BACKGROUND:Major depressive disorder (MDD) and bipolar disorder (BD) are associated with increased suicide risk and commonly feature metabolic dysfunctions such as insulin resistance (IR) and obesity. These conditions are also linked to systemic inflammation and white matter (WM) alterations, which may underlie suicidal behaviors. This study explores how immune-metabolic markers affect WM integrity and suicidality in mood disorders. METHODS:Inpatients with BD (n = 93) and MDD (n = 88) underwent diffusion tensor imaging to assess WM integrity. Blood samples were analyzed for insulin, glucose, and inflammatory markers. IR was assessed via HOMA-IR and QUICKI. Suicide risk was measured using the Beck Scale for Suicide Ideation (BSI) and the Hamilton Depression Rating Scale (HDRS). RESULTS:BD patients showed higher IR, BMI, and inflammation compared to MDD patients. In BD, both insulin and HOMA-IR positively correlated with suicide risk and were associated with increased suicidal ideation. BMI indirectly predicted suicide risk through IR, but not via inflammation. WM analysis revealed that in high-suicide-risk BD patients, higher insulin and HOMA-IR were associated with reduced fractional anisotropy and increased mean and radial diffusivity-markers of axonal and myelin disruption. These effects were not observed in MDD or BD patients with lower suicide risk. CONCLUSION:Insulin resistance emerges as a key contributor to suicidality in BD, possibly via its impact on WM integrity. Although BMI did not directly predict suicide risk, its effect through IR suggests metabolic health may be a modifiable target. Early intervention on IR and inflammation could benefit high-risk BD individuals.

The purpose of the present study is to provide a preliminary evidence of the possible involvement of extracellular nicotinamide phosphoribosyltransferase (eNAMPT) in antidepressant response. NAMPT is the major regulator of the cellular availability of nicotinamide adenine dinucleotide (NAD+), and, when released from the cells, it influences activity, energy expenditure, and neurotransmitter levels in mammals. We studied changes of blood circulating eNAMPT before and after treatment in 46 patients with major depressive disorder, treated with monoaminergic antidepressant drugs for 1 month, or with Bipolar Disorder, treated with antidepressant chronotherapeutics (repeated total sleep deprivation combined with light therapy) for 1 week. Participants showed high individual variation in eNAMPT before and after treatment. The increase in circulating eNAMPT concentration was associated with individual benefit from treatment independent of diagnosis or type of treatment. eNAMPT increase was not necessary to achieve response, but the best antidepressant effects were observed in patients showing the highest increase. These findings suggest that eNAMPT may facilitate treatment efficacy rather than acting as a direct mechanism of symptom reduction. Results are in agreement with the literature affirming a possible role of NAD+ homeostasis and mitochondrial mechanisms in mood disorders. If confirmed, they may pave the way to identify new targets for the treatment of depression.

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.

BACKGROUND:Major depressive disorder (MDD) and bipolar disorder (BD) are associated with persistent cognitive deficits, but the biological mechanisms underlying these impairments remain unclear. Metabolic dysfunction, particularly insulin resistance (IR), may contribute to brain structural alterations and cognitive decline. However, diagnosis-specific metabolic effects on gray matter volumes (GMVs) and cognition have not been fully explored. Partial least squares path modeling was applied to examine associations among metabolic biomarkers, GMVs, and cognitive performance in mood disorders, stratifying by diagnosis. METHODS:A total of 81 inpatients with BD (55 female, 26 male) and 78 inpatients with MDD (45 female, 33 male) underwent neuropsychological evaluation with the Brief Assessment of Cognition in Schizophrenia. T1-weighted magnetic resonance images were processed to extract GMVs. Blood samples were collected to assess metabolic markers. RESULTS:In the whole sample, the metabolism latent construct negatively predicted both GMV and cognition, with the GMV factor positively affecting cognition. A significant diagnostic difference emerged for the metabolism-to-cognition path (p = .0196). Stratified analyses showed that in BD, metabolism was significantly associated with both reduced GMVs and poorer cognition, whereas no significant structural paths were identified in MDD. IR markers and leptin were the strongest positive contributors to the metabolism factor in both the whole sample and the BD group. The brain regions most affected encompassed areas central to cognitive and emotional regulation, characterized by a high density of insulin and leptin receptors. CONCLUSIONS:These findings highlight the role of IR and leptin in shaping cognition in mood disorders and underscore the potential of insulin-related pathways as therapeutic targets, especially in BD with metabolic comorbidities.

