Although aberrant brain regional responses are reported in social anxiety disorder (SAD), little is known about resting-state functional connectivity at the macroscale network level. This study aims to identify functional network abnormalities using a multivariate data-driven method in a relatively large and homogenous sample of SAD patients, and assess their potential diagnostic value.

Forty-six SAD patients and 52 demographically-matched healthy controls (HC) were recruited to undergo clinical evaluation and resting-state functional MRI scanning. We used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra-/inter-network functional network connectivity (FNC). Furtherly, we explored the associations of FNC abnormalities with clinical characteristics, and assessed their ability to discriminate SAD from HC using support vector machine analyses.

SAD patients showed widespread intra-network FNC abnormalities in the default mode network, the subcortical network and the perceptual system (i.e. sensorimotor, auditory and visual networks), and large-scale inter-network FNC abnormalities among those high-order and primary RSNs. Some aberrant FNC signatures were correlated to disease severity and duration, suggesting pathophysiological relevance. Furthermore, intrinsic FNC anomalies allowed individual classification of SAD v. HC with significant accuracy, indicating potential diagnostic efficacy.

SAD patients show distinct patterns of functional synchronization abnormalities both within and across large-scale RSNs, reflecting or causing a network imbalance of bottom-up response and top-down regulation in cognitive, emotional and sensory domains. Therefore, this could offer insights into the neurofunctional substrates of SAD.

The differential impact of depression across different periods in life on mortality remains inconclusive. We aimed to examine the association of depression that occurs at different age with all-cause mortality, and to explore the roles of dementia, as well as genetic and early-life environmental factors, in this association.

From the Swedish Twin Registry, 44,919 twin individuals were followed for up to 18 years. Depression was ascertained using the National Patient Registry and categorized as early-life (<45 years), midlife (45–64 years), and late-life (≥65 years) depression according to the age of the first diagnosis. Deaths were identified through the Cause of Death Register. Generalized estimating equation, generalized structural equation, and conditional logistic regression were used for unmatched, mediation, and co-twin matched analyses, respectively.

In unmatched analyses, the multivariate-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of mortality were 1.71 (1.46–2.00) for depression at any age, 1.72 (1.36–2.17) for early-life, 1.51 (1.19–1.90) for midlife, and 4.10 (2.02–8.34) for late-life depression. Mortality was significantly higher in individuals with late-life depression than those with earlier-life depression (p < 0.05). The mediation analysis showed that 59.83% of the depression-mortality association was mediated by dementia. No significant difference in ORs between the unmatched and co-twin matched analyses was observed (p = 0.09).

Depression is associated with an increased risk of all-cause mortality, and dementia mediates approximately 60% of the impact of depression on mortality in late life. Genetic and early-life environmental factors may not play a significant role in the depression-mortality association.

Adolescent suicide is a severe public health problem in low- and middle-income countries (LMICs), and adolescents who are victims of bullying have a higher risk of suicidal behaviours. However, detailed global data concerning the association between bullying victimisation and suicide are lacking; thus, further multicontinental studies exploring the association of bullying victimisation at different frequencies and types with suicidal behaviours are urgent.

The data were extracted from the Global School-based Student Health Survey (GSHS) (2010–2017) conducted in 40 LMICs (n = 151 184, mean age: 14.77 years, s.d.: 1.59, 54.2% females). Data concerning past-30-day bullying victimisation, past 12-month suicidal behaviours (suicidal ideation, suicidal plans and suicidal attempts) and other adverse health behaviours or outcomes were collected. Chi-square tests were used to explore the correlations among the main variables. A multivariable logistic regression and stratified logistic regressions were conducted to assess the associations.

