Gene Expression Patterns in Calorically Restricted Mice: Partial Overlap with Long-Lived Mutant Mice

Richard A. Miller, Yayi Chang, Andrzej T. Galecki, Khalid Al-Regaiey, John J. Kopchick and Andrzej Bartke

Department of Pathology (R.A.M., Y.C.), Geriatrics Center (R.A.M., A.T.G.), and Institute of Gerontology (R.A.M., A.T.G.), University of Michigan, Ann Arbor, Michigan 48109; Department of Physiology (K.A.-R., A.B.), Southern Illinois University, Carbondale, Illinois 62901-6512; and Department of Biomedical Sciences (J.J.K.), College of Osteopathic Medicine and Edison Biotechnology Institute, Ohio University, Athens, Ohio 45701

Address all correspondence and requests for reprints to: Richard A. Miller, Room 5316 CCGCB, Box 0940, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109-0940. E-mail: millerr{at}umich.edu.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
To gain insight into the pathways by which caloric restriction (CR) slows aging, gene expression levels were assessed for each of 2352 genes in the livers of 9-month-old CR and control mice. A total of 352 genes were found to be significantly increased or decreased by CR. The distribution of affected genes among functional classes was similar to the distribution of genes within the test set. Surprisingly, a disruption or knockout of the gene for the GH receptor (GHR-KO), which also produces life extension, had a much smaller effect on gene expression, with no more than 10 genes meeting the selection criterion. There was, however, an interaction between the GHR-KO mutation and the CR diet: the effects of CR on gene expression were significantly lower in GHR-KO mice than in control mice. Of the 352 genes altered significantly by CR, 29 had shown a significant and parallel alteration in expression in a previous study of liver gene expression that compared mice of the long-lived Snell dwarf stock (dw/dw) to controls. These 29 genes, altered both by CR and in dwarf mice, provide a list of biochemical features common to both models of delayed aging, and thus merit confirmation and more detailed study.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
CALORIC RESTRICTION (CR) is the only robust, well documented intervention that can extend life span and delay or decelerate multiple aspects of aging in mammals (1). The biochemical, cellular, or metabolic pathways that slow aging in CR rodents are not well understood, in part because CR affects so many cell types, extracellular moieties, intracellular pathways, and hormonal circuits. Discriminating the molecular pathways among these multiple effects has been difficult.

Gene expression profiling based on cDNA or oligonucleotide arrays provides an alternate approach to resolving this problem. A small number of previous papers have included data from gene expression surveys of CR rodents (2, 3, 4, 5, 6). None of these reports, however, has included a formal statistical method to control the type I error rate, i.e. to estimate the proportion of apparently affected genes likely to reflect chance sampling variation. Indeed, the number of genes reported as affected in these studies has been similar to the expected number of false positives for the small sample sizes used. In addition, all but one (2) of these previous reports has involved comparisons between CR and control mice at advanced age, thus possibly confounding the effects of CR per se with the effects of CR-mediated deceleration of aging. Surveys based on contrasts between CR and control mice at old ages will in principle generate lists of two classes of genes: those in which the normal effects of aging have been blunted, and those that respond promptly to CR and could, potentially, mediate its effects. In contrast, studies of the effects of CR conducted at relatively early time points are more likely to reveal genes that mediate CR effects, without an admixture of genes whose expression reflects the interaction of aging and the CR diet.

There are now six published instances of single gene mutations that extend life span in mice (for review, see Ref. 7). Four of these six lead to diminution of the levels of IGF-I, a key mediator of the effects of GH. The Ames dwarf mouse (df/df) was the first of these mutants noted to have exceptionally long life span (8). Ames dwarf mice are homozygotes for a loss-of-function mutation (df/df) at the Prop-1 locus that is required for development of the embryonic pituitary cells that secrete thyroid stimulating hormone, GH, and prolactin (PRL; Ref. 9). They are very similar in most respects to mice of the Snell dwarf (dw/dw) lines, in which a mutation at the Pit-1 locus blocks the effects of Prop-1 in the embryonic pituitary. Snell dwarf mice, like Ames dwarfs, are long-lived, and demonstrations of delayed immune and collagen aging in these animals further support the conclusion that the aging process per se has been altered by these mutations (10). Two other mutations promote longevity by alteration of GH-dependent pathways specifically, i.e. without dramatic alterations of thyroid hormone or PRL levels. One of these, the lit/lit mutation at the locus encoding GHRH receptor (Ghrhr), extends life span by about 25% when the mice are provided a diet low in fat. The other, a disruption or knockout at the GH-receptor gene (GHR-KO) (11), leads to an increase of 55% in male longevity and a 38% increase in female longevity compared with wild-type controls (12). Tests of learning and memory also suggest that cognitive effects of aging are delayed in the Ames dwarf and the GHR-KO mice (13, 14). The physiological basis for life span extension in these mutant mice is at least partly distinct from the mechanisms that mediate the CR effect, in that df/df mice placed on a CR diet live distinctly longer than normal df/df mice and longer than genetically normal mice on the CR regimen (15).

