Mapping the Genomic Architecture of Obesity: Frequency Landscape of Six Metabolic Variants in Mexico City

Obesity is a major public health challenge worldwide, defined as a body mass index (BMI) of thirty kilograms per square meter or higher. In Mexico, the public health crisis is acute, with the country ranking second among Organization for Economic Co-operation and Development (OECD) nations in adult obesity prevalence. National data from the National Health and Nutrition Survey (ENSANUT) indicate that over seventy-five percent of Mexican adults live with overweight or obesity, driven by rapid dietary shifts toward processed foods, socioeconomic factors, and strong genetic susceptibility with heritability reaching up to seventy percent.

While genome-wide association studies (GWAS) have identified numerous single nucleotide variants (SNVs) linked to metabolic traits in European and Asian populations, data regarding genetically admixed groups remain limited. Published in Frontiers in Genetics in 2026, this descriptive cross-sectional population genetic study addresses this gap. By evaluating an urban cohort from Mexico City, researchers established baseline frequency data for six key metabolic variants within the FTO, ANKK1/DRD2, MC4R, FABP2, ADRB2, and SH2B1 genes.

Highlights

• Simultaneous Multi-gene Panel Screening: Concurrent characterization of six single nucleotide variants governing distinct physiological pathways, including central appetite regulation, reward processing, intestinal lipid transport, adipocyte lipolysis, and insulin signaling.
• High analytical precision: Deployment of real-time quantitative polymerase chain reaction (qPCR) using TaqMan minor groove binder (MGB) probe assays, achieving over ninety-nine percent analytical sensitivity and specificity with genotyping call rates above ninety-eight percent.
• Sex-stratified demographic control: Systematic evaluation across male and female subgroups to evaluate potential sex-specific genetic drift or selection bias in the urban sample.
• Multi-population comparative benchmarking: Direct comparison of local genotypic frequencies against regional Mexican cohorts and continental reference groups from the 1000 Genomes Project to assess population admixture.

Key Findings

The study analyzed a cohort of one hundred twenty-nine unrelated Mexican adults in Mexico City, comprising fifty-nine females and seventy males aged eighteen to eighty-seven years. The selected genetic loci and their molecular characteristics are summarized in Tab.1.

Tab.1 Overview of selected genetic variants associated with obesity and metabolic traits. (Perezcano, et al., 2026)

• Primary Genotypic and Allelic Frequencies

Genotypic and allelic distributions across the six single nucleotide variants revealed substantial variability in minor allele frequencies (MAF), ranging from a high of 0.41 down to 0.12. As presented in Tab.2, all six variants successfully conformed to Hardy-Weinberg equilibrium expectations (p > 0.05 by exact test), confirming the absence of severe genotyping error or non-random mating within the cohort.

Tab.2 Distribution of genotypes for six obesity-associated genetic variants in the study population. (Perezcano, et al., 2026)

• SH2B1 rs4788102 (G>A): Displayed the highest minor allele frequency in the cohort. As detailed in Tab.2, the major G allele frequency was 0.59 (count n = 151), while the minor A allele frequency reached 0.41 (count n = 107; 95% confidence interval [CI]: 0.35 to 0.47). Genotype counts were 43 homozygotes for G/G (0.33), 65 heterozygotes for G/A (0.51), and 21 homozygotes for A/A (0.16).
• ANKK1/DRD2 rs1800497 (C>T, Taq1A): The major C allele frequency was 0.68 (count n = 176), and the minor T allele frequency was 0.32 (count n = 82; 95% CI: 0.27 to 0.37). Genotype distributions were 61 for C/C (0.47), 54 for C/T (0.42), and 14 for T/T (0.11).
• FTO rs9939609 (T>A): The major T allele frequency was 0.69 (count n = 179), whereas the minor risk A allele frequency was 0.31 (count n = 79; 95% CI: 0.25 to 0.36). Genotype counts in Tab.2 revealed 62 individuals with T/T (0.48), 55 with T/A (0.43), and 12 with A/A (0.09).
• ADRB2 rs1042714 (G>C): The major G allele frequency was 0.75 (count n = 193), and the minor C allele frequency was 0.25 (count n = 65; 95% CI: 0.20 to 0.31). Genotype distributions were 71 for G/G (0.55), 51 for G/C (0.40), and 7 for C/C (0.05).
• FABP2 rs1799883 (A>G, Ala54Thr): The major A allele frequency was 0.76 (count n = 196), and the minor G allele frequency was 0.24 (count n = 62; 95% CI: 0.19 to 0.30). Genotype counts were 72 for A/A (0.56), 52 for A/G (0.40), and 5 for G/G (0.04).
• MC4R rs17782313 (T>C): Displayed the lowest minor allele frequency among all loci. The major T allele frequency was 0.88 (count n = 226), while the minor C allele frequency was 0.12 (count n = 32; 95% CI: 0.09 to 0.17). Genotype counts showed 99 for T/T (0.77), 28 for T/C (0.22), and 2 for C/C (0.01).