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.

INTRODUCTION:Depressive disorders are a leading cause of global disease burden, particularly with the challenge of treatment-resistant depression (TRD). Research points to a complex bidirectional relationship between cardiovascular (CV) risk factors and TRD, with CV risk negatively impacting brain structure and potentially influencing antidepressant resistance. Moreover, the association between depression and the genetic vulnerability to cardiovascular disease suggests a shared pathophysiological process between the two. This study investigates the mediating role of brain structural alterations in the relationship between CV and cerebrovascular (CeV) risk and treatment resistance in depression. METHODS:We assessed 165 inpatients with Major depressive disorder. Each patient's CV risk was assessed via the QRISK 3 calculator. For a subset of patients, CV and CeV disease polygenic risk scores (PRS) were obtained. All patients underwent a 3 T MRI scan, and white matter hyperintensities estimates and indicators of brain trophic state were obtained. RESULTS:Both CV risk and CV disease PRSs are associated with treatment resistance status, white matter hyperintensities, and indicators of brain atrophy. Mediation analyses suggested that CV-induced brain alterations might underlie the relation between CV genetic and phenotypic risk and antidepressant treatment resistance. CONCLUSION:These results underscore the need to explore cardiovascular risk management as part of treatment strategies for depression, pointing toward a shared pathophysiological process linking heart and brain health in treatment-resistant depression.

BACKGROUND: The neurobiological differences between women who have experienced a peripartum episode and those who have only had episodes outside of this period are not well understood. METHODS: Sixty-four parous female patients with major depressive disorder who had either a positive (n = 30) or negative (n = 34) history of peripartum depression (PPD) underwent magnetic resonance imaging acquisition to obtain structural brain images. An independent 2-sample t test comparing patients with and without a history of PPD was performed using voxel-based morphometry analysis. Additionally, polygenic risk scores for estradiol were calculated, and a moderation analysis was conducted between 3 estradiol polygenic risk scores and PPD history status on extracted cluster volumes using IBM SPSS PROCESS macro. RESULTS: The voxel-based morphometry analysis identified larger gray matter volumes in bilateral clusters encompassing the putamen, pallidum, caudate, and thalamus in patients with a PPD history than in patients without a history. The moderation analysis identified a significant interaction effect between 2 estradiol polygenic risk scores and PPD history on gray matter cluster volumes, with a positive effect in women with PPD and a negative effect in women with no history of PPD. CONCLUSIONS: Our findings demonstrate that women who have experienced a peripartum episode are neurobiologically distinct from women who have no history of PPD in a cluster within the basal ganglia, an area important for motivation, decision making, and emotional processing. Furthermore, we show that the genetic load for estradiol has a differing effect in this area based on PPD status, which supports the claim that PPD is associated with sensitivity to sex steroid hormones.

