Intestinal Flora and Inammation in Acute Coronary Syndromes

Background: Acute coronary syndromes (ACS) is closely associated with chronic low-grade inammation and gut microbiome composition. However, the composition and functional capacity of the gut microbiome in relation to ACS have not been systematically examined. Results: we perform a metagenome-wide association study on stools and plasma from 66 individuals with ACS and 46 healthy controls (HC). We then compared gut microbial composition using 16S ribosomal RNA gene sequencing in fecal samples to detect species with differential abundance between 2 groups. We reported that the altered composition of gut microbiota was associated with ACS and exacerbated inammatory status. Moreover, parameters in ACS including body weights (BWs), low-density lipoprotein (LDL), triglyceride (TG), total cholesterol (TC), C-reactive protein (CRP) and high homocysteine (HCY) were elevated; whereas high-density lipoprotein (HDL) was decreased. pro-inammatory interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α, monocyte chemoattractant protein-1(MCP-1) and lipopolysaccaride (LPS) in ACS were increased respectively. The results of 16S rRNA sequencing and analysis displayed that the overall community of gut microbiota in ACS was notably changed mainly through increasing the abundance of Bacteroidetes, Verrucomicrobia, Proteobacteria Parabacteroide, Unidentied_Enterobacteriaceae, Subdoligranulum, Akkermansia, Alistipes, Streptococcus, Paraprevotella as well as decreasing Subdoligranulum, Roseburia, Faecalibacterium, Blautia, Agathobacter, Anaerostipes, Bidobacterium. Further analysis showed that there was a signicant correlation between the above differences in gut microbiota and inammatory factors. Conclusions: Our data represent a comprehensive resource for further investigations on the role of the gut microbiome or preventing ACS. intestinal ora disorder. Therefore, this study analyzed the relationship between inammatory factors and intestinal ora, especially the correlation between differential bacteria and inammatory factors including IL-1β, IL-6, TNF- α, MCP-1, IL-10, LPS. The results showed that the relative abundance of Firmicutes was positively correlated with plasma IL-1β, TNF- α, IL-6, MCP-1 and LPS, while the relative abundance of Bacteroidetes was negatively correlated with inammatory factors IL-1β and TNF-α. The abundance of Bacteroides was negatively correlated with IL-1β, TNF- α, MCP-1 and LPS, while Akkermansia was positively correlated with IL-10, revealing that the disturbance of intestinal ora and inammatory indexes were closely correlated with each other in myocardial infarction. Interestingly, increases in both pro-inammatory and anti-inammatory factors suggested that there were dynamic changes of inammation in AMI and UAP.


Background
Acute Coronary Syndromes (ACS) are a group of disorders that can be caused by a signi cant reduction of blood ow in coronary arteries due to narrowing or blockage of the vessels, including unstable angina pectoris (UAP) and acute myocardial infarction (AMI) [1]. The most common reason of the vessel dysfunction is the development of atherosclerotic lesions and a blood clot formed in place of plaque rupture [2]. Cardiovascular disease is the leading cause of death worldwide. Atherosclerosis AS , the most common cause of cardiovascular disease, is the result of a complex series of events occurring within the arterial wall involving rheology, lipid metabolism, and in ammation [3]. Growing evidence has implicated gut microbiota alterations in the development of cardiovascular disease [4]. Next generation sequencing techniques and multi-omics approaches have dramatically expanded our knowledge of the intestinal microbial world [5].
The gut microbiota, comprising the trillions of bugs inhabiting the gastrointestinal tract, may be considered a complex bioreactor with several metabolic and immunological effects that extend beyond the gut itself [6]. Previous studies found that intestinal ora disturbance may lead to the occurrence or aggravation of coronary heart disease (CHD) to a certain extent [7]. Atherosclerotic heart disease is not only a lipid disorder but also a chronic in ammatory disease [8]. The formation and rupture of atherosclerotic plaque are related to high levels of gut microbiota-derived lipopolysaccharide (LPS) and in ammatory cytokines in the circulation [9]. Moreover, Trimethylamine (TMA) and TMA N-oxide, which are gut microbiota metabolites of dietary phosphatidylcholine, are known to be associated with cardiovascular disease and the atherosclerosis process in particular [10,11].
