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Alterations in cortical thickness have been identified in major depressive disorder (MDD), but findings have been variable and inconsistent. To date, no reliable tools have been available for the meta-analysis of surface-based morphometric (SBM) studies to effectively characterize what has been learned in previous studies, and drug treatments may have differentially impacted findings. We conducted a comprehensive meta-analysis of magnetic resonance imaging (MRI) studies that explored cortical thickness in medication-free patients with MDD, using a newly developed meta-analytic mask compatible with seed-based d mapping (SDM) meta-analytic software. We performed the meta-regression to explore the effects of demographics and clinical characteristics on variation in cortical thickness in MDD. Fifteen studies describing 529 patients and 586 healthy controls (HCs) were included. Medication-free patients with MDD, relative to HCs, showed a complex pattern of increased cortical thickness in some areas (posterior cingulate cortex, ventromedial prefrontal cortex, and anterior cingulate cortex) and decreased cortical thickness in others (gyrus rectus, orbital segment of the superior frontal gyrus, and middle temporal gyrus). Most findings in the whole sample analysis were confirmed in a meta-analysis of studies recruiting medication-naive patients. Using the new mask specifically developed for SBM studies, this SDM meta-analysis provides evidence for regional cortical thickness alterations in MDD, mainly involving increased cortical thickness in the default mode network and decreased cortical thickness in the orbitofrontal and temporal cortex.

For colorectal cancer patients, traditional biomarker deficient mismatch repair/microsatellite instability (dMMR/MSI) is an accurate predictor of immune checkpoint inhibitors (ICIs). Recent years, researchers considered tumor mutation burden (TMB) as another predictive biomarker which means the number of nonsynonymous mutations in cancer cells. Several studies have proven that TMB can evaluate the efficacy of ICI therapy in diverse types of cancer, especially in non-small cell lung cancer and melanoma. However, studies on the association between TMB and the response to ICI therapy in colorectal cancer alone are still lacking. In this study, we aim to verify the effect of TMB as a biomarker in predicting the efficacy of ICIs in colorectal cancer. We searched the PubMed and Ovid MEDLINE databases up to May 1, 2021 and screened studies for eligibility. Thirteen studies published from 2015 to 2021 with 5062 patients were included finally. We extracted and calculated hazard ratios (HRs) and odds ratios (ORs) of overall survival (OS) and objective response rates (ORRs) and their 95% confidence intervals (95% CIs). Pooled HR and OR were evaluated to compare OS and ORR between TMB-high and TMB-low groups in colorectal cancer patients. Meanwhile, we assessed heterogeneity with the statistic and p-values and performed publication bias assessments, sensitivity analyses, and subgroup analyses to search the cause of heterogeneity. The TMB-high patient group had a longer OS than the TMB-low patient group (HR = 0.68, 95% CI: 0.51, 0.92, p = 0.013) among colorectal cancer patients receiving ICIs. In addition, the TMB-high patient group was superior in terms of ORR (OR = 19.25, 95% CI: 10.06, 36.82, p < 0.001) compared to the TMB-low patient group. In conclusion, this meta-analysis revealed that TMB can be used as a potential predictive biomarker of colorectal cancer patients receiving ICI therapy. Nevertheless, this finding is not stable enough. Therefore, many more randomized controlled trials are needed to prove that TMB is reliable enough to be used clinically to predict the efficacy of immunotherapy in colorectal cancer. And the most relevant biomarker remains to be determined when TMB high overlaps with other biomarkers like MSI and TILs.

Abnormal neuroanatomic brain networks have been reported in schizophrenia, but their characterization across patients with psychotic disorders, and their potential alterations in nonpsychotic relatives, remain to be clarified. Participants recruited by the Bipolar and Schizophrenia Network for Intermediate Phenotypes consortium included 326 probands with psychotic disorders (107 with schizophrenia (SZ), 87 with schizoaffective disorder (SAD), 132 with psychotic bipolar disorder (BD)), 315 of their nonpsychotic first-degree relatives and 202 healthy controls. Single-subject gray matter graphs were extracted from structural MRI scans, and whole-brain neuroanatomic organization was compared across the participant groups. Compared with healthy controls, psychotic probands showed decreased nodal efficiency mainly in bilateral superior temporal regions. These regions had altered morphological relationships primarily with frontal lobe regions, and their network-level alterations were associated with positive symptoms of psychosis. Nonpsychotic relatives showed lower nodal centrality metrics in the prefrontal cortex and subcortical regions, and higher nodal centrality metrics in the left cingulate cortex and left thalamus. Diagnosis-specific analysis indicated that individuals with SZ had lower nodal efficiency in bilateral superior temporal regions than controls, probands with SAD only exhibited lower nodal efficiency in the left superior and middle temporal gyrus, and individuals with psychotic BD did not show significant differences from healthy controls. Our findings provide novel evidence of clinically relevant disruptions in the anatomic association of the superior temporal lobe with other regions of whole-brain networks in patients with psychotic disorders, but not in their unaffected relatives, suggesting that it is a disease-related trait. Network disorganization primarily involving frontal lobe and subcortical regions in nonpsychotic relatives may be related to familial illness risk.