The overall prevalence of bullying victimisation, suicidal ideation, suicidal plans and suicidal attempts were 28.72, 12.64, 11.84 and 10.79%, respectively. The results showed a positive association of different frequencies and types of bullying victimisation with suicidal behaviours: suicidal ideation (odds ratio (OR) = 2.43, 2.06–2.87), suicidal plans (OR = 2.69, 2.28–3.17) and suicidal attempts (OR = 3.23, 2.73–3.82). Adolescents also reported the effects of being made fun of because of their religion: suicidal ideation (OR = 1.63, 1.41–1.88), suicidal plans (OR = 1.44, 1.24–1.66) and suicidal attempts (OR = 1.73, 1.50–1.98). Moreover, these associations varied among teenagers of different gender and body mass indexes (BMIs) and were stronger among males and adolescents who were underweight, overweight or obese.

Different types of bullying victimisation were positively related to suicidal behaviours; these associations varied among adolescents by gender and BMI. This study offers a theoretical basis for the identification of adolescents at a high risk of suicide and is beneficial for informing effective psychological interventions for constructing sound school environments, improving adolescents’ mental health and reducing the risk of suicide to promote health in LMICs and globally.

Persistent psychological distress associated with the coronavirus disease 2019 (COVID-19) pandemic has been well documented. This study aimed to identify pre-COVID brain functional connectome that predicts pandemic-related distress symptoms among young adults.

Baseline neuroimaging studies and assessment of general distress using the Depression, Anxiety and Stress Scale were performed with 100 healthy individuals prior to wide recognition of the health risks associated with the emergence of COVID-19. They were recontacted for the Impact of Event Scale-Revised and the Posttraumatic Stress Disorder Checklist in the period of community-level outbreaks, and for follow-up distress evaluation again 1 year later. We employed the network-based statistic approach to identify connectome that predicted the increase of distress based on 136-region-parcellation with assigned network membership. Predictive performance of connectome features and causal relations were examined by cross-validation and mediation analyses.

The connectome features that predicted emergence of distress after COVID contained 70 neural connections. Most within-network connections were located in the default mode network (DMN), and affective network-DMN and dorsal attention network-DMN links largely constituted between-network pairs. The hippocampus emerged as the most critical hub region. Predictive models of the connectome remained robust in cross-validation. Mediation analyses demonstrated that COVID-related posttraumatic stress partially explained the correlation of connectome to the development of general distress.

Brain functional connectome may fingerprint individuals with vulnerability to psychological distress associated with the COVID pandemic. Individuals with brain neuromarkers may benefit from the corresponding interventions to reduce the risk or severity of distress related to fear of COVID-related challenges.

Patients with single ventricle CHD have significant morbidity and healthcare utilisation throughout their lifetime, including non-cardiac hospital admissions. Respiratory viral infections are the main cause of hospitalisation in children, but few data exist for single ventricle patients. We sought to identify how respiratory viral infections impact patients with single ventricle CHD and potential differences between Glenn and Fontan circulation.

We conducted a retrospective study of patients seen from 01/01/2011–12/31/2020. We identified patients with a history of single ventricle CHD and Glenn palliation, and a normoxic control group with isolated atrial septal defect requiring surgical closure. We compared viral-related clinical presentations, admissions, and admission characteristics.

A total of 312 patients were included (182 single ventricle, 130 atrial septal defect). Single ventricle patients were more likely than children with isolated atrial septal defect to be admitted with a respiratory virus (odds ratio 4.15 [2.30–7.46]), but there was no difference in mechanical ventilation or hospital length of stay (p = 0.4709). Single ventricle patients with Glenn circulation were more likely than those with Fontan circulation to present and be admitted (odds ratio 3.25 [1.62–6.52]), but there was no difference in ICU admission, mechanical ventilation, or hospital length of stay (p = 0.1516).

Respiratory viral infections are prevalent but uncomplicated in patients with single ventricle CHD. Viral-related presentations and admissions are more prevalent during the period of Glenn circulation compared to Fontan circulation; however, rate of mechanical ventilation and hospital length of stay are similar.

This study aimed to examine the impact of different dietary patterns on stroke outcomes among type 2 diabetes mellitus (T2DM) patients in China.

