Generating testable hypotheses for schizophrenia and rheumatoid arthritis pathogenesis by integrating epidemiological, genomic, and protein interaction data

Identifying frequency-dependent imaging genetic associations via hypergraph-structured multi-task sparse canonical correlation analysis

Identifying complex associations between genetic variations and imaging phenotypes is a challenging task in the research of brain imaging genetics. The previous study has proved that neuronal oscillations within distinct frequency bands are derived from frequency-dependent genetic modulation. Thus it is meaningful to explore frequency-dependent imaging genetic associations, which may give important insights into the pathogenesis of brain disorders. In this work, the hypergraph-structured multi-task sparse canonical correlation analysis (HS-MTSCCA) was developed to explore the associations between multi-frequency imaging phenotypes and single-nucleotide polymorphisms (SNPs). Specifically, we first created a hypergraph for the imaging phenotypes of each frequency and the SNPs, respectively. Then, a new hypergraph-structured constraint was proposed to learn high-order relationships among features in each hypergraph, which can introduce biologically meaningful information into the model. The frequency-shared and frequency-specific imaging phenotypes and SNPs could be identified using the multi-task learning framework. We also proposed a useful strategy to tackle this algorithm and then demonstrated its convergence. The proposed method was evaluated on four simulation datasets and a real schizophrenia dataset. The experimental results on synthetic data showed that HS-MTSCCA outperforms the other competing methods according to canonical correlation coefficients, canonical weights, and cosine similarity. And the results on real data showed that HS-MTSCCA could obtain superior canonical coefficients and canonical weights. Furthermore, the identified frequency-shared and frequency-specific biomarkers could provide more interesting and meaningful information, demonstrating that HS-MTSCCA is a powerful method for brain imaging genetics.

Diagnostic value and role of serum miR-15a-5p in patients with schizophrenia

BACKGROUND

More and more studies have confirmed that the heredity plays an important role in mental disorders, especially microRNA. The objective of this research was to explore the level of miR-15a-5p in patients with schizophrenia (SZ), and to evaluate the feasibility of this miRNA as a diagnostic marker of SZ.

METHODS

The serum level of miR-15a-5p in patients with SZ and healthy people was detected by RT-qPCR. ROC curve was established to evaluate the clinical diagnostic significance of miR-15a-5p in SZ. Pearson correlation coefficient was used to evaluate the correlation between miR-15a-5p level and PANSS score. Logistic regression was used to assess the risk factors of SZ. A rat model of SZ was established, and the effects of miR-15a-5p on the behavior of SZ rats were observed through water maze test and open field test.

RESULTS

The serum level of miR-15a-5p in patients with SZ was significantly increased, and ROC analysis revealed that miR-15a-5p had clinical diagnostic value in SZ. High level of miR-15a-5p was positively correlated with the positive symptom, negative symptom and general psychopathology subscore of patients. Logistic regression results showed that miR-15a-5p was a risk factor affecting the occurrence of SZ. Animal studies showed that the serum level of miR-15a-5p was elevated in the SZ rats, and inhibiting the expression of miR-15a-5p has a positive effect on improving the cognitive function and anxiety behavior of SZ rats.

CONCLUSIONS

Serum miR-15a-5p is a risk factor for SZ, which is of great significance for the diagnosis of SZ.

Immunologic profiling in schizophrenia and rheumatoid arthritis

The negative relationship between schizophrenia (SCZ) and rheumatoid arthritis (RA) has been observed for 85 years, but the mechanisms driving this association are unknown. This study analyzed differences in profiles of cytokines (IL-1β, IL-Ra, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IFNγ, TNFα), selected genes (HLA-DRB1, IL1RN, HP2), and antibodies related to gluten sensitivity (AGA-IgG, AGA-IgA), celiac disease (tTG), and systemic autoimmunity (ANA, anti-CCP, RF) in 40 subjects with SCZ, 40 with RA, and 40 healthy controls (HC). HLA-DRB1*04:01 alleles were enriched in persons with SCZ and RA compared with HC, and the HP2/HP2 genotype was 2-fold more prevalent in AGA/tTG-positive versus negative SCZ patients. Patients with SCZ demonstrated 52.5% positivity for any of the antibodies tested, compared to 90% of RA patients and 30% of HC. Cluster analysis of the cytokines revealed three clusters: one associated with SCZ marked by high levels of IL-1Ra, one associated with HC, and one associated with both SCZ and RA marked by elevated levels of IFNγ, TNFα, and IL-6. These analyses suggest that stratification of SCZ patients by cytokine profile may identify unique SCZ subgroups and enable the use of currently available cytokine-targeted treatment strategies.