Epigenetic modifications are plausible molecular sources of phenotypic heterogeneity across schizophrenia patients. The current study investigated biological heterogeneity in schizophrenia using peripheral epigenetic profiles to delineate illness subtypes independent of their phenomenological manifestations. We applied epigenome-wide profiling with a DNA methylation array from blood samples of 63 schizophrenia patients and 59 healthy controls. Non-negative matrix factorization (NMF) and k-means clustering were performed to identify DNA methylation-related patient subtypes. The validity of the partition was tested by assessing the profile of the T cell receptor (TCR) repertoires. The uniqueness of the identified subtypes in relation to brain structural and clinical measures were evaluated. Two distinct patterns of DNA methylation profiles were identified in patients. One subtype (60.3% of patients) showed relatively limited changes in methylation levels and cell composition compared to controls, while a second subtype (39.7% of patients) exhibited widespread methylation level alterations among genes enriched in immune cell activity, as well as a higher proportion of neutrophils and lower proportion of lymphocytes. Differentiation of the two patient subtypes was validated by TCR repertoires, which paralleled the partition based on DNA methylation profiles. The subtype with widespread methylation modifications had higher symptom severity, performed worse on cognitive measures, and displayed greater reductions in fractional anisotropy of white matter tracts and evidence of gray matter thickening compared to the other subtype. Identification of a distinct subtype of schizophrenia with unique molecular, cerebral, and clinical features provide a novel parcellation of the schizophrenia syndrome with potential to guide development of individualized therapeutics.

The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18–30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.

Background Individuals who have experienced severe traumatic events are estimated to have a post-traumatic stress disorder (PTSD) prevalence rate ranging from 10 to 50%, while those not affected by trauma exposure are often considered to possess psychological resilience. However, the neural mechanisms underlying the development of PTSD, especially resilience after trauma, remain unclear. This study aims to investigate changes of cortical morphometric similarity network (MSN) in PTSD and trauma-exposed healthy individuals (TEHI), as well as the associated molecular alterations in gene expression, providing potential targets for the prevention and intervention of PTSD. Methods We recruited PTSD patients and TEHI who had experienced severe earthquakes, and healthy controls who had not experienced earthquakes. We identified alterations in the whole-brain MSN changes in PTSD and TEHI, and established associations between these changes and brain-wide gene expression patterns from the Allen Human Brain Atlas microarray dataset using partial least squares regression. Results At the neuroimaging level, we found not only trauma-susceptible changes in TEHI same as those in PTSD, but also unique neurobiological alterations to counteract the deleterious impact of severe trauma. We identified 1444 and 2214 genes transcriptionally related to MSN changes in PTSD and TEHI, respectively. Functional enrichment analysis of weighted gene expression for PTSD and TEHI revealed distinct enrichments in Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, gene expression profiles of astrocytes, excitatory neurons, and microglial cells are highly related to MSN abnormalities in PTSD. Conclusions The formation of resilience may be by an active compensatory process of the brain. The combination of macroscopic neuroimaging changes and microscopic human brain transcriptomics could offer a more direct and in-depth understanding of the pathogenesis of PTSD and psychological resilience, shedding light on new targets for the prevention and treatment of PTSD.

Glioblastoma (GBM) is the most common malignant tumor of the central nervous system with poor prognosis. Although the field of immunotherapy in glioma is developing rapidly, glioblastoma is still prone to recurrence under strong immune intervention. The major challenges in the process of immunotherapy are evaluating the curative effect, accurately distinguishing between treatment-related reactions and tumor recurrence, and providing guidance for clinical decision-making. Since the conventional magnetic resonance imaging (MRI) is usually difficult to distinguish between pseudoprogression and the true tumor progression, many studies have used various advanced imaging techniques to evaluate treatment-related responses. Meanwhile, criteria for efficacy evaluation of immunotherapy are constantly updated and improved. A standard imaging scheme to evaluate immunotherapeutic response will benefit patients finally. This review mainly summarizes the application status and future trend of several advanced imaging techniques in evaluating the efficacy of GBM immunotherapy.

