Genetically predicted triglyceride levels and endometriosis risk: Mendelian randomization with exploratory multi-omics analyses
This study explored the genetic evidence linking triglyceride-related pathways and lipid-lowering drug targets with endometriosis risk and investigated the genetic association between TG levels and EM. Using genome-wide association study (GWAS) data, a two-sample Mendelian randomization (MR) analysis was conducted, estimating the association between genetically predicted TG levels and EM risk (OR = 1.1853, 95% CI: 1.070–1.313, p = 0.0011). Seven TG-lowering drug target genes ( SLC9A1, SCN3A, VEGFA, APOA1, TNF, ITGAV, BACE1 ) were identified. Transcriptome analysis revealed that SCN3A, BACE1, and APOA1 were significantly upregulated in EM patients compared to healthy controls. Enrichment pathway analysis showed that these genes are involved in lipid transport, localization, cell adhesion, and blood vessel development. PPARA was predicted to act as a transcription factor for five of these genes, while estrogen receptor 1 (ESR1) was predicted to regulate the majority of the others. Among the TG inhibitors examined, fibrate-related targets showed relatively broader target coverage in the present genetic analyses. These findings suggest that TG-related pathways and lipid-lowering drug targets, particularly fibrate-related targets, may be relevant to EM biology and warrant further experimental and clinical validation.
Authors
- Mengsha Qi (ORCID: https://orcid.org/0000-0002-9304-2183)
- 贾芝茂
- Yonghong Li
- Jianan He
- Min Yang
- Shuyun Liu
- Yuanqing Zhang
- Yidan Fan
Institutions
- University of Electronic Science and Technology of China (CN)
- Chengdu Medical College (CN)
- Maternal and Child Health Hospital of Sichuan Province (CN)
- Sichuan Provincial Library (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2026-08-13
- DOI
- https://doi.org/10.1371/journal.pone.0356100
- Primary Topic
- Endometriosis Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Department of Science and Technology of Sichuan Province