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.

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.

TSPO PET brain inflammation imaging: A transdiagnostic systematic review and meta-analysis of 156 case-control studies.

INTRODUCTION: The 18-kDa translocator protein (TSPO) is increasingly recognized as a molecular target for PET imaging of inflammatory responses in various central nervous system (CNS) disorders. However, the reported sensitivity and specificity of TSPO PET to identify brain inflammatory processes appears to vary greatly across disorders, disease stages, and applied quantification methods. To advance TSPO PET as a potential biomarker to evaluate brain inflammation and anti-inflammatory therapies, a better understanding of its applicability across disorders is needed. We conducted a transdiagnostic systematic review and meta-analysis of all in vivo human TSPO PET imaging case-control studies in the CNS. Specifically, we investigated the direction, strength, and heterogeneity associated with the TSPO PET signal across disorders in pre-specified brain regions, and explored the demographic and methodological sources of heterogeneity. METHODS: We searched for English peer-reviewed articles that reported in vivo human case-control TSPO PET differences. We extracted the demographic details, TSPO PET outcomes, and technical variables of the PET procedure. A random-effects meta-analysis was applied to estimate case-control standardized mean differences (SMD) of the TSPO PET signal in the lobar/whole-brain cortical grey matter (cGM), thalamus, and cortico-limbic circuitry between different illness categories. Heterogeneity was evaluated with the I2 statistic and explored using subgroup and meta-regression analyses for radioligand generation, PET quantification method, age, sex, and publication year. Significance was set at the False Discovery Rate (FDR)-corrected P < 0.05. RESULTS: 156 individual case-control studies were included in the systematic review, incorporating data for 2381 healthy controls and 2626 patients. 139 studies documented meta-analysable data and were grouped into 11 illness categories. Across all the illness categories, we observed a significantly higher TSPO PET signal in cases compared to controls for the cGM (n = 121 studies, SMD = 0.358, PFDR < 0.001, I2 = 68%), with a significant difference between the illness categories (P = 0.004). cGM increases were only significant for Alzheimer's disease (SMD = 0.693, PFDR < 0.001, I2 = 64%) and other neurodegenerative disorders (SMD = 0.929, PFDR < 0.001, I2 = 73%). Cortico-limbic increases (n = 97 studies, SMD = 0.541, P < 0.001, I2 = 67%) were most prominent for Alzheimer's disease, mild cognitive impairment, other neurodegenerative disorders, mood disorders and multiple sclerosis. Thalamic involvement (n = 79 studies, SMD = 0.393, P < 0.001, I2 = 71%) was observed for Alzheimer's disease, other neurodegenerative disorders, multiple sclerosis, and chronic pain and functional disorders (all PFDR < 0.05). Main outcomes for systemic immunological disorders, viral infections, substance use disorders, schizophrenia and traumatic brain injury were not significant. We identified multiple sources of between-study variance to the TSPO PET signal including a strong transdiagnostic effect of the quantification method (explaining 25% of between-study variance; VT-based SMD = 0.000 versus reference tissue-based studies SMD = 0.630; F = 20.49, df = 1;103, P < 0.001), patient age (9% of variance), and radioligand generation (5% of variance). CONCLUSION: This study is the first overarching transdiagnostic meta-analysis of case-control TSPO PET findings in humans across several brain regions. We observed robust increases in the TSPO signal for specific types of disorders, which were widespread or focal depending on illness category. We also found a large and transdiagnostic horizontal (positive) shift of the effect estimates of reference tissue-based compared to VT-based studies. Our results can support future studies to optimize experimental design and power calculations, by taking into account the type of disorder, brain region-of-interest, radioligand, and quantification method.

In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.

Role of the gut microbiome in three major psychiatric disorders.

Major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia-spectrum disorders (SSD) are heterogeneous psychiatric disorders, which place significant burden on patient's well-being and global health. Disruptions in the gut-microbiome may play a role in these psychiatric disorders. This review presents current data on composition of the human gastrointestinal microbiota, and its interaction mechanisms in the gut-brain axis in MDD, BD and SSD. Diversity metrics and microbial relative abundance differed across studies. More studies reported inconsistent findings (n = 7) or no differences (n = 8) than studies who reported lower α-diversity in these psychiatric disorders (n = 5). The most consistent findings across studies were higher relative abundances of the genera Streptococcus, Lactobacillus, and Eggerthella and lower relative abundance of the butyrate producing Faecalibacterium in patients with psychiatric disorders. All three increased genera were associated with higher symptom severity. Confounders, such as medication use and life style have not been accounted for. So far, the results of probiotics trials have been inconsistent. Most traditional and widely used probiotics (consisting of Bifidobacterium spp. and Lactobacillus spp.) are safe, however, they do not correct potential microbiota disbalances in these disorders. Findings on prebiotics and faecal microbiota transplantation (FMT) are too limited to draw definitive conclusions. Disease-specific pro/prebiotic treatment or even FMT could be auspicious interventions for prevention and therapy for psychiatric disorders and should be investigated in future trials.

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.

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.

Social Rhythm Disruption is Associated with Greater Depressive Symptoms in People with Mood Disorders: Findings from a Multinational Online Survey During COVID-19.

OBJECTIVES: Societal restrictions imposed to prevent transmission of COVID-19 may challenge circadian-driven lifestyle behaviours, particularly amongst those vulnerable to mood disorders. The overarching aim of the present study was to investigate the hypothesis that, in the routine-disrupted environment of the COVID-19, amongst a sample of people living with mood disorders, greater social rhythm disruption would be associated with more severe mood symptoms. METHODS: We conducted a two-wave, multinational survey of 997 participants (MAge=39.75±13.39,Female=81.6%) who self-reported a mood disorder diagnosis (i.e., major depressive disorder or bipolar disorder). Respondents completed questionnaires assessing demographics, social rhythmicity (The Brief Social Rhythm Scale), depression symptoms (Patient Health Questionnaire-9), sleep quality and diurnal preference (The Sleep, Circadian Rhythms and Mood questionnaire) and stressful life events during the COVID-19 pandemic (The Social Readjustment Rating Scale). RESULTS: The majority of participants indicated COVID-19-related social disruption had affected the regularity of their daily routines to at least some extent (n = 788, 79.1%). As hypothesised, lower social rhythmicity was associated with greater depressive symptoms when tested cross-sectionally (standardised ß = -.25, t = -7.94, P = 0.000) and when tested using a 2-level hierarchical linear model across two time points (b = -0.14, t = -3.46, df = 264, P ≤ 0.001). CONCLUSIONS: These results are consistent with the social zeitgeber hypothesis proposing that mood disorders are sensitive to life events that disrupt social rhythms.

Dysregulation of synaptic pruning as a possible link between intestinal microbiota dysbiosis and neuropsychiatric disorders.

The prenatal and early postnatal stages represent a critical time window for human brain development. Interestingly, this window partly overlaps with the maturation of the intestinal flora (microbiota) that play a critical role in the bidirectional communication between the central and the enteric nervous systems (microbiota-gut-brain axis). The microbial composition has important influences on general health and the development of several organ systems, such as the gastrointestinal tract, the immune system, and also the brain. Clinical studies have shown that microbiota alterations are associated with a wide range of neuropsychiatric disorders including autism spectrum disorder, attention deficit hyperactivity disorder, schizophrenia, and bipolar disorder. In this review, we dissect the link between these neuropsychiatric disorders and the intestinal microbiota by focusing on their effect on synaptic pruning, a vital process in the maturation and establishing efficient functioning of the brain. We discuss in detail how synaptic pruning is dysregulated differently in the aforementioned neuropsychiatric disorders and how it can be influenced by dysbiosis and/or changes in the intestinal microbiota composition. We also review that the improvement in the intestinal microbiota composition by a change in diet, probiotics, prebiotics, or fecal microbiota transplantation may play a role in improving neuropsychiatric functioning, which can be at least partly explained via the optimization of synaptic pruning and neuronal connections. Altogether, the demonstration of the microbiota's influence on brain function via microglial-induced synaptic pruning addresses the possibility that the manipulation of microbiota-immune crosstalk represents a promising strategy for treating neuropsychiatric disorders.

Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.

OBJECTIVES: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD. METHOD: A task force was convened to examine and integrate findings from the scientific literature related to machine learning and big data based studies to clarify terminology and to describe challenges and potential applications in the field of BD. We also systematically searched PubMed, Embase, and Web of Science for articles published up to January 2019 that used machine learning in BD. RESULTS: The results suggested that big data analytics has the potential to provide risk calculators to aid in treatment decisions and predict clinical prognosis, including suicidality, for individual patients. This approach can advance diagnosis by enabling discovery of more relevant data-driven phenotypes, as well as by predicting transition to the disorder in high-risk unaffected subjects. We also discuss the most frequent challenges that big data analytics applications can face, such as heterogeneity, lack of external validation and replication of some studies, cost and non-stationary distribution of the data, and lack of appropriate funding. CONCLUSION: Machine learning-based studies, including atheoretical data-driven big data approaches, provide an opportunity to more accurately detect those who are at risk, parse-relevant phenotypes as well as inform treatment selection and prognosis. However, several methodological challenges need to be addressed in order to translate research findings to clinical settings.

