Importance Childhood trauma is associated with increased risk for bipolar disorder, but the biological mechanisms of this association remain incompletely defined. Gray matter differences observed after trauma exposure overlap with those reported in bipolar disorder, suggesting that the association of childhood trauma with bipolar disorder might be mediated through brain morphology. Objective To determine whether cortical thickness, cortical surface, or subcortical volume mediate the association of childhood trauma with bipolar disorder. Design, Setting, and Participants This case-control study conducted a cross-sectional analysis of individuals with bipolar disorder and healthy controls from 19 international cohorts (Enhancing NeuroImaging Genetics Through Meta-Analyses [ENIGMA] Bipolar Disorder Working Group) from January 2010 to December 2022. Data were analyzed from January 2025 to January 2026. Exposures The primary exposure was the severity of total childhood trauma assessed with the Childhood Trauma Questionnaire, with secondary analyses of 5 subscales (emotional neglect and abuse, physical neglect and abuse, and sexual abuse). Main Outcomes and Measures The primary outcome was bipolar disorder diagnosis (case vs control). The primary measure was the mediation effects of childhood trauma on diagnosis via gray matter (75 bilateral-averaged cortical thickness, surface, and subcortical volume measures). The mediation pathway from severity of childhood trauma to bipolar disorder through brain morphology was specified a priori. High-dimensional mediation analysis, with leave-one-site-out cross-validation and permutation testing for significance (false discovery rate [FDR]), was conducted. Results The final sample included 2221 healthy controls (mean [SD] age, 35.6 [13.2] years; 1274 female [57%]) and 1031 participants with bipolar disorder (mean [SD] age, 38.6 [13.7] years; 579 female [56%]). Severity of childhood trauma was directly associated with higher likelihood of having a bipolar disorder diagnosis (median coefficient, 0.841; 95% CI, 0.834-0.851; range, 0.776-0.893; FDR P < .001). Less than 1% of the association between childhood trauma and bipolar disorder was mediated by brain morphology. Statistically significant mediators were hippocampal volume (median coefficient, 0.004; 95% CI, 0.002-0.005; range, 0-0.008; FDR P < .001), medial orbitofrontal gray matter thickness (median coefficient, 0.002; 95% CI, 0.002-0.003; range, 0-0.004; FDR P < .001), and superior frontal gyrus gray matter thickness (median coefficient, 0.002; 95% CI, 0.002-0.003; range, 0-0.005; FDR P < .001). Conclusions and Relevance This study found that severity of childhood trauma exposure was associated with bipolar disorder diagnosis in part through a smaller hippocampus, thinner cortex in the medial orbitofrontal gyrus, and thinner cortex in the superior frontal gyrus. The identification of this mechanistic pathway improves understanding of the disorder, could help to identify those at risk, and enable the development of new interventions.

INTRODUCTION:Bipolar depression (BD) is associated with altered intrinsic brain activity, and possibly impaired neurovascular coupling (NVC). Although rapid-acting chronotherapies are effective in BD, their neurophysiological mechanisms remain unclear. METHODS:In this longitudinal resting-state fMRI study, we examined fractional amplitude of low-frequency fluctuations (fALFF), indexing spontaneous neural activity, and hemodynamic response function (HRF) parameters, used as proxies of NVC, in 50 BD inpatients undergoing three cycles of combined total sleep deprivation and light therapy (TSD + LT), and in 30 healthy controls (HCs). Patients were scanned before (day 0) and after treatment (day 7), and depressive symptoms were evaluated with the Beck Depression Inventory Short Form. RESULTS:At baseline, BD patients showed reduced fALFF in frontal, temporal, insular-opercular, and cerebellar regions relative to HCs. After TSD + LT, fALFF increased in widespread occipito-temporal, frontal, and cerebellar clusters in BD patients. HRF analyses showed no baseline between-group differences, but revealed a significant post-treatment increase in HRF response height across occipital, temporal, frontal, and cerebellar regions. Remission after TSD + LT was associated with fALFF changes, whereas larger HRF response height increases were observed in patients who did not require antidepressant treatment switch or augmentation during hospitalization. CONCLUSION:TSD + LT was associated with modulation of both intrinsic neural activity and resting-state hemodynamic responses, with fALFF and HRF reflecting partly distinct aspects of short-term clinical outcome.

