Genetic and Biological Pathways


Several research projects at CTGlab focus on optimizing methods to define and model the effects of biological pathways on complex traits.

Brain disorders are amongst the most pressing health problems in today’s western society. Despite the fact that most brain disorders are highly heritable, only few disease genes have been identified so far, and the majority of brain disorders are influenced by many genes of small effect. This complex nature hampers gene-finding success. The lack of insight into genetic variation implicated in brain disease is a major obstacle for the design of effective therapeutic strategies.

To alleviate the problems of detecting and interpreting small genetic effect sizes, we work on alternative ways to model these multiple small genetic effects by evaluating the combined, (non-)additive effects of variations in multiple, functionally related genes.

We first developed the JAG tool - which uses permutation to assess statistical significance of set-association. JAG includes self-contained and competitive testing of gene-sets. We are currently working on an extended tool, which will be released soon, and uses slightly different statistical algorithms that allow modeling of dynamically defined gene-sets.

Apart from developing novel statistical strategies, we collaborate closely with biologists from the partner-sections in our department, the CNCR to define sets of genes, based on experimental data and expert knowledge. This has resulted in the generation of several expert-curated sets of genes that are functionally related.

Curation has focused on several main functional areas: genes involved in (pre- and post) synaptic signaling (partners Matthijs Verhage and Guus Smit), in glia and lipid function (partners Andrea Goudriaan and Mark Verheijen), and Alzheimer pathways (Wiep Scheper). These expert curated gene-sets are used by us and others and are freely available from our site.