CN112048565B

CN112048565B - Intestinal flora for diagnosing myasthenia gravis and application thereof

Info

Publication number: CN112048565B
Application number: CN202010966787.2A
Authority: CN
Inventors: 乞国艳
Original assignee: Shijiazhuang People's Hospital Shijiazhuang First Hospital Shijiazhuang Tumor Hospital Hebei Myasthenia Gravis Hospital Shijiazhuang Cardiovascular Disease Hospital
Current assignee: Shijiazhuang People's Hospital Shijiazhuang First Hospital Shijiazhuang Tumor Hospital Hebei Myasthenia Gravis Hospital Shijiazhuang Cardiovascular Disease Hospital
Priority date: 2020-09-15
Filing date: 2020-09-15
Publication date: 2023-04-28
Anticipated expiration: 2040-09-15
Also published as: CN112048565A

Abstract

The invention discloses a flora derived from intestinal tracts for diagnosing myasthenia gravis and application thereof, belonging to the field of biological medicine. The flora comprises Megamonas hyperspectral or a combination of Megamonas hyperspectral and Fusobacteria molar, and the risk of the subject to suffer from myasthenia gravis can be estimated through detection of the intestinal flora marker, so that auxiliary reference is provided for diagnosis and treatment of diseases.

Description

Intestinal flora for diagnosing myasthenia gravis and application thereof

Technical Field

The invention belongs to the technical field of biology, and relates to a flora derived from intestinal tracts for diagnosing myasthenia gravis and application thereof.

Background

Myasthenia gravis (Myasthenia gravis, MG) is a chronic autoimmune disease in which the transmission function between nerve-muscle junctions (synapses) is impaired, mainly mediated by antibodies to acetylcholine receptors (Acetylcholine Receptor, achR), cellular immunity and complement involvement leading to disruption of the normal structure of the postsynaptic membrane. Clinically, the symptoms are that the affected muscle groups are weak and easy to fatigue, and the symptoms are relieved after rest and application of cholinesterase inhibitors. The incidence rate of the Chinese medicine is 8.0-20.0/10 ten thousand people (the Chinese immunology department, the Chinese medical department, the Chinese diagnostic and therapeutic guidelines for myasthenia gravis 2015[ J ]. J.China department of neurology, 2015,48 (11): 934-940), wherein the incidence rate of children is 1-5/10 ten thousand people (Lai CH, tseng HF. National width preparation-Based Epidemiological Study of Myasthenia Gravis in Taiwan [ J ]. Neuroepide technology, 2010,35 (1): 66-71). Eye muscle involvement is the most common clinical first manifestation of childhood MG, which can be unilateral or bilateral eyelid prolapse, with or without blurred vision, ghosting, eye movement disorder, etc. characterized by a slight twitch in the morning. About 35% of patients develop systemic myasthenia gravis (Generalized Myasthenia Gravis, GMG) within 2 years (mulaney P, smith r.the Natural History and Ophthalmic Involvement in Childhood Myasthenia Gravis at The Hospital for Sick Children [ J ]. Onhharlmology.2000.107 (31:504-510.).

MG presents a different clinical symptom profile in children and adolescents than in adults, so diagnosis and treatment of MG, especially for young children, remains a challenge. Early diagnosis is extremely important to initiate proper treatment to prevent further exacerbation of muscle weakness from failing to achieve complete relief.

The change of intestinal microecology influences the occurrence and development of diseases, and more clinical reports and animal experiments prove that intestinal flora is an important factor influencing the diseases and the response of an immune system, and the composition of the intestinal flora also becomes a biological index for diagnosis and treatment, so that the occurrence, the development and the cure degree of the diseases can be judged by detecting the composition of the intestinal flora in the feces of patients to a certain extent. At present, the research on the intestinal flora of myasthenia gravis is less, the intestinal flora related to the myasthenia gravis is screened, the role of the intestinal flora in the development process of the myasthenia gravis is explored, and the method has important significance for enhancing the cognition of the myasthenia gravis and realizing the noninvasive diagnosis of the myasthenia gravis.