Identification of potential blood biomarkers for early diagnosis of schizophrenia through RNA sequencing analysis

Schizophrenia (SCZ) is a highly heritable, polygenic complex mental disorder with imprecise diagnostic boundaries. Finding sensitive and specific novel biomarkers to improve the biological homogeneity of SCZ diagnosis is still one of the research hotspots. To identify the blood specific diagnostic biomarkers of SCZ, we performed RNA sequencing (RNA-seq) on 30 peripheral blood samples from 15 first-episode drug-naïve SCZ patients and 15 healthy controls (CTL). By performing multiple bioinformatics analysis algorithms based on RNA-seq data and microarray datasets, including differential expression genes (DEGs) analysis, WGCNA and CIBERSORT, we first identified 6 specific key genes (TOMM7, SNRPG, KRT1, AQP10, TMEM14B and CLEC12A) in SCZ. Moreover, we found that the proportions of lymphocyte, monocyte and neutrophils were significantly distinct in SCZ patients with CTL samples. Therefore, combining various features including age, sex and the novel blood biomarkers, we constructed the risk prediction model with three classifiers (RF: Random Forest; SVM: support vector machine; DT: decision tree) through repeated k-fold cross validation ensuring better generalizability. Finest result of Area under Receiver Operating Characteristic (AUROC) score of 0.91 was achieved by RF classifier and with a comparable good performance of AUROC 0.77 in external validation dataset. A lower AUROC of 0.63 was demonstrated when it was further applied to a Bipolar disorder (BPD) cohort. In conclusion, the study identified three peripheral core immunocytes and six key genes associated with the occurrence of SCZ, and further studies are required to test and validate these novel biomarkers for early diagnosis and treatment of SCZ.

Etiology and Risk Factors for Rheumatoid Arthritis: A State-of-the-Art Review

Rheumatoid arthritis (RA) is the most common systemic inflammatory rheumatic disease. It is associated with significant burden at the patient and societal level. Extensive efforts have been devoted to identifying a potential cause for the development of RA. Epidemiological studies have thoroughly investigated the association of several factors with the risk and course of RA. Although a precise etiology remains elusive, the current understanding is that RA is a multifactorial disease, wherein complex interactions between host and environmental factors determine the overall risk of disease susceptibility, persistence and severity. Risk factors related to the host that have been associated with RA development may be divided into genetic; epigenetic; hormonal, reproductive and neuroendocrine; and comorbid host factors. In turn, environmental risk factors include smoking and other airborne exposures; microbiota and infectious agents; diet; and socioeconomic factors. In the present narrative review, aimed at clinicians and researchers in the field of RA, we provide a state-of-the-art overview of the current knowledge on this topic, focusing on recent progresses that have improved our comprehension of disease risk and development.

Generalized and social anxiety disorder interactomes show distinctive overlaps with striosome and matrix interactomes

Mechanisms underlying anxiety disorders remain elusive despite the discovery of several associated genes. We constructed the protein-protein interaction networks (interactomes) of six anxiety disorders and noted enrichment for striatal expression among common genes in the interactomes. Five of these interactomes shared distinctive overlaps with the interactomes of genes that were differentially expressed in two striatal compartments (striosomes and matrix). Generalized anxiety disorder and social anxiety disorder interactomes showed exclusive and statistically significant overlaps with the striosome and matrix interactomes, respectively. Systematic gene expression analysis with the anxiety disorder interactomes constrained to contain only those genes that were shared with striatal compartment interactomes revealed a bifurcation among the disorders, which was influenced by the anterior cingulate cortex, nucleus accumbens, amygdala and hippocampus, and the dopaminergic signaling pathway. Our results indicate that the functionally distinct striatal pathways constituted by the striosome and the matrix may influence the etiological differentiation of various anxiety disorders.

Assessment of Subclinical Psychotic Symptoms in Patients with Rheumatoid Arthritis and Spondyloarthritis

Inflammatory and autoimmune processes have been associated with the onset of depressive and psychotic symptoms. Rheumatoid arthritis (RA) and spondyloarthritis (SpA) are rheumatic diseases with an inflammatory etiology. A high prevalence of depressive and anxiety-related comorbidity has been reported for both diseases, with no evidence of a greater prevalence of psychosis. The objective of the present study was to evaluate for the first time subclinical psychotic symptoms in patients with RA and SpA. This is a cross-sectional, single-center study including RA and SpA patients, as well as healthy controls. Abnormal psychotic experiences (positive, negative, and depressive symptoms) were evaluated using the Community Assessment of Psychic Experiences (CAPE-42). Functional capacity was evaluated using the Short-Form Health Survey SF-12. We compared the CAPE and SF-12 scores between the three groups. We recruited 385 individuals: 218 with RA, 100 with SpA, and 67 healthy controls. According to the CAPE scale, the frequency of subclinical psychotic symptoms was greater in patients than in healthy controls (RA, 1.90 vs. 1.63, p < 0.001; SpA, 1.88 vs. 1.63, p = 0.001). Distress was also greater in patients than in controls owing to the presence of symptoms. No differences were observed between the three groups for the mental dimension scores in the SF-12 Health Survey (43.75 in RA, 45.54 in SpA, and 43.19 in healthy controls). Our findings point to a greater prevalence of subclinical psychotic symptoms in patients with RA and patients with SpA than in the general population. The results suggest an association between inflammation and depression/subclinical psychotic symptoms.

