A risk assessment-driven quantitative comparison of gene expression profiles in PBMCs and white adipose tissue of humans and rats after isoflavone supplementation

Vera van der Velpen, Pieter van 't Veer, M. Ariful Islam, C. J. F. ter Braak, F. X. Rolaf van Leeuwen, Lydia A. Afman, Peter C. Hollman, Evert G. Schouten, Anouk Geelen

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Quantitative insight into species differences in risk assessment is expected to reduce uncertainty and variability related to extrapolation from animals to humans. This paper explores quantification and comparison of gene expression data between tissues and species from intervention studies with isoflavones.

Gene expression data from peripheral blood mononuclear cells (PBMCs) and white adipose tissue (WAT) after 8wk isoflavone interventions in postmenopausal women and ovariectomized F344 rats were used. A multivariate model was applied to quantify gene expression effects, which showed 3–5-fold larger effect sizes in rats compared to humans. For estrogen responsive genes, a 5-fold greater effect size was found in rats than in humans. For these genes, intertissue correlations (r = 0.23 in humans, r = 0.22 in rats) and interspecies correlation in WAT (r = 0.31) were statistically significant. Effect sizes, intertissue and interspecies correlations for some groups of genes within energy metabolism, inflammation and cell cycle processes were significant, but weak.

Quantification of gene expression data reveals differences between rats and women in effect magnitude after isoflavone supplementation. For risk assessment, quantification of gene expression data and subsequent calculation of intertissue and interspecies correlations within biological pathways will further strengthen knowledge on comparability between tissues and species.
Original languageEnglish
Pages (from-to)203-210
Number of pages8
JournalFood and Chemical Toxicology
Early online date14 Jul 2016
Publication statusPublished - Sep 2016


  • Risk assessment
  • Gene expression
  • Species and tissue differences
  • Quantitative evaluation
  • Isoflavones
  • Multivariate model

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