The chronotherapeutic treatment of bipolar disorders: A systematic review and practice recommendations from the ISBD task force on chronotherapy and chronobiology.

AIMS: To systematically review the literature on the efficacy and tolerability of the major chronotherapeutic treatments of bipolar disorders (BD)-bright light therapy (LT), dark therapy (DT), treatments utilizing sleep deprivation (SD), melatonergic agonists (MA), interpersonal social rhythm therapy (IPSRT), and cognitive behavioral therapy adapted for BD (CBTI-BP)-and propose treatment recommendations based on a synthesis of the evidence. METHODS: PRISMA-based systematic review of the literature. RESULTS: The acute antidepressant (AD) efficacy of LT was supported by several open-label studies, three randomized controlled trials (RCTs), and one pseudorandomized controlled trial. SD showed rapid, acute AD response rates of 43.9%, 59.3%, and 59.4% in eight case series, 11 uncontrolled, studies, and one RCT, respectively. Adjunctive DT obtained significant, rapid anti-manic results in one RCT and one controlled study. The seven studies on MA yielded very limited data on acute antidepressant activity, conflicting evidence of both antimanic and maintenance efficacy, and support from two case series of improved sleep in both acute and euthymic states. IPSRT monotherapy for bipolar II depression had acute response rates of 41%, 67%, and 67.4% in two open studies and one RCT, respectively; as adjunctive therapy for bipolar depression in one RCT, and efficacy in reducing relapse in two RCTs. Among euthymic BD subjects with insomnia, a single RCT found CBTI-BP effective in delaying manic relapse and improving sleep. Chronotherapies were generally safe and well-tolerated. CONCLUSIONS: The outcome literature on the adjunctive use of chronotherapeutic treatments for BP is variable, with evidence bases that differ in size, study quality, level of evidence, and non-standardized treatment protocols. Evidence-informed practice recommendations are offered.

Volume, metabolites and neuroinflammation of the hippocampus in bipolar disorder - A combined magnetic resonance imaging and positron emission tomography study.

BACKGROUND: The hippocampus is one of the brain regions that is involved in several pathophysiological theories about bipolar disorder (BD), such as the neuroinflammation theory and the corticolimbic metabolic dysregulation theory. We compared hippocampal volume and hippocampal metabolites in bipolar I disorder (BD-I) patients versus healthy controls (HCs) with magnetic resonance imaging (MRI) and spectroscopy (MRS). We post hoc investigated whether hippocampal volume and hippocampal metabolites were associated with microglial activation and explored if potential illness modifying factors affected these hippocampal measurements and whether these were associated with experienced mood and functioning. MATERIALS AND METHODS: Twenty-two BD-I patients and twenty-four HCs were included in the analyses. All subjects underwent psychiatric interviews as well as an MRI scan, including a T1 scan and PRESS magnetic resonance spectroscopy (MRS). Volumetric analysis was performed with Freesurfer. MRS quantification was performed with LC Model. A subgroup of 14 patients and 11 HCs also underwent a successful [(11)C]-(R)-PK11195 neuroinflammation positron emission tomography scan. RESULTS: In contrast to our hypothesis, hippocampal volumes were not decreased in patients compared to HC after correcting for individual whole-brain volume variations. We demonstrated decreased N-acetylaspartate (NAA)+N-acetyl-aspartyl-glutamate (NAAG) and creatine (Cr)+phosphocreatine (PCr) concentrations in the left hippocampus. In the explorative analyses in the left hippocampus we identified positive associations between microglial activation and the NAA+NAAG concentration, between alcohol use and NAA+NAAG concentration, between microglial activation and the depression score and a negative relation between Cr+PCr concentration and experienced occupational disability. Duration of illness associated positively with volume bilaterally. CONCLUSION: Compared to HCs, the decreased NAA+NAAG concentration in the left hippocampus of BD-I patients suggests a decreased neuronal integrity in this region. In addition we found a positive relation between microglial activation and neuronal integrity in vivo, corresponding to a differentiated microglial function where some microglia induce apoptosis while others stimulate neurogenesis.

