Polygenic effects of schizophrenia on hippocampal grey matter volume and hippocampus-medial prefrontal cortex functional connectivity

Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives

Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.

Relations of Lifetime Perceived Stress and Basal Cortisol With Hippocampal Volume Among Healthy Adolescents and Those at Clinical High Risk for Psychosis: A Structural Equation Modeling Approach

BACKGROUND

Hippocampal volume (HV) is sensitive to environmental influences. Under normative conditions in humans, HV increases linearly into childhood and asymptotes in early adulthood. Studies of humans and nonhuman animals have provided evidence of inverse relationships between several measures of stress and HV.

METHODS

Using structural equation modeling, this study aimed to characterize the relationships of age, basal cortisol, biological sex, and lifetime perceived stress with bilateral HV in a sample of healthy adolescents and adolescents at clinical high risk for psychosis (CHR-P) (N = 571, 43% female; age range = 12-19.9 years). This sample included 469 individuals at CHR-P and 102 healthy comparison participants from the combined baseline cohorts of the second and third NAPLS (North American Prodrome Longitudinal Study).

RESULTS

A structural model that constrained the individual effects of basal cortisol and perceived stress to single path coefficients, and freely estimated the effects of age and biological sex in group models, optimized model fit and parsimony relative to other candidate models. Significant inverse relationships between basal cortisol and bilateral HV were observed in adolescents at CHR-P and healthy comparison participants. Significant sex differences in bilateral HV were also observed, with females demonstrating smaller HV than males in both groups.

CONCLUSIONS

Multigroup structural equation modeling revealed heterogeneity in the relationships of age and biological sex with basal cortisol, lifetime perceived stress, and bilateral HV in individuals at CHR-P and healthy comparison participants. Moreover, the findings support previous literature indicating that elevated basal cortisol is a nonspecific risk factor for reduced HV.

Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years.

STUDY DESIGN

The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade.

STUDY RESULTS

Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders.

CONCLUSIONS

We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.

Videogame training increases clinical well-being, attention and hippocampal-prefrontal functional connectivity in patients with schizophrenia

Recent research shows that videogame training enhances neuronal plasticity and cognitive improvements in healthy individuals. As patients with schizophrenia exhibit reduced neuronal plasticity linked to cognitive deficits and symptoms, we investigated whether videogame-related cognitive improvements and plasticity changes extend to this population. In a training study, patients with schizophrenia and healthy controls were randomly assigned to 3D or 2D platformer videogame training or E-book reading (active control) for 8 weeks, 30 min daily. After training, both videogame conditions showed significant increases in sustained attention compared to the control condition, correlated with increased functional connectivity in a hippocampal-prefrontal network. Notably, patients trained with videogames mostly improved in negative symptoms, general psychopathology, and perceived mental health recovery. Videogames, incorporating initiative, goal setting and gratification, offer a training approach closer to real life than current psychiatric treatments. Our results provide initial evidence that they may represent a possible adjunct therapeutic intervention for complex mental disorders.

Relationship between SLC6A2 gene polymorphisms and brain volume in Han Chinese adults who lost their sole child

BACKGROUND

Norepinephrine transporter (NET) is encoded by the SLC6A2 gene and is a potential target for studying the pathogenesis of PTSD. To the best of our knowledge, no prior investigations have examined SLC6A2 polymorphism-related neuroimaging abnormalities in PTSD patients.

METHODS

In 218 Han Chinese adults who had lost their sole child, we investigated the association between the T-182 C SLC6A2 genotype and gray matter volume (GMV). Participants included 57 PTSD sufferers and 161 non-PTSD sufferers, and each group was further separated into three subgroups based on each participant's SLC6A2 genotype (TT, CT, and CC). All participants received magnetic resonance imaging (MRI) and clinical evaluation. To assess the effects of PTSD diagnosis, genotype, and genotype × diagnosis interaction on GMV, 2 × 3 full factorial designs were used. Pearson's correlations were used to examine the association between GMV and CAPS, HAMD, and HAMA.

RESULTS

The SLC6A2 genotype showed significant main effects on GMV of the left superior parietal gyrus (SPG) and the bilateral middle cingulate gyrus (MCG). Additionally, impacts of the SLC6A2 genotype-diagnosis interaction were discovered in the left superior frontal gyrus (SFG). The CAPS, HAMA, and HAMD scores, as well as the genotype main effect and diagnostic SLC6A2 interaction, did not significantly correlate with each other.

CONCLUSION

These findings indicate a modulatory effect that the SLC6A2 polymorphism exerts on the SPG and MCG, irrespective of PTSD diagnosis. We found evidence to suggest that the SLC6A2 genotype-diagnosis interaction on SFG may potentially contribute to PTSD pathogenesis in adults who lost their sole child.

Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review

BACKGROUND AND HYPOTHESIS

Schizophrenia is highly heritable, with a polygenic effect of many genes conferring risk. Evidence on whether cumulative risk also predicts alterations in brain morphology and function is inconsistent. This systematic review examined evidence for schizophrenia polygenic risk score (sczPRS) associations with commonly used magnetic resonance imaging (MRI) measures. We expected consistent evidence to emerge for significant sczPRS associations with variation in structure and function, specifically in frontal, temporal, and insula cortices that are commonly implicated in schizophrenia pathophysiology.

