- Email: [email protected]
Structural brain aging in inbred mice: potential for genetic linkage
M. Jucker et al. / Experimental Gerontology 35 (2000) 1383±1388
1383
Experimental Gerontology 35 (2000) 1383±1388 www.elsevier.nl/locate/expgero
Structural brain aging in inbred mice: potential for genetic linkage M. Jucker a,*, L. Bondol® a, M.E. Calhoun b, J.M. Long c, D.K. Ingram c a
Neuropathology, Institute of Pathology, University of Basel, SchoÈnbeinstrasse 40, CH-4003 Basel, Switzerland b Neurobiology of Aging Laboratories, Mount Sinai School of Medicine, New York, NY, USA c Behavioral Neuroscience Section, Laboratory of Neurosciences, Gerontology Research Center, National Institute on Aging, NIH, Baltimore, MD, USA Received 11 July 2000; received in revised form 31 July 2000; accepted 31 July 2000
Abstract To identify genetic factors involved in brain aging, we have initiated studies assessing behavioral and structural changes with aging among inbred mouse strains. Cognitive performance of C57BL/6J mice is largely maintained with aging, and stereological analysis revealed no signi®cant age-related change in neuron number, synaptic bouton number or glial number in the hippocampus. Moreover, no change in cortical neuron number and cholinergic basal forebrain neuron number has been found in this strain. 129Sv/J mice have more pronounced age-related cognitive de®cits, although hippocampal and basal cholinergic forebrain neuron number also appear unchanged with aging. Differences in neurogenesis and neuron vulnerability in the adult CNS of C57BL/6, 129/Sv and other inbred strains have been reported, which in turn may have important consequences for brain aging. Age-related lesions, such as thalamic eosinophilic inclusions and hippocampal clusters of polyglucosan bodies also vary greatly among inbred strains although the functional signi®cance of these lesions is not clear. The continued assessment of such age-related structural and behavioral changes among inbred mouse strains offers the potential to identify genes that control age-related changes in brain structure and function. q 2000 Elsevier Science Inc. All rights reserved. Keywords: Aging; Brain; CNS; Neuron; Glia; Inclusions; Mouse; Strain; Hippocampus; Linkage; Genetics; Stereology; Neurodegeneration; Neurogenesis
1. Why study brain aging of normal inbred mice? Brain aging has been studied using a variety of animal models, with nonhuman primates * Corresponding author. Tel.: 141-61-265-2894; fax: 141-61-265-3194. E-mail address: [email protected] (M. Jucker). 0531-5565/00/$ - see front matter q 2000 Elsevier Science Inc. All rights reserved. PII: S 0531-556 5(00)00190-X
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and rats being the most popular. With the rapid evolution of mouse genetics and transgenic technology, murine models have gained increased attention. Transgenic technology has successfully been used to produce mouse models which recapitulate aspects of age-related neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, or Huntington's disease (Price et al., 1998; Masliah et al., 2000). Moreover, mice have been genetically engineered to test several hypotheses of brain aging (Jucker and Ingram, 1997). It has become clear that the phenotype of such transgenic mouse models is critically dependent on the genetic background in which a transgene or a null allele has been introduced (e.g. Carlson et al., 1997). Unfortunately, relatively little information is available about normal brain aging in inbred mice, which could guide the choice of the most appropriate genetic background for production of such models and ultimately would ease the assessment of resulting phenotypes. The interest in the aging inbred mouse brain is also driven by recent progress in genetic linkage analysis in the mouse (Takahashi et al., 1994; Nadeau et al., 2000) and the endeavor to sequence the entire mouse genome. Thus, for any given age-related trait observed in one mouse strain, but not in another, quantitative trait loci (QTL) analysis can be used to identify the underlying loci and genes (McClearn, 1997). Unfortunately, few studies thus far have quantitatively assessed brain aging in more than one strain, providing the prerequisite for this `forward genetic approach' to brain aging (Ingram and Jucker, 1999). For the above reasons, there is a growing need to characterize brain aging in inbred mice. More than 400 inbred strains have been described (Beck et al., 2000), and we estimate that brain aging has been studied in less than 5%. Assessment of brain aging should be quantitative, and reproducible among laboratories. In the present review we would like to focus on structural changes, since the necessary tools to assess such changes in the aging brain have recently been developed, referred to as `modern stereological techniques' (Gundersen et al., 1988; West, 1993; Long et al., 1999a; Calhoun and Mouton, 2000). For the behavioral analysis, standardized test batteries for mouse behavior have been suggested (Crawley and Paylor, 1997) but only rarely adopted in aging studies (Ingram, 1988, 1990). 2. Structural changes in the aging mouse brain Structural alterations in the aging mouse brain have been described in numerous studies (reviewed in Jucker and Ingram, 1997). Unfortunately most of these earlier studies have used techniques that can be questioned regarding their accuracy (Long et al., 1999a). Moreover, studies have rarely been conducted in more than one mouse strain, thus making comparisons in brain aging among mouse strains dif®cult (Ingram and Jucker, 1999). We and others have initiated studies to assess age-related structural changes in the mouse brain, including age-related changes in neuron number, synaptic bouton number and glia number. Results so far are limited to the C57BL/6J and 129Sv/J strain (Table 1). No change in neuron number was found in CA1 of hippocampus and in dentate gyrus of C57BL/6J mice (Calhoun et al., 1998) and 129/SvJ mice (unpublished observations). Similarly, no signi®cant change in neuron number was found in neocortex of aging
M. Jucker et al. / Experimental Gerontology 35 (2000) 1383±1388
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Table 1 Age-related changes in neuron and glia number in the mouse brain using modern stereology Neuron #
Neuron #
Neocortex Hippocampus C57BL/6J No change No change 129/Sv No change
Cholinergic Synaptic bouton Astroglia # neuron # # (Basal Forebrain) (Hippocampus) Hippocampus
Hippocampus
No change No change
No change Increase
No change
No change No change
Microglia #
C57BL/6J mice (Bondol® et al., unpublished observations). In both C57BL/6J and 129Sv mice, the number of cholinergic forebrain neurons also appear unchanged with aging (Ward et al., 2000; Boncristiano et al., unpublished observations). Synaptic bouton numbers have been assessed only in C57BL/6J mice, and no change has been reported in CA1 of hippocampus and in dentate gyrus (Calhoun et al., 1998). No age-related changes were reported for astrocyte and microglia number in hippocampal subregions of C57BL/6J mice (Long et al., 1998). In contrast, an age-related increase in glia number was found in selected hippocampal subregions of the 129/Sv strain (Long et al., 1999b). Furthermore, glia number between the C57BL/6J and 129/ Sv strain was different in speci®c hippocampal subregions, emphasizing the need to evaluate baseline neural parameters in more than one strain. Most of these results have been collected in male mice. Interestingly, a recent report suggests an age-related increase in astrocyte number in neocortex of female C57BL/6 mice pointing to possible sex differences in the age-related glia response (Mouton et al., 2000). Strain differences have been reported in the occurrence of age-related lesions in the hippocampus and thalamus of aging mice (Table 2). Clusters of periodic-acid Schiff (PAS)-positive granular bodies develop in the aging hippocampus of some, but not in other, inbred mouse strains (Jucker et al., 1994). These polyglucosan bodies have been localized to astrocyte cytoplasm and have been referred to as glia inclusions. The signi®cance of the lesions is still unclear, but they are likely the equivalent of unusual polyglucosan bodies described in the human brain (Sugiyama et al., 1993). The age-related occurrence of eosinophilic neuronal inclusions in the thalamus of aging C57BL/6 mice and 129 mice (Yanai et al., 1995; Fraser, 1969) and of some other commonly used inbred mice is summarized in Table 2. Similar thalamic inclusions have been reported in the human thalamus, but the pathogenesis has remained unclear (Pena, 1980). These striking
Table 2 Lesions in the aging mouse brain
C57BL/6J 129/Sv DBA/2J A/J FVB/J
Polyglucosan bodies in hippocampus
Eosinophilic neuronal inclusions in thalamus
Increase with aging Increase with aging Do not occur Do not occur Do not occur
Increase with aging Increase with aging Increase with aging Do not occur Increase with aging
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strain-dependent lesions in the aging mouse brain clearly ful®ll the prerequisite for QTL analysis and the identi®cation of an underlying genetic mechanisms.
3. Strain-dependent traits which may be important for brain aging One of the most striking age-related phenomenon is the reported 80±90% decrease in neurogenesis in the aging dentate gyrus of C57BL/6 mice (Kempermann et al., 1998). Neurogenesis has been suggested to account in large measure for changes in brain plasticity and response to environmental stimulation (Gage, 2000). Although changes in neurogenesis with aging in other mouse strains have not yet been examined, a genetic in¯uence on neurogenesis has been reported (Kempermann et al., 1997). For example, neurogenesis in the dentate gyrus of young 129/Sv mice is signi®cantly less compared to young C57BL/6 mice. Since in both strains, the number of neurons in the dentate gyrus remains unchanged with aging (see above), the ®ndings suggest that the turnover of dentate gyrus neurons is higher in C57BL/6 mice compared to 129/Sv mice. Decreased neurogenesis in the aging brain has been suggested to contribute to age-related cognitive de®cits (Cameron and McKay, 1999) and thus, strain differences in neurogenesis may re¯ect strain differences in age-related cognitive function. Strain differences have also been reported in other parameters with relevance to brain aging. For example, 129/Sv mice are more prone to excitotoxic cell death in the hippocampus after kainic acid injections compared to C57BL/6 mice (Schauwecker and Steward, 1997). Moreover, strain differences in neurodegeneration after brain trauma and ischemia have been reported (Yang et al., 1997; Steward et al., 1999). Such strain differences in the cellular response to injury may confound the phenotype of gene-targeted or transgenic mouse models, but they are also a great opportunity to study genes involved in the susceptibility to neurodegeneration and brain aging.
