Société Française de Bioinformatique

Mots-Clés

Multiomics integration Systems biology Post traumatic stress syndrome Gene regulatory networks

Description

Every year, one million family members of intensive care unit (ICU) patients in France are at risk of developing a post-intensive care syndrome (PICS-family), a myriad of mental problems leading to functional impairments. A major component of PICS-family is post-traumatic stress disorder (PTSD) affecting one third of family members overall, >60% of bereaved families. The FAME (Improving FAMily members’ Experience in the ICU) project collected blood samples and 6 months clinical follow-up for 350 family members in a prospective, longitudinal and observational cohort. Family members were enrolled and their blood sample were collected within the first 3 days of the admission at ICU. They completed structured questionaries assessing PTSD symptoms three and six months after hospital discharge. Three omic levels have been characterized on these blood samples: transcriptomic (RNA-seq) mirnomic (miRNA-seq) and methylomic (whole genome EM-seq).

An M2 internship is proposed to focus on the integrative bioinformatic, and statistical modelling of these omics data. We will take advantage of recently published data by the PsychENCODE consortium (Daskalakis et al, 2024 Science) and of the newly generated FAME multiomics data to build gene regulatory networks associated to PTSD using the NORDic framework (Reda et al 2023 JOSS).

By integrating data on two epigenetic mechanisms, and their impact on the genome’s expression, the aim is to identify more comprehensively and reliably peripheral gene regulations predictive of a higher risk of developing PTSD. This work will be supervised by Pr Andrée Delahaye-Duriez at the NeuroDiderot laboratory in Paris and Dr Clémence Réda. The work will be done with collaborators of the FAME project (ANR 21-RHUS-0009). The applicant will have the opportunity to gain a high level of competence in the highly demanded areas of systems biology and integrative genomics.