Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology · 2025
Associations between 1400 metabolites and subtypes of endometriosis: a two-sample Mendelian randomisation study.
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Yan Fei, Chen Zhouxiang, Wu Lingfeng, Huang Zongju
Аннотация
BACKGROUND: Endometriosis is a chronic inflammatory disease with a prevalence of approximately 10% in women of childbearing age. Metabolic pathways have been demonstrated by previous studies to be potential avenues for the development of new therapeutic strategies and may be used for early diagnosis of the disease. This study aimed to investigate the potential causal relationships between 1400 metabolites and various endometriosis subtypes using Mendelian randomisation (MR) analysis.
METHODS: Data from a genome-wide association study were analysed. MR analysis was performed using the inverse-variance weighted, MR-Egger, and weighted-median methods, accompanied by heterogeneity testing, sensitivity analysis, and pleiotropy analysis. Metabolic-pathway enrichment analysis was conducted on the preliminarily screened differential metabolites, and colocalisation analysis was subsequently performed for exposure-outcome pairs that remained causally associated after multiple-testing correction.
RESULTS: After multiple-testing correction, only the glycerol-to-palmitoylcarnitine (C16) ratio reduced the risk of stage 1-2 endometriosis (PFDR = 0.045; odds ratio [OR], 0.737; 95% confidence interval [CI], 0.638-0.852) and pelvic peritoneal endometriosis (PFDR = 0.039; OR, 0.721; 95% CI, 0.619-0.841). Colocalisation analysis revealed that they did not share causal variant loci at the genetic level. No reverse causal associations were found in the reverse Mendelian analysis. Metabolic pathway enrichment analysis identified major metabolic pathways, including caffeine metabolism, glutathione metabolism, arginine biosynthesis, sphingolipid metabolism, pantothenate and CoA biosynthesis, plasmalogen synthesis, and biosynthesis of unsaturated fatty acids.
CONCLUSIONS: Our study suggests potential causal relationships between metabolites and various endometriosis subtypes from an MR perspective. However, the limited number of associations that survived multiple-testing correction indicates that these findings are preliminary and require validation in larger cohorts. This exploratory analysis may contribute to advancing future research on metabolomics-based diagnosis, treatment, and prevention of endometriosis.
METHODS: Data from a genome-wide association study were analysed. MR analysis was performed using the inverse-variance weighted, MR-Egger, and weighted-median methods, accompanied by heterogeneity testing, sensitivity analysis, and pleiotropy analysis. Metabolic-pathway enrichment analysis was conducted on the preliminarily screened differential metabolites, and colocalisation analysis was subsequently performed for exposure-outcome pairs that remained causally associated after multiple-testing correction.
RESULTS: After multiple-testing correction, only the glycerol-to-palmitoylcarnitine (C16) ratio reduced the risk of stage 1-2 endometriosis (PFDR = 0.045; odds ratio [OR], 0.737; 95% confidence interval [CI], 0.638-0.852) and pelvic peritoneal endometriosis (PFDR = 0.039; OR, 0.721; 95% CI, 0.619-0.841). Colocalisation analysis revealed that they did not share causal variant loci at the genetic level. No reverse causal associations were found in the reverse Mendelian analysis. Metabolic pathway enrichment analysis identified major metabolic pathways, including caffeine metabolism, glutathione metabolism, arginine biosynthesis, sphingolipid metabolism, pantothenate and CoA biosynthesis, plasmalogen synthesis, and biosynthesis of unsaturated fatty acids.
CONCLUSIONS: Our study suggests potential causal relationships between metabolites and various endometriosis subtypes from an MR perspective. However, the limited number of associations that survived multiple-testing correction indicates that these findings are preliminary and require validation in larger cohorts. This exploratory analysis may contribute to advancing future research on metabolomics-based diagnosis, treatment, and prevention of endometriosis.