Abstract Background Heterogeneity in depression results from interactions of multiple biological and environmental factors. For instance, exposure to early-adverse events amplifies the cross-talk between inflammation and brain activity, resulting in depressive symptomatology [1]. This brain-immune relationship is particularly crucial for females who are more vulnerable to inflammation and its mood effects compared to males [2]. However, only 30% of patients exhibit an abnormal immune profile, suggesting that inflamed depression might represent a distinct subtype [3]. Data-driven approaches are promising in yielding novel insights into depression neurobiology while disentangling heterogeneity [4]. Aims & Objectives By applying an unsupervised machine learning approach, we aim to unveil immunophenotypes of depressed patients based on immune cell counts, also investigating sex, childhood trauma, and white matter differences. Methods Peripheral blood mononuclear cells (PBMC) from 145 depressed patients (92 Major Depressive Disorder [MDD], 53 Bipolar Disorder [BD]) were analysed using FlowJo v.10.8.1 (FlowJo LLC, Ashland, OR). An immune profile was generated on PBMC using a multiparametric flow cytometry. A 28-color flow cytometry panel was used to characterize lymphocyte phenotype and function. In a subsample of 108 patients (67 MDD, 41 BD), extracted tract-based fractional anisotropy and diffusivity indexes were computed from diffusion tensor images (TBSS, FSL). Exposure to childhood trauma was assessed through the Childhood Trauma Questionnaire (CTQ) [5], dichotomizing domains’ scores according to standard cut-offs [6]. A stability-based relative clustering validation approach [7] was applied to immune cell populations, considering K-means as clustering algorithm and support vector machine as classifier. Hyperparameters tuning was performed in a 2x10 repeated cross-validation, iterating over a number of clusters from 2 to 5. The solution that minimised the normalized stability (i.e., prediction error) were chosen as the best one. Statistical significance was assessed by 10,000 simulations from a single null Gaussian distribution. Differences in diagnosis, sex, extracted white matter diffusivity indices, and CTQ domains were assessed through chi-square and Mann-Whitney U tests. Results The unsupervised pipeline identified 2 clusters with a normalized stability of 0.28 (p<0.0001). While one cluster (N=53) showed a higher proportion of MDD patients (p=0.008) with higher i) lymphocytes; ii) CD4+ and CD8+CD69+; iii) NK; iv) CD4+CD25highFoxP3+CD39+; and v) CM, EM and TEMRA CD8+Perf-Grz+ cells count (pFDR<0.05), the other one (N=92) was characterized by higher F:M ratio (p=0.064) and higher i) CD4+CD25+; ii) CD4+CD25highFoxP3-CD39+; and iii) TEMRA, CM, EM CD8+Perf+GrzB- cells count (pFDR<0.05). Higher axial, radial, and mean diffusivity values in the genu of the corpus callosum and left cingulum were found in the first cluster (pFDR<0.05). Discussion & Conclusions Our results provided evidence of an immune cells-based stratification of depressed patients, suggesting the existence of 2 inflamed subgroups differentiated by distinct immune cell profiles and structural connectivity patterns. These findings foster our understanding of the neurobiological complexity of depression, which could have important implications in tailoring personalized treatments targeting the individual immune-biological profile. References [1]NUSSLOCK, R. &MILLER, G. E. 2016. Early-life adversity and physical and emotional health across the lifespan: A neuroimmune network hypothesis. Biological psychiatry, 80, 23-32. [2]DERRY, H. M., PADIN, A. C., KUO, J. L., HUGHES, S. &KIECOLT-GLASER, J. K. 2015. Sex differences in depression: does inflammation play a role? Current psychiatry reports, 17, 1-10. [3]CHAMBERLAIN, S. R., CAVANAGH, J., DE BOER, P., MONDELLI, V., JONES, D. N., DREVETS, W. C., COWEN, P. J., HARRISON, N. A., POINTON, L. &PARIANTE, C. M. 2019. Treatment-resistant depression and peripheral C-reactive protein. The British Journal of Psychiatry, 214, 11-19. [4]LYNALL, M.-E., TURNER, L., BHATTI, J., CAVANAGH, J., DE BOER, P., MONDELLI, V., JONES, D., DREVETS, W. C., COWEN, P. &HARRISON, N. A. 2020. Peripheral blood cell– stratified subgroups of inflamed depression. Biological psychiatry, 88, 185-196. [5]BERNSTEIN, D. P., STEIN, J. A., NEWCOMB, M. D., WALKER, E., POGGE, D., AHLUVALIA, T., STOKES, J., HANDELSMAN, L., MEDRANO, M. &DESMOND, D. 2003. Development and validation of a brief screening version of the Childhood Trauma Questionnaire. Child abuse & neglect, 27, 169-190. [6]MACDONALD, K., THOMAS, M. L., SCIOLLA, A. F., SCHNEIDER, B., PAPPAS, K., BLEIJENBERG, G., BOHUS, M., BEKH, B., CARPENTER, L. &CARR, A. 2016. Minimization of childhood maltreatment is common and consequential: results from a large, multinational sample using the childhood trauma questionnaire. PloS one, 11, e0146058. [7]LANDI, I., MANDELLI, V. &LOMBARDO, M. V. 2021. reval: A Python package to determine best clustering solutions with stability-based relative clustering validation. Patterns, 2, 100228.