Our research strategy is based on the idea that each of these models—germline mutations and low calorie diets—is likely to produce changes of expression in a wide range of genes, some of which are important to the aging process and others of which do not affect aging or the progression of late life susceptibility to disease and disability. We reasoned that one way to discriminate among these two classes of affected genes would be to see which genes were altered, in the same direction, in different models of decelerated or delayed aging. We therefore compiled a list of genes whose expression levels in liver are significantly altered in 9-month-old mice subjected to 90% CR started at 1 month of age and 70% CR 2 wk later. We then compared this to a previously developed list of genes altered, in young mice, by the Snell dwarf mutation. We report a list of 352 genes that are altered in young CR mice using a rigorous criterion for statistical significance. Twenty-nine of these are also modulated by the Snell dwarf mutation and are thus the most attractive current candidate for genes on pathways related to the antiaging effects of CR and the dwarf mutation. Surprisingly, the GHR-KO mutation had a much smaller effect on gene expression in young adult mice, suggesting that the mechanism by which GHR-KO mutations alter longevity may involve effects at different ages or in different tissues from those that mediate the effects of CR on longevity.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
The experimental liver samples were derived from a group of 32 young adult mice, among which 16 had been subjected to a CR diet and the other 16 were ad libitum (AL) controls given free access to food. This degree of CR is known from previous studies to extend longevity by 35–50% in most mouse stocks, but it has not yet been tested for effects on longevity in the GHR-KO mice or their littermate controls. In our colony, CR reduced the mean weight of the control mice from 27.1 to 20.1 g and reduced the mean weight of the GHR-KO mice from 13.2 to 11.2 g. Within each group of 16 mice, 8 were homozygous for a loss-of-function mutant of the GHR/binding protein (BP), and 8 were control, wild-type littermates (KO and normal mice, respectively). To determine whether any of the genes showed a response to a CR diet that was conditional on genotype, we conducted a two-factor ANOVA in which expression level was considered a function of genotype (G), diet (D), and the G x D interaction. Using Student’s t statistic for a comparison-wise criterion, we found only 15 genes for which the interaction term reached a P value less than 0.01, somewhat less than the 24 genes to be expected by chance alone in an analysis of 2352 genes, assuming that there were no real interaction effects and assuming complete independence among gene expression levels. We found none for which p(t) (the probability of the observed t statistic) is less than 0.001. Using a criterion that adjusts nominal P values for the number of genes examined [false discovery rate (FDR) <0.05], we found no individual genes with a significant interaction effect. Because there was no compelling evidence for a diet effect conditional on genotype, we pooled the data across the two genotypes in our analysis of diet effects.

Our primary statistical criterion for assessment of statistical significance was the FDR criterion as embodied in the Significance Analysis for Microarrays method of Tusher et al. (16). This criterion, unlike the Bonferroni method, does not control the chance of a type I error across the entire set of hypotheses considered, and thus does not provide an experiment-wise P value. It does, however, provide a measure of the proportion of rejected null hypotheses likely to have been rejected because of sampling error. In our data set, we found 352 genes for which FDR is less than 0.05 with this method, including 185 in which CR led to an increase in gene expression level and 167 that decreased. The use of the FDR criterion implies that about 5% of the genes on this list represent chance sampling variation alone. A listing of the 352 genes for which FDR is less than 0.05 can be found in Supplementary Table 1Go, a and b, which are published as supplemental data on The Endocrine Society’s Journals Online web site, http://mend.endojournals.org/, and also at the following URL: http://www-personal.umich.edu/~millerr/Data_sets.htm.


