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Erschienen in: Current Diabetes Reports 4/2014

01.04.2014 | Pathogenesis of Type 2 Diabetes and Insulin Resistance (RM Watanabe, Section Editor)

Nutrigenetics: Bridging Two Worlds to Understand Type 2 Diabetes

verfasst von: Janas M. Harrington, Catherine M. Phillips

Erschienen in: Current Diabetes Reports | Ausgabe 4/2014

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Abstract

The increasing global prevalence of type 2 diabetes mellitus (T2DM) is a major public health concern. Accumulating data provides strong evidence of the shared contribution of genetic and environmental factors to T2DM risk. Genome-wide association studies have hugely improved our understanding of the genetic basis of T2DM. However, it is obvious that genetics only partly account for an individuals’ predisposition to T2DM. The dietary environment has changed remarkably over the last century. Examination of individual macronutrients and more recently of foods and dietary patterns is becoming increasingly important in terms of developing public health strategies. Nutrigenetics offers the potential to improve diet-related disease prevention and therapy, but is not without its own challenges. In this review we present evidence on the dietary environment and genetics as risk factors for T2DM and bridging the 2 disciplines we highlight some key gene-nutrient interactions.
Literatur
1.
Zurück zum Zitat McRobbie MA, LJ, K. The academy’s pivotal role in supporting public-private partnerships to prevent chronic diseases. Prevent Chron Dis. 2009;6(2):A73. McRobbie MA, LJ, K. The academy’s pivotal role in supporting public-private partnerships to prevent chronic diseases. Prevent Chron Dis. 2009;6(2):A73.
2.
Zurück zum Zitat International Diabetes Federation. IDF diabetes Atlas, 5th edition. Brussels: International Diabetes Federation; 2011. International Diabetes Federation. IDF diabetes Atlas, 5th edition. Brussels: International Diabetes Federation; 2011.
3.
Zurück zum Zitat Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 2010;87:4–14.PubMedCrossRef Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 2010;87:4–14.PubMedCrossRef
4.
Zurück zum Zitat Popkin BM. Nutritional patterns and transitions. Popul Dev Rev. 1993;19:138–57.CrossRef Popkin BM. Nutritional patterns and transitions. Popul Dev Rev. 1993;19:138–57.CrossRef
6.•
Zurück zum Zitat Salas-Salvado J, Martinez-Gonzalez M, Bullo M, Ros E. The role of diet in the prevention of type 2 diabetes. Nutr Metab Cardiovasc Dis. 2011;21 Suppl 2:B32–48. This is a recent comprehensive review of the role of diet in the prevention of type 2 diabetes. PubMedCrossRef Salas-Salvado J, Martinez-Gonzalez M, Bullo M, Ros E. The role of diet in the prevention of type 2 diabetes. Nutr Metab Cardiovasc Dis. 2011;21 Suppl 2:B32–48. This is a recent comprehensive review of the role of diet in the prevention of type 2 diabetes. PubMedCrossRef
7.
Zurück zum Zitat Gluckman PD, Hanson MA, Cooper C, Thornburg KL. Effect of in utero and early-life conditions on adult health and disease. N Engl J Med. 2008;359:61–73.PubMedCentralPubMedCrossRef Gluckman PD, Hanson MA, Cooper C, Thornburg KL. Effect of in utero and early-life conditions on adult health and disease. N Engl J Med. 2008;359:61–73.PubMedCentralPubMedCrossRef
8.
Zurück zum Zitat Owen CG, Martin RM, Whincup PH, Smith GD, Cook DG. Does breastfeeding influence risk of type 2 diabetes in later life? A quantitative analysis of published evidence. Am J Clin Nutr. 2006;84:1043–54.PubMed Owen CG, Martin RM, Whincup PH, Smith GD, Cook DG. Does breastfeeding influence risk of type 2 diabetes in later life? A quantitative analysis of published evidence. Am J Clin Nutr. 2006;84:1043–54.PubMed
10.
Zurück zum Zitat Slattery ML, Randall DE. Trends in coronary heart disease mortality and food consumption in the United States between 1909 and 1980. Am J Clin Nutr. 1988;47:1060–7.PubMed Slattery ML, Randall DE. Trends in coronary heart disease mortality and food consumption in the United States between 1909 and 1980. Am J Clin Nutr. 1988;47:1060–7.PubMed
11.
Zurück zum Zitat The Multiple Risk Factor Intervention Trial Research Group. Mortality rates after 10.5 years for participants in the multiple risk factor intervention trial: findings related to a priori hypotheses of the trial. JAMA. 1990;263:1795–801.CrossRef The Multiple Risk Factor Intervention Trial Research Group. Mortality rates after 10.5 years for participants in the multiple risk factor intervention trial: findings related to a priori hypotheses of the trial. JAMA. 1990;263:1795–801.CrossRef
14.•
Zurück zum Zitat Wu JHY, Micha R, Imamura F, Pan A, Biggs ML, Ajaz O, et al. Omega-3 fatty acids and incident type 2 diabetes: a systematic review and meta-analysis. Br J Nutr. 2012;107(Suppl S2):S214–27. This is a large-scale meta-analysis examining the association between type 2 diabetes and omega-3 fatty acids among 25,670 incident cases of type 2 diabetes. PubMedCentralPubMedCrossRef Wu JHY, Micha R, Imamura F, Pan A, Biggs ML, Ajaz O, et al. Omega-3 fatty acids and incident type 2 diabetes: a systematic review and meta-analysis. Br J Nutr. 2012;107(Suppl S2):S214–27. This is a large-scale meta-analysis examining the association between type 2 diabetes and omega-3 fatty acids among 25,670 incident cases of type 2 diabetes. PubMedCentralPubMedCrossRef
15.
Zurück zum Zitat Patel PS, Forouhi NG, Kuijsten A, Schulze MB, van Woudenbergh GJ, Ardanaz E, et al. The prospective association between total and type of fish intake and type 2 diabetes in 8 European countries: EPIC-InterAct Study. Am J Clin Nutr. 2012;95:1445–53.PubMedCentralPubMedCrossRef Patel PS, Forouhi NG, Kuijsten A, Schulze MB, van Woudenbergh GJ, Ardanaz E, et al. The prospective association between total and type of fish intake and type 2 diabetes in 8 European countries: EPIC-InterAct Study. Am J Clin Nutr. 2012;95:1445–53.PubMedCentralPubMedCrossRef
16.
