Генетика, 2023, T. 59, № 8, стр. 870-887

Генетические полиморфизмы, ассоциированные с эффективностью коррекции массы тела: систематический обзор

Э. С. Егорова 1*, И. И. Ахметов 12

1 Казанский государственный медицинский университет
420012 Казань, Россия

2 Научно-исследовательский институт спорта и физических упражнений, Ливерпульский университет им. Джона Мурса
L3 5AF Ливерпуль, Великобритания

* E-mail: jastspring@yandex.ru

Поступила в редакцию 14.02.2023
После доработки 10.03.2023
Принята к публикации 20.03.2023

Аннотация

Индивидуальные особенности человека не только обусловливают различия в массе тела, но и детерминируют реакцию организма на диету и двигательную активность. Цель данного систематического обзора – описание генетических маркеров, ассоциированных со снижением массы тела в ответ на немедикаментозные методы лечения ожирения, диетотерапию и физические нагрузки. Приемлемые для включения в систематический обзор интервенционные исследования содержали все необходимые параметры генетического полиморфизма, диеты, физической нагрузки и изменений антропометрических или композиционных показателей тела. 91 статья соответствовала критериям и была включена в данный систематический обзор. Подавляющее число исследований (n = 88) было проведено с использованием ген-кандидатного подхода и только три работы выполнены с применением полногеномного поиска ассоциаций (GWAS). Всего было обнаружено 98 генетических вариантов, из которых 72 маркера ассоциированы с эффективностью диетотерапии и 26 – с индивидуальным ответом на физические нагрузки. Следует отметить, что значимость маркеров была подтверждена независимыми исследованиями только для 10 из 98 генетических вариантов. В ближайшие годы следует ожидать прогресса в этом направлении, результатом которого станет разработка метода индивидуального подбора каждому пациенту типа диеты и физической нагрузки для профилактики и лечения ожирения.

Ключевые слова: генетика ожирения, гены, полиморфизмы, физическая нагрузка, диета, коррекция массы тела, систематический обзор.

Список литературы

  1. Yanovski J.A. Obesity: Trends in underweight and obesity – scale of the problem // Nat. Rev. Endocrinol. 2018. V. 14. № 1. P. 5–6. https://doi.org/10.1038/nrendo.2017.157

  2. GBD 2017 Diet Collaborators. Health effects of dietary risks in 195 countries, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017 // Lancet. 2019. V. 393. e10184. P. 1958–1972. https://doi.org/10.1016/S0140-6736(19)30041-8

  3. Мартинчик А.Н., Лайкам К.Э., Козырева Н.А. и др. Распространение ожирения в различных социально-демографических группах населения России // Вопр. питания. 2021. Т. 90. № 3(535). С. 67–76.

  4. Narciso J., Silva A.J., Rodrigues V. et al. Behavioral, contextual and biological factors associated with obesity during adolescence: A systematic review // PLoS One. 2019. V. 14. № 4. https://doi.org/10.1371/journal.pone.0214941

  5. Gao R., Zhu C., Li H. et al. Dysbiosis signatures of gut microbiota along the sequence from healthy, young patients to those with overweight and obesity // Obesity (Silver Spring). 2018. V. 26. № 2. P. 351–361. https://doi.org/10.1002/oby.22088

  6. Romo-Nava F., Guerdjikova A.I., Mori N.N. et al. A matter of time: A systematic scoping review on a potential role of the circadian system in binge eating behavior // Front. Nutr. 2022. V. 9. https://doi.org/10.3389/fnut.2022.978412

  7. Silventoinen K., Jelenkovic A., Sund R. et al. Genetic and environmental effects on body mass index from infancy to the onset of adulthood: An individual-based pooled analysis of 45 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) study // Am. J. Clin. Nutr. 2016. V. 104. № 2. P. 371–379. https://doi.org/10.3945/ajcn.116.130252

  8. Silventoinen K., Jelenkovic A., Sund R. et al. Genetic and environmental variation in educational attainment: An individual-based analysis of 28 twin cohorts // Sci. Rep. 2020. V. 10. № 1. P. 12681. https://doi.org/10.1038/s41598-020-69526-6

  9. Bouchard C. Genetics of obesity: What we have learned over decades of research // Obesity (Silver Spring). 2021. V. 29. № 5. P. 802–820. https://doi.org/10.1002/oby.23116

  10. Fox C.S., Liu Y., White C.C. et al. Genome-wide association for abdominal subcutaneous and visceral adipose reveals a novel locus for visceral fat in women // PLoS Genet. 2012. V. 8. № 5. e1002695. https://doi.org/10.1371/journal.pgen.1002695

  11. Yengo L., Sidorenko J., Kemper K.E. et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry // Hum. Mol. Genet. 2018. V. 27. № 20. P. 3641–3649. https://doi.org/10.1093/hmg/ddy271

  12. Warner E.T., Jiang L., Adjei D.N. et al. A genome-wide association study of childhood body fatness // Obesity (Silver Spring). 2021. V. 29. № 2. P. 446–453. https://doi.org/10.1002/oby.23070

  13. Huang J., Huffman J.E., Huang Y. et al. Genomics and phenomics of body mass index reveals a complex disease network // Nat. Commun. 2022. V. 29. V. 13. № 1. P. 7973. https://doi.org/10.1038/s41467-022-35553-2

  14. Locke A.E., Kahali B., Berndt S.I. et al. Genetic studies of body mass index yield new insights for obesity biology // Nature. 2015. V. 518. № 7538. P. 197–206. https://doi.org/10.1038/nature14177

