Evidence map›Paper›PMID 40630117›Full record

ArticleFrontiers in genetics2025

Shared genetic loci connect cardiovascular disease with blood pressure and lipid traits in East Asian populations.

Peng Zhong, Chumeng Zhang, Qinfeng Wu, Xiao Chang

Abstract read
In one paragraph

Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Peng ZhongDepartment of Cardiology, Jining No.1 People's Hospital, Jining, Shandong, China.
Chumeng ZhangThe Second School of Clinical Medicine of Shandong First Medical University, Tai'an, Shandong, China.
Qinfeng WuCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Xiao ChangCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Cardiovascular diseases (CVDs), including myocardial infarction (MI), heart failure (HF), atrial fibrillation (AF), and arrhythmia, are major contributors to global mortality and often share overlapping risk factors and pathophysiological mechanisms. While genome-wide association studies (GWAS) have identified many loci for individual CVDs, the shared genetic architecture across related traits-particularly in East Asian populations-remains underexplored. Materials and methods: We integrated large-scale GWAS summary statistics from East Asian populations to perform genome-wide and local genetic correlation analyses across four CVD phenotypes and five cardiometabolic traits (blood pressure and lipid levels). Using stratified LD score regression, we assessed tissue-specific heritability enrichment. Multi-trait analysis of GWAS (MTAG) was then employed to identify pleiotropic loci associated with multiple traits, with functional annotation and expression quantitative trait loci (eQTL) data used to explore biological relevance. Results: We observed extensive genetic correlations among CVDs and between CVDs and cardiometabolic traits, with HF showing the strongest connections to both MI and arrhythmia. Notable genome-wide correlations were found between MI and SBP (rg = 0.35, Conclusion: Our findings provide comprehensive insight into the shared genetic determinants of cardiovascular and metabolic diseases in East Asian populations. The identification of pleiotropic and ancestry-specific loci, along with tissue-specific regulatory patterns, underscores the need for integrative multi-trait and population-informed approaches in cardiovascular genetics and risk prediction.

Indexed as

cardiometabolic traitscardiovascular diseasesgenetic correlationheart failuremulti-trait GWAS

Identifiers

PMID40630117
PMCPMC12234571

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.