Increasing evidence has established a strong association between social anxiety disorder and suicidal behaviours, including suicidal ideation and suicide attempts. However, the association between social anxiety disorder and suicide mortality remains unclear.

This study analysed data from 15,776 patients with social anxiety disorder, extracted from a nationwide Taiwanese cohort between 2003 and 2017. Two unexposed groups without social anxiety disorder, matched by birth year and sex in 1:4 and 1:10 ratios, respectively, were used for comparison. Suicide deaths during the same period were examined. Psychiatric comorbidities commonly associated with social anxiety disorder, including schizophrenia, bipolar disorder, major depression, alcohol use disorder (AUD), substance use disorder (SUD), obsessive-compulsive disorder, autism, and attention deficit hyperactivity disorder, were identified.

Time-dependent Cox regression models, adjusted for demographic factors and psychiatric comorbidities, revealed that individuals with social anxiety disorder had an increased risk of suicide (hazard ratio: 3.49 in the 1:4 matched analysis and 2.84 in the 1:10 matched analysis) compared with those without the disorder. Comorbidities such as schizophrenia, bipolar disorder, major depression, AUD, and SUD further increased the risk of suicide in patients with social anxiety disorder.

Social anxiety disorder is an independent risk factor for suicide death. Additional psychiatric comorbidities, including schizophrenia, major affective disorders, and AUD, further increased social anxiety disorder-related suicide risk. Therefore, mental health officers and clinicians should develop targeted suicide prevention strategies for individuals with social anxiety disorder.

Despite mounting evidence demonstrates circulating endothelial progenitor cells (cEPCs) quantitative changes in depression, no study has investigated cEPC functions in major depressive disorder (MDD). We investigated the role of cEPC adhesive and apoptotic functions in MDD.

We recruited 68 patients with MDD and 56 healthy controls (HCs). The depression symptoms, anxiety, psychosomatic symptoms, subjective cognitive dysfunction, quality of life, and functional disability were evaluated using the Hamilton Depression Rating Scale and Montgomery–Åsberg Depression Rating Scale, Hamilton Anxiety Rating Scale, Depression and Somatic Symptoms Scale (DSSS), Perceived Deficits Questionnaire-Depression, 12-Item Short Form Health Survey (SF-12), and Sheehan Disability Scale (SDS), respectively. Working memory and executive function were assessed using a 2-back task and Wisconsin Card Sorting Test (WCST). Inflammatory marker (soluble interleukin-6 receptor, C-reactive protein, and tumor necrosis factor-α receptor-1), cEPC adhesive, and apoptotic levels were measured using in vitro assays.

The MDD patients showed significantly lower cEPC adhesive levels than the HCs, and this difference in adhesive function remained statistically significant even after adjusting for inflammatory marker levels. The cEPC adhesion levels were in inverse correlations with commission and omission errors in 2-back task, the percent perseverative response and percent perseverative errors in WCST, and the DSSS and SDS scores, but in positive correlations with SF-12 physical and mental component scores. cEPC apoptotic levels did not differ significantly between the groups.

The findings indicate that cEPC adhesive function is diminished in MDD and impacts various aspects of cognitive and psychosocial functions associated with the disorder.

Evidence suggests a familial coaggregation of major psychiatric disorders, including schizophrenia, bipolar disorder, major depression (MDD), autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). Those disorders are further related to suicide and accidental death. However, whether death by suicide may coaggregate with accidental death and major psychiatric disorders within families remains unclear.

To clarify the familial coaggregation of deaths by suicide with accidental death and five major psychiatric disorders.

Using a database linked to the entire Taiwanese population, 68 214 first-degree relatives of individuals who died by suicide between 2003 and 2017 and 272 856 age- and gender-matched controls were assessed for the risks of death by suicide, accidental death and major psychiatric disorders.

A Poisson regression model showed that the first-degree relatives of individuals who died by suicide were more likely to die by suicide (relative risk RR = 4.61, 95% CI 4.02–5.29) or accident (RR = 1.62, 95% CI 1.43–1.84) or to be diagnosed with schizophrenia (RR = 1.53, 95% CI 1.40–1.66), bipolar disorder (RR = 1.99, 95% CI 1.83–2.16), MDD (RR = 1.98, 95% CI 1.89–2.08) or ADHD (RR = 1.34, 95% CI 1.24–1.44).

Our findings identified a familial coaggregation of death by suicide with accidental death, schizophrenia, major affective disorders and ADHD. Further studies would be required to elucidate the pathological mechanisms underlying this coaggregation.

Evidence has suggested that emotional dysregulation is a transdiagnostic feature in schizophrenia and major affective disorders. However, the relationship between emotional dysregulation and appetite hormone disturbance remains unknown in nonobese adolescents with first-episode schizophrenia, bipolar disorder, and major depressive disorder.