BACKGROUND:Obesity, which is common in bipolar disorder (BD), is associated with smaller hippocampal volumes. We do not know the role of weight/weight gain in relation to longitudinal hippocampal changes among individuals with BD. METHODS:In collaboration with the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)-BD Working Group, we obtained T1-weighted magnetic resonance imaging and clinical data from 233 participants with BD and 701 healthy control participants (HCs) scanned twice, 2.84 ± 1.63 years apart on average. We estimated subcortical volumes using FreeSurfer longitudinal image processing stream and used linear mixed models to assess the bidirectional relationship between baseline body mass index (BMI) or BMI change and hippocampal volume or volume change. While the hippocampus was our a priori region of interest, we repeated these analyses in other subcortical regions. RESULTS:Baseline BMI predicted future hippocampal atrophy, but baseline brain structure did not predict future weight changes. BMI increased significantly over time (F1,1085 = 15.98, p < .001). Individuals with lower baseline BMI experienced greater weight gain (F1,922 = 105.12, p < .001). Greater weight gain was associated with greater hippocampal atrophy over time (F1,899 = 16.33, p = .001), more so in participants with BD than HCs (F1,898 = 6.91, p = .009). Consequently, lower baseline BMI predicted greater future hippocampal volume loss (F1,904 = 14.77, p < .001). These associations were not observed in other subcortical regions. CONCLUSIONS:Our findings suggest that weight gain is a modifiable risk factor for hippocampal atrophy, especially in individuals with lower BMI and those with BD. Prevention of weight gain in general, but especially in people with BD, could provide neuroprotective benefits.

Abstract Elucidating the neurobiological basis of neurodevelopmental and psychiatric conditions (NDPCs) remains challenging because brain alterations vary within diagnoses and overlap across them. Whether diverse alterations follow a systematic organization that may reflect shared vulnerabilities remains unknown. Here, we assembled 10,135 individuals with schizophrenia, autism, bipolar, obsessive-compulsive, generalized anxiety, and major depressive disorders, and 11,998 reference participants across six continents through the ENIGMA consortium. Using normative modeling, we quantified individual deviations in cortical thickness, surface area, and subcortical volumes relative to lifespan reference trajectories (5 to 80 years). We show that structural deviations converged along cortical axes reflecting connectome organization, maturation, and cytoarchitectonic diversity. These axes mirrored typical population variation, but their expression differed across diagnoses and partly scaled with symptom severity. Even rare and highly individualized extreme deviations followed this organization, concentrating in densely connected regions. Finally, brain structural deviations overlapped substantially across diagnoses, while differences between them increased toward the association cortex. Together, we provide large-scale evidence that structural deviations across NDPCs are systematically constrained by the brain’s intrinsic architecture. This shared organization provides a framework for reconciling individual variability with transdiagnostic similarities and motivates an integrative, systems-level understanding of mental health.

