A two-step association study identifies CAV2 rs2270188 single nucleotide polymorphism interaction with fat intake in type 2 diabetes risk.

Multiple genetic and environmental factors underlie the etiology of type 2 diabetes. To evaluate the influence of the relationship between dietary fat intake and single nucleotide polymorphisms (SNPs) in genes involved in fat assimilation on disease susceptibility, a 2-step approach using an exploratory case-control study (n = 192/384) and an independent, confirmatory case-cohort study (n = 614/2248) taken from the same prospective study population (European Prospective Investigation into Cancer and Nutrition-Potsdam) was used. Sixty-three SNPs in 32 genes were initially analyzed. Total intake of fat and fatty acid intake were calculated from validated baseline FFQ. The SNP × nutrient interaction was tested in multivariate adjusted regression models. The initial screening step revealed evidence that, for 4 SNPs (CAV2 rs2270188, DBI rs2084202, PPARG rs1801282, and SREBF1 rs2297508), disease susceptibility might depend on the amount and quality of fat intake. The insulin receptor regulator CAV2 rs2270188 G > T SNP was found to interact with dietary fat in the confirmatory case-cohort study. Using pooled data, homozygous individuals of the rare T-allele showed a 100% greater risk of type 2 diabetes if daily fat intake was increased from 30 to 40 % energy. An increase in dietary SFA from 10 to 20 % energy predicted an ~200% greater risk of type 2 diabetes. We found preliminary evidence that CAV2 rs2270188 interacts with dietary fat to affect risk of type 2 diabetes.

[1]  J. Schrezenmeir,et al.  Evidence for the Thr79Met polymorphism of the ileal fatty acid binding protein (FABP6) to be associated with type 2 diabetes in obese individuals. , 2009, Molecular genetics and metabolism.

[2]  U. Risérus Fatty acids and insulin sensitivity , 2008, Current opinion in clinical nutrition and metabolic care.

[3]  J. Ordovás,et al.  Estimating Interaction Between Genetic and Environmental Risk Factors: Efficiency of Sampling Designs Within a Cohort , 2008, Epidemiology.

[4]  C. Gieger,et al.  Association of prostaglandin E synthase 2 (PTGES2) Arg298His polymorphism with type 2 diabetes in two German study populations. , 2007, The Journal of clinical endocrinology and metabolism.

[5]  P. Donnelly,et al.  Replicating genotype–phenotype associations , 2007, Nature.

[6]  C. Gieger,et al.  Association of acyl-CoA-binding protein (ACBP) single nucleotide polymorphisms and type 2 diabetes in two German study populations. , 2007, Molecular nutrition & food research.

[7]  J. Hampe,et al.  Candidate gene association study of type 2 diabetes in a nested case-control study of the EPIC-Potsdam cohort - role of fat assimilation. , 2007, Molecular nutrition & food research.

[8]  Francis S. Collins,et al.  Genes, environment and the value of prospective cohort studies , 2006, Nature Reviews Genetics.

[9]  Paolo Vineis,et al.  Design Options for Molecular Epidemiology Research within Cohort Studies , 2005, Cancer Epidemiology Biomarkers & Prevention.

[10]  M. Daly,et al.  Haploview: analysis and visualization of LD and haplotype maps , 2005, Bioinform..

[11]  M. Lisanti,et al.  Role of caveolae and caveolins in health and disease. , 2004, Physiological reviews.

[12]  M. Olivier A haplotype map of the human genome , 2003, Nature.

[13]  G. Christ,et al.  Caveolin-2-Deficient Mice Show Evidence of Severe Pulmonary Dysfunction without Disruption of Caveolae , 2002, Molecular and Cellular Biology.

[14]  David S. Park,et al.  Caveolin-1-deficient Mice Are Lean, Resistant to Diet-induced Obesity, and Show Hypertriglyceridemia with Adipocyte Abnormalities* , 2002, The Journal of Biological Chemistry.

[15]  J. Shaw,et al.  Global and societal implications of the diabetes epidemic , 2001, Nature.

[16]  W E Barlow,et al.  Analysis of case-cohort designs. , 1999, Journal of clinical epidemiology.

[17]  H Boeing,et al.  Validation of a self-administered food-frequency questionnaire administered in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study: comparison of energy, protein, and macronutrient intakes estimated with the doubly labeled water, urinary nitrogen, and repeated 24-h dietary , 1999, The American journal of clinical nutrition.

[18]  C. Peschle,et al.  Expression of Caveolin-1 Is Required for the Transport of Caveolin-2 to the Plasma Membrane , 1999, The Journal of Biological Chemistry.

[19]  H. Boeing,et al.  Follow-Up Procedures in EPIC-Germany – Data Quality Aspects , 1999, Annals of Nutrition and Metabolism.

[20]  H. Boeing,et al.  Recruitment Procedures of EPIC-Germany , 1999, Annals of Nutrition and Metabolism.

[21]  J. Engelman,et al.  Sequence and detailed organization of the human caveolin‐1 and ‐2 genes located near the D7S522 locus (7q31.1) , 1999, FEBS letters.

[22]  Y. Toya,et al.  Caveolin Is an Activator of Insulin Receptor Signaling* , 1998, The Journal of Biological Chemistry.

[23]  E. V. van Donselaar,et al.  Cell-type and Tissue-specific Expression of Caveolin-2 , 1997, The Journal of Biological Chemistry.

[24]  H. Lodish,et al.  Identification, sequence, and expression of caveolin-2 defines a caveolin gene family. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[25]  Walter C Willett,et al.  Dietary fats and prevention of type 2 diabetes. , 2009, Progress in lipid research.

[26]  S. Shadan,et al.  Lipids in health and disease , 2014, Nature.

[27]  Wj Gauderman,et al.  QUANTO 1.1: A computer program for power and sample size calculations for genetic-epidemiology studies , 2006 .

[28]  H Boeing,et al.  Reproducibility and relative validity of food group intake in a food frequency questionnaire developed for the German part of the EPIC project. European Prospective Investigation into Cancer and Nutrition. , 1997 .