Preventive Nutrition and Food Science

The Korean Society of Food Science and Nutrition (한국식품영양과학회)
권호 표지
DOI QR코드

DOI QR Code

Obesity: Interactions of Genome and Nutrients Intake

  • Doo, Miae (Department of Nutritional Science and Food Management, Ewha Womans University) ;
  • Kim, Yangha (Department of Nutritional Science and Food Management, Ewha Womans University)
  • Received : 2014.09.30
  • Accepted : 2014.12.15
  • Published : 2015.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Obesity has become one of the major public health problems all over the world. Recent novel eras of research are opening for the effective management of obesity though gene and nutrient intake interactions because the causes of obesity are complex and multifactorial. Through GWASs (genome-wide association studies) and genetic variations (SNPs, single nucleotide polymorphisms), as the genetic factors are likely to determine individuals' obesity predisposition. The understanding of genetic approaches in nutritional sciences is referred as "nutrigenomics". Nutrigenomics explores the interaction between genetic factors and dietary nutrient intake on various disease phenotypes such as obesity. Therefore, this novel approach might suggest a solution for the effective prevention and treatment of obesity through individual genetic profiles and help improve health conditions.

Keywords

References

  1. Formiguera X, Canton A. 2004. Obesity: epidemiology and clinical aspects. Best Pract Res Clin Gastroenterol 18: 1125-1146. https://doi.org/10.1016/S1521-6918(04)00091-5
  2. Akabas S, Lederman SA, Moore BJ. 2012. Textbook of obesity: biological, psychological and cultural influences. 1st ed. Wiley-Blackwell publishing, Chichester, UK. p 5-41.
  3. Bujnowski D, Xun P, Daviglus ML, Van Horn L, He K, Stamler J. 2011. Longitudinal association between animal and vegetable protein intake and obesity among men in the United States: the Chicago Western Electric Study. J Am Diet Assoc 111: 1150-1155.e1.
  4. Foster GD, Wyatt HR, Hill JO, McGuckin BG, Brill C, Mohammed BS, Szapary PO, Rader DJ, Edman JS, Klein S. 2003. A randomized trial of a low-carbohydrate diet for obesity. N Engl J Med 348: 2082-2090. https://doi.org/10.1056/NEJMoa022207
  5. Walker CG, Zariwala MG, Holness MJ, Sugden MC. 2007. Diet, obesity and diabetes: a current update. Clin Sci (Lond) 112: 93-111. https://doi.org/10.1042/CS20060150
  6. Sharma AM, Padwal R. 2010. Obesity is a sign-over-eating is a symptom: an aetiological framework for the assessment and management of obesity. Obes Rev 11: 362-370. https://doi.org/10.1111/j.1467-789X.2009.00689.x
  7. Stunkard AJ, Foch TT, Hrubec Z. 1986. A twin study of human obesity. JAMA 256: 51-54. https://doi.org/10.1001/jama.1986.03380010055024
  8. Hur YM. 2007. Sex difference in heritability of BMI in South Korean adolescent twins. Obesity (Silver Spring) 15: 2908-2911. https://doi.org/10.1038/oby.2007.346
  9. Cho EY, Park HY, Jee SH, Jang YS, Bae SJ, Lee JH, Jang YS. 2001. Korean familial resemblance in fat mass and fat free mass: cardiovascular genome study. Korean J Lipidol 11: 537-547.
  10. The Wellcome Trust Case Control Consortium. 2007. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447: 661-678. https://doi.org/10.1038/nature05911
  11. Frazer KA, Murray SS, Schork NJ, Topol EJ. 2009. Human genetic variation and its contribution to complex traits. Nat Rev Genet 10: 241-251
  12. Loktionov A. 2003. Common gene polymorphisms and nutrition: emerging links with pathogenesis of multifactorial chronic diseases. J Nutr Biochem 14: 426-451. https://doi.org/10.1016/S0955-2863(03)00032-9
  13. Amato R, Pinelli M, D'Andrea D, Miele G, Nicodemi M, Raiconi G, Cocozza S. 2010. A novel approach to simulate gene-environment interactions in complex diseases. BMC Bioinformatics 11: 8. https://doi.org/10.1186/1471-2105-11-8
  14. Hinney A, Vogel CI, Hebebrand J. 2010. From monogenic to polygenic obesity: recent advances. Eur Child Adolesc Psychiatry 19: 297-310. https://doi.org/10.1007/s00787-010-0096-6
  15. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, Singh GM, Gutierrez HR, Lu Y, Bahalim AN, Farzadfar F, Riley LM, Ezzati M; Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group (Body Mass Index). 2011. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet 377: 557-567. https://doi.org/10.1016/S0140-6736(10)62037-5
  16. Ministry of Health and Welfare. 2012. The Korea National Health and Nutrition Examination Survey (KNHANES V-3). Chungbuk, Korea.
