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Lessons Learned from the POUNDS Lost Study: Genetic, Metabolic, and Behavioral Factors Affecting Changes in Body Weight, Body Composition, and Cardiometabolic Risk

  • Obesity Treatment (CM Apovian, Section Editor)
  • Published:
Current Obesity Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

This paper reviews the genetic and non-genetic factors that provided predictions of, or were associated with, weight loss and other metabolic changes in the POUNDS Lost clinical trial of weight loss. This trial randomized 811 individuals who were overweight or obese to one of four diets that contained either 15% or 25% protein and 20% or 40% fat in a 2 × 2 factorial design. A standard behavioral weight loss program was available for all participants who were followed for 2 years with an 80% completion rate.

Recent Findings

Nineteen genes and five genetic risk scores were used along with demographic, behavioral, endocrine, and metabolic measurements. Genetic variations in most of the genes were associated with weight loss, but this association often varied with the dietary assignment. A number of demographic and behavioral factors, including attendance at behavioral sessions and food cravings were predictive of weight changes. A high baseline level of free triiodothyronine or free thyroxine predicted the magnitude of weight loss. Several perfluoroakyl compounds predicted more rapid weight regain.

Summary

Genetic evidence from POUNDS Lost provides guidance toward selection of a personalized weight loss diet and improvement in metabolic profile. There is still room for additional research into the predictors of weight loss.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. •• Sacks FM, Bray GA, Carey V, Smith SR, Ryan DH, Anton S, et al. Comparison of weight-loss diets with different compositions of fat, protein and carbohydrates. New Engl J Med. 2009;360:859–73 This paper used a 2 × 2 factorial design to compare four weight loss diets containing 20% or 40% fat or 15% protein or 25%. Diet composition did not influence the weight loss, but adherence to the diet did.

    Article  CAS  PubMed  Google Scholar 

  2. • Bray GA, Heisel WE, Afshin A, Jensen MD, Dietz WH, Long M, Kushner RF, Daniels SR, Wadden TA, Tsai AG, Hu FB, Jakicic JM, Ryan DH, Wolfe BM, Inge TH. The science of obesity management: an endocrine society scientific statement. Endocr Rev. 2018;39(2):79-132. This paper from the Endocrine Society provides a review of the components of clinical management of obesity including background information on prevalence and risk. Diet, exercise, behavior modification, medications, and surgery are all reviewed.

  3. • Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007–2008 to 2015–2016. JAMA. 2018;319(16):1723–5 This paper shows the increasing prevalence of obesity for BMI > 30 and BMI > 40 in the US over a 10-year period. BMI > 30 has increased from 33.7% to 39.6% and sever obesity (BMI > 40) has increased 5.7% to 7.7% over this time interval.

    Article  PubMed  PubMed Central  Google Scholar 

  4. • Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9945):766–81. Epub 2014 May 29. Erratum in: Lancet. 2014 Aug 30;384(9945):746. Between 1980 and 2013, BMI > 25 increased worldwide from 28.8 to 36.9% in men and from 29.8% to 38.0% in women. Boys and girls in developed countries participated in this world wide increase in obesity with 23.8% of boys and 22.6% of girls being overweight or obese.

  5. • Foster GD, Wyatt HR, et al. A randomized trial of a low-carbohydrate diet for obesity. N Engl J Med. 2003;348(21):2082–90 One of three papers testing whether a very low-carbohydrate diet produced more weight loss than a control diet thirty years after this idea had been published in the popular press. There was a significantly greater effect at 6 months, but not 12 months.

    Article  CAS  PubMed  Google Scholar 

  6. • Samaha FF, Iqbal N, et al. A low-carbohydrate as compared with a low-fat diet in severe obesity. N Engl J Med. 2003;348(21):2074–81 The second of three papers testing whether a very low-carbohydrate diet produced more weight loss than a control diet 30 years after this idea had been published in the popular press. There was a small positive effect of the low-carbohydrate diet that they authors cautioned should be interpreted cautiously because of the small magnitude of the difference.

    Article  CAS  PubMed  Google Scholar 

  7. • Brehm BJ, Seeley RJ, et al. A randomized trial comparing a very low carbohydrate diet and a calorie-restricted low-fat diet on body weight and cardiovascular risk factors in healthy women. J Clin Endocrinol Metab. 2003;88(4):1617–23 The third of three papers testing whether a very-low-carbohydrate diet produced more weight loss than a control diet 30 years after this idea had been published in the popular press. This trial like the other two suggested that in the short-term, the low-carbohydrate diet would produce more weight loss.