Abstract Background Immune-inflammatory mechanisms are promising targets for antidepressant pharmacology [1-3]. Based on reported immune cell abnormalities, we defined an antidepressant potentiation treatment with add-on low-dose interleukin 2 (IL-2), a T-cell growth factor of proven anti-inflammatory efficacy in autoimmune conditions, increasing thymic production of naï ve CD4+ T cells [4-6], and possibly correcting the partial T cell defect observed in mood disorders [7, 8]. Aims & Objectives We performed a single-center, randomised, double-blind, placebo-controlled phase II trial in depressed patients with major depressive or bipolar disorder administering low-dose IL-2 (aldesleukin). The primary endpoint was the change in the relative concentration of peripheral blood Tregs (CD3+CD4+FoxP3+CD127loCD25hi Treg). Secondary endpoints were changes in Th1 and Th2, Naï ve T cells, Central memory T cells; safety and antidepressant efficacy of aldesleukin at day 36 (end of treatment) and at day 60 (end of follow up). Methods Thirty-six consecutively recruited inpatients at the Mood Disorder Unit at San Raffaele Hospital in Milan, Italy, were randomised in a 2:1 ratio to receive either aldesleukin (12 MDD and 12 BD) or placebo (6 MDD and 6 BD). The treatment (either IL-2 or placebo) was administered daily for the first 5 days (induction phase) and weekly for the following 4 weeks (maintenance phase). Clinical evaluations (Montgomery-Å sberg Depression Rating Scale (MADRS), Inventory for Depressive Symptomatology Self-Rated (IDS-SR)) have been performed concurrently with each injection; blood samples have been collected at baseline, after 5 days and at week 60 and analysed through flow cytometry with a 28-color flow cytometry panel. Results Twenty-eight out of 36 enrolled patients, concluded the study (10 Placebo, 6 BD and 4 MDD) whereas all patients completed the induction phase. Low-dose IL-2 significantly potentiated antidepressant response to ongoing SSRI/SNRI treatment in both diagnostic groups as measured by a reduction in both MDRS and IDS-SR scores, and expanded the population of Treg, Th2, and Naive CD4+/CD8+ immune cell counts. Changes in cell counts were rapidly induced in the first five days of treatment, and predicted the later improvement of depression severity. No serious adverse effect was observed. Discussion & Conclusion This is the first RCT evidence supporting the hypothesis that a treatment able to strengthen the T cell system could be a successful way to correct the immuno-inflammatory abnormalities associated with mood disorders, and potentiate antidepressant response. Indeed, the main effect observed of IL-2 was to promote Tregs expansion and enhance response at 5 weeks of treatment preventing the subsequent relapse, thus promoting and consolidating improvement over time. References 1.Benedetti, F. and B. Vai, New biomarkers in mood disorders: Insights from immunopsychiatry and neuroimaging. European Neuropsychopharmacology: the Journal of the European College of Neuropsychopharmacology, 2023. 69: p. 56-57. 2.Benedetti, F., R. Zanardi, and M.G. Mazza, Antidepressant psychopharmacology: is inflammation a future target? International clinical psychopharmacology, 2022. 37(3): p. 79-81. 3.Branchi, I., et al., Brain-immune crosstalk in the treatment of major depressive disorder. European Neuropsychopharmacology, 2021. 45: p. 89-107. 4.Klatzmann, D. and A.K. Abbas, The promise of low-dose interleukin-2 therapy for autoimmune and inflammatory diseases. Nat Rev Immunol, 2015. 15(5): p. 283-94. 5.Rosenzwajg, M., et al., Immunological and clinical effects of low-dose interleukin-2 across 11 autoimmune diseases in a single, open clinical trial. Annals of the rheumatic diseases, 2019. 78(2): p. 209-217. 6.Graß hoff, H., et al., Low-dose IL-2 therapy in autoimmune and rheumatic diseases. Frontiers in immunology, 2021. 12: p. 648408. 7.Simon, M.S., et al., Monocyte mitochondrial dysfunction, inflammaging, and inflammatory pyroptosis in major depression. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 2021. 111: p. 110391. 8.Simon, M.S., et al., Premature T cell aging in major depression: A double hit by the state of disease and cytomegalovirus infection. Brain, Behavior, &Immunity-Health, 2023. 29: p. 100608.

