Investigating structural-functional brain covariation in bipolar disorder using a multimodal fusion approach.

Structural magnetic resonance imaging (MRI) studies reported gray matter (GM) loss in bipolar disorder (BD) in cingulate cortices, key regions subserving emotional regulation and cognitive functions in humans. The aim of this study was to further explore cingulate GM volumes in a sizeable group of BD patients with respect to healthy controls, particularly investigating the impact of gender and clinical variables. 39 BD patients (mean Age = 48.6 ±9.7, 15 males and 24 females) and 39 demographically matched healthy subjects (mean Age = 47.9 ± 9.1, 15 males and 24 females) underwent a 1.5T MRI scan. GM volumes within the cingulate cortex were manually detected, including anterior and posterior regions. BD patients had decreased left anterior cingulate volumes compared with healthy controls (F = 6.7, p = 0.01). Additionally, a significant gender effect was observed, with male patients showing reduced left anterior cingulate cortex (ACC) volumes compared to healthy controls (F = 5.1, p = 0.03). Furthermore, a significant inverse correlation between right ACC volumes and number of hospitalizations were found in the whole group of BD patients (r = -0.51, p = 0.04) and in male BD patients (r = -0.88, p = 0.04). Finally, no statistically significant correlations were observed in female BD patients. Our findings further confirm the putative role of the ACC in the pathophysiology of BD. Interestingly, this study also suggested the presence of gender-specific GM volume reductions in ACC in BD, which may also be associated to poor outcome.

Unprecedented 4D spatiotemporal infant regional cerebral blood flow framework and region-specific physiology–function coupling across infancy were elucidated, highlighting strong physiology–function coupling specifically at the default-mode network to meet extraneuronal metabolic demand for network emergence.

Despite a marked increase in treatment for bipolar disorder among youths, little is known about their pattern of service use. This article describes mental health service use in the year before and after a new clinical diagnosis of bipolar disorder. Claims were reviewed between April 1, 2004, and March 31, 2005, for 1,274,726 privately insured youths (17 years and younger) who were eligible for services at least one year before and after a service claim; 2,907 youths had new diagnosis of bipolar disorder during this period. Diagnoses of other mental disorders and prescriptions filled for psychotropic drugs were assessed in the year before and after the initial diagnosis of bipolar disorder. The one-year rate of a new diagnosis of bipolar disorder was .23%. During the year before the new diagnosis of bipolar disorder, youths were commonly diagnosed as having depressive disorder (46.5%) or disruptive behavior disorder (36.7%) and had often filled a prescription for an antidepressant (48.5%), stimulant (33.0%), mood stabilizer (31.8%), or antipsychotic (29.1%). Most youths with a new diagnosis of bipolar disorder had only one (28.8%) or two to four (28.7%) insurance claims for bipolar disorder in the year starting with the index diagnosis. The proportion starting mood stabilizers after the index diagnosis was highest for youths with five or more insurance claims for bipolar disorder (42.1%), intermediate for those with two to four claims (24.2%), and lowest for those with one claim (13.8%). Most youths with a new diagnosis of bipolar disorder had recently received treatment for depressive or disruptive behavior disorders, and many had no claims listing a diagnosis of bipolar disorder after the initial diagnosis. The service pattern suggests that a diagnosis of bipolar disorder is often given tentatively to youths treated for mental disorders with overlapping symptom profiles and is subsequently reconsidered.

IntroductionAlthough schizophrenia (SCZ) and bipolar disorder (BD) share elements of pathology, their neural underpinnings are still under investigation. Here, structural Magnetic Resonance Imaging (MRI) data collected from a large sample of BD and SCZ patients and healthy controls (HC) were analyzed in terms of gray matter volume (GMV) using both voxel based morphometry (VBM) and a region of interest (ROI) approach.MethodsThe analysis was conducted on two datasets, Dataset1 (802 subjects: 243 SCZ, 176 BD, 383 HC) and Dataset2, a homogeneous subset of Dataset1 (301 subjects: 107 HC, 85 BD and 109 SCZ). General Linear Model analyses were performed 1) at the voxel-level in the whole brain (VBM study), 2) at the regional level in the anatomical regions emerged from the VBM study (ROI study). The GMV comparison across groups was integrated with the analysis of GMV correlates of different clinical dimensions.ResultsThe VBM results of Dataset1 showed 1) in BD compared to HC, GMV deficits in right cingulate, superior temporal and calcarine cortices, 2) in SCZ compared to HC, GMV deficits in widespread cortical and subcortical areas, 3) in SCZ compared to BD, GMV deficits in insula and thalamus (p<0.05, cluster family wise error corrected). The regions showing GMV deficits in the BD group were mostly included in the SCZ ones. The ROI analyses confirmed the VBM results at the regional level in most of the clusters from the SCZ vs. HC comparison (p<0.05, Bonferroni corrected). The VBM and ROI analyses of Dataset2 provided further evidence for the enhanced GMV deficits characterizing SCZ. Based on the clinical-neuroanatomical analyses, we cannot exclude possible confounding effects due to 1) age of onset and medication in BD patients, 2) symptoms severity in SCZ patients.ConclusionOur study reported both shared and specific neuroanatomical characteristics between the two disorders, suggesting more severe and generalized GMV deficits in SCZ, with a specific role for insula and thalamus.

