Elevated levels of pro-inflammatory cytokines are frequently observed in mood disorders, but their relationship with psychosomatic symptomatology remains underexplored. This study aimed to examine whether interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) are associated with psychosomatic syndromes in patients with major depression (MD) and bipolar depression (BD), and whether these associations are moderated by sex. seventy-seven outpatients with MD or BD were assessed using the Diagnostic Criteria for Psychosomatic Research-Revised (DCPR-R) and the Patient Health Questionnaire-15 (PHQ-15) to evaluate psychosomatic symptoms. Depression and mania severity were measured with the Beck Depression Inventory-II (BDI-II) and the Mania Rating Scale (MRS). Circulating levels of IL-6 and TNF-α were analyzed. Associations were tested using multivariate regression and mediation analyses, controlling for demographic and health-related variables. both IL-6 and TNF-α were significantly associated with psychosomatic syndromes (as per DCPR-R) and PHQ-15 scores. IL-6, in particular, showed a strong association with persistent somatization (PS). These relationships remained significant after adjusting for affective-cognitive depressive symptoms and potential confounders. No significant moderating effect of sex was identified. Mediation analyses suggested that psychosomatic syndromes mediate the relationship between inflammatory cytokines and depressive symptomatology. findings suggest that the link between inflammation and mood disorders is more closely related to psychosomatic syndromes than to mood symptoms alone. Elevated IL-6 levels may reflect somatization processes within depression rather than being directly pro-depressive. Psychosomatic syndromes may thus represent a key clinical and therapeutic target in mood disorders with elevated inflammation.

Background: Neuropsychiatric symptoms (NPSs) are among the most clinically disruptive manifestations of major neurocognitive disorder (MND) and major contributors to caregiver distress. However, the differential contribution of specific neuropsychiatric domains to caregiver burden and sleep quality has remained insufficiently characterized. Methods: This single-center retrospective observational study included 164 patient–caregiver dyads. Patients were diagnosed with MND according to DSM-5 criteria. NPS were assessed using the Neuropsychiatric Inventory (NPI-Q). Caregiver burden and sleep quality were evaluated using the 12-item Zarit Burden Interview (ZBI-12) and the Pittsburgh Sleep Quality Index (PSQI), respectively. Beta and logistic regression models were applied to investigate associations between NPS severity and caregiver outcomes after adjustment for cognitive and functional status. Additional analyses explored the relative contribution of individual NPI-Q subdomains. Results: Greater overall NPS severity was significantly associated with both increased caregiver burden (β = 0.163, p < 0.001) and altered caregiver sleep quality (OR = 1.32, 95% CI: 1.12–1.59, p = 0.002). Clinically significant sleep disturbances (PSQI > 5) were observed in 61.6% of caregivers. Among NPS, delusions showed the strongest association with caregiver burden (β = 0.329, p < 0.001), followed by depressive symptoms (β = 0.156, p = 0.004) and irritability (β = 0.147, p = 0.005); furthermore, sleep and night-time behavior disorders emerged as the strongest contributors to altered caregiver sleep quality (p < 0.001). Conclusions: Greater NPS severity may be associated with increased caregiver burden and poorer sleep quality in caregivers of patients with MND. Different NPSs appear to be differentially associated with caregiver outcomes, despite the lack of caregiver-level covariates, supporting the need for multidimensional and caregiver-centered approaches in dementia care. Given the exploratory nature of these analyses, these findings should be interpreted as descriptive rather than confirmatory.

Late-life depression (LLD) is increasingly recognized as a complex multisystem disorder associated with accelerated biological aging, impaired physiological resilience, frailty, and an increased risk of cognitive decline and dementia. Although growing evidence supports the close relationship between depression, frailty, and neurodegeneration, the molecular mechanisms underlying this continuum remain incompletely understood. In particular, conventional clinical and imaging biomarkers capture established disease but provide limited insight into the systemic biological processes that precede neurodegeneration. Proteomics has emerged as a powerful systems biology approach capable of characterizing the dynamic molecular networks involved in aging, neuropsychiatric disorders, and neurodegenerative diseases. Recent advances in high-throughput mass spectrometry have identified alterations in proteins associated with chronic inflammation, complement activation, mitochondrial dysfunction, oxidative stress, lipid metabolism, synaptic integrity, neurotrophic signaling, and cellular senescence across LLD, frailty, cognitive impairment, and Alzheimer's disease (AD). These convergent proteomic signatures suggest that these conditions may share common biological pathways reflecting progressive loss of physiological resilience rather than independent pathological entities. In this review, we examine the current evidence supporting shared proteomic mechanisms linking LLD, frailty, cognitive frailty (CF), and neurodegeneration. We discuss the potential integration of large-scale proteomic profiling with established AD biomarkers within the AT(N) framework to improve biological characterization, early risk stratification, and prediction of cognitive decline. Particular emphasis is placed on CF as a transitional and potentially modifiable phenotype in which systemic molecular dysregulation precedes overt neurodegeneration. By integrating evidence from geroscience, neuropsychiatry, and proteomics, we propose that proteomic profiling can redefine LLD and frailty as manifestations of a common biological vulnerability continuum. This systems-level perspective may facilitate the identification of individuals at high risk for dementia, support the development of multimodal biomarker panels, and advance precision neuropsychiatry through earlier diagnosis and personalized preventive interventions.