Dataset Information

Urinary Proteomic of Myasthenia Gravis

ABSTRACT: We conducted data-independent acquisition (DIA) proteomic profiling using a high-resolution Orbitrap Astral mass spectrometer on urine samples from 10 MG patients and 10 healthy volunteers.

ORGANISM(S): Homo Sapiens

SUBMITTER: Kun Meng

PROVIDER: PXD072289 | iProX | Mon Dec 22 00:00:00 GMT 2025

REPOSITORIES: iProX

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Publications

Urinary proteomic profiling reveals diagnostic biomarkers and regulatory networks in myasthenia gravis.

Yang Jing J Yang Xi X Zhu Zhen-Kun ZK Shen Liang L San Shi-Ge SG Xiao Lianchen L Ye Fan F Wang Chun-Hua CH Meng Kun K

BMC neurology 20260109 1

<h4>Background</h4>Myasthenia gravis (MG) is a chronic autoimmune neuromuscular junction disorder mediated by autoantibodies. Existing diagnostic methods mainly rely on serum antibody detection and electrophysiological testing, which are limited by invasiveness and suboptimal sensitivity and specificity. This study aimed to identify potential urinary biomarkers for noninvasive MG diagnosis using proteomics.<h4>Methods</h4>Data-independent acquisition (DIA) proteomic profiling was performed using ...[more]

PMID: 41514217

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Project description:Myasthenia gravis (MG) is an autoimmune disease affecting the neuromuscular junction, whose clinical hallmark is muscle weakness and early fatigability. Azathioprine (AZA) is commonly used in Myasthenia Gravis therapy. AZA is a purine antagonist, which inhibits the cell cycle in the resting and DNA synthesis phases. It is usually used as an immunosuppressant to block T- and B-cell proliferation. AZA, bioconverted to 6-mercaptopurine by glutathione S-transferase (GST), can be metabolized either through the hypoxanthine phosphoribosyl transferase pathway to active 6-thioguanine nucleotides (6-TGN) or through the thiopurine S-methyltransferase (TPMT) pathway to inactive methyl-thiopurine metabolites. The incorporation of active 6-TGNs into DNA, causing breaks in DNA strands resulting in interference with RNA production and thereby protein synthesis, is responsible for the drug effect. The response to AZA is determined by which metabolic pathway is being favored. While balanced use of both HPRT and TPMT pathways results in responsiveness to AZA, hyperactivity of TPMT skews the balance towards the TPMT pathway and results in unresponsiveness to AZA with no pharmacological effect. In contrast, low TPMT activity skews the balance towards the HPRT pathway, resulting in increasing side-effects due to the accumulation of 6-TGNs. Current treatments for MG therapy are often inadequate because less than 40% of patients achieve complete remission with available drugs. This reflects the lack of drugs acting on target sites for which there is strong evidence of pathogenicity and the inability to identify responder patients. No criteria for responsiveness are available, exposing patients to unpredictable failures and unpredictable side effects. These individuals are at particular risk for adverse drug reaction (ADRs) or therapeutic failure. Genetic profiling with the Affymetrix drug metabolizing enzymes and transports genotyping array offers the ability to determine 1,931 variants and 225 genes involved in drug metabolism and disposition. Accordingly, the study of well-known drug-metabolizing genes can be involved in the specific metabolic pathway of a drug, which is more likely to define genotype-phenotype association and thereby genotype profiles relevant to drug response that can be applied as predictive biomarkers for pharmacological treatment.

Dataset Information

Urinary Proteomic of Myasthenia Gravis

Publications

Urinary proteomic profiling reveals diagnostic biomarkers and regulatory networks in myasthenia gravis.

Similar Datasets

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