STUDY DESIGN

In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE, Embase, and PsycINFO for peer-reviewed studies published between January 2013 and March 2022. Studies were screened against predetermined criteria and National Institutes of Health (NIH) quality assessment tools.

STUDY RESULTS

In total, 57 studies of T1-weighted structural, diffusion, and functional MRI were included (age range = 9-80 years, Nrange = 64-76 644). We observed moderate, albeit preliminary, evidence for higher sczPRS predicting global reductions in cortical thickness and widespread variation in functional connectivity, and to a lesser extent, region-specific reductions in frontal and temporal volume and thickness. Conversely, sczPRS does not predict whole-brain surface area or gray/white matter volume. Limited evidence emerged for sczPRS associations with diffusion tensor measures of white matter microstructure in a large community sample and smaller cohorts of children and young adults. These findings were broadly consistent across community and clinical populations.

CONCLUSIONS

Our review supports the hypothesis that schizophrenia is a disorder of disrupted within and between-region brain connectivity, and points to specific whole-brain and regional MRI metrics that may provide useful intermediate phenotypes.

Hippocampal Connectivity with the Default Mode Network is Linked to Hippocampal Volume in the Clinical High Risk for Psychosis Syndrome and Healthy Individuals

Reduced hippocampal volume (HV) is an established brain morphological feature of psychiatric conditions. HV is associated with brain connectivity in humans and non-human animals and altered connectivity is associated with risk for psychiatric illness. Associations between HV and connectivity remain poorly characterized in humans, and especially in phases of psychiatric illness that precede disease onset. This study examined associations between HV and hippocampal functional connectivity (FC) during rest in 141 healthy controls and 248 individuals at-risk for psychosis. Significant inverse associations between HV and hippocampal FC with the inferior parietal lobe (IPL) and thalamus were observed. Select associations between hippocampal FC and HV were moderated by diagnostic group. Significant moderation results shifted from implicating the IPL to the temporal pole after excluding participants on antipsychotic medication. Considered together, this work implicates hippocampal FC with the temporoparietal junction, within a specialized subsystem of the default mode network, as sensitive to HV.

Altered MANF and RYR2 concentrations associated with hypolipidemia in the serum of patients with schizophrenia

Schizophrenia (SCZ) is associated with abnormal serum lipid profiles, but their relationship is poorly understood. Mesencephalic astrocyte-derived neurotrophic factor (MANF) is an important regulator of lipid metabolism. Previous studies have shown its involvement in the pathogenesis of numerous neuropsychiatric disorders, while its role in SCZ is still unknown. Therefore, this study was conducted to examine serum MANF levels in patients with SCZ, and to investigate the potential relationship between MANF, serum lipid levels and SCZ. The results showed that total cholesterol (TC) levels were significantly lower in 225 patients with SCZ than in 233 healthy controls (HCs). According to Ingenuity Pathway Analysis, hypolipidemia is associated with SCZ via MANF/ryanodine receptor 2 (RYR2) pathway. This theory was supported by another sample set, which showed significantly lower MANF levels and higher RYR2 levels in the serum of 170 SCZ patients compared to 80 HCs. Moreover, MANF and RYR2 levels both were significantly correlated with the severity of psychotic symptoms and TC levels. In addition, a model consisting of MANF and RYR2 was found to be effective in distinguishing SCZ patients from HCs. These findings suggested that the MANF/RYR2 pathway might serve as a bridge between hypolipidemia and SCZ, and MANF and RYR2 held promise as biomarkers for SCZ.

Impaired large-scale cortico-hippocampal network connectivity, including the anterior temporal and posterior medial systems, and its associations with cognition in patients with first-episode schizophrenia

Background and objective

The cortico-hippocampal network is an emerging neural framework with striking evidence that it supports cognition in humans, especially memory; this network includes the anterior temporal (AT) system, the posterior medial (PM) system, the anterior hippocampus (aHIPPO), and the posterior hippocampus (pHIPPO). This study aimed to detect aberrant patterns of functional connectivity within and between large-scale cortico-hippocampal networks in first-episode schizophrenia patients compared with a healthy control group via resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the correlations of these aberrant patterns with cognition.

Methods

A total of 86 first-episode, drug-naïve schizophrenia patients and 102 healthy controls (HC) were recruited to undergo rs-fMRI examinations and clinical evaluations. We conducted large-scale edge-based network analysis to characterize the functional architecture of the cortico-hippocampus network and investigate between-group differences in within/between-network functional connectivity. Additionally, we explored the associations of functional connectivity (FC) abnormalities with clinical characteristics, including scores on the Positive and Negative Syndrome Scale (PANSS) and cognitive scores.

