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. 2022 Oct;42(7):1553-1563.
doi: 10.1007/s10875-022-01318-1. Epub 2022 Jul 5.

Raised Serum Markers of T Cell Activation and Exhaustion in Granulomatous-Lymphocytic Interstitial Lung Disease in Common Variable Immunodeficiency

Affiliations

Raised Serum Markers of T Cell Activation and Exhaustion in Granulomatous-Lymphocytic Interstitial Lung Disease in Common Variable Immunodeficiency

Mai Sasaki Aanensen Fraz et al. J Clin Immunol. 2022 Oct.

Abstract

Purpose: About 20-30% of patients with common variable immunodeficiency (CVID) develop granulomatous-lymphocytic interstitial lung disease (GLILD) as one of several non-infectious complications to their immunodeficiency. The purpose of this study was to identify biomarkers that could distinguish GLILD from other non-infectious complications in CVID.

Methods: We analyzed serum biomarkers related to inflammation, pulmonary epithelium injury, fibrogenesis, and extracellular matrix (ECM) remodeling, and compared three subgroups of CVID: GLILD patients (n = 16), patients with other non-infectious complications (n = 37), and patients with infections only (n = 20).

Results: We found that GLILD patients had higher levels of sCD25, sTIM-3, IFN-γ, and TNF, reflecting T cell activation and exhaustion, compared to both CVID patients with other inflammatory complications and CVID with infections only. GLILD patients also had higher levels of SP-D and CC16, proteins related to pulmonary epithelium injury, as well as the ECM remodeling marker MMP-7, than patients with other non-infectious complications.

Conclusion: GLILD patients have elevated serum markers of T cell activation and exhaustion, pulmonary epithelium injury, and ECM remodeling, pointing to potentially important pathways in GLILD pathogenesis, novel targets for therapy, and promising biomarkers for clinical evaluation of these patients.

Keywords: CVID; Common variable immunodeficiency; GLILD; ILD; granulomatous-lymphocytic interstitial lung disease; interstitial lung disease.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flow chart of the CVID subgroups
Fig. 2
Fig. 2
Serum markers of ten biomarkers (a sCD25, b sTIM-3, c IFN-γ, d TNF, e SP-D, f CC16, g MMP-7, h sBCMA, i YKL-40 and j sCD163) associated with GLILD in a CVID population, selected by initial Kruskal Wallis testing. p values over the diagrams are calculated by Dunn’s multiple comparisons test (Bonferroni adjusted) for GLILD vs OC, and for GLILD vs IO. The IQRs of HCs are marked as shaded areas with dotted line at median

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