4. Conclusion Quantitative neuroanatomical and morphological data can be exploited to map genes that are responsible for age-related structural changes in the brain (McClearn, 1997; Williams, 2000). The techniques for such linkage and mapping analysis of genes are in place. What is missing are reliable quantitative data about age-related changes among inbred mouse brains. The future success of identifying genes underlying brain aging belongs to those who have been or will start to weigh, count and measure age-related changes in various mouse strains. It is likely that this forward genetic approach will greatly advance our understanding of the genetic involvement in brain aging. At the same time, a careful characterization of brain aging among inbred mice is crucial for the interpretation of the phenotypes of transgenic mouse models of brain aging and age-related neurodegenerative diseases.
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Acknowledgements We would like to thank Dr P. Mouton for his support, and S. Boncristiano for sharing unpublished results. This work was supported by grants from the Swiss National Science Foundation and the VerUm Foundation, Munich, Germany.
References Beck, J.A., Lloyd, S., Hafezparast, M., Lennon-Pierce, M., Eppig, J.T., Festing, M.F.W., Fisher, E.M.C., 2000. Genealogies of mouse inbred strains. Nat. Genet. 24, 23±25. Calhoun, M.E., Kurth, D., Phinney, A.L., Long, J.M., Hengemihle, J., Mouton, P.E., Ingram, D.K., Jucker, M., 1998. Hippocampal neuron and synaptophysin-positive bouton number in aging C57BL/6 mice. Neurobiol. Aging 19, 599±606. Calhoun, M.E., Mouton, P.R., 2000. Length measurement: new developments in neurostereology and 3D imagery. J. Chem. Neuroanat. (in press). Cameron, H.A., McKay, R.D.G., 1999. Restoring production of hippocampal neurons in old age. Nat. Neurosci. 2, 894±897. Carlson, G.A., Borchelt, D.R., Dake, A., Turner, S., Danielson, V., Cof®n, J.D., Eckman, C., Meiners, J., Nilson, S.P., Younkin, S.G., Hsaio, K.K., 1997. Genetic modi®cation of the phenotypes produced by amyloid precursor protein overexpression in transgenic mice. Hum. Mol. Genet. 6, 1951±1959. Crawley, J.N., Paylor, R., 1997. A proposed test battery and constellations of speci®c behavioral paradigms to investigate the behavioral phenotypes of transgenic and knockout mice. Horm. Behav. 31, 197±211. Fraser, H., 1969. Eosinophilic bodies in some neurones in the thalamus of ageing mice. J. Pathol. 98, 201±204. Gage, F.H., 2000. Mammalian neural stem cells. Science 287, 1433±1438. Gundersen, H.J.G., Bagger, P., Bendtsen, T.F., Evans, S.M., Korbo, L., Marcussen, N., Moller, A., Nielsen, K., Nyengaard, J.R., Pakkenberg, B., Sorensen, F.B., Vesterby, A., West, M.J., 1988. The new stereological tools: disector, fractionator, nucleator and point sampled intercepts and their use in pathological research and diagnosis. Acta. Pathol. Immunol. Scand. 96, 857±881. Ingram, D.K., 1988. Motor performance variabilty during aging in rodents: assessment of reliability and validity of individual differences. Ann. N.Y. Acad. Sci. 515, 70±96. Ingram, D.K., 1990. Perspectives on genetic variability in behavioral aging of mice. In: Harrison, D.E. (Ed.). Genetic effects on aging II. Telford Press, Caldwell, NJ, pp. 205±231. Ingram, D.K., Jucker, M., 1999. Developing mouse models of aging: a consideration of strain differences in agerelated behavioral and neural parameters. Neurobiol. Aging 20, 137±145. Jucker, M., Ingram, D.K., 1997. Murine models of brain aging and age-related neurodegenerative diseases. Behav. Brain Res. 85, 1±25. Jucker, M., Walker, L.C., Schwarb, P., Hengemihle, J., Kuo, H., Snow, A.D., Bamert, F., Ingram, D.K., 1994. Age-related deposition of glia-associated ®brillar material in brains of C57BL/6 mice. Neuroscience 60, 875± 889. Kempermann, G., Kuhn, H.G., Gage, F.H., 1997. Genetic in¯uence on neurogenesis in the dentate gyrus of adult mice. Proc. Natl. Acad. Sci. USA 94, 10409±10414. Kempermann, G., Kuhn, H.G., Gage, F.H., 1998. Experience-induced neurogenesis in the senescent dentate gyrus. J. Neurosci. 18, 3206±3212. Long, J.M., Kalehua, A.N., Muth, N.J., Hengemihle, J.M., Calhoun, M.E., Jucker, M., Ingram, D.K., Mouton, P.R., 1998. Total number of astrocyte and microglia in hippocampus of C57BL/6 mice at different ages. Neurobiol. Aging 19, 497±503. Long, J.M., Mouton, P.R., Jucker, M., Ingram, D.K., 1999a. What counts in brain aging? Design-based stereological analysis of cell number. J. Gerontol. 54, B407±B417. Long, J.M., Hengemihle, J.M., Moon, E.K., Jucker, M., Calhoun, M.E., Mascarucci, P., Mouton, P.R., Ingram, D.K., 1999b. Comparison of hippocampal glia number C57BL/6J and 129/SvJ mice of different ages. Soc. Neurosci. Abstr. 25, 28.
