Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Mansour, Sherry; Puthumana, Jeremy; Coca, Steven; Gentry, Mark; Parikh, Chirag
• Is Part Of: BMC nephrology. Volume 18:Issue 1(2017)
• Page Start: 1
• Page End: 13
• Publication Date: 2017-12
• Subjects: Fibrosis -- Biomarkers -- Renal biopsy -- Chronic kidney disease -- Renal disease progression -- Outcomes; Kidneys -- Diseases -- Periodicals; 616.61005
• DOI: 10.1186/s12882-017-0490-0
• Languages: English
• ISSNs: 1471-2369

Abstract

Abstract Background Fibrosis is the unifying pathway leading to chronic kidney disease. Identifying biomarkers of fibrosis may help predict disease progression. Methods We performed a systematic review to evaluate the reliability of blood and urine biomarkers in identifying fibrosis on biopsy as well as predicting renal outcomes. Using MEDLINE and EMBASE, a two-stage search strategy was implemented. Stage I identified a library of biomarkers correlating with fibrosis on biopsy. Stage II evaluated the association between biomarkers identified in stage I, and renal outcomes. Only biomarkers with moderate positive correlation with fibrosis (r > 0.40) or acceptable area under the curve (AUC >0.65) advanced to stage II. Results Stage I identified 17 studies and 14 biomarkers. Five biomarkers met criteria to advance to stage II, but only three were independently associated with renal outcomes. Transforming growth factor β (TGF-β) correlated with fibrosis (r = 0.60), and was associated with 1.7–3.9 times the risk of worsening renal function in 426 patients. Monocyte chemoattractant protein-1 (MCP-1) diagnosed fibrosis with AUC of 0.66 and was associated with 2.3–11.0 times the risk of worsening renal function in 596 patients. Matrix metalloproteinase-2 (MMP-2) correlated with fibrosis (r = 0.41), and was associated with 2.5 times the risk of worsening renal function. Conclusions Given the heterogeneity of the data due to diverse patient populations along with differing renal outcomes, a meta-analysis could not be conducted. Nonetheless we can conclude from the published data that TGF-β, MCP-1 and MMP-2 may identify patients at risk for renal fibrosis and hence worse renal outcomes.