Results

Compared with the HC group, schizophrenia patients exhibited widespread alterations to within-network FC of the cortico-hippocampal network, with decreases in FC involving the precuneus (PREC), amygdala (AMYG), parahippocampal cortex (PHC), orbitofrontal cortex (OFC), perirhinal cortex (PRC), retrosplenial cortex (RSC), posterior cingulate cortex (PCC), angular gyrus (ANG), aHIPPO, and pHIPPO. Schizophrenia patients also showed abnormalities in large-scale between-network FC of the cortico-hippocampal network, in the form of significantly decreased FC between the AT and the PM, the AT and the aHIPPO, the PM and the aHIPPO, and the aHIPPO and the pHIPPO. A number of these signatures of aberrant FC were correlated with PANSS score (positive, negative, and total score) and with scores on cognitive test battery items, including attention/vigilance (AV), working memory (WM), verbal learning and memory (Verb_Lrng), visual learning and memory (Vis_Lrng), reasoning and problem-solving (RPS), and social cognition (SC).

Conclusion

Schizophrenia patients show distinct patterns of functional integration and separation both within and between large-scale cortico-hippocampal networks, reflecting a network imbalance of the hippocampal long axis with the AT and PM systems, which regulate cognitive domains (mainly Vis_Lrng, Verb_Lrng, WM, and RPS), and particularly involving alterations to FC of the AT system and the aHIPPO. These findings provide new insights into the neurofunctional markers of schizophrenia.

Effects of polygenic risk of schizophrenia on interhemispheric callosal white matter integrity and frontotemporal functional connectivity in first-episode schizophrenia

BACKGROUND

Schizophrenia is a severely debilitating psychiatric disorder with high heritability and polygenic architecture. A higher polygenic risk score for schizophrenia (SzPRS) has been associated with smaller gray matter volume, lower activation, and decreased functional connectivity (FC). However, the effect of polygenic inheritance on the brain white matter microstructure has only been sparsely reported.

METHODS

Eighty-four patients with first-episode schizophrenia (FES) patients and ninety-three healthy controls (HC) with genetics, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI) data were included in our study. We investigated impaired white matter integrity as measured by fractional anisotropy (FA) in the FES group, further examined the effect of SzPRS on white matter FA and FC in the regions connected by SzPRS-related white matter tracts.

RESULTS

Decreased FA was observed in FES in many commonly identified regions. Among these regions, we observed that in the FES group, but not the HC group, SzPRS was negatively associated with the mean FA in the genu and body of corpus callosum, right anterior corona radiata, and right superior corona radiata. Higher SzPRS was also associated with lower FCs between the left inferior frontal gyrus (IFG)-left inferior temporal gyrus (ITG), right IFG-left ITG, right IFG-left middle frontal gyrus (MFG), and right IFG-right MFG in the FES group.

CONCLUSION

Higher polygenic risks are linked with disrupted white matter integrity and FC in patients with schizophrenia. These correlations are strongly driven by the interhemispheric callosal fibers and the connections between frontotemporal regions.

Polygenic Risk for Schizophrenia, Major Depression, and Post-traumatic Stress Disorder and Hippocampal Subregion Volumes in Middle Childhood

Studies demonstrate that individuals with diagnoses for Major Depressive Disorder (MDD), Post-traumatic Stress Disorder (PTSD), and Schizophrenia (SCZ) may exhibit smaller hippocampal gray matter relative to otherwise healthy controls, although the effect sizes vary in each disorder. Existing work suggests that hippocampal abnormalities in each disorder may be attributable to genetic liability and/or environmental variables. The following study uses baseline data from the Adolescent Brain and Cognitive Development[Formula: see text] Study (ABCD Study[Formula: see text]) to address three open questions regarding the relationship between genetic risk for each disorder and hippocampal volume reductions: (a) whether polygenic risk scores (PGRS) for MDD, PTSD, and SCZ are related to hippocampal volume; (b) whether PGRS for MDD, PTSD, and SCZ are differentially related to specific hippocampal subregions along the longitudinal axis; and (c) whether the association between PGRS for MDD, PTSD, and SCZ and hippocampal volume is moderated by sex and/or environmental adversity. In short, we did not find associations between PGRS for MDD, PTSD, and SCZ to be significantly related to any hippocampal subregion volumes. Furthermore, neither sex nor enviornmental adversity significantly moderated these associations. Our study provides an important null finding on the relationship genetic risk for MDD, PTSD, and SCZ to measures of hippocampal volume.

Glutamate dehydrogenase: Potential therapeutic targets for neurodegenerative disease

Glutamate dehydrogenase (GDH) is a key enzyme in mammalian glutamate metabolism. It is located at the intersection of multiple metabolic pathways and participates in a variety of cellular activities. GDH activity is strictly regulated by a variety of allosteric compounds. Here, we review the unique distribution and expressions of GDH in the brain nervous system. GDH plays an essential role in the glutamate-glutamine-GABA cycle between astrocytes and neurons. The dysfunction of GDH may induce the occurrence of many neurodegenerative diseases, such as Parkinson's disease, epilepsy, Alzheimer's disease, schizophrenia, and frontotemporal dementia. GDH activators and gene therapy have been found to protect neurons and improve motor disorders in neurodegenerative diseases caused by glutamate metabolism disorders. To date, no medicine has been discovered that specifically targets neurodegenerative diseases, although several potential medicines are used clinically. Targeting GDH to treat neurodegenerative diseases is expected to provide new insights and treatment strategies.

