Year: 2007
Type: review
Abstract: Although schizophrenia is highly heritable, the search for susceptibility genes has been challenging. The "endophenotype" approach is an alternative method for measuring phenotypic variation that may make it easier to identify susceptibility genes in the context of complexly inherited traits. Neuroimaging methods in particular offer a powerful way to bridge the neurobiology of genes and behavior. Such investigations may be further empowered by complementary strategies involving chromosomal abnormalities associated with schizophrenia, which can help to localize causative genes and better understand the genetic complexity of the illness. Here, we illustrate our use of these convergent approaches, with a focus on neuroimaging studies using novel computational brain mapping algorithms, to investigate genetic influences on brain structure in the development of psychosis. These studies provide compelling evidence that specific genetic loci suspected to predispose to schizophrenia may affect quantitative variation in neural indicators underlying the neurobehavioral phenotype, and illustrate how genetic-neuroimaging paradigms can improve our understanding of the pathogenesis of this highly disabling mental illness.
Source: Human Brain Mapping
DOI: 10.1002/hbm.20404
Institution: University of California, Los Angeles
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Funders: National Institute on Aging, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Environmental Health Sciences, National Institute of Biomedical Imaging and Bioengineering, U.S. National Library of Medicine, National Center for Research Resources, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G130320643, G1723377432, G1757829149, Genetic influences on the brain: A twin imaging study, Identification of endophenotypes for bipolar disorder, Computational Anatomy and Multidimensional Modeling, Novel PDEs for Cortical Mapping and Analysis in Disease, G3642348494, UCLA Alzheimer's Disease Research Center, G4428947133, A Multidimensional Alzheimer's Disease Brain Atlas, Center for Computational Biology (CCB)(RMI), Environmental Etiologies of Neurological Disorders (NEUROTOXICOLOGY 24), Neural Phenotypes for Schizophrenia and Bipolar Disorder, G6644087359
OpenAlex ID: W2043189970