Evidence map›Paper›PMID 42701149›Full record

ArticleGeroScience2026

Longitudinal infection trajectories and biological aging acceleration in adults: a prospective cohort study.

Biying Wang, Kaiyue Shen, Chen Qian, Liping Yi, Youyi Zhang, Hongjie Yu, Xiaohua Liu, Yonggen Jiang, Tao Zhang, Genming Zhao

Abstract read
PubMed Publisher
In one paragraph

Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Biying WangShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China.
Kaiyue ShenDepartment of Epidemiology, School of Public Health, Fudan University, 130 Dong'an Road, Xuhui District, Shanghai, 200032, People's Republic of China.
Chen QianShanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute), Shanghai, 201299, China.
Liping YiDepartment of Epidemiology, School of Public Health, Fudan University, 130 Dong'an Road, Xuhui District, Shanghai, 200032, People's Republic of China.
Youyi ZhangDepartment of Epidemiology, School of Public Health, Fudan University, 130 Dong'an Road, Xuhui District, Shanghai, 200032, People's Republic of China.
Hongjie YuShanghai Jiading District Center for Disease Control and Prevention, Shanghai, 201899, China.
Xiaohua LiuShanghai Minhang District Center for Disease Control and Prevention, Shanghai, 201101, China.
Yonggen JiangShanghai Songjiang District Center for Disease Control and Prevention, Shanghai, 201620, China.
Tao ZhangShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China. tzhang@shmu.edu.cn.
Genming ZhaoShanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China. gmzhao@shmu.edu.cn.

Funding

Fudan School of Public Health-Jiading CDC key disciplines for the high-quality development of public health GWGZLXK-2023-02Shanghai Eastern Talent Plan Top-notch Project 202 BJWS2025025
6 · The paper itself

Abstract

Infections remain a major cause of mortality and may threaten healthy aging. Previous studies have focused on isolated severe infections rather than longitudinal infection burden. We aimed to examine associations of infection trajectories with biological age acceleration (BAA) and assessed infection severity and genetic susceptibility. We included adults aged 20-74 years from the Shanghai Suburban Adult Cohort and Biobank, China, enrolled between 2016 and 2019 with valid biological age (BA) measurements at baseline and follow-up. Infection-related episodes were identified from linked local health information systems and summarized quarterly between baseline and first follow-up. Group-based trajectory modeling identified infection trajectories. BA was estimated using the Klemera-Doubal method and BAA was defined as the residual from regressing BA on chronological age. Linear mixed-effects models assessed associations with annual BAA change. Polygenic risk scores and Cox models evaluated genetic susceptibility and all-cause mortality. Among 7614 participants, four infection trajectories were identified: infrequent (71.15%), decreasing (18.72%), increasing (8.18%), and frequent (1.96%). Compared with the infrequent group, the frequent group showed the largest estimate in the age- and sex-adjusted model (β = 0.67, 95% CI: 0.04-1.31). A greater proportion of severe episodes was associated with faster BAA change. Associations persisted in long-term analyses and appeared stronger among individuals with higher polygenic susceptibility. Frequent infection trajectories were also associated with higher mortality and greater years of life lost. Longitudinal infection trajectories, particularly frequent and severe patterns, were associated with greater increases in BAA and higher mortality, supporting attention to cumulative infection burden in vulnerable populations.

Indexed as

Biological agingGenetic susceptibilityInfectionTrajectory

Identifiers

What Socratic holds

Textmetadata
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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.