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The probabilistic reward task (PRT) has identified reward learning impairments in those with major depressive disorder (MDD), as well as anhedonia-specific reward learning impairments. However, attempts to validate the anhedonia-specific impairments have produced inconsistent findings. Thus, we seek to determine whether the Reward Behavior Disengagement (RBD), our proposed economic augmentation of PRT, differs between MDD participants and controls, and whether there is a level at which RBD is high enough for depressed participants to be considered objectively disengaged. Data were gathered as part of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a double-blind, placebo-controlled clinical trial of antidepressant response. Participants included 195 individuals with moderate to severe MDD (Quick Inventory of Depressive Symptomatology (QIDS–SR) score ≥ 15), not in treatment for depression, and with complete PRT data. Healthy controls (n = 40) had no history of psychiatric illness, a QIDS–SR score < 8, and complete PRT data. Participants with MDD were treated with sertraline or placebo for 8 weeks (stage I of the EMBARC trial). RBD was applied to PRT data using discriminant analysis, and classified MDD participants as reward task engaged (n = 137) or reward task disengaged (n = 58), relative to controls. Reward task engaged/disengaged groups were compared on sociodemographic features, reward–behavior, and sertraline/placebo response (Hamilton Depression Rating Scale scores). Reward task disengaged MDD participants responded only to sertraline, whereas those who were reward task engaged responded to sertraline and placebo (F(1293) = 4.33, p = 0.038). Reward task engaged/disengaged groups did not differ otherwise. RBD was predictive of reward impairment in depressed patients and may have clinical utility in identifying patients who will benefit from antidepressants. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a chronic condition that affects one in six adults in the US during their lifetime. The current practice of antidepressant medication prescription is a trial-and-error process. Additionally, over a third of patients with MDD fail to respond to two or more antidepressant treatments. There are no valid clinical markers to personalize currently available antidepressant medications, all of which have similar mechanisms targeting monoamine neurotransmission. The goal of this review is to summarize the recent findings of immune dysfunction in patients with MDD, the utility of inflammatory markers to personalize treatment selection, and the potential of targeting inflammation to develop novel antidepressant treatments. To personalize antidepressant prescription, a c-reactive protein (CRP)-matched treatment assignment can be rapidly implemented in clinical practice with point-of-care fingerstick tests. With this approach, 4.5 patients need to be treated for 1 additional remission as compared to a CRP-mismatched treatment assignment. Anti-cytokine treatments may be effective as novel antidepressants. Monoclonal antibodies against proinflammatory cytokines, such as interleukin 6, interleukin 17, and tumor necrosis factor α, have demonstrated antidepressant effects in patients with chronic inflammatory conditions who report significant depressive symptoms. Additional novel antidepressant strategies targeting inflammation include pharmaceutical agents that block the effect of systemic inflammation on the central nervous system. In conclusion, inflammatory markers offer the potential not only to personalize antidepressant prescription but also to guide the development of novel mechanistically-guided antidepressant treatments. [ABSTRACT FROM AUTHOR]

Over a third of patients with major depressive disorder (MDD) do not have an adequate response to first-line antidepressant treatments, i.e., they have treatment-resistant depression (TRD). These patients tend to have a more severe course of illness and are at an increased risk of suicide. Next step treatment options for patients with TRD, include switching to a different antidepressant, combining more than one antidepressant, or augmenting an antidepressant with another (non-antidepressant) medication. It is unclear which of these treatment approaches should be applied to a given patient, and in what order. Due to this ambiguity, comparing antidepressants and augmentation agents on the basis of their efficacy, tolerability, and speed of symptom relief would be beneficial for clinicians. To accomplish this, a systematic search was conducted following PRISMA guidelines. Only randomized controlled trials were included in this qualitative synthesis, resulting in 66 articles. This review identified several effective pharmaco-therapeutic strategies that are currently available for patients with TRD. Ketamine and esketamine appear to be effective for the treatment of TRD. Augmentation with certain second generation antipsychotics, such as quetiapine or aripiprazole is likewise effective, and may be preferred over switching to antidepressant monotherapy. While the combination of olanzapine and fluoxetine was one of the first pharmacotherapy approved for TRD, and its use may be limited by metabolic side-effects. Other effective strategies include augmentation with lithium, liothyronine (T3), lamotrigine, or combination of antidepressants including bupropion, tricyclics, or mirtazapine. There is insufficient research to demonstrate the efficacy of ziprasidone or levothyroxine (T4). A shared decision-making approach is recommended to guide treatment selection to address each patient's individual needs. [ABSTRACT FROM AUTHOR]

Background: Elevated S100 calcium binding protein B (S100B) levels in systemic circulation may induce neuroinflammation and reflect greater blood–brain barrier (BBB) dysfunction. Neuroinflammation in patients with major depressive disorder (MDD), in turn, may reduce likelihood of improvement with serotonergic antidepressants. Methods: Levels of S100B were measured in plasma samples obtained prior to initiation of treatment with bupropion-plus-escitalopram, escitalopram-plus-placebo, or venlafaxine-plus-mirtazapine in participants of Combining Medications to Enhance Depression Outcomes trial (n = 153). Depression severity was measured with 16-item Quick Inventory of Depressive Symptomatology Self-Report and anhedonia was measured with 3 items of 30-item Inventory of Depressive Symptomatology. Differential changes in depression severity and anhedonia over acute-phase (baseline, weeks 1, 2, 4, 6, 8, 10, and 12) in the three treatment arms were tested with logS100B-by-treatment-arm interaction in mixed model analyses after controlling for age, gender, and body mass index. Results: There was a significant logS100B-by-treatment-arm interaction for anhedonia (F = 3.21; df = 2, 142; p = 0.04) but not for overall depression severity (F = 1.99; df = 2, 142; p = 0.14). Higher logS100B levels were associated with smaller reductions in anhedonia (effect size = 0.67, p = 0.047) in escitalopram monotherapy but not in the other two arms. Correlation coefficients of anhedonia severity averaged over acute-phase (including baseline) with baseline S100B levels were 0.57, −0.19, and 0.22 for escitalopram monotherapy, bupropion-plus-escitalopram and venlafaxine-plus-mirtazapine arms respectively. Conclusion: Higher baseline S100B levels in depressed patients resulted in poorer response to escitalopram monotherapy. Addition of bupropion, a dopaminergic antidepressant, partially mitigated this effect. [ABSTRACT FROM AUTHOR]

Major depressive disorder affects one in five adults in the United States. While practice guidelines recommend universal screening for depression in primary care settings, clinical outcomes suffer in the absence of optimal models to manage those who screen positive for depression. The current practice of employing additional mental health professionals perpetuates the assumption that primary care providers (PCP) cannot effectively manage depression, which is not feasible, due to the added costs and shortage of mental health professionals. We have extended our previous work, which demonstrated similar treatment outcomes for depression in primary care and psychiatric settings, using measurement-based care (MBC) by developing a model, called Primary Care First (PCP-First), that empowers PCPs to effectively manage depression in their patients. This model incorporates health information technology tools, through an electronic health records (EHR) integrated web-application and facilitates the following five components: (1) Screening (2) diagnosis (3) treatment selection (4) treatment implementation and (5) treatment revision. We have implemented this model as part of a quality improvement project, called VitalSign6, and will measure its success using the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) framework. In this report, we provide the background and rationale of the PCP-First model and the operationalization of VitalSign6 project. [ABSTRACT FROM AUTHOR]