Literature DB >> 3830235

Assessing the predictive validity of psychomotor tests as measures of biological age in mice.

D K Ingram, M A Reynolds.   

Abstract

Two experiments assessed the predictive validity of a psychomotor test battery in male C57BL/6J mice. First, performance was recorded for 66 mice in rotorod, tightrope, grip strength, exploratory activity, and runwheel activity tasks at 24 mo of age. Except in the rotorod task, performance was positively and significantly correlated to lifespan, i.e. better performance indicated longer lifespan. Body weight and body temperature were also significantly correlated with lifespan, while water consumption was negatively related. Using the five behavioral scores in a multiple regression analysis, about 40% of the variance in lifespan was explainable. When measures of body weight, body temperature, and water consumption were added to the regression equation, about 54% of the variance in lifespan could be explained. As revealed by factor analysis, a high degree of interrelationship existed among variables. In a second experiment, 54 mice were tested in the psychomotor battery every 8 weeks from 24 mo. Scores in the tightrope and both locomotor activity tasks revealed age-related declines, whether considering all individuals or only those surviving to 28 mo. Significant correlations between first and subsequent scores indicated stability of individual differences for tightrope and exploratory activity at most ages and for runwheel activity at 26 mo but not later. Rotorod and grip strength scores were not stable and suggested confounding by learning. Significant correlations with lifespan were obtained at some ages for all tests. In contrast to the first experiment, however, there were no significant correlations between lifespan and scores at 24-mo for any test and little correlation among scores.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1986        PMID: 3830235     DOI: 10.1080/03610738608259454

Source DB:  PubMed          Journal:  Exp Aging Res        ISSN: 0361-073X            Impact factor:   1.645


  21 in total

1.  Profiling psychomotor and cognitive aging in four-way cross mice.

Authors:  Nathalie Sumien; Micaela N Sims; Hilary J Taylor; Michael J Forster
Journal:  Age (Dordr)       Date:  2006-11-25

2.  Changes in behaviors of male C57BL/6J mice across adult life span and effects of dietary restriction.

Authors:  Andreas Fahlström; Hugo Zeberg; Brun Ulfhake
Journal:  Age (Dordr)       Date:  2011-10-12

3.  Battery of behavioral tests in mice that models age-associated changes in human motor function.

Authors:  Jamie N Justice; Christy S Carter; Hannah J Beck; Rachel A Gioscia-Ryan; Matthew McQueen; Roger M Enoka; Douglas R Seals
Journal:  Age (Dordr)       Date:  2014-04

4.  The effects of aging and genotype on NMDA receptor expression in growth hormone receptor knockout (GHRKO) mice.

Authors:  Kathy Ruth Magnusson; Siba Ranjan Das; Daniel Kronemann; Andrzej Bartke; Peter R Patrylo
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2011-03-31       Impact factor: 6.053

5.  C57BL/6 neuromuscular healthspan scoring system.

Authors:  Ted G Graber; Lisa Ferguson-Stegall; Jong-Hee Kim; LaDora V Thompson
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2013-04-12       Impact factor: 6.053

6.  Quantitative grip strength assessment as a means of evaluating muscle relaxation in mice.

Authors:  M E Nevins; S A Nash; P M Beardsley
Journal:  Psychopharmacology (Berl)       Date:  1993       Impact factor: 4.530

Review 7.  Comparative Approaches to Understanding the Relation Between Aging and Physical Function.

Authors:  Jamie N Justice; Matteo Cesari; Douglas R Seals; Carol A Shively; Christy S Carter
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2015-04-23       Impact factor: 6.053

8.  Identifying and Implementing Endpoints for Geriatric Mice.

Authors:  Linda A Toth
Journal:  Comp Med       Date:  2018-11-28       Impact factor: 0.982

9.  Initiation of calorie restriction in middle-aged male rats attenuates aging-related motoric decline and bradykinesia without increased striatal dopamine.

Authors:  Michael F Salvatore; Jennifer Terrebonne; Victoria Fields; Danielle Nodurft; Cori Runfalo; Brian Latimer; Donald K Ingram
Journal:  Neurobiol Aging       Date:  2015-10-19       Impact factor: 4.673

10.  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

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