Imaging genetics of schizophrenia in the post-GWAS era

Transplantation of gut microbiota derived from patients with schizophrenia induces schizophrenia-like behaviors and dysregulated brain transcript response in mice

Schizophrenia (SCZ), as a neurodevelopmental disorder and devastating disease, affects approximately 1% of the world population. Although numerous studies have attempted to elucidate the causes of SCZ occurrence, it is not clearly understood. Recently, the emerging roles of the gut microbiota in a range of brain disorders, including SCZ, have attracted much attention. While the molecular mechanism of gut microbiota in regulating the pathogenesis of SCZ is still lacking. Here, we first confirmed the difference of gut microbiome between SCZ patients and healthy controls, and then, we performed fecal microbiota transplantation (FMT) to clarify the roles of SCZ patients-derived microbiota in a specific pathogen free (SPF) mice model. 16 S rDNA sequencing confirmed that a significant difference of gut microbiome was present between two groups of FMT mice, which has a similar trend with the above human gut microbiome. Furthermore, we found that transplantation of fecal microbiota from SCZ patients into SPF mice was sufficient to induce schizophrenia-like (SCZ-like) symptoms, such as deficits in sociability and hyperactivity. Furthermore, the brains of mice colonized with SCZ microbiota displayed dysregulated transcript response and alternative splicing of SCZ-relevant genes. Moreover, 10 key genes were identified to be correlated with SCZ by an integrative transcriptome data analysis. Finally, 4 key genes were identified to be correlated with the 12 differential genera between two groups of FMT mice. Our results thus demonstrated that the gut microbiome might modify the transcriptomic profile in the brain, thereby modulating social behavior, and our present study can help better understand the link between gut microbiota and SCZ pathogenesis through the gut-brain axis.

Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy

OBJECTIVE

The primary objective of this study is to address the challenge posed by the increasing number of variants of unknown clinical significance (VUS) within the GABRD gene, which encodes the δ subunit of γ-Aminobutyric acid type A receptors. The focus is on predicting the most pathogenic GABRD VUS to enhance precision medicine and improve our understanding of relevant pathophysiology.

METHODS

The study employs a combination of in silico algorithms to analyze 82 variants of unknown clinical significance of GABRD gene sourced from the ClinVar database. Initially, separate algorithms based on sequence homology are utilized to assess this variant set. Subsequently, consensus variants predicted as pathogenic undergo further evaluation through a web server employing an algorithm based on structural homology. The resulting 11 variants are then validated using in silico tools that assess variant effects based on genetic and molecular data. The evaluation includes consideration of disease association and protein stability due to amino acid substitutions.

RESULTS

The study identifies specific variants (L111R, R114C, D123N, G150S, and L243P) in the coding region of the GABRD gene, which are predicted as deleterious by multiple algorithms. These variants are evolutionarily conserved, mapped onto the extracellular domain of the δ subunit, and associated with idiopathic generalized epilepsy.

CONCLUSIONS

The findings suggest structural or functional consequences that lead to pathogenicity, offering valuable insights for wet-lab experimentation. Besides, the findings contribute to the validation of clinically significant genetic variants in the GABRD gene, which is critical for epilepsy precision medicine.

Navigating the Intersection of Technology and Depression Precision Medicine

This chapter primarily focuses on the progress in depression precision medicine with specific emphasis on the integrative approaches that include artificial intelligence and other data, tools, and technologies. After the description of the concept of precision medicine and a comparative introduction to depression precision medicine with cancer and epilepsy, new avenues of depression precision medicine derived from integrated artificial intelligence and other sources will be presented. Additionally, less advanced areas, such as comorbidity between depression and cancer, will be examined.

Association of dopamine-based genetic risk score with dynamic low-frequency fluctuations in first-episode drug-naïve schizophrenia

Alterations in dynamic intrinsic brain activity and signaling of neurotransmitters, such as dopamine, have been independently detected in schizophrenia patients. Yet, it remains unclear whether the dopamine genetic risk variants have association with brain intrinsic activity. We aimed to investigate the schizophrenia-specific dynamic amplitude of low frequency fluctuation (dALFF) altered pattern, and its association with dopamine genetic risk score in first-episode drug-naïve schizophrenia (FES). Fifty-two FES and 51 healthy controls were included. A sliding-window method based on the dALFF was adopted to estimate the dynamic alterations in intrinsic brain activity. Subjects were genotyped, and a genetic risk score (GRS), which combined the additive effects of ten risk genotypes from five dopamine-related genes, was calculated. We used the voxel-wise correlation analysis to explore the association of dopamine-GRS with dALFF. FES showed significantly increased dALFF left medial prefrontal cortex and significantly decreased dALFF in the right posterior cingulate cortex compared with healthy controls. Greater dopamine GRS in FES was associated with higher dALFF in the left middle frontal gyrus and left inferior parietal gyrus. Our findings indicate that cumulative dopamine genetic risk is associated with a known imaging phenotype for schizophrenia.

