Altered neural signaling and immune pathways in peripheral blood mononuclear cells of schizophrenia patients with cognitive impairment: A transcriptome analysis

miRNA cargo in circulating vesicles from neurons is altered in individuals with schizophrenia and associated with severe disease

While RNA expression appears to be altered in several brain disorders, the constraints of postmortem analysis make it impractical for well-powered population studies and biomarker development. Given that the unique molecular composition of neurons are reflected in their extracellular vesicles (EVs), we hypothesized that the fractionation of neuron derived EVs provides an opportunity to specifically profile their encapsulated contents noninvasively from blood. To investigate this hypothesis, we determined miRNA expression in microtubule associated protein 1B (MAP1B)-enriched serum EVs derived from neurons from a large cohort of individuals with schizophrenia and nonpsychiatric comparison participants. We observed dysregulation of miRNA in schizophrenia subjects, in particular those with treatment-resistance and severe cognitive deficits. These data support the hypothesis that schizophrenia is associated with alterations in posttranscriptional regulation of synaptic gene expression and provides an example of the potential utility of tissue-specific EV analysis in brain disorders.

Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia

To characterize the regulatory relationships between different types of transcripts and the altered molecular networks in schizophrenia (SCZ), we performed a whole transcriptome study by quantifying mRNAs, long noncoding RNAs (lncRNAs), miRNAs, and circular RNAs (circRNAs) in the same individuals simultaneously. A total of 807 dysregulated genes showed differential expression in SCZ cases compared with controls. Network-based analysis revealed dysregulation of molecular networks in SCZ. Finally, integration of the transcriptome data with published data identified promising SCZ candidate genes. Our study reveals that dysregulated molecular networks and regulatory relationships between different types of transcript may have a role in SCZ.

Neuronal expression of ndst3 in early zebrafish development is responsive to Wnt signaling manipulation

Heparan sulfate proteoglycans (HSPGs) are constituents of the cell surface and extracellular matrix and are vital for various activities within the cell. The N-deacetylase/N-sulfotransferase (heparin glucosaminyl) family of enzymes, or NDST, modifies heparan sulfate (HS) by catalyzing both the N-deacetylation and the N-sulfation of N-acetylglucosamine residues. In zebrafish, a single ndst3 gene is an orthologue of both mammalian NDST3 and NDST4 genes. The role of ndst3 in zebrafish development has not been investigated and such study may provide insight into the role(s) of both mammalian orthologues. Here, we characterized expression of ndst3 during early development in zebrafish and found it to be predominately neuronal. We found that expression of ndst3 is sensitive to Wnt signaling manipulation, with stimulation of the Wnt pathway resulting in robust expansion of ndst3 expression domains. Finally, using CRISPR/Cas9 genome editing, we mutagenized the ndst3 gene and isolated an allele, ndst3nu20, resulting in a frameshift and premature protein truncation. We discovered Ndst3 is not essential for zebrafish survival as ndst3nu20 homozygous mutants are viable and fertile.

Evidence that a working memory cognitive phenotype within schizophrenia has a unique underlying biology

It is suggested studying phenotypes within the syndrome of schizophrenia will accelerate understanding the complex molecular pathology of the disorder. Supporting this hypothesis, we have identified a sub-group within schizophrenia with impaired working memory (WM) and have used Affymetrix™ Human Exon 1.0 ST Arrays to compare their blood RNA levels (n=16) to a group of with intact WM (n=18). Levels of 72 RNAs were higher in blood from patients with impaired WM, 11 of which have proven links to the maintenance of different aspects of working memory (cognition). Overall, changed gene expression in those with impaired WM could be linked to cognition through glutamatergic activity, olfaction, immunity, inflammation as well as energy and metabolism. Our data gives preliminary support to the hypotheses that there is a working memory deficit phenotype within the syndrome of schizophrenia with has a biological underpinning. In addition, our data raises the possibility that a larger study could show that the specific changes in gene expression we have identified could prove to be the biomarkers needed to develop a blood test to identify those with impaired WM; a significant step toward allowing the use of personalised medicine directed toward improving their impaired working memory.