  15. Ge T., Chen C.Y., Neale B.M. et al. Phenome-wide heritability analysis of the UK Biobank // PLoS Genet. 2018. V. 14. № 2. e1007228. https://doi.org/10.1371/journal.pgen.1006711

  16. Khera A.V., Chaffin M., Wade K.H. et al. Polygenic prediction of weight and obesity trajectories from birth to adulthood // Cell. 2019. V. 177. № 3. P. 587–596. e9. https://doi.org/10.1016/j.cell.2019.03.028

  17. Wainschtein P., Jain D., Zheng Z. et al. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data // Nat. Genet. 2022. V. 54. № 3. P. 263–273. https://doi.org/10.1038/s41588-021-00997-7

  18. Higgins J.P., Altman D.G., Gøtzsche P.C. et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials // BMJ. 2011. V. 343. d5928. https://doi.org/10.1136/bmj.d5928

  19. Реброва О.Ю., Федяева В.К., Хачатрян Г.Р. Адаптация и валидизация вопросника для оценки риска систематических ошибок в рандомизированных контролируемых испытаниях // Мед. технологии. Оценка и выбор. 2015. Т. 1. № 19. С. 9–17.

  20. Wells G., Shea B., O’Connell D. et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses // Ottawa Hospital Res. Institute. 2000. https://www.ohri.ca//programs/clinical_epidemiology/oxford.20asp

  21. Реброва О.Ю., Федяева В.К. Вопросник для оценки риска систематических ошибок в нерандомизированных сравнительных исследованиях: русскоязычная версия шкалы Ньюкасл–Оттава // Мед. технологии. Оценка и выбор. 2016. Т. 3. № 25. С. 14–19.

  22. Campbell H., Rudan I. Interpretation of genetic association studies in complex disease // Pharm. J. 2002. V. 2. P. 349–360. https://doi.org/10.1038/sj.tpj.6500132

  23. Dietrich S., Jacobs S., Zheng J.S. et al. Gene-lifestyle interaction on risk of type 2 diabetes: A systematic review // Obes. Rev. 2019. V. 20. № 11. P. 1557–1571. https://doi.org/10.1111/obr.12921

  24. Nikpay M., Lau P., Soubeyrand S. et al. SGCG rs679482 associates with weight loss success in response to an intensively supervised outpatient program // Diabetes. 2020. V. 69. № 9. P. 2017–2026. https://doi.org/10.2337/db20-0219

  25. Valsesia A., Wang Q.P., Gheldof N. et al. Genome-wide gene-based analyses of weight loss interventions identify a potential role for NKX6.3 in metabolism // Nat. Commun. 2019. V. 10. № 1. P. 540. https://doi.org/10.1038/s41467-019-08492-8

  26. Garaulet M., Smith C.E., Hernández-González T. et al. PPARγ Pro12Ala interacts with fat intake for obesity and weight loss in a behavioural treatment based on the Mediterranean diet // Mol. Nutr. Food Res. 2011. V. 55. № 12. P. 1771–1779. https://doi.org/10.1002/mnfr.201100437

  27. Garaulet M., Vera B., Bonnet-Rubio G. et al. Lunch eating predicts weight-loss effectiveness in carriers of the common allele at PERILIPIN1: the ONTIME (Obesity, Nutrigenetics, Timing, Mediterranean) study // Am. J. Clin. Nutr. 2016. V. 104. № 4. P. 1160–1166. https://doi.org/10.3945/ajcn.116.134528

  28. Garaulet M., Sánchez-Moreno C., Smith C.E. et al. Ghrelin, sleep reduction and evening preference: relationships to CLOCK 3111 T/C SNP and weight loss // PLoS One. 2011. V. 6. № 2. e17435. https://doi.org/10.1371/journal.pone.0017435

  29. Aberle J., Flitsch J., Beck N.A. et al. Genetic variation may influence obesity only under conditions of diet: Analysis of three candidate genes // Mol. Genet. Metab. 2008. V. 95. № 3. P. 188–191. https://doi.org/10.1016/j.ymgme.2008.07.008

  30. Goni L., Riezu-Boj J.I., Milagro F.I. et al. Interaction between an ADCY3 genetic variant and two weight-lowering diets affecting body fatness and body composition outcomes depending on macronutrient distribution: a randomized trial // Nutrients. 2018. V. 10. № 6. P. 789. https://doi.org/10.3390/nu10060789

  31. Ramos-Lopez O., Cuervo M., Goni L. et al. Modeling of an integrative prototype based on genetic, phenotypic, and environmental information for personalized prescription of energy-restricted diets in overweight/obese subjects // Am. J. Clin. Nutr. 2020. V. 111. № 2. P. 459–470. https://doi.org/10.1093/ajcn/nqz286

  32. Garaulet M., Corbalán M.D., Madrid J.A. et al. CLOCK gene is implicated in weight reduction in obese patients participating in a dietary programme based on the Mediterranean diet // Int. J. Obes. (Lond). 2010. V. 34. № 3. P. 516–523. https://doi.org/10.1038/ijo.2009.255

  33. Sakane N., Yoshida T., Umekawa T. et al. Effects of Trp64Arg mutation in the beta 3-adrenergic receptor gene on weight loss, body fat distribution, glycemic control, and insulin resistance in obese type 2 diabetic patients // Diabetes Care. 1997. V. 20. № 12. P. 1887–1890. https://doi.org/10.2337/diacare.20.12.1887

  34. Tchernof A., Starling R.D., Turner A. et al. Impaired capacity to lose visceral adipose tissue during weight reduction in obese postmenopausal women with the Trp64Arg beta3-adrenoceptor gene variant // Diabetes. 2000. V. 49. № 10. P. 1709–1713. https://doi.org/10.2337/diabetes.49.10.1709