At present, a large number of studies have found that there is a serious systemic or local in ammatory response in ACS, and the degree of in ammatory reaction is related to the occurrence of coronary events. With the aggravation of in ammatory reaction, it may increase the occurrence of myocardial infarction and sudden death caused by coronary plaque rupture and thrombosis.
The changes of intestinal ora and in ammatory factors in ACS and their relationship are not clear in the north-western parts of China, so this study was to explore the changes of intestinal ora and immune in ammatory factors in ACS such as acute myocardial infarction (AMI) and unstable angina pectoris (UAP).
To address this, in this study, fecal samples from ACS patients and healthy controls were collected, variable regions of gut bacterial 16S rRNA were ampli ed, and DNA library was constructed. Then, highthrough put sequencing was used to assess the taxonomic composition of the gut microbiota in ACS patients. The data of this study may provide a theoretical basis of the development and progress of ACS and intestinal ora Methods Study population A cohort composed of 66 patients with ACS was recruited to the Department of Internal Medicine of the Heart Center in Hospital of Ningxia Medical University from April 2019 to October 2019 consecutively, and 30 healthy volunteers were recruited from the hospital health examination center during the same period. The subjects were Chinese residents aged 18-70 years, convenience sample is de ned as a non-probability/non-random sample of subjects nearest and most available to participate in this study. Inclusion criteria were diagnosed of UAP or STEMI, de ned as follows: TEMI diagnostic criteria. cardiac troponin (cTn) I/T > the upper limit of the normal reference value or creatine kinase isoenzyme > the upper limit of the normal reference value; electrocardiogram (ECG) showed ST segment elevation on 2 or more adjacent leads; and one or more of the following: persistent ischemic chest pain, abnormal segmental wall motion upon ECG, and abnormal coronary angiography. UAP diagnostic criteria. cTnI/T negative; ischemic chest pain; and either transient ST-segment depression / low-level Twave or inverted, rare ST-segment elevation upon ECG. Exclusion criteria: history of organic digestive system or digestive tract surgery; history of stroke, diabetes, kidney disease or respiratory diseases; history of alcohol abuse; infection within one month of the study or the use of a probiotic, antacid, antibiotic, or antibiotic preparation. Ethical considerations The study protocol was approved by the Ethics Committee of Hospital of Ningxia Medical University (2020-527) and all participated subjects provided signed informed consent. All procedures performed in studies relating to human participants were in accordance with the ethical standards of the Helsinki declaration and its later amendments or comparable ethical standards. Specimens Fasting blood specimens and fresh stool specimens were collected and centrifuged at 4 °C, 3000xg for 10 min, and the supernatant (serum, plasma) was frozen and stored at −80 °C for testing. The morning fresh fecal specimens (>300 mg) were collected from the AMI group, UAP group, AS group and the healthy control group, sealed and transported to the sample bank at 4 °C. Fecal specimens (300 mg) were placed into a sterile externally-circulated cryotube, and then sealed and placed in a refrigerator at −80 °C for storage. Determination of Plasma In ammatory Indicators Plasma and ovarian in ammatory cytokines including IL-1β, IL-6, IL-10, monocyte chemoattractantprotein-1 (MCP-1) and TNF-α were respectively measured by ELISA kits according to the manufacturer's instructions (Shanghai Jianglai Biotech, Shanghai, China). The sensitivities of the assays were 0.1, 1.0, 0.1, 1.0, and 0.1 pg/mL for IL-1β, IL-6, IL-10, TNF-α, and MCP-1, respectively. Each sample was tested in triplicate. The plasma LPS levels in each group were examined using a limulus amebocyte lysate kit (Xiamen Bioendo Technology Co, Ltd, Xiamen, China) according to the manufacturer's instruction. Brie y, 50 µl of diluted plasma (1:4 dilutions with endotoxin-free water) was dispensed to each well in a 96-well plate. At the