TWI745780B - Method of using intestinal flora to detect chronic kidney disease and its severity - Google Patents

Abstract

A method of using intestinal flora to detect chronic kidney disease and its severity, using a non-invasive stool test method to obtain Paraprevotella, Vibrio pseudobutyricum, Collins fecal strains, and Pseudomonas Escherichia The relative number of bacilli species present in the intestinal bacteria, and the changes in the relative numbers of the above four types of flora are used to assess the severity of kidney disease, and then provide guidelines for replenishment or reduction of the above-mentioned intestinal bacteria to achieve the goal of reducing kidney function damage.

Description

Method of using intestinal flora to detect chronic kidney disease and its severity

The present invention is a method for detecting kidney disease and its severity, in particular a method for detecting chronic kidney disease and its severity using intestinal flora, by non-invasive stool detection method to measure the counts of four intestinal bacteria Changes to diagnose chronic kidney disease and its severity, and provide therapeutic targets for reducing urinary toxins produced by the intestinal tract.

Chronic kidney disease increases cardiovascular disease, mortality and medical costs, and has become a public health dilemma in the world. At present, effective treatment strategies are still to be developed to reduce the occurrence and deterioration of chronic kidney disease. In patients with chronic kidney disease, due to accumulation of uremia, abnormal pH and electrolytes, changes in immune function, and multiple drug treatments, intestinal microecological disorders and changes in intestinal microbiota are caused. These intestinal abnormalities lead to metabolites. Changes cause damage to the kidneys. Several metabolites produced through the intestinal tract, such as indole sulfate and p-cresol sulfate, all directly cause damage to kidney cells and glomeruli, leading to decreased renal function.

According to the treatment guidelines of the American Kidney Foundation DOQI, creatinine and microalbuminuria in the blood are still traditionally used to diagnose chronic kidney disease and its severity. However, once these two indicators are abnormal, it means that the kidney has been pathologically damaged. , So the effect of early diagnosis cannot be achieved.

Early kidney damage is related to many factors. Although there are several biomarkers in blood and urine to assist in early diagnosis, the intestinal flora of chronic kidney disease is related to kidney function. And the severity of the disease, or the bacterial species related to the metabolites produced in the intestine are still unclear, so there is still room for improvement in the prior art.

The technical problem to be solved by the present invention is to provide a method for detecting chronic kidney disease and its severity using intestinal flora, using a non-invasive stool test method to detect Paraprevotella, pseudobutyric acid vibrio The relative numbers of the genus, Collins feces and Bacteroides escherichia species can be adjusted to reduce the metabolites produced in the intestines, thereby reducing the damage of kidney function.

In order to solve the above technical problems, the method for detecting chronic kidney disease and its severity using intestinal flora disclosed in the present invention includes the following steps:

Step 1: Collect the fecal samples of the subjects, and collect the intestinal bacterial DNA of the feces.

Step 2: Use polymerase chain reaction (PCR) to test the fourth variable region of the 16S rRna in intestinal bacteria for gene sequencing and generate a sequencing library.

Step 3: After processing, the sequencing reads are identified according to the phyla, class, order, family, genus, and species. Paraprevotella, Vibrio pseudobutyricum, Collins feces and Bacteroides escherichia are present in the intestine The relative number in the flora.

Step 4: As the severity of kidney disease increases, the relative number of the above-mentioned Paraprevotella, Vibrio pseudobutyricum, or Bacteroides escherichia species decreases, or the relative number of fecal Collins species increases, of which the above The relative concentration of Paraprevotella below 0.08% indicates the possibility of kidney disease. The relative concentration of Vibrio pseudobutyricum below 2.47% indicates the possibility of kidney disease. The aforementioned Collins faecalis The relative concentration of species above 0.02% indicates the possibility of kidney disease, while the relative concentration of the above-mentioned Bacteroides species below 0.05% indicates the possibility of kidney disease sex.