  35. Corella D., Qi L., Sorlí J.V. et al. Obese subjects carrying the 11482G>A polymorphism at the perilipin locus are resistant to weight loss after dietary energy restriction // J. Clin. Endocrinol. Metab. 2005. V. 90. № 9. P. 5121–5126. https://doi.org/10.1210/jc.2005-0576

  36. Ruiz J.R., Larrarte E., Margareto J. et al. Preliminary findings on the role of PLIN1 polymorphisms on body composition and energy metabolism response to energy restriction in obese women // Br. J. Nutr. 2011. V. 106. № 4. P. 486–490. https://doi.org/10.1017/S0007114511000432

  37. Qi Q., Bray G.A., Smith S.R. et al. 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. V. 124. № 5. P. 563–571. https://doi.org/10.1161/CIRCULATIONAHA.111.025767

  38. Ramos-Lopez O., Riezu-Boj J.I., Milagro F.I. et al. Models integrating genetic and lifestyle interactions on two adiposity phenotypes for personalized prescription of energy-restricted diets with different macronutrient distribution // Front. Genet. 2019. V. 10. № 686. https://doi.org/10.3389/fgene.2019.00686

  39. Goni L., Cuervo M., Milagro F.I., Martínez J.A. Gene-Gene interplay and gene-diet interactions involving the MTNR1B rs10830963 variant with body weight loss // J. Nutrigenet. Nutrigenomics. 2014. V. 7. № 4–6. P. 232–242. https://doi.org/10.1159/000380951

  40. de Luis D.A., Izaola O., Primo D., Aller R. Dietary-fat effect of the rs10830963 polymorphism in MTNR1B on insulin resistance in response to 3 months weight-loss diets // Endocrinol. Diabetes Nutr. (Engl. Ed). 2020. V. 67. № 1. P. 43–52. https://doi.org/10.1016/j.endinu.2019.02.007

  41. Chmurzynska A., Muzsik A., Krzyżanowska-Jankowska P. et al. PPARG and FTO polymorphism can modulate the outcomes of a central European diet and a Mediterranean diet in centrally obese postmenopausal women // Nutr. Res. 2019. V. 69. P. 94–100. https://doi.org/10.1016/j.nutres.2019.08.005

  42. Rajkumar A., Lamothe G., Bolongo P. et al. Acyl-CoA synthetase long-chain 5 genotype is associated with body composition changes in response to lifestyle interventions in postmenopausal women with overweight and obesity: A genetic association study on cohorts Montréal–Ottawa New Emerging Team, and Complications Associated with Obesity // BMC Med. Genet. 2016. V. 17. № 1. P. 56. https://doi.org/10.1186/s12881-016-0320-4

  43. Izaola Jáuregui O., López Gómez J.J., Primo Martín D. et al. ACYL-CoA synthetase long-chain 5 polymorphism is associated with weight loss and metabolic changes in response to a partial meal-replacement hypocaloric diet // Nutr. Hosp. 2020. V. 37. № 4. P. 757–762.https://doi.org/10.20960/nh.03019

  44. de Luis D.A., Mulero I., Primo D. et al. Effects of polymorphism rs3123554 in the cannabinoid receptor gene type 2 (CB2R) on metabolic and adiposity parameters after weight loss with two hypocaloric diets // Diabetes Res. Clin. Pract. 2018. V. 139. P. 339–347. https://doi.org/10.1016/j.diabres.2018.02.030

  45. de Luis D., Aller R., Izaola O. et al. Effect of fatty acid-binding protein 2 Ala54Thr genotype on weight loss and cardiovascular risk factors after a high-polyunsaturated fat diet in obese patients // J. Investig. Med. 2012. V. 60. № 8. P. 1194–1198. https://doi.org/10.2310/JIM.0b013e318271fb25

  46. Martinez-Lopez E., Garcia-Garcia M.R., Gonzalez-Avalos J.M. et al. Effect of Ala54Thr polymorphism of FABP2 on anthropometric and biochemical variables in response to a moderate-fat diet // Nutrition. 2013. V. 29. № 1. P. 46–51. https://doi.org/10.1016/j.nut.2012.03.002

  47. de Luis D.A., Aller R., Conde R. et al. The rs9939609 gene variant in FTO modified the metabolic response of weight loss after a 3-month intervention with a hypocaloric diet // J. Investig. Med. 2013. V. 61. № 1. P. 22–26. https://doi.org/10.2310/JIM.0b013e318276161d

  48. Huang T., Qi Q., Li Y. et al. FTO genotype, dietary protein, and change in appetite: the Preventing Overweight Using Novel Dietary Strategies trial // Am. J. Clin. Nutr. 2014. V. 99. № 5. P. 1126–1130. https://doi.org/10.3945/ajcn.113.082164

  49. de Luis D.A., Aller R., Izaola O., Pacheco D. Role of rs9939609 FTO gene variant in weight loss, insulin resistance and metabolic parameters after a high monounsaturated vs a high polyunsaturated fat hypocaloric diets // Nutr. Hosp. 2015. V. 32. № 1. P. 175–181. https://doi.org/10.3305/nh.2015.32.1.9169

  50. de Luis D.A., Aller R., Izaola O. et al. Effects of a high-protein/low-carbohydrate diet versus a standard hypocaloric diet on weight and cardiovascular risk factors: role of a genetic variation in the rs9939609 FTO gene variant // J. Nutrigenet. Nutrigenomics. 2015. V. 8. № 3. P. 128–136. https://doi.org/10.1159/000441142

  51. Verhoef S.P., Camps S.G., Bouwman F.G. et al. Genetic predisposition, dietary restraint and disinhibition in relation to short and long-term weight loss // Physiol. Behav. 2014. V. 128. P. 247–251. https://doi.org/10.1016/j.physbeh.2014.02.004