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Table 1. Twenty-Five of the 352 Genes Significantly Altered by CR in 9-Month-Old Mice

 
We also considered two more conservative criteria for significance assessment. We would expect to see, by chance, only two or three genes for which the nominal p(t) is less than 0.001. We observed 95 such genes and can thus be confident that most of these 95 genes do not reflect mere sampling error. The most conservative criterion, based on the Bonferroni adjustment, identified a group of 17 genes for which p(t) is less than 0.000021. This group of 17 genes thus has less than a 5% chance of containing even a single example of a statistical false positive. Table 1Go shows the 25 genes for which nominal P value is less than 0.000025.

Figure 1Go presents a summary of these findings, showing the relationship between expression ratio (CR/AL or AL/CR) and the nominal p(t) value. The approach documents statistical significance of gene expression effects with expression ratios as low as 1.5. There are 212 genes for which the CR/AL ratio, or its reciprocal, exceeds 1.5 but for which nominal P is greater than 0.05, consistent with previous evidence (16, 17) that reliance on ratios alone, without formal statistical assessment, is likely to yield a large number of apparently positive findings that could reflect sampling error.



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Figure 1. Relationship between Effect of CR Diet on Gene Expression and Nominal P Value for 2352 Genes in Mouse Liver

Each symbol shows one gene. Triangles show genes for which FDR is less than 0.05, and smaller circles show genes that are not statistically significant by this test. Six genes with CR/AL ratios above 4 are not shown in the figure; all were significantly affected. The horizontal line at P = 0.05 is shown for reference.

 
Confirmation of Selected Results by Semiquantitative PCR
To rule out systematic errors in array production or sample handling, we retested 10 of the genes listed in Supplementary Table 1Go, a and b, using an alternate method, real-time PCR amplification of cDNA. In each case, we tested samples from three AL and three CR mice and then calculated the ratio (CR/AL) of the mean values from the PCR data. In two cases, the RT-PCR results were inconclusive, in one instance because the primers selected did not produce detectable product in the first 30 cycles and in the other because one of the six mice tested appeared to have 10-fold higher levels of mRNA than any of the other five mice. Results for the other eight mRNAs are shown in Table 2Go. For six of these (indicated as confirmed in Table 2Go), the CR/AL ratio produced by the RT-PCR system was similar to (and in all but one case more extreme than) that generated by the array analysis. For two others, RT-PCR data gave no indication of an effect of diet on mRNA level. These two discrepancies were each examined in a separate RT-PCR experiment, again using RNA samples that had been used for the array experiments, and again produced no evidence for an effect of CR.


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Table 2. RT-PCR Analysis of mRNA Levels

 
Gene Classifications
To obtain an initial assessment of the effects of the CR diet on classes of genes, we made use of the Dragon annotation database (URL: http://pevsnerlab.kennedykrieger.org/dragon.htm) to generate a list of Swiss-Prot keywords corresponding to each of the 352 genes in Supplementary Table 1Go, a and b. This annotation process yielded 912 keyword assignments, distributed among 184 gene categories. Table 3Go shows the results for the 18 categories for which there were at least 10 genes among those altered by CR. For 11 of these categories, as indicated in the table, the average expression ratio was significantly greater than 1.0, by univariate t statistic, for the genes within the category. Among the 65 CR-sensitive genes that encode glycoproteins, for example, the mean CR/AL ratio was 1.79 ± 0.13, an average that is significantly (P < 0.05) different from 1. Table 3Go also shows the percentage of genes, among those affected by CR, that fall into each of the 18 categories, as well as the corresponding percentage among the entire set of 2352 genes examined. For most classes of genes—the exceptions are antigens and RNA-binding proteins—the proportion among CR-sensitive genes is quite close to the proportion within the entire set of tested genes, providing no evidence that CR leads preferentially to changes in specific groups of genes based upon SwissProt keyword assignments. In addition to the 18 categories listed in Table 3Go, 16 others showed a statistically significant overall effect of CR, including 8 in which the effect was to diminish gene expression level. A complete list of all categories with four or more members altered by the CR diet is available from the corresponding author.


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Table 3. Category Analysis of Genes Altered by CR Diet

 
Genes Altered by the GHR/BP-KO Mutation
We used the same method to seek evidence for an effect of the GHR knockout mutation on gene expression, pooling across the two diet groups to increase statistical power. Surprisingly, none of the 2352 genes tested met our primary significance criterion of FDR less than 0.05. Ten of the 2352 genes were found to have nominal P value less than 0.001, and these are listed in Table 4Go.


