Evidence map›Paper›PMID 39379299›Full record

ArticleRMD open2024

Cardiovascular risk according to genetic predisposition to gout, lifestyle and metabolic health across prospective European and Korean cohorts.

Ki Won Moon, Sang-Hyuk Jung, Hyunsue Do, Chang-Nam Son, Jaeyoung Kim, Yonghyun Nam, Jae-Seung Yun, Woong-Yang Park, Hong-Hee Won, Dokyoon Kim

Abstract read
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In one paragraph

Article in RMD open, 2024. 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.

Ki Won Moon *Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, South Korea.
Sang-Hyuk Jung *Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Hyunsue DoDepartment of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, South Korea.
Chang-Nam SonDepartment of Internal Medicine, Eulji University School of Medicine, Uijeongbu, South Korea.
Jaeyoung KimSamsung Advanced Institute for Health Sciences and Technology (SAIHST), Samsung Medical Center, Seoul, South Korea.
Yonghyun NamDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Jae-Seung YunDepartment of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Woong-Yang ParkSamsung Genome Institute, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Hong-Hee WonSamsung Advanced Institute for Health Sciences and Technology (SAIHST), Samsung Medical Center, Seoul, South Korea.
Dokyoon KimDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA dokyoon.kim@pennmedicine.upenn.edu.ORCID 0000-0002-4592-9564

Funding

Unravelling genetic basis of comorbidity using EHR-linked biobank dataR01GM138597 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI KIM, DOKYOON · 2020 to 2023
$2.2M
NIGMS NIH HHS R01 GM138597
6 · The paper itself

Abstract

objectiveRecent studies have reported that gout is associated with a risk of cardiovascular disease (CVD) later in life. However, the predictive value of genetic predisposition to gout combined with lifestyle habits for CVD risk remains unclear. This study aimed to examine the association between genetic predisposition to gout and lifestyle habits and the risk of developing CVD in two diverse prospective cohorts from different ancestries.

methodsA total of 224 689 participants of European descent from the UK Biobank and 50 364 participants of East Asian descent from the Korean Genome and Epidemiology Study were included. The genetic risk for gout was assessed using a polygenic risk score (PRS) derived from a meta-genome-wide association study (n=444 533). The incident CVD risk was evaluated according to genetic risk, lifestyle and metabolic syndrome (MetS).

resultsIndividuals at high genetic risk for gout had a higher risk of incident CVD than those with low genetic risk across ancestry. Notably, a reduction in CVD risk by up to 62% (HR 0.38; 95% CI 0.31 to 0.46; p <0.001) was observed in individuals at both low and high genetic risk for gout when they maintained ideal MetS and favourable lifestyle habits.

conclusionsOur findings indicate that a higher genetic risk of gout is significantly associated with an increased risk of CVD. Moreover, adherence to a favourable lifestyle can significantly reduce CVD risk, particularly in individuals with high genetic risk. These results underscore the potential of PRS-based risk assessment to improve clinical outcomes through tailored preventative strategies.

Indexed as

Cardiovascular DiseasesGenetic Predisposition to DiseaseGenome-Wide Association StudyGoutLife StyleMetabolic SyndromeAdultAgedAsian PeopleFemaleHumansMaleMiddle AgedMultifactorial InheritancePolymorphism, Single NucleotideProspective StudiesCardiovascular DiseaseGoutPolymorphism, Genetic

Identifiers

PMID39379299
PMCPMC11474875

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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.