Personalized nutrition and obesity

References

• Malik VS, Willett WC, Hu FB. Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol. 2013;9:13–27.
   PubMed Web of Science ®Google Scholar
• Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev. 2012;70:3–21.
   PubMed Web of Science ®Google Scholar
• Hu FB, Liu Y, Willett WC. Preventing chronic diseases by promoting healthy diet and lifestyle: public policy implications for China. Obes Rev. 2011;12:552–9.
   PubMed Web of Science ®Google Scholar
• Willett WC. Overview and perspective in human nutrition. Asia Pac J Clin Nutr. 2008;17(Suppl 1):1–4.
   PubMedGoogle Scholar
• Xia Q, Grant SF. The genetics of human obesity. Ann N Y Acad Sci. 2013;1281:178–90.
   PubMed Web of Science ®Google Scholar
• Qi L, Cho YA. Gene-environment interaction and obesity. Nutr Rev. 2008;66:684–94.
   PubMed Web of Science ®Google Scholar
• Qi Q, Chu AY, Kang JH, Jensen MK, Curhan GC, Pasquale LR, et al. Sugar-sweetened beverages and genetic risk of obesity. N Engl J Med. 2012;367:1387–96.
   PubMed Web of Science ®Google Scholar
• Qi Q, Bray GA, Hu FB, Sacks FM, Qi L. Weight-loss diets modify glucose-dependent insulinotropic polypeptide receptor rs2287019 genotype effects on changes in body weight, fasting glucose, and insulin resistance: the Preventing Overweight Using Novel Dietary Strategies trial. Am J Clin Nutr. 2012;95:506–13.
   PubMed Web of Science ®Google Scholar
• Zhang X, Qi Q, Zhang C, Smith SR, Hu FB, Sacks FM, et al. FTO genotype and 2-year change in body composition and fat distribution in response to weight-loss diets: the POUNDS LOST Trial. Diabetes. 2012;61:3005–11.
   PubMed Web of Science ®Google Scholar
• Prentice AM. Starvation in humans: evolutionary background and contemporary implications. Mech Ageing Dev. 2005;126:976–81.
   PubMed Web of Science ®Google Scholar
• Centers for Disease Control and Prevention (CDC). Trends in intake of energy and macronutrients--United States, 1971-2000. MMWR Morb Mortal Wkly Rep. 2004;53:80–2.
   PubMedGoogle Scholar
• Canoy D, Buchan I. Challenges in obesity epidemiology. Obes Rev. 2007;8(Suppl 1):1–11.
   PubMedGoogle Scholar
• Bahadoran Z, Mirmiran P, Hosseini-Esfahani F, Azizi F. Fast food consumption and the risk of metabolic syndrome after 3-years of follow-up: Tehran Lipid and Glucose Study. Eur J Clin Nutr. 2013;67:1303–9.
   PubMed Web of Science ®Google Scholar
• Duffey KJ, Gordon-Larsen P, Jacobs DR Jr, Williams OD, Popkin BM. Differential associations of fast food and restaurant food consumption with 3-y change in body mass index: the Coronary Artery Risk Development in Young Adults Study. Am J Clin Nutr. 2007;85:201–8.
   PubMed Web of Science ®Google Scholar
• Jaworowska A, Blackham T, Davies IG, Stevenson L. Nutritional challenges and health implications of takeaway and fast food. Nutr Rev. 2013;71:310–18.
   PubMed Web of Science ®Google Scholar
• Gross LS, Li L, Ford ES, Liu S. Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment. Am J Clin Nutr. 2004;79:774–9.
   PubMed Web of Science ®Google Scholar
• Gardner CD, Kiazand A, Alhassan S, Kim S, Stafford RS, Balise RR, et al. 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.
   PubMed Web of Science ®Google Scholar
• Sacks FM, Bray GA, Carey VJ, Smith SR, Ryan DH, Anton SD, et al. Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates. N Engl J Med. 2009;360:859–73.
