Plasma proteomics-based organ-specific aging for all-cause mortality and cause-specific mortality: a prospective cohort study

doi:10.1007/s11357-024-01411-w

. 2024 Oct 31.

doi: 10.1007/s11357-024-01411-w. Online ahead of print.

Plasma proteomics-based organ-specific aging for all-cause mortality and cause-specific mortality: a prospective cohort study

Renjia Zhao¹, Heyang Lu², Huangbo Yuan¹, Shuaizhou Chen³, Kelin Xu^{4

5}, Tiejun Zhang^{3

4

5}, Zhenqiu Liu^{1

5}, Yanfeng Jiang^{1

5}, Chen Suo^{6

7

8}, Xingdong Chen^{9

10

11

12}

Affiliations

¹ State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Science, Fudan University, Songhu Road 2005, Shanghai, China.
² Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
³ Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
⁴ Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China.
⁵ Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China.
⁶ Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China. suochen@fudan.edu.cn.
⁷ Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China. suochen@fudan.edu.cn.
⁸ Shanghai Institute of Infectious Disease and Biosecurity, Shanghai, China. suochen@fudan.edu.cn.
⁹ State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Science, Fudan University, Songhu Road 2005, Shanghai, China. xingdongchen@fudan.edu.cn.
¹⁰ Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China. xingdongchen@fudan.edu.cn.
¹¹ Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China. xingdongchen@fudan.edu.cn.
¹² National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China. xingdongchen@fudan.edu.cn.

PMID: 39477866
DOI: 10.1007/s11357-024-01411-w

Plasma proteomics-based organ-specific aging for all-cause mortality and cause-specific mortality: a prospective cohort study

Renjia Zhao et al. Geroscience. 2024.

. 2024 Oct 31.

doi: 10.1007/s11357-024-01411-w. Online ahead of print.

Authors

Renjia Zhao¹, Heyang Lu², Huangbo Yuan¹, Shuaizhou Chen³, Kelin Xu^{4

5}, Tiejun Zhang^{3

4

5}, Zhenqiu Liu^{1

5}, Yanfeng Jiang^{1

5}, Chen Suo^{6

7

8}, Xingdong Chen^{9

10

11

12}

Affiliations

¹ State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Science, Fudan University, Songhu Road 2005, Shanghai, China.
² Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
³ Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
⁴ Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China.
⁵ Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China.
⁶ Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China. suochen@fudan.edu.cn.
⁷ Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China. suochen@fudan.edu.cn.
⁸ Shanghai Institute of Infectious Disease and Biosecurity, Shanghai, China. suochen@fudan.edu.cn.
⁹ State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Science, Fudan University, Songhu Road 2005, Shanghai, China. xingdongchen@fudan.edu.cn.
¹⁰ Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China. xingdongchen@fudan.edu.cn.
¹¹ Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China. xingdongchen@fudan.edu.cn.
¹² National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China. xingdongchen@fudan.edu.cn.

PMID: 39477866
DOI: 10.1007/s11357-024-01411-w

Abstract

Individual's aging rates vary across organs. However, there are few methods for assessing aging at organ levels and whether they contribute differently to mortalities remains unknown. We analyzed data from 45,821 adults in the UK Biobank, using plasma proteomics and machine learning to estimate biological ages for 12 major organs. The differences between biological age and chronological age, referred to as "age gaps," were calculated for each organ. Partial correlation analyses were used to assess the association between age gaps and modifiable factors. Adjusted multivariable Cox regression models were applied to examine the association of age gaps with all-cause mortality, cause-specific mortalities, and cancer-specific mortalities. We reveal a complex network of varied associations between multi-organ aging and modifiable factors. All age gaps increase the risk of all-cause mortality by 6-60%. The risk of death varied from 5.54 to 29.18 times depending on the number of aging organs. Cause-specific mortalities are associated with certain organs' aging. For mental diseases mortality, and nervous system mortality, only brain aging exhibited a significant increased risk of HR 2.38 (per SD, 95% CI: 2.06-2.74) and 1.99 (per SD, 95% CI: 1.84-2.16), respectively. Age gaps of stomach were also a specific indicator for gastric cancer. Eventually, we find that an organ's biological age selectively influences the aging of other organ systems. Our study demonstrates that accelerated aging in specific organs increases the risk of mortality from various causes. This provides a potential tool for early identification of at-risk populations, offering a relatively objective method for precision medicine.

Keywords: All-cause mortality; Biological age; Precision medicine; Proteomics.

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References

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[1] Codd V, et al. Polygenic basis and biomedical consequences of telomere length variation. Nat Genet. 2021;53(10):1425–33. - DOI - PubMed - PMC

[2] Codd V, et al. Polygenic basis and biomedical consequences of telomere length variation. Nat Genet. 2021;53(10):1425–33. - DOI - PubMed - PMC

[3] Dempsey PC, et al. Investigation of a UK biobank cohort reveals causal associations of self-reported walking pace with telomere length. Commun Biol. 2022;5(1):381. - DOI - PubMed - PMC

[4] Dempsey PC, et al. Investigation of a UK biobank cohort reveals causal associations of self-reported walking pace with telomere length. Commun Biol. 2022;5(1):381. - DOI - PubMed - PMC

[5] Bell CG, et al. DNA methylation aging clocks: challenges and recommendations. Genome Biol. 2019;20(1):249. - DOI - PubMed - PMC

[6] Bell CG, et al. DNA methylation aging clocks: challenges and recommendations. Genome Biol. 2019;20(1):249. - DOI - PubMed - PMC

[7] Duan R, et al. Epigenetic clock: A promising biomarker and practical tool in aging. Ageing Res Rev. 2022;81:101743. - DOI - PubMed

[8] Duan R, et al. Epigenetic clock: A promising biomarker and practical tool in aging. Ageing Res Rev. 2022;81:101743. - DOI - PubMed

[9] Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:1–20. - DOI

[10] Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:1–20. - DOI

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Plasma proteomics-based organ-specific aging for all-cause mortality and cause-specific mortality: a prospective cohort study

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Plasma proteomics-based organ-specific aging for all-cause mortality and cause-specific mortality: a prospective cohort study

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