Evidence map›Paper›PMID 41023390›Full record

ArticleCommunications medicine2025

Decoding sexually dimorphic proteomic landscapes in the context of aging and mortality.

Zhihao Jin, Bingying Du, Xuehao Jiao, Zhengsheng Gu, Tianren Wang, Li Cao, Xiaoying Bi, Lei Yuan, Bo Peng, Yanxia Rao

Abstract read
PubMed Full text at PMC Publisher
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

10 authors.

Zhihao Jin *Department of Neurology, Zhongshan Hospital, Laboratory Animal Center, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0005-7007-0199
Bingying Du *Department of Neurology, Zhongshan Hospital, Laboratory Animal Center, Fudan University, Shanghai, China.
Xuehao JiaoDepartment of Neurology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.
Zhengsheng GuDepartment of Neurology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.
Tianren WangDepartment of Neurology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.
Li CaoKey Laboratory of Molecular Neurobiology, Ministry of Education, Navy Military Medical University, Shanghai, China.
Xiaoying BiDepartment of Neurology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.
Lei YuanDepartment of Health Management, Faculty of Military Health Service, Naval Medical University, Shanghai, China. yuanleigz@163.com.ORCID http://orcid.org/0000-0001-9069-9481
Bo PengNational Children's Medical Center, Children's Hospital, Institute for Translational Brain Research, State Key Laboratory of Brain Function and Disorders, MOE Frontiers Center for Brain Science, MOE Innovative Center for New Drug Development of Immune Inflammatory Diseases, Shanghai Key Laboratory of Gene Editing and Cell Therapy for Rare Diseases, Fudan University, Shanghai, China. peng@fudan.edu.cn.ORCID http://orcid.org/0000-0003-4183-5939
Yanxia RaoDepartment of Neurology, Zhongshan Hospital, Laboratory Animal Center, Fudan University, Shanghai, China. yanxiarao@fudan.edu.cn.ORCID http://orcid.org/0000-0001-5292-2056

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAging-associated changes are major contributors to the onset and progression of chronic diseases. Different aging clocks have been developed to assess biological aging, demonstrating their utility in predicting mortality, diagnosing disease, and evaluating the efficacy of antiaging interventions. However, the protein profile underlying the accelerating or decelerating rates of aging, hidden behind aging clocks, remains poorly understood.

methodBased on the UK Biobank (n = 53, 013; age range 39-71 years; 53.9% men and 46.1% women), we built a proteomic-based aging clock, ProteAge, and assessed its performance in predicting all-cause mortality. Sex-specific aging trajectories and aging rate-associated proteins (ARPs) were identified.

resultsProteAge reveals distinct aging trajectories for males and females, with females exhibiting more nonlinear changes in the aging rate than males do. We identify hundreds of accelerating and decelerating aging rate proteins (ARPs) in both sexes. Given the critical role of mortality prediction in aging and longevity research, we identify a subset of mortality-aging-associated proteins among ARPs, with a total of 1 protein in females but 172 in males. Furthermore, the protective and risk factors in both sexes are identified based on these ARPs.

conclusionsThese findings highlight sexually-dimorphic proteomic changes associated with aging and mortality, offering insights into the biological mechanisms underlying aging and longevity.

Identifiers

PMID41023390
PMCPMC12479788

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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.