Cargando…
Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review
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 pr...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319065/ https://www.ncbi.nlm.nih.gov/pubmed/28219345 http://dx.doi.org/10.1186/s12882-017-0490-0 |
_version_ | 1782509309478830080 |
---|---|
author | Mansour, Sherry G. Puthumana, Jeremy Coca, Steven G. Gentry, Mark Parikh, Chirag R. |
author_facet | Mansour, Sherry G. Puthumana, Jeremy Coca, Steven G. Gentry, Mark Parikh, Chirag R. |
author_sort | Mansour, Sherry G. |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12882-017-0490-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5319065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53190652017-02-24 Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review Mansour, Sherry G. Puthumana, Jeremy Coca, Steven G. Gentry, Mark Parikh, Chirag R. BMC Nephrol Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12882-017-0490-0) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-20 /pmc/articles/PMC5319065/ /pubmed/28219345 http://dx.doi.org/10.1186/s12882-017-0490-0 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Mansour, Sherry G. Puthumana, Jeremy Coca, Steven G. Gentry, Mark Parikh, Chirag R. Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review |
title | Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review |
title_full | Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review |
title_fullStr | Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review |
title_full_unstemmed | Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review |
title_short | Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review |
title_sort | biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319065/ https://www.ncbi.nlm.nih.gov/pubmed/28219345 http://dx.doi.org/10.1186/s12882-017-0490-0 |
work_keys_str_mv | AT mansoursherryg biomarkersforthedetectionofrenalfibrosisandpredictionofrenaloutcomesasystematicreview AT puthumanajeremy biomarkersforthedetectionofrenalfibrosisandpredictionofrenaloutcomesasystematicreview AT cocasteveng biomarkersforthedetectionofrenalfibrosisandpredictionofrenaloutcomesasystematicreview AT gentrymark biomarkersforthedetectionofrenalfibrosisandpredictionofrenaloutcomesasystematicreview AT parikhchiragr biomarkersforthedetectionofrenalfibrosisandpredictionofrenaloutcomesasystematicreview |