Diversity and Meta-Analysis of Microbial Differential Abundance in Nasal Metatranscriptomic Profiles of Asthma

J Respir Biol Transl Med. 2024 Dec;1(4):10018. doi: 10.70322/jrbtm.2024.10018. Epub 2024 Nov 4.

Abstract

Asthma affects millions worldwide and involves complex genetic, immunological, and environmental factors. The nasal microbiome is increasingly recognized for its role in asthma development, but inconsistent results and small sample sizes have limited a clear understanding. We aimed to clarify the nasal microbiome's role in asthma using large datasets and meta-transcriptomic analysis. RNA-seq data was analyzed from two large public studies: GALA II (694 children of Puerto Rican heritage; 441 asthmatics, 253 controls) and CAAPA (562 individuals of African ancestry; 265 asthmatics, 297 controls). After quality control and host read removal, microbial reads were annotated using Kraken2. α and β diversity analyses compared microbial diversity between asthmatic and control groups. Differential abundance analysis was conducted separately, controlling for age and sex, with results combined via meta-analysis. We found that asthmatic patients exhibited significantly higher α diversity indices (Shannon, Berger-Parker, Inverse Simpson, Fisher's) in nasal microbiota compared to controls in GALA II, with similar trends in CAAPA. β diversity analysis showed significant differences in microbial composition in GALA II data. Differential abundance analysis identified 20 species in GALA II and 9 species in CAAPA significantly associated with asthma. Meta-analysis revealed 11 species significantly associated with asthma, including Mycobacterium_tuberculosis. Our study demonstrates increased nasal microbiome α diversity in asthmatic patients and identifies specific microbial species associated with asthma risk. These findings enhance understanding of asthma pathogenesis from the nasal microbiome perspective and may inform future research and therapeutic strategies.

Keywords: Alpha diversity; Asthma; Beta diversity; Differential abundance analysis; Meta-analysis; Meta-transcriptomics; Nasal microbiome.