Long term calorie restriction has the benefit of increasing life span. Methods to screen interventions that mimic the effects of calorie restriction are disclosed. Extensive analysis of genes for which expression is statistically different between control and calorie restricted animals has demonstrated that specific genes are preferentially expressed during calorie restriction. Screening for interventions which produce the same expression profile will provide interventions that increase life span. In a further aspect, it has been discovered that test animals on a calorie restricted diet for a relatively short time have a similar gene expression profile to test animals which have been on a long term calorie restricted diet.
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0. 27. A method of identifying an intervention that mimics the effects of caloric restriction in cells, comprising:
obtaining a biological sample;
exposing the biological sample to an intervention;
waiting a specified period of time;
assessing changes in gene expression levels, levels of RNA, protein, or protein activity levels related to one or more biomarkers of aging; and
identifying the intervention as one that mimics the effects of caloric restriction if one or more changes in the levels also occurs in a reference animal subjected to short term caloric restriction.
0. 1. A method of identifiing an intervention that mimics the effects of caloric restriction in cells, comprising:
obtaining a biological sample;
exposing said biological sample to an intervention;
waiting a specified period of time;
assessing changes in gene expression levels, levels of RNA, protein, or protein activity levels related to one or more biomarkers of aging; and
identifying said intervention as one that mimics the effects of caloric restriction if one or more changes in said levels also occurs in caloric restriction.
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obtaining a gene expression profile from a calorie-restricted reference animal;
comparing changes in gene expression for the test animal to the gene expression profile of the calorie-restricted reference animal; and
identifying said intervention as one that mimics the effects of calorie restriction if the gene expression profile of the test animal is statistically similar to the gene expression profile of the calorie restricted animal.
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This application is a continuation in part of U.S. application Ser. No. 09/471,224, filed Dec. 23, 1999.
1. Field of the Invention
For years, researchers have attempted to identify biomarkers of aging to facilitate the identification of interventions that might slow or reverse the aging process. Dietary calorie restriction (CR) is the only well-documented method for extending life span in homeothermic vertebrates, and is the most effective means known for reducing cancer incidence. Although many of the physiological consequences of CR were described 65 years ago, there is no consensus regarding its mode of action. Consequently, there has been no practical method of identifying interventions that might mimic such calorie-restriction effects. Rather, a researcher would have to wait the test animal's lifetime to determine whether a particular intervention impacted life-span and/or cancer incidence.
2. Description of the Related Art
Mammals seem to share a common set of genes, and yet they have widely differing life spans. It is impossible to know at present whether the differences in life spans are due to differences in the sequence of specific genes, or to differences in their expression. However, it is clear from many years of study in dozens of laboratories that long term reduction in dietary calorie consumption (CR) delays most age-related physiological changes, and extends life span in all species tested, provided malnutrition is avoided (Weindruch, et al. The Retardation of Aging and Disease by Dietary Restriction (Charles C. Thomas, Springfield, Ill., 1988)). These studies also have shown that CR is the most effective means now known for reducing cancer incidence and increasing the mean age of onset of age-related diseases and tumors in homeothermic vertebrates (Weindruch et al. (1982) Science 215: 1415). Thus, it seems clear that life spans can be extended through a relatively simple dietary regimen. However, there are no studies on the effects of short term calorie restriction on metabolism and gene expression.
One report has been published of gene expression profiling in muscle (Lee et al. (1999) Science 285: 1390) In these studies, many age related changes in muscle gene expression appeared to be prevented or reversed by CR. The expression profiles of 6500 genes were compared among old, long-term CR and control mice, and young control mice. Some age-related changes in muscle gene expression appeared to be wholly or partially prevented by CR.
The present invention contemplates a method of identifying interventions within a short time frame that mimic the effects of calorie restriction. Such interventions will lead to increased life span, reduce cancer incidence, and/or increase the ago of onset of age-related diseases and tumors.
In a preferred embodiment a method of identifying an intervention that mimics the effects of caloric restriction in cells is disclosed, comprising the steps of:
The biological sample may be either in vitro or in vivo. In a preferred embodiment, the biological sample comprises cells. In a more preferred embodiment, the cells are obtained from a mammal. In an even more preferred embodiment, the mammal is a mouse.
In one embodiment, the change in gene expression levels, levels of RNA, protein, or protein activity levels corresponds to a change in gene expression for a gene encoding a chaperone protein. In a preferred embodiment, the chaperone protein is GRP78.
In one embodiment, said biomarker is apoptosis. In another preferred embodiment, said biomarker is aging. In another preferred embodiment, said biomarker of aging is a production of cancer cells.
In a preferred embodiment, the changes in said gene expression level, levels of RNA, protein, or protein activity levels related to one or more biomarkers of aging occur in 6 weeks or less. In a more preferred embodiment, the changes in said gene expression levels, levels of RNA, protein, or protein activity levels related to one or more biomarkers of aging occur in four weeks or less. In an even more preferred embodiment, the changes in said gene expression levels, levels of RNA, protein, or protein activity levels related to one or more biomarkers of aging occur in two weeks or less. In a most preferred embodiment, the changes in said gene expression levels, levels of RNA, protein, or protein activity levels related to one or more biomarkers of aging occur in about two days or less.
In a one embodiment, changes in gene expression are evaluated using a gene chip. In a preferred embodiment, the gene chip contains genes for immune system activation. In another preferred embodiment, the gene chip contains genes for DNA repair. In another preferred embodiment, the gene chip contains genes associated with apoptosis. In another preferred embodiment, the gene chip contains genes for the enteric nervous system.
In an alternate embodiment, the biological sample is a test animal. In a preferred embodiment the disclosed method additionally comprises determining changes in said levels in a reference animal having identifying characteristics of a long-term calorie-restricted animal wherein the reference animal has been on a calorie restricted diet for less than about 6 weeks and wherein said changes are used in said identifying said intervention as one that mimics the effects of calorie restriction. In a more preferred embodiment, the reference animal has been on a calorie restricted diet for less than about 4 weeks. In an even more preferred embodiment, the reference animal has been on a calorie restricted diet for less than about 2 weeks.
In a preferred embodiment, the test animal is a mouse. In a preferred embodiment, changes in gene expression are assessed in the test animal.
In a more preferred embodiment, the disclosed method further comprises:
In a more preferred embodiment, the gene expression profile of the test animal is determined to be statistically similar to the gene expression of the calorie restricted animal by one-way ANOVA followed by Fisher's test (P<0.05).
In another aspect of the invention, a system is disclosed for identifying an intervention that mimics the effects of calorie restriction in a test animal comprising a test animal and a gene chip comprising genes known to have altered expression during calorie restriction. In a preferred embodiment, the gene chip comprises genes selected from the group consisting of genes for immune system activation, genes for DNA repair, genes associated with apoptosis and genes for the enteric nervous system.
For purposes of summarizing the invention and the advantages achieved over the prior art, certain objects and advantages of the invention have been described above. Of course, it is to be understood that not necessarily all such objects or advantages may be achieved in accordance with any particular embodiment of the invention. Thus, for example, those skilled in the art will recognize that the invention may be embodied a carried out in a manner that achieves or optimizes one advantage or group of advantages as taught herein without necessarily achieving other objects or advantages as may be taught or suggested herein.
Further aspects, features and advantages of this invention will become apparent from the detailed description of the preferred embodiments which follow.
The file of this patent contains at least one drawing executed in color. Copies of this patent with color drawing(s) will be provided by the Patent and Trademark Office upon request and payment of the necessary fee.
These and other feature of this invention will now be described with reference to the drawings of preferred embodiments which are intended to illustrate and not to limit the invention.
FIG. 1. Effects of feeding on hepatic GRP78 and ERp72 mRNA. At 0, 1.5, 5 and 12 h following feeding, 5 mice from each dietary group were killed. Their weights after 24 h of fasting were 22.96±1.49 for CR and 37.12±1.19 g for control mice. GRP78 mRNA (A) and ERp72 mRNA (B) from control (closed circle) and CR (open circle) mice were quantified using dot-blots. RNA loading and transfer were normalized using data obtained from serial probings for 18S ribosomal RNA and S-II mRNA. Similar results were obtained with both control probes. CR and control mice, fed once daily for 30 days, were fasted for 24 hours and killed (n=5, 0 time point) or refed and killed at the times specified (n=5 for each time point). + represents P<0.01 significance of difference between CR and control at each time point. * represents P<0.01 significance of difference from the 0 time point within each dietary group. The 0 and 24 hour times points are the same data set.
FIG. 2. The gene and tissue specificity of the chaperone feeding response. A, The domain of chaperone genes responsive to feeding was determined by quantifying hepatic chaperone mRNA abundance using RNA from mice fasted for 48 hours (n=6; open bars) or from mice fasted 48 hours, refed and killed) 1.5 h later (n=6; filled bars). The mRNAs were quantified by dot-blotting and Northern blotting. There was no significant difference in the results obtained with either technique. The dot-blotting results are shown. B, Liver, kidney, and muscle GRP78 mRNA from 24-hour fasted mice (n=4), and from 24-hour fasted mice 1.5 hours after feeding (n=5). These data were from different mice than used in panel A. The statistical significance of the results are indicated (*, P<0.05; **, P<0.01; ***, P<0.001).
FIG. 3. Effects of CR on hepatic pre-mRNA and GRP78 mRNA abundance. A, RNase protection of pre-mRNA and mRNA in CR and control mice. Hepatic RNA was purified from control and CR mice and hybridized with an RNA probe for transcripts spanning the third intron and fourth exon boundary of the GRP78 gene. The precursor mRNA protected a 223 base region of the probe, labeled GRP78 pre-mRNA, while the GRP78 mRNA protected a 113 base fragment, so labeled in the figure. A probe for S-II mRNA coding sequences was included in each reaction as an internal control. It protected a 185 base fragment labeled S-II mRNA in the figure. Lane 1 shows the protected fragments produced by the GRP78 probe and mouse liver RNA. Lane 2 shows the fragments produced by the S-II probe hybridized to yeast total RNA. Lane 3 shows the results produced by the S-II probe hybridized to mouse liver RNA. Lanes 4, 6, and 8 show the results produced by hepatic RNA from control mice. Lanes 5, 7, and 9 show the results with RNA from CR mice. Quantification of the abundance of the protected fragments representing the GRP78 mRNA (B) and pre-mRNA (C). Studies such as than shown above were conducted using hepatic RNA from 6 CR and 6 control mice. The intensity of the protected fragments was quantified with a phosphorimager. The intensities of the pre-mRNA and mRNA fragments were normalized to the intensity of the protected fragment representing S-II mRNA. Statistical significance is indicated as in the legend to FIG. 2.
