Analysis of fecal flora in patients with hypertension complicated with ischemic stroke

doi:10.21203/rs.3.rs-2562136/v1

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Research Article

Analysis of fecal flora in patients with hypertension complicated with ischemic stroke

https://doi.org/10.21203/rs.3.rs-2562136/v1

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published 26 Sep, 2023

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Ischemic stroke is a disease with a very high incidence in the clinic, and hypertension is the most important variable risk factor of ischemic stroke. Studies have shown that intestinal microbes are involved in the occurrence and development of various diseases. The purpose of this study is to explore whether intestinal microbes play an important role in the pathogenesis of ischemic stroke in a hypertensive population. In this study, the inpatients in the Department of Neurology and Cardiology of the Second Affiliated Hospital of Shandong First Medical University in April 2021 were selected, including 7 patients with hypertension complicated with ischemic stroke and only 7 patients with hypertension. After collecting the stool samples of patients, the gene sequence of the samples was detected by 16SrRNA sequencing technology, and the double-ended 2×150bp sequencing was carried out. After sequencing, the results were analyzed by diversity analysis, species difference analysis, species function difference analysis, and other bioinformatics tests. According to the test results, serum proteomics and blood biochemical tests were carried out to verify. There was no significant difference in α diversity and β diversity between hypertension complicated with cerebral infarction group and the hypertension group. LEfSe analysis showed that at the genus level, compared with the hypertension group, Bacteroides, UCG_009, Eisenberg bacteria had significantly increased relative abundance. The genera with relatively significantly reduced abundance are Luminococcus, Methanobacterium, Burkholderia and Prevotella, and the LDA score of Prevotella is <-4, which indicates that there are significant differences. Compared with the blood biochemical indexes, the results showed that the level of APOA1 in hypertensive patients with ischemic stroke was significantly higher than that in hypertensive patients (p < 0.05), but there was no significant difference in total cholesterol (CHOL), triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), apolipoprotein B(APOB) and free fatty acid (NEFA). Proteomics analysis showed that there were 89 up-regulated genes and 51 down-regulated genes in the serum of the two groups, and the expression of APOC2 and APOC3 in the cerebral infarction group with hypertension was significantly higher than that in the hypertension group (p < 0.05). The intestinal diversity of patients with hypertension complicated with stroke is similar to that of patients with hypertension, but there are differences in flora, among which Prevotella is the most significant. Prevotella affects lipid metabolism so that APOC2 and APOC3 in the blood are significantly increased, which leads to cerebral artery atherosclerosis and finally ischemic stroke. This provides a new idea for the prevention and treatment of ischemic stroke in patients with hypertension, but it still needs further verification by basic medical research.

Ischemic stroke complicated with hypertension

Intestinal flora

16S rRNA

Ischemic stroke refers to the general name of brain tissue necrosis caused by narrow or occluded blood supply arteries (carotid artery and vertebral artery) and insufficient blood supply in the brain. As the second leading cause of death and the third leading cause of disability in the world, ischemic stroke has always been a common concern of human beings. In recent years, with the continuous extension of human life and the aging of the population, the incidence of ischemic stroke has also increased significantly (Roy-O'Reilly et al.,2018)), gradually becoming an important public health burden, so ischemic stroke Starting with its various risk factors is the most direct means to prevent stroke. Hypertension is the most important variable risk factor (Sarikaya et al,.2015)of stroke. Some studies have shown that treating hypertension can effectively reduce the risk of stroke (Paul et al,.2021). Therefore, it is very important to recognize the relevant mechanism between blood pressure and ischemic stroke.

There is a huge microbial community in the human body, the number of which is more than 10 times that of human cells (Sender et al,.2016). With the development of amplicon sequencing of 16S rRNA gene and whole genome sequencing, we can further understand the relationship between intestinal flora community structure and the human body. Intestinal flora is involved in a series of physiological processes that are vital to host health, including energy homeostasis, metabolism, intestinal epithelial health, immune activity, and neurobehavioral development. The metabolic capacity endowed by the genome exceeds that of a single host organism, which makes the intestinal microorganisms an active participants in host physiology (Barko et al,.2018). Intestinal flora can also lead to a variety of diseases, such as inflammatory bowel disease (IBD), inflammatory skin diseases (such as psoriasis and atopic dermatitis), autoimmune arthritis, type 2 diabetes, obesity, and atherosclerosis (Singh et al,.2018). In recent years, more and more studies have shown that intestinal flora and its metabolites play an important role in the risk factors of ischemic stroke such as hypertension, diabetes, and hyperlipidemia. The prevalence of hypertension is increasing year by year. In order to improve the prevention and control level of hypertension in China, the diagnostic threshold of hypertension has been lowered from systolic blood pressure ≥ 140mmHg and/or diastolic blood pressure ≥ 90mmHg to systolic blood pressure ≥ 130mmHg and/or diastolic blood pressure ≥ 80mmHg in China Clinical Practice Guide, which shows that people pay more and more attention to hypertension. Clinically, we found that hypertension is very common in the stroke population, and hypertension can promote ischemic stroke by increasing shear stress, endothelial dysfunction, and arteriosclerosis. Hypertension also promotes cerebral small vessel diseases through several mechanisms, including insufficient perfusion, decreased self-regulation ability, and local increase of blood-brain barrier permeability (Diener et al,.2020).