Brain Structure and Function Show Distinct Relations With Genetic Predispositions to Mental Health and Cognition

BACKGROUND

Mental health and cognitive achievement are partly heritable, highly polygenic, and associated with brain variations in structure and function. However, the underlying neural mechanisms remain unclear.

METHODS

We investigated the association between genetic predispositions to various mental health and cognitive traits and a large set of structural and functional brain measures from the UK Biobank (N = 36,799). We also applied linkage disequilibrium score regression to estimate the genetic correlations between various traits and brain measures based on genome-wide data. To decompose the complex association patterns, we performed a multivariate partial least squares model of the genetic and imaging modalities.

RESULTS

The univariate analyses showed that certain traits were related to brain structure (significant genetic correlations with total cortical surface area from r_g = -0.101 for smoking initiation to r_g = 0.230 for cognitive ability), while other traits were related to brain function (significant genetic correlations with functional connectivity from r_g = -0.161 for educational attainment to r_g = 0.318 for schizophrenia). The multivariate analysis showed that genetic predispositions to attention-deficit/hyperactivity disorder, smoking initiation, and cognitive traits had stronger associations with brain structure than with brain function, whereas genetic predispositions to most other psychiatric disorders had stronger associations with brain function than with brain structure.

CONCLUSIONS

These results reveal that genetic predispositions to mental health and cognitive traits have distinct brain profiles.

Domesticated HERV-W env contributes to the activation of the small conductance Ca2+-activated K+ type 2 channels via decreased 5-HT4 receptor in recent-onset schizophrenia

The human endogenous retroviruses type W family envelope (HERV-W env) gene is located on chromosome 7q21-22. Our previous studies show that HERV-W env is elevated in schizophrenia and HERV-W env can increase calcium influx. Additionally, the 5-HTergic system and particularly 5-hydroxytryptamine (5-HT) receptors play a prominent role in the pathogenesis and treatment of schizophrenia. 5-hydroxytryptamine receptor 4 (5-HT4R) agonist can block calcium channels. However, the underlying relationship between HERV-W env and 5-HT4R in the etiology of schizophrenia has not been revealed. Here, we used enzyme-linked immunosorbent assay to detect the concentration of HERV-W env and 5-HT4R in the plasma of patients with schizophrenia and we found that there were decreased levels of 5-HT4R and a negative correlation between 5-HT4R and HERV-W env in schizophrenia. Overexpression of HERV-W env decreased the transcription and protein levels of 5-HT4R but increased small conductance Ca²⁺-activated K⁺ type 2 channels (SK2) expression levels. Further studies revealed that HERV-W env could interact with 5-HT4R. Additionally, luciferase assay showed that an essential region (-364 to -176 from the transcription start site) in the SK2 promoter was required for HERV-W env-induced SK2 expression. Importantly, 5-HT4R participated in the regulation of SK2 expression and promoter activity. Electrophysiological recordings suggested that HERV-W env could increase SK2 channel currents and the increase of SK2 currents was inhibited by 5-HT4R. In conclusion, HERV-W env could activate SK2 channels via decreased 5-HT4R, which might exhibit a novel mechanism for HERV-W env to influence neuronal activity in schizophrenia.

The neural signatures of psychoses in Alzheimer's disease: a neuroimaging genetics approach

Psychoses in Alzheimer's disease (AD) are associated with worse prognosis. Genetic vulnerability for schizophrenia (SCZ) may drive AD-related psychoses, yet its impact on brain constituents is still unknown. This study aimed to investigate the association between polygenic risk scores (PRSs) for SCZ and psychotic experiences (PE) and grey matter (GM) volume in patients with AD with (AD-PS) and without (AD-NP) psychosis. Clinical, genetic and T1-weighted MRI data for 800 participants were extracted from the ADNI database: 203 healthy controls, 121 AD-PS and 476 AD-NP. PRSs were calculated using a Bayesian approach and analysed at ten p-value thresholds. Standard voxel-based morphometry was used to process MRI data. Logistic regression models including both PRSs for SCZ and PE, and an AD-PRS were used to predict psychosis in AD. Associations between PRSs and GM volume were investigated in the whole sample and the three groups independently. Only the AD-PRS predicted psychosis in AD. Inconsistent associations between the SCZ-PRS and PE-PRS and GM volumes were found across groups. The SCZ-PRS was negatively associated with medio-temporal/subcortical volumes and positively with medial/orbitofrontal volumes in the AD-PS group. Only medio-temporal areas were more atrophic in the AD-PS group, while there was no significant correlation between psychosis severity and GM volume. Although not associated with psychoses, the SCZ-PRS was correlated with smaller medio-temporal and larger orbitofrontal volumes in AD-PS. Similar alterations have also been observed in SCZ patients. This finding suggest a possible disconnection between these regions associated with psychoses in more advanced AD.

