Unsupervised Flow Cytometry Reveals a Constant Shift Towards Activated CD4⁺ T Cell Subsets in APECED.

Area of Science:

• Immunology
• Genetics
• Computational Biology

Background:

• Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) is a rare monogenic autoimmune disorder.
• It results from loss-of-function mutations in the Autoimmune Regulator (AIRE) gene, impairing thymic negative selection.
• Previous studies indicated T cell abnormalities, including activation and regulatory failures, often based on traditional flow cytometry.

Purpose of the Study:

• To investigate CD4+ T cell populations in APECED patients using unsupervised flow cytometry analysis.
• To identify novel T cell subsets or alterations associated with the disease.
• To present an optimized unsupervised workflow for flow cytometry data analysis.

Main Methods:

• Unsupervised flow cytometry analysis of CD4+ T cells from 20 APECED patients.
• Application of an optimized workflow including data quality control, batch correction, and clustering algorithms.
• Utilized dimensionality reduction techniques for population structure analysis.

Main Results:

• Confirmed increased T cell activation extending to T helper and regulatory T cells in APECED.
• Identified regulatory T cells with diminished suppressive potential in APECED patients.
• Discovered a novel CD45RA-negative, CCR7-negative, CD31-high, CD127-mid T cell population unique to APECED.
• Overall CD4+ T cell compartment structure showed similarity between APECED patients and controls.

Conclusions:

• Unsupervised flow cytometry provides a robust method for analyzing complex T cell populations in autoimmune diseases like APECED.
• APECED is characterized by altered regulatory T cell function and a unique T cell subset.
• The developed workflow enhances data quality control and automated clustering for flow cytometry analysis.