Inter-alpha-trypsin inhibitor heavy chain h3 is a potential biomarker for disease activity in myasthenia gravis

Neurology Medical Laboratory Science Information Science Artificial Intelligence Medicine Cell Biology Biochemistry Life Sciences Immunology
myasthenia gravis biomarker inter-alpha-trypsin inhibitor heavy chain h3 muscle proteomics neuromuscular junction acetylcholine receptor

Research Background

Myasthenia Gravis (MG) is a chronic antibody-mediated autoimmune disease that primarily affects synaptic transmission at the neuromuscular junction. Approximately 85% of MG patients are antibody-mediated targeting acetylcholine receptors (AChR). The clinical features of this disease include muscle weakness, especially fatigue-induced muscle weakness. Although some current anti-AChR antibody levels serve as diagnostic indicators, their value in predicting disease activity remains controversial. This creates a knowledge gap in the MG field—lacking biomarkers that indicate disease activity and identify high-risk patients. Given the emerging new treatment strategies for MG, identifying effective biomarkers to stratify patients and enhance monitoring has become an urgent need.

Source of the Paper

This study was jointly conducted by scholars Christina B. Schroeter, Christopher Nelke, Frauke Stascheit, Niklas Huntemann, Corinna Preusse, Vera Dobelmann, Lukas Theissen, Marc Pawlitzki, and others. The article was published in the 2024 volume of the journal “Acta Neuropathologica,” with the paper number 147:102.

Experimental Design and Methods

The main goal of this study is to find potential serum biomarkers for MG. The study used a mass spectrometry-based proteomics serum analysis method, including two independent MG antibody-positive patient cohorts—an exploration cohort of 114 patients and a validation cohort of 140 patients.

  1. Sample Collection and Clinical Data:

    • Patients were recruited from two MG specialty centers, namely Heinrich Heine University in Düsseldorf and Charité Medical Center in Berlin.
    • The recruitment period was from January 2016 to January 2022. All patients signed informed consent forms.
    • Patients’ conditions were assessed using scales (QMG and MG-ADL) and classified as “early onset” or “late onset.”

  2. Mass Spectrometry Analysis:

    • After pre-treatment, serum samples underwent mass spectrometry, identifying a total of 21,161 peptides.
    • Machine learning algorithms (ML) were used to analyze the data to determine potential biomarkers.

  3. Data Validation:

    • Enzyme-linked immunosorbent assay (ELISA) was used to verify protein expression levels and compare other MG subgroups and patients with myositis and neuropathy.
    • Radioimmunoassay (RIA) measured anti-AChR antibody levels.
    • Immunohistochemistry and immunofluorescence staining were used to verify ITIH3 localization in muscle biopsies.

Research Results

Machine learning algorithms identified ITIH3 (Inter-alpha-trypsin inhibitor heavy chain 3) as a potential serum biomarker reflecting disease activity.

  1. Proteomics Analysis:

    • Serum levels of ITIH3 correlated with disease activity scores in both the exploration and validation cohorts and were confirmed by ELISA.
    • ITIH3 showed significant expression at the neuromuscular junction in MG patients, but not in healthy controls.

  2. Significance of the Biomarker:

    • Serum levels of ITIH3 were positively correlated with disease activity, indicating its ability to reflect disease activity and predict treatment response.
    • In patients with ineffective treatment, ITIH3 levels did not change significantly.

  3. Result Validation:

    • ELISA validated ITIH3 specificity in anti-AChR antibody-positive MG, anti-MuSK antibody-positive MG, and other diseases.
    • ITIH3 measurements by ELISA and mass spectrometry were highly consistent.

  4. Pathological Validation:

    • Immunohistochemical analyses showed ITIH3 aggregated at the neuromuscular junction in MG patients and co-localized with neuron-specific enolase (NSE) and terminal complement complex (C5b-9).
    • Co-precipitation experiments identified ITIH3 interacting proteins such as Desmin and Plectin, which play important roles in maintaining the structural integrity of the neuromuscular junction.

Conclusion and Significance

This study proposes ITIH3 as a potential biomarker for MG disease activity for the first time and verifies its specificity and reliability through multiple experimental methods. The study also demonstrates the relationship of ITIH3 with neuromuscular junction structural damage and complement activation, providing clues to understand its pathological role in MG. Future research should further explore ITIH3’s application in clinical practice to improve disease management and treatment outcomes for MG patients.

Highlights and Innovations

  • Important Finding: Identified ITIH3 as a potential biomarker for MG disease activity and treatment response.
  • Method Innovation: Combined mass spectrometry analysis and machine learning algorithms, offering a novel biomarker discovery strategy.
  • Clinical Value: The study indicates that ITIH3 has the potential for widespread clinical application as a serum biomarker, aiding in more precise monitoring of disease progression and evaluation of treatment efficacy.

This study provides new research ideas and methods for the MG field, laying the foundation for future developments.