Details

Autor(en) / Beteiligte

• Bushel, P.R
• Heinloth, A.N
• Li, J
• Huang, L
• Chou, J.W
• Boorman, G.A
• Malarkey, D.E
• Houle, C.D
• Ward, S.M
• Wilson, R.E
• Fannin, R.D
• Russo, M.W
• Watkins, P.B
• Tennant, R.W
• Paules, R.S

Titel

Blood gene expression signatures predict exposure levels

Ist Teil von

• Proceedings of the National Academy of Sciences - PNAS, 2007-11, Vol.104 (46), p.18211-18216

Ort / Verlag

United States: National Academy of Sciences

Erscheinungsjahr

2007

Quelle

Elektronische Zeitschriftenbibliothek (Open access)

Beschreibungen/Notizen

• To respond to potential adverse exposures properly, health care providers need accurate indicators of exposure levels. The indicators are particularly important in the case of acetaminophen (APAP) intoxication, the leading cause of liver failure in the U.S. We hypothesized that gene expression patterns derived from blood cells would provide useful indicators of acute exposure levels. To test this hypothesis, we used a blood gene expression data set from rats exposed to APAP to train classifiers in two prediction algorithms and to extract patterns for prediction using a profiling algorithm. Prediction accuracy was tested on a blinded, independent rat blood test data set and ranged from 88.9% to 95.8%. Genomic markers outperformed predictions based on traditional clinical parameters. The expression profiles of the predictor genes from the patterns extracted from the blood exhibited remarkable (97% accuracy) transtissue APAP exposure prediction when liver gene expression data were used as a test set. Analysis of human samples revealed separation of APAP-intoxicated patients from control individuals based on blood expression levels of human orthologs of the rat discriminatory genes. The major biological signal in the discriminating genes was activation of an inflammatory response after exposure to toxic doses of APAP. These results support the hypothesis that gene expression data from peripheral blood cells can provide valuable information about exposure levels, well before liver damage is detected by classical parameters. It also supports the potential use of genomic markers in the blood as surrogates for clinical markers of potential acute liver damage.