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

Identification of asthma-related genes using asthmatic blood eQTLs of Korean patients.

BMC medical genomics - 24 Oct 2023

Kim Dong Jun, Lim Ji Eun, Jung Hae-Un, Chung Ju Yeon, Baek Eun Ju, Jung Hyein, Kwon Shin Young, Kim Han Kyul, Kang Ji-One, Park Kyungtaek, Won Sungho, Kim Tae-Bum, Oh Bermseok

Abstract excerpt

BACKGROUND: More than 200 asthma-associated genetic variants have been identified in genome-wide association studies (GWASs). Expression quantitative trait loci (eQTL) data resources can help identify causal genes of the GWAS signals, but it can be difficult to find an eQTL that reflects the disease state because most eQTL data are obtained from normal healthy subjects. METHODS: We performed a blood eQTL analysis...

Read the complete abstract on PubMed

Topics

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

Share to Asthma
Share to Asthma and respiratory diseases

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Gene Expression Profiling

Share to Genetic Associations and Epidemiology

Share to Genetic Predisposition to Disease

Share to Genome-Wide Association Study

Share to Polymorphism, Single Nucleotide

Share to Republic of Korea

Source

Open in PubMed Open full text

Identifiers

PMID: 37875944
DOI: 10.1186/s12920-023-01677-7
PMCID: PMC10599017

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identification of asthma-related genes using asthmatic blood eQTLs of Korean patients.PMID 37875944Read ↗

Identification of asthma-related genes using asthmatic blood eQTLs of Korean patientsSemantic proximity Read ↗

Lung eQTLs to help reveal the molecular underpinnings of asthma.Semantic proximity Read ↗

Family-based genome-wide association study for asthma among Han Chinese children.Semantic proximity Read ↗

Multi-Trait Genetic Analysis of Asthma and Eosinophils Uncovers Novel Loci in East AsiansSemantic proximity Read ↗

Airway Epithelial Expression Quantitative Trait Loci Reveal Genes Underlying Asthma and Other Airway Diseases.Semantic proximity Read ↗

Identification of shared genetic loci for asthma, allergic rhinitis, and pollinosis in East Asians.Semantic proximity Read ↗

Multi-trait genetic analysis of asthma and eosinophils uncovers pleiotropic loci in East AsiansSemantic proximity Read ↗

Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma.Semantic proximity Read ↗

eQTL of bronchial epithelial cells and bronchial alveolar lavage deciphers GWAS-identified asthma genes.Semantic proximity Read ↗

A multi-omics Mendelian randomization identiﬁes putatively causal genes and DNA methylation sites for asthmaSemantic proximity Read ↗

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations.Semantic proximity Read ↗

Integrated genomics analysis highlights important SNPs and genes implicated in moderate-to-severe asthma based on GWAS and eQTL datasets.Semantic proximity Read ↗

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