A machine learning case-control classifier for schizophrenia based on DNA methylation in blood

Epigenetic dysregulation is thought to contribute to the etiology of schizophrenia (SZ), but the cell type-specificity of DNA methylation makes population-based epigenetic studies of SZ challenging. To train an SZ case-control classifier based on DNA methylation in blood, therefore, we focused on human genomic regions of systemic interindividual epigenetic variation (CoRSIVs), a subset of which are represented on the Illumina Human Methylation 450K (HM450) array. HM450 DNA methylation data on whole blood of 414 SZ cases and 433 non-psychiatric controls were used as training data for a classification algorithm with built-in feature selection, sparse partial least squares discriminate analysis (SPLS-DA); application of SPLS-DA to HM450 data has not been previously reported. Using the first two SPLS-DA dimensions we calculated a "risk distance" to identify individuals with the highest probability of SZ. The model was then evaluated on an independent HM450 data set on 353 SZ cases and 322 non-psychiatric controls. Our CoRSIV-based model classified 303 individuals as cases with a positive predictive value (PPV) of 80%, far surpassing the performance of a model based on polygenic risk score (PRS). Importantly, risk distance (based on CoRSIV methylation) was not associated with medication use, arguing against reverse causality. Risk distance and PRS were positively correlated (Pearson r = 0.28, P = 1.28 × 10^-12), and mediational analysis suggested that genetic effects on SZ are partially mediated by altered methylation at CoRSIVs. Our results indicate two innate dimensions of SZ risk: one based on genetic, and the other on systemic epigenetic variants.

Targeted sequencing of NOTCH signaling pathway genes and association analysis of variants correlated with mandibular prognathism

Introduction

The purpose of this study was to systematically identify variants in NOTCH signaling pathway genes that correlate with mandibular prognathism (MP) in the general Chinese population.

Methods

Targeted sequencing of NOTCH signaling pathway genes was conducted in 199 MP individuals and 197 class I malocclusion control individuals. The associations of common and rare variants with MP, cephalometric parameters, and continuous cephalometric phenotypes were analyzed by principal component (PC) analysis. The associations between rare variants and MP were tested for each gene.

Results

Six SNPs, including rs415929, rs520688, and rs423023 in an exonic region of NOTCH4; rs1044006 in an exonic region of NOTCH3; rs1051415 in an exonic region of JAG1; and rs75236173 in the 3′-untranslated region (3′-UTR) of NUMB were associated with MP (P < 0.05). One common variant, rs1051415, in an exonic region of JAG1 was significantly related to PC1 (P  = 3.608 × 10^− 4), which explained 24.3% of the overall phenotypic variation observed and corresponded to the sagittal mandibular position towards the maxilla, ranging from a posterior positioned mandible to an anterior positioned mandible. Additionally, 41 other variants were associated with PC1–5 (P  <  0.05). With respect to rare variant analysis, variants within the EP300, NCOR2, and PSEN2 gene showed an association with MP (t   < 0 .05).

Conclusions

An association between NOTCH signaling pathway genes and MP has been identified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13005-021-00268-0.

Mental Comorbidity in Rheumatic Diseases

In this review, we summarise the most relevant studies in a PubMed Search term “mental disorders and rheumatic disease” in the last 15 years. Mental disorders such as depression and anxiety are common in people with rheumatic diseases. Treating these comorbidities can improve the patientʼs quality of life. The high prevalence of symptoms of psychiatric disorders is a challenge for rheumatologists, especially with regard to the differentiation of possible psychiatric components in rheumatological diseases. Screening for psychiatric problems in patients with rheumatic diseases should be evaluated as soon as possible, as these can have a major influence on the perception of pain and physical functioning status from the outset. Mental health disorders are seen as a risk factor for poor patient outcomes, as patients may not adhere to medical treatments. The potential side effects of biological agents can increase patient anxiety and affect adherence to therapy. Therefore, interdisciplinary care would be of great advantage in the treatment of rheumatic patients with psychological comorbidities.

