Copy Number Analyses Identified a Novel Gene: APOBEC3A Related to Lipid Metabolism in the Pathogenesis of Preeclampsia

Epigenetic biomarker for preeclampsia-associated preterm birth and potential preventative medicine

Preterm birth (PTB) has dramatically increased within the population (i.e. >10%) and preeclampsia is a significant sub-category of PTB. Currently, there are no practical clinical parameters or biomarkers which predict preeclampsia induced PTB. The current study investigates the potential use of epigenetic (DNA methylation) alterations as a maternal preeclampsia biomarker. Non-preeclampsia term births were compared to preeclampsia PTBs to identify DNA methylation differences (i.e. potential epigenetic biomarker). Maternal buccal cell cheek swabs were used as a marker cell for systemic epigenetic alterations in the individuals, which are primarily due to environmentally induced early life or previous generations impacts, and minimally impacted or associated with the disease etiology or gestation variables. A total of 389 differential DNA methylation regions (DMRs) were identified and associated with the presence of preeclampsia. The DMRs were genome-wide and were predominantly low CpG density (<2 CpG/100 bp). In comparison with a previous PTB buccal cell epigenetic biomarker there was a 15% (60 DMR) overlap, indicating that the majority of the DMRs are unique for preeclampsia. Few previously identified preeclampsia genes have been identified, however, the DMRs had gene associations in the P13 K-Akt signaling pathway and metabolic gene family, such as phospholipid signaling pathway. Preliminary validation of the DMR use as a potential maternal biomarker used a cross-validation analysis on the samples and provided 78% accuracy. Although prospective expanded clinical trials in first trimester pregnancies and clinical comparisons are required, the current study provides the potential proof of concept a preeclampsia epigenetic biomarker may exist. The availability of a preeclampsia PTB maternal susceptibility biomarker may facilitate clinical management and allow preventative medicine approaches to identify and treat the preeclampsia condition prior to its occurrence.

Pregnancy Metabolic Adaptation and Changes in Placental Metabolism in Preeclampsia

Pregnancy is a unique physiological state in which the maternal body undergoes a series of changes in the metabolism of glucose, lipids, amino acids, and other nutrients in order to adapt to the altered state of pregnancy and provide adequate nutrients for the fetus' growth and development. The metabolism of various nutrients is regulated by one another in order to maintain homeostasis in the body. Failure to adapt to the altered physiological conditions of pregnancy can lead to a range of pregnancy issues, including fetal growth limitation and preeclampsia. A failure of metabolic adaptation during pregnancy is linked to the emergence of preeclampsia. The treatment of preeclampsia by focusing on metabolic changes may provide new therapeutic alternatives.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets

Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes.