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Barman N, Atiqul Haque M, Firoz M, Abdullah Yusuf M, Islam ABMMK. Association of transcription factor 7-like 2 rs12255372 polymorphism with susceptibility of type 2 diabetes mellitus in Bangladeshi population. Mol Genet Genomics 2023; 298:1201-1209. [PMID: 37392217 DOI: 10.1007/s00438-023-02049-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 06/22/2023] [Indexed: 07/03/2023]
Abstract
Polymorphism of transcription factor 7-like 2 (TCF7L2) has a link with type 2 diabetes mellitus (T2DM) through β cell dysfunction that causes defect in blood glucose homeostasis. This case-control study recruited 67 T2DM as cases and 65 age-matched healthy individuals as controls to determine whether the polymorphism rs12255372 (G > T) in the TCF7L2 gene have an association with T2DM in Bangladeshi population. Genomic DNA was purified from peripheral whole blood sample and direct Sanger sequencing was done for genotyping of SNP. Bivariate logistic regression was done to find out the association between genetic variant and T2DM. In our study, the minor T allele frequency was significantly more frequent in T2DM group than healthy controls (29.1% vs. 16.9%). After adjusting with confounding factors, heterozygous-genotype GT had higher odds of developing T2DM (OR 2.4; 95% CI: 1.0-5.5; p value = 0.04) and in dominant model, having SNP in TCF7L2 increased the risk of T2DM 2.3 times (95% CI: 1.0-5.2; p value = 0.04). In interaction model, genetic susceptible SNP cases interacted significantly with increasing age and BMI, female gender, and having family history of diabetes mellitus to develop T2DM (pinteraction < 0.001). Having minor T allele either in heterozygous or homozygous variant form of rs12255372 (G > T) TCF7L2 had significant association with T2DM. In conclusion, TCF7L2 gene variant increases risk of developing T2DM among the Bangladeshi population.
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Affiliation(s)
- Nilima Barman
- Department of Genetic Engineering and Biotechnology, University of Dhaka, Dhaka, 1000, Bangladesh
- Department of Laboratory Medicine, Bangladesh Institute of Research and Rehabilitation of Diabetes, Endocrine and Metabolic Disorder (BIRDEM) General Hospital, Dhaka, 1000, Bangladesh
| | - Md Atiqul Haque
- Department of Public Health and Informatics, Bangabandhu Sheikh Mujib Medical University, Dhaka, 1000, Bangladesh
| | - Mohammuddunobi Firoz
- Department of Surgery, Bangladesh Institute of Research and Rehabilitation of Diabetes, Endocrine and Metabolic Disorder (BIRDEM) General Hospital, Dhaka, 1000, Bangladesh
| | - M Abdullah Yusuf
- Department of Microbiology, National Institute of Neurosciences and Hospital, Dhaka, 1207, Bangladesh
| | - Abul B M M K Islam
- Department of Genetic Engineering and Biotechnology, University of Dhaka, Dhaka, 1000, Bangladesh.
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Looker HC, Chang DC, Baier LJ, Hanson RL, Nelson RG. Diagnostic criteria and etiopathogenesis of type 2 diabetes and its complications: Lessons from the Pima Indians. Presse Med 2023; 52:104176. [PMID: 37783422 PMCID: PMC10805453 DOI: 10.1016/j.lpm.2023.104176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/28/2023] [Accepted: 07/19/2023] [Indexed: 10/04/2023] Open
Abstract
The Phoenix Epidemiology and Clinical Research Branch of the National Institute of Diabetes and Digestive and Kidney Diseases has conducted prospective studies of diabetes and its complications in the Pima Indians living in Arizona, USA for over 50 years. In this review we highlight areas in which these studies provided vital insights into the criteria used to diagnose type 2 diabetes, the pathophysiologic changes that accompany the development of type 2 diabetes, and the course and determinants of diabetes complications-focusing specifically on diabetic kidney disease. We include data from our longitudinal population-based study of diabetes and its complications, studies on the role of insulin resistance and insulin secretion in the pathophysiology of type 2 diabetes, and in-depth studies of diabetic kidney disease that include measures of glomerular function and research kidney biopsies. We also focus on the emerging health threat posed by youth-onset type 2 diabetes, which was first seen in the Pima Indians in the 1960s and is becoming an increasing issue worldwide.
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Affiliation(s)
- Helen C Looker
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Douglas C Chang
- Obesity and Diabetes Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Leslie J Baier
- Diabetes Molecular Genetics Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Robert L Hanson
- Diabetes Genetic Epidemiology Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Robert G Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA.
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Generation of Isogenic hiPSCs with Targeted Edits at Multiple Intronic SNPs to Study the Effects of the Type 2 Diabetes Associated KCNQ1 Locus in American Indians. Cells 2022; 11:cells11091446. [PMID: 35563754 PMCID: PMC9102014 DOI: 10.3390/cells11091446] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 04/11/2022] [Accepted: 04/18/2022] [Indexed: 11/17/2022] Open
Abstract
The top genetic association signal for type 2 diabetes (T2D) in Southwestern American Indians maps to intron 15 of KCNQ1, an imprinted gene. We aim to understand the biology whereby variation at this locus affects T2D specifically in this genomic background. To do so, we obtained human induced pluripotent stem cells (hiPSC) derived from American Indians. Using these iPSCs, we show that imprinting of KCNQ1 and CDKN1C during pancreatic islet-like cell generation from iPSCs is consistent with known imprinting patterns in fetal pancreas and adult islets and therefore is an ideal model system to study this locus. In this report, we detail the use of allele-specific guide RNAs and CRISPR to generate isogenic hiPSCs that differ only at multiple T2D associated intronic SNPs at this locus which can be used to elucidate their functional effects. Characterization of these isogenic hiPSCs identified a few aberrant cell lines; namely cell lines with large hemizygous deletions in the putative functional region of KCNQ1 and cell lines hypomethylated at the KCNQ1OT1 promoter. Comparison of an isogenic cell line with a hemizygous deletion to the parental cell line identified CDKN1C and H19 as differentially expressed during the endocrine progenitor stage of pancreatic-islet development.
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Verma S, Srivastava N, Banerjee M. Genetic polymorphisms in TCF7L2 and PPARG genes and susceptibility to Type 2 diabetes mellitus. Meta Gene 2021. [DOI: 10.1016/j.mgene.2021.100864] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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Hameed T, Khan Z, Imran M, Ali S, Albegali AA, Ullah MI, Ejaz H. Associations of transcription factor 7-Like 2 ( TCF7L2) gene polymorphism in patients of type 2 diabetes mellitus from Khyber Pakhtunkhwa population of Pakistan. Afr Health Sci 2021; 21:15-22. [PMID: 34394276 PMCID: PMC8356593 DOI: 10.4314/ahs.v21i1.4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) is the most prevalent component of metabolic syndrome. Environmental factors and various complex genes like transcription factor 7-like 2 (TCF7L2) gene have involved in the disease development. Objective To determine TCF7L2 genetic association (rs7903146C/T and rs12255372G/T) in T2DM patients of Khyber Pakhtunkhwa population of Pakistan. Subjects and methods This study comprised of 176 subjects including 118 T2DM patients and 58 healthy controls. Genomic DNA was extracted and genotype of common variants (rs7903146 C/T and rs12255372 G/T) was carried out by amplification-refractory mutation system (ARMS)-PCR of sequence specific oligonucleotides. Results The distribution of genotype of TCF7L2 SNPs (rs7903146 C/T and rs12255372 G/T) was significantly associated with T2DM as compared to the controls (p <0.0001). The genetic models of the rs7903146 (C/T) and rs12255372 (G/T) SNPs were significantly associated between cases and controls (p <0.0001). On the other hand, the significant association was observed between the two SNPs and different biochemical parameters like serum fasting glucose, lipid profile, creatinine and blood HbA1c levels (p <0.05). Conclusion It is concluded that the SNPs of the TCF7L2 gene are significantly associated with T2DM disease susceptibility in the population of Khyber Pakhtunkhwa of Pakistan.
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Affiliation(s)
- Taha Hameed
- Department of Biochemistry, University of Peshawar, Pakistan
| | - Zahid Khan
- Department of Biochemistry, University of Peshawar, Pakistan
| | - Muhammad Imran
- Department of Biochemistry, University of Peshawar, Pakistan
| | - Saif Ali
- Department of Biochemistry, University of Peshawar, Pakistan
| | | | - Muhammad Ikram Ullah
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University Sakaka, Saudi Arabia
| | - Hasan Ejaz
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University Sakaka, Saudi Arabia
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Younus DA, Mustafa SA, Abdullah LY, Mustafa MS. Transcription factor 7-like 2 (TCF7L2) rs12255372 variant and the risk of type 2 diabetes mellitus among the Kurdish population in Erbil, Iraq. Int J Diabetes Dev Ctries 2021. [DOI: 10.1007/s13410-021-00921-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Sarah EH, El Omri N, Ibrahimi A, El Jaoudi R. Metabolic and genetic studies of glimepiride and metformin and their association with type 2 diabetes. GENE REPORTS 2020. [DOI: 10.1016/j.genrep.2020.100787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Geoghegan G, Simcox J, Seldin MM, Parnell TJ, Stubben C, Just S, Begaye L, Lusis AJ, Villanueva CJ. Targeted deletion of Tcf7l2 in adipocytes promotes adipocyte hypertrophy and impaired glucose metabolism. Mol Metab 2019; 24:44-63. [PMID: 30948248 PMCID: PMC6531814 DOI: 10.1016/j.molmet.2019.03.003] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Revised: 03/02/2019] [Accepted: 03/09/2019] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Activation of the Wnt-signaling pathway is known to inhibit differentiation in adipocytes. However, there is a gap in our understanding of the transcriptional network regulated by components of the Wnt-signaling pathway during adipogenesis and in adipocytes during postnatal life. The key intracellular effectors of the Wnt-signaling pathway occur through TCF transcription factors such as TCF7L2 (transcription factor-7-like 2). Several genetic variants in proximity to TCF7L2 have been linked to type 2 diabetes through genome-wide association studies in various human populations. Our work aims to functionally characterize the adipocyte specific gene program regulated by TCF7L2 and understand how this program regulates metabolism. METHODS We generated Tcf7l2F/F mice and assessed TCF7L2 function in isolated adipocytes and adipose specific knockout mice. ChIP-sequencing and RNA-sequencing was performed on the isolated adipocytes with control and TCF7L2 knockout cells. Adipose specific TCF7L2 knockout mice were challenged with high fat diet and assessed for body weight, glucose tolerance, and lipolysis. RESULTS Here we report that TCF7L2 regulates adipocyte size, endocrine function, and glucose metabolism. Tcf7l2 is highly expressed in white adipose tissue, and its expression is suppressed in genetic and diet-induced models of obesity. Genome-wide distribution of TCF7L2 binding and gene expression analysis in adipocytes suggests that TCF7L2 directly regulates genes implicated in cellular metabolism and cell cycle control. When challenged with a high-fat diet, conditional deletion of TCF7L2 in adipocytes led to impaired glucose tolerance, impaired insulin sensitivity, promoted weight gain, and increased adipose tissue mass. This was accompanied by reduced expression of triglyceride hydrolase, reduced fasting-induced free fatty acid release, and adipocyte hypertrophy in subcutaneous adipose tissue. CONCLUSIONS Together our studies support that TCF7L2 is a central transcriptional regulator of the adipocyte metabolic program by directly regulating the expression of genes involved in lipid and glucose metabolism.
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Affiliation(s)
- Gisela Geoghegan
- Department of Biochemistry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Judith Simcox
- Department of Biochemistry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Marcus M Seldin
- Department of Human Genetics/Medicine, University of California, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, CA, USA
| | - Timothy J Parnell
- Bioinformatics Shared Resources, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Chris Stubben
- Bioinformatics Shared Resources, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Steven Just
- Department of Biochemistry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Lori Begaye
- Department of Biochemistry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Aldons J Lusis
- Department of Human Genetics/Medicine, University of California, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, CA, USA
| | - Claudio J Villanueva
- Department of Biochemistry, University of Utah School of Medicine, Salt Lake City, UT, USA.
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Kalantari S, Sharafshah A, Keshavarz P, Davoudi A, Habibipour R. Single and multi-locus association study of TCF7L2 gene variants with susceptibility to type 2 diabetes mellitus in an Iranian population. Gene 2019; 696:88-94. [PMID: 30776466 DOI: 10.1016/j.gene.2019.01.040] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 01/04/2019] [Accepted: 01/22/2019] [Indexed: 01/03/2023]
Abstract
Prior studies indicated that some of transcription factor 7-like 2 (TCF7L2) gene variants such as rs7903146, rs12255372 and rs11255372 are constantly associated with Type 2 diabetes mellitus (T2DM) in various populations and ethnic groups. The purpose of this study was to assess the association between TCF7L2 variants (rs7903146, rs11196205, and rs11255372) and T2DM by TaqMan assay. Statistical analysis was performed through SNPAlyze and SPSS. Significant associations of rs7903146 (P = 1.9 × 10-7), and rs11255372 (P = 2.98 × 10-10) both under a dominant model were found. Based on allele frequency, there was a significant difference between the two study groups at rs7903146 and rs12255372 variants (P = 6.8 × 10-10, and P = 9.3 × 10-11, respectively). Two haplotypes including Hap-1 (C-G-G) and Hap-2 (T-G-T) indicated a significant difference between the two study groups (P = 1.174 × 10-9and P = 7.432 × 109 respectively). In conclusion, rs7903146 and rs12255372 were significantly associated with T2DM in the specified Northern Iranian population.
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Affiliation(s)
- Saeed Kalantari
- Department of Endocrinology, Guilan University of Medical Sciences, Rasht, Iran
| | - Alireza Sharafshah
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Parvaneh Keshavarz
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
| | - Arash Davoudi
- Division of Cytogenetic, Medical Genetic Laboratory of Dr. Keshavarz, Rasht, Iran
| | - Razie Habibipour
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
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Beloso C, Souto J, Fabregat M, Romanelli G, Javiel G, Mimbacas A. Association of TCF7L2 mutation and atypical diabetes in a Uruguayan population. World J Diabetes 2018; 9:157-164. [PMID: 30254725 PMCID: PMC6153121 DOI: 10.4239/wjd.v9.i9.157] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Revised: 06/29/2018] [Accepted: 07/10/2018] [Indexed: 02/05/2023] Open
Abstract
AIM To investigate if mutations in TCF7L2 are associated with “atypical diabetes” in the Uruguayan population.