Considering medication exposure in genomic association studies of cognition in psychotic disorders

Cognitive dysfunction is a core feature of psychosis-spectrum illnesses, and the characterization of related genetic mechanisms may provide insights regarding the disease pathophysiology. Substantial efforts have been made to determine the genetic component of cognitive symptoms, without clear success. Illness-related moderators and environmental factors such as medications hinder the detection of genomic association with cognition. Polypharmacy is common in psychotic disorders, and the cumulative effects of medication regimens can confound gene-cognition associations. A review of the relative contributions of important pharmacological and genetic relationships identifies that the effects of medications on cognition in psychotic disorders may be at least, if not more, impactful than individual genes, thus underscoring the importance of accounting for medication exposure in gene-cognition association studies.

Systems biological assessment of altered cytokine responses to bacteria and fungi reveals impaired immune functionality in schizophrenia

Evidence suggests that complex interactions between the immune system and brain have important etiological and therapeutic implications in schizophrenia. However, the detailed cellular and molecular basis of immune dysfunction in schizophrenia remains poorly characterized. To better understand the immune changes and molecular pathways, we systemically compared the cytokine responses of peripheral blood mononuclear cells (PBMCs) derived from patients with schizophrenia and controls against bacterial, fungal, and purified microbial ligands, and identified aberrant cytokine response patterns to various pathogens, as well as reduced cytokine production after stimulation with muramyl dipeptide (MDP) in schizophrenia. Subsequently, we performed single-cell RNA sequencing on unstimulated and stimulated PBMCs from patients and controls and revealed widespread suppression of antiviral and inflammatory programs as well as impaired chemokine/cytokine-receptor interaction networks in various immune cell subpopulations of schizophrenic patients after MDP stimulation. Moreover, serum MDP levels were elevated in these patients and correlated with the course of the disease, suggesting increased bacterial translocation along with disease progression. In vitro assays revealed that MDP pretreatment altered the functional response of normal PBMCs to its re-stimulation, which partially recapitulated the impaired immune function in schizophrenia. In conclusion, we delineated the molecular and cellular landscape of impaired immune function in schizophrenia, and proposed a mutual interplay between innate immune impairment, reduced pathogen clearance, increased MDP translocation along schizophrenia development, and blunted innate immune response. These findings provide new insights into the pathogenic mechanisms that drive systemic immune activation, neuroinflammation, and brain abnormalities in schizophrenia.

What genes are differentially expressed in individuals with schizophrenia? A systematic review

Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.

Peripheral Blood-Based Gene Expression Studies in Schizophrenia: A Systematic Review

Schizophrenia is a disorder that is characterized by delusions, hallucinations, disorganized speech or behavior, and socio-occupational impairment. The duration of observation and variability in symptoms can make the accurate diagnosis difficult. Identification of biomarkers for schizophrenia (SCZ) can help in early diagnosis, ascertaining the diagnosis, and development of effective treatment strategies. Here we review peripheral blood-based gene expression studies for identification of gene expression biomarkers for SCZ. A literature search was carried out in PubMed and Web of Science databases for blood-based gene expression studies in SCZ. A list of differentially expressed genes (DEGs) was compiled and analyzed for overlap with genetic markers, differences based on drug status of the participants, functional enrichment, and for effect of antipsychotics. This literature survey identified 61 gene expression studies. Seventeen out of these studies were based on expression microarrays. A comparative analysis of the DEGs (n = 227) from microarray studies revealed differences between drug-naive and drug-treated SCZ participants. We found that of the 227 DEGs, 11 genes (ACOT7, AGO2, DISC1, LDB1, RUNX3, SIGIRR, SLC18A1, NRG1, CHRNB2, PRKAB2, and ZNF74) also showed genetic and epigenetic changes associated with SCZ. Functional enrichment analysis of the DEGs revealed dysregulation of proline and 4-hydroxyproline metabolism. Also, arginine and proline metabolism was the most functionally enriched pathway for SCZ in our analysis. Follow-up studies identified effect of antipsychotic treatment on peripheral blood gene expression. Of the 27 genes compiled from the follow-up studies AKT1, DISC1, HP, and EIF2D had no effect on their expression status as a result of antipsychotic treatment. Despite the differences in the nature of the study, ethnicity of the population, and the gene expression analysis method used, we identified several coherent observations. An overlap, though limited, of genetic, epigenetic and gene expression changes supports interplay of genetic and environmental factors in SCZ. The studies validate the use of blood as a surrogate tissue for biomarker analysis. We conclude that well-designed cohort studies across diverse populations, use of high-throughput sequencing technology, and use of artificial intelligence (AI) based computational analysis will significantly improve our understanding and diagnostic capabilities for this complex disorder.

Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods

Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found "Clostridium neurotoxicity" and "signaling events mediated by focal adhesion kinase" had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (PAK1:SYT1, PAK1:RFC5, DCTN1:STX1A, and GRIA1:MAP2K4) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.

Working memory deficits in schizophrenia are associated with the rs34884856 variant and expression levels of the NR4A2 gene in a sample Mexican population: a case control study

BACKGROUND

Cognitive functions represent useful endophenotypes to identify the association between genetic variants and schizophrenia. In this sense, the NR4A2 gene has been implicated in schizophrenia and cognition in different animal models and clinical trials. We hypothesized that the NR4A2 gene is associated with working memory performance in schizophrenia. This study aimed to analyze two variants and the expression levels of the NR4A2 gene with susceptibility to schizophrenia, as well as to evaluate whether possession of NR4A2 variants influence the possible correlation between gene expression and working memory performance in schizophrenia.

METHODS

The current study included 187 schizophrenia patients and 227 controls genotyped for two of the most studied NR4A2 genetic variants in neurological and neuropsychiatric diseases. Genotyping was performed using High Resolution Melt and sequencing techniques. In addition, mRNA expression of NR4A2 was performed in peripheral mononuclear cells of 112 patients and 118 controls. A group of these participants, 54 patients and 87 controls, performed the working memory index of the WAIS III test.

RESULTS

Both genotypic frequencies of the two variants and expression levels of the NR4A2 gene showed no significant difference when in patients versus controls. However, patients homozygous for the rs34884856 promoter variant showed a positive correlation between expression levels and auditory working memory.

CONCLUSIONS

Our finding suggested that changes in expression levels of the NR4A2 gene could be associated with working memory in schizophrenia depending on patients' genotype in a sample from a Mexican population.

Transcriptomics Analysis Reveals Shared Pathways in Peripheral Blood Mononuclear Cells and Brain Tissues of Patients With Schizophrenia

Background: Schizophrenia is a serious mental disorder with complicated biological mechanisms. Few studies explore the transcriptional features that are shared in brain tissue and peripheral blood. In the present study, we aimed to explore the biological pathways with similar expression patterns in both peripheral blood mononuclear cells (PBMCs) and brain tissues. Methods: The present study used transcriptomics technology to detect mRNA expression of PBMCs of 10 drug-naïve patients with schizophrenia and 20 healthy controls. Transcriptome data sets of brain tissue of patients with schizophrenia downloaded from public databases were also analyzed in our study. The biological pathways with similar expression patterns in the PBMCs and brain tissues were uncovered by differential expression analysis, weighted gene co-expression network analysis (WGCNA), and pathway analysis. Finally, the expression levels of differential expressed genes (DEGs) were validated by real-time fluorescence quantitative polymerase chain reaction (qPCR) in another 12 drug-naïve patients with schizophrenia and 12 healthy controls. Results: We identified 542 DEGs, 51 DEGs, 732 DEGs, and 104 DEGs in PBMCs, dorsolateral prefrontal cortex, anterior cingulate gyrus, and nucleus accumbent, respectively. Five DEG clusters were recognized as having similar gene expression patterns in PBMCs and brain tissues by WGCNA. The pathway analysis illustrates that these DEG clusters are mainly enriched in several biological pathways that are related to phospholipid metabolism, ribosome signal transduction, and mitochondrial oxidative phosphorylation. The differential significance of PLAAT3, PLAAT4, PLD2, RPS29, RPL30, COX7C, COX7A2, NDUFAF2, and ATP5ME were confirmed by qPCR. Conclusions: This study finds that the pathways associated with phospholipid metabolism, ribosome signal transduction, and energy metabolism have similar expression patterns in PBMCs and brain tissues of patients with schizophrenia. Our results supply a novel insight for revealing the pathogenesis of schizophrenia and might offer a new approach to explore potential biological markers of peripheral blood in schizophrenia.