Visual masking deficits in schizophrenia: a view into the genetics of the disease through an endophenotype

Schizophrenia is a severe psychiatric disorder determined by a complex mixture of genetic and environmental factors. To better understand the contributions of human genetic variations to schizophrenia, we performed a genome-wide association study (GWAS) of a highly sensitive endophenotype. In this visual masking endophenotype, two vertical bars, slightly shifted in the horizontal direction, are briefly presented (vernier offset). Participants are asked to indicate the offset direction of the bars (either left or right). The bars are followed by a grating mask, which makes the task both spatially and temporally challenging. The inter-stimulus interval (ISI) between the vernier and the mask was determined in 206 patients with schizophrenia, 109 first-order relatives, and 143 controls. Usually, in GWAS studies, patients are compared to controls (i.e., a binary task) without considering the large differences in performance between patients and controls, as it occurs in many paradigms. The masking task allows for a particularly powerful analysis because the differences in ISI within the patient population are large. We genotyped all participants and searched for associations between human polymorphisms and the masking endophenotype using a linear mixed model. We did not identify any genome-wide significant associations (p < 5 × 10^-8), indicating that common variants with strong effects are unlikely to contribute to the large inter-group differences in visual masking. However, we found significant differences in polygenetic risk scores (PRS) between patients and controls, and relatives and controls.

Effect Analysis of “Four-Step” Training and Assessment Tool in the Prevention and Control of COVID-19

Purpose

To improve the ability of infection prevention and control (IPC) of medical staff during the COVID-19 epidemic period, the “four-step” mode of whole staff training and assessment was used.

Methods

During the period from March 9 to March 18, 2020, 5425 medical staff from The First Affiliated Hospital of Nanjing Medical University were selected as the objects of this study. There are four stages in the training assessment mode. The first stage is the basic assessment stage; the second stage releases the electronic version of the knowledge point manual; the third stage conducts online exercises; the fourth stage conducts the final assessment.

Results

In the first stage, the participation rate of medical staff was 95.04%. In the fourth stage, the participation rate of medical staff was 98.01%. The average score of female medical staff in the first stage and the fourth stage was higher than that of males (P< 0.001). The average score of medical staff under 30 years old in the first stage and the fourth stage was higher than that of other age groups (P< 0.05). In the fourth stage, the correct rate of each part of exercises in the knowledge points of IPC was higher than that in the first stage (P< 0.001). In the two stages, the two parts of “COVID-19 prevention and control” and “multi-drug resistant bacteria prevention and control” had the highest accuracy, while the “disinfection and sterilization” and “infectious disease management” had the lowest accuracy (P< 0.001).

Conclusion

The “four-step” infection control training assessment mode has realized “full participation” and “effective training”, and the level of medical staff’s IPC has been significantly improved.

Quantitative neurogenetics: applications in understanding disease

Neurodevelopmental and neurodegenerative disorders (NNDs) are a group of conditions with a broad range of core and co-morbidities, associated with dysfunction of the central nervous system. Improvements in high throughput sequencing have led to the detection of putative risk genetic loci for NNDs, however, quantitative neurogenetic approaches need to be further developed in order to establish causality and underlying molecular genetic mechanisms of pathogenesis. Here, we discuss an approach for prioritizing the contribution of genetic risk loci to complex-NND pathogenesis by estimating the possible impacts of these loci on gene regulation. Furthermore, we highlight the use of a tissue-specificity gene expression index and the application of artificial intelligence (AI) to improve the interpretation of the role of genetic risk elements in NND pathogenesis. Given that NND symptoms are associated with brain dysfunction, risk loci with direct, causative actions would comprise genes with essential functions in neural cells that are highly expressed in the brain. Indeed, NND risk genes implicated in brain dysfunction are disproportionately enriched in the brain compared with other tissues, which we refer to as brain-specific expressed genes. In addition, the tissue-specificity gene expression index can be used as a handle to identify non-brain contexts that are involved in NND pathogenesis. Lastly, we discuss how using an AI approach provides the opportunity to integrate the biological impacts of risk loci to identify those putative combinations of causative relationships through which genetic factors contribute to NND pathogenesis.

