Application of Microbial Biomarkers in the Diagnosis of Diseases Related to Abnormal Uric Acid

Abstract

The present invention discloses the application of microbial markers in the diagnosis of diseases related to abnormal uric acid, specifically involving microbial markers of Prevotella_stercorea, Escherichia_coli, Bacteroides_eggerthii, Bacteroides_xylanisolvens, Bacteroides_uniformis, Bacteroides_coprocola_CAG.162, and Lachnospiraceae_bacterium_8_1_57FAA. The present invention also discloses products and methods for diagnosing diseases related to abnormal uric acid. The products and methods contain reagents for detecting the mutation levels of the microbial markers. The products and methods provided by the present invention have the advantages of non-invasive, simple, strong specificity, high sensitivity, high safety, etc., and have broad market prospects.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology and relates to the application of microbial markers in the diagnosis of diseases related to abnormal uric acid. Specifically, the microorganisms involved are Prevotella_stercorea, Escherichia_coli, Bacteroides_eggerthii, Bacteroides_xylanisolvens, Bacteroides_uniformis, Bacteroides_coprocola_CAG.162, and Lachnospiraceae_bacterium_8_1_57FAA. Background Art

[0002] Uric acid is the end product of purine metabolism in the human body. Normal adults produce about 700 mg of uric acid per day, of which about 500 mg is excreted through the kidneys and about 200 mg is excreted through the intestines to maintain the balance of uric acid in the body. Excessive production or poor excretion of uric acid will lead to an increase in blood uric acid. Generally, when the blood uric acid concentration is greater than 416 μmol / L, hyperuricemia can be clinically diagnosed. Once it is found that the uric acid exceeds the standard, dietary treatment with low-purine foods is the first choice for controlling hyperuricemia and gout. Urate crystals in the body of hyperuricemia patients deposit in the synovium, bursa, cartilage and other tissues of joints, causing recurrent inflammatory diseases, which is called gout, manifested as gouty acute arthritis, chronic arthritis, tophi and joint deformity, gouty nephropathy, etc.

[0003] Intestinal microorganisms refer to a large number of microorganisms existing in the animal intestine. These microorganisms rely on the animal intestine for life and at the same time help the host complete various physiological and biochemical functions. The intestine is not only an important place for human digestion and absorption, but also the largest immune organ, playing an extremely important role in maintaining normal immune defense functions. The human intestine provides a good habitat for microorganisms and has metabolic functions that the human body itself does not possess. Summary of the Invention

[0004] The present invention discloses the application of a reagent for detecting microbial markers in the preparation of a product for diagnosing diseases related to abnormal uric acid, and the microbial markers include Prevotella_stercorea, Escherichia_coli, Bacteroides_eggerthii, Bacteroides_xylanisolvens, Bacteroides_uniformis, Bacteroides_coprocola_CAG.162, and Lachnospiraceae_bacterium_8_1_57FAA.

[0005] Furthermore, the microbial markers are a combination of Prevotella_stercorea, Escherichia_coli, Bacteroides_eggerthii, Bacteroides_xylanisolvens, Bacteroides_uniformis, Bacteroides_coprocola_CAG.162, and Lachnospiraceae_bacterium_8_1_57FAA.

[0006] Furthermore, the microbial markers include a mutation at the 4571st base of the Prevotella_stercorea genome, a mutation at the 1122339th base of the Escherichia_coli genome, a mutation at the 51594th base of the Bacteroides_eggerthii genome, a mutation at the 5120272nd base of the Bacteroides_xylanisolven genome, a mutation at the 105620th base of the Bacteroides_uniformis genome, a mutation at the 246th base of the Bacteroides_coprocola_CAG.162 genome, and a mutation at the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome. The positions of the mutations can be referred to as SNP sites.

[0007] Furthermore, the microbial markers are a combination of a mutation at the 4571st base of the Prevotella_stercorea genome, a mutation at the 1122339th base of the Escherichia_coli genome, a mutation at the 51594th base of the Bacteroides_eggerthii genome, a mutation at the 5120272nd base of the Bacteroides_xylanisolven genome, a mutation at the 105620th base of the Bacteroides_uniformis genome, a mutation at the 246th base of the Bacteroides_coprocola_CAG.162 genome, and a mutation at the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome.

