Increasing evidences show that inflammation might be involved in bipolar disorder (BD), but the association between abnormal brain function and inflammation in BD is still unclear. In this study, we tried to explore the disrupted brain functional network topology, peripheral inflammatory cytokine levels, and their correlations in unmedicated bipolar II depression (BDII-D).

In this study, 65 individuals with unmedicated BDII-D and 50 healthy controls (HCs) underwent resting-state magnetic resonance imaging scans. Graph theory analysis was performed to investigate the topological properties of the whole-brain functional connectome at both global and nodal levels. Besides, serum levels of 17 inflammatory cytokines were measured in both BDII-D and HCs. Correlations between topological properties, clinical variables, and peripheral inflammatory cytokine levels in BDII-D were calculated.

Compared with HCs, at the global level, BDII-D showed significantly higher $ \lambda $, decreased $ \gamma $, $ \sigma $, Eglo, and Eloc; at the nodal level, BDII-D showed decreased Enodal in the right olfactory cortex, left pallidum, and vermis. Besides, BDII-D showed higher levels of interleukin-8 (IL-8), interleukin-10 (IL-10), and granulocyte colony-stimulating factor (G-CSF) compared with the HCs. In BDII-D, $ \gamma $ and $ \sigma $ were significantly negatively correlated with the Hamilton Depression Rating Scale (HDRS) scores and number of episodes. Also, IL-8 level showed significant negative correlation with $ \gamma $, $ \sigma $, and Enodal of the left pallidum in BDII-D.

Reduced information segregation and integration, and lower nodal efficiency in the left pallidum were associated with proinflammatory cytokine IL-8 level and might contribute to severe depressive symptoms in unmedicated BDII-D.

The comorbidity of psychiatric and metabolic conditions is prevalent and poses a heavy burden on public health. Several biopsychosocial factors are known to influence both metabolic and psychiatric health, including inflammation, eating behavior, physical activity, and early life stress. Few studies, however, have examined the constellation of interrelationships among multiple risk domains simultaneously.

Using a sample of 200 medically healthy adults enrolled in a parent study, we used Gaussian Graphical Modeling, a type of network analysis, to characterize interdependent cross-sectional associations between early life stress (childhood trauma), health behaviors (diet quality and physical activity), blood-based biomarkers of metabolic functioning (insulin resistance, HDL cholesterol, triglycerides) and inflammation (C-reactive protein [CRP]), and three domains of mental health symptoms (depressive, anxious, and post-traumatic stress symptoms). We hypothesized that the network structure would highlight a pattern whereby higher CRP, poorer diet quality, lower physical activity, and higher childhood trauma would associate with increased risk for both metabolic and psychiatric impairments.

Findings revealed a positive conditional association between CRP and childhood trauma, which may function as an intermediary process to increase risk for both metabolic impairments and psychiatric symptoms in adulthood. Further, higher physical activity was associated with lower insulin resistance and fewer depressive symptoms, and better diet quality was associated with lower CRP levels.

Results highlight potential avenues for interventions aimed at reducing inflammation, improving health behavior, and addressing the effects of childhood trauma to improve physical and mental health comorbidities.

Schizophrenia (SZ) is a debilitating psychiatric disorder where patients experience cognitive decline. Antipsychotic drugs alleviate positive symptoms but do not improve cognitive performance. We previously demonstrated that Toll-like receptors (TLRs), involved in cytokine production, can predict cognitive deficits in SZ patients. In this study, we aim to investigate the potential moderating effects of antipsychotic drugs on the associations between cytokines, TLRs, and cognition.

In total, 280 participants (201 controls and 79 cases of SZ) were recruited in Ireland. Venous blood from the participants was stimulated with TLR ligands. Levels of cytokines were measured from plasma and post-blood stimulation. The participants were administered a battery of cognitive tasks using the Cambridge Neuropsychological Test Automated Battery and Wechsler Adult Intelligence Scale-IIIR. Olanzapine equivalents were calculated using the defined daily dose method.