   PubMed Web of Science ®Google Scholar
• Pol K, Christensen R, Bartels EM, Raben A, Tetens I, Kristensen M. Whole grain and body weight changes in apparently healthy adults: a systematic review and meta-analysis of randomized controlled studies. Am J Clin Nutr. 2013;98:872–84.
   PubMed Web of Science ®Google Scholar
• Cho SS, Qi L, Fahey GC Jr, Klurfeld DM. Consumption of cereal fiber, mixtures of whole grains and bran, and whole grains and risk reduction in type 2 diabetes, obesity, and cardiovascular disease. Am J Clin Nutr. 2013;98:594–619.
   PubMed Web of Science ®Google Scholar
• Flores-Mateo G, Rojas-Rueda D, Basora J, Ros E, Salas-Salvado J. Nut intake and adiposity: meta-analysis of clinical trials. Am J Clin Nutr. 2013;97:1346–55.
   PubMed Web of Science ®Google Scholar
• Martinez-Gonzalez MA, Bes-Rastrollo M. Nut consumption, weight gain and obesity: epidemiological evidence. Nutr Metab Cardiovasc Dis. 2011;21(Suppl 1):S40–5.
   Google Scholar
• He K, Hu FB, Colditz GA, Manson JE, Willett WC, Liu S. Changes in intake of fruits and vegetables in relation to risk of obesity and weight gain among middle-aged women. Int J Obes Relat Metab Disord. 2004;28:1569–74.
   PubMed Web of Science ®Google Scholar
• Boeing H, Bechthold A, Bub A, Ellinger S, Haller D, Kroke A, et al. Critical review: vegetables and fruit in the prevention of chronic diseases. Eur J Nutr. 2012;51:637–63.
   PubMed Web of Science ®Google Scholar
• Chen M, Pan A, Malik VS, Hu FB. Effects of dairy intake on body weight and fat: a meta-analysis of randomized controlled trials. Am J Clin Nutr. 2012;96:735–47.
   PubMed Web of Science ®Google Scholar
• Malik VS, Popkin BM, Bray GA, Despres JP, Hu FB. Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk. Circulation. 2010;121:1356–64.
   PubMed Web of Science ®Google Scholar
• Schulze MB, Manson JE, Ludwig DS, Colditz GA, Stampfer MJ, Willett WC, et al. Sugar-sweetened beverages, weight gain, and incidence of type 2 diabetes in young and middle-aged women. JAMA. 2004;292: 927–34.
   PubMed Web of Science ®Google Scholar
• Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB. Changes in diet and lifestyle and long-term weight gain in women and men. N Engl J Med. 2011;364:2392–404.
   PubMed Web of Science ®Google Scholar
• Ebbeling CB, Feldman HA, Chomitz VR, Antonelli TA, Gortmaker SL, Osganian SK, et al. A randomized trial of sugar-sweetened beverages and adolescent body weight. N Engl J Med. 2012;367:1407–16.
   PubMed Web of Science ®Google Scholar
• de Ruyter JC, Olthof MR, Seidell JC, Katan MB. A trial of sugar-free or sugar-sweetened beverages and body weight in children. N Engl J Med. 2012;367:1397–406.
   PubMed Web of Science ®Google Scholar
• Lindstrom J, Peltonen M, Eriksson JG, Ilanne-Parikka P, Aunola S, Keinanen-Kiukaanniemi S, et al. Improved lifestyle and decreased diabetes risk over 13 years: long-term follow-up of the randomised Finnish Diabetes Prevention Study (DPS). Diabetologia. 2013;56:284–93.
   PubMed Web of Science ®Google Scholar
• Unick JL, Beavers D, Bond DS, Clark JM, Jakicic JM, Kitabchi AE, et al. The long-term effectiveness of a lifestyle intervention in severely obese individuals. Am J Med. 2013;126:236–42, 42 e1–2.