Participants were enrolled by a stratified random cluster sampling method in the study. After collecting dietary data using a quantified FFQ, latent class analysis was used to identify dietary patterns, and propensity score matching was used to reduce confounding effects between different dietary patterns. Binary logistic regression and conditional logistic regression were used to analyse the relationship between dietary patterns and stroke in patients with T2DM.

A cross-sectional survey available from December 2013 to January 2014.

A total of 13 731 Chinese residents aged 18 years or over.

Two dietary patterns were identified: 61·2 % of T2DM patients were categorised in the high-fat dietary pattern while 38·8 % of patients were characterised by the balanced dietary pattern. Compared with the high-fat dietary pattern, the balanced dietary pattern was associated with reduced stroke risk (OR = 0·63, 95 %CI 0·52, 0·76, P < 0·001) after adjusting for confounding factors. The protective effect of the balanced model did not differ significantly (interaction P > 0·05).

This study provides sufficient evidence to support the dietary intervention strategies to prevent stroke effectively. Maintaining a balanced dietary pattern, especially with moderate consumption of foods rich in quality protein and fresh vegetables in T2DM patients, might decrease the risk of stroke in China.

The role of neurological proteins in the development of bipolar disorder (BD) and schizophrenia (SCZ) remains elusive now. The current study aims to explore the potential genetic correlations of plasma neurological proteins with BD and SCZ.

By using the latest genome-wide association study (GWAS) summary data of BD and SCZ (including 41,917 BD cases, 11,260 SCZ cases, and 396,091 controls) derived from the Psychiatric GWAS Consortium website (PGC) and a recently released GWAS of neurological proteins (including 750 individuals), we performed a linkage disequilibrium score regression (LDSC) analysis to detect the potential genetic correlations between the two common psychiatric disorders and each of the 92 neurological proteins. Two-sample Mendelian randomisation (MR) analysis was then applied to assess the bidirectional causal relationship between the neurological proteins identified by LDSC, BD and SCZ.

LDSC analysis identified one neurological protein, NEP, which shows suggestive genetic correlation signals for both BD (coefficient = −0.165, p value = 0.035) and SCZ (coefficient = −0.235, p value = 0.020). However, those association did not remain significant after strict Bonferroni correction. Two sample MR analysis found that there was an association between genetically predicted level of NEP protein, BD (odd ratio [OR] = 0.87, p value = 1.61 × 10−6) and SCZ (OR = 0.90, p value = 4.04 × 10−6). However, in the opposite direction, there is no genetically predicted association between BD, SCZ, and NEP protein level.

This study provided novel clues for understanding the genetic effects of neurological proteins on BD and SCZ.

Mounting evidence showed that insula contributed to the neurobiological mechanism of suicidal behaviors in bipolar disorder (BD). However, no studies have analyzed the dynamic functional connectivity (dFC) of insular Mubregions and its association with personality traits in BD with suicidal behaviors. Therefore, we investigated the alterations of dFC variability in insular subregions and personality characteristics in BD patients with a recent suicide attempt (SA).

Thirty unmedicated BD patients with SA, 38 patients without SA (NSA) and 35 demographically matched healthy controls (HCs) were included. The sliding-window analysis was used to evaluate whole-brain dFC for each insular subregion seed. We assessed between-group differences of psychological characteristics on the Minnesota Multiphasic Personality Inventory-2. Finally, a multivariate regression model was adopted to predict the severity of suicidality.

Compared to NSA and HCs, the SA group exhibited decreased dFC variability values between the left dorsal anterior insula and the left anterior cerebellum. These dFC variability values could also be utilized to predict the severity of suicidality (r = 0.456, p = 0.031), while static functional connectivity values were not appropriate for this prediction. Besides, the SA group scored significantly higher on the schizophrenia clinical scales (p < 0.001) compared with the NSA group.

Our findings indicated that the dysfunction of insula–cerebellum connectivity may underlie the neural basis of SA in BD patients, and highlighted the dFC variability values could be considered a neuromarker for predictive models of the severity of suicidality. Moreover, the psychiatric features may increase the vulnerability of suicidal behavior.