More and more studies have shown that hypertension can promote the occurrence of ischemic stroke (Cipolla et al,.2018). However, we know little about the relationship between the occurrence of ischemic stroke and intestinal flora in the hypertensive population. Therefore, this study applied 16s r RNA gene sequencing, proteomics, and other technologies to compare the flora differences between hypertensive patients and hypertensive patients with ischemic stroke, and to explore the role of different flora in the disease development. In order to further understand the internal relationship between the occurrence and development of ischemic stroke and intestinal microbes, and to provide reasonable data reference and research support for finding and treating ischemic stroke from intestinal microbes.

Detection of fecal flora

Research object:In this experiment, we enrolled patients who were hospitalized in the Department of Neurology and Cardiology of the Second Affiliated Hospital of Shandong First Medical University in April 2021, including 7 patients with hypertension complicated with ischemic stroke and only 7 patients with hypertension.

The admission criteria of hypertension complicated with ischemic stroke group are: (1) Age over 18 years old; (2) Clinical diagnosis of acute cerebral infarction, and the onset time is less than 10 days; (3) Volunteer to participate in this research. Exclusion criteria: (1) Connective tissue disease; (2) diabetes; (3) suffering from acute and chronic digestive diseases; (4) Patients who are delirious and unable to collect stool samples correctly.

The admission criteria of the hypertension control group: are (1) Age over 18 years old; (2) Volunteer to participate in this research. Exclusion criteria: (1) Previous history of cerebral infarction; (2) Connective tissue disease; (3) diabetes; (4) suffering from acute and chronic digestive diseases; (5) Patients who are delirious and unable to collect stool samples correctly.

During the hospitalization, the feces were collected, and the blood lipid, blood glucose, blood routine, and other test indexes were recorded. Collect the clinical information of the experimental group and the control group, including gender, age, current medical history, past history, etc. This study was approved by the ethics committee of our hospital, and all participating researchers were informed.

Collection of feces:Use a sterile cotton swab to dip 50mg of the middle stool of each of the patients with hypertension complicated with stroke and those with hypertension only, immerse it in the sampling tube of cereal flora storage buffer, rotate and stir it for 30 seconds, then tighten the cover of the sampling tube, shake it left and right for 10 seconds to complete the mixing, record the name and collection time of the sample, store it at room temperature, and send it for inspection within one week.

DNA extraction:Use the DNA extraction kit GHFDE100 (Zhejiang Hangzhou Equipment Preparation 20190952) to extract the metagenomic DNA from the sample according to the manufacturer's instructions.

PCR amplification and 16S rRNA detection method:The V4 region of bacterial 16S rRNA gene was amplified by PCR using forward primer 515f (515F(5‘-GTGCCAGCMGCCGCGGTAA-3'-3') and reverse primer 806r (5' ggactachvgggtwtctaat-3'). Sample-specific paired-end 6-bp barcodes are integrated into the TrueSeq adapter for multiple sequencing. The polymerase chain reaction consists of 25μl Phusion High-Fidelity PCR Master Mix, 3μ l (10μ m) forward and reverse primers, 10μl template DNA,3μl dimethyl sulfoxide, and 6μl DDH_2O. Heat cycle includes initial denaturation at 98℃ for the 30s, then 25 cycles, including denaturation at 98℃ for 15s, annealing at 58℃ for 15s, renaturation at 72℃ for 15s, and extension at 72℃ for 1min. PCR amplification products were purified with Agencourt AMPure XP magnetic beads and quantified with PicoGreen dsDNA Assay Kit. After the individual quantitative step, the amplified fragments were mixed in equal amounts, and the double-ended 2×150bp sequencing was carried out using the IllLumina NovaSeq6000 platform of Guhe Information Technology Co., Ltd.

Statistics and analysis of OTU data:The original sequencing readings that exactly match the barcode are assigned to the corresponding samples and identified as valid sequences. Low-quality sequences were screened by the following criteria: sequences with a length of < 150 bp, sequences with an average Phred score of < 20, sequences with fuzzy bases, and sequences with single nucleotide repeats of > 8 bp. Use Vsearch v2.4.4 (-fastq _ mergepairs-fastq _ minovlen5) to assemble end-to-end reading, and then use Vsearch v2.15.0 to select the operational taxon (OTU), including de-replication, clustering and chimera detection. A microbial quantitative insight pipeline is used to process OTUs and sequencing data. According to the representative sequence set of SILVA138 database, OTU taxonomy was carried out.