Background: Up to 60% of bipolar disorder (BD) patients develop alcohol use disorders (AUD) at some point in their lives. The causes of this highly prevalent comorbidity are unknown. High trait impulsivity characterizes both isolated BD and AUD and may be a link to explain the association between BD and AUD. In this study, our aims were to investigate whether BD patients with comorbid AUD would present higher trait impulsivity levels compared to BD patients without comorbid AUD, and whether trait impulsivity levels differ within subgroups of BD according to the subcategory of AUD (abuse vs. dependence, alcoholism alone vs. alcoholism plus drug use disorders). Sampling and Methods: Forty-seven outpatients with BD with comorbid AUD (alcoholic BD group) were compared to 66 outpatients with BD alone (nonalcoholic BD group) and to 90 healthy controls (HC). BD and AUD diagnoses were obtained using the Structured Clinical Interview for DSM-IV diagnoses. Impulsivity was assessed using the Barratt Impulsiveness Scale (BIS-11), a self-report instrument that measures trait impulsivity in three domains: nonplanning, attentional and motor. Results: Alcoholic BD patients scored significantly higher than nonalcoholic BD and HC on the total and on each subscale BIS scores. Within the alcoholic BD patients, alcohol abusers and alcohol dependents did not statistically differ from each other on the BIS-11 scores. BD patients with AUD plus drug use disorders presented statistically higher nonplanning impulsivity than BD patients with AUD alone. Conclusions: This was a cross-sectional study and causal inferences about the relationship between impulsivity and the comorbidity phenomenon cannot be made. Increased impulsivity may be a trait marker for the co-occurrence between BD and AUD, and mediate some severe manifestations of this comorbidity.

Bipolar disorder (BD) is a severe mental disorder, characterized by episodes of mania and depression. The longitudinal neurobiological impact of BD episodes on brain structure remains largely unknown. In 124 age-sex-matched participants (62 BD patients; 62 healthy controls; HCs), aged 20-62 years, we investigated the longitudinal relationship between BD episodes and whole-brain gray matter volume (GMV) changes (3 Tesla MRI) during a two-year interval, using voxel-based morphometry in SPM12/CAT12. We compared GMV trajectories between BD patients with at least one depressive or manic episode during the two-year interval, BD patients without an episode, and HCs. We explored associations between GMV changes and clinical variables, like the number and duration of depressive or manic episodes both during the two-year interval and before baseline assessment. BD patients showed GMV increases in the right exterior cerebellum with an increasing number of depressive episodes during the two-year interval. BD patients without recurrence showed GMV reductions in this area, relative to BD patients with recurrence and HCs. Notably, BD patients without recurrence exhibited greater GMV reductions during the two-year interval, the longer they had spent in a manic episode before baseline. Our findings underscore the dynamic nature of brain changes in BD. GMV increases in BD patients with recurrence may be due to acute neuroinflammatory mechanisms including glial cell proliferation, whereas GMV reductions in BD patients without recurrence may result from abnormal synaptic refinement or pruning, as a consequence of past neuroinflammation during BD episodes.

Introduction:Bipolar disorder (BD) is one of the most encountered disorders in psychiatric clinics. Despite extensive research and advancements in BD treatment, little is known about the disease’s primary etiopathogenesis and relationship with different pathophysiological traits. The present study is aimed to evaluate the pathophysiological role of oxidative and nitrosative stress in BD patients and identify their familial aggregation.Methods:Blood samples from healthy individuals, drug-naive symptomatic BD patients, and their first-degree relatives were obtained, and intracellular reactive oxygen/nitrogen species (ROS/RNS), total nitrites, neuronal nitric oxide synthase (nNOS) mRNA expression, myeloperoxidase (MPO) activity in polymorphonuclear neutrophils (PMNs), and serum cortisol levels were assessed.Results:ROS, MPO activity, total-nitrite content, nNOS expression in PMNs, and serum cortisol concentration were considerably more in BD patients than in healthy volunteers. All these variables showed a substantial correlation with the YMRS score for disease severity and the presence of one or more manic episodes. Additionally, a positive correlation was noted between the MPO activity and serum cortisol levels of BD patients and their first-degree relatives.Conclusions:The results of the present study advance our knowledge about the role of oxidative and nitrosative stress in BD pathophysiology and its familial aggregation. Additionally, the study demonstrates a direct correlation between the disease severity and levels of ROS/RNS, MPO, total nitrite, and nNOS transcripts in PMNs. However, future research with larger and more diverse participant populations is required to understand these pathways for use as potential biomarkers for a deeper understanding of BD pathophysiology and to improve therapeutic strategies.

of a G72 susceptibility haplotype on fiber tract integrity in young healthy probands. They found clusters of increased fractional anisotropy in homozygous risk haplotype carriers in the right periinsular and inferior parietal region. Both regions have been hypothesized to be involved in the pathophysiology of bipolar disorder and schizophrenia, and alterations in fractional anisotropy may reflect changes in neuropil such as morphology of dendrites. In a functional magnetic resonance imaging (fMRI) study using a working memory task, Stegmayer et al. [4] found reduced functional interactions of the right amygdala with cortical regions supporting verbal working memory in 18 bipolar patients compared with 18 healthy controls. The results point to a disturbed right-hemispheric cognitive–emotional interaction between the amygdala and cortical regions, leading to deficits in working memory. In bipolar disorder, poorer prognosis is related to weight gain and obesity. Lackner et al. [5] investigated body mass index, obesity measures, lipometry, metabolic parameters and monoamines in a large sample of bipolar patients compared with healthy controls. In the patient group, they found increased abdominal fat accumulation and measures of the metabolic syndrome along with correlation with epinephrine levels. The glutamate system has been reported to be involved in the pathophysiology of both bipolar disorder and major depression. Quinolinic acid is produced by activated microglia and is an agonist at the glutamatergic N-methyl-d-aspartate (NMDA) receptor. In a postmortem study, Busse et al. [6] investigated immunohistochemistry of quinolinic acid in hippocampal subregions of 12 patients with depression, among them 6 unipolar and 6 bipolar, and 10 healthy controls. Quinolinic-positive microglia was reduced in unipolar and bipolar patients in the right CA1 subregion. A degradation of quinolinic acid may be involved in the In the new DSM-5 and ICD-11 classification systems, pure mania and mania with mild depression are subsumed under bipolar disorder. In a comprehensive review, Angst and Grobler [1] vote for improved differential diagnoses of unipolar mania. This is clinically relevant since the disorder has a prevalence of approximately 1.8 %, and clinical follow-up studies demonstrated good diagnostic stability. Moreover, mania is associated with a hyperthymic temperament, more psychotic symptoms and higher heritability compared with depression. In contrast, the concept of bipolar disorder has been widely investigated in neurogenetic studies. For example, the dopaminergic system has been suggested to be affected in bipolar disorder, but the impact of the genetic variants of the human dopamine transporter DAT1 (SLC6A3) is inconsistent. Huang et al. [2] investigated the association of 18 polymorphisms of the DAT1 gene with bipolar disorder and explored its influence on specific personality traits such as novelty seeking and harm avoidance. Several polymorphisms had a weak association with bipolar disorder, and the promotor G-A-C-G haplotype was overrepresented in their sample of 492 patients compared with 436 healthy controls. Bipolar II patients had the highest harm avoidance score and a significant association between rs40184 of DAT1 and this personality trait in patients with bipolar disorder. G72 (D-amino acid oxidase activator, DAOA) is a susceptibility gene for bipolar disorder and schizophrenia. In a diffusion tensor imaging (DTI) study, Nickl-Jockschat et al. [3] investigated the influence

