Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative.

Docherty AR, Fonseca-Pedrero E, Debbané M, Chan RCK, Linscott RJ, Jonas KG, Cicero DC, Green MJ, Simms LJ, Mason O, Watson D, Ettinger U, Waszczuk M, Rapp A, Grant P, Kotov R, DeYoung CG, Ruggero CJ, Eaton NR, Krueger RF, Patrick C, Hopwood C, O'Neill FA, Zald DH, Conway CC, Adkins DE, Waldman ID, van Os J, Sullivan PF, Anderson JS, Shabalin AA, Sponheim SR, Taylor SF, Grazioplene RG, Bacanu SA, Bigdeli TB, Haenschel C, Malaspina D, Gooding DC, Nicodemus K, Schultze-Lutter F, Barrantes-Vidal N, Mohr C, Carpenter WT, Cohen AS
Schizophr Bull. 2018 44 (suppl_2): S460-S467

PMID: 29788473 · PMCID: PMC6188505 · DOI:10.1093/schbul/sby059

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

MeSH Terms (8)

Datasets as Topic Humans Information Dissemination Intersectoral Collaboration Models, Theoretical Psychotic Disorders Schizophrenia Schizotypal Personality Disorder

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