ArticleBMC genomic data2026
A candidate-variant association study of self-reported asthma in mothers of the Cebu Longitudinal Health and Nutrition Survey (CLHNS) cohort.
Article in BMC genomic data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAsthma is an obstructive respiratory disease with greatest morbidity in low- and middle-income countries: 15% of the Filipino population are estimated to have asthma, half of whom have inadequately controlled disease. There are many known genetic associations with asthma, but lack of representation across ancestries means that understudied populations do not yet stand to benefit equally from genomic research. We performed the first genetic association study of asthma in a Filipino population. We performed a candidate-variant association study in 1,678 unrelated mothers (129 with self-reported asthma) of the Cebu Longitudinal Health and Nutrition Survey (CLHNS). Using the largest published multi-ancestry asthma GWAS (Global Biobank Meta-Analysis Initiative, GBMI), we selected sentinel single-nucleotide polymorphisms (SNPs) associated in the multi-ancestry analysis (P < 5 × 10
resultsTwenty-seven SNPs were analysed. Only one intronic variant in SMAD3 was associated with asthma at a Bonferroni-corrected threshold (rs17293632, OR 1.80, 95%CI 1.28-2.54, P = 0.0008). SMAD3 is involved in TGF-β signalling, related to airway remodelling in asthma. The GRS was associated with increased odds of asthma (OR per weighted allele increase 1.07 [95%CI 1.01-1.14], P = 0.022). Five of the 37 top signals in the EAS GWAS were associated in our study, although none of these five signals reached a Bonferroni p-value threshold of P = 1.35 × 10
conclusionsDespite the small sample size, we detected a known SNP-asthma association in CLHNS using a candidate-variant approach, and demonstrated the value of aggregating variants into GRS when power is limited (using confidently ascribed weights from large GWAS). However, we were underpowered to undertake a GWAS, and thus to discover novel associations. Commitment by the genomics field as a whole to cohort development and investment in understudied populations will be key to addressing inequity in asthma genetic research. CLINICAL TRIAL NUMBER: Not applicable.
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