Through the above method, non-invasive stool test methods are used to obtain the relative quantity of Paraprevotella, Vibrio pseudobutyricum, Collins feces and Bacteroides escherichia species in the intestinal bacteria, and Evaluate the severity of kidney disease through the changes in the relative numbers of the above four types of flora, and provide guidelines for replenishing or reducing the number of intestinal bacteria mentioned above to achieve the purpose of personal medical treatment.

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Figure 1 is a flow chart of the method for detecting chronic kidney disease and its severity using intestinal flora of the present invention

Figure 2 is the distribution of the relative concentration of Paraprevotella in the feces of different chronic kidney disease patients of the present invention. The dotted line refers to the trend of the average value of each group. The value of rho at the top of the figure represents the correlation coefficient (correlation). coefficient)

Figure 3 is the distribution of the relative concentration of Vibrio pseudobutyricum in the feces of different chronic kidney disease patients of the present invention. The dotted line refers to the trend of the average value of each group. The value of rho at the top of the figure represents the regression coefficient.

Figure 4 is the distribution of the relative concentration of Collins strains of feces of the present invention in the feces of different chronic kidney disease patients. The dotted line refers to the trend of the average value of each group. The value of rho at the top of the figure represents the regression coefficient.

Figure 5 is the distribution of the relative concentration of Bacteroides escherichia species present in the feces of different chronic kidney disease patients. The dotted line refers to the trend of the average value of each group, and the value of rho at the top of the figure represents the regression coefficient

Figure 6 shows the average serum urinary toxin concentration of chronic kidney disease of different severity according to the present invention

Figure 7 is a scatter diagram of the association between Paraprevotella and Vibrio pseudobutyricum and Log total PCS/Log free PCS and Log total IS/Log free IS of the present invention

As can be seen from the method flow chart in Figure 1, the present invention provides a method for detecting intestinal flora using intestinal flora. Methods of measuring chronic kidney disease and its severity include:

Step one S1: Collect a stool sample of the subject, and collect the intestinal bacterial DNA of the stool.

Step two S2: Use polymerase chain reaction (PCR) to test the fourth variable region of the 16S rRna in the intestinal bacteria for gene sequencing and generate a sequencing library.

Step 3: S3: The processed sequencing reads are identified in accordance with phyla, class, order, family, genus, and species. The relative number of tract flora.

Step 4: S4: As the severity of kidney disease increases, the relative number of the above-mentioned Paraprevotella, Pseudobutyrivibrio or Bacteroides eggerthii decreases, or stool The relative number of Collinsella stercoris has increased. The relative concentration of Paraprevotella is lower than 0.08%, which indicates the possibility of kidney disease. The relative concentration of Vibrio pseudobutyricum is lower than 2.47. % Means the possibility of kidney disease, the relative concentration of Collins species in feces is higher than 0.02%, it means the possibility of kidney disease, and the relative concentration of Bacteroides escherichia species is lower than 0.05%, it means the possibility of kidney disease. sex.

Through the above non-invasive method, the patient’s feces are used to measure the changes of the four intestinal bacteria: Paraprevotella, Vibrio pseudobutyricum, Collins feces and Bacteroides escherichia Assess chronic kidney disease and its severity, and provide treatment targets for reducing urinary toxins produced by the intestinal tract.

Table 1. A comparison table of the English names of the phylum, class, order, family, genus, and species of the genus Paraprevotella, Vibrio pseudobutyricum, Collins feces and Bacteroides escherichia species.

The detailed implementation example is as follows:

Fecal DNA isolation and 16S rRNA gene sequencing

Step 1: S1: Collect 10 grams of stool samples from 130 subjects, 30 of them have no renal dysfunction, 31 cases of mild, 30 cases of moderate and 39 cases of severe chronic kidney disease without dialysis, before sample collection Within 7 days, subjects should not take any supplements or foods containing probiotics, such as yogurt and yogurt. Use FastDNA SPIN Kit for Stool (MP Biomedical) to collect intestinal bacterial DNA from feces.

