Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases

John R B Perry, Benjamin F Voight, Loïc Yengo, Najaf Amin, Josée Dupuis, Martha Ganser, Harald Grallert, Pau Navarro, Man Li, Lu Qi, Valgerdur Steinthorsdottir, Robert A Scott, Peter Almgren, Dan E Arking, Yurii Aulchenko, Beverley Balkau, Rafn Benediktsson, Richard N Bergman, Eric Boerwinkle, Lori Bonnycastle, Noël P Burtt, Harry Campbell, Guillaume Charpentier, Francis S Collins, Christian Gieger, Todd Green, Samy Hadjadj, Andrew T Hattersley, Christian Herder, Albert Hofman, Andrew D Johnson, Anna Kottgen, Peter Kraft, Yann Labrune, Claudia Langenberg, Alisa K Manning, Karen L Mohlke, Andrew P Morris, Ben Oostra, James Pankow, Ann-Kristin Petersen, Peter P Pramstaller, Inga Prokopenko, Wolfgang Rathmann, William Rayner, Michael Roden, Igor Rudan, Denis Rybin, Laura J Scott, Gunnar Sigurdsson, Rob Sladek, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Jaakko Tuomilehto, Andre G Uitterlinden, Sidonie Vivequin, Michael N Weedon, Alan F Wright, MAGIC, DIAGRAM Consortium, GIANT Consortium, Frank B Hu, Thomas Illig, Linda Kao, James B Meigs, James F Wilson, Kari Stefansson, Cornelia van Duijn, David Altschuler, Andrew D Morris, Michael Boehnke, Mark I McCarthy, Philippe Froguel, Colin N A Palmer, Nicholas J Wareham, Leif Groop, Timothy M Frayling, Stéphane Cauchi, John R B Perry, Benjamin F Voight, Loïc Yengo, Najaf Amin, Josée Dupuis, Martha Ganser, Harald Grallert, Pau Navarro, Man Li, Lu Qi, Valgerdur Steinthorsdottir, Robert A Scott, Peter Almgren, Dan E Arking, Yurii Aulchenko, Beverley Balkau, Rafn Benediktsson, Richard N Bergman, Eric Boerwinkle, Lori Bonnycastle, Noël P Burtt, Harry Campbell, Guillaume Charpentier, Francis S Collins, Christian Gieger, Todd Green, Samy Hadjadj, Andrew T Hattersley, Christian Herder, Albert Hofman, Andrew D Johnson, Anna Kottgen, Peter Kraft, Yann Labrune, Claudia Langenberg, Alisa K Manning, Karen L Mohlke, Andrew P Morris, Ben Oostra, James Pankow, Ann-Kristin Petersen, Peter P Pramstaller, Inga Prokopenko, Wolfgang Rathmann, William Rayner, Michael Roden, Igor Rudan, Denis Rybin, Laura J Scott, Gunnar Sigurdsson, Rob Sladek, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Jaakko Tuomilehto, Andre G Uitterlinden, Sidonie Vivequin, Michael N Weedon, Alan F Wright, MAGIC, DIAGRAM Consortium, GIANT Consortium, Frank B Hu, Thomas Illig, Linda Kao, James B Meigs, James F Wilson, Kari Stefansson, Cornelia van Duijn, David Altschuler, Andrew D Morris, Michael Boehnke, Mark I McCarthy, Philippe Froguel, Colin N A Palmer, Nicholas J Wareham, Leif Groop, Timothy M Frayling, Stéphane Cauchi

Abstract

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m²) compared to obese cases (BMI≥30 Kg/m²). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m²) or 4,123 obese cases (BMI≥30 kg/m²), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10⁻⁹, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A--previously identified in South Asians but not Europeans--was associated with type 2 diabetes in obese cases (P = 1.3×10⁻⁸, OR = 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2×10⁻¹⁴. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2×10⁻¹⁶. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1. Test statistics for LAMA1 association…
Figure 1. Test statistics for LAMA1 association in lean and obese cases versus all controls.
Figure 2. Regional association plot for the…
Figure 2. Regional association plot for the LAMA1 gene in lean type 2 diabetes samples.
Figure 3. Test statistics for HMG20A association…
Figure 3. Test statistics for HMG20A association in lean and obese cases versus all controls.
Figure 4. Regional association plot for the…
Figure 4. Regional association plot for the HMG20A gene in obese type 2 diabetes samples.
Figure 5. Risk allele distribution for known…
Figure 5. Risk allele distribution for known type 2 diabetes SNPs in GoDARTs.
Plot shows number of type 2 diabetes risk alleles carried by the 263 lean type 2 diabetes cases, 1,735 obese type 2 diabetes cases and 3,691 controls from the GoDARTs study.
Figure 6. Relative risk for type 2…
Figure 6. Relative risk for type 2 diabetes depending on risk allele quintile, split by lean and obese BMI.
Individuals binned into quintiles based on risk-allele count of known SNPs, weighted by effect size of SNP. Risk estimates relative to median quintile. Total sample size across all quintiles is 263 lean type 2 diabetes cases, 1735 obese type 2 diabetes cases and 3691 controls from the GoDARTs study.

