The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Front Endocrinol (Lausanne). 2024 Sep 27;15:1335106. doi: 10.3389/fendo.2024.1335106. eCollection 2024.
More and more studies have found that polycystic ovary syndrome (PCOS) is significantly associated with recurrent spontaneous abortion (RSA), but the specific mechanism is not yet clear.
Based on the GEO database, we downloaded the PCOS (GSE10946, GSE6798 and GSE137684) and RSA (GSE165004, GSE26787 and GSE22490) datasets and performed differential analysis, weighted gene co-expression network (WGCNA), functional enrichment, and machine learning, respectively, on the datasets of the two diseases, Nomogram and integrated bioinformatics analysis such as immune infiltration analysis. Finally, the reliability of the diagnostic gene was verified by external verification and collection of human specimens.
In this study, PCOS and RSA datasets were obtained from Gene Expression Omnibus (GEO) database, and a total of 23 shared genes were obtained by differential analysis and WGCNA analysis. GO results showed that the shared genes were mainly enriched in the functions of lipid catabolism and cell cycle transition (G1/S). DO enrichment revealed that shared genes are mainly involved in ovarian diseases, lipid metabolism disorders and psychological disorders. KEGG analysis showed significant enrichment of Regulation of lipolysis in adipocytes, Prolactin signaling pathway, FoxO signaling pathway, Hippo signaling pathway and other pathways. A diagnostic gene FAM166 B was obtained by machine learning and Nomogram screening, which mainly played an important role in Cellular component. GSEA analysis revealed that FAM166B may be involved in the development of PCOS and RSA by regulating the cell cycle, amino acid metabolism, lipid metabolism, and carbohydrate metabolism. CIBERSORT analysis showed that the high expression of FAM166 B was closely related to the imbalance of multiple immune cells. Further verification by qPCR suggested that FAM166 B could be used as a common marker of PCOS and RSA.
In summary, this study identified FAM166B as a common biomarker for PCOS and RSA, and conducted in-depth research and analysis of this gene, providing new data for basic experimental research and early prognosis, diagnosis and treatment of clinical diseases.
越来越多的研究发现多囊卵巢综合征（PCOS）与复发性自然流产（RSA）显著相关，但具体机制尚不清楚。
基于 GEO 数据库，我们下载了 PCOS（GSE10946、GSE6798 和 GSE137684）和 RSA（GSE165004、GSE26787 和 GSE22490）数据集，并分别对两种疾病的数据集进行差异分析、加权基因共表达网络（WGCNA）、功能富集和机器学习，如Nomogram 和免疫浸润分析等综合生物信息学分析。最后，通过外部验证和人类标本收集来验证诊断基因的可靠性。
本研究从基因表达综合数据库（GEO）中获取 PCOS 和 RSA 数据集，通过差异分析和 WGCNA 分析共获得 23 个共有基因。GO 结果显示，共有基因主要富集在脂质代谢和细胞周期转换（G1/S）的功能中。DO 富集表明，共有基因主要参与卵巢疾病、脂质代谢紊乱和心理障碍。KEGG 分析显示，脂肪细胞脂解调节、催乳素信号通路、FoxO 信号通路、 Hippo 信号通路等通路显著富集。通过机器学习和 Nomogram 筛选获得了一个诊断基因 FAM166B，该基因主要在细胞成分中发挥重要作用。GSEA 分析表明，FAM166B 可能通过调节细胞周期、氨基酸代谢、脂质代谢和碳水化合物代谢参与 PCOS 和 RSA 的发生。CIBERSORT 分析表明，FAM166B 的高表达与多种免疫细胞的失衡密切相关。qPCR 进一步验证表明，FAM166B 可作为 PCOS 和 RSA 的共同标志物。
综上所述，本研究鉴定 FAM166B 为 PCOS 和 RSA 的共同生物标志物，并对该基因进行了深入研究和分析，为基础实验研究和临床疾病的早期预后、诊断和治疗提供了新的数据。
