AgingHallmarksDB: a web resource linking 11 aging hallmarks to 3111 genes
The abstract describes AgingHallmarksDB, a web platform for systems-level aging research built on 11 aging hallmarks and 3111 hallmark-associated genes, with example analyses of gene overlap, networks, diseases and a PM2.5 exposure skin dataset. [1]
Automatic summary · not editorially reviewed
The key findings
AgingHallmarksDB is described as an interactive web platform for systems-level aging research centered on 11 aging hallmarks, containing 3111 hallmark-associated genes from seven databases and a 1089-gene consensus set. [1]
Gene overlaps and Jaccard similarity showed interconnectedness among hallmarks, and network topology analysis found key age-associated genes acting as central hubs across multiple hallmarks. [1]
Gene set enrichment analysis of a PM2.5 exposure-associated skin transcriptome showed significant enrichment of aging hallmarks, particularly epigenetic alterations. [1]
The source at a glance
- Study type / format
- Database/resource description with example analyses (abstract)
- Population / context
- AgingHallmarksDB resource: 3111 hallmark-associated genes, a 1089-gene consensus set, and example analyses including a PM2.5 exposure-associated skin transcriptome.
- Summary based on
- Study abstract
- Original publication
- October 7, 2026
Platform built on 11 hallmarks and 3111 genes
According to the abstract, AgingHallmarksDB is an interactive web platform for systems-level aging research centered on 11 aging hallmarks. It contains 3111 aging hallmark-associated genes integrated from seven established databases, including a high-confidence consensus set of 1089 genes. It also incorporates tissue, cell-type class, exosomes, protein-protein and regulatory interactions. The abstract does not report how genes were assigned to hallmarks or how the consensus set was defined.
Supporting source [1]
Overlap, network hubs and disease enrichment examples
The abstract reports that gene overlaps and Jaccard similarity showed interconnectedness among the hallmarks, and network analyses showed these pairs are connected within the protein-protein interaction network. Network topology analysis of common hallmark genes revealed several key age-associated genes acting as central hubs across multiple hallmarks. Hallmark enrichment analyses showed extensive coverage across aging-related diseases compared with limited enrichment in non-aging-related diseases such as developmental and congenital diseases. Examples given include "Loss of proteostasis" in Alzheimer's disease and "Chronic inflammation" in atherosclerosis as highly significant hallmarks, supported by network proximity analyses. These are associations, not evidence of cause.
Supporting source [1]
PM2.5 skin dataset example and abstract-only scope
The abstract states that gene set enrichment analysis of a PM2.5 exposure-associated skin transcriptome identified significant enrichment of aging hallmarks, particularly "Epigenetic alterations", showing the resource's utility in interpreting transcriptomic datasets in the context of aging biology. The abstract presents the platform as a framework for investigating hallmark-associated functionality and potential therapeutic discovery in aging and longevity; this is a stated aim, not a demonstrated treatment. Only the abstract was reviewed; the full text was not reviewed, so methods, thresholds and validation details are unknown.
Supporting source [1]
How to interpret this
Abstract only; the full text was not reviewed. Methods, gene-assignment rules, thresholds and validation are not reported in the abstract. Reported disease and dataset links are associations, not causal findings, and no treatment benefit is demonstrated.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Tiwari R, Balaji M, Chivukula N, Sil P, Samal A. · europepmc.org · October 7, 2026