Further, the OTU table is generated to record the abundance of each OTU in each sample and the classification of these OTUs. All samples were discarded, which contained less than 0.001% OTU of the total sequence. In order to minimize the difference of sequencing depth among samples, an average and rounded thin OTU table is generated by averaging 100 uniformly resampled OTU subsets at the minimum sequencing depth of 90% for further analysis.

Bioinformatics and Statistical Analysis:Sequence analysis is mainly carried out by using QIIME2 and R software packages (version 3.2.0). Use OTU table in QIIME2 to calculate OTU-level α diversity index, such as Chao1 richness estimate, ACE measure (coverage estimate based on abundance), PD_whole_tree, Shannon diversity index and Simpson index. Generate the ordered abundance curve of OTU level to compare the abundance and uniformity of OTUs among samples. UniFrac distance measurement was used for β diversity analysis to investigate the structural changes of microbial communities in the samples, and it was visualized by principal coordinate analysis (PCoA) and non-metric multidimensional scale (NMDS). Students' T-test and Monte Carlo permutation test with 1000 permutations were used to determine the difference of Unifrac distance between groups, and visualized by box diagram. Principal component analysis (PCA) is also based on the composition profile of genus level. R package "vegan" was used to evaluate the significance of microbial community structure differences among groups by PERMANOVA (displacement multivariate analysis of variance). Venn diagram is generated by using R package Venn diagram according to the occurrence of OTU in samples/groups (regardless of its relative abundance) to show the shared and unique OTU between samples or groups.

The abundance of taxa at the level of phylum, class, order, family, genus and species in a sample or group was statistically compared by Kruskal.test in R stats software package. LEfSe (Linear Discriminant Analysis Effect Size) is executed with default parameters to detect the difference between different groups and enrich the classification groups. Random forest analysis is used to distinguish samples from different groups using R package "Random Forest", which has 1,000 trees and all default settings. Use 10x cross-validation to estimate generalization error. The expected "baseline" error of is also included, which is obtained by simply predicting the classifiers of the most common category labels. Co-occurrence analysis was carried out by calculating Spearman rank correlation among dominant taxonomic groups.

Based on high-quality sequences, the microbial function was predicted by PICRUST 2 (phylogenetic investigation of the community by reconstructing unobserved state, https://github.com/picrust/picrust2/). The bacterial function database and gut-brain module (GBMs) were also analyzed by using human gut metabolism module. For each sample, the function is analyzed using OMixer-RPM version 1.0 (https://github.com/raeslab/omixer-rpm) with KO redundancy predicted from PICRUSt 2.

The blood serum of patients hospitalized in the Second Affiliated Hospital of Shandong First Medical University in September 2022 was collected, including 2 patients with hypertension complicated with ischemic stroke and only 3 patients with hypertension. Add 2 L serum sample into 96-well plate, and further dilute 0.1M nh4hc 3 (Sigma, Missouri, USA), 6 M urea (Sigma, Missouri, USA), and 2 M thiourea (Sigma, Missouri, USA) with lysis buffer containing the following components. The disulfide bond was reduced at 33℃ for 45 minutes at 600 rpm, and 10 mM tris (2- carboxyethyl) phosphine hydrochloride (TCEP) was added and alkylated with iodoacetamide. All crude protein extracts were precipitated with acetone at 20℃ for 2 h, and then re-dissolved with 200μl Teab buffer. Then it was digested with trypsin at 37℃ overnight, and then TFA was added to extinguish it. Sep-Pak column of Waters Co was used to desalt these peptides.

Orbitrap Eclipse mass spectrometer and Easy-NLC 1200 system were used for data acquisition, and the chromatographic column was ACRADEST PepMapTM 100 C18 column (75μ m× 2cm, nanviper, 3μ m, 100, Thermoscience). The flow rate is 300nL/min. Mobile phase A is 5% acetonitrile +0.1% formic acid (v/v, the best LC/MS grade), mobile phase B is 80% acetonitrile +0.1% formic acid (v/v, the best LC/MS grade), mobile phase B is 3% ~ 5% B, 0.05 min; 5%~15%B,23.55 m in; 15%~28%B,21 m in; 28%~38%B,7.3 m in; 38%~100%B,0.05 m in; 100%B 7.25 m in。 The MS conditions are as follows: ion funnel Rf is 40,Ms1 Orbitrap resolution is 60000 (m/z 200), and MS1 maximum sampling time is 20ms. The charge state of the polypeptide is 2-7. Data-dependent acquisition mode was used to trigger precursor separation and sequencing. The MSOrbit RAP resolution is set to 15000(m/z200), and the high energy collision induced dissociation (HCD) with normalized collision energy is 30%. The MS2 isolation window is set to 1.6 Da.