    Article  CAS  PubMed  Google Scholar 

  8. Brinkworth GD, Noakes M, Buckley JD, Keogh JB, Clifton PM. Long-term effects of a very-low-carbohydrate weight loss diet compared with an isocaloric low-fat diet after 12 mo. Am J Clin Nutr. 2009;90:23–32.

    Article  CAS  PubMed  Google Scholar 

  9. Foster GD, Wyatt HR, Hill JO, Makris AP, Rosenbaum DL, Brill C, et al. Weight and metabolic outcomes after 2 years on a low-carbohydrate versus low-fat diet: a randomized trial. Ann Intern Med. 2010;153(3):147–57.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ebbeling CB, Leidig MM, Feldman HA, Lovesky MM, Ludwig DS. Effects of a low-glycemic load vs low-fat diet in obese young adults: a randomized trial. JAMA. 2007;297(19):2092–102.

    Article  CAS  PubMed  Google Scholar 

  11. • Hall KD, Guo J. No significant effect of dietary carbohydrate versus fat on the reduction in total energy expenditure during maintenance of lost weight. BMJ 2018. 2018(363):k4583/rr–16 This paper is a rebuttal to the data in reference 10. In this commentary, Hall & Guo show that if the authors had used their original proposed analysis plan there would have been no significant difference in diets. They suggested the changed analysis plan might have biased the interpretation of the doubly-labeled water data.

  12. Ello-Martin JA, Roe LS, Ledikwe JH, Beach AM, Rolls BJ. Dietary energy density in the treatment of obesity: a year-long trial comparing 2 weight-loss diets. Am J Clin Nutr. 2007;85(6):1465–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bueno NB, de Melo IS, de Oliveira SL, da Rocha Ataide T. 2013. Very-low-carbohydrate ketogenic diet vs. low-fat diet for long-term weight loss: a meta-analysis of randomised controlled trials. Br J Nutr. 110:1178–87.

  14. Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, weight watchers, and zone diets for weight loss and heart disease risk reduction: a randomized trial. Jama. 2005;293(1):43–53.

    Article  CAS  PubMed  Google Scholar 

  15. • Gardner CD, Trepanowski JF, Del Gobbo LC, Hauser ME, Rigdon J, Ioannidis JPA, et al. Effect of low-fat vs low-carbohydrate diet on 12-month weight loss in overweight adults and the association with genotype pattern or insulin secretion: the DIETFITS Randomized Clinical Trial. JAMA. 319(7):667–79 This is the second largest randomized trial comparing healthy low-fat and healthy low-fat diets, and like the POUNDS Lost study these authors found no evidence of preferential weight loss with either diet.

  16. McMillan-Price J, Petocz P, Atkinson F, O'neill K, Samman S, Steinbeck K, et al. Comparison of 4 diets of varying glycemic load on weight loss and cardiovascular risk reduction in overweight and obese young adults: a randomized controlled trial. Arch Intern Med. 2006;166(14):1466–75.

    Article  PubMed  Google Scholar 

  17. Howard BV, Manson JE, Stefanick ML, Beresford SA, Frank G, Jones B, et al. Low-fat dietary pattern and weight change over 7 years: the Women's Health Initiative Dietary Modification Trial. Jama. 2006;295(1):39–49.

    Article  CAS  PubMed  Google Scholar 

  18. Johnston BC, Kanters S, Bandayrel K, Wu P, Naji F, Siemieniuk RA, et al. Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. JAMA. 2014;312(9):923–33.

  19. Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, Greenberg I, et al. Stampfer MJ; dietary intervention randomized controlled trial (DIRECT) group. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. N Engl J Med. 2008;359(3):229–41.

    Article  CAS  PubMed  Google Scholar 

  20. Westman EC, Tondt J, Maguire E, Yancy WS Jr. Implementing a low-carbohydrate, ketogenic diet to manage type 2 diabetes mellitus. Expert Rev Endocrinol Metab. 2018;13(5):263–72.

  21. Yancy WS Jr, Olsen MK, et al. A low-carbohydrate, ketogenic diet versus a low-fat diet to treat obesity and hyperlipidemia: a randomized, controlled trial. Ann Intern Med. 2010;153(5):337–9.