FIG. 4. Effects of feeding on hepatic GRP78 mRNA and pre-mRNA abundance. A, RNase protection of probes for hepatic GRP78 pre-mRNA and mRNA in mice after 48 hours of fasting (n=5), or 1.5 h after feeding of 48-hour fasted mice (n=5). RNA purified from liver was hybridized either to a probe for primary transcripts containing the exon 7 and intron 7 boundary of the GRP78 gene which produced a 257 base protected fragment (labeled S-II+GRP78; lanes 7-12), or to a probe for primary transcripts spanning the exon 7 and intron 7 boundary, which protected a 200 nucleotide fragment (labeled S-II+tGRP78, lanes 13-18), as indicated in the figure. GRP78 mRNA produced a 143 nucleotide fragment representing GRP78 mRNA, as indicated in the figure. A probe for S-II mRNA coding sequences was included in each reaction as an internal control. With this probe, S-II mRNA protected a 277 nucleotide fragment, labeled S-II mRNA in the figure. Lane 1, RNA markers. Lanes 2-6, hybridization of the indicated probes with yeast tRNA. Lanes 7-12, hybridization of the GRP78 and S-II probes with RNA from fasted (lanes 7-9) and refed (lanes 10-12) mice. Lanes 13-18, hybridization of tGRP78 and S-II probes with RNA from fasted (lanes 13-15) and refed (lanes 16-18) mice. Quantification of the abundance of the protected fragments representing the GRP78 mRNA(B) and pre-mRNA (C). Studies such as those shown above were conducted using hepatic RNA from 6 CR and 6 control mice. The intensity of the protected fragments was quantified and normalized as described in
FIG. 5. Effects of protein synthesis inhibitors on the feeding response of GRP78 (A) and PEPCK (B) mRNA. Mice fasted for 48 h were injected i.p. with vehicle and after 1 hour injected a second time i.p with vehicle (Refed+Sham; n=6). Mice fasted for 48 hours were injected i.p. with vehicle 30 min before and 30 min after feeding (Refed+Sham, n=6). Mice fasted for 48 h were injected i.p. with cycloheximide and after 1 hour injected a second time i.p with cycloheximide (Fastest+Cycloheximide; n=6). Mice fasted for 48 h were injected i.p. with cycloheximide 30 min before and 30 min after feeding (Refed+Cycloheximide; n=6). Mice fasted for 48 h were injected i.p. with puromycin and after 1 hour injected a second time i.p with puromycin (Fasted+Puromycin; n=6). Mice fasted for 48 h were injected i.p. with puromycin 30 min before and 30 min after feeding (Refed+Puromycin; n=6). GRP78 and PEPCK mRNA abundance were determined using purified hepatic RNA. Bars without common superscripts are significantly different (P<0.005).
FIG. 6. Regulation of the fasting-feeding response by insulin, dibutyryl-cAMP, glucagon, and ingestion of mineral oil and cellulose. A, Groups of six mice were fasted for 48 h and treated as follows: Fasted+Sham mice were injected with vehicle and 1 h later vehicle injected a second time; Fed+Sham mice were sham injected with vehicle 30 min before and 30 min after feeding; Fed+cAMP mine were injected with dibutyryl-cAMP and theophylline 30 min before and 30 min after feeding; Fed+glucagon mice were injected with glucagon 30 min before and 30 min after feeding; Fasted Diabetic+Sham mice, previously rendered diabetic with STZ, were vehicle injected and 1 h later vehicle injected a second time; Fed Diabetic+Sham, STZ-diabetic mice were sham injected with vehicle 30 min before and 30 min after feeding; Fed Diabetic+cAMP, diabetic mice were injected with dibutyryl-cAMP and theophylline 30 min before and 30 min after feeding. All mice were killed 1 h after their last injection. Total RNA was isolated from the liver and subjected to dot-blot analysis. Bars with no common superscripts are significantly different (P<0.005). B, Effects of mineral oil and cellulose ingestion on liver GRP78 mRNA abundance. Groups of six mice were fasted for 48 h and treated as follows: Fasted, mice were fasted for 48 h and killed; Fed, mice were fasted for 48 h, fed, and killed 1.5 h later; Fasted+cellulose, mice fasted for 48 h were fed a mixture of cellulose and mineral oil, and killed 1.5 h later. Significance is indicated as in the legend to FIG. 5.
FIG. 7. Effects of adrenalectomy and dexamethasone administration on the expression and regulation of hepatic GRP78 mRNA. Groups of six mice were fasted for 48 h and treated as follows: Fasted+Sham, sham-operated mice were injected with vehicle IP 7.5 h and 1.5 h before they were killed; Fed+Sham, sham-operated mice were injected with vehicle IP 6 hours before and 30 min after feeding, and mice were killed 1 h after the last injection; Adx Fasted+Sham, adrenalectomized mice were injected with vehicle IP 7.5 h and 1.5 h before they were killed; Adx Fed+Sham, adrenalectomized mice were injected with vehicle IP 6 hours before and 30 min after feeding, and the mice killed 1 h later; Adx Fasted+Dex, adrenalectomized mice were injected IP with dexamethasone 7.5 h and 1.5 h before they were killed; Adx Fed+Dex, adrenalectomized mice were injected IP with dexamethasone 6 hours before and 30 min after feeding, and killed 1 h later. Significance is indicated as in the legend to FIG. 5.
FIG. 8. The hepatic gene expression profiles of old control, old CR, young control, and young CR mice. The mice weighed 37.2+1.9 g, 22.8+1.2 g, 26.0+2.8 g, and 19.4+1.6 g, respectively. The CR groups consumed approximately 50% fewer calories than their control counterparts post-weaning, as described. Levels of specific mRNA were determined using the Mu11KsubA and Mu11KsubB GeneChip o Oligonucleotide-based high-density array RNA expression assays were performed according to the standard Affrymetrix protocol. The biotinylated, fragmented cRNA was hybridized to the Mu11KsubA and Mu11KsubBGeneChip GeneChip® arrays (Affymetrix, Santa Clara, Calif.), which contain targets for more than 11,000 known mouse genes and ESTs. The arrays were washed, stained and scanned. Scanned image analysis and data quantification were performed using the Affymetrix GeneChip GeneChip® analysis suite v3.2 at default parameter settings. Resultant data were normalized by global scaling.
Data analysis. Data sets were normalized furher using GeneSpring 3.0 (Silicon Genetics, San Carlos, Calif.). Negative expression levels were forced to zero, and the expression data for each animal divided by the median of all experimental values for that chip above an expression level of 10. This step reduced cliip-to-chip signal variation. Fold change in expression was calculated by dividing the mean of the expression levels in the CR groups by the mean of the expression levels in the control group.
Statistical analysis. To test for significance of the effect of diet on gene expression, one-way ANOVA was followed by Fisher's test (P<0.05). Genes were placed in expression pattern groups (Table 2) for which they passed both tests. All statistical analyses were performed using Minitab Statistical Software.
The global patterns of hepatic gene expression in the three groups of mice as displayed by GeneSpring 3.0, are shown in FIG. 8. The 11,000 genes assayed in the study are grouped according to both structure and function by the GeneSpring gene clustering algorithm across the horizontal axes of the figure. While this representation of the data cannot be subjected to statistical tests, subjective examination of this color coded representation of the data obtained immediately suggests that striking similarities exist in the gene expression profile of long and short term CR mice. Likewise, examination of the figure suggests that both CR expression profiles are very different than the profile of control mice. An average-linkage hierarchical clustering dendrogram calculated from the data by the GeneSpring clustering algorithm is shown to the left of the expression profiles. The dendrogram shows that the algorithm clustered the short- and long-term CR groups together, separated from the control group. This analysis agrees with our subjective interpretation of the expression profile.
Another aspect of this representation of the data was of interest. Significantly larger areas of blue were found in the expression profile of the control mice. These areas represent genes for which expression was not detectable. In both groups of CR mice, many of these regions were red, indicating higher levels of expression. Thus, a major effect of CR was the activation of specific gene expression.
To quantify the similarities in gene expression among groups of mice, a global expression correlation coefficient was calculated for each possible pair of mice. Table 1 shows the nine by nine matrix of these pairwise comparisons. The values are a measure of the similarities in gene expression between pairs of mice. Because the mice were genetically identical, the intra-group values provide a measure of the maximum correlations attainable. The inter-group correlations of the short- and long-term CR mice were similar to their intra-group correlations, indicating that gene expression in all CR mice was similar. In contrast, the control mice have little correlation with the mice in either CR group. This analysis suggests that short- and long-term CR had highly similar effects on overall patterns of specific gene expression.
TABLE 1
Pairwise comparisons of the global gene expression
correlation coefficient calculated for each possible pair of mice.
CR
CONTROL
SWITCHED
CR
1.00*
0.25
0.32
0.01
0.04
−0.04
0.16
0.17
0.18
1.0
0.27
−0.03
0.03
−0.01
0.13
0.12
0.18
1.00
0.02
0.02
−0.02
0.18
0.14
0.21
CONTROL
1.00
0.29
0.42
0.0
0.03
0.07
1.00
0.28
0.07
0.10
0.01
1.00
−0.02
0.02
0.05
SWITCHED
1.00
0.24
0.18
1.0
0.16
1.00
The pseudogene function of GeneSpring 3.0, and statistical analysis of the data were utilized to sort the genes into one of seven possible categories of relative gene expression. These groups were: expression not different among groups; expression high in long-term CR, low in control, and high in short-term CR (termed, high-low-high) (Appendix A); expression low in long-term CR, high in control, and low in short-term CR (low-high-low) (Appendix B); expression low in long-term CR and control, but high in short-term CR (low-low-high) (Appendix C); expression high in long-term CR and control, and low in short-term CR (high-high-low) (Appendix D); expression high in long-term CR, and low in control and short-term CR (high-low-low) (Appendix E); and expression low in long-term CR and high in control and short-term CR (low-high-high) (Appendix F). The vast majority of the genes were not different among groups, and will not be discussed further.
Table 2 shows the number of genes and expressed sequence tags (ESTs) in each of the other groups. Ninety percent or these genes and ESTs were in the high-low-high and low-high-low groups. In these groups, the short- and long-term CR expression patterns are most similar. The other 4 groups accounted for only 10% of the remaining genes ans ESTs. These data indicate that short- and long-term CR produced remarkably similar effects on the expression of more than 11,000 hepatic genes and ESTs. A complete listing of the expression data for the genes and ESTs in each group is available (http://wwwbiochemistry.ucr.edu/faculty/spindler.html/GeneChipData) (This URL will be activated upon allowance of this application) on the internet.
By far the most common response to short- and long-term CR was the high-low-high expression pattern. It accounted for nearly 86% of the genes and ESTs in the groups. Thus, the most common effect of short- and long-term CR was the activation of gene expression. To determine whether short- and long-term CR induced expression to the same degree in the high-low-high group, we tabulated the number of known genes for which expression was statistically the same in the two groups. In high-low-high, 303 of 340 known genes (89%) were expressed at the same level in the short- and long-term CR groups. For 26 of these genes (8%), expression in the long-term CR mice was statistically greater. For 11 genes (3%), expression was greater in the short-term CR group. Thus, short- and long-term CR induced the expression of the vast majority of these genes to the same levels.