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Table 4. Genes with Most Significant Effect of GHR-KO Genotype

 
GHR-KO Genotype Blunts the Effect of CR Diet on Gene Expression Level
Using the two-factor ANOVA described above, we found no individual genes for which the effect of CR diet was significantly different in KO as opposed to wild-type controls, using the FDR less than 0.05 criterion. We also noted, in a post hoc analysis by t test, that of the 25 genes with strongest evidence for CR effort (lowest P values) in the pooled data set, all 25 reached a P value less than 0.05 when tested in the normal mice alone, and 24 of the 25 reached a P value less than 0.05 for the half of the mice that were of the GHR-KO genotype. These findings show that the effects of the CR diet are qualitatively similar in mice of the two genotypes.

To provide a more sensitive test for possible interactions between diet and genotype, we compared the effects of CR diet in normal mice to CR diet in KO mice for the 95 genes that showed the strongest evidence for a CR effect in the pooled data set, i.e. those where P value was less than 0.001. For this purpose, we calculated the CR/AL ratio in normal mice and divided by the CR/AL ratio in the KO mice, and then log-transformed this value for each of the 95 genes. The mean value of this effect ratio was 0.09 ± 0.02, corresponding to a 23% stronger average effect (101.09 - 1) of CR in normal mice than in the KO mice (95% confidence interval, 11–36%). We conclude that the effect of CR on gene expression is on average somewhat stronger in wild-type controls than in KO mice for those genes that are most sensitive to CR effects.

Comparison to Genes Altered by the Snell Dwarf Mutation
To determine whether the effects of CR on liver gene expression might mimic the gene expression pattern of long-lived Snell dwarf mutant mice (dw/dwJ), we compiled a table listing all genes that 1) met the FDR less than 0.05 criterion in either system, and 2) also met a more relaxed significance criterion (nominal P < 0.05) in the other comparison. Table 5Go lists the 13 mRNAs found to increase in both 9-month-old CR mice and Snell dwarf mice (at 6 months of age). Of the 13 mRNA species listed, all except wee-1-like protein kinase met the FDR criterion in the CR mice; for this mRNA, the CR effect had a P value equal to 0.004. Table 6Go lists the 16 mRNAs found to decrease in both models of delayed aging. All 16 of these met the FDR criterion for the CR effect. Thus, the 29 genes in these two tables show similar, statistically convincing alterations in both the genetic and dietary models and deserve further consideration as possible mediators, or indices, of antiaging effects in the liver. Only three of these 29 mRNAs also show parallel effects in the GHR/BP-KO mouse: hydroxysteroid 17-ß dehydrogenase 2 mRNA is 2.6-fold lower in GHR/BP-KO mice than in controls (P = 0.013), whereas mRNA for IGF binding protein (IGFBP)-2 (3.3-fold higher; P < 0.001) and macrophage migration inhibition factor (1.95-fold higher; P = 0.02) are both elevated in the liver of the knockout mice.


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Table 5. Thirteen Liver mRNAs Increased in CR Mice and in Snell Dwarf Mice

 

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Table 6. 16 Liver mRNAs Decreased in CR Mice and in Snell Dwarf Mice

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
This paper reports statistically significant effects of the CR diet on 352 genes in the liver of young mice. It is clear, and unsurprising, that CR has major effects on metabolic and control pathways in the liver, and indeed the data suggest that at least 15% of the 2352 genes tested are altered to a significant degree. The proportion of liver genes altered by CR is likely to be a good deal higher than this, because many (at least half) of the genes on the test arrays are not expressed by liver cells, and because the limited statistical power in a survey using only 16 mice per group has surely produced a number of type II (false negative) errors. In addition, the blunting of CR effects in the GHR-KO mice, which made up half of our study population, will also diminish statistical power somewhat. Our strategy has emphasized analysis of young adult mice on the grounds that the effects of CR on age-sensitive traits are likely to represent a retardation of age-dependent changes through adult life, but it is possible that some CR effects on gene expression may be either transient (reverting to control levels before the age at which we obtained our samples) or delayed to ages beyond 9 months.