  52. Holzapfel C., Sag S., Graf-Schindler J. et al. Association between single nucleotide polymorphisms and weight reduction in behavioural interventions-A pooled analysis // Nutrients. 2021. V. 13. № 3. https://doi.org/10.3390/nu13030819

  53. de Luis D.A., Izaola O., Primo D., Aller R. Association of the rs10830963 polymorphism in melatonin receptor type 1B (MTNR1B) with metabolic response after weight loss secondary to a hypocaloric diet based in Mediterranean style // Clin. Nutr. 2018. V. 37. № 5. P. 1563–1568. https://doi.org/10.1016/j.clnu.2017.08.015

  54. de Luis D.A., Izaola O., Primo D., Aller R. A circadian rhythm-related MTNR1B genetic variant (rs10830963) modulate body weight change and insulin resistance after 9 months of a high protein/low carbohydrate vs a standard hypocaloric diet // J. Diabetes Complications. 2020. V. 34. № 4. https://doi.org/10.1016/j.jdiacomp.2020.107534

  55. Goni L., Sun D., Heianza Y., Wang T. 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. 2019. V. 58. № 4. P. 1381–1389. https://doi.org/10.1007/s00394-018-1660-y

  56. Grau K., Cauchi S., Holst C. et al. TCF7L2 rs7903146-macronutrient interaction in obese individuals’ responses to a 10-wk randomized hypoenergetic diet // Am J. Clin. Nutr. 2010. V. 91. № 2. P. 472–479. https://doi.org/10.3945/ajcn.2009.27947

  57. Yoon Y., Park B.L., Cha M.H. et al. Effects of genetic polymorphisms of UCP2 and UCP3 on very low calorie diet-induced body fat reduction in Korean female subjects // Biochem. Biophys. Res. Commun. 2007. V. 359. № 3. P. 451–456. https://doi.org/10.1016/j.bbrc.2007.05.110

  58. Stocks T., Angquist L., Banasik K. et al. TFAP2B influences the effect of dietary fat on weight loss under energy restriction // PLoS One. 2012. V. 7. № 8. e43212. https://doi.org/10.1371/journal.pone.0043212

  59. Huang T., Wang T., Heianza Y. et al. HNF1A variant, energy-reduced diets and insulin resistance improvement during weight loss: The POUNDS Lost trial and DIRECT // Diabetes Obes. Metab. 2018. V. 20. № 6. P. 1445–1452. https://doi.org/10.1111/dom.13250

  60. Di Renzo L., Rizzo M., Iacopino L. et al. Body composition phenotype: Italian Mediterranean Diet and C677T MTHFR gene polymorphism interaction // Eur. Rev. Med. Pharmacol. Sci. 2013. V. 17. № 19. P. 2555–2565.

  61. Bojarczuk A., Boulygina E.A., Dzitkowska-Zabielska M. et al. Genome-wide association study of exercise-induced fat loss efficiency // Genes (Basel). 2022. V. 13. № 11. P. 1975. https://doi.org/10.3390/genes13111975

  62. Mazur I.I., Drozdovska S., Andrieieva O. et al. PPARGC1A gene polymorphism is associated with exercise-induced fat loss // Mol. Biol. Rep. 2020. V. 47. № 10. P. 7451–7457. https://doi.org/10.1007/s11033-020-05801-z

  63. Mitchell J.A., Church T.S., Rankinen T. et al. FTO genotype and the weight loss benefits of moderate intensity exercise // Obesity (Silver Spring). 2010. V. 18. № 3. P. 641–643. https://doi.org/10.1038/oby.2009.311

  64. Wang W., Yang K., Wang S. et al. The sex-specific influence of FTO genotype on exercise intervention for weight loss in adult with obesity // Eur. J. Sport Sci. 2022. V. 22. № 12. P. 1926–1931. https://doi.org/10.1080/17461391.2021.1976843

  65. Østergård T., Ek J., Hamid Y. et al. Influence of the PPAR-gamma2 Pro12Ala and ACE I/D polymorphisms on insulin sensitivity and training effects in healthy offspring of type 2 diabetic subjects // Horm. Metab. Res. 2005. V. 37. № 2. P. 99–105. https://doi.org/10.1055/s-2005-861174

  66. Franks P.W., Jablonski K.A., Delahanty L. et al. The Pro12Ala variant at the peroxisome proliferator-activated receptor gamma gene and change in obesity-related traits in the Diabetes Prevention Program // Diabetologia. 2007. V. 50. № 12. P. 2451–2460. https://doi.org/10.1007/s00125-007-0826-6

  67. Orkunoglu-Suer F.E., Gordish-Dressman H., Clarkson P.M. et al. INSIG2 gene polymorphism is associated with increased subcutaneous fat in women and poor response to resistance training in men // BMC Med. Genet. 2008. V. 23. № 9. P. 117. https://doi.org/10.1186/1471-2350-9-117

  68. Cameron J.D., Riou M.È., Tesson F. et al. The TaqIA RFLP is associated with attenuated intervention-induced body weight loss and increased carbohydrate intake in post-menopausal obese women // Appetite. 2013. V. 60. № 1. P. 111–116. https://doi.org/10.1016/j.appet.2012.09.010

  69. Andrade-Mayorga O., Díaz E., Salazar L.A. Effects of four lipid metabolism-related polymorphisms on body composition improvements after 12 weeks of high-intensity interval training and dietary energy restriction in overweight/obese adult women: A pilot study // Front. Physiol. 2021. V. 1. № 12. https://doi.org/10.3389/fphys.2021.712787