GutBalance: a server for the human gut microbiome-based disease prediction and biomarker discovery with compositionality addressed

The compositionality of the microbiome data is well-known but often neglected. The compositional transformation pertains to the supervised learning of microbiome data and is a critical step that decides the performance and reliability of the disease classifiers. We value the excellent performance of the distal discriminative balance analysis (DBA) method, which selects distal balances of pairs and trios of bacteria, in addressing the classification of high-dimensional microbiome data. By applying this method to the species-level abundances of all the disease phenotypes in the GMrepo database, we build a balance-based model repository for the classification of human gut microbiome-related diseases. The model repository supports the prediction of disease risks for new sample(s). More importantly, we highlight the concept of balance-disease associations rather than the conventional microbe-disease associations and develop the human Gut Balance-Disease Association Database (GBDAD). Each predictable balance for each disease model indicates a potential biomarker-disease relationship and can be interpreted as a bacteria ratio positively or negatively correlated with the disease. Furthermore, by linking the balance-disease associations to the evidenced microbe-disease associations in MicroPhenoDB, we surprisingly found that most species-disease associations inferred from the shotgun metagenomic datasets can be validated by external evidence beyond MicroPhenoDB. The balance-based species-disease association inference will accelerate the generation of new microbe-disease association hypotheses in gastrointestinal microecology research and clinical trials. The model repository and the GBDAD database are deployed on the GutBalance server, which supports interactive visualization and systematic interrogation of the disease models, disease-related balances and disease-related species of interest.

Genetic factors underlying the bidirectional relationship between autoimmune and mental disorders - Findings from a Danish population-based study

BACKGROUND

Previous studies have indicated the bidirectionality between autoimmune and mental disorders. However, genetic studies underpinning the co-occurrence of the two disorders have been lacking. In this study, we examined the potential genetic contribution to the association between autoimmune and mental disorders and investigated the genetic basis of overall autoimmune disease.

METHODS

We used diagnostic information from patients with seven autoimmune diseases and six mental disorders from the Danish population-based case-cohort sample (iPSYCH2012). We explored the epidemiological association using survival analysis and modelled the effect of polygenic risk scores (PRSs) on autoimmune and mental diseases. Genetic factors were investigated using GWAS and imputed HLA alleles in the iPSYCH cohort.

RESULTS

Of 64,039 individuals, a total of 43,902 (68.6%) were diagnosed with mental disorders and 1383 (2.2%) with autoimmune diseases. There was a significant comorbidity between the two disease classes (P = 2.67 × 10^-7, OR = 1.38, 95%CI = 1.22-1.56), with an overall bidirectional association, wherein individuals with autoimmune diseases had an increased risk of subsequent mental disorders (HR = 1.13, 95%CI: 1.07-1.21, P = 7.95 × 10^-5) and vice versa (HR = 1.27, 95%CI = 1.16-1.39, P = 8.77 × 10^-15). Adding PRSs to these adjustment models did not have an impact on the associations. PRSs for autoimmune diseases were only slightly associated with increased risk of mental disorders (HR = 1.01, 95%CI: 1.00-1.02, p = 0.038), whereas PRSs for mental disorders were not associated with autoimmune diseases overall. Our GWAS highlighted 12 loci on chromosome 6 (minimum P = 2.74 × 10^-36, OR = 1.80, 95% CI: 1.64-1.96), which were implicated in gene regulation through bioinformatic functional analyses, thereby identifying new candidate genes for overall autoimmune disease. Moreover, we observed 20 human leukocyte antigen (HLA) alleles strongly associated, either positively or negatively, with overall autoimmune disease, but we did not find significant evidence of their associations with overall mental disorders. A GWAS of a comorbid diagnosis of an autoimmune disease and a mental disorder identified a genome-wide significant locus on chromosome 7 as well (P = 1.43 × 10^-8, OR = 10.65, 95%CI = 3.21-35.36).

CONCLUSIONS

Our findings confirm the overall comorbidity and bidirectionality between autoimmune diseases and mental disorders and identify HLA genes which are significantly associated with overall autoimmune disease. Additionally, we identified several new candidate genes for overall autoimmune disease and ranked them based on their association with the investigated diseases.

The genetic basis for the inverse relationship between rheumatoid arthritis and schizophrenia

Introduction

Rheumatoid arthritis is a common autoimmune disease and schizophrenia is a relatively common and debilitating neurological disorder. There are several common features between rheumatoid arthritis and schizophrenia. The inverse relationship between rheumatoid arthritis and schizophrenia has been replicated in several studies. Despite evidence for an inverse epidemiological relationship and negative correlations for risk between rheumatoid arthritis and schizophrenia, there are no biological data that directly support this inverse relationship.

Materials and Methods’

We meta‐analyzed the genome‐wide association studies to investigate the shared association loci between rheumatoid arthritis and schizophrenia at the genome‐wide scale. Rheumatoid arthritis‐ and schizophrenia‐associated loci in most recent genome‐wide association studies of rheumatoid arthritis and schizophrenia were tested. Genetic risk score analysis was also conducted to investigate the collective contribution of schizophrenia risk loci to rheumatoid arthritis risk.

