Evidence map›Paper›PMID 41631277›Full record

ArticleGlobal medical genetics2026

Genetic link between metabolic syndrome and coronary artery disease: Insights from genome-wide cross-trait analysis.

Pengcheng Yi, Quanting Yin, Huanhuan Zhang, Chunhua Yang, Yanping Zhu, Zhenhong Xia, Fuyi Xu, Jia Mi

Abstract read
In one paragraph

Article in Global medical genetics, 2026. 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

8 authors.

Pengcheng YiSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.
Quanting YinSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.
Huanhuan ZhangSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.
Chunhua YangSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.
Yanping ZhuSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.
Zhenhong XiaSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.
Fuyi XuSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.
Jia MiSchool of Pharmacy, Binzhou Medical University, Shandong, Yantai 264003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic syndromes (MeS), marked by central obesity, high blood pressure, abnormal cholesterol and blood sugar, are key cardiovascular disease (especially coronary artery disease, CAD) risk factors. Genetic studies show MeS-CAD genetic overlap, indicating shared biological pathways. We used Summary-data-based Mendelian Randomization (SMR), Bayesian colocalization (with large GWAS summary stats for MeS/CAD and cis-eQTL data from 3 tissues) and Transcriptome-Wide Association Study (TWAS). We also investigated the effects of gene knockout on mouse phenotypes. SMR found 886/737/192 shared genes in blood/brain cortex/liver; colocalization identified 11/13/5 shared causal genes in these tissues and 46 shared loci (e.g., CAMK1D, OR=1.11; AGPAT1, OR=1.13; FDR<0.05). Moreover, knocking out these genes in mice affected metabolism, adipose tissue, cardiovascular function, glucose homeostasis, and the fat/muscle balance. This study identified common regulatory genes between MeS and CAD, suggesting that targeted therapies or interventions could potentially address both conditions simultaneously, offering prospects for more integrated treatment strategies.

Indexed as

Co-localizationCoronary artery diseaseDiabetesExpression quantitative lociGenetic correlationMendelian randomizationObesity

Identifiers

PMID41631277
PMCPMC12861156

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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.