Integrated analysis of transcriptomic datasets to identify placental biomarkers of spontaneous preterm birth

Abstract

Introduction: Preterm birth (PTB) remains the leading cause of neonatal morbidity and mortality in the United States. The mechanisms underlying spontaneous PTB (SPTB) involve multiple physiological processes and molecular transformations at the level of the placenta. This study aimed to identify consistent molecular correlates in the placenta linked with SPTB by cross-examining publicly available transcriptomic datasets within two publicly available repositories.

Methods: The National Center for Biotechnology Information and the European Bioinformatics Institute were queried, and relevant datasets were independently normalized, and then merged based on similarity in design. Differentially expressed genes between SPTB and term delivery (TD) were identified using a fixed effects linear model (p < 0.0001) and were evaluated for enrichment of biological processes and pathways. In general, global signatures associated with SPTB were unique to each study.

Results: A total of three datasets were used in the meta-analysis to assess the placental transcriptome in SPTB (11 samples) as compared to TD (15 samples). We identified 174 differentially expressed genes consistently correlated with SPTB across all studies, including previously proposed and new candidate biomarkers of SPTB. Differentially expressed genes were significantly enriched for master regulatory pathways relevant to placental development and disease, including chromatin organization and cellular response to stress.

Discussion: Identification of differentially expressed genes and associated pathways across multiple studies may identify transcriptomic biomarkers that can be applied in clinical investigations of SPTB and provide researchers enhanced insight into the underlying etiologies of SPTB.

Keywords: Epigenetics; Placenta; Pregnancy; Preterm birth; Stress; Transcriptome.