Evidence map›Paper›PMID 39415263›Full record

ArticleImmunity & ageing : I & A2024

Association between serum IgM and all-cause mortality risk in Chinese centenarians: a prospective cohort study.

Weiguang Zhang, Yuting Duan, Zhe Li, Yue Niu, Bin Wang, Zhe Feng, Ding Sun, Hao Li, Zehao Zhang, Zeyu Qu and 12 more

Abstract read
In one paragraph

Article in Immunity & ageing : I & A, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Multiorgan transcriptomics in mice identifies immunoglobulin heavy constant mu (Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Article
  5. 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

22 authors.

Weiguang Zhang *Department of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, 572013, China.
Yuting Duan *Department of Geriatric Medicine, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Zhe Li *Luoyang Key Laboratory of Clinical Multiomics and Translational Medicine, Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, College of Clinical Medicine of Henan, University of Science and Technology, Luoyang, 471003, China.
Yue NiuSenior Department of Nephrology, National Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, the First Medical Center of Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China.
Bin WangSenior Department of Nephrology, National Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, the First Medical Center of Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China.
Zhe FengSenior Department of Nephrology, National Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, the First Medical Center of Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China.
Ding SunDepartment of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, 572013, China.
Hao LiDepartment of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, 572013, China.
Zehao ZhangDepartment of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, 572013, China.
Zeyu QuDepartment of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, 572013, China.
Miao LiuInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Second Medical Center, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
Hongyan HuDepartment of Laboratory Medicine, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China.
Qiao ZhuCentral Laboratory, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China.
Yujian ChenCentral Laboratory, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China.
Chaoxue NingCentral Laboratory, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China.
Shihui FuDepartment of Cardiology, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China.
Shanshan YangDepartment of Disease Prevention and Control, First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
Shengshu WangInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Second Medical Center, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
Yali ZhaoCentral Laboratory, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China.
Yao HeInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Second Medical Center, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
Xiangmei ChenSenior Department of Nephrology, National Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, the First Medical Center of Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, National Clinical Research Center for Kidney Diseases, Beijing, 100853, China. xmchen301@126.com.
Yizhi ChenDepartment of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, 572013, China. yizchen@126.com.

Funding

Capital's Funds for Health Improvement and Research No. CFH 2024-1-5021National Key Research and Development Program of China No.2022YFC3602900National Natural Science Foundation of China No. 82270769Sanya science and technology innovation special project No. 2022KJCX02Science & Technology Project of Beijing No. Z221100007422121Specialized Project of Military Logistics Scientific Research and Health Care No. 21BJZ37Specific research fund of the Innovation Platform for Academicians of Hainan Province, Beijing Natural Science Foundation No.7242033
6 · The paper itself

Abstract

backgroundWe investigated the associations between IgM, IgG, IgA, and IgE levels and all-cause mortality risk in Chinese centenarians.

methodsAll participants were from the China Hainan Centenarian Cohort Study. Eligible participants were divided into quartiles based on their IgM, IgG, IgA, and IgE levels. We used restricted cubic spline analyses, Cox regression analyses, and Kaplan-Meier survival curves to analyze associations between IgM, IgG, IgA, and IgE and all-cause mortality risk.

resultsA total of 906 centenarian participants were included in this study (81.2% female; median age, 102 years). During a median follow-up of 30.1 months, 838 (92.5%) participants died. Restricted cubic spline analysis revealed a nonlinear relationship ("L" type) between serum IgM level and all-cause mortality. Compared with the higher three quartiles of serum IgM level, the lowest quartile was associated with a higher risk of death (Q1 versus Q2-Q4: HR, 1.365; 95% CI, 1.166-1.598; P < 0.001). Among individuals for whom IgM < 0.708 g/L (Q1), the risk of all-cause mortality was 36.5% higher. Kaplan-Meier analyses showed that centenarians with lower serum IgM levels had significantly shorter median survival time (Q1 versus Q2-Q4: 26 months versus 32 months, log-rank P = 0.001).

conclusionSerum IgM levels in centenarians significantly correlated with the risk of death, suggesting that they are suitable for predicting the overall risk of death in centenarians and can be used as an independent predictor of death.

Indexed as

AgingCentenariansImmunityImmunoglobulin MLongevityRisk of death

Identifiers

PMID39415263
PMCPMC11481244

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