Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database

Chiaki Kondo, Yohsuke Minowa, Takeki Uehara, Yasushi Okuno, Noriyuki Nakatsu, Atsushi Ono, Toshiyuki Maruyama, Ikuo Kato, Jyoji Yamate, Hiroshi Yamada, Yasuo Ohno, Tetsuro Urushidani

Research output: Contribution to journalArticle

47 Citations (Scopus)

Abstract

Drug-induced renal tubular injury is one of the major concerns in preclinical safety evaluations. Toxicogenomics is becoming a generally accepted approach for identifying chemicals with potential safety problems. In the present study, we analyzed 33 nephrotoxicants and 8 non-nephrotoxic hepatotoxicants to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. The compounds were administered orally or intravenously once daily to male Sprague-Dawley rats. The animals were exposed to four different doses of the compounds, and kidney tissues were collected on days 4, 8, 15, and 29. Gene expression profiles were generated from kidney RNA by using Affymetrix GeneChips and analyzed in conjunction with the histopathological changes. We used the filter-type gene selection algorithm based on t-statistics conjugated with the SVM classifier, and achieved a sensitivity of 90% with a selectivity of 90%. Then, 92 genes were extracted as the genomic biomarker candidates that were used to construct the classifier. The gene list contains well-known biomarkers, such as Kidney injury molecule 1, Ceruloplasmin, Clusterin, Tissue inhibitor of metallopeptidase 1, and also novel biomarker candidates. Most of the genes involved in tissue remodeling, the immune/inflammatory response, cell adhesion/proliferation/migration, and metabolism were predominantly up-regulated. Down-regulated genes participated in cell adhesion/proliferation/migration, membrane transport, and signal transduction. Our classifier has better prediction accuracy than any of the well-known biomarkers. Therefore, the toxicogenomics approach would be useful for concurrent diagnosis of renal tubular injury.

Original languageEnglish
Pages (from-to)15-26
Number of pages12
JournalToxicology
Volume265
Issue number1-2
DOIs
Publication statusPublished - Nov 9 2009
Externally publishedYes

Fingerprint

Toxicogenetics
Biomarkers
Genes
Databases
Kidney
Wounds and Injuries
Classifiers
Pharmaceutical Preparations
Cell adhesion
Tissue
Gene expression
Cell Adhesion
Cell Proliferation
Clusterin
Safety
Signal transduction
Ceruloplasmin
Transcriptome
Metabolism
Sprague Dawley Rats

Keywords

  • Biomarkers
  • Microarray
  • Necrosis
  • Nephrotoxicity
  • Rat
  • Toxicogenomics

ASJC Scopus subject areas

  • Toxicology

Cite this

Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database. / Kondo, Chiaki; Minowa, Yohsuke; Uehara, Takeki; Okuno, Yasushi; Nakatsu, Noriyuki; Ono, Atsushi; Maruyama, Toshiyuki; Kato, Ikuo; Yamate, Jyoji; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro.

In: Toxicology, Vol. 265, No. 1-2, 09.11.2009, p. 15-26.

Research output: Contribution to journalArticle

Kondo, C, Minowa, Y, Uehara, T, Okuno, Y, Nakatsu, N, Ono, A, Maruyama, T, Kato, I, Yamate, J, Yamada, H, Ohno, Y & Urushidani, T 2009, 'Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database', Toxicology, vol. 265, no. 1-2, pp. 15-26. https://doi.org/10.1016/j.tox.2009.09.003
Kondo, Chiaki ; Minowa, Yohsuke ; Uehara, Takeki ; Okuno, Yasushi ; Nakatsu, Noriyuki ; Ono, Atsushi ; Maruyama, Toshiyuki ; Kato, Ikuo ; Yamate, Jyoji ; Yamada, Hiroshi ; Ohno, Yasuo ; Urushidani, Tetsuro. / Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database. In: Toxicology. 2009 ; Vol. 265, No. 1-2. pp. 15-26.
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