KR102288299B1 - Biomarker composition for identifying disease progression of chronic liver diseases - Google Patents

Abstract

The present invention relates to a biomarker composition for discriminating the progression stage of chronic liver disease, in which total RNA-seq analysis is performed on tissues of patients with steatohepatitis and steatohepatitis to select genes showing characteristic expression patterns, As a result of constructing a classification model that can distinguish steatohepatitis and nonalcoholic steatohepatitis with genes, it was verified that the classification of steatohepatitis and nonalcoholic steatohepatitis is possible with high accuracy. Accordingly, the genes can be utilized as biomarkers to classify steatohepatitis and nonalcoholic steatohepatitis, and the development of gene therapy or other drugs that inhibit the expression or activity thereof can enhance the therapeutic effect of chronic liver disease.

Description

Biomarker composition for identifying disease progression of chronic liver diseases

The present invention relates to a biomarker composition for determining the stage of progression of chronic liver disease.

Fatty liver or steatosis refers to a state in which fat is accumulated in hepatocytes. In a normal liver, fat accounts for about 5%, and a state in which more fat is accumulated is called fatty liver. When the fatty liver worsens and the fat mass in the liver cells grows, important components of the cells, including the nucleus, are pushed to one side, and the function of the liver cells decreases. As a result, the circulation of blood and lymph in the liver is impaired. In this case, hepatocytes cannot receive adequate supply of oxygen and nutrients, and liver function deteriorates.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease and refers to a state in which fat is accumulated in liver cells without excessive alcohol intake. The prevalence of nonalcoholic fatty liver disease is rapidly increasing not only in the West but also in Korea along with the increase in the prevalence of obesity, and is closely related to type 2 diabetes, obesity, and metabolic syndrome. Although there is a slight difference in frequency by region, it has been reported that as few as 6.3%, as much as 33%, and on average, about 20% of patients worldwide develop non-alcoholic steatohepatitis (NASH) in some patients. ), it has been found to progress to end-stage liver disease such as cirrhosis or liver cancer. Although the pathogenesis of nonalcoholic steatohepatitis has not yet been fully elucidated, it has recently been reported that various factors such as fat deposition, inflammatory response, and genetic factors are related to each other.

Treatment of nonalcoholic fatty liver disease includes diet and exercise therapy. As drug treatment, vitamin E, insulin sensitizer, ursodeoxycholic acid (UCDA), and statin have been tried. is becoming However, the effect of the drug has not been clearly proven medically, and there is no approved drug for non-alcoholic fatty liver disease to date. In addition, although symptoms should be improved through diet and exercise therapy, patients often fail to practice this. Therefore, there is a need for research on the development of biomarkers that can discriminate fatty liver disease or non-alcoholic steatohepatitis.

Republic of Korea Patent Registration No. 10-2020031 (Registered on Sep. 3, 2019)

It is an object of the present invention to provide a biomarker composition for determining the progression stage of chronic liver disease.

Another object of the present invention is to provide a composition for determining the progression stage of chronic liver disease.

Another object of the present invention is to provide a kit for determining the progression stage of chronic liver disease.

Another object of the present invention is to provide a method for providing information necessary for determining the progression stage of chronic liver disease.

In order to achieve the above object, the present invention provides a biomarker composition for determining the stage of progression of chronic liver disease, comprising as an active ingredient any one or more proteins selected from the group consisting of HS3ST2 and CAPG or genes encoding them.

In addition, the present invention provides a composition for determining the progression stage of chronic liver disease, comprising as an active ingredient an agent capable of measuring the expression level of any one or more proteins selected from the group consisting of HS3ST2 and CAPG or a gene encoding the same.

In addition, the present invention provides a kit for determining the progression stage of chronic liver disease comprising the composition for determining the stage of progression of chronic liver disease.

In addition, the present invention comprises the steps of (a) measuring the expression level of any one or more proteins selected from the group consisting of HS3ST2 and CAPG from a sample isolated from a patient or the mRNA expression level of a gene encoding the same; And (b) applying the expression level of the protein or the mRNA expression level of the gene encoding it to a support vector machine (SVM) algorithm model; a method of providing information necessary for determining the stage of progression of chronic liver disease, including to provide.

