Aug 2026· OBM Neurobiology· Vol 010, pp. 1-24· 0 citations· 42 references
TL;DR
Results indicate that multi-omics integration, in addition to explaining the molecular architecture of MDD, also characterizes patient subgroups with pathophysiological mechanisms, dimensions of symptoms, and disease treatment, which demonstrates that there is a shift in psychiatry toward a more mechanistic approach.
Abstract
Major depressive disorder (MDD) has a widespread heterogeneity as per the psychiatric nosology, and traditional symptom-based diagnosis frameworks do not offer many clues regarding tailored therapy techniques. The recent development of multi-omics and data-driven solutions has now provided evidence for pathophysiologically different subtypes of MDD, moving the field toward precision psychiatry. The systematic review aggregates multimodal studies that combing neuroimaging, genomics, transcriptomics, epigenomics, metabolomics, and proteomics to define MDD subtypes. There are two to four candidate clusters that have been formed across these heterogeneous modalities, and each has a neurobiological and clinical profile. Cognitive subtypes are characterized by executive failure and loss of prefrontal and temporal gray matter. Neuroimaging-derived subtypes show specific patterns of functional connectivity that may predict response to selective serotonin reuptake inhibitors (SSRIs) or repetitive transcranial magnetic stimulation (rTMS) in preliminary studies. There are immune-metabolic subtypes characterized by increased inflammatory cytokines and dysregulation of metabolic pathways. Molecular subtypes appear to be differentiated by cellular mechanisms such as mitophagy and pyroptosis. Taken together, these results indicate that multi-omics integration, in addition to explaining the molecular architecture of MDD, also characterizes patient subgroups with pathophysiological mechanisms, dimensions of symptoms, and disease treatment. The growing body of literature demonstrates that there is a shift in psychiatry toward a more mechanistic approach and that biomarker-based diagnostics and personalized treatment regimens are urgently needed to improve clinical outcomes in depressive diseases.
Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.
Ali Inaltekin, Fakher Rahim, Abdullah Örs et al.· Psychiatry research. Neuroim...· 0 citations
Major depressive disorder (MDD) and bipolar disorder (BD) are highly prevalent psychiatric conditions, both characterized by depressive episodes and associated with substantial disability, marked clinical heterogeneity, and variable responses to pharmacological treatment. Despite the widespread use of antidepressants and antipsychotics, a significant proportion of patients experience delayed therapeutic response, adverse drug reactions, or treatment resistance, due to interindividual biological variability. In this context, pharmacogenomics has emerged as a key strategy to address this challenge by integrating genetic variability with pharmacokinetic and pharmacodynamic mechanisms to inform personalized treatment decisions. This narrative review aims to: (i) summarize key pharmacogenes and genetic variants implicated in the pharmacological treatment of MDD; (ii) differentiate genes with established clinical actionability from those requiring further evidence; and (iii) evaluate their current and future roles in precision psychiatry. Evidence was synthesized from curated pharmacogenomic guideline resources, including the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Pharmacogenomics Knowledge Base (PharmGKB), and the Dutch Pharmacogenetics Working Group (DPWG). Robust and replicated evidence supports the clinical employ of the pharmacokinetic genes CYP2D6 and CYP2C19, for which genotype-informed prescribing recommendations are available and have demonstrated benefits in optimizing drug exposure, reducing adverse effects, and improving treatment outcomes, particularly for selective serotonin reuptake inhibitors (SSRIs). CYP3A4 and CYP1A2 contribute substantially to the metabolism of many psychotropic drugs and influence dosing through both genetic and environmental modifiers (e.g., enzyme inducers/inhibitors and smoking), although formal guideline-level recommendations remain limited for a small subset of substrates. In contrast, pharmacodynamic and regulatory genes, including COMT, FKBP5, HTR2A, SLC6A4, and MTHFR, represent promising avenues for future clinical implementation. Polygenic risk scores for antidepressant response (PRS-AD) capture the highly polygenic architecture of treatment outcomes but, at present, lack the predictive performance required for routine clinical use, particularly across non-European ancestries. Randomised trials and meta-analyses (GUIDED, PRIME Care, IGNITE-network and others) provide moderate evidence that pharmacogenomic-guided prescribing modestly improves remission, response, and side-effect burden; however, the magnitude and durability of benefit remain under active debate. Pharmacogenomic testing therefore represents a clinically informative - though not curative - adjunct to psychiatric care; its full potential will be achieved by combining routine guideline-based testing of validated pharmacogenes with ongoing translational research on emerging candidates and polygenic models.