    Article  PubMed  Google Scholar 

  22. Avenell A, Brown TJ, McGee MA, Campbell MK, Grant AM, Broom J, et al. What interventions should we add to weight reducing diets in adults with obesity? A systematic review of randomized controlled trials of adding drug therapy, exercise, behaviour therapy or combinations of these interventions. J Hum Nutr Diet. 2004;17(4):293–316.

    Article  CAS  PubMed  Google Scholar 

  23. Nordmann AJ, Suter-Zimmermann K, Bucher HC, Shai I, Tuttle KR, Estruch R, et al. Meta-analysis comparing Mediterranean to low-fat diets for modification of cardiovascular risk factors. Am J Med. 2011;124(9):841–51.

    Article  PubMed  Google Scholar 

  24. Douketis, J. D., C. Macie, Thabane L, Williamson DF Systematic review of long-term weight loss studies in obese adults: clinical significance and applicability to clinical practice." Int J Obes 2005;29(10): 1153–1167.

  25. Hooper L, Abdelhamid A, Moore HJ, Douthwaite W, Skeaff CM, Summerbell CD. Effect of reducing total fat intake on body weight: systematic review and meta-analysis of randomised controlled trials and cohort studies. BMJ. 2012;345:e7666.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. •• Jensen MD, Ryan DH, Donato KA, et al. Guidelines (2013) for managing overweight and obesity in adults. Obesity. 2014;22(S2):S1–S410 This paper examined five questions related to weight loss and weighed the evidence. In their answer to the effect of diets in Question 4 they state that “to achieve weight loss, an energy deficit is required”. They also say “In overweight and obese adults, there are no difference in weight loss at 6 months with instruction to consume a carbohydrate-restricted diet (20 g/d for p to 3 months, followed by increasing levels of carbohydrate intake up to a point at which weight loss plateaus) in comparison with instruction to consume a calorie-restricted, low-fat diet.”.

    Article  Google Scholar 

  27. Taubes, G. Good calories bad calories New York: Knopf Inc.

  28. • Hall KD, Guyenet SJ, Leibel RL. The carbohydrate-insulin model of obesity is difficult to reconcile with current evidence. JAMA Intern Med. 2018;178(8):1103–5. This paper succinctly states the challenges to the carbohydrate-insulin model of obesity which underlies the belief in the value of very low carbohydrate diets.

  29. Rosenbaum M, Agurs-Collins T, Bray MS, Hall KD, Hopkins M, Laughlin M, et al. Accumulating data to optimally predict obesity treatment (ADOPT): recommendations from the biological domain. Obesity. 2018;26:S25–34.

  30. • Bray GA, Ryan DH, Johnson W, Champagne CM, Johnson CM, Rood J, et al. Markers of dietary protein intake are associated with successful weight loss in the POUNDS Lost trial. Clin Obes. 2017;18(7):715–23. This paper from the POUNDS Lost study showed the variability of weight loss with each diet where some people lost more than 20 kg whereas other actually gained weight, even though the average weight losses did not differ between diets.

  31. Williamson DA, Anton SD, Han H, Champagne CM, Allen R, Leblanc E, et al. Adherence is a multi-dimensional construct in the POUNDS lost trial. J Behav Med. 2010;33:35–45.

    Article  PubMed  Google Scholar 

  32. Williamson DA, Anton SD, Han H, Champagne CM, Allen R, LeBlanc E, et al. Early behavioral adherence predicts short and long-term weight loss in the POUNDS LOST study. J Behav Med. 2010;33(4):305–14.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Heianza Y, Sun D, Wang T, Bray GA, Sacks FM, Qi L. Starch digestion related amylase genetic variant affects 2-year changes in adiposity in response to weight-loss diets: the POUNDS lost trial. Diabetes. 2017;66(9):2416–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. 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(11):3005–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Huang T, Qi Q, Li Y, Hu FB, Bray GA, Sacks FM, et al. FTO genotype, dietary protein, and change in appetite: the preventing overweight using novel dietary strategies trial. Am J Clin Nutr. 2014;99:1126–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zheng Y, Huang T, Zhang X, Rood J, Bray GA, Sacks FM, et al. Dietary fat modifies the effects of FTO genotype on changes in insulin sensitivity: the POUNDS lost trial. J Nutr. 2015;145(5):977–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Huang T, Zheng Y, Hruby A, Williamson DA, Bray GA, Shen Y, et al. Dietary protein modifies the effect of the MC4R genotype on 2-year changes in appetite and food craving: the POUNDS lost trial. J Nutr. 2017;147(3):439–44.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhang X, Qi Q, Liang J, Hu FB, Sacks FM, Qi L. Neuropeptide Y promoter polymorphism modifies effects of a weight-loss diet on 2-year changes of blood pressure: the preventing overweight using novel dietary strategies trial. Hypertension. 2012;60(5):1169–75.

