An integrated resource for systems-level analysis of aging hallmarks and associated genes

ABSTRACT Aging is a complex biological process involving progressive cellular dysfunction, tissue decline, and increased susceptibility to multiple chronic diseases. A systemic view of aging through its established hallmarks provides a structured framework to understand this complexity and drive therapeutic discovery. Towards this, we present AgingHallmarksDB, an interactive web platform that enables systems-level analysis of hallmark-associated gene sets. Aging-related genes were first curated from seven established resources, and those present in at least 2 of these resources were considered as consensus aging-related genes. Using functional annotations derived from GO, KEGG, and Reactome, a total of 3111 genes were mapped to the 11 aging hallmarks, of which 2593 were supported by additional experimental or manually curated evidence, with 1089 of these forming the consensus set. Further, AgingHallmarksDB supplements gene annotations with tissue or cell type class specificity, exosomal profiles, and regulatory interactions. The platform allows users to interactively perform systems-level hallmark enrichment analysis across multiple condition-associated gene sets, while seamlessly integrating functional annotations and complex regulatory interactions to elucidate mechanistic hallmark-gene associations. The utility of the resource was explored through hallmark enrichment and network proximity analysis of gene sets corresponding to 11 chronic age-related diseases and PM2.5-associated skin transcriptome to explore relationships between aging hallmarks and disease mechanisms or environmental aging-related signatures. Overall, AgingHallmarksDB will support longevity research by enabling aging hallmark centered analysis, and the resource is accessible at https://cb.imsc.res.in/aginghallmarksdb/ .