White matter disruptions in patients with bipolar disorder

Early identification of patients with bipolar disorder during their first depressive episode is beneficial to the outcome of the disorder and treatment, but traditionally this has been a great challenge to clinicians. Recently, brain-derived neurotrophic factor (BDNF) has been suggested to be involved in the pathophysiology of bipolar disorder and major depressive disorder (MDD), but it is not clear whether BDNF levels can be used to predict bipolar disorder among patients in their first major depressive episode. To explore whether BDNF levels can differentiate between MDD and bipolar disorder in the first depressive episode. A total of 203 patients with a first major depressive episode as well as 167 healthy controls were recruited. After 3 years of bi-annual follow-up, 164 patients with a major depressive episode completed the study, and of these, 21 were identified as having bipolar disorder and 143 patients were diagnosed as having MDD. BDNF gene expression and plasma levels at baseline were compared among the bipolar disorder, MDD and healthy control groups. Logistic regression and decision tree methods were applied to determine the best model for predicting bipolar disorder at the first depressive episode. At baseline, patients in the bipolar disorder and MDD groups showed lower BDNF mRNA levels (P<0.001 and P = 0.02 respectively) and plasma levels (P = 0.002 and P = 0.01 respectively) compared with healthy controls. Similarly, BDNF levels in the bipolar disorder group were lower than those in the MDD group. These results showed that the best model for predicting bipolar disorder during a first depressive episode was a combination of BDNF mRNA levels with plasma BDNF levels (receiver operating characteristics (ROC) = 0.80, logistic regression; ROC = 0.84, decision tree). Our findings suggest that BDNF levels may serve as a potential differential diagnostic biomarker for bipolar disorder in a patient's first depressive episode.

BackgroundOne of the genes suggested to play an important role in the pathophysiology of bipolar disorder (BPD) is PDLIM5, which encodes LIM domain protein. Our main objective was to examine the effect of olanzapine treatment on PDLIM5 mRNA expression in the peripheral blood leukocytes of BPD patients.MethodsWe measured the expression of PDLIM5 mRNA from 16 patients with BPD Type I after 0, 4, and 8 weeks of treatment with olanzapine using quantitative real-time PCR. The Young Mania Rating Scale was used to evaluate the severity of manic symptoms in BPD patients. We also compared PDLIM5 mRNA expression in treatment-naïve BPD patients with that in healthy control subjects.ResultsNo significant difference was found in PDLIM5 mRNA expression between patients before olanzapine treatment and following 4 and 8 weeks of treatment (p>0.05). Although we observed a significant reduction in the severity of manic symptoms in all BPD patients (p<0.05), the effectiveness of the medication did not significantly correlate with the expression of PDLIM5 mRNA (p>0.05). Interestingly, PDLIM5 mRNA expression differed significantly between treatment-naïve BPD patients and healthy control subjects (p=0.002).ConclusionPDLIM5 mRNA expression did not appear to be a reflection of the efficacy of olanzapine in reducing the manic symptoms of BPD. The significant difference in expression of PDLIM5 mRNA in the peripheral blood leukocytes of treatment-naïve BPD patients versus that of healthy control subjects, however, suggests that it may be a good biological marker for BPD.

BackgroundGrowing literature continues to identify brain regions that are functionally altered in bipolar disorder. However, precise functional network correlates of bipolar disorder have yet to be determined due to inconsistent results. The overview of neurological alterations from a large‐scale network perspective may provide more comprehensive results and elucidate the neuropathology of bipolar disorder. Here, we critically review recent neuroimaging research on bipolar disorder using a network‐based approach.MethodsA systematic search was conducted on studies published from 2009 through 2019 in PubMed and Google Scholar. Articles that utilized functional magnetic resonance imaging technique to examine altered functional activity of major regions belonging to a large‐scale brain network in bipolar disorder were selected.ResultsA total of 49 studies were reviewed. Within‐network hypoconnectivity was reported in bipolar disorder at rest among the default mode, salience, and central executive networks. In contrast, when performing a cognitive task, hyperconnectivity among the central executive network was found. Internetwork functional connectivity in the brain of bipolar disorder was greater between the salience and default mode networks, while reduced between the salience and central executive networks at rest, compared to control.ConclusionThis systematic review suggests disruption in the functional activity of large‐scale brain networks at rest as well as during a task stimuli in bipolar disorder. Disrupted intra‐ and internetwork functional connectivity that are also associated with clinical symptoms suggest altered functional connectivity of and between large‐scale networks plays an important role in the pathophysiology of bipolar disorder.

