重性抑郁障碍
抗抑郁药
内科学
医学
萧条(经济学)
背景(考古学)
生物标志物
肿瘤科
临床心理学
心理学
经济
海马体
扁桃形结构
化学
古生物学
宏观经济学
生物
生物化学
作者
Francesco Benedetti,Sara Poletti,Benedetta Vai,Mario Gennaro Mazza,Cristina Lorenzi,S. Brioschi,Veronica Aggio,Igor Branchi,Cristina Colombo,Roberto Furlan,Raffaella Zanardi
标识
DOI:10.1016/j.euroneuro.2020.11.009
摘要
Raised pro-inflammatory immune/inflammatory setpoints, leading to an increased production of peripheral cytokines, have been associated with Major Depressive Disorder (MDD) and with failure to respond to first-line antidepressant drugs. However, the usefulness of these biomarkers in clinical psychopharmacology has been questioned because single findings did not translate into the clinical practice, where patients are prescribed treatments upon clinical need. We studied a panel of 27 inflammatory biomarkers in a sample of 108 inpatients with MDD, treated with antidepressant monotherapy for 4 weeks upon clinical need in a specialized hospital setting, and assessed the predictive effect of baseline peripheral measures of inflammation on antidepressing efficacy (response rates and time-lagged pattern of decrease of depression severity) using a machine-learning approach with elastic net penalized regression, and multivariate analyses in the context of the general linear model. When considering both categorical and continuous measures of response, baseline levels of IL-1β predicted non-response to antidepressants, with the predicted probability to respond being highly dispersed at low levels of IL-1β, and stratifying toward non-response when IL-1β is high. Significant negative effects were also detected for TNF-α, while IL-12 weakly predicted response. These findings support the usefulness of inflammatory biomarkers in the clinical psychopharmacology of depression, and add to ongoing research efforts aiming at defining reliable cutoff values to identify depressed patients in clinical settings with high inflammation, and low probability to respond.
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