In the present invention, genes showing characteristic expression patterns are selected by performing total RNA-seq analysis on tissues of patients with fatty liver disease and steatohepatitis, and a classification model that can distinguish steatohepatitis and nonalcoholic steatohepatitis is constructed with the genes. As a result, it was verified that the classification of fatty liver disease and nonalcoholic steatohepatitis was possible with high accuracy. Accordingly, the genes can be utilized as biomarkers to classify steatohepatitis and nonalcoholic steatohepatitis, and the development of gene therapy or other drugs that inhibit the expression or activity thereof can enhance the therapeutic effect of chronic liver disease.

1 shows a pipeline of total RAN-seq analysis using samples of steatohepatitis and nonalcoholic steatohepatitis.
2 is a diagram illustrating a classification model of fatty liver disease and nonalcoholic steatohepatitis using data obtained from the RAN-seq analysis.

Hereinafter, the present invention will be described in more detail.

The present invention provides a biomarker composition for determining the stage of progression of chronic liver disease, comprising as an active ingredient any one or more proteins selected from the group consisting of HS3ST2 and CAPG or a gene encoding the same.

In addition, the present invention provides a composition for determining the progression stage of chronic liver disease, comprising as an active ingredient an agent capable of measuring the expression level of any one or more proteins selected from the group consisting of HS3ST2 and CAPG or a gene encoding the same.

The agent capable of measuring the expression level of the protein is an antibody, peptide, aptamer or compound that specifically binds to the protein, and the agent capable of measuring the expression level of the gene is a primer or probe that specifically binds to the gene. may be, but is not limited thereto.

The chronic liver disease may be fatty liver disease or non-alcoholic steatohepatitis, but is not limited thereto.

As used herein, the term “primer” is a nucleic acid sequence having a short free 3'-hydroxyl group, capable of base pairing with a complementary template and serving as a starting point for template strand copying. short nucleic acid sequences that act. The primer is capable of initiating DNA synthesis in the presence of a reagent for polymerization (ie, DNA polymerase or reverse transcriptase) and four different nucleoside triphosphates in an appropriate buffer and temperature. PCR conditions and lengths of sense and antisense primers may be appropriately selected according to techniques known in the art.

The term “probe” used in the present invention refers to a nucleic acid fragment such as RNA or DNA corresponding to several bases to several hundred bases in length that can specifically bind to other than mRNA, and is labeled so that the presence or absence of a specific mRNA , the expression level can be confirmed. The probe may be manufactured in the form of an oligonucleotide probe, a single-stranded DNA probe, a double-stranded DNA probe, an RNA probe, or the like. Suitable probe selection and hybridization conditions can be appropriately selected according to techniques known in the art.

As used herein, the term “antibody” is a term known in the art and refers to a specific immunoglobulin directed against an antigenic site. The antibody in the present invention refers to an antibody that specifically binds to Gnpat of the present invention, and the antibody can be prepared according to a conventional method in the art. The form of the antibody includes a polyclonal antibody or a monoclonal antibody, and all immunoglobulin antibodies are included. The antibody refers to a complete form having two full-length light chains and two full-length heavy chains. Moreover, the said antibody also includes special antibodies, such as a humanized antibody.

The term “peptide” used in the present invention has the advantage of high binding strength to the target material, and no denaturation occurs even during heat/chemical treatment. In addition, since the molecular size is small, it can be attached to other proteins and used as a fusion protein. Specifically, it can be used as a diagnostic kit and drug delivery material because it can be used by attaching it to a polymer protein chain.

The term “aptamer” as used in the present invention is a special type of single-stranded nucleic acid (DNA, RNA or modified nucleic acid) that has a stable tertiary structure and can bind to a target molecule with high affinity and specificity. It refers to a type of polynucleotide composed. As described above, the aptamer can specifically bind to an antigenic substance in the same way as an antibody, but has higher stability than a protein, has a simple structure, and is composed of a polynucleotide that is easy to synthesize, so it can be used as an alternative to an antibody. can

In addition, the present invention provides a kit for determining the progression stage of chronic liver disease comprising the composition for determining the stage of progression of chronic liver disease.

