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Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable conditions with overlapping genetic liability. Transdiagnostic and disorder‐specific brain changes associated with familial risk for developing these disorders remain poorly understood. We carried out a meta‐analysis of diffusion tensor imaging (DTI) studies to investigate white matter microstructure abnormalities in relatives that might correspond to shared and discrete biomarkers of familial risk for psychotic or mood disorders. A systematic search of PubMed and Embase was performed to identify DTI studies in relatives of SCZ, BD, and MDD patients. Seed‐based d Mapping software was used to investigate global differences in fractional anisotropy (FA) between overall and disorder‐specific relatives and healthy controls (HC). Our search identified 25 studies that met full inclusion criteria. A total of 1,144 relatives and 1,238 HC were included in the meta‐analysis. The overall relatives exhibited decreased FA in the genu and splenium of corpus callosum (CC) compared with HC. This finding was found highly replicable in jack‐knife analysis and subgroup analyses. In disorder‐specific analysis, compared to HC, relatives of SCZ patients exhibited the same changes while those of BD showed reduced FA in the left inferior longitudinal fasciculus (ILF). The present study showed decreased FA in the genu and splenium of CC in relatives of SCZ, BD, and MDD patients, which might represent a shared familial vulnerability marker of severe mental illness. The white matter abnormalities in the left ILF might represent a specific familial risk for bipolar disorder. To characterize whether there are common and disorder‐specific genetic contributions to white matter integrity in individuals at increased familial risk for developing psychiatric disorders, we carried out a meta‐analysis including 25 prior diffusion tensor imaging studies in relatives of patients with schizophrenia, bipolar disorder, and major depressive disorder. Results showed that overall relatives of the three disorders exhibited reduced fractional anisotropy in the genu and splenium of the corpus callosum, which might represent shared familial vulnerability marker of severe mental illness.

The brain-derived neurotrophic factor (BDNF) Val66Met polymorphism has been proposed as a possible candidate for involvement in the pathophysiology of bipolar disorder (BD). To determine whether an association exists between the BDNF Val66Met genotype and morphometric abnormalities of the brain regions involved in memory and learning in BD and healthy subjects. Forty-two BD patients and 42 healthy subjects were studied. Interactions between BDNF Val66Met genotype and diagnosis in gray (GM) volumes were analyzed using an optimized voxel-based morphometry technique. Declarative memory function was assessed with the California Verbal Learning Test II. Left and right anterior cingulate GM volumes showed a significant interaction between genotype and diagnosis such that anterior cingulate GM volumes were significantly smaller in the Val/Met BD patients compared with the Val/Val BD patients (left P =0.01, right P =0.01). Within-group comparisons revealed that the Val/Met carriers showed smaller GM volumes of the dorsolateral prefrontal cortex compared with the Val/Val subjects within the BD patient ( P =0.01) and healthy groups (left P =0.03, right P =0.03). The Val/Met healthy subjects had smaller GM volumes of the left hippocampus compared with the Val/Val healthy subjects ( P <0.01). There was a significant main effect of diagnosis on memory function ( P =0.04), but no interaction between diagnosis and genotype was found ( P =0.48). The findings support an association between the BDNF Val66Met genotype and differential gray matter content in brain structures, and suggest that the variation in this gene may play a more prominent role in brain structure differences in subjects affected with BD.

Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable psychiatric disorders with partially overlapping genetic liability. Shared and disorder-specific neurobiological abnormalities associated with familial risk for developing mental illnesses are largely unknown. We performed a meta-analysis of structural brain imaging studies in relatives of patients with SCZ, BD, and MDD to identify overlapping and discrete brain structural correlates of familial risk for mental disorders. Search for voxel-based morphometry studies in relatives of patients with SCZ, BD, and MDD in PubMed and Embase identified 33 studies with 2292 relatives and 2052 healthy controls (HC). Seed-based d Mapping software was used to investigate global differences in gray matter volumes between relatives as a group versus HC, and between those of each psychiatric disorder and HC. As a group, relatives exhibited gray matter abnormalities in left supramarginal gyrus, right striatum, right inferior frontal gyrus, left thalamus, bilateral insula, right cerebellum, and right superior frontal gyrus, compared with HC. Decreased right cerebellar gray matter was the only abnormality common to relatives of all three conditions. Subgroup analyses showed disorder-specific gray matter abnormalities in left thalamus and bilateral insula associated with risk for SCZ, in left supramarginal gyrus and right frontal regions with risk for BD, and in right striatum with risk for MDD. While decreased gray matter in right cerebellum might be a common brain structural abnormality associated with shared risk for SCZ, BD, and MDD, regional gray matter abnormalities in neocortex, thalamus, and striatum appear to be disorder-specific.

