Diversified Shifts in the Cross Talk between Members of the Gut Microbiota and Development of Coronary Artery Diseases

• Published in: Microbiology spectrum 2022-12, Vol.10 (6), p.e0280422-e0280422
• Main Authors: Zhang, Tao, Ren, Haiqing, Du, Zhihui, Zou, Tong, Guang, Xuefeng, Zhang, Yanan, Tian, Yuqing, Zhu, Lei, Yu, Jiangkun, Yu, Xue, Zhang, Zhigang, Dai, Hailong
• Format: Article
• Language: English
• Subjects: acute myocardial infarction; CAD; Clinical Microbiology; Coronary Artery Disease - diagnosis; Coronary Artery Disease - drug therapy; Gastrointestinal Microbiome - genetics; gut microbiota; Humans; Hypertension; Microbiota; mild coronary stenosis; Myocardial Infarction; Research Article; stable angina; unstable angina
• ISSN: 2165-0497; 2165-0497
• DOI: 10.1128/spectrum.02804-22

Coronary artery disease (CAD) is one of leading causes of mortality worldwide. Studies on roles that the gut microbiota plays in development of atherosclerosis or acute myocardial infarction (AMI) have been widely reported. However, the gut microbiota is affected by many factors, including age, body mass index (BMI), and hypertension, that lead to high CAD risk. However, the associations between gut microbiota and CAD development or other CAD risk factors remain unexplored. Here, we performed a 16S RNA gene sequencing analysis of 306 fecal samples collected from patients with mild coronary stenosis (MCS;  = 36), stable angina (SA;  = 91), unstable angina (UA;  = 48), and acute myocardial infarction (AMI;  = 66) and 65 non-CAD controls. Using a noise-corrected method based on principal-component analysis (PCA) and the random forest algorithm, we identified the interference with gut microbial profiling of multiple factors (including age, gender, BMI, and hypertension) that potentially contributed significantly to the development of CAD. After correction of noise interference from certain interfering factors, we found consistent indicator microbiota organisms (such as , , and ) associated with the presence of MCS, SA, and AMI. Establishment of a diagnostic model revealed better performance in early CAD than clinical indexes with indicator microbes. Furthermore, indicator microbes can improve the accuracy of clinical indexes for the diagnosis of AMI. Additionally, we found that the microbial indicators of AMI and showed consistent positive and negative correlations to the clinical indexes creatine kinase (CK) and hemoglobin (Hb), respectively. As a control indicator of AMI, was negatively correlated with CK but positively correlated with Hb. Our study discovered the effect of confounding factors on gut microbial variations and identified gut microbial indicators possibly associated with the CAD development after noise correction. Our discovered indicator microbes may have potential for diagnosis or therapy of cardiovascular disorders.