Integrating genome-wide association study and methylation functional annotation data identified candidate genes and pathways for schizophrenia

BACKGROUND

Schizophrenia (SCZ) is a severe mental disorder. Both environmental and genetic factors contribute to the development of SCZ. The estimated heritability of SCZ is about 80%. Previous genetic studies of SCZ mainly focused on the genetic variations associated the risk of SCZ. Limited efforts are paid to explore the roles and biological mechanism of nuclear acid methylation implicated in the pathogenesis of SCZ.

METHODS

A two-stage integrative analysis of SCZ GWAS and nuclear acid methylation functional annotation data (including meQTLs and m6A) was performed in this study. First, the discovery GWAS of SCZ was aligned with genomic meQTLs and m6A annotation data to identify the candidate genes associated with SCZ. Second, another independent replication GWAS dataset of SCZ was applied to validate the discovery results. Furthermore, the functional relevance of identified candidate genes with SCZ were validated by the mRNA expression profiling of SCZ brain tissues. Gene ontology (GO) and pathway enrichment analysis of identified candidate genes was performed by the DAVID tool.

RESULTS

The two-stage integrative analysis detected 106 meQTLs related candidate genes for SCZ. After comparing with the differentially expressed genes in SCZ brain tissues, 49 overlapped genes were identified for meQTLs, such as ZSCAN12, BTN3A2 and HLA-DQA1. Besides, for meQTLs, 29 SCZ associated pathways and 56 SCZ associated GO terms were detected, such as cell adhesion molecules and asthma. For m6A, 25 candidate genes were detected by the two-stage integrative analysis for SCZ, such as ZSCAN12, HLA-DQA1 and SNX19. Furthermore, 17 of the 25 genes were detected in the mRNA expression profiling of SCZ brain tissues.

CONCLUSION

This study identified multiple SCZ associated genes and pathways, supporting the implication of nuclear acid methylation in the pathogenesis of SCZ.

Evaluation of miRNA Expression Profiles in Schizophrenia Using Principal-Component Analysis-Based Unsupervised Feature Extraction Method

Schizophrenia (SZ) is a disease that causes mental disability and affects 1% of the total population in the world. Our aim was to identify new molecular targets that would help to diagnose and treat these patients. The GSE54578 microRNA expression profile was downloaded from the Gene Expression Omnibus database that consists of peripheral blood samples of 15 first-onset SZ patients and 15 healthy controls. Principal-component analysis-based unsupervised feature extraction (FE), protein-protein interaction network, and pathway enrichment were performed, and microRNA (miRNA)-hub gene network was established. A set of seven miRNA (hsa-miR-373-5p, hsa-miR-199a-3p, hsa-miR-22-5p, hsa-miR-4711-3p, hsa-miR-3157-3p, hsa-miR-542-5p, and hsa-miR-3615) could successfully discriminate SZ patients from healthy controls with high accuracy. We identified two miRNAs (hsa-miR-373-5p and hsa-miR-199a-3p) as a signature that mostly related to SZ. These miRNAs could be potential novel biomarkers and could contribute to the clinical treatment of this disease.

Dysregulation of a specific immune-related network of genes biologically defines a subset of schizophrenia

