have produced mixed results to date. Therefore, the objective of this research was to quantify the contribution of BGA to racial/ethnic disparities in T2DM incidence controlling for the mediating influences of socioeconomic factors. METHODS We analyzed data from the Boston Area Community Health Survey, a prospective cohort with approximately equal numbers of black, Hispanic, and white participants. We used 63 ancestry-informative markers to calculate the percentages of participants with West African and Native American ancestry. We used logistic regression with G-computation to analyze the contribution of BGA and socioeconomic factors to racial/ethnic disparities in T2DM incidence. RESULTS We found that socioeconomic factors accounted for 44.7% of the total effect of T2DM attributed to black race and 54.9% of the effect attributed to Hispanic ethnicity. We found that BGA had almost no direct association with T2DM and was almost entirely mediated by self-identified race/ethnicity and socioeconomic factors. CONCLUSIONS It is likely that nongenetic factors, specifically socioeconomic factors, account for much of the reported racial/ethnic disparities in T2DM incidence.
Collapse
|
45
|
Bentley AR, Chen G, Shriner D, Doumatey AP, Zhou J, Huang H, Mullikin JC, Blakesley RW, Hansen NF, Bouffard GG, Cherukuri PF, Maskeri B, Young AC, Adeyemo A, Rotimi CN. Gene-based sequencing identifies lipid-influencing variants with ethnicity-specific effects in African Americans. PLoS Genet 2014; 10:e1004190. [PMID: 24603370 DOI: 10.1371/journal.pgen.1004190] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2013] [Accepted: 01/07/2014] [Indexed: 01/11/2023] Open
Abstract
Although a considerable proportion of serum lipids loci identified in European ancestry individuals (EA) replicate in African Americans (AA), interethnic differences in the distribution of serum lipids suggest that some genetic determinants differ by ethnicity. We conducted a comprehensive evaluation of five lipid candidate genes to identify variants with ethnicity-specific effects. We sequenced ABCA1, LCAT, LPL, PON1, and SERPINE1 in 48 AA individuals with extreme serum lipid concentrations (high HDLC/low TG or low HDLC/high TG). Identified variants were genotyped in the full population-based sample of AA (n = 1694) and tested for an association with serum lipids. rs328 (LPL) and correlated variants were associated with higher HDLC and lower TG. Interestingly, a stronger effect was observed on a "European" vs. "African" genetic background at this locus. To investigate this effect, we evaluated the region among West Africans (WA). For TG, the effect size among WA was the same in AA with only African local ancestry (2-3% lower TG), while the larger association among AA with local European ancestry matched previous reports in EA (10%). For HDLC, there was no association with rs328 in AA with only African local ancestry or in WA, while the association among AA with European local ancestry was much greater than what has been observed for EA (15 vs. ∼ 5 mg/dl), suggesting an interaction with an environmental or genetic factor that differs by ethnicity. Beyond this ancestry effect, the importance of African ancestry-focused, sequence-based work was also highlighted by serum lipid associations of variants that were in higher frequency (or present only) among those of African ancestry. By beginning our study with the sequence variation present in AA individuals, investigating local ancestry effects, and seeking replication in WA, we were able to comprehensively evaluate the role of a set of candidate genes in serum lipids in AA.
Collapse
|
46
|
Charles BA, Shriner D, Rotimi CN. Accounting for linkage disequilibrium in association analysis of diverse populations. Genet Epidemiol 2014; 38:265-73. [PMID: 24464495 DOI: 10.1002/gepi.21788] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2013] [Revised: 11/14/2013] [Accepted: 12/03/2013] [Indexed: 12/25/2022]
Abstract
The National Human Genome Research Institute's catalog of published genome-wide association studies (GWAS) lists over 10,000 genetic variants collectively associated with over 800 human diseases or traits. Most of these GWAS have been conducted in European-ancestry populations. Findings gleaned from these studies have led to identification of disease-associated loci and biologic pathways involved in disease etiology. In multiple instances, these genomic findings have led to the development of novel medical therapies or evidence for prescribing a given drug as the appropriate treatment for a given individual beyond phenotypic appearances or socially defined constructs of race or ethnicity. Such findings have implications for populations throughout the globe and GWAS are increasingly being conducted in more diverse populations. A major challenge for investigators seeking to follow up genomic findings between diverse populations is discordant patterns of linkage disequilibrium (LD). We provide an overview of common measures of LD and opportunities for their use in novel methods designed to address challenges associated with following up GWAS conducted in European-ancestry populations in African-ancestry populations or, more generally, between populations with discordant LD patterns. We detail the strengths and weaknesses associated with different approaches. We also describe application of these strategies in follow-up studies of populations with concordant LD patterns (replication) or discordant LD patterns (transferability) as well as fine-mapping studies. We review application of these methods to a variety of traits and diseases.