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Masliah, E., Rockenstein, E., Veinbergs, I., Mallory, M., Hashimoto, M., Takeda, A., Sagara, Y., Sisk, A., Mucke, L., 2000. Dopaminergic loss and inclusion body formation in a-synuclein mice: implications for neurodegenerative disorders. Science 287, 1265±1269. McClearn, G.E., 1997. Prospects for quantitative trait locus methodology in gerontology. Exp. Gerontol. 32, 49± 54. Mouton, P.R., Long, J.M., Stocks, E.A., Ram, S., Howard, U., Juclier, M., Calhoun, M.E. 2000. Age- and genderrelated differences in total numbers of astrocytes and microglia in hippoconupal subregions of C57BL16 mouse brains. Soc. Neurosa. Abstr. 26 (in press). Nadeau, J.H., Singer, J.B., Matin, A., Lander, E.S., 2000. Analysing complex genetic traits with chromosome substitution strains. Nat. Genet. 24, 221±225. Pena, C.E., 1980. Intracytoplasmic neuronal inclusions in the human thalamus. Acta Neuropathol. (Berl) 52, 157±159. Price, D.L., Sisodia, S.S., Borchelt, D.R., 1998. Genetic neurodegenerative diseases: the human illness and transgenic models. Science 282, 1079±1083. Schauwecker, P.E., Steward, O., 1997. Genetic determinants of susceptibility to excitotoxic cell death: implications for gene targeting approaches. Proc. Natl. Acad. Sci. USA 94, 4103±4108. Steward, O., Schauwecker, P.E., Guth, L., Zhang, Z., Fujiki, M., Inman, D., Wrathall, J., Kempermann, G., Gage, F.H., Saatman, K.E., Raghupathi, R., McIntosh, T., 1999. Genetic approaches to neurotrauma research: opportunities and potential pitfalls of murine models. Exp. Neurol. 157, 19±42. Sugiyama, H., Hainfellner, J.A., Lassmann, H., Indravasu, S., Budka, H., 1993. Uncommon types of polyglucosan bodies in the human brain: distribution and relation to disease. Acta Neuropathol. 86, 484±490. Takahashi, J.S., Pinto, L.H., Vitaterna, M.H., 1994. Forward and reverse genetic approaches to behavior in the mouse. Science 264, 1724±1733. Ward, N.L., Stanford, L.E., Brown, R.E., Hagg, T., 2000. Cholinergic medial septum neurons do not degenerate in aged 129/Sv control or p75 NGFR 2 /2mice. Neurobiol. Aging 21, 125±134. West, M.J., 1993. New stereological methods for counting neurons. Neurobiol. Aging 14, 275±285. Williams, R.W., 2000. Mapping genes that modulate mouse brain development: a quantitive approach. In: Goef®net, A., Rakic, P. (Eds.). In: Mouse Brain Development, Springer Verlag, New York, pp. 21±49. Yanai, T., Masegi, T., Yoshida, K., Ishikawa, K., Kawada, M., Iwasaki, T., Yamazoe, K., Suzuki, Y., Goto, N., 1995. Eosinophilic neuronal inclusions in the thalamus of ageing B6C3F1 mice. J. Comp. Path. 113, 287± 290. Yang, G., Kitagawa, K., Matsushita, K., Mabuchi, T., Yagita, Y., Yanagihara, T., Matsumoto, M., 1997. C57BL/6 strain is most susceptible to cerebral ischemia following bilateral common carotid occlusion among seven mouse strains: selective neuronal death in the murine transient forebrain ischemia. Brain Res. 752, 209±218.
