The Translational Neurogenomics Laboratory is headed by Professor Eske Derks. The group currently includes 10 members (two postdocs, two visiting scientists, two PhD students and three undergraduate students). The Translational Neurogenomics Laboratory has identified genetic risk factors for a range of neuropsychiatric conditions, including substance use disorders, schizophrenia, depression, and obsessive compulsive disorder. Researchers in this group use genetic data to address questions, such as: Which genetic variants in the DNA increase the risk of developing a neuropsychiatric disease? What is the genetic overlap across different psychiatric disorders? What are the downstream molecular consequences underlying statistical genetic associations? Which existing drugs may be repurposed for prevention and treatment of neuropsychiatric diseases?
CURRENT RESEARCH
- genetics of cannabis use: Eske Derks is co-PI of the International Cannabis Consortium. Eske and Zac Gerring (postdoc) contributed to the analysis of genetic profiles of >180,000 subjects to identify genetic variants associated with cannabis use and established genetic overlap between cannabis use and other traits (see right image below). Research findings challenged the commonly held belief that cannabis use increases the risk of schizophrenia. Our Mendelian Randomization analysis showed that individuals with a high genetic liability for schizophrenia are more likely to initiate cannabis use (although a bi-directional relationship could not be ruled out).
- functional genomics and tissue-specific gene regulation in the brain: A substantial proportion of gene expression regulation is tissue-specific. Zac Gerring has built tissue-relevant gene co-expression networks by correlating gene expression values within multiple human tissues, including brain tissue. We aim to use these gene co-expression networks to characterise the impact of genetic variation on biological pathways and processes, and thereby refine our understanding of disease mechanisms. Because most genetic variation associated with complex disease lies in non-coding regions, understanding these genetic associations is a crucial step in genomics
- exploring genetic and phenotypic heterogeneity of depression
- how-to-guide on Genome Wide Association Studies (GWAS)
- GWAS has become increasingly popular to identify associations between single nucleotide polymorphisms (SNPs) and phenotypic traits. However, statistical analyses will need to be carefully conducted and the use of dedicated genetics software will be required. Eske Derks and Andries Marees have developed a tutorial that provides practical guideline for conducting genetic analyses. Example scripts are shared through a github https://github.com/MareesAT/GWA_tutorial/
Staff
- Briar Wormington, PhD Student, Research Assistant
- Damian Woodward, PhD Student
- Dillensinh Jhala, Research Assistant
- Jackson Thorp, Research Officer
- Tingyan Yang, PhD Student
- Yelena Reznikova, Research Assistant
- Associate Professor Zachary Gerring, Senior Research Officer
Internal Collaborators
External Relations
- Professor Dorret Boomsma, Free University Amsterdam
- Professor Jacqueline Vink, Radboud University, Nijmegen
- Dr Florence Vorspan, Universités Paris Descartes – Paris Diderot
- Professor Peter Visscher, University of Queensland
- Professor Naomi Wray, University of Queensland
- Professor Christel Middeldorp, University of Queensland
- Dr Lea Davis, Vanderbilt University
- Dr Eric Gamazon, Vanderbilt University
- Professor Wim van den Brink, Academic Medical Center, Amsterdam
- Professor Damiaan Denys, Academic Medical Center, Amsterdam
- Dr Dorien Nieman, Academic Medical Center, Amsterdam
- Dr Dirk Smit, Academic Medical Center, Amsterdam
- Professor Koos Zwinderman, Academic Medical Center, Amsterdam
- Professor Karien Stronks, Academic Medical Center, Amsterdam
- Dr Henrike Galenkamp, Academic Medical Center, Amsterdam
- Foundation Volksbond Rotterdam
- Netherlands Organization for Scientific Research
STUDENT PROJECTS
Understanding the shared and unique genetic risk factors between neuropsychiatric disorders and their comorbidities
Investigating the genetic relationships of Alzheimer’s disease and sleep apnea
Integrating genomic data to characterise inherited risk factors for mental health disorders
The interplay between environmental and genetic risk factors in the aetiology of substance use disorders
- Analysis of genetic profiles to identify genetic variants associated with cannabis use
2. Genetic overlap between cannabis use and other traits
3. The Figure shows a heatmap of a gene co-expression network in brain tissue. Dark areas within the heatmap represent highly correlated (co-expressed) genes.
4. Our findings suggest that the large phenotypic heterogeneity observed for depression is recapitulated at a genetic level