Distribution of Polymorphisms Associated With Obesity in a Sample of Admixed Mexican Adults
; Ruderman, Anahí
; Chacón Duque, Juan Camilo ; Adhikari, Kaustubh ; Bortolini, María Cátira ; Acuña Alonzo, Victor ; Canizales Quinteros, Samuel ; Gallo, Carla ; Poletti, Giovanni ; Rothhammer, Francisco ; Rojas, Winston ; Ruiz-Linares, Andres ; Gonzalez-Jose, Rolando 
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Fecha
03/2026
Editorial
Wiley-liss, div John Wiley & Sons Inc.
Revista
American Journal of Human Biology
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Institución organizadora
ISSN
1042-0533
eISSN
1520-6300
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Inglés
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Resumen
Objective: In Mexico, two-thirds of the adult population are overweight and almost a quarter are affected by obesity. These high obesity rates are primarily attributed to low-nutrient,high-calorie diets, reduced physical activity, and to a certain extent, genetic factors. Most genetic variants for obesity risk have been identified through studies based predominantly on European populations. This study examines the roles of subcontinental ancestry, genetic polymorphisms, and socio-environmental factors in anthropometric measures within an admixed Mexican population.Methods: We analyzed a sample of 1195 adult volunteers from the CANDELA consortium. Regression models were used to assess the influence of subcontinental Native American ancestries, socioeconomic level (education and SES), and genetic background on body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Polygenic risk scores (PRS) wereconstructed for each index using established alleles. Results: An increase in obesity indices was significantly associated with a higher proportion of Native American ancestry, particularly waist-to-hip ratio. Polygenic risk scores were significantly associated with all indices, with BMI showing the highest risk. The effect of obesity scores was not influenced by ancestry on any of the evaluated indices, although the average frequency of risk alleles was slightly inversely correlated with higher Native American ancestry content. Conclusions: This study highlights the challenges of assessing genetic predisposition to complex disease in admixed populations, where numerous factors contribute to observed differences, emphasizing the need to consider regional genetic diversity in obesity research.
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