The dysregulated brain: consequences of spatial and temporal brain complexity for bipolar disorder pathophysiology and diagnosis.

Increasingly, evidence has been accumulating emphasizing the importance of looking at bipolar disorder (BD) from a neurodevelopmental and transdimensional perspective to better understand its origins and its course. In this overview article, the problems facing pathophysiological psychiatric research in BD are addressed and interpreted in the light of brain complexity. Brain complexity can be split into spatial complexity, which constitutes the physiological levels of the central nervous system (i.e., the genetic, molecular, cellular, neuronal circuit and phenomenological levels), and temporal complexity, that is, neurodevelopment. The consequences of this consideration are discussed and suggestions for clinical practice and pathophysiological psychiatric research are made.

Feature-expression heat maps--a new visual method to explore complex associations between two variable sets.

INTRODUCTION: Existing methods such as correlation plots and cluster heat maps are insufficient in the visual exploration of multiple associations between genetics and phenotype, which is of importance to achieve a better understanding of the pathophysiology of psychiatric and other illnesses. The implementation of a combined presentation of effect size and statistical significance in a graphical method, added to the ordering of the variables based on the effect-ordered data display principle was deemed useful by the authors to facilitate in the process of recognizing meaningful patterns in these associations. MATERIALS AND METHODS: The requirements, analyses and graphical presentation of the feature-expression heat map are described. The graphs display associations of two sets of ordered variables where a one-way direction is assumed. The associations are depicted as circles representing a combination of effect size (color) and statistical significance (radius). RESULTS: An example dataset is presented and relation to other methods, limitations, areas of application and possible future enhancements are discussed. CONCLUSION: The feature-expression heat map is a useful graphical instrument to explore associations in complex biological systems where one-way direction is assumed, such as genotype-phenotype pathophysiological models.

Neuroinflammation in bipolar disorder - A [(11)C]-(R)-PK11195 positron emission tomography study.

BACKGROUND: The "monocyte-T-cell theory of mood disorders" regards neuroinflammation, i.e. marked activation of microglia, as a driving force in bipolar disorder. Microglia activation can be visualized in vivo using [(11)C]-(R)-PK11195 PET. Indirect evidence suggests the hippocampus as a potential focus of neuroinflammation in bipolar disorder. We aim to determine if there is increased [(11)C]-(R)-PK11195 binding to activated microglia in the hippocampus of patients with bipolar I disorder when compared to healthy controls. MATERIAL AND METHODS: Fourteen patients with bipolar I disorder and eleven healthy controls were included in the analyses. Dynamic 60-min PET scans were acquired after the injection of [(11)C]-(R)-PK11195. All subjects underwent psychiatric interviews as well as an MRI scan, which was used for anatomic co-registration in the data analysis. The data from the PET scans was analyzed with a two-tissue-compartment model to calculate the binding potential, using the metabolite-corrected plasma and blood curve as input. RESULTS: A significantly increased [(11)C]-(R)-PK11195 binding potential, which is indicative of neuroinflammation, was found in the right hippocampus of the patients when compared to the healthy controls (1.66 (CI 1.45-1.91) versus 1.33 (CI 1.16-1.53); p=0.033, respectively). Although the same trend was observed in the left hippocampus, this difference was not statistically significant. CONCLUSION: This study is the first to demonstrate the presence of focal neuroinflammation in the right hippocampus in bipolar I disorder.

Relationship between clinical features and inflammation-related monocyte gene expression in bipolar disorder - towards a better understanding of psychoimmunological interactions.

OBJECTIVES: Existing and previously published datasets were examined for associations between illness and treatment characteristics and monocyte pro-inflammatory gene expression in patients with bipolar disorder (BD). We hypothesized a priori that increased monocyte pro-inflammatory gene expression would be found more frequently in patients with a lifetime history of psychotic symptoms. METHODS: Monocyte quantitative polymerase chain reaction and symptom data from 64 patients with BD were collected from three Dutch studies. Regression analyses were performed to analyze the various associations between pro-inflammatory gene expression and clinical features, from which feature-expression heat maps were drawn. RESULTS: No associations were found between pro-inflammatory gene expression and lifetime psychotic symptoms, whereas a positive association was identified between subcluster 2 genes and manic symptoms. For several subcluster 1a genes, a negative association was found with age at onset. For most subcluster 2 genes, a positive association was found with the duration of illness. Current use of antidepressants and of anti-epileptic agents was associated with subcluster 2 gene expression, and current use of lithium and antipsychotic agents with subcluster 1a gene expression. CONCLUSIONS: Our hypothesis that lifetime psychotic features would be associated with pro-inflammatory monocyte gene expression was not confirmed. In an explorative analysis we found: (i) a possible relationship between pro-inflammatory gene expression and manic symptomatology; (ii) a differential immune activation related to age at onset and duration of illness; and (iii) support for the concept of an immune suppressive action of some of the mood-regulating medications.

