Literature DB >> 15130756

Body weight, hormones and T cell subsets as predictors of life span in genetically heterogeneous mice.

James M Harper1, Andrzej T Galecki, David T Burke, Richard A Miller.   

Abstract

Previous studies have shown that T cell subset levels, early life body weight, and levels of leptin and thyroid hormones can each serve, independently, as predictors of life span in populations of genetically heterogeneous mice. New data now confirm, in a replicate cohort, that T cell subset patterns predict longevity, and show that they can do so when measured in mice as young as 8 months of age. Individual T cell subsets, as well as composite indices that combine data from two or more T cell measures at 8 or 18 months, can be combined with 3- and 9-month body weight data to provide better prediction of life span than either immune or weight measures alone. Mice whose immune and weight measures are both in the lowest quartile have mean and maximal life spans that are 18% and 16-25% higher, respectively, than mice in the opposite quartiles for both traits. Thyroxine levels measured at 4 months lead to further improvement over models that combine weight and immune data only. A genome scan provided evidence for loci on chromosomes 2, 12, 13, and 17 that modulate age-sensitive T cell subset patterns at both 8 and 18 months of age. These data show that late-life mortality risks are influenced to a measurable degree by factors that modulate growth trajectory and hormone and immune status in the first third of the life span, and provide clues as to which early life systems deserve further scrutiny as potential mediators of late life disease risk.

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Year:  2004        PMID: 15130756     DOI: 10.1016/j.mad.2004.03.003

Source DB:  PubMed          Journal:  Mech Ageing Dev        ISSN: 0047-6374            Impact factor:   5.432


  17 in total

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Authors:  Richard A Miller; Jaclynn Kreider; Andrzej Galecki; Steven A Goldstein
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2.  Life extension by diet restriction and N-acetyl-L-cysteine in genetically heterogeneous mice.

Authors:  Kevin Flurkey; Clinton M Astle; David E Harrison
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2010-09-05       Impact factor: 6.053

3.  Tail tendon break time: a biomarker of aging?

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4.  Design of aging intervention studies: the NIA interventions testing program.

Authors:  N L Nadon; R Strong; R A Miller; J Nelson; M Javors; Z D Sharp; J M Peralba; D E Harrison
Journal:  Age (Dordr)       Date:  2008-04-18

Review 5.  Nutrition and energetics in rodent longevity research.

Authors:  Victoria K Gibbs; Daniel L Smith
Journal:  Exp Gerontol       Date:  2016-04-09       Impact factor: 4.032

6.  Chronic resveratrol intake reverses pro-inflammatory cytokine profile and oxidative DNA damage in ageing hybrid mice.

Authors:  Yee Ting Wong; Jan Gruber; Andrew M Jenner; Francis Eng Hock Tay; Runsheng Ruan
Journal:  Age (Dordr)       Date:  2010-08-21

7.  Wild-derived mouse stocks: an underappreciated tool for aging research.

Authors:  James M Harper
Journal:  Age (Dordr)       Date:  2008-05-30

8.  Genetic linkages for thyroxine released in response to thyrotropin stimulation in three sets of recombinant inbred mice provide evidence for shared and novel genes controlling thyroid function.

Authors:  Sepehr Hamidi; Holly A Aliesky; Robert W Williams; Basil Rapoport; Sandra M McLachlan
Journal:  Thyroid       Date:  2013-03       Impact factor: 6.568

9.  How long will my mouse live? Machine learning approaches for prediction of mouse life span.

Authors:  William R Swindell; James M Harper; Richard A Miller
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2008-09       Impact factor: 6.053

10.  Genes and gene expression modules associated with caloric restriction and aging in the laboratory mouse.

Authors:  William R Swindell
Journal:  BMC Genomics       Date:  2009-12-07       Impact factor: 3.969

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