In total, 22 adolescents with schizophrenia; 31 with bipolar disorder; 33 with major depressive disorder; and 41 healthy age-, sex-, and body mass index (BMI)/BMI percentile-matched controls were enrolled for assessing levels of appetite hormones, namely leptin, ghrelin, insulin, and adiponectin. Emotional regulation symptoms were measured using the parent-reported Child Behavior Checklist―Dysregulation Profile.

Adolescents with first-episode schizophrenia, bipolar disorder, and major depressive disorder exhibited greater emotional dysregulation symptoms than the control group (P = .037). Adolescents with bipolar disorder demonstrated higher log-transformed levels of insulin (P = .029) and lower log-transformed levels of leptin (P = .018) compared with the control group. BMI (P < .05) and log-transformed ghrelin levels (P = .028) were positively correlated with emotional dysregulation symptoms.

Emotional dysregulation and appetite hormone disturbance may occur in the early stage of severe mental disorders. Further studies are required to clarify the unidirectional or bidirectional association of emotional dysregulation with BMI/BMI percentile and appetite hormones among patients with severe mental disorder.

The genetic load for major depressive disorder (MDD) may be higher in people who develop MDD earlier in life. This study aimed to investigate whether the parents of adolescents with MDD were more likely to have MDD, bipolar disorder (BD), schizophrenic disorder (SZ), alcohol use disorder, or substance use disorder than the parents of adolescents without MDD. We also examined whether the response to antidepressant treatment predicted the likelihood of parental psychiatric disorders.

In all, 1,758 adolescents aged 12–19 years with antidepressant-resistant depression, 7,032 (1:4) age-/sex-matched adolescents with antidepressant-responsive depression and 7,032 (1:4) age-/sex-matched controls were included. Parental psychiatric disorders of individuals enrolled were assessed.

The parents of the adolescents with MDD were more likely to be diagnosed with MDD, BD, SZ, alcohol use disorder, or substance use disorder than the parents of the control group. The parents of adolescents who were antidepressant resistant and the mothers of adolescents who were either treatment resistant or treatment responsive were more likely to be diagnosed with a psychiatric disorder.

Our study demonstrated that parents of adolescents with MDD may be more likely to be diagnosed with MDD, BD, SZ, alcohol use disorder, or substance use disorder than parents of adolescents without MDD, suggesting the within-disorder transmission and cross-disorder transmission of these psychiatric disorders. Furthermore, the parent’s sex and the response to antidepressant treatment may affect the within-disorder transmission of MDD.

Emotional dysregulation (ED) is a common characteristic of both attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD), especially in adolescents. However, whether ADHD and MDD may share the specific ED-related neural networks remains unknown.

In total, 43 adolescents with clinical ED (22 adolescents with ADHD and 21 with MDD) were recruited; in addition, 29 sex- and age-matched healthy controls (HCs) were included. Resting-state functional connectivity (RSFC) analysis, voxel-based morphometry, and diffusion tensor imaging analysis were performed for each patient. In addition, we determined the significant regions of interest in patients with ED due to ADHD and MDD as compared with HCs and tested their correlations with clinical rating scale scores.

Compared with HCs, patients with ED had greater RSFC in the cerebellum and supramarginal gyrus (SMG), especially between vermis VI and the SMG in the attention networks, and lower RSFC between the right supplementary motor area and right lateral parietal area. Lower gray matter (GM) volume in the SMG was also found. RSFC was significantly correlated with clinical rating scale scores for all patients with ED due to ADHD or MDD. GM change was correlated with ED and MDD rating scale scores.

The cerebellum and attention networks might play major roles in ED pathophysiology in adolescents with ADHD and MDD. Increased connectivity of the vermis to the SMG serves as a possible underlying neural network.

Evidence has demonstrated associations of bipolar disorder (BD) with cognitive impairment, dysregulated proinflammatory cytokines, and appetite hormones.

To compare executive dysfunction, proinflammatory cytokines, and appetite hormones between patients with first-episode and multiple-episode BDs.

This cross-sectional study included young adults aged 18 to 39 years who were diagnosed as having type 1 BD in the first or recurrent episode and a group of age-/sex-matched healthy controls. Data regarding patient characteristics, clinical symptoms, cytokines (C-reactive protein [CRP], interleukin-6, and tumor necrosis factor [TNF]-α), appetite hormones (leptin, adiponectin, ghrelin, and insulin), and executive function evaluated using the Wisconsin Card Sorting Test (WCST) were collected.

