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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, Lencz, Todd, Cao, Hengyi, Kraguljac, Nina, Dhamala, Elvisha, Homan, Philipp, Horga, Guillermo, Sarpal, Deepak, Argyelan, Miklos, Gallego, Juan, Cholewa, John, Barber, Anita, Kane, John, Maholtra, Anil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441472/
https://www.ncbi.nlm.nih.gov/pubmed/37609149
http://dx.doi.org/10.21203/rs.3.rs-3185688/v1
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author Rubio, Jose
Lencz, Todd
Cao, Hengyi
Kraguljac, Nina
Dhamala, Elvisha
Homan, Philipp
Horga, Guillermo
Sarpal, Deepak
Argyelan, Miklos
Gallego, Juan
Cholewa, John
Barber, Anita
Kane, John
Maholtra, Anil
author_facet Rubio, Jose
Lencz, Todd
Cao, Hengyi
Kraguljac, Nina
Dhamala, Elvisha
Homan, Philipp
Horga, Guillermo
Sarpal, Deepak
Argyelan, Miklos
Gallego, Juan
Cholewa, John
Barber, Anita
Kane, John
Maholtra, Anil
author_sort Rubio, Jose
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-104414722023-08-22 Replication of a neuroimaging biomarker for striatal dysfunction in psychosis Rubio, Jose Lencz, Todd Cao, Hengyi Kraguljac, Nina Dhamala, Elvisha Homan, Philipp Horga, Guillermo Sarpal, Deepak Argyelan, Miklos Gallego, Juan Cholewa, John Barber, Anita Kane, John Maholtra, Anil Res Sq 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. American Journal Experts 2023-08-07 /pmc/articles/PMC10441472/ /pubmed/37609149 http://dx.doi.org/10.21203/rs.3.rs-3185688/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Rubio, Jose
Lencz, Todd
Cao, Hengyi
Kraguljac, Nina
Dhamala, Elvisha
Homan, Philipp
Horga, Guillermo
Sarpal, Deepak
Argyelan, Miklos
Gallego, Juan
Cholewa, John
Barber, Anita
Kane, John
Maholtra, 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/PMC10441472/
https://www.ncbi.nlm.nih.gov/pubmed/37609149
http://dx.doi.org/10.21203/rs.3.rs-3185688/v1
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