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.

Adverse childhood experiences (ACEs) are risk factors for both major depressive (MDD) and bipolar disorder. ACEs have been associated with white matter (WM) alterations, but whether they have different effects in MDD and BD remains unclear. Polygenic risk scores (PRS) allow for an individual estimation of genetic liabilities for most psychiatric conditions. The aim of the present study was to characterize the effect of ACEs on WM microstructure in MDD and BD, testing a possible differential effect between the two diagnoses and investigating whether genetic liabilities might modulate this relation. 260 depressed inpatients (140 MDD and 120 BD, mean age 49.29 ± 10.60, F = 161) underwent 3T MRI scan and ACEs evaluation. MDD and BD PRS were calculated in a subset of patients. Significant ACEs x diagnosis interactions were found for several DTI metrics. Single group analyses showed widespread detrimental effects of ACEs on WM integrity in BD, and less pronounced effects in MDD. Significant moderating effect of BD PRS in the whole sample and in MDD specifically were found for the relation between ACEs, fractional anisotropy and radial diffusivity, with bipolar-like relations for higher values of BD PRS. The differential effect of ACEs on WM microstructure in the two diagnostic groups points towards putative differential pathophysiological routes through which childhood maltreatment affects the two conditions, while the identification of a BD PRS moderation on the whole sample and in MDD specifically sheds light on the causal relation between ACEs, diagnostic phenotype and DTI metrics, and provides a possible tool to disentangle MDD heterogeneity.

An estimated 30 % of Major Depressive Disorder (MDD) patients exhibit resistance to conventional antidepressant treatments. Identifying reliable biomarkers of treatment-resistant depression (TRD) represents a major goal of precision psychiatry, which is hampered by the clinical and biological heterogeneity. To uncover biologically-driven subtypes of MDD, we applied an unsupervised data-driven framework to stratify 102 MDD patients on their neuroimaging signature, including extracted measures of cortical thickness, grey matter volumes, and white matter fractional anisotropy. Our novel analytical pipeline integrated different machine learning algorithms to harmonize data, perform data dimensionality reduction, and provide a stability-based relative clustering validation. The obtained clusters were characterized for immune-inflammatory peripheral biomarkers, TRD, history of childhood trauma and depressive symptoms. Our results indicated two different clusters of patients, differentiable with 67 % of accuracy: one cluster (n = 59) was associated with a higher proportion of TRD, and higher scores of energy-related depressive symptoms, history of childhood abuse and emotional neglect; this cluster showed a widespread reduction in cortical thickness (d = 0.43-1.80) and volumes (d = 0.45-1.05), along with fractional anisotropy in the fronto-occipital fasciculus, stria terminalis, and corpus callosum (d = 0.46-0.52); the second cluster (n = 43) was associated with cognitive and affective depressive symptoms, thicker cortices and wider volumes. Multivariate analyses revealed distinct brain-inflammation relationships between the two clusters, with increase in pro-inflammatory markers being associated with decreased cortical thickness and volumes. Our stratification of MDD patients based on structural neuroimaging identified clinically-relevant subgroups of MDD with specific symptomatic and immune-inflammatory profiles, which can contribute to the development of tailored personalized interventions for MDD.

