Novel variants in women with premature ovarian function decline identified via whole-exome sequencing
Other
OA: closed
AI-generated summary
Whole-exome sequencing of women with premature ovarian insufficiency and diminished ovarian reserve identified polygenic variants in genes regulating follicular development and meiosis, revealing shared genetic backgrounds between these conditions.
One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works
Abstract
PURPOSE: To investigate the potential etiologies of premature ovarian insufficiency (POI) and diminished ovarian reserve (DOR).
METHODS: Fourteen women with sporadic POI and 6 women with DOR were enrolled. We used whole-exome sequencing (WES) and bioinformatics analysis to identify variants in a subset of 599 selected POI candidate genes. The identified genes were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and protein-protein interaction (PPI) network analyses to uncover key genes and pathways.
RESULTS: Among the 20 patients, 79 heterozygous variants were detected in 49 genes, which were classified as "likely pathogenic" or "variants of uncertain significance" according to the guidelines of the American College of Medical Genetics and Genomics. Most patients (17/20) carried two or more variants. Monoacylglycerol O-acyltransferase 1 mutations were found in six patients, and cytochrome P450 family 26 subfamily B member 1 and Bardet-Biedl syndrome 9 mutations were each found in four patients. Some variants were shared between DOR and POI. Enrichment analyses showed that the identified genes participate in key ovarian processes, such as follicular development, gonadal development, meiosis, Fanconi anemia, homologous recombination, and transforming growth factor β signaling. A PPI network revealed interactions between these proteins.
CONCLUSION: Premature ovarian function decline may be polygenic, and overlap exists between the genetic backgrounds of DOR and POI. WES and in silico analyses may be a useful clinical tool for etiological diagnosis and risk prediction for high-risk women in the future.
My notes (saved in your browser only)
MeSH descriptors
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
Source provenance
- europepmc
- last seen: 2026-10-11T09:27:45.537177+00:00
- pubmed
- last seen: 2026-10-08T21:28:11.599399+00:00