[0008] In the present invention, the reference genome of Prevotella_stercorea strain is GenBank ID: QRNO01000027.1, and the reference genome link is: https: / / www.ncbi.nlm.nih.gov / nuccore / QRNO01000027.1. Among them, the 4571st base is T base in the reference genome. When the T base at this site mutates to C base, the risk of hyperuricemia decreases.

[0009] In the present invention, the reference genome of Escherichia_coli strain is GenBank ID: CP076470.1, and the reference genome link is: https: / / www.ncbi.nlm.nih.gov / nuccore / CP076470.1. Among them, the 1122339th base is G base in the reference genome. When the G base at this site mutates to C base, the risk of hyperuricemia increases.

[0010] In the present invention, the reference genome of Bacteroides_eggerthii strain is GenBank ID: CP072228.1, and the reference genome link is: https: / / www.ncbi.nlm.nih.gov / nuccore / CP072228.1. Among them, the 51594th base is T base in the reference genome. When the T base at this site mutates to G or A base, the risk of hyperuricemia decreases.

[0011] In the present invention, the reference genome of Bacteroides_xylanisolvens strain is GenBank ID: CP072216.1, and the reference genome link is: https: / / www.ncbi.nlm.nih.gov / nuccore / CP072216.1. Among them, the 5120272nd base is T base in the reference genome. When the T base at this site mutates to G base, the risk of hyperuricemia decreases.

[0012] In the present invention, the reference genome of Bacteroides_uniformis strain is GenBank ID: CP054204.1, and the reference genome link is: https: / / www.ncbi.nlm.nih.gov / nuccore / CP054204.1. Among them, the 105620th base is C base in the reference genome. When the C base at this site mutates to T base, the risk of hyperuricemia increases.

[0013] In the present invention, the reference genome of the Bacteroides_coprocola_CAG.162 strain is GenBank ID: FR881015.1, and the reference genome link is: https: / / www.ncbi.nlm.nih.gov / nuccore / FR881015.1. Among them, the 246th base is T in the reference genome, and the risk of hyperuricemia increases when the T base at this site mutates to a C base.

[0014] In the present invention, the reference genome of the Lachnospiraceae_bacterium_8_1_57FAA strain is GenBank ID: GL622453.1, and the reference genome link is: https: / / www.ncbi.nlm.nih.gov / nuccore / GL622453.1. Among them, the 77201st base is C in the reference genome, and the risk of hyperuricemia decreases when the C base at this site mutates to a T base.

[0015] Furthermore, the product includes a reagent capable of detecting the microbial marker, a kit, a chip, a primer, a probe or a chromatographic test strip containing the reagent.

[0016] Furthermore, the reagent includes specific primers, probes, antisense oligonucleotides, aptamers or antibodies for detecting Prevotella_stercorea, Escherichia_coli, Bacteroides_eggerthii, Bacteroides_xylanisolvens, Bacteroides_uniformis, Bacteroides_coprocola_CAG.162, Lachnospiraceae_bacterium_8_1_57FAA.

[0017] Further, the reagent detects mutations at the 4571st base of the Prevotella_stercorea genome (GenBank ID: QRNO01000027.1), mutations at the 1122339th base of the Escherichia_coli genome (GenBank ID: CP076470.1), mutations at the 51594th base of the Bacteroides_eggerthii genome (GenBank ID: CP072228.1), mutations at the 5120272nd base of the Bacteroides_xylanisolven genome (GenBank ID: CP072216.1), mutations at the 105620th base of the Bacteroides_uniformis genome (GenBank ID: CP054204.1), mutations at the 246th base of the Bacteroides_coprocola_CAG.162 genome (GenBank ID: FR881015.1), and / or mutations at the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome (GenBank ID: GL622453.1) with specific primers, probes, antisense oligonucleotides, aptamers or antibodies.

[0018] In the present invention, the term "probe" refers to a molecule that can bind to a specific sequence or subsequence or other part of another molecule. Unless otherwise indicated, the term "probe" generally refers to a polynucleotide probe that can bind to another polynucleotide (often referred to as the "target polynucleotide") through complementary base pairing. Depending on the stringency of the hybridization conditions, the probe can bind to a target polynucleotide that lacks complete sequence complementarity to the probe. The probe can be directly or indirectly labeled, and its scope includes primers. Hybridization methods include, but are not limited to: solution phase, solid phase, mixed phase or in situ hybridization assays.

[0019] Further, the product includes determining whether a subject has a disease associated with abnormal uric acid or the risk of developing a disease associated with abnormal uric acid by detecting mutations of the microbial biomarker in a sample.