Decreased Oligodendrocyte Number in Hippocampal Subfield CA4 in Schizophrenia: A Replication Study

Hippocampus-related cognitive deficits in working and verbal memory are frequent in schizophrenia, and hippocampal volume loss, particularly in the cornu ammonis (CA) subregions, was shown by magnetic resonance imaging studies. However, the underlying cellular alterations remain elusive. By using unbiased design-based stereology, we reported a reduction in oligodendrocyte number in CA4 in schizophrenia and of granular neurons in the dentate gyrus (DG). Here, we aimed to replicate these findings in an independent sample. We used a stereological approach to investigate the numbers and densities of neurons, oligodendrocytes, and astrocytes in CA4 and of granular neurons in the DG of left and right hemispheres in 11 brains from men with schizophrenia and 11 brains from age- and sex-matched healthy controls. In schizophrenia, a decreased number and density of oligodendrocytes was detected in the left and right CA4, whereas mean volumes of CA4 and the DG and the numbers and density of neurons, astrocytes, and granular neurons were not different in patients and controls, even after adjustment of variables because of positive correlations with postmortem interval and age. Our results replicate the previously described decrease in oligodendrocytes bilaterally in CA4 in schizophrenia and point to a deficit in oligodendrocyte maturation or a loss of mature oligodendrocytes. These changes result in impaired myelination and neuronal decoupling, both of which are linked to altered functional connectivity and subsequent cognitive dysfunction in schizophrenia.

The Association Between Neighborhood Poverty and Hippocampal Volume Among Individuals at Clinical High-Risk for Psychosis: The Moderating Role of Social Engagement

Reductions in hippocampal volume (HV) have been associated with both prolonged exposure to stress and psychotic illness. This study sought to determine whether higher levels of neighborhood poverty would be associated with reduced HV among individuals at clinical high-risk for psychosis (CHR-P), and whether social engagement would moderate this association. This cross-sectional study included a sample of participants (N  =  174, age-range = 12-33 years, 35.1% female) recruited for the second phase of the North American Prodrome Longitudinal Study. Generalized linear mixed models tested the association between neighborhood poverty and bilateral HV, as well as the moderating role of social engagement on this association. Higher levels of neighborhood poverty were associated with reduced left (β  =  -0.180, P  =  .016) and right HV (β  =  -0.185, P  =  .016). Social engagement significantly moderated the relation between neighborhood poverty and bilateral HV. In participants with lower levels of social engagement (n  =  77), neighborhood poverty was associated with reduced left (β  =  -0.266, P  =  .006) and right HV (β = -0.316, P  = .002). Among participants with higher levels of social engagement (n = 97), neighborhood poverty was not significantly associated with left (β  =  -0.010, P  =  .932) or right HV (β  =  0.087, P  =  .473). In this study, social engagement moderated the inverse relation between neighborhood poverty and HV. These findings demonstrate the importance of including broader environmental influences and indices of social engagement when conceptualizing adversity and potential interventions for individuals at CHR-P.

The effect of polygenic risk scores for major depressive disorder, bipolar disorder and schizophrenia on morphological brain measures: A systematic review of the evidence

BACKGROUND

Major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SCZ) share clinical features and genetic bases. Magnetic Resonance Imaging (MRI) studies assessing the effect of polygenic risk score (PRS) for psychiatric disorders on brain structure show heterogeneous results. Therefore, we provided an overview of the existing evidence on the association between PRS for MDD, BD and SCZ and MRI abnormalities in clinical and healthy populations.

METHODS

A search on PubMed, Web of Science and Scopus was performed to identify the studies exploring the effect of PRS for MDD, BD and SCZ on MRI measures. A total of 25 studies were included (N = 13 on healthy individuals and N = 12 on clinical populations).

RESULTS

Both in affected and unaffected individuals, PRS for BD and SCZ showed either positive or negative correlations with cortical thickness (CT), mostly involving fronto-temporal areas, whereas PRS for MDD was associated with cortical alterations in prefrontal regions in healthy subjects.

LIMITATIONS

The heterogeneity in the methods limits the conclusions of this review.

CONCLUSIONS

Overall the evidence on the effect of PRS for MDD, BD and SCZ on brain is considerably heterogeneous and far to be conclusive. However, from the results emerged that PRS for MDD, BD and SCZ were associated with widespread cortical abnormalities in all the populations explored, suggesting that genetic risk for MDD, BD and SCZ might affect neurodevelopmental processes, resulting in cortical alterations that transcend diagnostic boundaries and seem to be independent from the clinical status.

Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer's disease

The roles of brain regions activities and gene expressions in the development of Alzheimer's disease (AD) remain unclear. Existing imaging genetic studies usually has the problem of inefficiency and inadequate fusion of data. This study proposes a novel deep learning method to efficiently capture the development pattern of AD. First, we model the interaction between brain regions and genes as node-to-node feature aggregation in a brain region-gene network. Second, we propose a feature aggregation graph convolutional network (FAGCN) to transmit and update the node feature. Compared with the trivial graph convolutional procedure, we replace the input from the adjacency matrix with a weight matrix based on correlation analysis and consider common neighbor similarity to discover broader associations of nodes. Finally, we use a full-gradient saliency graph mechanism to score and extract the pathogenetic brain regions and risk genes. According to the results, FAGCN achieved the best performance among both traditional and cutting-edge methods and extracted AD-related brain regions and genes, providing theoretical and methodological support for the research of related diseases.