METHODS Healthy, nondiabetic controls (n = 133) and patients with type 2 diabetes (n = 177) were selected from among the presenting population at level-3 referral healthcare centers in Uruguay. Patients with type 2 diabetes were subgrouped according to “atypical diabetes” (n = 92) and “classical diabetes” (n = 85). Genotyping for the rs12255372 and rs7903146 single nucleotide polymorphisms (SNPs) in the TCFTL2 gene was carried out with TaqMan® probes. Random samples were sequenced by Macrogen Ltd. (South Korea). Statistical analysis of the SNP data was carried out with the SNPStats online tool (http://bioinfo.iconcologia.net/SNPstats). The best inheritance model was chosen according to the lowest values of Akaike’s information criterion and Bayesian information criterion. Differences between groups were determined by unpaired t-tests after checking the normal distribution or were converted to normalize the data. The association of SNPs was tested for matched case-control samples by using χ2 analysis and calculation of odds ratios (ORs) with 95% confidence intervals (CIs). All statistical tests were performed using SPSS v10.0 and EpiInfo7 statistical packages. Significant statistical differences were assumed in all cases showing adjusted P < 0.05.
RESULTS We genotyped two TCF7L2 SNPs (rs7903146 and rs12255372) in a population-based sample of 310 Uruguayan subjects, including 133 healthy control subjects and 177 clinical diagnosed with type 2 diabetes. For both SNPs analyzed, the best model was the dominant type: rs12255372 = G/G vs G/T+T/T, OR = 0.63, 95%CI: 0.40-0.98, P < 0.05 and rs7903146 = C/C vs C/T+T/T, OR = 0.79, 95%CI: 0.41-1.55, P = 0.3. The rs12255372 SNP showed high association with the type 2 diabetes cases (OR = 1.60, 95%CI: 1.20-2.51, P < 0.05). However, when the type 2 diabetics group was analyzed according to the atypical and classical subgroupings, the association with diabetes existed only for rs12255372 and the classical subgroup (vs controls: OR = 2.1, 95%CI: 1.21-3.75, P < 0.05); no significant differences were found for either SNP or atypical diabetes.
CONCLUSION This is the first time SNPs_TCF7L2 were genotyped in a diabetic population stratified by genotype instead of phenotype. Classical and atypical patients showed statistical differences.
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Affiliation(s)
- Carolina Beloso
- Biodiversity and Genetics Department, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo 11600, Uruguay
| | - Jorge Souto
- Cytogenetics Laboratory, Hematology and Transplant Service of Hematopoietic Progenitors, Maciel Hospital, ASSE, Montevideo 11600, Uruguay
- Department of Genetics, Faculty of Medicine, UDELAR, Montevideo 11800, Uruguay
| | - Matias Fabregat
- Human Molecular Genetics Laboratory, Institut Pasteur de Montevideo 11400, Uruguay
| | - Gerardo Romanelli
- Cell Signaling and Nanobiology Laboratory, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo 11600, Uruguay
| | - Gerardo Javiel
- Unit of Diabetes Hospital Pasteur, ASSE-Ministry of Public Health, Montevideo 11400, Uruguay
- Diabetologyc Service of Private Health Center, Centro de Asistencia del Sindicato Médico del Uruguay, Montevideo 11600, Uruguay
| | - Adriana Mimbacas
- Biodiversity and Genetics Department, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo 11600, Uruguay
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Adams JD, Vella A. What Can Diabetes-Associated Genetic Variation in TCF7L2 Teach Us About the Pathogenesis of Type 2 Diabetes? Metab Syndr Relat Disord 2018; 16:383-389. [PMID: 29993315 DOI: 10.1089/met.2018.0024] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a polygenic metabolic disorder characterized by hyperglycemia occurring as a result of impaired insulin secretion and/or insulin resistance. Among the various genetic factors associated with T2DM, a common genetic variant within the transcription factor 7-like 2 locus (TCF7L2) confers the greatest genetic risk for development of the disease. However, the mechanism(s) by which TCF7L2 predisposes to diabetes remain uncertain. Here we review the current literature pertaining to the potential mechanisms by which TCF7L2 confers risk of T2DM, using genetic variation as a probe to understand the pathogenesis of the disease.
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Affiliation(s)
- J D Adams
- Endocrine Research Unit, Department of Endocrinology, Diabetes and Nutrition, Mayo Clinic College of Medicine , Rochester, Minnesota
| | - Adrian Vella
- Endocrine Research Unit, Department of Endocrinology, Diabetes and Nutrition, Mayo Clinic College of Medicine , Rochester, Minnesota
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Muller YL, Piaggi P, Chen P, Wiessner G, Okani C, Kobes S, Knowler WC, Bogardus C, Hanson RL, Baier LJ. Assessing variation across 8 established East Asian loci for type 2 diabetes mellitus in American Indians: Suggestive evidence for new sex-specific diabetes signals in GLIS3 and ZFAND3. Diabetes Metab Res Rev 2017; 33. [PMID: 27862917 DOI: 10.1002/dmrr.2869] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 10/24/2016] [Accepted: 10/29/2016] [Indexed: 01/20/2023]
Abstract
BACKGROUND Eight new loci for type 2 diabetes mellitus (T2DM) were identified in an East Asian genome-wide association study meta-analysis. We assess tag SNPs across these loci for associations with T2DM in American Indians. METHODS A total of 435 SNPs that tag (R2 ≥ .85) common variation across the 8 loci were analyzed for association with T2DM (n = 7710), early onset T2DM (n = 1060), body mass index (n = 6839), insulin sensitivity (n = 555), and insulin secretion (n = 298). RESULTS Tag SNPs within FITM2-R3HDML-HNF4A, GLIS3, KCNK16, and ZFAND3 associated with T2DM after accounting for locus-wide multiple testing. The T2DM association in FITM2-R3HDML-HNF4A (rs3212183; P = .0002; OR = 1.19 [1.09-1.30]) was independent from the East Asian lead SNP (rs6017317), which did not associate with T2DM in American Indians. The top signals in GLIS3 (rs7875253; P = .0004; OR = 1.23 [1.10-1.38]) and KCNK16 (rs1544050; P = .002; OR = 1.16 [1.06-1.27]) were attenuated after adjustment for the East Asian lead SNPs (rs7041847 in GLIS3; rs1535500 in KCNK16), both of which also associated with T2DM in American Indians (P = .02; OR = 1.11 [1.01-1.21]; P = .007; OR = 1.19 [1.05-1.36] respectively). The top SNP in ZFAND3 (rs9470794; P = .002; OR = 1.43 [1.14-1.80]) was the identical East Asian lead SNP. Additional SNPs in GLIS3 (rs180867004) and ZFAND3 (rs4714120 and rs9470701) had significant genotype × sex interactions (P ≤ .008). The GLIS3 SNP (rs180867004) associated with T2DM only in men (P = .00006, OR = 1.94 [1.40-2.68]). The ZFAND3 SNPs (rs4714120 and rs9470701) associated with T2DM only in women (P = .0002, OR = 1.35 [1.16-1.59]; P = .0003, OR = 1.37 [1.16-1.63] respectively). CONCLUSIONS Replication of lead T2DM SNPs in GLIS3, KCNK16, and ZFAND3 was observed in American Indians. Sex-specific T2DM signals in GLIS3 and ZFAND3, which are distinct from the East Asian GWAS signals, were also identified.
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Affiliation(s)
- Yunhua L Muller
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Paolo Piaggi
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Peng Chen
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Gregory Wiessner
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Chidinma Okani
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Clifton Bogardus
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona, USA
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Gallardo-Blanco HL, Villarreal-Perez JZ, Cerda-Flores RM, Figueroa A, Sanchez-Dominguez CN, Gutierrez-Valverde JM, Torres-Muñoz IC, Lavalle-Gonzalez FJ, Gallegos-Cabriales EC, Martinez-Garza LE. Genetic variants in KCNJ11, TCF7L2 and HNF4A are associated with type 2 diabetes, BMI and dyslipidemia in families of Northeastern Mexico: A pilot study. Exp Ther Med 2016; 13:523-529. [PMID: 28352326 PMCID: PMC5348709 DOI: 10.3892/etm.2016.3990] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Accepted: 01/20/2016] [Indexed: 12/19/2022] Open
Abstract
The aim of the present study was to investigate whether genetic markers considered risk factors for metabolic syndromes, including dyslipidemia, obesity and type 2 diabetes mellitus (T2DM), can be applied to a Northeastern Mexican population. A total of 37 families were analyzed for 63 single nucleotide polymorphisms (SNPs), and the age, body mass index (BMI), glucose tolerance values and blood lipid levels, including those of cholesterol, low-density lipoprotein (LDL), very LDL (VLDL), high-density lipoprotein (HDL) and triglycerides were evaluated. Three genetic markers previously associated with metabolic syndromes were identified in the sample population, including KCNJ11, TCF7L2 and HNF4A. The KCNJ11 SNP rs5210 was associated with T2DM, the TCF7L2 SNP rs11196175 was associated with BMI and cholesterol and LDL levels, the TCF7L2 SNP rs12255372 was associated with BMI and HDL, VLDL and triglyceride levels, and the HNF4A SNP rs1885088 was associated with LDL levels (P<0.05).
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Affiliation(s)
- Hugo Leonid Gallardo-Blanco
- Department of Genetics, School of Medicine, Autonomous University of Nuevo León, Monterrey, Nuevo León, CP 64460, Mexico
| | - Jesus Zacarías Villarreal-Perez
- Department of Endocrinology, University Hospital 'José Eleuterio González', Autonomous University of Nuevo León, Monterrey, Nuevo León, CP 64460, Mexico
| | | | - Andres Figueroa
- Department of Computer Science, University of Texas Rio Grande Valley, TX 78539, USA
| | - Celia Nohemi Sanchez-Dominguez
- Department of Biochemistry and Molecular Medicine, School of Medicine, Autonomous University of Nuevo León, Monterrey, Nuevo León, CP 64460, Mexico
| | | | - Iris Carmen Torres-Muñoz
- Department of Genetics, School of Medicine, Autonomous University of Nuevo León, Monterrey, Nuevo León, CP 64460, Mexico
| | - Fernando Javier Lavalle-Gonzalez
- Department of Endocrinology, University Hospital 'José Eleuterio González', Autonomous University of Nuevo León, Monterrey, Nuevo León, CP 64460, Mexico
| | | | - Laura Elia Martinez-Garza
- Department of Genetics, School of Medicine, Autonomous University of Nuevo León, Monterrey, Nuevo León, CP 64460, Mexico
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Andersen MK, Pedersen CET, Moltke I, Hansen T, Albrechtsen A, Grarup N. Genetics of Type 2 Diabetes: the Power of Isolated Populations. Curr Diab Rep 2016; 16:65. [PMID: 27189761 DOI: 10.1007/s11892-016-0757-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Type 2 diabetes (T2D) affects millions of people worldwide. Improving the understanding of the underlying mechanisms and ultimately improving the treatment strategies are, thus, of great interest. To achieve this, identification of genetic variation predisposing to T2D is important. A large number of variants have been identified in large outbred populations, mainly from Europe and Asia. However, to elucidate additional variation, isolated populations have a number of advantageous properties, including increased amounts of linkage disequilibrium, and increased probability for presence of high frequency disease-associated variants due to genetic drift. Collectively, this increases the statistical power to detect association signals in isolated populations compared to large outbred populations. In this review, we elaborate on why isolated populations are a powerful resource for the identification of complex disease variants and describe their contributions to the understanding of the genetics of T2D.
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Affiliation(s)
- Mette Korre Andersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark
| | - Casper-Emil Tingskov Pedersen
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Ida Moltke
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark, J.B. Winsløws Vej 19, 3, 5000, Odense, Denmark
| | - Anders Albrechtsen
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark.
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15
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Morris MR, Ludwar BC, Swingle E, Mamo MN, Shubrook JH. A New Method to Assess Asymmetry in Fingerprints Could Be Used as an Early Indicator of Type 2 Diabetes Mellitus. J Diabetes Sci Technol 2016; 10:864-71. [PMID: 26830490 PMCID: PMC4928221 DOI: 10.1177/1932296816629984] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Inexpensive screening tools are needed to identify individuals predisposed to developing diabetes mellitus (DM). Such early identification coupled with an effective intervention could help many people avoid the substantial health costs of this disease. We investigated the hypothesis that fluctuating asymmetry (FA) in fingerprints is an indicator of type 2 diabetes mellitus (T2DM). METHODS Participants with T2DM, with T1DM, and without any indication or known family history of diabetes were fingerprinted with a Crossmatch Verifier 320 LC scanner. Asymmetry scores for each finger pair were assessed using both pattern analysis (ridge counts), and a wavelet-based analysis. RESULTS Both methods for scoring asymmetry predicted risk of T2DM for finger pair IV, controlling for gender and age. AUC scores were significantly greater than the null for pattern asymmetry scores (finger IV AUC = 0.74), and wavelet asymmetry scores for finger pair IV (AUC = 0.73) and finger pair V (AUC = 0.73), for predicting T2DM. In addition, wavelet asymmetry scores for finger pair IV (AUC = 0.80) and finger pair V (AUC = 0.85) significantly predicted risk of T1DM. CONCLUSIONS A diagnostic tool based on FA in the fingerprints of finger pair IV, measured using a wavelet analysis could be developed for predicting risk prior to associated health problems for both T2DM and T1DM. In addition, given that that the prints for fingers IV and V develop during the 14-17 weeks of gestation, we predict that interventions during this time period of pregnancy will be most successful.
