Monocyte LOXHD1 and RHOB Expression Predictive of Progressive Systemic Sclerosis-Associated Interstitial Lung Disease

A leading cause of death among patients with scleroderma (SSc), interstitial lung disease (ILD) remains challenging to prognosticate. The discovery of biomarkers that accurately determine which patients would benefit from close monitoring and aggressive therapy would be an essential clinical tool. We aimed to identify gene signatures that would predict progressive ILD.

We compared previously identified serum biomarkers, bulk peripheral blood mononuclear cell (PBMC) RNA gene expression (39 patients with progressive SSc-ILD and 43 patients with stable SSc-ILD), and single-cell RNA gene expression of PBMC (13 patients with progressive SSc-ILD, 14 patients with stable SSc-ILD, and 6 control participants).

In previous studies, male sex, Krebs von den Lungen 6 levels, and C-reactive protein levels were predictors of progressive disease in patients. Monocyte expression of lipoxygenase homology domains 1 (LOXHD1) and Ras homolog gene family, member B (RHOB) strongly predicted progression, suggesting a key role in immune dysregulation. LOXHD1 and related genes were enriched in inflammatory gene networks, which may support monocyte-associated inflammation in patients. RHOB was consistently up-regulated in both CD14+ and CD16+ monocytes across single-cell and bulk RNA data, underscoring robust association with progressive disease. In contrast, ataxin-2-like (ATXN2L) protein was down-regulated in patients with progressive disease, suggesting dysregulation of cellular stress responses. Additionally, S100 calcium-binding protein A12 (S100A12), chitinase-3-like protein 1 (CHI3L1), and matrix metalloproteinase-9 (MMP9), previously linked to tissue remodeling, were again associated with progression in bulk RNA sequencing and previous microarray studies, reinforcing their role in fibrosis.

With several potential biomarkers of progressive disease in patients, the next step includes validation in larger, multicenter cohorts for use in clinical decision-making.