initial time point, 50 µl of the limulus amebocyte lysate reagent was added, respectively. The plate was incubated at 37•C for 30 min. Then, 100 µl of the chromogenic substrate warmed to 37•C was added to each well, and incubation was extended for an additional 6 min at 37•C. The reaction was stopped by adding 100 µl of 25% solution of glacial acetic acid. Optical density at 545 nm was measured with a microplate reader (Thermo Scienti c, USA). Gut microbiota analysis Extraction of bacterial DNA by cetyltrimethylammonium ammonium bromide (CTAB) was performed by adding the appropriate amount of lysozyme and sample to 1,000 µl CTABlysate. The mixture was placed in a 65•C water bath and mixed by inversion several times in order to facilitate the complete lysis of the sample. Next, phenol (pH 8.0), chloroform, and isoamyl alcohol were added to the supernatant after centrifugation so that the ratio of the three was 25:24:1, with mixing by inversion and centrifugation at 12,000 × g for 10 min. In the same way, chloroform and isoamyl alcohol (24:1) were added to the obtained supernatant, followed by centrifugation. The collected supernatant was added with isopropanol. The mixture was precipitated at −20•C after shaking up and down. Then, the mixture was centrifuged again according to the previous centrifugation conditions. The obtained precipitate was washed twice with 1 ml 75% ethanol. Then, the precipitate was blown dry on a clean bench or air-dried at room temperature. The DNA samples were dissolved in ddH2O. If the sample was di cult to dissolve, it needed to be incubated at 55-60•C for 10 min. Finally,1 µl of RNase A was added to the dissolved DNA sample, which was allowed to be kept at 37•C for 15 min to obtain bacterial DNA. The extracted DNA was stored at −20•C until application. The DNA sequences involving the V3 and the V4 regions of the 16S rDNA hypervariable regions were ampli ed by PhusionR, High-Fidelity PCR Master Mix with GC Buffer (New England Biolab, USA) using the following primers (5′to 3′): 341F-CCTAYGGGRBGCASCAG, 806R-GGACTACNNGGGTATCTAAT. The PCR product was analyzed and separated on 2% agarose gel, which was puri ed using the GeneJE Gel Recovery Kit (Thermo Scienti c, USA). The library was constructed using the TruSeqR DNA PCR-Free Sample Preparation Kit in order to carry out Qubit quantitation and library detection. After passing the test, the library was sequenced using the iIllumina HiSeq 2500 platform by Beijing Novogene Technology Co., Ltd., China. Statistical analysis. Demographic and clinical characteristics, prognostic markers, and microbial taxa are presented as n (%) for sex and mean ± standard. Differences between groups were compared using Fisher's exact test for sex; two-sample comparison was used t-test while numerical data with normal distribution; Mann-Whitney U test was used for numerical data without normal distribution; one-way ANOVA for numerical data after adjusting for variables that varied signi cantly by demographic or clinical characteristics. All statistical assessments were two-tailed and considered signi cantly at P < 0.05. All statistical analyses were carried out using IBM SPSS statistical software version 26 (IBM Corp., Armonk, NY , USA) and Graphpad 8.0.

Results
Study population. Comparison of general data between the HC and ACS group. There were no statistically signi cant differences in age, sex, previous history of basic diabetes between the HC and the ACS groups (P>0.05), and the data were comparable (Table 1). A total of 66 consecutive cardiology patients were enrolled according to the exclusion criteria, the remaining 66 were divided in three groups for analysis: an ACS group, including 31AMI patients, 29 UAP patients and 6AS patients; and a control group comprising 46 healthy volunteers, no evidence of enrollment bias was found.
Characteristics of study participants. The baseline characteristics of UAP patients, AMI patients, AS patients and healthy controls were shown in Table 1. Compared to healthy controls, parameters in ACS including body weights (BWs), low-density lipoprotein (LDL)(Fig1), triglyceride (TG), total cholesterol (TC), C-reactive protein (CRP) and high homocysteine (HCY) were elevated; whereas high-density lipoprotein (HDL) were decreased.