[0020] Further, the sample includes blood, serum, and feces.

[0021] Further, the method for detecting microbial biomarkers in the sample includes any one or more of 16S sequencing, whole genome sequencing, quantitative polymerase chain reaction, PCR-pyrosequencing, fluorescence in situ hybridization, microarray, and / or PCR-ELISA detection.

[0022] Further, the diseases related to abnormal uric acid include hyperuricemia, hypouricemia, gout, urinary tract stones, gouty nephropathy, and uric acid nephrolithiasis.

[0023] The present invention provides a method for determining the status of an individual using microbial markers, wherein the microbial markers include the microbial markers described in any one of the preceding items, and the method includes:

[0024] 1) Determining the mutations of the microbial markers in the sample of the individual;

[0025] 2) Comparing the mutations of the microbial markers determined in step 1) with their bases in the control group, and determining the status of the individual based on the obtained comparison results. The control group consists of samples of one or more groups of individuals in the same status, and the status includes having a disease related to abnormal uric acid and / or not having a disease related to abnormal uric acid.

[0026] Further, step 1) includes obtaining sequencing data of nucleic acid sequences in the sample of the individual, and the sequencing data includes multiple reads;

[0027] Aligning the reads to the genome of the microbial markers to obtain an alignment result;

[0028] Based on the alignment result, determining the mutation level of the microbial markers.

[0029] Further, the control group in step 2) includes samples of multiple healthy individuals. When the mutations of the microbial markers determined in step 1) have no differences from their bases in the control group, it is determined that the status of the individual is not suffering from a disease related to abnormal uric acid.

[0030] Further, the sample includes blood, serum, and fecal samples.

[0031] Further, the diseases related to abnormal uric acid include hyperuricemia, hypouricemia, gout, urinary tract stones, gouty nephropathy, and uric acid nephrolithiasis.

[0032] In certain specific embodiments, the method for determining the status of an individual using microbial markers includes obtaining sequencing data of nucleic acid sequences in the blood and serum samples of the individual, where the sequencing data includes multiple reads; assembling the reads to obtain a gene set, the gene set includes multiple assembled fragments, and the assembled fragments in the gene set are non-redundant sequences; determining the assembled fragments included in various microorganisms in the markers; based on the sequencing data, respectively determining the mutations of each assembled fragment in the gene set, including determining the mutation levels of the assembled fragments included in various microorganisms in the markers respectively; and respectively determining the mutation levels of various microorganisms based on the determined mutation levels of the assembled fragments.

[0033] The term "biomarker" should be understood in a broad sense, which includes any detectable biological indicator that can reflect an abnormal state, and may include gene markers, species markers (species markers / genus markers), and functional markers. Among them, the meaning of gene markers is not limited to genes that can be expressed as and have biological activity at present, but also includes any nucleic acid fragment, which can be DNA or RNA, can be modified DNA or RNA, or can be unmodified DNA or RNA. In this article, gene markers can sometimes also be called characteristic fragments. In particular, the biomarker of the present invention is a microbial biomarker.

[0034] The present invention provides a method for classifying multiple individuals using microbial biomarkers, where the microbial biomarkers include the microbial biomarkers described in any one of the preceding items, and the method includes:

[0035] Using the method for determining the state of an individual using microbial biomarkers described above to determine the state of each individual;

[0036] Classifying the individuals according to the state of each individual obtained.

[0037] Furthermore, the state of each individual is the state of an individual suffering from a disease related to abnormal uric acid or the risk of suffering from a disease related to abnormal uric acid.

[0038] Furthermore, the state of the individual is determined by detecting the microbial biomarkers described in any one of the preceding items, specifically:

[0039] When the 4571st base of the Prevotella_stercorea genome (GenBank ID: QRNO01000027.1) is T,

[0040] When the 1122339th base of the Escherichia_coli genome (GenBank ID: CP076470.1) is C,

[0041] When the 51594th base of the Bacteroides_eggerthii genome (GenBank ID: CP072228.1) is T,

[0042] When the 5120272nd base of the Bacteroides_xylanisolven genome (GenBank ID: CP072216.1) is T,

[0043] When the 105620th base of the Bacteroides_uniformis genome (GenBank ID: CP054204.1) is T,

[0044] When the 246th base of the Bacteroides_coprocola_CAG.162 genome (GenBank ID: FR881015.1) is C, and / or