Disclosure of Invention

Aiming at the defects of the prior art, the invention aims to provide intestinal flora related to occurrence and development of myasthenia gravis and application thereof in diagnosis and treatment of myasthenia gravis, so as to overcome the defects that the existing diagnosis of myasthenia gravis cannot realize early warning, noninvasive diagnosis cannot be realized, and the like, and can help diagnosis of diseases, guide medicine research, accurately take medicine and the like.

In order to achieve the above purpose, the present invention adopts the following technical scheme:

in a first aspect the invention provides a microorganism marker of myasthenia gravis, the microorganism marker comprising the species Megamonas hypermegale and/or fusarium molar.

In a second aspect, the invention provides a reagent for detecting a myasthenia gravis biomarker according to the first aspect of the invention.

A third aspect of the invention provides the use of a myasthenia gravis biomarker according to the first aspect of the invention or an agent according to the second aspect of the invention, the use comprising:

1) A computational model for constructing a predicted risk of myasthenia gravis;

2) Preparing a reagent for diagnosing myasthenia gravis diseases; or (b)

3) Preparing a myasthenia gravis diagnosis kit.

Further, the input variable of the calculation model is the content of the myasthenia gravis biomarker according to the first aspect of the present invention.

Further, the method for determining the abundance of the myasthenia gravis biomarkers comprises any one or more of metagenomic sequencing, 16S sequencing or qPCR quantitative detection. The invention takes the abundance or content of the flora as a prediction index, so that whether metagenome sequencing and quantification or 16S sequencing and quantification or qPCR quantification is used as a measurement means, and diversified quantification means breaks through the limitation of specific experimental setup and experimental skills, so that some laboratories without specific experimental equipment can also test the data measurement and prediction of the invention.

In a fourth aspect, the invention provides a diagnostic kit for myasthenia gravis, comprising reagents for detecting the level of a biomarker for myasthenia gravis according to the first aspect of the invention.

Further, the reagent includes a polymerase chain reaction, a reverse transcription-polymerase chain reaction, a nested PCR or a reagent for nucleic acid hybridization.

Further, the myasthenia gravis biomarker content is determined by amplifying a fragment of the myasthenia gravis biomarker in the subject sample.

Further, the fragment is a fragment of a microorganism marker species-specific gene.

Further, the amplification is achieved by polymerase chain reaction.

Further, the amplification utilizes detectably labeled primers.

Further, detection is achieved using electrophoresis.

Further, the sample is a stool sample.

In a fifth aspect, the invention provides a system for diagnosing or predicting myasthenia gravis using the microbial markers described in the first aspect of the invention, the system comprising a nucleic acid sample isolation device, a sequencing device, and an alignment device, the alignment device being connected to the sequencing device.

Further, the comparison device comprises a data processing unit and a result judging unit.

In a sixth aspect, the invention provides the use of the microbial marker according to the first aspect in the preparation of a medicament or functional food for treating or preventing myasthenia gravis, wherein the medicament or functional food for treating or preventing myasthenia gravis designed for Megamonas hypermegale or Fusobacterium molar is capable of reducing the content of Megamonas hypermegale or Fusobacterium molar.

The invention has the beneficial effects and advantages that:

the invention provides a myasthenia gravis microorganism marker which can be used for prediction and auxiliary diagnosis of myasthenia gravis, has good detection specificity and high sensitivity, indicates the condition of intestinal microorganism flora, guides the adjustment of intestinal microecology and reduces the prevalence rate of myasthenia gravis.

The method for predicting the myasthenia gravis risk model has the advantages of good sensitivity and high accuracy, only uses specific strain abundance as an input index, is not limited to a measuring means, only supports the model method by an experimental means capable of obtaining strain abundance values, and is beneficial to model realization and popularization.

Drawings

FIG. 1 is a violin diagram of an α diversity and β diversity distribution; wherein a-C is a profile of alpha diversity based on shannon index at the gate (a), genus (B) and species (C) level; D-F is a distribution of beta diversity at the gate (D), genus (E) and species (F) levels based on the Bray-Curtis distance.

