Evidence map›Paper›PMID 42687813›Full record

ArticleInternational journal of rheumatic diseases2026

Cross-Sectional and Longitudinal Association Between Biological Aging Acceleration and the Risk of Osteoarthritis: A Cohort Study From UK Biobank.

Sisi Liu, Weishu Wang, Chengxu Li, Yuxin Lai, Zhounan Zhou, Menglin Han, Yujie Zhang, Yan Zhang, Ke Tang, Haitao Sun and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of rheumatic diseases, 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Sisi LiuClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0006-3610-4743
Weishu WangClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0006-8897-0731
Chengxu LiClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Yuxin LaiClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0002-7387-8941
Zhounan ZhouClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0000-9662-2469
Menglin HanClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0009-6370-7277
Yujie ZhangDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0002-0702-8298
Yan ZhangClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0001-9126-4922
Ke TangDepartment of Orthopedics, 904th Hospital of the PLA Joint Logistic Support Force, Wuxi, Jiangsu, China.
Haitao SunClinical Biobank Center, Microbiome Medicine Center, Department of Laboratory Medicine, Guangdong Provincial Clinical Research Center for Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0001-7925-9506
Qian YangMRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK.ORCID https://orcid.org/0000-0001-8778-4132
Muhui ZengClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0002-4347-3495
Tianxiang FanClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0008-4972-1868
Zhong Alan LiDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, P.R. China.ORCID https://orcid.org/0000-0002-6009-629X
GO Consortium
Changhai DingClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0002-9479-730X
David J HunterClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0003-3197-752X
Zhaohua ZhuClinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0003-3913-2564

Funding

National Natural Science Foundation of China 82372428
6 · The paper itself

Abstract

objectiveTo evaluate the relationship between biological ages and the prevalence and incidence of osteoarthritis (OA).

methods332 261 participants from UK Biobank were analyzed. Biological aging was measured using phenotypic age (PhenoAge) and Klemera-Doubal (KDMAge). KDMAge was derived from nine clinical biomarkers to gauge system integrity decline, while PhenoAge was computed from chronological age and nine clinical biomarkers to gauge mortality risk. Biological aging accelerations were computed as residuals from regressing KDMAge and PhenoAge against chronological age. The associations between biological aging and prevalence and incidence of OA were analyzed using logistic and Cox regression models.

resultsAt baseline, 55.4% of included individuals had younger PhenoAge aging acceleration. In cross-sectional analyses, individuals with accelerated aging had higher odds of OA compared to those with non-accelerated aging (odds ratios [OR]: 1.12 [95% CI: 1.09-1.14] for PhenoAge acceleration and 1.05 [1.03-1.08] for KDMAge acceleration). In the longitudinal analyses, increased PhenoAge acceleration was associated with a higher risk of incident OA (hazard ratios [HR]: 1.12 [1.10-1.15]). However, the association between KDMAge acceleration and the incidence of OA was not statistically significant (HR: 0.99 [0.97-1.01]). Accelerated biological aging showed a more pronounced association with OA among individuals > 60 years. No additive or multiplicative interactions were found between OA polygenic risk score (PRS) and biological aging.

conclusionAdvanced biological aging may increase the risk of OA, independent of OA genetic risk, particularly in individuals aged over 60 years. The two biological aging indicators hold potential as novel composite clinical biomarkers, directing prevention and intervention strategies for high-risk populations for OA.

Indexed as

AgingOsteoarthritisAgedAge FactorsBiological Specimen BanksBiomarkersCross-Sectional StudiesFemaleHumansIncidenceLongitudinal StudiesMaleMiddle AgedPhenotypePrevalenceRisk AssessmentBiomarkersagingbiological ageosteoarthritis

Identifiers

PMID42687813
PMCPMC13539371

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