Zurück zum Zitat Anderson JW, Randles KM, Kendall CWC, Jenkins DJA. Carbohydrate and fiber recommendations for individuals with diabetes: a quantitative assessment and meta-analysis of the evidence. J Am Coll Nutr. 2004;23:5–17.PubMedCrossRef Anderson JW, Randles KM, Kendall CWC, Jenkins DJA. Carbohydrate and fiber recommendations for individuals with diabetes: a quantitative assessment and meta-analysis of the evidence. J Am Coll Nutr. 2004;23:5–17.PubMedCrossRef
17.
Zurück zum Zitat Buyken AE, Mitchell P, Ceriello A, Brand-Miller J. Optimal dietary approaches for prevention of type 2 diabetes: a life-course perspective. Diabetologia. 2010;53:406–18.PubMedCrossRef Buyken AE, Mitchell P, Ceriello A, Brand-Miller J. Optimal dietary approaches for prevention of type 2 diabetes: a life-course perspective. Diabetologia. 2010;53:406–18.PubMedCrossRef
18.
Zurück zum Zitat Salmeron J, Ascherio A, Rimm E, Colditz G, Spiegelman D, Jenkins D, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care. 1997;20:545–50.PubMedCrossRef Salmeron J, Ascherio A, Rimm E, Colditz G, Spiegelman D, Jenkins D, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care. 1997;20:545–50.PubMedCrossRef
19.•
Zurück zum Zitat Barclay AW, Petocz P, McMillan-Price J, Flood VM, Prvan T, Mitchell P, et al. Glycemic index, glycemic load, and chronic disease risk—a meta-analysis of observational studies. Am J Clin Nutr. 2008;87:627–37. This meta-analysis documents the association between GI, GL, and chronic disease, including of over 40,000 incident cases of chronic disease, including type 2 diabetes. PubMed Barclay AW, Petocz P, McMillan-Price J, Flood VM, Prvan T, Mitchell P, et al. Glycemic index, glycemic load, and chronic disease risk—a meta-analysis of observational studies. Am J Clin Nutr. 2008;87:627–37. This meta-analysis documents the association between GI, GL, and chronic disease, including of over 40,000 incident cases of chronic disease, including type 2 diabetes. PubMed
20.
Zurück zum Zitat Carter P, Gray LJ, Troughton J, Khunti K, Davies MJ. Fruit and vegetable intake and incidence of type 2 diabetes mellitus: systematic review and meta-analysis. BMJ. 2010;341. doi:10.1136/bmj.c4229. Carter P, Gray LJ, Troughton J, Khunti K, Davies MJ. Fruit and vegetable intake and incidence of type 2 diabetes mellitus: systematic review and meta-analysis. BMJ. 2010;341. doi:10.​1136/​bmj.​c4229.
21.
Zurück zum Zitat Villegas R, Shu XO, Gao YT, Yang G, Elasy T, Li H, et al. Vegetable but not fruit consumption reduces the risk of type 2 diabetes in Chinese women. J Nutr. 2008;138:574–80.PubMedCentralPubMed Villegas R, Shu XO, Gao YT, Yang G, Elasy T, Li H, et al. Vegetable but not fruit consumption reduces the risk of type 2 diabetes in Chinese women. J Nutr. 2008;138:574–80.PubMedCentralPubMed
22.••
Zurück zum Zitat Cooper AJ, Forouhi NG, Ye Z, Buijsse B, Arriola L, Balkau B, et al. Fruit and vegetable intake and type 2 diabetes: EPIC-InterAct prospective study and meta-analysis. Eur J Clin Nutr. 2012;66:1082–92. The EPIC-InterAct Study is a European based nested case-control study designed to examine gene-diet and gene-lifestyle interactions in T2DM. This is the largest study of its kind to date involving over 12,000 incident T2DM cases and over 16,000 non-cases selected from approximately 3 million people. This paper is a prospective analysis of the association of fruit and vegetable intake with type 2 diabetes and includes an updated meta-analysis of the associations. PubMedCentralPubMedCrossRef Cooper AJ, Forouhi NG, Ye Z, Buijsse B, Arriola L, Balkau B, et al. Fruit and vegetable intake and type 2 diabetes: EPIC-InterAct prospective study and meta-analysis. Eur J Clin Nutr. 2012;66:1082–92. The EPIC-InterAct Study is a European based nested case-control study designed to examine gene-diet and gene-lifestyle interactions in T2DM. This is the largest study of its kind to date involving over 12,000 incident T2DM cases and over 16,000 non-cases selected from approximately 3 million people. This paper is a prospective analysis of the association of fruit and vegetable intake with type 2 diabetes and includes an updated meta-analysis of the associations. PubMedCentralPubMedCrossRef
23.
24.
Zurück zum Zitat Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002;13:3–9.PubMedCrossRef Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002;13:3–9.PubMedCrossRef
25.
Zurück zum Zitat Panagiotakos DB, Pitsavos C, Stefanadis C. α-Priori and α-Posterior dietary pattern analyses have similar estimating and discriminating ability in predicting 5-year incidence of cardiovascular disease: methodological issues in nutrition assessment. J Food Sci. 2009;74:H218–24.PubMedCrossRef Panagiotakos DB, Pitsavos C, Stefanadis C. α-Priori and α-Posterior dietary pattern analyses have similar estimating and discriminating ability in predicting 5-year incidence of cardiovascular disease: methodological issues in nutrition assessment. J Food Sci. 2009;74:H218–24.PubMedCrossRef
26.
Zurück zum Zitat Romaguera D, Guevara M, Norat T, Lagenberg C, Forouhi N, Sharp S, et al. Mediterranean diet and type 2 diabetes risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study: the InterAct project. Diabetes Care. 2011;34:1913–8.PubMedCrossRef Romaguera D, Guevara M, Norat T, Lagenberg C, Forouhi N, Sharp S, et al. Mediterranean diet and type 2 diabetes risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study: the InterAct project. Diabetes Care. 2011;34:1913–8.PubMedCrossRef
27.
Zurück zum Zitat Villegas R, Salim A, Flynn A, Perry IJ. Prudent diet and the risk of insulin resistance. Nutr Metab Cardiovasc Dis. 2004;14:334–43.PubMedCrossRef Villegas R, Salim A, Flynn A, Perry IJ. Prudent diet and the risk of insulin resistance. Nutr Metab Cardiovasc Dis. 2004;14:334–43.PubMedCrossRef
28.