Glioblastoma (GBM), one of the most common primary intracranial malignant tumours, is very difficult to be completely excised by surgery due to its irregular shape. Here, we use an MRI/NIR fluorescence dual-modal imaging nanoprobe that includes superparamagnetic iron oxide nanoparticles (SPIONs) modified with indocyanine (Cy7) molecules and peptides (ANG or D ANG) to locate malignant gliomas and guide accurate excision. Both peptides/Cy7-SPIONs probes displayed excellent tumour-homing properties and barrier penetrating abilities in vitro, and both could mediate precise aggregation of the nanoprobes at gliomas sites in in vivo magnetic resonance imaging (MRI) and ex vivo near-infrared (NIR) fluorescence imaging. However, compared with ANG/Cy7-SPIONs probes, D ANG/Cy7-SPIONs probes exhibited better enhanced MR imaging effects. Combining all these features together, this MRI/NIR fluorescence imaging dual-modal nanoprobes modified with retro-enantio isomers of the peptide have the potential to accurately display GBMs preoperatively for precise imaging and intraoperatively for real-time imaging.

The core domains of social anxiety disorder (SAD), generalized anxiety disorder (GAD), panic disorder (PD) with and without agoraphobia (GA), and specific phobia (SP) are cognitive and physical symptoms that are related to the experience of fear and anxiety. It remains unclear whether these highly comorbid conditions that constitute the anxiety disorder subgroups of the Diagnostic and Statistical Manual for Mental Disorders--Fifth Edition (DSM-5) represent distinct disorders or alternative presentations of a single underlying pathology. A systematic search of voxel-based morphometry (VBM) studies of SAD, GAD, PD, GA, and SP was performed with an effect-size signed differential mapping (ES-SDM) meta-analysis to estimate the clusters of significant gray matter differences between patients and controls. Twenty-four studies were eligible for inclusion in the meta-analysis. Reductions in the right anterior cingulate gyrus and the left inferior frontal gyrus gray matter volumes (GMVs) were noted in patients with anxiety disorders when potential confounders, such as comorbid major depressive disorder (MDD), age, and antidepressant use were controlled for. We also demonstrated increased GMVs in the right dorsolateral prefrontal cortex (DLPFC) in comorbid depression-anxiety (CDA), drug-naïve and adult patients. Furthermore, we identified a reduced left middle temporal gyrus and right precentral gyrus in anxiety patients without comorbid MDD. Our findings indicate that a reduced volume of the right ventral anterior cingulate gyrus and left inferior frontal gyrus is common in anxiety disorders and is independent of comorbid depression, medication use, and age. This generic effect supports the notion that the four types of anxiety disorders have a clear degree of overlap that may reflect shared etiological mechanisms. The results are consistent with neuroanatomical DLPFC models of physiological responses, such as worry and fear, and the importance of the ventral anterior cingulate (ACC)/medial prefrontal cortex (mPFC) in mediating anxiety symptoms.

Abstract It has previously been shown that cerebello-thalamo-cortical (CTC) hyperconnectivity is likely a state-independent neural signature for psychosis. However, the potential clinical utility of this change has not yet been evaluated. Here, using fMRI and clinical data acquired from 214 untreated first-episode patients with schizophrenia (62 of whom were clinically followed-up at least once at the 12th and 24th months after treatment initiation) and 179 healthy controls, we investigated whether CTC hyperconnectivity would serve as an individualized biomarker for diagnostic classification and prediction of long-term treatment outcome. Cross-validated LASSO regression was conducted to estimate the accuracy of baseline CTC connectivity for patient-control classification, with the generalizability of classification performance tested in an independent sample including 42 untreated first-episode patients and 65 controls. Associations between baseline CTC connectivity and clinical outcomes were evaluated using linear mixed model and leave-one-out cross validation. We found significantly increased baseline CTC connectivity in patients (P = .01), which remained stable after treatment. Measures of CTC connectivity discriminated patients from controls with moderate classification accuracy (AUC = 0.68, P < .001), and the classification model had good generalizability in the independent sample (AUC = 0.70, P < .001). Higher CTC connectivity at baseline significantly predicted poorer long-term symptom reduction in negative symptoms (R = 0.31, P = .01) but not positive or general symptoms. These findings provide initial evidence for the putative “CTC hyperconnectivity” anomaly as an individualized diagnostic and prognostic biomarker for schizophrenia, and highlight the potential of this measure in precision psychiatry.