   PubMed Web of Science ®Google Scholar
• Kaisari P, Yannakoulia M, Panagiotakos DB. Eating frequency and overweight and obesity in children and adolescents: a meta-analysis. Pediatrics. 2013;131:958–67.
   PubMed Web of Science ®Google Scholar
• Odegaard AO, Jacobs DR Jr, Steffen LM, Van Horn L, Ludwig DS, Pereira MA. Breakfast frequency and development of metabolic risk. Diabetes Care. 2013;36:3100–6.
   PubMed Web of Science ®Google Scholar
• Lee M, Kim A, Chua SC Jr, Obici S, Wardlaw SL. Transgenic MSH overexpression attenuates the metabolic effects of a high-fat diet. Am J Physiol Endocrinol Metab. 2007;293:E121–31.
   Web of Science ®Google Scholar
• Zheng H, Lenard NR, Shin AC, Berthoud HR. Appetite control and energy balance regulation in the modern world: reward-driven brain overrides repletion signals. Int J Obes (Lond). 2009;33(Suppl 2):S8–13.
   PubMedGoogle Scholar
• Cohen DA, Babey SH. Contextual influences on eating behaviours: heuristic processing and dietary choices. Obes Rev. 2012;13:766–79.
   PubMed Web of Science ®Google Scholar
• Rankinen T, Bouchard C. Genetics of food intake and eating behavior phenotypes in humans. Annu Rev Nutr. 2006;26:413–34.
   PubMed Web of Science ®Google Scholar
• Chu AY, Workalemahu T, Paynter NP, Rose LM, Giulianini F, Tanaka T, et al. Novel locus including FGF21 is associated with dietary macronutrient intake. Hum Mol Genet. 2013;22:1895–902.
   PubMed Web of Science ®Google Scholar
• Leturque A, Brot-Laroche E, Le Gall M. Carbohydrate intake. Prog Mol Biol Transl Sci. 2012;108:113–27.
   PubMed Web of Science ®Google Scholar
• Steinle NI, Hsueh WC, Snitker S, Pollin TI, Sakul H, St Jean PL, et al. Eating behavior in the Old Order Amish: heritability analysis and a genome-wide linkage analysis. Am J Clin Nutr. 2002;75:1098–106.
   PubMed Web of Science ®Google Scholar
• Hasselbalch AL, Silventoinen K, Keskitalo K, Pietilainen KH, Rissanen A, Heitmann BL, et al. Twin study of heritability of eating bread in Danish and Finnish men and women. Twin Res Hum Genet. 2010;13:163–7.
   PubMed Web of Science ®Google Scholar
• Greenfield JR. Melanocortin signalling and the regulation of blood pressure in human obesity. J Neuroendocrinol. 2011;23:186–93.
   PubMed Web of Science ®Google Scholar
• Valette M, Bellisle F, Carette C, Poitou C, Dubern B, Paradis G, et al. Eating behaviour in obese patients with melanocortin-4 receptor mutations: a literature review. Int J Obes (Lond). 2013;37:1027–35.
   PubMed Web of Science ®Google Scholar
• Branson R, Potoczna N, Kral JG, Lentes KU, Hoehe MR, Horber FF. Binge eating as a major phenotype of melanocortin 4 receptor gene mutations. N Engl J Med. 2003;348:1096–103.
   PubMed Web of Science ®Google Scholar
• Qi L, Kraft P, Hunter DJ, Hu FB. The common obesity variant near MC4R gene is associated with higher intakes of total energy and dietary fat, weight change and diabetes risk in women. Hum Mol Genet. 2008;17:3502–8.
   PubMed Web of Science ®Google Scholar
• de Krom M, van der Schouw YT, Hendriks J, Ophoff RA, van Gils CH, Stolk RP, et al. Common genetic variations in CCK, leptin, and leptin receptor genes are associated with specific human eating patterns. Diabetes. 2007;56:276–80.
   PubMed Web of Science ®Google Scholar
• Lancha A, Fruhbeck G, Gomez-Ambrosi J. Peripheral signalling involved in energy homeostasis control. Nutr Res Rev. 2012;25:223–48.
