DOI: 10.3390/biomedicines14071470 ISSN: 2227-9059

Genetic Diversity Analysis of Risk Variants Associated with Bone and Cartilage Metabolism in Nine Mexican Subpopulations

Ismael Nuño-Arana, Alejandra Villagómez Vega, Gabriela Martínez Cortés

Backgrounds/Objectives: Allele frequencies of genetic variants associated with complex diseases can contribute to varying degrees to predisposition depending on the population’s genetic profile. The aim of this study was to analyze the genetic diversity of 15 relevant SNVs that could modulate bone and cartilage metabolism in underrepresented structured populations. Methods: In a sample of 130 Mestizos and 304 natives from 8 native Mexican populations, SNVs related to multifactorial diseases were genotyped using a SNaPShot Multiplex kit and analyzed via capillary electrophoresis using an ABI PrismTM 3130 Genetic Analyzer (Applied Biosystems, Waltham, MA, USA.), and genetic profiles for 15 SNVs were obtained using GeneMapper software v. 3.2. Allele frequencies were calculated by locus and population using Power Stats and Arlequin v.3.1 software, for which the EM algorithm was used to compare reference populations obtained from the dbSNV database of the International HapMap project. Population structure, paired comparisons, and genetic differentiation between native, admixed, and reference populations (p value) were estimated through Fst tests using the STRUCTURE v.2.3.2 and Arlequin v.3.1 software. Results: Haplotype frequency combinations grouped as profiles showed higher predominance in the allelic combination A/A/G for rs9340799 (ESR1), rs700518 (CYP19A1), and rs1800795 (IL6) genes, respectively. Conclusions: Allelic profiles could be useful as medical tools for preventing and managing individuals or populations. Mexican populations showed high genetic variability among allelic risk profiles for estrogen control and response, as well as high frequencies of variant combinations associated with an increased inflammatory response, potentially resulting in high osteoclastogenesis. This analysis advances our understanding of the complexity of bone and cartilage metabolism in highly stratified populations.

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