Step 2 S2: Use polymerase chain reaction (PCR) to amplify the fourth variable region (V4) of the 16S rRNA coding gene in intestinal bacteria, and use the barcoded bacteria/archaea primer 515F/806R to amplify 16S The V4 region of the rRNA gene. The amplicons were purified using GeneJET Gel Extraction Kit (Thermo Scientific), and then quantified using Qubit dsDNA HS Assay Kit (Qubit) on Qubit 2.0 Fluorometer (Qubit). Use NEBNext® Ultra ^TM DNA Library Preparation Kit (Illumina) (NEB) and generate sequencing libraries, quantify, standardize and merge the purified libraries, and apply them to the Illumina HiSeq 2500 platform for cluster generation and sequencing to generate 250bp Paired terminal reading.

Process and analyze sequence data

Step three S3: Use FLASH v1.2.7 to merge the paired terminal readings, and use the QIIME 1.7 software analysis process to evaluate the quality of the filtered readings, and then use UCHIME chimera detection software to discard the chimeric sequences in sequence, and the sequencing processed by the UPARSE algorithm Readings (valid tags), and cluster the sequences with 97% identity into operational taxonomic units (OTU), and then assign bacteriological phylum classification based on the information retrieved from the SILVA gene sequence database. According to Phylum, Class ), Order, Family, Genus, Species Identify various bacteria and calculate the relative abundancy of various bacteria in the intestinal flora. Delete a single sequence (single sub) that only appears once or only a sequence detected in one sample, and exclude samples with an effective label ^{less than 3×10 4 for further analysis.} In order to evaluate the phylogenetic relevance of different OTUs, PyNAST software v.1.2 was used to compare multiple sequences against the data set of the SILVA database, and the FastTree software suite was used to generate a phylogenetic tree. Before analyzing the diversity of α and β, the data of OTU abundance is sparsed to the minimum sequence depth to standardize the variation of sequence depth between samples. The measurement method of Chao1 index is used to evaluate species richness to estimate α diversity. Randomly select a certain amount of sequencing data from each sample to represent the number of observed species, and generate a rareaction curve, and plot the species with the frequency of new OTU (species) in continuous sampling Accumulation curve. The Bray-Curtis density similarity coefficient difference and the comparison with the vegan phase are used to evaluate the β diversity, the Bray-Curtis distance is used for principal coordinate analysis (PCoA), and the QIIME software analysis process is used to calculate the weighted and unweighted UniFrac parameter evaluation The distance between the microbial community samples is transformed into a new set of orthogonal axes using the weighted or unweighted UniFrac parameter distance matrix in the sample, and the weighted correlation network analysis (WGCNA) in R software, stat and ggplot2 software are used for non- Metric Scaling Analysis (NMDS).

Statistical Analysis

Step 4: S4: Descriptive statistics are expressed as average, median or ratio. Use the Kolmogorov-Simirnov method to test statistics to test the normality of numerical variables, apply the Student's t test or Kruskal-Wallis single-factor multi-sample median difference test in order to determine the difference in clinical index between groups, and application Spearman correlation is used to determine the correlation between the main genera (genera, >0.1% abundance and >90% in the sample) with serum biomarkers and disease severity, and then use Bonferroni correction ( Bonferroni) correction performs multiple corrections to adjust the p value (n=55). Use the 22nd edition of statistical product and service solution statistical software (SPSS 22.0, SPSS Inc., Chicago, IL) supported by Microsoft XP to analyze the data. Apply the overall taxonomy, the abundance of the genus level or the species level to analyze the most recognizable bacterial taxa in different CKD states, and use SPSS to construct a receiver operating characteristic curve (ROC) to test the CKD used to distinguish different stages Or the performance of intestinal microbial abundance in peritoneal dialysis patients and non-CKD controls. The two-sample Z-test was used to calculate the statistical difference between the AUC of the ROC curve, and multiple calibration tests were performed with Bonferroni correction (n=80, for species present in >80% of the samples; n=98, for existing genera >98% of samples). All statistical tests are two-tailed, and p<0.05 is considered statistically significant. The four significant bacteria identified, namely Paraprevotella, Vibrio pseudobutyricum, Collins feces, and Bacteroides escherichia, are present in the intestinal flora in relative numbers, and the other 98 The population of peritoneal dialysis (representing severe kidney disease) patients was verified.

