Evidence map›Paper›PMID 42050229›Full record

ArticleBiogerontology2026

Pleiotropy and disease interactors: the dual nature of genes linking ageing and ageing-related diseases.

Gustavo Daniel Vega Magdaleno, João Pedro de Magalhães

Abstract read
In one paragraph

Article in Biogerontology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Gustavo Daniel Vega MagdalenoIntegrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L78TX, UK.
João Pedro de MagalhãesIntegrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L78TX, UK. jp@senescence.info.

Funding

Wellcome TrustWellcome Trust 208375/Z/17/Z
6 · The paper itself

Abstract

Ageing-related diseases (ARDs) display diverse phenotypes yet share an age-dependent rise in incidence, suggesting mechanistic links with ageing processes. We examined whether ageing-related genes differ systematically from genes associated with multiple ARD clusters. Across 57 ARDs from UK Biobank, network analyses showed that ageing-related genes, although rarely ARD-associated, lie significantly closer to many ARDs through greater-than-chance proximity in protein-protein interaction (PPI) and KEGG networks. Consistent with this network overlap, ageing-related genes tend to occupy intermediate tiers in KEGG signalling cascades and exhibit strong coexpression with disease-associated genes as well as low tissue specificity, supporting that they play regulatory roles across multiple tissues. In contrast, genes associated with multiple ARDs are enriched for immune disorders and tend to have fewer ARD-associated neighbors in PPI networks. Accordingly, genes associated with multiple ARDs also tend to be located in terminal branches of KEGG pathways and show high tissue specificity coupled with weak coexpression with other ARD genes. Lastly, machine learning integration based on gene-disease network topology identified candidate ageing-related genes enriched for intracellular signal transduction and programmed cell death. Altogether, this work reveals two genetic architectures of multi-ARD influence: a cross-tissue regulatory mechanism enriched in ageing-related genes, and a tissue-specific, immune-driven mechanism among pleiotropic disease-related genes.

Indexed as

AgingGenetic PleiotropyGene Regulatory NetworksGenetic Predisposition to DiseaseHumansProtein Interaction MapsSignal TransductionUK BiobankCoexpressionLongevityMultimorbidityTissue specificity

Identifiers

PMID42050229
PMCPMC13124933

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.