Zurück zum Zitat Centritto F, Iacoviello L, di Giuseppe R, De Curtis A, Costanzo S, Zito F, et al. Dietary patterns, cardiovascular risk factors and C-reactive protein in a healthy Italian population. Nutr Metabol Cardiovasc Dis. 2009;19:697–706.CrossRef Centritto F, Iacoviello L, di Giuseppe R, De Curtis A, Costanzo S, Zito F, et al. Dietary patterns, cardiovascular risk factors and C-reactive protein in a healthy Italian population. Nutr Metabol Cardiovasc Dis. 2009;19:697–706.CrossRef
29.
Zurück zum Zitat Liu E, McKeown NM, Newby PK, Meigs JB, Vasan RS, Quatromoni PA, et al. Cross-sectional association of dietary patterns with insulin-resistant phenotypes among adults without diabetes in the Framingham Offspring Study. Br J Nutr. 2009;102:576–83.PubMedCentralPubMedCrossRef Liu E, McKeown NM, Newby PK, Meigs JB, Vasan RS, Quatromoni PA, et al. Cross-sectional association of dietary patterns with insulin-resistant phenotypes among adults without diabetes in the Framingham Offspring Study. Br J Nutr. 2009;102:576–83.PubMedCentralPubMedCrossRef
30.•
Zurück zum Zitat Kastorini C, Panagiotakos D. Dietary patterns and prevention of type 2 diabetes: from research to clinical practice; a systematic review. Curr Diabetes Rev. 2009;5:221–7. This is a comprehensive review of 40 studies documenting the association between dietary patterns and type 2 diabetes. PubMedCrossRef Kastorini C, Panagiotakos D. Dietary patterns and prevention of type 2 diabetes: from research to clinical practice; a systematic review. Curr Diabetes Rev. 2009;5:221–7. This is a comprehensive review of 40 studies documenting the association between dietary patterns and type 2 diabetes. PubMedCrossRef
31.
32.
Zurück zum Zitat Tarasuk VS, Brooker A-S. Interpreting epidemiologic studies of diet-disease relationships. J Nutr. 1997;127:1847–52.PubMed Tarasuk VS, Brooker A-S. Interpreting epidemiologic studies of diet-disease relationships. J Nutr. 1997;127:1847–52.PubMed
33.
Zurück zum Zitat Florez JC, Hirschhorn J, Altshuler D. The inherited basis of diabetes mellitus: implications for the genetic analysis of complex traits. Annu Rev Genomics Hum Genet. 2003;4:257–91.PubMedCrossRef Florez JC, Hirschhorn J, Altshuler D. The inherited basis of diabetes mellitus: implications for the genetic analysis of complex traits. Annu Rev Genomics Hum Genet. 2003;4:257–91.PubMedCrossRef
35.
Zurück zum Zitat Moore AF, Florez JC. Genetic susceptibility to type 2 diabetes and implications for antidiabetic therapy. Annu Rev Med. 2008;59:95–111.PubMedCrossRef Moore AF, Florez JC. Genetic susceptibility to type 2 diabetes and implications for antidiabetic therapy. Annu Rev Med. 2008;59:95–111.PubMedCrossRef
36.
Zurück zum Zitat Kaprio J, Tuomilehto J, Koskenvuo M, Romanov K, Reunanen A, Eriksson J, et al. Concordance for type 1 (insulin-dependent) and type 2 (non-insulin-dependent) diabetes mellitus in a population-based cohort of twins in Finland. Diabetologia. 1992;35:1060–7.PubMedCrossRef Kaprio J, Tuomilehto J, Koskenvuo M, Romanov K, Reunanen A, Eriksson J, et al. Concordance for type 1 (insulin-dependent) and type 2 (non-insulin-dependent) diabetes mellitus in a population-based cohort of twins in Finland. Diabetologia. 1992;35:1060–7.PubMedCrossRef
37.
Zurück zum Zitat Medici F, Hawa M, Ianari A, Pyke DA, Leslie RD. Concordance rate for type II diabetes mellitus in monozygotic twins: actuarial analysis. Diabetologia. 1999;42:146–50.PubMedCrossRef Medici F, Hawa M, Ianari A, Pyke DA, Leslie RD. Concordance rate for type II diabetes mellitus in monozygotic twins: actuarial analysis. Diabetologia. 1999;42:146–50.PubMedCrossRef
38.
Zurück zum Zitat Newman B, Selby JV, King MC, Slemenda C, Fabsitz R, Friedman GD. Concordance for type 2 (non-insulin-dependent) diabetes mellitus in male twins. Diabetologia. 1987;30:763–8.PubMedCrossRef Newman B, Selby JV, King MC, Slemenda C, Fabsitz R, Friedman GD. Concordance for type 2 (non-insulin-dependent) diabetes mellitus in male twins. Diabetologia. 1987;30:763–8.PubMedCrossRef
40.
Zurück zum Zitat Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet. 2000;26:76–80.PubMedCrossRef Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet. 2000;26:76–80.PubMedCrossRef
41.
Zurück zum Zitat Gloyn AL, Weedon MN, Owen KR, Turner MJ, Knight BA, Hitman G, et al. Large-scale association studies of variants in genes encoding the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes. Diabetes. 2003;52:568–72.PubMedCrossRef Gloyn AL, Weedon MN, Owen KR, Turner MJ, Knight BA, Hitman G, et al. Large-scale association studies of variants in genes encoding the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes. Diabetes. 2003;52:568–72.PubMedCrossRef
42.
Zurück zum Zitat Grant SF, Thorleifsson G, Reynisdottir I, Benediktsson R, Manolescu A, Sainz J, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genet. 2006;38:320–3.PubMedCrossRef Grant SF, Thorleifsson G, Reynisdottir I, Benediktsson R, Manolescu A, Sainz J, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genet. 2006;38:320–3.PubMedCrossRef
43.
Zurück zum Zitat Horikawa Y, Oda N, Cox NJ, Li X, Orho-Melander M, Hara M, et al. Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus. Nat Genet. 2000;26:163–75.PubMedCrossRef Horikawa Y, Oda N, Cox NJ, Li X, Orho-Melander M, Hara M, et al. Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus. Nat Genet. 2000;26:163–75.PubMedCrossRef
44.
