Identification of Galectin-3 as Potential Biomarkers for Renal Fibrosis by RNA-Sequencing and Clinicopathologic Findings of Kidney Biopsy

Abstract

Background: Galectin-3 (Gal-3) is a multifunctional glycan-binding protein shown to be linked to chronic inflammation and fibrogenesis. Plasma Gal-3 is associated with proteinuria and renal dysfunction, but its role has never been confirmed with kidney biopsy results. In our study, we aimed to explore the expression of Gal-3 in biopsy-proven patients, and we tested the hypothesis that chronic kidney disease (CKD) leads to upregulation of plasma Gal-3 expression in corresponding biopsy findings and RNA sequencing analysis. Method: In 249 patients (male/female: 155/94, age: 57.2 ± 16.3 years) who underwent kidney biopsy, plasma levels of Gal-3 were measured to estimate the association of renal fibrosis. Relationships between plasma Gal-3 levels, estimated glomerular filtration rate (eGFR) and renal histology findings were also assessed. We further examined the gene expression of Gal-3 in RNA-sequencing analysis in biopsy-proven patients. Results: Compared to patients without CKD, CKD patients had higher levels of plasma Gal-3 (1,016.3 ± 628.1 pg/mL vs. 811.6 ± 369.6 pg/ml; P = 0.010). Plasma Gal-3 was inversely correlated with eGFR (P = 0.005) but not with proteinuria. Higher Gal-3 levels were associated with interstitial fibrosis, tubular atrophy and vascular intimal fibrosis. RNA-sequencing analysis showed the upregulation of Gal-3 in fibrotic kidney biopsy samples, and the differentially expressed genes were mainly enhanced in immune cell activation and the regulation of cell-cell adhesion. Conclusions: Plasma Gal-3 levels are inverse correlated with eGFR but positively correlated with renal fibrosis, which may be involved in the immune response and associated pathways. These findings support the role of Gal-3 as a predictive marker of renal fibrosis.

Keywords: RNA-sequencing analysis; chronic kidney disease; galectin-3; interstitial fibrosis; kidney biopsy; tubular atrophy.

Figure 1

Correlation between plasma Gal-3, eGFR, creatinine, UACR and UPCR. (A) Correlation plots between Gal-3 and eGFR. (B) Correlation plots between Gal-3 and creatinine. (C) Correlation plots between Gal-3 and UACR. (D) Correlation plots between Gal-3 and UPCR. Gal-3, Galectin-3; eGFR, estimated glomerular filtration rate; UACR, urine albumin-creatinine ratio; UPCR, urine protein-creatinine ratio.

Figure 2

Plasma Gal-3 predicts risk of annual change of eGFR in non-CKD patients whose eGFR > 60 ml/min/1.73 m². (A) Restricted cubic spline plots of the association between annual change of eGFR and plasma Gal-3 levels. The red line indicates the change of eGFR with the respective 95% confidence interval (gray area). (B) Annual change of eGFR according to tertile of plasma Gal-3 levels. Gal-3, Galectin-3; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease.

Figure 3

Kidney biopsy specimens for pathology and RNA sequencing analysis. (A) The algorithm of the collections of kidney biopsy specimens. (B) The associations between different pathological diagnoses and plasma Gal-3 levels. (C) The hierarchical clustering heat map shows the expression of different genes between fibrotic groups and non-fibrotic controls. Gal-3, galectin-3; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; MCD, minimal change disease; FSGS, focal segmental glomerulosclerosis; IgA, immunoglobulin A; DM, diabetes mellitus.

Figure 4

Volcano plots and GO and KEGG enrichment analysis according to RNA sequence analysis. (A) Volcano plot of differentially expressed genes between fibrotic groups and non-fibrotic controls. (B) The biological process, cellular components and molecular function identified from the GO and (C) KEGG enrichment analysis of the RNA sequencing. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.