The results indicate that antipsychotic drug dose does not predict TLR activity or cognition, indicating that antipsychotic drug dose does not have a direct effect on cognition or TLR activity. However, the relationship between TLR4 activity and visual learning and memory is moderated by the antipsychotic drug dose (B = −0.065; p < 0.001), where increasing doses have a decreasing impact on their relationship.

Our data indicate that the dose of antipsychotic drugs alone cannot predict changes in cognitive performance and TLR4-activity. It also suggests that antipsychotic drug doses significantly affect TLR activity and its relationship with cognition. These effects are more pronounced on some domains than others. These findings open up new avenues for understanding the complex interplay between antipsychotic drugs, TLRs, and cognitive deficits in SZ.

Bipolar disorder (BD) involves immune-inflammatory dysregulation. This systematic review and meta-analysis assessed complete blood count-based inflammatory indices – neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), and platelet-to-lymphocyte (PLR) ratios – in BD versus healthy controls (HCs), major depressive disorder (MDD), and across BD mood states.

Databases were searched through June 2025 for observational studies reporting at least one ratio in adults with BD and including as comparators either HCs, MDD, or within-BD mood-state contrasts (mania, bipolar depression, euthymia). Quality was appraised using BIOCROSS. Random-effects meta-analyses, sensitivity analyses, and meta-regressions were performed. GRADE was adapted to rate evidence certainty.

Fifty-one studies (38,309 participants) met the inclusion criteria. Compared to HCs, BD showed higher NLR (SMD = 0.44, p < 0.001) and MLR (SMD = 0.28, p < 0.001). In mania, NLR (SMD = 0.62, p < 0.001), MLR (SMD = 0.51, p < 0.001), and PLR (SMD = 0.18, p = 0.014) were all elevated versus HCs. Depression showed lower PLR (SMD = –0.14, p < 0.001) and euthymia higher NLR (SMD = 0.37, p = 0.002). Compared to MDD, BD had higher NLR (SMD = 0.21, p < 0.001) and MLR (SMD = 0.18, p < 0.001). Similarly, mania showed higher NLR (SMD = 0.53, p < 0.001) and MLR (SMD = 0.41, p < 0.001), while bipolar depression lower PLR (SMD = –0.15, p < 0.001). Mania had higher NLR (SMD = 0.32, p < 0.001), MLR (SMD = 0.32, p < 0.001), and PLR (SMD = 0.14, p = 0.028) than depression and higher MLR than euthymia (SMD = 0.44, p = 0.027), while depression had lower NLR (SMD = –0.28, p = 0.012) and PLR (SMD = –0.22, p < 0.001). Evidence certainty was mixed.

NLR, MLR, and PLR emerge as non-specific, group-level correlates of immune-inflammatory dysregulation in BD, however offering limited discrimination between bipolar and unipolar depression. Notwithstanding their potential role as trait- and state-related markers in BD, further studies are needed to support translation into clinically useful biomarkers.

Schizophrenia (SCZ) shows marked biological heterogeneity, with negative symptoms linked to poor outcomes and hypothesised immune dysregulation. This study examined whether a peripheral cytokine–long non-coding RNA (lncRNA) panel could distinguish patients with SCZ and Brief Negative Symptom Scale (BNSS)-defined subgroups from healthy controls (HC).

Forty-one hospitalised patients with SCZ completed the BNSS and the Positive and Negative Syndrome Scale (PANSS). Twenty HCs, frequency-matched for age and sex, served as comparison samples. Severe negative-symptom subgroups were defined using two BNSS criteria: a broader (SNS1) and a more restrictive (SNS2) threshold. Serum cytokines – interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α), interleukin-10 (IL-10) – and leukocyte lncRNAs (MALAT1, NEAT1, MEG3) were quantified by enzyme-linked immunosorbent assay and quantitative RT-PCR. Covariate-adjusted logistic and multinomial models (adjusting for age, sex, body mass index, and smoking) assessed discrimination using area under the receiver-operating-characteristic curve (AUC) and interquartile-range odds ratios (OR_IQR).