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Affiliation(s)
- Molly R Morris
- Department of Biological Sciences, Ohio University, Athens, OH, USA
| | | | - Evan Swingle
- Department of Biological Sciences, Ohio University, Athens, OH, USA
| | | | - Jay H Shubrook
- College of Osteopathic Medicine, Touro University California, Vallejo, CA, USA
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16
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Jin T. Current Understanding on Role of the Wnt Signaling Pathway Effector TCF7L2 in Glucose Homeostasis. Endocr Rev 2016; 37:254-77. [PMID: 27159876 DOI: 10.1210/er.2015-1146] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The role of the Wnt signaling pathway in metabolic homeostasis has drawn our intensive attention, especially after the genome-wide association study discovery that certain polymorphisms of its key effector TCF7L2 are strongly associated with the susceptibility to type 2 diabetes. For a decade, great efforts have been made in determining the function of TCF7L2 in various metabolic organs, which have generated both considerable achievements and disputes. In this review, I will briefly introduce the canonical Wnt signaling pathway, focusing on its effector β-catenin/TCF, including emphasizing the bidirectional feature of TCFs and β-catenin post-translational modifications. I will then summarize the observations on the association between TCF7L2 polymorphisms and type 2 diabetes risk. The main content, however, is on the intensive functional exploration of the metabolic role of TCF7L2, including the disputes generated on determining its role in the pancreas and liver with various transgenic mouse lines. Finally, I will discuss those achievements and disputes and present my future perspectives.
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Affiliation(s)
- Tianru Jin
- Division of Advanced Diagnostics, Toronto General Research Institute, University Health Network, Toronto, ON M5G 2C4, Canada
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17
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Hohenadel MG, Baier LJ, Piaggi P, Muller YL, Hanson RL, Krakoff J, Thearle MS. The impact of genetic variants on BMI increase during childhood versus adulthood. Int J Obes (Lond) 2016; 40:1301-9. [PMID: 27076275 DOI: 10.1038/ijo.2016.53] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Revised: 02/04/2016] [Accepted: 02/21/2016] [Indexed: 01/13/2023]
Abstract
BACKGROUND Genetic variants that predispose individuals to obesity may have differing influences during childhood versus adulthood, and additive effects of such variants are likely to occur. Our ongoing studies to identify genetic determinants of obesity in American Indians have identified 67 single-nucleotide polymorphisms (SNPs) that reproducibly associate with maximum lifetime non-diabetic body mass index (BMI). This study aimed to identify when, during the lifetime, these variants have their greatest impact on BMI increase. SUBJECTS/METHODS A total of 5906 Native Americans of predominantly Pima Indian heritage with repeated measures of BMI between the ages of 5 and 45 years were included in this study. The association between each SNP with the rates of BMI increase during childhood (5-19 years) and adulthood (20-45 years) were assessed separately. The significant SNPs were used to calculate a cumulative allelic risk score (ARS) for childhood and adulthood, respectively, to assess the additive effect of these variants within each period of life. RESULTS The majority of these SNPs (36 of 67) were associated with rate of BMI increase during childhood (P-value range: 0.00004-0.05), whereas only nine SNPs were associated with rate of BMI change during adulthood (P-value range: 0.002-0.02). These 36 SNPs associated with childhood BMI gain likely had a cumulative effect as a higher childhood-ARS associated with rate of BMI change (β=0.032 kg m(-2) per year per risk allele, 95% confidence interval: 0.027-0.036, P<0.0001), such that at age 19 years, individuals with the highest number of risk alleles had a BMI of 10.2 kg m(-2) greater than subjects with the lowest number of risk alleles. CONCLUSIONS Overall, our data indicates that genetic polymorphisms associated with lifetime BMI may influence the rate of BMI increase during different periods in the life course. The majority of these polymorphisms have a larger impact on BMI during childhood, providing further evidence that prevention of obesity will need to begin early in life.
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Affiliation(s)
- M G Hohenadel
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - L J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - P Piaggi
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Y L Muller
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - R L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - J Krakoff
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - M S Thearle
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
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18
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Cuellar-Barboza AB, Winham SJ, McElroy SL, Geske JR, Jenkins GD, Colby CL, Prieto ML, Ryu E, Cunningham JM, Frye MA, Biernacka JM. Accumulating evidence for a role of TCF7L2 variants in bipolar disorder with elevated body mass index. Bipolar Disord 2016; 18:124-35. [PMID: 26934194 DOI: 10.1111/bdi.12368] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 11/03/2015] [Accepted: 11/09/2015] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Bipolar disorder (BD) is a complex disease associated with various hereditary traits, including a higher body mass index (BMI). In a prior genome-wide association study, we found that BMI modified the association of rs12772424 - a common variant in the gene encoding transcription factor 7-like 2 (TCF7L2) - with risk for BD. TCF7L2 is a transcription factor in the canonical Wnt pathway, involved in multiple disorders, including diabetes, cancer and psychiatric conditions. Here, using an independent sample, we evaluated 26 TCF7L2 single nucleotide polymorphisms (SNPs) to explore further the association of BD with the TCF7L2-BMI interaction. METHODS Using a sample of 662 BD cases and 616 controls, we conducted SNP-level and gene-level tests to assess the evidence for an association between BD and the interaction of BMI and genetic variation in TCF7L2. We also explored the potential mechanism behind the detected associations using human brain expression quantitative trait loci (eQTL) analysis. RESULTS The analysis provided independent evidence of an rs12772424-BMI interaction (p = 0.011). Furthermore, while overall there was no evidence for SNP marginal effects on BD, the TCF7L2-BMI interaction was significant at the gene level (p = 0.042), with seven of the 26 SNPs showing SNP-BMI interaction effects with p < 0.05. The strongest evidence of interaction was observed for rs7895307 (p = 0.006). TCF7L2 expression showed a significant enrichment of association with the expression of other genes in the Wnt canonical pathway. CONCLUSIONS The current study provides further evidence suggesting that TCF7L2 involvement in BD risk may be regulated by BMI. Detailed, prospective assessment of BMI, comorbidity, and other possible contributing factors is necessary to explain fully the mechanisms underlying this association.
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Affiliation(s)
- Alfredo B Cuellar-Barboza
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.,Department of Psychiatry, University Hospital, Universidad Autonoma de Nuevo Leon, Monterrey, Mexico
| | - Stacey J Winham
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | - Jennifer R Geske
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | - Colin L Colby
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Miguel L Prieto
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.,Departamento de Psiquiatría, Facultad de Medicina, Universidad de los Andes.,Clínica Universidad de los Andes, Unidad de Salud Mental, Santiago, Chile
| | - Euijung Ryu
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Julie M Cunningham
- Department of Laboratory Medicine and Pathology, Mayo Clinic Rochester, Rochester, MN, USA
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Joanna M Biernacka
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.,Department of Health Sciences Research, Mayo Clinic, Rochester, MN
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Ibrahim AT, Hussain A, Salih MAM, Ibrahim OA, Jamieson SE, Ibrahim ME, Blackwell JM, Mohamed HS. Candidate gene analysis supports a role for polymorphisms at TCF7L2 as risk factors for type 2 diabetes in Sudan. J Diabetes Metab Disord 2016; 15:4. [PMID: 26937418 PMCID: PMC4774008 DOI: 10.1186/s40200-016-0225-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Accepted: 02/25/2016] [Indexed: 11/10/2022]
Abstract
Background Genetic susceptibility to type 2 diabetes (T2D) is multifactorial. A growing number of genes have been identified as risk factors for T2D across multiple ethnicities in trans-ancestry meta-analysis of large-scale genome-wide association studies. Few studies have looked at these genes in Sub-Saharan African populations. This study was undertaken to look for associations between T2D and single nucleotide polymorphisms (SNPs) in a number of the top candidate genes in a selected Sudanese population. Methods A total 240 T2D cases and 128 unrelated healthy control subjects were included in this study. Age, sex, weight and height were recorded, blood pressure and biochemical profiles of glucose and lipids were analysed. Single nucleotide polymorphism (SNP) genotyping was performed using the Sequenom MassARRAY® system. Fourteen SNPs were selected across 7 genes: CAPN10 (rs2975760 and rs5030952), PPARG (rs17036314 and rs1801282), IGF2BP2 (rs4402960 and rs1470579), CDKAL1 (rs9465871), HHEX (rs1111875), TCF7L2 (rs7903146, rs11196205 and rs12255372), and KCNJ11 (rs5215, rs1800467 and rs5219). Allelic and haplotype association analyses were performed under additive models in PLINK. P ≤ 0.007 (=0.05/7 genes) was the P-value required to achieve correction for multiple testing. Results A significant genetic association between the SNPs rs7903146 (odds ratio 1.69, 95 % confidence interval 1.21–2.38, P = 0.002) and rs12255372 (odds ratio 1.70, 95 % confidence interval 1.20–2.41, P = 0.003) at TCF7L2 and T2D was found in Sudanese population. These associations were retained after adjusting for age, sex and BMI (e.g. rs7903146: odds ratio 1.70, Padj:age/sex/BMI = 0.005). The strongest haplotype association (odds ratio 2.24; Padj:age/sex/BMI = 0.0003) comprised the two point haplotype T_C across rs7903146 and rs11196205. Stepwise logistic regression demonstrated that SNP rs7903146 added significant main effects to rs11196205 or rs12255372, whereas the reverse was not true, indicating that the main effect for association with T2D in this population is most strongly tagged by SNP rs7903146. Adjusted analyses also provided support for protection from T2D associated with minor alleles at SNPs rs2975760 at CAPN10 (odds ratio 0.44, 95 % confidence interval 0.20-0.97, Padj:age/sex/BMI = 0.042) and rs1111876 at HHEX (odds ratio 0.60, 95 % confidence interval 0.39- 0.93, Padj:age/sex/BMI = 0.022). Conclusions Multiethnic associations between T2D and SNPs at TCF7L2, CAPN10 and HHEX extend to Sub-Saharan Africa, specifically Sudan.
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Affiliation(s)
- Amir T Ibrahim
- Central Laboratory, Ministry of Science and Technology, Khartoum, Sudan
| | - Ayman Hussain
- Institute of Endemic Disease, University of Khartoum, P. O. Box 102 Khartoum, Sudan
| | - Mohamed A M Salih
- Central Laboratory, Ministry of Science and Technology, Khartoum, Sudan
| | | | - Sarra E Jamieson
- Telethon Kids Institute, University of Western Australia, Subiaco, Australia
| | - Muntaser E Ibrahim
- Institute of Endemic Disease, University of Khartoum, P. O. Box 102 Khartoum, Sudan
| | - Jenefer M Blackwell
- Telethon Kids Institute, University of Western Australia, Subiaco, Australia
| | - Hiba S Mohamed
- Institute of Endemic Disease, University of Khartoum, P. O. Box 102 Khartoum, Sudan
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20
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Nair AK, Baier LJ. Complex Genetics of Type 2 Diabetes and Effect Size: What have We Learned from Isolated Populations? Rev Diabet Stud 2016; 12:299-319. [PMID: 27111117 DOI: 10.1900/rds.2015.12.299] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Genetic studies in large outbred populations have documented a complex, highly polygenic basis for type 2 diabetes (T2D). Most of the variants currently known to be associated with T2D risk have been identified in large studies that included tens of thousands of individuals who are representative of a single major ethnic group such as European, Asian, or African. However, most of these variants have only modest effects on the risk for T2D; identification of definitive 'causal variant' or 'causative loci' is typically lacking. Studies in isolated populations offer several advantages over outbred populations despite being, on average, much smaller in sample size. For example, reduced genetic variability, enrichment of rare variants, and a more uniform environment and lifestyle, which are hallmarks of isolated populations, can reduce the complexity of identifying disease-associated genes. To date, studies in isolated populations have provided valuable insight into the genetic basis of T2D by providing both a deeper understanding of previously identified T2D-associated variants (e.g. demonstrating that variants in KCNQ1 have a strong parent-of-origin effect) or providing novel variants (e.g. ABCC8 in Pima Indians, TBC1D4 in the Greenlandic population, HNF1A in Canadian Oji-Cree). This review summarizes advancements in genetic studies of T2D in outbred and isolated populations, and provides information on whether the difference in the prevalence of T2D in different populations (Pima Indians vs. non-Hispanic Whites and non-Hispanic Whites vs. non-Hispanic Blacks) can be explained by the difference in risk allele frequencies of established T2D variants.
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Affiliation(s)
- Anup K Nair
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona 85004, USA
| | - Leslie J Baier
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona 85004, USA
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21
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Yako YY, Madubedube JH, Kengne AP, Erasmus RT, Pillay TS, Matsha TE. Contribution of ENPP1, TCF7L2, and FTO polymorphisms to type 2 diabetes in mixed ancestry ethnic population of South Africa. Afr Health Sci 2015; 15:1149-60. [PMID: 26958016 DOI: 10.4314/ahs.v15i4.14] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Transcription factor 7-like 2 gene (TCF7L2), fat mass and obesity-associated gene (FTO), and ectonucleotide pyrophosphatase/phosphodiesterase gene (ENPP1) are known risk loci for type 2 diabetes (T2DM) mostly in European populations. OBJECTIVES To assess the association of these genes with T2DM risk in a South African mixed-ancestry population. METHODS Five hundred and sixty six participants were genotyped for ENPP1-rs997509 and -rs1044498, FTO-9941349 and -rs3751812, TCF7L2-rs12255372 and -rs7903146 polymorphisms using Taqman genotyping assays and validated by automated sequencing to assess the association of the polymorphisms with cardiometabolic traits. RESULTS In logistic regression models adjusted for age, sex, body mass index (BMI) and insulin resistance, minor allele of rs997509 was associated with a higher risk of prevalent T2DM under a recessive model [odd ratio 4.60 (95% confidence interval: 1.07 to 19.86); p = 0.040].Under additive model, the rs7903146 [1.43 (1.00 to 2.04); p= 0.053] and rs9941349 [1.43 (1.00 to 2.04); p = 0.052] minor alleles showed marginally significant associations with a high risk of T2DM. However, only the rs7903146 alleles (p=0.011) and genotypes (p=0.025) distributions were statistically significantly different between diabetic and non-diabetic individuals. CONCLUSION Our findings demonstrate that ENPP1, TCF7L2, and FTO may predispose to T2DM in the mixed-ancestry population.
