Evidence of Interaction between Type 2 Diabetes Susceptibility Genes and Dietary Fat Intake for Adiposity and Glucose Homeostasis-Related Phenotypes

Background/Aims: Genome-wide association studies have led to the identification of several susceptibility genes for type 2 diabetes mellitus (T2DM). The objective of this study was to test the hypothesis that the associations between single nucleotide polymorphisms (SNPs) in these genes and adiposity and glucose homeostasis-related phenotypes are influenced by dietary fat intake. Methods: Thirty-three SNPs in 9 T2DM genes (CDKAL1, CDKN2A/B, HHEX, HNF1B, IGF2BP2, KCNJ11, SLC30A8, TCF7L2 and WFS1) were tested in a maximum of 669 subjects from the Quebec Family Study. Subjects were measured for several adiposity indices and underwent a 75-gram oral glucose tolerance test. Total fat intake was estimated from a 3-day dietary record. Results: We observed 13 significant (p ≤ 0.01) SNP-dietary fat interactions. Among them, IGF2BP2 rs4402960, alone or in interaction with dietary fat intake, influenced abdominal total fat (ATF: SNP effect, p = 0.006, interaction effect, p = 0.009) and abdominal visceral fat (AVF: SNP effect, p = 0.007, interaction effect, p = 0.01). Similarly, TCF7L2 rs12573128 alone or in interaction with dietary fat intake, influenced insulin sensitivity (SNP effect and interaction effect, p ≤ 0.008) and glucose tolerance (SNP effect p ≤ 0.009 and interaction effect, p ≤ 0.01). Conclusion: These results suggest that gene-dietary fat interactions may influence glucose homeostasis-related phenotypes and play an important role in determining the increased risk of diabetes associated with the T2DM susceptibility genes.

[1]  C. Bouchard,et al.  Association between insulin secretion, insulin sensitivity and type 2 diabetes susceptibility variants identified in genome-wide association studies , 2009, Acta Diabetologica.

[2]  L. Groop,et al.  Previously Associated Type 2 Diabetes Variants May Interact With Physical Activity to Modify the Risk of Impaired Glucose Regulation and Type 2 Diabetes , 2009, Diabetes.

[3]  C. Hoggart,et al.  Genome-wide association analysis of metabolic traits in a birth cohort from a founder population , 2008, Nature Genetics.

[4]  M. Patti,et al.  The emerging genetic architecture of type 2 diabetes. , 2008, Cell metabolism.

[5]  D. Altshuler,et al.  Extension of Type 2 Diabetes Genome-Wide Association Scan Results in the Diabetes Prevention Program , 2008, Diabetes.

[6]  T. Frayling,et al.  New gene variants alter type 2 diabetes risk predominantly through reduced beta-cell function , 2008, Current opinion in clinical nutrition and metabolic care.

[7]  M. McCarthy,et al.  Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes , 2008, Nature Genetics.

[8]  D. Gudbjartsson,et al.  Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes , 2007, Nature Genetics.

[9]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[10]  Marcia M. Nizzari,et al.  Genome-Wide Association Analysis Identifies Loci for Type 2 Diabetes and Triglyceride Levels , 2007, Science.

[11]  J. Gulcher,et al.  A variant in CDKAL1 influences insulin response and risk of type 2 diabetes , 2007, Nature Genetics.

[12]  M. McCarthy,et al.  Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes , 2007, Science.

[13]  Tom R. Gaunt,et al.  Molecular genetics of human growth hormone, insulin-like growth factors and their pathways in common disease , 2007, Human Genetics.

[14]  T. Hudson,et al.  A genome-wide association study identifies novel risk loci for type 2 diabetes , 2007, Nature.

[15]  N. Wareham,et al.  Gene-lifestyle interaction on risk of type 2 diabetes. , 2007, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[16]  K. Dawson,et al.  Application of nutrigenomic concepts to Type 2 diabetes mellitus. , 2007, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[17]  David M Nathan,et al.  TCF7L2 polymorphisms and progression to diabetes in the Diabetes Prevention Program. , 2006, The New England journal of medicine.

