Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Integration of summary data from GWAS and eQTL studies identified novel risk genes for coronary artery disease.

Medicine - 19 Mar 2021

Zhong Yigang, Chen Liuying, Li Jingjing, Yao Yinghao, Liu Qiang, Niu Kaimeng, Ma Yunlong, Xu Yizhou

Abstract excerpt

ABSTRACT: Several genetic loci have been reported to be significantly associated with coronary artery disease (CAD) by multiple genome-wide association studies (GWAS). Nevertheless, the biological and functional effects of these genetic variants on CAD remain largely equivocal. In the current study, we performed an integrative genomics analysis by integrating large-scale GWAS data (N = 459,534) and 2 independent...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Antigens, Ly
Share to Coronary Artery Disease

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Regulatory Networks

Share to Heart Disease Risk Factors

Share to Mitochondrial Proteins

Share to Protein Interaction Maps

Share to Ribosomal Proteins

Share to Tubulin

Source

Open in PubMed Open full text

Identifiers

PMID: 33725943
DOI: 10.1097/MD.0000000000024769
PMCID: PMC7982177

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 3 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Integration of summary data from GWAS and eQTL studies identified novel risk genes for coronary artery disease.PMID 33725943Read ↗

Integration of Multiple-Omics Data to Analyze the Population-Specific Differences for Coronary Artery Disease.Semantic proximity Read ↗

A framework for studying multi-omic risk factors and their interplay: application to coronary artery diseaseSemantic proximity Read ↗

A versatile data repository for GWAS summary statistics-based downstream genomic analysis of human complex traitsSemantic proximity Read ↗

Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci.Semantic proximity Read ↗

Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci.Semantic proximity Read ↗

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data.Semantic proximity Read ↗

Multi-Omic Insight Into the Molecular Networks in the Pathogenesis of Coronary Artery Disease.Semantic proximity Read ↗

Genetics of coronary artery disease in the post-GWAS era.Semantic proximity Read ↗

Integrative genomics reveals novel molecular pathways and gene networks for coronary artery disease.Semantic proximity Read ↗

Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participantsSemantic proximity Read ↗

Identification of susceptibility modules for coronary artery disease using a genome wide integrated network analysis.Semantic proximity Read ↗

Systematic Integration of genomics with transcriptomics for the Study of Coronary Artery Disease and Subclinical AtherosclerosisSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.