Pathogeny Detection for Mild Cognitive Impairment via Weighted Evolutionary Random Forest with Brain Imaging and Genetic Data

Medical imaging technology and gene sequencing technology have long been widely used to analyze the pathogenesis and make precise diagnoses of mild cognitive impairment (MCI). However, few studies involve the fusion of radiomics data with genomics data to make full use of the complementarity between different omics to detect pathogenic factors of MCI. This paper performs multimodal fusion analysis based on functional magnetic resonance imaging (fMRI) data and single nucleotide polymorphism (SNP) data of MCI patients. In specific, first, using correlation analysis methods on sequence information of regions of interests (ROIs) and digitalized gene sequences, the fusion features of samples are constructed. Then, introducing weighted evolution strategy into ensemble learning, a novel weighted evolutionary random forest (WERF) model is built to eliminate the inefficient features. Consequently, with the help of WERF, an overall multimodal data analysis framework is established to effectively identify MCI patients and extract pathogenic factors. Based on the data of MCI patients from the ADNI database and compared with some existing popular methods, the superiority in performance of the framework is verified. Our study has great potential to be an effective tool for pathogenic factors detection of MCI.

A Pathway-Specific Polygenic Risk Score is Associated with Tau Pathology and Cognitive Decline

Background: Tauopathy is a primary neuropathological hallmark of Alzheimer’s disease with a strong relationship to cognitive impairment. In the brain, tau aggregation is associated with the regulation of tau kinases and the binding ability of tau to microtubules. Objective: To explore the potential for using specific polygenic risk scores (PRSs), combining the genetic influences involved in tau-protein kinases and the tau-protein binding pathway, as predictors of tau pathology and cognitive decline in non-demented individuals. Methods: We computed a pathway-specific PRS using summary statistics from previous large-scale genome-wide association studies of dementia. We examined whether PRS is related to tau uptake in positron emission tomography (PET), tau levels, and the rate of tau level changes in cerebrospinal fluid (CSF). We further assessed whether PRS is associated with memory impairment mediated by CSF tau levels. Results: A higher PRS was related to elevated CSF tau levels and tau-PET uptake at baseline, as well as greater rates of change in CSF tau levels. Moreover, PRS was associated with memory impairment, mediated by increased CSF tau levels. The association between PRS and tau pathology was significant when APOE was excluded, even among females. However, the effect of PRS on cognitive decline appeared to be driven by the inclusion of APOE. Conclusion: The influence of genetic risk in a specific tau-related biological pathway may make an individual more susceptible to tau pathology, resulting in cognitive dysfunction in an early preclinical phase of the disease.

Multisite schizophrenia classification by integrating structural magnetic resonance imaging data with polygenic risk score

Previous brain structural magnetic resonance imaging studies reported that patients with schizophrenia have brain structural abnormalities, which have been used to discriminate schizophrenia patients from normal controls. However, most existing studies identified schizophrenia patients at a single site, and the genetic features closely associated with highly heritable schizophrenia were not considered. In this study, we performed standardized feature extraction on brain structural magnetic resonance images and on genetic data to separate schizophrenia patients from normal controls. A total of 1010 participants, 508 schizophrenia patients and 502 normal controls, were recruited from 8 independent sites across China. Classification experiments were carried out using different machine learning methods and input features. We tested a support vector machine, logistic regression, and an ensemble learning strategy using 3 feature sets of interest: (1) imaging features: gray matter volume, (2) genetic features: polygenic risk scores, and (3) a fusion of imaging features and genetic features. The performance was assessed by leave-one-site-out cross-validation. Finally, some important brain and genetic features were identified. We found that the models with both imaging and genetic features as input performed better than models with either alone. The average accuracy of the classification models with the best performance in the cross-validation was 71.6%. The genetic feature that measured the cumulative risk of the genetic variants most associated with schizophrenia contributed the most to the classification. Our work took the first step toward considering both structural brain alterations and genome-wide genetic factors in a large-scale multisite schizophrenia classification. Our findings may provide insight into the underlying pathophysiology and risk mechanisms of schizophrenia.

Nonclinical psychotic-like experiences and schizotypy dimensions: Associations with hippocampal subfield and amygdala volumes

Schizotypy and psychotic-like experiences (PLE) form part of the wider psychosis continuum and may have brain structural correlates in nonclinical cohorts. This study aimed to compare the effects of differential schizotypy dimensions, PLE, and their interaction on hippocampal subfields and amygdala volumes in the absence of clinical psychopathology. In a cohort of 367 psychiatrically healthy individuals, we assessed schizotypal traits using the Oxford-Liverpool Inventory of Life Experiences (O-LIFE) and PLE using the short form of the Prodromal Questionnaire (PQ-16). Based on high-resolution structural MRI scans, we used automated segmentation to estimate volumes of limbic structures. Sex and total intracranial volume (Step 1), PLE and schizotypy dimensions (Step 2), and their interaction terms (Step 3) were entered as regressors for bilateral amygdala and hippocampal subfield volumes in hierarchical multiple linear regression models. Positive schizotypy, but not PLE, was negatively associated with left amygdala and subiculum volumes. O-LIFE Impulsive Nonconformity, as well as the two-way interaction between positive schizotypy and PLE, were associated with larger left subiculum volumes. None of the estimators for right hemispheric hippocampal subfield volumes survived correction for multiple comparisons. Our findings support differential associations of hippocampus subfield volumes with trait dimensions rather than PLE, and support overlap and interactions between psychometric positive schizotypy and PLE. In a healthy cohort without current psychosis risk syndromes, the positive association between PLE and hippocampal subfield volume occurred at a high expression of positive schizotypy. Further studies combining stable, transient, and genetic parameters are required.

