Research in CTGlab explores the genetic and environmental causes of individual differences in brain-related health and disease. We integrate knowledge from different fields (genetics, neuroscience, bioinformatics, biology, machine learning), use and develop analytical tools to analyze and understand genomic data for complex traits, and connect to neuroscience to prove causation in wet-lab experiments.
NWO Brain & Cognition has awarded CTGlab PhD students Anke Hammerschlag and Sabine Mous the first prize for best integrated project and the attractive joint presentation of their collaboration on “An Integrative Theory of the Genetically Mediated Neural Substrates of ADHD”.
CTGlab was setup in 2008 by Danielle Posthuma as a small research group within the CNCR at the VU and the Amsterdam University Medical Centre. Since 2014 CTGlab is a sub-department of the CNCR and Amsterdam-UMC. We participate in Amsterdam Neuroscience.
The paper of CNCR researcher Ilan Libedinsky “Genetic timeline of human brain and cognitive traits” has been awarded the Best Student Paper Award at the 23rd annual conference of the International Society for Intelligence Research (ISIR), held in Berkeley, California, from July 27-29, 2023.
Dr. Stephanie Dooves, Liza Kok and colleagues performed a study aiming to enhance our understanding of the disease mechanisms behind 4H leukodystrophy. This study, performed under the supervision of Dr. Vivi Heine and Prof. Nicole Wolf, provides the first insights into the cellular mechanisms underlying 4H leukodystrophy.
In the post-GWAS era the aim of genetic research has expanded to the identification of the actual genes underlying stable genetic contributions to various key traits of behavior, cognition and health. Identifying these genes is important as it may lead us to understand why some people are more prone to mental disorders and physical disease than others, and may help improve early diagnosis, prevention and treatment of disease.
Research in our lab explores the genetic and environmental causes of individual differences in human traits related to behavior, cognition and mental and physical health. We integrate knowledge from different fields (biology, genetics, neuroimaging, bioinformatics) and use and develop statistical tools to analyze and understand GWAS data for complex traits.
