Genomic background effects in psychiatric disorders

Authors

Jędrzej Kubica

Univ. Grenoble Alpes, TIMC Grenoble, France

Nicolas Thierry-Mieg

University Grenoble Alpes, CNRS, TIMC, Grenoble, France

Sébastien Déjean

Institut de Mathématiques de Toulouse, France

Project Description

Some individuals carry disease-associated genomic variants, however, they exhibit no clinical phenotype. This suggests that additional factors such as genomic backgrounds (i.e. combinations of common variants) determine whether individuals develop specific phenotypes, including diseases. With recent advancements in genomics, we can now identify variants or their combinations that predispose individuals to disease risk, and search for new patient-specific therapies.

In this project, we will focus on the genetic risk of psychiatric disorders across different genomic backgrounds. The two aims are: to develop a computational method for comparing different combinations of disorder-associated variants, and to associate them with promising drugs. During the hackathon, we will use two public databases: ClinVar, to define and compare the genomic backgrounds of the disorders, and Open Targets, to find drug-variant associations. In the future, this method could also be extended to genetic predispositions underlying other disorders or diseases, for instance Alzheimer’s disease. The expected outcomes of this project will be important for future population-scale research in new therapeutic opportunities.

Project requirements

We would welcome young and senior researchers, including Master’s and PhD students, interested in the development of bioinformatics methods. Basic programming skills (e.g. Python) will be helpful. Familiarity with genomic variant datasets would be an addition plus.

Programming languages used in this project

Python, R, Bash, Linux terminal

Who are we looking for?

  • Computer science
  • Medicine
  • Neurobiology,
  • Psychology
  • Biotechnology

Everyone interested in the topic of the project is welcome to contribute.

What can you gain from participating?

  • Develop a bioinformatics method for a biomedical problem
  • Integrate large-scale public datasets
  • Analyze genomic variant data
  • Collaborate in an interdisciplinary team

Key resources

  1. Grotzinger, A.D., Werme, J., Peyrot, W.J. et al. Mapping the genetic landscape across 14 psychiatric disorders. Nature 649, 406–415 (2026). https://doi.org/10.1038/s41586-025-09820-3
  2. J. Kubica, H. Jethwani, K.H. Banecki, et al., Decoding Complex Genotype-Phenotype Interactions by Discretizing the Genome. BioHackrXiv (2025). https://doi.org/10.37044/osf.io/xhkc3_v1
  3. ClinVar: https://www.ncbi.nlm.nih.gov/clinvar
  4.  Open Targets Platform: https://platform.opentargets.org