Laboratory of population genomics

Department                          Internal Medicine

Principal investigator          Jeroen van Rooij

E-mail address                             


Polygenic risk scores in cancer disease prevention

Genetic risk scores include summing up many genetic risk variants for a certain disease. For example, the 313 genetic variants identified to influence risk of breast cancer. In this project, we build prediction models based on these genetic variants to inform population screening, treatment decisions and use the biological mechanisms these variants are expected to influence to inform drug development.


  • Bioinformatics
  • Epidemiology
  • Translation/implementation science
  • Machine learning applications

Further reading

Lakeman, I.M.M., et al. (2020). Genetics in medicine, 22(11), 1803–1811. DOI: 10.1038/s41436-020-0884-4.


Combining multiple genomic layers in neurodegenerative brain samples

In this project we have collected DNA, RNA and proteomic data from multiple post-mortem brain samples of dementia patients. Most of these datasets have been analyzed separately, but additional insights are to be gained by multi-omic data analyses. We focus mostly on frontotemporal dementia, which is different from Alzheimer’s disease, and small (n=20) datasets with large numbers of measured genes/proteins (20k/5k, on average). This is a collaboration with the department of Neurology.


  • Bioinformatics
  • Statistics
  • Molecular biology
  • Machine learning

Further reading

Mol, M. O., et al. (2022). Acta neuropathologica communications, 10(1), 190. DOI: 10.1186/s40478-022-01499-1.