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.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

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.

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.

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts.

OBJECTIVE: A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia. METHOD: Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA-Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior. RESULTS: We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15-0.97; r range: 0.21-0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments. CONCLUSIONS: Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.

BACKGROUND: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. METHODS: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. RESULTS: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. CONCLUSIONS: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Long-term effect of childhood trauma: Role of inflammation and white matter in mood disorders.

Bipolar disorder (BD) and major depressive disorder (MDD) are severe psychiatric illnesses that share among their environmental risk factors the exposure to adverse childhood experiences (ACE). Exposure to ACE has been associated with long-term changes in brain structure and the immune response. In the lasts decades, brain abnormalities including alterations of white matter (WM) microstructure and higher levels of peripheral immune/inflammatory markers have been reported in BD and MDD and an association between inflammation and WM microstructure has been shown. However, differences in these measures have been reported by comparing the two diagnostic groups. The aim of the present study was to investigate the interplay between ACE, inflammation, and WM in BD and MDD. We hypothesize that inflammation will mediate the association between ACE and WM and that this will be different in the two groups. A sample of 200 patients (100 BD, 100 MDD) underwent 3T MRI scan and ACE assessment through Childhood Trauma Questionnaire. A subgroup of 130 patients (75 MDD and 55 BD) underwent blood sampling for the assessment of immune/inflammatory markers. We observed that ACE associated with higher peripheral levels of IL-2, IL-17, bFGF, IFN-γ, TNF-α, CCL3, CCL4, CCL5, and PDGF-BB only in the BD group. Further, higher levels of CCL3 and IL-2 associated with lower FA in BD. ACE were found to differently affect WM microstructure in the two diagnostic groups and to be negatively associated with FA and AD in BD patients. Mediation analyses showed a significant indirect effect of ACE on WM microstructure mediated by IL-2. Our findings suggest that inflammation may mediate the detrimental effect of early experiences on brain structure and different mechanisms underlying brain alterations in BD and MDD.

The parental psychological distress caused by separation from their critically ill child during the COVID-19 pandemic: A tale of two cities.

Introduction: A child's critical illness is a stressful event for the entire family, causing significant emotional distress among parents and changes to family functioning. The Severe Acute Respiratory Syndrome-Related Coronavirus 2 (SARS-CoV-2) pandemic has abruptly caused modifications in visitation policies of Pediatric Intensive Care Units (PICUs) in many countries. We hypothesized that caregivers with no or severely restricted access to PICUs would demonstrate increased psychological distress as compared to those who had limitless access (LA) to PICUs. Methods: Sociodemographic variables, levels of psychological distress, ratings of family functioning, and ability to cope with stressful events were collected with an online survey in a group of caregivers after their child's hospitalization. Ratings of psychological distress were compared between caregivers with no/severely restricted (NA) and with LA to PICUs. Results: Measures of depression, anxiety, and global severity index (GSI) of psychological distress were significantly higher in NA caregivers as compared to LA. Among demographic characteristics of the sample, only gender influenced the severity of psychological symptoms: women showed an increased score on levels of somatization, depression, anxiety, and GSI. Avoidant coping style positively correlated with measures of depression. Univariate General Linear Model (GLM) analyses of the effects of sex, age, visitation policies of PICUs, and score of avoidant coping strategies on measures of psychological distress confirmed a significant univariate effect of no access to PICUs on parents' psychopathological scores. Conclusion: Restrictions imposed on visitation policies in PICU during the pandemic negatively impacted families' psychological wellbeing. A balance between the safety of patients, families, and health care professionals and meeting the needs of families is of utmost importance.

Antidepressant chronotherapeutics normalizes prefrontal 1H-MRS glutamate in bipolar depression.

BACKGROUND: Dysfunctional glutamatergic neurotransmission has been proposed both, as a biological underpinning of mood disorder and as a target for rapid-acting antidepressant treatments. Total sleep deprivation and light therapy (TSD + LT) can prompt antidepressant response in drug-resistant bipolar depression. Here we explored the effects of TSD + LT on dorsolateral prefrontal cortex (DLPFC) glutamate and/or glutamine+glutamate (Glx) levels. METHODS: We studied single voxel 1H-MRS measures of DLPFC Glu and Glx levels of 48 healthy participants and 55 inpatients with a major depressive episode in course of Bipolar Disorder, a subset of which (N = 23) underwent three cycles of repeated TSD + LT and were evaluated before and after treatment. Treatment effects of mood and on Glu and Glx concentrations were analyzed in the context of the Generalized Linear Model (GLM), correcting for age, sex and ongoing lithium treatment. RESULTS: Higher concentration of Glu (adjusted Z = -2189, p = 0,0285) and Glx (adjusted Z = -3,13, p = 0,0017) were observed in BD patients compared to HC. Treatment caused a significant rapid reduction of depressive symptom severity over time (F = 63.98, p < 0.01). Change in depression levels after TSD + LT treatment was significantly influenced by delta change in Glu levels (LR χ2 = 4.619, p = 0.0316) and in Glx levels (LR χ2 = 4.486, p = 0.0341). CONCLUSION: A reduction in Glu and Glx levels associated with depression could contribute to the mechanism of action of TSD + LT, directly acting on glutamatergic neurons, or to the interaction between the glutamatergic system and dopamine (DA) and serotonin (5-HT) levels, known to be targeted by TSD. This is in line with several studies showing a glutamatergic modulation effects of antidepressants and mood stabilizing agents. This finding deepens our understanding of antidepressant effect of chronoterapeutics.