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Affiliation(s)
- Yandiswa Y Yako
- Department of Surgery, Faculty of Health Sciences, University of Witwatersrand, South Africa
| | - Jabulisile H Madubedube
- Department of Biomedical Sciences Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa
| | - Andre P Kengne
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa; Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Rajiv T Erasmus
- Division of Chemical Pathology, Faculty of Medicine and Health Sciences, National Health Laboratory Service (NHLS) and University of Stellenbosch, Cape Town, South Africa
| | - Tahir S Pillay
- Institute for Cellular and Molecular Medicine, Molecular Endocrinology, University of Pretoria
| | - Tandi E Matsha
- Department of Biomedical Sciences Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa
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Pourahmadi M, Erfanian S, Moradzadeh M, Jahromi AS. Non-Association between rs7903146 and rs12255372 Polymorphisms in Transcription Factor 7-Like 2 Gene and Type 2 Diabetes Mellitus in Jahrom City, Iran. Diabetes Metab J 2015; 39:512-7. [PMID: 26616591 PMCID: PMC4696988 DOI: 10.4093/dmj.2015.39.6.512] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Accepted: 08/17/2015] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Transcription factor 7-like 2 (TCF7L2) is a transcription factor in the Wnt signaling pathway. High levels of TCF7L2 have been reported in most human tissues, including the heart, lung, brain, liver, kidney, placenta, adipose tissues, and pancreatic β-cells. The purpose of this study was to assess the association between TCF7L2 polymorphisms (rs12255372 and rs7903146) and type 2 diabetes mellitus in the city of Jahrom, Iran. METHODS This case-control study was conducted with 200 patients referred to Diabetes Clinics and 200 healthy subjects in Jahrom City. Biochemical characteristics were first determined. TCF7L2 rs1255372 and rs7903146 polymorphisms were then genotyped using the polymerase chain reaction-restriction fragment length polymorphism method. RESULTS T-allele frequencies of both single nucleotide polymorphisms (SNPs) were significantly higher in diabetic patients than in normal glucose-tolerant subjects (rs12255372: 20.3% vs. 14.5%; rs7903146: 28.5% vs. 22.25%). The rs12255372 (G/T) polymorphism analysis showed an odds ratio of 0.473 (95% confidence interval [CI], 0.170 to 1.314; P=0.151) for the TT genotype and 0.646 (95% CI, 0.410 to 1.019; P=0.060) for the TG genotype, compared with the GG genotype. The rs7903146 (C/T) polymorphism odds ratios for TT and TC genotypes were 0.564 (95% CI, 0.280 to 1.135; P=0.109) and 0.751 (95% CI, 0.487 to 1.157; P=0.194) compared with the CC genotype, respectively. CONCLUSION The rs12255372 and rs7903146 SNPs of the TCF7L2 gene were not associated with insulin resistance in the evaluated population.
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Affiliation(s)
- Mohammad Pourahmadi
- Department of Anatomy, Jahrom University of Medical Sciences, Jahrom, Iran
- Research Center for Non-Communicable Diseases, Jahrom University of Medical Sciences, Jahrom, Iran
| | - Saiedeh Erfanian
- Research Center for Non-Communicable Diseases, Jahrom University of Medical Sciences, Jahrom, Iran.
| | - Malihe Moradzadeh
- Department of New Sciences and Technology, Mashhad University of Medical Sciences, Mashhad, Iran
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Assmann TS, Duarte GCK, Rheinheimer J, Cruz LA, Canani LH, Crispim D. The TCF7L2 rs7903146 (C/T) polymorphism is associated with risk to type 2 diabetes mellitus in Southern-Brazil. ACTA ACUST UNITED AC 2015; 58:918-25. [PMID: 25627047 DOI: 10.1590/0004-2730000003510] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Accepted: 09/14/2014] [Indexed: 02/26/2023]
Abstract
OBJECTIVE The aim of this study was to investigate the association between the rs7903146 (C/T) polymorphism in the TCF7L2 gene and type 2 diabetes mellitus, in a Southern-Brazilian population. MATERIALS AND METHODS The TCF7L2 rs7903146 polymorphism was genotyped in 953 type 2 diabetic patients and 535 non-diabetic subjects. All subjects were white. The polymorphism was genotyped by Real-Time PCR using TaqMan MGB probes (Life Technologies). Odds ratios (OR) and 95% confidence intervals (CI) were calculated for additive, recessive and dominant inheritance models. RESULTS Genotype and allele frequencies of the rs7903146 polymorphism differed significantly between type 2 diabetic patients and non-diabetic subjects (P = 0.001 and P = 0.0001, respectively). The frequency of the minor allele was 38% in type 2 diabetes group and 31% in non-diabetic subjects, and this allele was significantly associated with type 2 diabetes risk (OR = 1.42, 95% CI 1.15 - 1.76 for the dominant model of inheritance). Moreover, the T/T genotype was associated with a higher risk for type 2 diabetes (OR = 1.83, 95% CI 1.3-2.5) than the presence of only one copy of the T allele (OR = 1.31, 95% CI 1.1-1.6). Both results were adjusted for age and gender. CONCLUSIONS Our results confirm the association between the TCF7L2 rs7903146 polymorphism and increase risk for type 2 diabetes in Southern-Brazil.
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Affiliation(s)
- Taís S Assmann
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Guilherme C K Duarte
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Jakeline Rheinheimer
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Lavínia A Cruz
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Luís H Canani
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Daisy Crispim
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
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Hanson RL, Rong R, Kobes S, Muller YL, Weil EJ, Curtis JM, Nelson RG, Baier LJ. Role of Established Type 2 Diabetes-Susceptibility Genetic Variants in a High Prevalence American Indian Population. Diabetes 2015; 64:2646-57. [PMID: 25667308 PMCID: PMC4477349 DOI: 10.2337/db14-1715] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Accepted: 02/03/2015] [Indexed: 01/08/2023]
Abstract
Several single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM) have been identified, but there is little information on their role in populations at high risk for T2DM. We genotyped SNPs at 63 T2DM loci in 3,421 individuals from a high-risk American Indian population. Nominally significant (P < 0.05) associations were observed at nine SNPs in a direction consistent with the established association. A genetic risk score derived from all loci was strongly associated with T2DM (odds ratio 1.05 per risk allele, P = 6.2 × 10(-6)) and, in 292 nondiabetic individuals, with lower insulin secretion (by 4% per copy, P = 4.1 × 10(-6)). Genetic distances between American Indians and HapMap populations at T2DM markers did not differ significantly from genomic expectations. Analysis of U.S. national survey data suggested that 66% of the difference in T2DM prevalence between African Americans and European Americans, but none of the difference between American Indians and European Americans, was attributable to allele frequency differences at these loci. These analyses suggest that, in general, established T2DM loci influence T2DM in American Indians and that risk is mediated in part through an effect on insulin secretion. However, differences in allele frequencies do not account for the high population prevalence of T2DM.
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Affiliation(s)
- Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Rong Rong
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Yunhua Li Muller
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - E Jennifer Weil
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Jeffrey M Curtis
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Robert G Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
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25
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Nanfa D, Sobngwi E, Atogho-Tiedeu B, Noubiap JJN, Donfack OS, Mofo EPM, Guewo-Fokeng M, Nguimmo Metsadjio A, Ndonwi Ngwa E, Pokam Fosso P, Djahmeni E, Djokam-Dadjeu R, Evehe MS, Aminkeng F, Mbacham WF, Mbanya JC. Association between the TCF7L2 rs12255372 (G/T) gene polymorphism and type 2 diabetes mellitus in a Cameroonian population: a pilot study. Clin Transl Med 2015; 4:17. [PMID: 25995831 PMCID: PMC4434239 DOI: 10.1186/s40169-015-0058-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2015] [Accepted: 04/01/2015] [Indexed: 01/22/2023] Open
Abstract
Background To study the relationship between the rs12255372 (G/T) polymorphism of the transcription factor 7-like 2 (TCF7L2) and type 2 diabetes mellitus (T2DM) in a Cameroonian population. Methods This case–control study included 60 T2DM patients and 60 healthy normoglycemic controls, all unrelated and of Cameroonian origin, aged above 40 years (range 40–87). The Restriction Fragment Length Polymorphism - Polymerase Chain Reaction (RFLP-PCR) was used for genotyping. Results The T allele frequency was significantly higher in the diabetic group (0.44) than in the control group (0.17). This allele was significantly associated to a greater risk of developing T2DM as compared to the G allele (OR = 3.92, 95% CI 2.04 – 7.67, p < 0.0001). The codominant (additive) model explained best the risk of developing the disease, as the TT genotype was significantly associated to T2DM when compared to the GG genotype (OR = 4.45, 95% CI 1.64 – 12.83, p = 0.0014). By logistic regression adjusted for age, this OR was 4.33 (95% CI: 1.57 – 11.92, p = 0.005). Conclusion Our findings suggest that the rs12255372 (G/T) polymorphism of the TCF7L2 gene is an important risk factor for T2DM in the Cameroonian population.
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Affiliation(s)
- Dieudonne Nanfa
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Eugene Sobngwi
- Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon ; Department of Internal Medicine and Specialties, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon ; National Obesity Center, Yaoundé Central Hospital, Yaoundé, Cameroon
| | - Barbara Atogho-Tiedeu
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Jean Jacques N Noubiap
- Department of Medicine, Groote Schuur Hospital and University of Cape Town, Cape Town, South Africa ; Medical Diagnostic Center, Yaoundé, Cameroon
| | - Olivier Sontsa Donfack
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Edith Pascale Mato Mofo
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Magellan Guewo-Fokeng
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | | | - Elvis Ndonwi Ngwa
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Priscille Pokam Fosso
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Eric Djahmeni
- Department of Medicine, Groote Schuur Hospital and University of Cape Town, Cape Town, South Africa
| | - Rosine Djokam-Dadjeu
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Marie-Solange Evehe
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Folefac Aminkeng
- The Canadian Pharmacogenomics Network for Drug Safety (CPNDS), Center for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Wilfred F Mbacham
- Department of Biochemistry, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon ; Laboratory for Public Health Research Biotechnologies, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon
| | - Jean Claude Mbanya
- Laboratory for Molecular Medicine and Metabolism, Biotechnology Center, University of Yaoundé I, Yaoundé, Cameroon ; Department of Internal Medicine and Specialties, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon ; National Obesity Center, Yaoundé Central Hospital, Yaoundé, Cameroon
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Anderson D, Cordell HJ, Fakiola M, Francis RW, Syn G, Scaman ESH, Davis E, Miles SJ, McLeay T, Jamieson SE, Blackwell JM. First genome-wide association study in an Australian aboriginal population provides insights into genetic risk factors for body mass index and type 2 diabetes. PLoS One 2015; 10:e0119333. [PMID: 25760438 PMCID: PMC4356593 DOI: 10.1371/journal.pone.0119333] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2014] [Accepted: 01/28/2015] [Indexed: 12/15/2022] Open
Abstract
A body mass index (BMI) >22kg/m2 is a risk factor for type 2 diabetes (T2D) in Aboriginal Australians. To identify loci associated with BMI and T2D we undertook a genome-wide association study using 1,075,436 quality-controlled single nucleotide polymorphisms (SNPs) genotyped (Illumina 2.5M Duo Beadchip) in 402 individuals in extended pedigrees from a Western Australian Aboriginal community. Imputation using the thousand genomes (1000G) reference panel extended the analysis to 6,724,284 post quality-control autosomal SNPs. No associations achieved genome-wide significance, commonly accepted as P<5x10-8. Nevertheless, genes/pathways in common with other ethnicities were identified despite the arrival of Aboriginal people in Australia >45,000 years ago. The top hit (rs10868204 Pgenotyped = 1.50x10-6; rs11140653 Pimputed_1000G = 2.90x10-7) for BMI lies 5' of NTRK2, the type 2 neurotrophic tyrosine kinase receptor for brain-derived neurotrophic factor (BDNF) that regulates energy balance downstream of melanocortin-4 receptor (MC4R). PIK3C2G (rs12816270 Pgenotyped = 8.06x10-6; rs10841048 Pimputed_1000G = 6.28x10-7) was associated with BMI, but not with T2D as reported elsewhere. BMI also associated with CNTNAP2 (rs6960319 Pgenotyped = 4.65x10-5; rs13225016 Pimputed_1000G = 6.57x10-5), previously identified as the strongest gene-by-environment interaction for BMI in African-Americans. The top hit (rs11240074 Pgenotyped = 5.59x10-6, Pimputed_1000G = 5.73x10-6) for T2D lies 5' of BCL9 that, along with TCF7L2, promotes beta-catenin's transcriptional activity in the WNT signaling pathway. Additional hits occurred in genes affecting pancreatic (KCNJ6, KCNA1) and/or GABA (GABRR1, KCNA1) functions. Notable associations observed for genes previously identified at genome-wide significance in other populations included MC4R (Pgenotyped = 4.49x10-4) for BMI and IGF2BP2 Pimputed_1000G = 2.55x10-6) for T2D. Our results may provide novel functional leads in understanding disease pathogenesis in this Australian Aboriginal population.