Importance:Childhood trauma is associated with increased risk for bipolar disorder, but the biological mechanisms of this association remain incompletely defined. Gray matter differences observed after trauma exposure overlap with those reported in bipolar disorder, suggesting that the association of childhood trauma with bipolar disorder might be mediated through brain morphology. Objective:To determine whether cortical thickness, cortical surface, or subcortical volume mediate the association of childhood trauma with bipolar disorder. Design, Setting, and Participants:This case-control study conducted a cross-sectional analysis of individuals with bipolar disorder and healthy controls from 19 international cohorts (Enhancing NeuroImaging Genetics Through Meta-Analyses [ENIGMA] Bipolar Disorder Working Group) from January 2010 to December 2022. Data were analyzed from January 2025 to January 2026. Exposures:The primary exposure was the severity of total childhood trauma assessed with the Childhood Trauma Questionnaire, with secondary analyses of 5 subscales (emotional neglect and abuse, physical neglect and abuse, and sexual abuse). Main Outcomes and Measures:The primary outcome was bipolar disorder diagnosis (case vs control). The primary measure was the mediation effects of childhood trauma on diagnosis via gray matter (75 bilateral-averaged cortical thickness, surface, and subcortical volume measures). The mediation pathway from severity of childhood trauma to bipolar disorder through brain morphology was specified a priori. High-dimensional mediation analysis, with leave-one-site-out cross-validation and permutation testing for significance (false discovery rate [FDR]), was conducted. Results:The final sample included 2221 healthy controls (mean [SD] age, 35.6 [13.2] years; 1274 female [57%]) and 1031 participants with bipolar disorder (mean [SD] age, 38.6 [13.7] years; 579 female [56%]). Severity of childhood trauma was directly associated with higher likelihood of having a bipolar disorder diagnosis (median coefficient, 0.841; 95% CI, 0.834-0.851; range, 0.776-0.893; FDR P < .001). Less than 1% of the association between childhood trauma and bipolar disorder was mediated by brain morphology. Statistically significant mediators were hippocampal volume (median coefficient, 0.004; 95% CI, 0.002-0.005; range, 0-0.008; FDR P < .001), medial orbitofrontal gray matter thickness (median coefficient, 0.002; 95% CI, 0.002-0.003; range, 0-0.004; FDR P < .001), and superior frontal gyrus gray matter thickness (median coefficient, 0.002; 95% CI, 0.002-0.003; range, 0-0.005; FDR P < .001). Conclusions and Relevance:This study found that severity of childhood trauma exposure was associated with bipolar disorder diagnosis in part through a smaller hippocampus, thinner cortex in the medial orbitofrontal gyrus, and thinner cortex in the superior frontal gyrus. The identification of this mechanistic pathway improves understanding of the disorder, could help to identify those at risk, and enable the development of new interventions.

BACKGROUND:Elevated inflammatory biomarkers have been consistently associated with a subset of depressive symptoms, particularly atypical and energy-related features, as well as antidepressant treatment resistance. This evidence has supported the definition of an inflammatory subtype of major depressive disorder (ISMDD), characterized by immune-inflammatory dysregulation and reduced response to first- and second-line antidepressants. However, a lack of consensus on its definition and assessment tools limits research and treatment development. METHODS:Using a Delphi approach, international experts from the ASPIRE consortium (Advanced Stratification of People with Depression based on Inflammation, n = 25) identified ISMDD symptom domains, which were then evaluated by the European College of Neuropsychopharmacology Immuno-Neuropsychiatry Network (INPN-ECNP, n = 12). Using the same consensus structure, the coverage of these domains by depression rating scales was then assessed. People with lived experience (PWLE, n = 11) provided perspectives on the clinical relevance and impact of the emerged symptoms. RESULTS:ASPIRE consensus identified ten ISMDD symptom domains: fatigue/low energy, hypersomnia, increased weight/appetite, cognitive difficulties, lack of motivation, anhedonia, diminished interest, leaden paralysis, psychomotor retardation, and insomnia, with the first five being also confirmed by INPN-ECNP consensus. Except for increased weight/appetite, PWLE identified these domains as negatively affecting quality of life; most of them were also reported as not extensively assessed in clinical care. Among rating scales, the Inventory of Depressive Symptomatology tools, including their Quick versions, were the only instruments covering all or almost all the ISMDD domains. CONCLUSION:These findings support a framework for ISMDD and highlight the importance of symptom assessment to improve clinical evaluation, research, and personalized immunopsychiatric treatment.

BACKGROUND:Bipolar disorder (BD) is characterized by circadian rhythm disruptions, contributing to mood instability and recurrence. These rhythms are regulated by clock genes in the suprachiasmatic nucleus, including the CLOCK 3111T/C (rs1801260) polymorphism that has been linked to delayed sleep phase, insomnia, and altered circadian expression. Both circadian disruption and adverse childhood experiences (ACEs) correlate with white matter (WM) abnormalities. We hypothesized that rs1801260 moderates ACE effects on WM microstructure in BD. METHODS:We enrolled 137 BD patients in depressive episodes. Participants underwent 3T MRI, rs1801260 genotyping and completed the Childhood Trauma Questionnaire. Moderation (PROCESS) tested genotype-ACE interactions on whole-brain fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) values; voxel-wise TBSS (FSL Randomize) localized effects, with sex-stratified and GLZ analyses for genotype-sex interactions. RESULTS:Significant rs1801260 × ACE interactions emerged for FA and RD across physical abuse, physical neglect, and emotional neglect. Higher ACEs were associated with lower FA/higher RD only in CLOCK rs1801260*C carriers, mainly females. TBSS showed physical abuse × rs1801260 interaction in the corpus callosum, internal capsule and corona radiata. A GLZ model with separate slopes confirmed physical abuse × sex × rs1801260 interactions on FA/RD, with effects specific to female CLOCK rs1801260*C carriers but genotype-independent in males. CONCLUSIONS:rs1801260 moderates the impact of early-life stress on WM integrity in BD, particularly in emotion-regulation tracts, with CLOCK rs1801260*C carriers showing greater vulnerability. Effects are genotype-specific in females but genotype-independent in males, possibly reflecting sex-dimorphic neurodevelopment driven by estrogen-androgen modulation of clock genes, HPA axis, and myelination.

Studies of brain morphology in mental illness often focus on a few neuroimaging phenotypes. Here we present a comprehensive morphological characterization in obsessive-compulsive disorder (OCD) in a large sample (2255 OCD, 2264 controls) using nine cortical and four subcortical phenotypes, including several not previously examined in OCD, among them a subcortical structural similarity network phenotype developed here. Spatially distinct regional alterations emerged across structural phenotypes: cortical curvature alterations in default mode and frontoparietal networks, increased structural similarity network node degree in sensorimotor regions, widespread volume reductions associated with medication use, and localized subcortical shape alterations. In brain-behavior predictive models, curvature phenotypes showed the strongest associations with clinical features. Cortical alterations, especially in structural similarity networks, were associated with specific gene expression patterns, implicating dysregulation of excitatory neurons. RNA-sequencing data from tissue collected during functional neurosurgery revealed that genes downregulated in the dorsolateral prefrontal cortex in OCD contributed to the gene expression patterns linked to cortical alterations. Previously reported differentially expressed genes from postmortem brain studies of OCD also contributed. These findings support the importance of a comprehensive approach to characterizing brain morphology and suggest that cortical curvature and structural similarity alterations reflect key pathophysiological processes in OCD.

Recent research suggests that brain anatomy may help identify the most effective pharmacological treatment for each individual with bipolar disorder and reduce trial-and-error prescribing. We aimed to investigate whether brain anatomy predicts whether a medication is currently prescribed or has been discontinued, as a proxy for treatment effectiveness. The rationale is that medications that provide clinical benefit without unacceptable side effects are likely to be continued, whereas those with limited benefit or poor tolerability are typically discontinued. We used T1-weighted MRI from twelve ENIGMA-BD cohorts (n = 2462; 473 individuals with BD [61% female, age 18-73] and 1989 controls) to derive regional cortical thickness and surface area and subcortical volumes. Site differences were harmonized using ComBat models fitted on controls' data. Within cross-validation, models were trained to first adjust for cumulative dose and other covariates and then predict medication status. On test sets, current prescription (vs. discontinuation) of lithium was predicted by greater cortical thickness and reduced surface area, whereas current prescription (vs. discontinuation) of antidepressants and atypical antipsychotics was predicted by greater cortical thickness. Predictive regions for atypical antipsychotics were generally consistent across subgroups of age, gender, illness duration, and history of psychosis, and in the largest site, and differed from those associated with cumulative effects of medication on the cortex. Predictions were poor for subcortical volumes and for antiepileptic mood stabilizers and typical antipsychotics. These findings provide preliminary support that cortical anatomy may help inform future development of biomarkers for treatment selection, pending validation in longitudinal studies.

