• Annamaria Cattaneo, Clarissa Ferrari, Rudolf Uher, Luisella Bocchio-Chiavetto, Marco Andrea Riva, MRC ImmunoPsychiatry Consortium, and Carmine M Pariante.
• Stress, Psychiatry and Immunology Laboratory, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom (Drs Cattaneo and Pariante); Biological Psychiatry Unit, IRCCS Fatebenefratelli Institute, Brescia, Italy (Dr Cattaneo); Statistical Service, IRCCS Fatebenefratelli Institute, Brescia, Italy (Dr Ferrari); Genetic Unit, IRCCS Fatebenefratelli Institute Brescia, Italy and Faculty of Psychology, eCampus University, Novedrate, Como, Italy (Dr Bocchio-Chiavetto); Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada (Dr Uher); The Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom (Dr Uher); Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy (Dr Riva). annamaria.cattaneo@kcl.ac.uk.
• Int. J. Neuropsychopharmacol. 2016 Oct 1; 19 (10).

BackgroundIncreased 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.MethodsHere 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.ResultsWe 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.ConclusionWe 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.© The Author 2016. Published by Oxford University Press on behalf of CINP.

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