Of the genes in the high-low-high group, 146 of 340 genes were activated from undetectable levels in the control mice to much higher, but very similar levels in both CR groups. Expression of these genes averaged 1.25±0.25 and 1.23±0.23, in the short- and long-term CR groups, respectively. These observations reinforce the idea that short- and long-term CR have highly homologous effects on the expression of genes.
To further understand the genomnic effects of CR, we identified the genes in the high-low-high group described above.
TABLE 2
GENES WHICH DIFFER FROM CONTROL IN
RESPONSE TO CR
LT CR*
CONTROL
ST CR**
GENES
ESTs
PERCENT
High
Low
High
340
860
85.7
Low
High
Low
23
37
4.3
High
High
Low
4
9
0.9
Low
Low
High
13
19
2.3
High
Low
Low
26
55
5.8
Low
High
High
9
6
1.1
*Long-term CR
**Short-term CR
Many of the genes which were induced by CR in the long and short term CR group were genes involved with immune system activation. Without being limited to any specific mechanism, this result provides support for the theory that the immune system plays a central role in the rate and many of the pathologies of aging. Slightly more than 130 T-cell receptor, IgG, IgA, IgD, IgK, and IgM, genes were present in the high-low-high group. The average fold relative expression of these mRNAs in the long and short term CR groups was 1.24±0.86 and 1.23±0.25, verses 0.16±0.16 in the control group. Thus, CR increased immunoglobulin and T-cell receptor expression more then 10-fold. It is highly unlikely that this increase was due to an increase in the amount of blood in the CR livers. The level of globin mRNA found in these mRNA samples was actually reduced by about 20% in the long and short term CR groups. No statistically significant difference was found in the globin mRNA concentration in the blood of these animals.
Other changes in gene expression indicate that CR activates the immune system (Table 3). As can be seen in the table, both long and short term CR induced the expression of hemopoietic and lymphopoetic cytokines, hormones, signal transduction proteins, protein kinase modulators of the cell cycle and signal transduction, cell-surface receptors, and transcription factors. Not shown are a group of 20 immune cell specific genes known to be involved in endocytosis, cell adhesion, phagocytosis, potassium channels, lymphocyte activation, VDJ recombination, and immune cell activation which were strongly and significantly induced by CR (3- to 40-fold; P≦0.037). Together, these data evidence that CR enhances the activity of the immune system.
TABLE 3
Immune system genes activated by short- and long-term CR
LTCR*
STCR*
P
GENE
Hormones/Cytokines/Chemokines
4
4
0.003
Antigen, B cell receptor, L43567
53
55
<0.001
Calcium/calmodulin-dependent protein kinase IV (Camk4);
multifunctional serine-threonine protein kinase; T cells; X58995
>100
>100
<0.001
Chemokine (C—C) receptor 1 (Cmkbr1); growth inhibitory effects;
liver and spleen; U28404
13
17
<0.001
Chemokine (C—C) receptor 5 (Cmkbr5); induces mobilization of
intercellular calcium; beta-chemokine; leucocyte cheatoallractant;
liver, thymus, spleen, elsewhere: LT62976
>100
>100
0.003
Chemokine (C-X-C) receptor 4 (Cmkbr4); integral membrane G-
protein-coupled receptor; chemotaxis and calcium flux; directs
monocytes and lymphocytes to their target tissues; thymus, T cells,
and monocytes; ET62920
19
21
0.002
Colo9ny stimulating factor 1 (macrophage) (Caf1); receptor; liver;
X06368
10
8
0.016
Complement receptor 2 (Cr2); Late pre-B cells; M35684
3
2
0.015
Interferon beta type 1; growth factor; T helper cell differentiation
factor; antiviral; modulated immune response to foreign and self-
antigenes; immune system cells, others; V00755
11
10
<0.001
Interferon-related developmental regulator (Ifrd1); T cells; V00756
9
6
0.044
Interleukin 2 (Il2); stimulated proliferation of activated T
lymphocytes; M16762
>100
>100
0.015
Interleukin 2 receptor (Il2r); T cells; M26271
2
2
0.014
Interleukin 6 (Il6); promoter B cell maturation to tg-secreting cells;
activation of T cells; some helper T cells and macrophages; X54542
5
6
0.004
Interleukin 7 (Il7); growth factor, B cell progenitors; X07962
4
3
0.046
Killer cell lectin-like receptor, subfamily A, member 3 (Klra3); Ly-
49C; involved in graft rejections; subpopulation of natural killer cell;
U49866
>100
>100
0.034
Killer cell lectin-like receptor, subfamily A, member 6 (Klra6); Ly-
49F; NK cell surface antigen; determinant of IL-2-activated NK cell
proteins; NK cells, U10092
13
11
<0.001
Lymphocyte antigen 84 (Ly84); signal transduction protein 2; T
cells; D13695
5
6
0.007
Mast cell protease 7 (Mcpt7); released when mast cells are activated;
mast cells; ET61471
3
2
0.037
Myc box dependent interacting protein 1 (Bin1); endocytosis and
signal transduction; recycling synaptic vesicle components;
macrophages, neurons, endocrine cells; U86405
>100
>100
<0.001
Paired-Ig-like receptor A1 (Pira1); activates B lymphocytes,
dendritic and mycloid-linage cells; ET62839
5
4
0.027
Paired-Ig-like-receptor A6 (Pira6); appears to activate
immunoglobulin-related receptor; H lymphocytes, myeloid lineage
cells; ET62844
3
4
0.038
Preprosomatostatia (Stnst); regulates T cell IFN-gamma production;
macrophages, nervous system; X51468
>100
>100
<0.001
Protein tyrosine phosphatase, receptor type B (Ptpre);
transmembranal, receptor-like form and a cytoplasmic, non-receptor
form; hematopoietic tissues; ET61424
23
41
0.010
Proviral integration site (Pim2); serine/threonine kinase 2; cell
proliferation; mitogen stimulated; long-term potentiation in
hippocampus; immune and epithelial cells, CNS; L41495
Receptors/Signal Transduction Proteins
11
8
0.001
Small inducible cytokine subfamily, member 2 (Scyb2); small
inducible cytokine; macrophages; X5379H
8
8
0.002
Son of sevenless 1, homologue 1 (Drosophila) (Sos1); Ras-specific
exchange factor; T cells; Z11574
>100
>100
<0.001
Son of sevenless 2 homologue 2 (Drosophila) (Sos2); Ras-specific
exchange factor; T cells; Z11664
>100
>100
0.002
Spleen protein kinase (Syk); signal transduction; lymphopoietic and
haematopoietic cells, plateleta, anacrophages and neutrophils;
ET61263
>100
>100
0.048
Tbel; domains homologous to tre-2 oncogene and yeast mitosis
regulators BUB2 and cdc16; nuclear localization; B lymphocytes;
deadritic cells, myeloid-linage cells; U33005
2
2
0.044
Thrombin receptor; transmembrane G-protein-coupled receptor;
activated by serine protease cleavage; mitogen and apoptosis inducer
following vessel injury; plateleta, monocytes, endothelial cells,
neuronal and glial cells; U36757
>100
>100
0.002
Weel homologue (S. pombe) (Weel); inhibits entry into mitosis by
phosphorylatios of the Cdc2 kinase; lymphocytes; D30743
Transcription Factors
38
35
<0.001
Abelson nurine leukemia oncogene (Abl); nonreceptor tyrosine
kinase; role in cell progression, cell proliferation and
differentiation; liver, B cells, others; X07540
>100
>100
0.047
Homeo box A4 (Hoxa4); transcription factor; embryonic spinal cord
and adult testis; X13538
4
7
0.026
Homeo box B4 (Hoxb4); transcription factor; embryonic
development; haematopoiesis; NK cells; M36654
6
10
0.029
Homeo box B7 (Hoxb7); transcription factor; embryonic
development; haematopoiesis; developing embryo; blood, bone
marrow, natural killer cells; X06762
8
9
<0.001
Homeo box C6 (Hoxc6); transcription factor; embryogenesis;
haematopoiesis; lliver and many other tissues; X16510
40
36
0.001
Homeo box D1 (Hoxd1); transcription factor; neurogenesis;
developing CNS and forelimb bud; X60034
>100
>100
<0.001
Nuclear factor of activated T cells, cytoplasmic 2 (Nfatc2); T cell
transcription factor isoform B; T cells; U36575
5
5
0.001
SRY-box containing gene 4 (Sox4); Sox gene family transcription
factor; thymus, bone marrow, gonads; ET62444
2
2
0.012
Zinc finger protein 79 (Zfp79); Kruppel type zinc finger putative
transcriptional repressor; associates with RB in vitro; haematopoietic
cells, perhaps others; U29513
Primary Response Genes
>100
>100
0.005
Fos-like antigen-1 (Fosl1); spleenocytes; U34245
>100
>100
<0.001
Immunity associated protein, 38 kDa (Imap38); spleenocytes;
Y08026
>100
>100
<0.001
Immunorespossive gene 1 (Irg1); activated by bacterial LPS
treatment; macrophages; L38281
>100
>100
<0.001
Prostaglandin-endoperoxide synthase (Ptgs2); putative mediator of
inflammation; induced by growth factors and cytokines; monocytes
and fibroblasts; M88242
388
353
0.001
T-cell actue lymphocytic leukemia 2 (Ts12); putative basic helix-
loop-helix transcription factor activated in T-cell acute
lymphoblastic leukemia; T cells; M81077
>100
>100
<0.001
Tumor necrosis factor inducted protein 3 (Tnfip3); putative helix-
loop-helix transcription factor activated in T-cell acute
lymphoblastic leukemia; lymphocytes; U19463
Cell Adhesion/Membrane Components
>100
>100
0.002
ADP-ribosyltransferase 2s (Art2s); homologue of the rat T cell
differentiation marker RT6; cell-cell signaling; cytotoxic T
lymphocytes; X52991
9
9
0.013
Cadherin 9 (Cdh9); calcium-binding membrane glycoprotein; cell
adhesion molecule; thymocytes; U69136
6
5
0.015
CD22 antigen (Cd22); mediated B cell interactions with endothelial
cells; B cells; L16928
7
7
0.002
CD53 antigen (Cd53); pan-leukocyte antigen; cell membrane
glycoprotein; thymocytes; X97227
40
36
<0.001
Erythrocyte protein bond 7.2 (Epb7.2); involved in Na+/K+
permeability of cells; spleen, lung, testis; X91043
8
8
0.006
Integria alpha 4 (Iiga4); cell adhesion; lymphocytes; X53176
>100
>100
<0.001
Mannose receptor, C type 2 (Mrc2); cell adhesion; antigen
presentation; widespread tissue distribution, fetal liver, U56734
Immune Cell Function
38
44
<0.001
Cytochrome b-245, beta polypeptide (Cybb); gp91phox;
flavocytochrome mediating electron transfer from NADPH to
molecular oxygen in the respiratory burst oxidase; phagocytes;
U43384
8
8
<0.001
Cytotoxic T lymphocyte-associated protein 2 beta (Ctla2b);
homologue of cysteine protease proregion, T cells; X15592
>100
>100
<0.001
GraezyineG (Gzng); CTL serine protease 3; may play a role in
cytolytic lymphocyte activation; T lymphocytes; X14092
>100
>100
0.007
Helicase, lymphoid specific (Hells); replication, repair,
recombination and transcription; T and B cells; U25691
>100
>100
0.001
Mast cell protease 4 (Mcpt4); secretory granule serine protease;
peritoneal and most connective tissue mast cells; M55617
5
6
0.007
Mast cell protease 7 (Mcpt7); released when mast cells are activated;
mast cells; ET61471
8
8
0.005
Potassium voltage gated channel, shaker related subfamily, member
2 (Kena2); T cells, myelinating Schwann cells; M30440
3
3
0.003
Terminal deoxynucleotidyl transferase (Tdt); VDJ assembly;
recombination; earliest stage B and T cells; X04123
*Fold of control
Further support for this view was found in the liver specific genes which were strongly induced in expression by CR (Table 4). Long and short-term CR significantly enhanced the expression of the CD44 hyaluronan receptor gene, which has a role in lymphocyte homing and activation. Likewise, CR activated the mRNA abundance of the chemokine receptor 4, which is also involved in stimulating growth of pre-B cells; the mannose receptor, C type 2, which is involved in antigen presentation; colony stimulating factor 1, which is a macrophage growth factor; and proteaseome 3, which enhances the generation of class I binding peptides.