Thermoproteome Discoverer (PD, 2.4.1.15) was used to carry out feature detection, database search and protein/polypeptide quantification on all original documents. The identity of MS polypeptide sequence and protein was determined by matching fragment patterns in the UniProt mouse database (downloaded on March 23, 2021, containing 17 040 sequences). Aminomethylation of cysteine residues is set as fixed modification. There are only two missing cleavages per peptide. The fragment quality tolerance is 0.02Da. Label-free quantification (LFQ) was calculated in each parameter group. Select unique polypeptide and razor polypeptide for protein quantification. Mass spectrometry protein omics data has been stored in ProteomeXchange consortium (http://proteomesscentral. proteomexc ange.org) through Pride partner repository with data set identifier PXD030026. Bioinformatics analysis was carried out using David, Cytoscape and OMICStudio tools. Only protein with p value < 0.05 was included in GO concentration analysis and network formation.

2.3 Analysis of hematological indicators

research object:This experiment enrolled the inpatients in the Department of Applied Neurology and Cardiology of the Second Affiliated Hospital of Shandong First Medical University from 2021 to 2022, including 80 patients with hypertension complicated with ischemic stroke and 48 patients with hypertension only.

The admission criteria of hypertensive stroke group are: (1) Age over 18 years old; (2) The clinical diagnosis is acute cerebral infarction, and the onset time is less than 10 days. Exclusion criteria: (1) Connective tissue disease; (2) diabetes; (3) suffering from acute and chronic digestive diseases; (4) Patients who are delirious and unable to collect stool samples correctly. The admission criteria of hypertension control group: (1) Age over 18 years old. Exclusion criteria: (1) Previous history of cerebral infarction; (2) Connective tissue disease; (3) Diabetes. The blood lipid, blood sugar, blood routine and other test indexes were recorded. Collect the clinical information of the experimental group and the control group, including gender, age, current medical history, past history, etc. This study was approved by the ethics committee of our hospital, and all participating researchers were informed.

detection methods:After fasting for 12 hours, 5ml venous blood was collected at 7-9am the next morning, serum was centrifuged, and seven blood lipids were analyzed by immunoturbidimetry. BECKMAN COULTER AU5800 automatic biochemical analyzer is adopted, and the operation procedures are strictly followed. The daily maintenance and quality control of the instrument are well done.

Reference range immunoturbidimetry :

Total cholesterol (CHOL): 2. 33 ~ 5.69 mmol/L.

TG (triglyceride): 0. 58 ~ 1.88 mmol/L.

High-density lipoprotein (HDL): 1. 03 ~ 1. 85mmol /L

Low-density lipoprotein (LDL): 2. 07-3. 33 mmol/L.

Apolipoprotein A (ApoA): 1 ~ 1. 6g /L

Apolipoprotein B (ApoB): 0. 6 ~ 1. 1g /L

Free fatty acid (NEFA): 0. 1 ~ 0. 6mmol /L

Statistical analysis:SPSS25.0 software is used, and the data is expressed by the mean standard deviation. If the data is normal, two independent samples T-test is adopted, but it is not normal, and a nonparametric rank sum test is adopted.

ELISA detection

This experiment enrolled the inpatients in the Department of Applied Neurology and Cardiology of the Second Affiliated Hospital of Shandong First Medical University in 2022, including 6 hypertensive patients with ischemic stroke and 4 hypertensive patients.

The admission criteria of the hypertensive stroke group are: (1) Age over 18 years old; (2) The clinical diagnosis is acute cerebral infarction, and the onset time is less than 10 days. Exclusion criteria: (1) Connective tissue disease; (2) diabetes; (3) suffering from acute and chronic digestive diseases; (4) Patients who are delirious and unable to collect stool samples correctly.The admission criteria of the hypertension control group: (1) Age over 18 years old. Exclusion criteria: (1) Previous history of cerebral infarction; (2) Connective tissue disease; (3) Diabetes. After fasting all night (at least 10 hours), blood samples were collected from the subjects' anterior elbow vein from 7:30 am to 9:00 am. The collected blood was coagulated at 4 C for 30 min, and then centrifuged at 3000 rpm at 4 C for 20 min. Immediately store the analysis sample at-20 C to avoid repeated freeze-thaw cycles. ELISA kit (Jiangsu Enzyme-free Industry Co., Ltd., Jiangsu, China, catalogue number E1766H1) was used to determine the concentration of APOC2 and APOC3, and the operation was carried out according to the manufacturer's plan.