The goals of the current study were to determine whether topological organization of brain structural networks is altered in youth with bipolar disorder, whether such alterations predict treatment outcomes, and whether they are normalized by treatment. Youth with bipolar disorder were randomized to double-blind treatment with quetiapine or lithium and assessed weekly. High-resolution MRI images were collected from children and adolescents with bipolar disorder who were experiencing a mixed or manic episode (n = 100) and healthy youth (n = 63). Brain networks were constructed based on the similarity of morphological features across regions and analyzed using graph theory approaches. We tested for pretreatment anatomical differences between bipolar and healthy youth and for changes in neuroanatomic network metrics following treatment in the youth with bipolar disorder. Youth with bipolar disorder showed significantly increased clustering coefficient (Cp) (p = 0.009) and characteristic path length (Lp) (p = 0.04) at baseline, and altered nodal centralities in insula, inferior frontal gyrus, and supplementary motor area. Cp, Lp, and nodal centrality of the insula exhibited normalization in patients following treatment. Changes in these neuroanatomic parameters were correlated with improvement in manic symptoms but did not differ between the two drug therapies. Baseline structural network matrices significantly differentiated medication responders and non-responders with 80% accuracy. These findings demonstrate that both global and nodal structural network features are altered in early course bipolar disorder, and that pretreatment alterations in neuroanatomic features predicted treatment outcome and were reduced by treatment. Similar connectome normalization with lithium and quetiapine suggests that the connectome changes are a downstream effect of both therapies that is related to their clinical efficacy.

Disrupted topological organization of brain functional networks has been widely reported in bipolar disorder. However, the potential clinical implications of structural connectome abnormalities have not been systematically investigated. The present study included 109 unmedicated subjects with acute mania who were assigned to 8 weeks of treatment with quetiapine or lithium and 60 healthy controls. High resolution 3D-T1 weighted magnetic resonance images (MRI) were collected from both groups at baseline, week 1 and week 8. Brain networks were constructed based on the similarity of morphological features across brain regions and analyzed using graph theory approaches. At baseline, individuals with bipolar disorder illness showed significantly lower clustering coefficient (Cp) (p = 0.012) and normalized characteristic path length (λ) (p = 0.004) compared to healthy individuals, as well as differences in nodal centralities across multiple brain regions. No baseline or post-treatment differences were identified between drug treatment conditions, so change after treatment were considered in the combined treatment groups. Relative to healthy individuals, differences in Cp, λ and cingulate gyrus nodal centrality were significantly reduced with treatment; changes in these parameters correlated with changes in Young Mania Rating Scale scores. Baseline structural connectome matrices significantly differentiated responder and non-responder groups at 8 weeks with 74% accuracy. Global and nodal network alterations evident at baseline were normalized with treatment and these changes associated with symptomatic improvement. Further, baseline structural connectome matrices predicted treatment response. These findings suggest that structural connectome abnormalities are clinically significant and may be useful for predicting clinical outcome of treatment and tracking drug effects on brain anatomy in bipolar disorder.Clinical Trials Registration: Name: Functional and Neurochemical Brain Changes in First-episode Bipolar Mania Following Successful Treatment with Lithium or Quetiapine. URL: https://clinicaltrials.gov/. Registration number: NCT00609193. Name: Neurofunctional and Neurochemical Markers of Treatment Response in Bipolar Disorder. URL: https://clinicaltrials.gov/. Registration number: NCT00608075.

The need for treatment response predictive biomarkers is being increasingly recognized in children and adolescents with psychiatric disorders. Structural gray matter abnormalities as a predictor of treatment outcome in pediatric bipolar disorder have not been systematically investigated, especially early in the illness course. With a prospective longitudinal study design, the present study enrolled 52 bipolar adolescents with no history of treatment with mood stabilizers or a therapeutic dose of antipsychotic drugs and 31 healthy controls. Patients were randomly assigned to treatment with quetiapine or lithium after pretreatment data collection. A hierarchical cluster analysis was performed using pretreatment cortical thickness data that identified two discrete patient subgroups. Compared to healthy subjects, patients in subgroup 1 (n = 16) showed widespread greater cortical thickness mainly across heteromodal cortex but also involving some regions of unimodal cortex, while those in subgroup 2 (n = 36) showed regional cortical thinning mainly in superior temporal and superior parietal regions. Patients within subgroup 1 showed a significantly higher response rate to quetiapine than those in subgroup 2 (100% vs 53%). No statistically significant difference was found in lithium response rate between the patient subgroups (63% vs 53%). Pretreatment clinical ratings and neuropsychological data did not differ across subgroups. Our findings suggest the existence of distinct and clinically relevant subgroups of pediatric bipolar patients, as defined by pattern of cortical thickness. These groups appear to differentially respond to antipsychotic treatment—notably with greater cortical thickness relative to controls predicting better treatment response.