  70. Phares D.A., Halverstadt A.A., Shuldiner A.R. et al. Association between body fat response to exercise training and multilocus ADR genotypes // Obes. Res. 2004. V. 12. № 5. P. 807–815. https://doi.org/10.1038/oby.2004.97

  71. de Luis D.A., Gonzalez Sagrado M., Aller R. et al. Influence of the Trp64Arg polymorphism in the beta 3 adrenoreceptor gene on insulin resistance, adipocytokine response, and weight loss secondary to lifestyle modification in obese patients // Eur. J. Intern. Med. 2007. V. 18. № 8. P. 587–592. https://doi.org/10.1016/j.ejim.2007.04.019

  72. Huh J.Y. The role of exercise-induced myokines in regulating metabolism // Arch. Pharm. Res. 2018. V. 41. № 1. P. 14–29. https://doi.org/10.1007/s12272-017-0994-y

  73. Ludwig D.S., Willett W.C., Volek J.S., Neuhouser M.L. Dietary fat: from foe to friend? // Science. 2018. V. 362. P. 764–770.

  74. Wu L., Shen C., Seed Ahmed M. et al. Adenylate cyclase 3: A new target for anti-obesity drug development // Obes. Rev. 2016. V. 17. № 9. P. 907–914. https://doi.org/10.1111/obr.12430

  75. Pitman J.L., Wheeler M.C., Lloyd D.J. et al. A gain-of-function mutation in adenylate cyclase 3 protects mice from diet-induced obesity // PLoS One. 2014. V. 9. № 10. https://doi.org/10.1371/journal.pone.0110226

  76. Tong T., Shen Y., Lee H.W. et al. Adenylyl cyclase 3 haploinsufficiency confers susceptibility to diet-induced obesity and insulin resistance in mice // Sci. Rep. 2016. V. 6. https://doi.org/10.1038/srep34179

  77. URL: https://gtexportal.org.

  78. Markgraf D.F., Al-Hasani H., Lehr S. Lipidomics-reshaping the analysis and perception of type 2 diabetes // Int. J. Mol. Sci. 2016. V. 17. № 11. https://doi.org/10.3390/ijms17111841

  79. Bille D.S., Banasik K., Justesen J.M. et al. Implications of central obesity-related variants in LYPLAL1, NRXN3, MSRA, and TFAP2B on quantitative metabolic traits in adult Danes // PLoS One. 2011. V. 6. № 6. https://doi.org/10.1371/journal.pone.0020640

  80. Kok B.P., Ghimire S., Kim W. et al. Discovery of small-molecule enzyme activators by activity-based protein profiling // Nat. Chem. Biol. 2020. V. 16. № 9. P. 997–1005. https://doi.org/10.1038/s41589-020-0555-4

  81. Lyssenko V., Nagorny C.L., Erdos M.R. et al. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion // Nat. Genet. 2009. V. 41. № 1. P. 82–88.

  82. Weaver D.R., Reppert S.M. The Mel1a melatonin receptor gene is expressed in human suprachiasmatic nuclei // Neuroreport. 1996. V. 20. № 8. P. 109–112. https://doi.org/10.1097/00001756-199612200-00022

  83. Laermans J., Depoortere I. Chronobesity: Role of the circadian system in the obesity epidemic // Obes. Rev. 2016. V. 17. P. 108–125. https://doi.org/10.1111/obr.12351

  84. Oosterman J.E., Kalsbeek A., la Fleur S.E., Belsham D.D. Impact of nutrients on circadian rhythmicity // Am. J. Physiol. – Regul. Integr. Comp. Physiol. 2015. V. 308. № 5. P. R337–R350. https://doi.org/10.1152/ajpregu.00322.2014

  85. Garaulet M., Madrid J.A. Chronobiology, genetics and metabolic syndrome // Curr. Opin. Lipidol. 2009. V. 20. № 2. P. 127–134. https://doi.org/10.1097/MOL.0b013e3283292399

  86. Naja F., Hasan H., Khadem S.H. et al. Adherence to the Mediterranean diet and its association with sleep quality and chronotype among youth: A cross-sectional study // Front. Nutr. 2022. V. 8. https://doi.org/10.3389/fnut.2021.805955

  87. Corbalán M.D., Morales E.M., Canteras M. et al. Effectiveness of cognitive-behavioral therapy based on the Mediterranean diet for the treatment of obesity // Nutrition. 2009. V. 25. № 7–8. P. 861–869. https://doi.org/10.1016/j.nut.2009.02.013

  88. Fu J., Tan L.J., Lee J.E., Shin S. Association between the mediterranean diet and cognitive health among healthy adults: A systematic review and meta-analysis // Front. Nutr. 2022. V. 9. https://doi.org/10.3389/fnut.2022.946361

  89. Maciejewska-Skrendo A., Massidda M., Tocco F., Leźnicka K. The influence of the differentiation of genes encoding peroxisome proliferator-activated receptors and their coactivators on nutrient and energy metabolism // Nutrients. 2022. V. 14. № 24. https://doi.org/10.3390/nu14245378

  90. Kubota N., Terauchi Y., Miki H. et al. PPAR gamma mediates high-fat diet-induced adipocyte hypertrophy and insulin resistance // Mol. Cell. 1999. V. 4. № 4. P. 597–609. https://doi.org/10.1016/s1097-2765(00)80210-5

  91. Marcinkiewicz A., Gauthier D., Garcia A. et al. The phosphorylation of serine 492 of perilipin a directs lipid droplet fragmentation and dispersion // J. Biol. Chem. 2006. V. 281. P. 11901–11909.

