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Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients
BACKGROUND: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an indivi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5091822/ https://www.ncbi.nlm.nih.gov/pubmed/27207917 http://dx.doi.org/10.1093/ijnp/pyw045 |
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author | Cattaneo, Annamaria Ferrari, Clarissa Uher, Rudolf Bocchio-Chiavetto, Luisella Riva, Marco Andrea Pariante, Carmine M. |
author_facet | Cattaneo, Annamaria Ferrari, Clarissa Uher, Rudolf Bocchio-Chiavetto, Luisella Riva, Marco Andrea Pariante, Carmine M. |
author_sort | Cattaneo, Annamaria |
collection | PubMed |
description | BACKGROUND: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms. METHODS: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. RESULTS: We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration. CONCLUSION: We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more assertive antidepressant strategies, including the addition of other antidepressants or antiinflammatory drugs. |
format | Online Article Text |
id | pubmed-5091822 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-50918222016-11-03 Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients Cattaneo, Annamaria Ferrari, Clarissa Uher, Rudolf Bocchio-Chiavetto, Luisella Riva, Marco Andrea Pariante, Carmine M. Int J Neuropsychopharmacol Regular Research Article BACKGROUND: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms. METHODS: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. RESULTS: We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration. CONCLUSION: We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more assertive antidepressant strategies, including the addition of other antidepressants or antiinflammatory drugs. Oxford University Press 2016-05-11 /pmc/articles/PMC5091822/ /pubmed/27207917 http://dx.doi.org/10.1093/ijnp/pyw045 Text en © The Author 2016. Published by Oxford University Press on behalf of CINP. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Regular Research Article Cattaneo, Annamaria Ferrari, Clarissa Uher, Rudolf Bocchio-Chiavetto, Luisella Riva, Marco Andrea Pariante, Carmine M. Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients |
title | Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients |
title_full | Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients |
title_fullStr | Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients |
title_full_unstemmed | Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients |
title_short | Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients |
title_sort | absolute measurements of macrophage migration inhibitory factor and interleukin-1-β mrna levels accurately predict treatment response in depressed patients |
topic | Regular Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5091822/ https://www.ncbi.nlm.nih.gov/pubmed/27207917 http://dx.doi.org/10.1093/ijnp/pyw045 |
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