Processed meat intake and incident gout: Integrated evidence from epidemiology, plasma proteomics, and machine learning
Wang Z, Shi D, Pan X, Chen W, Zheng S, Liu S, Zhao J, Tang X, Qin Y
Journal of advanced research · 0 citations
Review labels
Neutral facts our review recorded about how this study was done. They describe method, never whether we like the result.
How it was studied
- Design
- Cohort study (classified by our AI screen)
- Studied in
- People
- Main outcome
- Clinical events such as disease or death
- Intake measured by
- Not stated
Who paid for it
- Funding
- Funding not disclosed
Publication
- Published
- 2026-07-01 · J Adv Res
- Publisher
- Elsevier BV
- Cited
- 0 citations · more than 58% of similar papers · 0.0× the field average
- References
- 46 works
- Access
- Open access (journal) · CC-BY-NC-ND
- Research areas
- Gout, Hyperuricemia, Uric Acid · Nutritional Studies and Diet · Thyroid Disorders and Treatments
- Keywords
- Gout, Proportional hazards model, Hazard ratio, Biobank, Cohort, Prospective cohort study, Cohort study, Red meat
9 authors
From CN, GB
- Zhengda WangJilin University
- Daqian ShiQueen Mary University of London
- Xiangjun PanJilin University
- Wei ChenJilin University
- Shengyuan ZhengJilin University
- Shibo LiuJilin University
Abstract
Introduction
Gout is a common metabolic inflammatory disorder whose incidence parallels modern dietary shifts. Although processed meat intake is linked to metabolic dysregulation, its independent association with incident gout and related biological signatures remains unclear.
Objectives
To investigate the association between processed meat intake and incident gout and to characterize related biological signatures using integrated epidemiological, machine-learning, and plasma proteomic approaches.
Methods
This prospective cohort study included 395,356 UK Biobank participants free of gout at baseline. Associations between processed meat intake and incident gout were assessed using Cox proportional hazards models and time-varying Cox proportional hazards models. Socioeconomic and lifestyle factors were incorporated into the analyses. Supervised machine learning models were applied to evaluate the relative importance of behavioral determinants. In a proteomic subcohort, circulating proteins jointly associated with processed meat intake and gout were identified, followed by pathway enrichment analyses.
Results
During a mean follow-up of 15.7 years, 8,215 participants developed gout. Higher processed meat intake was independently associated with increased gout risk, with hazard ratios of 1.12 (95% CI: 1.06-1.18, P < 0.001) and 1.19 (95% CI: 1.07-1.31, P < 0.001) for middle and high intake, respectively, compared with low intake. In time-varying Cox proportional hazards models, the corresponding risk estimates increased to 1.52 (95% CI: 1.19-1.95, P < 0.001) and 1.84 (95% CI: 1.14-2.98, P = 0.012). Lower socioeconomic status and unfavorable lifestyle profiles were also associated with higher gout risk. Proteomic analyses identified 40 plasma proteins jointly associated with processed meat intake and gout status, suggesting potential involvement of biological processes related to metabolic dysregulation, inflammation, and neuroendocrine signaling.
Conclusions
Processed meat intake was independently associated with a higher risk of incident gout. These findings support a consideration of processed meat intake within broader dietary, socioeconomic, and lifestyle contexts, and provide exploratory proteomic evidence for biological processes potentially related to this association.
Abstract via Europe PMC. Copyright remains with the authors or publisher (CC BY-NC-ND).
Community trust
Loading…
How much do you trust this study's findings?
Comments
Sign in to rate, comment on or flag this study.Sign inSomething wrong here?
Flag this study if its information, labels or funding look wrong. An editor reviews every flag.
Sign in to rate, comment on or flag this study.Sign inEducational information about published research. Not medical advice, and not a recommendation to start or stop anything.