  17. Reedy J, Krebs-Smith SM. 2010. Dietary sources of energy, solid fats, and added sugars among children and adolescents in the United States. J Am Diet Assoc 110: 1477-1484. https://doi.org/10.1016/j.jada.2010.07.010
  18. Giskes K, van Lenthe F, Avendano-Pabon M, Brug J. 2011. A systematic review of environmental factors and obesogenic dietary intakes among adults: are we getting closer to understanding obesogenic environments? Obes Rev 12: e95-e106. https://doi.org/10.1111/j.1467-789X.2010.00769.x
  19. Deram S, Villares SM. 2009. Genetic variants influencing effectiveness of weight loss strategies. Arq Bras Endocrinol Metabol 53: 129-138. https://doi.org/10.1590/S0004-27302009000200003
  20. Summerbell CD, Cameron C, Glasziou PP. 2008. WITHDRAWN: Advice on low-fat diets for obesity. Cochrane Database Syst Rev 16: CD003640.
  21. Alinia S1, Hels O, Tetens I. 2009. The potential association between fruit intake and body weight-a review. Obes Rev 10: 639-647. https://doi.org/10.1111/j.1467-789X.2009.00582.x
  22. Cargill M, Altshuler D, Ireland J, Sklar P, Ardlie K, Patil N, Shaw N, Lane CR, Lim EP, Kalyanaraman N, Nemesh J, Ziaugra L, Friedland L, Rolfe A, Warrington J, Lipshutz R, Daley GQ, Lander ES. 1999. Characterization of singlenucleotide polymorphisms in coding regions of human genes. Nat Genet 22: 231-238. https://doi.org/10.1038/10290
  23. den Dunnen JT, Antonarakis SE. 2001. Nomenclature for the description of human sequence variations. Hum Genet 109: 121-124. https://doi.org/10.1007/s004390100505
  24. Kruglyak L, Nickerson DA. 2001. Variation is the spice of life. Nat Genet 27: 234-236. https://doi.org/10.1038/85776
  25. Vakili S, Caudill MA. 2007. Personalized nutrition: nutritional genomics as a potential tool for targeted medical nutrition therapy. Nutr Rev 65: 301-315. https://doi.org/10.1111/j.1753-4887.2007.tb00308.x
  26. Lewis SN, Nsoesie E, Weeks C, Qiao D, Zhang L. 2011. Prediction of disease and phenotype associations from genome-wide association studies. PLoS One 6: e27175. https://doi.org/10.1371/journal.pone.0027175
  27. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, Hirschhorn JN. 2008. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet 9: 356-369. https://doi.org/10.1038/nrg2344
  28. Delahanty RJ, Beeghly-Fadiel A, Xiang YB, Long J, Cai Q, Wen W, Xu WH, Cai H, He J, Gao YT, Zheng W, Shu XO. 2011. Association of obesity-related genetic variants with endometrial cancer risk: a report from the Shanghai Endometrial Cancer Genetics Study. Am J Epidemiol 174: 1115-1126. https://doi.org/10.1093/aje/kwr233
  29. Gandhi S, Wood NW. 2010. Genome-wide association studies: the key to unlocking neurodegeneration? Nat Neurosci 13: 789-794. https://doi.org/10.1038/nn.2584
  30. Chial H, Craig J. 2008. Genome-wide association studies (GWAS) and obesity. Nature Education 1: 80
  31. Gresham D, Dunham MJ, Botstein D. 2008. Comparing whole genomes using DNA microarrays. Nat Rev Genet 9: 291-302 https://doi.org/10.1038/nrg2335
  32. Pearson TA, Manolio TA. 2008. How to interpret a genomewide association study. JAMA 299: 1335-1344. https://doi.org/10.1001/jama.299.11.1335