Collapse
Affiliation(s)
- Bashira A Charles
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | | | | |
Collapse
|
47
|
Simpson CL, Wojciechowski R, Yee SS, Soni P, Bailey-Wilson JE, Stambolian D. Regional replication of association with refractive error on 15q14 and 15q25 in the Age-Related Eye Disease Study cohort. Mol Vis 2013; 19:2173-86. [PMID: 24227913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2013] [Accepted: 10/30/2013] [Indexed: 11/25/2022] Open
Abstract
PURPOSE Refractive error is a complex trait with multiple genetic and environmental risk factors, and is the most common cause of preventable blindness worldwide. The common nature of the trait suggests the presence of many genetic factors that individually may have modest effects. To achieve an adequate sample size to detect these common variants, large, international collaborations have formed. These consortia typically use meta-analysis to combine multiple studies from many different populations. This approach is robust to differences between populations; however, it does not compensate for the different haplotypes in each genetic background evidenced by different alleles in linkage disequilibrium with the causative variant. We used the Age-Related Eye Disease Study (AREDS) cohort to replicate published significant associations at two loci on chromosome 15 from two genome-wide association studies (GWASs). The single nucleotide polymorphisms (SNPs) that exhibited association on chromosome 15 in the original studies did not show evidence of association with refractive error in the AREDS cohort. This paper seeks to determine whether the non-replication in this AREDS sample may be due to the limited number of SNPs chosen for replication. METHODS We selected all SNPs genotyped on the Illumina Omni2.5v1_B array or custom TaqMan assays or imputed from the GWAS data, in the region surrounding the SNPs from the Consortium for Refractive Error and Myopia study. We analyzed the SNPs for association with refractive error using standard regression methods in PLINK. The effective number of tests was calculated using the Genetic Type I Error Calculator. RESULTS Although use of the same SNPs used in the Consortium for Refractive Error and Myopia study did not show any evidence of association with refractive error in this AREDS sample, other SNPs within the candidate regions demonstrated an association with refractive error. Significant evidence of association was found using the hyperopia categorical trait, with the most significant SNPs rs1357179 on 15q14 (p=1.69×10⁻³) and rs7164400 on 15q25 (p=8.39×10⁻⁴), which passed the replication thresholds. CONCLUSIONS This study adds to the growing body of evidence that attempting to replicate the most significant SNPs found in one population may not be significant in another population due to differences in the linkage disequilibrium structure and/or allele frequency. This suggests that replication studies should include less significant SNPs in an associated region rather than only a few selected SNPs chosen by a significance threshold.
Collapse
|
48
|
Polfus LM, Smith JA, Shimmin LC, Bielak LF, Morrison AC, Kardia SLR, Peyser PA, Hixson JE. Genome-wide association study of gene by smoking interactions in coronary artery calcification. PLoS One 2013; 8:e74642. [PMID: 24098343 PMCID: PMC3789744 DOI: 10.1371/journal.pone.0074642] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2013] [Accepted: 08/05/2013] [Indexed: 12/21/2022] Open
Abstract
Many GWAS have identified novel loci associated with common diseases, but have focused only on main effects of individual genetic variants rather than interactions with environmental factors (GxE). Identification of GxE interactions is particularly important for coronary heart disease (CHD), a major preventable source of morbidity and mortality with strong non-genetic risk factors. Atherosclerosis is the major cause of CHD, and coronary artery calcification (CAC) is directly correlated with quantity of coronary atherosclerotic plaque. In the current study, we tested for genetic variants influencing extent of CAC via interaction with smoking (GxS), by conducting a GxS discovery GWAS in Genetic Epidemiology Network of Arteriopathy (GENOA) sibships (N = 915 European Americans) followed by replication in Framingham Heart Study (FHS) sibships (N = 1025 European Americans). Generalized estimating equations accounted for the correlation within sibships in strata-specific groups of smokers and nonsmokers, as well as GxS interaction. Primary analysis found SNPs that showed suggestive associations (p≤10−5) in GENOA GWAS, but these index SNPs did not replicate in FHS. However, secondary analysis was able to replicate candidate gene regions in FHS using other SNPs (+/−250 kb of GENOA index SNP). In smoker and nonsmoker groups, replicated genes included TCF7L2 (p = 6.0×10−5) and WWOX (p = 4.5×10−6); and TNFRSF8 (p = 7.8×10−5), respectively. For GxS interactions, replicated genes included TBC1D4 (p = 6.9×10−5) and ADAMTS9 (P = 7.1×10−5). Interestingly, these genes are involved in inflammatory pathways mediated by the NF-κB axis. Since smoking is known to induce chronic and systemic inflammation, association of these genes likely reflects roles in CAC development via inflammatory pathways. Furthermore, the NF-κB axis regulates bone remodeling, a key physiological process in CAC development. In conclusion, GxS GWAS has yielded evidence for novel loci that are associated with CAC via interaction with smoking, providing promising new targets for future population-based and functional studies of CAC development.
