Dysbiosis of oral and gut microbiota and its association with metabolites in patients with different degrees of coronary artery stenosis

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To the Editor: Coronary atherosclerotic heart disease (CAD) arises from coronary atherosclerosis (CAS) plaque buildup, resulting in coronary stenosis (CS) and occlusion, ultimately causing myocardial ischemia hypoxia, and necrosis. Studies showed that the high-grade CS may be an important predictor of ST segment elevation myocardial infarction in subsequent months.[1] Recent research has underscored the significant impact of alterations in oral and gut flora on CAS. Dysbiosis, for instance, triggers oxidative stress, inflammatory responses, and metabolic disturbances, thereby initiating the atherosclerotic process.[2] However, a systematic study is still needed to elucidate the distinctions in oral and gut microbial traits and metabonomic features among CAS patients with different degrees of coronary artery stenosis, and to confirm the relationship between them, which may provide novel approach to the early diagnosis and precise treatment of CAS. To address these concerns, we conducted an analysis of the oral and gut microbial traits in 63 CAS patients and 31 controls using 16S ribosomal RNA (rRNA) amplicon sequencing. Blood samples were collected on the first day of hospitalization, and untargeted metabolomics analysis was performed using Liquid Chromatography combined with Tandem Mass Spectrometry (LC-MS/MS). Genomic DNA was extracted from oral and fecal samples and used for amplifying the gene sequence in the V4 region of bacterial 16S rRNA. Raw reads were obtained and subjected to quality analysis. Furthermore, we employed a multi-omics approach to explore the potential cooperative regulation of metabolism by oral and gut microbiota in CAS patients with varying degrees of stenosis. Wilcoxon rank-sum test was used for analysis, one-way analysis of variance and pairwise comparisons were performed among groups, and a P value of <0.05 was considered statistically significant. This study received ethical approval from the Second Hospital of Shanxi Medical University Ethics Committee (No. 2022-YX-084). Informed consent forms were signed by the patients and their families. The participants who underwent coronary angiography were divided into three groups as follows: Minimal and mild coronary stenosis (MMCS) group (N = 33), with stenosis <50% in at least one coronary segment; moderate and severe coronary stenosis (MSCS) group (N = 30), with stenosis >50% in at least one coronary segment;[3] and the control group (negative results in coronary computed tomography or coronary angiography, N = 31). The clinical features of the subjects are summarized in Supplementary Table 1, https://links.lww.com/CM9/B877. Trained dentists evaluated periodontal health indexes [Supplementary Table 2, https://links.lww.com/CM9/B877]. Intra-community alpha diversity, representing microbial richness and evenness, was analyzed, and there was no statistically significant difference in oral microbial community alpha diversity among the three groups. Beta-diversity assessed whether there were significant differences in microbial community between groups. While, the weighted-unifrac-based beta diversity of the oral microbial community differed significantly between the MMCS and control group (P <0.001), as well as between the MSCS and control group (P <0.001) [Figure 1A].Figure 1: Oral and intestinal microbiology, analysis. (A) Weighted-unifrac-based beta diversity of the oral microbial community among three groups. (B) Evaluation of alpha diversity of the intestinal microbial community using sobs indices among three groups. (C) Weighted-unifrac-based beta diversity of the intestinal microbial community among three groups. Cladogram using the LEfSe method indicating the phylogenetic distribution of the oral microbiotas (D,E) and gut microbiotas (F,G). The oral microbiotas (H,I) and gut microbiota (J,K) with significant differences between two groups (LDA score >2.0). * P <0.05, † P <0.01. LEfSe: Linear discriminant analysis effect size; MMCS: Minimal and mild coronary stenosis; MSCS: Moderate and severe coronary stenosis; NS: Not significant.Regarding gut microbial community alpha diversity, the sobs index of the control group was the highest and statistically significantly different from the other two groups (control group vs. MMCS group, P = 0.041; control group vs. MSCS group, P = 0.005; MMCS group vs. MSCS group, P = 0.027) [Figure 1B, Supplementary table 3, https://links.lww.com/CM9/B877]. The weighted-unifrac-based beta diversity of the gut microbial community showed statistically significant differences between the MMCS and control group, the MSCS and control group, and the MMCS and MSCS group (control group vs. MMCS group, P <0.001; control group vs. MSCS group, P <0.001; MMCS group vs. MSCS group, P <0.001) [Figure 1C]. Based on the abundance profiles, the features with significantly differential abundance across groups were determined using the Wilcoxon rank-sum test. Linear discriminant analysis effect size (LEfSe) analysis was utilized to detect biomarkers in saliva and feces [Figure 1D–K] for distinguishing MMCS and MSCS from normal coronary arteries. In saliva samples, compared to the control group, the MMCS group exhibited significantly increased levels of genus Tessaracoccus and Mobiluncus (P <0.05). Similarly, the MSCS group, when compared to the control group, showed significantly increased levels of the genus Howardella in saliva. Moreover, in the saliva of MSCS patients, compared to the control group, the order Cardiobacteriales and Burkholderiales, family Cardiobacteriaceae and Burkholderiaceae, genus Cardiobacterium and Lautropia, were significantly lower (P <0.05). In fecal samples, compared to the control group, the MMCS group exhibited significantly increased levels of the genus Fusicatenibacter, and significantly decreased levels of the genus Olsenella and Litorilinea (P <0.05). On the other hand, in the fecal samples of the MSCS group compared to the control group, the genus Desulfovibrio, Moraxella, and Actinomyces were significantly increased, while genus Ilumatobacter, Aeromonas and Loktanella were significantly decreased (P <0.05). The data presented in the study are deposited in the NCBI Sequence Read Archive repository, accession number: PRJNA1033397 and PRJNA1042880. Based on the orthogonal partial least-squares discriminant analysis (OPLS-DA) models of metabolite profiling data, we observed significantly different metabolite profiles in patients with MMCS and MSCS compared to control subjects [Supplementary Figure 1A and 1B, https://links.lww.com/CM9/B877]. These models identified 64 different metabolites in the MMCS group and 170 different metabolites in the MSCS group (screening criteria for differential metabolites: level ≤4, variable importance in projection≥1, fold change ≥1.2 or ≤0.83, P <0.05) [Supplementary Figure 2A and 2B, https://links.lww.com/CM9/B877]. Next, we analyzed the metabolites identified in the MMCS and MSCS groups using the receiver operating characteristic (ROC) curve to find the metabolic biomarkers of MMCS and MSCS in serum. The results of the area under the curve (AUC) are shown in Supplementary Table 3, https://links.lww.com/CM9/B877. Some of the differential metabolites with predictive value for MMCS included verrucarol, 3-hydroxytetradecanedioic acid (3-HA, and geranylacetone), among others. Similarly, the differential metabolites with predictive value for MSCS included glucuronic acid-3,6-lactone, 3-HA (1-oleoyl-rac-glycerol, and athamantin), among others. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results in MMCS group and MSCS group are showed in Supplementary Figure 1C and 1D, https://links.lww.com/CM9/B877. Inflammation serves as the primary mechanism in the regulation of CAS. Studies showed that the pathogenic bacteria involved in periodontitis may participate in the pathogenesis of CAS through direct inflammatory response.[2] Our studies also confirmed the results. Compared to the control grou

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