The kit of the present invention includes an antibody that specifically binds to a biomarker component, a secondary antibody conjugate to which a label that develops color by reaction with a substrate is conjugated, a chromogenic substrate solution to react with the label, a washing solution and an enzyme It may include a reaction stopper and the like, and may be manufactured as a plurality of separate packaging or compartments containing the reagent components used.

In addition, the present invention comprises the steps of (a) measuring the expression level of any one or more proteins selected from the group consisting of HS3ST2 and CAPG from a sample isolated from a patient or the mRNA expression level of a gene encoding the same; And (b) applying the expression level of the protein or the mRNA expression level of the gene encoding it to a support vector machine (SVM) algorithm model; a method of providing information necessary for determining the stage of progression of chronic liver disease, including to provide.

As used herein, the term “sample isolated from a patient” refers to a sample, such as tissue, cell, whole blood, serum, plasma, saliva, sputum, cerebrospinal fluid, or urine, that differs from the control group in the expression level of the protein or gene. It may include, and may be, more specifically, liver tissue, hepatocytes, but is not limited thereto.

Specifically, the method for measuring the mRNA expression level is RT-PCR, competitive RT-PCR (Competitive RT-PCR), real-time RT-PCR (Real-time RT-PCR), RNase protection assay (RPA; RNase protection assay) ), Northern blotting and DNA chips are used, but are not limited thereto.

More specifically, the method for measuring the protein expression level includes Western blot, radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immunodiffusion method, rocket ) immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, Complement Fixation Assay, FACS, protein chip and ELISA analysis, but is not limited thereto.

Hereinafter, the present invention will be described in more detail through examples. These examples are only for illustrating the present invention in more detail, and it will be apparent to those skilled in the art that the scope of the present invention is not limited by these examples according to the gist of the present invention. .

Example 1: Sample Preparation

A total of 98 patients with non-alcoholic fatty liver disease (NAFLD) developed steatosis stage (n=42) or chronic liver disease (CLD) from non-alcoholic steatohepatitis ( Liver tissue was collected at the non-alcoholic steatohepatitis (NASH) stage (n=56).

The samples at the NASH stage were divided into stages F0, F1, F2, F3, and F4 according to the stage of liver fibrosis. Stages F3 and F4 were grouped as NASH, and the fatty liver disease group and NASH group were divided based on histological analysis.

Example 2: Total RNA-seq raw data analysis

Total RNA-seq was performed by extracting total RNA from liver tissues of the fatty liver disease group (n=42) and NASH group (n=56).

To check and improve the quality of total RNA-seq raw data ( .fastq ), the results were obtained using Trim Galore. In this process, internally, the read quality was checked with FastQC, and low-quality reads or remaining adapter seq were removed with Cutadapt. Afterwards, the STAR alignment tool was used to align the read to the human genome as a reference. The alignment results in the Reference to improve the accuracy of the prognostic markers excavation through the later transcript expression level analysis file (.bam) was obtained as a result file (.bam) duplication is removed using a tool Picard mark duplication.

To calculate the gene expression level at each stage of the disease, the samples ( .bam ) are grouped into fatty liver disease, NASH, and cuffdiff is performed to compare and analyze the expression level of each group and sample at the gene level. The results were obtained.

In order to distinguish and diagnose disease progression, about 30% of a total of 98 samples were randomly selected, and 33 training sets (fatty hepatosis group: 14, NASH group: 19), 65 testing sets (fatty liver disease group: 28, NASH group: 37), and applied to a support vector machine (SVM) algorithm.

In order to analyze which gene is suitable for classifying the disease progression stage for all 26,000 genes of the human genome obtained in this way, ① the average value of expression in the fatty liver disease or NASH group of the training set is 0.5 or more, ② Genes whose average expression level within each group is greater than the standard deviation, and ③ 3342 genes with at least a 1.3-fold difference in mean expression level between groups were primarily selected, and sigFeature(Significant Feature Selection by Using SVM-RFE & t-statistic) method, genes showing characteristic expression patterns in both groups were ranked. The method calculates whether each of 3342 genes in the training data set can accurately distinguish fatty liver disease from NASH based on the SVM-RFE algorithm, that is, the order of importance of the genes.