Currently, the clinical diagnosis of schizophrenia relies solely on self-reporting and clinical interview, and likely comprises heterogeneous biological subsets. Such subsets may be defined by an underlying biology leading to solid biomarkers. A transgenic rat model modestly overexpressing the full-length, non-mutant Disrupted-in-Schizophrenia 1 (DISC1) protein (tgDISC1 rat) was generated that defines such a subset, inspired by our previous identification of insoluble DISC1 protein in post mortem brains from patients with chronic mental illness. Besides specific phenotypes such as DISC1 protein pathology, abnormal dopamine homeostasis, and changes in neuroanatomy and behavior, this animal model also shows subtle disturbances in overarching signaling pathways relevant for schizophrenia. In a reverse-translational approach, assuming that both the animal model and a patient subset share common disturbed signaling pathways, we identified differentially expressed transcripts from peripheral blood mononuclear cells of tgDISC1 rats that revealed an interconnected set of dysregulated genes, led by decreased expression of regulator of G-protein signaling 1 (RGS1), chemokine (C-C) ligand 4 (CCL4), and other immune-related transcripts enriched in T-cell and macrophage signaling and converging in one module after weighted gene correlation network analysis. Testing expression of this gene network in two independent cohorts of patients with schizophrenia versus healthy controls (n = 16/50 and n = 54/45) demonstrated similar expression changes. The two top markers RGS1 and CCL4 defined a subset of 27% of patients with 97% specificity. Thus, analogous aberrant signaling pathways can be identified by a blood test in an animal model and a corresponding schizophrenia patient subset, suggesting that in this animal model tailored pharmacotherapies for this patient subset could be achieved.

Gene expression changes related to immune processes associate with cognitive endophenotypes of schizophrenia

Schizophrenia is a heterogeneous disorder characterized by a spectrum of symptoms and many different underlying causes. Thus, instead of using the broad diagnosis, intermediate phenotypes can be used to possibly decrease the underlying complexity of the disorder. Alongside the classical symptoms of delusions and hallucinations, cognitive deficits are a core feature of schizophrenia. To increase our understanding of the biological processes related to these cognitive deficits, we performed a genome-wide gene expression analysis. A battery of 14 neuropsychological tests was administered to 844 individuals from a Finnish familial schizophrenia cohort. We grouped the applied neuropsychological tests into five factors for further analysis. Cognitive endophenotypes, whole blood mRNA, genotype, and medication use data were studied from 47 individuals. Expression level of several RNA probes were significantly associated with cognitive performance. The factor representing Verbal Working Memory was associated with altered expression levels of 11 probes, of which one probe was also associated with a specific sub-measure of this factor (WMS-R Digit span backward). While, the factor Processing speed was related to one probe, which additionally associated among 55 probes with a specific sub-measure of this factor (WAIS-R Digit symbol). Two probes were associated with the measure recognition memory performance. Enrichment analysis of these differentially expressed probes highlighted immunological processes. Our findings are in line with genome-wide genetic discoveries made in schizophrenia, suggesting that immunological processes may be of biological interest for future drug design towards schizophrenia and the cognitive dysfunctions that underlie it.

Longitudinal Analyses of Blood Transcriptome During Conversion to Psychosis

The biological processes associated with the onset of schizophrenia remain largely unknown. Current hypotheses favor gene × environment interactions as supported by our recent report about DNA methylation changes during the onset of psychosis. Here, we conducted the first longitudinal transcriptomic analysis of blood samples from 31 at-risk individuals who later converted to psychosis and 63 at-risk individuals who did not. Individuals were followed for a maximum of 1 year. Blood samples were collected at baseline and at the end of follow-up and individuals served as their own controls. Differentially expressed genes between the 2 groups were identified using the RNA sequencing of an initial discovery subgroup (n = 15 individuals). The most promising results were replicated using high-throughput real-time qPCR in the whole cohort (n = 94 individuals). We identified longitudinal changes in 4 brain-expressed genes based on RNAseq analysis. One of these genes (CPT1A) was replicated in the whole cohort. The previously observed hypermethylation in NRP1 and GSTM5 during the onset of psychosis correlated with a decrease in corresponding gene expression. RNA sequencing also identified 2 co-expression networks that were impaired after conversion compared with baseline-the Wnt pathway including AKT1, CPT1A and semaphorins, and the Toll-like receptor pathway, related to innate immunity. This longitudinal study of transcriptomic changes in individuals with at-risk mental state revealed alterations during conversion to psychosis in pathways and genes relevant to schizophrenia. These results may be a first step toward better understanding psychosis onset. They may also help to identify new biomarkers and targets for disease-modifying therapeutic strategies.

