Rethinking the Treatment-Resistant Depression.
Advances in experimental medicine and biology 2026 DOI: 10.1007/978-981-95-6872-7_5 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Review Peer reviewed |
|---|---|
| Topics | Ketamine Depression |
| Keywords | Biomarkers Individualized treatment Inflammation Neural regulation Refractory depression |
| Citations | 1 |
| Key findings | Treatment-resistant depression affects about one-third of people with major depression and involves glutamatergic dysregulation, default-mode network hyperactivity, impaired neuroplasticity, chronic inflammation, and epigenetic changes, with distinct subtypes guiding personalized care. |
Abstract
Treatment-resistant depression (TRD) affects about one-third of people with major depression and leads to higher suicide rates, impaired functioning, and increased healthcare use. Originally defined as nonresponse to tricyclic antidepressants, TRD now encompasses inadequate response to multiple antidepressant classes, psychotherapy, and neuromodulation. Inconsistent criteria-varying by agency, required treatment failures, dosage/duration thresholds, and symptom scales-complicate prevalence estimates and clinical decision-making. Differential diagnosis is challenging: many presumed TRD cases actually involve bipolar depression, personality or anxiety disorders, somatic symptom disorders, or early neurocognitive conditions. Neurobiological research identifies glutamatergic dysregulation, default-mode network hyperactivity, impaired neuroplasticity, chronic inflammation, and epigenetic changes as TRD markers. Clinically, TRD patients experience persistent anhedonia, cognitive deficits, somatic complaints, and sleep disturbances. Latent class analysis yields subtypes-anxiety-agitation, cognitive-executive dysfunction, somatic-dominant, and affective-deficit-with distinct treatment responses. Biomarker-driven categories (e.g., high-inflammation profiles, connectivity patterns) and developmental/response-based subgroups (e.g., early-onset, ketamine-responsive) guide personalized care. Future work must standardize definitions, integrate multimodal biomarkers, and validate criteria across cultures to improve early identification, prognosis, and targeted interventions.