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Updated: Jan 20, 2026

Detection of Anti-MDA5 Autoantibodies Using HeLa Cells and Immunocytochemistry with Light Microscopy
Published on: October 31, 2025
ATR-FTIR Spectroscopy for Detection of Anti-interferon-Gamma Autoantibodies
Chanchai Hongsa1,2, Molin Wongwattanakul2,3, Patutong Chatchawal2,3
1Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand.
None:
Introduction: Adult-onset immunodeficiency (AOID) unrelated to HIV is commonly linked to anti-interferon-gamma autoantibodies (AIGAs), predisposing patients to life-threatening opportunistic infections. Current AIGA detection methods are time-consuming and resource intensive. This study aimed to develop and validate an attenuated total reflectance-Fourier transform infrared (ATR-FTIR) technique for detecting and differentiating AIGA-positive patients. Methods: We recruited individuals into three groups: AIGA-positive patients (n = 45), AIGA-negative patients (n = 15), and healthy controls (n = 15). Heparinized plasma or serum samples underwent ATR-FTIR spectroscopy. Spectral profiles were examined using principal component analysis (PCA) and partial least-squares-discriminant analysis (PLS-DA). The reference standard for AIGA concentration was determined by the inhibitory enzyme-linked immunosorbent assay (ELISA). Results: ATR-FTIR spectra revealed significant differences, especially in the amide and fingerprint regions, particularly at key wavenumbers 1632 cm-1 and 1535 cm-1. The Amide I/Amide I + II + III ratio is significant between AIGA-positive and others and a secondary structure protein conformational change α-helix to β-sheet. PCA and PLS-DA enabled effective separation of patient groups; PLS-DA and k-NN achieved 95% accuracy, 93.3% sensitivity, and 100% specificity for differentiating AIGA-positive from negative/healthy individuals (NPV 83.3%; PPV 100%). The amide region (1700-1500 cm‑1) delivered the best prediction accuracy. Conclusion: ATR-FTIR spectroscopy demonstrates significant potential as a rapid and effective diagnostic tool for differentiating AIGA-positive patients from healthy individuals, providing a valuable addition to clinical diagnostic practices. Further validation in larger, diverse populations is warranted.
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