Amniotic fluid metabolic fingerprinting contributes to shaping the unfavourable intrauterine environment in monochorionic diamniotic twins

Abstract

Amniotic fluid (AF) is the primary intrauterine environment for fetal growth throughout gestation. Selective fetal growth restriction (sFGR) is an adverse complication characterized by unequal growth in twins with nearly identical genetic makeup. However, the influence of AF-mediated intrauterine environment on the development and progression of sFGR remains unexplored. High-throughput targeted metabolomics analysis (G350) was performed on AF samples collected from sFGR (n=18) and MCDA twins with birth weight concordance (MCDA-C, n=20) cases. Weighted correlation network analysis (WGCNA) was used to identify clinical features that may influence the metabolite composition in AF. Subsequently, partial least-squares discriminant analysis (PLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to compare the different types of sFGR and MCDA-C twins. Receiver operating characteristic (ROC) and multivariate ROC curves were utilized to explore potential AF markers in twins with sFGR. In our study, 182 metabolites were quantified in 76 AF samples. WGCNA indicated that the metabolite composition in late AF may not be influenced by gestational age. PLSDA demonstrated distinct variations between the metabolite profiles of AF in the sFGR and MCDA-C twins, with a significant emphasis on amino acids as the primary differential metabolite. The dissimilarities observed in sFGR twins were predominantly attributed to lipid metabolism-related metabolites. In particular, the KEGG enrichment metabolic pathway analysis revealed significant associations of both types of sFGR twins with central carbon metabolism in cancer. The multivariate ROC curves indicated that the combination of carnosine, sarcosine, l-alanine, beta-alanine, and alpha-n-phenylacetylglutamine significantly improved the AUC to 0.928. Notably, the ROC curves highlighted creatine (AUC:0.934) may be a potential biomarker for severe sFGR. The data presented in this study offer a comprehensive metabolic map of the AF in cases of sFGR, shedding light on potential biomarkers associated with fetal growth and development in MCDA twins.