The above verification results are shown in Figure 2~Figure 7 below: Refer to Figure 2~Figure 5, you can see four types of intestinal bacteria (paraprevotella, Vibrio pseudobutyricum, Collins feces and Bacteroides escherichia) in the feces of different chronic kidney disease patients In the relative concentration distribution, Non-CKD in the figure refers to the group without kidney disease, and Mil.CKD refers to mild kidney disease. In the visceral disease group, Mod.CKD is the moderate kidney disease group, and Adv.CKD is the severe kidney disease group; it can be seen from the figure that as the severity of kidney disease increases, the genus Paraprevotella and Vibrio pseudobutyricum The relative number of genus or Bacteroides escherichia species decreased, or the relative number of fecal Collins species increased.

Refer to Table 2 below. In the figure, Non-CKD (30) refers to 30 people in the group without kidney disease, mild CKD (31) refers to 31 people in the group with mild kidney disease, and PD refers to peritoneal dialysis (peritoneal dialysis). dialysis), AUC refers to the total area under the ROC surface, and Pc (Corrected P) refers to the P value with Bonferroni correction for multiple correction tests. The area under curve of Paraprevotella, Vibrio pseudobutyricum, Collins faecalis and Bacteroides escherichia when diagnosed with or without chronic kidney disease are all better than the traditional markers of "urinary protein/ The "urine protein-creatinine ratio" (urine protein-creatinine ratio) is significantly larger, and the p-value is still statistically significant after correction. The area under curve of Paraprevotella, Vibrio pseudobutyricum, Collins fecal and Bacteroides escherichia when diagnosed with mild or no chronic kidney disease is better than the traditional marker "Urine". The "urine protein-creatinine ratio" (urine protein-creatinine ratio) is significantly greater. After the p value is corrected, the area under curve of Paraprevotella, Vibrio pseudobutyricum, Collins faecalis and Bacteroides escherichia are all diagnosed with mild or no chronic kidney disease. It is significantly larger than the traditional marker "urine protein-creatinine ratio" (urine protein-creatinine ratio). In the validation group, the species of Paraprevotella, Vibrio pseudobutyricum, and Collins feces are still significant. In other words, the use of Paraprevotella, Vibrio pseudobutyricum, Collins fecal and Bacteroides escherichia species as tests to assess chronic kidney disease and its severity is compared to the traditional use of creatinine and creatinine in blood. The detection of microalbuminuria is better.

Table 2. Comparison of intestinal bacteria markers and traditional markers for the diagnosis of chronic kidney disease and its disease severity in the invention group and the verification group.

Refer to Table 3 below. In the figure, Non-CKD refers to the group without kidney disease, Mod.CKD refers to the moderate kidney disease group, Adv.CKD refers to the severe kidney disease group, Paraprevotella, Vibrio pseudobutyricum The area under the curve (area undcr curve) of the genus, Collins fecal and Bacteroides escherichia species in the diagnosis of no or moderate chronic kidney disease are all better than the traditional marker "urine protein-creatinine liver ratio" (urine protein-creatinine ratio). ratio) is significantly greater, and the p-value is still statistically significant after correction; the above four intestinal bacteria markers are used to diagnose severe or non-chronic kidney disease when the area under curve is more significant than traditional The mark is smaller. Therefore, compared with traditional urine markers, these four intestinal bacteria markers are more accurate for identifying moderate chronic kidney disease, but they are not better for identifying severe chronic kidney disease.