Childhood developmental vulnerabilities associated with early life exposure to infectious and noninfectious diseases and maternal mental illness

BACKGROUND

Fetal exposure to infectious and noninfectious diseases may influence early childhood developmental functioning, on the path to later mental illness. Here, we investigated the effects of in utero exposure to maternal infection and noninfectious diseases during pregnancy on offspring developmental vulnerabilities at age 5 years, in the context of estimated effects for early childhood exposures to infectious and noninfectious diseases and maternal mental illness.

METHODS

We used population data for 66,045 children from an intergenerational record linkage study (the New South Wales Child Development Study), for whom a cross-sectional assessment of five developmental competencies (physical, social, emotional, cognitive, and communication) was obtained at school entry, using the Australian Early Development Census (AEDC). Child and maternal exposures to infectious or noninfectious diseases were determined from the NSW Ministry of Health Admitted Patients Data Collection (APDC) and maternal mental illness exposure was derived from both APDC and Mental Health Ambulatory Data collections. Multinomial logistic regression analyses were used to examine unadjusted and adjusted associations between these physical and mental health exposures and child developmental vulnerabilities at age 5 years.

RESULTS

Among the physical disease exposures, maternal infectious diseases during pregnancy and early childhood infection conferred the largest associations with developmental vulnerabilities at age 5 years; maternal noninfectious illness during pregnancy also retained small but significant associations with developmental vulnerabilities even when adjusted for other physical and mental illness exposures and covariates known to be associated with early childhood development (e.g., child's sex, socioeconomic disadvantage, young maternal age, prenatal smoking). Among all exposures examined, maternal mental illness first diagnosed prior to childbirth conferred the greatest odds of developmental vulnerability at age 5 years.

CONCLUSIONS

Prenatal exposure to infectious or noninfectious diseases appear to influence early childhood physical, social, emotional and cognitive developmental vulnerabilities that may represent intermediate phenotypes for subsequent mental disorders.

Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways

It remains challenging to boost statistical power of genome-wide association studies (GWASs) to identify more risk variants or loci that can account for "missing heritability." Furthermore, since most identified variants are not in gene-coding regions, a biological interpretation of their function is largely lacking. On the other hand, recent biotechnological advances have made it feasible to experimentally measure the three-dimensional organization of the genome, including enhancer-promoter interactions in high resolutions. Due to the well-known critical roles of enhancer-promoter interactions in regulating gene expression programs, such data have been applied to link GWAS risk variants to their putative target genes, gaining insights into underlying biological mechanisms. However, their direct use in GWAS association testing is yet to be exploited. Here we propose integrating enhancer-promoter interactions into GWAS association analysis to both boost statistical power and enhance interpretability. We demonstrate that through an application to two large-scale schizophrenia (SCZ) GWAS summary data sets, the proposed method could identify some novel SCZ-associated genes and pathways (containing no significant SNPs). For example, after the Bonferroni correction, for the larger SCZ data set with 36,989 cases and 113,075 controls, our method applied to the gene body and enhancer regions identified 27 novel genes and 11 novel KEGG pathways to be significant, all missed by the transcriptome-wide association study (TWAS) approach. We conclude that our proposed method is potentially useful and is complementary to TWAS and other standard gene- and pathway-based methods.

HLA typing using genome wide data reveals susceptibility types for infections in a psychiatric disease enriched sample

BACKGROUND

The infections Toxoplasma gondii (T. gondii), cytomegalovirus, and Herpes Simplex Virus Type 1 (HSV1) are common persistent infections that have been associated with schizophrenia and bipolar disorder. The major histocompatibility complex (MHC, termed HLA in humans) region has been implicated in these infections and these mental illnesses. The interplay of MHC genetics, mental illness, and infection has not been systematically examined in previous research.

METHODS

In a cohort of 1636 individuals, we used genome-wide association data to impute 7 HLA types (A, B, C, DRB1, DQA1, DQB1, DPB1), and combined this data with serology data for these infections. We used regression analysis to assess the association between HLA alleles, infections (individually and collectively), and mental disorder status (schizophrenia, bipolar disorder, controls).