  33. Collins FS, Guyer MS, Chakravarti A. 1997. Variations on a theme: cataloging human DNA sequence variation. Science 278: 1580-1581. https://doi.org/10.1126/science.278.5343.1580
  34. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, Wichmann HE, Meitinger T, Hunter D, Hu FB, Colditz G, Hinney A, Hebebrand J, Koberwitz K, Zhu X, Cooper R, Ardlie K, Lyon H, Hirschhorn JN, Laird NM, Lenburg ME, Lange C, Christman MF. 2006. A common genetic variant is associated with adult and childhood obesity. Science 312: 279-283. https://doi.org/10.1126/science.1124779
  35. Lyon HN, Emilsson V, Hinney A, Heid IM, Lasky-Su J, Zhu X, Thorleifsson G, Gunnarsdottir S, Walters GB, Thorsteinsdottir U, Kong A, Gulcher J, Nguyen TT, Scherag A, Pfeufer A, Meitinger T, Bronner G, Rief W, Soto-Quiros ME, Avila L, Klanderman B, Raby BA, Silverman EK, Weiss ST, Laird N, Ding X, Groop L, Tuomi T, Isomaa B, Bengtsson K, Butler JL, Cooper RS, Fox CS, O'Donnell CJ, Vollmert C, Celedon JC, Wichmann HE, Hebebrand J, Stefansson K, Lange C, Hirschhorn JN. 2007. The association of a SNP upstream of INSIG2 with body mass index is reproduced in several but not all cohorts. PLos Genet 3: e61. https://doi.org/10.1371/journal.pgen.0030061
  36. Dina C, Meyre D, Samson C, Tichet J, Marre M, Jouret B, Charles MA, Balkau B, Froguel P. 2007. Comment on "a common genetic variant is associated with adult and childhood obesity". Science 315: 187.
  37. Andreasen CH, Mogensen MS, Borch-Johnsen K, Sandbaek A, Lauritzen T, Sorensen TI, Hansen L, Almind K, Jorgensen T, Pedersen O, Hansen T. 2008. Non-replication of genomewide based associations between common variants in INSIG2 and PFKP and obesity in studies of 18,014 Danes. PLoS ONE 3: e2872. https://doi.org/10.1371/journal.pone.0002872
  38. Hinney A, Nguyen TT, Scherag A, Friedel S, Bronner G, Muller TD, Grallert H, Illig T, Wichmann HE, Rief W, Schafer H, Hebebrand J. 2007. Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants. PLoS ONE 2: e1361. https://doi.org/10.1371/journal.pone.0001361
  39. Hunt SC, Stone S, Xin Y, Scherer CA, Magness CL, Iadonato SP, Hopkins PN, Adams TD. 2008. Association of the FTO gene with BMI. Obesity (Silver Spring) 16: 902-904. https://doi.org/10.1038/oby.2007.126
  40. Loos RJ, Lindgren CM, Li S, Wheeler E, Zhao JH, Prokopenko I, Inouye M, Freathy RM, Attwood AP, Beckmann JS, Berndt SI; Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, Jacobs KB, Chanock SJ, Hayes RB, Bergmann S, Bennett AJ, Bingham SA, Bochud M, Brown M, Cauchi S, Connell JM, Cooper C, Smith GD, Day I, Dina C, De S, Dermitzakis ET, Doney AS, Elliott KS, Elliott P, Evans DM, Sadaf Farooqi I, Froguel P, Ghori J, Groves CJ, Gwilliam R, Hadley D, Hall AS, Hattersley AT, Hebebrand J, Heid IM; KORA, Lamina C, Gieger C, Illig T, Meitinger T, Wichmann HE, Herrera B, Hinney A, Hunt SE, Jarvelin MR, Johnson T, Jolley JD, Karpe F, Keniry A, Khaw KT, Luben RN, Mangino M, Marchini J, McArdle WL, McGinnis R, Meyre D, Munroe PB, Morris AD, Ness AR, Neville MJ, Nica AC, Ong