Population genomics

Department                          Internal Medicine

Principal investigator          Jeroen van Rooij

E-mail address                      j.vanrooij@erasmusmc.nl   

Website                                    https://www.erasmusmc.nl/en/research/groups/genetic-laboratory-of-internal-medicine

Dissecting heterogeneity in stroke using subtype-specific polygenic risk scores

Stroke is a complex and heterogeneous cardiovascular disease with distinct genetic architectures across its subtypes. While genome-wide association studies (GWAS) have identified genetic risk factors for stroke, aggregating all cases into a single polygenic risk score (PRS) may dilute subtype-specific signals and reduce clinical utility, while subtype-specific GWAS’s often remain underpowered. This project aims to leverage GWAS data at the stroke subtype level to disentangle shared and unique genetic risks. Using UK Biobank data, we will construct subtype-specific PRS. These will be compared to overall stroke PRS to assess improvements in prediction accuracy, risk stratification, and biological insight. The framework could also be extended to potentially other cardiovascular diseases.

Further reading (click to link to article)

Collister, J. A., Liu, X., & Clifton, L. (2022). Calculating Polygenic Risk Scores (PRS) in UK Biobank: A Practical Guide for Epidemiologists. Frontiers in Genetics, 13, 818574.

Google for genetics? Using the AlphaGenome model to search for molecular effects of risk variants for IBD

Genome-wide association studies have identified more than 300 genetic variants associated with inflammatory bowel disease (IBD). However, it is challenging to determine the biological effects of risk variants, because the majority are found within the non-coding regulatory genome. Recently, the team behind Google DeepMind released a new AI model, AlphaGenome, for predicting the effects of genetic variation on the regulatory genome. In this project, the AlphaGenome model will be explored, benchmarked and implemented to determine the likely effects of IBD risk variants on cell type-specific regulatory mechanisms.This will help us to identify causal variants and genes and develop new hypotheses about disease mechanisms, laying the groundwork for novel therapeutic strategies.

Further reading (click to link to article)

Avsec, Ž., Latysheva, N., Cheng, J., Novati, G., Taylor, K.R., Ward, T., Bycroft, C., Nicolaisen, L., Arvaniti, E., Pan, J., Thomas, R., Dutordoir, V., Perino, M., De, S., Karollus, A., Gayoso, A., Sargeant, T., Mottram, A., Wong, L.H., Drotár, P., Kosiorek, A., Senior, A., Tanburn, R., Applebaum, T., Basu, S., Hassabis, D., Kohli, P., 2025. AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence model. bioRxiv 2025.06.25.661532. https://doi.org/10.1101/2025.06.25.661532

Disentangling the shared genetics of blood cell traits and IBD

Pleiotropy is a phenomenon whereby genetic variants are associated with more than one trait or disease. The study of pleiotropy is garnering increasing interest in the field of population genomics, because understanding cross-trait genetics could help us to pinpoint biological connections between cellular function and disease processes, leading us towards more effective treatment strategies. This project aims to disentangle shared genetic signals between inflammatory bowel disease (IBD) and blood cell traits, through a new fine-mapping and colocalisation pipeline. This will help us to identify potentially disease causal variants, with measurable effects on cellular properties. In the future, the disease mechanisms identified in this work could be exploited to develop new treatments and even personalised therapeutic approaches in the blood.

Further reading (click to link to article)

Homilius, M., Zhu, W., Eddy, S.S., Thompson, P.C., Zheng, H., Warren, C.N., Evans, C.G., Kim, D.D., Xuan, L.L., Nsubuga, C., Strecker, Z., Pettit, C.J., Cho, J., Howie, M.N., Thaler, A.S., Wilson, E., Wollison, B., Smith, C., Nascimben, J.B., Nascimben, D.N., Lunati, G.M., Folks, H.C., Cupelo, M., Sridaran, S., Rheinstein, C., McClennen, T., Goto, S., Truslow, J.G., Vandenwijngaert, S., MacRae, C.A., Deo, R.C., 2024. Perturbational phenotyping of human blood cells reveals genetically determined latent traits associated with subsets of common diseases. Nature genetics 56, 37–50. https://doi.org/10.1038/s41588-023-01600-x

Pharmacogenetics: personalizing drug treatment based on your genetic information

Pharmacogenetics (PGx) is the collective name for genetic variants influencing drug responses. For example, a genetic variant in the enzymes metabolizing your drugs can cause you to breakdown a drug too quickly – giving side effects, or not fast enough, thus not reaching the functional dose. It’s estimated that 11% of all hospitalizations are caused by drug-induced side-effects, and PGx could explain a large part of that. At the same time, the genetic measurements used in PGx are complex, and therefore not used at a large scale. In this project, we investigate if a standardized genetic measurement method can be applied to detect PGx variants at a high throughput.

Further reading (click to link to article)

A comparison of genotyping arrays Joost A. M. Verlouw, Eva Clemens, Jard H. de Vries, Oliver Zolk, Annemieke J. M. H. Verkerk, Antoinette am Zehnhoff-Dinnesen, Carolina Medina-Gomez, Claudia Lanvers-Kaminsky, Fernando Rivadeneira, Thorsten Langer, Joyce B. J. van Meurs, Marry M. van den Heuvel-Eibrink, André G. Uitterlinden & Linda Broer European Journal of Human Genetics volume 29, pages 1611–1624 (2021).