Gut microbial pro le in patients with ACS and HC diversity index analysis Shown in Figure2.A and B, with the increase of sample sequencing depth, the observed species index curve tended to be at, indicating that the current sequencing depth is su cient to detect predominant species contained in each sample. The abundance was re ected by the length of the curve on the horizontal axis and the evenness was re ected by the shape of the curve. After analyzing the rankabundance curve about OTU of the samples, we found a smooth curve, indicting high evenness among samples. The gut microbiota of HCs and patients with ACS showed consistent values in the analysis of observed species and Shannon diversity index. Figure2C represented species diversity and indicated signi cant differences in the number of species among AS-HC (p=0.0000), HC-UAP (p=0.0000) and AMI-HC (p=0.0000). There was no signi cant difference in the number of species among AMI-AS (p=0.7204) AMI-UAP (p=0.792) and AS-UAP (p=0.8776). It was suggested that there were signi cant differences between the disease group (AMI, UAP, AS) and the healthy group. There was no difference in comparative analysis between disease groups. Figure.2D representing the Shannon index found the signi cant differences in HC-UAP (p=0.0000), AMI-HC (p=0.0001) and AS-HC (p=0.0291). There was no signi cant difference in Shannon index between AS-UAP (p=0.5457), AMI-AS (p=0.7100) and AMI-UAP (p=0.7232). Principle Coordinate Analysis (PCoA) (weighted UniFrac distance) between the ACS and control groups showed distinguished in total (Fig. 2C), top 40 abundant stool microbial taxa, and overlapping clustering (Fig.2D) was observed in AMI, UAP and AS groups. β diversity analysis Based on unweighted UniFrac distance and Bray-Curtis distance matrices of the 16S rRNA sequence, samples contribution rates of the rst pCoA(PC1), second pCoA(PC2) were 21.45% and 9.25%, respectively, which highlighted a clear clustering of the microbial populations of the ACS patients away from that of the healthy controls.(A) NMDS(B) showed that the ACS and control groups were distinguished by total (Fig. 3A) or top 40 (Fig. 3B) abundant stool microbial taxa (stress=0.16, Stress<0.2), and overlapping clustering was observed in AMI, UAP and AS groups.

OUT analysis
A Venn diagram (Fig.4) showed that 789 OTUs were commonly detected between HC and AMI, common OTUs in the two groups of HC and UAP were 788, 632 OTUs were generally recognized between HC and AS, in addition, 596 OTUs were commonly detected in the four groups, while 450, 91, 144 and 20 OTUs were unique in the HC, AMI, UAP, or AS, respectively.
The ACS and HC samples were signi cantly different in multivariate analyses. At the phylum level (Fig.  5), compared to healthy controls, the dominant stool microbes in the ACS group were Firmicutes, Bacteroidetes, Proteobacteria. The relative abundances of Bacteroidetes, Proteobacteria, and Verrucomicrobia were increased, while Firmicutes was decreased in the ACS group compared to the HC group(p<0.05). At the genus level (Fig. 6), compared to HC group, the levels of Bacteroides, Parabacteroide, Unidenti ed Enterobacteriaceae, Subdoligranulum, Akkermansia, Alistipes, Streptococcus, Paraprevotella and Paraprevotella were signi cantly increased, whereas Subdoligranulum, Roseburia, Faecalibacterium, Blautia, Agathobacter, Bi dobacterium and Anaerostipes were signi cantly reduced.
Further analysis of the vegetation of the AMI, UAP, AS and HC healthy groups using the network diagram showed that there are signi cant differences in four groups (Fig.7). Compared with the entire HC group, the dominant ACS bacteria (AMI, UAP) in Bacteroides, Parabacteroide, Unidenti ed_Enterobacteriaceae and Subdoligranulum were increased signi cantly. Akkermansia, Anaerostipes Blautia, Agathbacter were decreased signi cantly. The abundances of Alistipes, Streptococcus and Paraprevotella were also higher in ACS than those in control samples.

Correlations of changes in clinical indexes, in ammatory factors with alterations in intestinal ora
According to the correlation between clinical acute coronary syndrome and clinical correlation index and ora in ammation, we further analyzed the correlation between clinical related indexes such as age (Age), body mass index (BMI), alanine aminotransferase (ALT), hyperhomocysteine (HCY) and differential bacteria (Fig. 9A). The analysis of the relationship between age and differential bacteria found that age was negatively correlated with Firmicutes, but positively correlated with Bacteroidetes, Proteobacteria and Verrucomicrobia, suggesting that under disease conditions, the increase of age had obvious in uence on the disorder of micro ora. BMI was negatively correlated with Firmicutes and positively correlated with Bacteroidetes. In the disease condition, changes in body weight affected microbial changes. ALT was negatively correlated with Firmicutes and positively correlated with Bacteroidetes, suggesting that liver function damage was closely related to the bacterial community. HCY was positively correlated with Proteobacteria and Bacteroidetes, and negatively correlated with Firmicutes. There was a correlation between HDL-C and different bacteria. HDL-C is positively correlated with Firmicutes, negatively correlated with Bacteroidetes, and positively correlated with F/B. There was no statistical difference in the correlation analysis between LDL-C and bacteria. It may be caused by the small number of cases, drug intervention and other related interfering factors. TG was negatively correlated with Firmicutes and positively correlated with Bacteroidetes. It was suggested that age, weight, liver function damage and HCY sepsis in AMI and UAP patients can affect the distribution of micro ora.
