No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels

Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.

Tanya M. Teslovich | Audrey Y. Chu | Toshiko Tanaka | J. Pankow | L. Ferrucci | F. Hu | E. Boerwinkle | T. Hansen | O. Pedersen | N. Grarup | T. Jørgensen | L. Groop | M. Laakso | F. Collins | Z. Kutalik | S. Bergmann | M. Boehnke | M. Walker | S. Bumpstead | U. Ekelund | C. Cooper | A. Hingorani | D. Couper | C. Fox | B. Psaty | D. Siscovick | D. Arking | E. Ingelsson | M. Marmot | L. Bonnycastle | M. Erdos | H. Stringham | P. Chines | A. Jackson | R. Watanabe | V. Lyssenko | J. Florez | B. Isomaa | J. Rotter | P. Froguel | M. Stumvoll | J. Meigs | N. Wareham | Han Chen | J. Dupuis | K. Rice | V. Lagou | S. Gustafsson | I. Prokopenko | S. Brage | P. Franks | P. Marques‐Vidal | K. North | I. Barroso | P. Vollenweider | G. Waeber | A. Manning | R. Scott | A. Stančáková | N. Forouhi | G. Hallmans | J. Kuusisto | C. Langenberg | N. Dowling | Ajay Yesupriya | N. Bouatia-Naji | C. Levy-marchal | Mario A. Morken | N. Glazer | R. Loos | D. Rybin | A. Wood | A. Jonsson | D. Shungin | M. Goodarzi | M. Kumari | S. Bornstein | M. Kivimaki | P. Schwarz | Guo Li | E. Brunner | I. Johansson | W. Kao | F. Payne | P. Shrader | P. Kovacs | A. Tönjes | A. Chu | J. Grässler | G. Müller | F. Renström | D. Witte | C. Sandholt | C. Lecoeur | D. Marek | M. Aadahl | E. Dennison | O. Carlson | J. Holloway | L. Rasmussen-Torvik | M. Hivert | D. Barnes | Weijia Xie | A. Sayer | K. Jameson | G. Williams | Josephine Egan | Y. Chen | P. Marques-Vidal | R. Watanabe | Toshiko Tanaka | B. Psaty | R. Loos | M. Morken | R. Scott | Weijia Xie | Diana Marek | Weijia Xie | R. Scott | T. Hansen | F. Hu | A. Jackson | C. Lévy‐Marchal | Nicole F. Dowling | Denis Rybin | C. Cooper

[1]  Henrik,et al.  Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index , 2012 .

[2]  Alan R. Shuldiner,et al.  Common Variants in 40 Genes Assessed for Diabetes Incidence and Response to Metformin and Lifestyle Intervention in the Diabetes Prevention Program , 2010, Diabetes.

[3]  Jing Hua Zhao,et al.  Physical Activity Attenuates the Genetic Predisposition to Obesity in 20,000 Men and Women from EPIC-Norfolk Prospective Population Study , 2010, PLoS medicine.

[4]  Ayellet V. Segrè,et al.  Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis , 2010, Nature Genetics.

[5]  V. Beral,et al.  Gene–environment interactions in 7610 women with breast cancer: prospective evidence from the Million Women Study , 2010, The Lancet.

[6]  S. Sharp,et al.  American Journal of Epidemiology Practice of Epidemiology Challenges in the Use of Literature-based Meta-analysis to Examine Gene- Environment Interactions , 2022 .

[7]  Alex Doney,et al.  Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge , 2010, Nature Genetics.

[8]  Christian Gieger,et al.  New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk , 2010, Nature Genetics.

[9]  Tanya M. Teslovich,et al.  Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index , 2010 .

[10]  C. Fox,et al.  TCF7L2 variants are associated with increased proinsulin/insulin ratios but not obesity traits in the Framingham Heart Study , 2009, Diabetologia.

[11]  M. Laakso,et al.  Interaction of single nucleotide polymorphisms in ADRB2, ADRB3, TNF, IL6, IGF1R, LIPC, LEPR, and GHRL with physical activity on the risk of type 2 diabetes mellitus and changes in characteristics of the metabolic syndrome: The Finnish Diabetes Prevention Study. , 2008, Metabolism: clinical and experimental.

[12]  D. Altshuler,et al.  The Pro12Ala variant at the peroxisome proliferator-activated receptor γ gene and change in obesity-related traits in the Diabetes Prevention Program , 2007, Diabetologia.

[13]  Peter Almgren,et al.  Mechanisms by which common variants in the TCF7L2 gene increase risk of type 2 diabetes. , 2007, The Journal of clinical investigation.

[14]  David M Nathan,et al.  Effects of the type 2 diabetes-associated PPARG P12A polymorphism on progression to diabetes and response to troglitazone. , 2007, The Journal of clinical endocrinology and metabolism.

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

[16]  J. Gulcher,et al.  Refining the impact of TCF7L2 gene variants on type 2 diabetes and adaptive evolution , 2007, Nature Genetics.

[17]  David W. Dunstan,et al.  Beneficial Associations of Physical Activity With 2-h but Not Fasting Blood Glucose in Australian Adults , 2006, Diabetes Care.

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

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

[20]  M. Laakso,et al.  The G-250A promoter polymorphism of the hepatic lipase gene predicts the conversion from impaired glucose tolerance to type 2 diabetes mellitus: the Finnish Diabetes Prevention Study. , 2004, The Journal of clinical endocrinology and metabolism.

[21]  Jaakko Tuomilehto,et al.  The Finnish Diabetes Prevention Study (DPS): Lifestyle intervention and 3-year results on diet and physical activity. , 2003, Diabetes care.

[22]  N E Day,et al.  The detection of gene-environment interaction for continuous traits: should we deal with measurement error by bigger studies or better measurement? , 2003, International journal of epidemiology.

[23]  G. Gallus,et al.  Age- and sex-specific prevalences of diabetes and impaired glucose regulation in 13 European cohorts. , 2003, Diabetes care.

[24]  J. Tuomilehto,et al.  Post-challenge hyperglycaemia is associated with premature death and macrovascular complications , 2003, Diabetologia.

[25]  S. Fowler,et al.  Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. , 2002 .

[26]  T. Valle,et al.  Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. , 2001, The New England journal of medicine.

[27]  M. Wong,et al.  Glucose intolerance and physical inactivity: the relative importance of low habitual energy expenditure and cardiorespiratory fitness. , 2000, American journal of epidemiology.

[28]  J. Manson,et al.  Physical activity and incidence of non-insulin-dependent diabetes mellitus in women , 1991, The Lancet.

[29]  N E Day,et al.  The design of case-control studies: the influence of confounding and interaction effects. , 1984, International journal of epidemiology.