Identification of intestinal microbial spectrum in patients with hypertension complicated with ischemic stroke

Analysis of α diversity and β diversity of intestinal microorganisms in hypertension group and hypertension complicated with stroke group:A total of 1372 OTUs were obtained from 14 samples, including 1013 OTUs in both groups, 100 unique OTUs in the hypercholesterolemic group and 299 unique OTUs in the hypertensive group with stroke, which indicates that compared with the hypertensive group, the hypertensive group with stroke has more specific OTU(Figure 1A). In this study, we used different multi-α diversity indexes to evaluate the difference of species richness and evenness between the two groups. The results showed that (Figure 1b), there was no significant difference in Chao 1, Shannon and Simpson indexes between hypertension group and hypertension complicated with stroke group (p > 0.05). Compared with hypertensive patients, the richness and uniformity of intestinal microbial species in hypertensive patients with stroke did not change significantly.

According to Anosim analysis (Figure 1C), there was no significant difference between and within the hypertension group and hypertension complicated with stroke group (R<0,P>0.05). In order to compare the similarities or differences between the two groups of samples, we conducted PCoA analysis and inter-group NMDS analysis. According to the results (Figure 1D-G), there was no obvious aggregation between the same group of samples, so there was no obvious difference in species composition between the two groups.

Analysis of intestinal flora difference between hypertension group and hypertension complicated with stroke group

At phylum level, the first three groups of dominant bacteria in the two groups are Bacteroides, Sclerotinia and Proteus (Figure 2A). At the level of two genera, the top three genera with the highest abundance in hypertension group are Prevotella, Bacteroides and Festuca. Bacteroides, Enterobacter, and Shigella (Figure 2B) are the top three with the highest abundance in hypertensive stroke group. The cluster heat map (Figure 2C,D) of species composition between different species and between groups shows the species with high abundance in the sample more intuitively. It represents the trend of relative abundance of species in hypertension group and hypertension complicated with stroke group. Post-cluster thermogram showed that Bacteroides had the highest abundance, followed by Enterobacter. LEfSe analysis can find the species with significant differences in abundance among groups. The experimental results show that (Figure 2E,F), at the genus level, compared with hypertension group, bacteroides, UCG_009 and Eisenberg bacteria with significantly increased relative abundance in hypertension group with stroke are respectively; The genera with relatively significantly reduced abundance are Luminococcus, Methanobacterium, Burkholderia and Prevotella, and the LDA score of Prevotella is <-4, which indicates that there are significant differences.

Analysis of the difference of intestinal flora function between hypertension group and hypertension complicated with ischemic stroke group

Based on the functional difference analysis of GMM metabolic module between the two groups (Figure 3A), the results showed that the difference of tryptophan degradation (p=0.009, p<0.01) and lysine I degradation (p=0.044,p<0.05) in hypertension combined with stroke group were significantly higher than those in hypertension group. Tryptophan can be hydrolyzed by tryptophanase into indole, ammonia and pyruvic acid, the latter being the key precursor to form acetyl CoA, which is used to generate energy through citric acid cycle (Bellmaine et al,.2020). The first step of lysine catabolism pathway is to form sugar crown base, followed by 2- aminoadipic acid. Through decarboxylation, 2- aminoadipic acid is converted into glutaryl-CoA and crotonyl-CoA, and finally oxidized into acetyl-CoA, which enters the tricarboxylic acid cycle (Matthews et al,.2020). To sum up, the intestinal flora of hypertensive patients with stroke is significantly higher than that of hypertensive patients in providing energy for the body.

Based on the functional difference analysis of Megacycle metabolic pathway database (Figure3B), the results showed that in hypertension complicated with stroke group, there were super pathway of lipopolysaccharide biosynthesis (p=0.0379), butyric acid II produced by acetyl-CoA fermentation (P = 0.0379), ketogluconic acid metabolism (p=0.002), butyl acetate produced by L- lysine fermentation (P = 0.002)gram-negativegermA unique kind of wall layer.chemistryComponent, bacterial lipopolysaccharide, also known as endotoxin, is an important component of the outer membrane of the cell wall of Gram-negative bacteria, which has the ability to produce a variety of inflammation-related factors and participate in inflammatory reaction. Studies have shown that ketogluconic acid metabolism can enhance the toxicity of some bacteria, such as Streptococcus pneumoniae (Hu et al,.2019). To sum up, hypertension with stroke group is stronger than hypertension group in promoting inflammatory reaction, bacterial toxicity and the production of some short-chain fatty acids.

Prokaryotic function of culturable bacteria between the two groups was predicted by FAPROTAX (Figure3C). The results showed that the reduction effect of nitric acid in hypertension group was significantly higher than that in hypertension complicated with ischemic stroke group (p=0.035). Studies have shown that nitric acid reduction can dilate blood vessels (Sindler et al,.2014).

