Evidence map›Paper›PMID 39807002›Full record

ArticleJournal of Korean medical science2025

Effects of Genetic Risk and Lifestyle Habits on Gout: A Korean Cohort Study.

Hyunjung Kim, Hyunsue Do, Chang-Nam Son, Jae-Won Jang, Sun Shim Choi, Ki Won Moon

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Hyunjung KimDivision of Biomedical Convergence, College of Biomedical Science, Institute of Bioscience & Biotechnology, Kangwon National University, Chuncheon, Korea.ORCID https://orcid.org/0009-0006-3876-8308
Hyunsue DoDivision of Rheumatology, Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0002-9550-1048
Chang-Nam SonEulji Rheumatology Research Institute, Eulji University School of Medicine, Uijeongbu, Korea.ORCID https://orcid.org/0000-0002-1722-2190
Jae-Won JangDepartment of Neurology, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0003-3540-530X
Sun Shim ChoiDivision of Biomedical Convergence, College of Biomedical Science, Institute of Bioscience & Biotechnology, Kangwon National University, Chuncheon, Korea. schoi@kangwon.ac.kr.ORCID https://orcid.org/0000-0001-6289-4220
Ki Won MoonDivision of Rheumatology, Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0002-4182-8328

Funding

Kangwon National University HospitalNational Research Foundation of Korea NRF-2022R1F1A1065348National Research Foundation of Korea RS-2024-00341909
6 · The paper itself

Abstract

backgroundGout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders.

methodsWe analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex.

resultsAmong 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32-6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61-13.40) group. Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups.

conclusionGenetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.

Indexed as

Genetic Predisposition to DiseaseGoutLife StyleAdultAgedAge FactorsBody Mass IndexCohort StudiesEast Asian PeopleFemaleGenome-Wide Association StudyHumansHypertensionHypertriglyceridemiaLogistic ModelsMaleGoutKorean CohortLifestyle HabitsMetabolic SyndromePolygenic Risk Score

Identifiers

PMID39807002
PMCPMC11729237

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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.