Influence of dietary protein intake and glycemic index on the association between TCF7L2 HapA and weight gain

American Journal of Clinical Nutrition

Volumn 95, Issue 6, 2012, Pages 1468-1476

  Fisher, Eva ^a   Meidtner, Karina ^a   Ängquist, Lars ^b   Holst, Claus ^b   Hansen, Rikke Dalgaard ^c   Halkjær, Jytte ^c   Masala, Giovanna ^d   Østergaard, Jane Nautrup ^e,f   Overvad, Kim ^e,f   Palli, Domenico ^d   Vimaleswaran, Karani S ^g   Tjønneland, Anne ^c   Van Der A, Daphne L ^h   Wareham, Nicholas J ^g   Sørensen, Thorkild I A ^b   Loos, Ruth J F ^g   Boeing, Heiner ^a  

^a GERMAN INSTITUTE OF HUMAN NUTRITION   (Germany)

^b The Capital Region   (Denmark)

^c INSTITUTE OF CANCER EPIDEMIOLOGY   (Denmark)

^d CANCER RESEARCH AND PREVENTION INSTITUTE ISPO   (Italy)

^e AALBORG UNIVERSITY HOSPITAL   (Denmark)

^f AARHUS UNIVERSITY   (Denmark)

^g INSTITUTE OF METABOLIC SCIENCE   (United Kingdom)

^h NATIONAL INSTITUTE FOR PUBLIC HEALTH AND THE ENVIRONMENT   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN HAPA; TRANSCRIPTION FACTOR; TRANSCRIPTION FACTOR 7 LIKE 2; UNCLASSIFIED DRUG;

ADULT; ALCOHOL CONSUMPTION; ALLELE; ARTICLE; BLOOD SAMPLING; BODY WEIGHT; CALORIC INTAKE; CARBOHYDRATE INTAKE; COHORT ANALYSIS; CONTROLLED STUDY; DISEASE ASSOCIATION; FAT INTAKE; FEMALE; FOLLOW UP; GENE FREQUENCY; GENOTYPE; GLYCEMIC INDEX; HOMOZYGOTE; HUMAN; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; MOLECULAR INTERACTION; NUTRITIONAL ASSESSMENT; OBSERVATIONAL STUDY; PROSPECTIVE STUDY; PROTEIN INTAKE; SINGLE NUCLEOTIDE POLYMORPHISM; SMOKING; WAIST CIRCUMFERENCE; WEIGHT GAIN;

ADULT; ALLELES; ANIMALS; BODY MASS INDEX; DIET; DIETARY PROTEINS; ENERGY INTAKE; EUROPE; FEMALE; FOLLOW-UP STUDIES; GENOTYPE; GLYCEMIC INDEX; HUMANS; MALE; MIDDLE AGED; OBESITY; PROSPECTIVE STUDIES; REGRESSION ANALYSIS; TRANSCRIPTION FACTOR 7-LIKE 2 PROTEIN; WEIGHT GAIN;

ANIMALIA;

EID: 84861537514     PISSN: 00029165     EISSN: 19383207     Source Type: Journal    
DOI: 10.3945/ajcn.111.014670     Document Type: Article

References (47)

