Aug 2026· Nature reviews. Drug discovery· 0 citations· 186 references
Medicine
TL;DR
This Perspective discusses mechanistic approaches that focus on excitation-inhibition balance, reward and aversion circuits, hippocampal-prefrontal neuroplasticity, and processing of social cues, highlighting how these frameworks can elucidate drug mechanisms and predict treatment responses.
Precision psychiatry is an emerging framework that seeks to improve diagnosis, prognosis, and treatment in mental disorders through the integration of biological, behavioral, environmental, and clinical information. Current diagnostic systems show substantial heterogeneity within categories and symptom overlap across disorders, reflecting limited biological validity and constraining treatment development. This review presents a conceptual framework for precision psychiatry that emphasizes multimodal approaches. We describe key sources of information, including demographic and psychosocial factors, as well as biological data, particularly neuroimaging, genetics, and molecular profiling. We also outline analytic strategies designed to move beyond showing average associations, including mediation and interaction analyses and machine learning approaches that enable the evaluation of intermediate pathways and heterogeneous effects. Despite increasing availability of multimodal data, key challenges include limited clinical utility of biomarkers when used in isolation and insufficient availability of integrated datasets. Shared infrastructures and validated analytic platforms are essential to support multimodal approaches and translation into clinical care.
Z. Narita, A. K. Mathur, Kun Yang· International Review of Psyc...· 0 citations
The review underscores the need for longitudinal research, refined diagnostic frameworks, and context-sensitive implementation strategies to advance holistic, patient-centered management of depression in schizophrenia.
Oshi Malik, Priyanka Yadav· Indian Journal of Medical Sp...· 0 citations
The latest developments in connectome-based modeling of the suicidal brain can not only inform neurobiological mechanisms but also help to advance clinical translation, and a novel paradigm using normative models to develop a connectome-based suicide risk calculator is proposed.
Kun Qin, Junni Ran, Nanfang Pan et al.· Biological Psychiatry· 0 citations
The global aging demographic has precipitated a surge in late-life mental disorders (LMDs)—including late-life depression (LLD), anxiety, and behavioral and psychological symptoms of dementia (BPSD)—posing critical public health challenges. This review synthesizes current evidence on the unique pathophysiology, clinical management, and emerging frontiers of geriatric mental health, emphasizing the interplay of neurobiological aging, multimorbidity, and psychosocial stressors. Key pathophysiological mechanisms include “inflammaging” (microglial overactivation), cerebral small vessel disease (CSVD), and senescence of monoaminergic systems, which collectively reduce neural resilience and complicate diagnosis. Clinical challenges—such as atypical symptom presentation (e.g., somatic masking of depression), polypharmacy risks, and diagnostic ambiguity between LLD and pseudodementia—necessitate tailored interventions. Notably, caregiver burden represents an independent predictor of patient institutionalization. Multiple systematic reviews and meta-analyses have consistently identified caregiver burden and distress as significant predictors of nursing home admission, with carer stress sometimes serving as the single determining factor for this transition. This underscores the critical need to integrate caregiver well-being into routine clinical assessment. Pharmacological strategies prioritize SSRIs/SNRIs but require cautious dosing due to age-related pharmacokinetic alterations (e.g., reduced renal clearance) and cardiovascular/metabolic risks. Emerging targets (e.g., ketamine for treatment-resistant LLD, anti-inflammatory agents guided by biomarker profiling) highlight a shift toward precision. Psychotherapeutic adaptations—including modified cognitive behavioral therapy (CBT), problem-solving therapy (PST), and life review therapy—address cognitive and psychosocial needs, while integrated care models (e.g., Collaborative Care Model [CoCM]) demonstrate superior outcomes over fragmented care. Lifestyle interventions (exercise) and neuromodulation (rTMS) further expand treatment options. Critical gaps remain, including underrepresentation of older adults in clinical trials and pervasive polypharmacy. Future directions emphasize pharmacogenomics, AI-driven early detection, and culturally equitable care to advance precision psychiatry for LMDs. This synthesis provides clinicians and researchers with a roadmap to navigate the complexities of geriatric mental health, advocating for multidisciplinary, patient-centered approaches to improve outcomes in aging populations.
Jing Wang, An-Qi Li· Frontiers in Psychiatry· 0 citations
One of the most significant challenges in treating individuals suffering from psychiatric illnesses is the biological heterogeneity that exists throughout the patient population. This heterogeneity has hindered both timely diagnoses for those impacted as well as the development of new treatment options to combat these disorders. Ongoing efforts have been centered around stratifying individuals based on comprehensive phenotyping; however, biological heterogeneity remains a critical driver of psychiatric illness and poses a significant challenge in the field. Here, we review the current state of the field in biomarker development and the need for personalized medicine in psychiatry. Neurosteroid-based treatments have proven effective for the treatment of postpartum depression, but failed to gain approval for major depressive disorder, likely due to the inability to stratify patients amenable to this treatment approach. We discuss the potential of a biomarker approach to identify individuals with disruption in endogenous neurosteroid synthesis that may have transdiagnostic potential. Exciting emerging studies suggest that a biomarker indicating altered or a reduced capacity for endogenous neurosteroidogenesis would be beneficial for identifying individuals at risk for postpartum depression and could potentially predict treatment response to neurosteroid-based treatments. This review aims to provide a comprehensive report on the production of endogenous neurosteroids in the brain, the current clinical landscape for the use of neurosteroid-based therapies in psychiatry, and the potential utility of measuring neurosteroidogenesis capacity as a biomarker for the diagnosis and treatment of psychiatric illnesses.
Tauryn Dargan, N. Walton, Jamie L. Maguire· Biological Psychiatry· 0 citations
Schizophrenia is a complex neuropsychiatric disorder manifesting with diverse positive and negative symptoms as well as cognitive impairments. Current antipsychotics primarily address positive symptoms and frequently cause substantial side effects, highlighting the need for novel therapeutics targeting alternative pathomechanisms. Animal models are widely used to investigate schizophrenia's neurobiology and guide drug discovery, yet their clinical relevance for proof-of-concept (PoC) studies remains controversial. This Current Opinion critically examines the key limitations of animal models in schizophrenia research from a clinical perspective. The disorder’s multifaceted nature, involving genetic, environmental, and neurodevelopmental factors, makes accurate replication in animals challenging. Additionally, core human-specific symptoms, like hallucinations and thought disorders, cannot directly be modeled, although some underlying cross-species constructs can be operationalized. We argue that animal models are most informative when used to test specific, well-defined mechanistic hypotheses and when readouts are anchored to human-relevant biomarkers and neurophysiology, rather than interpreted as proxies for diagnostic categories. Accordingly, translational utility is not uniform: predictive performance depends on the induction paradigm, the construct validity of behavioral and neurophysiological readouts, and the clinical endpoint being modeled. We advocate for close collaboration between preclinical and clinical researchers to refine existing models, establish new and translationally relevant paradigms, and clearly define their interpretive scope. Integrating complementary advanced in vitro and in silico models may enhance mechanistic understanding and help prioritize hypotheses and candidates. Still, these approaches should be viewed as adjuncts, not superior replacements, because they cannot yet capture the circuit- and systems-level dynamics relevant to schizophrenia.
Inga Dammann-Bawadkji, F. M. Leweke, Cathrin Rohleder· Pharmaceutical Medicine· 0 citations
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