Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.

Importance: Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies. Objective: To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk...

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Autores: Mongan, D., Föcking, M., Healy, C., Susai, S. R., Heurich, M., Wynne, K., Nelson, B., McGorry, P. D., Amminger, G. P., Nordentoft, M., Krebs, M. O., Riecher-Rössler, A., Bressan, R A., Barrantes Vidal, Neus, Borgwardt, S., Ruhrmann, S., Sachs, S., Pantelis, Christos, van der Gaag, M., de Haan, L., Valmaggia, L., Pollak, T. A., Kempton, Matthew J., Rutten, B. P. F., Whelan, R., Cannon, M., Zammit, S., Cagney, G., Cotter, D. R., McGuire, P. for the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI)., Rosa de la Cruz, Araceli
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/180215
Acceso en línea:https://hdl.handle.net/2445/180215
Access Level:acceso abierto
Palabra clave:Psicosi en els adolescents
Marcadors bioquímics
Pronòstic mèdic
Psychoses in adolescence
Biochemical markers
Prognosis
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network_name_str España
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dc.title.none.fl_str_mv Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
title Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
spellingShingle Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
Mongan, D.
Psicosi en els adolescents
Marcadors bioquímics
Pronòstic mèdic
Psychoses in adolescence
Biochemical markers
Prognosis
title_short Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
title_full Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
title_fullStr Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
title_full_unstemmed Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
title_sort Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.
dc.creator.none.fl_str_mv Mongan, D.
Föcking, M.
Healy, C.
Susai, S. R.
Heurich, M.
Wynne, K.
Nelson, B.
McGorry, P. D.
Amminger, G. P.
Nordentoft, M.
Krebs, M. O.
Riecher-Rössler, A.
Bressan, R A.
Barrantes Vidal, Neus
Borgwardt, S.
Ruhrmann, S.
Sachs, S.
Pantelis, Christos
van der Gaag, M.
de Haan, L.
Valmaggia, L.
Pollak, T. A.
Kempton, Matthew J.
Rutten, B. P. F.
Whelan, R.
Cannon, M.
Zammit, S.
Cagney, G.
Cotter, D. R.
McGuire, P. for the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI).
Rosa de la Cruz, Araceli
author Mongan, D.
author_facet Mongan, D.
Föcking, M.
Healy, C.
Susai, S. R.
Heurich, M.
Wynne, K.
Nelson, B.
McGorry, P. D.
Amminger, G. P.
Nordentoft, M.
Krebs, M. O.
Riecher-Rössler, A.
Bressan, R A.
Barrantes Vidal, Neus
Borgwardt, S.
Ruhrmann, S.
Sachs, S.
Pantelis, Christos
van der Gaag, M.
de Haan, L.
Valmaggia, L.
Pollak, T. A.
Kempton, Matthew J.
Rutten, B. P. F.
Whelan, R.
Cannon, M.
Zammit, S.
Cagney, G.
Cotter, D. R.
McGuire, P. for the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI).
Rosa de la Cruz, Araceli
author_role author
author2 Föcking, M.
Healy, C.
Susai, S. R.
Heurich, M.
Wynne, K.
Nelson, B.
McGorry, P. D.
Amminger, G. P.
Nordentoft, M.
Krebs, M. O.
Riecher-Rössler, A.
Bressan, R A.
Barrantes Vidal, Neus
Borgwardt, S.
Ruhrmann, S.
Sachs, S.
Pantelis, Christos
van der Gaag, M.
de Haan, L.
Valmaggia, L.
Pollak, T. A.
Kempton, Matthew J.
Rutten, B. P. F.
Whelan, R.
Cannon, M.
Zammit, S.
Cagney, G.
Cotter, D. R.
McGuire, P. for the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI).
