Genetic differences according to onset age and lung function in asthma: A cluster analysis.

Area of Science:

• Genetics
• Pulmonology
• Bioinformatics

Background:

• Asthma heterogeneity is not fully understood, particularly regarding genetic risk differences among subtypes.
• Identifying genetic variants specific to asthma subtypes is crucial for understanding its complex genetic basis.

Purpose of the Study:

• To employ an unsupervised method to identify genetic variants associated with distinct asthma subtypes.
• To gain insights into the genetic underpinnings of asthma heterogeneity based on onset age and lung function.

Main Methods:

• Utilized the UK Biobank dataset, including 36,086 asthma cases and 283,410 controls.
• Performed k-means clustering based on asthma onset age and predicted forced expiratory volume in one second percent (FEV1%).
• Conducted cluster-specific genome-wide association studies (GWASs), heritability estimation, eQTL, and gene-set enrichment analyses.

Main Results:

• Identified four distinct asthma clusters: early onset with normal lung function (n=8172), early onset with reduced lung function (n=8925), late-onset with normal lung function (n=12,481), and late-onset with reduced lung function (n=6508).
• Discovered 5 novel loci, 14 novel signals, and 51 cluster-specific signals through GWASs.
• Early onset asthma with reduced lung function exhibited the highest heritability (h²=0.212) and the most associated variants (71 SNPs); pathway analysis linked symptom worsening to immune responses.

Conclusions:

• Early onset asthma with reduced lung function represents the most genetically predisposed asthma subtype.
• Asthma subtypes with reduced lung function are genetically distinct from those with normal lung function.
• This study reveals significant genetic variations between asthma clusters, offering key insights into asthma's genetic heterogeneity.