    Article  CAS  PubMed  Google Scholar 

  39. Lin X, Qi Q, Zheng Y, Huang T, Lathrop M, Diana Zelenika D, et al. Neuropeptide Y genotype, central obesity and abdominal fat distribution: the POUNDS lost trial. Am J Clin Nutr. 2015;102(2):514–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Heianza Y, Ma W, Huang T, Wang T, Zheng Y, Smith SR, et al. Macronutrient intake–associated FGF21 genotype modifies effects of weight-loss diets on 2-year changes of central adiposity and body composition: the POUNDS lost trial. Diabetes Care. 2016;39:1909–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Qi Q, Bray GA, Smith SR, Hu FB, Sacks FM, Qi L. Insulin receptor substrate-1 (IRS1) gene variation modifies insulin resistance response to weight-loss diets in a two-year randomized trial: the preventing obesity by using novel dietary strategies (POUNDS LOST) trial. Circulation. 2011;124(5):563–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Qi Q, Xu M, Wu H, Liang L, Champagne CM, Bray GA, et al. IRS1 genotype modulated metabolic syndrome reversion in response to 2-year weight-loss diet intervention. Diabetes Care. 2013;36:3442–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. 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(2):506–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. 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(5):1129–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Goni L, Sun D, Heianza Y, Wang T, Huang T, Martínez JA, et al. A circadian rhythm-related MTNR1B genetic variant modulates the effect of weight-loss diets on changes in adiposity and body composition: the POUNDS lost trial. Eur J Nutr. 2018. https://doi.org/10.1007/s00394-018-1660-y.

  46. Mirzaei K, Xu M, Qibin Qi Q, Bray GA, Frank Sacks F, Qi L. Glucose and circadian related genetic variants affect response of energy expenditure to weight-loss diets: the POUNDS LOST trial. Am J Clin Nutr. 2014;99(2):392–9.

    Article  CAS  PubMed  Google Scholar 

  47. Goni L, Sun D, Heianza Y, Wang T, Wang T, Cuervo M, et al. Macronutrient-specific effect of MTNR1B genotype on lipid levels in response to 2-year weight-loss diets. J Lipid Res. 2018;59(1):155–61.

    Article  CAS  PubMed  Google Scholar 

  48. Huang T, Wang T, Heianza Y, Sun D, Ivey K, Durst R, et al. HNF1A variant, energy-reduced diets and insulin resistance improvement during weight loss: the POUNDS Lost and DIRECT trials. Diabetes Obes Metab. 2018;20(6):1445–52.

    Article  CAS  PubMed  Google Scholar 

  49. Zhang X, Qibin Q, Bray GA, Hu FB, Sacks FM, Qi L. APOA5 genotype modulate 2-year changes in lipid profile in response to weight-loss diet intervention: the Pounds Lost Trial. Am J Clin Nutr. 2012;96(4):917–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Xu M, Qi Q, Liang J, Bray GA, Frank Hu F, Sacks F, et al. Genetic determinant for amino acid metabolites and changes in body weight and insulin resistance in response to weight-loss diets: the POUNDS LOST trial. Circulation. 2013;127:1283–9.

    Article  PubMed  Google Scholar 

  51. Xu M, Ng SS, Bray GA, Ryan DH, Sacks FM, Ning G, et al. Dietary fat intake modifies the effect of a common variant in the LIPC gene on changes in serum lipids during a long-term intervention: the POUNDS Lost trial. J Nutr. 2015;145(6):1289–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Qi Q, Durst R, Schwarzfuchs D, Leitersdorf E, Shpitzen S, Li Y, et al. CETP genotype and changes in lipid levels in response to weight-loss diet intervention: gene-diet interaction analysis in the POUNDS Lost and DIRECT randomized trials. J Lipid Res. 2015;56(3):713–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Huang T, Huang J, Qi Q, Li Y, Bray GA, Rood J, et al. PCSK7 genotype modifies effect of a weight-loss diet on 2-year changes of insulin resistance: the POUNDS LOST trial. Diabetes Care. 2015;38(3):439–44.

