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Genomics· 16-page report· 4 figures

Longevity Gene Analysis

Map model organism longevity genes to human orthologs and evaluate their validation through GWAS studies.

What this research found

Genes that extend lifespan in worms, flies, and mice are the backbone of aging research, but how many of them have any human genetic backing? Fifty top longevity genes from the GenAge database were mapped to human orthologs, cross-checked against the GWAS Catalog, and then scored on network centrality, druggability, and clinical-trial activity. Seventy-four percent fall short: 37 of the 50 either have no clear human ortholog or have one with zero genome-wide significant associations for longevity-relevant traits, and no gene scored above 57.9 out of a possible 100.

  • The translation gap is 37 of 50 genes, or 74.0%. Twenty genes (40.0%) have no clear human ortholog at all, and another 17 (34.0%) have an ortholog with no genome-wide significant association for longevity-relevant traits. Only 13 genes (26.0%) clear both bars.
  • Orthology is the smaller obstacle. Of the 30 genes that did map to a human ortholog, 13 (43.3%) had supporting associations, so most of the loss happens at the human-genetics step rather than the mapping step.
  • Translation rates differ by source organism: the gap is 24 of 31 genes (77.4%) for Caenorhabditis elegans and 13 of 17 (76.5%) for Drosophila melanogaster, while both of the two Mus musculus genes were validated.
  • Mitochondrial energy metabolism dominates the top of the ranking. Four of the five highest-scoring genes — CYC1, TUFM, CYCS, and SDHB — are mitochondrial proteins, and mitochondrial proteins also make up most of the 7 genes (14.0%) that qualify as protein-interaction network hubs.
  • Scores are low almost everywhere: the mean total score is 16.9 out of 100 and the median is 14.1. The top-ranked gene, AGE-1 mapping to human PIK3C2G at 57.9, earned only 10 of 25 available human-genetics points and has zero aging-relevant associations; its rank comes from a 1000% lifespan extension in C. elegans plus a maximal druggability score.
  • Existing drugs already hit 21 of the 50 genes (42.0%), largely kinase inhibitors such as imatinib and trametinib at Phase 4, yet only one gene, CYCS, has aging-related clinical trials — 10 of them.

How it was done

Fifty top longevity genes from GenAge were mapped to human orthologs through Ensembl, then checked against the GWAS Catalog for genome-wide significant associations at p < 5e-8 across longevity and parental lifespan, cardiovascular disease, neurodegeneration, cancer, and metabolic traits. STRING supplied the protein interaction network for hub and degree-centrality analysis, DrugBank and ChEMBL supplied drug-target and bioactivity data, and ClinicalTrials.gov supplied trial status. A 0 to 100 translation score combined five min-max-normalised components: lifespan effect in the model organism (25 points), human genetic evidence (25), network centrality (20), druggability (20), and active clinical trials (10). The result was a ranked scorecard covering all 50 genes, detailed dossiers for the top 20, and a 16-page manuscript with 30 verified citations and five figures.

Data sources

  • GenAge — top 50 model organism longevity genes (31 Caenorhabditis elegans, 17 Drosophila melanogaster, 2 Mus musculus)
  • GWAS Catalog — genome-wide significant associations at p < 5e-8 for longevity, cardiovascular, neurodegenerative, cancer, and metabolic traits
  • Ensembl — human ortholog mapping and confidence calls
  • STRING — protein-protein interaction network
  • DrugBank and ChEMBL — drug target and compound bioactivity data
  • ClinicalTrials.gov — aging-related trial status

Limitations

The gene set is small — 50 genes, only two of them from mouse — so the per-organism translation rates rest on very few observations. A gene counts as unvalidated whenever the catalog holds no genome-wide significant hit in the chosen trait categories, which reflects what has been studied in humans as much as the gene's actual role in lifespan.

Figures from this analysis

How this research was produced

K-Dense Web planned and ran this genomics investigation end to end — gathering the sources, carrying out the analysis, producing the figures, and drafting the report. The full session transcript, including every intermediate step, is available to view.

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