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. 2022 Mar 2;10(3):585.
doi: 10.3390/biomedicines10030585.

Urinary Galectin-3 as a Novel Biomarker for the Prediction of Renal Fibrosis and Kidney Disease Progression

Shuo-Ming Ou  1   2   3   4 , Ming-Tsun Tsai  1   2   3   4 , Huan-Yuan Chen  5 , Fu-An Li  5 , Kuo-Hua Lee  1   2   3   4 , Wei-Cheng Tseng  1   2   3   4 , Fu-Pang Chang  6   7 , Yao-Ping Lin  1   2   3   4 , Ruey-Bing Yang  5 , Der-Cherng Tarng  1   2   3   4   8
Affiliations

Urinary Galectin-3 as a Novel Biomarker for the Prediction of Renal Fibrosis and Kidney Disease Progression

Shuo-Ming Ou et al. Biomedicines. .

Abstract

Plasma galectin-3 (Gal-3) is associated with organ fibrosis, but whether urinary Gal-3 is a potential biomarker of kidney disease progression has never been explored. Between 2018 and 2021, we prospectively enrolled 280 patients who underwent renal biopsy and were divided into three groups based on their urinary Gal-3 levels (<354.6, 354.6−510.7, and ≥510.8 pg/mL) to assess kidney disease progression (defined as ≥40% decline in the estimated glomerular filtration rate or end-stage renal disease) and renal histology findings. Patients in the highest urinary Gal-3 tertile had the lowest eGFRs and highest proteinuria levels. In multivariate Cox regression models, patients in the highest tertile had the highest risk of kidney disease progression (adjusted hazard ratio, 4.60; 95% confidence interval, 2.85−7.71) compared to those in the lowest tertile. Higher urinary Gal-3 levels were associated with more severe renal fibrosis. Intrarenal mRNA expression of LGALS3 (Gal-3-encoded gene) was most correlated with the renal stress biomarkers (IGFBP7 and TIMB2), renal function biomarkers (PTGDS) and fibrosis-associated genes (TGFB1). The urinary Gal-3 level may be useful for the identification of patients at high risk of kidney disease progression and renal fibrosis, and for the early initiation of treatments for these patients.

Keywords: galectin-3; kidney disease progression; renal biopsy; renal fibrosis; urinary biomarkers.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Correlation between urinary Gal-3, plasma Gal-3, eGFR, creatinine, and UPCR. (A) Correlation plots between urinary Gal-3 and plasma Gal-3 levels. (B) Correlation plots between urinary Gal-3 level and eGFR. (C) Correlation plots between urinary Gal-3 level and creatinine. (D) Correlation plots between urinary Gal-3 level and UPCR. Abbreviations: Gal-3, Galectin-3; eGFR, estimated glomerular filtration rate; UPCR, spot urine protein–creatinine ratio.
Figure 2
Figure 2
The associations between urinary Gal-3 levels and renal outcomes. (A) Urinary Gal-3 levels increased as CKD stage progressed. (B) Kaplan–Meier curves for the risks of kidney disease progression in tertiles of urinary Gal-3. (C) The associations between different pathological diagnoses and urinary Gal-3 levels. Abbreviations: Gal-3, Galectin-3; CKD, chronic kidney disease; MCD, minimal change disease; MGN, membranous glomerulonephritis; FSGS, focal segmental glomerulosclerosis; IgA, immunoglobulin A; DM, diabetes mellitus.
Figure 3
Figure 3
Correlation plots of (A) urinary Gal-3 and intrarenal LGALS3 as well as LGALS3 with (B) IGFBP7, (C) TIMP2, (D) PTGDS, (E) TGFB1 and (F) COL1A1 in kidney biopsy specimens. Abbreviations: Gal-3, galectin-3.
See this image and copyright information in PMC

References

    1. Cockwell P., Fisher L.A. The global burden of chronic kidney disease. Lancet. 2020;395:662–664. doi: 10.1016/S0140-6736(19)32977-0. - DOI - PubMed
    1. Parmar M.S. Chronic renal disease. BMJ. 2002;325:85–90. doi: 10.1136/bmj.325.7355.85. - DOI - PMC - PubMed
    1. Chen T.K., Knicely D.H., Grams M.E. Chronic Kidney Disease Diagnosis and Management: A Review. JAMA. 2019;322:1294–1304. doi: 10.1001/jama.2019.14745. - DOI - PMC - PubMed
    1. Harpole M., Davis J., Espina V. Current state of the art for enhancing urine biomarker discovery. Expert Rev. Proteom. 2016;13:609–626. doi: 10.1080/14789450.2016.1190651. - DOI - PMC - PubMed
    1. Thomas C.E., Sexton W., Benson K., Sutphen R., Koomen J. Urine collection and processing for protein biomarker discovery and quantification. Cancer Epidemiol. Prev. Biomark. 2010;19:953–959. doi: 10.1158/1055-9965.EPI-10-0069. - DOI - PMC - PubMed

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