    Article  CAS  PubMed  Google Scholar 

  54. Qi Q, Zheng Y, Huang T, Rood J, Bray GA, Sacks FM, et al. Vitamin D metabolism-relataed genetic variants, dietary protein intake and improvement of insulin resistance of resistance in a 2 year weight loss trial: POUNDS Lost. Diabetologia. 2015;58(12):2791–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Heianza Y, Sun D, Smith SR, Bray GA, Sacks FM, Qi L. Changes in gut microbiota-related metabolites and Long-term successful weight loss in response to weight-loss diets: the POUNDS Lost trial. Diabetes Care. 2018;41(3):413–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Sun D, Heianza Y, Huang T, Ma W, Smith SR, Bray GA, et al. Genetic, epigenetic, and transcriptional variations at NFATC2IP locus with weight loss in response to diet interventions: the POUNDS Lost Trial. Diabetes Obes Metab. 2018;20:2298–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Zheng Y, Ceglarek U, Huang T, Wang T, Heianza Y, Ma W, et al. Plasma taurine, genetic predisposition, and changes of insulin sensitivity in response to weight-loss diets. the POUNDS Lost Trial JCEM 2016. 2016;101(10):3820–6.

    CAS  Google Scholar 

  58. Huang T, Ley SH, Zheng Y, Wang T, Bray GA, Sacks FM, et al. Genetic susceptibility to diabetes and long-term improvement of insulin resistance and beta cell function during 3 weight loss: the POUNDS lost trial. Am J Clin Nutr. 2016 Jul;104(1):198–204.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Wang T, Huang T, Zheng Y, Rood J, Bray GA, Sacks FM, et al. Genetic variation of fasting glucose and changes in glycemia in response to 2-year weight-loss diet intervention: the POUNDS Lost trial. Int J Obes. 2016;40(7):1164–9.

    Article  CAS  Google Scholar 

  60. Ma W, Huang T, Heianza Y, Wang T, Sun D, Tong J, et al. Genetic variations of circulating adiponectin levels modulate changes in appetite in response to weight-loss diets. J Clin Endocrinol Metab. 2017;102(1):316–25.

    PubMed  Google Scholar 

  61. Han L, Ma W, Sun D, Heianza Y, Wang T, Zheng Y, et al. Genetic variation of habitual coffee consumption and glycemic changes in response to weight-loss diet intervention: the Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial. Am J Clin Nutr. 2017;106(5):1321–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Zhou T, Sun D, Heianza Y, Li X, Champagne CM, LeBoff MS, et al. Genetically determined vitamin D levels and change in bone density during a weight-loss diet intervention: the preventing overweight using novel dietary strategies (POUNDS Lost) trial. Am J Clin Nutr. 2018;108(5):1129–13.

    Article  PubMed  Google Scholar 

  63. He H, Sun D, Zeng Y, Wang R, Zhu W, Cao S, et al. A systems genetics approach identified GPD1L and its molecular mechanism for obesity in human adipose tissue. Sci Rep. 2017;7(1):179.

    Article  CAS  Google Scholar 

  64. • Kettunen J, Tukiainen T, Sarin AP, Ortega-Alonso A, Tikkanen E, Lyytikäinen LP, et al. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat Genet. 2012;44(3):269–76. 216 phenotypes established from nuclear magnetic resonance serum samples and compared with a GWAS of 8,330 Finnish adults. 31 loci, including 11 new ones were identified. One of these was the ratio of branched chain amino acids to aromatic amino acids in the serum which is characteristic of liver dysfunction.

  65. • Bonder MJ, Kurilshikov A, Tigchelaar EF, Mujagic Z, Imhann F, Vila AV, et al. The effect of host genetics on the gut microbiome. Nat Genet. 2016;48(11):1407–12 This study is relevant to POUNDS Lost because the authors report a function LCT (lactase) SNP with the Bifidobacterium genus and provide evidence for gene-diet interaction in the gelation of the Bifidobacterium abundance.

