4.4 Article

Molecular biomarker panels for assessment of selenium status in rats

期刊

EXPERIMENTAL BIOLOGY AND MEDICINE
卷 235, 期 9, 页码 1046-1052

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1258/ebm.2010.010111

关键词

glutathione peroxidase; kidney; liver; mRNA; nutrition; panel; requirements

资金

  1. NIH [DK74184]
  2. University of Wisconsin Agricultural Experiment Station [WIS04909]

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Molecular biomarkers are mRNA transcripts that indicate the (nutrient) status of an organism or tissue. Molecular biomarker panels have the potential to readily and more accurately determine nutrient status than individual traditional biomarkers. To study the efficacy of molecular biomarker panels for predicting selenium (Se) status, we examined 30 biomarkers from rats fed graded levels of Se from deficient to eight times the minimum Se requirement, including four liver and four kidney traditional biomarkers, and 13 liver and nine kidney selenoprotein mRNA levels. Multiple regression analysis against liver and kidney Se and glutathione peroxidase-1 (Gpx1) activity, with stepwise single elimination of biomarkers that did not significantly contribute, was used to identify biomarker panels with significant (P < 0.05) regression coefficients. Resulting regression equations were then used to predict Se status, and compared with traditional Se biomarkers panels. Over the full spectrum of Se status from 0 to 0.8 mu g Se/g diet, the resulting 4-selenoprotein mRNA biomarker panel predicted liver Se concentration with a correlation of 0.948, which was nominally higher and statistically the same as the correlation of 0.909 for the panel based on Gpx1 activity. The molecular biomarker panels for predicting kidney Se and liver and kidney Gpx1 activity were all comparable to predictions based on traditional biomarkers. These analyses show that molecular biomarker panels can be used to predict accurately two traditional biomarkers of Se status. The resulting analyses also illustrate that additional orthogonal biomarkers reflecting higher Se intakes are needed to better predict supernutritional Se status and further strengthen this approach.

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