Aims: The burden of mental disorders is increasing worldwide, thus, affecting society and healthcare systems. This study investigated the independent influences of age, period and cohort on the global prevalence of mental disorders from 1990 to 2019; compared them by sex; and predicted the future burden of mental disorders in the next 25 years. Methods: The age-specific and sex-specific incidence of mental disorders worldwide was analysed according to the general analysis strategy used in the Global Burden of Disease Study in 2019. The incidence and mortality trends of mental disorders from 1990 to 2019 were evaluated through joinpoint regression analysis. The influences of age, period and cohort on the incidence of mental disorders were evaluated with an age–period–cohort model. Results: From 1990 to 2019, the sex-specific age-standardized incidence and disability-adjusted life years (DALY) rate decreased slightly. Joinpoint regression analysis from 1990 to 2019 indicated four turning points in the male DALY rate and five turning points in the female DALY rate. In analysis of age effects, the relative risk (RR) of incidence and the DALY rate in mental disorders in men and women generally showed an inverted U-shaped pattern with increasing age. In analysis of period effects, the incidence of mental disorders increased gradually over time, and showed a sub-peak in 2004 (RR, 1.006 for males; 95% CI, 1.000–1.012; 1.002 for women, 0.997–1.008). Analysis of cohort effects showed that the incidence and DALY rate decreased in successive birth cohorts. The incidence of mental disorders is expected to decline slightly over the next 25 years, but the number of cases is expected to increase. Conclusions: Although the age-standardized burden of mental disorders has declined in the past 30 years, the number of new cases and deaths of mental disorders worldwide has increased, and will continue to increase in the near future. Therefore, relevant policies should be used to promote the prevention and management of known risk factors and strengthen the understanding of risk profiles and incidence modes of mental disorders, to help guide future research on control and prevention strategies.

Functional changes of white matter are largely unexplored in patients with psychiatric disorders. This study examined white matter dysfunctions common in four major psychiatric disorders (including schizophrenia, major depressive disorder, bipolar disorder and obsessive–compulsive disorder) using multimodal magnetic resonance imaging. Here we found increased brain activity in the bilateral anterior thalamic radiation in major psychiatric disorder patients when compared with healthy controls. The spatial pattern of white matter dysfunction in patients with major psychiatric disorders was correlated with the distributions of disease-related neurotransmitters and expression maps of specific genes. These genes were enriched in excitatory neurons and ontological terms related to synaptic function. These findings were replicated in an independent dataset. Collectively, imaging dysfunction of white matter and its molecular genetic basis provided new clues to understand the pathophysiology of major psychiatric disorders.

A large proportion of patients with obsessive–compulsive disorder (OCD) respond unsatisfactorily to pharmacological and psychological treatments. An alternative novel treatment for these patients is repetitive transcranial magnetic stimulation (rTMS). This study aimed to investigate the underlying neural mechanism of rTMS treatment in OCD patients. A total of 37 patients with OCD were randomized to receive real or sham 1‐Hz rTMS (14 days, 30 min/day) over the right pre‐supplementary motor area (preSMA). Resting‐state functional magnetic resonance imaging data were collected before and after rTMS treatment. The individualized target was defined by a personalized functional connectivity map of the subthalamic nucleus. After treatment, patients in the real group showed a better improvement in the Yale–Brown Obsessive Compulsive Scale than the sham group (F_1,35 = 6.0, p = .019). To show the neural mechanism involved, we identified an “ideal target connectivity” before treatment. Leave‐one‐out cross‐validation indicated that this connectivity pattern can significantly predict patients' symptom improvements (r = .60, p = .009). After real treatment, the average connectivity strength of the target network significantly decreased in the real but not in the sham group. This network‐level change was cross‐validated in three independent datasets. Altogether, these findings suggest that personalized magnetic stimulation on preSMA may alleviate obsessive–compulsive symptoms by decreasing the connectivity strength of the target network.

Idiopathic generalized epilepsy (IGE) is a brain network disease, but the location of this network and its relevance for treatment remain unclear. We combine the locations of brain abnormalities in IGE (131 coordinates from 21 studies) with the human connectome to identify an IGE network. We validate this network by showing alignment with structural brain abnormalities previously identified in IGE and brain areas activated by generalized epileptiform discharges in simultaneous electroencephalogram-functional magnetic resonance imaging. The topography of the IGE network aligns with brain networks involved in motor control and loss of consciousness consistent with generalized seizure semiology. To investigate therapeutic relevance, we analyze data from 21 patients with IGE treated with deep brain stimulation (DBS) for generalized seizures. Seizure frequency reduced a median 90% after DBS and stimulation sites intersect an IGE network peak in the centromedian nucleus of the thalamus. Together, this study helps unify prior findings in IGE and identify a brain network target that can be tested in clinical trials of brain stimulation to control generalized seizures.