   PubMed Web of Science ®Google Scholar
• Tanaka T, Ngwa JS, van Rooij FJ, Zillikens MC, Wojczynski MK, Frazier-Wood AC, et al. Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. Am J Clin Nutr. 2013;97:1395–402.
   PubMed Web of Science ®Google Scholar
• Yang Q, Cogswell ME, Flanders WD, Hong Y, Zhang Z, Loustalot F, et al. Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults. JAMA. 2012;307:1273–83.
   PubMed Web of Science ®Google Scholar
• Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA. 2012;307:491–7.
   PubMed Web of Science ®Google Scholar
• Zhang X, Qi Q, Bray GA, Hu FB, Sacks FM, Qi L. APOA5 genotype modulates 2-y changes in lipid profile in response to weight-loss diet intervention: the Pounds Lost Trial. Am J Clin Nutr. 2012;96:917–22.
   PubMed Web of Science ®Google Scholar
• Mattei J, Qi Q, Hu FB, Sacks FM, Qi L. TCF7L2 genetic variants modulate the effect of dietary fat intake on changes in body composition during a weight-loss intervention. Am J Clin Nutr. 2012;96:1129–36.
   PubMed Web of Science ®Google Scholar
• Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, Greenberg I, et al. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. N Engl J Med. 2008;359:229–41.
   PubMed Web of Science ®Google Scholar
• Qi L, Liang J. Interactions between genetic factors that predict diabetes and dietary factors that ultimately impact on risk of diabetes. Curr Opin Lipidol. 2010;21:31–7.
   PubMed Web of Science ®Google Scholar
• Qi L, Hu FB, Hu G. Genes, environment, and interactions in prevention of type 2 diabetes: a focus on physical activity and lifestyle changes. Curr Mol Med. 2008;8:519–32.
   PubMed Web of Science ®Google Scholar
• Chen JJ. Not getting lost in the gene-environment interaction exploration. J Urol. 2012;188:2361.
   PubMed Web of Science ®Google Scholar
• Corella D, Arnett DK, Tucker KL, Kabagambe EK, Tsai M, Parnell LD, et al. A high intake of saturated fatty acids strengthens the association between the fat mass and obesity-associated gene and BMI. J Nutr. 2011;141:2219–25.
   PubMed Web of Science ®Google Scholar
• Qi Q, Li Y, Chomistek AK, Kang JH, Curhan GC, Pasquale LR, et al. Television watching, leisure time physical activity, and the genetic predisposition in relation to body mass index in women and men. Circulation. 2012;126:1821–7.
   PubMed Web of Science ®Google Scholar
• Ahmad S, Rukh G, Varga TV, Ali A, Kurbasic A, Shungin D, et al. Gene x physical activity interactions in obesity: combined analysis of 111,421 individuals of European ancestry. PLoS Genet. 2013;9:e1003607.
   PubMed Web of Science ®Google Scholar
• Qi Q, Bray GA, Smith SR, Hu FB, Sacks FM, Qi L. Insulin receptor substrate 1 gene variation modifies insulin resistance response to weight-loss diets in a 2-year randomized trial: the Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial. Circulation. 2011;124:563–71.
   PubMed Web of Science ®Google Scholar
• Heni M, Herzberg-Schafer S, Machicao F, Haring HU, Fritsche A. Dietary fiber intake modulates the association between variants in TCF7L2 and weight loss during a lifestyle intervention. Diabetes Care. 2012;35:e24.
   Web of Science ®Google Scholar
• Erez G, Tirosh A, Rudich A, Meiner V, Schwarzfuchs D, Sharon N, et al. Phenotypic and genetic variation in leptin as determinants of weight regain. Int J Obes (Lond). 2011;35:785–92.
   PubMed Web of Science ®Google Scholar
• Waki H, Yamauchi T, Kadowaki T. The epigenome and its role in diabetes. Curr Diab Rep. 2012;12:673–85.
