ArticleMedicine2025
Causal associations between 1400 circulating metabolites and spontaneous abortion: A bidirectional 2-sample Mendelian randomization study.
Article in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Spontaneous abortion (SA) affects approximately 10% to 15% of clinically recognized pregnancies. The potential causal role of metabolic disturbances in SA remains poorly defined. We performed a bidirectional 2-sample Mendelian randomization (MR) analysis to evaluate causal associations between 1400 plasma metabolites and SA. Genetic instruments for metabolites were obtained from a genome-wide association study of 8299 individuals from the Canadian longitudinal study on aging. Summary statistics for SA were derived from the FinnGen R12 dataset, including 23,167 cases and 1,99,279 controls. Primary MR analyses used the inverse variance weighted method, with MR-Egger, weighted median, Mendelian Randomization Pleiotropy RESidual Sum and Outlier, and leave-one-out analyses conducted to assess robustness. Thirty-six circulating metabolites showed significant causal associations with SA. Key findings included protective associations for phenylacetylglutamine (odds ratio [OR], 0.89; 95% confidence interval [CI], 0.83-0.96; P = .0019) and risk-enhancing effects for the glycerol-to-carnitine ratio (OR, 1.07; 95% CI: 1.03-1.12; P = .0021), 1-methyl-5-imidazoleacetate (OR, 1.09; 95% CI: 1.03-1.16; P = .0040), and the caffeine-to-theophylline ratio (OR, 1.08; 95% CI: 1.03-1.15; P = .0041). Sensitivity analyses showed no evidence of horizontal pleiotropy or heterogeneity. Reverse MR identified 5 metabolites potentially influenced by genetic predisposition to SA, though forward causal effects were more prominent. This study provides genetic evidence supporting a causal role of specific circulating metabolites in the pathophysiology of SA. These findings offer novel mechanistic insights into early pregnancy loss and highlight potential biomarkers for reproductive risk stratification and targeted intervention.
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