[0045] When the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome (GenBank ID: GL622453.1) is C, an individual has a disease related to abnormal uric acid or an increased risk of developing a disease related to abnormal uric acid;

[0046] When the 4571st base of the Prevotella_stercorea genome (GenBank ID: QRNO01000027.1) is C,

[0047] When the 1122339th base of the Escherichia_coli genome (GenBank ID: CP076470.1) is G,

[0048] When the 51594th base of the Bacteroides_eggerthii genome (GenBank ID: CP072228.1) is G or A,

[0049] When the 5120272nd base of the Bacteroides_xylanisolven genome (GenBank ID: CP072216.1) is G,

[0050] When the 105620th base of the Bacteroides_uniformis genome (GenBank ID: CP054204.1) is C,

[0051] When the 246th base of the Bacteroides_coprocola_CAG.162 genome (GenBank ID: FR881015.1) is T, and / or

[0052] When the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome (GenBank ID: GL622453.1) is T, an individual has a disease related to abnormal uric acid or a decreased risk of developing a disease related to abnormal uric acid.

[0053] The present invention provides a product for diagnosing diseases related to abnormal uric acid, and the product includes reagents for detecting the mutation levels of microbial markers Prevotella_stercorea, Escherichia_coli, Bacteroides_eggerthii, Bacteroides_xylanisolvens, Bacteroides_uniformis, Bacteroides_coprocola_CAG.162, and Lachnospiraceae_bacterium_8_1_57FAA.

[0054] Further, the microbial markers include the microbial markers described in any one of the preceding items.

[0055] Further, the diseases related to abnormal uric acid include hyperuricemia, hypouricemia, gout, urinary calculi, gouty nephropathy, and uric acid nephrolithiasis.

[0056] Further, the reagents include specific primers, probes, aptamers, or antibodies for detecting the microbial markers.

[0057] A "primer" is an oligonucleotide that, when paired with one strand of DNA, is capable of initiating the synthesis of a primer extension product in the presence of a suitable polymerase. The primer is preferably single-stranded to obtain maximum amplification efficiency, but it can also be double-stranded. The primer must be long enough to initiate the synthesis of the extension product in the presence of the polymerase. The length of the primer depends on many factors, including the application, the temperature to be employed, the template reaction conditions, other reagents, and the primer source. For example, depending on the complexity of the target sequence, oligonucleotide primers generally contain 15 to 35 or more nucleotide residues, but they can contain fewer nucleotide residues. The primer can be a large polynucleotide, such as from about 200 nucleotide residues to several thousand bases or more. The primer can be selected to be "substantially complementary" to the sequence on the template to which it is designed to hybridize and serve as the site for the initiation of synthesis. "Substantially complementary" means that the primer complementarity is sufficient to hybridize to the target polynucleotide. In some embodiments, the primer does not contain mismatches with the template to which it is designed to hybridize, but this is not necessary. For example, non-complementary nucleotide residues can be linked to the 5' end of the primer, while the rest of the primer sequence is complementary to the template. Alternatively, non-complementary nucleotide residues or a stretch of non-complementary nucleotide residues can be interspersed within the primer, as long as the primer sequence has sufficient complementarity with the template sequence to which it is to hybridize and thereby form a template for the synthesis of the primer extension product.

[0058] The term "diagnosis" or "auxiliary diagnosis" refers to the identification or classification of a molecular or pathological state, disease or disorder. For example, through molecular characteristics (such as the microbiome, specific genes, proteins encoded by specific genes), it is determined whether there is an abnormal uric acid or the risk of abnormal uric acid.

[0059] As is well known to those skilled in the art, the step of associating a microbial biomarker mutation or content with a certain probability or risk can be implemented and achieved in different ways. In a specific embodiment, the mutation level or content of the microbial biomarker is mathematically operated, and the operation value is associated with the underlying diagnostic problem. The biomarkers can be combined by any suitable prior art mathematical method.

[0060] The present invention provides the application of microbial biomarkers in constructing a computer model for diagnosing diseases related to abnormal uric acid, and the microbial biomarkers include the microbial biomarkers described in any one of the foregoing.

