Investigação da relação de marcadores moleculares nos genes TCF2L7, ADBR3 e FTO com os parâmetros bioquímicos e antropométricos
##plugins.themes.bootstrap3.article.main##
Resumo
Objetivo: Selecionar e analisar de maneira sistemática, trabalhos nos quais a avaliação da correlação entre polimorfismos e medidas antropométricas e bioquímicas eram discutidas. Métodos: Trata-se de uma revisão integrativa, com base nas recomendações da Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) e utilizando da base de dados da PubMed com os SNPs, sendo possível inserir um SNP de interesse no campo de busca e ter acesso somente às publicações referentes a esse marcador genético específico, o período dos trabalhos pesquisados foi de 2017 a 2021. Resultados: Com base na estratégia de busca, foram identificados 96 trabalhos na plataforma PubMed, constatou-se que algumas alterações genéticas (mudança de base) podem influenciar no desenvolvimento de fenótipos associados a doenças como diabetes e obesidade, entre os trabalhos analisados, um exemplo foi os SNPs rs7901695 e rs12255372 no gene TCF7L2 com a transcrição encontrada para a regulação de glicose, resultando em uma suscetibilidade para DM2. Considerações finais: Fatores epigenéticos podem agir influenciando o fenótipo juntamente com os fatores genéticos, ademais, deve-se considerar a heterogeneidade genética e diferença entre as populações na investigação da associação de polimorfismos e expressão gênica associada a doenças não transmissíveis.
##plugins.themes.bootstrap3.article.details##
Copyright © | Todos os direitos reservados.
A revista detém os direitos autorais exclusivos de publicação deste artigo nos termos da lei 9610/98.
Reprodução parcial
É livre o uso de partes do texto, figuras e questionário do artigo, sendo obrigatória a citação dos autores e revista.
Reprodução total
É expressamente proibida, devendo ser autorizada pela revista.
Referências
2. BEGO T, et al. Association of FTO gene variant (rs8050136) with type 2 diabetes and markers of obesity, glycaemic control and inflammation. Journal of medical biochemistry. 2019; 38(2): 153–163.
3. BOUTARI C e MANTZOROS CS. A 2022 update on the epidemiology of obesity and a call to action: as its twin COVID-19 pandemic appears to be receding, the obesity and dysmetabolism pandemic continues to rage on. Metabolism. 2022; 133: 155217.
4. CHEN B, et al. Association of fat mass and obesity-associated and retinitis pigmentosa guanosine triphosphatase (GTPase) regulator-interacting protein-1 like polymorphisms with body mass index in Chinese women. Endocrine jornal. 2018: 65(7): 783–791.
5. DAGHESTANI M, et al. ADRB3 polymorphism rs4994 (Trp64Arg) associates significantly with bodyweight elevation and dyslipidaemias in Saudis but not rs1801253 (Arg389Gly) polymorphism in ARDB1. Lipids in health and disease. 2018; 17(1).
6. DUICU C, et al. FTO rs 9939609 SNP Is Associated With Adiponectin and Leptin Levels and the Risk of Obesity in a Cohort of Romanian Children Population. Medicine (Baltimore). 2016; 95.
7. GALVÃO TF, et al. Principais itens para relatar Revisões sistemáticas e Meta-análises: A recomendação PRISMA. Epidemiol. Serv. Saúde. 2015; 24.
8. O´BEIRNE SL, et al. Type 2 Diabetes Risk Allele Loci in the Qatari Population. PLoS One. 2016; 11.
9. GU Z. et al. FTO polymorphisms are associated with metabolic dysfunction-associated fatty liver disease (MAFLD) susceptibility in the older Chinese Han population. Clinical interventions in aging. 2020; 15: 1333–1341.
10. KHAN SM, et al. Association between type 2 diabetes mellitus & TCF7L2 gene variants in the Emirati population: Genetics of diabetes in the United Arab Emirates. National Library of Medicine: American Journal of Human Biology. 2020; 33.
