Frontiers in Genetics (Jan 2020)

Data-Mining Approach on Transcriptomics and Methylomics Placental Analysis Highlights Genes in Fetal Growth Restriction

  • Floris Chabrun,
  • Floris Chabrun,
  • Noémie Huetz,
  • Noémie Huetz,
  • Xavier Dieu,
  • Xavier Dieu,
  • Guillaume Rousseau,
  • Guillaume Rousseau,
  • Guillaume Bouzillé,
  • Guillaume Bouzillé,
  • Juan Manuel Chao de la Barca,
  • Juan Manuel Chao de la Barca,
  • Vincent Procaccio,
  • Vincent Procaccio,
  • Guy Lenaers,
  • Guy Lenaers,
  • Odile Blanchet,
  • Guillaume Legendre,
  • Delphine Mirebeau-Prunier,
  • Delphine Mirebeau-Prunier,
  • Marc Cuggia,
  • Marc Cuggia,
  • Philippe Guardiola,
  • Pascal Reynier,
  • Pascal Reynier,
  • Geraldine Gascoin,
  • Geraldine Gascoin

DOI
https://doi.org/10.3389/fgene.2019.01292
Journal volume & issue
Vol. 10

Abstract

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Intrauterine Growth Restriction (IUGR) affects 8% of newborns and increases morbidity and mortality for the offspring even during later stages of life. Single omics studies have evidenced epigenetic, genetic, and metabolic alterations in IUGR, but pathogenic mechanisms as a whole are not being fully understood. An in-depth strategy combining methylomics and transcriptomics analyses was performed on 36 placenta samples in a case-control study. Data-mining algorithms were used to combine the analysis of more than 1,200 genes found to be significantly expressed and/or methylated. We used an automated text-mining approach, using the bulk textual gene annotations of the discriminant genes. Machine learning models were then used to explore the phenotypic subgroups (premature birth, birth weight, and head circumference) associated with IUGR. Gene annotation clustering highlighted the alteration of cell signaling and proliferation, cytoskeleton and cellular structures, oxidative stress, protein turnover, muscle development, energy, and lipid metabolism with insulin resistance. Machine learning models showed a high capacity for predicting the sub-phenotypes associated with IUGR, allowing a better description of the IUGR pathophysiology as well as key genes involved.

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