IL-6 correlated with PANSS Total (ρ = 0.48, p = 0.001) and Negative (ρ = 0.34, p = 0.032) scores and was higher in SCZ than HC (p = 0.033), with further increases in SNS subgroups. NEAT1 was significantly reduced only within BNSS-defined subgroups (p ≤ 0.025). The dual-marker pattern (IL-6 ↑, NEAT1 ↓) showed the strongest discrimination for SNS1 versus HC (AUC = 0.85) and the steepest multinomial contrasts for SNS2 (IL-6 OR_IQR = 4.98; NEAT1 OR_IQR = 0.11).

Elevated IL-6 and decreased NEAT1 define a peripheral signature linked to negative-symptom severity in SCZ and may support biologically informed stratification and longitudinal research.

Emerging evidence suggests that metabolic and hormonal disturbances in polycystic ovary syndrome (PCOS) may increase vulnerability to neurodegenerative disorders. However, the link between PCOS and Alzheimer’s disease (AD)-related pathology remains unclear.

In this cross-sectional study, plasma levels of β-amyloid (Aβ40, Aβ42), phosphorylated tau (p-tau181), neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) were quantified in women with PCOS and age-matched controls. Homeostasis model assessment of insulin resistance (HOMA-IR), inflammatory cytokines (IL-6, TNF-α) and hormonal parameters were assessed. Mediation and moderation analyses were conducted to explore metabolic and hormonal pathways underlying biomarker alterations.

Among 400 women (200 PCOS, 200 controls), age and BMI were comparable (P > 0.05). Compared with controls, PCOS participants had increased Aβ40, p-tau181, NfL and GFAP, a slightly higher Aβ42, and a lower Aβ42/40 ratio (all P < 0.05). p-tau181 correlated positively with HOMA-IR (r = 0.41) and IL-6 (r = 0.36), while Aβ42/40 ratio correlated negatively with HOMA-IR (r = –0.27). In multivariable analysis, p-tau181 (aOR = 1.34, 95% CI 1.05–1.71), IL-6 (aOR = 1.19) and TNF-α (aOR = 1.14) were independent predictors of insulin resistance. Mediation analysis indicated that HOMA-IR, IL-6 and TNF-α jointly mediated ∼ 71% of the PCOS–p-tau181 association, suggesting a metabolic–inflammatory pathway linking PCOS to AD-related tau pathology.

PCOS is linked to peripheral markers of early Alzheimer’s pathology, largely mediated by insulin resistance and inflammation. PCOS may provide a clinical context to explore metabolic–inflammatory contributors to early neurodegenerative changes.

Major depression (MDD) is linked to neuro-immune, metabolic, and oxidative stress (NIMETOX) pathways. The gut microbiome may contribute to these pathways via leaky gut and immune–metabolic processes.

To identify gut microbial alterations in MDD and to quantify functional pathways and enzyme gene families and integrate these with the clinical phenome and immune–metabolic biomarkers of MDD.

Shotgun metagenomics with taxonomic profiling was performed in MDD versus controls using MetaPhlAn v4.0.6, and functional profiling was conducted using HUMAnN v3.9, aligning microbial reads to species-specific pangenomes (Bowtie2 v2.5.4) followed by alignment to the UniRef90 v201901 protein database (DIAMOND v2.1.9).

