Please use this identifier to cite or link to this item: https://doi.org/10.2174/1389200220666190711114504
Title: Serial Quantification of Urinary Protein Biomarkers to Predict Drug-induced Acute Kidney Injury
Authors: Da, Yi
Akalya, K 
Murali, Tanusya 
Vathsala, Anantharaman 
Tan, Chuen-Seng 
Low, Sanmay
Lim, Hui-Ning
Teo, Boon-Wee 
Lau, Titus
Ong, Lizhen
Chua, Horng-Ruey 
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Pharmacology & Pharmacy
Antimicrobials
beta-2-microglobulin
biomarkers
calcineurin inhibitors
clusterin
drug-induced acute kidney injury
nephrotoxicity
BETA-LACTAM
NEPHROTOXICITY
VANCOMYCIN
METAANALYSIS
COMBINATION
GENTAMICIN
MOLECULE-1
CLUSTERIN
TOXICITY
KIM-1
Issue Date:  1
Publisher: BENTHAM SCIENCE PUBL LTD
Citation: Da, Yi, Akalya, K, Murali, Tanusya, Vathsala, Anantharaman, Tan, Chuen-Seng, Low, Sanmay, Lim, Hui-Ning, Teo, Boon-Wee, Lau, Titus, Ong, Lizhen, Chua, Horng-Ruey (1). Serial Quantification of Urinary Protein Biomarkers to Predict Drug-induced Acute Kidney Injury. CURRENT DRUG METABOLISM 20 (8) : 656-664. ScholarBank@NUS Repository. https://doi.org/10.2174/1389200220666190711114504
Abstract: Background: Drug-induced Acute Kidney Injury (AKI) develops in 10-15% of patients who receive nephrotoxic medications. Urinary biomarkers of renal tubular dysfunction may detect nephrotoxicity early and predict AKI. Methods: We prospectively studied patients who received aminoglycosides, vancomycin, amphotericin, or calcineurin inhibitors, and collected their serial urine while on therapy. Patients who developed drug-induced AKI (ful-filling KDIGO criteria) were matched with non-AKI controls in a 1:2 ratio. Their urine samples were batch-analyzed at time-intervals leading up to AKI onset; the latter benchmarked against the final day of nephrotoxic therapy in non-AKI controls. Biomarkers examined include clusterin, beta-2-microglobulin, KIM1, MCP1, cystatin-C, trefoil-factor-3, NGAL, interleukin-18, GST-Pi, calbindin, and osteopontin; biomarkers were normalized with corresponding urine creatinine. Results: Nine of 84 (11%) patients developed drug-induced AKI. Biomarkers from 7 AKI cases with pre-AKI samples were compared with those from 14 non-AKI controls. Corresponding mean ages were 55(±17) and 52(±16) years; baseline eGFR were 99(±21) and 101(±24) mL/min/1.73m2 (all p=NS). Most biomarker levels peaked before the onset of AKI. Median levels of 5 biomarkers were significantly higher in AKI cases than controls at 1-3 days before AKI onset (all µg/mmol): clusterin [58(8-411) versus 7(3-17)], beta-2-microglobulin [1632(913-3823) versus 253(61-791)], KIM1 [0.16(0.13-0.76) versus 0.07(0.05-0.15)], MCP1 [0.40(0.16-1.90) versus 0.07(0.04-0.17)], and cystatin-C [33(27-2990) versus 11(7-19)], all p<0.05; their AUROC for AKI prediction were >0.80 (confidence intervals >0.50), with average accuracy highest for clusterin (86%), followed by beta-2-microglobulin, cystatin-C, MCP1, and KIM1 (57%) after cross-validation. Conclusion: Serial surveillance of these biomarkers could improve the lead time for nephrotoxicity detection by days.
Source Title: CURRENT DRUG METABOLISM
URI: https://scholarbank.nus.edu.sg/handle/10635/229107
ISSN: 13892002
18755453
DOI: 10.2174/1389200220666190711114504
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