Sex-Specific Perturbation of Systemic Lipidomic Profile in Newborn Lambs Impacted by Prenatal Testosterone Excess

Gestational hyperandrogenism adversely impacts offspring health. Using an ovine model, we found that prenatal testosterone (T) excess adversely affects growth and cardiometabolic outcomes in female offspring and produces sex-specific effects on fetal myocardium. Since lipids are essential to cardiometabolic function, we hypothesized that prenatal T excess leads to sex-specific disruptions in lipid metabolism at birth. Shotgun lipidomics was performed on the plasma samples collected 48 hours after birth from female (F) and male (M) lambs of control (C) and (T) sheep (CF = 4, TF = 7, CM = 5, TM = 10) and data were analyzed by univariate analysis, multivariate dimensionality reduction modeling followed by functional enrichment, and pathway analyses. Biosynthesis of phosphatidylserine was the major pathway responsible for sex differences in controls. Unsupervised and supervised models showed separation between C and T in both sexes with glycerophospholipids and glycerolipids classes being responsible for the sex differences between C and T. T excess increased cholesterol in females while decreasing phosphatidylcholine levels in male lambs. Specifically, T excess: 1) suppressed the phosphatidylethanolamine N-methyltransferase (PEMT) phosphatidylcholine synthesis pathway overall and in TM lambs as opposed to suppression of carnitine levels overall and TF lambs; and 2) activated biosynthesis of ether-linked (O-)phosphatidylethanolamine and O-phosphatidylcholine from O-diacylglycerol overall and in TF lambs. Higher cholesterol levels could underlie adverse cardiometabolic outcomes in TF lambs, whereas suppressed PEMT pathway in TM lambs could lead to endoplasmic reticulum stress and defective lipid transport. These novel findings point to sex-specific effects of prenatal T excess on lipid metabolism in newborn lambs, a precocial ovine model of translational relevance.

Life course of retrospective harmonization initiatives: key elements to consider

Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the 'life course' of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.