References

    1. Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet. 2010;42:579–589.
    1. Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42:105–116.
    1. Qi L, Cornelis MC, Kraft P, Stanya KJ, Linda Kao WH, et al. Genetic variants at 2q24 are associated with susceptibility to type 2 diabetes. Hum Mol Genet. 2010;19:2706–2715.
    1. Tsai FJ, Yang CF, Chen CC, Chuang LM, Lu CH, et al. A genome-wide association study identifies susceptibility variants for type 2 diabetes in Han Chinese. PLoS Genet. 2010;6:e1000847. doi: .
    1. Yamauchi T, Hara K, Maeda S, Yasuda K, Takahashi A, et al. A genome-wide association study in the Japanese population identifies susceptibility loci for type 2 diabetes at UBE2E2 and C2CD4A-C2CD4B. Nat Genet. 2010;42:864–868.
    1. Shu XO, Long J, Cai Q, Qi L, Xiang YB, et al. Identification of new genetic risk variants for type 2 diabetes. PLoS Genet. 2010;6:e1001127. doi: .
    1. Kooner JS, Saleheen D, Sim X, Sehmi J, Zhang W, et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet 2011
    1. Lyssenko V, Nagorny CL, Erdos MR, Wierup N, Jonsson A, et al. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat Genet. 2009;41:82–88.
    1. Prokopenko I, Langenberg C, Florez JC, Saxena R, Soranzo N, et al. Variants in MTNR1B influence fasting glucose levels. Nat Genet. 2009;41:77–81.
    1. Freathy RM, Mook-Kanamori DO, Sovio U, Prokopenko I, Timpson NJ, et al. Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight. Nat Genet. 2010;42:430–435.
    1. Perry JR, Weedon MN, Langenberg C, Jackson AU, Lyssenko V, et al. Genetic evidence that raised sex hormone binding globulin (SHBG) levels reduce the risk of type 2 diabetes. Hum Mol Genet. 2010;19:535–544.
    1. Tuomi T, Carlsson A, Li H, Isomaa B, Miettinen A, et al. Clinical and genetic characteristics of type 2 diabetes with and without GAD antibodies. Diabetes. 1999;48:150–157.
    1. Pearson ER, Flechtner I, Njolstad PR, Malecki MT, Flanagan SE, et al. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med. 2006;355:467–477.
    1. Timpson NJ, Lindgren CM, Weedon MN, Randall J, Ouwehand WH, et al. Adiposity-related heterogeneity in patterns of type 2 diabetes susceptibility observed in genome-wide association data. Diabetes. 2009;58:505–510.
    1. Cauchi S, Nead KT, Choquet H, Horber F, Potoczna N, et al. The genetic susceptibility to type 2 diabetes may be modulated by obesity status: implications for association studies. BMC Med Genet. 2008;9:45.
    1. Cauchi S, Choquet H, Gutierrez-Aguilar R, Capel F, Grau K, et al. Effects of TCF7L2 polymorphisms on obesity in European populations. Obesity (Silver Spring) 2008;16:476–482.
    1. Guey LT, Kravic J, Melander O, Burtt NP, Laramie JM, et al. Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants. Genet Epidemiol 2011
    1. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet. 2010;42:937–948.
    1. Zhou K, Bellenguez C, Spencer CC, Bennett AJ, Coleman RL, et al. Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes. Nat Genet. 2011;43:117–120.
    1. Soranzo N, Sanna S, Wheeler E, Gieger C, Radke D, et al. Common variants at 10 genomic loci influence hemoglobin A(C) levels via glycemic and nonglycemic pathways. Diabetes. 2010;59:3229–3239.
    1. Saxena R, Hivert MF, Langenberg C, Tanaka T, Pankow JS, et al. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat Genet. 2010;42:142–148.
    1. Goring HH, Curran JE, Johnson MP, Dyer TD, Charlesworth J, et al. Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nat Genet. 2007;39:1208–1216.
    1. Idaghdour Y, Czika W, Shianna KV, Lee SH, Visscher PM, et al. Geographical genomics of human leukocyte gene expression variation in southern Morocco. Nat Genet. 2010;42:62–67.
    1. Heap GA, Trynka G, Jansen RC, Bruinenberg M, Swertz MA, et al. Complex nature of SNP genotype effects on gene expression in primary human leucocytes. BMC Med Genomics. 2009;2:1.
    1. Dixon AL, Liang L, Moffatt MF, Chen W, Heath S, et al. A genome-wide association study of global gene expression. Nat Genet. 2007;39:1202–1207.
    1. Stranger BE, Nica AC, Forrest MS, Dimas A, Bird CP, et al. Population genomics of human gene expression. Nat Genet. 2007;39:1217–1224.