The relative abundance of Firmicutes was positively correlated with plasma in ammatory factors IL-1β, TNF-α, MCP-1 and LPS (Fig. 9B). The abundance of Bacteroides was negatively correlated with IL-1β, TNF-α, MCP-1 and LPS; Akkermansia was positively correlated with IL-10, and there was no signi cant difference in the correlation between IL-6 and Firmicutes and Streptococcus, suggesting that intestinal ora and in ammatory indicators interfered with each other and were closely related in ACS.

Discussion
Awareness increases markedly regarding the involvement of gut microbes in the development of numerous cardiometabolic disease [12][13][14]. Growing evidences have shown that intestinal micro ora plays an important role in the development of coronary heart disease. [15] The intestinal ora of healthy people was dominated by bene cial bacteria, with fewer harmful bacteria ,these two kinds of bacteria were dynamically balanced to maintain the health of the host. However, in abnormal conditions, the intestinal microbiota could be signi cantly changed by reducing bene cial bacteria and increasing harmful ora.
[16] Unbalanced intestinal micro ora could further worsen the disease, leading to a vicious circle. Studies have shown that intestinal micro ora imbalance was closely related to infectious diseases, in ammation and metabolic diseases. The imbalance of intestinal micro ora can lead to the disorder of bacterial structure and destroy the basic metabolic process of the host, which may be closely related to the occurrence of cardiovascular diseases such as coronary heart disease, hypertension and heart failure [17][18][19][20].
A large number of studies have shown that intestinal ora was involved in the process of atherosclerosis, but the speci c regulatory role was unknown. Recent macroeconomic studies displayed the expression pro le of intestinal microorganisms in patients with coronary heart disease, but the e cacy of speci c intestinal ora in the prevention and treatment of coronary heart disease were still unclear [21].The purpose of this study was to explore the changes of bacterial diversity among ACS(AMI, UAP), AS patients and healthy controls. The results showed that compared with healthy group, there were signi cant ora changes in acute myocardial infarction and unstable angina pectoris, and there were also ora changes between AS and HC healthy controls, which were consistent with previous studies [22]. It was also supported that there were signi cant differences in intestinal ora in patients with atherosclerosis. At the same time, there was no difference between AMI and UAP, AMI and AS, UAP and AS, which may be related to clinical complexity, such as multiple unknown risk factors, drugs and so on.
In this study, dilution curve, rank-abundance, species richness, shannon index, PCoA and NMDS were separately used to analyze the diversity of different samples and species. The results showed that there were obvious changes in AS vs. HC, HC vs. UAP and AMI vs. HC ora, supporting that the ora distribution of coronary atherosclerotic heart disease and AS patients was signi cantly different from that of healthy controls [23].
In this study, the common and unique OUTs among diverse groups were obtained from the Wayne diagram (VennGraph). There were 789 species of common bacteria in AMI and HC healthy groups, 368 species of endemic bacteria in AMI, 788 species of endemic bacteria in UAP and HC healthy groups, 414 species of endemic bacteria in UAP, 632 species in healthy groups of AS and HC, and 182 species of endemic bacteria in AS. There were 596 species of healthy bacteria in AMI, UAP, AS and HC. It was further suggested that there were signi cant differences in ora between the disease group and the healthy group.
