| PATENT NUMBER | This data is not available for free |
| PATENT GRANT DATE | June 18, 2002 |
| PATENT TITLE |
Interventions to mimic the effects of calorie restriction |
| PATENT ABSTRACT |
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. |
| PATENT INVENTORS | This data is not available for free |
| PATENT ASSIGNEE | This data is not available for free |
| PATENT FILE DATE | August 25, 2000 |
| PATENT REFERENCES CITED |
Lee et al. Science, vol. 285, Aug. 1999, pp. 1390-1393.* Lee et al., Gene Expression Profile of Aging and Its Retardation by Caloric Restriction, (1999) Science 285:1390. Weindruch et al., Dietary Restriction in Mice Beginning at 1 Year of Age: Effect on Life-Span and Spontaneous Cancer Incidence, (1982) Science 215-1415. |
| PATENT PARENT CASE TEXT | This data is not available for free |
| PATENT CLAIMS |
What is claimed is: 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. 2. The method of claim 1, wherein said biological sample comprises cells. 3. The method of claim 2, wherein said cells are obtained from a mammal. 4. The method of claim 3, wherein said mammal is a mouse. 5. The method of claim 1, wherein said 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. 6. The method of claim 5, wherein said gene encoding a chaperone protein is GRP78. 7. The method of claim 1, wherein said biomarker is apoptosis. 8. The method of claim 1, wherein said biomarker is aging. 9. The method of claim 8, wherein said biomarker of aging is a production of cancer cells. 10. The method of claim 1, wherein said 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. 11. The method of claim 10, wherein said 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. 12. The method of claim 11, wherein said 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. 13. The method of claim 12, wherein said 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. 14. A method according to claim 1 wherein changes in gene expression are evaluated using a gene chip. 15. The method of claim 14, wherein the gene chip contains genes for immune system activation. 16. The method of claim 14, wherein the gene chip contains genes for DNA repair. 17. The method of claim 14, wherein the gene chip contains genes associated with apoptosis. 18. The method of claim 14, wherein the gene chip contains genes for the enteric nervous system. 19. The method of claim 1, wherein said biological sample is a test animal. 20. The method of claim 19 additionally comprising 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. 21. The method of claim 20, wherein the reference animal has been on a calorie restricted diet for less than about 4 weeks. 22. The method of claim 20, wherein the reference animal has been on a calorie restricted diet for less than about 2 weeks. 23. The method of claim 19, wherein said test animal is a mouse. 24. The method of claim 19, wherein changes in gene expression are assessed in said test animal. 25. The method of claim 19 which further comprises: 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. 26. The method of claim 25, wherein 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). -------------------------------------------------------------------------------- |
| PATENT DESCRIPTION |
BACKGROUND OF THE INVENTION 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. SUMMARY OF THE INVENTION 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 age 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: 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. 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: 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 identifyng 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. 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 or 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. BRIEF DESCRIPTION OF THE DRAWINGS 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 those 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. 3 above. Statistical significance is indicated as in the legend to FIG. 2. 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 (Fasted+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 mice 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 arrays (Affymetrix, Santa Clara, Calif.) containing targets for approximately 12,000 known mouse genes and ESTs. The experiment tree function of GeneSpring 3.0 (Silicon Genetics, San Carlos, Calif.) was utilized to display the results. The horizontal axis represents the position of each gene assigned by the "gene tree" average-linkage hierarchical clustering algorithmn of the program. Below the position assigned to each gene is a color-coded indication of its relative expression level, based on a continuous scale. Bright blue indicates no detectable expression, purple average expression, and bright red high expression. The average expression of each gene in each group is shown. The GeneSpring "experiment tree" clustering algorithm calculated an average- linkage hierarchical clustering dendrogram of the data for each group of mice, which is shown to the left of the expression profiles. FIG. 9. Schematic representation of the hypothesis that CR acts by preventing age-related changes in gene expression. During aging, some genes become over expressed or under-expressed relative to their levels in young aninals (lower and upper lines). Unchanged expression with age is represented by the horizontal line. These deviations are assumed to be deleterious. The important genes effected by CR, in this hypothesis, are the over- or under-expressed genes returned to youthful levels of expression (arrows). The numbers of genes and ESTs in each category are shown at the ends of the lower and upper lines. The number of known genes in each category returned to baseline expression by LT- and ST-CR are given after the colons. Long-term and short-term CR both acted to reverse or prevent 23 of the increases and 41 of the decreases. Thus, long-term LT-CR actually prevented the increased expression of only 30 genes and ESTs and the decreased expression of only 24 genes and ESTs. FIG. 10. Average of pairwise comparison of the global gene expression correlation coefficient for each possible pair of mice FIG. 11. The hepatic gene expression profiles of young CR, young control and streptozotocin (STZ)-treated mice. Levels of specific mRNA were determined using the Mu11KsubA and Mu11KsubB GeneChip arrays (Affymetrix, Santa Clara, Calif.) containing targets for approximately 12,000 known mouse genes and ESTs. The experiment tree function of GeneSpring 3.0 (Silicon Genetics, San Carlos, Calif.) was utilized to display the results. The horizontal axis represents the position of each gene assigned by the "gene tree" average-linkage hierarchical clustering algorithm of the program. Below the position assigned to each gene is a color-coded indication of its relative expression level, based on a continuous scale. Bright blue indicates no detectable expression, purple average expression, and bright red high expression. The average expression of each gene in each group is shown. The GeneSpring "experiment tree" clustering algorithm calculated an average-linkage hierarchical clustering dendrogram of the data for each group of mice, which is shown to the left of the expression profiles. FIG. 12. Average of pairwise comparison of the global gene expression correlation coefficient for each possible pair of mice. FIG. 13. The hepatic gene expression profiles of old CR, old control and aminoguanidine (AG)-treated mice. Levels of specific mRNA were determined using the Mu11KsubA and Mu11KsubB GeneChip arrays (Affymetrix, Santa Clara, Calif.) containing targets for approximately 12,000 known mouse genes and ESTs. The experiment tree function of GeneSpring 3.0 (Silicon Genetics, San Carlos, Calif.) was utilized to display the results. The horizontal axis represents the position of each gene assigned by the "gene tree" average-linkage hierarchical clustering algorithm of the program. Below the position assigned to each gene is a color-coded indication of its relative expression level, based on a continuous scale. Bright blue indicates no detectable expression, purple average expression, and bright red high expression. The average expression of each gene in each group is shown. The GeneSpring "experiment tree" clustering algorithm calculated an average-linkage hierarchical clustering dendrogram of the data for each group of mice, which is shown to the left of the expression profiles. |
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