KR20210104206A - Composition for diagnosing polymyositis or dermatomyositis - Google Patents

Abstract

The present invention relates to a composition for diagnosis of polymyositis or dermatomyositis, and more particularly, by including an agent for detecting the expression level of gene NAPA, it is possible to diagnose polymyositis or dermatomyositis with high accuracy.

Description

Composition for diagnosing polymyositis or dermatomyositis {COMPOSITION FOR DIAGNOSING POLYMYOSITIS OR DERMATOMYOSITIS}

The present invention relates to a composition for diagnosing polymyositis or dermatomyositis.

Polymyositis and dermatomyositis are very rare inflammatory muscle diseases, and it is reported that the incidence rate is about 7.98 per 1 million people per year. These two diseases mainly occur in developed countries and are accompanied by muscle weakness and inflammation. Polymyositis and dermatomyositis are mainly classified together due to the similarity of disease progression and muscle lesions, and they are distinguished by the presence or absence of skin lesions. Serological and clinical characteristics such as myositis-specific autoantibodies have been revealed by recent studies, and it is known that many autoimmune diseases have characteristics, but the exact pathogenesis has not yet been clearly elucidated.

Inflammatory muscle diseases include pediatric dermatomyositis and inclusion body myositis in addition to polymyositis and dermatomyositis, but these are treated separately based on clinical characteristics. For example, although childhood dermatomyositis has symptoms similar to those of adult dermatomyositis, it has been mentioned in a recent study that the prognosis of the disease and the types of complications are significantly different. Unlike polymyositis and dermatomyositis, inclusion body myositis is well-known for its very late onset and characteristic asymmetric muscle weakness.

Evidence suggests that patients with polymyositis and dermatomyositis are more likely to develop serious complications such as various cancers and cardiovascular diseases. In addition, as a result of population-based cohort surveys and observational studies, it was suggested that the overall incidence of malignant diseases was increased in patients with polymyositis and dermatomyositis. In addition, venous thromboembolism and coronary artery disease may also appear as complications, and the incidence rate increased by 11.1 times and 2.24 times, respectively. Therefore, it is important to understand the biological mechanisms of polymyositis and dermatomyositis with such life-threatening complications.

Meanwhile, since the 2000s, researchers have been conducting gene expression analysis using mass rapid processing technology to understand the onset and progression of diseases. However, despite the fact that these datasets are distributed free of charge by the National Center for Biotechnology Information (NCBI) and continue to be used to discover new biomarkers and potential drug targets, the small sample size, non-biological laboratory errors, heterogeneity of individual studies, etc. Therefore, it was not possible to solve the problem of errors that occurred in the process of merging different studies. In order to overcome these shortcomings and to better understand insulin resistance disease, it is important to be able to increase statistical power by combining various studies using a meta-analysis that combines multiple studies.

Korean Patent No. 1289134

An object of the present invention is to provide a composition for diagnosing polymyositis or dermatomyositis.

An object of the present invention is to provide a kit for diagnosing polymyositis or dermatomyositis.

An object of the present invention is to provide an information providing method for diagnosing polymyositis or dermatomyositis.

An object of the present invention is to provide a composition for screening polymyositis or dermatomyositis therapeutic agent candidates.

1. A composition for diagnosing polymyositis or dermatomyositis comprising an agent for detecting the expression level of gene NAPA.

2. The composition for diagnosing polymyositis or dermatomyositis according to 1 above, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3.

3. The method of 1 above, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1, polymyositis or skin A composition for diagnosing myositis.

4. The polymyositis or dermatomyositis according to 1 above, further comprising an agent for detecting at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579. Diagnostic composition.

5. A kit for diagnosing polymyositis or dermatomyositis comprising the composition of any one of items 1 to 4.

6. A method for diagnosing polymyositis or dermatomyositis, comprising the step of detecting the expression level of the gene NAPA from a sample isolated from an individual.

7. The method for diagnosing polymyositis or dermatomyositis according to the above 6, further comprising: detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3 from the sample.

8. The method of 6 above, further comprising: detecting at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1 from the sample; A method of providing information for the diagnosis of myositis.

9. Polymyositis according to 6 above, further comprising the step of detecting at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579 from the sample; or a method of providing information for diagnosing dermatomyositis.