TABLE 4
Liver specific and ubiquitous genes
LTCR*
STCR*
P
GENE
Cytokines/Growth Factors
12
7
0.003
C-Fow induced growth factor (Fief); secreted growth factor;
mitogenic and morphogenic activity; endothelial cells of liver
during embryonic development; X99572
2
2
0.002
Fibroblast growth factor 2 (Fgf2); mitogen, differentiation and
survival factor, angiogenic factor; stimulates hepatocyte
>100
>100
0.001
Fibroblast growth factor 3 (Ffg3); liver epithelial cells; Y00648
3
3
0.012
Fibroblast growth factor 7 (Ffg7); liver epithelial cells; ET62118
>100
>100
0.001
Follistatis (Fst); binds and inactivates activia; control of the
inflammatory cascase; liver; Z29532
>100
>100
0.005
Inhibin beta B (Iabbb); transforming growth factor beta (TGF-
beta) superfamily member; liver and elsewhere; X69620
>100
>100
0.001
Inhibin beta E (Iabbe); transforming growth factor beta (TGF-
beta) superfamily member; liver and elsewhere; U96386
13
9
0.000
Interferon alpha gene family leukocyte (Iafa); inhibition of cell
proliferation; ubiquitous; M28587
3
2
0.015
Interferon beta type 1; growth factor; T helper cell differentiation
factor; antiviral; modulates immune responses to foreign and self-
antigens; ubiquitous; V00755
11
11
0.001
Interferon-beta (Ifnb); inhibitor of inflammations; liver and other
cells; J00424
13
13
<0.001
Neurotrophin 3 (Ntf3); secreted protein; binds high affinity
receptor trk C; may be involved in postestial development; liver
parenchymal cells, cerebellu, thymus, other; X53257
4
5
0.003
Preproendothelin 1 (Edn1); activates p38 MAP kinase and JNK;
portal vein contriction; hepatic stellate cells, liver and arterial
smooth muscle cells, others; U07982
10
15
0.003
Transforming growth factor beta 2 (Tgfb2); cell proliferation;
liver stellate cells; X57413
Cell Surface Receptors
>100
>100
0.020
Bradykinin receptor beta (Bdkrb); G-protein-coupled membrane
bouad; T-kininogen modulation during acute phase protein
synthesis; liver (ubiquitous); ET61559
2
2
0.017
CD44 antigen (Cd44); receptor for hyaluronan; cell surface
glycoprotein; hyaluronan clearance from the blood; lymphocyte
homing and activation; liver, CNS, other; U57612
>100
>100
<0.001
Chemokine (C—C) receptor 1 (Cmkbr1); mediates growth
inhibitory effects of the chemokine; liver and spleen; U28404
12
8
0.013
Chemokine (C-X-C) receptor 4 (Cmkar4); primary receptor
stromal cell-derived factor/pre-B growth stimulating factor; seven
transmembrane domain receptor; liver and bone marrow; X99581
>100
>100
<0.001
Fibroblast growth factor receptor 2 (Fgfr2); membrane;spanning
tyrosine kinase; activated by three members of the FGF family;
liver development; liver parenchymal cells and others; M86441
4
3
0.001
Leptin receptor (Lepr); transmembrane receptor; liver, lung,
muscle, brain, other; ET61693
4
3
0.027
Melanocortin 5 receptor (Mc5r); G-protein-coupled receptor,
stimulates adenylyl cyclase; widely expressed; X76295
3
4
0.029
Pancreatic polypeptide receptor 1 (Ppyr1); aeuropeptide Y;
peptide YY receptor; O-protein-coupled; liver; U40189
>100
>100
<0.001
Proteaseome 3 (Psme3); Ki antigen; cell proliferation; enchances
generation of class I binding peptides; liver, broad tissue
distribution; U60330
>100
>100
<0.001
Purinergic receptor P2X, ligand-gated ion channel 1 (P2rx1);
mediated Ca(2+) influx; liver, ubiquitous; X84896
64
68
0.001
Ryasodine receptor 2 (Ryr2); endoplasmic reticulon membrane
Ca2+ channels; controls cytosolic calcium levels; liver, cardiac
muscle, neurons, most excitable cells; X83933
>100
>100
0.003
Transferrin receptor (Trfr); cell surface glycoprotein; cell growth;
iron uptake; liver; X57349
Signal Transduction/Cell Cycle/Cell Growth
38
35
<0.001
Abelson murine leukemia oncogene (Abl); nonreceptor tyrosine
kinase; role in cell proliferation and differentiation; liver, B cells;
X07540
>100
>100
0.006
Cyclin-dependent kinase inhibitor 1B (P27) (Cdkn1b); cell cycle;
ubiquitous; U10440
35
40
0.003
Gusnine nucleotide binding protein, alpha inhibiting 1 (Gnail);
liver, cerebral cortex, others; U38501
>100
>100
0.013
Gusnine nucleotide binding protein beta 4 (Gab4); liver, brain,
blood cell; M63658
>100
>100
0.001
Histamine recepotr H1 (Hrb1); coupled to phosphoinositide
turnover-calcium mobilization signaling pathway; regulates IOF-1
expression and cell proliferation; regulates thyroxine transport
into hepatocytes; liver, brain, spleen (ubiquitous); D50095
>100
>100
0.002
Interferon-activated gene 204 (Ifi204); mediates antimicrobial,
immunomodulary and cell growth-regulatory activities of
interferons; nucleoli; M31419
4
4
0.004
Kinase interacting with leukemia-associated gene (Kis); cytosolic
phosphoprotein; integration of intracellular proliferation and
differentiation signaling; ubiquitous; X82320
9
8
0.004
MAD homologue 5 (Madh5); downstream component in the
TGF-beta family signaling cascase; liver development
angiogenesis; liver; ET62570
>100
>100
0.002
MAP kinase kinase kinase (Map3k1), serine-threonine kinase;
regulates sequential protein phosphorylation pathways involving
mitogen-activated protein kinase (MAPKs); ubiquitous;
ET61257
>100
>100
0.002
Mitogen activated protein kinase 1 (Mapk1); signal transduction;
cell proliferation, differentiation, and apopiosis; liver, ubiquitous;
U85608
>100
>100
0.004
NIMA-related expressed kinase (Nek1); ubiquitous; S45828
3
3
0.041
Neuroblastoma ras oncogene (Nras); key component of growth
signaling pathways; liver, wide tissue distribution; X13664
>100
>100
<0.001
Phosphatidylinositol 3-kinase regulatory subunit, polypeptide 1
(p85alpha) (Pik3r1); role in cell growth, differentiation, survival,
and vesicular transport; liver; ET61628
>100
>100
0.003
Phospholipase C, gamma 1 (Pleg1); produces second messengers
of signal transduction pathways related to cell proliferation;
ubiquitous; ET63005
>100
>100
<0.001
Proteasome 3 (Psme3); Ki antigen; cell proliferation; enchances
the generation of class I binding peptides by altering the cleavage
pattern of the proteosome; liver, neurons, broad tissue
distribution; U60330
3
2
0.002
Protein tyrosine phosphatase, non-receptor type 16 (Ptpn16);
growth factor-induced immediate early gene; dephosphorylates
MAP kinase; liver parenchyenal and vascular smooth muscle
cells, others; X61940
11
12
0.001
Ras-GTPase-activating protein SH3-domain binding protein 2
(G3bp2-pending); essential for Ras signaling; ubiquitous; U65313
2
2
0.001
Rhodopsin kinase (Rhok); small GTPase and serine/threonine
protein kinase; regulates actia cytoskeletal reorganization;
enhances secretion; ubiquitous except for brain and muscle;
U58513
15
14
0.016
Ros 1 proto-oncogene (Ros1); embryonic develoopment; tyrosine
kinase catalytic domains; expressed in neoplastic and fetal tissues;
neoplastic and fetal tissues; U15443
6
4
0.010
SUMO-1 activating enzyme subunit 1; conjugates SUMO-1 (a
small ubiquitin-like protein) to other proteins; modification of I
Kappy B alpha blocks NF kappa B-dependent transcriptional
activation; ubiquitous; AA162130
>100
>100
<0.001
Wingless related MMTV integration site 10b (Wat10b);
development regulation of cell growth and differentiation;
ET62229
Nuclear Receptors
19
17
0.016
Thyroid hormone receptor alpha (Thra); energy balance,
thermoregulation, substrate uptake; liver; X07751
10
9
0.003
Glucocorticoid receptor 1 (Gd1); energy balance; substrate
uptake; liver; X04435
45
42
<0.001
Nuclear receptor subfamily 2, group P member 1 (Nr2f1); COUP-
TF1; orphan steroid hormone receptor, transcription factor; liver,
X74134
>100
>100
0.010
Nuclear receptor subfamily 2, group F member 2 (Nr2(2);
apolipoprotein regulatory protein 1; member of the COUP-family
of steroid hormone orphan reception; liver, lung, kidney; X76653
Transcription Factors
4
3
0.016
Sine oculis-related homeobox 1 homologue (Drosophila) (Six1);
AREC3; expressed in many cell-types during development;
ET61028
9
7
0.003
cAMP responsive element binding protein 1 (Creb1); a mediator
of cAMP responsive transcriptional regulation; ubiquitous;
X67719
>100
>100
<0.001
Reticuloendotheliosis (Rel); c-rel; member of the ReVauclear
factor (NF)-kappa B family of transcriptional factors; ubiquitous;
X15842
>100
>100
<0.001
E4F transcription factor 1 (E4f1); DNA binding transcription
factor; ubiquitous; X76858
4
4
0.026
Forkhead box C2 (Foxc2); transcription factor; hepatocytes;
X74040
11
11
0.001
Homeo box A9 (Hoxa9); transcription factor; embryogenesis;