A total of 112 participants (38 patients in the multiple-episode BD group, 31 patients in the first-episode BD group, and 43 in the control group) were included. Multivariate analysis revealed that patients in the multiple-episode BD group performed significantly worse in the WCST (P < .05) and had higher levels of ghrelin (P = .002), and lower levels of CRP (P = .040) than those in the first-episode BD group. Patients with BD had significantly higher TNF-α and ghrelin levels compared with the healthy controls. No significant associations of CRP, TNF-α, and ghrelin levels with executive function were observed.

Profiles in proinflammatory cytokines and appetite hormones as well as executive function significantly differed between patients with first-episode and multiple-episode BDs and controls, which may suggest their potential roles in the clinical stages and pathophysiology of type 1 BD.

Support vector machines (SVMs) based on brain-wise functional connectivity (FC) have been widely adopted for single-subject prediction of patients with schizophrenia, but most of them had small sample size. This study aimed to evaluate the performance of SVMs based on a large single-site dataset and investigate the effects of demographic homogeneity and training sample size on classification accuracy.

The resting functional Magnetic Resonance Imaging (fMRI) dataset comprised 220 patients with schizophrenia and 220 healthy controls. Brain-wise FCs was calculated for each participant and linear SVMs were developed for automatic classification of patients and controls. First, we evaluated the SVMs based on all participants and homogeneous subsamples of men, women, younger (18–30 years), and older (31–50 years) participants by 10-fold nested cross-validation. Then, we hold out a fixed test set of 40 participants (20 patients and 20 controls) and evaluated the SVMs based on incremental training sample sizes (N = 40, 80, …, 400).

We found that the SVMs based on all participants had accuracy of 85.05%. The SVMs based on male, female, young, and older participants yielded accuracy of 84.66, 81.56, 80.50, and 86.13%, respectively. Although the SVMs based on older subsamples had better performance than those based on all participants, they generalized poorly to younger participants (77.24%). For incremental training sizes, the classification accuracy increased stepwise from 72.6 to 83.3%, with >80% accuracy achieved with sample size >240.

The findings indicate that SVMs based on a large dataset yield high classification accuracy and establish models using a large sample size with heterogeneous properties are recommended for single subject prediction of schizophrenia.

Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear.

To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age.

The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed.

The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = −0.326, P = 0.014).

The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.

Cognitive impairment is common in late-life depression, which may increase Alzheimer disease (AD) risk. Therefore, we aimed to investigate whether late-life major depressive disorder (MDD) has worse cognition and increases the characteristic AD neuropathology. Furthermore, we carried out a comparison between treatment-resistant depression (TRD) and non-TRD. We hypothesized that patients with late-life depression and TRD may have increased β-amyloid (Aβ) deposits in brain regions responsible for global cognition.

We recruited 81 subjects, including 54 MDD patients (27 TRD and 27 non-TRD) and 27 matched healthy controls (HCs). Neurocognitive tasks were examined, including Mini-Mental State Examination and Montreal Cognitive Assessment to detect global cognitive functions. PET with Pittsburgh compound-B and fluorodeoxyglucose were used to capture brain Aβ pathology and glucose use, respectively, in some patients.

MDD patients performed worse in Montreal Cognitive Assessment (p = 0.003) and had more Aβ deposits than HCs across the brain (family-wise error-corrected p < 0.001), with the most significant finding in the left middle frontal gyrus. Significant negative correlations between global cognition and prefrontal Aβ deposits existed in MDD patients, whereas positive correlations were noted in HCs. TRD patients had significantly more deposits in the left-sided brain regions (corrected p < 0.001). The findings were not explained by APOE genotypes. No between-group fluorodeoxyglucose difference was detected.

Late-life depression, particularly TRD, had increased brain Aβ deposits and showed vulnerability to Aβ deposits. A detrimental role of Aβ deposits in global cognition in patients with late-onset or non-late-onset MDD supported the theory that late-life MDD could be a risk factor for AD.

Few studies have explored the complex relationship of pro- and anti-inflammatory cytokines with cognitive function in adolescents with first-episode schizophrenia, bipolar disorder, or major depressive disorder.

In total, 26, 35, and 29 adolescents with first-episode schizophrenia, bipolar disorder, and major depressive disorder, respectively, and 22 age- and sex-matched controls were included in the current study. Cytokines, namely interleukin (IL)-2, IL-6, tumor necrosis factor (TNF)-α, and C-reactive protein (CRP), were assessed. The Wisconsin Card Sorting Test (WCST) and the working memory task were administered to assess cognitive function.