Gut microbiome diversity, both species richness and evenness, is quite similar between MDD and controls. The top enriched taxa in the multivariate discriminant profile of MDD reflect gut dysbiosis associated with leaky gut and NIMETOX mechanisms, that is, Ruminococcus gnavus, Veillonella rogosaem, and Anaerobutyricum hallii. The top four protective taxa enriched in controls indicate an anti-inflammatory ecosystem and microbiome resilience, that is, Vescimonas coprocola, Coprococcus, Faecalibacterium prausnitzii, and Faecalibacterium parasitized. Pathway analysis indicates loss of barrier protection, antioxidants, and short-chain fatty acids, and activation of NIMETOX pathways. The differential abundance of gene families suggests that there are metabolic distinctions between both groups, indicating aberrations in purine, sugar, and protein metabolism. The gene and pathway scores explain a larger part of the variance in suicidal ideation, recurrence of illness, neurocognitive impairments, immune functions, and atherogenicity.

The gut microbiome changes might contribute to activated peripheral NIMETOX pathways in MDD.

As the global shift towards autocracy continues and soft political repression rises, it is crucial to understand its long-term health implications. Typical tactics of soft political repression are surveillance, denunciation and harassment, operating beneath the threshold of criminal or violent persecution. Despite its prevalence, soft repression remains underexplored, particularly in terms of its psychobiological health consequences.

The current study investigates the long-term sequelae of soft political repression in the German Democratic Republic (GDR: 1949–1990), focusing on psychological distress, systemic inflammation and cellular ageing.

The cross-sectional laboratory study included 100 50–78 years old participants from the states of Thuringia and Saxony in Germany. Participants in the repression group (n = 49) had experienced at least two forms of state-organised soft repression in the GDR. The age, gender and origin matched control group reported no such experiences. Psychological measures included depressive, anxiety and trauma symptoms. Physiological health outcomes were measured through the inflammatory markers interleukin-6 and high sensitivity C-reactive protein (hs-CRP), as well as telomere length as a marker of cellular ageing. Resilience, social support and socioeconomic status were included in the analyses as potential buffers of repression effects.

Participants with repression experience (versus control group) scored significantly higher on all psychological distress variables. Furthermore, they exhibited higher levels of interleukin-6, indicating increased systemic inflammation. No group differences were found for hs-CRP or telomere length. However, in the repression group, lower social support was associated with shorter telomeres.

This study is the first to explore the psychobiological health consequences of soft political repression. Findings emphasise its long-term consequences on the psyche and immune system and highlight the potential role of social support in mitigating cellular ageing. As authoritarian tactics are becoming more prevalent worldwide, understanding the impact of soft repression on health is essential for supporting affected individuals.

Contrary to the negative acute-phase protein (APP) response, there is no consistent correlation between serum pentameric C-reactive protein (pCRP) and major depression (MDD). Monomeric CRP (mCRP), a dissociation product of pCRP under immune-inflammatory conditions, exhibits pro-inflammatory effects; however, it has not been investigated in MDD or its subtypes, major dysmood disorder (MDMD) and simple dysmood disorder (SDMD).

To examine serum mCRP, albumin, transferrin, M1 macrophage and Thelper-17 immune profiles, and adverse childhood experiences (ACEs) in MDD, MDMD and SDMD.

Seventy-nine MDMD patients, 30 SDMD patients, and 40 controls were included. Serum mCRP was measured by ELISA; albumin, transferrin, and pCRP by biochemical assays; and cytokines using Luminex technology.

MDMD patients showed significantly higher mCRP compared with SDMD and controls, while both patient groups exhibited reduced albumin and transferrin. Combining mCRP with albumin and transferrin showed an adequate accuracy for MDD (area under the ROC Curve = 0.793). Adding IL-17A and ACEs improved accuracy (ROC = 0.855). Serum mCRP levels are additionally associated with pCRP, M1 macrophage profile, body mass index, and ACEs. Up to 36.6% of the variance in overall severity of depression was explained by mCRP, T-helper-17 profile, ACEs (all positively), albumin and transferrin (both inversely).

Future research in MDD should employ mCRP rather than pCRP as a biomarker of depression/MDMD. Combining mCRP with biomarkers of the negative acute-phase response identified 63.7% of MDD patients with a smouldering acute-phase response, with a specificity of 82.1%. We recommend to assess mCRP rather than pCRP in MDD studies.