[0061] In a preferred embodiment of the application of the present invention, the input scalar of the calculation model is the relative mutation levels of the microbial biomarkers Prevotella_stercorea, Escherichia_coli, Bacteroides_eggerthii, Bacteroides_xylanisolvens, Bacteroides_uniformis, Bacteroides_coprocola_CAG.162, Lachnospiraceae_bacterium_8_1_57FAA. In a specific embodiment, the method for measuring the relative mutation level of the microbial biomarker includes one or more of metagenomic sequencing, 16S rRNA amplicon sequencing, droplet digital PCR, and qPCR quantitative detection.

[0062] The present invention uses the relative mutation level or content of the gut microbiota (i.e., the microbial biomarker of the present invention) as a prediction index. Therefore, the above-mentioned molecular biological methods can be used to detect it. This diverse quantitative means can break through the limitations of specific experimental conditions and experimental skills, enabling some laboratories without specific experimental equipment to also conduct data measurement and prediction of the present invention.

[0063] As used herein, the terms "comprising", "including", "having", "containing" or any other variation thereof. For example, a composition, step, method, article or device comprising the listed elements need not be limited to those elements, but may include other elements not expressly listed or elements inherent to such composition, step, method, article or device.

[0064] The present invention provides a prediction system or device for diseases related to abnormal uric acid based on microbial markers, wherein the microbial markers include the microbial markers described in any one of the preceding items, and the prediction system or device includes:

[0065] Input unit: obtaining mutation level data of microbial markers obtained from a subject sample;

[0066] Processing unit: analyzing and processing the mutation level data of the microbial markers of the input unit to obtain a prediction result of the subject;

[0067] Output unit: outputting the prediction result of the subject obtained by analyzing and processing by the processing unit;

[0068] Furthermore, the diseases related to abnormal uric acid include hyperuricemia, hypouricemia, gout, urinary calculi, gouty nephropathy, and uric acid nephrolithiasis.

[0069] Furthermore, the sample includes blood, serum, and fecal samples.

[0070] In the present invention, the term "sample" includes cells, tissues, organs, body fluids (such as blood, lymph fluid, etc.), digestive fluids, expectoration, alveolar bronchial lavage fluid, urine, feces, etc. In the specific embodiments of the present invention, the sample is blood and serum.

[0071] In the present invention, a "subject" includes an animal that can suffer from or contract abnormal uric acid. Examples of subjects include mammals, such as humans, non-human primates, dogs, cows, horses, pigs, sheep, goats, cats, mice, rabbits, rats, and transgenic non-human animals. In the specific embodiments of the present invention, the subject is a human.

[0072] Compared with the prior art, the present invention has the following beneficial effects:

[0073] The present invention provides microbial markers related to abnormal uric acid, which have the potential to be used as detection markers for abnormal uric acid. They can be used for non-invasive auxiliary diagnosis of abnormal uric acid, with good specificity, high sensitivity, high cost performance, and can guide the adjustment of the microbial environment of the intestinal flora, reducing the possibility of abnormal uric acid. Description of the Drawings

[0074] Figure 1 is the ROC curve graph for diagnosing abnormal uric acid using microbial markers in the test set;

[0075] Figure 2 is the ROC curve graph for diagnosing abnormal uric acid using microbial markers in the validation set;

[0076] Figure 3Schematic diagram of a prediction system or device for diseases related to abnormal uric acid based on microbial markers. Detailed implementation manners

[0077] The present invention will be further described below in conjunction with specific embodiments, which are only used to explain the present invention and cannot be construed as a limitation to the present invention. Those of ordinary skill in the art can understand that: various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and purposes of the present invention, and the scope of the present invention is defined by the claims and their equivalents. The experimental methods without specific conditions noted in the following embodiments are usually implemented according to conventional conditions or according to the conditions recommended by the manufacturers.

[0078] As a preferred implementation manner, it includes the following steps:

[0079] (1) Collection and processing of samples: Collect relevant samples and use a kit for DNA extraction to obtain nucleic acid samples;

[0080] (2) Library construction and sequencing: Use high-throughput sequencing for DNA library construction and sequencing to obtain the nucleic acid sequences of the gut microbiota contained in the samples;

[0081] (3) Determine the specific gut microbiota nucleic acid sequences related to abnormal uric acid through bioinformatics analysis methods.

[0082] AUC is the estimated area under the curve. The larger the AUC, the higher the diagnostic ability. For each species, a diagnostic critical value is determined such that the sum of the diagnostic sensitivity and specificity is the highest at this critical value. The detailed method for determining the critical value is as follows: Sort the relative mutation levels of the species from small to large, and then sequentially take a value as the candidate critical value. Calculate the sensitivity and specificity at this candidate critical value, and take the candidate critical value with the largest sum of sensitivity and specificity as the final optimal critical value.