The FDR statistic, which we used as our primary criterion for compiling a list of genes altered by the CR diet or by the GHR-KO mutation, provides protection against false positive inferences resulting from sampling error but does not protect against other sources of error, such as those that might result from mistakes in data annotation or clone identification, or biochemical artifacts that might arise from cross-hybridization in the array method or cross-priming in the RT-PCR assays shown in Table 2Go. The RT-PCR data provide evidence against major systematic errors of the kind that can result from misidentification of clones or the accidental use of cDNAs of the wrong polarity in array preparation. Table 2Go shows, however, that even a small survey of eight mRNAs was able to reveal two cases in which RT-PCR data failed to confirm the implications of the array data set. It is not possible to decide, without further work, whether these discrepancies reflect errors in the array system or in the RT-PCR system, but they certainly emphasize the value of rechecking inferences on a gene-by-gene basis as a prelude to additional studies that might focus on individual genes and their products. The two genes indicated as not confirmed in Table 2Go represent a different kind of false positive result, not the sort of type I sampling error controlled by statistical procedures, but instead a source of false inferences derived from biochemical artifact or bioinformatic error that cannot be corrected by increased sample size. The limited number of genes evaluated by RT-PCR in Table 2Go do not provide a very precise estimate of the proportion of mRNAs, in Supplementary Table 1Go, a and b, that would fail to be confirmed by RT-PCR; a ratio of two failures in eight attempts represents a proportion of 25%, but this estimate has a 95% confidence interval of 3–65%. It is thus possible that as few as 3% of the genes in Supplementary Table 1Go, a and b, would fail an RT-PCR confirmation test, or as many as 65%.

Table 2Go also shows quantitative discrepancies between array-based and RT-PCR-based estimates of relative mRNA abundance. It is not surprising to us that the mean ratio computed from 6 samples in the RT-PCR experiment should differ somewhat from the mean ratio derived from 32 samples tested by array expression, but it is possible that a more comprehensive analysis might reveal, for some of the genes, a systematic difference between the RT-PCR estimates and those derived from the array method.

Among the several published studies of the effects of CR on gene expression in mice and rats (2, 4, 6), only one (2) has included a comparison of CR to AL animals early in life. Of the 25 genes listed in that paper as affected by the CR diet in the young mice, 9 were included in the CLONTECH arrays used in the present study, based on shared Locuslink identification numbers. None of these nine genes was found to be altered to a statistically significant degree (FDR < 0.05) in our own data set. Although this discrepancy may reflect differences in assay methodology or strain background, we suspect the lack of correspondence can be attributed in part to differences in the methods used for deciding whether a specific mRNA is or is not altered to a significant degree (16, 18, 19).

We see very little evidence that the genes altered by CR fall preferentially into specific functional classes; as shown in Table 3Go, the distribution of CR-affected genes into functional groups is in most cases very similar to the proportion of genes in the set of 2352 genes examined. There is, however, clear evidence for directional changes in many of the functional classes. Among the 65 affected genes in the glycoprotein group, for example, the average level of expression in CR mice is 79% above that in the AL group, a value significantly different from a 1:1 ratio. In all, 11 of the functional categories listed in Table 3Go show a significant increase from CR for those genes that are altered by diet to a significant degree. Such an analysis is the first step toward formulating a specific molecular hypothesis about genetic or physiological pathways that might lead to coordinated expression of specific gene sets. Developing specific hypotheses of this sort will require both a more comprehensive analysis of a larger fraction of liver-expressed genes and development of automated and statistically rigorous algorithms for relating lists of expressed genes to kinetically explicit metabolic pathways.

Certain of the genes and gene families listed in Supplementary Table 1Go, a and b, deserve specific comment, in that they suggest testable hypotheses about the ways in which CR might modulate aging. It is noteworthy that several of the up-regulated genes, including those for insulin receptor, IGFBP-2 and IGFBP-5, and the somatostatin receptor-1, are all up-regulated by CR, consistent with models that point to insulin and IGF-I signals as potential mediators of aging rate. The list of affected genes includes five mRNAs whose protein products play a role in translation initiation, as well as four DEAD-box proteins, putative RNA helicases that may also contribute to translation initiation; in each of these nine cases restricted mice have significantly lower mRNA levels. In contrast, each of the six affected genes encoding factors for initiation of transcription shows an increase in the CR mice. Each of the 13 mRNAs for CD antigens, which are typically expressed by leukocytes and involved in inflammatory responses, is up-regulated by the CR diet, although it will require further work to determine whether these changes reflect alterations of hepatocyte biology or, more likely, a relative increase in the proportion of leukocytic cells in the liver of CR mice. There is also a notable consistency among the mRNAs encoding members of the intermediate filament family: all seven members of the keratin family, as well as vimentin and glial fibrillary acidic protein, have lower mRNA levels in CR than in control mice. All four of the affected heat shock mRNAs are lower in CR mice, despite a significant increase in the mRNA for heat shock factor 1. The decline, in CR mice, of three mRNAs for DNA methyl-transferases is consistent with models in which CR might lead to extensive changes in expression patterns mediated by altered methylation levels. There also seem to be alterations of extracellular matrix metabolism, indicated by decline in all three of the affected matrix metalloproteinases and up-regulation of integrins {alpha}8, ß2, and ß5. Among the CR-sensitive genes, those related to TNF signals also show an interesting pattern, with all three members of the TNF-receptor family up-regulated, and all three of the genes that respond (in vascular endothelial cells) to TNF signals down-regulated by the CR diet.

