Dataset Information

Identification of Novel Biomarkers for Predicting Kidney Injury Due to Drugs Using "Omic" Strategies.

ABSTRACT: Drug-induced kidney injury accounts for 20% of community- and hospital-acquired cases of acute kidney injury (AKI). The incidence is higher among older individuals, who often have co-existing morbidities and are exposed to more diagnostic procedures and therapies. While demographic and clinical components have been identified as risk factors, the proposed cellular mechanisms of drug-induced kidney injury are numerous and complicated. There are also limitations recognized in the use of traditional biomarkers, such as serum creatinine and blood urea nitrogen, to provide high sensitivity, specificity, and timeliness to identification of drug-induced kidney injury. Therefore, novel biomarkers are currently being investigated, identified, developed, and validated for their performance over the traditional biomarkers. This review will provide an overview of drug-induced kidney injury and will discuss what is known regarding "omic" (proteomic, genomic, transcriptomic, and metabolomic) biomarker strategies for drugs known to induce nephrotoxicity.

SUBMITTER: Awdishu L

PROVIDER: S-EPMC7719321 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Novel Biomarkers for Predicting Kidney Injury Due to Drugs Using "Omic" Strategies.

Awdishu Linda L Atilano-Roque Amandla A Tuey Stacey S Joy Melanie S MS

Pharmacogenomics and personalized medicine 20201202

Drug-induced kidney injury accounts for 20% of community- and hospital-acquired cases of acute kidney injury (AKI). The incidence is higher among older individuals, who often have co-existing morbidities and are exposed to more diagnostic procedures and therapies. While demographic and clinical components have been identified as risk factors, the proposed cellular mechanisms of drug-induced kidney injury are numerous and complicated. There are also limitations recognized in the use of traditiona ...[more]

PMID: 33293850

Similar Datasets

Project description:The study of novel urinary biomarkers of acute kidney injury has expanded exponentially. Effective interpretation of data and meaningful comparisons between studies require awareness of factors that can adversely affect measurement. We examined how variations in short-term storage and processing might affect the measurement of urine biomarkers.Cross-sectional prospective.Hospitalized patients from 2 sites: Yale New Haven Hospital (n=50) and University of California, San Francisco Medical Center (n=36).We tested the impact of 3 urine processing conditions on these biomarkers: (1) centrifugation and storage at 4°C for 48 hours before freezing at -80°C, (2) centrifugation and storage at 25°C for 48 hours before freezing at -80°C, and (3) uncentrifuged samples immediately frozen at -80°C.Urine concentrations of 5 biomarkers: neutrophil gelatinase-associated lipocalin (NGAL), interleukin 18 (IL-18), kidney injury molecule 1 (KIM-1), liver-type fatty acid-binding protein (L-FABP), and cystatin C.We measured urine biomarkers by established enzyme-linked immunosorbent assay methods. Biomarker values were log-transformed, and agreement with a reference standard of immediate centrifugation and storage at -80°C was compared using concordance correlation coefficients (CCCs).Neither storing samples at 4°C for 48 hours nor centrifugation had a significant effect on measured levels, with CCCs higher than 0.9 for all biomarkers tested. For samples stored at 25°C for 48 hours, excellent CCC values (>0.9) also were noted between the test sample and the reference standard for NGAL, cystatin C, L-FABP and KIM-1. However, the CCC for IL-18 between samples stored at 25°C for 48 hours and the reference standard was 0.81 (95% CI, 0.66-0.96).No comparisons to fresh, unfrozen samples; no evaluation of the effect of protease inhibitors.All candidate markers tested using the specified assays showed high stability with both short-term storage at 4°C and without centrifugation prior to freezing. For optimal fidelity, urine for IL-18 measurement should not be stored at 25°C before long-term storage or analysis.

Project description:Acute kidney injury (AKI) is a global public health concern associated with high morbidity, mortality, and health-care costs, and the therapeutic measures are still limited. This study aims to investigate crucial genes correlated with AKI, and their potential functions, which might contribute to a better understanding of AKI pathogenesis. The high-throughput data GSE52004 and GSE98622 were downloaded from Gene Expression Omnibus; four group sets were extracted and integrated. Differentially expressed genes (DEGs) in the four group sets were identified by limma package in R software. The overlapping DEGs among four group sets were further analyzed by the VennDiagram package, and their potential functions were analyzed by the GO and KEGG pathway enrichment analyses using the DAVID database. Furthermore, the protein-protein interaction (PPI) network was constructed by STRING, and the functional modules of the PPI network were filtered by MCODE and ClusterOne in Cytoscape. Hub genes of overlapping DEGs were identified by Cyto-Hubba and cytoNCA. The expression of 35 key genes was validated by quantitative real-time PCR (qRT-PCR). Western blot and immunofluorescence were performed to validate an important gene Egr1. A total of 722 overlapping DEGs were differentially expressed in at least three group sets. These genes mainly enriched in cell proliferation and fibroblast proliferation. Additionally, 5 significant modules and 21 hub genes, such as Havcr1, Krt20, Sox9, Egr1, Timp1, Serpine1, Edn1, and Apln were screened by analyzing the PPI networks. The 5 significant modules were mainly enriched in complement and coagulation cascades and Metabolic pathways, and the top 21 hub genes were mainly enriched in positive regulation of cell proliferation. Through validation, Krt20 were identified as the top 1 upregulated genes with a log2 (fold change) larger than 10 in all these 35 genes, and 21 genes were validated as significantly upregulated; Egr1 was validated as an upregulated gene in AKI in both RNA and protein level. In conclusion, by integrated analysis of different high-throughput data and validation by experiment, several crucial genes were identified in AKI, such as Havcr1, Krt20, Sox9, Egr1, Timp1, Serpine1, Edn1, and Apln. These genes were very important in the process of AKI, which could be further utilized to explore novel diagnostic and therapeutic strategies.

Dataset Information

Identification of Novel Biomarkers for Predicting Kidney Injury Due to Drugs Using "Omic" Strategies.

Publications

Identification of Novel Biomarkers for Predicting Kidney Injury Due to Drugs Using "Omic" Strategies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets