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Urinary Proteomic Biomarkers for Diagnosis and Risk Stratification of Autosomal Dominant Polycystic Kidney Disease: A Multicentric Study

Overview of attention for article published in PLOS ONE, January 2013
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Title
Urinary Proteomic Biomarkers for Diagnosis and Risk Stratification of Autosomal Dominant Polycystic Kidney Disease: A Multicentric Study
Published in
PLOS ONE, January 2013
DOI 10.1371/journal.pone.0053016
Pubmed ID
Authors

Andreas D. Kistler, Andreas L. Serra, Justyna Siwy, Diane Poster, Fabienne Krauer, Vicente E. Torres, Michal Mrug, Jared J. Grantham, Kyongtae T. Bae, James E. Bost, William Mullen, Rudolf P. Wüthrich, Harald Mischak, Arlene B. Chapman

Abstract

Treatment options for autosomal dominant polycystic kidney disease (ADPKD) will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS), we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI). The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV) based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001) with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD.

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Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Czechia 1 1%
Canada 1 1%
Unknown 90 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 22%
Student > Ph. D. Student 14 15%
Student > Doctoral Student 7 7%
Student > Bachelor 7 7%
Student > Master 6 6%
Other 18 19%
Unknown 21 22%
Readers by discipline Count As %
Medicine and Dentistry 30 32%
Agricultural and Biological Sciences 14 15%
Biochemistry, Genetics and Molecular Biology 9 10%
Unspecified 3 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 10 11%
Unknown 26 28%