Lidan Liu, Bo Liu, Ming Liao, Bin Zeng, Lang Qin, Mujun Li
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引用次数: 0
Abstract
Purpose: The relationship between metabolites and female infertility is unclear. This study employed a bidirectional Mendelian randomization analysis to determine the causal relationship between metabolites and female infertility.
Method: The causal relationship between 1,400 metabolites and female infertility was analyzed using publicly available GWAS data. Significant SNPs were selected as instrumental variables (IVs), with those in linkage disequilibrium (LD) or with an F-statistic below 10 excluded to ensure validity. Independent GWAS datasets for metabolites and infertility were used to avoid sample overlap. The primary method employed was inverse-variance weighted (IVW). Heterogeneity and pleiotropy were assessed, and the results were further validated using single SNP and leave-one-out analyses.
Results: The phosphate to mannose ratio, X-17,654 levels, 1-palmitoleoyl-GPC (16:1) levels, glucose-to-mannose ratio,androstenediol (3alpha, 17alpha) monosulfate (3) levels, 3-methylglutaconate levels, octadecadienedioate (C18:2-DC) levels, bilirubin degradation product, C17H18N2O4 (2) levels, 3-methylglutarylcarnitine (2) levels, eicosenedioate (C20:1-DC) levels, and the phosphate-to-mannose ratio were positively associated with the risk of female infertility. the adenosine 5'-diphosphate (ADP)-to-citrate ratio, 2,2'-methylenebis(6-tert-butyl-p-cresol) levels, sphingomyelin (d18:2/16:0, d18:1/16:1) levels, bilirubin degradation product, C16H18N2O5 (3) levels, and the mannose to trans-4-hydroxyproline ratio were negatively associated with the risk of female infertility. No reverse causal link was identified between metabolites and female infertility.
Conclusion: A significant causal association was identified between 16 specific metabolites and female infertility, with 11 metabolites increasing the risk of infertility, while the other 5 exhibited a protective effect.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.