RESULTS

After Bonferroni correction for multiple comparisons, HLA C∗07:01 was associated with increased HSV1 infection among mentally healthy controls (OR 3.4, p = 0.0007) but not in the schizophrenia or bipolar groups (P > 0.05). For the multiple infection outcome, HLA B∗ 38:01 and HLA C∗12:03 were protective in the healthy controls (OR ≈ 0.4) but did not have a statistically-significant effect in the schizophrenia or bipolar groups. T. gondii had several nominally-significant positive associations, including the haplotypes HLA DRB∗03:01 ∼ HLA DQA∗05:01 ∼ HLA DQB∗02:01 and HLA B∗08:01 ∼ HLA C∗07:01.

CONCLUSIONS

We identified HLA types that showed strong and significant associations with neurotropic infections. Since some of these associations depended on mental illness status, the engagement of HLA-related pathways may be altered in schizophrenia due to immunogenetic differences or exposure history.

Exon Array Biomarkers for the Differential Diagnosis of Schizophrenia and Bipolar Disorder

This study developed potential blood-based biomarker tests for diagnosing and differentiating schizophrenia (SZ), bipolar disorder type I (BD), and normal control (NC) subjects using mRNA gene expression signatures. A total of 90 subjects (n = 30 each for the three groups of subjects) provided blood samples at two visits. The Affymetrix exon microarray was used to profile the expression of over 1.4 million probesets. We selected potential biomarker panels using the temporal stability of the probesets and also back-tested them at two different visits for each subject. The 18-gene biomarker panels, using logistic regression modeling, correctly differentiated the three groups of subjects with high accuracy across the two different clinical visits (83-88% accuracy). The results are also consistent with the actual data and the "leave-one-out" analyses, indicating that the models should be predictive when applied to independent data cohorts. Many of the SZ and BD subjects were taking antipsychotic and mood stabilizer medications at the time of blood draw, raising the possibility that these drugs could have affected some of the differential transcription signatures. Using an independent Illumina data set of gene expression data from antipsychotic medication-free SZ subjects, the 18-gene biomarker panels produced a receiver operating characteristic curve accuracy greater than 0.866 in patients that were less than 30 years of age and medication free. We confirmed select transcripts by quantitative PCR and the nCounter® System. The episodic nature of psychiatric disorders might lead to highly variable results depending on when blood is collected in relation to the severity of the disease/symptoms. We have found stable trait gene panel markers for lifelong psychiatric disorders that may have diagnostic utility in younger undiagnosed subjects where there is a critical unmet need. The study requires replication in subjects for ultimate proof of the utility of the differential diagnosis.

Integrating eQTL data with GWAS summary statistics in pathway-based analysis with application to schizophrenia

Many genetic variants affect complex traits through gene expression, which can be exploited to boost statistical power and enhance interpretation in genome-wide association studies (GWASs) as demonstrated by the transcriptome-wide association study (TWAS) approach. Furthermore, due to polygenic inheritance, a complex trait is often affected by multiple genes with similar functions as annotated in gene pathways. Here, we extend TWAS from gene-based analysis to pathway-based analysis: we integrate public pathway collections, expression quantitative trait locus (eQTL) data and GWAS summary association statistics (or GWAS individual-level data) to identify gene pathways associated with complex traits. The basic idea is to weight the SNPs of the genes in a pathway based on their estimated cis-effects on gene expression, then adaptively test for association of the pathway with a GWAS trait by effectively aggregating possibly weak association signals across the genes in the pathway. The P values can be calculated analytically and thus fast. We applied our proposed test with the KEGG and GO pathways to two schizophrenia (SCZ) GWAS summary association data sets, denoted by SCZ1 and SCZ2 with about 20,000 and 150,000 subjects, respectively. Most of the significant pathways identified by analyzing the SCZ1 data were reproduced by the SCZ2 data. Importantly, we identified 15 novel pathways associated with SCZ, such as GABA receptor complex (GO:1902710), which could not be uncovered by the standard single SNP-based analysis or gene-based TWAS. The newly identified pathways may help us gain insights into the biological mechanism underlying SCZ. Our results showcase the power of incorporating gene expression information and gene functional annotations into pathway-based association testing for GWAS.

