Identifying subtypes of depression in clinician-annotated text: a retrospective cohort study

Current criteria for depression are imprecise and do not accurately characterize its distinct clinical presentations. As a result, its diagnosis lacks clinical utility in both treatment and research settings. Data-driven efforts to refine criteria have typically focused on a limited set of symptoms that do not reflect the disorder’s heterogeneity. By contrast, clinicians often write about patients in depth, creating descriptions that may better characterize depression. However, clinical text is not commonly used to this end. Here we show that clinically relevant depressive subtypes can be derived from unstructured electronic health records. Five subtypes were identified amongst 18,314 patients with depression treated at a large mental healthcare provider by using unsupervised machine learning: severe-typical, psychotic, mild-typical, agitated, and anergic-apathetic. Subtypes were used to place patients in groups for validation; groups were found to be associated with future outcomes and characteristics that were consistent with the subtypes. These associations suggest that these categorizations are actionable due to their validity with respect to disease prognosis. Moreover, they were derived with automated techniques that might theoretically be widely implemented, allowing for future analyses in more varied populations and settings. Additional research, especially with respect to treatment response, may prove useful in further evaluation.

Biological mechanisms of atypical and melancholic major depressive disorder

Background: This review summarizes recent findings in molecular biology and neuroimaging and their applicability to the classification and identification of depression. We discuss whether there is reliable evidence that could become a basis for biomarkers or subtyping that may enhance our understanding of the biological foundations of depression and may be useful for clinical practice with respect to diagnosis and prognosis as well as the selection of treatments. Objective: The purpose of this investigation is to present molecular mechanisms that contribute to different origins of depressions that could prove useful in daily psychiatric clinic based practices. Method: The authors analyzed and summarized electronic publications available via PubMed, Science Direct, Google Scholar, and Scopus. Results: The introduction of molecular diagnostics methods into medical practice is a promising method to improve the accuracy of the diagnosis of depression in clinical settings. The literature analysis revealed structural changes in some areas of the brain, its neuroplasticity, as well as changes at the molecular, epigenetic, and genetic levels. However, there are no current reliable biomarkers for differential diagnosis of the types and subtypes of depression. Conclusion: Major depressive disorder is a biologically and genetically heterogeneous disorder. Given its complexity, subtyping is worthwhile to identify biological bases of conditions. The literature review provides ample findings that reveal possible underlying biological mechanisms associated with atypical and melancholic depression. Additional, focused research should be continued with respect to the molecular and genetic biology of different types of depression. There already are promising findings, but additional research to define biologically based depressive subtypes is needed and worthwhile.

Characteristics and subtypes of depressive symptoms in Chinese female breast cancer patients of different ages: a cross-sectional study

<abstract><sec> <title>Purpose</title> <p>To identify the characteristics and subtypes of depressive symptoms and explore the relationship between depressive subtypes and age among Chinese female breast cancer patients.</p> </sec><sec> <title>Method</title> <p>In this cross-sectional study, 566 breast cancer patients were recruited from three tertiary comprehensive hospital in Shandong Province, China through convenient sampling from April 2013 to June 2019. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9). Data analyses included descriptive analyses, latent class analysis.</p> </sec><sec> <title>Results</title> <p>There were significant differences in specific depressive symptoms by age group, but no significant difference in total scores on PHQ-9. The depressive subtypes were severe (Class 4), relatively severe (Class 3; with lower psychomotor agitation/retardation and suicidal ideation), moderate (Class 2; with higher psychomotor agitation/retardation and suicidal ideation), and mild depressive symptoms (Class 1). The distribution of depression subtypes is different in various age groups. In the 45–59 age groups, severe symptoms subtype showed the highest ratios (i.e. 50.3%).</p> </sec><sec> <title>Conclusion</title> <p>This is the first study that analyses depressive symptom characteristics and identifies depressive subtypes in Chinese women with breast cancer across ages to explore symptom heterogeneity. Our findings can contribute to identifying the mechanisms behind these relationships and developing targeted interventions for patients with specific depressive subtypes.</p> </sec></abstract>

Inflammatory Proteins and Clinical Response to Psychological Therapy in Patients with Depression: An Exploratory Study

In people with depression, immune dysfunctions have been linked with treatment non-response, but examinations of psychological therapy outcomes, particularly longitudinal biomarker studies, are rare. This study investigated relationships between inflammation, depressive subtypes and clinical outcomes to psychological therapy. Adults with depression (n = 96) were assessed before and after a course of naturalistically-delivered psychological therapy. In total, 32 serum inflammatory proteins were examined alongside therapy outcomes and depressive subtypes (somatic/cognitive symptom subtype, and bipolar/unipolar depression). Overall, 49% of participants responded to treatment. High levels of tumour necrosis factor (TNFα), interleukin-6 (IL-6) and soluble intracellular adhesion molecule-1 (sICAM1), and low interferon-γ (IFNγ), preceded a poorer response to therapy. After therapy, non-responders had elevated c-reactive protein (CRP), thymus and activation-regulated chemokine (TARC) and macrophage chemoattractant protein-4 (MCP4), and attenuated IFNy. Non-somatic depressive symptoms were universally not associated with proteins, while somatic-depressive symptom severity was positively correlated with several pro-inflammatory markers. In the somatic subgroup only, IL-6 and serum amyloid alpha (SAA) decreased between pre- and post-therapy timepoints. Regardless of treatment response, IL-7, IL-8, IL-15 and IL-17 increased over time. These results suggest that inflammation is associated with somatic symptoms of depression and non-response to psychological therapy. Future work may enhance the prospective prediction of treatment-response by examining larger samples of individuals undertaking standardised treatment programmes.

Diagnosis, classification, and differential diagnosis of mood disorders

This chapter discusses DSM and non-DSM definitions and approaches to mood illness. Before 1980, the concept of manic–depressive illness (MDI) meant both bipolar illness and recurrent unipolar depression. Evidence on diagnostic validators since 1980 has not strengthened that claim and may be interpreted to support the original MDI concept, that is, that bipolar illness and unipolar depression are part of the same overall disease (MDI). As a corollary, the concept of major depressive disorder (MDD) may represent a spectrum of different depressive subtypes: mixed (depression with manic symptoms), melancholic, pure, vascular, and neurotic depression. Each subtype differs from the other, based on diagnostic validators of course, genetics, and biological aspects and/or treatment effects. The scientific evidence for this heterogeneity of MDD appears to weaken the claim dating to DSM-III in 1980 that this condition is a different diagnosis/illness from bipolar disorder. The differential diagnosis of mood conditions is described.