Abstract
Coronary heart disease (CHD) is top risk factor for health in modern society, causing high mortality rate each year. However, there is no reliable way for early diagnosis and prevention of CHD so far. So study the mechanism of CHD and development of novel biomarkers is urgently needed. In this study, metabolomics and metagenomics technology are applied to discover new biomarkers from plasma and urine of 59 CHD patients and 43 healthy controls and trace their origin. We identify GlcNAc-6-P which has good diagnostic capability and can be used as potential biomarkers for CHD, together with mannitol and 15 plasma cholines. These identified metabolites show significant correlations with clinical biochemical indexes. Meanwhile, GlcNAc-6-P and mannitol are potential metabolites originated from intestinal microbiota. Association analysis on species and function levels between intestinal microbes and metabolites suggest a close correlation between Clostridium sp. HGF2 and GlcNAc-6-P, Clostridium sp. HGF2, Streptococcus sp. M143, Streptococcus sp. M334 and mannitol. These suggest the metabolic abnormality is significant and gut microbiota dysbiosis happens in CHD patients.
Highlights
Screening and the Coronary heart disease (CHD) risk prediction at early stage
mass spectrometry (MS)-based metabolomics approach was applied to study the metabolic phenotype variations between CHD patients (n = 53) and healthy controls (n = 49) with complementary metagenomics technology for bacterial metabolites associated intestinal flora discovery. Among these 59 CHD patients, 32 patients had undergone Percutaneous Coronary Intervention (PCI) before but no difference had been observed between these 32 postoperative patients group and those 27 patients group with no surgery, suggest the PCI did not influence the whole metabolic pattern in patients
Some conditions were not taken into considerations in our study, such as age, gender, BMI, pre-clinical treatments (medications for hypertension, nonsteroidal anti-inflammatory drug (NSAID) use, prescribed lipid-lowering drugs etc), cardiovascular disease history, physical activity, special diet, dietary supplement use, total energy intake per day, cigarette smoking, sleeping, education, overweight, obesity, family genetics
Summary
Screening and the CHD risk prediction at early stage. So non-invasive and highly accurate approaches to diagnose and predict CHD are urgently needed. Choline and phosphatidylcholine from diet could be metabolized to trimethylamine (TMA) by intestinal microbiota which would be further metabolized to a proatherogenic factor – trimethylamine-N-oxide (TMAO), which has proved to accelerate atherosclerosis in mice by chronic dietary L-carnitine and associate with increased risks for both prevalent CVD and incident major adverse cardiac events (myocardial infarction, stroke or death)[9,10]. To explore potential characteristic metabolites signatures associated with CHD, non-targeted metabolomics technique is performed to discover potential metabolites by analysis of plasma and urine samples, and metagenomics technology is applied to further validate the potential metabolites originated from the fecal metagenomics data of CHD patients and healthy subjects. Statistical and bioinformatics methods are used to identify significantly different metabolites that can discriminate CHD cases from healthy controls. Integrated analysis of metabolomics and metagenomics could pave a new way to reveal the interactions between host and gut microbiobes
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