Collapse
Affiliation(s)
- Linda M. Polfus
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Lawrence C. Shimmin
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Lawrence F. Bielak
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Alanna C. Morrison
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Sharon L. R. Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - James E. Hixson
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
- * E-mail:
| |
Collapse
|
49
|
Fesinmeyer MD, Meigs JB, North KE, Schumacher FR, Bůžková P, Franceschini N, Haessler J, Goodloe R, Spencer KL, Voruganti VS, Howard BV, Jackson R, Kolonel LN, Liu S, Manson JE, Monroe KR, Mukamal K, Dilks HH, Pendergrass SA, Nato A, Wan P, Wilkens LR, Le Marchand L, Ambite JL, Buyske S, Florez JC, Crawford DC, Hindorff LA, Haiman CA, Peters U, Pankow JS. Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study. BMC Med Genet 2013; 14:98. [PMID: 24063630 PMCID: PMC3849560 DOI: 10.1186/1471-2350-14-98] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/04/2012] [Accepted: 09/10/2013] [Indexed: 11/10/2022]
Abstract
BACKGROUND Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S. METHODS As part of the 'Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites. RESULTS Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 × 10-15), versus 3/9 in AA (p= 0.03 to 6 × 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only. CONCLUSIONS Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.
Collapse
Affiliation(s)
- Megan D Fesinmeyer
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis MN, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
50
|
Wang H, Liu L, Zhao J, Cui G, Chen C, Ding H, Wang DW. Large scale meta-analyses of fasting plasma glucose raising variants in GCK, GCKR, MTNR1B and G6PC2 and their impacts on type 2 diabetes mellitus risk. PLoS One 2013; 8:e67665. [PMID: 23840762 DOI: 10.1371/journal.pone.0067665] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2013] [Accepted: 05/22/2013] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The evidence that the variants GCK rs1799884, GCKR rs780094, MTNR1B rs10830963 and G6PC2 rs560887, which are related to fasting plasma glucose levels, increase the risk of type 2 diabetes mellitus (T2DM) is contradictory. We therefore performed a meta-analysis to derive a more precise estimation of the association between these polymorphisms and T2DM. METHODS All the publications examining the associations of these variants with risk of T2DM were retrieved from the MEDLINE and EMBASE databases. Using the data from the retrieved articles, we computed summary estimates of the associations of the four variants with T2DM risk. We also examined the studies for heterogeneity, as well as for bias of the publications. RESULTS A total of 113,025 T2DM patients and 199,997 controls from 38 articles were included in the meta-analysis. Overall, the pooled results indicated that GCK (rs1799884), GCKR (rs780094) and MTNR1B (rs10830963) were significantly associated with T2DM susceptibility (OR, 1.04; 95%CI, 1.01-1.08; OR, 1.08; 95%CI, 1.05-1.12 and OR, 1.05; 95%CI, 1.02-1.08, respectively). After stratification by ethnicity, significant associations for the GCK, MTNR1B and G6PC2 variants were detected only in Caucasians (OR, 1.09; 95%CI, 1.02-1.16; OR, 1.10; 95%CI, 1.08-1.13 and OR, 0.97; 95%CI, 0.95-0.99, respectively), but not in Asians (OR, 1.02, 95% CI 0.98-1.05; OR, 1.01; 95%CI, 0.98-1.04 and OR, 1.12; 95%CI, 0.91-1.32, respectively). CONCLUSIONS Our meta-analyses demonstrated that GCKR rs780094 variant confers high cross-ethnicity risk for the development of T2DM, while significant associations between GCK, MTNR1B and G6PC2 variants and T2DM risk are limited to Caucasians.
Collapse
|