Delayed and accelerated aging share common longevity assurance mechanisms

Abstract

Mutant dwarf and calorie-restricted mice benefit from healthy aging and unusually long lifespan. In contrast, mouse models for DNA repair-deficient progeroid syndromes age and die prematurely. To identify mechanisms that regulate mammalian longevity, we quantified the parallels between the genome-wide liver expression profiles of mice with those two extremes of lifespan. Contrary to expectation, we find significant, genome-wide expression associations between the progeroid and long-lived mice. Subsequent analysis of significantly over-represented biological processes revealed suppression of the endocrine and energy pathways with increased stress responses in both delayed and premature aging. To test the relevance of these processes in natural aging, we compared the transcriptomes of liver, lung, kidney, and spleen over the entire murine adult lifespan and subsequently confirmed these findings on an independent aging cohort. The majority of genes showed similar expression changes in all four organs, indicating a systemic transcriptional response with aging. This systemic response included the same biological processes that are triggered in progeroid and long-lived mice. However, on a genome-wide scale, transcriptomes of naturally aged mice showed a strong association to progeroid but not to long-lived mice. Thus, endocrine and metabolic changes are indicative of "survival" responses to genotoxic stress or starvation, whereas genome-wide associations in gene expression with natural aging are indicative of biological age, which may thus delineate pro- and anti-aging effects of treatments aimed at health-span extension.

Figure 1. Genome-wide expression correlations between mouse models of accelerated and delayed aging.

(A) Spearman's rank correlation r between the expression profiles of the significantly differentially expressed genes of the progeroid Csb^m/m;Xpa^−/− or non-progeroid Csb^m/m and Xpa^−/− mouse groups (as compared to their respective wt control mouse group) and those of the long-lived mouse groups (relative to corresponding wt controls). The comparison examines whether the genes that have significantly changed expression in the livers of short-lived Csb^m/m;Xpa^−/− progeroid mouse groups relative to their respective wt control mice show the same or opposite direction of expression change in the liver of long-lived mouse groups relative to their corresponding wt controls. (B) Spearman's rank correlation between the significant expression profiles of the Ames-CR mouse group relative to the group of respective wt controls and each of the long-lived (Ghr^−/−, Ames, CR and Snell), progeroid NER (Csb^m/m;Xpa^−/−, Ercc1^−/−, Ercc1^−/Δ−7) and non-progeroid NER (Csb^m/m and Xpa^−/−) mouse groups relative to their respective wt controls. (C) The correlation heat-map depicts the Pearson's rank correlation between the transcriptomes of individual mice to one another (mice are plotted on the x and y axis; e.g., indicated in a dotted line) on the basis of a predefined data set. This data set includes the genes whose expression changed significantly in all progeroid mice (Csb^m/m;Xpa^−/−, Ercc1^−/− and Ercc1^−/Δ−7) as compared to their respective controls and the genes whose expression changed significantly in all long-lived mice (Ghr ^−/−, Ames, CR, Ames-CR and Snell) as compared to their corresponding wt control mice (Figure S1A, two-sided t-test, p<0.01). The deep red color indicates a strong positive correlation between the transcriptomes of NER progeroid and long-lived mice. Blue and white indicate a negative or no correlation, respectively, as seen for all wt mice and non-progeroid mutants.

Figure 2. Significantly over-represented biological processes in NER progeria, dwarfism and CR.

