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Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative

  • Anna R. Docherty
  • , Eduardo Fonseca-Pedrero
  • , Martin Debbané
  • , Raymond C.K. Chan
  • , Richard J. Linscott
  • , Katherine G. Jonas
  • , David C. Cicero
  • , Melissa J. Green
  • , Leonard J. Simms
  • , Oliver Mason
  • , David Watson
  • , Ulrich Ettinger
  • , Monika Waszczuk
  • , Alexander Rapp
  • , Phillip Grant
  • , Roman Kotov
  • , Colin G. DeYoung
  • , Camilo J. Ruggero
  • , Nicolas R. Eaton
  • , Robert F. Krueger
  • Christopher Patrick, Christopher Hopwood, F. Anthony O'Neill, David H. Zald, Christopher C. Conway, Daniel E. Adkins, Irwin D. Waldman, Jim Van Os, Patrick F. Sullivan, John S. Anderson, Andrey A. Shabalin, Scott R. Sponheim, Stephan F. Taylor, Rachel G. Grazioplene, Silviu A. Bacanu, Tim B. Bigdeli, Corinna Haenschel, Dolores Malaspina, Diane C. Gooding, Kristin Nicodemus, Frauke Schultze-Lutter, Neus Barrantes-Vidal, Christine Mohr, William T. Carpenter, Alex S. Cohen
  • University of Utah
  • Virginia Commonwealth University
  • Universidad de La Rioja
  • University College London
  • University of Geneva
  • CAS - Institute of Psychology
  • Chinese Academy of Sciences
  • University of Otago
  • Stony Brook University
  • University of Hawai'i at Mānoa
  • University of New South Wales
  • University of Surrey
  • University of Notre Dame
  • University of Bonn
  • University of Tübingen
  • Justus Liebig University Giessen
  • Münster University of Applied Sciences
  • University of Minnesota Twin Cities
  • University of North Texas
  • Florida State University
  • University of California at Davis
  • Queen's University Belfast
  • Vanderbilt University
  • College of William and Mary
  • Emory University
  • Maastricht University
  • King's College London
  • Utrecht University
  • University of North Carolina at Chapel Hill
  • Karolinska Institutet
  • University of Michigan, Ann Arbor
  • Yale University
  • SUNY Downstate Health Sciences University
  • City, University of London
  • Icahn School of Medicine at Mount Sinai
  • University of Wisconsin-Madison
  • University of Edinburgh
  • Heinrich Heine University Düsseldorf
  • Autonomous University of Barcelona
  • University of North Carolina at Greensboro
  • Sant Pere Claver - Fundació Sanitària
  • University of Lausanne
  • University of Maryland, Baltimore
  • Louisiana State University

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

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.

Original languageEnglish
Pages (from-to)S460-S467
JournalSchizophrenia Bulletin
Volume44
DOIs
StatePublished - Oct 15 2018

Keywords

  • HiTOP
  • ICSR
  • data sharing
  • genetic
  • phenotype
  • psychosis
  • schizophrenia
  • schizotypal
  • schizotypy

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