Depressed patients exhibit altered levels of immune-inflammatory markers both in the peripheral blood and in the cerebrospinal fluid (CSF) and inflammatory processes have been widely implicated in the pathophysiology of mood disorders. The Choroid Plexus (ChP), located at the base of each of the four brain ventricles, regulates the exchange of substances between the blood and CSF and several evidence supported a key role for ChP as a neuro-immunological interface between the brain and circulating immune cells. Given the role of ChP as a regulatory gate between periphery, CSF spaces and the brain, we compared ChP volumes in patients with bipolar disorder (BP) or major depressive disorder (MDD) and healthy controls, exploring their association with history of illness and levels of circulating cytokines. Plasma levels of inflammatory markers and MRI scans were acquired for 73 MDD, 79 BD and 72 age- and sex-matched healthy controls (HC). Patients with either BD or MDD had higher ChP volumes than HC. With increasing age, the bilateral ChP volume was larger in patients, an effect driven by the duration of illness; while only minor effects were observed in HC. Right ChP volumes were proportional to higher levels of circulating cytokines in the clinical groups, including IFN-γ, IL-13 and IL-17. Specific effects in the two diagnostic groups were observed when considering the left ChP, with positive association with IL-1ra, IL-13, IL-17, and CCL3 in BD, and negative associations with IL-2, IL-4, IL-1ra, and IFN-γ in MDD. These results suggest that ChP could represent a reliable and easy-to-assess biomarker to evaluate the brain effects of inflammatory status in mood disorders, contributing to personalized diagnosis and tailored treatment strategies.

Immune-inflammatory mechanisms are promising targets for antidepressant pharmacology. Immune cell abnormalities have been reported in mood disorders showing a partial T cell defect. Following this line of reasoning we defined an antidepressant potentiation treatment with add-on low-dose interleukin 2 (IL-2). IL-2 is a T-cell growth factor which has proven anti-inflammatory efficacy in autoimmune conditions, increasing thymic production of naïve CD4 + T cells, and possibly correcting the partial T cell defect observed in mood disorders. We performed a single-center, randomised, double-blind, placebo-controlled phase II trial evaluating the safety, clinical efficacy and biological responses of low-dose IL-2 in depressed patients with major depressive (MDD) or bipolar disorder (BD). 36 consecutively recruited inpatients at the Mood Disorder Unit were randomised in a 2:1 ratio to receive either aldesleukin (12 MDD and 12 BD) or placebo (6 MDD and 6 BD). Active treatment significantly potentiated antidepressant response to ongoing SSRI/SNRI treatment in both diagnostic groups, and expanded the population of T regulatory, T helper 2, and percentage of Naive CD4+/CD8 + immune cells. Changes in cell frequences were rapidly induced in the first five days of treatment, and predicted the later improvement of depression severity. No serious adverse effect was observed. This is the first randomised control trial (RCT) evidence supporting the hypothesis that treatment to strengthen the T cell system could be a successful way to correct the immuno-inflammatory abnormalities associated with mood disorders, and potentiate antidepressant response.

Background: The genetic determinants of peripartum depression (PPD) are not fully understood. Using a multi-polygenic score approach, we characterized the relationship between genome-wide information and the history of PPD in patients with mood disorders, with the hypothesis that multiple polygenic risk scores (PRSs) could potentially influence the development of PPD. Methods: We calculated 341 PRSs for 178 parous mood disorder inpatients affected by major depressive disorder (MDD) or bipolar disorder (BD) with (n = 62) and without (n = 116) a history of PPD. We used partial least squares regression in a novel machine learning pipeline to rank PRSs based on their contribution to the prediction of PPD, in the whole sample and separately in the two diagnostic groups. Results: The PLS linear regression in the whole sample defined a model explaining 27.12% of the variance in the presence of PPD history, 56.73% of variance among MDD, and 42.96% of variance in BD. Our findings highlight that multiple genetic factors related to circadian rhythms, inflammation, and psychiatric diagnoses are top contributors to the prediction of PPD. Specifically, in MDD, the top contributing PRS was monocyte count, while in BD, it was chronotype, with PRSs for inflammation and psychiatric diagnoses significantly contributing to both groups. Conclusions: These results confirm previous literature about the immune system dysregulation in postpartum mood disorders, and shed light on which genetic factors are involved in the pathophysiology of PPD.

