Fight Aging!

The degree to which interventions targeting different mechanisms associated with longevity might stack or synergize to produce greater gains is a woefully understudied topic. Study of synergies between treatment approaches is in general poorly studied and poorly developed throughout the medical biotechnology community; the incentives in place discourage this sort of work at every level of development. Funding is sparse, and different groups holding intellectual property for different approaches tend not to cooperate with one another. Thus, thirty years in to the modern study of interventions that can extend longevity in laboratory species, whether or not the scores of different approaches synergize, and to what degree, remains largely unexplored and unknown.

For what it is worth, it does seems unlikely that combining three or more marginal effects based on stress response upregulation will produce an outcome worth caring about. Equally, many of the diverse mechanisms demonstrated to modestly slow aging in animal models are just different ways of influencing the same underlying system, and shouldn't be expected to produce synergies. Nonetheless, this area of study is criminally neglected, and this will become ever more an issue as the first narrow rejuvenation therapies are developed, approaches that repair specific forms of underlying damage that are causative of aging, and can thus produce sizable benefits. As an example of one of the few projects of recent years to focus on the foundations needed to discover and develop combinatorial therapies, researchers here establish a database of reported interactions between longevity-associated genes.

SynergyAge

The main goal of the SynergyAge database is to host high-quality, manually curated information about the synergistic and antagonistic lifespan effects of genetic interventions in model organisms. Although our group aims to better understand human aging, data on the effect of multiple genetic manipulations in humans is inexistent (for obvious reasons). As such, SynergyAge relies on reporting combinations of genetic manipulations from model organisms only.

Currently three organisms are included, worms, flies and mice, with data curated so far coming mostly from worms. This bias is mainly due to a easier methodology of modulating gene expression in worms (e.g. through RNAi) but also due to lifespan screening in worms being much faster (worms live much less and are a friendly model for this type of studies). All entries in SynergyAge are based on experimentally validated results from peer-reviewed scientific literature and are manually extracted by our database curators.

SynergyAge: a curated database for synergistic and antagonistic interactions of longevity-associated genes

Interventional studies on genetic modulators of longevity have significantly changed gerontology. While available lifespan data is continually accumulating, further understanding of the aging process is still limited by the poor understanding of epistasis and of the non-linear interactions between multiple longevity-associated genes. Unfortunately, based on observations so far, there is no simple method to predict the cumulative impact of genes on lifespan. As a step towards applying predictive methods, but also to provide information for a guided design of epistasis lifespan experiments, we developed SynergyAge - a database containing genetic and lifespan data for animal models obtained through multiple longevity-modulating interventions.

The studies included in SynergyAge focus on the lifespan of animal strains which are modified by at least two genetic interventions, with single gene mutants included as reference. SynergyAge provides an easy to use web-platform for browsing, searching and filtering through the data, as well as a network-based interactive module for visualization and analysis.