Evidence map›Paper›PMID 39663608›Full record

ArticleAging cell2025

Associations of combined accelerated biological aging and genetic susceptibility with incidence of heart failure in a population-based cohort study.

Hao Zhao, Xuening Zhang, Yanzhi Li, Wanxin Wang, Wenjian Lai, Wenjing Zhang, Kai Kang, Xiali Zhong, Lan Guo

Abstract read
In one paragraph

Article in Aging cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

9 authors.

Hao ZhaoDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.ORCID 0000-0002-8799-8533
Xuening ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID 0000-0002-9987-030X
Yanzhi LiDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.ORCID 0000-0001-7436-2440
Wanxin WangDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.
Wenjian LaiDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.
Wenjing ZhangDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.
Kai KangCardiovascular Department, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Xiali ZhongGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.ORCID 0009-0008-1925-439X
Lan GuoDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, China.ORCID 0000-0002-5213-2158

Funding

Natural Science Foundation of China 82473652Natural Science Foundation of Guangdong Province 2021A1515111184Natural Science Foundation of Guangdong Province 2022A1515012333Natural Science Foundation of Guangdong Province 2023A1515012255
6 · The paper itself

Abstract

The global aging population raises concerns about heart failure (HF), yet its association with accelerated biological age (BA) remains inadequately understood. We aimed to examine the longitudinal association between BA acceleration and incident HF risk, assess its modifying effect on genetic susceptibility, and how much BA acceleration mediates the impact of modifiable health behaviors on incident HF. We analyzed 274,608 UK Biobank participants without HF at baseline. Two BA accelerations (Biological Age Acceleration [BioAgeAccel] and Phenotypic Age Acceleration [PhenoAgeAccel]) were calculated by regressing clinical biomarker-based BA on chronological age, with higher values indicating accelerated aging. Health behavior scores were computed based on diet, physical activity, tobacco/nicotine, sleep, and BMI. Genetic risk scores (GRS) were calculated by 12 HF-associated loci. During a median follow-up of 13.5 years, 8915 HF cases were documented. Each standard deviation increase in BioAgeAccel and PhenoAgeAccel was associated with an increased incident HF risk, yielding HRs of 1.45 (95% CI, 1.42-1.48) and 1.42 (95% CI, 1.40-1.45), respectively. Participants with high GRS and highest quartile of BioAgeAccel had an HR of 2.69 (95% CI, 2.42-2.99), and for PhenoAgeAccel, an HR of 2.83 (95% CI, 2.52-3.18), compared to those with low GRS, and lowest quartile. Additive interactions were observed between GRS and BA accelerations. Health behaviors reduced HF risk, with 21.1% (95% CI, 19.5%-22.8%) mediated by decreased BioAgeAccel and 20.9% (95% CI, 19.5%-22.6%) by decreased PhenoAgeAccel. Accelerated BA is associated with an increased incident HF risk, with an additive effect when combined with genetic susceptibility. Maintaining health behaviors may help mitigate BA aging and reduce HF risk.

Indexed as

AgingGenetic Predisposition to DiseaseHeart FailureAgedCohort StudiesFemaleHumansIncidenceMaleMiddle AgedRisk Factorsbiological agegenetic susceptibilityhealth behaviorheart failurepublic health

Identifiers

PMID39663608
PMCPMC11984684

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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.