Evidence map›Paper›PMID 41326677›Full record

ArticleCommunications medicine2025

Synergistic and heterogeneous aging using composite phenotypes and multiple organ systems aging clocks.

Yucan Li, Xinming Xu, Yi Zheng, Rui Li, Xin Zhang, Jiacheng Wang, Ningxin Gao, Jianming Wang, Yawen Wang, Jialin Li and 10 more

Abstract read
In one paragraph

Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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

20 authors.

Yucan LiState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-9778-9057
Xinming XuDepartment of Nutrition and Food Hygiene, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
Yi ZhengState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Rui LiDepartment of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
Xin ZhangDepartment of Biostatistics, School of Public Health, The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Jiacheng WangSchool of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Ningxin GaoDepartment of Biostatistics, School of Public Health, The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Jianming WangDepartment of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai, China.
Yawen WangDepartment of Biostatistics, School of Public Health, The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Jialin LiState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Jincheng LiState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Danke WangState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Zhenqiu LiuState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-5244-6894
Mei CuiDepartment of Neurology, Huashan Hospital, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-6449-8106
Yanfeng JiangState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Yingzhe WangDepartment of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
Chen SuoSchool of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-1908-8941
Tiejun ZhangSchool of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Kelin XuDepartment of Biostatistics, School of Public Health, The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China. xukelin@fudan.edu.cn.ORCID http://orcid.org/0000-0002-6788-4256
Xingdong ChenState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. xingdongchen@fudan.edu.cn.ORCID http://orcid.org/0000-0003-3763-160X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82304239
6 · The paper itself

Abstract

backgroundAssessing aging pace through biological age offers a precise perspective and underscores the need for further investigation into organ-level disparities.

methodsThis observational study utilized multi-scale phenotypes from the Taizhou Imaging Study, encompassing brain imaging, cognitive assessment, blood biochemistry, omics, and physical measures. A total of 904 individuals (403 men and 501 women) aged 55-65 years were included. Age correlations with single and composite phenotypes were assessed, and multi-modal aging clocks were developed, incorporating organ systems, cognition, and the whole body.

resultsHere we show that composite phenotypes, such as those of cardiovascular system and bone, alter with age progression and could serve as aging clock features. Despite existing connections among various organs' aging rates, their low intensity (under 0.25) indicates the variability of aging. Accelerated aging in the brain (mediating 12.46%, 95% CI: 4.37% to 24.44%) and kidneys (mediating 6.94%, 95% CI: 1.08% to 18.63%) partially mediates the relationship between smoking and the decline in olfactory identification. The diversity of organ aging is also evident as accelerated aging extends from the cardiovascular system to the kidneys and brain with increasing metabolic risk factors. Moreover, the biological ages of cardiovascular system, bone, metabolism, brain and the whole body show stronger associations with cardiovascular events risk than chronological age.

conclusionsThe overlap between composite phenotypes and biological age provides valuable insights into multi-phenotypic aging. The unearthing of the heterogeneity in aging processes could further inform the development of personalized interventions to slow organ-specific aging and better manage age-related health problems.

Identifiers

PMID41326677
PMCPMC12669247

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.