  92. Rankinen T., Rice T., Teran-Garcia M. et al. FTO genotype is associated with exercise training-induced changes in body composition // Obesity (Silver Spring). 2010. V. 18. № 2. P. 322–326. https://doi.org/10.1038/oby.2009.205

  93. Danaher J., Stathis C.G., Wilson R.A. et al. High intensity exercise downregulates FTO mRNA expression during the early stages of recovery in young males and females // Nutr. Metab. (Lond). 2020. V. 17. № 68. https://doi.org/10.1186/s12986-020-00489-1

  94. Wu W., Feng J., Jiang D. et al. AMPK regulates lipid accumulation in skeletal muscle cells through FTO-dependent demethylation of N6-methyladenosine // Sci. Rep. 2017. V. 7. https://doi.org/10.1038/srep41606

  95. Li S., Zhao J.H., Luan J. et al. Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women from EPIC-Norfolk prospective population study // PLoS Med. 2010. V. 7. № 8. https://doi.org/10.1371/journal.pmed.1000332

  96. Loos R.J., Yeo G.S. The bigger picture of FTO: The first GWAS-identified obesity gene // Nat. Rev. Endocrinol. 2014. V. 10. № 1. P. 51–61. https://doi.org/10.1038/nrendo.2013.227

  97. Kilpeläinen T.O., Qi L., Brage S. et al. Physical activity attenuates the influence of FTO variants on obesity risk: A meta-analysis of 218 166 adults and 19 268 children // PLoS Med. 2011. V. 8. № 11. https://doi.org/10.1371/journal.pmed.1001116

  98. Vimaleswaran K.S., Li S., Zhao J.H. et al. Physical activity attenuates the body mass index-increasing influence of genetic variation in the FTO gene // Am. J. Clin. Nutr. 2009. V. 90. № 2. P. 425–428. https://doi.org/10.3945/ajcn.2009.27652

  99. Reddon H., Gerstein H.C., Engert J.C. et al. Physical activity and genetic predisposition to obesity in a multiethnic longitudinal study // Sci. Rep. 2016. V. 6. https://doi.org/10.1038/srep18672

  100. Zarebska A., Jastrzebski Z., Cieszczyk P. et al. The Pro12Ala polymorphism of the peroxisome proliferator-activated receptor gamma gene modifies the association of physical activity and body mass changes in Polish Women // PPAR Res. 2014. V. 2014. https://doi.org/10.1155/2014/373782

  101. Li S., He C., Nie H. et al. G allele of the rs1801282 polymorphism in PPARγ gene confers an increased risk of obesity and hypercholesterolemia, While T allele of the rs3856806 polymorphism displays a protective role against dyslipidemia: A systematic review and meta-analysis // Front. Endocrinol. (Lausanne). 2022. V. 13. https://doi.org/10.3389/fendo.2022.919087

  102. Masud S., Ye S., SAS Group. Effect of the peroxisome proliferator activated receptor-gamma gene Pro12Ala variant on body mass index: a meta-analysis // J. Med. Genet. 2003. V. 40. № 10. https://doi.org/10.1136/jmg.40.10.773

  103. Qi Q., Chu A.Y., Kang J.H. et al. Sugar-sweetened beverages and genetic risk of obesity // N. Engl. J. Med. 2012. V. 367. P. 1387–1396. https://doi.org/10.1056/NEJMoa1203039

  104. Qi Q., Chu A.Y., Kang J.H. et al. Fried food consumption, genetic risk, and body mass index: Gene-diet interaction analysis in three us cohort studies // BMJ. 2014. V. 348. https://doi.org/10.1136/bmj.g1610

  105. Jääskeläinen A., Schwab U., Kolehmainen M. et al. Meal frequencies modify the effect of common genetic variants on body mass index in adolescents of the northern Finland birth cohort 1986 // PLoS One. 2013. V. 10. № 9. e73802. https://doi.org/10.1371/journal.pone.0073802

  106. Cienfuegos S., Gabel K., Kalam F. et al. Effects of 4- and 6-h time-restricted feeding on weight and cardiometabolic health: A randomized controlled trial in adults with obesity // Cell Metab. 2020. V. 32. № 3. P. 366–378. https://doi.org/10.1016/j.cmet.2020.06.018

  107. Pellegrini M., Cioffi I., Evangelista A. et al. Effects of time-restricted feeding on body weight and metabolism. A systematic review and meta-analysis // Rev. Endocr. Metab. Disord. 2020. V. 21. № 1. P. 17–33. https://doi.org/10.1007/s11154-019-09524-w

  108. Heianza Y., Sun D., Wang T. et al. Starch digestion-related amylase genetic variant affects 2-year changes in adiposity in response to weight-loss diets: The POUNDS Lost Trial // Diabetes. 2017. V. 66. № 9. P. 2416–2423. https://doi.org/10.2337/db16-1482

  109. Zhang X., Qi Q., Zhang C. 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. 2013. V. 62. № 2. P. 662. https://doi.org/10.2337/db11-1799

  110. Frey U.H., Hauner H., Jöckel K.H. et al. A novel promoter polymorphism in the human gene GNAS affects binding of transcription factor upstream stimulatory factor 1, Galphas protein expression and body weight regulation // Pharmacogenet. Genomics. 2008. V. 18. № 2. P. 141–151. https://doi.org/10.1097/FPC.0b013e3282f49964

  111. Razquin C., Martinez J.A., Martinez-Gonzalez M.A. et al. A Mediterranean diet rich in virgin olive oil may reverse the effects of the -174G/C IL6 gene variant on 3-year body weight change // Mol. Nutr. Food Res. 2010. V. 54. Suppl. 1. P. S75–S82. https://doi.org/10.1002/mnfr.200900257

