Mots-Clés

biostatistics omics diabetes metabolism biostatistique bioinformatique, omique diabète métabolisme genetics genomics

Description

Missions

We are offering a PhD position, as part of the Imperial-CNRS Joint PhD Programme, to investigate the tissue-specific interaction between aging and genetic predisposition of age-related diseases, including type 2 diabetes (T2D), sarcopenia, and metabolic dysfunction-associated steatohepatitis (MASH).

Genome wide association studies (GWAS) has pinpointed key genetic loci linked to these diseases, and expression quantitative trait loci (eQTL) studies have shed light into how these genetic variants influence gene expression. However, missing heritability suggests that other factors remain to be explored. Given that aging is a significant risk factor for T2D and its complications, this project aims to integrate GWAS and aging-related epigenetic data to explore their combined and downstream biological effects. The student will have unique access to extensive multi-tissue, multi-omic datasets, including data from muscle, liver, and pancreatic islets, in addition to publicly available resources.

Activities

Key objectives & methodologies:

• Tissue-specific eQTLs - utilise public GWAS data for relevant diseases, including insulin resistance, T2D, sarcopenia and MASH, to perform comprehensive eQTL analyses. This will involve using both in-house datasets and GTEx data.
• Advanced statistical models - to examine interaction between genetic risk scores with tissue-specific epigenetic clocks to predict disease risk and other relevant outcomes.
• Integrate interaction with transcriptomic data - analyse how genetic risk factors, aging, and gene expression influence disease mechanisms.

Skills

The successful applicant should have :

• an MSc (or equivalent) degree in bioinformatics, computational biology or applied statistics.
• have a good knowledge of programming.
• to master the English language,
• demonstrate critical thinking, problem solving and ability to work within a multidisciplinary team.

Work Context

This PhD project is a part of the Imperial-CNRS Joint PhD Programme, a collaborative effort between leading clinical and statistical experts at Imperial College London and the University of Lille. The student will be based in the UMR1283/U8199: Metabolic Functional (epi)genomics and Molecular Mechanisms Involved in type 2 Diabetes and Related Diseases (EGENODIA) in EGID, recognised by ‘Laboratory of Excellence’ award, headed by Prof Philippe Froguel. The student will benefit from working with a multi-disciplinary team at UMR1293/8199, headed by Dr Amélie Bonnefond (DR, Inserm), and includes bioinformaticians, biostatisticians, functional biologists and sequencing platforms. Supervision will be provided by Dr Amna Khamis.