1. Cauchi S, El Achhab Y, Choquet H, Dina C, Krempler F, Weitgasser R, Nejjari C, Patsch W, Chikri M, Meyre D, 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. (Pubitemid 47063530)
2. Florez JC. The new type 2 diabetes gene TCF7L2. Curr Opin Clin Nutr Metab Care 2007;10:391-6. (Pubitemid 46934105)
3. Lyssenko V. The transcription factor 7-like 2 gene and increased risk of type 2 diabetes: an update. Curr Opin Clin Nutr Metab Care 2008;11:385-92.
4. Gaulton KJ, Nammo T, Pasquali L, Simon JM, Giresi PG, Fogarty MP, Panhuis TM, Mieczkowski P, Secchi A, Bosco D, et al. A map of open chromatin in human pancreatic islets. Nat Genet 2010;42:255-9.
5. Hansson O, Zhou Y, Renstrom E, Osmark P. Molecular function of TCF7L2: Consequences of TCF7L2 splicing for molecular function and risk for type 2 diabetes. Curr Diab Rep 2010;10:444-51.
6. Helgason A, Palsson S, Thorleifsson G, Grant SFA, Emilsson V, Gunnarsdottir S, Adeyemo A, Chen Y, Chen G, Reynisdottir I, et al. Refining the impact of TCF7L2 gene variants on type 2 diabetes and adaptive evolution. Nat Genet 2007;39:218-25. (Pubitemid 46184353)
7. Florez JC, Jablonski KA, Bayley N, Pollin TI, de Bakker PI, Shuldiner AR, Knowler WC, Nathan DM, Altshuler D. TCF7L2 polymorphisms and progression to diabetes in the Diabetes Prevention Program. N Engl J Med 2006;355:241-50. (Pubitemid 44079339)
8. Wang J, Kuusisto J, VanttinenM, Kuulasmaa T, Lindstrom J, Tuomilehto J, Uusitupa M, Laakso M. 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. (Pubitemid 46701561)
9. Stancáková A, Kuulasmaa T, Paananen J, Jackson AU, Bonnycastle LL, Collins FS, Boehnke M, Kuusisto J, Laakso M. Association of 18 confirmed susceptibility loci for type 2 diabetes with indices of insulin release, proinsulin conversion, and insulin sensitivity in 5,327 nondiabetic Finnish men. Diabetes 2009;58:2129-36.
10. Stolerman ES, Manning A, McAteer J, Fox C, Dupuis J, Meigs J, Florez J. TCF7L2 variants are associated with increased proinsulin/insulin ratios but not obesity traits in the Framingham Heart Study. Diabetologia 2009;52:614-20.
11. Zhang C, Qi L, Hunter DJ, Meigs JB, Manson JE, van Dam RM, Hu FB. Variant of transcription factor 7-like 2 (TCF7L2) gene and the risk of type 2 diabetes in large cohorts of U.S. women and men. Diabetes 2006;55:2645-8. (Pubitemid 44871168)
12. Ng MC, Park KS, Oh B, Tam CH, Cho YM, Shin HD, Lam VK, Ma RC, So WY, Cho YS, et al. Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes 2008;57:2226-33.
13. Cauchi S, Choquet H, Gutierrez-Aguilar R, Capel F, Grau K, Proenca C, Dina C, Duval A, Balkau B, Marre M, et al. Effects of TCF7L2 polymorphisms on obesity in European populations. Obesity (Silver Spring) 2008;16:476-82. (Pubitemid 351271935)
14. Grau K, Cauchi S, Holst C, Astrup A, Martinez JA, Saris WH, Blaak EE, Oppert J-M, Arner P, Rossner S, et al. TCF7L2 rs7903146-macronutrient interaction in obese individuals' responses to a 10-wk randomized hypoenergetic diet. Am J Clin Nutr 2010;91:472-9.
15. Kopp W. Nutrition, evolution and thyroid hormone levels - a link to iodine deficiency disorders? Med Hypotheses 2004;62:871-5. (Pubitemid 38680350)
16. Eaton SB, Konner M. Paleolithic nutrition. A consideration of its nature and current implications. N Engl J Med 1985;312:283-9. (Pubitemid 15199367)
17. Verginelli F, Aru F, Battista P, Mariani-Costantini R. Nutrigenetics in the light of human evolution. J Nutrigenet Nutrigenomics 2009;2:91-102.
18. Brand-Miller J, McMillan-Price J, Steinbeck K, Caterson I. Dietary glycemic index: health implications. J Am Coll Nutr 2009;28(suppl):446S-9S.
19. Vergnaud AC, Norat T, Romaguera D, Mouw T, May AM, Travier N, Luan J,Wareham N, Slimani N, Rinaldi S, et al. Meat consumption and prospective weight change in participants of the EPIC-PANACEA study. Am J Clin Nutr 2010;92:398-407.
20. Halkjaer J, Olsen A, Overvad K, Jakobsen MU, Boeing H, Buijsse B, Palli D, Tognon G, Du H, van der A DL, et al. Intake of total, animal and plant protein and subsequent changes in weight or waist circumference in European men and women: the Diogenes project. Int J Obes 2011;35:1104-13 .
21. Larsen TM, Dalskov S-M, van Baak M, Jebb SA, Papadaki A, Pfeiffer AFH, Martinez JA, Handjieva-Darlenska T, Kunešová M, Pihlsgård M, et al. Diets with high or low protein content and glycemic index for weight-loss maintenance. N Engl J Med 2010;363(22):2102-13.
22. Westerterp-Plantenga MS, Nieuwenhuizen A, Tomé D, Soenen S, Westerterp KR. Dietary protein, weight loss, and weight maintenance. Ann Rev Nutr 2009;29(1):21-41 .
23. Summerbell CD, Douthwaite W, Whittaker V, Ells LJ, Hillier F, Smith S, Kelly S, Edmunds LD, Macdonald I. The association between diet and physical activity and subsequent excess weight gain and obesity assessed at 5 years of age or older: a systematic review of the epidemiological evidence. Int J Obes (Lond) 2009;33(suppl 3):S1-92.