Functional connectome-wide associations of schizophrenia polygenic risk

Schizophrenia is a highly heritable mental disorder characterized by functional dysconnectivity across the brain. However, the relationships between polygenic risk factors and connectome-wide neural mechanisms are unclear. Here, combining genetic and multiparadigm fMRI data of 623 healthy Caucasian adults drawn from the Human Connectome Project, we found that higher schizophrenia polygenic risk scores were significantly correlated with lower functional connectivity in a large-scale brain network primarily encompassing the visual system, default-mode system, and frontoparietal system. Such correlation was robustly observed across multiple fMRI paradigms, suggesting a brain-state-independent neural phenotype underlying individual genetic liability to schizophrenia. Moreover, using an independent clinical dataset acquired from the Consortium for Neuropsychiatric Phenomics, we further demonstrated that the connectivity of the identified network was reduced in patients with schizophrenia and significantly correlated with general cognitive ability. These findings provide the first evidence for connectome-wide associations of schizophrenia polygenic risk at the systems level and suggest that disrupted integration of sensori-cognitive information may be a hallmark of genetic effects on the brain that contributes to the pathogenesis of schizophrenia.

Low-Frequency Magnetic Stimulation of Shenmen Acupoint Reduces Blood Oxygen Levels in the Prefrontal Cortex of Healthy Subjects: A Near-Infrared Brain Functional Imaging Study

OBJECTIVE

To explore the effect of low-frequency magnetic stimulation at Shenmen (HT 7) acupoint on blood oxygen levels in the prefrontal cortex of healthy subjects.

METHODS

Functional near-infrared spectroscopy (fNIRS) technology was used to collect real-time data of oxygenated hemoglobin (oxy-Hb) in the prefrontal cortex of 16 healthy subjects at resting state and low-frequency magnetic stimulation of Shenmen. The mean and integral values of blood oxygen concentration were analyzed.

RESULTS

Compared with the resting state, the mean and integral values of blood oxygen concentration were decreased during the task period, recovery period, and the whole process in the magnetic stimulation of Shenmen acupoint (P<0.05). In particular, the difference was statistically significant in the recovery period (P<0.01).

CONCLUSIONS

The prefrontal cortex was widely activated and produced an immediate effect by reducing the local blood oxygen concentration at low-frequency magnetic stimulation of Shenmen acupoint, which verifies the sedative effect of Shenmen acupoint.

Serotonin modulation of hippocampal functions: From anatomy to neurotherapeutics

The hippocampal region receives a dense serotoninergic innervation originating from both medial and dorsal raphe nuclei. This innervation regulates hippocampal activity through the activation of distinct receptor families that are expressed in excitatory and inhibitory neurons, terminals of several afferent neurotransmitter systems, and glial cells. Preclinical and clinical studies indicate that hippocampal dysfunctions are involved in learning and memory deficits, dementia, Alzheimer's disease, epilepsy and mood disorders such as anxiety, depression and post-traumatic syndrome disorder, whereas the hippocampus participates also in the therapeutic mechanisms of numerous medicines. Not surprisingly, several drugs acting via 5-HT mechanisms are efficacious to some extent in some diseases and the link between 5-HT and the hippocampus although clear remains difficult to untangle. For this reason, we review reported data concerning the distribution and the functional roles of the 5-HT receptors in the hippocampal region in health and disease. The impact of the 5-HT systems on the hippocampal function is such that the research of new 5-HT mechanisms and drugs is still very active. It concerns notably drugs acting at the 5-HT_1A,_2A,_2C,_4,6 receptor subtypes, in addition to the already existing drugs including the selective serotonin reuptake inhibitors.

Comparative Study on the Functional Connectivity of Amygdala and Hippocampal Neural Circuits in Patients With First-Episode Schizophrenia and Other High-Risk Populations