Fig. 2 is PcoA at the relative abundances of all participants at different taxonomic levels, where plots a-F are PcoA at the relative abundances at the phylum, class, order, family, genus, species taxonomic levels, respectively, red and blue triangles represent MG and HC, respectively.

FIG. 3 shows a plot of abundance of megamonas hypermegale.

FIG. 4 is a graph of ROC of Megamonas_hypermegale as a test variable.

Detailed Description

The microbial markers of the present invention batch analyze stool samples from healthy individuals and myasthenia gravis patients by using whole genome sequencing. Based on the high throughput sequencing data, a healthy population is aligned with a myasthenia gravis patient population to determine specific nucleic acid sequences associated with the myasthenia gravis patient population.

Briefly, the procedure is as follows:

sample collection and processing: collecting fecal samples of healthy people and myasthenia gravis patient groups, and extracting DNA by using a kit to obtain a nucleic acid sample;

library construction and sequencing: DNA library construction and sequencing is performed using high throughput sequencing to obtain nucleic acid sequences of intestinal microorganisms contained in fecal samples;

by bioinformatic analysis methods, specific intestinal microbial nucleic acid sequences associated with myasthenia gravis patients were determined. First, the sequenced sequences (reads) are aligned with a reference gene set (also referred to as a reference gene set, which may be a newly constructed gene set or a database of any known sequences, for example, using a known human intestinal microflora non-redundant gene set). Next, based on the comparison results, the relative abundance of each gene in the nucleic acid samples from the stool samples of the healthy and myasthenia gravis patient populations, respectively, was determined. By comparing the sequencing sequence with the reference gene set, a corresponding relationship can be established between the sequencing sequence and the genes in the reference gene set, so that the number of the sequencing sequences corresponding to the specific genes in the nucleic acid sample can effectively reflect the relative abundance of the genes. Thus, the relative abundance of genes in a nucleic acid sample can be determined by comparison and conventional statistical analysis. Finally, after determining the relative abundance of each gene in the nucleic acid sample, the relative abundance of each gene in the nucleic acid sample from the faeces of the healthy and myasthenia gravis patient population is statistically examined, whereby it can be judged whether there is a gene having a significant difference in relative abundance between the healthy and myasthenia gravis patient population, and if there is a significant difference in the gene, the gene is regarded as a biomarker of an abnormal state, i.e., a nucleic acid marker.

In addition, for known or newly constructed reference gene sets, they typically contain genetic species information and functional annotations, whereby, based on determining the relative abundance of genes, the species information and functional annotations of genes can be further categorized to determine the relative abundance of species of each microorganism in the intestinal flora, and thus further determine the species markers and functional markers of abnormal states.

Briefly, the method of determining a species marker and a functional marker further comprises: comparing the sequencing sequences of the healthy population and the myasthenia gravis patient population to a reference gene set; based on the comparison result, determining the species relative abundance and the function relative abundance of each gene in the nucleic acid samples of the healthy population and the myasthenia gravis patient population respectively; the relative abundance of species and relative abundance of function for each gene in nucleic acid samples from healthy and myasthenia gravis patient populations were statistically calculated.

Finally, a biological marker is determined for a significant difference in relative abundance between fecal samples of a healthy population and a myasthenia gravis patient population, whereby the presence or absence of a subject is effectively determined by detecting the presence or absence of at least one of the aforementioned microorganisms and can be used to monitor the therapeutic effect of a myasthenia gravis patient. In the present invention, it is possible to qualitatively analyze whether or not a sample contains a corresponding target, quantitatively analyze the target in the sample, and further statistically analyze the obtained quantitative analysis result with a reference (for example, a quantitative analysis result obtained by parallel test of a sample having a known state) or any known mathematical operation. Those skilled in the art can readily select as desired and as test conditions. According to embodiments of the present invention, it is also possible to determine whether a subject suffers from or is susceptible to myasthenia gravis, and to monitor the therapeutic effect of a patient suffering from myasthenia gravis by determining the relative abundance of these microorganisms in the intestinal flora.

