From genotype to EEG endophenotype: a route for post-genomic understanding of complex psychiatric disease?
Twin and family studies have shown the importance of biological variation in psychiatric disorders. Heritability estimates vary from 50% to 80% for cognitive disorders, such as schizophrenia, attention deficit hyperactivity disorder and autism, and from 40% to 65% for affective disorders, such as major depression, anxiety disorders and substance abuse. Pinpointing the actual genetic variants responsible for this heritability has proven difficult, even in the recent wave of genome-wide association studies. Brain endophenotypes derived from electroencephalography (EEG) have been proposed as a way to support gene-finding efforts. A variety of EEG and event-related-potential endophenotypes are linked to psychiatric disorders, and twin studies have shown a striking genetic contribution to these endophenotypes. However, the clear need for very large sample sizes strongly limits the usefulness of EEG endophenotypes in gene-finding studies. They require extended laboratory recordings with sophisticated and expensive equipment that are not amenable to epidemiology-scaled samples. Instead, EEG endophenotypes are far more promising as tools to make sense of candidate genetic variants that derive from association studies; existing clinical data from patients or questionnaire-based assessment of psychiatric symptoms in the population at large are better suited for the association studies themselves. EEG endophenotypes can help us understand where in the brain, in which stage and during what type of information processing these genetic variants have a role. Such testing can be done in the more modest samples that are feasible for EEG research. With increased understanding of how genes affect the brain, combinations of genetic risk scores and brain endophenotypes may become part of the future classification of psychiatric disorders.
de Geus
Eco Jc
EJ
Department of Biological Psychology, VU University, van der Boechorststraat 1, 1081 BT, Amsterdam, the Netherlands. eco@psy.vu.nl.