Maternal blood lipidomics analyses link critical metabolic pathways associated with severe preeclampsia

Preeclampsia is a pregnancy specific syndrome characterized by hypertension and proteinuria after 20 weeks of gestation. To reveal the relationship between lipids and preeclampsia, we conduct lipidomic profiling of maternal serums of 44 severe preeclamptic and 20 healthy pregnancies from a multi-ethnic cohort in Hawaii. Correlation network analysis shows that oxidized phospholipids (OxPLs) have increased inter-correlations and connections in preeclampsia, while other lipids, including triacylglycerols (TAGs), have reduced network correlations and connections. Thirty-one lipid species from various lipid classes demonstrate predominantly reductions and causal relationships with preeclampsia. They include phosphatidylglycerol (PG), TAG, diacylglycerol (DAG), phosphatidylcholine (PC), cholesterol esters (CE), phosphatidylethanolamine (PE), sphingomyelin (SM), ceramides (Cer-NS), hexosyl ceramides (HexCer-NS), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), and free fatty acid (FFA). Many of these lipids are also selected as important features by a linear discriminant analysis (LDA) classifier with high predictive accuracy (F-1 statistic 0.941 and balanced accuracy 0.88), indicating their potential to serve as biomarkers for severe preeclampsia. Our study supports the hypothesis of a phospholipid (PL) centered, dysregulated lipidomic metabolic atlas. That is, severe preeclampsia may be originated from hypoxia, which induces the accumulation of OxPLs through oxidative stress whereas reduces many other lipids (eg. reduced PCs, TAGs and ceramides). These molecular changes coherently lead to dysregulated biological functions, such as insulin signaling and inflammation/infections. Moreover, the lipid changes may also be responsible for the comorbidity between preeclampsia and gestational diabetes, a clinically known risk factor for preeclampsia. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement LXG is supported by grants K01ES025434 awarded by NIEHS through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative ([www.bd2k.nih.gov][1]), R01 LM012373 and LM012907 awarded by NLM, R01 HD084633 (LXG and SS) awarded by NICHD. SS is supported by, NIH grants, R01 LM012595, U01 DK097430, U01 CA200147, U01 CA198941, U19 AI090023, R01 HL106579, R01 HL108735, R01 HD084633, R01 DK109365, NSF CCF-0939370, and a Welcome-Trust Award. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the Western IRB board (WIRB Protocol 20151223). All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The lipidomics data set has been deposited to Metabolomic Workbench, a public repository of metabolomics, under the study ID ST001360. [1]: http://www.bd2k.nih.gov