We initially expected to see extensive overlap between the list of CR-sensitive mRNAs and those altered by the GHR-KO mutation. Four of the six mouse mutations that lead to increased life span interfere with the production of IGF-I. Two of these, the Snell dwarf (dw/dw) and Ames dwarf (df/df), produce syndromes in which thyroid hormones and PRL are diminished in addition to the decline in GH and IGF-I, but two others, GHR-KO (12) and the Ghrhr-deficient lit/lit mutation (20), affect GH/IGF-I pathways without direct alteration of thyroid and PRL pathways. Because CR itself leads to a depression of IGF-I levels early in adult life (21, 22), we thought it reasonably likely that the CR effect on life span might be mediated, in part, by IGF-I deficit, a condition also seen in the GHR-KO mouse. From this perspective, it was surprising that the liver gene expression patterns were minimally affected by the GHR-KO mutation; as shown in Table 4Go, only 10 of the 2352 genes met the P value less than 0.001 criterion, and none met the FDR-based criterion reached by 15% of the genes in the CR contrast. Restricting the analysis to mice on the normal diet did not substantially increase the number of genes affected by the KO mutation (data not shown), although this analysis uses only eight mice per group and thus has less statistical power than the full study. It is consistent with expectations, and therefore reassuring, to note the 9-fold decline in the level of mRNA for IGF-I in the GHR-KO mice. It is also provocative to note the 3.3-fold increase (P < 0.0001) in mRNA for the IGFBP-2 in the GHR-KO mice, because this mRNA also shows significant increases in CR mice and dw/dw mice (see Table 4Go).

There is clearly an interaction between the CR diet and the GHR-KO mutation, in that the CR effect is on average significantly smaller for KO mice than when applied to genetically normal animals. It is not easy to reconcile the paucity of gene expression effects in these GHR-KO mice with the dramatic effect of this mutation on longevity (12), which has now been confirmed in a separate laboratory (23). It is possible that the key changes that mediate longevity increase in these mice involve organ systems other than the liver (brain or endocrine organs, for example). It is also possible that changes in gene expression in GHR-defective mice are compensated in young mice, but then become dramatic only at older ages. It is also possible that the changes in gene expression that contribute to the life span effects in the GHR-KO mice involve genes not represented among the 2352 cDNAs evaluated in the CLONTECH Laboratories, Inc. (Palo Alto, CA) system, or involve changes in genes whose expression level (mRNA abundance) is too low to be easily quantified using array hybridization. It is also possible that the effects of this mutation (and indeed of CR itself) might involve alterations in other aspects of cell biology, such as the biophysical properties of membranes or cytoskeletal organization or mitochondrial coupling, that do not depend on broad-scale changes in gene expression patterns at all. Still, these are ad hoc explanations, and the apparent paucity of gene expression changes attributable to the GHR-KO genotype is surprising enough to justify additional analyses at older ages and in other tissues.

Tables 5Go and 6Go represent the key result of this study, a list of 29 genes that show parallel, and statistically significant, effects of both the CR diet (this paper) and the dw/dw mutation (24). The purpose of making such a comparison is to try to distinguish genes affected by CR (or the dw/dw mutation) that are related to the longevity effect from those that are altered by the diet or mutation but unrelated to aging rate. More work will be needed, for each of these genes, to confirm the diet and mutation effects on other backgrounds and using other detection systems, and to see whether protein levels are affected to the extent suggested by the mRNA data; an array experiment of the kind presented here is only the first step in such an analysis, a screening tool to focus attention on subsets of genes likely to merit more intense scrutiny. Indeed, our RT-PCR results, although limited in scope, suggest that array-specific artifacts, including possible cross-reactivity among mRNAs and/or misidentified cDNA sequences among those on the probe array, may lead to false impressions of mRNA abundance that justify verification of our findings using alternate methods, preferably including tests of protein levels corresponding to the RNAs of interest.

