Abnormal functional brain connectivity could be considered an endophenotype of psychosis in schizophrenia. Identifying candidate endophenotypes may serve as a tool for elucidating its biological and neural mechanisms. The present study investigated the similarities and differences of features of brain network connectivity between patients and their first-degree relatives. Independent component analysis was conducted on imaging data collected from 34 healthy controls, 33 schizophrenia patients, and 30 unaffected first-degree relatives. The correlation between functional connectivity with neurocognitive performance and clinical symptoms were calculated. Abnormalities of between-network connectivity largely overlapped in patients and first-degree relatives, but the extent of such abnormalities was relatively minor in relatives. Negative connectivity between language networks and executive control networks was impaired in schizophrenia patients and their first-degree relatives, and this decreased connectivity was correlated with performance in language processing. Similar impairments were found in high-visual network and executive network coupling, and this decreased connection was correlated with the severity of positive symptoms in patients. The results indicated that abnormal functional connectivity within and between perceptual systems (i.e., high-visual and language) and executive control networks was related to the generic risk of schizophrenia, which makes it a potential endophenotype for schizophrenia.

Chronic pain and sleep disturbance are highly comorbid disorders, which leads to barriers to treatment and significant healthcare costs. Understanding the underlying genetic and neural mechanisms of the interplay between sleep disturbance and chronic pain is likely to lead to better treatment. In this study, we combined 1206 participants with phenotype data, resting-state functional magnetic resonance imaging (rfMRI) data and genotype data from the Human Connectome Project and two large sample size genome-wide association studies (GWASs) summary data from published studies to identify the genetic and neural bases for the association between pain and sleep disturbance. Pittsburgh sleep quality index (PSQI) score was used for sleep disturbance, pain intensity was measured by Pain Intensity Survey. The result showed chronic pain was significantly correlated with sleep disturbance (r = 0.171, p-value < 0.001). Their genetic correlation was r_g = 0.598 using linkage disequilibrium (LD) score regression analysis. Polygenic score (PGS) association analysis showed PGS of chronic pain was significantly associated with sleep and vice versa. Nine shared functional connectivity (FCs) were identified involving prefrontal cortex, temporal cortex, precentral/postcentral cortex, anterior cingulate cortex, fusiform gyrus and hippocampus. All these FCs mediated the effect of sleep disturbance on pain and seven FCs mediated the effect of pain on sleep disturbance. The chronic pain PGS was positively associated with the FC between middle temporal gyrus and hippocampus, which further mediated the effect of chronic pain PGS on PSQI score. Mendelian randomization analysis implied a possible causal relationship from chronic pain to sleep disturbance was stronger than that of sleep disturbance to chronic pain. The results provided genetic and neural evidence for the association between pain and sleep disturbance, which may inform future treatment approaches for comorbid chronic pain states and sleep disturbance.

Background and Objectives: This study aimed to elucidate the role of the glymphatic system—a crucial pathway for clearing waste in the brain—in the aging process and its contribution to cognitive decline. We specifically focused on the diffusion tensor imaging analysis along the perivascular space (ALPS) index as a noninvasive biomarker of glymphatic function. Methods: Data were drawn from the Alzheimers Disease Neuroimaging Initiative (ADNI) database and a separate validation cohort to analyze the ALPS index in cognitively normal older adults. The relationships among the ALPS index, brain morphometry, and memory performance were examined. Results: As a biomarker of glymphatic function, the ALPS index appeared to decline with age in both cohorts. According to the brain morphology analysis, the ALPS index was positively correlated with the thickness of the left entorhinal cortex (r = 0.258, P _{false discovery rate (FDR)} = 2.96 × 10^-4), and it played a mediating role between aging and left entorhinal cortex thinning. The independent cohort further validated the correlation between the ALPS index and the left entorhinal cortex thickness (r = 0.414, P _FDR = 0.042). Additionally, in both the primary and validation cohorts, the ALPS index played a significant mediating role in the relationship between age and durable or delayed memory decline. Conclusion: This study highlights the ALPS index as a promising biomarker for glymphatic function and links it to atrophy of the core memory brain regions during aging. Furthermore, these results suggest that targeting glymphatic dysfunction could represent a novel therapeutic approach to mitigate age-related memory decline.

