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

小桶 代谢组学 代谢物 代谢组 医学 生物 内科学 内分泌学 遗传学 生物信息学 基因 基因表达 转录组
作者
Nana Huang,Hai Jiang,Youzhen Zhang,Xiya Sun,Yixin Li,Yuan Wei,Jing Yang,Yangyu Zhao
出处
期刊:Clinical Nutrition [Elsevier]
卷期号:43 (1): 111-123
标识
DOI:10.1016/j.clnu.2023.11.002
摘要

Summary

Background & aims

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.

Methods

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.

Results

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.

Conclusion

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.
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