Zurück zum Zitat Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007;445:881–5.PubMedCrossRef Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007;445:881–5.PubMedCrossRef
45.
Zurück zum Zitat Florez JC, Jablonski KA, Bayley N, Pollin TI, de Bakker PI, Shuldiner AR, et al. TCF7L2 polymorphisms and progression to diabetes in the Diabetes Prevention Program. N Engl J Med. 2006;355:241–50.PubMedCentralPubMedCrossRef Florez JC, Jablonski KA, Bayley N, Pollin TI, de Bakker PI, Shuldiner AR, et al. TCF7L2 polymorphisms and progression to diabetes in the Diabetes Prevention Program. N Engl J Med. 2006;355:241–50.PubMedCentralPubMedCrossRef
46.
Zurück zum Zitat Cauchi S, El Achhab Y, Choquet H, Dina C, Krempler F, Weitgasser R, et al. TCF7L2 is reproducibly associated with type 2 diabetes in various ethnic groups: a global meta-analysis. J Mol Med. 2007;85:777–82.PubMedCrossRef Cauchi S, El Achhab Y, Choquet H, Dina C, Krempler F, Weitgasser R, et al. TCF7L2 is reproducibly associated with type 2 diabetes in various ethnic groups: a global meta-analysis. J Mol Med. 2007;85:777–82.PubMedCrossRef
47.
Zurück zum Zitat Cauchi S, Meyre D, Dina C, Choquet H, Samson C, Gallina S, et al. Transcription factor TCF7L2 genetic study in the French population: expression in human beta-cells and adipose tissue and strong association with type 2 diabetes. Diabetes. 2006;55:2903–8.PubMedCrossRef Cauchi S, Meyre D, Dina C, Choquet H, Samson C, Gallina S, et al. Transcription factor TCF7L2 genetic study in the French population: expression in human beta-cells and adipose tissue and strong association with type 2 diabetes. Diabetes. 2006;55:2903–8.PubMedCrossRef
48.
Zurück zum Zitat Chandak GR, Janipalli CS, Bhaskar S, Kulkarni SR, Mohankrishna P, Hattersley AT, et al. Common variants in the TCF7L2 gene are strongly associated with type 2 diabetes mellitus in the Indian population. Diabetologia. 2007;50:63–7.PubMedCrossRef Chandak GR, Janipalli CS, Bhaskar S, Kulkarni SR, Mohankrishna P, Hattersley AT, et al. Common variants in the TCF7L2 gene are strongly associated with type 2 diabetes mellitus in the Indian population. Diabetologia. 2007;50:63–7.PubMedCrossRef
49.
Zurück zum Zitat Hayashi T, Iwamoto Y, Kaku K, Hirose H, Maeda S. Replication study for the association of TCF7L2 with susceptibility to type 2 diabetes in a Japanese population. Diabetologia. 2007;50:980–4.PubMedCrossRef Hayashi T, Iwamoto Y, Kaku K, Hirose H, Maeda S. Replication study for the association of TCF7L2 with susceptibility to type 2 diabetes in a Japanese population. Diabetologia. 2007;50:980–4.PubMedCrossRef
50.
Zurück zum Zitat Humphries SE, Gable D, Cooper JA, Ireland H, Stephens JW, Hurel SJ, et al. Common variants in the TCF7L2 gene and predisposition to type 2 diabetes in UK European Whites, Indian Asians and Afro-Caribbean men and women. J Mol Med. 2006;84(12 Suppl):1–10. Humphries SE, Gable D, Cooper JA, Ireland H, Stephens JW, Hurel SJ, et al. Common variants in the TCF7L2 gene and predisposition to type 2 diabetes in UK European Whites, Indian Asians and Afro-Caribbean men and women. J Mol Med. 2006;84(12 Suppl):1–10.
51.
Zurück zum Zitat Wang J, Kuusisto J, Vanttinen M, Kuulasmaa T, Lindstrom J, Tuomilehto J, et al. Variants of transcription factor 7-like 2 (TCF7L2) gene predict conversion to type 2 diabetes in the Finnish Diabetes Prevention Study and are associated with impaired glucose regulation and impaired insulin secretion. Diabetologia. 2007;50:1192–200.PubMedCrossRef Wang J, Kuusisto J, Vanttinen M, Kuulasmaa T, Lindstrom J, Tuomilehto J, et al. Variants of transcription factor 7-like 2 (TCF7L2) gene predict conversion to type 2 diabetes in the Finnish Diabetes Prevention Study and are associated with impaired glucose regulation and impaired insulin secretion. Diabetologia. 2007;50:1192–200.PubMedCrossRef
52.
Zurück zum Zitat Steinthorsdottir V, Thorleifsson G, Reynisdottir I, Benediktsson R, Jonsdottir T, Walters GB, et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet. 2007;39:770–5.PubMedCrossRef Steinthorsdottir V, Thorleifsson G, Reynisdottir I, Benediktsson R, Jonsdottir T, Walters GB, et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet. 2007;39:770–5.PubMedCrossRef
53.
Zurück zum Zitat Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–6.PubMedCrossRef Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–6.PubMedCrossRef
54.
Zurück zum Zitat Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316:1341–5.PubMedCentralPubMedCrossRef Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316:1341–5.PubMedCentralPubMedCrossRef
55.
Zurück zum Zitat Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336–41.PubMedCentralPubMedCrossRef Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336–41.PubMedCentralPubMedCrossRef
56.