It remains challenging to identify depression accurately due to its biological heterogeneity. As people suffering from depression are associated with functional brain network alterations, we investigated subtypes of patients with first‐episode drug‐naive (FEDN) depression based on brain network characteristics. This study included data from 91 FEDN patients and 91 matched healthy individuals obtained from the International Big‐Data Center for Depression Research. Twenty large‐scale functional connectivity networks were computed using group information guided independent component analysis. A multivariate unsupervised normative modeling method was used to identify subtypes of FEDN and their associated networks, focusing on individual‐level variability among the patients for quantifying deviations of their brain networks from the normative range. Two patient subtypes were identified with distinctive abnormal functional network patterns, consisting of 10 informative connectivity networks, including the default mode network and frontoparietal network. 16% of patients belonged to subtype I with larger extreme deviations from the normal range and shorter illness duration, while 84% belonged to subtype II with weaker extreme deviations and longer illness duration. Moreover, the structural changes in subtype II patients were more complex than the subtype I patients. Compared with healthy controls, both increased and decreased gray matter (GM) abnormalities were identified in widely distributed brain regions in subtype II patients. In contrast, most abnormalities were decreased GM in subtype I. The informative functional network connectivity patterns gleaned from the imaging data can facilitate the accurate identification of FEDN‐MDD subtypes and their associated neurobiological heterogeneity.

Background and aims: The inclusion of gaming disorder as a new diagnosis in the 11th revision of the International Statistical Classification of Diseases (ICD-11) has caused ongoing debate. This review aimed to summarise the potential neural mechanisms of gaming disorder and provide additional evidence for this debate.Methods: We conducted a comprehensive literature review of gaming disorder, focusing on studies that investigated its clinical characteristics and neurobiological mechanisms. Based on this evidence, we further discuss gaming disorder as a psychiatric disorder.Results: The present review demonstrated that the brain regions involved in gaming disorder are related to executive functioning (e.g., anterior cingulate cortex and dorsolateral prefrontal cortex), reward systems (e.g., striatum and orbitofrontal cortex), and emotional regulation (e.g., insula and amygdala). Despite the inclusion of gaming disorder in the ICD-11, the debate remains on the benefits and harms of classifying it as a mental health disorder. Opponents argue that the current manifestations that support gaming disorder as a psychiatric disorder remain inadequate, it could cause moral panic among healthy gamers, and that the label of gaming disorder is stigmatising.Discussion: Evidence suggests that gaming disorder shares similar neurobiological alterations with other types of behavioural and substance-related addictions, which further supports gaming disorder as a behavioural addiction. Ongoing debates on whether gaming disorder is a psychiatric disorder push for further exploring the nature of gaming disorder and resolving this dilemma in the field.

Background: Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive form of brain stimulation. It has been used in many mental health institutions to treat mental disorders worldwide. However, comprehensive knowledge about rTMS is not yet widespread among psychiatrists. The present study assessed psychiatrists’ knowledge and attitudes about rTMS in China and investigated related factors. Methods: A quantitative observational cross-sectional study was conducted using an online survey. The sample consisted of 522 psychiatrists. Multinomial logistic regression and multiple linear regression analyses were used to explore factors that contributed to psychiatrists’ knowledge about rTMS. We also ascertained psychiatrists’ attitudes about rTMS and provide recommendations for the more widespread use of rTMS. Results: The majority of respondents (86.4%) reported having access to rTMS at their institution. A total of 379 psychiatrists (72.6%) knew that rTMS was approved by the United States Food and Drug Administration for treatment-resistant depression. Univariate logistic regression indicated that psychiatrists who were older, had a senior professional title, worked more years, had an onsite clinical rTMS program in their hospital, and received formal training in theory and application (all p < 0.05) were more likely to know that rTMS was approved by the Food and Drug Administration for the treatment of depression. The percentages of respondents who knew most or all indications, the mechanism of action, parameter settings, adverse reactions were 51.9, 40.2, 27.4, and 41.4%. Linear regression showed that formal training in rTMS theory and practice were associated with higher knowledge scores (all p < 0.05). Most of the subjects had negative attitudes about using rTMS to treat mental disorders. When asked about their attitudes about continuing rTMS education, nearly all of the respondents indicated that they were willing to pursue continuing training in rTMS in the future. Conclusions: Many psychiatrists had an insufficient level of knowledge about rTMS and negative attitudes about rTMS. Psychiatrists who had formal rTMS training experience had higher levels of rTMS knowledge. rTMS training and relevant policy making should be strengthened.