  112. Heianza Y., Sun D., Ma W. et al. Gut-microbiome-related LCT genotype and 2-year changes in body composition and fat distribution: the POUNDS Lost Trial // Int. J. Obes. (Lond). 2018. V. 42. № 9. P. 1565–1573. https://doi.org/10.1038/s41366-018-0046-9

  113. Sun D., Heianza Y., Li X. 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. V. 20. № 9. P. 2298–2303. https://doi.org/10.1111/dom.13333

  114. Lin X., Qi Q., Zheng Y. et al. Neuropeptide Y genotype, central obesity, and abdominal fat distribution: the POUNDS Lost Trial // Am. J. Clin. Nutr. 2015. V. 102. № 2. P. 514–519. https://doi.org/10.3945/ajcn.115.107276

  115. Valeeva F.V., Medvedeva M.S., Khasanova K.B. et al. Association of gene polymorphisms with body weight changes in prediabetic patients // Mol. Biol. Rep. 2022. V. 49. № 6. P. 4217–4224. https://doi.org/10.1007/s11033-022-07254-y

  116. Heianza Y., Ma W., Huang T. 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. V. 39. № 11. P. 1909–1914. https://doi.org/10.2337/dc16-1111

  117. Xu M., Qi Q., Liang J. 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. V. 127. № 12. P. 1283–1289. https://doi.org/10.1161/CIRCULATIONAHA.112.000586

  118. Mansego M.L., Milagro F.I., Zulet M.A., Martinez J.A. SH2B1 CpG-SNP is associated with body weight reduction in obese subjects following a dietary restriction program // Ann. Nutr. Metab. 2015. V. 66. № 1. P. 1–9. https://doi.org/10.1159/000368425

  119. Mattei J., Qi Q., Hu F.B. et al. 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. V. 96. № 5. P. 1129–1136. https://doi.org/10.3945/ajcn.112.038125

  120. Aberle J., Evans D., Beil F.U., Seedorf U. A polymorphism in the apolipoprotein A5 gene is associated with weight loss after short-term diet // Clin. Genet. 2005. V. 68. № 2. P. 152–154. https://doi.org/10.1111/j.1399-0004.2005.00463.x

  121. Hamada T., Kotani K., Nagai N. et al. Genetic polymorphisms of the renin-angiotensin system and obesity-related metabolic changes in response to low-energy diets in obese women // Nutrition. 2011. V. 27. № 1. P. 34–39. https://doi.org/10.1016/j.nut.2009.10.012

  122. Tsuzaki K., Kotani K., Nagai N. et al. Adiponectin gene single-nucleotide polymorphisms and treatment response to obesity // J. Endocrinol. Invest. 2009. V. 32. № 5. P. 395–400. https://doi.org/10.1007/BF03346474

  123. Ruiz J.R., Larrarte E., Margareto J. et al. Role of β2-adrenergic receptor polymorphisms on body weight and body composition response to energy restriction in obese women: preliminary results // Obesity (Silver Spring). 2011. V. 19. № 1. P. 212–215. https://doi.org/10.1038/oby.2010.130

  124. de Luis D.A., Fernández Ovalle H., Izaola O. et al. Rs 10767664 gene variant in Brain Derived Neurotrophic Factor (BDNF) affect metabolic changes and insulin resistance after a standard hypocaloric diet // J. Diabetes Complications. 2018. V. 32. № 2. P. 216–220. https://doi.org/10.1016/j.jdiacomp.2017.10.005

  125. de Luis D.A., Gonzalez Sagrado M., Aller R. et al. Effects of C358A missense polymorphism of the endocannabinoid degrading enzyme fatty acid amide hydrolase on weight loss after a hypocaloric diet // Metabolism. 2011. V. 60. № 5. P. 730–734. https://doi.org/10.1016/j.metabol.2010.07.007

  126. Mammès O., Aubert R., Betoulle D. et al. LEPR gene polymorphisms: associations with overweight, fat mass and response to diet in women // Eur. J. Clin. Invest. 2001. V. 31. № 5. P. 398–404. https://doi.org/10.1046/j.1365-2362.2001.00843.x

  127. Abete I., Goyenechea E., Crujeiras A.B., Martínez J.A. Inflammatory state and stress condition in weight-lowering Lys109Arg LEPR gene polymorphism carriers // Arch. Med. Res. 2009. V. 40. № 4. P. 306–310. https://doi.org/10.1016/j.arcmed.2009.03.005

  128. Thamer C., Machann J., Stefan N. et al. Variations in PPARD determine the change in body composition during lifestyle intervention: A whole-body magnetic resonance study // J. Clin. Endocrinol. Metab. 2008. V. 93. № 4. P. 1497–1500. https://doi.org/10.1210/jc.2007-1209

  129. Matsuo T., Nakata Y., Katayama Y. et al. PPARG genotype accounts for part of individual variation in body weight reduction in response to calorie restriction // Obesity (Silver Spring). 2009. V. 17. № 10. P. 1924–1931. https://doi.org/10.1038/oby.2009.199

  130. Yamakage H., Konishi Y., Muranaka K. et al. Association of protein tyrosine phosphatase 1B gene polymorphism with the effects of weight reduction therapy on bodyweight and glycolipid profiles in obese patients // J. Diabetes Investig. 2021. V. 12. № 8. P. 1462–1470. https://doi.org/10.1111/jdi.13492

  131. Heni M., Herzberg-Schäfer S., Machicao F. et al. Dietary fiber intake modulates the association between variants in TCF7L2 and weight loss during a lifestyle intervention // Diabetes Care. 2012. V. 35. № 3. e24. https://doi.org/10.2337/dc11-2012

