Table 2. Summary of studies investigating the association between upper airway microbiota and adult asthma.

Study	Country	Participant (n)	Asthma definition	Asthma rate (%)	Age (yr)	Comorbidity	Sample	Bacterial sequence, region	Method	Changes in diversity and richness	Taxonomical changes
Durack et al., 2018 [32]	USA	45	Lung function test	48.8	27–45	Rhinitis 55%	Nasal brushing	16S rRNA V4	Illumina MiSeq	No changes in α-diversity	Decreased Corynebacterium (p = 0.07)
Fazlollahi et al., 2018 [23]	USA	72	Physician diagnosed and self-report	70.8	35.8 ± 16	Rhinitis 70.5%	Nasal swab	16S rRNA V3-V4	Illumina MiSeq	Increased α-diversity (not significant)	Increased Bacteroidetes (r = 0.33, p = 5.1×10-3) and Proteobacteria (r = 0.29, p = 1.4×10-2).
											Prevotella buccalis (p = 1.0×10-2), Gardnerella vaginalis (p = 2.8×10-3), Alkanindiges hongkongensis (p = 2.6×10-3)
											Dialister invisus (p = 9.1×10-3)
Lee et al., 2019 [8]	Korea	80	Physician diagnosis, symptom and lung test	75	18–45, > 65	NA	Nasopharyngeal swab	16S rRNA V1-V3, whole metagenome	Roche 454 pyrosequencing, Illumina HiSeq	No changes in Shannon diversity	Increased Proteobacteria (p < 0.05), decreased Corynebacteriales (p < 0.01)
											Moraxella (p < 0.05)
Park et al., 2014 [24]	Korea	47	Symptoms-based	38.2	23–79	NA	Oropharyngeal sample	16S rRNA V1-V3	Roche 454 pyrosequencing,	Shannon diversity decreased (2.4 ± 1) vs. control (3.5 ± 0.7)	Increased Pseudomonas spp. and Lactobacillus spp. (p < 0.0001), decreased Streptococcus spp., Neisseria spp., Veillonella spp., and Prevotella spp. (p < 0.0001)