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Experimental Gerontology 35 (2000) 1383±1388 www.elsevier.nl/locate/expgero
Structural brain aging in inbred mice: potential for genetic linkage M. Jucker a,*, L. Bondol® a, M.E. Calhoun b, J.M. Long c, D.K. Ingram c a
Neuropathology, Institute of Pathology, University of Basel, SchoÈnbeinstrasse 40, CH-4003 Basel, Switzerland b Neurobiology of Aging Laboratories, Mount Sinai School of Medicine, New York, NY, USA c Behavioral Neuroscience Section, Laboratory of Neurosciences, Gerontology Research Center, National Institute on Aging, NIH, Baltimore, MD, USA Received 11 July 2000; received in revised form 31 July 2000; accepted 31 July 2000
Abstract To identify genetic factors involved in brain aging, we have initiated studies assessing behavioral and structural changes with aging among inbred mouse strains. Cognitive performance of C57BL/6J mice is largely maintained with aging, and stereological analysis revealed no signi®cant age-related change in neuron number, synaptic bouton number or glial number in the hippocampus. Moreover, no change in cortical neuron number and cholinergic basal forebrain neuron number has been found in this strain. 129Sv/J mice have more pronounced age-related cognitive de®cits, although hippocampal and basal cholinergic forebrain neuron number also appear unchanged with aging. Differences in neurogenesis and neuron vulnerability in the adult CNS of C57BL/6, 129/Sv and other inbred strains have been reported, which in turn may have important consequences for brain aging. Age-related lesions, such as thalamic eosinophilic inclusions and hippocampal clusters of polyglucosan bodies also vary greatly among inbred strains although the functional signi®cance of these lesions is not clear. The continued assessment of such age-related structural and behavioral changes among inbred mouse strains offers the potential to identify genes that control age-related changes in brain structure and function. q 2000 Elsevier Science Inc. All rights reserved. Keywords: Aging; Brain; CNS; Neuron; Glia; Inclusions; Mouse; Strain; Hippocampus; Linkage; Genetics; Stereology; Neurodegeneration; Neurogenesis
1. Why study brain aging of normal inbred mice? Brain aging has been studied using a variety of animal models, with nonhuman primates * Corresponding author. Tel.: 141-61-265-2894; fax: 141-61-265-3194. E-mail address: [email protected] (M. Jucker). 0531-5565/00/$ - see front matter q 2000 Elsevier Science Inc. All rights reserved. PII: S 0531-556 5(00)00190-X
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and rats being the most popular. With the rapid evolution of mouse genetics and transgenic technology, murine models have gained increased attention. Transgenic technology has successfully been used to produce mouse models which recapitulate aspects of age-related neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, or Huntington's disease (Price et al., 1998; Masliah et al., 2000). Moreover, mice have been genetically engineered to test several hypotheses of brain aging (Jucker and Ingram, 1997). It has become clear that the phenotype of such transgenic mouse models is critically dependent on the genetic background in which a transgene or a null allele has been introduced (e.g. Carlson et al., 1997). Unfortunately, relatively little information is available about normal brain aging in inbred mice, which could guide the choice of the most appropriate genetic background for production of such models and ultimately would ease the assessment of resulting phenotypes. The interest in the aging inbred mouse brain is also driven by recent progress in genetic linkage analysis in the mouse (Takahashi et al., 1994; Nadeau et al., 2000) and the endeavor to sequence the entire mouse genome. Thus, for any given age-related trait observed in one mouse strain, but not in another, quantitative trait loci (QTL) analysis can be used to identify the underlying loci and genes (McClearn, 1997). Unfortunately, few studies thus far have quantitatively assessed brain aging in more than one strain, providing the prerequisite for this `forward genetic approach' to brain aging (Ingram and Jucker, 1999). For the above reasons, there is a growing need to characterize brain aging in inbred mice. More than 400 inbred strains have been described (Beck et al., 2000), and we estimate that brain aging has been studied in less than 5%. Assessment of brain aging should be quantitative, and reproducible among laboratories. In the present review we would like to focus on structural changes, since the necessary tools to assess such changes in the aging brain have recently been developed, referred to as `modern stereological techniques' (Gundersen et al., 1988; West, 1993; Long et al., 1999a; Calhoun and Mouton, 2000). For the behavioral analysis, standardized test batteries for mouse behavior have been suggested (Crawley and Paylor, 1997) but only rarely adopted in aging studies (Ingram, 1988, 1990). 2. Structural changes in the aging mouse brain Structural alterations in the aging mouse brain have been described in numerous studies (reviewed in Jucker and Ingram, 1997). Unfortunately most of these earlier studies have used techniques that can be questioned regarding their accuracy (Long et al., 1999a). Moreover, studies have rarely been conducted in more than one mouse strain, thus making comparisons in brain aging among mouse strains dif®cult (Ingram and Jucker, 1999). We and others have initiated studies to assess age-related structural changes in the mouse brain, including age-related changes in neuron number, synaptic bouton number and glia number. Results so far are limited to the C57BL/6J and 129Sv/J strain (Table 1). No change in neuron number was found in CA1 of hippocampus and in dentate gyrus of C57BL/6J mice (Calhoun et al., 1998) and 129/SvJ mice (unpublished observations). Similarly, no signi®cant change in neuron number was found in neocortex of aging
