Schizophrenia and other forms of psychosis affect approximately 3% of the population with a disorder that is usually chronic and disabling. The peak age of onset is between ages 18-30, occurring just as life's most productive years are beginning. Although genetic liability and abnormal brain development are known contributing factors, the etiology and pathophysiology of schizophrenia and related syndromes is largely unknown. To date, prospective observation of onset, i.e., the transition from vulnerability to disorder has not been possible because most persons at true risk cannot be identified premorbidly. This has hampered efforts at prevention. However, recent progress in risk ascertainment methodology has enabled reliable identification of help-seeking persons with pre-psychotic or """"""""prodromal"""""""" clinical syndromes who develop psychosis within 1-2 years at rates between 20%-50%. Thus, clinical high-risk populations are now available for tracking prospectively the development and emergence of psychosis. However, because of the low incidence of schizophrenia and the heterogeneity of outcomes in clinical high-risk cases, single site studies cannot efficiently exploit the risk criteria in identifying predictors and mechanisms of psychosis. The NAPLS consortium was created to solve this problem. Eight NIMH-funded sites in North America studying prodromal patients using a common prodromal assessment instrument pooled data to create the largest sample of such persons worldwide (N=291), 35% of whom converted to psychosis after 2 years. An algorithm of baseline data was generated predicting psychosis with about 80% positive predictive power and 40% sensitivity. In this revised proposal, we describe a collaborative prospective study for which we will recruit 800 cases and 400 appropriate controls over 5 years using common, standardized clinical and neurobiological measures.
The aim i s to collect a sample with sufficient size and power to rigorously test elements critical to the liability for and development of psychosis in the biomarker domains of brain structure, electrophysiology, stress hormones, and genomics, and in the clinical domains of prodromal presentation and epidemiology. The revised proposal addresses reviewers'concerns, including the integration of the research plan and measures into a unifying framework. The findings will enhance our ability to identify persons at high risk for imminent psychosis, by refining predictors of conversion, and expanding our understanding of the underlying neural mechanisms. Such knowledge is critical for future efforts at early detection, intervention and prevention of psychotic disorders.

Public Health Relevance

Preventing schizophrenia and other psychoses could relieve an enormous burden of personal and family suffering and economic losses to society. This 8-site project aims to increase our ability to identify high-risk individuals prior to onset and to pinpoint neurobiological changes that underlie the emergence of a psychotic disorder. These efforts are critical to the development of effective preventative intervention strategies for psychotic disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01MH081857-04S1
Application #
8413646
Study Section
Special Emphasis Panel (ZRG1-BBBP-D (60))
Program Officer
Rumsey, Judith M
Project Start
2008-09-30
Project End
2013-04-30
Budget Start
2011-02-08
Budget End
2013-01-31
Support Year
4
Fiscal Year
2012
Total Cost
$103,500
Indirect Cost
$41,150
Name
Feinstein Institute for Medical Research
Department
Type
DUNS #
110565913
City
Manhasset
State
NY
Country
United States
Zip Code
11030
Addington, Jean; Piskulic, Danijela; Liu, Lu et al. (2017) Comorbid diagnoses for youth at clinical high risk of psychosis. Schizophr Res 190:90-95
Tso, Ivy F; Taylor, Stephan F; Grove, Tyler B et al. (2017) Factor analysis of the Scale of Prodromal Symptoms: data from the Early Detection and Intervention for the Prevention of Psychosis Program. Early Interv Psychiatry 11:14-22
Noble, Stephanie; Scheinost, Dustin; Finn, Emily S et al. (2017) Multisite reliability of MR-based functional connectivity. Neuroimage 146:959-970
Ryan, Arthur T; Addington, Jean; Bearden, Carrie E et al. (2017) Latent class cluster analysis of symptom ratings identifies distinct subgroups within the clinical high risk for psychosis syndrome. Schizophr Res :
Buchy, Lisa; Mathalon, Daniel H; Cannon, Tyrone D et al. (2016) Relation between cannabis use and subcortical volumes in people at clinical high risk of psychosis. Psychiatry Res 254:3-9
Carrión, Ricardo E; Demmin, Docia; Auther, Andrea M et al. (2016) Duration of attenuated positive and negative symptoms in individuals at clinical high risk: Associations with risk of conversion to psychosis and functional outcome. J Psychiatr Res 81:95-101
Seidman, Larry J; Shapiro, Daniel I; Stone, William S et al. (2016) Association of Neurocognition With Transition to Psychosis: Baseline Functioning in the Second Phase of the North American Prodrome Longitudinal Study. JAMA Psychiatry 73:1239-1248
Carrión, Ricardo E; Cornblatt, Barbara A; Burton, Cynthia Z et al. (2016) Personalized Prediction of Psychosis: External Validation of the NAPLS-2 Psychosis Risk Calculator With the EDIPPP Project. Am J Psychiatry 173:989-996
Cannon, Tyrone D; Yu, Changhong; Addington, Jean et al. (2016) An Individualized Risk Calculator for Research in Prodromal Psychosis. Am J Psychiatry 173:980-988
Marshall, Catherine; Deighton, Stephanie; Cadenhead, Kristin S et al. (2016) The Violent Content in Attenuated Psychotic Symptoms. Psychiatry Res 242:61-66

Showing the most recent 10 out of 42 publications