The role of educational attainment and brain morphology in major depressive disorder: Findings from the ENIGMA major depressive disorder consortium.

Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite sample of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-sample split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in individuals with low educational attainment, but less likely to predict MDD in individuals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: A systematic review and meta-analysis.

Applying machine learning (ML) to objective markers may overcome prognosis uncertainty due to the subjective nature of the diagnosis of bipolar disorder (BD). This PRISMA-compliant meta-analysis provides new systematic evidence of the BD classification accuracy reached by different markers and ML algorithms. We focused on neuroimaging, electrophysiological techniques, peripheral biomarkers, genetic data, neuropsychological or clinical measures, and multimodal approaches. PubMed, Embase and Scopus were searched through 3rd December 2020. Meta-analyses were performed using random-effect models. Overall, 81 studies were included in this systematic review and 65 in the meta-analysis (11,336 participants, 3903 BD). The overall pooled classification accuracy was 0.77 (95%CI[0.75;0.80]). Despite subgroup analyses for diagnostic comparison group, psychiatric disorders, marker, ML algorithm, and validation procedure were not significant, linear discriminant analysis significantly outperformed support vector machine for peripheral biomarkers (p = 0.03). Sample size was inversely related to accuracy. Evidence of publication bias was detected. Ultimately, although ML reached a high accuracy in differentiating BD from other psychiatric disorders, best practices in methodology are needed for the advancement of future studies.

Selective association of cytokine levels and kynurenine/tryptophan ratio with alterations in white matter microstructure in bipolar but not in unipolar depression.

Bipolar (BD) and major depression (MDD) disorders are severe mental illnesses characterised by altered levels of immune/inflammatory markers and disrupted white matter (WM) microstructure. A pro-inflammatory state was suggested to activate indoleamine 2,3-dioxygenase which, in turn, increases the amount of tryptophan (Trp) converted into kynurenine (Kyn). We investigated whether plasma levels of Trp, Kyn and Kyn/Trp ratio are associated with peripheral levels of immune/inflammatory markers and whether they are related to WM integrity in 100 MDD and 66 BD patients. Patients also underwent MRI, and fractional anisotropy (FA) was estimated as a measure of WM microstructure. BD patients showed higher Kyn levels and Kyn/Trp ratio than MDD patients, and lower FA in several WM tracts, including the corpus callosum and the inferior fronto-occipital fasciculus (IFO). Lower Trp levels associated with a more severe depressive symptomatology irrespective of diagnosis and with lower FA in the corpus callosum (CC) and external capsule (EC). We found an association of immune/inflammatory markers with Kyn/Trp ratio selectively in BD patients: IL-1ß and TNF-α showed a positive relationship and IL-2 and IL-9 a negative relationship; in addition, higher IL-4 correlated with lower Kyn levels; higher Kyn/Trp ratio and IL-1ß correlated with lower FA in the CC and IFO. Notably, the detrimental effect of IL-1ß on the IFO was moderated by the Kyn/Trp ratio. These data suggest that in BD, cytokines and the conversion of Trp into Kyn may affect WM microstructure and support the idea that distinct mechanisms underlie the pathophysiology of BD and MDD.

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.

AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.

Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group.

BACKGROUND: Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD. METHODS: Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables. RESULTS: Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18

Brain correlates of depression, post-traumatic distress, and inflammatory biomarkers in COVID-19 survivors: A multimodal magnetic resonance imaging study.

