Dataset Information

Schizophrenia Proteome Research

ABSTRACT: Despite of multiple systematic studies of schizophrenia pathogenesis, reconstruction of the mechanism established on proteomics, metabolomics, and genome-wide significant loci is still a challenging task. We suggested that advanced data for quantitative proteomics, metabolomics, and genome-wide association study (GWAS) may enhance the current evidence and fundamental knowledge about molecular pathogenesis of schizophrenia. Liquide chromatography and ultra-high-resolution mass-spectrometry were utilized for proteomic and metabolomic assay, and high throughput genotyping for the GWAS study. Proteomic and metabolomic results were quantitatively evaluated and overlayed on the GWAS data. After statistical analysis using R-package, the resulting features were associated in a multilayer mode with adjusted biological processes in a reconstructed unified map of molecular events. We have identified 20 DFE proteins that were validated on an independent cohort of patients that are significant for schizophrenia, including ALS, A1AG1, PEDF, VTDB, CERU, APOB, APOH, FASN, GPX3, etc. Almost half of them are new for schizophrenia. The metabolomic survey revealed 18 compounds most of which were the part transformation of tyrosine and steroids with the incline to androgens (androsterone sulfate, thyroliberin, thyroxine, dihydrotestosterone, androstenedione, cholesterol sulfate, metanephrine, dopaquinone, etc.) which were extracted as group-specific determinants that permits to isolate patients with schizophrenia. The GWAS assay revealed 52 loci were integrated into proteome-metabolome data as significantly implicated in schizophrenia. We integrated three layers of omics science (proteomics, metabolomics and GWAS) and quantitative analysis utilized systematic approach to reconstruct the proposed map of molecular events associated with the considered psychopathology. The resulting interplay between different layers emphasized strict implication of lipids metabolism, oxidative stress, imbalance in steroidogenesis and associated impartments of thyroid hormones and sex hormones interconnection. The proposed interplay map can give opportunity in the understanding how the regulation of distinct metabolic axis is achieved and what happens in proteome arrangements to produce a schizophrenia-specific pattern of pathology condition.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

DISEASE(S): Schizophrenia

SUBMITTER: Arthur Kopylov

LAB HEAD: Dr. Anna L. Kaysheva

PROVIDER: PXD035863 | Pride | 2023-02-08

REPOSITORIES: Pride

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Publications

Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia.

Kopylov Arthur T AT Stepanov Alexander A AA Butkova Tatiana V TV Malsagova Kristina A KA Zakharova Natalia V NV Kostyuk Georgy P GP Elmuratov Artem U AU Kaysheva Anna L AL

Scientific reports 20230206 1

Despite of multiple systematic studies of schizophrenia based on proteomics, metabolomics, and genome-wide significant loci, reconstruction of underlying mechanism is still a challenging task. Combination of the advanced data for quantitative proteomics, metabolomics, and genome-wide association study (GWAS) can enhance the current fundamental knowledge about molecular pathogenesis of schizophrenia. In this study, we utilized quantitative proteomic and metabolomic assay, and high throughput geno ...[more]

PMID: 36747015

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Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from peripheral blood samples. SUPPLEMENTARY FILES: CEL files were processed by manufacture's protocol. Genotype data were analyzed with the GeneSpring GT (Varia) 2.0 software package developed by Agilent Technologies (Santa Clara, CA). Matrix tables for the Genetic programs were produced (Linkage format: http://bioinformatics.med.utah.edu/~alun/software/docs/linkage.html) File 1: Matrix file_SNP_Map.txt File 2: Matrix file_Family_Information.txt File 3: Matrix file_Pedigree_Format.txt (Genotyping data of Linkage format) Transmission disequilibrium test was performed using the R program (http://www.r-project.org). File 4: Matrix file_results.txt

Project description:Schizophrenia is a chronic mental illness that is among the world’s top twenty causes of years lost to disability according to the global burden of disease 2019 (10.1016/S0140-6736(20)30925-9). Positive symptoms, including hallucinations and delusions in schizophrenia, often improved with conventional antipsychotic medication, which exerts its therapeutic effects mainly by antagonizing the dopamine D2 receptors. Haloperidol was one of the first antipsychotics to be approved by the FDA, and it is since then widely used for the treatment of psychotic disorders including schizophrenia. Despite its high affinity for dopamine D2 receptors, it has been shown that haloperidol interacts with other receptors, such as dopamine D3 and D4 receptors, α-adrenergic receptor 1 and to some extent 5HT2A. Dopaminergic dysfunction is known for decades to be involved in the pathophysiology of schizophrenia, but only recently has the striatum been implicated in such devasting disorder. The dorsal striatum is a brain region involved in motor, cognitive and motivational functions, highly impacted by antipsychotic drugs. Particularly, it is well-recognized that chronic haloperidol administration has a tremendous impact on striatal synaptic plasticity, by changing the volume of dorsal striatum, the number of striatal neurons and the synaptic morphology, both in humans and rodents. Despite the overwhelming evidence correlating chronic haloperidol administration with striatum alterations, so far, the exact striatal synaptic mechanism by which haloperidol exerts its beneficial effects remains unclear. Although dopamine D2 receptor blockade can be achieved within hours after haloperidol administration, the onset of action is delayed by weeks. Thus, it is crucial to better understand the neuronal mechanism behind the delayed clinical effects of haloperidol to improve the treatment outcome. Using proteomic analysis and whole-cell patch-clamp recordings (Figure 1), we demonstrate for the first time a possible mechanism by which haloperidol may be contributing to its beneficial long-term therapeutic effect. Specifically, we demonstrate that modulation of D2-MSNs by chronic haloperidol administration leads to a slow remodeling of D1-neurons that may be responsible for its positive therapeutic effects.

Project description:Genome-wide association studies (GWAS) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium (LD) makes it challenging to discern causal variants. Computational finemapping prioritized thousands of credible variants, ~98% of which lie within poorly characterized non-coding regions. To functionally validate their regulatory effects, we performed a massively parallel reporter assay (MPRA) on 5,173 finemapped schizophrenia GWAS variants in primary human neural progenitors (HNPs). We identified 440 variants with allelic regulatory effects (MPRA-positive variants), with 72% of GWAS loci containing at least one MPRA-positive variant. Transcription factor binding had modest predictive power for predicting the allelic activity of MPRA-positive variants, while GWAS association, finemap posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit eQTL signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. MPRA-positive variants differed from eQTLs, as they were more frequently located in distal neuronal enhancers. Therefore, we leveraged neuronal 3D chromatin architecture to identify 273 genes that physically interact with MPRA-positive variants. These genes annotated by chromatin interactome displayed higher mutational constraints and regulatory complexity than genes annotated by eQTLs, recapitulating a recent finding that eQTL- and GWAS-detected variants map to genes with different properties. Finally, we propose a model in which allelic activity of multiple variants within a GWAS locus can be aggregated to predict gene expression by taking chromatin contact frequency and accessibility into account. In conclusion, we demonstrate that MPRA can effectively identify functional regulatory variants and delineate previously unknown regulatory principles of schizophrenia.

Dataset Information

Schizophrenia Proteome Research

Publications

Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia.

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