AIM:Bipolar disorder (BD) is characterized by circadian dysregulation, altered sleep-wake behaviors, and heterogeneous antidepressant response. Chronotherapeutic interventions such as total sleep deprivation combined with light therapy (TSD + LT) produce rapid antidepressant effects, but predictors of outcome are lacking. We investigated whether fractal dynamics of motor activity, indexed by the short-term scaling exponent α₁, are associated with antidepressant response, sleep-wake regulation, and structural brain measures and may serve as a biomarker of treatment responsiveness. METHODS:Sixty-eight BD inpatients underwent three cycles of TSD + LT. Depressive symptoms were assessed with the Hamilton Depression Rating Scale (HDRS), and treatment response was defined as a post-treatment HDRS score <8. α₁ was derived from actigraphy using detrended fluctuation analysis, with values close to 1 indicating optimal fractal regulation. α₁ was computed before and after TSD + LT, and Δα₁ represented treatment-related change. Sleep-wake and circadian parameters were examined. A subsample underwent multimodal magnetic resonance imaging (MRI). RESULTS:TSD + LT induced clinical improvement in 65.3% of patients. Responders showed a significant reduction in α₁ toward values close to 1, whereas nonresponders did not. Δα₁ correlated with symptom improvement (P = 0.035) and was independently associated with treatment response (P = 0.039). Baseline α₁ was associated with sleep-wake parameters, cerebellar gray matter volume, and white-matter microstructure, including cerebellar peduncles and thalamo-cortical tracts. Circadian rhythmicity increased in responders and decreased in nonresponders. CONCLUSION:Fractal motor activity tracks clinical changes during chronotherapeutic treatment in BD and may represent a candidate marker of treatment-related behavioral regulation. Its association with cerebellar and white-matter measures suggests multimodal relevance, warranting validation in larger longitudinal studies.

AIM:Bipolar disorder (BD) and schizophrenia (SCZ) share many clinical and neurobiological features, and a continuum between the two has been postulated. Bipolar patients leaning toward the SCZ pole of the continuum may have a higher risk of neuroprogression. Here we investigated the relationships between illness course, white matter integrity, levels of N-acetylaspartate (NAA), and polygenic score (PRS) of SCZ. METHODS:A sample of 103 depressed bipolar inpatients underwent magnetic resonance imaging (MRI) acquisition to perform diffusion tensor imaging (DTI) analysis and magnetic resonance spectroscopy to assess NAA. Genotyping and PRS calculation were also performed in a subsample of 75 patients. Associations between illness course, NAA, and white matter microstructure were explored; indirect effects were investigated through mediation models; further, a possible moderating effect of SCZ-PRS was tested. RESULTS:Negative associations emerged between number of affective episodes and NAA. Manic episodes were also negatively associated with white matter integrity, and NAA significantly mediated the effect of manic episodes on DTI metrics. SCZ-PRS moderated the relation between illness duration and NAA. Moderated mediation analyses showed that only at high SCZ-PRS, illness duration negatively affected NAA, which in turn was linked to reduced fractional anisotropy. CONCLUSION:Our results support the concept of neuroprogression in BD, suggesting a deleterious effect of acute episodes, particularly manic ones, on neurochemical and white matter alterations. Further, patients with a higher SCZ-PRS seem to show detrimental effects related to illness duration, possibly suggesting a longitudinal course closer to SCZ.

Six years into the COVID-19 pandemic, evidence is increasingly clear that long COVID affects women disproportionately, with higher rates of persistent cognitive and neurological symptoms. Yet, the biological mechanisms underlying this sex-dimorphic impact remain elusive. We investigated whether the immune storm of acute COVID-19 leaves a silent yet sex-specific scar on white matter integrity that shapes long-term cognitive health. In 60 previously hospitalized COVID-19 survivors, we combined an inflammatory snapshot at admission proxied by the systemic immune-inflammation index (SII) with 3T diffusion MRI and a comprehensive cognitive battery (BACS) acquired three months after recovery. Sex reshaped the inflammation-brain relationship: a higher SII predicted a diffuse alteration pattern within core associative and inter-hemispheric fibres in females only, sparing the male architecture despite a comparable inflammatory burden. In women, white matter damage coupled with poorer psychomotor coordination, and mean diffusivity fully mediated the link, unveiling a female-specific pathway from systemic inflammation to cognitive slowdown. COVID-19 inflammation imprints a durable, sex-sensitive footprint on white matter that selectively undermines psychomotor coordination in female survivors, despite a clinical recovery. This work positions women's white matter as a critical target of post-COVID neuroinflammation and argues for sex-informed monitoring and interventions that explicitly tackle immune-brain crosstalk in long COVID.