24. Thomas DE, Elliott Elizabeth J, Baur L. Low glycaemic index or low glycaemic load diets for overweight and obesity. Cochrane Database Syst Rev 2007;3:
25. Riboli E, Kaaks R. The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int J Epidemiol 1997;26(suppl 1):S6-14.
26. Ferrari P, Slimani N, Ciampi A, Trichopoulou A, Naska A, Lauria C, Veglia F, Bueno-de-Mesquita HB, Ocke MC, Brustad M, et al. Evaluation of under- and overreporting of energy intake in the 24-hour diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 2002;5(6B):1329-45. (Pubitemid 36313622)
27. Ferrari P, Day NE, Boshuizen HC, Roddam A, Hoffmann K, Thiebaut A, Pera G, Overvad K, Lund E, Trichopoulou A, et al. The evaluation of the diet/disease relation in the EPIC study: considerations for the calibration and the disease models. Int J Epidemiol 2008;37:368-78. (Pubitemid 351494214)
28. Slimani N, Deharveng G, Unwin I, Southgate DA, Vignat J, Skeie G, Salvini S, Parpinel M, Moller A, Ireland J, et al. The EPIC nutrient database project (ENDB): a first attempt to standardize nutrient data-bases across the 10 European countries participating in the EPIC study. Eur J Clin Nutr 2007;61:1037-56. (Pubitemid 47386588)
29. van Bakel MM, Kaaks R, Feskens EJ, Rohrmann S, Welch AA, Pala V, Avloniti K, van der Schouw YT, van der A DL, Du H, et al. Dietary glycaemic index and glycaemic load in the European Prospective Investigation into Cancer and Nutrition. Eur J Clin Nutr 2009;63(suppl 4):S188-205.
30. Rinaldi S, Key TJ, Peeters PH, Lahmann PH, Lukanova A, Dossus L, Biessy C, Vineis P, Sacerdote C, Berrino F, et al. Anthropometric measures, endogenous sex steroids and breast cancer risk in post-menopausal women: a study within the EPIC cohort. Int J Cancer 2006;118:2832-9. (Pubitemid 43673364)
31. Færch K, Lau C, Tetens I, Pedersen OB, Jørgensen T, Borch-Johnsen K, Glümer C. A statistical approach based on substitution of macronutrients provides additional information to models analyzing single dietary factors in relation to type 2 diabetes in Danish adults: the Inter99 Study. J Nutr 2005;135:1177-82. (Pubitemid 40638324)
32. Schulze MB, Schulz M, Heidemann C, Schienkiewitz A, Hoffmann K, Boeing H. Carbohydrate intake and incidence of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Br J Nutr 2008;99:1107-16.
33. Sterne JAC. Meta-analysis: an updated collection from the Stata Journal. College Station, TX: Stata Press, 2009.
34. R Development Core Team. R: a language and environment for statistical computing. Version 2.11.1. Available from: http://www.R-project.org ed. Vienna, Austria: R Foundation for Statistical Computing, 2010 (cited 6 July 2010).
35. Schwarzer G. Meta-analysis with R. RM package version 1.6-0. 2010. Available from: http://CRAN.R-project.org/package=meta (cited 6 July 2010).
36. Gauderman WJ, Morrison J. QUANTO 1.2: a computer program for power and sample size calculations for genetic-epidemiology studies. 2007. Available from: http://hydra.usc.edu/gxe (cited July 2009).
37. 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.
38. Skov AR, Toubro S, Ronn B, Holm L, Astrup A. Randomized trial on protein vs carbohydrate in ad libitum fat reduced diet for the treatment of obesity. Int J Obes Relat Metab Disord 1999;23(5):528-36. (Pubitemid 29237736)
39. Te Morenga LA, Levers M, Williams S, Brown R, Mann J. Comparison of high protein and high fiber weight-loss diets in women with risk factors for the metabolic syndrome: a randomized trial. Nutr J 2011; 10:40.
40. Gardner CD, Kiazand A, Alhassan S, Kim S, Stafford R, Balise R, Kraemer H, King A. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A TO Z Weight Loss Study: a randomized trial. JAMA 2007;297:969-77. (Pubitemid 46376751)
41. Johnston CS, Tjonn S, Swan P. High-protein, low-fat diets are effective for weight loss and favorably alter biomarkers in healthy adults. J Nutr 2004;134:586-91. (Pubitemid 38298500)
42. Noakes M, Keogh J, Foster P, Clifton P. Effect of an energy-restricted, high-protein, low-fat diet relative to a conventional high-carbohydrate, low-fat diet on weight loss, body composition, nutritional status, and markers of cardiovascular health in obese women. Am J Clin Nutr 2005;81:1298-306. (Pubitemid 41710230)
43. Gilbert JA, Bendsen NT, Tremblay A, Astrup A. Effect of proteins from different sources on body composition. Nutr Metab Cardiovasc Dis 2011;21(suppl 2):B16-31.
44. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, Allen HL, Lindgren CM, Luan J, Magi R, et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010;42:937-48.
45. Loos RJ, Lindgren CM, Li S, Wheeler E, Zhao JH, Prokopenko I, Inouye M, Freathy RM, Attwood AP, Beckmann JS, et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet 2008;40:768-75.
46. Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM, Berndt SI, Elliott AL, Jackson AU, Lamina C, et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 2009;41:25-34.
47. The International HapMap Consortium. The International HapMap Project. Nature 2003;426:789-96.