(A) Shared and (B) distinct biological processes associated with NER progeria, dwarfism and CR. All significant differentially transcribed genes derived from each mouse group (Csb^m/m;Xpa^−/−, Ercc1^−/− and Ercc1^−/Δ−7, Ghr ^−/−, Ames, Ames-CR and Snell) against their corresponding controls (Figure S1A) were grouped into functional GO categories and tested for overrepresentation. Among others, lipid and carbohydrate metabolism, hormonal regulation and a response to oxidative stress were significantly over-represented in both progeroid and long-lived mouse groups. Amino acid metabolism, purine metabolism and cell cycle were only identified in NER progeria, whereas immune responses were limited only to long-lived mice. (C) Expression of genes associated with over-represented biological processes. The average gene expression (upregulation in red; downregulation in green) in each of the mouse groups (X-axis) is compared to that of the corresponding wt controls. (D) Quantitative real time PCR evaluation of % of relative mRNA expression levels of genes associated with the GH/IGF1 somatotropic axis (Igf1, Ghr, Prlr, dio1) and carbohydrate metabolism (gck, aco1) in 15-day old Ercc1^−/− and 16-week old Ercc1^−/Δ−7 mice as compared to corresponding age matched wt controls. For each biological process, p-values represent the average of p-values obtained for each over-represented process that exceeded the significance threshold (−log (p-value)>1.3) when each progeroid and long-lived mouse group was compared relative to its respective wt control group (error bar = SD).

Figure 3. Age-related expression changes and significantly over-represented biological processes.

(A) Circular map with age-related expression changes in the spleen, lung, kidney and liver of 2.5 year-old mice relative to 13 week-old young adult mice. Each ring of the map depicts the expression of the complete mouse transcriptome in each tissue. The innermost ring depicts the average fold change in expression across all four organs. A large fraction of genes have similar (i.e., 3/4 organs; section II and IV) or identical expression (i.e. 4/4 organs; section I and V) in the four organs with aging. Green and red arrows indicate down- and up-regulated genes respectively. Percentages indicate the fraction of probe sets associated with each section over the entire mouse transcriptome. (B) Over-represented biological processes within each section of the circular map. Sections IV and V contain the genes that are significantly upregulated with aging and include immune, stress and apoptotic responses whereas sections I and II, which are genes significantly downregulated with aging, contain processes associated with metabolism. (C) Over-represented signaling pathways within sections I and V of the map.

Figure 4. Relative mRNA expression levels of genes associated with significantly over-represented biological processes.

(A–D) % of relative mRNA expression levels of genes associated with immune responses (A), apoptosis (B), carbohydrate (Impa12, Gyk, Phkb) and lipid metabolism (Crot, Dhrs8, Akr1d1) (C), and energy derivation and biosynthesis (D) in the liver of an independent aging cohort of 130-week old compared to 13-week old wt male mice. For each gene, expression levels in the 130-week old livers are plotted relative to those of 13-week old tissues (red colored dotted line). Error bars indicate S.E.M between replicates (n≥6).

Figure 5. Genome-wide expression correlations between progeroid, long-lived and naturally aged mice.

(A) Correlation between the transcriptomes of individual NER progeroid or long-lived mouse livers as compared to their respective wt controls and naturally aged mouse livers. The analysis was performed by pooling all progeroid (Csb^m/m;Xpa^−/−, Ercc1^−/− and Ercc1^−/Δ−7) and long lived mice (Ghr ^−/−, Ames, CR, Ames-CR and Snell) into two separate groups and derive the genes whose expression changed significantly as compared to the group of all their respective controls (i.e. all the wt mice of either the progeroid or long-lived mice; Figure S1A, two-sided t-test, p<0.01). Using the non-parametric Spearman's rank correlation coefficient, we then asked whether the “progeroid” or “long-lived” genes have the same or opposite direction of expression change with those seen in the livers of 130-week old as compared to 13-week old mice. Note the significant positive correlation (red) between NER progeroid but not long-lived and naturally aged mouse liver expression profiles. (B) A model for the pro-survival/life extension response that occurs with aging: DNA damage accumulates with age or rapidly in organisms with defects in DNA repair. This triggers a systemic response that includes the suppression of the GH/IGF1 axis and oxidative metabolism and up-regulation of stress responses. Similar transcriptional changes are seen in long-lived organisms (dwarf mutants or as a consequence of CR) and with aging. This response shifts resources from growth to somatic maintenance, thereby protecting against cancer and delaying the onset of age-related pathology.