Exosome Transplantation From Patients With Schizophrenia Causes Schizophrenia-Relevant Behaviors in Mice: An Integrative Multi-omics Data Analysis

Exosomes are involved in the pathophysiology of neuropsychiatric diseases, but the role of exosomes in schizophrenia (SCZ) is unclear. Here, we demonstrate that transplantation of serum exosomes from SCZ patients into mice caused behavioral abnormalities such as deficits in prepulse inhibition and sociability, hyperactivity, and anxiogenesis. A comparative bioinformatics analysis suggested shared and distinct differentially expressed genes (DEGs) and enriched molecular pathways in the brains of SCZ exosome-recipient mice, methylazoxymethanol acetate-treated rats, and SCZ patients, which correlates evidence of altered prefrontal-hippocampal functional coherence in SCZ. A large proportion of SCZ-relevant DEGs in the exosome-recipient mice were targets of DE exosomal miRNAs in SCZ patients. Furthermore, we identified 20 hub genes for SCZ risk genes, including BDNF and NRG1, which were DE miRNA targets in SCZ. Collectively, our study suggests that SCZ exosome transplantation caused SCZ-relevant behaviors in mice, and epigenetic regulation may contribute to the phenotypes in the SCZ exosome-recipient mice. Our results may provide a potential animal model and novel therapeutic targets for SCZ.

A knowledge-based multivariate statistical method for examining gene-brain-behavioral/cognitive relationships: Imaging genetics generalized structured component analysis

With advances in neuroimaging and genetics, imaging genetics is a naturally emerging field that combines genetic and neuroimaging data with behavioral or cognitive outcomes to examine genetic influence on altered brain functions associated with behavioral or cognitive variation. We propose a statistical approach, termed imaging genetics generalized structured component analysis (IG-GSCA), which allows researchers to investigate such gene-brain-behavior/cognitive associations, taking into account well-documented biological characteristics (e.g., genetic pathways, gene-environment interactions, etc.) and methodological complexities (e.g., multicollinearity) in imaging genetic studies. We begin by describing the conceptual and technical underpinnings of IG-GSCA. We then apply the approach for investigating how nine depression-related genes and their interactions with an environmental variable (experience of potentially traumatic events) influence the thickness variations of 53 brain regions, which in turn affect depression severity in a sample of Korean participants. Our analysis shows that a dopamine receptor gene and an interaction between a serotonin transporter gene and the environment variable have statistically significant effects on a few brain regions' variations that have statistically significant negative impacts on depression severity. These relationships are largely supported by previous studies. We also conduct a simulation study to safeguard whether IG-GSCA can recover parameters as expected in a similar situation.

Genetic Risk Assessment in Psychiatry

Most psychiatric disorders of pediatric and adult onset are caused by a complex interplay of genetic and environmental risk factors. Risk assessment in genetic counseling is correspondingly complicated. Outside of neurodevelopmental conditions, genetic and genomic testing has not achieved clinical utility. Genetic counselors most often base risk assessment on the client's medical and family history and empiric recurrence risk data. In rare cases significant familial risk may arise from variants of large effect. New approaches such as polygenic risk scores have the potential to inform diagnosis and management of affected individuals and risk status for at-risk individuals. Research on the genetic and environmental factors that increase risk for schizophrenia and etiologically related disorders are reviewed, guidance in determining and communicating risks to families is delivered, and new opportunities and challenges that will come with translating new research findings to psychiatric risk assessment and genetic counseling are anticipated.

iPSC-derived homogeneous populations of developing schizophrenia cortical interneurons have compromised mitochondrial function

