How premature aging resembles extended longevity, part II

Last year we heard about the counterintuitive observation that DNA repair mutants (which exhibit premature aging and shortened lifespans) have significant phenotypic and transcriptional overlap with genetically dwarfed or calorie restricted (CR) animals (which exhibit delayed aging and extended longevity).

The interpretation of those surprising results: Both DNA repair deficiency and CR cause organisms to divert resources away from reproduction and growth, and toward maintenance and repair. (It just happens to be fruitless for the DNA repair mutants, since they’re dumping energy into a compromised pathway.) Chalk one up for the disposable soma theory of aging.

Now, a follow-up paper from (basically) the same research group compares age-related transcriptional changes between mice aging normally, prematurely or slowly. The study, which includes data from multiple organ systems across the entire lifespan, confirms and expands on the observation that progeria and extended lifespan share common phenotypic features. From Schumacher et al.:

Delayed and Accelerated Aging Share Common Longevity Assurance Mechanisms

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.

Those last two sentences are very important, in that they address a critical issue in studies of transcription (indeed of any phenotype) as it changes with age. Given the observation that expression of gene X (or hormone Z) changes with age, one must next ask: How do we know whether this change reflects a causative feature of aging, a defensive response to another age-related change, a passive response of no great import, an epiphenomenon, or an artifact of the experimental system? (I’ve discussed this concern before, in the context of age-specific regulation of micro-RNAs.)

The authors would argue that the changes that are common to both progeroid and long-lived animals represent true protective/defensive responses to age-related stresses (according to the same logic that underlies the interpretation of the earlier work, discussed above). In contrast, those features shared between natural aging and progeria — of which there are far more — are signs of deterioration and decrepitude, and thus reflect age-related decline.

This logic is powerful: Having distinguished between these two classes of age-related transcriptional change, we’re far better equipped to start meaningfully measuring biological age.



  1. Isn’t this just another way of saying that aging is now confirmed as a genetically initiated program and that CR has the ability interrupt that program – albeit in a limited way, while progeria like processes accelerate the program?

    One of the oldest biological processes are cascade processes. You see them in the immune system where one event ultimately triggers many, many other events in pyramid fashion. A genetic aging program would be similar – a pyramidic expression of relatively few key genes that ultimately shut down essential biological processes (cell maintenance, replacement DNA repair, etc.) and produce typical age related symptoms. It seems CR interrupts the expression of key gene components of the aging expression pyramid, where as progeria accelerates the expression by causing earlier than normal expression of these same aging cascade genes. We see how the process is tied to reproduction in species like salmon where breeding initiates gene expression that results in the accelerated shut down of all biological systems in a process similar to in some ways, but considered different than accelerated aging. We might theorize that salmon’s senescence gene expression occurs higher up in the aging cascade pyramid – before those genes affected by CR like process can be affected. Again showing that aging initiates in gene expression cascade beginning in youth.

    I believe the genetic understanding of the aging process extremely important work, because eventually it may provide much greater key understandings of those genetic processes which begin the aging expression cascade in humans. Once the gene expression process is understood in exact detail, we will have the gene locations where correct genetic intervention will stop the aging cascade from ever being initiated, beginning and or perhaps even reverse some or all of it. The age gene expression cascade model fits the reality of aging because only the initial gene expressions are necessarily purposeful, but the bulk of the expression cascade process are simply cause and effect – not unlike a domino cascade – once the first domino falls others in chain are inevitably affected – unless something stops the process.

    Using the age cascade process model we can see how the gene expression caused by CR might only limit and or delay a significant number of the cascade chains, but not all of the gene expressions of the cascade. Some will continue to flow around and eventually overcome the CR expression intervention effects. The ever broadening base of the pyramid like genetic age cascade ultimately produces the very wide range of what we think of as typical age related damage.

    Unfortunately, it’s the bottom of the age cascade (the elderly) that most scientist continue to study whereas it is more likely that the top of the cascade (the post puberty young) where the age cascade begins and is where solutions and intervention processes will be discovered and optimally implemented. Before this happens, we will likely continue to learn of ways that can intervene in chains or strands of the gene expression cascade – like CR, trans resveratrol, etc.

    In my opinion it is very important that our research approaches examine the genetic components of the aging process from their origins in youth as well as intervention processes that will delay aging in later ages. I believe current research is far too focused on the symptoms of aging, rather than the genetic causes.

  2. In my opinion it is very important that our research approaches examine the genetic components of the aging process from their origins in youth as well as intervention processes that will delay aging in later ages. I believe current research is far too focused on the symptoms of aging, rather than the genetic causes.

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