Fight Aging!

It seems clear that many of the varied approaches to adjusting the operation of metabolism in ways that (usually modestly) slow aging in animal models achieve this outcome by acting on a set of common underlying mechanisms. For example, a great deal of effort has gone towards the study of autophagy in this context, a response to mild stress that improves cell function by recycling damaged molecular machinery. Upregulation of autophagy appears to be a feature of most of the better studied approaches to slowing aging, and certainly those derived from investigations of calorie restriction.

What do more sophisticated efforts to find commonalities between age-slowing interventions look like? Today's open access paper offers some insight into that question. The authors report on an approach to the analysis of omics data from biological samples taken from mice following intervention, in search of a greater understanding of the resulting changes in metabolism. This is potentially a vast amount of data, and the exercise is narrowed by considering only liver tissue samples. Even so, the researchers identify changes in the operation of fatty acid metabolism as a common feature of several quite diverse approaches shown to slow aging in short-lived species. The idea is that this sort of analysis will aid in the more deliberate design of different, better interventions in the future.

Lifespan-extending interventions induce consistent patterns of fatty acid oxidation in mouse livers

Some nutritional and pharmacological interventions consistently extend lifespan and healthspan (i.e., the period free from age-associated diseases and disabilities) in mouse and other animal models. Nutritional interventions include calorie restriction (CR), methionine restriction, and ketogenic diet. While the number of possible geroprotectors (i.e., drugs aiming to prevent, slow, or reverse aging process) has been growing, pharmacological interventions whose effects on lifespan extension have been documented by the National Institute on Aging (NIA) Interventions Testing Program (ITP) include acarbose (ACA), canagliflozin, 17α-estradiol (17aE2), glycine, nordihydroguaiaretic acid, Protandim (a Nrf2 inducer), and rapamycin (Rapa).

Rapa modulates nutrient-sensing pathways by inhibiting the activity of mTOR through complex formation with FK506-binding protein 12, which globally attenuates protein translation via mTOR complex 1 (mTORC1) and ultimately reduces inflammation, increases autophagy, and improves stem cell maintenance. ACA could share some aspects of CR; it is an oral antidiabetic drug which competitively inhibits the activity of α-glucosidase enzymes to digest polysaccharides, resulting in the delay of sugar uptake in the gastrointestinal tract. ACA treatment has been shown to extend lifespan in male mice more than in female mice, possibly related to sex-dependent differences observed in heart, liver, and gut metabolite profiles. 17aE2 is a stereoisomer of the dominant female sex hormone 17β-estradiol, having much weaker binding affinity to the classical estrogen receptors, stronger affinity to the brain estrogen receptor, and neuroprotective properties. 17aE2 treatment extends lifespan in male but not in female mice, potentially related to male-specific reduction of age-associated neuroinflammation and sex-specific metabolomic responses observed in liver and plasma metabolite profiles. Because these lifespan-extending drugs were tested with standardized protocols in the NIA ITP and because they have differences in primary mode of action, comparisons of their effects on molecular regulation are valuable for our understanding of common, fundamental, or core aging and longevity mechanisms.

A module of a biological system can be represented as a molecular network where nodes and edges correspond to biomolecules (e.g., gene transcripts, proteins, and metabolites) and relationships (e.g., physical interactions, chemical reactions), respectively. For each sample, ranks of biomolecules can be obtained from experimental data by ordering the values of interest (e.g., abundances, levels of specific post-translational modification) between the biomolecules within a module. When these ranks are highly conserved among the samples within a population of a specific phenotype, the module is considered tightly regulated in the population, because biological regulatory mechanisms or pressures must act consistently across the samples to produce this high conservation pattern. In contrast, low rank conservation among the samples within a phenotype indicates loose module regulation in the population.

In this study, we report systemic changes in the molecular regulation of biological processes under multiple lifespan-extending interventions, by jointly leveraging systems-level analyses on two mouse liver proteomic datasets, which were generated in the NIA Longevity Consortium, and a previously published mouse liver transcriptomic dataset. Differential Rank Conservation (DIRAC) analyses of mouse liver proteomics and transcriptomics data show that mechanistically distinct lifespan-extending interventions (acarbose, 17α-estradiol, rapamycin, and calorie restriction) generally tighten the regulation of biological modules. These tightening patterns are similar across the interventions, particularly in processes such as fatty acid oxidation, immune response, and stress response.