Schizophrenia (SCZ) is a neurodevelopmental disorder. Thus, studying pathogenetic mechanisms underlying SCZ requires studying the development of brain cells. Cortical interneurons (cINs) are consistently observed to be abnormal in SCZ postmortem brains. These abnormalities may explain altered gamma oscillation and cognitive function in patients with SCZ. Of note, currently used antipsychotic drugs ameliorate psychosis, but they are not very effective in reversing cognitive deficits. Characterizing mechanisms of SCZ pathogenesis, especially related to cognitive deficits, may lead to improved treatments. We generated homogeneous populations of developing cINs from 15 healthy control (HC) iPSC lines and 15 SCZ iPSC lines. SCZ cINs, but not SCZ glutamatergic neurons, show dysregulated Oxidative Phosphorylation (OxPhos) related gene expression, accompanied by compromised mitochondrial function. The OxPhos deficit in cINs could be reversed by Alpha Lipoic Acid/Acetyl-L-Carnitine (ALA/ALC) but not by other chemicals previously identified as increasing mitochondrial function. The restoration of mitochondrial function by ALA/ALC was accompanied by a reversal of arborization deficits in SCZ cINs. OxPhos abnormality, even in the absence of any circuit environment with other neuronal subtypes, appears to be an intrinsic deficit in SCZ cINs.

Effects of the LHPP gene polymorphism on the functional and structural changes of gray matter in major depressive disorder

Background

A single-nucleotide polymorphism (SNP) of the LHPP gene (rs35936514) has been reported to be associated with major depressive disorder (MDD) in genome-wide association studies. However, the systems-level neural effects of rs35936514 that mediate the association are unknown. We hypothesized that variations in rs35936514 would be associated with structural and functional changes in gray matter (GM) at rest in MDD patients.

Methods

A total of 50 MDD patients and 113 healthy controls (HCs) were studied. Functional connectivity (FC) was analyzed by defining the bilateral hippocampus as the seed region. Voxel-based morphometry (VBM) was performed to assess the patterns of GM volume. The subjects were further divided into two groups: a CC homozygous group (CC; 24 MDD and 56 HC) and a risk T-allele carrier group (CT/TT genotypes; 26 MDD and 57 HC). A 2×2 analysis of variance (ANOVA: diagnosis × genotype) was used to determine the interaction effects and main effect (P<0.05).

Results

Significant diagnosis × genotype interaction effects on brain morphology and FC were noted. Compared to other subgroups, the MDD patients with the T allele showed an increased hippocampal FC in the bilateral calcarine cortex and cuneus and a decreased hippocampal FC in the right dorsolateral prefrontal cortex (DLPFC), bilateral anterior cingulate cortex (ACC), and medial prefrontal cortex (MPFC), in addition to reduced GM volume in the right DLPFC, bilateral temporal cortex, and posterior cingulate cortex (PCC).

Conclusions

LHPP gene polymorphisms may affect functional and structural changes in the GM at rest and may play an important role in the pathophysiological mechanisms of MDD.

Transgenic mice overexpressing miR-137 in the brain show schizophrenia-associated behavioral deficits and transcriptome profiles

Schizophrenia is a psychiatric disorder characterized by positive and negative symptoms and cognitive deficits. The exact cause of schizophrenia is still unknown, but substantial evidence indicates that it has a genetic component. Genome wide association studies demonstrate variants within miR-137 host gene are a risk factor for schizophrenia. However, the direct relationship between the pathophysiology of schizophrenia and the dosage of miR-137 remains unclear. Therefore, in this study, we generated transgenic mice overexpressing miR-137 (miR-137 Tg mice) with the neuron-specific Thy-1 promoter and examined schizophrenia-related phenotypes in these mice. Overexpression of miR-137 was observed in various brain regions of the miR-137 Tg mice, with down-regulation of putative miR-137 targets. MiR-137 Tg mice showed sensory gating deficits in a prepulse inhibition test, social deficits in a sociability and social novelty test, and cognitive deficits in a novel object recognition test. Interestingly, the predicted-altered pathways of the medial prefrontal cortex of miR-137 Tg mice were partially overlapped with those of the dorsolateral prefrontal cortex in postmortem brain of patients who died in equal to or less than 4 years after initial diagnosis of schizophrenia in published data. These results suggest that overexpression of miR-137 in the whole brain induces the several phenotypes that are relevant to aspects of psychiatric disorders, such as schizophrenia. Based on these findings, miR-137 Tg mice may have the potential to become a useful tool in researching the pathophysiology of psychiatric disorders.

Development of Neuroimaging-Based Biomarkers in Psychiatry

This chapter presents an overview of accumulating neuroimaging data with emphasis on translational potential. The subject will be described in the context of three disease states, i.e., schizophrenia, bipolar disorder, and major depressive disorder, and for three clinical goals, i.e., disease risk assessment, subtyping, and treatment decision.