Childhood trauma is a risk factor for bipolar disorder, but the biological mechanisms of this association remain incompletely defined. Gray matter differences observed after trauma exposure overlap with those reported in bipolar disorder, suggesting that the association between childhood trauma and bipolar disorder might be mediated through brain morphology. Our goal was to determine whether cortical thickness, cortical surface or subcortical volume mediate the association between childhood trauma and bipolar disorder. We leveraged a large multi-site dataset from the ENIGMA Bipolar Disorder Working Group, comprising of 1,031 participants with bipolar disorder and 2,221 controls from 19 international cohorts. To identify brain morphology mediators of the association of childhood trauma and bipolar disorder, we used high-dimensional mediation analysis and validated our results using leave-one-site-out cross-validation and permutation testing for significance. Severity of childhood trauma was directly associated with higher likelihood of having a bipolar disorder diagnosis (median coefficient 0.841, 95% CI: [0.834, 0.851], p<0.001). Significant mediators were hippocampal volume (0.004, 95% CI: [0.002, 0.005], p<0.001), medial orbitofrontal gray matter thickness (0.002, 95% CI: [0.002, 0.003], p<0.001), and superior frontal gyrus gray matter thickness (0.002, 95% CI: [0, 0.005], p<0.001). Our results show that the severity of childhood trauma exposure is associated with bipolar disorder diagnosis in part through a smaller hippocampus, thinner cortex in the medial orbitofrontal gyrus and thinner cortex in the superior frontal gyrus. The identification of this mechanistic pathway improves our etiologic understanding of bipolar disorder and could help to identify those at risk and enable the development of new interventions.

Growing evidence suggests the neurobiological mechanism upholding post-COVID-19 depression mainly relates to immune response and subsequent unresolved low-grade inflammation. Herein we exploit a broad panel of cytokines serum levels measured in COVID-19 survivors at one- and three-month since infection to predict post-COVID-19 depression. 87 COVID survivors were screened for depressive symptomatology at one- and three-month after discharge through the Beck Depression Inventory (BDI-13) and the Zung Self-Rating Depression Scale (ZSDS) at San Raffaele Hospital. Blood samples were collected at both timepoints and analyzed through Luminex. We entered one-month 42 inflammatory compounds into two separate penalized logistic regression models to evaluate their reliability in identifying COVID-19 survivors suffering from clinical depression at the two timepoints, applied within a machine learning routine. Delta values of analytes lowering between timepoints were entered in a third model predicting presence long-term depression. 5000 bootstraps were computed to determine significance of predictors. The cross-sectional model reached a balance accuracy (BA) of 76 % and a sensitivity of 70 %. Post-COVID-19 depression was predicted by high levels of CCL17, CCL22. On the other hand, CXCL10, CCL2, CCL3, CCL8, CXCL5, CCL15, CCL23, CXCL13, and GM-CSF showed protective effects. The longitudinal model obtained good performance as well (BA = 74 % and sensitivity = 68 %), revealing CXCL16 and CCL25 as additional drivers of clinical depression. Moreover, dynamic changes of analytes over time accurately predicted long-term depression (BA = 76 % and sensitivity = 75 %). Our findings unveil a putative immune profile upholding post-COVID-19 depression, thus reinforcing the need to deepen molecular mechanisms to appropriately target depression.

BACKGROUND:Negative Cognitive Styles (NCS) are key features of depression contributing to severe clinical outcomes by sustaining negative affect. However, depression is clinically heterogeneous, reflecting complex neurobiological and environmental interactions. Characterizing heterogeneity using multimodal data could help identify mechanisms mapping onto different phenotypes and discover high-impact biomarkers. METHODS:Using a stability-based relative clustering validation pipeline, 344 depressed patients (135 major depressive disorder, 209 bipolar disorder) were stratified based on multimodal neuroimaging data, including grey matter volumes, cortical thickness, white matter diffusivity indices, resting-state functional connectivity (FC), and spontaneous neural activity. Clusters were derived from each modality separately and in combination, and profiled for Adverse Childhood Experiences (ACEs) and NCS. RESULTS:All neuroimaging modalities stratified depressed patients into two clusters, with the FC-based model achieving the highest accuracy (85 %). Compared with healthy controls (HC, N = 138), these clusters exhibited opposite patterns of global functional hyper-integration (Cluster 1) and hyper-segregation (Cluster 2). Unique multivariate neurobiological-ACEs relationships characterized the FC-based clusters. While ACEs negatively affected FC in Cluster 1 and HC, Cluster 2 showed opposite effects specific to ACE subtypes, with sexual abuse positively influencing FC. Mediation analysis showed that FC strength mediated the relationship between ACEs and NCS of overgeneralize only in Cluster 2. ACE-related functional alterations pinpoint brain regions involved in socioemotional and cognitive development, sensitive to maturational neural changes. CONCLUSIONS:These findings provide evidence of clinically meaningful depression "biotypes" shaped by ACEs and associated with NCS, underlining the feasibility of computational psychiatry tools to uncover data-driven patterns for precision psychiatry.

