Insulin-like growth factor binding protein 7 as a candidate biomarker for systemic sclerosis.

OBJECTIVES

Systemic sclerosis (SSc) is an autoimmune disease clinically characterised by skin and internal organs fibrosis with high mortality. However, the pathogenesis of SSc is still controversial and the effect of the current treatment is far from satisfactory. We aimed to find out novel candidate genes related to the pathological process in SSc.

METHODS

In this study, the weighted correlation network analysis (WGCNA) was conducted to identify the key module and hub genes most related to SSc in GSE58095, a microarray dataset from the Gene Expression Omnibus (GEO) database. Also, the key module was analysed by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then we validated hub genes in other datasets (GSE32413, GSE125362, GSE45485, GSE76885, GSE95065). The serum of 37 patients with SSc and 25 healthy control subjects (HCs) were recruited and detected by Enzyme-Linked Immunosorbent Assay (ELISA).

RESULTS

Five interested genes (IGFBP7, LRRC32, STMN2, C1QTNF5, CPXM1) were up-regulated in SSc microarray datasets from the GEO. And the level of serum IGFBP7, which encodes a secreted protein, was upregulated in SSc patients-also in dcSSc patients and SSc with ILD patients.

CONCLUSIONS

Among the five interested genes, the IGFBP7 was a novel candidate gene for SSc and may be served as potential target and early biomarker for accurate treatment, which also provides further insights into the pathogenesis of SSc at the molecular level.