Early Senescence and Leukocyte Telomere Shortening in SCHIZOPHRENIA: A Role for Cytomegalovirus Infection?

Schizophrenia is a severe, chronic mental disorder characterized by delusions and hallucinations. Several evidences support the link of schizophrenia with accelerated telomeres shortening and accelerated aging. Thus, schizophrenia patients show higher mortality compared to age-matched healthy donors. The etiology of schizophrenia is multifactorial, involving genetic and environmental factors. Telomere erosion has been shown to be accelerated by different factors including environmental factors such as cigarette smoking and chronic alcohol consumption or by psychosocial stress such as childhood maltreatment. In humans, telomere studies have mainly relied on measurements of leukocyte telomere length and it is generally accepted that individuals with short leukocyte telomere length are considered biologically older than those with longer ones. A dysregulation of both innate and adaptive immune systems has been described in schizophrenia patients and other mental diseases supporting the contribution of the immune system to disease symptoms. Thus, it has been suggested that abnormal immune activation with high pro-inflammatory cytokine production in response to still undefined environmental agents such as herpesviruses infections can be involved in the pathogenesis and pathophysiology of schizophrenia. It has been proposed that chronic inflammation and oxidative stress are involved in the course of schizophrenia illness, early onset of cardiovascular disease, accelerated aging, and premature mortality in schizophrenia. Prenatal or neonatal exposures to neurotropic pathogens such as Cytomegalovirus or Toxoplasma gondii have been proposed as environmental risk factors for schizophrenia in individuals with a risk genetic background. Thus, pro-inflammatory cytokines and microglia activation, together with genetic vulnerability, are considered etiological factors for schizophrenia, and support that inflammation status is involved in the course of illness in schizophrenia.

Research Progress in Biological Studies of Schizophrenia in China in 2017

Schizophrenia is a severe mental disorder and its etiology and pathological mechanism are unknown. This article mainly introduces the progress of biological studies of schizophrenia in China in 2017, including neuroimaging, genetics, and immunology studies. It also introduces the research progress of high-risk psychotic syndrome and physiotherapy.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.

Novel functional variants at the GWAS-implicated loci might confer risk to major depressive disorder, bipolar affective disorder and schizophrenia

BACKGROUND

A challenge of understanding the mechanisms underlying cognition including neurodevelopmental and neuropsychiatric disorders is mainly given by the potential severity of cognitive disorders for the quality of life and their prevalence. However, the field has been focused predominantly on protein coding variation until recently. Given the importance of tightly controlled gene expression for normal brain function, the goal of the study was to assess the functional variation including non-coding variation in human genome that is likely to play an important role in cognitive functions. To this end, we organized and utilized available genome-wide datasets from genomic, transcriptomic and association studies into a comprehensive data corpus. We focused on genomic regions that are enriched in regulatory activity-overlapping transcriptional factor binding regions and repurpose our data collection especially for identification of the regulatory SNPs (rSNPs) that showed associations both with allele-specific binding and allele-specific expression. We matched these rSNPs to the nearby and distant targeted genes and then selected the variants that could implicate the etiology of cognitive disorders according to Genome-Wide Association Studies (GWAS). Next, we use DeSeq 2.0 package to test the differences in the expression of the certain targeted genes between the controls and the patients that were diagnosed bipolar affective disorder and schizophrenia. Finally, we assess the potential biological role for identified drivers of cognition using DAVID and GeneMANIA.

RESULTS

As a result, we selected fourteen regulatory SNPs locating within the loci, implicated from GWAS for cognitive disorders with six of the variants unreported previously. Grouping of the targeted genes according to biological functions revealed the involvement of processes such as 'posttranscriptional regulation of gene expression', 'neuron differentiation', 'neuron projection development', 'regulation of cell cycle process' and 'protein catabolic processes'. We identified four rSNP-targeted genes that showed differential expression between patient and control groups depending on brain region: NRAS-in schizophrenia cohort, CDC25B, DDX21 and NUCKS1-in bipolar disorder cohort.

CONCLUSIONS

Overall, our findings are likely to provide the keys for unraveling the mechanisms that underlie cognitive functions including major depressive disorder, bipolar disorder and schizophrenia etiopathogenesis.

Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges

Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ.