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Neuroimaging studies have demonstrated that migraine is accompanied by spontaneous brain activity alterations in specific regions. However, these findings are inconsistent, thus hindering our understanding of the potential neuropathology. Hence, we performed a quantitative whole‐brain meta‐analysis of relevant resting‐state functional imaging studies to identify brain regions consistently involved in migraine. A systematic search of studies that investigated the differences in spontaneous brain activity patterns between migraineurs and healthy controls up to April 2022 was conducted. We then performed a whole‐brain voxel‐wise meta‐analysis using the anisotropic effect size version of seed‐based d mapping software. Complementary analyses including jackknife sensitivity analysis, heterogeneity test, publication bias test, subgroup analysis, and meta‐regression analysis were conducted as well. In total, 24 studies that reported 31 datasets were finally eligible for our meta‐analysis, including 748 patients and 690 controls. In contrast to healthy controls, migraineurs demonstrated consistent and robust decreased spontaneous brain activity in the angular gyrus, visual cortex, and cerebellum, while increased activity in the caudate, thalamus, pons, and prefrontal cortex. Results were robust and highly replicable in the following jackknife sensitivity analysis and subgroup analysis. Meta‐regression analyses revealed that a higher visual analog scale score in the patient sample was associated with increased spontaneous brain activity in the left thalamus. These findings provided not only a comprehensive overview of spontaneous brain activity patterns impairments, but also useful insights into the pathophysiology of dysfunction in migraine. In this article, we performed the first quantitative voxel‐wise meta‐analysis of spontaneous brain activity abnormalities in patients with migraine, and found several brain regions associated with migraine, including the angular gyrus, visual cortex, cerebellum, caudate, thalamus, pons, and prefrontal cortex.

The human brain is an extremely complex system in which neurons, clusters of neurons, or regions are connected to form a complex network. With the development of neuroimaging techniques, magnetic resonance imaging (MRI)-based brain networks play a key role in our understanding of the intricate architecture of human brain. Among them, the structural MRI-based brain morphological network approach has attracted increasing attention due to the advantages in data acquisition, image quality, and in revealing the structural organizing principles intrinsic to the brain. This review is to summarize the methodology and related applications of individual-level morphological networks. There have been a growing number of studies related to brain morphological similarity networks. Conventional morphological networks are intersubject covariance networks constructed using a certain morphological indicator of a group of subjects; individual-level morphological networks, on the other hand, measure the morphological similarity between brain regions for individual brains and can reflect the morphological information of single subjects. In recent years, individual morphological networks have demonstrated significant worth in exploring the topological changes of the human brain under both normal and disease conditions. Such studies provided novel perspectives for understanding human brain development and exploring the pathological mechanisms of neuropsychiatric disorders. This paper mainly focuses on the studies of brain morphological networks at the individual level, introduces several ways for network construction, reviews representative work in this field, and finally points out current problems and future directions.

Aims Previous studies have indicated that smoking is linked to an increased risk of developing schizophrenia, and that individuals with schizophrenia are more prone to engaging in antisocial behavior. However, the causal effects of smoking behaviors on antisocial behavior and the potential mediating role of schizophrenia remains largely unclear. Methods In the present study, using the summary data from genome wide association studies of smoking phenotypes (N = 323,386–805,431), schizophrenia (Ncases = 53,386, Ncontrols = 77,258), and antisocial behavior (N = 85,359), we assessed bidirectional causality between smoking phenotypes and schizophrenia by the Mendelian randomization (MR) approach. Using a two‐step MR approach, we further examined whether causal effects of smoking phenotypes/schizophrenia on antisocial behavior were mediated by schizophrenia/smoking phenotypes. Results The results showed that smoking initiation (SmkInit) and age of smoking initiation (AgeSmk) causally increase the risk of schizophrenia (SmkInit: OR = 2.06, 95% CI = 1.77–2.39, p = 4.36 × 10−21; AgeSmk: OR = 0.32, 95% CI = 0.16–0.62, p = 8.11 × 10−4, Bonferroni corrected). However, there was no causal effect that liability to schizophrenia leads to smoking phenotypes. MR evidence also revealed causal influences of SmkInit and the amount smoked (CigDay) on antisocial behavior (SmkInit: OR = 1.28, 95% CI = 1.17–1.41, p = 2.53 × 10−7; CigDay: OR = 1.16, 95% CI = 1.06–1.27, p = 1.60 × 10−3, Bonferroni corrected). Furthermore, the mediation analysis indicated that the relationship between SmkInit and antisocial behavior was partly mediated by schizophrenia (mediated proportion = 6.92%, 95% CI = 0.004–0.03, p = 9.66 × 10−3). Conclusions These results provide compelling evidence for taking smoking interventions as a prevention strategy for schizophrenia and its related antisocial behavior. This study showed that the relationship between smoking initiation and antisocial behavior was partly mediated by schizophrenia using a two‐step Mendelian randomization analysis.

