Cells and Surveys Should Biological Measures Be Included in Social Science Research? (2001) / Chapter Skim
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Biomarkers and Genetics of Aging Mice
Biomarkers and Genetics of Aging Mice
Pages 180-212
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From page 180... ...
The goal of this essay is to present, for the nonbiologist, a summary of how studies of age-sensitive biological traits can contribute to our knowledge of aging, its measurement, and its genetics. We will begin with a discussion about the nature of aging and whether its rate can be measured, present a set of proposed criteria for deciding if an age-sensitive trait provides a useful biomarker of aging, illustrate these validation criteria with examples drawn from T-cell subset testing, and show how genetic data can help to sort out the relation of age-related physiological changes to disease risk and life span.
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From page 181... ...
differential survival, which removes individuals from their age cohort and does so nonrandomly with respect to age-dependent physiological effects. Is There An "Aging Process" Per Se?
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From page 182... ...
Selective pressures in this new ecological niche favored slow-aging genotypes, and the resulting population survives much longer than their mainland cousins. Initial mortality rates do not differ greatly between the two populations, suggesting that differences in predation pressure per se contribute relatively little to these survival statistics, but changes in the slope of the mortality risk curve support the idea that the island opossums age more slowly than their mainland cousins by a factor of nearly two.
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From page 183... ...
Natural selection has produced long-lived species and subspecies from shorter-lived ones dozens of times (e.g., turtles, tuna, elephants, bats, parrots, and chimps do not share a recent common ancestors. Evolution of extended longevity seems to emerge over and over again from selective conditions that promote large body size, slowed development, and relatively small litter sizes.
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From page 184... ...
An individual unlucky enough to inherit the genes for cystic fibrosis, be infected by HIV, or hit by a bus may die at an age at which aging has yet to cause much increase in vulnerability. Although changes in the mean longevity of a test population may be altered by interventions with little effect on aging, the slope of the mortality curve (or the mortality rate doubling time)
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From page 185... ...
It is regrettably safe to agree that "it is too early to constitute a definitive panel of biomarkers for either animal models or humans" (Sprott, 1999:464~. Proposed validation rules for candidate biomarkers vary widely among different experts, and sometimes between different formulations from the same experts.
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From page 186... ...
for specific forms of death would otherwise qualify: unstable angina, high titers of serum HIV, or a consistent history of cigarette or drug use are all predictors of subsequent longevity because of their association with specific causes of death, but these traits do not provide information about the kind of underlying aging processes that would, by hypothesis, increase risk factors for the wide range of late-life causes of death.
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From page 187... ...
, and is decelerated by calorically restricted diets that postpone aging and
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From page 188... ...
The filled circles and darker line represent female mice, and the open circles and lighter line represent males. There is a significant correlation between CD4M levels and longevity; R2 = 0.18, p = 0.0003 after adjustment for gender effects.
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From page 189... ...
If CD4M levels are indeed useful as biomarkers of an underlying aging process, then their association with longevity should be equally apparent for a wide range of terminal diseases. Indeed, the strength of this association was found to be similar in subgroups of the mice dying of different causes, including fibrosarcoma, lymphoma, mammary carcinoma, and a miscellaneous group of other neoplasms (Miller et al., 1997~; the association reached statistical significance in the two subgroups with the largest numbers of cases.
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From page 190... ...
There is a significant inverse correlation at each age: mice with high levels of CD4M cells tend to have low levels of muscle force. SOURCES: Faulkner et al.
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From page 191... ...
Female mice (dark line, filled circles) show no association between CD4P levels and life expectancy, but male mice (lighter line, open circles)
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From page 192... ...
None of the T-cell subsets tested at 8 months of age was able to predict subsequent longevity in the virgin males or virgin females, but there was a significant inverse correlation between CD8M cells and longevity in the mated females. Figure 8-4 shows the scatterplots for all four sets of mice.
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From page 193... ...
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From page 194... ...
have reluctantly decided to use mouse life span as a crude surrogate for aging itself, reasoning that genetic alleles that extend life span well beyond the median for the tested population may be operating via an influence on aging itself. Work conducted using recombinant inbred mouse stocks (German et al., 1988; de Haan and Van Zant, 1999)
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From page 195... ...
Mice bred in this way are, from a genetic perspective, all siblings; each shares a random half of its alleles with every other animal in the UM-HET3 population. The current set of analyses was conducted when genotype and longevity data were available from a group of 110 virgin males and 143 virgin females.
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From page 196... ...
FIGURE 8-5 Genetic regulation of longevity in mice stratified by cause of death. Female mice that inherit the C3H allele at D2Mit58 plus the BALB allele at D16Mitl82 (light gray bars)
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From page 197... ...
Twenty-two of the mice died of congestive heart failure, inanition, amyloidosis, endometritis, or another non-neoplastic illness, and among these the favorable allele combination was associated with 165 days of additional life span. The bottom two bars in the figure document the effects of the C3H-plus-BALB alleles on the 39 mice dying of lymphoma (effect size 186 days, p = 0.02)
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From page 198... ...