Zurück zum Zitat Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 2008;40:638–45.PubMedCentralPubMedCrossRef Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 2008;40:638–45.PubMedCentralPubMedCrossRef
57.•
Zurück zum Zitat Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet. 2010;42:579–89. This is a recent publication from the DIAGRAM+ consortium based on meta-analyses of of GWAS data wherein they outline asociations with over 30 replicated loci. PubMedCentralPubMedCrossRef Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet. 2010;42:579–89. This is a recent publication from the DIAGRAM+ consortium based on meta-analyses of of GWAS data wherein they outline asociations with over 30 replicated loci. PubMedCentralPubMedCrossRef
58.••
Zurück zum Zitat Morris AP, Voight BF, Teslovich TM, Ferreira T, Segre AV, Steinthorsdottir V, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44:981–90. This is a large-scale meta-analysis of genetic variants on the recently developed Metabochip involving 34,840 cases and 114,981 controls (including 12,171 cases and 56,862 controls from DIAGRAMv3), which identified 10 novel T2DM susceptibility loci. PubMedCentralPubMedCrossRef Morris AP, Voight BF, Teslovich TM, Ferreira T, Segre AV, Steinthorsdottir V, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44:981–90. This is a large-scale meta-analysis of genetic variants on the recently developed Metabochip involving 34,840 cases and 114,981 controls (including 12,171 cases and 56,862 controls from DIAGRAMv3), which identified 10 novel T2DM susceptibility loci. PubMedCentralPubMedCrossRef
59.••
Zurück zum Zitat Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42:105–16. This is a large-scale meta-analyses of 21 GWAS studies informative for fasting glucose and insulin levels, beta-cell function and insulin resistance in up to 46,186 nondiabetic participants, with further follow-up of 25 loci in over 75,000 people, which identifed 16 T2DM relevant loci. PubMedCentralPubMedCrossRef Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42:105–16. This is a large-scale meta-analyses of 21 GWAS studies informative for fasting glucose and insulin levels, beta-cell function and insulin resistance in up to 46,186 nondiabetic participants, with further follow-up of 25 loci in over 75,000 people, which identifed 16 T2DM relevant loci. PubMedCentralPubMedCrossRef
60.
Zurück zum Zitat Saxena R, Hivert MF, Langenberg C, Tanaka T, Pankow JS, Vollenweider P, et al. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat Genet. 2010;42:142–8.PubMedCentralPubMedCrossRef Saxena R, Hivert MF, Langenberg C, Tanaka T, Pankow JS, Vollenweider P, et al. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat Genet. 2010;42:142–8.PubMedCentralPubMedCrossRef
61.
Zurück zum Zitat Ingelsson E, Langenberg C, Hivert MF, Prokopenko I, Lyssenko V, Dupuis J, et al. Detailed physiologic characterization reveals diverse mechanisms for novel genetic Loci regulating glucose and insulin metabolism in humans. Diabetes. 2010;59:1266–75.PubMedCentralPubMedCrossRef Ingelsson E, Langenberg C, Hivert MF, Prokopenko I, Lyssenko V, Dupuis J, et al. Detailed physiologic characterization reveals diverse mechanisms for novel genetic Loci regulating glucose and insulin metabolism in humans. Diabetes. 2010;59:1266–75.PubMedCentralPubMedCrossRef
62.
Zurück zum Zitat Soranzo N, Sanna S, Wheeler E, Gieger C, Radke D, Dupuis J, et al. Common variants at 10 genomic loci influence hemoglobin A(1)(C) levels via glycemic and nonglycemic pathways. Diabetes. 2010;59:3229–39.PubMedCentralPubMedCrossRef Soranzo N, Sanna S, Wheeler E, Gieger C, Radke D, Dupuis J, et al. Common variants at 10 genomic loci influence hemoglobin A(1)(C) levels via glycemic and nonglycemic pathways. Diabetes. 2010;59:3229–39.PubMedCentralPubMedCrossRef
63.
Zurück zum Zitat Strawbridge RJ, Dupuis J, Prokopenko I, Barker A, Ahlqvist E, Rybin D, et al. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes. Diabetes. 2011;60:2624–34.PubMedCentralPubMedCrossRef Strawbridge RJ, Dupuis J, Prokopenko I, Barker A, Ahlqvist E, Rybin D, et al. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes. Diabetes. 2011;60:2624–34.PubMedCentralPubMedCrossRef
64.••
Zurück zum Zitat Manning AK, Hivert MF, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H, et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet. 2012;44:659–69. This paper employed a novel joint meta-analytical approach to test associations with fasting glucose and insulin on a genome-wide scale within the MAGIC consortium, which identified 6 previously unknown insulin associated loci in 52 studies involving up to 96,496 nondiabetic subjects. PubMedCentralPubMedCrossRef Manning AK, Hivert MF, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H, et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet. 2012;44:659–69. This paper employed a novel joint meta-analytical approach to test associations with fasting glucose and insulin on a genome-wide scale within the MAGIC consortium, which identified 6 previously unknown insulin associated loci in 52 studies involving up to 96,496 nondiabetic subjects. PubMedCentralPubMedCrossRef
65.•
Zurück zum Zitat Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet. 2012;44:991–1005. This meta-analysis of over 66,000 Metabochip follow-up SNPs in up to 133,010 subjects identified 53 glycemic loci, 33 of which also increase T2DM risk..PubMedCentralPubMedCrossRef Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet. 2012;44:991–1005. This meta-analysis of over 66,000 Metabochip follow-up SNPs in up to 133,010 subjects identified 53 glycemic loci, 33 of which also increase T2DM risk..PubMedCentralPubMedCrossRef
66.
Zurück zum Zitat Cornelis MC, Qi L, Zhang C, Kraft P, Manson J, Cai T, et al. Joint effects of common genetic variants on the risk for type 2 diabetes in U.S. men and women of European ancestry. Ann Intern Med. 2009;150:541–50.PubMedCentralPubMedCrossRef Cornelis MC, Qi L, Zhang C, Kraft P, Manson J, Cai T, et al. Joint effects of common genetic variants on the risk for type 2 diabetes in U.S. men and women of European ancestry. Ann Intern Med. 2009;150:541–50.PubMedCentralPubMedCrossRef
67.
Zurück zum Zitat Talmud PJ, Hingorani AD, Cooper JA, Marmot MG, Brunner EJ, Kumari M, et al. Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. BMJ. 2010;340:b4838.PubMedCentralPubMedCrossRef Talmud PJ, Hingorani AD, Cooper JA, Marmot MG, Brunner EJ, Kumari M, et al. Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. BMJ. 2010;340:b4838.PubMedCentralPubMedCrossRef
68.
Zurück zum Zitat van Hoek M, Dehghan A, Witteman JC, van Duijn CM, Uitterlinden AG, Oostra BA, et al. Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: a population-based study. Diabetes. 2008;57:3122–8.PubMedCentralPubMedCrossRef van Hoek M, Dehghan A, Witteman JC, van Duijn CM, Uitterlinden AG, Oostra BA, et al. Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: a population-based study. Diabetes. 2008;57:3122–8.PubMedCentralPubMedCrossRef
69.