    Article  CAS  PubMed  Google Scholar 

  66. Heianza Y, Sun D, Ma W, Zheng Y, Champagne CM, Bray GA, et al. Gut-microbiome-related LCT genotype and 2-year changes in body composition and fat distribution: the POUNDS Lost Trial. Int J Obes. 2018;42(9):1565–73.

    Article  Google Scholar 

  67. • Wahl S, Drong A, Lehne B, Loh M, Scott WR, Kunze S, et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature. 2017;541(7635):81–6. https://doi.org/10.1038/nature20784 This study is related to the POUNDS Lost investigation by showing that body mass index is associated with widespread changes in DNA methylation.

    Article  CAS  PubMed  Google Scholar 

  68. • Ding M, Bhupathiraju SN, Chen M, van Dam RM, Hu FB. Caffeinated and decaffeinated coffee consumption and risk of type 2 diabetes: a systematic review and a dose-response meta-analysis. Diabetes Care. 2014;37:569–86 This meta-analysis is related to the POUNDS Lost investigation by providing the basis for the inverse relationship between coffee consumption and the risk of diabetes.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Anton SD, Gallagher J, Carey V, Laranjo N, Cheng J, Champagne CM, et al. Diet type and changes in food cravings following weight loss: findings from the POUNDS LOST trial. Eat Weight Disord. 2012;17(2):e101–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Anton SD, LeBlanc HR, Karabetian AC, Sacks F, Bray G, Williamson DA. Use of a computer tracking system to monitor and provide feedback on dietary goals for calorie restricted diets: the POUNDS LOST study. J Diab Sci Technology. 2012;6(5):1216–25.

    Article  Google Scholar 

  71. Thomas DM, Ivanescu AE, Martin CK, Heymsfield SB, Marshall K, Bodrato VE, et al. Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study). Am J Clin Nutr. 2015;101(3):449–54.

    Article  CAS  PubMed  Google Scholar 

  72. Ma W, Huang T, Wang M, Zheng Y, Wang T, Heianza Y, et al. Two-year changes in circulating adiponectin, ectopic fat distribution, and body composition in response to weight-loss diets: the POUNDS lost trial. Int J Obes. 2016;40(11):1723–9.

    Article  CAS  Google Scholar 

  73. Zheng Y, Ceglarek UC, Huang T, Li L, Rood J, Stampfer M, et al. Weight-loss diets and 2-year change of circulating amino acids in two randomized intervention trials. Am J Clin Nutr. 2016;103(2):505–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Ma W, Huang T, Zheng Y, Molin Wang M, Bray GA, Sacks FM, et al. Weight-loss diets, adiponectin, and changes of cardiometabolic risk in the 2-year POUNDS LOST trial. J Clin Endocrinol Metab. 2016;101(6):2415–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Vadiveloo M, Sacks FM, Champagne CM, Bray GA, Mattei J. Healthful dietary variety and 2-year changes in weight and adiposity among participants in the POUNDS Lost trial. J Nutr. 2016;146(8):1552–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. •• Ghosh S, Bouchard C. Convergence between biological, behavioural and genetic determinants of obesity. Nat Rev Genet. 2017;18(12):731–48. This timely review examined the biological and behavioral aspects of the genetic determinants of obesity. Included is an extensive list of factors and traits associated with obesity, followed by an examination of the major findings from three major genetic studies: The GIANT-BMI study, the EGG-BMI study and the BF%-Study. This is followed by an examination of many of the individual genes involved with obesity.

  77. Heianza Y, Sun D, Li X, Didona AJ, Bray GA, Sacks FM, et al. Gut microbiota metabolites, amino acid metabolites, and improvements in insulin sensitivity and glucose metabolism: the POUNDS Lost trial. Gut. 2019;68(2):263–70.

    Article  CAS  PubMed  Google Scholar 

  78. Tong J, Hanseman D, Laranja NM, Carey V, Bray G, Williamson D, Landrum SC, Qi L, Harsh B, Anton A, Sacks FM. Changes in diet restraint and sweet craving predict weight regain in the POUNDS LOST Trial. Obesity 2014: (Abs T-2645-P).

  79. Tong J, Houseman D, Laranja NM, Williamson DA, Bray G, Qi L, et al. Food craving and self control of eating are predictors of weight loss in the POUNDS Lost Trial. Obesity. 2014; (Abs T-3009-OR).