11. HOSSEINI FE, et al. Dietary patterns modify the association between fat mass and obesity-associated genetic variants and changes in obesity phenotypes. The British journal of nutrition. 2019; 121(11): 1247–1254.
12. KOOCHAKPOUR G, et al. Evaluating the interaction of common FTO genetic variants, added sugar, and trans-fatty acid intakes in altering obesity phenotypes. Nutrition, metabolism, and cardiovascular diseases: NMCD. 2019; 29(5): 474–480.
13. LÓPEZ GR, et al. Common polymorphisms in MC4R and FTO genes are associated with BMI and metabolic indicators in Mexican children: Differences by sex and genetic ancestry. Gene. 2020; 754: 144840.
14. PRADEEPA R e MOHAN V. Epidemiology of type 2 diabetes in India. Indian Journal of Ophthalmology. 2021; 69.
15. RANASINGHE P, et al. The range of non-traditional anthropometric parameters to define obesity and obesity-related disease in children: a systematic review. European journal of clinical nutrition. 2020; 373–384.
16. RANA S e BHATTI AA. Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis. Sci Rep. 2021; 11.
17. REDDY A, et al. Intron-specific single nucleotide polymorphisms of Fat mass and obesity- associated gene in obese and overweight individuals of the Indian adult population- A pilot study. Current diabetes reviews. 2019; 16(1): 84–94.
18. REDONDO MJ, et al. TCF7L2 Genetic Variants Contribute to Phenotypic Heterogeneity of Type 1 Diabetes. National Library of Medicine. 2018; 41: 311-317.
19. SAKAMOTO Y, et al. Beta-3-adrenergic receptor rs4994 polymorphism is a potential biomarker for the development of nonalcoholic fatty liver disease in overweight/obese individuals. Disease markers. 2019; 4065327.
20. SAKLAYEN MG. The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep, 2018; 20.
21. SALINAS SMA, et al. Assessment of biochemical parameters and characterization of TNFα -308G/A and PTPN22 +1858C/T gene polymorphisms in the risk of obesity in adolescents. Biomedical Reports. 2015; 107-111.
22. SEDAGHATI KB, et al. Lack of association between FTO gene variations and metabolic healthy obese (MHO) phenotype: Tehran Cardio-metabolic Genetic Study (TCGS). Eating and weight disorders. 2018; 25(1): 25-35.
23. SINGH S, et al. Clinical Prediction of Type 2 Diabetes Mellitus (T2DM) via Anthropometric and Biochemical Variations in Prakriti. Diseases. 2022; 10.
24. TARNOWSKI M, et al. Effect of FTO and IGF2BP2 gene polymorphisms on duration of pregnancy and Apgar scores in women with gestational diabetes. Journal of obstetrics and gynaecology: the journal of the Institute of Obstetrics and Gynaecology. 2019; 39(2): 151–156.
25. VALADARES LTS, et al. Prevalence of metabolic syndrome in Brazilian adults in the last 10 years: a systematic review and meta-analysis. BMC Public Health. 2022; 22.
26. WANG K, et al. A genome-wide association study on obesity and obesity-related traits. PLoS One. 2011; 6.
27. ZAFAR U. et al. Adrenergic receptor beta-3 rs4994 (T>C) and liver X receptor alpha rs12221497 (G>A) polymorphism in Pakistanis with metabolic syndrome. The Chinese journal of physiology. 2019; 62(5): 196–202.
28. ZAHARAN NL, et al. Non-synonymous single-nucleotide polymorphisms and physical activity interactions on adiposity parameters in Malaysian adolescents. Frontiers in endocrinology. 2018; 9: 00209.
29. ZHAO F, et al. The Uyghur population and genetic susceptibility to type 2 diabetes: potential role for variants in CAPN10, APM1 and FUT6 genes. Journal of Cellular and Molecular Medicine. 2016; 20: 2138-2147.