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Affiliation(s)
- Denise Anderson
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Heather J. Cordell
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 3BZ, United Kingdom
| | - Michaela Fakiola
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
- Cambridge Institute for Medical Research, Department of Medicine, and Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Richard W. Francis
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Genevieve Syn
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Elizabeth S. H. Scaman
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Elizabeth Davis
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
- Department of Endocrinology and Diabetes, Princess Margaret Hospital for Children, Subiaco, Western Australia, 6008, Australia
| | - Simon J. Miles
- Ngangganawili Aboriginal Health Service, Wiluna, Western Australia, 6646, Australia
| | - Toby McLeay
- Ngangganawili Aboriginal Health Service, Wiluna, Western Australia, 6646, Australia
| | - Sarra E. Jamieson
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Jenefer M. Blackwell
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
- Cambridge Institute for Medical Research, Department of Medicine, and Department of Pathology, University of Cambridge, Cambridge, United Kingdom
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27
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Nair AK, Muller YL, McLean NA, Abdussamad M, Piaggi P, Kobes S, Weil EJ, Curtis JM, Nelson RG, Knowler WC, Hanson RL, Baier LJ. Variants associated with type 2 diabetes identified by the transethnic meta-analysis study: assessment in American Indians and evidence for a new signal in LPP. Diabetologia 2014; 57:2334-8. [PMID: 25112377 PMCID: PMC4180905 DOI: 10.1007/s00125-014-3351-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2014] [Accepted: 07/22/2014] [Indexed: 10/29/2022]
Abstract
AIM/HYPOTHESIS A recent genome-wide trans-ancestry meta-analysis identified seven new loci associated with type 2 diabetes. We assessed the replication of the seven lead single nucleotide polymorphisms (SNPs) and evaluated these loci for additional signals in American Indians. METHODS Seven SNPs were genotyped in 7,710 individuals from a longitudinally studied American Indian population, and associations with type 2 diabetes, BMI and related phenotypes were assessed. Previous genome-wide association study (GWAS) data from these individuals were used to screen for additional type 2 diabetes signals at these loci. A variant independent of the trans-ancestry meta-analysis was identified within LPP, and its replication was assessed in an additional 3,106 urban American Indians. RESULTS SNP rs6813195 near to TMEM154 was nominally associated with type 2 diabetes (p = 0.01, OR 1.12 [95% CI 1.03, 1.22]) and adiposity: the type 2 diabetes risk allele was associated with a lower percentage body fat (β = -1.451%, p = 4.8 × 10(-4)). Another SNP, rs3130501 near to POU5F1-TCF19, was associated with BMI (β = -0.012, p = 0.004), type 2 diabetes adjusted for BMI (p = 0.02, OR 1.11 [95% CI 1.02, 1.22]), 2 h glucose concentrations (β = 0.080 mmol/l, p = 0.02) and insulin resistance estimated by homeostatic model (β = 0.039, p = 0.009). The independent variant identified at the LPP locus in our American Indian GWAS for type 2 diabetes was replicated in the additional samples (all American Indian meta-analysis, p = 8.9 × 10(-6), OR 1.29 [95% CI 1.15, 1.45]). CONCLUSIONS/INTERPRETATION For two of the seven newly identified variants, there was nominal evidence for association with type 2 diabetes and related traits in American Indians. Identification of an independent variant at the LPP locus suggests the existence of more than one type 2 diabetes signal at this locus.
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Affiliation(s)
- Anup K. Nair
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Yunhua Li Muller
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Nellie A. McLean
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Maryam Abdussamad
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Paolo Piaggi
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - E. Jennifer Weil
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Jeffrey M. Curtis
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Robert G. Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - William C. Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Robert L. Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
| | - Leslie J. Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 445 North 5th Street, Phoenix, AZ 85004 USA
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28
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Wang J, Zhang J, Shen J, Hu D, Yan G, Liu X, Xu X, Pei L, Li Y, Sun C. Association of KCNQ1 and KLF14 polymorphisms and risk of type 2 diabetes mellitus: A global meta-analysis. Hum Immunol 2014; 75:342-7. [PMID: 24486580 DOI: 10.1016/j.humimm.2014.01.008] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2013] [Revised: 01/03/2014] [Accepted: 01/14/2014] [Indexed: 12/31/2022]
Abstract
rs151290 in KCNQ1 and rs972283 in KLF14 have been evaluated in terms of risk of type 2 diabetes mellitus (T2DM), but the results are inconsistent. We performed an meta-analysis to assess the contributions of rs151290 in KCNQ1 and rs972283 in KLF14 to risk of T2DM. We searched the worldwide literature published from 2008 to 2013 in MEDLINE via PubMed, EMBASE, Cochrane CENTRAL and Chinese databases. Two reviewers extracted data independently using a standardized protocol, and any discrepancies were resolved by a third reviewer. Fixed- and random-effects meta-analyses were performed to pool the odds ratios (ORs). Publication bias and heterogeneity were examined. A total of 11 articles were included in the meta-analysis: 6 studies with 6696 cases and 7151 controls investigated rs151290 in KCNQ1, and 5 studies with 50,552 cases and 106,535 controls investigated rs972283 in KLF14. We obtained highly significant ORs for the risk allele C for rs151290 and the risk allele G for rs972283. The population attributable risk percentage for rs151290 and rs972283 was 6.83% and 4.18%, respectively. The risk allele C of rs151290 in KCNQ1 and risk allele G of rs972283 in KLF14 were both associated with increased risk of T2DM in a global population.
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Affiliation(s)
- Jinjin Wang
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
| | - Jianfeng Zhang
- Henan Armed Police Corps Hospital, Zhengzhou 450000, People's Republic of China.
| | - Jie Shen
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
| | - Dongsheng Hu
- Shenzhen University School of Medicine, Shenzhen 518060, People's Republic of China.
| | - Guoli Yan
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
| | - Xiaohui Liu
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
| | - Xueqin Xu
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
| | - Lanying Pei
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
| | - Yanfang Li
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
| | - Chunyang Sun
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, People's Republic of China.
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Hanson RL, Muller YL, Kobes S, Guo T, Bian L, Ossowski V, Wiedrich K, Sutherland J, Wiedrich C, Mahkee D, Huang K, Abdussamad M, Traurig M, Weil EJ, Nelson RG, Bennett PH, Knowler WC, Bogardus C, Baier LJ. A genome-wide association study in American Indians implicates DNER as a susceptibility locus for type 2 diabetes. Diabetes 2014; 63:369-76. [PMID: 24101674 PMCID: PMC3868048 DOI: 10.2337/db13-0416] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Most genetic variants associated with type 2 diabetes mellitus (T2DM) have been identified through genome-wide association studies (GWASs) in Europeans. The current study reports a GWAS for young-onset T2DM in American Indians. Participants were selected from a longitudinal study conducted in Pima Indians and included 278 cases with diabetes with onset before 25 years of age, 295 nondiabetic controls ≥45 years of age, and 267 siblings of cases or controls. Individuals were genotyped on a ∼1M single nucleotide polymorphism (SNP) array, resulting in 453,654 SNPs with minor allele frequency >0.05. SNPs were analyzed for association in cases and controls, and a family-based association test was conducted. Tag SNPs (n = 311) were selected for 499 SNPs associated with diabetes (P < 0.0005 in case-control analyses or P < 0.0003 in family-based analyses), and these SNPs were genotyped in up to 6,834 additional Pima Indians to assess replication. Rs1861612 in DNER was associated with T2DM (odds ratio = 1.29 per copy of the T allele; P = 6.6 × 10(-8), which represents genome-wide significance accounting for the number of effectively independent SNPs analyzed). Transfection studies in murine pancreatic β-cells suggested that DNER regulates expression of notch signaling pathway genes. These studies implicate DNER as a susceptibility gene for T2DM in American Indians.
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Franceschini N, Haack K, Göring HHH, Voruganti VS, Laston S, Almasy L, Lee ET, Best LG, Fabsitz RR, North KE, Maccluer JW, Meigs JB, Pankow JS, Cole SA. Epidemiology and genetic determinants of progressive deterioration of glycaemia in American Indians: the Strong Heart Family Study. Diabetologia 2013; 56:2194-202. [PMID: 23851660 PMCID: PMC3773080 DOI: 10.1007/s00125-013-2988-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2013] [Accepted: 06/18/2013] [Indexed: 01/01/2023]
Abstract
AIMS/HYPOTHESIS Type 2 diabetes is a chronic, heterogeneous disease and a major risk factor for cardiovascular diseases. The underlying mechanisms leading to progression to type 2 diabetes are not fully understood and genetic tools may help to identify important pathways of glycaemic deterioration. METHODS Using prospective data on American Indians from the Strong Heart Family Study, we identified 373 individuals defined as progressors (diabetes incident cases), 566 individuals with transitory impaired fasting glucose (IFG) and 1,011 controls (normal fasting glycaemia at all visits). We estimated the heritability (h(2)) of the traits and the evidence for association with 16 known variants identified in type 2 diabetes genome-wide association studies. RESULTS We noted high h(2) for diabetes progression (h(2) = 0.65 ± 0.16, p = 2.7 × 10(-6)) but little contribution of genetic factors to transitory IFG (h(2) = 0.09 ± 0.10, p = 0.19) for models adjusted for multiple risk factors. At least three variants (in WFS1, TSPAN8 and THADA) were nominally associated with diabetes progression in age- and sex-adjusted analyses with estimates showing the same direction of effects as reported in the discovery European ancestry studies. CONCLUSIONS/INTERPRETATION Our findings do not exclude these loci for diabetes susceptibility in American Indians and suggest phenotypic heterogeneity of the IFG trait, which may have implications for genetic studies when diagnosis is based on a single time-point measure.
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Affiliation(s)
- N Franceschini
- Department of Epidemiology, University of North Carolina, 137 E. Franklin St, Suite 306 CB No 8050, Chapel Hill, NC 27599-8050, USA.
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Hanson RL, Guo T, Muller YL, Fleming J, Knowler WC, Kobes S, Bogardus C, Baier LJ. Strong parent-of-origin effects in the association of KCNQ1 variants with type 2 diabetes in American Indians. Diabetes 2013; 62:2984-91. [PMID: 23630301 PMCID: PMC3717865 DOI: 10.2337/db12-1767] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Parent-of-origin effects were observed in an Icelandic population for several genetic variants associated with type 2 diabetes, including those in KLF14 (rs4731702), MOB2 (rs2334499), and KCNQ1 (rs2237892, rs231362). We analyzed parent-of-origin effects for these variants, along with two others in KCNQ1 identified in previous genome-wide association studies (rs2237895, rs2299620), in 7,351 Pima Indians from 4,549 nuclear families; 34% of participants had diabetes. In a subset of 287 normoglycemic individuals, acute insulin secretion was measured by an intravenous glucose tolerance test. Statistically significant (P < 0.05) parent-of-origin effects were seen for association with type 2 diabetes for all variants. The strongest effect was seen at rs2299620 in KCNQ1; the C allele was associated with increased diabetes when maternally derived (odds ratio [OR], 1.92; P = 4.1 × 10(-12)), but not when paternally derived (OR, 0.93; P = 0.47; P = 9.9 × 10(-6) for difference in maternal and paternal effects). A maternally derived C allele also was associated with a 28% decrease in insulin secretion (P = 0.002). This study confirms parent-of-origin effects in the association with type 2 diabetes for variants in KLF14, MOB2, and KCNQ1. In Pima Indians, the effect of maternally derived KCNQ1 variants appears to be mediated through decreased insulin secretion and is particularly strong, accounting for 4% of the variance in liability to diabetes.
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Affiliation(s)
- Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA.
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Wang J, Zhang J, Li L, Wang Y, Wang Q, Zhai Y, You H, Hu D. Association of rs12255372 in the TCF7L2 gene with type 2 diabetes mellitus: a meta-analysis. Braz J Med Biol Res 2013; 46:382-93. [PMID: 23579632 PMCID: PMC3854403 DOI: 10.1590/1414-431x20132677] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2012] [Accepted: 01/25/2013] [Indexed: 12/21/2022] Open
Abstract
Our objective was to evaluate the association of rs12255372 in the
TCF7L2 gene with type 2 diabetes mellitus (T2DM) in the world
population. We carried out a survey of the literature about the effect of rs12255372
on genetic susceptibility to T2DM by consulting PubMed, the Cochrane Library, and
Embase from 2006 to 2012, and then performed a meta-analysis of all the studies in
order to evaluate the association between rs12255372 and T2DM. A total of 33 articles
including 42 studies (with 34,076 cases and 36,192 controls) were confirmed to be
eligible and were included in the final meta-analysis: 6 studies conducted on
Europeans, 14 on Caucasians, 17 on Asians, 2 on Africans, and 3 on Americans.
Overall, the effect size was as follows: for the variant allele T (OR = 1.387, 95%CI
= 1.351-1.424), for the TT genotype (OR = 1.933, 95%CI = 1.815-2.057), for the GT
genotype (OR = 1.363, 95%CI = 1.315-1.413), for the dominant model (OR = 1.425, 95%CI
= 1.344-1.510), and for the recessive model (OR = 1.659, 95%CI = 1.563-1.761). In
summary, by pooling all available qualified data from genetic studies on rs12255372
and T2DM, we have confirmed that rs12255372 is significantly associated with
susceptibility to T2DM in the global population.
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Affiliation(s)
- Jinjin Wang
- Discipline of Public Health and Preventive Medicine, Center of Preventive Medicine Research and Assessment, Henan University of Traditional Chinese Medicine, Zhengzhou, China
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Uma Jyothi K, Jayaraj M, Subburaj KS, Prasad KJ, Kumuda I, Lakshmi V, Reddy BM. Association of TCF7L2 gene polymorphisms with T2DM in the population of Hyderabad, India. PLoS One 2013; 8:e60212. [PMID: 23577093 PMCID: PMC3618330 DOI: 10.1371/journal.pone.0060212] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2012] [Accepted: 02/22/2013] [Indexed: 11/19/2022] Open
Abstract
We attempt to evaluate the nature of association of TCF7L2 gene variants with T2DM, for the first time in the population of Hyderabad, which is considered to be diabetic capital of India. It is a case-control study of the three SNPs of TCF7L2, rs7903146, rs12255372 and rs11196205, genotyped on Sequenom Massarray platform, in a sample of 758 patients and 621 controls. The risk allele frequency of the three SNPs was found to be significantly higher in the T2DM cases than controls, implicating susceptibility for diabetes (p<0.01). The greatest risk of developing the disease was conferred by rs7903146. Further, the logistic regression of genotypes of each SNP under log additive model, and the haplotypes constituted by at least one of the three risk alleles also show significantly greater risk of developing T2DM when compared to the wild type haplotype. Further, BMI and WHR emerge as significant covariates with confounding effects. The strong association of the TCF7L2 SNPs with T2DM is consistent with the findings among other Indian and Non-Indian populations, suggesting universal phenomena of its association across ethnic groups globally, both within and outside the Indian subcontinent, albeit the functional relevance of these SNPs needs yet to be established.