Whether a subject has or is susceptible to myasthenia gravis can be effectively determined by detecting the presence of at least one of the microbial markers in the subject's intestinal flora, or by detecting the presence of two or more of the biological markers in the subject's intestinal flora, i.e., the presence of a combination of biological markers, and can be used to monitor the therapeutic effect of a patient suffering from myasthenia gravis. In the present invention, the term "biomarker combination" refers to a set of biomarkers (i.e., a combination of two or more biomarkers).

The presence or absence of species and function in the intestinal flora can also be determined by a person skilled in the art for species markers and function markers by conventional means of strain identification and biological activity assay. For example, strain identification can be performed by QPCR or metagenome.

In an embodiment of the invention, the invention diagnoses myasthenia gravis by: one or more nucleic acid fragments corresponding to a species associated with diagnosis of myasthenia gravis are detected in a nucleic acid sample from an individual. In a particular embodiment, the detection corresponds to a nucleic acid fragment directed against Megamonas_hypermegale or Fusobacterium_Mortiferum. In practicing the methods described herein, many conventional techniques in molecular biology, protein biochemistry, cell biology, immunology, microbiology, and recombinant DNA are used, which are well known.

As an alternative embodiment, the method of detecting a microbial marker is a method of sequencing, which is a method of sequencing including, but not limited to, a second generation sequencing method or a third generation sequencing method. The means for sequencing is not particularly limited, and rapid and efficient sequencing can be achieved by sequencing through a second-generation or third-generation sequencing method. As a specific embodiment, the sequencing method is performed by at least one selected from the group consisting of Hiseq2000, SOLiD, 454, and single molecule sequencing device. Therefore, the high-throughput and deep sequencing characteristics of the sequencing devices can be utilized, so that the analysis of subsequent sequencing data, particularly the precision and accuracy in the process of statistical inspection, is facilitated.

The invention provides a system for diagnosing or predicting myasthenia gravis by utilizing a microbial marker aiming at Megamonas hypermegale or Fusobacteria molar, which comprises a nucleic acid sample separation device, a sequencing device and an alignment device, wherein the alignment device is connected with the sequencing device. The comparison device comprises a data processing unit and a result judging unit.

As an alternative embodiment, the sequencing device is connected to a sample separation device, a DNA library is constructed based on the obtained nucleic acid sample, and the DNA library is sequenced to obtain sequencing results. An alignment device is coupled to the sequencing device and, based on the sequencing results, compares the sequencing results to a reference gene set to determine relative abundance information for the biomarker.

As an alternative embodiment, the sequencing device is not particularly limited. Preferably, the apparatus is performed using a second generation sequencing method or a third generation sequencing method. Preferably, the sequencing device is at least one selected from the group consisting of a Hiseq2000, SOLiD, 454, and single molecule sequencing device. Therefore, the high-throughput and deep sequencing characteristics of the sequencing devices can be utilized, so that the analysis of subsequent sequencing data, particularly the precision and accuracy in the process of statistical inspection, is facilitated.

It is known to those skilled in the art that when the sample size is further expanded, the normal content value interval (absolute value) of each biomarker in the sample can be derived using sample detection and calculation methods well known in the art. The absolute value of the biomarker content detected may be compared to a normal content value, optionally in combination with statistical methods, to derive a myasthenia gravis risk assessment, diagnosis, efficiency for monitoring the therapeutic effect of a myasthenia gravis patient, etc.

Without wishing to be bound by any theory, the inventors point out that these biomarkers are intestinal flora present in humans. The method provided by the invention is used for carrying out correlation analysis on the intestinal flora of a subject, and the biomarker for obtaining the myasthenia gravis population shows a certain content range value in flora detection. Meanwhile, the biomarker for myasthenia gravis has better specificity.