Objective: Cortical-limbic system neural circuit abnormalities are closely related to the onset of schizophrenia (SZ). The amygdala, hippocampus, cingulate, and prefrontal lobe are important components of the loop. In this study, we compared resting-state functional connectivity (rs-FC) between the amygdala/hippocampus and cingulate/prefrontal regions among patients with first-episode schizophrenia (FE-SZ), high risk populations with SZ (HR-SZ), and healthy controls (HCs). By discovering the abnormal pattern of the cortical-limbic system of SZ and HR-SZ, we attempted to elucidate the pathophysiological mechanism of SZ. Method: This study collected seventy-five FE-SZ patients, 59 HR-SZ, and 64 HCs. Analysis of variance and chi-square tests were used to analyze their demographic data. Analysis of covariance and post-hoc analysis were performed on the functional connectivity of the three groups. Finally, correlation analysis between the significant brain functional connectivity value and the scale score was performed. Results: The results of the analysis of covariance showed that there were significant differences in rs-FC between the amygdala and the right middle cingulate and between the hippocampus and the bilateral medial superior frontal gyrus among the three groups (Gaussian random field (GRF)-corrected voxel p < 0.001, cluster p < 0.05). Post hoc comparisons showed that the rs-FC of the amygdala-right middle cingulate and the hippocampus-bilateral medial superior frontal gyrus in patients with SZ was significantly lower than that of HR-SZ and HC (Bonferroni corrected p < 0.001). There was no significant difference between the HR-SZ and HC groups. The results of the correlation analysis showed that rs-FC of the hippocampus-medial frontal gyrus in patients with SZ was positively correlated with core depression factor scores on the Hamilton Depression Scale (P = 0.006, R = 0.357). Conclusion: There were different patterns of functional connectivity impairment in the amygdala and hippocampal neural circuits in the schizophrenic cortical-limbic system, and these patterns may be more useful than genetics as state-related imaging changes of the disease.

Social support modulates the association between PTSD diagnosis and medial frontal volume in Chinese adults who lost their only child

Losing an only child is a devastating life event that a parent can experience and may lead to post-traumatic stress disorder (PTSD). Social support could buffer against the negative influence of this trauma, but the neural mechanism underlying this alleviation effect remains poorly understood. In this study, voxel-based morphometry was conducted on brain MRI of 220 Han Chinese adults who had lost their only child. We performed multiple regression analysis to investigate the associations between social support scores – along with PTSD diagnosis, age, sex, body mass index (BMI) – and brain grey matter (GM) volumes in these bereaved parents. For all trauma-exposed adults, social support-by-diagnosis interaction was significantly associated with medial prefrontal volume (multiple comparisons corrected P ˂ 0.05), where positive correlation was found in adults with PTSD but not in those without PTSD. Besides, PTSD diagnosis was associated with decreased GM volume in medial and middle frontal gyri (P ˂ 0.001, uncorrected); older age was associated with widespread GM volume deficits; male sex was associated with lower GM volume in rolandic operculum, insular, postcentral gyrus (corrected P ˂ 0.05), and lower GM in thalamus but greater GM in parahippocampus (P ˂ 0.001, uncorrected); higher BMI was associated with GM deficits in occipital gyrus (corrected P ˂ 0.05) and precuneus (P ˂ 0.001, uncorrected). In conclusions, social support modulates the association between PTSD diagnosis and medial frontal volume, which may play an important role in the emotional disturbance in PTSD development in adults who lost their only child.

Cerebral regional and network characteristics in asthma patients: a resting-state fMRI study

Asthma is a serious health problem that involves not only the respiratory system but also the central nervous system. Previous studies identified either regional or network alterations in patients with asthma, but inconsistent results were obtained. A key question remains unclear: are the regional and neural network deficits related or are they two independent characteristics in asthma? Answering this question is the aim of this study. By collecting resting-state functional magnetic resonance imaging from 39 patients with asthma and 40 matched health controls, brain functional measures including regional activity (amplitude of low-frequency fluctuations) and neural network function (degree centrality (DC) and functional connectivity) were calculated to systematically characterize the functional alterations. Patients exhibited regional abnormities in the left angular gyrus, right precuneus, and inferior temporal gyrus within the default mode network. Network abnormalities involved both the sensorimotor network and visual network with key regions including the superior frontal gyrus and occipital lobes. Altered DC in the lingual gyrus was correlated with the degree of airway obstruction. This study elucidated different patterns of regional and network changes, thereby suggesting that the two parameters reflect different brain characteristics of asthma. These findings provide evidence for further understanding the potential cerebral alterations in the pathophysiology of asthma.

Neuroanatomical Features That Predict Response to Electroconvulsive Therapy Combined With Antipsychotics in Schizophrenia: A Magnetic Resonance Imaging Study Using Radiomics Strategy

OBJECTIVE

Neuroimaging-based brain signatures may be informative in identifying patients with psychosis who will respond to antipsychotics. However, signatures that inform the electroconvulsive therapy (ECT) health care professional about the response likelihood remain unclear in psychosis with radiomics strategy. This study investigated whether brain structure-based signature in the prediction of ECT response in a sample of schizophrenia patients using radiomics approach.

METHODS

This high-resolution structural magnetic resonance imaging study included 57 patients at baseline. After ECT combined with antipsychotics, 28 and 29 patients were classified as responders and non-responders. Features of gray matter were extracted and compared. The logistic regression model/support vector machine (LRM/SVM) analysis was used to explore the predictive performance.

RESULTS

The regularized multivariate LRM accurately discriminated responders from non-responders, with an accuracy of 90.91%. The structural features were further confirmed in the validating data set, resulting in an accuracy of 87.59%. The accuracy of the SVM in the training set was 90.91%, and the accuracy in the validation set was 91.78%.

CONCLUSION

Our results support the possible use of structural brain feature-based radiomics as a potential tool for predicting ECT response in patients with schizophrenia undergoing antipsychotics, paving the way for utilization of markers in psychosis.