Results

Rheumatoid arthritis and schizophrenia meta‐genome‐wide association study showed a significant peak at the major histocompatibility complex locus on chromosome 6 in both rheumatoid arthritis‐schizophrenia meta‐genome‐wide association study and inverted meta‐genome‐wide association study datasets. Testing rheumatoid arthritis‐ and schizophrenia‐associated loci outside the human leukocyte antigen region showed no association with both rheumatoid arthritis and schizophrenia at a genome‐wide level of significance. Weighted genetic risk scores showed no evidence for a statistically significant association between rheumatoid arthritis and schizophrenia.

Conclusion

The finding of our study is consistent with the role of the major histocompatibility complex locus in the genetic correlation between rheumatoid arthritis and schizophrenia, and suggests that either schizophrenia has an autoimmune basis and/or rheumatoid arthritis has an active neurological component.

Schizophrenia in a genomic era: a review from the pathogenesis, genetic and environmental etiology to diagnosis and treatment insights

Schizophrenia is a common multigenic and debilitating neurological disorder characterized by chronic psychotic symptoms and psychosocial impairment. Complex interactions of genetics and environmental factors have been implicated in etiology of schizophrenia. There is no central pathophysiology mechanism, diagnostic neuropathology, or biological markers have been defined for schizophrenia. However, a number of different hypotheses including neurodevelopmental and neurochemical hypotheses have been proposed to explain the neuropathology of schizophrenia. This review provides an overview of pathogenesis, genetic and environmental etiologies to diagnosis and treatment insights in clinical management of schizophrenia in light of the recent discoveries of genetic loci associated with susceptibility to schizophrenia.

Association of HLA-A, -B, -C, -DRB1 and -DQB1 alleles at amino acid level in individuals with schizophrenia: A study from South India

BACKGROUND

Schizophrenia, a chronic severe psychiatric illness of unknown aetiology, has been shown to be associated with HLA alleles but at varied degree in different population. The present study has focussed on analysing the frequency of HLA class I and class II alleles in persons with schizophrenia from South India.

METHODS

Ninety seven individuals with schizophrenia and 103 age- and gender-matched controls were typed for HLA- A, B, C, DRB1 and DQB1 loci by next-generation sequencing in Illumina MiniSeq using MIA FORA NGS FLEX HLA typing kit.

RESULTS

The results showed that HLA-A*01:01:01, B*37:01:01 and C*01:02:01 were positively associated with schizophrenia while HLA-B*35:03:01 and DRB1*04:03:01 were negatively associated. Gender-specific associations revealed that DRB1*10:01:01 and DQB1*05:01:01 were positively associated while DQB1*03:02:01 was negatively associated with female subjects with schizophrenia. A*24:02:01~B*37:01:01~C*06:02:01~DRB1*10:01:01~DQB1*05:01:01 is the predominant haplotype in schizophrenia population when compared to healthy controls. Amino acid association in susceptible and protective alleles has shown that the presence of peptide in the peptide-binding groves of mature HLA-A protein (K, M, V, R and V at 44th, 67th, 150th, 156th and 158th position), HLA-B protein (D and S at 77th and 99th position) and HLA-C protein (M at 99th position) confer susceptibility to the disease, only in the absence of E (Glutamic acid) at 74th position in mature HLA-DRB1 protein. Interaction of amino acids in protective alleles namely B*35:01:01 and DRB1*04:03:01 has revealed that aspartic acid at 114th (D) position in mature HLA-B protein and glutamic acid (E) at 74th position of mature HLA-DRB1 protein have a combined effect in protecting against the disease.

CONCLUSION

The study has revealed the HLA association with schizophrenia in south Indian population. The amino acid interaction with the disease needs to be confirmed in a larger population.

Interactome of SARS-CoV-2 / nCoV19 modulated host proteins with computationally predicted PPIs

World over, people are looking for solutions to tackle the pandemic coronavirus disease (COVID-19) caused by the virus SARS-CoV-2/nCoV-19. Notable contributions in biomedical field have been characterizing viral genomes, host transcriptomes and proteomes, repurposable drugs and vaccines. In one such study, 332 human proteins targeted by nCoV19 were identified. We expanded this set of host proteins by constructing their protein interactome, including in it not only the known protein-protein interactions (PPIs) but also novel, hitherto unknown PPIs predicted with our High-precision Protein-Protein Interaction Prediction (HiPPIP) model that was shown to be highly accurate. In fact, one of the earliest discoveries made possible by HiPPIP is related to activation of immunity upon viral infection. We found that several interactors of the host proteins are differentially expressed upon viral infection, are related to highly relevant pathways, and that the novel interaction of NUP98 with CHMP5 may activate an antiviral mechanism leading to disruption of viral budding. We are making the interactions available as downloadable files to facilitate future systems biology studies and also on a web-server at http://hagrid.dbmi.pitt.edu/corona that allows not only keyword search but also queries such as "PPIs where one protein is associated with 'virus' and the interactors with 'pulmonary'".

