Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Extracellular Vesicle Biomarkers for Complement System Dysfunction in Schizophrenia

ABSTRACT: Schizophrenia has a high rate of misdiagnosis, leading to inappropriate or delayed treatment. Combining with extracellular vesicles’ (EVs) proteome profiling and XGBoost-based machine learning, we developed new pan-EVs markers and yielded personalized discrimination scores (PDS) for schizophrenia diagnosis, subtyping and predicting treatment response.

ORGANISM(S): Homo Sapiens

SUBMITTER: Donghong Cui

PROVIDER: PXD040261 | iProX | Mon Feb 20 00:00:00 GMT 2023

REPOSITORIES: iProX

ACCESS DATA

Json Xml

Publications

Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

Xue Ting T Liu Wenxin W Wang Lijun L Shi Yuan Y Hu Ying Y Yang Jing J Li Guiming G Huang Hongna H Cui Donghong D

Brain : a journal of neurology 20240301 3

Schizophrenia, a complex neuropsychiatric disorder, frequently experiences a high rate of misdiagnosis due to subjective symptom assessment. Consequently, there is an urgent need for innovative and objective diagnostic tools. In this study, we used cutting-edge extracellular vesicles' (EVs) proteome profiling and XGBoost-based machine learning to develop new markers and personalized discrimination scores for schizophrenia diagnosis and prediction of treatment response. We analysed plasma and pla ...[more]

PMID: 37816260

Similar Datasets

Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

Project description:Schizophrenia, a complex neuropsychiatric disorder, frequently experiences a high rate of misdiagnosis due to subjective symptom assessment. Consequently, there is an urgent need for innovative and objective diagnostic tools. In this study, we used cutting-edge extracellular vesicles' (EVs) proteome profiling and XGBoost-based machine learning to develop new markers and personalized discrimination scores for schizophrenia diagnosis and prediction of treatment response. We analysed plasma and plasma-derived EVs from 343 participants, including 100 individuals with chronic schizophrenia, 34 first-episode and drug-naïve patients, 35 individuals with bipolar disorder, 25 individuals with major depressive disorder and 149 age- and sex-matched healthy controls. Our innovative approach uncovered EVs-based complement changes in patients, specific to their disease-type and status. The EV-based biomarkers outperformed their plasma counterparts, accurately distinguishing schizophrenia individuals from healthy controls with an area under curve (AUC) of 0.895, 83.5% accuracy, 85.3% sensitivity and 82.0% specificity. Moreover, they effectively differentiated schizophrenia from bipolar disorder and major depressive disorder, with AUCs of 0.966 and 0.893, respectively. The personalized discrimination scores provided a personalized diagnostic index for schizophrenia and exhibited a significant association with patients' antipsychotic treatment response in the follow-up cohort. Overall, our study represents a significant advancement in the field of neuropsychiatric disorders, demonstrating the potential of EV-based biomarkers in guiding personalized diagnosis and treatment of schizophrenia.

| S-EPMC10907082 | biostudies-literature

Genetic inactivation of serine racemase produces behavioral phenotypes related to schizophrenia in mice

Project description:Abnormal N-methyl-D-aspartate receptor (NMDAR) function has been implicated in the pathophysiology of schizophrenia. D-serine is an important NMDAR modulator, and to elucidate the role of the D-serine synthesis enzyme serine racemase (Srr) in schizophrenia, we identified and characterized mice with an ENU-induced mutation that results in a complete loss of Srr activity and drastically reduced D-serine levels. Mutant mice displayed behaviors relevant to schizophrenia, including impairments in prepulse inhibition, sociability and spatial discrimination. Behavioral deficits were rescued by D-serine and the atypical antipsychotic clozapine, and were conversely, amplified by NMDAR inhibition. Expression profiling revealed that the Srr mutation influenced several genes that have been linked to schizophrenia and cognitive ability. Furthermore, analysis of Srr genetic variants in humans identified a robust association with schizophrenia. This study demonstrates that aberrant serine racemase function and diminished D-serine may contribute to schizophrenia pathogenesis, and that D-serine may be a beneficial form of treatment Keywords: genetic-mutant vs. wildtype comparison

2009-09-05 | GSE13974 | GEO

Schizophrenia metagenome

Project description:Schizophrenia metagenome

| PRJEB29415 | ENA

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions (striatum DBCBB).