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Affiliation(s)
- Kommoju Uma Jyothi
- Molecular Anthropology Group, Biological Anthropology Unit, Indian Statistical Institute, Hyderabad, India
| | - Maruda Jayaraj
- Molecular Anthropology Group, Biological Anthropology Unit, Indian Statistical Institute, Hyderabad, India
| | - Kadarkarai Samy Subburaj
- Molecular Anthropology Group, Biological Anthropology Unit, Indian Statistical Institute, Hyderabad, India
| | | | - Irgam Kumuda
- Molecular Anthropology Group, Biological Anthropology Unit, Indian Statistical Institute, Hyderabad, India
| | - Velaga Lakshmi
- Department of Human Genetics, Andhra University, Visakhapatnam, India
| | - Battini Mohan Reddy
- Molecular Anthropology Group, Biological Anthropology Unit, Indian Statistical Institute, Hyderabad, India
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ACE I/D and MTHFR C677T polymorphisms are significantly associated with type 2 diabetes in Arab ethnicity: a meta-analysis. Gene 2013; 520:166-77. [PMID: 23458876 DOI: 10.1016/j.gene.2013.02.017] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2012] [Revised: 01/28/2013] [Accepted: 02/06/2013] [Indexed: 12/14/2022]
Abstract
In this meta-analysis study, SNPs were investigated for their association with type 2 diabetes (T2D) in both Arab and Caucasian ethnicities. A total of 55 SNPs were analyzed, of which 11 fulfilled the selection criteria, and were used for analysis. It was found that TCF7L2 rs7903146 was significantly associated with a pooled OR of 1.155 (95%C.I.=1.059-1.259), p<0.0001 and I(2)=78.30% among the Arab population, whereas among Caucasians, the pooled OR was 1.45 (95%C.I.=1.386-1.516), p<0.0001 and I(2)=77.20%. KCNJ11 rs5219 was significantly associated in both the populations with a pooled OR of 1.176(1.092-1.268), p<0.0001 and I(2)=32.40% in Caucasians and a pooled OR of 1.28(1.111-1.475), p=0.001 among Arabs. The ACE I/D polymorphism was found to be significantly associated with a pooled OR of 1.992 (95%C.I.=1.774-2.236), p<0.0001 and I(2)=83.20% among the Arab population, whereas among Caucasians, the pooled OR was 1.078 (95%C.I.=0.993-1.17), p=0.073 and I(2)=0%. Similarly, MTHFR C677T polymorphism was also found to be significantly associated among Arabs with a pooled OR of 1.924 (95%C.I.=1.606-2.304), p<0.0001 and I(2)=27.20%, whereas among Caucasians, the pooled OR was 0.986 (95%C.I.=0.868-1.122), p=0.835 and I(2)=0%. Meanwhile PPARG-2 Pro12Ala, CDKN2A/2B rs10811661, IGF2BP2 rs4402960, HHEX rs7923837, CDKAL1 rs7754840, EXT2 rs1113132 and SLC30A8 rs13266634 were found to have no significant association with T2D among Arabs. In conclusion, it seems from this study that both Arabs and Caucasians have different SNPs associated with T2D. Moreover, this study sheds light on the profound necessity for further investigations addressing the question of the genetic components of T2D in Arabs.
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35
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Hale PJ, López-Yunez AM, Chen JY. Genome-wide meta-analysis of genetic susceptible genes for Type 2 Diabetes. BMC SYSTEMS BIOLOGY 2012; 6 Suppl 3:S16. [PMID: 23281828 PMCID: PMC3524015 DOI: 10.1186/1752-0509-6-s3-s16] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background Many genetic studies, including single gene studies and Genome-wide association studies (GWAS), aim to identify risk alleles for genetic diseases such as Type II Diabetes (T2D). However, in T2D studies, there is a significant amount of the hereditary risk that cannot be simply explained by individual risk genes. There is a need for developing systems biology approaches to integrate comprehensive genetic information and provide new insight on T2D biology. Methods We performed comprehensive integrative analysis of Single Nucleotide Polymorphisms (SNP's) individually curated from T2D GWAS results and mapped them to T2D candidate risk genes. Using protein-protein interaction data, we constructed a T2D-specific molecular interaction network consisting of T2D genetic risk genes and their interacting gene partners. We then studied the relationship between these T2D genes and curated gene sets. Results We determined that T2D candidate risk genes are concentrated in certain parts of the genome, specifically in chromosome 20. Using the T2D genetic network, we identified highly-interconnected network "hub" genes. By incorporating T2D GWAS results, T2D pathways, and T2D genes' functional category information, we further ranked T2D risk genes, T2D-related pathways, and T2D-related functional categories. We found that highly-interconnected T2D disease network “hub” genes most highly associated to T2D genetic risks to be PI3KR1, ESR1, and ENPP1. The well-characterized TCF7L2, contractor to our expectation, was not among the highest-ranked T2D gene list. Many interacted pathways play a role in T2D genetic risks, which includes insulin signalling pathway, type II diabetes pathway, maturity onset diabetes of the young, adipocytokine signalling pathway, and pathways in cancer. We also observed significant crosstalk among T2D gene subnetworks which include insulin secretion, regulation of insulin secretion, response to peptide hormone stimulus, response to insulin stimulus, peptide secretion, glucose homeostasis, and hormone transport. Overview maps involving T2D genes, gene sets, pathways, and their interactions are all reported. Conclusions Large-scale systems biology meta-analyses of GWAS results can improve interpretations of genetic variations and genetic risk factors. T2D genetic risks can be attributable to the summative genetic effects of many genes involved in a broad range of signalling pathways and functional networks. The framework developed for T2D studies may serve as a guide for studying other complex diseases.
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Affiliation(s)
- Paul J Hale
- School of Informatics, Indiana University-Purdue University, Indianapolis, IN, USA
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36
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Peng S, Zhu Y, Lü B, Xu F, Li X, Lai M. TCF7L2 gene polymorphisms and type 2 diabetes risk: a comprehensive and updated meta-analysis involving 121,174 subjects. Mutagenesis 2012. [PMID: 23188737 DOI: 10.1093/mutage/ges048] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Recently, many new loci associated with type 2 diabetes have been uncovered by genetic association studies and genome-wide association studies. As more reports are made, particularly with respect to varying ethnicities, there is a need to determine more precisely the effect sizes in each major racial group. In addition, some reports have claimed ethnic-specific associations with alternative single-nucleotide polymorphisms (SNPs), and to that end there has been a degree of confusion. We conducted a meta-analysis using an additive genetic model. Eight polymorphisms in 155 studies with 121174 subjects (53385 cases and 67789 controls) were addressed in this meta-analysis. Significant associations were found between type 2 diabetes and rs7903146, rs12255372, rs11196205, rs7901695, rs7895340 and rs4506565, with summary odds ratios (ORs) (95% confidence interval) of 1.39 (1.34-1.45), 1.33 (1.27-1.40), 1.20 (1.14-1.26), 1.32 (1.25-1.39), 1.21 (1.13-1.29) and 1.39 (1.29-1.49), respectively. In addition, no significant associations were found between the two polymorphisms (rs290487 and rs11196218) and type 2 diabetes. The summary ORs for the six statistically significant associations (P < 0.05) were further evaluated by estimating the false-positive report probability, with results indicating that all of the six significant associations were considered noteworthy, and may plausibly be true associations. Significant associations were found between the six polymorphisms (rs7903146, rs12255372, rs11196205, rs7901695, rs7895340 and rs4506565) in the TCF7L2 gene and type 2 diabetes risk, and the other two polymorphisms (rs11196218 and rs290487) were not found to be significantly associated with type 2 diabetes. Subgroups analyses show that significant associations are not found between the six SNPs (rs7903146, rs12255372, rs11196205, rs7901695, rs7895340, and rs4506565) and the type 2 diabetes in some ethnic populations.
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Affiliation(s)
- Sihua Peng
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou 310058, PR China
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37
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Turki A, Al-Zaben GS, Mtiraoui N, Marmmuoch H, Mahjoub T, Almawi WY. Transcription factor-7-like 2 gene variants are strongly associated with type 2 diabetes in Tunisian Arab subjects. Gene 2012; 513:244-8. [PMID: 23142382 DOI: 10.1016/j.gene.2012.10.086] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2012] [Revised: 10/10/2012] [Accepted: 10/26/2012] [Indexed: 12/11/2022]
Abstract
Genome-wide association studies validated transcription factor 7-like 2 (TCF7L2) gene as confirmed type 2 diabetes (T2DM) susceptibility locus, and an ethnic contribution of TCF7L2 variants to T2DM risk was indicated. The aim of this study was to replicate in a Tunisian Arab population identified associations of common TCF7L2 variants with T2DM. We tested the association of TCF7L2 variants: rs4506565, rs7903146, rs12243326, and rs12255372, with T2DM in 900 Tunisian patients and 875 control subjects. TCF7L2 genotyping was done by allelic discrimination/real-time PCR method. Minor allele frequencies of rs4506565 (P=2.4×10(-8)), rs7903146 (P=1.2×10(-6)), rs12243326 (P=8.4×10(-8)) and rs12255372 (P=1.1×10(-5)) were significantly higher in cases. The four tested TCF7L2 variants were in linkage disequilibrium, and 4-locus (rs4506565, rs7903146, rs12243326, rs12255372) haplotype analysis demonstrated that haplotype 1111 was negatively associated (Pc<0.001), while haplotypes 2222 (Pc=0.008) and 2211 (Pc=0.020) were positively associated with T2DM risk, after controlling for a number of covariates. The strong contribution of TCF7L2 gene variants to T2DM among Tunisians is in line with similar findings in other ethnic groups, confirming TCF7L2 as a common T2DM candidate gene.
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Affiliation(s)
- Amira Turki
- Faculty of Pharmacy of Monastir, University of Monastir, Monastir, Tunisia
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38
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Ip W, Chiang YTA, Jin T. The involvement of the wnt signaling pathway and TCF7L2 in diabetes mellitus: The current understanding, dispute, and perspective. Cell Biosci 2012; 2:28. [PMID: 22892353 PMCID: PMC3468386 DOI: 10.1186/2045-3701-2-28] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2012] [Accepted: 06/19/2012] [Indexed: 12/17/2022] Open
Abstract
The Wnt signaling pathway was initially discovered for its role in tumorigenesis and the development of Drosophila and other eukaryotic organisms. The key effector of this pathway, the bipartite transcription factor β-cat/TCF, is formed by free β-catenin (β-cat) and a TCF protein, including TCF7L2. Extensive recent investigations have highlighted the role of the Wnt signaling pathway in metabolic homeostasis and its implication in diabetes and other metabolic diseases. Genome-wide association studies have shown that several key components of the Wnt signaling pathway are implicated in metabolic homeostasis and the development of type 2 diabetes (T2D). Despite controversial observations regarding the role of Wnt signaling in the development and function of pancreatic islets, the discovery of the association between certain single nucleotide polymorphisms of TCF7L2 and T2D susceptibility has fueled great efforts to explore the role of Wnt signaling in the function of pancreatic β-cells and glucose homeostasis. Here we have introduced our basic understanding of the canonical Wnt signaling pathway, summarized our current knowledge on its implication in metabolic homeostasis and T2D, discussed the work on TCF7L2 as a T2D susceptibility gene, and presented the controversial role of Wnt signaling and TCF7L2 in pancreatic islets as well as their potential metabolic function in other organs. We then expanded our view into the crosstalk among Wnt, insulin and FOXO signaling cascades, which further illustrates the complexity of the Wnt signaling pathway in metabolic homeostasis. Finally, we have presented our perspectives.
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Affiliation(s)
- Wilfred Ip
- Institute of Medical Science, University of Toronto, Toronto, Canada.
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39
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Alami FM, Ahmadi M, Bazrafshan H, Tabarraei A, Khosravi A, Tabatabaiefar MA, Samaei NM. Association of the TCF7L2 rs12255372 (G/T) variant with type 2 diabetes mellitus in an Iranian population. Genet Mol Biol 2012; 35:413-7. [PMID: 22888288 PMCID: PMC3389527 DOI: 10.1590/s1415-47572012005000029] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2011] [Accepted: 01/24/2012] [Indexed: 12/18/2022] Open
Abstract
In various populations worldwide, common variants of the TCF7L2 (Transcription factor 7-like 2) gene are associated with the risk of type 2 diabetes mellitus (T2DM). The aim was to investigate the association between rs12255372 (G/T) polymorphism in the TCF7L2 gene and T2DM in an Iranian population. 236 unrelated patients with T2DM, and 255 normoglycemic controls without diabetes were studied. The PCR-RFLP method was used for genotyping rs12255372 (G/T) polymorphism, and the SPSS version 18.0 for Windows for statistical analysis. The minor T allele of TCF7L2 rs12255372 was found to significantly increase the risk of T2DM, with an allelic odds ratio (OR) of 1.458 (95% CI 1.108–1.918, p = 0.007). A significant difference in TT genotype was observed between T2DM patients and normoglycemic controls (OR 2.038, 95% CI 1.147–3.623; p = 0.014). On assuming dominant and recessive models, ORs of 1.52 [95% CI (1.05–2.21) p = 0.026)] and 1.74 [95% CI (1.01–3.00) p = 0.043] were obtained, respectively, thereby implying that the co-dominant model would best fit the susceptible gene effect. This study further confirms the TCF7L2 gene as enhancing susceptibility to the development of T2DM.
