Fig 1.
Study population and data processing workflow.
Participants were recruited from Tsukuba Cohorts 1 and 2, including healthy volunteers and bronchial asthma patients from the University of Tsukuba Hospital and affiliated centers. Healthy volunteers were enrolled through routine health check-ups, while bronchial asthma patients were clinically diagnosed according to established guidelines. Data processing involved excluding participants with incomplete data on BMI, age of asthma onset, or predicted forced expiratory volume in one second. After calculating BMI-genetic risk scores, 685 bronchial asthma patients were included in the final analysis. Cluster analysis was performed using BMI, BMI-genetic risk scores, predicted forced expiratory volume in one second, and age of asthma onset. HV: Healthy Volunteer; BA: Bronchial Asthma; BMI: Body Mass Index; pFEV1: Predicted Forced Expiratory Volume in One Second; BMI-GRS: Body Mass Index-Genetic Risk Score.
Fig 2.
SNP Selection and genotyping workflow.
This figure summarizes the workflow of SNP selection and genotyping. From 85 BMI-associated SNPs, 78 were initially targeted. After genotype imputation using a reference panel constructed from alternate cohort data and searching for alternative SNPs in strong linkage disequilibrium (R2 > 0.8) using HaploReg, 65 SNPs were retained. Six SNPs with consistent associations with BMI were used for BMI-genetic risk score calculation. SNP: Single Nucleotide Polymorphism; BMI: Body Mass Index; BMI-GRS: Body Mass Index-Genetic Risk Score.
Table 1.
Six SNPs used to calculate BMI – GRS.
Table 2.
Clinical characteristics of the study participants.
Fig 3.
Correlation between BMI-GRS and BMI in study groups.
(A) A significant positive correlation between BMI and BMI-GRS was observed in non-asthmatic healthy individuals (R2 = 0.029, p = 2.77 × 10 ⁻ ¹¹). (B) No significant correlation was found in asthmatic patients (R2 = 0.005, p = 0.046), suggesting a limited genetic contribution to BMI in this group. BMI: Body Mass Index; BMI-GRS: Body Mass Index-Genetic Risk Score.
Fig 4.
Comparative analysis of BMI and BMI-GRS between groups.
(A) Asthmatic patients exhibited significantly higher BMI than healthy individuals (p = 0.002). (B) No significant difference in BMI-GRS was found between the two groups (p = 0.56), indicating that increased BMI in asthmatic patients is not solely attributable to genetic predisposition. BMI: Body Mass Index; BMI-GRS: Body Mass Index-Genetic Risk Score.
Fig 5.
BMI-GRS comparisons according to disease status and BMI.
Overall group differences were significant (ANCOVA, p < 0.001). Post hoc pairwise comparisons (Bonferroni-adjusted) showed that Obese Healthy Volunteers had significantly higher BMIGRS compared with Non-Obese Healthy Volunteers (p < 0.001) and Non-Obese Asthma (p = 0.001). In contrast, Obese Asthma did not significantly differ from any other group (all p > 0.05), including Non-Obese Asthma (p = 0.56). No significant differences were observed between asthma and non-asthma groups within the same obesity category. Data are presented as mean ± standard error. Statistical differences were evaluated using ANCOVA adjusted for age, sex, and smoking index, followed by Bonferroni-corrected pairwise comparisons. NOA: Non-Obese Asthma, NOHV: Non-Obese Healthy Volunteers, OA: Obese Asthma, OHV: Obese Healthy Volunteers.
Fig 6.
Summary of cluster analysis of adult asthma.
The six clusters are plotted according to BMI and BMI-GRS. The diameter of each pie represents the population size of each cluster. The grey area of the pie chart indicates the proportion of atopic individuals. In addition, the four numbers given for each pie chart represent clockwise from top left, the percentage of females, the percentage of current and former smokers, pFEV1, and age at asthma onset. BMI: Body Mass Index, BMI-GRS: Body Mass Index-Genetic Risk Score, pFEV1: predicted Forced Expiratory Volume in 1 second.
Table 3.
Detailed characteristics of each asthma cluster.
Table 4.
Multinominal logistic regression model of BMI-GRS on adult asthma clusters.