KK, O'Rahilly S, Owen KR, Palmer CN, Papadakis K, Potter S, Pouta A, Qi L; Nurses' Health Study, Randall JC, Rayner NW, Ring SM, Sandhu MS, Scherag A, Sims MA, Song K, Soranzo N, Speliotes EK; Diabetes Genetics Initiative, Syddall HE, Teichmann SA, Timpson NJ, Tobias JH, Uda M; SardiNIA Study, Vogel CI, Wallace C, Waterworth DM, Weedon MN; Wellcome Trust Case Control Consortium, Willer CJ; FUSION, Wraight, Yuan X, Zeggini E, Hirschhorn JN, Strachan DP, Ouwehand WH, Caulfield MJ, Samani NJ, Frayling TM, Vollenweider P, Waeber G, Mooser V, Deloukas P, McCarthy MI, Wareham NJ, Barroso I, Jacobs KB, Chanock SJ, Hayes RB, Lamina C, Gieger C, Illig T, Meitinger T, Wichmann HE, Kraft P, Hankinson SE, Hunter DJ, Hu FB, Lyon HN, Voight BF, Ridderstrale M, Groop L, Scheet P, Sanna S, Abecasis GR, Albai G, Nagaraja R, Schlessinger D, Jackson AU, Tuomilehto J, Collins FS, Boehnke M, Mohlke KL. 2008. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet 40: 768-775. https://doi.org/10.1038/ng.140
  41. Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM, Berndt SI, Elliott AL, Jackson AU, Lamina C, Lettre G, Lim N, Lyon HN, McCarroll SA, Papadakis K, Qi L, Randall JC, Roccasecca RM, Sanna S, Scheet P, Weedon MN, Wheeler E, Zhao JH, Jacobs LC, Prokopenko I, Soranzo N, Tanaka T, Timpson NJ, Almgren P, Bennett A, Bergman RN, Bingham SA, Bonnycastle LL, Brown M, Burtt NP, Chines P, Coin L, Collins FS, Connell JM, Cooper C, Smith GD, Dennison EM, Deodhar P, Elliott P, Erdos MR, Estrada K, Evans DM, Gianniny L, Gieger C, Gillson CJ, Guiducci C, Hackett R, Hadley D, Hall AS, Havulinna AS, Hebebrand J, Hofman A, Isomaa B, Jacobs KB, Johnson T, Jousilahti P, Jovanovic Z, Khaw KT, Kraft P, Kuokkanen M, Kuusisto J, Laitinen J, Lakatta EG, Luan J, Luben RN, Mangino M, McArdle WL, Meitinger T, Mulas A, Munroe PB, Narisu N, Ness AR, Northstone K, O'Rahilly S, Purmann C, Rees MG, Ridderstrale M, Ring SM, Rivadeneira F, Ruokonen A, Sandhu MS, Saramies J, Scott LJ, Scuteri A, Silander K, Sims MA, Song K, Stephens J, Stevens S, Stringham HM, Tung YC, Valle TT, Van Duijn CM, Vimaleswaran KS, Vollenweider P, Waeber G, Wallace C, Watanabe RM, Waterworth DM, Watkins N; Wellcome Trust Case Control Consortium, Witteman JC, Zeggini E, Zhai G, Zillikens MC, Altshuler D, Caulfield MJ, Chanock SJ, Farooqi IS, Ferrucci L, Guralnik JM, Hattersley AT, Hu FB, Jarvelin MR, Laakso M, Mooser V, Ong KK, Ouwehand WH, Salomaa V, Samani NJ, Spector TD, Tuomi T, Tuomilehto J, Uda M, Uitterlinden AG, Wareham NJ, Deloukas P, Frayling TM, Groop LC, Hayes RB, Hunter DJ, Mohlke KL, Peltonen L, Schlessinger D, Strachan DP, Wichmann HE, McCarthy MI, Boehnke M, Barroso I, Abecasis GR, Hirschhorn JN; Genetic Investigation of ANthropometric Traits Consortium. 2009. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 41: 25-34. https://doi.org/10.1038/ng.287