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Affiliation(s)
- Faranak Mahmoudi Alami
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran
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40
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Saxena R, Elbers C, Guo Y, Peter I, Gaunt T, Mega J, Lanktree M, Tare A, Castillo B, Li Y, Johnson T, Bruinenberg M, Gilbert-Diamond D, Rajagopalan R, Voight B, Balasubramanyam A, Barnard J, Bauer F, Baumert J, Bhangale T, Böhm B, Braund P, Burton P, Chandrupatla H, Clarke R, Cooper-DeHoff R, Crook E, Davey-Smith G, Day I, de Boer A, de Groot M, Drenos F, Ferguson J, Fox C, Furlong C, Gibson Q, Gieger C, Gilhuijs-Pederson L, Glessner J, Goel A, Gong Y, Grant S, Grobbee D, Hastie C, Humphries S, Kim C, Kivimaki M, Kleber M, Meisinger C, Kumari M, Langaee T, Lawlor D, Li M, Lobmeyer M, Maitland-van der Zee AH, Meijs M, Molony C, Morrow D, Murugesan G, Musani S, Nelson C, Newhouse S, O'Connell J, Padmanabhan S, Palmen J, Patel S, Pepine C, Pettinger M, Price T, Rafelt S, Ranchalis J, Rasheed A, Rosenthal E, Ruczinski I, Shah S, Shen H, Silbernagel G, Smith E, Spijkerman A, Stanton A, Steffes M, Thorand B, Trip M, van der Harst P, van der A D, van Iperen E, van Setten J, van Vliet-Ostaptchouk J, Verweij N, Wolffenbuttel B, Young T, Zafarmand M, Zmuda J, Boehnke M, Altshuler D, McCarthy M, Kao W, Pankow J, Cappola T, Sever P, Poulter N, Caulfield M, Dominiczak A, Shields D, Bhatt DL, Zhang L, Curtis S, Danesh J, Casas J, van der Schouw Y, Onland-Moret N, Doevendans P, Dorn G, Farrall M, FitzGerald G, Hamsten A, Hegele R, Hingorani A, Hofker M, Huggins G, Illig T, Jarvik G, Johnson J, Klungel O, Knowler W, Koenig W, März W, Meigs J, Melander O, Munroe P, Mitchell B, Bielinski S, Rader D, Reilly M, Rich S, Rotter J, Saleheen D, Samani N, Schadt E, Shuldiner A, Silverstein R, Kottke-Marchant K, Talmud P, Watkins H, Asselbergs FW, de Bakker P, McCaffery J, Wijmenga C, Sabatine M, Wilson J, Reiner A, Bowden D, Hakonarson H, Siscovick D, Keating B. Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci. Am J Hum Genet 2012; 90:410-25. [PMID: 22325160 PMCID: PMC3309185 DOI: 10.1016/j.ajhg.2011.12.022] [Citation(s) in RCA: 195] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2011] [Revised: 12/06/2011] [Accepted: 12/31/2011] [Indexed: 01/12/2023] Open
Abstract
To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ∼2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.
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Affiliation(s)
- Richa Saxena
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Clara C. Elbers
- Department of Genetics, University of Pennsylvania, School of Medicine, Philadelphia, PA 19104, USA
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Yiran Guo
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- BGI Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, NY 10029 USA
| | - Tom R. Gaunt
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, Department of Social Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Jessica L. Mega
- Thrombolysis in Myocardial Infarction Study Group, Cardiovascular Division, Brigham and Women's Hospital, Boston, MA 021155 USA
| | - Matthew B. Lanktree
- Department of Biochemistry, University of Western Ontario, London, ON N6A 5C1, Canada
| | - Archana Tare
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - Berta Almoguera Castillo
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Servicio de Genética Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Avda. Reyes Católicos 228040, Madrid, Spain
| | - Yun R. Li
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Toby Johnson
- Clinical Pharmacology, Barts and the London Genome Centre, Queen Mary University of London, London EC1M 6BQ, UK
- William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Marcel Bruinenberg
- LifeLines Cohort Study and Biobank, University Medical Center Groningen, University of Groningen, the Netherlands
| | - Diane Gilbert-Diamond
- Children's Environmental Health and Disease Prevention Center at Dartmouth, Hanover, NH 03755, USA
- Section of Biostatistics and Epidemiology, Department of Community and Family Medicine, Dartmouth Medical School, Hanover, NH 03756, USA
| | | | - Benjamin F. Voight
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - Ashok Balasubramanyam
- Translational Metabolism Unit, Division of Diabetes, Endocrinology and Metabolism, Baylor College of Medicine, Houston, TX 77030, USA
| | - John Barnard
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Florianne Bauer
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Jens Baumert
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Tushar Bhangale
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Bernhard O. Böhm
- Cardiology Group Frankfurt-Sachsenhausen, Frankfurt 60598, Germany
| | - Peter S. Braund
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Paul R. Burton
- Department of Health Sciences, University of Leicester, University Rd, Leicester LE1 7RH, UK
| | - Hareesh R. Chandrupatla
- Cardiovascular Institute, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Robert Clarke
- Clinical Trial Service Unit, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX37LF, UK
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL 32610, USA
- Division of Cardiovascular Medicine, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | | | - George Davey-Smith
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, Department of Social Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Ian N. Day
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, Department of Social Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Anthonius de Boer
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Mark C.H. de Groot
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Fotios Drenos
- Centre for Cardiovascular Genetics, Department of Medicine, University College London, 5 University Street, London, WC1E 6JF, UK
| | - Jane Ferguson
- Cardiovascular Institute, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Caroline S. Fox
- Framingham Heart Study, Boston University School of Medicine, Boston, MA 02118, USA
| | - Clement E. Furlong
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA 98195, USA
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Quince Gibson
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lisa A. Gilhuijs-Pederson
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Joseph T. Glessner
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Anuj Goel
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Yan Gong
- Division of Cardiovascular Medicine, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Struan F.A. Grant
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Diederick E. Grobbee
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Claire Hastie
- British Heart Foundation Glasgow Cardiovascular Research Centre, Division of Cardiovascular and Medical Sciences, Western Infirmary, University of Glasgow, Glasgow G12 8TA, UK
| | - Steve E. Humphries
- Centre for Cardiovascular Genetics, Department of Medicine, University College London, 5 University Street, London, WC1E 6JF, UK
| | - Cecilia E. Kim
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, London, UK
- Genetic Epidemiology Group, Department of Epidemiology and Public Health, University College London, London WC1E 6BT, UK
| | - Marcus Kleber
- LURIC Study, Freiburg im Breisgau 79098, Germany
- Synlab Center of Laboratory Diagnostics Heidelberg, Heidelberg 69037, Germany
| | - Christa Meisinger
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Meena Kumari
- Genetic Epidemiology Group, Department of Epidemiology and Public Health, University College London, London WC1E 6BT, UK
| | - Taimour Y. Langaee
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL 32610, USA
| | - Debbie A. Lawlor
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, Department of Social Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Mingyao Li
- Cardiovascular Institute, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Maximilian T. Lobmeyer
- Division of Cardiovascular Medicine, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Anke-Hilse Maitland-van der Zee
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Matthijs F.L. Meijs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cliona M. Molony
- Department of Genetics, Rosetta Inpharmatics, Seattle, WA 98109, USA
| | - David A. Morrow
- Thrombolysis in Myocardial Infarction Study Group, Cardiovascular Division, Brigham and Women's Hospital, Boston, MA 021155 USA
| | - Gurunathan Murugesan
- Department of Clinical Pathology, Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Solomon K. Musani
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Stephen J. Newhouse
- Clinical Pharmacology, Barts and the London Genome Centre, Queen Mary University of London, London EC1M 6BQ, UK
- William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Jeffery R. O'Connell
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Sandosh Padmanabhan
- British Heart Foundation Glasgow Cardiovascular Research Centre, Division of Cardiovascular and Medical Sciences, Western Infirmary, University of Glasgow, Glasgow G12 8TA, UK
| | - Jutta Palmen
- Centre for Cardiovascular Genetics, Department of Medicine, University College London, 5 University Street, London, WC1E 6JF, UK
| | - Sanjey R. Patel
- Division of Sleep Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Carl J. Pepine
- Division of Cardiovascular Medicine, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Mary Pettinger
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Thomas S. Price
- Medical Research Council Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London WC2R 2LS, UK
| | - Suzanne Rafelt
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Jane Ranchalis
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA 98195, USA
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Elisabeth Rosenthal
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA 98195, USA
| | - Ingo Ruczinski
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Sonia Shah
- University College Genetics Institute, University College London, 5 University St London, WC1E 6BT, UK
| | - Haiqing Shen
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Günther Silbernagel
- Division of Endocrinology, Diabetology, Nephrology, Vascular Disease, and Clinical Chemistry, Department of Internal Medicine, Eberhard-Karls-University Tübingen, Tübingen 72074, Germany
| | | | | | - Alice Stanton
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
| | - Michael W. Steffes
- Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN 55455, USA
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Mieke Trip
- Department of Vascular Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Genetics, University Medical Center Groningen and Groningen University, 9700 RB Groningen, The Netherlands
| | - Daphne L. van der A
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | | | - Jessica van Setten
- Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jana V. van Vliet-Ostaptchouk
- Molecular Genetics, Department of Pathology and Medical Biology, University Medical Center Groningen and University of Groningen, The Netherlands
- Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Bruce H.R. Wolffenbuttel
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Taylor Young
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - M. Hadi Zafarmand
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joseph M. Zmuda
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, 130 DeSoto St, Pittsburgh, PA 15261, USA
| | | | | | - Michael Boehnke
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - David Altshuler
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Mark McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
| | - W.H. Linda Kao
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21287, USA
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55454, USA
| | - Thomas P. Cappola
- Cardiovascular Institute, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Peter Sever
- International Centre for Circulatory Health, Imperial College London, London W2 1PG, UK
| | - Neil Poulter
- International Centre for Circulatory Health, Imperial College London, London W2 1PG, UK
| | - Mark Caulfield
- Clinical Pharmacology, Barts and the London Genome Centre, Queen Mary University of London, London EC1M 6BQ, UK
- William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Anna Dominiczak
- British Heart Foundation Glasgow Cardiovascular Research Centre, Division of Cardiovascular and Medical Sciences, Western Infirmary, University of Glasgow, Glasgow G12 8TA, UK
| | - Denis C. Shields
- Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Ireland
| | | | - Li Zhang
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Sean P. Curtis
- Merck Research Laboratories, P.O. Box 2000, Rahway, NJ 07065, USA
| | - John Danesh
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Juan P. Casas
- Department of Epidemiology and Public Health, University College London, London, UK
- Department of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - N. Charlotte Onland-Moret
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Pieter A. Doevendans
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Gerald W. Dorn
- Washington University Center for Pharmacogenetics, 660 S. Euclid Ave, Campus Box 8220, St. Louis, MO 63110, USA
| | - Martin Farrall
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Department of Cardiovascular Medicine, University of Oxford, Level 6 West Wing, John Radcliffe Hospital, Headley Way, Headington, Oxford OX3 9DU, UK
| | - Garret A. FitzGerald
- The Institute for Translational Medicine and Therapeutics, School of Medicine, University of Pennsylvania, Philadelphia, PA 19146, USA
| | - Anders Hamsten
- Cardiovascular Genetics Group, Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, SE-17176 Stockholm, Sweden
| | - Robert Hegele
- Department of Biochemistry, University of Western Ontario, London, ON N6A 5C1, Canada
| | - Aroon D. Hingorani
- Centre for Clinical Pharmacology, Department of Medicine, University College London, London WC1E 6JF, UK
| | - Marten H. Hofker
- University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Gordon S. Huggins
- Molecular Cardiology Research Institute, Center for Translational Genomics, Tufts Medical Center and Tufts University, Boston, MA 02114, USA
| | - Thomas Illig
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, 30625 Hannover, Germany
| | - Gail P. Jarvik
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA 98195, USA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL 32610, USA
- Division of Cardiovascular Medicine, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Olaf H. Klungel
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - William C. Knowler
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ 85104, USA
| | - Wolfgang Koenig
- Department of Internal Medicine II-Cardiology, University of Ulm Medical Center, Ulm, Germany
| | - Winfried März
- Synlab Center of Laboratory Diagnostics Heidelberg, Heidelberg 69037, Germany
- Mannheim Institute of Public Health, Social and Preventive Medicine, Medical Faculty Mannheim, University of Heidelberg D-68167 Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, 8010 Graz, Austria
| | - James B. Meigs
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- General Medicine Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Olle Melander
- Clinical Research Center, Malmö University Hospital, Malmö SE-205 02, Sweden
| | - Patricia B. Munroe
- Clinical Pharmacology, Barts and the London Genome Centre, Queen Mary University of London, London EC1M 6BQ, UK
- William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Susan J. Bielinski
- Division of Epidemiology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
| | - Daniel J. Rader
- Cardiovascular Institute, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Muredach P. Reilly
- Cardiovascular Institute, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22902, USA
| | - Jerome I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Pakistan
- Merck Research Laboratories, P.O. Box 2000, Rahway, NJ 07065, USA
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, LE3 9QP, UK
| | | | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Roy Silverstein
- Department of Cell Biology, Lerner Research Institute, Cleveland Clinic Foundation, Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, 9500 Euclid Avenue Cleveland, OH 44195, USA
| | | | - Philippa J. Talmud
- Centre for Cardiovascular Genetics, Department of Medicine, University College London, 5 University Street, London, WC1E 6JF, UK
| | - Hugh Watkins
- Washington University Center for Pharmacogenetics, 660 S. Euclid Ave, Campus Box 8220, St. Louis, MO 63110, USA
| | - Folkert W. Asselbergs
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Paul I.W. de Bakker
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jeanne McCaffery
- Weight Control and Diabetes Research Center, The Miriam Hospital and Warren Alpert School of Medicine at Brown University, Providence, RI 02906, USA
| | - Cisca Wijmenga
- Department of Genetics, University Medical Center Groningen and Groningen University, 9700 RB Groningen, The Netherlands
| | - Marc S. Sabatine
- Thrombolysis in Myocardial Infarction Study Group, Cardiovascular Division, Brigham and Women's Hospital, Boston, MA 021155 USA
| | - James G. Wilson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Alex Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Donald W. Bowden
- Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC 27106, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - David S. Siscovick
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA 98101, USA
| | - Brendan J. Keating
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
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Genetic variants of TCF7L2 are associated with type 2 diabetes in a northeastern Chinese population. Gene 2012; 495:115-9. [PMID: 22245614 DOI: 10.1016/j.gene.2011.12.055] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2011] [Revised: 12/14/2011] [Accepted: 12/22/2011] [Indexed: 12/21/2022]
Abstract
Variants in the gene encoding transcription factor 7-like 2 (TCF7L2) are associated with type 2 diabetes mellitus (T2D) in several ethnic groups. Two intronic variants, rs290487 and rs11196218, were originally identified as T2D modifiers in Hong Kong Chinese and Taiwan Chinese populations, respectively. However, discrepancies were noted in subsequent replicated studies. In this study, an association of these two loci with T2D was investigated in a Harbin Chinese population. Whereas the two populations in the initial studies were southern Han Chinese, Harbin Chinese are from northeastern China. The SNPs rs290487 and rs11196218 were genotyped by ligase detection reactions in 700 T2D patients and 570 unrelated non-diabetic controls. Association analyses, which were carried out using the case-control sample set, yielded a significant association between rs290487 and T2D, with a trend opposite to that described in a previous report. Specifically, rs290487T was found to be significantly associated with disease susceptibility (p=0.039), and the allelic OR of rs290487T carriers was 1.184 (95% CI 1.008-1.391). There was no significant association between rs11196218 and T2D. Taken together, TCF7L2 may be an important susceptibility gene for T2D in some Chinese populations. The discrepancies in the allelic associations determined for northern vs. southern Chinese allude to the presence of genetic variation among the Han Chinese.
