AgingHallmarksDB: Mapping the Genes and Networks Behind the Hallmarks of Aging

Using functional annotations, the researchers mapped 3,111 genes to 11 of the 12 established Hallmarks of Aging.

Of these, 2,593 genes had additional experimental or manually curated supporting evidence.

A more stringent group of 1,089 consensus aging-related genes was also identified. These genes appeared in at least two of the seven aging-related resources used by the researchers.

The platform deliberately provides gene sets with different levels of evidence, allowing researchers to choose more inclusive or more stringent criteria depending on the analysis.

One hallmark — dysbiosis — was not assigned genes.

The authors reported that currently available human-relevant functional annotations were insufficient for reliable gene assignment to this hallmark.

This means that AgingHallmarksDB currently represents 11 rather than all 12 Hallmarks of Aging.

One of the central findings was that the hallmarks did not appear as isolated biological units.

Network separation and proximity analyses demonstrated substantial functional interconnectedness between hallmark-associated gene modules within the human molecular interaction network.

Epigenetic alterations showed particularly strong connections with:

* genomic instability, * cellular senescence, * stem cell exhaustion.

By comparison, telomere attrition showed strong network interconnectedness primarily with cellular senescence and genomic instability.

These findings support a systems-level view of aging in which different hallmarks interact through shared molecular mechanisms.

Rather than representing twelve independent causes of aging, the hallmarks appear to form parts of a broader interconnected biological network.

The researchers also examined genes associated with multiple hallmarks.

Network analysis identified several highly connected genes and regulatory molecules.

Examples included UBC, TP53, AKT1 and members of the MAPK signalling family.

These genes participate in important biological processes such as DNA damage responses, cellular metabolism, nutrient sensing, inflammation and cellular senescence.

Their presence across multiple hallmarks illustrates how individual molecular regulators may connect different components of aging biology.

However, identifying a highly connected gene does not establish that it drives human aging or that targeting it therapeutically would slow aging.

The analysis identifies biologically interesting candidates for further investigation.

The researchers tested AgingHallmarksDB using gene sets from eight chronic age-related diseases and seven developmental and congenital diseases.

Age-related diseases showed substantially stronger associations with the Hallmarks of Aging than developmental and congenital diseases.

Specific patterns were biologically consistent with established disease mechanisms.

For example, Alzheimer’s disease showed a strong association with loss of proteostasis, reflecting disturbances in the maintenance and handling of proteins.

It was also associated with deregulated nutrient sensing, while network analysis supported a relationship with chronic inflammation.

Atherosclerosis showed a close association with chronic inflammation, consistent with the established role of inflammatory processes in atherosclerotic disease.

These analyses demonstrate how the platform can connect disease-associated genes with biological mechanisms of aging.

They do not establish that a particular hallmark causes the disease.

The researchers additionally analysed gene-expression changes in skin associated with exposure to fine particulate air pollution known as PM2.5.

The analysis identified significant associations with two Hallmarks of Aging:

* epigenetic alterations * chronic inflammation

Both mechanisms are biologically relevant to environmentally induced skin damage and aging.

This analysis illustrates how AgingHallmarksDB can be used not only to study diseases but also to investigate how environmental exposures may interact with molecular pathways associated with aging.

It does not demonstrate that PM2.5 exposure directly accelerates whole-body biological aging.