The invention will now be described in further detail with reference to the drawings and examples. The following examples are only illustrative of the present invention and are not intended to limit the scope of the invention. The experimental procedure, in which specific conditions are not noted in the examples, is generally followed by conventional conditions.

Example 1 screening for intestinal flora associated with myasthenia gravis

1. Study and sample collection

55 children myasthenia gravis patients and 36 Healthy Controls (HC) of the corresponding ages and sexes collected in the first hospital myasthenia gravis treatment center in Shi-Jianzhong City of Hebei were studied, and sample information is shown in Table 1.

Diagnostic criteria: (1) clinical manifestations: eyelid ptosis, compound vision, strabismus; (2) neostigmine test positive; (3) acetylcholine receptor antibody positive; (4) electromyography: the facial nerve attenuates at low frequency and does not increase at high frequency. One of (1) + (2) or (3) or (4) can be diagnosed explicitly.

Parting: new clinical typing and quantitative myasthenia gravis score (QMG) criteria were proposed by reference to the american myasthenia gravis association (MGFA) in 2000.

Inclusion criteria: the patient is clearly diagnosed as myasthenia gravis type, and meets the diagnosis standard.

Exclusion criteria: (1) age <2 years 10 months or no age information; (2) Antibiotics other than beta-lactams were used within 3 months; (3) administering other drugs/hormones for treating diseases; (4) using anti-inflammatory drugs or unknown Chinese herbal medicines.

Table 1 sample clinical features

2. DNA extraction and sequencing

DNA was extracted from the samples using the DNA extraction kit, and the procedure was performed according to instructions. The concentration of DNA was measured using a fluorometer or microplate reader (e.g., qubit Fluorometer, invitrogen) and the integrity and purity of the samples were measured using agarose gel electrophoresis (agarose gel concentration: 1%V, voltage: 150V, electrophoresis time: 40 min). The genomic DNA was randomly disrupted using Covaris and fragmented genomic DNA with an average size of 200-400bp was screened with magnetic beads. The resulting DNA fragment was subjected to end repair, 3 '-end was subjected to adenylation, and a linker was attached to the end of the 3' -end adenylated fragment, followed by PCR amplification. The PCR products were purified using magnetic beads. The double-stranded PCR product was subjected to heat distortion and circularization with a splint oligonucleotide sequence, single-stranded loop DNA (SsCir DNA) was formatted to construct the final library, and quality control was performed on the library quality. Amplifying the library by phi29 to obtain a DNA Nanosphere (DNB) with a molecular copy number of more than 300. The resulting DNBs were added to the network wells on the chip (immobilized on an arrayed silicon chip) and double-ended sequences with read length of 100bp/150bp were obtained by combining probe-anchored polymerization (cPAS) and double-ended sequencing by multiple displacement amplification (MDA-PE).

3. Quality control

And performing quality control processing on the measured data to finally obtain high-quality data for subsequent analysis, wherein the quality control steps are as follows: 1) Filtering low quality reads; 2) The contamination of human genome sequences was removed, low quality reads and sequence-adapted sequences were screened using FastP (REF 21) and its default parameters, reads were aligned with human genome (Hg 38) using Bowtie2 (REF 22), and paired reads that were not aligned with human genome were screened using Samtools as clean reads for subsequent analysis.

4. Classification annotation and functional annotation

High quality reads were mapped to the mpa_v20 marker gene database using Metlan2, resulting in a classification abundance map at different classification levels for each sample. The results of all samples were combined using merge_meta_tables.py and combined abundance spectra at different species levels were obtained using internal script. On the other hand, high quality reads were mapped to uniref90 and chocophlan using humann2 to obtain gene abundance and pathway abundance maps. Then, the abundances of all samples were pooled using humann2_join_ Tables, humann2_renorm_table and humann2_split_strayfied_table, respectively, and normalized and hierarchically classified annotated for abundance. In addition, KEGG and GO enrichment analysis was performed using humann2_regroup_table and humann2.

