The GENtervention Database: Gene Expression Profiles for Interventions that Slow Aging

Vadim Gladyshev's team has put online the new GENtervention database that shows gene expression profile data for mouse livers, assessed across a range of interventions known to slow aging in that species. Since many or even near all these interventions work through a similar collection of stress response and cellular maintenance mechanisms, such as macroautophagy, proteasomal function, and so forth, there are many commonalities in the profiles. The paper is not open access, though the usual approaches work if you want to read it, but the database is freely available.

We collected and characterized RNA-seq data on several lifespan-extending interventions, including three that had never been analyzed at the level of gene expression, across sexes, doses, and age groups. We observed a significant feminizing pattern of gene expression changes in males in response to genetic and dietary interventions at both transcriptomic and metabolomic levels. This effect was associated with perturbations of common genes and molecular pathways including those regulated by growth hormone. The feminizing effect could not explain lifespan extension but was associated with the diminution of sex-associated differences pointing to the converging effect of lifespan-extending interventions on hepatic transcriptome and metabolome across sexes.

Expanding this analysis with available microarray data allowed us to define gene expression signatures associated with individual interventions (rapamycin, calorie restriction, and growth hormone deficiency) as well as shared across longevity interventions. We observed that despite some differences, most of them perturb similar genes and pathways, including upregulation of xenobiotic metabolizing enzymes regulated by NRF2, TCA cycle, oxidative phosphorylation, and ribosome protein genes and downregulation of complement and coagulation cascades. Many of these functions turned out to be affected across tissues. Moreover, some genes involved in stress response, apoptosis, glucose metabolism, and immune response, as well as certain pathways, such as oxidative phosphorylation, were found to be commonly perturbed across interventions and, at the same time, associated with the degree of lifespan extension effect, serving as both qualitative and quantitative predictors of longevity. These genes and processes seem to be most persistent and reliable determinants of longevity in mice and deserve further exploration. We further developed a publicly available web application GENtervention that can be used to interrogate this dataset.

Finally, we employed gene expression signatures to identify new lifespan-extending interventions based on gene expression data. Here, our algorithm could distinguish two mouse strains of the same age with different expected lifespans. We have also found that hypoxia and hepatocyte-specific Keap1 knockout are positively associated with longevity signatures at the level of gene expression, and therefore appear to be strong candidates for experimental validation. In addition, we demonstrated the applicability of this method to predict new candidate lifespan-extending compounds and validated the detected positive association of gene expression induced by mTOR inhibitor KU-0063794 and ascorbyl-palmitate, making them appealing candidates for further investigation and survival studies.


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