Meta-Analysis of Transcriptomic Data of Dorsolateral Prefrontal Cortex and of Peripheral Blood Mononuclear Cells Identifies Altered Pathways in Schizophrenia

Schizophrenia (SCZ) is a psychiatric disorder characterized by both positive and negative symptoms, including cognitive dysfunction, decline in motivation, delusion and hallucinations. Antipsychotic agents are currently the standard of care treatment for SCZ. However, only about one-third of SCZ patients respond to antipsychotic medications. In the current study, we have performed a meta-analysis of publicly available whole-genome expression datasets on Brodmann area 46 of the brain dorsolateral prefrontal cortex in order to prioritize potential pathways underlying SCZ pathology. Moreover, we have evaluated whether the differentially expressed genes in SCZ belong to specific subsets of cell types. Finally, a cross-tissue comparison at both the gene and functional level was performed by analyzing the transcriptomic pattern of peripheral blood mononuclear cells of SCZ patients. Our study identified a robust disease-specific set of dysfunctional biological pathways characterizing SCZ patients that could in the future be exploited as potential therapeutic targets.

Potentially repurposable drugs for schizophrenia identified from its interactome

We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further to identify whether any of them may potentially be repurposable for schizophrenia. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the drugs from the interactome using the BaseSpace Correlation Engine, and shortlisted those that had a negative correlation with differential gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes with opposite drug-induced versus schizophrenia-associated expression profiles were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had a pathophysiological overlap with schizophrenia. Drugs that targeted the same genes as the shortlisted drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis will help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development which faces a high failure rate.

Assessing whether the association between rheumatoid arthritis and schizophrenia is bidirectional: A nationwide population-based cohort study

Since many studies have shown a reduction in the incidence of rheumatoid arthritis (RA) in patients with schizophrenia (SCZ), little effort has been devoted to studying this link in the Asian population. Moreover, the relationship between these two disorders could be bidirectional, but the influence of RA on the SCZ incidence is unclear. The study aims to determine whether there is a bidirectional association between RA and SCZ in an Asian population. We analyzed a 10-year population- based longitudinal cohort using the National Health Insurance Research Database of Taiwan. In the first analysis, we included a total of 58,847 SCZ patients and 235,382 non-SCZ controls, and in the second analysis, a total of 30,487 RA patients and 121,833 non-RA controls, both matched by gender, age, and index date. Cox regression analyses were performed to examine the risk of RA incidence in the first analysis and the risk of SCZ incidence in the second analysis. The main finding of this study was the discovery of a lower incidence of RA in patients with SCZ (hazard ratio (HR): 0.48, 95% confidence interval (95% CI): 0.31–0.77) after adjustment for baseline demographics and comorbidities. Additionally, the presence of RA predicted a reduced incidence rate for SCZ, but the estimate was not statistically significant (HR: 0.77, 95% CI: 0.44–1.37). The study found a unidirectional association between RA and SCZ. However, RA has an age of onset later than RA, and the protective effect of RA on SCZ incidence would be biased due to the limited number of cases.

[A role of the immune system in the pathogenesis of schizophrenia]

The review addresses immunological aspects of schizophrenia, a multifactor disease caused by genetic factors, innate disorders of the central nervous system (CNS), including the consequences of perinatal hypoxia and infections, and adverse environmental influences. Neuroinflammation as a part of the pathophysiology of schizophrenia is characterized by the higher transcription of CNS inflammatory mediators, excessive activation of microglia, inhibition of glutamatergic receptors that leads to the decrease in the number of cortical synapses and neuronal apoptosis. The authors discuss a role of genetic polymorphisms of cytokine genes, complement system components etc. The literature data on the changes in systemic immune response and imbalance in Th1/Th2 adaptive immune responses are analyzed as well. Some papers showed higher levels of proinflammatory mediators in CSF and blood of patients with schizophrenia that indicated the involvement of blood brain barrier (BBB) dysfunction. The authors present the recent data on BBB dysfunction in schizophrenia and its role in the pathogenesis of the disease, autoimmunity in patients comparing it with immune activation and genetic predisposition. An important and arguable issues about a role of parasite and viral infections in the pathogenesis of schizophrenia, initiation of immune responses and direct impacts on the brain, an influence of antipsychotic treatment on immunity are discussed. In author's opinion, conflicting results of genetic and immunological studies of schizophrenia may be explained by different methodological approaches to selection of patients and healthy controls and the differences in schizophrenia classification.