M28449
>100
>100
0.003
Homeo box msh-like 1 (Max1); transcription factor; early stage of
eye developmental regulation in embryo; embryogenesis; X59251
2
3
0.003
Inhibitor of DNA binding 4 (Idb4); domineer negative regulator
of bHLH transcription factors; myogenesis, neurogenesis D83 and
haematopoiesis; liver and elsewhere; X75018
>100
>100
0.010
Myogen factor 5 (Myf5); transcription factor, embryonic liver and
heart; X56182
6
8
0.003
Nuclear transcription factor-Y alpha (Nfye); CAAT-box DNA
binding protein subunit A; involved in activation of many hepatic
genes; ubiquitous; X55315
3
3
0.018
Paired box gene 2 (Pax2); Pax2 transcription factor; developing
embryo excretory and CNS; X55781
12
13
0.003
RE2-silencing transcription factor (Rest); transcription factor;
represses expression of neuronal genes; many noancuronal cells
and tissues; U13878
>100
>100
0.002
Sine oculia-related homeobox 1 homolog (Drosophila) (Six1);
homeobox; development of limb teadons; skeletal and smooth
muscle cells; X80339
>100
>100
0.005
SRY-box containing gene 12 (Sox12); transcription factor; Sox
family plays important role in development; developing embryos;
ET62446
2
3
0.032
T-box 4 (Tbx4); DNA binding domain putative transcription
factor; putative roll in inductive interactions during
embryogenesis; embryonic development; ET62078
>100
>100
0.009
Trans-acting transcription factor 1 (Sp1); transcription factor;
component of some hepatic glucose response elements,
ubiquitous; X60136
>100
>100
0.024
Transcription elongation factor A 1 (Tcea1); transcription
elongation factor; liver; D00925
14
12
<0.001
Yes-associated protein, 65 kDa (Yap); transcription activator,
ubiquitous; X80508
10
10
<0.001
Zinc finger protein 37 (Zfp37); putative transcription factor;
peroxisome proliferator responsive; liver; X89264
>100
>100
0.009
Zinc finger protein 61 (Zfp61); putative transcription factor, liver,
elsewhere; L28167
Translation/Splicing/Rna Processing Factors
7
7
0.001
Cytoplasmic polyadenylatice element binding protein (Cpeb);
RNA binding protein that promotes polyadenylation and
translational activation; ubiquitous; Y08260
4
4
0.011
Eukayotic translation initiation factor 1A (Eif1a); ubiquitous;
U28419
>100
>100
<0.001
Ribosomal protein L32, pseudogene (Rp132ps); ubiquitous;
X02060
>100
>100
0.000
Ribosomal protein L7 (Rp17); incorporated into 60 S subunit;
ubiquitous; X57960
18
13
0.001
Signal recognition particle 9 kDa (Srp9); synthesis and
translocation of membrane and secreted proteins into the
endoplasmic reticulum; ubiquitous; X78304
>100
>100
0.004
Splicing factor arginine/serine-rich 3 (Sfrs3); splicing factor
belonging to the highly conserved family of SR proteins;
regulation of constitutive and alternative splicing; ubiquitous;
X91656
Chromatin Structure
4
5
0.009
Chromobox homologue (Drosophila HP1beta) (Cbx); modifs
chromatin heritably activating or silencing genes; ubiquitous
during development; X56690
>100
>100
0.026
Histone H1 subtype e (Hle); chromatin structure; ubiquitous;
L04141
>100
>100
<0.001
Histone H1; chromatin structure; ubiquitous; J03482
109
70
<0.001
Histone H1b; chromatin structure; ubiquitous; ET62262
>100
>100
0.024
Histone H2A; chromatin structure; ubiquitous; X16495
4
3
0.030
Histone H2B; chromatin structure; ubiquitous; ET62908
7
8
0.006
Histone H3; 1-D (H3-D) and histone H4-D (H4-D); chromatin
structure; ubiquitous; U62672.
>100
>100
<0.001
Histone H3.2-F (H3-F), histone H2a.1-F (H2a-F), histone H2b-F
(H2b-F); chromatin structure; ubiquitous; U62669
4
4
0.034
HpaH tiny fragments locus 9c (Htf9c); structural similarity with
yeast mucleic acid-modifying enzymes; activated at the G1/S
transition, and S phase; down-regulated in growth arrested cells;
liver (ubiquitous); X56044
*Fold of control
The accumulation of genetic damage has been postulated to be a cause of aging. Without being limited to any specific mechanism, CR has been postulated to either reduce the rate of accumulation of genetic damage, or to enhance its rate of repair. Both long and short term CR enhanced the expression of numerous genes associated with DNA repair (Table 5). These genes included Xpa, which is involved in nucleotide excision DNA repair; and the Brca2 gene, which is important in DNA double-strand break repair and DNA damage-induced cell-cycle checkpoint activation.
A theory of aging closely related to the DNA damage theory proposes that the reduction of apoptosis with age, and its restoration with CR plays and important role in aging. This hypothesis purposes that the accumulation of damaged cells with age contributes to aging itself and to the onset of the diseases of aging. Long and short term CR greatly enhanced the expression of a number of genes which choreograph the progression of a cell through the apoptotic pathway (Table 5). These genes included Casp1, Casp3, Bax, and Bcl2 which code for key components of the apoptotic pathway.
TABLE 5
Genetic stability and apoptosis
LTCR*
STCR*
P
GENE
DNA Replication/Repair
9
8
<0.001
Antigenic determinant of rec-A protein (Kia); Kia17; DNA-
binding nuclear protein upregulated in response to UV and ionizing
radiation; accomulated in the nucleus of proliferating cells;
ubiquitious; X58472
>100
>100
0.001
Breast cancer 2 (brc32); DNA double-strand break repair and DNA
damage-induced cell-cycle checkpoint activation; ubiquitous;
ET62746
3
3
0.029
DNA primase p49 subunit (Prim); DNA replication; liver
(ubiquitdus); X74351
6
5
0.009
Mut L. homologue 1 (E. Coli(M1h1); treanscription-coupled
nucleotide excision repair; cell cycle checkpoint control;
ubiquitous; ET63479
3
3
0.025
Xeroderina pigmentosum complementation group A (Xpa);
nucleotide excisine DNA repair; ubiquitous; X7435
Apoptosis
>100
>100
0.001
B-cell leukemia/lymphoma 2 (Bcl2); suppresses apoptosis by
controlling mitochondrial membrane permeability; many cells and
tissues; L31532
>100
>100
<0.001
Bcl2-associated X protein (Bax); pro-apoptotic activity; can form
channels in lipid membranes; many cells and tissues; L22472
5
4
0.033
Caspase 1 (casp1); cysteiac protease mediator of apoptosis;
ubiquitous; U04269
2
3
0.000
Caspase 3 (Casp3); cysteine protease mediator of apoptosis;
ubiquitous; ET63241
3
4
0.005
Cyclin G (Ccng); augments apoptosis; target gene of P53; liver,
elsewhere; Z37110
>100
>100
<0.001
Fused toca (Fta); a gene related to ubiquitin-conjugating enzymes;
suggested role in apoptosis during development; expression
distribution poorly defined; X71978
22
21
<0.001
P53 specific ubiquitin ligase 2 (Mdm2); promotes ubiquitination
and proteaesome degradation of p53; inactivation by stress causes
cell cycle arrest and apoptosis; liver, elsewhere; X58876
>100
>100
<0.001
RNA-dependent EIF-2 alpha kinase; double-stranded RNA-
dependent protein kinase; key mediator of antiviral effects of
interferon; ubiquitous; ET61211
>100
>100
0.009
Tumor necrosis factor (Tnf); Proapoptotic factor in liver; X02611
*Fold of control
The liver is a highly innervated organ. This innervation includes elements of the enteric nervous system, as well as sympathetic innervation in the small arteries of the hepatic mesentery. This nervous innervation is essential to the activity of the liver. Nervous innervation has a role in the release of glucose by hepatocytes in response to insulin. As shown in Table 6, long and short term CR activated the expression of a large number of genes associated with the membrane receptor signaling, including membrane receptors for protein and small molecule neurotransmitters, and for cell growth and maintenance factors. CR induced the expression of genes for both phosphatases and kinases involved in signaling by these receptors. CR also induced the expression of four neuronal tissue specific transcription factors (Table 6).
CR enhanced the ability of liver neurons to transduce and respond to nervous system signaling. Eight genes for membrane channels were induced, including genes for sodium, potassium, and water channels (Table 6). Also induced were a number of integral membrane proteins such as proteolipid protein and cadherin 8, as well as the products of 5 genes for molecular motors which are probably involved in neural plasticity and remodeling. These proteins included 4 members of the dynein, axon, heavy chain family. Our results are consistent with the idea that CR increases the remodeling and activity of hepatic nerves after only 4 weeks.
TABLE 6
Neuromal Cell Specific Genes
LTCR*
STCR*
P
GENE
Signal Transduction
19
18
0.001
5-hydroxytryptamine (serotonin) receptor 1E beta (Htrieb); G-
protein-coupled receptor; CNS; Z14224
>100
>100
<0.001
Activia A receptor, type 1B (Acvt1b); limb development; embryo
brain, dorsal rool ganglin, spinal cord, vibrisae, elsewhere; Z31663
5
5
0.005
Ankynin 3 (Ank3); implicated in Na(+) channel clustering and
activity; neurosal axons, wide distribution; ET62740
3
3
0.022
Bone morphogenetic protein receptor, type 1B (Bmpr1b); activin
receptor-like kinase-6; serine-threonine kinase; CNS, muscle, blood
vessels, others; Z23143
5
6
0.004
Discs, large homologue 1 (Drosophila) (Digh1); role in localization
and function of glutamate receptors and K(+) channels; neurons,
epithelial cells; ET61665
67
70
0.001
Eph receptor A7 (Epo7); developmental kinase 1; member of
receptor tyrosine kinase family; brain, testes and spleen; X79082
>100
>100
0.001
Fibroblast growth factor 9 (Fgf9); autocrine/paracrine growth factor;
embryonic acural cell differentiation; adult and developing acuronal
cells, epithelial cells, others; U33535
14
15
<0.001
Fibroblast growth factor homologous factor 1 (Fgf1); nervous
system development and function; highest in brain and skeletal
muscle; U66201
17
19
0.003
G-protein-coupled receptor, family C, group 1, member H (Gprc1b);
glutamate receptor, metabotropic 8, CNS, glial cells, retina,
olfactory bulb, stellate/basket cells; U17152
28
29
<0.001
Gamma-aminobutyric acid (GABA-A) receptor, subunit beta 3
(Gabrb3); links binding of GABA to inhibitory chloride flux; CNS;
U14420
12
11
<0.001
Glutamic receptor, iosotropic, kainate 1 (Grik1); CNS; X66118
>100
>100
0.007
Gosadotropia releasing hormone recepotr (Garbr); G-protein-
coupled receptor; activates MAPK cascases; brain, anterior pituitary,
reproductive organs; L28756
4
3
0.018
H6 homeo box 2 (hmx2); specification of neuronal cells; developing
CNS; S80989
>100
>100
0.001
Histamine receptor H1 (Hrb1); coupled to phosphoisositide
turnover-calcium mobilization signaling; regulates IGF-I expression,
cell proliferation, several function; neurons, liver, elsewhere; D50095
64
73
<0.001
Neuropeptide Y receptor Y6 (Npy6r); regulates energy balance
through its oranigenic, antithermogenic, and insulin secretagogue
actions, neurons, vascular smooth muscle cells; U58367
>100
>100
<0.001
Paired-Ig-like receptor A1 (Pira1); activating receptor on B
lymphocytes, deadritic and myeloid-linage cells; ET62839
4
4
0.003
Preproglucagon (Ocg); glucagon-like peptides I and II;
neuropeptide; CNS, pancreatic alpha cells, ileum, Z46845
>100
>100
0.013
Protein kinase, cGMP-dependent, type II (Prkg2); signal
transductions; brain, kidney, small intestine, colon; L12460
>100
>100
0.001
Protein tyrosine phosphatase, receptor type, M (Ptprm); expressed in
capillaries in developing neural tissue, lung; X58287
>100
>100
<0.001
Reluxin precursor (Rln); insulin gene family; remodeling of
collagen; brain, uterus, prostate, pancrease and kidney; Z27088
>100
>100
<0.001
Ryanodine receptor 3 (Ryr3); intracellular Ca2+ channels; neurons,
skeletal and smooth muscle; ET61090
Neuronal Tissue Specific Transcription Factors
>100
>100
<0.001
Atonal homologue 5 (Drosophila) (Aloh 5); neurogeain 3;
transcription factor; neuroD-related bHLH protein; CNS; U76208
19
18
0.003
Embigin (Emb); DNA-binding transcription factor; class Vt POU
domain; CNS; D13801
>100
>100
0.026
Paired box gene 6 (Pax6); transcription factor; development of CNS,
eye; X63963
>100
>100
<0.001
Zinc finger protein 2 (Zfp2); Mkr-2; differentiation and/or
maintenance of neurons; central and peripheral neurons; Y00850
Channels
4
3
0.007
Aquaporia 4 (Aqp4); allows water and small solutes through plasma
membrane; brain and other tissues; U48397
5
6
0.004
Discs, large homologue 1 (Drosophila) (Dlgh1); localization and
function of glutamate receptors and K(+) channels; neural sysapacs;
ET61665
22
25
0.001
Gap junction membrane channel protein beta 6 (Gjb6); connexin 30;
forms transmembranous gap junction channels between adjacent
cells; brain, skin; ET63385
11
11
0.001
K+ channel beta-subunit; ion channel; brain and kidney; X97281
14
16
0.001
Potassium inwardly-rectifying channel, subfamily J, member 6
(Kcnj6); neurons; ET61642
8
8
0.005
Potassium, voltage gated channel, shaker related subfamily, member
2 (Kena2); T cells, myelinating Schwann cells; M30440
27
28
<0.001
Sodium channel 27; brain; L22340
11
11
<0.001
Sodium channel, type X, alpha polypeptide (Scn10a); brain
unmyelinated axons; Y09108
Molecular Motors
2
2
0.004
Dilute lethal-20J; Class-V myosin; vesicular membrane trafficking;
transport of endoplasmic reticulum vesicles in neurons; M33467
7
8
0.001
Dynein, axon, heavy chain 1 (Dashe1)k dyneins are molecular
motors that drive the beating of cilis and flagella; brain, trachea,
testis; ET63395
>100
>100
<0.001
Dynein, axon, heavy chain 3 (Dnahc3); brain, trachea, testis;
ET63399
5
6
0.013
Dynein, axon, heavy chain 6 (Dnahc6); brain, trachea, testis;
ET63402
4
5
0.002
Dynein, axon, heavy chain 9 (Dnahc9); brain, trachea, testis;
ET63405
Cell Surface and Secreted Proteins
>100
>100
0.001
Cadherin 9 (Cdh8); adhesion molecule; subdivisions of the early
CNS and thymus; ET63017
37
36
<0.001
Glutamic acid decarboxylase, 67 kD; responsible for gamma-
aminobutyric acid synthesis; brain, islets; Y12257
2
2
0.011
Glypius 4 (Gpc4); cell surface heparis sulfate proteoglycan; role in
regulation of neural cell transition from proliferation to
differentiation; neurons; X83577
19
20
<0.001
Neurexophilin 2 (Nxph2); neuronal glycoprotein; binds to alpha-
neurexine; brain; U56650
13
13
<0.001
Neurotrophin 3 (Ntf3); secreted protein; resistenance and plasticity
of neurons; enteric neurons, others; X53257
43
41
0.001
Proteolipid protein (Plp), main integral protein of myelin; CNS;
X07215
4
4
0.043
Sema domain, immunglobulin domain (lg), short basic domain,
secreted, (serinaphonin) 3E (Sema3e); glycoprotein involved in
embryonic development; developing neural tubes, lungs, skeletal
elements; ET63410
>100
>100
<0.001
Sema domain, seven thrombospondin repeats (type 1 and type 1-
like) (Sema5a); axonal guidance; early embryogenesis; X97817
Other Genes
6
7
0.015
Disabled homolog 1 (Drosophila) (Dah1); adaptor molecule in
neural development; neuronal and hematopoietic cells; ET63156
23
24
<0.001
Galanin (Gal); neuropeptide; enhances hepatic glucose production:
hepatic nerves and elsewhere; L38580
3
4
0.006
Netrin 1 (Nta1); axon outgrowth-promoting protein; guidance
molecule; guides growing axons in development; CNS; U65418
127
129
<0.001
Nucleosome assembly protein 1-like 2 (Nap12); Bpx; brain; X92352
>100
>100
<0.001
Proteasecome 3 (Ptne3); Ki antigen; cell proliferation; enhances
generation of class I binding peptides; liver, neurons, elsewhere;
U60330
58
58
<0.001
UDP-glucoronosyltransferase 8 (Ugt8); cerebroside and sulfatide
biosynthesis; CNS and peripheral nervous system; X92122
*Fold of control
Of the approximately 200 genes reported to be expressed either liver specifically or ubiquitously, 13 code for cytokines or growth factors; 12 for cell surface receptors; 21 for signal transduction, cell cycle or cell growth related proteins; 4 for nuclear receptors, 20 for transcription factors; 6 for translation, splicing, or RNA processing related factors; and 9 for chromatin structure related genes (Table 4). The overall pattern of genes induced in this group of genes suggests that CR stimulates the growth, remodeling and responsiveness of liver cells to signaling systems. These results are consistent with those found for neuronal genes, discussed above.
Both long and short term CR induced the expression of the cell growth factors Tgfb2, Fgf1, Fgf2, Fgf3, Fgf7, Fgf9, Figf, Inhbb, Inhbe, and 3 interferon-related genes. Likewise, a large number of genes coding for cell cycle regulation were induced by CR. These genes included Ptpn16, Nck1, Plcg1, Map3k1, Mapk1, Madb5, Wnt10b , Ab1, and others. Without being limited to any specific mechanism, the hypothesis that CR induces cell remodeling and growth of liver cells is further supported by the observation that both long and short term CR very strongly induced the expression of 7 histone genes. In 6 cases, these mRNA levels were induced from undetectable, or nearly undetectable levels. Two other genes which appear to be associated with chromatin structural modification were also strongly induced by CR (Htf9c and homologous to Drosphila Hp1; Table 4). Further evidence that CR enhance cell division and remodeling is the up regulation of the mRNA for the transferrin receptor, which mediates cellular iron uptake, a process essential for cell growth and division.
Three receptor mRNAs associated with energy balance were induced by CR. Two of these were for neuropeptide Y receptor Y6 (Table 6) and pancreatic polypeptide receptor 1, and one was for the leptin receptor (Table 4).
We have tested the hypotheses that CR produces similar effects on gene expression early and late in life by examining the effects of aging and caloric intake on the expression of approximately 12,000 genes and ESTs in the liver of old (27-month-old) and young (7-month-old), control and CR mice, using GeneChip oligonucleotide based high-density microarrays. We found that CR produced a massive reprogramming of gene expression early and late in life. The patterns of expression induced by CR in young and old mice were highly homologous. Comparison of gene expression in the groups of mice indicated that CR only prevented age-related changes in the expression of a few genes. Examination of the genes involved does not support the idea that they have a principle role in the age-retarding effects of CR. Together, the results do not support the idea that CR acts principally to prevent deleterious age-related changes in gene expression. Instead, CR induces a highly-homologous, major reprogramming of gene expression in animals of all ages.
The average global hepatic gene expression profile for each group of mice, displayed using GeneSpring 3.0 (Silicon Genetics, San Carlos, Calif), is shown in FIG. 8. The GeneSpring experiment tree algorithm clustered gene expression in the young and old CR mice together, and separately clustered expression in the young and old control mice together. These results indicate that that the effects of the CR diet on gene expression was significantly greater than the effect of age. Further, these data indicate that CR produced homologous effects on gene expression in the young and old mice.
TABLE 7
Pairwise comparisons of the global gene expression
correlation coefficients for each possible pair of mice.
Young-
Old-CR
Old-Control
Young-CR
Control
Old-CR
0.53 ± 0.02*
−0.09 ± 0.02
0.41 ± 0.04
−0.10 ± 0.03
Old-Control
0.28 ± 0.06
−0.11 ± 0.03
0.23 ± 0.02
Young-CR
0.41 ± 0.01
−0.06 ± 0.02
Young-
0.22 ± 0.02
Control
*All values average values, ± SD are calculated as the Log (1+ the mRNA level)
These conclusions are supported by comparison of the correlation coefficients calculated from the expression data for each possible pair of mice in the study (Table 7). Because the mice were genetically identical, infra-group values provide a measure of the maximum correlations attainable. Inter-group values measure the similarity between groups. Inter-group comparisons between young and old CR and control mice indicated that gene expression in all CR mice was highly homologous, regardless of the age of the animals. Likewise, regardless of age, the intra-group expression patterns of the control mice were highly homologous. In contrast, there was no intra-group correlation between mice in different dietary groups, regardless of age. These data indicate that the number of calories consumed, but not age was the major influence in determining the global patterns of gene expression in these mice. This novel result is fuirther supported by the analysis described below.