  42. Thorleifsson G, Walters GB, Gudbjartsson DF, Steinthorsdottir V, Sulem P, Helgadottir A, Styrkarsdottir U, Gretarsdottir S, Thorlacius S, Jonsdottir I, Jonsdottir T, Olafsdottir EJ, Olafsdottir GH, Jonsson T, Jonsson F, Borch-Johnsen K, Hansen T, Andersen G, Jorgensen T, Lauritzen T, Aben KK, Verbeek AL, Roeleveld N, Kampman E, Yanek LR, Becker LC, Tryggvadottir L, Rafnar T, Becker DM, Gulcher J, Kiemeney LA, Pedersen O, Kong A, Thorsteinsdottir U, Stefansson K. 2009. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat Genet 41: 18-24. https://doi.org/10.1038/ng.274
  43. Meyre D, Delplanque J, Chevre JC, Lecoeur C, Lobbens S, Gallina S, Durand E, Vatin V, Degraeve F, Proenca C, Gaget S, Korner A, Kovacs P, Kiess W, Tichet J, Marre M, Hartikainen AL, Horber F, Potoczna N, Hercberg S, Levy-Marchal C, Pattou F, Heude B, Tauber M, McCarthy MI, Blakemore AI, Montpetit A, Polychronakos C, Weill J, Coin LJ, Asher J, Elliott P, Jarvelin MR, Visvikis-Siest S, Balkau B, Sladek R, Balding D, Walley A, Dina C, Froguel P. 2009. Genome-wide association study for early-onset and morbid adult obesity identifies three new risk loci in European populations. Nat Genet 41: 157-159. https://doi.org/10.1038/ng.301
  44. Raqib R, Cravioto A. 2009. Nutrition, immunology, and genetics: future perspectives. Nutr Rev 67: S227-S236. https://doi.org/10.1111/j.1753-4887.2009.00244.x
  45. Fenech M. 2008. Genome health nutrigenomics and nutrigenetics-diagnosis and nutritional treatment of genome damage on an individual basis. Food Chem Toxicol 46: 1365-1370. https://doi.org/10.1016/j.fct.2007.06.035
  46. Panagiotou G, Nielsen J. 2009. Nutritional systems biology: definitions and approaches. Annu Rev Nutr 29: 329-339. https://doi.org/10.1146/annurev-nutr-080508-141138
  47. Rimbach G, Minihane AM. 2009. Nutrigenetics and personalised nutrition: how far have we progressed and are we likely to get there? Proc Nutr Soc 68: 162-172. https://doi.org/10.1017/S0029665109001116
  48. Sonestedt E, Roos C, Gullberg B, Ericson U, Wirfalt E, Orho-Melander M. 2009. Fat and carbohydrate intake modify the association between genetic variation in the FTO genotype and obesity. Am J Clin Nutr 90: 1418-1425. https://doi.org/10.3945/ajcn.2009.27958
  49. Warodomwichit D, Shen J, Arnett DK, Tsai MY, Kabagambe EK, Peacock JM, Hixson JE, Straka RJ, Province MA, An P, Lai CQ, Parnell LD, Borecki IB, Ordovas JM. 2009. ADIPOQ polymorphisms, monounsaturated fatty acids, and obesity risk: the GOLDN study. Obesity (Silver Spring) 17: 510-517. https://doi.org/10.1038/oby.2008.583
  50. Phillips CM, Goumidi L, Bertrais S, Field MR, McManus R, Hercberg S, Lairon D, Planells R, Roche HM. 2011. Gene-nutrient interactions and gender may modulate the association between ApoA1 and ApoB gene polymorphisms and metabolic syndrome risk. Atherosclerosis 214: 408-414. https://doi.org/10.1016/j.atherosclerosis.2010.10.029
  51. Doo MA, Kim YH. 2011. Association between ESR1 rs1884051 polymorphism and dietary total energy and plant protein intake on obesity in Korean men. Nutr Res Pract 5: 527-532. https://doi.org/10.4162/nrp.2011.5.6.527
  52. Cha SW, Koo IH, Park BL, Jeong SK, Choi SM, Kim KS, Shin HD, Kim JY. 2011. Genetic effects of FTO and MC4R polymorphisms on body mass in constitutional types. Evid Based Complement Alternat Med 2011: 106390.
