Accumulating evidences indicated that mitochondrial abnormalities were associated with bipolar disorder. As a sensitive index of mitochondrial function and biogenesis, Mitochondrial DNA copy number (mtDNAcn) may be involved in the pathophysiology of bipolar disorder. Leukocyte relative mtDNAcn was measured by quantitative polymerase chain reaction in subjects with BD (n = 131) in manic, depressive, and euthymic symptoms. Thirty-four healthy individuals were used as comparison control. BD clinical symptomatology was evaluated by Young Mania Rating Scale (YMRS), Hamilton Depression Scale (HAM-D), Clinical Global Impression-Bipolar Disorder-Severity of Illness Scale (CGI-BD-S), and the Positive and Negative Syndrome Scale (PANSS). Compared to healthy controls, BD patients with manic and depressive symptoms presented significantly decreased mtDNAcn levels (p-value = 0.009 and 0.041, respectively). No significant differences were detected in mtDNAcn between euthymic patients and healthy controls. The mtDNAcn was negatively correlated with the number of relapses in manic patients (β = − 0.341, p = 0.044). Our study described the first evidence of (1) a significant decline of mtDNAcn in manic BD patients, (2) a similar decreased level of mtDNAcn between manic and depressed BD patients, (3) a negative correlation of mtDNAcn with number of relapses in patients suffering from manic states. Alterations of mtDNAcn in manic and depressed patients, which may reflect disturbances of energy metabolism, supported the role of mitochondrial abnormalities in the pathophysiology of BD.

Background: Childhood trauma confers risks to mental health. However, little is known about whether home quarantine (HQ) during the coronavirus disease 2019 (COVID-19) pandemic exaggerated or mitigated the effect of childhood trauma on mental health.Objective: To examine the modulating effects of prior childhood traumas on the longitudinal changes of psychiatric symptoms in college students before and after HQ during the pandemic.Methods: This was a two-wave longitudinal study on the mental health of 2,887 college students before and after HQ during the COVID-19 pandemic. The relationships between the changes in the Patient Health Questionnaire-9 (PHQ-9), Symptom Checklist-90 (SCL-90), 16-item Prodromal Questionnaire (PQ-16), Childhood Trauma Questionnaire (CTQ), and Social Support Rating Scale (SSRS) scores were analyzed.Results: The students with childhood trauma showed a significantly greater decrement in psychiatric symptoms after HQ (F = 17.21, 14.11, 18.87, and 17.42 for PHQ-9, PQ-16 objective and distress, and SCL-90, respectively). The correlation coefficients between the CTQ and these symptoms scales were significant at baseline (r = 0.42, 0.34, 0.37, and 0.39), and decreased after HQ (r = 0.17, 0.20, 0.18, and 0.19). The decrement of depressive, psychotic, and overall symptoms was positively correlated with the scores of the CTQ (r = 0.08–0.27) but negatively correlated with SSRS (r = −0.08−−0.14). Multilinear regression analysis confirmed the results of the CTQ and SSRS regarding the modulation of the dynamic changes in psychiatric symptoms. A constructed structural equation model indicated that the total effects of childhood trauma on decreased psychiatric symptoms were partly mediated by lower baseline social support.Conclusion: Home quarantine during the COVID-19 pandemic could blunt the adverse effects of childhood trauma on mental health, especially for prodromal psychotic symptoms in college students. Changes in relative deprivation and social support may be mediating factors.