Project description:Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular etiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, many residing in the vicinity of genes previously implicated in schizophrenia including NCAM1, SYNPO, GBP4, PRDM9, GADD45B and DISC1. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with etiological variation in complex disease.

2016-11-10 | GSE89705 | GEO

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions (hippocampus LNDBB).

2016-11-10 | GSE89703 | GEO

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions (cerebellum DBCBB).

2016-11-10 | GSE89702 | GEO

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions (striatum LNDBB).

2016-11-10 | GSE89706 | GEO

Schizophrenia monocytes

Project description:Schizophrenia is a severe psychiatric disorder. Another study in BD has shown an aberrant pro-inflammatory status of monocytes/macrophages. Therefore, this study aimed at studying the monocyte compartment in schizophrenia, by transcription profiling of CD14+ monocytes in patients and controls.

2010-11-20 | E-MEXP-2998 | biostudies-arrayexpress

KCNH2-3.1 mediates aberrant complement activation to impair hippocampal-medial prefrontal pathway associated with schizophrenia

Project description:Although elevated KCNH2-3.1 potassium channel expression is associated with cognitive dysfunctions and with schizophrenia, little is known about the pathophysiology of synapses in patient neurons and how elevated levels of KCNH2-3.1 potassium channel could lead to synaptic deficits in humans. Here, we identified specific and delayed disruption of hippocampal-mPFC synaptic transmission and connection unexpectedly associated with age-dependent reduction of SERPING1, CFH and CD74 in the KCNH2-3.1 overexpression transgenic mice, and dysfunctional interactions between hippocampus and prefrontal cortex in the fMRI coupling signal during working memory encoding in healthy subjects carrying schizophrenia-associated risk alleles of KCNH2 potassium channel. These three genes are enriched in neurons or microglia, and reduced expression of these genes dysregulates the complement cascade activation underlying impaired synaptic connectivity of hippocampal-mPFC projections. Knockdown of these genes’ expression impairs synapse formation, and replenishing reduced CFH gene expression rescues KCNH2-3.1-induced impaired synaptogenesis. Our results uncover a previously unrecognized role of truncated KCNH2-3.1 potassium channel mediating reduced expression of three genes mentioned above, which enhances aberrant complement cascade activation during development. These results direct an important conceptual advance that truncated KCNH2-3.1 causes synapse loss mediated by abnormally activated complement system, rather than aberrant neuronal firing, may represent the therapeutic targets for a number of patients with schizophrenia.

2019-08-23 | GSE118989 | GEO

A snapshot of blood plasma proteomics in clinical response to atypical antipsychotics in schizophrenia – An exploratory study

Project description:Antipsychotics are usually the first option to treat schizophrenia; however, for a considerable fraction of patients, it lacks efficacy. Furthermore, there are no known biomarkers to indicate a treatment’s efficacy in a patient. Schizophrenia causes a large socioeconomic burden on countries along with an unquestionable impairment of the quality of life of patients and their relatives. As proteomics can identify, quantify, and characterize proteins in different conditions, it is a powerful tool to study complex diseases such as schizophrenia, also capable of revealing potential biomarkers. To improve treatment efficacy during the early stages of schizophrenia, a critical time period, molecular markers for a positive treatment response were sought. Blood plasma samples were collected in vivo from 26 patients before treatment with the atypical antipsychotics olanzapine and risperidone; they were then classified as good (GR) and poor (PR) responders. We were able to identify a potential panel of proteins that may predict a positive outcome to olanzapine and risperidone treatment. Although still exploratory, this data will assist in the development of personalized medicine strategies with potential clinical implementation

2020-06-01 | PXD015213 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data