Zurück zum Zitat Vassy JL, Durant NH, Kabagambe EK, Carnethon MR, Rasmussen-Torvik LJ, Fornage M, et al. A genotype risk score predicts type 2 diabetes from young adulthood: the CARDIA study. Diabetologia. 2012;55:2604–12.PubMedCentralPubMedCrossRef Vassy JL, Durant NH, Kabagambe EK, Carnethon MR, Rasmussen-Torvik LJ, Fornage M, et al. A genotype risk score predicts type 2 diabetes from young adulthood: the CARDIA study. Diabetologia. 2012;55:2604–12.PubMedCentralPubMedCrossRef
70.
Zurück zum Zitat Neel JV. Diabetes mellitus: a “thrifty” genotype rendered detrimental by “progress”? Am J Hum Genet. 1962;14:353–62.PubMedCentralPubMed Neel JV. Diabetes mellitus: a “thrifty” genotype rendered detrimental by “progress”? Am J Hum Genet. 1962;14:353–62.PubMedCentralPubMed
71.
Zurück zum Zitat Neel JV. The thrifty genotype in 1998. Nutr Rev. 1999;57(5 Pt 2):S2–9.PubMed Neel JV. The thrifty genotype in 1998. Nutr Rev. 1999;57(5 Pt 2):S2–9.PubMed
72.
Zurück zum Zitat Hales CN, Barker DJ. Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia. 1992;35:595–601.PubMedCrossRef Hales CN, Barker DJ. Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia. 1992;35:595–601.PubMedCrossRef
73.
Zurück zum Zitat Esparza-Romero J, Valencia ME, Martinez ME, Ravussin E, Schulz LO, Bennett PH. Differences in insulin resistance in Mexican and U.S. Pima Indians with normal glucose tolerance. J Clin Endocrinol Metab. 2010;95:E358–62.PubMedCentralPubMedCrossRef Esparza-Romero J, Valencia ME, Martinez ME, Ravussin E, Schulz LO, Bennett PH. Differences in insulin resistance in Mexican and U.S. Pima Indians with normal glucose tolerance. J Clin Endocrinol Metab. 2010;95:E358–62.PubMedCentralPubMedCrossRef
74.
Zurück zum Zitat Schulz LO, Bennett PH, Ravussin E, Kidd JR, Kidd KK, Esparza J, et al. Effects of traditional and western environments on prevalence of type 2 diabetes in Pima Indians in Mexico and the U.S. Diabetes Care. 2006;29:1866–71.PubMedCrossRef Schulz LO, Bennett PH, Ravussin E, Kidd JR, Kidd KK, Esparza J, et al. Effects of traditional and western environments on prevalence of type 2 diabetes in Pima Indians in Mexico and the U.S. Diabetes Care. 2006;29:1866–71.PubMedCrossRef
75.••
Zurück zum Zitat Langenberg C, Sharp S, Forouhi NG, Franks PW, Schulze MB, Kerrison N, et al. Design and cohort description of the InterAct Project: an examination of the interaction of genetic and lifestyle factors on the incidence of type 2 diabetes in the EPIC Study. Diabetologia. 2011;54:2272–82. The EPIC-InterAct Study is a European based nested case-control study designed to examine gene-diet and gene-lifestyle interactions in T2DM. This is the largest study of its kind to date involving over 12,000 incident T2DM cases and over 16,000 non-cases selected from approximately 3 million people. PubMedCrossRef Langenberg C, Sharp S, Forouhi NG, Franks PW, Schulze MB, Kerrison N, et al. Design and cohort description of the InterAct Project: an examination of the interaction of genetic and lifestyle factors on the incidence of type 2 diabetes in the EPIC Study. Diabetologia. 2011;54:2272–82. The EPIC-InterAct Study is a European based nested case-control study designed to examine gene-diet and gene-lifestyle interactions in T2DM. This is the largest study of its kind to date involving over 12,000 incident T2DM cases and over 16,000 non-cases selected from approximately 3 million people. PubMedCrossRef
76.
Zurück zum Zitat Phillips C, Lopez-Miranda J, Perez-Jimenez F, McManus R, Roche HM. Genetic and nutrient determinants of the metabolic syndrome. Curr Opin Cardiol. 2006;21:185–93.PubMedCrossRef Phillips C, Lopez-Miranda J, Perez-Jimenez F, McManus R, Roche HM. Genetic and nutrient determinants of the metabolic syndrome. Curr Opin Cardiol. 2006;21:185–93.PubMedCrossRef
77.•
Zurück zum Zitat Phillips CM. Nutrigenetics and metabolic disease: current status and implications for personalised nutrition. Nutrients. 2013;5:32–57. This comprehensive review outlines the evidence for, and implications of gene-nutrient interactions in diet-related polygenic disease with a particular focus on obesity and metabolic syndrome. PubMedCentralPubMedCrossRef Phillips CM. Nutrigenetics and metabolic disease: current status and implications for personalised nutrition. Nutrients. 2013;5:32–57. This comprehensive review outlines the evidence for, and implications of gene-nutrient interactions in diet-related polygenic disease with a particular focus on obesity and metabolic syndrome. PubMedCentralPubMedCrossRef
78.
Zurück zum Zitat Phillips CM, Tierney AC, Roche HM. Gene-nutrient interactions in the metabolic syndrome. J Nutrigenet Nutrigenomics. 2008;1:136–51.PubMedCrossRef Phillips CM, Tierney AC, Roche HM. Gene-nutrient interactions in the metabolic syndrome. J Nutrigenet Nutrigenomics. 2008;1:136–51.PubMedCrossRef
79.
Zurück zum Zitat Roche HM, Phillips C, Gibney MJ. The metabolic syndrome: the crossroads of diet and genetics. Proc Nutr Soc. 2005;64:371–7.PubMedCrossRef Roche HM, Phillips C, Gibney MJ. The metabolic syndrome: the crossroads of diet and genetics. Proc Nutr Soc. 2005;64:371–7.PubMedCrossRef
80.
Zurück zum Zitat Luan J, Browne PO, Harding AH, Halsall DJ, O'Rahilly S, Chatterjee VK, et al. Evidence for gene-nutrient interaction at the PPARgamma locus. Diabetes. 2001;50:686–9.PubMedCrossRef Luan J, Browne PO, Harding AH, Halsall DJ, O'Rahilly S, Chatterjee VK, et al. Evidence for gene-nutrient interaction at the PPARgamma locus. Diabetes. 2001;50:686–9.PubMedCrossRef
81.