Cognitive impairment is a core symptom of schizophrenia (SZ), with GABAergic dysfunction in the brain potentially serving as a critical pathological mechanism underlying this condition. Intracortical inhibition (ICI), which includes short-interval intracortical inhibition (SICI) and long-interval intracortical inhibition (LICI), can be used to assess the inhibitory function of cortical GABAergic neurons. The aim of this study was to investigate the relationship between ICI and cognitive function, as well as psychopathological symptoms, in SZ patients. We recruited 130 SZ patients and 105 healthy controls (HCs). All subjects underwent paired-pulse transcranial magnetic stimulation (ppTMS) measurements, which included resting motor threshold (RMT), SICI and LICI. The cognitive function of all subjects was assessed using the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB). The psychopathological symptoms of the SZ group were assessed using the Positive and Negative Syndrome Scale (PANSS). We examined group differences in MCCB scores, RMT, SICI, and LICI. Within the SZ group, we assessed the relationship between ICI and cognitive function, as well as psychopathological symptoms. Two-way ANOVA, Mann–Whitney U test, Receiver operating characteristic (ROC) curves, and partial Spearman correlation analysis were performed. The SZ group showed a worse cognitive score in all 6 cognitive dimensions of the MCCB compared to the HC group (all p < 0.05). The SZ group had lower degree of SICI and LICI compared to the HC group (both p < 0.05). ROC curves analysis showed that SICI and LICI all displayed good performance in differentiating SZ patients and HCs (both p < 0.05), and SICI exhibited a better performance, yielding an area under the curve (AUC) of 0.856 (95% CI 0.807–0.904). Furthermore, in the SZ group, SICI demonstrated a significant negative correlation with PANSS positive score, negative score, general psychopathology score, and total score (all p_Bonferroni < 0.05), and LICI demonstrated a significant negative correlation with PANSS positive score, general psychopathology score and total score (all p_Bonferroni < 0.05). Additionally, in the SZ group, SICI demonstrated a significant positive correlation with speed of processing score, working memory score, verbal learning score, visual learning score, and reasoning and problem-solving score of the MCCB (all p_Bonferroni < 0.05), while LICI was only weakly positive correlated with speed of processing score of the MCCB (r = 0.247, p = 0.005, p_Bonferroni = 0.03). Our results demonstrate that the reduction of ICI could serve as a trait-dependent in-vivo biomarker of GABAergic deficits for SZ and related cognitive impairments.

The temporal onset of polygenic brain disorders has been closely linked to the developmental dynamics of genome-wide risk gene expression. In this study, we systematically characterized the spatiotemporal expression patterns of these risk genes and their relevance in differentiating major neuropsychiatric disorders. We analyzed genome-wide risk gene sets for Intelligence Quotient (IQ), Autism Spectrum Disorders (ASD), Attention Deficit Hyperactive Disorder (ADHD), Tourette's Syndrome (TS), Obsessive Compulsive Disorder (OCD), Anorexia Nervosa (ANO), Neuroticism, Panic disorder, Major Depressive Disorder (MDD), Bipolar Disorder (BIP), Schizophrenia (SZ), Epilepsy, Alzheimer's Disease (AD), and Parkinson's Disease (PD). Our results reveal distinct patterns of spatiotemporal enrichment across these traits, allowing their classification into three clusters. To validate the biological significance of these enrichment patterns, we integrated clinical MRI datasets and confirmed structural alterations within the identified spatiotemporal “hot-spots”. Furthermore, by combining gene co-expression network analysis and single-cell transcriptomic data, we delineated the cell-type specificity and functional pathways underlying risk gene enrichment. In situ hybridization data from the marmoset brain further provided a comprehensive map of risk gene related module expression. This work reinforces the link between dynamic gene expression and disease mechanisms, while highlighting potential biomarkers and therapeutic targets arising from these identified “hot-spots” and pathways.

Brain development is guided by dynamic gene expression programs that vary across brain regions and developmental stages. Although numerous risk genes for neuropsychiatric disorders have been identified, the spatiotemporal contexts in which they act remain unclear. Here we show the spatiotemporal expression patterns of genome-wide risk gene sets across 15 neuropsychiatric traits, including autism, attention deficit hyperactive disorder, obsessive compulsive disorder, major depression, bipolar disorder, schizophrenia, epilepsy, Alzheimer's disease and Parkinson's disease, using bulk and single-cell transcriptomic data from the human brain. We identify trait-specific spatiotemporal enrichment patterns, allowing a classification of disorders into prenatally and postnatally enriched groups that align with known ages of disease onset. Integration with brain imaging datasets and gene co-expression network analysis further identifies synaptic development and function, as well as RNA processing during early brain development, in neuropsychiatric risk. These findings provide a systems-level framework linking genetic risk to neurodevelopmental and neuroanatomical contexts.