A conserved transcriptional signature of delayed aging and reduced disease vulnerability is partially mediated by SIRT3

Abstract

Aging is the most significant risk factor for a range of diseases, including many cancers, neurodegeneration, cardiovascular disease, and diabetes. Caloric restriction (CR) without malnutrition delays aging in diverse species, and therefore offers unique insights into age-related disease vulnerability. Previous studies suggest that there are shared mechanisms of disease resistance associated with delayed aging, however quantitative support is lacking. We therefore sought to identify a common response to CR in diverse tissues and species and determine whether this signature would reflect health status independent of aging. We analyzed gene expression datasets from eight tissues of mice subjected to CR and identified a common transcriptional signature that includes functional categories of mitochondrial energy metabolism, inflammation and ribosomal structure. This signature is detected in flies, rats, and rhesus monkeys on CR, indicating aspects of CR that are evolutionarily conserved. Detection of the signature in mouse genetic models of slowed aging indicates that it is not unique to CR but rather a common aspect of extended longevity. Mice lacking the NAD-dependent deacetylase SIRT3 fail to induce mitochondrial and anti-inflammatory elements of the signature in response to CR, suggesting a potential mechanism involving SIRT3. The inverse of this transcriptional signature is detected with consumption of a high fat diet, obesity and metabolic disease, and is reversed in response to interventions that decrease disease risk. We propose that this evolutionarily conserved, tissue-independent, transcriptional signature of delayed aging and reduced disease vulnerability is a promising target for developing therapies for age-related diseases.

Fig 1. Identification of a multi-tissue transcriptional signature of CR in mice.

(A) Volcano plot depicting all gene ontology (GO) terms represented across eight mouse tissues. Using the constraints that both FDR adjusted p-values were ≤0.00285 and that the median Z-score ≥ 2.58 or ≤ -2.58 (up- or downregulated by CR, respectively), we identified 43 GO terms that were significantly modulated by CR across all tissues (red dots). (B) Each row indicates one of the 43 GO terms in the CR transcriptional signature, columns indicate the eight mouse tissues studied (Cx = cerebral cortex, Hc = hippocampus, Ch = cochlea, Ht = heart, Lv-liver, Kd = kidney, WAT = epididymal white adipose tissue, Gn = gastrocnemius). The 43 GO terms were clustered into four functional categories including mitochondrial oxidative phosphorylation, mitochondrial redox metabolism, immune response/inflammation and ribosomal structure, and are ordered (top to bottom) as listed in S2 Table. Red or blue fill indicates up- or downregulation by CR, respectively; black fill indicates pathways not changed by treatment (median Z-score = 0).

Fig 2. The multi-tissue transcriptional signature of CR in mice is significantly recapitulated in diverse species on CR and in long-lived mouse models.

(A) The far-left column represents the median Z-score across tissues with GO terms sorted as in Fig. 1 and described in S2 Table. Subsequent columns (left to right) indicate the effect of CR in other species and tissues (Drosophila, rat heart, rat white adipose tissue, rhesus monkey vastus lateralis muscle and rhesus monkey peripheral blood mononuclear cells), as well as in four long-lived mouse genetic models. Red or blue fill indicates pathways activated or inhibited, respectively, by treatment; black fill indicates pathways not changed by treatment and grey fill indicates pathways not represented in the dataset. (B) The observed Spearman correlation between the median Z-score for mouse CR and other species subjected to CR (r = 0.316) is greater than would be predicted by model-based (Monte Carlo) permutation (p = 0.001), indicating that the overall transcriptional signature of CR in mice is conserved in other species and tissues. (C) The observed Spearman correlation between the median Z-score for mouse CR and the median Z-score in four mouse models of delayed aging (r = 0.201) is greater than would be predicted by model-based permutation (p = 0.001), demonstrating that the overall transcriptional signature of CR in mice is similarly observed in other models of delayed aging. See S1 Table for a detailed description of the individual studies.

Fig 3. SIRT3 partially mediates the transcriptional signature of delayed aging that is also indicative of risk of disease in mice and humans.

Rows indicate GO terms for the conserved signature of delayed aging and are ordered as in Fig. 1 and as described in S2 Table. (A) Analysis of gene expression in mouse muscle indicates that the response to CR is seen in wild-type control mice, however absence of the Sirt3 gene (Sirt3ko) partially blunts the response to CR. (B) Consumption of a high fat diet in mice, obesity in humans, and individuals diagnosed with polycystic ovary syndrome (PCOS) display the inverse transcriptional pattern for the longevity signature, whereas (C) interventions that decrease risk of disease (treatment with thiazolidinediones in mice and humans, consumption of resveratrol and weight loss) show an induction of the transcriptional signature of delayed aging. See S1 Table for a detailed description of the individual studies.