In the training set, the SVM model that can distinguish between fatty liver disease and nonalcoholic steatohepatitis was established by applying the above characteristic genes to the linear kernel-based SVM algorithm from 1st place to nth place. The SVM classification technique maps all features present in one sample to each vector to obtain a linear classification axis between them, and to create a model that can be classified based on this axis. The modeling process of the SVM classifier is to vectorize all gene expression levels in the training data and find the most suitable linearity to divide this value into two groups: fatty liver disease and NASH. When the testing set was input to the SVM model made in this way and the accuracy was checked, it was confirmed that the classification accuracy was the highest when the classification model was made using HS3ST2 and CAPG, and the top two genes.

Using the genes showing the characteristic expression pattern, an SVM model was created based on the training set and when tested with the training set, a model having the following results was created.

Predict / Actual Steatosis NASH Steatosis 11 3 NASH 3 16

That is, when 14 samples of fatty liver disease and 19 samples of nonalcoholic steatohepatitis were applied to the SVM model made based on the training set and the classification results were confirmed, 11 samples out of 14 samples for fatty liver disease were fatty liver disease, and 3 samples were non-steatohepatitis samples. It was classified as alcoholic steatohepatitis, and out of 19 samples with nonalcoholic steatohepatitis, 16 samples were classified as nonalcoholic steatohepatitis, and 3 samples were classified as steatohepatitis.

When the disease progression stage of the testing set was predicted by the SVM algorithm in this model, 24 out of 28 fatty liver disease groups in the testing data set were classified as fatty liver disease and 37 cases were classified using the top two genes (HS3ST2 and CAPG). 34 of the nonalcoholic steatohepatitis groups were classified as nonalcoholic steatohepatitis, and it was confirmed that the classification accuracy was 89.23%.

Predict / Actual Steatosis NASH Steatosis 24 3 NASH 4 34

When the expression values of the two genes of the patient were input into the model created in this way, it was possible to distinguish whether the disease stage of the patient was steatohepatitis or nonalcoholic steatohepatitis, and it was confirmed that the classification accuracy was 87.69%. The following figures show the average values of expression levels of two genes used for classification among all samples.

Gene / Class Ensemble ID Steatosis NASH HS3ST2 ENSG00000122254 0.18 0.71 CAPG ENSG00000042493 1.65 4.29

As the specific parts of the present invention have been described in detail above, for those of ordinary skill in the art, these specific descriptions are only preferred embodiments, and it is clear that the scope of the present invention is not limited thereto. Accordingly, the substantial scope of the present invention will be defined by the appended claims and their equivalents.

The scope of the present invention is indicated by the following claims, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention.

Claims (6)

A biomarker composition for discriminating the progression stage of nonalcoholic steatohepatitis (NAFLD) and nonalcoholic steatohepatitis (NASH) comprising as an active ingredient any one or more proteins selected from the group consisting of HS3ST2 and CAPG or a gene encoding the same. Non-alcoholic steatohepatitis (NAFLD) and non-alcoholic steatohepatitis (NASH) comprising as an active ingredient a formulation capable of measuring the expression level of any one or more proteins selected from the group consisting of HS3ST2 and CAPG or genes encoding them. A composition for determining the stage of progress. According to claim 2, wherein the agent capable of measuring the expression level of the protein is an antibody, peptide, aptamer or compound that specifically binds to the protein, and the agent capable of measuring the expression level of the gene is specific to the gene. Non-alcoholic steatohepatitis (NAFLD) and non-alcoholic steatohepatitis (NASH), characterized in that it is a primer or probe that binds to a composition for determining the progression stage. delete A kit for discriminating the progression stage of nonalcoholic steatohepatitis (NAFLD) and nonalcoholic steatohepatitis (NASH) comprising the composition of claim 2 . (a) measuring the expression level of any one or more proteins selected from the group consisting of HS3ST2 and CAPG from a sample isolated from a patient or the mRNA expression level of a gene encoding the same; and
(b) applying the expression level of the protein or the mRNA expression level of the gene encoding it to a support vector machine (SVM) algorithm model;
A method of providing information necessary for determining the progression stage of nonalcoholic steatohepatitis (NAFLD) and nonalcoholic steatohepatitis (NASH) comprising a.

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