Literature DB >> 19225031

Can we develop genetically tractable models to assess healthspan (rather than life span) in animal models?

Marc Tatar1.   

Abstract

Understanding healthspan is arguably the most relevant clinical, social, and economic feature of aging research. The model systems of worm, fly, and mouse are potentially powerful tools to achieve this aim. These models provide two unique approaches. The first is based on genetic screening for gain or loss of function mutations that ameliorate senescence. Genetic factors discovered by this process permit us to recognize causal and regulatory mechanisms of aging. A related screen looks for compounds that slow aging or act upon proteins that were initially identified from genetic analysis. The second research strategy uses manipulations of targeted genetic factors to test causal explanations for aging. These studies include transgenic organisms and genetic epistasis analysis. Overall, genetically driven research with model organisms is largely responsible for the breakthrough of aging biology in the past 15 years. Aging in these contexts, however, has been measured almost exclusively from cohort survival statistics such as life expectancy and age-specific mortality. This is for a good reason. Manipulated factors that extend life span are thought to unambiguously slow senescence and thus to reflect underlying causes of the aging process. But this approach is also common for a practical reason--healthspan is a poorly defined commodity in humans, let alone for genetic animal model systems. It was the consensus of the working session that making healthspan an operational metric would be an innovation needed for the genetic power of model systems to address this aspect of human aging.

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Year:  2009        PMID: 19225031      PMCID: PMC2655017          DOI: 10.1093/gerona/gln067

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


  11 in total

1.  Insulin regulation of heart function in aging fruit flies.

Authors:  Robert J Wessells; Erin Fitzgerald; James R Cypser; Marc Tatar; Rolf Bodmer
Journal:  Nat Genet       Date:  2004-11-21       Impact factor: 38.330

2.  A proposed set of descriptors for functional senescence data.

Authors:  Ian Martin; Julia Warner Gargano; Michael S Grotewiel
Journal:  Aging Cell       Date:  2005-06       Impact factor: 9.304

3.  Functional analysis of the Drosophila immune response during aging.

Authors:  Sean Ramsden; Yeuk Yu Cheung; Laurent Seroude
Journal:  Aging Cell       Date:  2008-01-21       Impact factor: 9.304

4.  Aging of the innate immune response in Drosophila melanogaster.

Authors:  Melissa Zerofsky; Ephat Harel; Neal Silverman; Marc Tatar
Journal:  Aging Cell       Date:  2005-04       Impact factor: 9.304

5.  Correlates of sleep and waking in Drosophila melanogaster.

Authors:  P J Shaw; C Cirelli; R J Greenspan; G Tononi
Journal:  Science       Date:  2000-03-10       Impact factor: 47.728

6.  Stress response genes protect against lethal effects of sleep deprivation in Drosophila.

Authors:  Paul J Shaw; Giulio Tononi; Ralph J Greenspan; Donald F Robinson
Journal:  Nature       Date:  2002-05-16       Impact factor: 49.962

7.  Trade-offs between longevity and pathogen resistance in Drosophila melanogaster are mediated by NFkappaB signaling.

Authors:  Sergiy Libert; Yufang Chao; Xiaowen Chu; Scott D Pletcher
Journal:  Aging Cell       Date:  2006-12       Impact factor: 9.304

8.  KCNQ potassium channel mutations cause cardiac arrhythmias in Drosophila that mimic the effects of aging.

Authors:  Karen Ocorr; Nick L Reeves; Robert J Wessells; Martin Fink; H-S Vincent Chen; Takeshi Akasaka; Soichiro Yasuda; Joseph M Metzger; Wayne Giles; James W Posakony; Rolf Bodmer
Journal:  Proc Natl Acad Sci U S A       Date:  2007-02-28       Impact factor: 11.205

9.  Increased internal and external bacterial load during Drosophila aging without life-span trade-off.

Authors:  Chunli Ren; Paul Webster; Steven E Finkel; John Tower
Journal:  Cell Metab       Date:  2007-08       Impact factor: 27.287

10.  Stochastic and genetic factors influence tissue-specific decline in ageing C. elegans.

Authors:  Laura A Herndon; Peter J Schmeissner; Justyna M Dudaronek; Paula A Brown; Kristin M Listner; Yuko Sakano; Marie C Paupard; David H Hall; Monica Driscoll
Journal:  Nature       Date:  2002-10-24       Impact factor: 49.962

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  27 in total

1.  Inflammation and mortality in a frail mouse model.

Authors:  Fred Ko; Qilu Yu; Qian-Li Xue; Wenliang Yao; Cory Brayton; Huanle Yang; Neal Fedarko; Jeremy Walston
Journal:  Age (Dordr)       Date:  2011-06-02

Review 2.  Calorie restriction: what recent results suggest for the future of ageing research.

Authors:  Daniel L Smith; Tim R Nagy; David B Allison
Journal:  Eur J Clin Invest       Date:  2010-05       Impact factor: 4.686

3.  Dietary effects on sex-specific health dynamics of medfly: support for the dynamic equilibrium model of aging.

Authors:  Nikos T Papadopoulos; Stella Papanastasiou; Hans-Georg Müller; Jane-Ling Wang; Wenjing Yang; James R Carey
Journal:  Exp Gerontol       Date:  2011-09-12       Impact factor: 4.032

Review 4.  Genetics, life span, health span, and the aging process in Caenorhabditis elegans.

Authors:  Heidi A Tissenbaum
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2012-04-12       Impact factor: 6.053

5.  FOXO3 gene variants and human aging: coding variants may not be key players.

Authors:  Timothy A Donlon; J David Curb; Qimei He; John S Grove; Kamal H Masaki; Beatriz Rodriguez; Ayako Elliott; D Craig Willcox; Bradley J Willcox
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2012-03-28       Impact factor: 6.053

Review 6.  Healthspan, translation, and new outcomes for animal studies of aging.

Authors:  James L Kirkland; Charlotte Peterson
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2009-02-05       Impact factor: 6.053

7.  Longevity effect of a polysaccharide from Chlorophytum borivilianum on Caenorhabditis elegans and Saccharomyces cerevisiae.

Authors:  Steve Thomas Pannakal; Sibylle Jäger; Albert Duranton; Amit Tewari; Subarna Saha; Aneesha Radhakrishnan; Nita Roy; Jean François Kuntz; Soraya Fermas; Darryl James; Jane Mellor; Namita Misra; Lionel Breton
Journal:  PLoS One       Date:  2017-07-20       Impact factor: 3.240

Review 8.  Methusaleh's Zoo: how nature provides us with clues for extending human health span.

Authors:  S N Austad
Journal:  J Comp Pathol       Date:  2009-12-04       Impact factor: 1.311

9.  Beneficial effects of a Q-ter based nutritional mixture on functional performance, mitochondrial function, and oxidative stress in rats.

Authors:  Jinze Xu; Arnold Y Seo; Darya A Vorobyeva; Christy S Carter; Stephen D Anton; Angela M S Lezza; Christiaan Leeuwenburgh
Journal:  PLoS One       Date:  2010-05-11       Impact factor: 3.240

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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