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Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative
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 phenotypi...
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Published in: | Schizophrenia bulletin 2018-10, Vol.44 (suppl_2), p.S460-S467 |
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creator | Docherty, Anna R Fonseca-Pedrero, Eduardo Debbané, Martin Chan, Raymond C K Linscott, Richard J Jonas, Katherine G Cicero, David C Green, Melissa J Simms, Leonard J Mason, Oliver Watson, David Ettinger, Ulrich Waszczuk, Monika Rapp, Alexander Grant, Phillip Kotov, Roman DeYoung, Colin G Ruggero, Camilo J Eaton, Nicolas R Krueger, Robert F Patrick, Christopher Hopwood, Christopher O’Neill, F Anthony Zald, David H Conway, Christopher C Adkins, Daniel E Waldman, Irwin D van Os, Jim Sullivan, Patrick F Anderson, John S Shabalin, Andrey A Sponheim, Scott R Taylor, Stephan F Grazioplene, Rachel G Bacanu, Silviu A Bigdeli, Tim B Haenschel, Corinna Malaspina, Dolores Gooding, Diane C Nicodemus, Kristin Schultze-Lutter, Frauke Barrantes-Vidal, Neus Mohr, Christine Carpenter, William T Cohen, Alex S |
description | 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. |
doi_str_mv | 10.1093/schbul/sby059 |
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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.</description><identifier>ISSN: 0586-7614</identifier><identifier>EISSN: 1745-1701</identifier><identifier>DOI: 10.1093/schbul/sby059</identifier><identifier>PMID: 29788473</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Datasets as Topic ; Humans ; Information Dissemination ; Intersectoral Collaboration ; Invited Theme ; Models, Theoretical ; Psychotic Disorders - classification ; Schizophrenia - classification ; Schizotypal Personality Disorder - classification</subject><ispartof>Schizophrenia bulletin, 2018-10, Vol.44 (suppl_2), p.S460-S467</ispartof><rights>The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c420t-dd008695753d068354e03448081381466888ee7169c36d470d67537a1af055063</citedby><cites>FETCH-LOGICAL-c420t-dd008695753d068354e03448081381466888ee7169c36d470d67537a1af055063</cites><orcidid>0000-0002-1910-223X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6188505/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6188505/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29788473$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Docherty, Anna R</creatorcontrib><creatorcontrib>Fonseca-Pedrero, Eduardo</creatorcontrib><creatorcontrib>Debbané, Martin</creatorcontrib><creatorcontrib>Chan, Raymond C K</creatorcontrib><creatorcontrib>Linscott, Richard J</creatorcontrib><creatorcontrib>Jonas, Katherine G</creatorcontrib><creatorcontrib>Cicero, David C</creatorcontrib><creatorcontrib>Green, Melissa J</creatorcontrib><creatorcontrib>Simms, Leonard J</creatorcontrib><creatorcontrib>Mason, Oliver</creatorcontrib><creatorcontrib>Watson, David</creatorcontrib><creatorcontrib>Ettinger, Ulrich</creatorcontrib><creatorcontrib>Waszczuk, Monika</creatorcontrib><creatorcontrib>Rapp, Alexander</creatorcontrib><creatorcontrib>Grant, Phillip</creatorcontrib><creatorcontrib>Kotov, Roman</creatorcontrib><creatorcontrib>DeYoung, Colin G</creatorcontrib><creatorcontrib>Ruggero, Camilo J</creatorcontrib><creatorcontrib>Eaton, Nicolas R</creatorcontrib><creatorcontrib>Krueger, Robert F</creatorcontrib><creatorcontrib>Patrick, Christopher</creatorcontrib><creatorcontrib>Hopwood, Christopher</creatorcontrib><creatorcontrib>O’Neill, F Anthony</creatorcontrib><creatorcontrib>Zald, David H</creatorcontrib><creatorcontrib>Conway, Christopher C</creatorcontrib><creatorcontrib>Adkins, Daniel E</creatorcontrib><creatorcontrib>Waldman, Irwin D</creatorcontrib><creatorcontrib>van Os, Jim</creatorcontrib><creatorcontrib>Sullivan, Patrick F</creatorcontrib><creatorcontrib>Anderson, John S</creatorcontrib><creatorcontrib>Shabalin, Andrey A</creatorcontrib><creatorcontrib>Sponheim, Scott