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Kahveci C, Koldemir M, Cagatay P, Bayer H, Yildiz S, Bagriacik N, Duman BS. Relationship of transcription factor 7 like 2 gene rs7903146 variation with type 2 diabetes and obesity related parameters. Diabetes Metab Syndr 2012; 6:48-53. [PMID: 23014255 DOI: 10.1016/j.dsx.2012.05.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
AIMS The allele frequencies of transcription factor 7 like 2 (TCF7L2) gene rs7903146 polymorphism in type 2 diabetes mellitus (T2DM) and non-T2DM controls were determined. METHODS TCF7L2 rs7903146 genotypes were determined with qPCR. RESULTS The TCF7L2 gene rs7903146 genotype frequencies for homozygous wild type (C/C), heterozygous (C/T) and homozygous polymorphic (T/T) for T2DM patients were determined, respectively, as 71.4%, 14.3%, 14.3% and 72.5%, 11.8%, 15.7% for controls. The weight, length and lean body mass were higher in C/T+T/T compared to C/C carriers. Glucose, insulin, insulin resistance and homeostatic model assessment (HOMA) were nonsignificantly higher in rs7903146C/T+T/T in comparison to C/C. TCF7L2 gene rs7903146 genotypes were not found to interact with drugs. The absence of any difference between genotype frequencies among study groups indicates that no association persists with TCF7L2 gene rs7903146 polymorphism and T2DM. CONCLUSIONS The effects of rs7903146 variation over some obesity variables suggest that this variation may effect T2DM development via obesity.
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Affiliation(s)
- Cigdem Kahveci
- Marmara University, Faculty of Science and Arts, Department of Biology, Istanbul, Turkey
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Manolopoulos VG, Ragia G, Tavridou A. Pharmacogenomics of oral antidiabetic medications: current data and pharmacoepigenomic perspective. Pharmacogenomics 2011; 12:1161-91. [PMID: 21843065 DOI: 10.2217/pgs.11.65] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is an increasingly prevalent disease. Several classes of drugs are currently available to treat T2DM patients; however, clinical response to these drugs often exhibits significant variation among individuals. For the oral antidiabetic drug classes of sulfonylureas, nonsulfonylurea insulin secretagogs, biguanides and thiazolidinediones, pharmacogenomic evidence has accumulated demonstrating an association between specific gene polymorphisms and interindividual variability in their therapeutic and adverse reaction effects. These polymorphisms are in genes of molecules involved in metabolism, transport and therapeutic mechanisms of the aforementioned drugs. Overall, it appears that pharmacogenomics has the potential to improve the management of T2DM and help clinicians in the effective prescribing of oral antidiabetic medications. Although pharmacogenomics can explain some of the heterogeneity in dose requirements, response and incidence of adverse effects of drugs between individuals, it is now clearly understood that much of the diversity in drug effects cannot be solely explained by studying the genomic diversity. Epigenomics, the field that focuses on nongenomic modifications that influence gene expression, may expand the scope of pharmacogenomics towards optimization of drug therapy. Therefore, pharmacoepigenomics, the combined analysis of genetic variations and epigenetic modifications, holds promise for the realization of personalized medicine. Although pharmacoepigenomics has so far been evaluated mainly in cancer pharmacotherapy, studies on epigenomic modifications during T2DM development provide useful data on the potential of pharmacoepigenomics to elucidate the mechanisms underlying interindividual response to oral antidiabetic treatment. In summary, the present article focuses on available data from pharmacogenomic studies of oral antidiabetic drugs and also provides an overview of T2DM epigenomic research, which has the potential to boost the development of pharmacoepigenomics in antidiabetic treatment.
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Affiliation(s)
- Vangelis G Manolopoulos
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Dragana Campus, 68100 Alexandroupolis, Greece.
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Guinan KJ. Worldwide distribution of type II diabetes-associated TCF7L2 SNPs: evidence for stratification in Europe. Biochem Genet 2011; 50:159-79. [PMID: 21898192 DOI: 10.1007/s10528-011-9456-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2010] [Accepted: 05/12/2011] [Indexed: 12/24/2022]
Abstract
Type II diabetes is a multifactorial disease with a complex etiology. Numerous genes have been implicated in disease pathogenesis. In particular, SNPs at the TCF7L2 locus have consistently shown strong associations with type II diabetes. This study characterizes the global distribution of type II diabetes-associated TCF7L2 SNPs utilizing HapMap, HGDP-CEPH, and Alfred databases and the literature. High frequencies of rs7903146(T), rs12255372(T), and rs7901695(C) SNPs are observed in Africa, Europe, and the Middle East, but they are reduced and almost absent in Southeast Asian and Native American populations. In contrast, rs11196218(A) has the highest frequency in Eurasia but is reduced in sub-Saharan African and Native American populations. Regional variations in rs7903146(T) follow a gradient of decreasing frequency from southern into northeastern Europe. These findings demonstrate extensive global and regional variations in the frequencies of TCF7L2 SNPs, which may contribute to differences in the incidence of type II diabetes worldwide.
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Kifagi C, Makni K, Boudawara M, Mnif F, Hamza N, Abid M, Granier C, Ayadi H. Association of Genetic Variations in TCF7L2, SLC30A8, HHEX, LOC387761, and EXT2 with Type 2 Diabetes Mellitus in Tunisia. Genet Test Mol Biomarkers 2011; 15:399-405. [DOI: 10.1089/gtmb.2010.0199] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Affiliation(s)
- Chamseddine Kifagi
- “Targets for Diagnosis and Therapeutic in the Human Pathology” Research Unit, Center of Biotechnology of Sfax, Sfax, Tunisia
- Laboratoire International Associé N° 135, “Gènes et protéines dans les maladies multigéniques,” Sfax (Tunisia)/Montpellier (France)
| | - Kaouthar Makni
- “Targets for Diagnosis and Therapeutic in the Human Pathology” Research Unit, Center of Biotechnology of Sfax, Sfax, Tunisia
- Laboratoire International Associé N° 135, “Gènes et protéines dans les maladies multigéniques,” Sfax (Tunisia)/Montpellier (France)
| | | | - Fatma Mnif
- Department of Endocrinology, Hédi Chaker Hospital, Sfax, Tunisia
| | - Naziha Hamza
- Laboratory of Analyses, Social National Case of Sfax, Sfax, Tunisia
| | - Mouhamed Abid
- Department of Endocrinology, Hédi Chaker Hospital, Sfax, Tunisia
| | - Claude Granier
- Laboratoire International Associé N° 135, “Gènes et protéines dans les maladies multigéniques,” Sfax (Tunisia)/Montpellier (France)
- SysDiag CNRS UMR3145, Montpellier, France
| | - Hammadi Ayadi
- “Targets for Diagnosis and Therapeutic in the Human Pathology” Research Unit, Center of Biotechnology of Sfax, Sfax, Tunisia
- Laboratoire International Associé N° 135, “Gènes et protéines dans les maladies multigéniques,” Sfax (Tunisia)/Montpellier (France)
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Franco L, Crispim F, Pereira A, Moisés R. Variants of transcription factor 7-like 2 (TCF7L2) gene and incident glucose intolerance in Japanese-Brazilians. Braz J Med Biol Res 2011; 44:240-4. [DOI: 10.1590/s0100-879x2011007500010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2010] [Accepted: 01/03/2011] [Indexed: 11/22/2022] Open
Affiliation(s)
| | - F. Crispim
- Universidade Federal de São Paulo, Brasil
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Abstract
This chapter reviews statistical issues related to gene association studies. The goal is to review various aspects of study design and analysis for individuals who do not have an extensive statistical background. We will review statistical issues as they relate to both genome-wide and candidate gene studies. Topics reviewed include study design, power and sample size, data checking, statistical methods, population stratification, and multiple testing. We draw examples from the type 2 diabetes genetics literature to illustrate some of the issues discussed.
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Affiliation(s)
- Richard M Watanabe
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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48
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Vacante M, Malaguarnera M, Motta M. Revision of the ADA-classification of diabetes mellitus type 2 (DMT2): the importance of maturity onset diabetes (MOD), and senile diabetes (DS). Arch Gerontol Geriatr 2010; 53:113-9. [PMID: 20800300 DOI: 10.1016/j.archger.2010.06.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2010] [Revised: 06/22/2010] [Accepted: 06/26/2010] [Indexed: 02/06/2023]
Abstract
The changing social and economic conditions and the increase of the life span induced a progressive increase of the general prevalence of DMT2, particularly in the elderly population of the highly evoluted countries. Up to now 18 genetic loci have been identified, each of them consisting of several single nucleotide polymorphisms (SNPs). The evidence that the DMT2 is regulated by a high number of genes, demonstrate the pathogenetic complexity of this disease. The onset of diabetes mellitus (DM) in medium age is a consequence of the breakdown of the glycemic homeostasis in correlation with the genetic factors, such as the variants of the TCF7L2, obesity, etc., and the environmental factors, such as the life-style, the evolution of chronic-degenerative diseases, etc. In case of DM that onsets in old age we have to add the deterioration of the anti-aging defense mechanisms, characterized by the antagonistic action of the genes of longevity and aging. One can observe several clinical and therapeutic differences; therefore, the authors of this review propose the reinsertion of three forms into the DMT2 correlated with the age of onset and with the actual age of the subjects: the maturity onset diabetes (MOD), the maturity onset diabetes in elderly (MODE), and the senile diabetes (DS).
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Affiliation(s)
- Marco Vacante
- Department of Senescence, Urological and Neurological Sciences, University of Catania, Ospedale Cannizzaro, Viale Messina, 829, I-95125 Catania, Italy
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Racial differences in the interaction between family history and risk factors associated with diabetes in the National Health and Nutritional Examination Survey, 1999-2004. Genet Med 2009; 11:542-7. [PMID: 19606541 DOI: 10.1097/gim.0b013e3181a70917] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
PURPOSE We sought to determine whether the association between family history, a surrogate for genetic predisposition, and diabetes was modified by any known diabetes risk factors and if these relationships were constant across different ethnic groups. METHODS We examined 10,899 adults from the National Health and Nutrition Examination Survey (1999 -2004) to identify interactions between family history and clinical, demographic, and lifestyle variables for the outcome of diabetes using logistic regression analysis in racial/ethnic subgroups. RESULTS There was significant heterogeneity by race/ethnicity in the interaction between covariates and family history in relation to diabetes. In black (P = 0.0001) and Hispanic (P = 0.013), but not white (P = 0.75) subgroups, high-familial risk was a strong risk factor for diabetes among lean individuals but less so among overweight or obese subjects.Among blacks, high-familial risk conferred a 20-fold increased odds of diabetes among lean subjects and only a sixfold increased odds among obese individuals. CONCLUSIONS These findings suggest possible race/ethnic-specific differences in gene by environment interaction and identify body mass index as an important effect modifier of familial risk in diabetes in non-white populations. These findings may help guide future genetic studies and improve the utility of family history as a public health screening tool.
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Ruchat SM, Elks CE, Loos RJF, Vohl MC, Weisnagel SJ, Rankinen T, Bouchard C, Pérusse L. Association between insulin secretion, insulin sensitivity and type 2 diabetes susceptibility variants identified in genome-wide association studies. Acta Diabetol 2009; 46:217-26. [PMID: 19082521 DOI: 10.1007/s00592-008-0080-5] [Citation(s) in RCA: 69] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2008] [Accepted: 11/05/2008] [Indexed: 12/14/2022]
Abstract
Several single nucleotide polymorphisms (SNPs) for type 2 diabetes mellitus (T2DM) risk have been identified by genome wide association studies (GWAS). The objective of the present study was to investigate the impact of these SNPs on T2DM intermediate phenotypes in order to clarify the physiological mechanisms through which they exert their effects on disease etiology. We analysed 23 SNPs in 9 T2DM genes (CDKAL1, CDKN2B, HHEX/IDE, IGF2BP2, KCNJ11, SLC30A8, TCF2, TCF7L2 and WFS1) in a maximum of 712 men and women from the Quebec Family Study. The participants underwent a 75 g oral glucose tolerance test (OGTT) and were measured for glucose, insulin and C-peptide levels. Indices of insulin sensitivity and insulin secretion were derived from fasting and OGTT measurements. We confirmed the significant associations of variants in CDKAL1, CDKN2B, HHEX/IDE, KCNJ11 and TCF7L2 with insulin secretion and also found associations of some of these variants with insulin sensitivity and glucose tolerance. IGF2BP2 and SLC30A8 SNPs were not associated with insulin secretion but were with insulin sensitivity and glucose tolerance (0.002 <or= P <or= 0.02). To examine the joint effects of these variants and their contribution to T2DM endophenotypes variance, stepwise regression models were used and the model R (2) was computed. The variance in the phenotypes explained by combinations of variants ranged from 2.0 to 8.5%. Diabetes-associated variants in CDKAL1, CDKN2B, HHEX/IDE, IGF2BP2, KCNJ11, SLC30A8 and TCF7L2 are associated with physiological alterations leading to T2DM, such as glucose intolerance, impaired insulin secretion or insulin resistance, supporting their role in the disease aetiology. These variants were found to account for 2.0-8.5% of the variance of T2DM-related traits.
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