M. Jucker et al. / Experimental Gerontology 35 (2000) 1383±1388
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Table 1 Age-related changes in neuron and glia number in the mouse brain using modern stereology Neuron #
Neuron #
Neocortex Hippocampus C57BL/6J No change No change 129/Sv No change
Cholinergic Synaptic bouton Astroglia # neuron # # (Basal Forebrain) (Hippocampus) Hippocampus
Hippocampus
No change No change
No change Increase
No change
No change No change
Microglia #
C57BL/6J mice (Bondol® et al., unpublished observations). In both C57BL/6J and 129Sv mice, the number of cholinergic forebrain neurons also appear unchanged with aging (Ward et al., 2000; Boncristiano et al., unpublished observations). Synaptic bouton numbers have been assessed only in C57BL/6J mice, and no change has been reported in CA1 of hippocampus and in dentate gyrus (Calhoun et al., 1998). No age-related changes were reported for astrocyte and microglia number in hippocampal subregions of C57BL/6J mice (Long et al., 1998). In contrast, an age-related increase in glia number was found in selected hippocampal subregions of the 129/Sv strain (Long et al., 1999b). Furthermore, glia number between the C57BL/6J and 129/ Sv strain was different in speci®c hippocampal subregions, emphasizing the need to evaluate baseline neural parameters in more than one strain. Most of these results have been collected in male mice. Interestingly, a recent report suggests an age-related increase in astrocyte number in neocortex of female C57BL/6 mice pointing to possible sex differences in the age-related glia response (Mouton et al., 2000). Strain differences have been reported in the occurrence of age-related lesions in the hippocampus and thalamus of aging mice (Table 2). Clusters of periodic-acid Schiff (PAS)-positive granular bodies develop in the aging hippocampus of some, but not in other, inbred mouse strains (Jucker et al., 1994). These polyglucosan bodies have been localized to astrocyte cytoplasm and have been referred to as glia inclusions. The signi®cance of the lesions is still unclear, but they are likely the equivalent of unusual polyglucosan bodies described in the human brain (Sugiyama et al., 1993). The age-related occurrence of eosinophilic neuronal inclusions in the thalamus of aging C57BL/6 mice and 129 mice (Yanai et al., 1995; Fraser, 1969) and of some other commonly used inbred mice is summarized in Table 2. Similar thalamic inclusions have been reported in the human thalamus, but the pathogenesis has remained unclear (Pena, 1980). These striking
Table 2 Lesions in the aging mouse brain
C57BL/6J 129/Sv DBA/2J A/J FVB/J
Polyglucosan bodies in hippocampus
Eosinophilic neuronal inclusions in thalamus
Increase with aging Increase with aging Do not occur Do not occur Do not occur
Increase with aging Increase with aging Increase with aging Do not occur Increase with aging
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strain-dependent lesions in the aging mouse brain clearly ful®ll the prerequisite for QTL analysis and the identi®cation of an underlying genetic mechanisms.
3. Strain-dependent traits which may be important for brain aging One of the most striking age-related phenomenon is the reported 80±90% decrease in neurogenesis in the aging dentate gyrus of C57BL/6 mice (Kempermann et al., 1998). Neurogenesis has been suggested to account in large measure for changes in brain plasticity and response to environmental stimulation (Gage, 2000). Although changes in neurogenesis with aging in other mouse strains have not yet been examined, a genetic in¯uence on neurogenesis has been reported (Kempermann et al., 1997). For example, neurogenesis in the dentate gyrus of young 129/Sv mice is signi®cantly less compared to young C57BL/6 mice. Since in both strains, the number of neurons in the dentate gyrus remains unchanged with aging (see above), the ®ndings suggest that the turnover of dentate gyrus neurons is higher in C57BL/6 mice compared to 129/Sv mice. Decreased neurogenesis in the aging brain has been suggested to contribute to age-related cognitive de®cits (Cameron and McKay, 1999) and thus, strain differences in neurogenesis may re¯ect strain differences in age-related cognitive function. Strain differences have also been reported in other parameters with relevance to brain aging. For example, 129/Sv mice are more prone to excitotoxic cell death in the hippocampus after kainic acid injections compared to C57BL/6 mice (Schauwecker and Steward, 1997). Moreover, strain differences in neurodegeneration after brain trauma and ischemia have been reported (Yang et al., 1997; Steward et al., 1999). Such strain differences in the cellular response to injury may confound the phenotype of gene-targeted or transgenic mouse models, but they are also a great opportunity to study genes involved in the susceptibility to neurodegeneration and brain aging.
