VEGFA rs2010963 (−634G>C) Genotype Patterns Across Obesity Grades: An Exploratory Aggregate-Data Study with Implications for Polycystic Ovary Syndrome Research

N. N. Tursunova *

Department of Obstetrics and Gynecology, Samarkand State Medical University, Samarkand, Uzbekistan.

*Author to whom correspondence should be addressed.


Abstract

Background: Angiogenic signalling is biologically relevant to polycystic ovary syndrome (PCOS) and placental adaptation, but evidence linking VEGFA sequence variants to reproductive complications is inconsistent. Obesity may complicate interpretation of such genetic studies.

Objective: To examine whether aggregated VEGFA rs2010963 (−634G>C) genotype distributions differed between an obesity-stratified study group and a comparison group, and across three obesity grades.

Methods: We reanalysed genotype counts supplied in three summary tables. The obesity-stratified group included 60 individuals (grade I, n=25; grade II, n=30; grade III, n=5); the comparison group included 50. Allele frequencies were reconstructed from diploid genotype counts. Exact Hardy–Weinberg equilibrium (HWE) tests, Fisher tests for binary genotype contrasts, and Monte Carlo Fisher–Freeman–Halton tests for multi-category tables were used. No patient-level pregnancy or PCOS-status records were available for this genetic dataset.

Results: GG, GC and CC genotypes occurred in 42 (70.0%), 15 (25.0%) and 3 (5.0%) participants in the obesity-stratified group versus 30 (60.0%), 18 (36.0%) and 2 (4.0%) in the comparator. The overall 2×3 genotype comparison was not statistically significant (Monte Carlo exact P=0.464). The odds ratio for GG versus GC/CC was 1.56 (95% CI 0.71–3.43; Fisher P=0.317). Variation across obesity grades was not statistically conclusive (3×3 exact Monte Carlo P=0.118). In grade III obesity, the sample comprised only five individuals.

Conclusion: These aggregate data do not establish a reproducible association between rs2010963 and obesity grade. They support careful design of future studies integrating validated PCOS phenotyping, angiogenic biomarkers and pregnancy outcomes; they cannot substantiate a clinical prediction or prevention algorithm.

Keywords: VEGFA, rs2010963, −634G>C, obesity, polycystic ovary syndrome, angiogenesis, genotype distribution, exploratory analysis


How to Cite

Tursunova, N. N. 2026. “VEGFA rs2010963 (−634G>C) Genotype Patterns Across Obesity Grades: An Exploratory Aggregate-Data Study With Implications for Polycystic Ovary Syndrome Research”. Journal of Advances in Medicine and Medical Research 38 (11):163-69. https://doi.org/10.9734/jammr/2026/v38i116244.

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