Fully funded PhD Project – Epigenetics, microRNAs & Precision Medicine in Inflammatory Diseases
| ABG-137217 | Thesis topic | |
| 2026-03-26 | Public funding alone (i.e. government, region, European, international organization research grant) |
- Biology
- Health, human and veterinary medicine
Topic description
Epigenetic alterations are now recognized as key drivers of complex human diseases, providing an additional regulatory layer that complements genetic variation. These mechanisms offer powerful opportunities for advancing precision medicine and enabling more personalized treatment strategies.
Spondyloarthritis (SpA) is a common chronic inflammatory rheumatic disease that can lead to complete spinal ankylosis through pathological bone formation, as well as destruction of peripheral joints. Its development arises from a complex interplay between genetic predisposition and environmental exposures. Positioned at the crossroads of these influences, epigenetic regulation - particularly microRNAs - represents a critical and still underexplored component of SpA pathophysiology.
In this context, we have generated a unique high-resolution dataset of microRNA expression profiles from FACS-sorted immune cell populations (CD4+ and CD8+ T cells, and monocytes) in 100 patients undergoing biologic therapies (anti-TNF or anti-IL17). Samples were collected prior to treatment initiation alongside detailed clinical follow-up. This work has revealed extensive, cell-type-specific microRNA alterations in patients compared to healthy controls. Importantly, we have identified a subset of microRNAs whose baseline expression levels are predictive of clinical response to therapy.
This PhD project aims to take these findings to the next level by:
- translating microRNA expression patterns into a robust predictive signature, to be validated in an independent cohort using a novel multiplex digital PCR approach;
- uncovering the molecular mechanisms through which selected microRNAs modulate treatment response;
- testing, in in vitro systems and potentially in vivo models, whether modulation of these microRNAs can enhance or synergize with existing biologic therapies.
This project offers a unique opportunity to work at the interface of molecular biology, immunology, and data science, with strong translational potential. It is expected to deliver a compelling proof of concept for the use of microRNA-based biomarkers in guiding treatment decisions in complex diseases - beyond the field of oncology.
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Presentation of host institution and host laboratory
The Laboratory for Epigenetics & Environment of the CNRGH, led by Jörg Tost, has been working in the field of epigenetics for more than 20 years. The research focuses on the development and application of technologies to analyze DNA methylation, smallRNAs and other epigenetic modifications at high resolution at target loci and genome-wide as well as the development of bioinformatic tools for the processing of such data. The laboratory aimns notably at translating epigenetic changes into biomarkers for the next generation of personalized medicine tests. The main focus of the LEE has been the analysis of epigenetic modifications and associated functional assays of immune cells implicated in complex diseases including cancer and inflammatory and autoimmune and diseases.
More information on http://jacob.cea.fr/drf/ifrancoisjacob/english/Pages/Departments/CNRGH/Laboratories/epigenetic-environment.aspx
The National Center of Human Genomics Research (CNRGH) is part of the François Jacob Institute of Biology (IBFJ) within the Fundamental Research Division (DRF) of the CEA. The CNRGH’s main objective is to advance research of the genetics/genomics of human diseases through internal and collaborative research programs. For this purpose, the CNRGH has developed a number of state-of-the-art genomics technology platforms and laboratories for the management of biological resources, for discovery of disease genes and biomarkers, and for follow-up studies using various approaches including functional genomics. Key platforms include high-throughput platforms for genotyping, sequencing (WGS, WES, genes panel etc.), expression profiling (RNA-seq), DNA methylation analysis and a number of functional genomic applications (e.g. oxWGBS, WGBS, HiC, DNase-seq, ATAC-seq, ChIP-seq etc.). The infrastructure offered by the CEA-CNRGH results each year in more than 100 collaborative projects and 70 publications. The CEA-CNRGH employs a total of 80 staff (scientists, engineers, technicians, administrative & support personnel) that is regrouped into several scientific platforms, a bioinformatics group and an administration unit. In addition the CEA-CNRGH hosts several Post-Docs, PhD and Master students.
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Candidate's profile
Applicants should demonstrate a solid background in molecular biology, with practical experience in standard techniques such as qPCR and magnetic- or fluorescence-based cell sorting. Experience in cell culture and the manipulation of cell lines or primary cells will be considered a strong advantage. Prior exposure to digital PCR is not required but would represent an additional asset.
The project will involve the analysis of large-scale datasets generated from high-throughput sequencing experiments. While established processing pipelines are available within the laboratory, the successful candidate will be expected to conduct downstream analyses using the R/Bioconductor environment and to appropriately structure and manage data for these purposes (note that no GALAXY environment is available). Although advanced programming expertise is not mandatory, the ability—or strong motivation—to rapidly acquire proficiency in R/Bioconductor or Python is essential. Prior knowledge of statistical and machine learning approaches for molecular signature development (e.g., logistic regression, random forests, LASSO) will be highly valued. Bioinformatics support will be provided at both laboratory and departmental (CNRGH) levels but does not substitute for prior exposure to data analysis.
Applicants should hold a Master’s degree in genomics or genomic data analysis, or a related field, or have completed an equivalent dual training in life sciences and quantitative disciplines. Candidates must demonstrate a strong willingness to acquire additional skills as required by the project. Fluency in either English or French is mandatory.
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