Similar effect sizes are seen for mice dying of cancer or of non-neoplastic illnesses ("benign") , and among the cancer deaths the genetic effect is similar for deaths due to lymphoma and hepatoma.
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From page 199... ...
postponement of death in male mice dying of diseases other than MUS, but are associated with a significant acceleration of death in those mice that do die of MUS. The bottom panel shows that the risk among males of dying of MUS is associated with the C3H allele at D6Mit268.
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From page 200... ...
Large differences in longevity across species are sometimes due to alterations in mortality rate doubling time, but in other cases reflect alterations in initial mortality risks; Finch (1990) , for example, notes that the threefold difference in longevity between rhesus monkeys and humans reflects a 100fold difference in initial mortality rate without any detectable difference in mortality rate doubling time.
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From page 201... ...
It is worth stressing that this initial study involved analysis of only 145 mice, and thus had very low statistical power for detecting genetic effects that controlled less than 25 percent or so of the phenotypic variance. Similar analyses are now underway in larger samples of the same genetic constitution and should reveal additional examples of gene/subset associations.
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From page 202... ...
The bottom panel shows the relationship between genotype at D9MitllO and the CD4P subset: mice inheriting the C3H allele have higher levels of CD4P cells at 18 months of age, but there is no genotypic effect at 8 months. SOURCE: Jackson et al.
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From page 203... ...
Mice with this particular combination of alleles, together with randomly chosen sibling controls, could then be tested, at any age, for factors telomere length, fibroblast growth patterns, levels of protein oxidation, immunological vigor hypothesized to play a role in controlling age-sensitive physiological changes or disease risks. By providing a way to identify siblings destined for longer or shorter lives, the gene-selected mouse populations could provide an approach to sorting the long list of potential aging mechanisms into those that do or do not show the expected association with longevity.
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From page 204... ...
Genetic and biomarker analysis of mice whose great-grandparents include both wild-derived and laboratory-derived stocks could help to determine which early life traits growth rate, reproductive scheduling, early or sustained immune function are best associated with differences in life span and disease risk, and set the stage for mapping the corresponding QTL that distinguish wild-derived from laboratory-derived mice in these respects. The Height-Life Span Nexus Several observations and lines of experimentation have raised the issue of whether interindividual differences in aging rate are influenced by genes that modulate body size and early-life growth patterns.
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From page 205... ...
Differences among these stocks in longevity did not reflect major differences in the cause of death, except for one large, short-lived stock in which most animals died of pituitary adenoma, potentially a source of growth hormone overproduction. These results are thus consistent with the idea that genetic effects on life span may, to an important degree, be the side effects of genes selected (naturally by ecological forces or artificially by selective breeding schemes)
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From page 206... ...
GENE EXPRESSION SCREENING Gene mapping methods deal with questions of inherited characteristics the variations in DNA sequences that influence differences between people in body size, eye color, life span, and personality characteristics. Gene expression studies, in contrast, generate lists of which genes are expressed in specific cell types.
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From page 207... ...
Would some of these genes also prove to be differentially expressed by mice inheriting the genetic alleles associated with longer life span in the QTL analyses? Would a subset also prove to distinguish longer-lived mouse stocks in the Atchley set or to discriminate wild mice from those born into laboratory stocks?
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From page 208... ...
Some questions about genetic influences on traits of interest will require genotyping at a very small number of loci and thus require no more DNA than that available from a small blood sample; other genetic questions may require a stable, larger supply of DNA and thus justify the expense of setting up long-term cultures from blood cells or cheek scrapings. Questions that require information about transient hormonal levels, chronic exposure to blood chemicals, patterns of gene expression, or responsiveness of specific cell types will each imply very different sample collection (and in some cases sample preparation and archiving)
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From page 209... ...
Analytical strategies that depend upon correlations between variables measured in middle age and those tested in old age are reasonably straightforward in rodent colonies, but exceptionally difficult in human populations. The hypothesis that T-cell subsets predict future health status, or that diets high in a specific antioxidant might help to postpone neoplasia or cataracts, or that the rate of skeletal growth in the first 10th of the life span influences cancer risk at late ages, or that mildly elevated serum glucocorticoid levels in young adulthood are associated with higher mean longevity, can be tested first in mouse or rat populations; those hypotheses that still appear promising after such a screening process will thus earn consideration for incorporation into studies of human populations.
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From page 210... ...
Patterson, and E.R. Froesch 1984 Body size parallels insulin-like growth factor I levels but not growth hormone secretory capacity.
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From page 211... ...
Faulkner 1996 Candidate biomarkers of aging: Age-sensitive indices of immune and muscle function co-vary in genetically heterogeneous mice. Journal of Gerontology: Biological Sciences 52A:B39-B47.
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From page 212... ...
A Zimmerman 1993 Low methionine ingestion by rats extends life span.
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