Changes of serum protein in hypertensive patients with ischemic stroke.

We collected the serum of 2 patients with hypertension complicated with stroke and only 3 patients with hypertension. on the platform of protein omics, we used Orbitrap Eclipse mass spectrometer and Easy-NLC 1200 system to collect the data. The Thermoproteome Discoverer (PD, 2.4.1.15) was used to detect the features of all the original documents, search the database and quantify protein/polypeptide. The hierarchical cluster analysis (Figure4A,C) of 131 LFQ- protein intensities showed that there were 89 up-regulated genes and 51 down-regulated genes. APOC2 and APOC3 were expressed in hypertension complicated with stroke group.

KEGG analysis of differential protein (Figure4B) shows that the pathways related to differential proteins are: 1. Complement and coagulation cascade reaction; 2. Staphylococcus aureus infection; 3. Systemic lupus erythematosus; 4. Cholesterol metabolism; 5. Pertussis; 6. Puen virus disease; 7.ECM- receptor interaction; 8. Amoebiasis African trypanosomiasis; 9. Vitamin digestion and absorption. There are two groups of different genes in cholesterol metabolism pathway: APOA1, APOA2, APOA4, APOC1, APOC2, APOC3, APOB, LCAT(Figure4C).

To further verify the results of protein's omics analysis, we selected the serum of 6 patients with hypertension complicated with cerebral infarction and 4 patients with hypertension only, and compared APOC2 and APOC3 of the two groups by ELISA.The results show that the level of APOC2(p=0.043) and APOC3(p=0.002) in hypertension complicated with stroke is significantly higher than that in hypertension group(Figure4D,E).

Changes of hematological indexes in patients with hypertension complicated with stroke

In order to further explore the difference of related genes in cholesterol metabolism pathway between the two groups, we selected 80 hypertensive patients with cerebral infarction and 48 hypertensive patients only, collected 5ml venous blood at 7-9am, centrifuged the serum, and made seven blood lipid analysis by immunoturbidimetry (Table 1). The results in the table show the changes. The results show that the level of APOA1 in hypertension complicated with stroke is significantly higher than that in hypertension group (p=0.040), but there is no significant difference in blood glucose (GLU), total cholesterol (CHOL), triglyceride (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), apolipoprotein B(APOB) and free fatty acid (NEFA).

The number of microorganisms in human intestine is about 10¹⁴, including bacteria, viruses, fungi and protozoa. There are more than 1,000 kinds of bacteria in the intestine, and the intestinal flora plays a particularly important role in maintaining the health of the host (Gomaa et al,.2020). For example, Treg cells in the intestine maintain the anti-inflammatory environment of the intestine by inhibiting the differentiation of T helper (TH)17 cells and the proliferation of γδT cells (Benakis et al,.2016). At the same time, intestinal microbes can also lead to a variety of diseases, such as inflammatory bowel disease (IBD), inflammatory skin diseases (such as psoriasis and atopic dermatitis), autoimmune arthritis, type 2 diabetes, obesity and atherosclerosis (Singh et al,.2017). Studies have also shown that intestinal microbes are related to ischemic stroke. After stroke, the ecological imbalance of intestinal microbes leads to the increase of intestinal permeability and the activation of intestinal immune system, which in turn leads to heterotopia of intestinal bacteria and pro-inflammatory cells, which enter the brain tissue through the damaged blood-brain barrier (Hu et al,.2020). Intestinal microbiome also promotes the development of cerebral atherosclerosis by producing intermediate metabolites, including trimethylamine oxide (TMAO), lipopolysaccharide (LPS), phenylacetylglutamine (PAGln) and reduced butyrate (Chen et al,.2020). According to the known risk factors and chronic diseases, the subjects who had no previous stroke history and were older than 60 years old were divided into low-risk, medium-risk and high-risk groups by researchers such as Ulizeng. The results showed that the enrichment of conditional pathogenic bacteria (such as Enterobacteriaceae and Vironidae) and lactic acid-producing bacteria (such as Bifidobacterium and Lactobacillus) in high-risk group was significantly higher than that in low-risk group, while butyric acid-producing bacteria (such as Lactobacillus and Lactococcus) decreased relatively (Zeng et al,.2019). Li et al. found that the α diversity and structure of intestinal microbes in ischemic stroke patients were similar to those in healthy people, but there were many bacteria that could produce short-chain fatty acids in the intestinal microflora of stroke patients, including Corynebacterium, Ackerman, Ruminococcus UCG005 and Brucella (Li et al,.2019). Zhang WT and other researchers found that the abundance of Pseudomonas aeruginosa, cocci, sphinctenophilus and Klebsiella Adler in patients with cerebral infarction was significantly higher than that in healthy people, and the levels of IL-4, tumor necrosis factor-β (TN-β), IL-1β and C-reactive protein in patients with cerebral infarction were significantly higher than those in healthy people. This experiment showed that intestinal flora played a vital role in inducing cerebral infarction, but the specific mechanism was unknown (Zhang et al,.2020)

