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Association Between Genetic Variants Linked to Premature Ovarian Insufficiency and Inflammatory Markers: A Cross-Sectional Study

Abstract

Background: Premature menopause (PM) is the cessation of ovarian function before age 40. PM women are more likely to have cardiovascular diseases (CVDs), diabetes, and mental disorders. This is the first study that assessed the association of single nucleotide polymorphisms (SNPs) with anti-heat shock protein 27 (Hsp27), High-sensitivity C-reactive protein (hs- CRP), and PM and serum pro-oxidant-antioxidant balance (PAB), as putative risk factors for CVDs. We aimed to explore the association of oxidative stress markers with eight different SNPs shown to be related to premature menopause.

Materials And Methods: In this cross-sectional research, we included 183 healthy women and 117 premature menopausal women. We determined baseline characteristics for all participants and measured serum hs-CRP, anti-HSP-27 antibody titer, and PAB levels using the established methods. Genotyping for eight SNPs was done using the tetra amplification refractory mutation system polymerase chain reaction (Tetra-ARMS PCR) and allele-specific oligonucleotide PCR (ASO-PCR) methods.

Results: We found a significant difference between mean serum PAB levels and the genetic variant of rs16991615 (P=0.03). ANCOVA showed a significant effect of the genotypes rs4806660 and rs10183486 on hs-CRP serum levels in the case and control groups, respectively (P=0.04 and P=0.007). ANCOVA also showed an association between rs244715 genotypes and anti-hsp27 serum levels in the case group (P=0.02). There was a significant effect of the genotypes of rs451417 on the serum hs-CRP level in the control group (P=0.03).

Conclusion: There was a significant association of the genetic variants related to PM with oxidative stress and inflammatory markers (serum PAB, anti-hsp27 antibody, and hs-CRP). Accordingly, this seems to be an effective approach to predicting susceptible subjects for cardiovascular and mental disorders as well as various cancers.

Citing Articles

Drosophila modeling to identify causative genes and reveal the underlying molecular mechanisms for primary ovarian insufficiency.

Ma Y, Liu Y, Xu M, Yin X, Hu C, Yang X J Mol Med (Berl). 2025; 103(2):239-253.

PMID: 39853375 DOI: 10.1007/s00109-025-02516-1.

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