Human Ageing Genomic Resources: 2018 Update

Abstract

In spite of a growing body of research and data, human ageing remains a poorly understood process. To facilitate studies of ageing, over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), which are now the leading online resource for biogerontologists. In this update, we present HAGR's main functionalities, including new additions and improvements to HAGR. HAGR consists of five databases: 1) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; 2) the AnAge database of animal ageing and longevity, featuring >4000 species; 3) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; 4) the LongevityMap database of human genetic association studies of longevity with >500 entries; 5) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; 6) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts to ensure a high quality data and presented in an intuitive and clear interface that includes cross-links across our databases and to external resources. HAGR is freely available online (http://genomics.senescence.info/).

Gene Expression-Based Drug Repurposing to Target Ageing

“…The fact that we successfully re-discovered a statistically significant number of known lifespan modulators, without using any prior drug ageing information, suggests that the other drugs that we identified also have a high potential to be modulators of the ageing process / lifespan. Eleven of these had targets implicated in ageing, based on GenAge database (Tacutu et al, 2017). These targets include extensively studied ageingmodulators such as PI3K subunits and histone deacetylases.…”

“…For the cases where the database entries are manually curated and consistent, we used CHEMBL (Bento et al, 2014), DrugBank (Law et al, 2014), and PubChem (Kim et al, 2016). We downloaded GenAge model organism and human datasets (Tacutu et al, 2017) on 10 th October 2017 using GenAge website. Using the human orthologues for the model organisms (genage_models_orthologs_export.tsv) and the human dataset, we asked if any of the drug targets were previously shown to be implicated in ageing.…”

F1F0ATP Hydrolysis is a Determinant of Metabolic Rate, a Correlate of Lifespan, and a Weakness of Cancer

“…A prediction atop of Figure 1, for future testing, is that if the ambient temperature was instead at the mouse's normal body temperature (around 37°C [5]), or safely higher, then no body temperature drop would occur. Even at high drug doses.…”

“…This F1F0 ATP hydrolysis data was sourced from [29] (column titled "Ischemic" in its Table 1), along with its heart rate and body mass data therein. Maximum lifespan data was sourced from the AnAge database [5]. Specific basal metabolic rate data herein, for each cited species, is the mean of values for that species sourced from AnAge [5] and the landmark papers by Max Kleiber in 1932 and 1947 [36][37], which set out Kleiber's Law.…”

“…Maximum lifespan data was sourced from the AnAge database [5]. Specific basal metabolic rate data herein, for each cited species, is the mean of values for that species sourced from AnAge [5] and the landmark papers by Max Kleiber in 1932 and 1947 [36][37], which set out Kleiber's Law. But the specific basal metabolic rate of rat value from [37] was omitted from this mean, because its value is not from an adult.…”