Autoimmune Diseases and Psychotic Disorders

The notion of immunological pathways playing a role in the etiology of a subset of psychotic disorders has received increased interest in the last decades. One of the findings that has spiked interest herein, is an apparent link between autoimmune diseases and psychotic disorders. This is supported by genetic findings associating immune-related genetic markers with schizophrenia and clinical studies finding increased levels of inflammatory markers in patients with psychosis. Several large-scale epidemiologic studies have found positive associations between autoimmune diseases and psychosis. Particularly, autoimmune diseases as multiple sclerosis and lupus are known to have higher frequencies of neuropsychiatric symptoms, including psychosis, compared to healthy controls. Cross sectional studies have found higher prevalence of psychiatric diagnoses among those with autoimmune diseases, and longitudinal studies have shown bidirectional associations between several autoimmune diseases and increased risks associated with schizophrenia. Moreover, a family history of autoimmune diseases has been shown to be associated with an increased risk of psychotic disorders and vice versa. In this review we will summarize the epidemiologic evidence on associations between autoimmune diseases and psychosis. Possible mechanisms accountable for the association will be discussed, amongst others the probable role of shared genetic risk factors, the impact of infections on both autoimmunity and the development of psychotic disorders, and the potential role of the microbiome. We discuss the findings on and influence of autoantibodies and dysregulation of T- and B-cells in both disease categories, and why further research hereon is needed. In addition to the potential importance of autoimmunity in etiological mechanisms of psychotic disorders, the association also brings important attention to somatic comorbidity in patients with psychotic disorders.

Associations Between Non-neurological Autoimmune Disorders and Psychosis: A Meta-analysis

BACKGROUND

A relationship between non-neurological autoimmune (NNAI) disorders and psychosis has been widely reported but not yet subjected to meta-analysis. We conducted the first meta-analysis examining the association between NNAI disorders and psychosis and investigated the effect of 1) temporality (as determined by study design), 2) psychiatric diagnosis, and 3) specific autoimmune disorders.

METHODS

Major databases were searched for articles published until April 2018; 31 studies, comprising data for >25 million individuals, were eligible. Using random-effects models, we examined the overall association between all NNAI disorders and psychosis; rheumatoid arthritis was examined separately given the well-established negative association with psychosis. Stratified analyses investigated the effect of temporality, psychiatric diagnosis, and specific NNAI disorders.

RESULTS

We observed a positive overall association between NNAI disorders and psychosis (odds ratio [OR] = 1.26; 95% confidence interval [CI], 1.12-1.41) that was consistent across study designs and psychiatric diagnoses; however, considerable heterogeneity was detected (I² = 88.08). Patterns varied across individual NNAI disorders; associations were positive for pernicious anemia (OR = 1.91; 95% CI, 1.29-2.84), pemphigoid (OR = 1.90; 95% CI, 1.62-2.24), psoriasis (OR = 1.70; 95% CI, 1.51-1.91), celiac disease (OR = 1.53; 95% CI, 1.12-2.10), and Graves' disease (OR = 1.33; 95% CI, 1.03-1.72) and negative for ankylosing spondylitis (OR = 0.72; 95% CI, 0.54-0.98) and rheumatoid arthritis (OR = 0.65; 95% CI, 0.50-0.84).

CONCLUSIONS

While we observed a positive overall association between NNAI disorders and psychosis, this was not consistent across all NNAI disorders. Specific factors, including distinct inflammatory pathways, genetic influences, autoantibodies targeting brain proteins, and exposure to corticosteroid treatment, may therefore underlie this association.

Altered Expression of a Unique Set of Genes Reveals Complex Etiology of Schizophrenia

Background: The etiology of schizophrenia is extensively debated, and multiple factors have been contended to be involved. A panoramic view of the contributing factors in a genome-wide study can be an effective strategy to provide a comprehensive understanding of its causality. Materials and Methods: GSE53987 dataset downloaded from GEO-database, which comprised mRNA expression data of post-mortem brain tissue across three regions from control (C) and age-matched subjects (T) of schizophrenia (N = Hippocampus [HIP]: C-15, T-18, Prefrontal cortex [PFC]: C-15, T-19, Associative striatum [STR]: C-18, T-18). Bio-conductor-affy-package used to compute mRNA expression, and further t-test applied to investigate differential gene expression. The analysis of the derived genes performed using the PANTHER Classification System and NCBI database. Further, a protein interactome analysis of the derived gene set was performed using STRING v10 database (https://string-db.org/) Results: A set of 40 genes showed significantly altered (p < 0.01) expression across all three brain regions. The analyses unraveled genes implicated in biological processes and events, and molecular pathways relating basic neuronal functions. Conclusions: The aberrant expression of genes maintaining basic cell machinery explains compromised neuronal processing in SCZ.

