Despite intensive search for schizophrenia (SZ) susceptibility genes, the neurobiological mechanisms underlying the development of this devastating illness remain elusive. A complementary strategy that may provide valuable insights into the pathogenesis of SZ is the study of a disorder with known genetic etiology that shares its phenotypic characteristics. The 22q11.2 Deletion Syndrome (Velocardiofacial/DiGeorge syndrome;22qDS) is a compelling model, as it represents the most common known genetic risk factor for the development of psychosis (30-fold increase relative to the general population). As such, 22qDS represents a unique window into the neural correlates of SZ in a disorder with known genetic cause. Our hypothesis is that a life-long biological vulnerability, resulting from haploinsufficiency for specific genes critical for neurodevelopment, leads to reduced synaptic plasticity &disconnectivity, which sets the stage for increased vulnerability to psychosis in adolescence in 22qDS patients. Examining the strength of functional connections between different brain regions in 22qDS can offer empirical support for this dysconnection hypothesis. Resting state fMRI (rs-fMRI) is increasingly recognized as a valuable method for probing the brain's intrinsic functional architecture, yielding valuable insights into brain-behavior relationships in several neurodevelopmental &psychiatric disorders. However, almost nothing is known about resting state functional connectivity (RSFC) in 22qDS, nor how it may relate to variability in clinical outcomes. The purpose of the proposed project is to map the functional architecture of the brain in 22qDS, &probe the relationship of this connectivity to psychotic symptoms and behavior, cross-sectionally &over time.
Aim 1 will first investigate 22qDS-related anomalies in RSFC using a combination of hypothesis-driven (i.e., seed-based) &data-driven approaches (i.e., Independent Component Analysis);&will use these methods to characterize the developmental trajectory of RSFC alterations throughout the critical adolescent period in 22qDS patients, relative to controls.
Aim 2 will examine the Aim 1-derived resting state networks as predictors of psychotic symptoms &psychosocial functioning within 22qDS patients, cross-sectionally &longitudinally.
Aim 3 will employ analysis techniques from the field of Graph Theory to the rs-fMRI data in an attempt to further quantify the degree to which the character and topology of functional networks are adversely impacted by the 22q11.2 mutation. [The proposed project will allow the applicant to leverage his ongoing interest in state-of-the-art neuroimaging analysis techniques with the clinical experience &knowledge of developmental psychopathology he will gain in the training program described herein, in order to] expand the current sphere of knowledge about the relationship between brain function, behavior &psychosis risk in this genetically distinct sample. Further research within this unique clinical population will strengthen the link between genetic variation &brain dysfunction, hopefully helping to elucidate the complex neurobiological mechanisms by which SZ may arise.

Public Health Relevance

Schizophrenia (SZ) is one of the most well-known mental health disorders affecting our society, but the precise neurobiological mechanisms by which it wreaks its devastating effects remains elusive. 22q11.2 Deletion Syndrome (22qDS) represents the most common genetic risk factor for the development of psychosis. Investigating the functional and cognitive correlates of a known genetic cause of SZ, as we propose to do here by assessing resting state functional connectivity in 22qDS, offers the best chance at unraveling the complexity and heterogeneity of psychosis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
1F31MH099786-01A1
Application #
8594513
Study Section
Special Emphasis Panel (ZRG1-F01-F (20))
Program Officer
Rubio, Mercedes
Project Start
2013-08-01
Project End
2016-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
1
Fiscal Year
2013
Total Cost
$35,832
Indirect Cost
Name
University of California Los Angeles
Department
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Schreiner, Matthew; Forsyth, Jennifer K; Karlsgodt, Katherine H et al. (2017) Intrinsic Connectivity Network-Based Classification and Detection of Psychotic Symptoms in Youth With 22q11.2 Deletions. Cereb Cortex 27:3294-3306