The patterns of gene expression in the mice were further evaluated by successive application of the Venn Diagram Function of GeneSpring 3.0, one-way ANOVA, and Fisher's test (P<0.05) to the levels of expression of each gene and expressed sequence tag (EST) in the 4 groups of mice. These operations sorted the genes and ESTs into one of 9 possible categories (Tables 8A and B). Only statistically significant differences of 2-fold or more are shown. The expression of most genes and ESTs were not affected by either CR (−80% unchanged) or aging (95% unchanged). Of the genes and ESTs which did changed expression among the groups, 5-times as many genes and ESTs changed expression level in response to CR (2456) as changed in response to age (561). Of the genes and ESTs responsive to CR, most (40%) were upregulated in both young and old mice. Two other groups of genes and ESTs were upregulated either in old mice only (28% of the genes that changed expression), or in young mice only (19% of the genes that changed expression). An even smaller number of genes and ESTs were down regulated by the CR diet in young or old mice (13% of the genes that changed expression).
TABLE 8
The effects of age and diet on gene expression
a. Diet Effect
Young
Old (CR/Control)*
(CR/Control)*
Up**
Unchanged
Down**
Total
Up**
975 (8.1%**)
473 (3.9%)
0
1448
Unchanged
685 (5.7%)
9587
172 (1.4%)
(79.6%)
Down**
0
105 (0.9%)
46 (0.4%)
151
Total
1660
218
b. Age Effect
Control
CR (Old/Young)*
(Old/Young)*
Up**
Unchanged
Down**
Total
Up**
6 (0.05%***)
136
2 (0%)
144
(1.1%)
Unchanged
186 (1.5%)
11482 (95%)
112 (0.9%)
Down**
1 (0%)
113
6 (0.4%)
119
(0.9%)
Total
193
119
Three novel conclusions can be drawn from these data. First, CR induced a substantial age-independent reprogramming of gene expression. A large number of genes and ESTs (975) were up regulated by CR in both young and old mice (Table 8A). In this group, 208 were known genes (See Appendix G) All of these known genes were among the group of 340 genes induced in 30 month old mice by both long-term CR (LT-CR; life-long) and short-term CR (ST-CR; only 4 weeks of CR). This highly reproducible, age-independent, responsiveness to CR suggests to us that these genes and ESTs are likely to mediate the life- and health-span extending effects of CR. At a minimum, the dietary responsiveness of these genes can be used as a gauge of the effectiveness of other treatments in reproducing the effects of CR on global patterns of gene expression. Further, because 90% of the genes and ESTs induced by lifelong CR (which includes the age-independent and age-dependent genes and ESTs) can be induced after only 4 weeks of CR, the vast majority of the genetic reprogramming induced by CR can be reproduced rapidly.
There is a second novel conclusion which can be drawn from the results in Table 8A . CR produced some “age-dependent” reprogramming of gene expression in both young and old mice. Of the 473 genes and ESTs induced by CR only in young mice, 142 are known genes (Appendix H) These results indicate that this subset of genes was also CR responsive in old mice, but not to sufficient levels that they were distinguished statistically from control expression levels in these studies. Thus, Table 8A overestimates the number of young-specific induced genes by approximately 25%. Of the young-specific genes, 8% are involved in transcriptional regulation; 5% are growth factors, cytokines or hormones; 18% are involved in signal transduction or cell cycle regulation; 14% are involved in embryogenesis and development; 14% are involved in cellular adhesion, or are components of the extracellular matrix or membrane; 7% are channels or ion pumps; 3% are involved in extracellular transport or secretion; 3% are involved in metabolism; 3% in DNA replication, repair or apoptosis; 3% in chromatin structure; 9% in immune function or in the primary response; and 15% are involved in other functions.
Or the 685 genes and ESTs induced by CR in old mice, the identity of 200 are known (Table 8A); (Appendix I). Of these, 122 (61%) previously were shown to be induced by ST-CR in old mice. Thus, the majority are rapidly responsive to CR. Of the remaining 78 genes, approximately 12% are transcriptional regulators; 8% are growth factor, cytokines or hormones; 13% are involved in signal transduction or cell cycle regulation; 11% are involved in embryogenesis and development; 10% are involved in cellular adhesion, or are components of the extracellular matrix or membrane; 4% are channels or ion pumps; 4% are involved in extracellular transport or secretion; 3% are involved in metabolism; 3% in DNA replication, repair or apoptosis; 2% in chromatin structure; 3% in immune function or in the primary response; 2% in translation, splicing or RNA processing; 2% are cell surface receptors; and 23% are involved in other functions.
The proportion of genes involved in each functional category above are remarkably similar. Further, many of the genes induced by CR in young mice were members of similar gene families or were structurally or functionally related to genes induced only in old mice. These similarities suggest that CR has highly homologous age-specific effects. It is less likely that the relative proportion of genes falling into each category, and the identity of these genes is an artifact of the probes present on the chip. Firstly, all of the results are statistically significant. Second, the genomic profiles produced in several drug studies were strikingly different from those found here as to the identity of the genes affected, and their functional categories (data not shown). Together, these results indicate that CR has a robust, pervasive, and highly homologous effect in both young and old mice. It induced the expression of a substantial group of genes involved in a wide variety of cellular functions.
A commonly expressed view in the literature of CR and aging assumes tacitly or explicitly that CR acts by preventing deleterious, age-related changes in gene expression. This view is shown schematically in FIG. 9. This hypothesis assumes that prevention of age related changes in gene expression underlies the health- and life-span extending effects of CR. During aging, some genes become over expressed or under-expressed relative to their levels in young animals (lower and upper lines, FIG. 9). Some of these deviations are assumed to be deleterious. Preferably, no changes would change with time, and aging would either not occur or occur more slowly (center line, FIG. 9). In this view, CR should wholly or partially return over- or under-expressed genes to their youthful levels (arrows, FIG. 9). Although the reasoning is circular, some have said that if CR changes the expression of a gene toward the center line in the figure, it restored youthful levels of expression. We have analyzed the results of the studies reported here to evaluate this hypothesis further.
Of the approximately 12,000 genes and ESTs examined, aging of control mice increased the expression of 257 genes and ESTs, and decreased expression of 191 genes and ESTs (FIG. 9). Long-term CR wholly or partially, reversed or prevented 55 of the increases and 70 of the decreases. Short-term CR reversed 45 of the increases and 59 of the decreases in gene expression. Long-term and short-term CR both acted to reverse or prevent 23 of the increases and 41 of the decreases. Thus, long-term CR actually prevented the increased expression of only 32 genes and ESTs and the decreased expression of only 29 genes and ESTs. It is likely that the number of ESTs in each class overestimates the number of authentic genes in each category. First, the genes and ESTs which responded to CR in only 4 weeks are likely a subset of the genes and ESTs which respond acutely to CR. We have not yet examined longer times on the domain of genes responsive to acute CR. Some genes may be “slow changers” in response to acute CR. Second, we have found that many of the known genes present on these chips are redundant (e.g., multiple immunoglobulin genes of each class and T cell receptor genes, cloned chromosome break-points representing parts of two genes, uncharacterized chromosome regions, uninvestigated, unpublished cDNA sequences, etc.). For example, of the 23 genes and ESTs reduced to baseline expression levels only by LT-CR, 12 were known genes (Table 9). Of the 27 genes and ESTs which were decreased in expression by age and returned to baseline expression only by LT-CR, only 13 were from known genes (Table 10).
Of the 12 genes prevented from increasing with age by CR, few are involved in signal transduction. Rather, 6 are involved in immune system function, particularly in macrophage differentiation, proliferation, apoptosis, and activity. Of these, platelet-activating factor acetylhydrolase activity reduces plasma platelet activating factor mRNA levels. Platelet activating factor is a potent pro-inflammatory autacoid with diverse physiological and pathological actions. It does not seem likely that the return of these genes to baseline expression levels is due to a general reduction in inflammation, stress, or immune activity. In a previous study, we found that 61 immune system genes, including 6 primary response genes, and an additional 9 apoptotic genes were up regulated by both LT- and ST-CR in the liver of mice. Similar considerations apply to the other 6 genes in this group, and to the genes prevented from decreasing with age (Table 10). One can speculate about why reduction in the expression of the relatively few immune system specific, acute phase response genes and other genes listed in Table 9, or enhanced expression of the 13 immune system, and neuron or liver specific genes in Table 10 might be important in reducing the rate of aging. However, with few exceptions, very similar genes, and in some cases closely related family members of the genes in these lists are present in the group of 340 known genes induced by both LT- and ST-CR. Thus, it seems intuitively and statistically much more likely that the massive reprogramming of gene expression induced by CR (Tables 9 and 10) is responsible for the increase in life- and health-span induced by CR. The genes prevented from increasing and decreasing with age (Tables 9 and 10) seem much more likely to be the result, rather than the cause of these effects.
In summary, the studies presented here show that a major effect of CR is to massively (more than 10% of the genes and ESTs investigated) reprogram gene expression to a new pattern associated with slower aging and delayed onset of age-related diseases. This reprogramming includes age-independent induction of a relatively large group of genes and ESTs, as well as induction of smaller groups of genes age-dependently. Further, we found that age-related changes in gene expression are relatively rare. Even rarer are instances in which life-long CR prevents these changes. The rarity of such genes, and their identity suggest to as that they do not play a major role in the physiological effects of CR. The large and rapid response induced by CR on total liver gene expression suggests that major, systemic regulators of gene expression are altered by CR. Study of the regulation of a number of these genes should yield the identity of the regulators, and reveal how they are influenced by CR.
