History of Peripartum Depression Moderates the Association Between Estradiol Polygenic Risk Scores and Basal Ganglia Volumes in Major Depressive Disorder.

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: 64 parous female patients with major depressive disorder that have either a positive (n=30) or negative (n=34) history of peripartum depression (PPD) underwent MRI acquisition to obtain structural brain images. An independent two-sample t-test comparing patients with and without a history of PPD was performed using voxel-based morphometry analysis (VBM). Additionally, polygenic risk scores (PRSs) for estradiol were calculated and a moderation analysis was conducted between 3 estradiol PRSs and PPD history status on extracted cluster volumes using IBM SPSS PROCESS macro. RESULTS: The VBM analysis identified larger grey matter volumes in bilateral clusters encompassing the putamen, pallidum, caudate, and thalamus in patients with PPD history compared to patients without a history. The moderation analysis identified a significant interaction of 2 estradiol PRSs and PPD history on grey matter cluster volumes with a positive effect in PPD women 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.

Inflammatory mediators in major depression and bipolar disorder.

Major depressive disorder (MDD) and bipolar disorder (BD) are highly disabling illnesses defined by different psychopathological, neuroimaging, and cognitive profiles. In the last decades, immune dysregulation has received increasing attention as a central factor in the pathophysiology of these disorders. Several aspects of immune dysregulations have been investigated, including, low-grade inflammation cytokines, chemokines, cell populations, gene expression, and markers of both peripheral and central immune activation. Understanding the distinct immune profiles characterizing the two disorders is indeed of crucial importance for differential diagnosis and the implementation of personalized treatment strategies. In this paper, we reviewed the current literature on the dysregulation of the immune response system focusing our attention on studies using inflammatory markers to discriminate between MDD and BD. High heterogeneity characterized the available literature, reflecting the heterogeneity of the disorders. Common alterations in the immune response system include high pro-inflammatory cytokines such as IL-6 and TNF-α. On the contrary, a greater involvement of chemokines and markers associated with innate immunity has been reported in BD together with dynamic changes in T cells with differentiation defects during childhood which normalize in adulthood, whereas classic mediators of immune responses such as IL-4 and IL-10 are present in MDD together with signs of immune-senescence.

Multimodal brain-derived subtypes of Major depressive disorder differentiate patients for anergic symptoms, immune-inflammatory markers, history of childhood trauma and treatment-resistance.

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.

Adverse childhood experiences differently affect Theory of Mind brain networks in schizophrenia and healthy controls.

Patients with schizophrenia (SZ) show impairments in both affective and cognitive dimensions of theory of mind (ToM). SZ are also particularly vulnerable to detrimental effect of adverse childhood experiences (ACE), influencing the overall course of the disorder and fostering poor social functioning. ACE associate with long-lasting detrimental effects on brain structure, function, and connectivity in regions involved in ToM. Here, we investigated whether ToM networks are differentially affected by ACEs in healthy controls (HC) and SZ, and if these effects can predict the disorder clinical outcome. 26 HC and 33 SZ performed a ToM task during an fMRI session. Whole-brain functional response and connectivity (FC) were extracted, investigating the interaction between ACEs and diagnosis. FC values significantly affected by ACEs were entered in a cross-validated LASSO regression predicting Positive and Negative Syndrome Scale (PANSS), Interpersonal Reactivity Index (IRI), and task performance. ACEs and diagnosis showed a widespread interaction at both affective and cognitive tasks, including connectivity between vmPFC, ACC, precentral and postcentral gyri, insula, PCC, precuneus, parahippocampal gyrus, temporal pole, thalamus, and cerebellum, and functional response in the ACC, thalamus, parahippocampal gyrus and putamen. FC predicted the PANSS score, the fantasy dimension of IRI, and the AToM response latency. Our results highlight the crucial role of early stress in differentially shaping ToM related brain networks in HC and SZ. These effects can also partially explain the clinical and behavioral outcomes of the disorder, extending our knowledge of the effects of ACEs.

Low-dose interleukin 2 antidepressant potentiation in unipolar and bipolar depression: Safety, efficacy, and immunological biomarkers.

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.

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

Choroid plexus volume is increased in mood disorders and associates with circulating inflammatory cytokines.

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.

Circulating cytotoxic immune cell composition, activation status and toxins expression associate with white matter microstructure in bipolar disorder.

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.

Association between NTRK2 Polymorphisms, Hippocampal Volumes and Treatment Resistance in Major Depressive Disorder.

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.

Melatonin secretion patterns are associated with cognitive vulnerability and brain structure in bipolar depression.

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.