Higher T central and lower effector memory cells in bipolar disorder: A differentiation abnormality?

The aim of this study was to elucidate the nature of T cell abnormalities in bipolar disorder (BD). With the use of multicolor flow cytometry, we first quantified the composition of the different memory and pro-inflammatory immune subpopulations in samples of 58 patients with BD and compared them to 113 healthy controls. Second, to assess if cytomegalovirus infection was related to the resulted immune subpopulation compositions in the two groups, we measured cytomegalovirus-specific antibodies in serum. Thirdly, we assessed differences between the two groups in the serum levels of the immune cell differentiation factor interleukin-7. Compared to healthy controls, patients showed significantly higher T helper-17, T regulatory and T central memory cells (CD4+ and CD8+). Besides, patients showed significantly lower CD4+ T effector memory and CD4+ T effector memory re-expressing RA cells. Cytomegalovirus infection was not related to the observed abnormalities, with the exception of T helper-17 cells. This immune subpopulation was significantly higher only in patients seropositive to cytomegalovirus infection. Finally, interleukin-7 levels were significantly lower in BD compared to healthy controls. In conclusion, the aberrant levels of T memory cell populations in BD may suggest a T cell differentiation abnormality. The role of interleukin-7 in this putative abnormality should be further investigated.

Antidepressant efficacy of cariprazine in bipolar disorder and the role of its pharmacodynamic properties: A hypothesis based on data.

The treatment of bipolar depression is one of the most challenging needs in contemporary psychiatry. Currently, only quetiapine, olanzapine-fluoxetine combination, lurasidone, cariprazine, and recently lumateperone have been FDA-approved to treat this condition. The neurobiology of bipolar depression and the possible targets of bipolar antidepressant therapy remain elusive. The current study investigated whether the pharmacodynamic properties of cariprazine fit into a previously developed model which was the first to be derived based on the strict combination of clinical and preclinical data. The authors performed a systematic review of the literature to identify the pharmacodynamic properties of cariprazine. The original model suggests that a constellation of effects on different receptors is necessary and that serotonin reuptake inhibition does not appear to play a significant role in acute bipolar depression. On the contrary, norepinephrine activity seems to be necessary. Probably the early antidepressant effect can be achieved through an agonistic activity at 5HT-1A and antagonism at alpha1 noradrenergic and 5-HT2A receptors, but the presence of a norepinephrine reuptake inhibition appears essential to sustain it. Overall, the properties of cariprazine fit well the proposed model and add to its validity. A point that needs further clarification is norepinephrine reuptake inhibition which is not yet fully studied for cariprazine.

Serum free thiols in recently diagnosed patients with schizophrenia spectrum disorder: A potentially useful biomarker of oxidative stress.

Schizophrenia spectrum disorders (SSD) have been linked to oxidative stress (OS). Recent findings from our group show that serum free thiols (R-SH, sulfhydryl groups) can function as an accurate biomarker of systemic OS, since they are readily oxidized by reactive species (ROS), thereby serving as potent antioxidants. The aim of this study is to investigate if reduced R-SH levels can be demonstrated in recently diagnosed patients with SSD compared to healthy controls (HC). In this study, 102 patients with recently diagnosed SSD (< three years), and 42 HC were included. Levels of R-SH were quantified and studied for correlations with age, C-reactive protein (CRP) as proxy of inflammation as well as body mass index (BMI) and total cholesterol as indices of metabolic health. R-SH levels were significantly lower in patients when compared to HC. When correcting for age the difference was borderline significant (p=0.05). Moreover, R-SH correlated significantly with age (r = -0.29) and CRP (r = -0.29) in patients with SSD, but not in the HC. R-SH levels are reduced in SSD as compared to HC and correlate negatively with CRP and age in SSD. Future studies are required to further investigate R-SH and its role in SSD.