10. A composition for screening polymyositis or dermatomyositis candidate drug candidates, comprising an agent for detecting the expression level of gene NAPA.

11. The composition for screening polymyositis or dermatomyositis candidates according to the above 10, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3.

12. The polymyositis or skin of the above 10, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1 A composition for screening candidate substances for the treatment of myositis.

13. The polymyositis or dermatomyositis of the above 10, further comprising an agent for detecting at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579. A composition for screening therapeutic candidates.

Polymyositis or dermatomyositis can be diagnosed with high accuracy by using the composition or kit for diagnosing polymyositis or dermatomyositis of the present invention.

The information providing method for diagnosing polymyositis or dermatomyositis of the present invention can provide information on whether polymyositis or dermatomyositis is present with high accuracy.

By using the composition for screening polymyositis or dermatomyositis candidates of the present invention, a therapeutic agent effective for polymyositis or dermatomyositis can be selected with high accuracy.

1 shows information on differentially expressed genes (DEGs) derived as a result of meta-analysis.
2 shows the results of GSEA analysis using Hallmark genes.
3 shows a network constructed with genes involved in protein secretion or unfolded protein reaction.

Hereinafter, the present invention will be described in detail.

The present invention provides a composition for diagnosing polymyositis and/or dermatomyositis.

The present inventors have confirmed that the expression of the gene NAPA is correlated with polymyositis and/or dermatomyositis. devised.

The diagnostic composition of the present invention includes an agent for detecting the expression level of the gene NAPA (NSF attachment protein alpha).

The gene NAPA may be a sequence known to NCBI genbank or the like, and is a gene of Gene ID 8775 in humans.

The diagnostic composition of the present invention is an agent for detecting the expression level of at least one gene selected from the group consisting of YKT6 (YKT6 v-SNARE homolog), COPB2 (coatomer protein complex subunit beta-2) and SPCS3 (signal peptidase complex subunit 3). may further include.

The diagnostic composition of the present invention may further include an agent for detecting the expression level of at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1.

The inventors have confirmed that the above genes are also correlated with polymyositis and/or dermatomyositis, and by detecting the expression level of the genes, polymyositis and/or dermatomyositis can be diagnosed with higher accuracy.

The gene of the present invention described above may be a gene derived from an individual to be diagnosed with polymyositis and/or dermatomyositis.

The individual may be a mammal, for example, a mouse, a rat, a cat, a guinea pig, a hamster, a dog, a monkey, a chimpanzee, a human, etc., and specifically may be a human.

The agent for detecting the expression level of a gene may be a substance for detecting the presence and/or amount of the gene itself, the mRNA transcribed by the gene, or both.

The agent for detecting the expression level of a gene may be used without limitation those used for detecting gene expression in the art, for example, it may be at least one selected from the group consisting of primers and probes or at least one.

The term 'primer' refers to a short nucleic acid sequence having a short free three-terminal hydroxyl group, capable of base pairing with a complementary template and serving as a starting point for template strand copying. Primers can be used for diagnosis, DNA sequencing, etc., and can be synthesized and used with a length of typically 15 to 30 base pairs, but can be synthesized by varying the length depending on the purpose of use, and can be modified by methylation, capping, etc. by known methods. have.

The term 'probe' refers to a nucleic acid fragment such as RNA or DNA corresponding to several bases to several hundred bases in length that can form specific binding to mRNA, and is labeled so that the presence or absence of a specific mRNA can be confirmed. have. 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. A person skilled in the art can design the primer 　 or 　 probe according to a conventional method in the art based on the sequence of the gene to be measured for expression level.

The expression level of the gene may be detected by a method known in the art, for example, real-time polymerase reaction (Real-time PCR), reverse transcription polymerase reaction (RT-PCR), competitive reverse transcription polymerase reaction (Competitive) At least one method selected from the group consisting of RT-PCR), real-time reverse transcription polymerase reaction (Realtime RT-PCR), RNase protection assay (RPA), Northern blotting and DNA chip may be used can

The diagnostic composition of the present invention may further include an agent for detecting at least one SNP (single nucleotide polymorphism) selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579.

