Evidence map›Paper›PMID 38589871›Full record

ArticleBMC medicine2024

Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases.

Xiaohui Sun, Yu Qian, Weiqiu Cheng, Ding Ye, Bin Liu, Dan Zhou, Chengping Wen, Ole A Andreassen, Yingying Mao

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 3 institutions in 2 countries.

Xiaohui Sun *Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Yu Qian *Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Weiqiu Cheng *NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, 0407, Norway.
Ding YeDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Bin LiuDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Dan ZhouSchool of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Chengping WenCollege of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Ole A AndreassenNORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, 0407, Norway. ole.andreassen@medisin.uio.no.
Yingying MaoDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China. myy@zcmu.edu.cn.ORCID 0000-0003-3644-9160
Zhejiang Chinese Medical University · CNUniversity of Oslo · NOSecond Affiliated Hospital of Zhejiang University · CN

Funding

he Foundation of Zhejiang Chinese Medical University 2020ZG01he Foundation of Zhejiang Chinese Medical University KC201905National Natural Science Foundation of China 81973663National Natural Science Foundation of China 82174208Natural Science Foundation of Zhejiang Province LQ20H260008Natural Science Foundation of Zhejiang Province LQ21H260001part of convergence environment [4MENT] funded by UiO:Life Science and Scientia Fellows, European Union's Horizon2020 Research and Innovation programme #801133part of convergence environment [4MENT] funded by UiO:Life Science and Scientia Fellows, European Union's Horizon2020 Research and Innovation programme No. 847776Research Council of Norway #223273Research Council of Norway #324252the Foundation of Zhejiang Chinese Medical University 2020ZG016the Foundation of Zhejiang Chinese Medical University 2021JKZKTS004A
6 · The paper itself

Abstract

backgroundDespite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD.

methodsBased on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets.

resultsCompared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure.

conclusionsThis study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

Indexed as

Arthritis, RheumatoidCardiovascular DiseasesCoronary Artery DiseaseHeart FailureStrokeGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideCardiovascular diseasesEpidemiological associationGenetic correlationPleiotropic lociRheumatoid arthritis

Identifiers

PMID38589871
PMCPMC11003061
OpenAlexW4394582331

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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.