Zurück zum Zitat Haupt A, Thamer C, Heni M, Ketterer C, Machann J, Schick F, et al. Gene variants of TCF7L2 influence weight loss and body composition during lifestyle intervention in a population at risk for type 2 diabetes. Diabetes. 2010;59:747–50.PubMedCentralPubMedCrossRef Haupt A, Thamer C, Heni M, Ketterer C, Machann J, Schick F, et al. Gene variants of TCF7L2 influence weight loss and body composition during lifestyle intervention in a population at risk for type 2 diabetes. Diabetes. 2010;59:747–50.PubMedCentralPubMedCrossRef
82.
Zurück zum Zitat Phillips CM, Goumidi L, Bertrais S, Field MR, McManus R, Hercberg S, et al. Dietary saturated fat, gender and genetic variation at the TCF7L2 locus predict the development of metabolic syndrome. J Nutr Biochem. 2011;23(3):239–44. Phillips CM, Goumidi L, Bertrais S, Field MR, McManus R, Hercberg S, et al. Dietary saturated fat, gender and genetic variation at the TCF7L2 locus predict the development of metabolic syndrome. J Nutr Biochem. 2011;23(3):239–44.
83.
Zurück zum Zitat Delgado-Lista J, Perez-Martinez P, Garcia-Rios A, Phillips CM, Williams CM, Gulseth HL, et al. Pleiotropic effects of TCF7L2 gene variants and its modulation in the metabolic syndrome: from the LIPGENE study. Atherosclerosis. 2011;214:110–6.PubMedCrossRef Delgado-Lista J, Perez-Martinez P, Garcia-Rios A, Phillips CM, Williams CM, Gulseth HL, et al. Pleiotropic effects of TCF7L2 gene variants and its modulation in the metabolic syndrome: from the LIPGENE study. Atherosclerosis. 2011;214:110–6.PubMedCrossRef
84.
Zurück zum Zitat Lee HJ, Kim IK, Kang JH, Ahn Y, Han BG, Lee JY, et al. Effects of common FTO gene variants associated with BMI on dietary intake and physical activity in Koreans. Clin Chim Acta. 2010;411:1716–22.PubMedCrossRef Lee HJ, Kim IK, Kang JH, Ahn Y, Han BG, Lee JY, et al. Effects of common FTO gene variants associated with BMI on dietary intake and physical activity in Koreans. Clin Chim Acta. 2010;411:1716–22.PubMedCrossRef
85.
Zurück zum Zitat Sonestedt E, Roos C, Gullberg B, Ericson U, Wirfalt E, Orho-Melander M. Fat and carbohydrate intake modify the association between genetic variation in the FTO genotype and obesity. Am J Clin Nutr. 2009;90:1418–25.PubMedCrossRef Sonestedt E, Roos C, Gullberg B, Ericson U, Wirfalt E, Orho-Melander M. Fat and carbohydrate intake modify the association between genetic variation in the FTO genotype and obesity. Am J Clin Nutr. 2009;90:1418–25.PubMedCrossRef
86.
Zurück zum Zitat Lappalainen T, Lindstrom J, Paananen J, Eriksson JG, Karhunen L, Tuomilehto J, et al. Association of the fat mass and obesity-associated (FTO) gene variant (rs9939609) with dietary intake in the Finnish Diabetes Prevention Study. Br J Nutr. 2012;108:1859–65.PubMedCrossRef Lappalainen T, Lindstrom J, Paananen J, Eriksson JG, Karhunen L, Tuomilehto J, et al. Association of the fat mass and obesity-associated (FTO) gene variant (rs9939609) with dietary intake in the Finnish Diabetes Prevention Study. Br J Nutr. 2012;108:1859–65.PubMedCrossRef
87.
Zurück zum Zitat Phillips CM, Kesse-Guyot E, McManus R, Hercberg S, Lairon D, Planells R, et al. High dietary saturated fat intake accentuates obesity risk associated with the fat mass and obesity-associated gene in adults. J Nutr. 2012;142:824–31.PubMedCrossRef Phillips CM, Kesse-Guyot E, McManus R, Hercberg S, Lairon D, Planells R, et al. High dietary saturated fat intake accentuates obesity risk associated with the fat mass and obesity-associated gene in adults. J Nutr. 2012;142:824–31.PubMedCrossRef
88.
89.
Zurück zum Zitat Fisher E, Boeing H, Fritsche A, Doering F, Joost HG, Schulze MB. Whole-grain consumption and transcription factor-7-like 2 (TCF7L2) rs7903146: gene-diet interaction in modulating type 2 diabetes risk. Br J Nutr. 2009;101:478–81.PubMedCrossRef Fisher E, Boeing H, Fritsche A, Doering F, Joost HG, Schulze MB. Whole-grain consumption and transcription factor-7-like 2 (TCF7L2) rs7903146: gene-diet interaction in modulating type 2 diabetes risk. Br J Nutr. 2009;101:478–81.PubMedCrossRef
90.•
Zurück zum Zitat Nettleton JA, McKeown NM, Kanoni S, Lemaitre RN, Hivert MF, Ngwa J, et al. Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies. Diabetes Care. 2010;33:2684–91. This is a large-scale meta-analysis of gene-nutrient interactions focused on wholegrains and fasting insulin and glucose concentrations, which identified novel GCKR-wholegrain interactions. PubMedCentralPubMedCrossRef Nettleton JA, McKeown NM, Kanoni S, Lemaitre RN, Hivert MF, Ngwa J, et al. Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies. Diabetes Care. 2010;33:2684–91. This is a large-scale meta-analysis of gene-nutrient interactions focused on wholegrains and fasting insulin and glucose concentrations, which identified novel GCKR-wholegrain interactions. PubMedCentralPubMedCrossRef
91.•
Zurück zum Zitat Kanoni S, Nettleton JA, Hivert MF, Ye Z, van Rooij FJ, Shungin D, et al. Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis. Diabetes. 2011;60:2407–16. This is a large-scale meta-analysis of gene-micronutrient interactions focused on zinc and fasting insulin and glucose concentrations, which identified novel SLC30A8-zinc interactions..PubMedCentralPubMedCrossRef Kanoni S, Nettleton JA, Hivert MF, Ye Z, van Rooij FJ, Shungin D, et al. Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis. Diabetes. 2011;60:2407–16. This is a large-scale meta-analysis of gene-micronutrient interactions focused on zinc and fasting insulin and glucose concentrations, which identified novel SLC30A8-zinc interactions..PubMedCentralPubMedCrossRef
92.