  53. Lee HJ, Kim IK, Kang JH, Ahn YJ, Han BG, Lee JY, Song JH. 2010. Effects of common FTO gene variants associated with BMI on dietary intake and physical activity in Koreans. Clin Chim Acta 411: 1716-1722. https://doi.org/10.1016/j.cca.2010.07.010
  54. Kim IC, Cha MH, Kim DM, Lee HY, Moon JS, Choi SM, Kim KS, Yoon YS. 2011. A functional promoter polymorphism -607G>C of WNT10B is associated with abdominal fat in Korean female subjects. J Nutr Biochem 22: 252-258. https://doi.org/10.1016/j.jnutbio.2010.02.002

Cited by

  1. An infection of human adenovirus 31 affects the differentiation of preadipocytes into fat cells, its metabolic profile and fat accumulation vol.88, pp.3, 2016, https://doi.org/10.1002/jmv.24362
  2. The future of nutrition: Nutrigenomics and nutrigenetics in obesity and cardiovascular diseases 2017, https://doi.org/10.1080/10408398.2017.1349731
  3. Association between exonic polymorphism (rs629849, Gly1619Arg) of <i>IGF2R</i> gene and obesity in Korean population vol.11, pp.5, 2015, https://doi.org/10.12965/jer.150239
  4. Lycium barbarum Reduces Abdominal Fat and Improves Lipid Profile and Antioxidant Status in Patients with Metabolic Syndrome vol.2017, 2017, https://doi.org/10.1155/2017/9763210
  5. The role of nutrition related genes and nutrigenetics in understanding the pathogenesis of cancer vol.4, pp.3, 2016, https://doi.org/10.1016/j.jmau.2016.02.002
  6. A Narrative Review of Obesity and Its Associated Complications in Iranian Women vol.In Press, pp.In Press, 2017, https://doi.org/10.17795/whb-40546
  7. )) and dietary intake in pregnant women vol.120, pp.4, 2018, https://doi.org/10.1017/S0007114518001423
  8. Genomic Influence in the Prevention of Cardiovascular Diseases with a Sterol-Based Treatment vol.6, pp.2, 2018, https://doi.org/10.3390/diseases6020024
  9. The Interaction between Genetic Polymorphisms in FTO and TCF7L2 Genes and Dietary Intake with Regard to Body Mass and Composition: An Exploratory Study vol.9, pp.1, 2019, https://doi.org/10.3390/jpm9010011
  10. Congenic mice demonstrate the presence of QTLs conferring obesity and hypercholesterolemia on chromosome 1 in the TALLYHO mouse vol.28, pp.11, 2015, https://doi.org/10.1007/s00335-017-9719-2
  11. The State of Nutrigenomic Education in Poland vol.11, pp.2, 2015, https://doi.org/10.1159/000494332
  12. High Maternal Body Mass Index Is Associated with an Early-Onset of Overweight/Obesity in Pre-School-Aged Children in Malawi. A Multilevel Analysis of the 2015-16 Malawi Demographic and Health Survey vol.65, pp.2, 2015, https://doi.org/10.1093/tropej/fmy028
  13. The FTO genetic variants are associated with dietary intake and body mass index amongst Emirati population vol.14, pp.10, 2015, https://doi.org/10.1371/journal.pone.0223808
  14. Perioperative Heart-Brain Axis Protection in Obese Surgical Patients: The Nutrigenomic Approach vol.27, pp.2, 2020, https://doi.org/10.2174/0929867325666181015145225
  15. Dietary Patterns and Their Associations With the FTO and FGF21 Gene Variants Among Emirati Adults vol.8, pp.None, 2021, https://doi.org/10.3389/fnut.2021.668901
  16. Natural Extracts to Augment Energy Expenditure as a Complementary Approach to Tackle Obesity and Associated Metabolic Alterations vol.11, pp.3, 2021, https://doi.org/10.3390/biom11030412
  17. Polyphenols and obesity prevention: critical insights on molecular regulation, bioavailability and dose in preclinical and clinical settings vol.61, pp.11, 2015, https://doi.org/10.1080/10408398.2020.1765736
  18. Waistline to the gumline: Relationship between obesity and periodontal disease‐biological and management considerations vol.87, pp.1, 2015, https://doi.org/10.1111/prd.12390
  19. Hypothalamic-pituitary hormones will be affected by the interaction between 5q13-14-rs2239670 (CARTPT) gene variants and diet in different obesity phenotypes vol.14, pp.1, 2015, https://doi.org/10.1186/s13104-021-05857-5