From proteome to pathogenesis: investigating polycystic ovary syndrome with Mendelian randomization analysis

被引:0
作者
Zhang, Jiaqi [1 ]
Li, Yuqing [2 ]
Gong, Aixia [1 ]
Wang, Jingmin [2 ]
机构
[1] Dalian Med Univ, Affiliated Hosp 1, Dept Digest Endoscopy, Dalian, Liaoning, Peoples R China
[2] Dalian Med Univ, Affiliated Hosp 1, Dept Obstet & Gynecol, Dalian, Liaoning, Peoples R China
来源
FRONTIERS IN ENDOCRINOLOGY | 2024年 / 15卷
关键词
polycystic ovary syndrome; metabolism; proteome; Mendelian randomization; bioinformatics; ALPHA GENE POLYMORPHISMS; INSULIN-RESISTANCE; PERIPHERAL-BLOOD; ELEVATED CDCP1; PCOS; EXPRESSION; CELLS; INFLAMMATION; WOMEN; SUSCEPTIBILITY;
D O I
10.3389/fendo.2024.1442483
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Polycystic ovary syndrome (PCOS) is defined by oligo/anovulation, hyperandrogenism, and polycystic ovaries with uncertain pathogenesis. The proteome represents a substantial source of therapeutic targets, and their coding genes may elucidate the mechanisms underlying PCOS. However, reports on the profiles of the human plasma protein-coding genes and PCOS are limited. Here, we aimed to investigate novel biomarkers or drug targets for PCOS by integrating genetics and the human plasma proteome.Methods Our study acquired the protein quantitative trait loci from DECODE Genetics, offering 4,907 proteins in 35,559 individuals while obtaining PCOS summary statistics by accessing the FinnGen biobank (1,639 cases and 218,970 controls) and the genome-wide association study catalog (797 cases and 140,558 controls). Herein, we sequentially used two-sample Mendelian randomization (MR) analyses and colocalization to verify the causal link between candidate proteins, their coding genes, and PCOS. Further PCOS data download was conducted by accessing the Gene Expression Omnibus and Zenodo platforms. Gene expression level analysis, pathway enrichment analysis, immune cell infiltration, and transcription factor prediction were performed, aiming at detecting specific cell types with enriched expression and exploring potential optimized treatments for PCOS.Results MR analysis revealed 243 protein-coding genes with a causal relationship to PCOS risk, of which 12 were prioritized with the most significant evidence. Through colocalization analysis, three key genes, CUB domain-containing protein 1 (CDCP1), glutaredoxin 2 (GLRX2), and kirre-like nephrin family adhesion molecule 2 (KIRREL2), were identified. Subsequently, the three genes were strongly related to immune function and metabolism in terms of biological significance. In single-cell analysis, the expression levels of genes in ovarian theca cells were explored.Conclusion Overall, three protein-coding genes (CDCP1, GLRX2, and KIRREL2) may be related to a higher PCOS risk, suggesting that they may be entry points for exploration of PCOS pathogenesis and treatment, warranting further clinical investigations.
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页数:16
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