Although it is possible that some of the genes listed in Tables 5Go and 6Go will be shown to play a causal role in the regulation of aging and late-life disease, it is likely that most of them are altered as secondary effects of the causal process. Major urinary protein-1, for example, which acts to convey pheromone components in male urine (25), is known to be regulated by both testosterone and GH levels (26), and is thus more likely to be an index of fundamental shifts in endocrine balance than a cause of such shifts. Further work, using more comprehensive gene arrays, is sure to produce a more comprehensive view of the overlaps between CR and the antiaging effects of the dw/dw genotype. It will be particularly informative to extend these studies to alternate models of decelerated aging in mice, including tests of mutations of p66shc (27), of diets in which growth is restricted by limited availability of an essential amino acid (28), and comparisons between laboratory-derived mouse stocks and longer-lived mice derived from wild-trapped progenitors (29, 30). Eventually, work along these lines will provide a catalog of genes whose expression levels correlate consistently with life expectancy across a range of such delayed-aging models. It will then become possible to use this listing to develop hypotheses about the mechanism of life span control in mice, either by determining common elements of cellular control, such as regulatory hormones or metabolic signals, or by finding commonalties of molecular control such as shared promoter sequences or other regulators of gene expression at the levels of transcription or mRNA stability.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Animals
GHR-KO mice and normal littermate controls were produced in a closed colony maintained in Southern Illinois University Vivarium (Carbondale, IL) by mating heterozygous (+/-) carriers of the disrupted GHR/GHBP gene or homozygous knockout (-/-) males with +/- females. The genetic background of these animals is derived from 129/Ola embryonic stem cells and from BALB/c, C57BL/6, and C3H inbred strains. The animals were weaned at the age of 21 d and housed in groups of four or five with animals of the same gender and phenotype. The rooms were maintained at 22 ± 2 C, the lights were on from 0600–1800 h, and the animals had free access to tap water and pelleted diet (LabDiet, PMI Feeds, Inc., St. Louis, MO), except as noted below. All mice were maintained in accordance with the standards specified in the National Institutes of Health Guide for the Care and Use of Laboratory Animals.

Starting at the age of 1 month, half of the animals in each genotype/gender group were subjected to CR by reducing their daily food intake to 90% of AL food intake of animals of the same genotype and sex during 1 wk, 80% during the next week, and 70% for the remainder of the study. Food consumption of AL animals was monitored throughout the study, and the CR animals were fed daily, at approximately 1700 h, 70% of the average amount of food consumed daily by AL animals during the preceding week. At the age of 8–9 months, the animals were anesthetized with Isoflurane, bled by cardiac puncture, and killed by decapitation, and the livers (as well as other organs used for studies not reported here) were removed, quickly frozen on dry ice, and stored at -70 C. Samples of liver tissue were shipped on dry ice to the University of Michigan for analysis.

Preparation of Labeled cDNA Targets and Hybridization to Immobilized Probe Sets
Total RNA was extracted from each liver using the Atlas Pure Total RNA Isolation Kit (CLONTECH Laboratories, Inc.) after the vendor’s protocol. The RNA was digested with RNase-free DNase I to remove genomic DNA contamination. To prepare labeled cDNAs, we used the Atlas cDNA Expression Array Kit (CLONTECH Laboratories, Inc.) after the manufacturer’s recommended protocol. Briefly, in each case, 5 µg of total RNA were converted into 32P-labeled first strand cDNA by means of Superscript II reverse transcriptase (Invitrogen, Carlsbad, CA). The purification of the labeled cDNA from unincorporated 32P-labeled nucleotides was achieved with CHROMA SPIN-200 column chromatography. cDNA fractions of highest activity were pooled and hybridized to the Mouse Atlas 1.2 Array and 1.2 Array II membranes, each of which contains 1176 spotted mouse cDNA fragments as well as control spots; these will be referred to as type I and type II membranes, respectively. After prehybridization for 30 min at 68 C in ExpressHyb (CLONTECH Laboratories, Inc.) supplemented with 100 µg/ml sheared salmon testes DNA (Sigma), the heat-denatured cDNA target preparation was added. Hybridization occurred overnight at 68 C with continuous rolling agitation. Membranes were washed four times for 30 min in 2x SSC/1% SDS at 68 C, followed by two washes in 0.1x SSC/0.5% SDS (30 min, 68 C). Membranes were sealed in sample bags (Perkin-Elmer Life Sciences, Boston, MA), exposed to a storage phosphor screen for 4 d, and evaluated with a PhosphorImager (Molecular Dynamics, Inc., Sunnyvale, CA).