    1. Kwan T, Benovoy D, Dias C, Gurd S, Provencher C, et al. Genome-wide analysis of transcript isoform variation in humans. Nat Genet. 2008;40:225–231.
    1. Heinzen EL, Ge D, Cronin KD, Maia JM, Shianna KV, et al. Tissue-specific genetic control of splicing: implications for the study of complex traits. PLoS Biol. 2008;6:e1. doi: .
    1. Zeller T, Wild P, Szymczak S, Rotival M, Schillert A, et al. Genetics and beyond–the transcriptome of human monocytes and disease susceptibility. PLoS ONE. 2010;5:e10693. doi: .
    1. Emilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, et al. Genetics of gene expression and its effect on disease. Nature. 2008;452:423–428.
    1. Greenawalt DM, Dobrin R, Chudin E, Hatoum IJ, Suver C, et al. A survey of the genetics of stomach, liver, and adipose gene expression from a morbidly obese cohort. Genome Res. 2011;21:1008–1016.
    1. Kompass KS, Witte JS. Co-regulatory expression quantitative trait loci mapping: method and application to endometrial cancer. BMC Med Genomics. 2011;4:6.
    1. Webster JA, Gibbs JR, Clarke J, Ray M, Zhang W, et al. Genetic control of human brain transcript expression in Alzheimer disease. Am J Hum Genet. 2009;84:445–458.
    1. Schadt EE, Molony C, Chudin E, Hao K, Yang X, et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol. 2008;6:e107. doi: .
    1. Innocenti F, Cooper GM, Stanaway IB, Gamazon ER, Smith JD, et al. Identification, replication, and functional fine-mapping of expression quantitative trait loci in primary human liver tissue. PLoS Genet. 2011;7:e1002078. doi: .
    1. Grundberg E, Kwan T, Ge B, Lam KC, Koka V, et al. Population genomics in a disease targeted primary cell model. Genome Res. 2009;19:1942–1952.
    1. Ding J, Gudjonsson JE, Liang L, Stuart PE, Li Y, et al. Gene expression in skin and lymphoblastoid cells: Refined statistical method reveals extensive overlap in cis-eQTL signals. Am J Hum Genet. 2010;87:779–789.
    1. Dimas AS, Deutsch S, Stranger BE, Montgomery SB, Borel C, et al. Common regulatory variation impacts gene expression in a cell type-dependent manner. Science. 2009;325:1246–1250.
    1. Han B, Eskin E. Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies. Am J Hum Genet. 2011;88:586–598.
    1. Antinozzi PA, Garcia-Diaz A, Hu C, Rothman JE. Functional mapping of disease susceptibility loci using cell biology. Proc Natl Acad Sci U S A. 2006;103:3698–3703.
    1. Jiang FX, Harrison LC. Convergence of bone morphogenetic protein and laminin-1 signaling pathways promotes proliferation and colony formation by fetal mouse pancreatic cells. Exp Cell Res. 2005;308:114–122.
    1. Vasir B, Aiello LP, Yoon KH, Quickel RR, Bonner-Weir S, et al. Hypoxia induces vascular endothelial growth factor gene and protein expression in cultured rat islet cells. Diabetes. 1998;47:1894–1903.
    1. Bonner-Weir S, Taneja M, Weir GC, Tatarkiewicz K, Song KH, et al. In vitro cultivation of human islets from expanded ductal tissue. Proc Natl Acad Sci U S A. 2000;97:7999–8004.
    1. Gao R, Ustinov J, Pulkkinen MA, Lundin K, Korsgren O, et al. Characterization of endocrine progenitor cells and critical factors for their differentiation in human adult pancreatic cell culture. Diabetes. 2003;52:2007–2015.
    1. Jiang FX, Georges-Labouesse E, Harrison LC. Regulation of laminin 1-induced pancreatic beta-cell differentiation by alpha6 integrin and alpha-dystroglycan. Mol Med. 2001;7:107–114.
    1. Jiang FX, Cram DS, DeAizpurua HJ, Harrison LC. Laminin-1 promotes differentiation of fetal mouse pancreatic beta-cells. Diabetes. 1999;48:722–730.
    1. Geutskens SB, Homo-Delarche F, Pleau JM, Durant S, Drexhage HA, et al. Extracellular matrix distribution and islet morphology in the early postnatal pancreas: anomalies in the non-obese diabetic mouse. Cell Tissue Res. 2004;318:579–589.
    1. Hu C, Oliver JA, Goldberg MR, Al-Awqati Q. LRP: a new adhesion molecule for endothelial and smooth muscle cells. Am J Physiol Renal Physiol. 2001;281:F739–750.
    1. Williams RC, Muller YL, Hanson RL, Knowler WC, Mason CC, et al. HLA-DRB1 reduces the risk of type 2 diabetes mellitus by increased insulin secretion. Diabetologia. 2011;54:1684–1692.

Source: PubMed

Sponsorzy i współpracownicy

Warunki medyczne

Interwencje lekowe

3
Subskrybuj