Integrative multi-omic investigation of biomarkers for depression

Type de poste
Niveau d'étude minimal
Durée du poste
Contrat renouvelable
Contrat non renouvelable
Date de prise de fonction
Date de fin de validité de l'annonce

8 allée du général Rouvillois
67000 Strasbourg

Pierre-Eric Lutz
Email du/des contacts

Doctoral project
We are looking for a highly-motivated student willing to apply for a doctoral fellowship at Strasbourg University on our project entitled “Integrative multi-omic investigation of biomarkers for depression”.

Depression is a frequent and severe psychiatric disorder defined by the recurrence of depressive episodes, and characterized by low mood and anhedonia. Despite intense research efforts, no molecular objective biomarkers are currently available to support the diagnosis and evaluation of clinical course in depressed patients, which remain based on clinical evaluation only. Psychiatric disorders such as depression results from complex interplay between life experiences, social environments, and individual genetic vulnerability factors. Recently, behavioral epigenetics has emerged as a promising strategy to better capture the molecular mechanisms that mediate such interplay. Epigenetics define stable traits that cannot be attributed to changes in the DNA sequence. They rely on physical and chemical processes, control functional organization of the genome, and include DNA methylation, micro-RNAs, and histone modifications. Accumulating data indicates that these mechanisms are modified in individuals affected by psychiatric phenotypes.

Hypothesis & objective
The characterization of molecular processes underlying psychiatric phenotypes is severely limited by the impossibility of sampling brain tissue from living individuals. As such, there has been much interest in the use of peripheral tissues, and recent data suggests that there is a significant correlation between inter-individual variability of gene expression detected in the blood and that detected in the brain. Therefore, our primary hypothesis is that blood is a peripheral tissue that can be used to investigate biomarkers of depression.
While previous studies largely focused on individual epigenetic substrates, it is currently acknowledged that these processes represent interacting layers of regulation that altogether contribute to modulate gene expression and cell function. Therefore, our second hypothesis is that characterizing depression-related changes across multiple epigenetic layers will advance understanding of the disease. Here, we propose a doctoral project that will use integrated systems biology approaches in order to analyze genomics data generated using blood samples from depressed individuals, and identify biomarkers of this condition.

The proposed doctoral work will take advantage of new datasets: gene expression, micro-RNAs, and DNA methylation measures generated using RNA-Sequencing, small RNA-Seq and EPIC arrays, respectively. These techniques are currently used to investigate blood samples from a well-characterized cohort of depressed individuals and matched controls (N=155 subjects in total). All data will be available at the beginning of the doctoral project.
At the differential analysis level, we will perform group comparisons in order to identify changes in gene or micro-RNA expression, as well as methylomic profiles, that reveal biological pathways altered as a function of depression. Potential confounding factors (including age and gender) will be tested and controlled for using linear general models. At the systems biology level, we will use network theories to construct co-expression gene networks (using in particular the Weighted Gene Correlation Network Analysis, WGCNA), where each gene corresponds to a node, and groups of nodes correspond to modules. We will seek to reveal modules of genes that strongly correlate with depression. The project will be co-supervised by Drs Lutz & Belzeaux, who have complementary expertise in bioinformatics processing of large data sets and the characterization of biomarkers for psychiatric phenotypes, respectively.

Expected results
By integrating multiple types of epigenetic data, we believe that we will be able to characterize more comprehensively and reliably peripheral biomarkers of depression. In the long term, this may contribute to the development of personalized care, and improve the prognosis of depression in most severely affected individuals.

Preferred profile
- Previous experience with at least one programming language (R and/or Python) & bash/shell scripting
- Engaged in a master degree in Bioinformatics or Neuroscience
- Strong interest in computational biology and the analysis of large-scale datasets

The doctoral work will take place in Strasbourg, at the ‘Institut des Neurosciences Cellulaires et Intégratives’ (, INCI CNRS UPR 3212, 8 allée du Général Rouvillois, 67000 Strasbourg), under co-supervision by Drs Pierre-Eric Lutz and Raoul Belzeaux.

Please contact Dr Pierre-Eric Lutz:, Institut des Neurosciences Cellulaires et Intégratives, Phone : +33 3 88 45 67 29 ; or Dr Raoul Belzeaux :, Institut des Neurosciences de la Timone, Phone +33 4 91 74 40 82.

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