Nearly 60 % of individuals with bipolar disorder (BD) are initially classified as major depressive disorder (MDD) patients, resulting in inappropriate drug treatment. Identifying reliable biomarkers for the differential diagnosis between MDD and BD patients may allow to define the best treatment option since the early phases. In this study, we deployed machine learning predictive models to classify 62 MDD and 63 BD patients with a current depressive episode from resting functional neuroimaging feature (rs-fMRI), including fractional amplitude of low-frequency fluctuations, regional homogeneity, atlas-based connectivity across 434 regions of interest, seed-based connectivity maps for 44 seeds, and 14 dual regression components. Models were also compared to 76 healthy controls. Only the model trained on seed-based connectivity reached the statistical significance in permutation test reaching the highest classification performance (69.36 % of accuracy for BD and 63.08 % for MDD). Seed-based connectivity also reached the best performance in identifying MDD (78.33 %) and BD (71.67 %) relative to controls. Connectivity patterns in key brain regions of the reward and aversion systems appeared crucial in differentiating the disorders, possibly identifying distinct clinical phenotypes of disorders, beyond the depressive ongoing episode.

Post-COVID syndrome has unveiled intricate connections between inflammation, depressive psychopathology, and cognitive impairment. This study investigates these relationships in 101 COVID-19 survivors, focusing on sex-specific variations. Utilizing path modelling techniques, we analyzed the interplay of a one-month 48-biomarker inflammatory panel, with three-months of depressive symptoms and cognitive performance. The findings indicate that cognitive impairment is influenced by both inflammation and depression in the overall cohort. However, prominent sex-specific differences emerged. In females, a lingering imbalance between pro- and anti-inflammatory responses—likely reflecting the long-lasting immune alterations triggered by COVID-19—significantly affects cognitive functioning and shows a marginal, though not statistically significant, association with depressive symptoms. This suggests that a mixed inflammatory profile may contribute to these outcomes. Conversely, in males, inflammation was inversely associated with depression severity, with protective effects from regulatory mediators (IL-2, IL-4, IL-6, IL-15, LIF, TNF-α, β-NGF) against depression. In males, cognitive impairment appeared to be driven mainly by depressive symptoms, with minimal influence from inflammatory markers. These results highlight distinct sex-specific pathways in immune and inflammatory responses post-COVID-19, potentially shaped by endocrine mechanisms. The findings suggest that persistent inflammation may foster long-term neuropsychiatric sequelae, possibly through its effects on the brain, and underscore the need for sex-tailored therapeutic strategies to address the lasting impact of COVID-19.

AIMS:After 3 years from the beginning of SARS-CoV-2 pandemic, a substantial proportion of affected patients still present at least one symptom after infection. Given that: magnetic resonance imaging studies up to two years after COVID-19 reported changes in white matter (WM) microstructure and in functional connectivity; WM associates with glutamate and N-acetyl-aspartate levels in BD; the link between cognitive impairment and WM integrity, the aim of the study was to investigate metabolites associations with alterations in structural and functional brain connectivity and cognition in 64 COVID-19 survivors and 33 healthy controls (HC). METHODS:We compared WM microstructure and metabolites levels between individuals recovering from COVID-19 and HCs. Then, we investigated the associations between WM and glutamate and N-acetyl-aspartate in the two groups. RESULTS:Patients showed: higher levels of glutamate and NAA compared to HCs with a positive effect on cognitive complaints; higher fractional anisotropy (FA), and lower radial (RD) and mean diffusivity (MD); glutamate and N-acetyl-aspartate significant positive associations with FA, and a negative one with MD and RD. FA levels moderated the relation between the glutamate and cognitive deficits. Finally, N-acetyl-aspartate associated with higher rs-FC between VOI and the posterior cingulate gyrus in individuals recovering from COVID-19. CONCLUSIONS:Our findings suggest that a process of brain repair and remyelination, as suggested by higher levels of glutamate and N-acetyl-aspartate and by higher measures of WM microstructure, may occur after SARS‑CoV‑2 infection which may help the recovery from long COVID-19 symptoms such as cognitive impairment.