Introduction About 60% of bipolar disorder (BD) cases are initially misdiagnosed as major depressive disorder (MDD), preventing BD patients from receiving appropriate treatment. An urgency exists to identify reliable biomarkers for improving differential diagnosis (DD). Machine learning methods may help translate current knowledge on biomarkers of mood disorders into clinical practice by providing individual-level classification. No study so far has combined biological data with clinical data to provide a multifactorial predictive model for DD. Objectives Define a predictive algorithm for BD and MDD by integrating structural neuroimaging and inflammatory data with neuropsychological measures (NM). Two different algorithms were compared: multiple kernel learning (MKL) and elastic net regularized logistic regression (EN). Methods In a sample of 141 subjects (70 MDD; 71 BD), two different models were implemented for each algorithm: 1) structural neuroimaging measures only (i.e. voxel-based morphometry (VBM), white matter fractional anisotropy (FA), and mean diffusivity (MD)); 2) VBM, FA, and MD combined with NM. In a subsample of 71 subjects (36 BD; 38 MDD), two similar models were implemented: 1) VBM, FA, and, MD combined with only NM; 2) VBM, FA, and MD combined with NM and peripheral inflammatory markers. Finally, the best model was selected for comparison with healthy controls (HC). Results Overall, the EN model based on all the modalities achieved the highest accuracy (AUC = 90.2%), outperforming MKL (AUC=85%). EN correctly classified BD and MDD with a diagnostic accuracy of 78.3%, sensitivity of 75%, and specificity of 81.6%. The most significant predictors of BD (variable inclusion probability (VIP) > 80%) were the parahippocampal cingulate, interleukin 9, chemokine CCL5, posterior thalamic radiation, and internal capsule, whereas MDD was best predicted by chemokine CCL23, the anterior cerebellum, and the sagittal stratum. In contrast, NM did not help to differentiate between MDD and BD. However, they help to distinguish patients from HC. Psychomotor coordination and speed of information processing discriminated between MDD and HC (VIP>90%), whereas fluency, working memory, and executive functions differentiated between BD and HC (VIP>80%). Conclusions In summary, BD was predicted by a strong proinflammatory profile, whereas MDD was identified by structural neuroimaging data. A multimodal approach offers additional instruments to improve personalized diagnosis in clinical practice and enhance the ability to make DD. Disclosure of Interest None Declared

Circadian rhythm disruption is a core symptom of bipolar disorder (BD), also reflected in altered patterns of melatonin release. Reductions of grey matter (GM) volumes are well documented in BD. We hypothesized that levels and timing of melatonin secretion in bipolar depression could be associated with depressive psychopathology and brain GM integrity. The onset of melatonin secretion under dim light conditions (DLMO) and the amount of time between DLMO and midsleep (i.e. phase angle difference; PAD) were used as circadian rhythm markers. To study the time course of melatonin secretion, an exponential curve fitting the melatonin values was calculated, and the slope coefficients (SLP) were obtained for each participant. Significant differences were found between HC and BD in PAD measures and melatonin profiles. Correlations between PAD and depressive psychopathology were identified. Melatonin secretion patterns were found to be associated with GM volumes in the Striatum and Supramarginal Gyrus in BD. Our findings emphasized the role of melatonin secretion role as a biological marker of circadian synchronization in bipolar depression and provided a novel insight for a link between melatonin release and brain structure.

Patients with bipolar disorder (BD) show higher immuno-inflammatory setpoints, with in vivo alterations in white matter (WM) microstructure and post-mortem infiltration of T cells in the brain. Cytotoxic CD8 + T cells can enter and damage the brain in inflammatory disorders, but little is known in BD. Our study aimed to investigate the relationship between cytotoxic T cells and WM alterations in BD. In a sample of 83 inpatients with BD in an active phase of illness (68 depressive, 15 manic), we performed flow cytometry immunophenotyping to investigate frequencies, activation status, and expression of cytotoxic markers in CD8 + and tested for their association with diffusion tensor imaging (DTI) measures of WM microstructure. Frequencies of naïve and activated CD8 + cell populations expressing Perforin, or both Perforin and Granzyme, negatively associated with WM microstructure. CD8 + Naïve cells negative for Granzyme and Perforin positively associates with indexes of WM integrity, while the frequency of CD8 + memory cells negatively associates with index of WM microstructure, irrespective of toxins expression. The resulting associations involve measures representative of orientational coherence and myelination of the fibers (FA and RD), suggesting disrupted oligodendrocyte-mediated myelination. These findings seems to support the hypothesis that immunosenescence (less naïve, more memory T cells) can detrimentally influence WM microstructure in BD and that peripheral CD8 + T cells may participate in inducing an immune-related WM damage in BD mediated by killer proteins.

