Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative

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  • Docherty, Anna R
  • Fonseca-Pedrero, Eduardo
  • Debbané, Martin
  • Chan, Raymond C K
    • Other Affiliation: Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
  • Linscott, Richard J
  • Jonas, Katherine G
  • Cicero, David C
  • Green, Melissa J
  • Simms, Leonard J
  • Mason, Oliver
  • Watson, David
    • Other Affiliation: Department of Psychology, University of Notre Dame, Notre Dame, IN
  • Ettinger, Ulrich
  • Waszczuk, Monika
  • Rapp, Alexander
    • Other Affiliation: Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
  • Grant, Phillip
    • Other Affiliation: Department of Psychology, Justus-Liebig-University Giessen, Giessen, Germany
  • Kotov, Roman
    • Other Affiliation: Department of Psychiatry, Stony Brook School of Medicine, Stony Brook, NY
  • DeYoung, Colin G
    • Other Affiliation: Department of Psychology, University of Minnesota, Minneapolis, MN
  • Ruggero, Camilo J
  • Eaton, Nicolas R
    • Other Affiliation: Department of Psychology, Stony Brook University, Stony Brook, NY
  • Krueger, Robert F
  • Patrick, Christopher
    • Other Affiliation: Department of Psychology, Florida State University, Tallahassee, FL
  • Hopwood, Christopher
  • O’Neill, F Anthony
  • Zald, David H
  • Conway, Christopher C
    • Other Affiliation: Department of Psychology, College of William & Mary, Williamsburg, VA
  • Adkins, Daniel E
    • Other Affiliation: Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT
  • Waldman, Irwin D
    • Other Affiliation: Department of Psychology, Emory University, Atlanta, GA
  • van Os, Jim
  • Sullivan, Patrick F
    • School of Medicine, Department of Psychiatry
  • Anderson, John S
    • Other Affiliation: Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT
  • Shabalin, Andrey A
  • Sponheim, Scott R
  • Taylor, Stephan F
  • Grazioplene, Rachel G
    • Other Affiliation: Department of Psychology, Yale University, New Haven, CT
  • Bacanu, Silviu A
    • ORCID: https://orcid.org/0000-0002-4364-1583
    • Other Affiliation: Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA
  • Bigdeli, Tim B
    • Other Affiliation: Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA
  • Haenschel, Corinna
  • Malaspina, Dolores
  • Gooding, Diane C
    • Other Affiliation: Department of Psychology, University of Wisconsin—Madison, Madison, WI
  • Nicodemus, Kristin
    • Other Affiliation: Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
  • Schultze-Lutter, Frauke
  • Barrantes-Vidal, Neus
  • Mohr, Christine
  • Carpenter, William T
    • Other Affiliation: Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD
  • Cohen, Alex S
Abstract
  • 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.
Date of publication
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DOI
Identifier
Resource type
  • Article
Rights statement
  • In Copyright
Journal title
  • Schizophrenia Bulletin
Journal volume
  • 44
Journal issue
  • suppl_2
Page start
  • s460
Page end
  • s467
Funder
  • United States Department of Veterans Affairs
  • National Institute of Mental Health
  • VA Office of Research and Development
ISSN
  • 0586-7614
  • 1745-1701
Publisher
  • Oxford University Press (OUP)

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