ArticleClinical and translational allergy2023
Genetic differences according to onset age and lung function in asthma: A cluster analysis.
Article in Clinical and translational allergy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Studying rare variant polygenic risk scores using whole exome sequencing and imputed genotype data.Communications biology · 2025Article
- Genetic interactions and pleiotropy in metabolic diseases: Insights from a comprehensive GWAS analysis.Journal of cellular and molecular medicine · 2024Article
- A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.JMIR medical informatics · 2024Article
- Analysis of global gene expression using RNA-sequencing reveals novel mechanism of Yanghe Pingchuan decoction in the treatment of asthma.BMC pulmonary medicine · 2024Article
- Genetic differences according to onset age and lung function in asthma: A cluster analysis.Clinical and translational allergy · 2023Article
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Authors and funding
12 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundThe extent of differences between genetic risks associated with various asthma subtypes is still unknown. To better understand the heterogeneity of asthma, we employed an unsupervised method to identify genetic variants specifically associated with asthma subtypes. Our goal was to gain insight into the genetic basis of asthma.
methodsIn this study, we utilized the UK Biobank dataset to select asthma patients (All asthma, n = 50,517) and controls (n = 283,410). We excluded 14,431 individuals who had no information on predicted values of forced expiratory volume in one second percent (FEV1%) and onset age, resulting in a final total of 36,086 asthma cases. We conducted k-means clustering based on asthma onset age and predicted FEV1% using these samples (n = 36,086). Cluster-specific genome-wide association studies were then performed, and heritability was estimated via linkage disequilibrium score regression. To further investigate the pathophysiology, we conducted eQTL analysis with GTEx and gene-set enrichment analysis with FUMA.
resultsClustering resulted in four distinct clusters: early onset asthma
conclusionsOur findings suggest that early onset asthma
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Registered trials
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.