Zurück zum Zitat Hruby A, Ngwa JS, Renstrom F, Wojczynski MK, Ganna A, Hallmans G, et al. Higher magnesium intake is associated with lower fasting glucose and insulin, with no evidence of interaction with select genetic loci, in a meta-analysis of 15 CHARGE Consortium Studies. J Nutr. 2013;143:345–53.PubMedCentralPubMedCrossRef Hruby A, Ngwa JS, Renstrom F, Wojczynski MK, Ganna A, Hallmans G, et al. Higher magnesium intake is associated with lower fasting glucose and insulin, with no evidence of interaction with select genetic loci, in a meta-analysis of 15 CHARGE Consortium Studies. J Nutr. 2013;143:345–53.PubMedCentralPubMedCrossRef
93.
Zurück zum Zitat Pasquale LR, Loomis SJ, Aschard H, Kang JH, Cornelis MC, Qi L, et al. Exploring genome-wide - dietary heme iron intake interactions and the risk of type 2 diabetes. Front Genet. 2013;4:7.PubMedCentralPubMedCrossRef Pasquale LR, Loomis SJ, Aschard H, Kang JH, Cornelis MC, Qi L, et al. Exploring genome-wide - dietary heme iron intake interactions and the risk of type 2 diabetes. Front Genet. 2013;4:7.PubMedCentralPubMedCrossRef
94.
Zurück zum Zitat Nettleton JA, Hivert MF, Lemaitre RN, McKeown NM, Mozaffarian D, Tanaka T, et al. Meta-analysis investigating associations between healthy diet and fasting glucose and insulin levels and modification by loci associated with glucose homeostasis in data from 15 cohorts. Am J Epidemiol. 2013;177:103–15.PubMedCentralPubMedCrossRef Nettleton JA, Hivert MF, Lemaitre RN, McKeown NM, Mozaffarian D, Tanaka T, et al. Meta-analysis investigating associations between healthy diet and fasting glucose and insulin levels and modification by loci associated with glucose homeostasis in data from 15 cohorts. Am J Epidemiol. 2013;177:103–15.PubMedCentralPubMedCrossRef
95.
Zurück zum Zitat Ortega-Azorin C, Sorli JV, Asensio EM, Coltell O, Martinez-Gonzalez MA, Salas-Salvado J, et al. Associations of the FTO rs9939609 and the MC4R rs17782313 polymorphisms with type 2 diabetes are modulated by diet, being higher when adherence to the Mediterranean diet pattern is low. Cardiovasc Diabetol. 2012;11:137.PubMedCentralPubMedCrossRef Ortega-Azorin C, Sorli JV, Asensio EM, Coltell O, Martinez-Gonzalez MA, Salas-Salvado J, et al. Associations of the FTO rs9939609 and the MC4R rs17782313 polymorphisms with type 2 diabetes are modulated by diet, being higher when adherence to the Mediterranean diet pattern is low. Cardiovasc Diabetol. 2012;11:137.PubMedCentralPubMedCrossRef
96.
Zurück zum Zitat Qi L, Cornelis MC, Zhang C, van Dam RM, Hu FB. Genetic predisposition, Western dietary pattern, and the risk of type 2 diabetes in men. Am J Clin Nutr. 2009;89:1453–8.PubMedCentralPubMedCrossRef Qi L, Cornelis MC, Zhang C, van Dam RM, Hu FB. Genetic predisposition, Western dietary pattern, and the risk of type 2 diabetes in men. Am J Clin Nutr. 2009;89:1453–8.PubMedCentralPubMedCrossRef
97.
Zurück zum Zitat Rung J, Cauchi S, Albrechtsen A, Shen L, Rocheleau G, Cavalcanti-Proenca C, et al. Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia. Nat Genet. 2009;41:1110–5.PubMedCrossRef Rung J, Cauchi S, Albrechtsen A, Shen L, Rocheleau G, Cavalcanti-Proenca C, et al. Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia. Nat Genet. 2009;41:1110–5.PubMedCrossRef
98.
Zurück zum Zitat Bouatia-Naji N, Bonnefond A, Cavalcanti-Proenca C, Sparso T, Holmkvist J, Marchand M, et al. A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat Genet. 2009;41:89–94.PubMedCrossRef Bouatia-Naji N, Bonnefond A, Cavalcanti-Proenca C, Sparso T, Holmkvist J, Marchand M, et al. A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat Genet. 2009;41:89–94.PubMedCrossRef
99.
Zurück zum Zitat Lyssenko V, Nagorny CL, Erdos MR, Wierup N, Jonsson A, Spegel P, et al. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat Genet. 2009;41:82–8.PubMedCentralPubMedCrossRef Lyssenko V, Nagorny CL, Erdos MR, Wierup N, Jonsson A, Spegel P, et al. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat Genet. 2009;41:82–8.PubMedCentralPubMedCrossRef
100.
Zurück zum Zitat Prokopenko I, Langenberg C, Florez JC, Saxena R, Soranzo N, Thorleifsson G, et al. Variants in MTNR1B influence fasting glucose levels. Nat Genet. 2009;41:77–81.PubMedCentralPubMedCrossRef Prokopenko I, Langenberg C, Florez JC, Saxena R, Soranzo N, Thorleifsson G, et al. Variants in MTNR1B influence fasting glucose levels. Nat Genet. 2009;41:77–81.PubMedCentralPubMedCrossRef
101.
Zurück zum Zitat WTCCC. Genome-wide association study of 14,000 cases of seven common diseases and 3000 shared controls. Nature. 2007;447:661–78. WTCCC. Genome-wide association study of 14,000 cases of seven common diseases and 3000 shared controls. Nature. 2007;447:661–78.
Metadaten
Titel
Nutrigenetics: Bridging Two Worlds to Understand Type 2 Diabetes
verfasst von
Janas M. Harrington
Catherine M. Phillips
Publikationsdatum
01.04.2014
Verlag
Springer US
Erschienen in
Current Diabetes Reports / Ausgabe 4/2014
Print ISSN: 1534-4827
Elektronische ISSN: 1539-0829
DOI
https://doi.org/10.1007/s11892-014-0477-1

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