Mild traumatic brain injury (mTBI) often leads to persistent cognitive and emotional symptoms, but the underlying neurobiological mechanisms remain unclear. Although previous studies have reported alterations in resting‐state brain activity in mTBI patients, the findings have been inconsistent, and the genetic basis of these changes has not been fully explored. A coordinate‐based voxel‐wise meta‐analysis was conducted to investigate resting‐state brain activity changes in mTBI, using nine datasets from 374 patients and 302 healthy controls (HCs). Transcription‐neuroimaging association analyses were performed using gene expression data from the Allen Human Brain Atlas (AHBA) to identify genes associated with brain activity alterations. Enrichment analyses were conducted to explore the biological functions of these genes. Compared to HCs, mTBI patients showed increased resting‐state brain activity in the left insula and right fusiform gyrus, and decreased activity in the bilateral middle frontal gyrus. Transcription‐neuroimaging association analyses identified 840 genes significantly correlated with these brain activity changes. Enrichment analyses revealed 15 biological processes significantly associated with the identified genes, primarily involving chemical synaptic transmission, multicellular organism development, and cell–cell signaling. These genes were also enriched in Pnoc+, Ntsr+, and Cort+ neurons and were expressed predominantly from the late fetal to early adulthood stages. Our findings suggest that alterations in resting‐state brain activity in mTBI are linked to specific gene expression patterns, highlighting potential biological pathways involved in mTBI‐related brain changes. This study explores consistent patterns of resting‐state brain activity alterations in patients with mild traumatic brain injury and examines the genetic correlates associated with these neural changes.

Depressive disorder prevalence in patients with schizophrenia has been reported to be 40%. People with low socioeconomic status (SES) are more likely to suffer from schizophrenia and major depressive disorder (MDD). However, the causal relationship between schizophrenia and depression and the potential mediating role of SES remains unclear. Two-sample Mendelian randomization (MR) analyses were conducted to explore the bidirectional causal relationship between schizophrenia and MDD with the largest sample size of European ancestry from public genome-wide association studies (sample size ranged from 130,644 to 480,359). Inverse variance weighted (IVW) method was used as the primary analysis, and several canonical MR methods were used as validation analyses. The mediating role of SES (educational years, household income, employment status, and Townsend deprivation index) was estimated by the two-step MR method. MR analyses showed that genetically predicted schizophrenia was associated with an increased risk of MDD (IVW odds ratio [OR] = 1.137 [95% CI 1.095, 1.181]). Reversely, MDD was also associated with an increased risk of schizophrenia (IVW OR = 1.323 [95% CI 1.118, 1.565]). The mediation analysis via the two-step MR method revealed that the causal effect of schizophrenia on MDD was partly mediated by the Townsend deprivation index with a proportion of 10.27%, but no significant mediation effect was found of SES on the causal effect of MDD on schizophrenia. These results suggest a robust bidirectional causal effect between schizophrenia and MDD. Patients with schizophrenia could benefit from the early and effective intervention of the Townsend deprivation index.

Schizophrenia is a mental health disorder characterized by functional dysconnectivity. Eigenvector centrality mapping (ECM) has been employed to investigate alterations in functional connectivity in schizophrenia, yet the results lack consistency, and the genetic mechanisms underlying these changes remain unclear. In this study, whole-brain voxel-wise ECM analyses were conducted on resting-state functional magnetic resonance imaging data. A cohort of 91 patients with schizophrenia and 91 matched healthy controls were included during the discovery stage. Additionally, in the replication stage, 153 individuals with schizophrenia and 182 healthy individuals participated. Subsequently, a comprehensive analysis was performed using an independent transcriptional database derived from six postmortem healthy adult brains to explore potential genetic factors influencing the observed functional dysconnectivity, and to investigate the roles of identified genes in neural processes and pathways. The results revealed significant and reliable alterations in the ECM across multiple brain regions in schizophrenia. Specifically, there was a significant decrease in ECM in the bilateral superior and middle temporal gyrus, and an increase in the bilateral thalamus in both the discovery and replication stages. Furthermore, transcriptional analysis revealed 420 genes whose expression patterns were related to changes in ECM, and these genes were enriched mainly in biological processes associated with synaptic signaling and transmission. Together, this study enhances our knowledge of the neural processes and pathways involved in schizophrenia, shedding light on the genetic factors that may be linked to functional dysconnectivity in this disorder.

