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A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases
BACKGROUND: Clinical and histological parameters are valid prognostic markers in renal disease, although they may show considerable interindividual variability and sometimes limited prognostic value. Novel molecular markers and pathways have the potential to increase the predictive prognostic value...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4301948/ https://www.ncbi.nlm.nih.gov/pubmed/25540021 http://dx.doi.org/10.1186/s12920-014-0075-8 |
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author | Neuwirt, Hannes Perco, Paul Kainz, Alexander Mühlberger, Irmgard Leierer, Johannes Braniff, Suzie-Jane Mayer, Bernd Mayer, Gert Rudnicki, Michael |
author_facet | Neuwirt, Hannes Perco, Paul Kainz, Alexander Mühlberger, Irmgard Leierer, Johannes Braniff, Suzie-Jane Mayer, Bernd Mayer, Gert Rudnicki, Michael |
author_sort | Neuwirt, Hannes |
collection | PubMed |
description | BACKGROUND: Clinical and histological parameters are valid prognostic markers in renal disease, although they may show considerable interindividual variability and sometimes limited prognostic value. Novel molecular markers and pathways have the potential to increase the predictive prognostic value of the so called “traditional markers”. METHODS: Transcriptomics profiles from laser-capture microdissected proximal tubular epithelial cells from routine kidney biopsies were correlated with a chronic renal damage index score (CREDI), an inflammation score (INSCO), and clinical parameters. We used data from 20 renal biopsies with various proteinuric renal diseases with a median follow-up of 49 months (discovery cohort). For validation we performed microarrays from whole kidney biopsies from a second cohort consisting of 16 patients with a median follow-up time of 28 months (validation cohort). RESULTS: 562 genes correlated with the CREDI score and 285 genes correlated with the INSCO panel, respectively. 39 CREDI and 90 INSCO genes also correlated with serum creatinine at follow-up. After hierarchical clustering we identified 5 genes from the CREDI panel, and 10 genes from the INSCO panel, respectively, which showed kidney specific gene expression. After exclusion of genes, which correlated to each other by > 50% we identified VEGF-C from the CREDI panel and BMP7, THBS1, and TRIB1 from the INSCO panel. Traditional markers for chronic kidney disease progression and inflammation score predicted 44% of the serum creatinine variation at follow-up. VEGF-C did not further enhance the predictive value, but BMP7, THBS1 and TRIB1 together predicted 94% of the serum creatinine at follow up (p < 0.0001). The model was validated in a second cohort of patients yielding also a significant prediction of follow up creatinine (48%, p = 0.0115). CONCLUSION: We identified and validated a panel of three genes in kidney biopsies which predicted serum creatinine at follow-up and therefore might serve as biomarkers for kidney disease progression. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-014-0075-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4301948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43019482015-01-22 A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases Neuwirt, Hannes Perco, Paul Kainz, Alexander Mühlberger, Irmgard Leierer, Johannes Braniff, Suzie-Jane Mayer, Bernd Mayer, Gert Rudnicki, Michael BMC Med Genomics Research Article BACKGROUND: Clinical and histological parameters are valid prognostic markers in renal disease, although they may show considerable interindividual variability and sometimes limited prognostic value. Novel molecular markers and pathways have the potential to increase the predictive prognostic value of the so called “traditional markers”. METHODS: Transcriptomics profiles from laser-capture microdissected proximal tubular epithelial cells from routine kidney biopsies were correlated with a chronic renal damage index score (CREDI), an inflammation score (INSCO), and clinical parameters. We used data from 20 renal biopsies with various proteinuric renal diseases with a median follow-up of 49 months (discovery cohort). For validation we performed microarrays from whole kidney biopsies from a second cohort consisting of 16 patients with a median follow-up time of 28 months (validation cohort). RESULTS: 562 genes correlated with the CREDI score and 285 genes correlated with the INSCO panel, respectively. 39 CREDI and 90 INSCO genes also correlated with serum creatinine at follow-up. After hierarchical clustering we identified 5 genes from the CREDI panel, and 10 genes from the INSCO panel, respectively, which showed kidney specific gene expression. After exclusion of genes, which correlated to each other by > 50% we identified VEGF-C from the CREDI panel and BMP7, THBS1, and TRIB1 from the INSCO panel. Traditional markers for chronic kidney disease progression and inflammation score predicted 44% of the serum creatinine variation at follow-up. VEGF-C did not further enhance the predictive value, but BMP7, THBS1 and TRIB1 together predicted 94% of the serum creatinine at follow up (p < 0.0001). The model was validated in a second cohort of patients yielding also a significant prediction of follow up creatinine (48%, p = 0.0115). CONCLUSION: We identified and validated a panel of three genes in kidney biopsies which predicted serum creatinine at follow-up and therefore might serve as biomarkers for kidney disease progression. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-014-0075-8) contains supplementary material, which is available to authorized users. BioMed Central 2014-12-24 /pmc/articles/PMC4301948/ /pubmed/25540021 http://dx.doi.org/10.1186/s12920-014-0075-8 Text en © Neuwirt et al.; licensee BioMed Central. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Neuwirt, Hannes Perco, Paul Kainz, Alexander Mühlberger, Irmgard Leierer, Johannes Braniff, Suzie-Jane Mayer, Bernd Mayer, Gert Rudnicki, Michael A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases |
title | A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases |
title_full | A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases |
title_fullStr | A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases |
title_full_unstemmed | A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases |
title_short | A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases |
title_sort | 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4301948/ https://www.ncbi.nlm.nih.gov/pubmed/25540021 http://dx.doi.org/10.1186/s12920-014-0075-8 |
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