Proteomics and Metabolomics for AKI Diagnosis

David Marx, Jochen Metzger, Martin Pejchinovski, Ryan Bruce Gil, Maria Frantzi, Agnieszka Latosinska, Iwona Belczacka, Silke Sophie Heinzmann, Holger Husi, Jerome Zoidakis, Matthias Klingele, Stefan Herget-Rosenthal

Research output: Contribution to journalArticlepeer-review

57 Citations (Scopus)
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Acute kidney injury (AKI) is a severe and frequent condition in hospitalized patients. Currently, no efficient therapy of AKI is available. Therefore, efforts focus on early prevention and potentially early initiation of renal replacement therapy to improve the outcome in AKI. The detection of AKI in hospitalized patients implies the need for early, accurate, robust, and easily accessible biomarkers of AKI evolution and outcome prediction because only a narrow window exists to implement the earlier-described measures. Even more challenging is the multifactorial origin of AKI and the fact that the changes of molecular expression induced by AKI are difficult to distinguish from those of the diseases associated or causing AKI as shock or sepsis. During the past decade, a considerable number of protein biomarkers for AKI have been described and we expect from recent advances in the field of omics technologies that this number will increase further in the future and be extended to other sorts of biomolecules, such as RNAs, lipids, and metabolites. However, most of these biomarkers are poorly defined by their AKI-associated molecular context. In this review, we describe the state-of-the-art tissue and biofluid proteomic and metabolomic technologies and new bioinformatics approaches for proteomic and metabolomic pathway and molecular interaction analysis. In the second part of the review, we focus on AKI-associated proteomic and metabolomic biomarkers and briefly outline their pathophysiological context in AKI
Original languageEnglish
Pages (from-to)63-87
Number of pages25
JournalSeminars in Nephrology
Issue number1
Early online date29 Dec 2017
Publication statusPublished - Jan 2018


  • AKI diagnosis
  • Proteomics
  • metabolomics
  • pathway analysis


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