Data Reduction
The digital images from the PhosphorImager were processed using the ArrayVision program (Imaging Research, Inc., St. Catherines, Ontario, Canada) to generate background-subtracted pixel volumes for each of the 1176 spots on each membrane. For a small number of spots (about 2% of the total), the background subtraction produces a negative value because the spot in question was adjacent to another spot whose exceptionally high intensity produces a high background reading. Spots in this class were treated as missing data and for convenience were arbitrarily assigned a value of 1 pixel unit. Each individual experiment included a set of four mice, one from each of the four [D x G] classes. One set of four membranes was lost because of a technical error, and thus the data set consisted of information on 32 mice using type II membranes and 28 of these mice using type I membranes. Each value was then transformed to its common logarithm to avoid undue influence of the small number of very intense spots in the subsequent analysis. The data were then normalized as in previous work (24). In brief, a standard array was calculated as the median level for each of the 2352 genes across the set of 28–32 mice. Linear regression was then used to adjust each set of measurements to obtain the same slope and intercept as observed for the calculated standard array. These regression-adjusted values were used in all further calculations.

Assessment of Statistical Significance
Our primary criterion for assessing the significance of the CR effect on gene expression was the Significance Assessment for Microarrays algorithm developed by Tusher et al. (16). This method employs an S statistic that is similar to the ordinary t statistic, but adjusted to reduce the apparent significance of genes with a very low SD. Use of the S-statistic reduces the likelihood that a gene that is only slightly altered by the intervention (e.g. CR diet) will be called significant merely because sampling variation has led to a very small estimated SD. The algorithm, available in the form of an Excel add-in from the group’s web site (http://www-stat.stanford.edu/~tibs/SAM/), allows the user to control the FDR and thereby modulate the sensitivity and specificity of the gene selection process. In this paper, we chose a FDR less than 0.05 as our primary criterion; thus, we can be 95% confident, for any individual gene listed in the report, that the effects of diet or mutation have not arisen by chance alone. We also calculated the Student’s t statistic (two-tailed, assuming homoscedasticity, i.e. equal variances among groups) for each gene in the data set, and refer to the resulting probabilities as nominal P values because, unlike the FDR statistic, these values are not adjusted to reduce the type I errors expected in a series of multiple simultaneous comparisons. Other statistical tests are described in the text where appropriate.

Semiquantitative RT-PCR
cDNA synthesis and target amplification was accomplished in a single step starting with 200–300 ng total RNA using the LightCycler-RNA Amplification Kit SYBR Green I (Roche, Indianapolis, IN) and the LightCycler System (Roche) after manufacturer’s protocols. Primers were at 0.4 µM each. Taq polymerase was preincubated for 10 min at 4 C with anti-Taq antibody (CLONTECH Laboratories, Inc.). The mixtures were denatured at 95 C for 1 min and then cycled 50 times with 56–58 C annealing for 8 sec, 72 C extension for 12 sec, with slopes of 20 C/sec for all steps. The LightCycler analysis software was used for the relative quantification. Supplementary Table 2Go, which is published as supplemental data on The Endocrine Society’s Journals Online web site, http://mend.endojournals.org/, and at http://www-personal.umich.edu/~millerr/Data_sets.htm, lists the primers used for these amplification responses.


    ACKNOWLEDGMENTS
 
We thank Ray Krzesicki and Lynn Winkleman for technical assistance with the array experiments.


    FOOTNOTES
 
This work was supported by National Institutes of Health Grants AG-08808, AG-19899, and AG-13283. J.J.K. was supported in part by the State of Ohio’s Eminent Scholar Program, which includes a gift from Milton and Lawrence Goll, and by DiAthegen LLC, Inc.

Abbreviations: AL, Ad libitum; BP, binding protein; CR, caloric restriction; D, diet; FDR, false discovery rate; G, genotype; GHR, GH receptor gene; GHR-KO, GHR knockout; IGFBP, IGF binding protein; PRL, prolactin; p(t), probability of observed t statistic.

Received for publication April 16, 2002. Accepted for publication August 7, 2002.


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