Cross-tissue eQTL enrichment of associations in schizophrenia

The genome-wide association study of the Psychiatric Genomics Consortium identified over one hundred schizophrenia susceptibility loci. The number of non-coding variants discovered suggests that gene regulation could mediate the effect of these variants on disease. Expression quantitative trait loci (eQTLs) contribute to variation in levels of mRNA. Given the co-occurrence of schizophrenia and several traits not involving the central nervous system (CNS), we investigated the enrichment of schizophrenia associations among eQTLs for four non-CNS tissues: adipose tissue, epidermal tissue, lymphoblastoid cells and blood. Significant enrichment was seen in eQTLs of all tissues: adipose (β = 0.18, p = 8.8 × 10-06), epidermal (β = 0.12, p = 3.1 × 10-04), lymphoblastoid (β = 0.19, p = 6.2 × 10-08) and blood (β = 0.19, p = 6.4 × 10-06). For comparison, we looked for enrichment of association with traits of known relevance to one or more of these tissues (body mass index, height, rheumatoid arthritis, systolic blood pressure and type-II diabetes) and found that schizophrenia enrichment was of similar scale to that observed when studying diseases in the context of a more likely causal tissue. To further investigate tissue specificity, we looked for differential enrichment of eQTLs with relevant Roadmap affiliation (enhancers and promoters) and varying distance from the transcription start site. Neither factor significantly contributed to the enrichment, suggesting that this is equally distributed in tissue-specific and cross-tissue regulatory elements. Our analyses suggest that functional correlates of schizophrenia risk are prevalent in non-CNS tissues. This could be because of pleiotropy or the effectiveness of variants affecting expression in different contexts. This suggests the utility of large, single-tissue eQTL experiments to increase eQTL discovery power in the study of schizophrenia, in addition to smaller, multiple-tissue approaches. Our results conform to the notion that schizophrenia is a systemic disorder involving many tissues.

Predicted protein interactions of IFITMs may shed light on mechanisms of Zika virus-induced microcephaly and host invasion

After the first reported case of Zika virus (ZIKV) in Brazil, in 2015, a significant increase in the reported cases of microcephaly was observed. Microcephaly is a neurological condition in which the infant's head is significantly smaller with complications in brain development. Recently, two small membrane-associated interferon-inducible transmembrane proteins (IFITM1 and IFITM3) have been shown to repress members of the flaviviridae family which includes ZIKV. However, the exact mechanisms leading to the inhibition of the virus are yet unknown. Here, we assembled an interactome of IFITM1 and IFITM3 with known protein-protein interactions (PPIs) collected from publicly available databases and novel PPIs predicted using the High-confidence Protein-Protein Interaction Prediction (HiPPIP) model. We analyzed the functional and pathway associations of the interacting proteins, and found that there are several immunity pathways (toll-like receptor signaling, cd28 signaling in T-helper cells, crosstalk between dendritic cells and natural killer cells), neuronal pathways (axonal guidance signaling, neural tube closure and actin cytoskeleton signaling) and developmental pathways (neural tube closure, embryonic skeletal system development) that are associated with these interactors. Our novel PPIs associate cilia dysfunction in ependymal cells to microcephaly, and may also shed light on potential targets of ZIKV for host invasion by immunosuppression and cytoskeletal rearrangements. These results could help direct future research in elucidating the mechanisms underlying host defense to ZIKV and other flaviviruses.

Predicted protein interactions of IFITMs may shed light on mechanisms of Zika virus-induced microcephaly and host invasion

After the first reported case of Zika virus (ZIKV) in Brazil, in 2015, a significant increase in the reported cases of microcephaly was observed. Microcephaly is a neurological condition in which the infant’s head is significantly smaller with complications in brain development. Recently, two small membrane-associated interferon-inducible transmembrane proteins (IFITM1 and IFITM3) have been shown to repress members of the flaviviridae family which includes ZIKV. However, the exact mechanisms leading to the inhibition of the virus are yet unknown. Here, we assembled an interactome of IFITM1 and IFITM3 with known protein-protein interactions (PPIs) collected from publicly available databases and novel PPIs predicted using the High-confidence Protein-Protein Interaction Prediction (HiPPIP) model. We analyzed the functional and pathway associations of the interacting proteins, and found that there are several immunity pathways (toll-like receptor signaling, cd28 signaling in T-helper cells, crosstalk between dendritic cells and natural killer cells), neuronal pathways (axonal guidance signaling, neural tube closure and actin cytoskeleton signaling) and developmental pathways (neural tube closure, embryonic skeletal system development) that are associated with these interactors. Our novel PPIs associate cilia dysfunction in ependymal cells to microcephaly, and may also shed light on potential targets of ZIKV for host invasion by immunosuppression and cytoskeletal rearrangements. These results could help direct future research in elucidating the mechanisms underlying host defense to ZIKV and other flaviviruses.