There are more and more articles about the relationship between ischemic stroke and intestinal microbes, and some of them have studied its pathogenesis from the perspective of basic medicine. Studies have shown that intestinal symbiotic microorganisms can favorably regulate regulatory T cells (Treg) and γδT cells, both of which are related to cerebral ischemia injury. γδ T cells, a major lymphocyte group with innate immune function, located on the epithelial surface, can aggravate ischemic brain/injury by secreting IL-17 and generating chemotactic signals for peripheral myeloid cells. Effector T cells contribute to ischemic injury, but Treg cells can promote neuroprotection by down-regulating inflammation after ischemia. After the acute stage of ischemic stroke, Treg cells appear in ischemic tissues and play a neuroprotective role by secreting anti-inflammatory cytokine IL-10. Treg cells in the intestine are essential to maintain the anti-inflammatory environment of the intestine by inhibiting the differentiation of T helper (TH)17 cells and the proliferation of γδT cells (Benakis et al,.2016). Singv et al. made a mouse model of massive cerebral infarction (FMCAo), and intervened and detected it. After FMCAo, the microflora was out of balance, and Th1 and Th17 responses, which were mainly pro-inflammatory, were induced, which was related to the increase of infarct volume. However, the expression of interferon-β and IL-17 cytokines, which are markers of Th1 and Th17 T cell polarization (Singh et al,.2016), were significantly increased in mice treated with fMCAo.

Hypertension is the most important variable factor leading to ischemic stroke. The incidence of cerebral infarction in hypertensive patients is increasing year by year. So what kind of intestinal flora of hypertensive patients is likely to lead to acute cerebral infarction? Or what is the specific mechanism of hypertension increasing the incidence of acute cerebral infarction through intestinal microorganisms.

In this study, by comparing the composition and function of intestinal microflora between hypertensive patients and hypertensive patients with ischemic stroke, we found that there was no obvious difference in α diversity and β diversity of intestinal microorganisms between the two groups, but there were still some different genera at the genus level. Compared with hypertensive patients with cerebral infarction, the relative abundance of bacteroides, UCG_009 and Eisenberg bacteria were significantly increased. The genera with relatively significantly reduced abundance are Luminococcus, Methanobacterium, Burkholderia and Prevotella, and the LDA score of Prevotella is <-4, which indicates that there are significant differences.

Prevost is a Gram-negative obligate anaerobic bacterium, belonging to Bacteroidea, which is one of the largest bacterial phylum known to us-a main branch of Bacteroidea (Accetto et al,.2021). It can appear in many parts of human body, such as skin, oral cavity, vagina and gastrointestinal tract (Tett et al,.2021). Studies have shown that Prevotella has the ability to regulate blood lipid, reduce weight and cholesterol(Liang et al,.2021;Guevara-Cruz et al,.2019;Medina-Vera et al,.2019;Chen et al,.2021;Christensen et al,.2019;Eriksen et al,.2020;Xia et al,.2017). By feeding Sprague-Dawley rats with whole-grain diet (WGQ), some researchers found that the levels of serum total cholesterol, low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol in rats decreased, and the abundance of Prevotella was significantly increased (Xia et al,.2017). Studies have shown that Prevotella has the ability to regulate blood lipid, reduce weight and cholesterol. Lars Christensen and other researchers found that there was a negative correlation between the abundance of Prevost bacteria and weight change through a 6-week, parallel and random experiment on overweight people (Christensen et al,.2019). Jingfeng Chen and other researchers found that several risk factors (waist circumference, body mass index, diastolic blood pressure, systolic blood pressure, fasting blood glucose, glycated hemoglobin, total cholesterol, triglyceride and low density lipoprotein cholesterol) and inflammatory markers (white blood cell count and absolute value of neutrophils) in CAS group were significantly higher than those in control group. However, the abundance of Prevotella in the control group was significantly higher than that in the CAS group, which indicated that the abundance of Prevotella was negatively correlated with hyperlipidemia (Chen et al,.2021). There is more and more evidence that Prevotella has the function of lowering blood lipid, but the specific mechanism is still unclear.

Let's imagine whether it is because of the lack of Prevotella in the intestines of some patients with hypertension, which leads to uncontrolled blood lipids, thus leading to cerebral atherosclerosis, and finally leading to ischemic stroke. Therefore, we compared serum proteomics between hypertensive patients and hypertensive patients with ischemic stroke, and found that there are 89 up-regulated genes and 51 down-regulated genes, and 8 genes involved in cholesterol metabolism, namely APOA1, APOA2, APOA4 and APOC1.

