Metabolomics reveals biomarkers of opioid use disorder
Abstract 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 differenti...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Publishing Group
2021-02-01
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| Series: | Translational Psychiatry |
| Online Access: | https://doi.org/10.1038/s41398-021-01228-7 |
| _version_ | 1818459649687420928 |
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| author | Reza Ghanbari Yuanyuan Li Wimal Pathmasiri Susan McRitchie Arash Etemadi Jonathan D. Pollock Hossein Poustchi Afarin Rahimi-Movaghar Masoumeh Amin-Esmaeili Gholamreza Roshandel Amaneh Shayanrad Behrouz Abaei Reza Malekzadeh Susan C. J. Sumner |
| author_facet | Reza Ghanbari Yuanyuan Li Wimal Pathmasiri Susan McRitchie Arash Etemadi Jonathan D. Pollock Hossein Poustchi Afarin Rahimi-Movaghar Masoumeh Amin-Esmaeili Gholamreza Roshandel Amaneh Shayanrad Behrouz Abaei Reza Malekzadeh Susan C. J. Sumner |
| author_sort | Reza Ghanbari |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-14T23:17:43Z |
| format | Article |
| id | doaj.art-11853b79c46c4b648fd605f2499ea286 |
| institution | Directory Open Access Journal |
| issn | 2158-3188 |
| language | English |
| last_indexed | 2024-12-14T23:17:43Z |
| publishDate | 2021-02-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Translational Psychiatry |
| spelling | doaj.art-11853b79c46c4b648fd605f2499ea2862022-12-21T22:44:02ZengNature Publishing GroupTranslational Psychiatry2158-31882021-02-0111111010.1038/s41398-021-01228-7Metabolomics reveals biomarkers of opioid use disorderReza Ghanbari0Yuanyuan Li1Wimal Pathmasiri2Susan McRitchie3Arash Etemadi4Jonathan D. Pollock5Hossein Poustchi6Afarin Rahimi-Movaghar7Masoumeh Amin-Esmaeili8Gholamreza Roshandel9Amaneh Shayanrad10Behrouz Abaei11Reza Malekzadeh12Susan C. J. Sumner13Department of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel HillDepartment of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel HillDepartment of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel HillDepartment of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel HillDivision of Cancer Epidemiology and Genetics, National Cancer Institute (NCI)Genetics, Epigenetics, and Developmental Neuroscience Branch, National Institute on Drug Abuse (NIDA)Digestive Oncology Research Center, Digestive Diseases Research Institute, Tehran University of Medical ScienceIranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences (TUMS)Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences (TUMS)Golestan Research Center of Gastroenterology and Hepatology, Golestan University of Medical SciencesDigestive Oncology Research Center, Digestive Diseases Research Institute, Tehran University of Medical ScienceDigestive Oncology Research Center, Digestive Diseases Research Institute, Tehran University of Medical ScienceDigestive Oncology Research Center, Digestive Diseases Research Institute, Tehran University of Medical ScienceDepartment of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel HillAbstract 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.https://doi.org/10.1038/s41398-021-01228-7 |
| spellingShingle | Reza Ghanbari Yuanyuan Li Wimal Pathmasiri Susan McRitchie Arash Etemadi Jonathan D. Pollock Hossein Poustchi Afarin Rahimi-Movaghar Masoumeh Amin-Esmaeili Gholamreza Roshandel Amaneh Shayanrad Behrouz Abaei Reza Malekzadeh Susan C. J. Sumner Metabolomics reveals biomarkers of opioid use disorder Translational Psychiatry |
| 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 |
| url | https://doi.org/10.1038/s41398-021-01228-7 |
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