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Related Experiment Video

Updated: Sep 6, 2025

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry
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Novel immunoprofiling method for diagnosing SLE and evaluating therapeutic response.

Jan-Mou Lee1, Ming-Huang Chen2, Kai-Yuan Chou1

  • 1Department of Advanced Research, FullHope Biomedical Co Ltd, New Taipei City, Taiwan.

Lupus Science & Medicine
|June 23, 2022
PubMed
Summary

This study reveals distinct immune cell patterns in Systemic Lupus Erythematosus (SLE) patients, developing an immune signature algorithm to aid in SLE diagnosis and understanding disease pathogenesis.

Keywords:
autoimmune diseasesautoimmunitylupus erythematosus, systemic

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Area of Science:

  • Immunology
  • Systemic Lupus Erythematosus (SLE) research
  • Diagnostic biomarker development

Background:

  • Systemic Lupus Erythematosus (SLE) diagnosis is challenging due to heterogeneous early-onset clinical manifestations.
  • Identifying reliable biomarkers for SLE is crucial for timely and accurate diagnosis.

Purpose of the Study:

  • To evaluate immunoprofiling features in SLE patients.
  • To develop an immune signature algorithm for supporting SLE diagnosis.
  • To explore the dynamic changes in immunoprofiling post-treatment.

Main Methods:

  • Analyzed immunoprofiling of peripheral blood mononuclear cells (PBMCs) from 13 newly diagnosed SLE patients and 9 healthy controls using flow cytometry.
  • Developed an immune signature score based on ranked immunoprofiling data.
  • Monitored immunoprofiling changes in four SLE patients after immunosuppressant treatment.

Main Results:

  • Identified significant differences in 29 out of 93 immune cell subsets between SLE patients and controls.
  • Observed lower percentages of dendritic and natural killer cells, and higher CD8+ T-cell percentages in SLE patients.
  • Found distinct immune cell subset profiles, including regulatory T cells and PD-1/PD-L1 expression, correlating with disease activity (SLEDAI-2K) post-treatment.

Conclusions:

  • Immunoprofiling reveals a distinct pattern in SLE patients compared to healthy controls.
  • The developed immune signature algorithm shows potential for supporting SLE diagnosis.
  • These findings contribute to understanding SLE pathogenesis and developing novel immune-based diagnostic tools.