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Abstract
Background: Obesity is influenced by both environmental and genetic factors, including variation in the melanocortin-4 receptor (MC4R) gene, which plays a role in appetite regulation and energy balance. Identifying genetic risks, particularly whether obesity linked to inherited dysregulation of appetite, is crucial for early intervention and personalized prevention strategies.
Objectives: This study aimed to examine the association between MC4R genotype and body fat percentage as an indicator of obesity among Indonesian adults.
Methods: A cross-sectional study was conducted among 79 Indonesian adults aged 21–56 years in Jakarta. Participants were consecutively recruited and screened based on predefined inclusion and exclusion criteria. Anthropometric data, including height and weight, were obtained using a standardized stadiometer and digital scale to calculate body mass index (BMI). Body fat percentage (BFP) was assessed using bioelectrical impedance analysis (BIA) with an Omron Karada Scan device. Genomic DNA was extracted from venous blood samples, and the MC4R rs17782313 polymorphism was genotyped using the polymerase chain reaction– fragment length polymorphism (PCR-RFLP) method. Statistical analyses were performed to assess the association between genotypes and body fat percentages.
Results: Most participants were classified as overweight (36.1%) or obese (41.7%) based on BMI. The genotypic distribution of rs17782313 was TT (48.1%), CT (39.2%), and CC (12.7%). Higher body fat percentages were significantly more common among individuals carrying the C allele. The CC genotype demonstrated the strongest association with obesity, with an odds ratio (OR) of 4.00 (95% CI: 1.02–15.64, p=0.04) compared to the wild-type TT genotype.
Conclusion: Variations in the MC4R rs17782313 gene are associated with increased body fat percentage and a higher risk of obesity among Indonesian adults. Individuals carrying the risk allele may have greater susceptibility to excess fat accumulation, underscoring the importance of incorporating genetic factors into obesity prevention and management strategies.
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Copyright (c) 2026 Meutia Atika Faradilla, Yohana Yohana, Deasyka Yastani, Astri Handayani, Suweino Suweino

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