Refer to Table 4 below. The relative concentrations of Paraprevotella, Vibrio pseudobutyricum, Collins feces and Bacteroides escherichia are better than traditional urine markers in the diagnosis of chronic kidney disease with or without chronic kidney disease and its severity. It is meaningful to further calculate the relative concentration quantitative value, specificity and sensitivity of the above four bacterial species in the diagnosis of chronic kidney disease and its severity; specificity is the probability of successfully excluding patients in a population without the disease, and the sensitivity is Among the affected population, the probability of successfully confirming the disease. The relative concentration of Paraprevotella is less than 0.16%, the sensitivity for diagnosing mild kidney disease is 0.5667, and the specificity is 0.8387; the relative concentration is less than 0.08%, it can be diagnosed with kidney disease (specificity sensitivity is 0.9000, sensitivity is 0.6196). The relative concentration of Vibrio pseudobutyricum is lower than 2.47%, which can diagnose kidney disease (mild or with or without kidney disease). The relative concentration of fecal Collins strains is higher than 0.01%, the specificity of the diagnosis of mild kidney disease is 0.6333, the sensitivity is 0.9032; the relative concentration of higher than 0.02% can be diagnosed with the kidney disease (specificity is 0.7000, sensitivity is 0.8913). The relative concentration of Bacteroides escherichia species is less than 0.04%, and the specificity for the diagnosis of mild kidney disease is 0.8667, and the sensitivity is 0.6774; the relative concentration is less than 0.05% for the diagnosis of kidney disease (specificity is 0.8667, sensitivity is 0.75).

Refer to Figure 6, revealing that the serum urinary toxin concentration increases significantly with the severity of chronic kidney disease (Non-CKD: no kidney disease group, Mil.CKD: mild kidney disease group, Mod.CKD: moderate kidney disease Group, Adv.CKD: severe kidney disease group, IS: indole sulfate, PCS: p-cresol sulfate, *p<0.001).

Refer to Table 5 below, which is the Spearman correlation between log-transformed serum total PCS, total IS, free PCS, free IS and bacterial markers or renal function, and PCS is the abbreviation of p-thiocresol, IS is indyl sulfate Doxyphene. Both the genus Paraprevotella and Vibrio pseudobutyricum are significantly negatively correlated with Log total PCS/Log free PCS and Log total IS/Log free IS, indicating that the genus Prevotella and Vibrio pseudobutyricum are significantly negatively correlated. The higher the amount of Acid Vibrio, the lower the urinary toxin. Fecal Collins strain has a significant positive correlation with Log total IS and Log free IS.

Refer to Figure 7. The higher the relative concentration of Paraprevotella and Vibrio pseudobutyricum, the lower the serum concentration of Log total PCS/Log free PCS and Log total IS/Log free IS, which is representative of chronic kidney disease patients. Increasing the relative concentration of Paraprevotella and Vibrio pseudobutyricum can reduce IS/PCS and other urinary toxins, and provide a treatment target. Therefore, Paraprevotella and Vibrio pseudobutyricum may be used as targets for functional probiotics to reduce the concentration of urinary toxins.

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Claims (3)

A method of using intestinal flora to detect chronic kidney disease and its severity. The steps are as follows: Step 1: Collect a sample of the subject’s feces and take the fecal intestinal bacteria DNA; Step 2: Use polymerase chain reaction (PCR) Test the fourth variable region of 16S rRNA in intestinal bacteria for gene sequencing and generate a sequencing library; Step 3: After processing, the sequencing reads are identified according to the phyla, class, order, family, genus, and species of Paraprevotella, The relative quantity of Vibrio pseudobutyricum, Collins feces and Bacteroides escherichia species in the intestinal flora; Step 4: As the severity of kidney disease increases, The relative number of acid Vibrio species or Bacteroides escherichia species decreased, or the relative number of fecal Collins species increased. The relative concentration of the above-mentioned Paraprevotella species below 0.08% indicates the possibility of kidney disease , The relative concentration of Vibrio pseudobutyricum below 2.47% indicates the possibility of kidney disease, and the relative concentration of the above fecal Collins species above 0.02% indicates the possibility of kidney disease. The above Bacteroides escherichia A relative concentration of less than 0.05% indicates the possibility of kidney disease. The method of using intestinal flora to detect chronic kidney disease and its severity as described in the first item of the scope of patent application, wherein the second step is to amplify the V4 of the 16S rRNA gene by using the barcoded bacteria/archaea primer 515F/806R area. The method of using intestinal flora to detect chronic kidney disease and its severity as described in item 1 of the scope of patent application, in which step 3 first deletes a single sequence that only appears once or only in one sample after identifying the relative quantity The sequence is detected, and samples with valid labels ^{less than 3×10 4 are excluded.}

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