   PubMed Web of Science ®Google Scholar
• Sandoval J, Esteller M. Cancer epigenomics: beyond genomics. Curr Opin Genet Dev. 2012;22:50–5.
   PubMed Web of Science ®Google Scholar
• van Abeelen AF, Elias SG, Bossuyt PM, Grobbee DE, van der Schouw YT, Roseboom TJ, et al. Famine exposure in the young and the risk of type 2 diabetes in adulthood. Diabetes. 2012;61:2255–60.
   PubMed Web of Science ®Google Scholar
• Li Y, Jaddoe VW, Qi L, He Y, Lai J, Wang J, et al. Exposure to the Chinese famine in early life and the risk of hypertension in adulthood. J Hypertens. 2011;29:1085–92.
   PubMed Web of Science ®Google Scholar
• Li Y, He Y, Qi L, Jaddoe VW, Feskens EJ, Yang X, et al. Exposure to the Chinese famine in early life and the risk of hyperglycemia and type 2 diabetes in adulthood. Diabetes. 2010;59:2400–6.
   PubMed Web of Science ®Google Scholar
• Tobi EW, Heijmans BT, Kremer D, Putter H, Delemarre-van de Waal HA, Finken MJ, et al. DNA methylation of IGF2, GNASAS, INSIGF and LEP and being born small for gestational age. Epigenetics. 2011;6: 171–6.
   PubMed Web of Science ®Google Scholar
• Heijmans BT, Tobi EW, Stein AD, Putter H, Blauw GJ, Susser ES, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Natl Acad Sci U S A. 2008;105:17046–9.
   PubMed Web of Science ®Google Scholar
• Ortega FJ, Mercader JM, Catalan V, Moreno-Navarrete JM, Pueyo N, Sabater M, et al. Targeting the circulating microRNA signature of obesity. Clin Chem. 2013;59:781–92.
   PubMed Web of Science ®Google Scholar
• Friedrich N. Metabolomics in diabetes research. J Endocrinol. 2012;215:29–42.
   PubMed Web of Science ®Google Scholar
• Rasmiena AA, Ng TW, Meikle PJ. Metabolomics and ischaemic heart disease. Clin Sci (Lond). 2013;124:289–306.
   PubMed Web of Science ®Google Scholar
• Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, et al. Metabolite profiles and the risk of developing diabetes. Nat Med. 2011;17:448–53.
   PubMed Web of Science ®Google Scholar
• Gu Y, Zhao A, Huang F, Zhang Y, Liu J, Wang C, et al. Very low carbohydrate diet significantly alters the serum metabolic profiles in obese subjects. J Proteome Res. 2013;12:5801–11.
   PubMed Web of Science ®Google Scholar
• McCormack SE, Shaham O, McCarthy MA, Deik AA, Wang TJ, Gerszten RE, et al. Circulating branched-chain amino acid concentrations are associated with obesity and future insulin resistance in children and adolescents. Pediatr Obes. 2013;8:52–61.
   PubMed Web of Science ®Google Scholar
• Goldberger JJ, Buxton AE. Personalized medicine vs guideline-based medicine. JAMA. 2013;309:2559–60.
   PubMed Web of Science ®Google Scholar
• Kettunen J, Tukiainen T, Sarin AP, Ortega-Alonso A, Tikkanen E, Lyytikainen LP, et al. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat Genet. 2012;44:269–76.
   PubMed Web of Science ®Google Scholar
• Taneera J, Lang S, Sharma A, Fadista J, Zhou Y, Ahlqvist E, et al. A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets. Cell Metab. 2012;16:122–34.
   PubMed Web of Science ®Google Scholar
• Xu M, Qi Q, Liang J, Bray GA, Hu FB, Sacks FM, et al. Genetic determinant for amino acid metabolites and changes in body weight and insulin resistance in response to weight-loss diets: the Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial. Circulation. 2013;127:1283–9.
   PubMed Web of Science ®Google Scholar