• Sex-Stratified Comparative Analysis

Evaluation across fifty-nine females and seventy males showed consistent allele proportions across sexes:

• FTO rs9939609: Female A allele MAF = 0.31 vs. male A allele MAF = 0.30.
• ANKK1/DRD2 rs1800497: Female T allele MAF = 0.30 vs. male T allele MAF = 0.33.
• MC4R rs17782313: Female C allele MAF = 0.11 vs. male C allele MAF = 0.13.
• FABP2 rs1799883: Female G allele MAF = 0.21 vs. male G allele MAF = 0.26.
• ADRB2 rs1042714: Female C allele MAF = 0.21 vs. male C allele MAF = 0.29.
• SH2B1 rs4788102: Female A allele MAF = 0.39 vs. male A allele MAF = 0.44.

Fisher's exact testing with Benjamini-Hochberg false discovery rate (FDR) adjustment confirmed no significant differences between sexes for any variant (p > 0.05), supporting combined population analyses.

• Global and Regional Genetic Landscape Comparison

Comparison with global 1000 Genomes reference data and regional Mexican cohorts revealed clear population genetic patterns:

• FTO rs9939609: Central Mexico MAF (0.31) matches Western Mexico (0.31 and 0.30) but is double Southern Mexico (0.16). Internationally, it sits between European (0.4135) and East Asian (0.1687) frequencies.
• ANKK1/DRD2 rs1800497: Observed MAF (0.32) aligns with 1000 Genomes global (0.3257) and American (0.3110) panels, while remaining lower than Western (0.4110) and Southern (0.4400) Mexican cohorts.
• MC4R rs17782313: MAF (0.12) matches Western Mexico (0.12) and 1000 Genomes American panels (0.1340), but is lower than European (0.2396), African (0.2776), or South Asian (0.3200) groups.
• FABP2 rs1799883: MAF (0.24) mirrors Western Mexico (0.27) and American reference panels (0.2310), while standing below South Asian samples (0.48).
• ADRB2 rs1042714: MAF (0.25) aligns with American panels (0.2420), between East Asian (0.0734) and European (0.4095) populations.
• SH2B1 rs4788102: MAF (0.41) matches American ancestry panels (0.4860) and European groups (0.3290), but exceeds East Asian (0.1260) and African (0.2247) cohorts.

Research Approaches & Support

Further investigation in genomic epidemiology, population genetics, and nutrigenomics requires robust approaches for genetic variant analysis, population stratification, and metabolic phenotyping. To support these research efforts, Protheragen provides high-throughput TaqMan SNP genotyping with customized assay design. In parallel, metabolic biomarker profiling can support the quantitative assessment of lipid profiles, glucose homeostasis markers, and relevant hormonal signals, helping researchers integrate genetic variation with metabolic phenotypes and explore potential gene–nutrition–metabolism relationships.

Interpretation & Translational Value

The findings of this population genetic study emphasize that obesity risk alleles carry population-specific frequencies shaped by historical admixture between Indigenous American and European ancestries. Recognizing the precise baseline frequencies of single nucleotide variants across the FTO, ANKK1/DRD2, MC4R, FABP2, ADRB2, and SH2B1 genes is essential for accurately calibrating polygenic risk scores, mapping metabolic biological pathways, and designing targeted nutrigenomic interventions. By demonstrating that genetic risk distribution does not significantly differ by sex in urban Mexico City, this research establishes an objective baseline to guide future large-scale genomic epidemiology studies, precision prevention frameworks, and personalized public health strategies tailored to Latin American populations.