4. Conclusion Quantitative neuroanatomical and morphological data can be exploited to map genes that are responsible for age-related structural changes in the brain (McClearn, 1997; Williams, 2000). The techniques for such linkage and mapping analysis of genes are in place. What is missing are reliable quantitative data about age-related changes among inbred mouse brains. The future success of identifying genes underlying brain aging belongs to those who have been or will start to weigh, count and measure age-related changes in various mouse strains. It is likely that this forward genetic approach will greatly advance our understanding of the genetic involvement in brain aging. At the same time, a careful characterization of brain aging among inbred mice is crucial for the interpretation of the phenotypes of transgenic mouse models of brain aging and age-related neurodegenerative diseases.
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Acknowledgements We would like to thank Dr P. Mouton for his support, and S. Boncristiano for sharing unpublished results. This work was supported by grants from the Swiss National Science Foundation and the VerUm Foundation, Munich, Germany.
References Beck, J.A., Lloyd, S., Hafezparast, M., Lennon-Pierce, M., Eppig, J.T., Festing, M.F.W., Fisher, E.M.C., 2000. Genealogies of mouse inbred strains. Nat. Genet. 24, 23±25. Calhoun, M.E., Kurth, D., Phinney, A.L., Long, J.M., Hengemihle, J., Mouton, P.E., Ingram, D.K., Jucker, M., 1998. Hippocampal neuron and synaptophysin-positive bouton number in aging C57BL/6 mice. Neurobiol. Aging 19, 599±606. Calhoun, M.E., Mouton, P.R., 2000. Length measurement: new developments in neurostereology and 3D imagery. J. Chem. Neuroanat. (in press). Cameron, H.A., McKay, R.D.G., 1999. Restoring production of hippocampal neurons in old age. Nat. Neurosci. 2, 894±897. Carlson, G.A., Borchelt, D.R., Dake, A., Turner, S., Danielson, V., Cof®n, J.D., Eckman, C., Meiners, J., Nilson, S.P., Younkin, S.G., Hsaio, K.K., 1997. Genetic modi®cation of the phenotypes produced by amyloid precursor protein overexpression in transgenic mice. Hum. Mol. Genet. 6, 1951±1959. Crawley, J.N., Paylor, R., 1997. A proposed test battery and constellations of speci®c behavioral paradigms to investigate the behavioral phenotypes of transgenic and knockout mice. Horm. Behav. 31, 197±211. Fraser, H., 1969. Eosinophilic bodies in some neurones in the thalamus of ageing mice. J. Pathol. 98, 201±204. Gage, F.H., 2000. Mammalian neural stem cells. Science 287, 1433±1438. Gundersen, H.J.G., Bagger, P., Bendtsen, T.F., Evans, S.M., Korbo, L., Marcussen, N., Moller, A., Nielsen, K., Nyengaard, J.R., Pakkenberg, B., Sorensen, F.B., Vesterby, A., West, M.J., 1988. The new stereological tools: disector, fractionator, nucleator and point sampled intercepts and their use in pathological research and diagnosis. Acta. Pathol. Immunol. Scand. 96, 857±881. Ingram, D.K., 1988. Motor performance variabilty during aging in rodents: assessment of reliability and validity of individual differences. Ann. N.Y. Acad. Sci. 515, 70±96. Ingram, D.K., 1990. Perspectives on genetic variability in behavioral aging of mice. In: Harrison, D.E. (Ed.). Genetic effects on aging II. Telford Press, Caldwell, NJ, pp. 205±231. Ingram, D.K., Jucker, M., 1999. Developing mouse models of aging: a consideration of strain differences in agerelated behavioral and neural parameters. Neurobiol. Aging 20, 137±145. Jucker, M., Ingram, D.K., 1997. Murine models of brain aging and age-related neurodegenerative diseases. Behav. Brain Res. 85, 1±25. Jucker, M., Walker, L.C., Schwarb, P., Hengemihle, J., Kuo, H., Snow, A.D., Bamert, F., Ingram, D.K., 1994. Age-related deposition of glia-associated ®brillar material in brains of C57BL/6 mice. Neuroscience 60, 875± 889. Kempermann, G., Kuhn, H.G., Gage, F.H., 1997. Genetic in¯uence on neurogenesis in the dentate gyrus of adult mice. Proc. Natl. Acad. Sci. USA 94, 10409±10414. Kempermann, G., Kuhn, H.G., Gage, F.H., 1998. Experience-induced neurogenesis in the senescent dentate gyrus. J. Neurosci. 18, 3206±3212. Long, J.M., Kalehua, A.N., Muth, N.J., Hengemihle, J.M., Calhoun, M.E., Jucker, M., Ingram, D.K., Mouton, P.R., 1998. Total number of astrocyte and microglia in hippocampus of C57BL/6 mice at different ages. Neurobiol. Aging 19, 497±503. Long, J.M., Mouton, P.R., Jucker, M., Ingram, D.K., 1999a. What counts in brain aging? Design-based stereological analysis of cell number. J. Gerontol. 54, B407±B417. Long, J.M., Hengemihle, J.M., Moon, E.K., Jucker, M., Calhoun, M.E., Mascarucci, P., Mouton, P.R., Ingram, D.K., 1999b. Comparison of hippocampal glia number C57BL/6J and 129/SvJ mice of different ages. Soc. Neurosci. Abstr. 25, 28.
