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Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response
Precision medicine has been considered a promising approach to diagnosis, treatment, and various interventions, considering the individual clinical and biological characteristics. Recent advances in biomarker development hold promise for guiding a new era of precision medicine style trials for psych...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779239/ https://www.ncbi.nlm.nih.gov/pubmed/35055346 http://dx.doi.org/10.3390/jpm12010031 |
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author | Lee, Ho Sung Kim, Ji Sun |
author_facet | Lee, Ho Sung Kim, Ji Sun |
author_sort | Lee, Ho Sung |
collection | PubMed |
description | Precision medicine has been considered a promising approach to diagnosis, treatment, and various interventions, considering the individual clinical and biological characteristics. Recent advances in biomarker development hold promise for guiding a new era of precision medicine style trials for psychiatric illnesses, including psychosis. Electroencephalography (EEG) can directly measure the full spatiotemporal dynamics of neural activation associated with a wide variety of cognitive processes. This manuscript reviews three aspects: prediction of diagnosis, prognostic aspects of disease progression and outcome, and prediction of treatment response that might be helpful in understanding the current status of electrophysiological biomarkers in precision medicine for patients with psychosis. Although previous EEG analysis could not be a powerful method for the diagnosis of psychiatric illness, recent methodological advances have shown the possibility of classifying and detecting mental illness. Some event-related potentials, such as mismatch negativity, have been associated with neurocognition, functioning, and illness progression in schizophrenia. Resting state studies, sophisticated ERP measures, and machine-learning approaches could make technical progress and provide important knowledge regarding neurophysiology, disease progression, and treatment response in patients with schizophrenia. Identifying potential biomarkers for the diagnosis and treatment response in schizophrenia is the first step towards precision medicine. |
format | Online Article Text |
id | pubmed-8779239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87792392022-01-22 Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response Lee, Ho Sung Kim, Ji Sun J Pers Med Review Precision medicine has been considered a promising approach to diagnosis, treatment, and various interventions, considering the individual clinical and biological characteristics. Recent advances in biomarker development hold promise for guiding a new era of precision medicine style trials for psychiatric illnesses, including psychosis. Electroencephalography (EEG) can directly measure the full spatiotemporal dynamics of neural activation associated with a wide variety of cognitive processes. This manuscript reviews three aspects: prediction of diagnosis, prognostic aspects of disease progression and outcome, and prediction of treatment response that might be helpful in understanding the current status of electrophysiological biomarkers in precision medicine for patients with psychosis. Although previous EEG analysis could not be a powerful method for the diagnosis of psychiatric illness, recent methodological advances have shown the possibility of classifying and detecting mental illness. Some event-related potentials, such as mismatch negativity, have been associated with neurocognition, functioning, and illness progression in schizophrenia. Resting state studies, sophisticated ERP measures, and machine-learning approaches could make technical progress and provide important knowledge regarding neurophysiology, disease progression, and treatment response in patients with schizophrenia. Identifying potential biomarkers for the diagnosis and treatment response in schizophrenia is the first step towards precision medicine. MDPI 2022-01-02 /pmc/articles/PMC8779239/ /pubmed/35055346 http://dx.doi.org/10.3390/jpm12010031 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Lee, Ho Sung Kim, Ji Sun Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response |
title | Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response |
title_full | Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response |
title_fullStr | Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response |
title_full_unstemmed | Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response |
title_short | Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response |
title_sort | implication of electrophysiological biomarkers in psychosis: focusing on diagnosis and treatment response |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779239/ https://www.ncbi.nlm.nih.gov/pubmed/35055346 http://dx.doi.org/10.3390/jpm12010031 |
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