Further analysis on the ora composition at the phylum and genus level, compared with the healthy group, at the phylum level: Firmicutes, Bacteroidetes and Proteobacteria were the main dominant ora, the relative abundance of Firmicutes was decreased signi cantly, the relative abundance of Bacteroidetes was increased signi cantly, the F/B ratio was decreased, and the relative abundance of Verrucomicrobia was increased signi cantly. At the genus level, there were also ora differences among the four groups. Compared with the HC healthy group, ACS (AMI, UAP) analysis showed that Bacteroides Unidenti ed_Enterobacteriaceae Subdoligranulum Alistipes, Streptococcus, Akkermansia and Parabacteroide were increased signi cantly, Subdoligranulum, Roseburia, Faecalibacterium, Blautia, Agathobacter, Anaerostipes, Bi dobacterium were decreased signi cantly. Butyrate-producing bacteria played a key role in human health, and these bacteria, including Roseburia, Subdoligranulum and Faecalibacterium , were relatively depleted in atherosclerotic cardiovascular disease (ACVD) and type 2 diabetes (T2D) samples [24]. The butyrate-producing bacterium Roseburia was inversely correlated with atherosclerotic lesion development in mice, and the addition of Roseburia in combination with a high-ber diet reduced the sizes of atherosclerotic plaques in the aorta. Faecalibacterium was an anti-in ammation-associated bacterium that produced butyrate.
Treatment with atorvastatin increased the abundance of Faecalibacterium in 27 hypercholesterolemic patients compared with that found in 15 untreated hypercholesterolemic patients [25] .The results of this study were consistent with the results of Emoto et al.
[26] using terminal restriction fragment length polymorphism (T-RFLP) and 16s rRNA to study the differences of intestinal microorganisms between patients with coronary heart disease and healthy volunteers in 2016. The results showed that the number of mature Lactobacilli increased signi cantly, but Bacteroides (Bi dobacterium and Proteus) were notably decreased in patients with coronary heart disease. In addition, the ratio of Firmicutes to Bacteroides was increased signi cantly. The results were consistent with the results reported by Karlssion et al in 2012 [21]using genome-wide sequencing to determine the possible link between changes in intestinal micro ora and atherosclerotic heart disease. Compared with healthy people, the number of Escherichia coli was increased, while numbers of Rosella and Eubacterium were decreased.
In ammation was an important process of myocardial infarction, which was caused by the release of cytokines and activation of the immune system in the injured myocardium [27][28][29]. In the rst 24-72 hours after myocardial infarction, cardiomyocyte injury triggered the activation of macrophages mediated by damage-associated molecular patterns (DAMPs), which secreted pro-in ammatory cytokines including IL-1β, IL-6 and TNF-α. The cascade release of in ammatory factors aggravated brosis, microvascular and myocardial dysfunction. In this study, when intestinal ora disturbance occurred in ACS patients, the intestinal mucosa would be damaged to lead to excessive in ammatory response with elevated serum levels of CRP, IL-6, MCP-1 and TNF-α, which may contribute to the pathogenesis of atherosclerotic diseases. At the same time, we analyzed the presence of intestinal ora disorder in ACS. At present, a large number of studies have shown that in ammatory factors were closely related to intestinal ora disorder. Therefore, this study analyzed the relationship between in ammatory factors and intestinal ora, especially the correlation between differential bacteria and in ammatory factors including IL-1β, IL-6, TNF-α, MCP-1, IL-10, LPS. The results showed that the relative abundance of Firmicutes was positively correlated with plasma IL-1β, TNF-α, IL-6, MCP-1 and LPS, while the relative abundance of Bacteroidetes was negatively correlated with in ammatory factors IL-1β and TNF-α. The abundance of Bacteroides was negatively correlated with IL-1β, TNF-α, MCP-1 and LPS, while Akkermansia was positively correlated with IL-10, revealing that the disturbance of intestinal ora and in ammatory indexes were closely correlated with each other in myocardial infarction. Interestingly, increases in both pro-in ammatory and anti-in ammatory factors suggested that there were dynamic changes of in ammation in AMI and UAP.  Clinical indexes in different groups. * P<0.05 ** P<0.01 *** P<0.001.     Plasma from 4 groups were respectively collected for the determination of tumor necrosis factor (TNF)-α; monocyte chemoattractant protein-1(MCP-1); interleukin (IL)-6; IL-1β and IL-10 concentrations using ELISA kit. Plasma lipopolysaccharide (LPS) levels in diverse groups were determined using a Limulus amebocyte lysate kit. * P<0.05.