323 - Specialized proresolving lipid bioactive-related pathways may play a role in neonatal adiposity: A placental lipidomics and transcriptomics study

Publication Number: 3312.323

Carmen Monthe-dreze, Women & Infants Hospital of Rhode Island, Providence, RI, United States; Perrie O'Tierney-Ginn, Tufts University School of Medicine, Boston, MA, United States; Sarbattama Sen, Women & Infants Hospital of Rhode Island, providence, RI, United States

Background: A pro-inflammatory lipotoxic fetal environment may underpin excess fetal adiposity, a risk factor for metabolic syndrome in offspring. Deficiencies of specialized pro-resolving lipid mediators (SPMs), key regulators in placental function and inflammation, may contribute to pregnancy complications. However, the role of SPMs in modulating fetal adiposity and their molecular mechanisms remain unknown.

Objective: To investigate SPM-driven placental gene expression signatures and their implication in fetal adiposity. We hypothesize that inflammation-resolving placental SPMs will be negatively associated with fetal growth and adiposity and with a unique protective gene expression signature previously shown to modulate metabolism.

Design/Methods: In 15 female term placentae, we measured concentrations of SPMs (RvD1, Mar1, precursors 17-HDoHE and 14-HDoHE) using reverse phase high performance liquid chromatography-mass spectrometry in a targeted lipidomics study. We collected birth anthropometrics and assessed infant adiposity using air displacement plethysmography at birth. We determined associations between placental SPM concentrations with birthweight z-score (BWz) and neonatal % fat mass (%FM) using linear regression adjusted for maternal BMI and age. We then performed transcriptomic profiling (nCounter 750-gene Metabolic Pathway Panel) of placentae with high vs. low concentrations (dichotomized at the 50%ile) of SPMs altered with neonatal adiposity, and performed enrichment (GSEA, Nanostring) and pathway analysis (Enrichr).

Results: Mean maternal BMI and infant %FM were 32.3 kg/m2 and 16.2 %, respectively. Higher placentae 14-HDoHE was associated with lower BWz (β: -0.25, CI: -0.42,-0.07) and %FM (-0.93%; -1.8,-0.9). Other SPMs were not associated with growth or adiposity. A total of 39 genes were differentially expressed in placentae with high vs. low 14-HDoHE (p < 0.05), including 23 up- and 16 down- regulated genes (Fig.1, Table 1). In GSEA, placentae with higher 14-HDoHE had upregulation of gene sets most related to DNA damage repair and the cell cycle and down-regulation of gene sets related to epigenetic regulation and mTOR (Fig.2A). MSigDB Pathway analysis also showed downregulation of the fatty acid metabolism pathway (Fig.2B/C).

Conclusion(s): Placental SPM 14-HDoHE is associated with lower fetal growth and adiposity and may drive a placental transcriptomic signature implicated in cell cycle and repair, epigenetic regulation, and nutrient metabolism. Future studies are needed to establish the role of SPMs as a novel protective strategy in pregnancies at risk for excessive fetal growth and adiposity.

Figure 1. Volcano plot and heatmap of differentially expressed genes
(A) Volcano plot of differentially expressed genes in placentae with high (n=8) vs. low (n=7) 14-HDoHE concentrations with absolute FC < or > |1| and P-value < 0.05. The x-axis represents log2 fold change (log2 FC), and the y-axis represents -log10 (P-value). Green dots indicate the 23 upregulated genes in placentae with high vs. low 14-HDoHe, and purple dots indicate the 16 downregulated genes in placentae with high vs. low 14-HDoHE. The differential expression analysis did not meet significance threshold after correction for FDR. (B) Heatmap shows unsupervised hierarchical cluster analysis of placentae metabolic transcriptome data using the Euclidean distance method with average linkage. All 39 genes differentially expressed in placentae with high vs. low 14-HDoHE were included in the heatmap with relative expression displayed as normalized and scaled z-scores. Red indicates a high expression level; blue indicates a low expression level. Unsupervised hierarchical clustering led to 2 gene clusters.

Table 1. Differentially expressed metabolic genes in placentae with high vs. low 14HDoHE concentrations1
1There were 39 significant differentially regulated genes in placenta with high vs. low 14-HDoHE (P-value < 0.05). However, comparison did not meet FDR (P-Adj > 0.05). Upregulated genes belonged to cluster 1, and downregulated genes to cluster 2.

Figure 2. Enrichment and Pathway analysis.
(A) Direct global significance score from Nanostring GSEA based on the differential expression testing of placentae with high vs. low 14-HDOHE concentrations. Direct global significance scores measure the extent to which a given geneset is up- or down-regulated relative to a given exposure by summarizing the statistical significance of all genes in the geneset and is calculated as the square root of the mean signed squared t-statistics. A higher score indicates that a larger proportion of the genes in the geneset exhibits changes in expression relative to a given exposure. MSigDB Pathway analysis of (B) the 23 significantly upregulated genes (cluster 1) and (C) the 16 significantly downregulated genes (cluster 2) in placentae with high vs low concentrations of 14-HDOHE. The reference (background) genes included all the genes measured in the experiment. P-value for all pathways < 0.05.