Maternal plasma lipids are involved in the pathogenesis of preterm birth

Author:

Chen Yile1,He Bing1,Liu Yu1,Aung Max T2,Rosario-Pabón Zaira3,Vélez-Vega Carmen M3,Alshawabkeh Akram4,Cordero José F5,Meeker John D6,Garmire Lana X1ORCID

Affiliation:

1. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48105, USA

2. Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, School of Medicine, San Francisco, CA 94158, USA

3. University of Puerto Rico Graduate School of Public Health, UPR Medical Sciences Campus, San Juan, Puerto Rico 365067, Spain

4. College of Engineering, Northeastern University, Boston, MA 02115, USA

5. Department of Epidemiology and Biostatistics, University of Georgia, Athens, GA 30602, USA

6. Department of Environmental and Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA

Abstract

Abstract Background Preterm birth is defined by the onset of labor at a gestational age shorter than 37 weeks, and it can lead to premature birth and impose a threat to newborns’ health. The Puerto Rico PROTECT cohort is a well-characterized prospective birth cohort that was designed to investigate environmental and social contributors to preterm birth in Puerto Rico, where preterm birth rates have been elevated in recent decades. To elucidate possible relationships between metabolites and preterm birth in this cohort, we conducted a nested case-control study to conduct untargeted metabolomic characterization of maternal plasma of 31 women who experienced preterm birth and 69 controls who underwent full-term labor at 24–28 gestational weeks. Results A total of 333 metabolites were identified and annotated with liquid chromatography/mass spectrometry. Subsequent weighted gene correlation network analysis shows that the fatty acid and carene-enriched module has a significant positive association (P = 8e−04, FDR = 0.006) with preterm birth. After controlling for potential clinical confounders, a total of 38 metabolites demonstrated significant changes uniquely associated with preterm birth, where 17 of them were preterm biomarkers. Among 7 machine-learning classifiers, the application of random forest achieved a highly accurate and specific prediction (AUC = 0.92) for preterm birth in testing data, demonstrating their strong potential as biomarkers for preterm births. The 17 preterm biomarkers are involved in cell signaling, lipid metabolism, and lipid peroxidation functions. Additional modeling using only the 19 spontaneous preterm births (sPTB) and controls identifies 16 sPTB markers, with an AUC of 0.89 in testing data. Half of the sPTB overlap with those markers for preterm births. Further causality analysis infers that suberic acid upregulates several fatty acids to promote preterm birth. Conclusions Altogether, this study demonstrates the involvement of lipids, particularly fatty acids, in the pathogenesis of preterm birth.

Funder

National Institute of Environmental Health Sciences

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

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