# Th17-related genes PGAP1 and TMBIM1 serve as potential diagnostic and predictive biomarkers in systemic sclerosis: bioinformatic identification and murine model validation

## TL;DR

This study identifies PGAP1 and TMBIM1 as Th17-related genes that could help diagnose and treat systemic sclerosis, a connective tissue disease.

## Contribution

Novel identification and validation of PGAP1 and TMBIM1 as Th17-related biomarkers with diagnostic and therapeutic potential in systemic sclerosis.

## Key findings

- PGAP1 and TMBIM1 showed high diagnostic accuracy with an AUC of 0.9852 in a nomogram model.
- Both genes are linked to immune cell infiltration and fibrotic pathways like oxidative phosphorylation and proteasome.
- In a mouse model, TMBIM1 was upregulated while PGAP1 was downregulated in fibrotic tissues.

## Abstract

T helper 17 (Th17) cells participate in all pathological stages of systemic sclerosis (SSc). Molecular markers associated with Th17 cells hold promise as therapeutic targets for SSc. This study aims to screen and validate key genes related to Th17 cells that have diagnostic and predictive value in SSc and to identify potential therapeutic targets for SSc.

Candidate genes were identified by intersecting Th17 cell-dysregulated genes (TCDRGs) from single-cell RNA sequencing data (GSE292979) with bulk RNA sequencing data (GSE95065). Machine learning algorithms, receiver operating characteristic (ROC) curve analysis, and expression level validation were employed to further identify key Th17-related genes. Subsequently, the diagnostic and predictive capabilities of these Th17-related genes were validated using a nomogram model. Then, gene set enrichment analysis (GSEA), immune infiltration analysis, drug prediction, and molecular docking were conducted on the key genes. Finally, the expression of genes was confirmed in bleomycin (BLM)-induced SSc mice.

We identified 48 candidate genes from 472 TCDRGs and 1653 bulk DEGs. Using the Boruta feature selection algorithm and random forest (RF) model, two genes related to Th17 cells, PGAP1 and TMBIM1, were identified. PGAP1 and TMBIM1 exhibited exceptional discriminative efficiency with an AUC of 0.9852 in the nomogram model. Moreover, GSEA analysis revealed that both genes were co-enriched in pathways such as oxidative phosphorylation and the proteasome. Immune infiltration analysis indicated that PGAP1 and TMBIM1 were closely associated with five types of immune cells, exhibiting opposing correlation trends, such as with M1-type macrophages. Drug prediction analysis identified 45 potential drugs targeting PGAP1 and 36 targeting TMBIM1. Notably, Bafilomycin A1 was associated with PGAP1, while Ciglitazone was associated with TMBIM1, and both displayed stable binding conformations. Finally, in a BLM-induced mouse model, quantitative real-time PCR analysis and immunohistochemical experiments revealed upregulation of TMBIM1, whereas PGAP1 expression was downregulated in fibrotic skin and lung tissues. These results suggest the relevance of PGAP1 and TMBIM1 in fibrotic processes. However, further studies using human SSc samples are warranted to confirm their diagnostic and therapeutic potential.

PGAP1 and TMBIM1 have been identified as key molecules associated with Th17 cells. They exhibit significant diagnostic and predictive value in SSc and show promise as therapeutic targets for SSc.
Key Points• SSc skin tissues exhibit significant changes in the composition of immune and non-immune cells.• PGAP1 and TMBIM1 have been identified as key molecules in SSc that are associated with Th17 cells, showing remarkable diagnostic accuracy.• PGAP1 and TMBIM1 exhibit a negative correlation in their expression patterns in SSc.

Key Points

• SSc skin tissues exhibit significant changes in the composition of immune and non-immune cells.

• PGAP1 and TMBIM1 have been identified as key molecules in SSc that are associated with Th17 cells, showing remarkable diagnostic accuracy.

• PGAP1 and TMBIM1 exhibit a negative correlation in their expression patterns in SSc.

The online version contains supplementary material available at 10.1007/s10067-026-07950-1.