Exploring the Wnt signaling pathway in schizophrenia and bipolar disorder

The Wnt signaling pathway plays a crucial role in neurodevelopment and in regulating the function and structure of the adult nervous system. Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental disorders with evidence of subtle neurodevelopmental, structural and functional neuronal abnormalities. We aimed to elucidate the role of aberrant regulation of the Wnt system in these disorders by evaluating plasma levels of secreted Wnt modulators in patients (SCZ = 551 and BD = 246) and healthy controls (HCs = 639) using enzyme immune-assay. We also investigated the expression of 141 Wnt-related genes in whole blood in a subsample (SCZ = 338, BD = 241, and HCs = 263) using microarray analysis. Both SCZ and BD had dysregulated mRNA expression of Wnt-related genes favoring attenuated canonical (beta-catenin-dependent) signaling, and there were also indices of enhanced non-canonical Wnt signaling. In particular, FZD7, which may activate all Wnt pathways, but favors non-canonical signaling, and NFATc3, a downstream transcription factor and readout of the non-canonical Wnt/Ca²⁺ pathway, were significantly increased in SCZ and BD (p < 3 × 10^-4). Furthermore, patients had lower plasma levels of soluble dickkopf 1 and sclerostin (p < 0.01) compared with HC. Our findings suggest that SCZ and BD are characterized by abnormal Wnt gene expression and plasma protein levels, and we propose that drugs targeting the Wnt pathway may have a role in the treatment of severe mental disorders.

How Wnt Signaling Builds the Brain: Bridging Development and Disease

Wnt/β-catenin signaling plays a crucial role throughout all stages of brain development and remains important in the adult brain. Accordingly, many neurological disorders have been linked to Wnt signaling. Defects in Wnt signaling during neural development can give rise to birth defects or lead to neurological dysfunction later in life. Developmental signaling events can also be hijacked in the adult and result in disease. Moreover, knowledge about the physiological role of Wnt signaling in the brain might lead to new therapeutic strategies for neurological diseases. Especially, the important role for Wnt signaling in neural differentiation of pluripotent stem cells has received much attention as this might provide a cure for neurodegenerative disorders. In this review, we summarize the versatile role of Wnt/β-catenin signaling during neural development and discuss some recent studies linking Wnt signaling to neurological disorders.

Activated Phosphorylated STAT1 Levels as a Biologically Relevant Immune Signal in Schizophrenia

OBJECTIVE

Activation of STAT1 is directly downstream of the cytokine receptors that signal from specific proinflammatory cytokines known to be dysregulated in schizophrenia (SZ), such as IFNγ, IL6, IL2 and IL10, as well as hypoxia, viral/bacterial infections and peptide growth factors. If the increased cytokine protein levels repeatedly observed in SZ have biological consequences, then the measurement of pSTAT1 is a logical step forward.

METHODS

Peripheral blood mononuclear cells (PBMCs) from controls (n = 13) and subjects with SZ (n = 22) were extracted using the Ficoll method. Participants with SZ were diagnosed using the SCID, clinical symptomatology was measured using the Positive and Negative Syndrome Scale (PANSS), and cognitive functioning was measured using the MATRICS Consensus Cognitive Battery. Levels of activated STAT1 (Y701), i.e. phosphorylated STAT1 (pSTAT1), were measured by a commercially available ELISA in nuclear extracts from PBMCs.

RESULTS

There was a significant bimodal distribution in the sample, with an SZ subgroup expressing significantly greater levels of activated pSTAT1 than the remainder of the participants. In this subgroup, levels of pSTAT1 were significantly higher than in the control group, as well as significantly higher than in the remainder of the SZ subjects. Furthermore, this subsample of patients manifested significantly poorer cognitive performance on several measures of the MATRICS.

DISCUSSION

pSTAT1 levels may provide a measure of the biological relevance of widely reported elevations in levels of cytokines in SZ over the past several decades. Activation of kinase cascades can be used to partition or disassemble the composite immune signal in patients living with SZ.