Differential response to SSRI versus Placebo and distinct neural signatures among data-driven subgroups of patients with major depressive disorder

OBJECTIVE

To identify data-driven subgroups in Major Depressive Disorder (MDD) in order to elucidate underlying neural correlates and determine if these subgroups have utility in predicting response to antidepressant versus placebo.

METHODS

Using 27 clinical measures at baseline of Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study, participants with MDD (n=244) were sub grouped using principal component (PC) analysis. Baseline-to-week-8 changes in depression severity with sertraline versus placebo were compared in these subgroups. Resting-state functional connectivity of these subgroups were compared to those of healthy controls (n=38).

RESULTS

Eight subgroups were identified from four PCs: (PC1) severity of depression-associated symptoms, (PC2) sub-threshold mania and anhedonia, (PC3) childhood trauma, medical comorbidities, and sexual dysfunction, and (PC4) personality traits of openness and agreeableness. Participants with high childhood trauma experienced greater improvement with sertraline (Cohen's d=0.87), whereas those with either higher levels of subthreshold hypomanic symptoms (Cohen's d=0.67) or with lower levels of agreeableness and openness experienced greater improvement with placebo (Cohen's d=0.71). Participants with high childhood trauma had greater connectivity between salience and dorsal attention networks, whereas those with higher levels of subthreshold hypomanic symptoms and lower levels of agreeableness and openness had greater connectivity within limbic network and that of visual network with hippocampus and dorsal attention network.

CONCLUSION

Assessing history of childhood trauma, presence of subthreshold hypomanic symptoms and personality traits may help to identify subgroups of patients with MDD who respond differentially to sertraline or placebo and have distinct neural signatures.

Neuroimaging Heterogeneity in Psychosis: Neurobiological Underpinnings and Opportunities for Prognostic and Therapeutic Innovation

Heterogeneity in symptom presentation, outcomes, and treatment response has long been problematic for researchers aiming to identify biological markers of schizophrenia or psychosis. However, there is increasing recognition that there may likely be no such general illness markers, which is consistent with the notion of a group of schizophrenia(s) that may have both shared and unique neurobiological pathways. Instead, strategies aiming to capitalize on or leverage such heterogeneity may help uncover neurobiological pathways that may then be used to stratify groups of patients for prognostic purposes or for therapeutic trials. A shift toward larger sample sizes with adequate statistical power to overcome small effect sizes and disentangle the shared variance among different brain-imaging or behavioral variables has become a priority for the field. In addition, recognition that two individuals with the same clinical diagnosis may be more different from each other (at brain, genetic, and behavioral levels) than from another individual in a different disorder or nonclinical control group-coupled with computational advances-has catapulted data-driven efforts forward. Emerging challenges for this new approach include longitudinal stability of new subgroups, demonstration of validity, and replicability. The "litmus test" will be whether computational approaches that are successfully identifying groups of patients who share features in common, more than current DSM diagnostic constructs, also provide better prognostic accuracy over time and in addition lead to enhancements in treatment response and outcomes. These are the factors that matter most to patients, families, providers, and payers.