  132. Nagai N., Sakane N., Kotani K. et al. Uncoupling protein 1 gene —3826 A/G polymorphism is associated with weight loss on a short-term, controlled-energy diet in young women // Nutr. Res. 2011. V. 31. № 4. P. 255–261. https://doi.org/10.1016/j.nutres.2011.03.010

  133. Cha M.H., Kim K.S., Suh D., Yoon Y. Effects of genetic polymorphism of uncoupling protein 2 on body fat and calorie restriction-induced changes // Hereditas. 2007. V. 144. № 5. P. 222–227. https://doi.org/10.1111/j.2007.0018-0661.02005.x

  134. Papazoglou D., Papathanasiou P., Papanas N. et al. Uncoupling protein-2 45-base pair insertion/deletion polymorphism: is there an association with severe obesity and weight loss in morbidly obese subjects? // Metab. Syndr. Relat. Disord. 2012. V. 10. № 4. P. 307–311. https://doi.org/10.1089/met.2012.0003

  135. de Luis D.A., Aller R., Izaola O. et al. Relation of ‒55CT polymorphism of UCP3 gene with weight loss and metabolic changes after a high monounsaturated fat diet in obese non diabetic patients // Eur. Rev. Med. Pharmacol. Sci. 2013. V. 17. № 20. P. 2810–2815.

  136. Cha M.H., Shin H.D., Kim K.S. et al. The effects of uncoupling protein 3 haplotypes on obesity phenotypes and very low-energy diet-induced changes among overweight Korean female subjects // Metabolism. 2006. V. 55. № 5. P. 578–586. https://doi.org/10.1016/j.metabol.2005.11.012

  137. Corbi G., Polito R., Monaco M.L. et al. Adiponectin expression and genotypes in Italian people with severe obesity undergone a hypocaloric diet and physical exercise program // Nutrients. 2019. V. 11. № 9. https://doi.org/10.3390/nu11092195

  138. Leońska-Duniec A., Jastrzębski Z., Jażdżewska A. et al. Individual responsiveness to exercise-induced fat loss and improvement of metabolic profile in young women is associated with polymorphisms of adrenergic receptor genes // J. Sports Sci. Med. 2018. V. 17. № 1. P. 134–144.

  139. Suchanek P., Kralova-Lesna I., Poledne R. et al. An AHSG gene variant modulates basal metabolic rate and body composition development after a short-time lifestyle intervention // Neuro Endocrinol. Lett. 2011. V. 32. Suppl. 2. P. 32–36.

  140. Tworoger S.S., Chubak J., Aiello E.J. et al. The effect of CYP19 and COMT polymorphisms on exercise-induced fat loss in postmenopausal women // Obes. Res. 2004. V. 12. № 6. P. 972–981. https://doi.org/10.1038/oby.2004.119

  141. de Luis D.A., Aller R., Izaola O. et al. Influence of ALA54THR polymorphism of fatty acid binding protein 2 on lifestyle modification response in obese subjects // Ann. Nutr. Metab. 2006. V. 50. № 4. P. 354–360. https://doi.org/10.1159/000094299

  142. Franzago M., Di Nicola M., Fraticelli F. et al. Nutrigenetic variants and response to diet/lifestyle intervention in obese subjects: A pilot study // Acta Diabetol. 2022. V. 59. № 1. P. 69–81. https://doi.org/10.1007/s00592-021-01787-7

  143. Ficek K., Ciȩszczyk P., Leźnicka K. et al. Novel associations between interleukin-15 polymorphisms and post-training changes of body composition parameters in young nonobese women // Front. Physiol. 2019. V. 5. № 10. https://doi.org/10.3389/fphys.2019.00876

  144. Suchánek P., Lánská V., Hubáček J.A. Body composition changes in adult females after lifestyle intervention are influenced by the NYD-SP18 variant // Cent. Eur. J. Publ. Health. 2015. V. 23. Suppl. Р. 19–S22. https://doi.org/10.21101/cejph.a4105

  145. Leońska-Duniec A., Cieszczyk P., Jastrzębski Z. et al. The polymorphisms of the PPARD gene modify post-training body mass and biochemical parameter changes in women // PLoS One. 2018. V. 13. № 8. https://doi.org/10.1371/journal.pone.0202557

  146. Haupt A., Thamer C., Heni M. 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. V. 59. № 3. P. 747–750. https://doi.org/10.2337/db09-1050

  147. Lim K.I., Shin Y.A. Impact of UCP2 polymorphism on long-term exercise-mediated changes in adipocytokines and markers of metabolic syndrome // Aging Clin. Exp. Res. 2014. V. 26. № 5. P. 491–496. https://doi.org/10.1007/s40520-014-0213-3

  148. de Luis D.A., Aller R., Izaola O. et al. Modulation of adipocytokines response and weight loss secondary to a hypocaloric diet in obese patients by –55CT polymorphism of UCP3 gene // Horm. Metab. Res. 2008. V. 40. № 3. P. 214–218. https://doi.org/10.1055/s-2008-1046796

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Приложение 1.
Таблица 1. Оценка уровней риска систематической ошибки в РКИ
Таблица 2. Оценка риска систематических ошибок нерандомизированных контролируемых исследований и итоговые оценки риска в соответствии со шкалой Ньюкасла-Оттавы
Таблица 3. Оценка методологического качества исследования в соответствии с критериями, важными для исследований, изучающих генетическую ассоциацию
Таблица 4. Оценка методологического качества исследования в соответствии с критериями, важными для исследований, изучающих генетическую ассоциацию
Таблица 5. Полиморфизмы генов, ассоциированные с эффективностью диетотерапии
Таблица 6. Полиморфизмы генов, ассоциированные с эффективностью физической нагрузки