[0083] Sensitivity is also called the true positive rate, which is the probability that an actual patient is diagnosed as a patient by the index, that is, the probability that a patient is diagnosed as positive. Specificity is also called the true negative rate, which refers to the probability that an actual non-patient is diagnosed as a non-patient by the index, that is, the probability that a non-patient is diagnosed as negative.

[0084] The terms used herein have the meanings commonly understood by those of ordinary skill in the relevant fields of the present invention. Terms such as "a", "an" and "the" refer not only to a single entity but also to a general category that can be used to illustrate a specific embodiment. The terms in this article are used to describe the specific embodiments of the present invention, but their use does not limit the present invention unless specified in the claims.

[0085] In the present invention, according to the selected sequencing platform, the sequencing can be, but is not limited to, semiconductor sequencing technology platforms such as PGM, synthesis sequencing technology platforms such as the HISeq and Miseq sequence platforms of Illumina, Inc., and single molecule real-time sequencing platforms such as the PaCBio sequence platform. The sequencing method can be single-end sequencing or paired-end sequencing. The off-machine data obtained are the sequenced fragments, called reads.

[0086] In the present invention, the so-called assembly can be carried out using known sequence assembly methods or software, such as SOAPdenovo, velvet, etc.

[0087] Example 1 Screening and testing of gut microbiota related to abnormal uric acid

[0088] 1. Research subjects and sample collection

[0089] Blood, serum, and fecal samples were collected from 258 subjects, including 129 patients with abnormal uric acid and 129 healthy individuals.

[0090] 2. Experimental methods

[0091] 1) Collection of blood, serum, and fecal samples and DNA extraction

[0092] After collecting the blood, serum, and fecal samples of the above-mentioned population, a kit was used for DNA extraction to obtain the extracted DNA samples.

[0093] 2) Metagenomic high-throughput sequencing and analysis

[0094] Reference genomes of 7 microbial species, namely Prevotella_stercorea (GenBank ID: QRNO01000027.1), Escherichia_coli (GenBank ID: CP076470.1), Bacteroides_eggerthii (GenBank ID: CP072228.1), Bacteroides_xylanisolvens (GenBank ID: CP072216.1), Bacteroides_uniformis (GenBank ID: CP054204.1), Bacteroides_coprocola_CAG.162 (GenBank ID: FR881015.1), and Lachnospiraceae_bacterium_8_1_57FAA (GenBank ID: GL622453.1), were downloaded from the NCBI database. First, quality control was performed on the sequences obtained from the original sequencing. The sequenced sequences after quality control were aligned with the 7 genomes using the BWA software to obtain the sequences of each genome. The SAMTools software (parameters: "-vmO z -V indels") and the VCF tools software (parameters: 1 / d = 10 / a = 4 / Q = 15 / q = 10 / .) were used to find SNP sites and filter out high-quality SNP sites. To reduce the false positives in the results, the VarScan2 software (parameters: "--min-coverage 10 --min-reads2 4 --min-var-freq 0.2 --p-value 0.05.") was also used to find and filter SNPs. Finally, the SNP results for downstream analysis were the intersection of the screening results of the two software.

[0095] 3) Diagnostic efficacy analysis

[0096] The receiver operating characteristic curve (ROC) was plotted using the R package "pROC" to analyze the AUC value, sensitivity, and specificity of the microbial markers with significantly different mutation levels between healthy individuals and subjects with abnormal uric acid levels in the test set, so as to judge their diagnostic efficacy for diseases related to abnormal uric acid.

[0097] Among them, the mutations of the microbial markers were used for evaluation and analysis, and the point corresponding to the maximum Youden index was selected as its cutoff value, that is, the optimal division threshold was determined by the point with the maximum Youden index.

[0098] 3. Experimental results

[0099] The genome-wide association analysis of SNPs in the bacterial genome and uric acid phenotype was performed using the BLINK software and FarmCPU software in GAPIT. The results showed that the mutation levels of Prevotella_stercorea (GenBank ID: QRNO01000027.1), Escherichia_coli (GenBank ID: CP076470.1), Bacteroides_eggerthii (GenBank ID: CP072228.1), Bacteroides_xylanisolvens (GenBank ID: CP072216.1), Bacteroides_uniformis (GenBank ID: CP054204.1), Bacteroides_coprocola_CAG.162 (GenBank ID: FR881015.1), and Lachnospiraceae_bacterium_8_1_57FAA (GenBank ID: GL622453.1) strains were significantly correlated with uric acid levels.