Psychiatric sequelae substantially contribute to the post-acute burden of disease associated with COVID-19, persisting months after clearance of the virus. Brain imaging shows white matter (WM) hypodensities/hyperintensities, and the involvement of grey matter (GM) in prefrontal, anterior cingulate (ACC) and insular cortex after COVID, but little is known about brain correlates of persistent psychopathology. With a multimodal approach, we studied whole brain voxel-based morphometry, diffusion-tensor imaging, and resting-state connectivity, to correlate MRI measures with depression and post-traumatic distress (PTSD) in 42 COVID-19 survivors without brain lesions, at 90.59 â€‹± â€‹54.66 days after COVID. Systemic immune-inflammation index (SII) measured in the emergency department, which reflects the immune response and systemic inflammation based on peripheral lymphocyte, neutrophil, and platelet counts, predicted worse self-rated depression and PTSD, widespread lower diffusivity along the main axis of WM tracts, and abnormal functional connectivity (FC) among resting state networks. Self-rated depression and PTSD inversely correlated with GM volumes in ACC and insula, axial diffusivity, and associated with FC. We observed overlapping associations between severity of inflammation during acute COVID-19, brain structure and function, and severity of depression and post-traumatic distress in survivors, thus warranting interest for further study of brain correlates of the post-acute COVID-19 syndrome. Beyond COVID-19, these findings support the hypothesis that regional GM, WM microstructure, and FC could mediate the relationship between a medical illness and its psychopathological sequelae, and are in agreement with current perspectives on the brain structural and functional underpinnings of depressive psychopathology.

Effective Antidepressant Chronotherapeutics (Sleep Deprivation and Light Therapy) Normalize the IL-1ß:IL-1ra Ratio in Bipolar Depression.

BACKGROUND: Mood disorders associate with peripheral markers of low-grade inflammation, among which circulating levels of interleukin-1ß (IL-1ß) consistently predict diagnosis and poor outcomes. Antidepressant chronotherapeutics (total sleep deprivation and light therapy, TSD+LT) prompts response in drug-resistant bipolar depression, but its effect on peripheral inflammation were never assessed. Here we explored the effects of TSD+LT on IL-1ß signaling. METHODS: We studied the ratio between IL-1ß and its receptor antagonist (IL-1ß:IL1ra) in 33 healthy participants, and in 26 inpatients with a major depressive episode in course of Bipolar Disorder, before and after treatment with three cycles of repeated TSD+LT, interspersed with sleep recovery nights, administered during 1 week. Treatment effects of mood and on IL-1ß:IL1ra were analyzed in the context of the Generalized Linear Model (GLM). RESULTS: At baseline, patients had higher IL-1ß, IL1ra, and IL-1ß:IL1ra than controls. Treatment significantly decreased IL-1ß:IL1ra, by decreasing IL-1ß and increasing IL1ra, the effect being proportional to baseline levels and normalizing values. Patients with higher baseline levels showed the highest decrease in IL-1ß:IL-1ra, which associated with the immediate antidepressant response at the first cycle; while patients with lower baseline values showed negligible changes in the IL-1ß:IL-1ra, unrelated to treatment response. CONCLUSION: We observed a parallel change of inflammatory biomarkers and severity of depression after chronotherapeutics, suggesting that a reduction in inflammation associated with depression could contribute to the mechanism of action of TSD+LT, and warranting interest for controlled studies addressing the role of inflammation in the recovery from bipolar depression.

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

Anxiety and depression in COVID-19 survivors: Role of inflammatory and clinical predictors.

Infection-triggered perturbation of the immune system could induce psychopathology, and psychiatric sequelae were observed after previous coronavirus outbreaks. The spreading of the Severe Acute Respiratory Syndrome Coronavirus (COVID-19) pandemic could be associated with psychiatric implications. We investigated the psychopathological impact of COVID-19 in survivors, also considering the effect of clinical and inflammatory predictors. We screened for psychiatric symptoms 402 adults surviving COVID-19 (265 male, mean age 58), at one month follow-up after hospital treatment. A clinical interview and a battery of self-report questionnaires were used to investigate post-traumatic stress disorder (PTSD), depression, anxiety, insomnia, and obsessive-compulsive (OC) symptomatology. We collected sociodemographic information, clinical data, baseline inflammatory markers and follow-up oxygen saturation levels. A significant proportion of patients self-rated in the psychopathological range: 28% for PTSD, 31% for depression, 42% for anxiety, 20% for OC symptoms, and 40% for insomnia. Overall, 56% scored in the pathological range in at least one clinical dimension. Despite significantly lower levels of baseline inflammatory markers, females suffered more for both anxiety and depression. Patients with a positive previous psychiatric diagnosis showed increased scores on most psychopathological measures, with similar baseline inflammation. Baseline systemic immune-inflammation index (SII), which reflects the immune response and systemic inflammation based on peripheral lymphocyte, neutrophil, and platelet counts, positively associated with scores of depression and anxiety at follow-up. PTSD, major depression, and anxiety, are all high-burden non-communicable conditions associated with years of life lived with disability. Considering the alarming impact of COVID-19 infection on mental health, the current insights on inflammation in psychiatry, and the present observation of worse inflammation leading to worse depression, we recommend to assess psychopathology of COVID-19 survivors and to deepen research on inflammatory biomarkers, in order to diagnose and treat emergent psychiatric conditions.