Evidence map›Paper›PMID 42378240›Full record

ArticlePloS one2026

Somatic mutation profiles in aged military nuclear test veterans: A comparative whole-genome sequence study.

Justin Ofosu-Dankwa, Cristina Sisu, Rhona M Anderson

Abstract readComparative Study
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Justin Ofosu-DankwaCentre for Health Effects of Radiological and Chemical Agents, Uxbridge, England.
Cristina SisuCentre for Health Effects of Radiological and Chemical Agents, Uxbridge, England.
Rhona M AndersonCentre for Health Effects of Radiological and Chemical Agents, Uxbridge, England.ORCID https://orcid.org/0000-0003-2258-656X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Veterans of the British nuclear testing programme represent an aged group of ex-military personnel who may have been exposed to ionising radiation through their participation at nuclear testing sites. This study aimed to compare the somatic mutational landscape of a cohort of 30 nuclear test veterans with that of an age-matched cohort of 30 control veterans. Variants were identified from publicly available whole-genome sequencing data using a bioinformatics pipeline developed in accordance with the gold standard approaches as defined by the Broad Institute. The resulting set of raw SNV and INDEL variants for each individual veteran were subjected to several filtering steps to reduce the noise arising from common mutations, before the average number and types were compared for each cohort using the Grubbs test. The genomic distribution of these variants was also examined by assessing for any mutation clustering considered characteristic of radiation exposure (SNVs and/or INDELs occurring within 10 bp) using a 10 bp running window and separately, the identification of mutational signatures by fitting SNVs to the COSMIC database Human Cancer v3.4. When comparing the nuclear test veteran and control cohorts, we found no statistically elevated frequency of any variant type or clusters. The dominant SBS signatures in both cohorts were those typically associated with ageing. A qualitative assessment of the functional impact of the most prevalently observed variants in each cohort showed these to also be associated with age. For example, in the control cohort, variants were found in LINC02098-ETS1 and RCL1, genes linked to classic age-related conditions such as hair loss and osteoarthritis. In the nuclear test veteran cohort, we observed multiple variants affecting the CHODL gene in approximately 40% of participants. CHODL encodes chondrolectin, a protein important for maintaining the structural integrity and function of tissues. In conclusion, the absence of significant genetic differences between cohorts, together with the prevalence of age-associated mutations, is consistent with ageing being one of the primary drivers of the observed somatic variation in these veterans, overshadowing any potential environmental, including historical radiation, effects.

Indexed as

MutationVeteransWhole Genome SequencingAgedGenome, HumanHumansINDEL MutationMaleMiddle AgedMilitary Personnel

Identifiers

PMID42378240
PMCPMC13318011

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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.