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Replication of a neuroimaging biomarker for striatal dysfunction in psychosis

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to dis...

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Autores principales: Rubio, Jose M, Lencz, Todd, Cao, Hengyi, Kraguljac, Nina, Dhamala, Elvisha, Homan, Philipp, Horga, Guillermo, Sarpal, Deepak K., Argyelan, Miklos, Gallego, Juan, Cholewa, John, Barber, Anita, Kane, John, Malhotra, Anil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371185/
https://www.ncbi.nlm.nih.gov/pubmed/37503088
http://dx.doi.org/10.1101/2023.07.17.23292779
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author Rubio, Jose M
Lencz, Todd
Cao, Hengyi
Kraguljac, Nina
Dhamala, Elvisha
Homan, Philipp
Horga, Guillermo
Sarpal, Deepak K.
Argyelan, Miklos
Gallego, Juan
Cholewa, John
Barber, Anita
Kane, John
Malhotra, Anil
author_facet Rubio, Jose M
Lencz, Todd
Cao, Hengyi
Kraguljac, Nina
Dhamala, Elvisha
Homan, Philipp
Horga, Guillermo
Sarpal, Deepak K.
Argyelan, Miklos
Gallego, Juan
Cholewa, John
Barber, Anita
Kane, John
Malhotra, Anil
author_sort Rubio, Jose M
collection PubMed
description To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n=101) from healthy controls (n=51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n=97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC=75.4%, 95%CI=67.0%-83.3%; in non-affective psychosis AUC=80.5%, 95%CI=72.1-88.0%, and in affective psychosis AUC=58.7%, 95%CI=44.2-72.0%). Test-retest reliability ranged between ICC=0.48 (95%CI=0.35-0.59) and ICC=0.22 (95%CI=0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC=0.51 (95%CI=0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 minutes, diagnostic classification of the FSA increased from AUC=71.7% (95%CI=63.1%-80.3%) to 75.4% (95%CI=67.0%-83.3%) and phase encoding direction reliability from ICC=0.29 (95%CI=0.14-0.43) to ICC=0.51 (95%CI=0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic – but not prognostic – biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.
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spelling pubmed-103711852023-07-27 Replication of a neuroimaging biomarker for striatal dysfunction in psychosis Rubio, Jose M Lencz, Todd Cao, Hengyi Kraguljac, Nina Dhamala, Elvisha Homan, Philipp Horga, Guillermo Sarpal, Deepak K. Argyelan, Miklos Gallego, Juan Cholewa, John Barber, Anita Kane, John Malhotra, Anil medRxiv Article To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n=101) from healthy controls (n=51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n=97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC=75.4%, 95%CI=67.0%-83.3%; in non-affective psychosis AUC=80.5%, 95%CI=72.1-88.0%, and in affective psychosis AUC=58.7%, 95%CI=44.2-72.0%). Test-retest reliability ranged between ICC=0.48 (95%CI=0.35-0.59) and ICC=0.22 (95%CI=0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC=0.51 (95%CI=0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 minutes, diagnostic classification of the FSA increased from AUC=71.7% (95%CI=63.1%-80.3%) to 75.4% (95%CI=67.0%-83.3%) and phase encoding direction reliability from ICC=0.29 (95%CI=0.14-0.43) to ICC=0.51 (95%CI=0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic – but not prognostic – biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data. Cold Spring Harbor Laboratory 2023-07-23 /pmc/articles/PMC10371185/ /pubmed/37503088 http://dx.doi.org/10.1101/2023.07.17.23292779 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Rubio, Jose M
Lencz, Todd
Cao, Hengyi
Kraguljac, Nina
Dhamala, Elvisha
Homan, Philipp
Horga, Guillermo
Sarpal, Deepak K.
Argyelan, Miklos
Gallego, Juan
Cholewa, John
Barber, Anita
Kane, John
Malhotra, Anil
Replication of a neuroimaging biomarker for striatal dysfunction in psychosis
title Replication of a neuroimaging biomarker for striatal dysfunction in psychosis
title_full Replication of a neuroimaging biomarker for striatal dysfunction in psychosis
title_fullStr Replication of a neuroimaging biomarker for striatal dysfunction in psychosis
title_full_unstemmed Replication of a neuroimaging biomarker for striatal dysfunction in psychosis
title_short Replication of a neuroimaging biomarker for striatal dysfunction in psychosis
title_sort replication of a neuroimaging biomarker for striatal dysfunction in psychosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371185/
https://www.ncbi.nlm.nih.gov/pubmed/37503088
http://dx.doi.org/10.1101/2023.07.17.23292779
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