[0100] The results of species difference analysis showed significant differences in the mutation levels at the 4571st base of the Prevotella_stercorea genome (GenBank ID: QRNO01000027.1), the 1122339th base of the Escherichia_coli genome (GenBank ID: CP076470.1), the 51594th base of the Bacteroides_eggerthii genome (GenBank ID: CP072228.1), the 5120272nd base of the Bacteroides_xylanisolven genome (GenBank ID: CP072216.1), the 105620th base of the Bacteroides_uniformis genome (GenBank ID: CP054204.1), the 246th base of the Bacteroides_coprocola_CAG.162 genome (GenBank ID: FR881015.1), and the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome (GenBank ID: GL622453.1), as shown in Table 1.

[0101] Table 1

[0102]

[0103]

[0104] The results showed that there were significant differences in the mutation levels of 7 microbial markers between the hyperuricemia population and the normal population. The OR values indicated that the mutation detection sites of the 7 microbial markers were all influencing factors for hyperuricemia. The mutation of the 4571st base of the Prevotella_stercorea genome (GenBank ID: QRNO01000027.1), the 51594th base of the Bacteroides_eggerthii genome (GenBank ID: CP072228.1), the 5120272nd base of the Bacteroides_xylanisolven genome (GenBank ID: CP072216.1), and the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome (GenBank ID: GL622453.1) were protective factors; the mutation of the 1122339th base of the Escherichia_coli genome (GenBank ID: CP076470.1), the 105620th base of the Bacteroides_uniformis genome (GenBank ID: CP054204.1), and the 246th base of the Bacteroides_coprocola_CAG.162 genome (GenBank ID: FR881015.1) were risk factors.

[0105] Taking the microbial markers as detection variables, ROC curves were plotted and their AUC values were calculated. The results are as Figure 1 shown, with the AUC value being 0.8295, indicating that using the combination of microbial markers as detection variables has high specificity and sensitivity.

[0106] Example 2 verifies the ability of microbial markers to diagnose diseases related to abnormal uric acid

[0107] 1. Research objects and sample collection

[0108] Collect 50 samples of human populations, including blood, serum, and fecal samples from 25 patients with abnormal uric acid and 25 healthy people.

[0109] 2. Experimental methods

[0110] 1) Collection of blood, serum, and fecal samples and DNA extraction

[0111] After collecting blood, serum, and fecal samples from the above-mentioned population, DNA extraction was performed using a kit to obtain the extracted DNA samples.

[0112] 2) Metagenomic high-throughput sequencing and analysis

[0113] Reference genomes of 7 microbial species, namely Prevotella_stercorea (GenBank ID: QRNO01000027.1), Escherichia_coli (GenBank ID: CP076470.1), Bacteroides_eggerthii (GenBank ID: CP072228.1), Bacteroides_xylanisolvens (GenBank ID: CP072216.1), Bacteroides_uniformis (GenBank ID: CP054204.1), Bacteroides_coprocola_CAG.162 (GenBank ID: FR881015.1), and Lachnospiraceae_bacterium_8_1_57FAA (GenBank ID: GL622453.1), were downloaded from the NCBI database. First, quality control was performed on the sequences obtained from the original sequencing. The quality-controlled sequencing sequences were aligned with the 7 genomes using the BWA software to obtain the sequences of each genome. The SAMTools software (parameters: "-vmO z -V indels") and the VCF tools software (parameters: 1 / d = 10 / a = 4 / Q = 15 / q = 10 / .) were used to find SNP sites and filter out high-quality SNP sites. To reduce false positives in the results, the VarScan2 software (parameters: "--min-coverage 10 --min-reads2 4 --min-var-freq 0.2 --p-value 0.05.") was also used to find and filter SNPs. Finally, the SNP results for downstream analysis were the intersection of the screening results of the two software.

[0114] 3) Diagnostic efficacy analysis

[0115] The receiver operating characteristic curve (ROC) was plotted using the R package "pROC" to analyze the AUC value, sensitivity, and specificity of the microbial markers with significantly different mutation levels between healthy individuals and subjects with abnormal uric acid in the test set, in order to judge their diagnostic efficacy for diseases related to abnormal uric acid.

[0116] Among them, the mutation of the microbial biomarker is used for evaluation and analysis, and the point corresponding to the maximum Youden index is selected as its cutoff value, that is, the optimal division threshold is determined by the point with the maximum Youden index.

[0117] 3. Experimental results

[0118] ROC curve analysis of microbial biomarkers for diagnosing diseases related to abnormal uric acid

[0119] Taking the mutation combination of microbial biomarkers as the detection variable, the ROC curve is plotted and its AUC value is calculated. The results are as Figure 2 shown, showing that the AUC value is 0.7613, indicating that the mutation combination of microbial biomarkers can be used as a microbial biomarker for diagnosing diseases related to abnormal uric acid.

Claims

1. Use of a reagent for detecting a microbial biomarker in the preparation of a product for diagnosing hyperuricemia, characterized in that, The microbial biomarker is a combination of mutations at the 4571st base of the Prevotella_stercorea genome, the 1122339th base of the Escherichia_coli genome, the 51594th base of the Bacteroides_eggerthii genome, the 5120272nd base of the Bacteroides_xylanisolven genome, the 105620th base of the Bacteroides_uniformis genome, the 246th base of the Bacteroides_coprocola_CAG.162 genome, and the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome. The positions of the mutations are SNP sites; When the 4571st base of the Prevotella_stercorea genome in the microbial biomarker is T, the 1122339th base of the Escherichia_coli genome is C, the 51594th base of the Bacteroides_eggerthii genome is T, the 5120272nd base of the Bacteroides_xylanisolven genome is T, the 105620th base of the Bacteroides_uniformis genome is T, the 246th base of the Bacteroides_coprocola_CAG.162 genome is C, and the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome is C, the risk of an individual having hyperuricemia increases; when the 4571st base of the Prevotella_stercorea genome in the microbial biomarker is C, the 1122339th base of the Escherichia_coli genome is G, the 51594th base of the Bacteroides_eggerthii genome is G or A, the 5120272nd base of the Bacteroides_xylanisolven genome is G, the 105620th base of the Bacteroides_uniformis genome is C, the 246th base of the Bacteroides_coprocola_CAG.162 genome is T, and the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome is T, the risk of an individual having hyperuricemia decreases; The GenBank ID of the Prevotella_stercorea genome is QRNO01000027.1, the GenBank ID of the Escherichia_coli genome is CP076470.1, the GenBank ID of the Bacteroides_eggerthii genome is CP072228.1, the GenBank ID of the Bacteroides_xylanisolven genome is CP072216.1, the GenBank ID of the Bacteroides_uniformis genome is CP054204.1, the GenBank ID of the Bacteroides_coprocola_CAG.162 genome is FR881015.1, and the GenBank ID of the Lachnospiraceae_bacterium_8_1_57FAA genome is GL622453.

1.

2. The application according to claim 1, wherein, The product includes reagents capable of detecting the microbial biomarker.

3. According to the application described in claim 1, the reagent includes specific primers, probes or antisense oligonucleotides for detecting mutations at the 4571st base of the Prevotella_stercorea genome, mutations at the 1122339th base of the Escherichia_coli genome, mutations at the 51594th base of the Bacteroides_eggerthii genome, mutations at the 5120272nd base of the Bacteroides_xylanisolven genome, mutations at the 105620th base of the Bacteroides_uniformis genome, mutations at the 246th base of the Bacteroides_coprocola_CAG.162 genome, and mutations at the 77201st base of the Lachnospiraceae_bacterium_8_1_57FAA genome.

4. The application according to claim 1, wherein The product determines whether a subject has hyperuricemia by measuring the mutation level of the microbial biomarker in a sample.

5. According to the application described in claim 1, the sample is feces.

6. Use of microbial biomarkers in constructing a computer model for diagnosing hyperuricemia, characterized in that, The microbial biomarker is the microbial biomarker described in claim 1.

7. A prediction system for hyperuricemia based on microbial markers, characterized in that, The microbial biomarker is the microbial biomarker described in claim 1, and the prediction system includes: Input unit: Obtain the mutation level data of the microbial biomarker obtained from a subject's sample; Processing unit: Analyze and process the mutation level data of the microbial biomarker from the input unit to obtain the prediction result of the subject; Output unit: Output the prediction result of the subject obtained by the analysis and processing of the processing unit.

8. The prediction system according to claim 7, wherein The sample is feces.

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