1388
M. Jucker et al. / Experimental Gerontology 35 (2000) 1383±1388
Masliah, E., Rockenstein, E., Veinbergs, I., Mallory, M., Hashimoto, M., Takeda, A., Sagara, Y., Sisk, A., Mucke, L., 2000. Dopaminergic loss and inclusion body formation in a-synuclein mice: implications for neurodegenerative disorders. Science 287, 1265±1269. McClearn, G.E., 1997. Prospects for quantitative trait locus methodology in gerontology. Exp. Gerontol. 32, 49± 54. Mouton, P.R., Long, J.M., Stocks, E.A., Ram, S., Howard, U., Juclier, M., Calhoun, M.E. 2000. Age- and genderrelated differences in total numbers of astrocytes and microglia in hippoconupal subregions of C57BL16 mouse brains. Soc. Neurosa. Abstr. 26 (in press). Nadeau, J.H., Singer, J.B., Matin, A., Lander, E.S., 2000. Analysing complex genetic traits with chromosome substitution strains. Nat. Genet. 24, 221±225. Pena, C.E., 1980. Intracytoplasmic neuronal inclusions in the human thalamus. Acta Neuropathol. (Berl) 52, 157±159. Price, D.L., Sisodia, S.S., Borchelt, D.R., 1998. Genetic neurodegenerative diseases: the human illness and transgenic models. Science 282, 1079±1083. Schauwecker, P.E., Steward, O., 1997. Genetic determinants of susceptibility to excitotoxic cell death: implications for gene targeting approaches. Proc. Natl. Acad. Sci. USA 94, 4103±4108. Steward, O., Schauwecker, P.E., Guth, L., Zhang, Z., Fujiki, M., Inman, D., Wrathall, J., Kempermann, G., Gage, F.H., Saatman, K.E., Raghupathi, R., McIntosh, T., 1999. Genetic approaches to neurotrauma research: opportunities and potential pitfalls of murine models. Exp. Neurol. 157, 19±42. Sugiyama, H., Hainfellner, J.A., Lassmann, H., Indravasu, S., Budka, H., 1993. Uncommon types of polyglucosan bodies in the human brain: distribution and relation to disease. Acta Neuropathol. 86, 484±490. Takahashi, J.S., Pinto, L.H., Vitaterna, M.H., 1994. Forward and reverse genetic approaches to behavior in the mouse. Science 264, 1724±1733. Ward, N.L., Stanford, L.E., Brown, R.E., Hagg, T., 2000. Cholinergic medial septum neurons do not degenerate in aged 129/Sv control or p75 NGFR 2 /2mice. Neurobiol. Aging 21, 125±134. West, M.J., 1993. New stereological methods for counting neurons. Neurobiol. Aging 14, 275±285. Williams, R.W., 2000. Mapping genes that modulate mouse brain development: a quantitive approach. In: Goef®net, A., Rakic, P. (Eds.). In: Mouse Brain Development, Springer Verlag, New York, pp. 21±49. Yanai, T., Masegi, T., Yoshida, K., Ishikawa, K., Kawada, M., Iwasaki, T., Yamazoe, K., Suzuki, Y., Goto, N., 1995. Eosinophilic neuronal inclusions in the thalamus of ageing B6C3F1 mice. J. Comp. Path. 113, 287± 290. Yang, G., Kitagawa, K., Matsushita, K., Mabuchi, T., Yagita, Y., Yanagihara, T., Matsumoto, M., 1997. C57BL/6 strain is most susceptible to cerebral ischemia following bilateral common carotid occlusion among seven mouse strains: selective neuronal death in the murine transient forebrain ischemia. Brain Res. 752, 209±218.