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Metabolomics reveals biomarkers of opioid use disorder
Opioid use disorder (OUD) is diagnosed using the qualitative criteria defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Diagnostic biomarkers for OUD do not currently exist. Our study focused on developing objective biological markers to differentiate chron...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862627/ https://www.ncbi.nlm.nih.gov/pubmed/33542199 http://dx.doi.org/10.1038/s41398-021-01228-7 |
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author | Ghanbari, Reza Li, Yuanyuan Pathmasiri, Wimal McRitchie, Susan Etemadi, Arash Pollock, Jonathan D. Poustchi, Hossein Rahimi-Movaghar, Afarin Amin-Esmaeili, Masoumeh Roshandel, Gholamreza Shayanrad, Amaneh Abaei, Behrouz Malekzadeh, Reza Sumner, Susan C. J. |
author_facet | Ghanbari, Reza Li, Yuanyuan Pathmasiri, Wimal McRitchie, Susan Etemadi, Arash Pollock, Jonathan D. Poustchi, Hossein Rahimi-Movaghar, Afarin Amin-Esmaeili, Masoumeh Roshandel, Gholamreza Shayanrad, Amaneh Abaei, Behrouz Malekzadeh, Reza Sumner, Susan C. J. |
author_sort | Ghanbari, Reza |
collection | PubMed |
description | Opioid use disorder (OUD) is diagnosed using the qualitative criteria defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Diagnostic biomarkers for OUD do not currently exist. Our study focused on developing objective biological markers to differentiate chronic opiate users with OUD from chronic opiate users without OUD. Using biospecimens from the Golestan Cohort Study, we compared the metabolomics profiles of high opium users who were diagnosed as OUD positive with high opium users who were diagnosed as OUD negative. High opium use was defined as maximum weekly opium usage greater than or equal to the median usage (2.4 g per week), and OUD was defined as having 2 or more DSM-5 criteria in any 12-month period. Among the 218 high opium users in this study, 80 were diagnosed as OUD negative, while 138 were diagnosed as OUD positive. Seven hundred and twelve peaks differentiated high opium users diagnosed as OUD positive from high opium users diagnosed as OUD negative. Stepwise logistic regression modeling of subject characteristics data together with the 712 differentiating peaks revealed a signature that is 95% predictive of an OUD positive diagnosis, a significant (p < 0.0001) improvement over a 63% accurate prediction based on subject characteristic data for these samples. These results suggest that a metabolic profile can be used to predict an OUD positive diagnosis. |
format | Online Article Text |
id | pubmed-7862627 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78626272021-02-16 Metabolomics reveals biomarkers of opioid use disorder Ghanbari, Reza Li, Yuanyuan Pathmasiri, Wimal McRitchie, Susan Etemadi, Arash Pollock, Jonathan D. Poustchi, Hossein Rahimi-Movaghar, Afarin Amin-Esmaeili, Masoumeh Roshandel, Gholamreza Shayanrad, Amaneh Abaei, Behrouz Malekzadeh, Reza Sumner, Susan C. J. Transl Psychiatry Article Opioid use disorder (OUD) is diagnosed using the qualitative criteria defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Diagnostic biomarkers for OUD do not currently exist. Our study focused on developing objective biological markers to differentiate chronic opiate users with OUD from chronic opiate users without OUD. Using biospecimens from the Golestan Cohort Study, we compared the metabolomics profiles of high opium users who were diagnosed as OUD positive with high opium users who were diagnosed as OUD negative. High opium use was defined as maximum weekly opium usage greater than or equal to the median usage (2.4 g per week), and OUD was defined as having 2 or more DSM-5 criteria in any 12-month period. Among the 218 high opium users in this study, 80 were diagnosed as OUD negative, while 138 were diagnosed as OUD positive. Seven hundred and twelve peaks differentiated high opium users diagnosed as OUD positive from high opium users diagnosed as OUD negative. Stepwise logistic regression modeling of subject characteristics data together with the 712 differentiating peaks revealed a signature that is 95% predictive of an OUD positive diagnosis, a significant (p < 0.0001) improvement over a 63% accurate prediction based on subject characteristic data for these samples. These results suggest that a metabolic profile can be used to predict an OUD positive diagnosis. Nature Publishing Group UK 2021-02-04 /pmc/articles/PMC7862627/ /pubmed/33542199 http://dx.doi.org/10.1038/s41398-021-01228-7 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ghanbari, Reza Li, Yuanyuan Pathmasiri, Wimal McRitchie, Susan Etemadi, Arash Pollock, Jonathan D. Poustchi, Hossein Rahimi-Movaghar, Afarin Amin-Esmaeili, Masoumeh Roshandel, Gholamreza Shayanrad, Amaneh Abaei, Behrouz Malekzadeh, Reza Sumner, Susan C. J. Metabolomics reveals biomarkers of opioid use disorder |
title | Metabolomics reveals biomarkers of opioid use disorder |
title_full | Metabolomics reveals biomarkers of opioid use disorder |
title_fullStr | Metabolomics reveals biomarkers of opioid use disorder |
title_full_unstemmed | Metabolomics reveals biomarkers of opioid use disorder |
title_short | Metabolomics reveals biomarkers of opioid use disorder |
title_sort | metabolomics reveals biomarkers of opioid use disorder |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862627/ https://www.ncbi.nlm.nih.gov/pubmed/33542199 http://dx.doi.org/10.1038/s41398-021-01228-7 |
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