Using generalized linear models with adjustment for demographic data and clinical symptoms, patients with bipolar disorder were found to exhibit the highest levels of CRP (P = .023), IL-6 (P = .022), and TNF-α (P = .011), and had the lowest IL-2 levels (P = .034) among the four groups. According to the results of the WCST and working memory task, adolescents with schizophrenia exhibited the lowest performance in cognitive function. In addition, among the assessed cytokines, only CRP levels (P = .027) were negatively associated with WCST scores.

Dysregulated pro- and anti-inflammatory cytokines and impaired cognitive functioning were observed in first-episode adolescent-onset schizophrenia, bipolar disorder, and major depressive disorder. The altered cytokine profiles may play important roles in the pathophysiology of schizophrenia, bipolar disorder, and major depressive disorder.

Dysregulated proinflammatory cytokines have been shown to be associated with suicidal behavior. Cognitive deficits in working memory and inhibitory control have been demonstrated in depressed patients and people with suicidal ideation (SI). However, the association between proinflammatory cytokines, SI, and cognitive deficits in patients with major depressive disorder (MDD) remains unclear.

A total of 77 patients with MDD and age-/sex-matched 60 healthy individuals were recruited. MDD patients were divided into two groups: with SI (n = 36) and no SI (n = 41). SI was defined by a score of ≥2 in item 3 of the 17-item Hamilton Rating Scale for Depression. Levels of proinflammatory cytokines, including soluble interleukin-6 receptor, soluble tumor necrosis factor-α receptor type 1, and C-reactive protein (CRP), were measured, and cognitive function was assessed using 2-back task and Go/No-Go task.

Patients with SI had higher levels of CRP than those without SI and controls (P = .007). CRP was positively associated with SI (β = 0.21, P = .037), independent of cognitive function and depressive symptoms. Furthermore, SI was associated with cognitive deficits in working memory and inhibitory control after adjusting for confounding factors (P < .05).

Our findings suggest that higher levels of serum CRP and deficits in working memory and inhibitory control may be associated with higher SI among patients with MDD.

Altered immunity and metabolic profiles have been compared between bipolar depression (BD) and major depressive disorder (MDD). This study aimed at developing a composite predictor of appetite hormones and proinflammatory cytokines to differentiate BD from MDD.

This cross-sectional study enrolled patients with BD and those with MDD aged 20 to 59 years and displaying depressive episodes. Clinical characteristics (age, sex, body mass index, and depression severity), cytokines (C-reactive protein, interleukin [IL]-2, IL-6, tumor necrosis factor [TNF]-α, P-selectin, and monocyte chemoattractant protein), and appetite hormones (leptin, adiponectin, ghrelin, and insulin) were assessed as potential predictors using a classification and regression tree (CRT) model for differentiating BD from MDD.

The predicted probability of a composite predictor of ghrelin and TNF-α was significantly greater (for BD: area under curve = 0.877; for MDD: area under curve = 0.914) than that of any one marker (all P > .05) to distinguish BD from MDD. The most powerful predictors for diagnosing BD were high ghrelin and TNF-α levels, whereas those for MDD were low ghrelin and TNF-α levels.

A composite predictor of ghrelin and TNF-α driven by CRT could assist in the differential diagnosis of BD from MDD with high specificity. Further clinical studies are warranted to validate our results and to explore underlying mechanisms.

Recent imaging studies of large datasets suggested that psychiatric disorders have common biological substrates. This study aimed to identify all the common neural substrates with connectomic abnormalities across four major psychiatric disorders by using the data-driven connectome-wide association method of multivariate distance matrix regression (MDMR).

This study analyzed a resting functional magnetic resonance imaging dataset of 100 patients with schizophrenia, 100 patients with bipolar I disorder, 100 patients with bipolar II disorder, 100 patients with major depressive disorder, and 100 healthy controls (HCs). We calculated a voxel-wise 4,330 × 4,330 matrix of whole-brain functional connectivity (FC) with 8-mm isotropic resolution for each participant and then performed MDMR to identify structures where the overall multivariate pattern of FC was significantly different between each patient group and the HC group. A conjunction analysis was performed to identify common neural regions with FC abnormalities across these four psychiatric disorders.

The conjunction of the MDMR maps revealed that the four groups of patients shared connectomic abnormalities in distributed cortical and subcortical structures, which included bilateral thalamus, cerebellum, frontal pole, supramarginal gyrus, postcentral gyrus, lingual gyrus, lateral occipital cortex, and parahippocampus. The follow-up analysis based on pair-wise FC of these regions demonstrated that these psychiatric disorders also shared similar patterns of FC abnormalities characterized by sensory/subcortical hyperconnectivity, association/subcortical hypoconnectivity, and sensory/association hyperconnectivity.

These findings suggest that major psychiatric disorders share common connectomic abnormalities in distributed cortical and subcortical regions and provide crucial support for the common network hypothesis of major psychiatric disorders.