To investigate prevalence rates and clinical correlates of alcohol use disorders (AUD) among bipolar disorder (BD) patients in a large sample from the Brazilian Bipolar Research Network. Four hundred and eighty-three DSM-IV BD patients, divided according to the presence or absence of a lifetime AUD diagnosis (BD-AUD vs. BD-nonAUD), were included. Demographic and clinical characteristics of these two groups were compared. Logistic regression was performed to identify which characteristics were most strongly associated with a lifetime AUD diagnosis. Nearly 23% presented a lifetime AUD diagnosis. BD-AUD patients were more likely to be male, to present rapid cycling, post-traumatic stress disorder (PTSD), anorexia, other substance use disorders (SUD), family history of SUD, any substance misuse during the first mood episode, history of psychosis, suicide attempts, and younger age at onset of illness than BD-nonAUD patients. Logistic regression showed that the variables most strongly associated with a lifetime AUD diagnosis were SUD (non-alcohol), any substance misuse during the first mood episode, PTSD, male gender, suicide attempt, family history of SUD, and younger age at onset of BD. BD-AUD patients begin their mood disorder earlier and present more suicidal behaviors than BD-nonAUD patients. Personal and family history of SUD may be good predictors of comorbid AUD among BD patients. These variables are easily assessed in the clinical setting and may help to identify a particularly severe subgroup of BD patients.

Children of individuals with bipolar disorder (bipolar offspring) are at increased risk for developing mood disorders, but strategies to predict mood episodes are unavailable. In this study, we used support vector machine (SVM) to characterize the potential of proton magnetic resonance spectroscopy (1H-MRS) in predicting the first mood episode in youth bipolar offspring. From a longitudinal neuroimaging study, 19 at-risk youth who developed their first mood episode (converters), and 19 without mood episodes during follow-up (non-converters) were selected and matched for age, sex and follow-up time. Baseline 1H-MRS data were obtained from anterior cingulate cortex (ACC) and bilateral ventrolateral prefrontal cortex (VLPFC). Glutamate (Glu), myo-inositol (mI), choline (Cho), N-acetyl aspartate (NAA), and phosphocreatine plus creatine (PCr + Cr) levels were calculated. SVM with a linear kernel was adopted to classify converters and non-converters based on their baseline metabolites. SVM allowed the significant classification of converters and non-converters across all regions for Cho (accuracy = 76.0%), but not for other metabolites. Considering all metabolites within each region, SVM allowed the significant classification of converters and non-converters for left VLPFC (accuracy = 76.5%), but not for right VLPFC or ACC. The combined mI, PCr + Cr, and Cho from left VLPFC achieved the highest accuracy differentiating converters from non-converters (79.0%). Our findings from this exploratory study suggested that 1H-MRS levels of mI, Cho, and PCr + Cr from left VLPFC might be useful to predict the development of first mood episode in youth bipolar offspring using machine learning. Future studies that prospectively examine and validate these metabolites as predictors of mood episodes in high-risk individuals are necessary.

The association between suicidal behavior and quality of life (QoL) in bipolar disorder (BD) is poorly understood. Worse QoL has been associated with suicide attempts and suicidal ideation in schizophrenic patients, but this relationship has not been investigated in BD. This study tested whether a history of suicide attempts was associated with poor QoL in a well-characterized sample of patients with BD, as has been observed in other psychiatric disorders and in the general population. One hundred eight patients with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition BD type I (44 with previous suicide attempts, 64 without previous suicide attempts) were studied. Quality of life was assessed using the World Health Organization's Quality of Life Instrument–Short Version. Depressive and manic symptoms were assessed using the Hamilton Depression Rating Scale–17 items and the Young Mania Rating Scale. Patients with BD and previous suicide attempts had significantly lower scores in all the 4 domains of the World Health Organization's Quality of Life Instrument–Short Version scale than did patients with BD but no previous suicide attempts (physical domain P = .001; psychological domain P < .0001; social domain P = .001, and environmental domain P = .039). In the euthymic subgroup (n = 70), patients with previous suicide attempts had significantly lower scores only in the psychological and social domains ( P = .020 and P = .004). This was a cross-sectional study, and no causal associations can be assumed. Patients with BD and a history of previous suicide attempts seem to have a worse QoL than did patients who never attempted suicide. Poorer QoL might be a marker of poor copying skills and inadequate social support and be a risk factor for suicidal behavior in BD. Alternatively, poorer QoL and suicidal behavior might be different expressions of more severe BD.

The association between psychosocial factors and systemic lupus erythematosus (SLE) is still a matter of discussion. Mood disorders may represent neuropsychiatric manifestations of SLE disease activity or may be a consequence of the stress of having a chronic major disease. We examined the hypothesis that SLE disease activity is related to the presence and severity of major depression in patients with SLE. Seventy-one patients with SLE were evaluated for the presence and intensity of major depressive disorder, psychosocial stressors, functional disability, SLE disease activity, and cumulative damage. Patients with major depression presented a trend toward having greater severity of SLE disease activity compared with those without major depression ( P = .056). Major depression was also associated with life events ( P = .017) and hassles ( P < .001). Reinforcing these findings, depression severity was directly correlated with disease activity ( r = 0.26, P = .026) and with functional disability ( r = 0.46, P < .001). Moreover, multiple linear regression analysis, controlling for stressful life events and previous major depressive episodes, demonstrated that SLE disease activity still was associated with depression severity ( P = .014). In conclusion, these results support the hypothesis that SLE disease activity is a potential risk factor for the presence and severity of major depression in patients with SLE. Whether major depression in active SLE is a central nervous system manifestation of the disease that is mediated by an autoimmune mechanism deserves further research.