[18]  A. Heald,et al.  The insulin‐like growth factor system and diabetes—an overview , 2006, Diabetic medicine : a journal of the British Diabetic Association.

[19]  S. Kersten,et al.  Nutrigenomics: goals and strategies , 2003, Nature Reviews Genetics.

[20]  E. Lander,et al.  Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease , 2003, Nature Genetics.

[21]  P. Trumbo,et al.  Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids. , 2002, Journal of the American Dietetic Association.

[22]  R. Bergman,et al.  Accurate Assessment of β-Cell Function: The Hyperbolic Correction , 2002 .

[23]  M. Stumvoll,et al.  Use of the oral glucose tolerance test to assess insulin release and insulin sensitivity. , 2000, Diabetes care.

[24]  C. Bogardus,et al.  Evaluation of simple indices of insulin sensitivity and insulin secretion for use in epidemiologic studies. , 2000, American journal of epidemiology.

[25]  K. Livak,et al.  Allelic discrimination using fluorogenic probes and the 5' nuclease assay. , 1999, Genetic analysis : biomolecular engineering.

[26]  J R O'Connell,et al.  PedCheck: a program for identification of genotype incompatibilities in linkage analysis. , 1998, American journal of human genetics.

[27]  C. Bouchard,et al.  Familial correlations in the Québec family study: cross-trait familial resemblance for body fat with plasma glucose and insulin , 1996, Diabetologia.

[28]  N. Risch,et al.  A comparison of linkage disequilibrium measures for fine-scale mapping. , 1995, Genomics.

[29]  P. Wahl,et al.  Association of fasting glucose levels with a delayed secretion of insulin after oral glucose in subjects with glucose intolerance. , 1990, The Journal of clinical endocrinology and metabolism.

[30]  J. Cederholm,et al.  Insulin release and peripheral sensitivity at the oral glucose tolerance test. , 1990, Diabetes research and clinical practice.

[31]  C. Bouchard,et al.  Assessment of adipose tissue distribution by computed axial tomography in obese women: association with body density and anthropometric measurements , 1989, British Journal of Nutrition.

[32]  R. Turner,et al.  Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man , 1985, Diabetologia.

[33]  C. Bouchard,et al.  The reproducibility of a three-day dietary record , 1983 .

[34]  R. Ward.  WHO – Definition, Diagnosis and Classification of Diabetes , 2011 .

[35]  Inês Barroso,et al.  Variants in MTNR1B influence fasting glucose levels , 2009, Nature Genetics.

[36]  P. Elliott,et al.  A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk , 2009, Nature Genetics.

[37]  D. Panagiotakos,et al.  Genes, diet and type 2 diabetes mellitus: a review. , 2007, The review of diabetic studies : RDS.

[38]  R. Bergman,et al.  Accurate assessment of beta-cell function: the hyperbolic correction. , 2002, Diabetes.

[39]  C. Bouchard.  Genetic epidemiology, association, and sib-pair linkage: results from the Quebec Family Study , 1996 .

[40]  T. Lohman,et al.  Anthropometric Standardization Reference Manual , 1988 .

[41]  W. Siri,et al.  The gross composition of the body. , 1956, Advances in biological and medical physics.

[42]  G. Abecasis,et al.  Supporting Online Material Materials and Methods Figs. S1 to S8 Tables S1 to S10 References a Genome-wide Association Study of Type 2 Diabetes in Finns Detects Multiple Susceptibility Variants , 2022 .

[43]  Ingrid B. Borecki,et al.  Pacific Symposium on Biocomputing 13:190-200(2008) GATHERING THE GOLD DUST: METHODS FOR ASSESSING THE AGGREGATE IMPACT OF SMALL EFFECT GENES IN GENOMIC SCANS ∗ , 2022 .