Neuroimaging studies have revealed that patients with schizophrenia exhibit disrupted resting-state functional connectivity. However, the inconsistent findings across these studies have hindered our comprehensive understanding of the functional connectivity changes associated with schizophrenia, and the molecular mechanisms associated with these alterations remain largely unclear. A quantitative meta-analysis was first conducted on 21 datasets, involving 1057 patients and 1186 healthy controls, to examine disrupted resting-state functional connectivity in schizophrenia, as measured by whole-brain voxel-wise functional network centrality (FNC). Subsequently, partial least squares regression analysis was employed to investigate the relationship between FNC changes and gene expression profiles obtained from the Allen Human Brain Atlas database. Finally, gene enrichment analysis was performed to unveil the biological significance of the altered FNC-related genes. Compared with healthy controls, patients with schizophrenia show consistently increased FNC in the right inferior parietal cortex extending to the supramarginal gyrus, angular gyrus, bilateral medial prefrontal cortex, and right dorsolateral prefrontal cortex, while decreased FNC in the bilateral insula, bilateral postcentral gyrus, and right inferior temporal gyrus. Meta-regression analysis revealed that increased FNC in the right inferior parietal cortex was positively correlated with clinical score. In addition, these observed functional connectivity changes were found to be spatially associated with the brain-wide expression of specific genes, which were enriched in diverse biological pathways and cell types. These findings highlight the aberrant functional connectivity observed in schizophrenia and its potential molecular underpinnings, providing valuable insights into the neuropathology of dysconnectivity associated with this disorder.

Schizophrenia, a multifaceted mental disorder characterized by disturbances in thought, perception, and emotion, has been extensively investigated through resting-state fMRI, uncovering changes in spontaneous brain activity among those affected. However, a bibliometric examination regarding publication trends in resting-state fMRI studies related to schizophrenia is lacking. This study obtained relevant publications from the Web of Science Core Collection spanning the period from 1998 to 2022. Data extracted from these publications included information on countries/regions, institutions, authors, journals, and keywords. The collected data underwent analysis and visualization using VOSviewer software. The primary analyses included examination of international and institutional collaborations, authorship patterns, co-citation analyses of authors and journals, as well as exploration of keyword co-occurrence and temporal trend networks. A total of 859 publications were retrieved, indicating an overall growth trend from 1998 to 2022. China and the United States emerged as the leading contributors in both publication outputs and citations, with Central South University and the University of New Mexico being identified as the most productive institutions. Vince D. Calhoun had the highest number of publications and citation counts, while Karl J. Friston was recognized as the most influential author based on co-citations. Key journals such as Neuroimage, Schizophrenia Research, Schizophrenia Bulletin, and Biological Psychiatry played pivotal roles in advancing this field. Recent popular keywords included support vector machine, antipsychotic medication, transcranial magnetic stimulation, and related terms. This study systematically synthesizes the historical development, current status, and future trends in resting-state fMRI research in schizophrenia, offering valuable insights for future research directions.

Mesothelioma (MESO) is an infrequent tumor derived from mesothelial cells of pleura, peritoneum, pericardium, and tunica vaginalis testis. Despite advancement in technologies and better understanding of tumor progression mechanism, the prognosis of MESO remains poor. The role of alternative splicing events (ASEs) in the oncogenesis, tumor metastasis and drug resistance has been widely discussed in multiple cancers. But the prognosis and potential therapeutic value of ASEs in MESO were not clearly studied by now. We constructed a prognostic model using RNA sequencing data and matched ASE data of MESO patients obtained from the TCGA and TCGASpliceSeq database. A total of 3,993 ASEs were identified associated with overall survival using Cox regression analysis. Eight of them were finally figured out to institute the model by lasso regression analysis. The risk score of the model can predict the prognosis independently. Among the identified 390 splicing factors (SF), HSPA1A and DDX3Y was significantly associated with 43 OS‐SEs. Among these OS‐SEs, SNX5‐58744‐AT (p = 0.048) and SNX5‐58745‐AT (p = 0.048) were significantly associated with bone metastasis. Co‐expression analysis of signal pathways and SNX5‐58744‐AT, SNX5‐58745‐AT was also depicted using GSVA. Finally, we proposed that splicing factor (SF) HSPA1A could regulate SNX5‐58744‐AT (R = −0.414) and SNX5‐58745‐AT (R = 0.414) through the pathway “Class I MHC mediated antigen processing and presentation” (R = 0.400). In this way, tumorigenesis and bone metastasis of MESO were controlled. Despite advancement in technologies and better understanding of tumor progression mechanism, the prognosis of Mesothelioma (MESO) remains poor. Alternative splicing events (ASEs) are widely reported in the tumorigenesis, metastasis and drug resistance of multiple cancers. Based on the results of this study, we proposed that splicing factor (SF) HSPA1A could regulate SNX5‐58744‐AT (R = ‐0.414) and SNX5‐58745‐AT through “Class I MHC mediated antigen processing and presentation” pathway and subsequently impact tumorigenesis and bone metastasis of MESO.