Genetic Variation’s Impact on Weight: Systematic Review and Meta-Analysis
Abstract
This study investigates the genetic factors influencing precision weight management, contributing insights to the enduring debate on hereditary versus environmental influences on obesity. The primary objective is to identify genetic variations as predictive markers for weight management and evaluate their impact on weight control. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guideline, this research systematically reviews articles that meet specific criteria, with no specific timeline due to limited research on genetic variation in this context. Inclusion criteria mandate the provision of weight and BMI data at the beginning and end of interventions, demonstrating weight reduction. Exclusions cover animal studies, non-English papers, and articles lacking baseline or pre/post-intervention data. The review incorporates comprehensive searches on Scopus, Medline, PubMed, and Web of Science, employing Review Manager for meta-analysis. The study concentrates on Single Nucleotide Polymorphisms (SNPs) rs9939609, rs10830963, and rs1052700 across 10 investigations. Despite lacking statistical significance, the findings suggest that these genetic polymorphisms enhance weight loss potential for recessive genotypes. A discernible preference for non-risk genotypes in weight loss efforts emerges. For instance, individuals with the non-risk A allele of rs9939609 experience weight loss with a Polyunsaturated Fatty Acid (PUFA) diet, while those with the non-risk G allele of rs10830963 effectively manage weight with a low-fat diet. Similarly, rs1052700 indicates that individuals with the T allele shed more weight by consuming meals earlier during the day. Although statistically insignificant, the non-risk genotype for all three SNPs demonstrates potential for weight loss. This suggests that participants possessing the non-risk allele can effectively manage their weight through interventions provided by weight loss programs.
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