Evidence map›Paper›PMID 39535692›Full record

ArticleGeroScience2025

Plasma proteomic signature of risk and prognosis of frailty in the UK Biobank.

Jianhong Xu, Jingyun Liu, Junhan Tang, Jinhui Liao, Xiaojuan Liu, Michelle C Odden, Chenkai Wu

Abstract read
In one paragraph

Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
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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

7 authors.

Jianhong Xu *Global Health Research Center, Duke Kunshan University, Academic Building 3038, No. 8 Duke Avenue, Kunshan, 215316, Jiangsu, China.
Jingyun Liu *Global Health Research Center, Duke Kunshan University, Academic Building 3038, No. 8 Duke Avenue, Kunshan, 215316, Jiangsu, China.
Junhan TangGlobal Health Research Center, Duke Kunshan University, Academic Building 3038, No. 8 Duke Avenue, Kunshan, 215316, Jiangsu, China.
Jinhui LiaoSchool of Public Health, Fudan University, Shanghai, China.
Xiaojuan LiuDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
Michelle C OddenDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
Chenkai WuGlobal Health Research Center, Duke Kunshan University, Academic Building 3038, No. 8 Duke Avenue, Kunshan, 215316, Jiangsu, China. chenkai.wu@dukekunshan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The availability of proteomics data in large, population-based cohort studies offers an unprecedented opportunity to understand the onset and progression of aging-related diseases and syndromes. We examined the proteomic signature of the onset of frailty and the progression to death among the prefrail and frail. A total of 2920 proteins were assayed using Olink among 43,895 participants (aged 39-70 years) in the UK Biobank. Using multinomial logistic models, we identified 102 and 90 proteins cross-sectionally associated with baseline prefrailty and frailty (Bonferroni-corrected p-value < 0.05), respectively. Additionally, cox regression identified 87 and 48 proteins associated with death among initially prefrail (n = 16,661) and frail (n = 1647) individuals, respectively. Eight overlapping proteins were cross-sectionally associated with prefrailty and frailty at baseline and prospectively associated with death among prefrail and frail individuals. CD300E, GDF15, and PLAUR were the most significant proteins among these eight proteins. LASSO regression selected 73 and 23 proteins predicting death in prefrail and frail participants, respectively. Protein-based prediction models based on LASSO regression and the light gradient boosting machine classifier demonstrated satisfactory discrimination, calibration, and reclassification among the prefrail and frail. GDF15, WFDC2, and NEFL were the most important proteins predicting death among prefrail and frail individuals. Proteins associated with the onset and progression of prefrailty and frailty were enriched in pathways involving protein metabolism, cellular signaling in disease, apoptosis, and inflammation. Our research could uncover novel therapeutic targets for addressing the onset and progression of frailty, potentially informing the design of patient-centered treatment strategies and management plans.

Indexed as

Frail ElderlyFrailtyProteomicsAdultAgedBiological Specimen BanksBiomarkersCross-Sectional StudiesFemaleGrowth Differentiation Factor 15HumansMaleMiddle AgedPrognosisRisk AssessmentUK BiobankBiomarkersGrowth Differentiation Factor 15AgingFrailtyFrailty predictionOlinkProteinProteomics

Identifiers

PMID39535692
PMCPMC11979046

What OpenQuestion holds

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Registered trials

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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.