Airway Microbiome Is Associated with Atherosclerosis in Adults from Southern Caribbean

Subclinical atherosclerosis (SCA) has been associated with lung function in many populations. Accordingly, those factors involved in respiratory health may contribute to the mechanisms linking pulmonary and cardiovascular disorders. Since the airway microbiome plays a key role in respiratory pathophysiology, microbial abundance and diversity in the upper airway may be associated with SCA risk. This study aimed to assess the association of upper airway microbiome abundance and diversity with SCA risk. A nested case–control study was carried out among adults from the Southern Caribbean. SCA was defined by carotid Doppler ultrasound as a carotid intima-media thickness ≥ 0.8 mm or the presence of carotid plaque. Oropharyngeal mucosal samples were collected under fasting conditions, and the V3-V4 region of the 16SRNA gene was sequenced. Differences in genus-level abundance were assessed using Microbiome Multivariable Association with Linear Models 2 (MaAsLin2). Alpha-diversity indices were compared through Wilcoxon tests. Principal coordinates analysis (PCoA) and Permutational Multivariate Analysis of Variance (PERMANOVA), adjusted for age, body mass index, and smoking status, were performed to assess associations between Bray–Curtis distances and SCA. MaAsLin2 was also applied to determine predicted metabolic pathway enrichment. A total of 40 cases and 40 controls were analyzed. The oropharyngeal microbiomes composition was dominated by three genera: Prevotella (cases: 26.0%; controls: 29.8%), Veillonella (cases: 16.3%; controls: 13.7%) and Fusobacterium (cases: 7.5%; controls: 8.0%). Significant differences in relative abundance were found for Streptococcus, Aureimonas, Mogibaecterium, Candidatus Saccharimonas, Pseudomonas, Segatella, Stomatobaculum, Oribacterium and Lachnoanaerobaculum, with lower abundance in cases for all these genera. Alpha-diversity was lower in cases than in controls, as reflected by the Shannon index (cases: 5.95 IQR [4.87; 6.35] vs. controls: 6.49 IQR [6.29; 6.75], p < 0.001), Simpson index (cases: 0.994, IQR [0.989; 0.996] vs. controls: 0.997 IQR [0.997; 0.998], p < 0.001) and Chao1 richness (cases: 1076.2 IQR [345.2; 1473.4] vs. controls: 1136.1, IQR [841.1; 1635.3], p = 0.04) were compared. In adjusted-PERMANOVA, 8.2% of microbiome variations were associated with SCA (pseudo-F = 7.49, R2 = 0.082, p < 0.001), although this finding may have been influenced by intra-group dispersion among cases (PERMDISP: pseudo-F = 5.62, p = 0.018; Tukey’s HSD test: mean difference = −0.071, 95% CI [−0.118, −0.025], p = 0.003) Predicted enrichment of phenylalanine metabolism and indole alkaloid biosynthesis was higher in cases. In conclusion, these exploratory analyses suggest that reduced oropharyngeal microbiome diversity is associated with SCA. Further studies are warranted to clarify the role of the airway microbiome on cardiovascular outcomes.