R</creatorcontrib><creatorcontrib>Taylor, Stephan F</creatorcontrib><creatorcontrib>Grazioplene, Rachel G</creatorcontrib><creatorcontrib>Bacanu, Silviu A</creatorcontrib><creatorcontrib>Bigdeli, Tim B</creatorcontrib><creatorcontrib>Haenschel, Corinna</creatorcontrib><creatorcontrib>Malaspina, Dolores</creatorcontrib><creatorcontrib>Gooding, Diane C</creatorcontrib><creatorcontrib>Nicodemus, Kristin</creatorcontrib><creatorcontrib>Schultze-Lutter, Frauke</creatorcontrib><creatorcontrib>Barrantes-Vidal, Neus</creatorcontrib><creatorcontrib>Mohr, Christine</creatorcontrib><creatorcontrib>Carpenter, William T</creatorcontrib><creatorcontrib>Cohen, Alex S</creatorcontrib><title>Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative</title><title>Schizophrenia bulletin</title><addtitle>Schizophr Bull</addtitle><description>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.</description><subject>Datasets as Topic</subject><subject>Humans</subject><subject>Information Dissemination</subject><subject>Intersectoral Collaboration</subject><subject>Invited Theme</subject><subject>Models, Theoretical</subject><subject>Psychotic Disorders - classification</subject><subject>Schizophrenia - classification</subject><subject>Schizotypal Personality Disorder - classification</subject><issn>0586-7614</issn><issn>1745-1701</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFkU1LAzEQhoMoWqtHr7JHL6uT5nMvgtSvgqjQ6jWk2bQb2SY12RX6711prXryNId5eN5hXoROMJxjKMhFMtW0rS_SdAWs2EE9LCjLsQC8i3rAJM8Fx_QAHab0BoBpwQf76GBQCCmpID30euMr7Y3z8-w5rUwVkkv5eGlNE9tF9hhSqMN8lU2qGNp5lWmfjXxjo9eNC17X2bVudDaudPwyjLxrXLf5sEdob6brZI83s49ebm8mw_v84eluNLx6yA0dQJOXJYDkBROMlMAlYdQCoVSCxERiyrmU0lqBeWEIL6mAkneo0FjPgDHgpI8u195lO13Y0ljfRF2rZXQLHVcqaKf-bryr1Dx8KI6lZMA6wdlGEMN7a1OjFi4ZW9fa29AmNQBKcPcqRjs0X6MmhpSinW1jMKivLtS6C7XuouNPf9-2pb-f_5Md2uU_rk8czpV8</recordid><startdate>20181015</startdate><enddate>20181015</enddate><creator>Docherty, Anna R</creator><creator>Fonseca-Pedrero, Eduardo</creator><creator>Debbané, Martin</creator><creator>Chan, Raymond C K</creator><creator>Linscott, Richard J</creator><creator>Jonas, Katherine G</creator><creator>Cicero, David C</creator><creator>Green, Melissa J</creator><creator>Simms, Leonard J</creator><creator>Mason, Oliver</creator><creator>Watson, David</creator><creator>Ettinger, Ulrich</creator><creator>Waszczuk, Monika</creator><creator>Rapp, Alexander</creator><creator>Grant, Phillip</creator><creator>Kotov, Roman</creator><creator>DeYoung, Colin G</creator><creator>Ruggero, Camilo J</creator><creator>Eaton, Nicolas R</creator><creator>Krueger, Robert F</creator><creator>Patrick, Christopher</creator><creator>Hopwood, Christopher</creator><creator>O’Neill, F Anthony</creator><creator>Zald, David H</creator><creator>Conway, Christopher C</creator><creator>Adkins, Daniel E</creator><creator>Waldman, Irwin D</creator><creator>van Os, Jim</creator><creator>Sullivan, Patrick F</creator><creator>Anderson, John S</creator><creator>Shabalin, Andrey A</creator><creator>Sponheim, Scott R</creator><creator>Taylor, Stephan F</creator><creator>Grazioplene, Rachel G</creator><creator>Bacanu, Silviu A</creator><creator>Bigdeli, Tim B</creator><creator>Haenschel, Corinna</creator><creator>Malaspina, Dolores</creator><creator>Gooding, Diane C</creator><creator>Nicodemus, Kristin</creator><creator>Schultze-Lutter, Frauke</creator><creator>Barrantes-Vidal, Neus</creator><creator>Mohr, Christine</creator><creator>Carpenter, William T</creator><creator>Cohen, Alex S</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1910-223X</orcidid></search><sort><creationdate>20181015</creationdate><title>Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative</title><author>Docherty, Anna R ; Fonseca-Pedrero, Eduardo ; Debbané, Martin ; Chan, Raymond C K ; Linscott, Richard J ; Jonas, Katherine G ; Cicero, David C ; Green, Melissa J ; Simms, Leonard J ; Mason, Oliver ; Watson, David ; Ettinger, Ulrich ; Waszczuk, Monika ; Rapp, Alexander ; Grant, Phillip ; Kotov, Roman ; DeYoung, Colin G ; Ruggero, Camilo J ; Eaton, Nicolas R ; Krueger, Robert F ; Patrick, Christopher ; Hopwood, Christopher ; O’Neill, F Anthony ; Zald, David H ; Conway, Christopher C ; Adkins, Daniel E ; Waldman, Irwin D ; van Os, Jim ; Sullivan, Patrick F ; Anderson, John S ; Shabalin, Andrey A ; Sponheim, Scott R ; Taylor, Stephan F ; Grazioplene, Rachel G ; Bacanu, Silviu A ; Bigdeli, Tim B ; Haenschel, Corinna ; Malaspina, Dolores ; Gooding, Diane C ; Nicodemus, Kristin ; Schultze-Lutter, Frauke ; Barrantes-Vidal, Neus ; Mohr, Christine ; Carpenter, William T ; Cohen, Alex S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c420t-dd008695753d068354e03448081381466888ee7169c36d470d67537a1af055063</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Datasets as Topic</topic><topic>Humans</topic><topic>Information Dissemination</topic><topic>Intersectoral Collaboration</topic><topic>Invited Theme</topic><topic>Models, Theoretical</topic><topic>Psychotic Disorders - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Schizophrenia bulletin</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Docherty, Anna R</au><au>Fonseca-Pedrero, Eduardo</au><au>Debbané, Martin</au><au>Chan, Raymond C K</au><au>Linscott, Richard J</au><au>Jonas, Katherine G</au><au>Cicero, David C</au><au>Green, Melissa J</au><au>Simms, Leonard J</au><au>Mason, Oliver</au><au>Watson, David</au><au>Ettinger, Ulrich</au><au>Waszczuk, Monika</au><au>Rapp, Alexander</au><au>Grant, Phillip</au><au>Kotov, Roman</au><au>DeYoung, Colin G</au><au>Ruggero, Camilo J</au><au>Eaton, Nicolas R</au><au>Krueger, Robert F</au><au>Patrick, Christopher</au><au>Hopwood, Christopher</au><au>O’Neill, F Anthony</au><au>Zald, David H</au><au>Conway, Christopher C</au><au>Adkins, Daniel E</au><au>Waldman, Irwin D</au><au>van Os, Jim</au><au>Sullivan, Patrick F</au><au>Anderson, John S</au><au>Shabalin, Andrey A</au><au>Sponheim, Scott R</au><au>Taylor, Stephan F</au><au>Grazioplene, Rachel G</au><au>Bacanu, Silviu A</au><au>Bigdeli, Tim B</au><au>Haenschel, Corinna</au><au>Malaspina, Dolores</au><au>Gooding, Diane C</au><au>Nicodemus, Kristin</au><au>Schultze-Lutter, Frauke</au><au>Barrantes-Vidal, Neus</au><au>Mohr, Christine</au><au>Carpenter, William T</au><au>Cohen, Alex S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative</atitle><jtitle>Schizophrenia bulletin</jtitle><addtitle>Schizophr Bull</addtitle><date>2018-10-15</date><risdate>2018</risdate><volume>44</volume><issue>suppl_2</issue><spage>S460</spage><epage>S467</epage><pages>S460-S467</pages><issn>0586-7614</issn><eissn>1745-1701</eissn><abstract>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.</abstract><cop>US</cop><pub>Oxford University Press</pub><pmid>29788473</pmid><doi>10.1093/schbul/sby059</doi><orcidid>https://orcid.org/0000-0002-1910-223X</orcidid><oa>free_for_read</oa></addata></record> |
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source | Oxford Journals Online; PubMed Central |
subjects | Datasets as Topic Humans Information Dissemination Intersectoral Collaboration Invited Theme Models, Theoretical Psychotic Disorders - classification Schizophrenia - classification Schizotypal Personality Disorder - classification |
title | Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T23%3A22%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Enhancing%20Psychosis-Spectrum%20Nosology%20Through%20an%20International%20Data%20Sharing%20Initiative&rft.jtitle=Schizophrenia%20bulletin&rft.au=Docherty,%20Anna%20R&rft.date=2018-10-15&rft.volume=44&rft.issue=suppl_2&rft.spage=S460&rft.epage=S467&rft.pages=S460-S467&rft.issn=0586-7614&rft.eissn=1745-1701&rft_id=info:doi/10.1093/schbul/sby059&rft_dat=%3Cproquest_pubme%3E2043184754%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c420t-dd008695753d068354e03448081381466888ee7169c36d470d67537a1af055063%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2043184754&rft_id=info:pmid/29788473&rft_oup_id=10.1093/schbul/sby059&rfr_iscdi=true |