To further verify the hypothesis, we compared the blood biochemical indexes of patients in the hospital, and found that there was significant difference in APOA1 between the two groups. Then, we selected APOC2 and APOC3 with obvious differences in proteomics results for ELISA, and found thatIn the end, we concluded that the lack of Prevotella in the intestines of some patients with hypertension caused the blood lipid level not to be adjusted in time, which promoted the development of atherosclerosis, and finally led to the increased risk of ischemic stroke. However, its specific mechanism needs further study. This experiment provided a new idea for preventing the occurrence of ischemic stroke, further enhanced people's understanding of intestinal microbes, explored its mechanism, and finally applied the role of intestinal microbes in disease development to clinic.

In addition, we found that Prevotella produces short-chain fatty acids (SCFA) by decomposing carbohydrates. SCFA can not only provide energy for intestinal epithelial cells, but also affect the production of mucin, and physiologically affect the blood flow of colonic mucosa, the interaction between liquid and electrolyte, autonomic nervous system and the secretion of intestinal hormones (Ohira et al,.2017). Studies have shown that the increase of circulating SCFA is related to the direct decrease of adipocyte and adipogenesis (Morrison et al,.2016), and the regulation of blood lipid is helpful to slow down the occurrence and development of atherosclerosis. Studies have also shown that SCFAs directly or indirectly regulates microbiome-gut-brain interactions, including immune, endocrine, neural and humoral pathways (Dalile et al,.2019). Studies have found that ischemic stroke reduces the level of SCFAs in intestine, and transplantation of fecal microflora rich in these metabolites is an effective way to treat the disease. Butyric acid supplementation can effectively treat ischemic stroke model by remodeling intestinal microbiome, enriching beneficial lactobacillus and repairing leaky intestine (Chen et al,.2020). In our study, the prevalence of Prevotella in the intestines of hypertensive patients is significantly higher than that of ischemic stroke, which indicates that the lack of SCFA caused by different flora may be an important factor in the occurrence of ischemic stroke in hypertensive patients.

When FAPROTAX technology was used to predict the prokaryotic function of bacteria in patients, we found that the reduction effect of nitric acid in hypertensive patients was significantly higher than that in hypertension complicated with stroke. Some studies have shown that the reduction effect of nitric acid can dilate blood vessels (Sindler et al,.2014), so we suspect that this may be due to different intestinal flora, which leads to different degrees of vasodilation, and ultimately leads to different risks of ischemic stroke in hypertensive people. This conjecture still needs further experimental verification.

ACKNOWLEDGMENTS

We are grateful for the support from the Tai 'an Science and technology innovation development project（2020NS267）；Tai 'an Science and technology innovation development project（2021NS300）；Shandong Medicine and Health Science and Technology Plan Development Project（202103090628）

Authors declare no conflict of interests.

DATA AVAILABILITY STATEMENT

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

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Table 1 Comparison of blood lipid and blood glucose between hypertensive patients and hypertensive patients with ischemic stroke

Item	Hypertension（46）	Stroke+Hypertension（72）	P
ALP(U/L)	63.13±18.55	62.92±15.78	0.524
glucose(mmol/L)	5.02±052	5.17±1.02	0.888
TC(mmol/L)	4.40±1.02	4.67±0.76	0.053
TG(mmol/L)	1.49±0.75	1.43±0.80	0.643
HDL(mmol/L)	1.11±0.21	1.20±0.28	0.159
LDL(mmol/L)	2.59±0.83	2.72±0.61	0.347
APOA1	1.17±0.14	1.27±0.20	0.040*
APOB	0.91±0.23	0.91±0.19	0.966
LP（a)	186.30±236.49	260.85±257.75	0.073
Hcy(umol/L)	15.64±10.75	16.88±9.19	0.205
NEFA(mmol/L)	0.52±0.25	0.48±0.27	0.397

Table1 Comparison of blood lipid and blood glucose between hypertension group and hypertension complicated with cerebral infarction group. The normal distribution test showed that low density lipoprotein, apolipoprotein B and free fatty acid were normal, and two independent samples T test was adopted, p>0.05, indicating that there was no significant statistical difference in low density lipoprotein, apolipoprotein B and free fatty acid between the two groups. However, alkaline phosphatase (ALP), blood glucose (glucose), TC, TG, HDL, APOA1, LP, HCY do not conform to the normal distribution. The nonparametric rank sum test shows that P (apolipoprotein A1) is < 0.05, indicating that there is a significant statistical difference in apolipoprotein A1 between the two groups, and the remaining P values are all greater than 0.05, with no significant statistical difference.

No competing interests reported.

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Analysis of fecal flora in patients with hypertension complicated with ischemic stroke

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