  80. Liu G, Liang L, Bray GA, Qi L, Hu FB, Rood J, Sacks FM, Sun Q Thyroid hormones and changes in body weight and metabolic parameters in response to weight loss diets: the POUNDS LOST trial. Int J Obes 2017;41(6):878–886.

  81. Liu G, Dhana K, Furtado JD, Rood J, Zong G, Liang L, et al. Perfluoroalkyl substances and changes in body weight and resting metabolic rate in response to weight-loss diets: a prospective study. PLoS Med. 2018;15(2):e1002502. https://doi.org/10.1371/journal.pmed.1002502.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Hjorth MF, Bray GA, Zohar Y, Urban L, Miketinas DC, Williamson DA, et al. Pretreatment fasting glucose and insulin as determinants of weight loss on diets varying in macronutrients and dietary fibers – the POUNDS lost study. Nutrients. 2019; in press.

  83. • Stunkard AJ, Messick S. The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J Psychosom Res. 1985;29(1):71–83 This set of three variables, dietary restraint, disinhibition and hunger can be assessed with this questionnaire and has provided significant insight into food and food choices.

    Article  CAS  PubMed  Google Scholar 

  84. Apolzan J, Myers C, Champagne C, Beyl R, Raynor H, Anton S, et al. Frequency of consuming foods predicts changes in cravings for those foods during weight loss: the POUNDS Lost study. Obesity. 2017;25(8):1343–8.

    Article  PubMed  Google Scholar 

  85. • Loos RJ. The genetics of adiposity. Curr Opin Genet Dev. 2018;50:86–95.This review examines the genetic factors that are related to the development of adiposity with a focus on the genome-wide association studies (GWAS).

  86. Rodin J, Bray GA, Atkinson RL, Dahms WT, Greenway FL, Hamilton K, et al. Predictors of successful weight loss in an out-patient obesity clinic. Int J Obes. 1977;1:79–87.

    CAS  PubMed  Google Scholar 

  87. Diabetes Prevention Program. (Writing Group: Delahanty LM, Conroy MB, Nathan DM) for the Diabetes Prevention Program Research Group. Psychological predictors of physical activity in the diabetes prevention program. J Am Diet Assoc. 2006 May;106(5):698–705.

    Article  Google Scholar 

  88. Wadden TA, Neiberg RH, Wing RR, Clark JM, Delahanty LM, Hill JO, Krakoff J, Otto A, Ryan DH, Vitolins MZ; Look AHEAD Research Group. Four-year weight losses in the Look AHEAD study: factors associated with long-term success. Obesity (Silver Spring). 2011 Oct;19(10):1987–98.

  89. Espeland M, Bray GA, Neiberg R, Rejeski WJ, Knowler WC, Lang W, et al. Describing patterns of weight changes using principal components analysis: results from the action for health in diabetes (look AHEAD) study group. Ann Epidemiol. 2009;19:701–10.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Espeland MA, Beavers KM, Gibbs BB, Johnson KC, Hughes TM, Baker LD, et al. Ankle-brachial index and inter-artery blood pressure differences as predictors of cognitive function in overweight and obese older adults with diabetes: results from the action for health in diabetes movement and memory study. Int J Geriatr Psychiatry. 2015;30(10):999–1007.

    Article  PubMed  Google Scholar 

  91. Dansinger ML, Tatsioni A, Wong JB, Chung M, Balk EM. Meta-analysis: the effect of dietary counseling for weight loss. Ann Intern Med. 2007;147:41–50.

    Article  PubMed  Google Scholar 

  92. Unick JL, Neiberg RH, Hogan PE, Cheskin LJ, Dutton GR, Jeffery R, et al. Weight change in the first 2 months of a lifestyle intervention predicts weight changes 8 years later. Obesity (Silver Spring). 2015;23(7):1353–6.

  93. Atkins, R. C. 2002. Dr. Atkins's new diet revolution. New York, Avon.

  94. Ornish D. Eat more, weigh less: Dr. Dean Ornish's life choice program for losing weight safely while eating abundantly. New York: HarperCollins; 1993.