BackgroundWhile patients with major depressive disorder (MDD) and bipolar disorder (BD) exhibited default mode network (DMN) dysfunction revealed by aberrant resting-state functional connectivity (rsFC) patterns, previous findings have been inconsistent. Little is known about the similarities and differences in DMN rsFC between MDD and BD. MethodsA voxel-wise meta-analysis of seed-based DMN rsFC studies on MDD or BD was performed using the Seed-based d Mapping software with permutation of subject images (SDM-PSI). Aberrant DMN rsFC in both disorders was investigated separately, followed by conjunction and between-disorder comparison analyses. Functional decoding was performed to implicate the psychophysiological underpinnings of derived brain abnormalities. ResultsThirty-four studies comparing 1316 MDD patients with 1327 HC, and 22 studies comparing 1059 BD patients with 1396 HC were included. Compared to HC, MDD patients exhibited DMN hyperconnectivity with frontolimbic systems, and hypoconnectivity with temporal lobe and posterior cingulate cortex. BD patients displayed increased DMN connectivity with bilateral precuneus, and reduced connectivity with prefrontal cortex and middle temporal gyrus. No common patterns of DMN rsFC abnormalities were observed between MDD and BD. Compared to BD, MDD patients showed DMN hyperconnectivity with triangular part of the left inferior frontal gyrus and left fusiform gyrus. Functional decoding found that patterns of DMN rsFC alteration between MDD and BD were primarily related to action and perception domains. ConclusionDistinct DMN dysfunction patterns in MDD and BD enhance current understanding of the neural substrates of mood disorders and may provide a potential biomarker for differentiation.

Bipolar disorder (BD) is commonly associated with cognitive impairments, that directly contribute to patients' functional disability. However, there is no effective treatment targeting cognition in BD. A key reason for the lack of pro-cognitive interventions is the limited insight into the brain correlates of cognitive impairments in these patients. This is the first study investigating the resting-state neural underpinnings of cognitive impairments in different neurocognitive subgroups of patients with BD. Patients with BD in full or partial remission and healthy controls (final sample of n = 144 and n = 50, respectively) underwent neuropsychological assessment and resting-state functional magnetic resonance imaging. We classified the patients into cognitively impaired (n = 83) and cognitively normal (n = 61) subgroups using hierarchical cluster analysis of the four cognitive domains. We used independent component analysis (ICA) to investigate the differences between the neurocognitive subgroups and healthy controls in resting-state functional connectivity (rsFC) in the default mode network (DMN), executive central network (ECN), and frontoparietal network (FPN). Cognitively impaired patients displayed greater positive rsFC within the DMN and less negative rsFC within the ECN than healthy controls. Across cognitively impaired patients, lower positive connectivity within DMN and lower negative rsFC within ECN correlated with worse global cognitive performance. Cognitive impairments in BD seem to be associated with a hyper-connectivity within the DMN, which may explain the failure to suppress task-irrelevant DMN activity during the cognitive performance, and blunted anticorrelation in the ECN. Thus, aberrant connectivity within the DMN and ECN may serve as brain targets for pro-cognitive interventions.

Symptom heterogeneity characterizes psychotic disorders and hinders the delineation of underlying biomarkers. Here, we identify symptom-based subtypes of recent-onset psychosis (ROP) patients from the multi-center PRONIA (Personalized Prognostic Tools for Early Psychosis Management) database and explore their multimodal biological and functional signatures. We clustered N = 328 ROP patients based on their maximum factor scores in an exploratory factor analysis on the Positive and Negative Syndrome Scale items. We assessed inter-subgroup differences and compared to N = 464 healthy control (HC) individuals regarding gray matter volume (GMV), neurocognition, polygenic risk scores, and longitudinal functioning trajectories. Finally, we evaluated factor stability at 9- and 18-month follow-ups. A 4-factor solution optimally explained symptom heterogeneity, showing moderate longitudinal stability. The ROP-MOTCOG (Motor/Cognition) subgroup was characterized by GMV reductions within salience, control and default mode networks, predominantly throughout cingulate regions, relative to HC individuals, had the most impaired neurocognition and the highest genetic liability for schizophrenia. ROP-SOCWD (Social Withdrawal) patients showed GMV reductions within medial fronto-temporal regions of the control, default mode, and salience networks, and had the lowest social functioning across time points. ROP-POS (Positive) evidenced GMV decreases in salience, limbic and frontal regions of the control and default mode networks. The ROP-AFF (Affective) subgroup showed GMV reductions in the salience, limbic, and posterior default-mode and control networks, thalamus and cerebellum. GMV reductions in fronto-temporal regions of the salience and control networks were shared across subgroups. Our results highlight the existence of behavioral subgroups with distinct neurobiological and functional profiles in early psychosis, emphasizing the need for refined symptom-based diagnosis and prognosis frameworks.