Major Depressive Disorder (MDD) and Bipolar Disorder (BD) involve alterations of immune-inflammatory setpoints that activate the kynurenine pathway (KP), affecting serotoninergic and glutamatergic neurotransmission through indoleamine-2,3-dioxygenase (IDO) activity. This process produces metabolites like Kynurenine (Kyn), 3-Hydroxykynurenine (3-HK), Quinolinic acid (QuinA), and Kynurenic acid (KynA), these last two acting as agonist and antagonist at glutamatergic N-methyl-D-aspartate receptors (NMDARs), respectively. NMDARs, expressed in the choroid plexus (ChP) and arteriolar smooth muscle cells, regulate blood-brain-barrier permeability and cerebral artery dilation, suggesting that KP may influence neurovascular coupling, aligning blood flow with neural energy demand. KP's role in modulating vascular tone supports this hypothesis. Altered fractional amplitude of low-frequency fluctuations (fALFF) and disrupted default mode network (DMN) activity in mood disorders are linked to cognitive deficits possibly through neurovascular uncoupling like in neurological diseases. This makes fALFF and hemodynamic response function (HRF) potential indicators of these changes. We investigated KP associations with ChP volumes, functional-MRI at rest measures like spontaneous neural activity (fALFF) and hemodynamic response function (HRF) parameters within the default mode network (DMN), and cognitive performance in 42 MDD and 36 BD inpatients experiencing a depressive episode. Results revealed that lower QuinA/KynA ratios and higher KynA levels predict larger ChP volumes. Higher KYN and 3-HK levels, along with lower KynA levels, were associated with increased DMN fALFF and shorter time-to-peak (TTP) in HRF, suggesting altered neurovascular coupling. Mediation analyses indicated that KP metabolites influenced cognitive performance through their effects on resting state measures, affecting global cognitive functioning score, verbal fluency, and psychomotor coordination. These findings suggest that KP metabolites modulate brain function and structure via NMDAR-mediated pathways and vascular-based mechanisms, offering insights into the cognitive impairments observed in mood disorders and identifying potential therapeutic targets.

Low-grade systemic inflammation is linked to cardiometabolic diseases and increased cardiovascular risk. Patients with mood disorders, such as Major Depressive Disorder (MDD) and Bipolar Disorder (BD), also show elevated cardiovascular risk and inflammatory markers, suggesting shared biological pathways between mood and cardiometabolic conditions. The kynurenine (KYN) pathway, activated by inflammatory cytokines and involved in neurotransmitter systems linked to mood, provides a promising area to explore inflammatory-related genetic overlaps in these disorders, with increasing interest in the SH2B3 rs3184504 SNP. Imaging markers like white matter hyperintensities (WMHs) and white matter (WM) microstructure alterations are associated with mood and cardiovascular disorders. This study aimed to investigate the genetic load linked to KYN levels, such as KYN polygenic risk score (PRS) and its effect on white matter hyperintensities (WMHs), outcomes of presumed vascular suffering, and WM microstructure in a sample of 95 MDD and 80 BD patients. Higher PRS for KYN was associated with increased circulating KYN levels and KYN/TRP ratio. KYN PRS predicted the presence of WMHs. The SH2B3 rs3184504 T variant was associated with increased PRS for KYN and a higher number of WMHs. KYN levels and KYN/TRP ratio were not associated with WMHs, while KYN PRS positively correlated with higher axial (AD) and mean diffusivity (MD), with a nominal significance for radial diffusivity (RD). The findings support a genetic contribution to elevated KYN and WM integrity alterations in mood disorders. PRS for KYN indicates a potential predisposition to inflammatory and vascular dysregulation, and SH2B3 rs3184504 may modulate this risk.