    Google Scholar 

  95. •• Hall KD, Guo J. Obesity energetics: body weight regulation and the effects of diet composition. Gastroenterology. 2017;152(7):1718–27 This paper contains a meta-analysis of low carbohydrate and low-fat weight loss diets in which the protein was held constant and the control of diet was known. They conclude that when there is no variation of protein there is no clinically significant difference in the weight loss produced by low-fat and very low carbohydrate diets.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Due A, Tourbro S, Slender S, Skov AR, Astrup A. The effect of diets high in protein or carbohydrate on inflammatory markers in overweight subjects. Diab Obes Metabol. 2005;7:223–9.

    Article  CAS  Google Scholar 

  97. Larsen TM, Dalskov SM, van Baak M, Jebb SA, Papadaki A, Pfeiffer AF, et al. Diet, obesity, and genes (Diogenes) project. Diets with high or low protein content and glycemic index for weight-loss maintenance. N Engl J Med. 2010;363(22):2102–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Layman DK, Evans EM, Erickson D, Seyler J, Weber J, Bagshaw D, et al. A moderate-protein diet produces sustained weight loss and long-term changes in body composition and blood lipids in obese adults. J Nutr. 2009;139(3):514–21.

    Article  CAS  PubMed  Google Scholar 

  99. Noakes M, Keogh JB, Foster PR, Clifton PM. 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(6):1298–306.

    Article  CAS  PubMed  Google Scholar 

  100. Schwingshackl L, Hoffmann G. Low-carbohydrate diets and cardiovascular risk factors. Obes Rev. 2013;14(2):183–4.

  101. Westerterp-Plantenga MS, Nieuwenhuizen A, Tomé D, Soenen S, Westerterp KR. Dietary protein, weight loss, and weight maintenance. Annu Rev Nutr. 2009;29:21–41 Review.

    Article  CAS  PubMed  Google Scholar 

  102. Wycherley TP, Moran LJ, Clifton PM, Noakes M, Brinkworth GD. Effects of energy-restricted high-protein, low-fat compared with standard-protein, low-fat diets: a meta-analysis of randomized controlled trials. Am J Clin Nutr. 2012 Dec;96(6):1281–98.

    Article  CAS  PubMed  Google Scholar 

  103. Rohde K, Keller M, la Cour PL, Blüher M, Kovacs P, Böttcher Y. Genetics and epigenetics in obesity. Metabolism. 2019;92:37–50.

  104. Rauschert S, Kirchberg FF, Marchioro L, Koletzko B, Hellmuth C, Uhl O. Early programming of obesity throughout the life course: a metabolomics perspective. Ann Nutr Metab. 2017;70(3):201–9.

    Article  CAS  PubMed  Google Scholar 

  105. • Heianza Y, Qi L. Impact of genes and environment on obesity and cardiovascular disease. Endocrinology. 2018. https://doi.org/10.1210/en.2018-00591 This review includes a number of the studies from POUNDS Lost and focuses on the dietary advice that can be given.

  106. Qi L. Personalized nutrition and obesity. Ann Med. 2014 Aug;46(5):247–52.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Wang T, Xu M, Bi Y, Ning G. Interplay between diet and genetic susceptibility in obesity and related traits. Front Med. 2018;12(6):601–7.

  108. 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(15):1387–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

We thank all of the participants in the POUNDS Lost study without whose help and willingness to participate in the study there would have been nothing to report. We also thank the staff who participated in the design and execution of this study, in the data collection, and the analysis and storage of the data.

Funding

The study has been supported in part by grants from the National Heart, Lung, and Blood Institute (HL071981, HL034594, HL126024), the National Institute of Diabetes and Digestive and Kidney Diseases (DK091718, DK100383, DK078616).

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Correspondence to George A. Bray.

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Dr. Bray declares that he has no conflict of interest.

Dr. Krauss declares that he has no conflict of interest.

Dr. Sacks reports grants from NHLBI during the conduct of the study.

Dr. Qi declares that he has no conflict of interest.

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All reported studies/experiments with human or animal subjects performed by the authors were performed in accordance with all applicable ethical standards including the Helsinki declaration and its amendments, institutional/national research committee standards, and international/national/institutional guidelines.

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Bray, G.A., Krauss, R.M., Sacks, F.M. et al. Lessons Learned from the POUNDS Lost Study: Genetic, Metabolic, and Behavioral Factors Affecting Changes in Body Weight, Body Composition, and Cardiometabolic Risk. Curr Obes Rep 8, 262–283 (2019). https://doi.org/10.1007/s13679-019-00353-1

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