Development of an efficient, robust MS-based platform for early detection of acute kidney injury

Lead Research Organisation: University of Glasgow
Department Name: College of Medical, Veterinary &Life Sci


Acute Kidney Injury (AKI) as a severe complication in hospitalized patients, a life-threatening complication that still has a high mortality. In addition, AKI is associated with high costs for intensive and prolongued treatment. To date, no early detection of AKI is possible. However, early detection is essential to initiate appropriate treatment, thereby preventing development of disease, or at least reducing the severity. Such an appproach would reduce mortality, and also costs.
The proposal aims at developing a technology platform that enables early detection of AKI, based on specific proteins an peptides in urine, so-called biomarkers. These biomarkers have already been identified. For their efficient clinical application a plattform that allows accurate and fast analysis has to be developed, this development is the scope of the project. Upon successful completion of the project, a robust technology will be available that enables early detection of AKI, hence initiation of appropriate early therapeutic measures. We anticipate that as a result of this project, mortality due to AKI can be significantly decreased, and costs can be reduced.

Technical Summary

Acute kidney injury (AKI) is a frequent and serious condition in critically-ill patients, increasing mortality rate independent of other risk factors. Currently, serum creatinine is monitored to detect AKI; this is an inadequate test, enabling only late-stage detection. Earlier AKI detection is an important component of reducing renal morbidity, and mortality in the critical care population. New biomarkers cystatin C, kidney injury molecule-1(KIM-1), neutrophil gelatinase-associated lipocalin (NGAL) and interleukin-18 (IL-18), promised earlier diagnosis, but results were not convincing when validated in independent studies. Proteome analysis, by capillary electrophoresis mass spectrometry (CE-MS), has enabled the identification and validation of a novel urinary biomarker panel for AKI detection. However, CE-MS is slow, expensive, and inappropriate for routine intensive care unit (ICU) use. This proposal will establish an alternative analytical platform to assess our novel biomarker panel, which is efficient, inexpensive and acceptable for routine ICU use. Two platforms - matrix assisted laser desorption/ionisation-time of flight (MALDI-TOF) and multiple reaction monitoring (MRM) triple-quad-MS - will be explored as dual development strategy to optimise outcome.


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