Michel Haddad, L. Dieckmann, Giovana Regina Weber Hoss et al.· Journal of Affective Disorde...· 0 citations
Major depressive disorder (MDD) is one of the leading psychiatric causes of disability worldwide and is characterized by marked heterogeneity, high recurrence risk, and low treatment rates. Traditional models have emphasized monoaminergic neurotransmitter imbalance, hypothalamic-pituitary-adrenal axis dysfunction, structural and functional brain remodeling, and inflammatory activation. Although these perspectives have substantially advanced our understanding of MDD, they do not fully account for its complex pathogenesis, and further investigation may support the development of novel prevention and treatment strategies. Increasing evidence indicates that MDD is closely associated with endocrine and metabolic abnormalities. This review summarizes evidence suggesting that endocrine and metabolic dysregulation may provide mechanistic insights into symptom burden, variability in disease progression, and treatment difficulties in certain patients. Particular attention is given to five interrelated domains: shared genetic and environmental susceptibility, dysfunction of the hypothalamic-pituitary-target gland axes, chronic low-grade inflammation and immune imbalance, impaired insulin signaling, and disruption of cerebral energy metabolic homeostasis. The review further explores potential clinical implications, including targeted endocrine and metabolic assessment, metabolism-related pharmacological strategies, modulation of the gut-brain axis, and lifestyle interventions. Rather than simply describing associative findings, this review aims to identify endocrine and metabolic abnormalities with potential predictive, modifiable, and clinically meaningful value, thereby providing a cautious and evidence-based framework for future risk assessment, disease-course interpretation, and adjunctive treatment of depression.
Ee Chang, Yiran Zhu, Wei Wei et al.· Neurobiology of Disease· 1 citation
These findings provide a hypothesis-generating reframing of the traditional comorbidity model, suggesting that divergent molecular programs may converge on shared pathways and offer a preliminary foundation for exploring therapeutic strategies at the mood–metabolism interface.
Xingpei Li, Chunling Chen, Huibin Li et al.· Frontiers in Genetics· 0 citations
BACKGROUND
Neuroimaging research of individuals with major depressive disorder (MDD) has identified varying deficits across affective, cognitive, and resting-state paradigms and distinct patterns of activation associated with these domains. As this heterogeneity may be related to variation in clinical prognosis, we examined convergence across neuroimaging studies of MDD treatment biomarkers within and across domains.
METHODS
Using a PubMed search and reference lists from topical reviews, we identified research in which adults with MDD exhibited pretreatment neural responses associated with clinical response to antidepressant medication or cognitive behavioral therapy. We performed activation likelihood estimation meta-analyses of peak voxel coordinates to identify domain-general (i.e., elicited across all tasks) and domain-specific (i.e., affective, cognitive, or resting-state) biomarkers associated with treatment response.
RESULTS
The meta-analyses included 46 experiments with 996 unique participants. Across studies showing pre-treatment activation associated with poor treatment outcome, a cluster in the right anterior insula (rAI) was identified as a domain-general biomarker. For the domain-specific meta-analysis of neuroimaging studies of negatively-valenced emotion processing, significant convergence of baseline activation associated with treatment response emerged in the rAI and in the subgenual anterior cingulate cortex. No significant convergence of biomarkers emerged across resting-state metabolic studies or among studies reporting biomarkers of positive treatment outcomes.
CONCLUSIONS
Across domains, heightened pretreatment activation in the rAI, a key node in the salience network, emerged as a strong biomarker of poor prognosis in adults with MDD. Moreover, pretreatment limbic and paralimbic responses elicited by negative emotional stimuli may provide valuable information about subsequent response to treatment.
Katherine L. McCurry, Vanessa M. Brown, Vansh Bansal et al.· Biological Psychiatry· 0 citations
Identifying generalizable brain-based biotypes across independent cohorts is critical for parsing heterogeneity in Major Depressive Disorder (MDD), yet robust subtypes spanning micro- and macroscales remain poorly defined. We applied stability-based clustering to cortical thickness data from 1,531 MDD individuals in UK Biobank (UKB), with external validation in 144 inpatients from IRCCS Ospedale San Raffaele (HSR). Two distinguishable clusters emerged (accuracy=87.5%), with one showing widespread cortical thinning, anergy-related symptoms, childhood trauma, and diabetes comorbidity. This profile generalized with 96.5% accuracy in a hold-out UKB sample and 80.6% in HSR. Mapping clusters cortical profiles onto Neurosynth meta-analytic activation patterns revealed a ventral-dorsal gradient linked with emotion regulation, interoceptive, and motivational processes. Spatial correlations with 19 neurotransmitter receptors and transporters obtained from positron emission tomography identified dopamine transporter as the dominant contributor in UKB, and histamine receptor H3 in HSR. These findings provide a reproducible framework linking MDD subtypes to multiscale biological complexity.
F. Colombo, L. Fortaner-Uyá, T. Cazzella et al.· medRxiv· 0 citations