Polycystic ovary syndrome (PCOS), a prevalent reproductive disorder in women of reproductive age, features androgen excess, ovulatory dysfunction, and polycystic ovaries. Despite its high prevalence, specific pharmacologic intervention for PCOS is challenging. In this study, we identified artemisinins as anti-PCOS agents. Our finding demonstrated the efficacy of artemisinin derivatives in alleviating PCOS symptoms in both rodent models and human patients, curbing hyperandrogenemia through suppression of ovarian androgen synthesis. Artemisinins promoted cytochrome P450 family 11 subfamily A member 1 (CYP11A1) protein degradation to block androgen overproduction. Mechanistically, artemisinins directly targeted lon peptidase 1 (LONP1), enhanced LONP1-CYP11A1 interaction, and facilitated LONP1-catalyzed CYP11A1 degradation. Overexpression of LONP1 replicated the androgen-lowering effect of artemisinins. Our data suggest that artemisinin application is a promising approach for treating PCOS and highlight the crucial role of the LONP1-CYP11A1 interaction in controlling hyperandrogenism and PCOS occurrence.

Background: The association between subclinical hypothyroidism (SCH) and polycystic ovary syndrome (PCOS) has been reported in several studies，but it is not well recognized. The aim of this study was to evaluate the prevalence of SCH in women with PCOS. Methods: An extensive literature search was conducted in PubMed, Embase, Web of Science, and Cochrane Library databases. All articles published before May 2018 was considered for eligibility. No language restrictions were implemented. The prevalence of SCH in PCOS was performed by the meta-analysis to produce an odds ratio (OR) with 95% confidence interval (CI). Results: A total of 6 studies including 692 PCOS patients and 540 controls were eligible for the meta-analysis. The combined odds ratio (OR) of SCH risk for women with PCOS compared with controls was 2.87 (95% CI=1.82-9.92; P <0.000001). The OR increased to 3.59 when limiting TSH cut-off. Conclusions: This meta-analysis demonstrated that women with PCOS were more likely to develop SCH.

The treatment of polycystic ovary syndrome (PCOS) faces challenges as all known treatments are merely symptomatic. The US Food and Drug Administration has not approved any drug specifically for treating PCOS. As the significance of genetics and epigenetics rises in drug development, their pivotal insights have greatly enhanced the efficacy and success of drug target discovery and validation, offering promise for guiding the advancement of PCOS treatments. In this context, we outline the genetic and epigenetic advancement in PCOS, which provide novel insights into the pathogenesis of this complex disease. We also delve into the prospective method for harnessing genetic and epigenetic strategies to identify potential drug targets and ensure target safety. Additionally, we shed light on the preliminary evidence and distinctive challenges associated with gene and epigenetic therapies in the context of PCOS.

BACKGROUND: Ovarian aging occurs earlier than the aging of many other organs and has a lasting impact on women’s overall health and well-being. However, effective interventions to slow ovarian aging remain limited, primarily due to an incomplete understanding of the underlying molecular mechanisms and drug targets. Recent advances in omics data resources, combined with innovative computational tools, are offering deeper insight into the molecular complexities of ovarian aging, paving the way for new opportunities in drug discovery and development. OBJECTIVE AND RATIONALE: This review aims to synthesize the expanding multi-omics data, spanning genome, transcriptome, proteome, metabolome, and microbiome, related to ovarian aging, from both tissue-level and single-cell perspectives. We will specially explore how the analysis of these emerging omics datasets can be leveraged to identify novel drug targets and guide therapeutic strategies for slowing and reversing ovarian aging. SEARCH METHODS: We conducted a comprehensive literature search in the PubMed database using a range of relevant keywords: ovarian aging, age at natural menopause, premature ovarian insufficiency (POI), diminished ovarian reserve (DOR), genomics, transcriptomics, epigenomics, DNA methylation, RNA modification, histone modification, proteomics, metabolomics, lipidomics, microbiome, single-cell, genome-wide association studies (GWAS), whole-exome sequencing, phenome-wide association studies (PheWAS), Mendelian randomization (MR), epigenetic target, drug target, machine learning, artificial intelligence (AI), deep learning, and multi-omics. The search was restricted to English-language articles published up to September 2024. OUTCOMES: Multi-omics studies have uncovered key mechanisms driving ovarian aging, including DNA damage and repair deficiencies, inflammatory and immune responses, mitochondrial dysfunction, and cell death. By integrating multi-omics data, researchers can identify critical regulatory factors and mechanisms across various biological levels, leading to the discovery of potential drug targets. Notable examples include genetic targets such as BRCA2 and TERT, epigenetic targets like Tet and FTO, metabolic targets such as sirtuins and CD38+, protein targets like BIN2 and PDGF-BB, and transcription factors such as FOXP1. WIDER IMPLICATIONS: The advent of cutting-edge omics technologies, especially single-cell technologies and spatial transcriptomics, has provided valuable insights for guiding treatment decisions and has become a powerful tool in drug discovery aimed at mitigating or reversing ovarian aging. As technology advances, the integration of single-cell multi-omics data with AI models holds the potential to more accurately predict candidate drug targets. This convergence offers promising new avenues for personalized medicine and precision therapies, paving the way for tailored interventions in ovarian aging. REGISTRATION NUMBER: Not applicable.

Context: Extensive studies have provided considerable evidence suggesting the role of inflammation in the development of female reproductive diseases. However, causality has not been established.Objective: To explore whether genetically determined circulating levels of cytokines are causally associated with female reproductive diseases and discover potential novel drug targets for these diseases.Methods: Instrumental variables (IVs) for 47 circulating cytokines were obtained from a genome-wide association study (GWAS) meta-analysis of 31 112 European individuals. Protein quantitative trait loci and expression quantitative trait loci close to genes served as our IVs. Summary data of 9 female reproductive diseases were mainly derived from GWAS meta-analysis of the UK biobank and FinnGen. We elevated the association using the Wald ratio or inverse variance–weighted Mendelian randomization (MR) with subsequent assessments for MR assumptions in several sensitivity and colocalization analyses. We consider a false discovery rate <0.05 as statistical significance in MR analyses. Replication studies were conducted for further validation, and phenome-wide association studies were designed to explore potential side effects.Results: Our results indicated that high levels of macrophage colony-stimulating factor (MCSF), growth-regulated oncogene-alpha (GROα), and soluble intercellular adhesion molecule-1 were associated with increased risks of endometriosis, female infertility, and pre-eclampsia, respectively. High platelet-derived growth factor-BB (PDGF-BB) levels that reduced the risk of ovarian aging were also supported. Replication analysis supported the relationship between GROα and female infertility, and between MCSF and endometriosis.Conclusion: We identified 4 correlated pairs that implied potential protein drug targets. Notably, we preferred highlighting the value of PDGF-BB as a drug target for ovarian aging, and MCSF as a drug target for endometriosis.