Introduction Choroid plexus (CP) is a physiological barrier, producing cerebrospinal fluid (CSF), neurotrophic, and inflammatory factors. It’s also involved in the neuro-immune axis, facilitating the interplay between central and peripheral inflammation, allowing trafficking of immune cells. Coherently, CP enlargement has been found in psychiatric diseases characterized by inflammatory signature. Although CP volume correlates with central microglia activation in major depressive disorder (MDD), it’s never been directly associated with peripheral markers in mood disorders. Objectives Examine CP volume in mood disorders and healthy controls (HC) in relation to clinical features and peripheral inflammatory markers. Methods CP volume was extracted with FreeSurfer in 72 HC and 152 age- and sex-matched depressed patients: 79 BD and 73 MDD. Plasma analytes in patients were collected through immunoassay technology (Bioplex). We tested for the effect of age by group on CP volume. Then we focused on the interaction between illness duration and diagnosis in predicting CP volume. After testing the effect of specific analytes by diagnosis, we calculated moderated moderation models (SPSS, PROCESS) setting each analyte as independent variable, CP volume as predicted variable and illness duration and diagnosis as moderators. We get the effects’ significance with the likelihood ratio statistic, always controlling for age, sex, and intracranial volume. Results Patients were comparable in illness duration and severity. CP volume is differentially distributed through groups (right: p=0.04; left: p<0.01), with higher volumes in the clinical groups. Age by group significantly predict right CP volume (p=0.01). Also, duration of illness differently predicts right CP volume in MDD and BD (p=0.03) (Figure1). Then, given the significant interaction effect of IL13 (p=0.02) and IL1ra (p=0.01) in predicting right CP, we run the moderated moderation model. Longer illness duration has an effect in strengthening the opposite predicting value of IL1ra (ΔR2=0.03, p<0.01) on right CP volume in MDD and BD (Figure2). Image: Image 2: Conclusions Our findings propose CP as a proxy of inflammation in depression, being significantly predicted by peripheral immune markers in MDD and BD. In particular, the signature of inflammation in depression, could represent the neurotoxic load of the disease over the illness, with a worse effect in BD, with possible disruption of brain barriers permeability and an opposite effect of tightening and central segregation in MDD. Further analyses are needed to better elucidate this neurobiological mechanisms across mood disorders. Disclosure of Interest None Declared

Despite the increasing availability of antidepressant drugs, a high rate of patients with major depression (MDD) does not respond to pharmacological treatments. Brain-derived neurotrophic factor (BDNF)-tyrosine receptor kinase B (TrkB) signaling is thought to influence antidepressant efficacy and hippocampal volumes, robust predictors of treatment resistance. We therefore hypothesized the possible role of BDNF and neurotrophic receptor tyrosine kinase 2 (NTRK2)-related polymorphisms in affecting both hippocampal volumes and treatment resistance in MDD. A total of 121 MDD inpatients underwent 3T structural MRI scanning and blood sampling to obtain genotype information. General linear models and binary logistic regressions were employed to test the effect of genetic variations related to BDNF and NTRK2 on bilateral hippocampal volumes and treatment resistance, respectively. Finally, the possible mediating role of hippocampal volumes on the relationship between genetic markers and treatment response was investigated. A significant association between one NTRK2 polymorphism with hippocampal volumes and antidepressant response was found, with significant indirect effects. Our results highlight a possible mechanistic explanation of antidepressant action, possibly contributing to the understanding of MDD pathophysiology.