Literature DB >> 11283189

Biomarkers of aging: prediction of longevity by using age-sensitive T-cell subset determinations in a middle-aged, genetically heterogeneous mouse population.

R A Miller1.   

Abstract

Seven T-cell subset values were measured in each of 559 mice at 8 months of age, and then again in the 494 animals that reached 18 months of age. The group included virgin males, virgin females, and mated females, and it was produced by using a four-way cross-breeding system that generates genetic heterogeneity equivalent to a very large sibship. An analysis of covariance showed that four T-cell subsets-CD4, CD4 memory, CD4 naïve, and CD4 cells expressing P:-glycoprotein-were significant predictors (p <.003) of longevity when measured at 18 months of age after adjustment for the possible effects of gender and mating. The subset marked by CD4 and P:-glycoprotein expression showed a significant interaction effect: this subset predicted longevity only in males. Among subsets measured when the mice were 8 months of age, only the levels of CD8 memory cells predicted longevity (p =.016); the prognostic value of this subset was largely limited to mated females. A cluster analysis that separated mice into two groups based upon similarity of T-cell subset patterns measured at 18 months showed that these two groups differed in life expectancy. Specifically, mice characterized by relatively low levels of CD4 and CD8 memory cells, high levels of CD4 naïve cells, and low levels of CD4 cells with P:-glycoprotein (64% of the total) lived significantly longer (50 days = 6%; p <.0007) than mice in the other cluster. The results are consistent with the hypothesis that patterns of T-cell subsets vary among mice in a manner than can predict longevity in middle age, and they suggest that these subsets may prove to be useful for further studies of the genetics of aging and age-sensitive traits.

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Year:  2001        PMID: 11283189     DOI: 10.1093/gerona/56.4.b180

Source DB:  PubMed          Journal:  J Gerontol A Biol Sci Med Sci        ISSN: 1079-5006            Impact factor:   6.053


  15 in total

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