5. Statistical analysis

All abundance results were differentially analyzed using the wilcox.test two.side function in R, depending on the grouping of samples. The P-value in each result will be corrected according to the BH method to obtain q-value (FDR) for screening species and pathways that clearly exhibit significant differences. Alpha diversity was calculated for each sample using Shannon index. Under the same input, β diversity was calculated using the Vegan packet in R with the parameter 'method=dist_method'. ROC curves were also plotted using pROC analysis of R and AUC areas thereof were calculated.

Principal Component Analysis (PCA) is carried out on the classification map, the eig result of the PCA is calculated by using an Ade4 software package of R, the dudi.pca function is used for obtaining feature vectors of different PCs, the li result is used for obtaining coordinates of each sample on a PC axis, and the cl is used for obtaining contribution percentage of each PC in the total variance.

To relate the differential species to the clinical phenotype of the sample, the Spearman correlation between the characteristic and the clinical phenotype was calculated using the corr.tes method in the R-package according to the parameters 'method=spearman, use=parilwise, adjust=bh'.

6. Results

The α -diversity and β -diversity at different classification levels based on Shannon index were not significantly different between patient and healthy population (fig. 1).

PCA and PcoA results showed no significant aggregation profile in patients and healthy persons (fig. 2).

Analysis of species variability results showed 20 species exhibiting significant differences, 11 of which ROC detection AUC values >0.7, as shown in table 2. The results of the combined diagnostic analysis on the 20 differential bacterial groups are shown in Table 3. Wherein, compared with healthy controls, megamonas hypermegale was significantly increased in MG patients (fig. 3), the AUC value was 0.731, the diagnostic threshold was 0.003, the specificity at the optimal critical point was 0.889, the sensitivity was 0.582 (fig. 4), and the combined diagnostic efficacy of Megamonas hypermegale and fusarium molar was analyzed, and the combination of Megamonas hypermegale and fusarium molar was found to have higher efficacy (AUC value of 0.863), indicating that the above flora alone or in combination as a detection index could effectively distinguish myasthenia gravis patients from healthy persons.

TABLE 2 differential flora and AUC values

Table 3 combined diagnostic AUC values

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Example 2 verification of genomic sequencing accuracy

Samples 19 of myasthenia gravis and 13 of healthy subjects were collected as in example 1, and the patient information is shown in Table 4.

Table 4 sample clinical features

The differential flora, prevotella copri, clostridium bartlettii, fusobacterium mortiferum, helicobacter cinaedi, was randomly selected for sequencing validation and calculated for diagnostic efficacy in myasthenia gravis.

The results showed that the AUC values of Prevotella copri, clostridium bartlettii, fusobacterium mortiferum, helicobacter cinaedi were 0.736842105, 0.672064777, 0.821862348, 0.615384615, respectively, comparable to the results of the previous assays, indicating accurate sequencing data for the metagenome.

The above description of the embodiments is only for the understanding of the method of the present invention and its core ideas. It should be noted that it will be apparent to those skilled in the art that several improvements and modifications can be made to the present invention without departing from the principle of the invention, and these improvements and modifications will fall within the scope of the claims of the invention.

Claims

1. Use of a reagent for detecting the content of intestinal microbial markers of myasthenia gravis in the preparation of a kit for diagnosing myasthenia gravis, characterized in that the intestinal microbial markers comprise the species Megamonas hypermegale and fusarium mobiricum.

2. The use according to claim 1, wherein the reagent comprises a reagent for polymerase chain reaction or nucleic acid hybridization.

3. The use according to claim 2, wherein the polymerase chain reaction comprises reverse transcription-polymerase chain reaction, nested PCR.

4. The use according to any one of claims 1 to 3, wherein the myasthenia gravis intestinal microbial marker content is determined by amplifying a fragment of each of the myasthenia gravis intestinal microbial markers in a sample from the subject.

5. The use according to claim 4, wherein the amplification is achieved by polymerase chain reaction.

6. The use according to claim 4, wherein the amplification utilizes a detectably labeled primer.

7. The use according to claim 4, wherein detection is achieved by electrophoresis.