Pan-Genomic Regulation of Gene Expression in Normal and Pathological Human Placentas

Author:

Apicella Clara1,Ruano Camino S. M.1,Thilaganathan Basky23ORCID,Khalil Asma23ORCID,Giorgione Veronica23ORCID,Gascoin Géraldine4,Marcellin Louis5ORCID,Gaspar Cassandra6,Jacques Sébastien1,Murdoch Colin E.7ORCID,Miralles Francisco1,Méhats Céline1ORCID,Vaiman Daniel1ORCID

Affiliation:

1. Team ‘From Gametes to Birth’, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, 75014 Paris, France

2. Fetal Medicine Unit, St George’s University Hospitals NHS Foundation Trust, London SW17 0RE, UK

3. Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of London, London SW17 0RE, UK

4. Department of Neonatology, Angers University Hospital, F-49000 Angers, France

5. Department of Gynaecology, Obstetrics and Reproductive Medicine, Centre Hospitalier Universitaire (CHU) Cochin Faculté de Médecine, Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpitaux Universitaires Paris Centre (HUPC), Université de Paris, 138 Boulevard de Port-Royal, 75014 Paris, France

6. Sorbonne Université, Inserm, UMS Production et Analyse des données en Sciences de la vie et en Santé, PASS, Plateforme Post-génomique de la Pitié-Salpêtrière, 75013 Paris, France

7. Systems Medicine, School of Medicine, University of Dundee, Dundee DD1 9SY, UK

Abstract

In this study, we attempted to find genetic variants affecting gene expression (eQTL = expression Quantitative Trait Loci) in the human placenta in normal and pathological situations. The analysis of gene expression in placental diseases (Pre-eclampsia and Intra-Uterine Growth Restriction) is hindered by the fact that diseased placental tissue samples are generally taken at earlier gestations compared to control samples. The difference in gestational age is considered a major confounding factor in the transcriptome regulation of the placenta. To alleviate this significant problem, we propose here a novel approach to pinpoint disease-specific cis-eQTLs. By statistical correction for gestational age at sampling as well as other confounding/surrogate variables systematically searched and identified, we found 43 e-genes for which proximal SNPs influence expression level. Then, we performed the analysis again, removing the disease status from the covariates, and we identified 54 e-genes, 16 of which are identified de novo and, thus, possibly related to placental disease. We found a highly significant overlap with previous studies for the list of 43 e-genes, validating our methodology and findings. Among the 16 disease-specific e-genes, several are intrinsic to trophoblast biology and, therefore, constitute novel targets of interest to better characterize placental pathology and its varied clinical consequences. The approach that we used may also be applied to the study of other human diseases where confounding factors have hampered a better understanding of the pathology.

Funder

European Union’s Horizon 2020 research and innovation program

Publisher

MDPI AG

Subject

General Medicine

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