16 cases of LCMSMS organization raw data.zip

<b><i>Background</i></b><b>: </b>Unexplained recurrent spontaneous abortion (URSA) is a complex pregnancy complication contributing to high miscarriage rate, which posed a heavy family and social burden. The lack of molecular mechanism affecting URSA lead to the limited effective treatment methods, we aimed to explore the underlying pathogenesis of URSA through the metabonomic and bioinformatics technology.<b><i>Methods</i></b>: The decidual tissues samples of 8 URSA and 8 normal pregnancy decidual tissues were used for the liquid chromatography-mass spectrum (LC-MS) testing by using the metabolomics software Progenesis QI. We used the Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) for differential metabolites analysis and the Human Metabolome Database (HMDB) was used for pathway enrichment analysis. The KEGG pathway topological analysis was used for pathway importance, and the differential proteins were identified by the Fold change difference. Finally, the metabolic network was visualized by using the Cytoscape tool.<b><i>Results</i></b>: After LC-MS testing and quality control, the samples in the same group had highly consistency associated with good reliability. The differential metabolites between NC and URSA groups involved in five type biological process and the glycerophospholipid metabolism contained the greatest number of differential metabolites. KEGG enrichment pathway of group difference showed that the glycerophospholipid metabolism, bile secretion, and choline metabolism pathways existed significantly difference and the glycerophospholipid metabolism had higher pathway importance in pathway topological analysis. There are 65 overlapping pathways between proteome and metabolome, and finally the key genes of <i>PLD1</i>, <i>CHPT1</i> and <i>PLA2G2A </i>in<i> </i>glycerophospholipid metabolism pathway were identified.<b><i>Conclusion</i></b>: We performed the LC-MS analysis and identified the glycerophospholipid metabolism pathway and its three key genes affecting URSA progression. Our findings provide novel insights into the treatment strategy of URSA.