Evidence map›Paper›PMID 41219961›Full record

ArticleBMC medicine2025

Expanded mosaic chromosomal alterations, frailty, and risks of all-cause and cause-specific mortality among Chinese and the UK adults: evidence from two prospective cohorts.

Mingyu Song, Zilun Shao, Yuting Han, Yuxuan Zhao, Jun Lv, Canqing Yu, Pei Pei, Ling Yang, Iona Y Millwood, Robin G Walters and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2025. 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

21 authors.

Mingyu SongDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Zilun ShaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Yuting HanDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Yuxuan ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Pei PeiPeking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China.
Ling YangClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Iona Y MillwoodClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Robin G WaltersClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Yiping ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Huaidong DuClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Xiaoming YangClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Mengwei WangNon-communicable Diseases Prevention and Control Department, Henan Provincial Center for Disease Control and Prevention, Zhengzhou, Henan, China.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, China.
Zhengming ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Giulio GenoveseProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Chikashi TeraoLaboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Dianjianyi SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China. dsun1@bjmu.edu.cn.
China Kadoorie Biobank Collaborative Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMosaic chromosomal alterations (mCAs) served as a novel indicator of genomic aging. We aimed to investigate the association of expanded mCAs (cell fraction ≥ 10%) with all-cause and cause-specific mortality, and to examine the joint effect of expanded mCAs and frailty index (FI), an indicator of phenotypic aging, on mortality in two large prospective cohorts.

methodsA total of 100,237 participants in the China Kadoorie Biobank (CKB) and 456,283 participants in the UK Biobank (UKB) were included, followed till Dec 31, 2023, and Nov 30, 2022, respectively. MoChA pipeline was used to detect expanded mCAs events and the subtypes. FIs were calculated using previously validated equations, with 28 items included in the CKB and 49 items in the UKB, and categorized participants into three groups: robust, prefrail, and frail. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated to examine the associations of the expanded mCAs and joint categories of frailty-mCAs with all-cause and cause-specific mortality by using Cox proportional hazards models. The combined effect values of two cohorts were estimated using random-effects models by meta-analysis.

resultsThe prevalence of expanded mCAs in the CKB and UKB was 2.2% and 3.4%, respectively. After a median follow-up of 17.2 years in the CKB and 13.7 years in the UKB, expanded mCAs carriers had a higher risk of all-cause (HRs [95% CIs]: 1.20 [1.16, 1.24]) and risks of cause-specific mortality (HRs [95% CIs]: 1.27 [1.21, 1.34], 1.13 [1.02, 1.25], and 1.24 [1.12, 1.37] for death from cancers, circulatory diseases, and respiratory diseases, respectively). Such associations largely did not overlap with FI, especially for all-cause and cancer mortality. Joint analyses revealed that individuals with lower frailty level but with expanded mCAs had a comparable and even higher risk of cancer mortality compared to those with higher frailty level but without mCAs. Similar pattern was also found in terms of adjusted 10-year cancer mortality rates.

conclusionsOur findings suggested that expanded mCAs were significantly associated with all-cause and cause-specific deaths and could serve as a complement to the FI in providing a more comprehensive perspective on mortality risk, especially for cancer mortality.

Indexed as

Chromosome AberrationsFrailtyMosaicismAdultAgedAged, 80 and overCause of DeathChinaEast Asian PeopleFemaleHumansMaleMiddle AgedProspective StudiesRisk FactorsUnited KingdomAll-cause deathCause-specific deathFrailty indexMosaic chromosomal alterationsProspective cohort study

Identifiers

PMID41219961
PMCPMC12607034

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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.