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Background <p>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.</p> Methods <p>Data-independent acquisition (DIA) proteomic profiling was performed using a high-resolution Orbitrap Astral mass spectrometer on urine samples from 10 MG patients and 10 healthy controls. Differentially expressed proteins (DEPs) were identified and analyzed through Gene Ontology and KEGG pathway enrichment. LASSO regression and support vector machine models were applied to identify hub diagnostic proteins. The expression and diagnostic performance of the hub protein TPD52 were further validated in an independent cohort of 34 participants using ELISA.</p> Results <p>A total of 2,003 urinary proteins were identified between MG patients and healthy controls, among which 216 were significantly differentially expressed (|fold change| ≥ 1.2, <i>p</i> &lt; 0.05). Enrichment analysis revealed that these DEPs were associated with neurodegenerative and neuroinflammatory diseases. Eight key proteins (TPD52, SORL1, PLAU, TSPAN3, CASP14, QPCT, CILP2, and CTHRC1) were identified by both LASSO and SVM algorithms, all exhibiting strong diagnostic performance (AUC &gt; 0.76). In the independent validation cohort, the urinary expression of TPD52 was confirmed to be significantly elevated in MG patients, and ROC analysis yielded an AUC of 0.746, supporting its potential diagnostic value.</p> Conclusion <p>This pilot urinary proteomic study provides preliminary evidence for urinary TPD52 as a potential noninvasive biomarker for MG and suggests its possible involvement in MG pathogenesis. These findings offer new insights into the molecular mechanisms of MG and lay a foundation for applying urinary proteomics in neuroimmune disorders.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月9日

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  • Jing Yang,
  • Xi Yang,
  • Zhen-kun Zhu,
  • Liang Shen,
  • Shi-ge San,
  • Lianchen Xiao,
  • Fan Ye,
  • Chun-hua Wang,
  • Kun Meng

摘要

Background

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.

Methods

Data-independent acquisition (DIA) proteomic profiling was performed using a high-resolution Orbitrap Astral mass spectrometer on urine samples from 10 MG patients and 10 healthy controls. Differentially expressed proteins (DEPs) were identified and analyzed through Gene Ontology and KEGG pathway enrichment. LASSO regression and support vector machine models were applied to identify hub diagnostic proteins. The expression and diagnostic performance of the hub protein TPD52 were further validated in an independent cohort of 34 participants using ELISA.

Results

A total of 2,003 urinary proteins were identified between MG patients and healthy controls, among which 216 were significantly differentially expressed (|fold change| ≥ 1.2, p < 0.05). Enrichment analysis revealed that these DEPs were associated with neurodegenerative and neuroinflammatory diseases. Eight key proteins (TPD52, SORL1, PLAU, TSPAN3, CASP14, QPCT, CILP2, and CTHRC1) were identified by both LASSO and SVM algorithms, all exhibiting strong diagnostic performance (AUC > 0.76). In the independent validation cohort, the urinary expression of TPD52 was confirmed to be significantly elevated in MG patients, and ROC analysis yielded an AUC of 0.746, supporting its potential diagnostic value.

Conclusion

This pilot urinary proteomic study provides preliminary evidence for urinary TPD52 as a potential noninvasive biomarker for MG and suggests its possible involvement in MG pathogenesis. These findings offer new insights into the molecular mechanisms of MG and lay a foundation for applying urinary proteomics in neuroimmune disorders.