TABLE 9
mRNAs increased by age and returned to control levels by LT-CB
GenBank
Phenotype
Immune System
AF018268
Apoptosis inhibitory 6 (Api6); a member of macrophage scavenger receptor cysteine-
rich domain superfamily; inhibits apoptosis of a variety of cell types; secreted
specifically by macrophages
M13018
Cysteine rich intestinal protein (Crip); double zinc finger protein; expression changes
with acute liver injury (cellular change); may function in cell proliferation,
differentiation or turnover; high expression in immune cells, low in liver
J04596
GRO1 oncogene (Gro1); encodes a cytokine; mediator of inflammatory and immune
responses; also called melanoma growth-stimulatory activity; cell cycle regulator;
platelets
L20315
Macrophage expressed gene 1 (Mpeg1 or Mpg-1); increased when murine fetal liver
hematopoietic progenitor cells induced to differentiate into macrophages; high levels
in macrophages, moderate levels in certain myelomonocytic cell lines
U34277
Phospholipase A2 group VII, platelet-activating factor acetylhydrolase, plasma
(Pln2g7); secreted phopholipase A1 which modifies the pre-inflammatory platelet-
activating factor (PAF) to yield the biologically inactive lyo-PAF; regulates baseline
circulating PAF levels and may be critical in resolving inflammation; high PAF is a
predictor of heart disease; liver macrophages
L27990
Sjogren syndrome antigen A1 (Seal); Ho52; stress response gene; ribonucleoprotein;
macrophages
Ubiquitous
D86729
Heterogeneous nuclear ribonucleoprotein A1 (Hnrpa1); ribonucleoprotein, RNA
processing; early down-regulation of this gene contributes to the cytotoxicity of the
topoisomerase inhibitors that induce DNA cleavage; ubiquitous
U50850
Retinoblastoma-like 2 (Rbl2); p130; transcriptional cell cycle repression through G1
phase (controls cyclia A, cdc 25G and cdc2 genes); tumor suppressor gene; expressed
independently of retinoblastoma gene; expressed in embryo and ubiquitously in adult
U34042
Tolloid-like (Tl1), an alternatively spliced product of the bone morphogenic protein-1
gene; metalloprotease purified from extracts capable of inducing ectopic bone
formation; ubiquitous
Liver Specific
U60438
Serum amyloid A protein isoform 2 (Saa2); encodes an acute-phase reactant serum
protein; liver
Not Reported in Liver
M27501
Protamine 2 (Prm2); compacting chromatin; expressed in posimiotic male germ cells
during late stages of spermatogenesis
U52433
Tubby (Tub); mutation is the tub gene causes maturity-onset obesity; adipocyte fat
storage increased by 5-6 fold, insulin resistance; mutant mice have retinal and
cochlear degeneration; gene function unknown; brain, hypothalamus, cochlea, retina
TABLE 10
mRNAs decreased by age and returned to control levels by LT-CB
GenBank
Phenotype
Immune System
M30903
B lymphocyte kinase (Blk); sac-family protein tyrosine kinase; plays important role in
B-cell development/activities and immune responses; B-lineage cells
U43384
Cytochrome b-245, beta polypeptide (Cybb, cytochrome b558); integral component of
the microbicidal oxidase electron transport chain of phagocytic cells, respiratory burst
oxidase; phagocytes
U10871
Mitogen activated protein kinase 14 (Mapk14); signal transduction, stimulate
phosphorytation of transcription factors; major upstream activator of MAPKAP kinas
2; hematopoietic stem cells
Z22649
Myeloproliferative leukemia virus oncogene (Mp1); Member of hematopoietic
cytokine receptor family, cell cycle regulator, induces proliferation and differentiation
of hematopoietic cell lines; hematopoietic precursor cells, platelets
and megakaryocytes
Y07521
Potassium voltage gated channel, Show-related subfamily member 1 (Kene1)
potassium channels with properties of delayed rectifiers; nervous system, skeletal
system, T lymphocytes
U87456
Flavin-containing monooxygenase 1 (Fmo1); xenobiotic metabolism; highly expressed
in liver, lung, kidney, lower expressed in heart, spleen, testis, brain
U40189
Pancreatic polypeptide receptor 1 (Ppyr1), neuropeptide Y receptor, peptide Y
receptor; G-protein-coupled receptor; liver, gastrointestinal tract, prostate, aeurosa
endocrine cells
Neuron Specific
U16297
Cytochrome b-561 (Cyb561); electron transfer protein unique to aeuroendocrine
secretory vesicles; vectoral transmembrane electron transport; brain
D50032
Trans-golgi network protein 2 (Tiga2); integral membrane protein localized to the
Trans-Golgi network; involved in the budding of exocytic transport vesicles; brain
neurons
Liver Specific/Ubiquitous
D82019
Basigin (Bag), CD147, neurothelin; membrane glycoprotein, immunoglobulin
superfamily, homology to MIICs, acts as an adhesion molecule or a receptor, neural
network formation and tumor progression; embryo, liver and other organs
U38990
Glucokinase (Gk), key glycolytic enzyme; liver
U50631
Heat-responsive protein 12 (Hrp12); heat-responsive, phosphorylated protein
sequence simularity to Hbp20; liver, kidney
U39818
Tuberous sclerosis 2 (Tsc2); mutationally inactivated in some families with tuberous
sclerosis; encodes a large, membrane-associated GTPase activating protein (GAP
tuberlin); may have a key role in the regulation of cellular growth; ubiquitous
Streptozotocin (STZ) induces diabetes. Mice receiving three treatments with STZ were diabetic for about 4 weeks. Diabetes reduces insulin levels to almost zero. CR has a similar effect in that it lowers insulin levels, although not as low as in STZ-treated animals. Also, while CR lengthens life span, STZ has the opposite effect and shortens life span.
Aminoguanidine is believed to retard aging by preventing cross-linking of protein initiated by the aldehyde form of glucose. However, mice fed aminoguanidine exhibited little or no effect on life span. However, a large effect on gene expression was observed (FIG. 12). Gene expression for aminoguanidine-treated mice did not correlate with either old CR or old control. A visual representation of this finding is shown in FIG. 13. In conclusion, although aminoguanidine has little effect on aging in mice, major differences in gene expression are observed. These effects are not like those of CR, and this is consistent with the absence of a strong effect on the life-span of mice.
To determine whether certain interventions mimic calorie restriction in mice, the following groups of mice are prepared.
Group 1: Controls
Group 2: Troglitazone (synthetic proposed calorie restriction mimetic drug that lowers insulin levels in rats and mice, lowers blood pressure and triglycerides, inhibits free radicals, increases mitochondrial mass, and doesn't seem to change food intake in rodents): treatment starts at 10 months
Group 3: IGF-1 (natural proposed calorie restriction mimetic hormone that lowers both insulin and glucose levels and which may be directly involved in the basic mechanisms of aging; has rejuvenating effects on immune, muscular, and other systems): treatment starts at 12 months
Group 4: ALT-711 (or other AGE breaking agent: proposed calorie restriction mimetic that acts by reversing the effects of elevated glucose levels as they occur or after they occur, rather than by reducing glucose levels): treatment starts at 18 months.
Animals in all groups will receive the same, known amount of food throughout the study.
Troglitazone and IGF-1 doses will be chosen to set glucose and insulin levels in the range for young or preferably calorie-restricted animals. Glucose and insulin will be measured but not controlled in the control and ALT-711 groups. Troglitazone will be supplied at a dose of ˜0.2% of the diet (standard for troglitazone studies for other purposes). Similarly, ALT-711 will be incorporated into the diet. A low (two-toxic) level of ALT-711 is used that will remain constant over time.
It is assumed that IGF-1 will be supplied by injection (3 times per week, minimum) unless a continuous delivery method can be arranged. The preferred dosage method is implantation of non-dividing IGF-1-secreting cells, to attain steady IGF-1 levels, and if possible, this will be done. If this is not possible, IGF-1 will be obtained as a gift from Genentech or another manufacturer. Other possible alternatives to injection are: osmotic minipump; injection of IGF-1 into subcutaneous slow-release reservoirs; infusion by means of minipumps used by Celtrix; use of skin patches that allow slow-release to the body.
There will be 60 animals in each longevity-testing group (LTG). Each LTG will be accompanied by another set of, on average, 40 similarly-treated animals, which will be set aside for sacrifice to permit biochemical assays and histological documentation of the condition of the animals at fixed ages (sacrifice group, SG). In the case of the IGF-1 and troglitazone groups, some animals will be earmarked for pilot dose-finding experiments in a manner that will allow the average SG size to remain at 40, as described below. The groups earmarked for dose-verification will be referred to as the pilot dose groups, or PDGs.
For troglitazone, about a 2-month supply of each of three troglitazone diets (containing 0.1%, 0.2%, or 0.3% troglitazone) will be initially ordered. The main 0.2% troglitazone dose will be tested on a small pilot mouse population before committing the troglitazone group proper to this dose. If 0.2% troglitazone is not found to yield the expected changes in circulating insulin after 2 weeks on the 0.2% troglitazone, the diet will be changed to the more appropriate dose diet at that time and verified on a second small pilot mouse population.
Similarly, some animals will be used for IGP-1 injection pilot experiments to determine the proper starting dose.
At age 12 months: Sacrifice 3 animals/SG to obtain common baseline group of 12 animals to be compared to all subsequent results. This is the middle-aged universal control group. All subsequent data can be compared to the results for this pooled group.
At age 12.5 months: Begin the IGF-1 PDG with 7 mice given the best estimated dose of IGF-1. Sacrifice two weeks later for determination of insulin and glucose levels. Begin a verification/second trial dose of IGF-1 at 13 months, 1 week of ago, and sacrifice this second PDG at 13 months, 3 weeks of age. Assuming the assays for insulin and glucose can be completed in 1 week, this regimen will allow the final dose for the LTG to be determined prior to age 14 months. Similarly, at 12.5 months, place 7 mice on the 0.2% troglitazone diet. Two weeks later, sacrifice and assay for insulin and glucose. Begin adjusted-dose or verification dose group at 13 months, 1 week and sacrifice after two weeks.
At age 14 months: Begin troglitazone and IGF-1 at the experimentally-determined or estimated optimal doses for each.
At age 15 months: Sacrifice six animals from the IGF-1 and troglitazone SGs for determinations of glucose, insulin, and all other endpoints involved in the study. If necessary, adjust the IGF-1 dose again (both in the LTG and the untapped portion of the IGF-1 SG) and/or order diet with a modified troglitazone content. Sacrifice three animals each from the SGs for the controls and the ALT-11 groups and pool to create a common group of six animals for comparison to the IGF-1 and troglitazone groups.
At age 18 months: same as at 15 months, but use 7 mice/SG for IGF-1 and troglitazone and 4 mice/SG for the control and for the ALT-711 group. Begin the ALT-711 groups on ALT-711 immediately after this sampling.
At around 27 months (˜24-30 months): Sample all remaining surviving SG mice.
If the total initial numbers of mice in the sacrifice groups for treatments 1, 2, 3, and 4 are 30, 50, 50, and 30, respectively, then if there were no mortality in any of these groups, there would be 20 animals left in each SG at the time of final sampling. But if we assume that only ⅓ of this number will be alive, then about 7 animals will remain to be sampled at the final sample time, or about the minimum required for statistical significance. It the mean survival rate at 27 month is over 73%, the 27 month end point may be postponed to a greater age.
In addition to other biochemical markers, assays may include:
Spindler, Stephen R., Dhahbi, Joseph M.
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