Rosa de la Cruz, Araceli
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Psicosi en els adolescents
Marcadors bioquímics
Pronòstic mèdic
Psychoses in adolescence
Biochemical markers
Prognosis
topic Psicosi en els adolescents
Marcadors bioquímics
Pronòstic mèdic
Psychoses in adolescence
Biochemical markers
Prognosis
description Importance: Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies. Objective: To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population. Design, Setting, and Participants: This diagnostic study comprised 2 case-control studies nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) and the Avon Longitudinal Study of Parents and Children (ALSPAC). EU-GEI is an international multisite prospective study of participants at CHR referred from local mental health services. ALSPAC is a United Kingdom-based general population birth cohort. Included were EU-GEI participants who met CHR criteria at baseline and ALSPAC participants who did not report PEs at age 12 years. Data were analyzed from September 2018 to April 2020. Main Outcomes and Measures: In EU-GEI, transition status was assessed by the Comprehensive Assessment of At-Risk Mental States or contact with clinical services. In ALSPAC, PEs at age 18 years were assessed using the Psychosis-Like Symptoms Interview. Proteomic data were obtained from mass spectrometry of baseline plasma samples in EU-GEI and plasma samples at age 12 years in ALSPAC. Support vector machine learning algorithms were used to develop predictive models. Results: The EU-GEI subsample (133 participants at CHR (mean [SD] age, 22.6 [4.5] years; 68 [51.1%] male) comprised 49 (36.8%) who developed psychosis and 84 (63.2%) who did not. A model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0%; and negative predictive value [NPV], 98.6%). Functional analysis of differentially expressed proteins implicated the complement and coagulation cascade. A model based on the 10 most predictive proteins accurately predicted transition status in training (AUC, 0.99; PPV, 76.9%; and NPV, 100%) and test (AUC, 0.92; PPV, 81.8%; and NPV, 96.8%) data. The ALSPAC subsample (121 participants from the general population with plasma samples available at age 12 years (61 [50.4%] male) comprised 55 participants (45.5%) with PEs at age 18 years and 61 (50.4%) without PEs at age 18 years. A model using proteomic data at age 12 years predicted PEs at age 18 years, with an AUC of 0.74 (PPV, 67.8%; and NPV, 75.8%). Conclusions and Relevance: In individuals at risk of psychosis, proteomic biomarkers may contribute to individualized prognosis and stratification strategies. These findings implicate early dysregulation of the complement and coagulation cascade in the development of psychosis outcomes.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/180215
url https://hdl.handle.net/2445/180215
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1001/jamapsychiatry.2020.2459
JAMA Psychiatry, 2020, vol. 78, num. 1, p. 77-90
https://doi.org/10.1001/jamapsychiatry.2020.2459
info:eu-repo/grantAgreement/EC/FP7/241909
dc.rights.none.fl_str_mv (c) American Medical Association (AMA), 2020
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) American Medical Association (AMA), 2020
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv American Medical Association (AMA)
publisher.none.fl_str_mv American Medical Association (AMA)
dc.source.none.fl_str_mv Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence.Mongan, D.Föcking, M.Healy, C.Susai, S. R.Heurich, M.Wynne, K.Nelson, B.McGorry, P. D.Amminger, G. P.Nordentoft, M.Krebs, M. O.Riecher-Rössler, A.Bressan, R A.Barrantes Vidal, NeusBorgwardt, S.Ruhrmann, S.Sachs, S.Pantelis, Christosvan der Gaag, M.de Haan, L.Valmaggia, L.Pollak, T. A.Kempton, Matthew J.Rutten, B. P. F.Whelan, R.Cannon, M.Zammit, S.Cagney, G.Cotter, D. R.McGuire, P. for the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI).Rosa de la Cruz, AraceliPsicosi en els adolescentsMarcadors bioquímicsPronòstic mèdicPsychoses in adolescenceBiochemical markersPrognosisImportance: Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies. Objective: To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population. Design, Setting, and Participants: This diagnostic study comprised 2 case-control studies nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) and the Avon Longitudinal Study of Parents and Children (ALSPAC). EU-GEI is an international multisite prospective study of participants at CHR referred from local mental health services. ALSPAC is a United Kingdom-based general population birth cohort. Included were EU-GEI participants who met CHR criteria at baseline and ALSPAC participants who did not report PEs at age 12 years. Data were analyzed from September 2018 to April 2020. Main Outcomes and Measures: In EU-GEI, transition status was assessed by the Comprehensive Assessment of At-Risk Mental States or contact with clinical services. In ALSPAC, PEs at age 18 years were assessed using the Psychosis-Like Symptoms Interview. Proteomic data were obtained from mass spectrometry of baseline plasma samples in EU-GEI and plasma samples at age 12 years in ALSPAC. Support vector machine learning algorithms were used to develop predictive models. Results: The EU-GEI subsample (133 participants at CHR (mean [SD] age, 22.6 [4.5] years; 68 [51.1%] male) comprised 49 (36.8%) who developed psychosis and 84 (63.2%) who did not. A model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0%; and negative predictive value [NPV], 98.6%). Functional analysis of differentially expressed proteins implicated the complement and coagulation cascade. A model based on the 10 most predictive proteins accurately predicted transition status in training (AUC, 0.99; PPV, 76.9%; and NPV, 100%) and test (AUC, 0.92; PPV, 81.8%; and NPV, 96.8%) data. The ALSPAC subsample (121 participants from the general population with plasma samples available at age 12 years (61 [50.4%] male) comprised 55 participants (45.5%) with PEs at age 18 years and 61 (50.4%) without PEs at age 18 years. A model using proteomic data at age 12 years predicted PEs at age 18 years, with an AUC of 0.74 (PPV, 67.8%; and NPV, 75.8%). Conclusions and Relevance: In individuals at risk of psychosis, proteomic biomarkers may contribute to individualized prognosis and stratification strategies. These findings implicate early dysregulation of the complement and coagulation cascade in the development of psychosis outcomes.American Medical Association (AMA)2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/180215Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1001/jamapsychiatry.2020.2459JAMA Psychiatry, 2020, vol. 78, num. 1, p. 77-90https://doi.org/10.1001/jamapsychiatry.2020.2459info:eu-repo/grantAgreement/EC/FP7/241909(c) American Medical Association (AMA), 2020info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1802152026-05-27T06:46:51Z
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