The term 'single nucleotide polymorphism (SNP)' refers to the difference in single base-pair variation in DNA between individuals and is the most common form of DNA sequence polymorphism. is known SNPs are known to occur at a frequency of about once every 1,000 bp (about 1/1 kb) in humans. When these SNPs affect a phenotype such as a disease, a polynucleotide comprising the SNP can be used to diagnose the disease.

The term 'rs number' or 'SNP (single nucleotide polymorphism) rs number' refers to a unique SNP (single nucleotide polymorphism) reference number that is assigned when a new SNP is reported in the reference SNP cluster ID database, Through this unique number, you can access the SNP cluster ID database and check the base sequence, SNP site, and mutation of the corresponding SNP. Therefore, by specifying the SNP rs number, a person skilled in the art can identify the chromosome number, locus, nucleotide sequence, SNP site, and mutant base in which the SNP exists. , information providing methods and screening compositions are specified. Each SNP information can be obtained from GTEx.

Agents for detecting SNPs may be used without limitation those used for SNP detection in the art, and may be, for example, primers or probes.

Polymyositis or dermatomyositis can be diagnosed when the expression level of at least one of the above-mentioned genes is higher than that of the normal group or at least one SNP of the above-mentioned SNPs is detected when the diagnostic composition of the present invention is used.

In addition, the present invention provides a kit for diagnosing polymyositis or dermatomyositis comprising the aforementioned diagnostic composition.

The kit may further include other components, compositions, solutions, or devices suitable for detecting the expression level of at least one of the above-mentioned genes or the presence of at least one of the above-mentioned SNPs in addition to the above-described agents.

For example, the kit may include a test tube or other suitable container, reaction buffer, deoxyribonucleotides (dNTPs), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNase inhibitors, DEPC-water (dEPC water), sterile water. and the like.

In addition, the present invention provides an information providing method for diagnosing polymyositis or dermatomyositis.

The method of the present invention may include; detecting the expression level of NAPA from a sample isolated from an individual.

The detection of the expression level of NAPA may be detected by mixing a sample isolated from an individual with a reagent containing an agent for detecting the expression level of gene NAPA.

The gene NAPA is a gene derived from a subject to be diagnosed, and the subject may be within the range exemplified above, and since the preparation for detecting the gene expression level has been described above, a detailed description thereof will be omitted.

The present inventors confirmed that the NAPA gene is correlated with polymyositis or dermatomyositis. By detecting the expression level of the NAPA gene, polymyositis or dermatomyositis can be diagnosed with higher accuracy or information can be provided. .

The expression level of the gene can be detected according to a method suitable for each agent, which can be according to a known bar.

The sample may be at least one selected from the group consisting of tissue, cells, whole blood, serum, plasma, saliva, sputum, cerebrospinal fluid, and urine.

The method of the present invention may further include; detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3 from a sample isolated from an individual.

The detection of the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3 includes an agent for detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3 in a sample isolated from an individual It may be detected by mixing with a reagent.

The method of the present invention may further include a step of detecting the expression level of at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1 from a sample isolated from an individual; .

TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163, and detection of the expression level of at least one gene selected from the group consisting of TM4SF1, TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, The detection may be performed by mixing with a reagent containing an agent for detecting the expression level of at least one gene selected from the group consisting of SLC25A24, CD163 and TM4SF1.

The genes YKT6, COPB2, SPCS3, TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1 are genes derived from the subject to be diagnosed. can be Since the preparation for detecting the gene expression level has been described above, a detailed description thereof will be omitted.

The present inventors have confirmed that the genes are correlated with polymyositis or dermatomyositis. By detecting the expression level of the gene, polymyositis or dermatomyositis can be diagnosed with higher accuracy or information can be provided.

The method of the present invention may further include detecting at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579 from a sample isolated from a subject.

and the detection of at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579 is, It may be detected by mixing with a reagent containing an agent for detecting at least one SNP selected from the group consisting of rs75364579.

The present inventors have confirmed that the SNPs are correlated with polymyositis or dermatomyositis. By detecting the SNPs, polymyositis or dermatomyositis can be diagnosed with higher accuracy or information can be provided.

In addition, the present invention provides a composition for screening polymyositis or dermatomyositis therapeutic agent candidates.

The composition for screening of the present invention includes an agent for detecting the expression level of NAPA.

As described above, since the expression level of the gene NAPA may be increased in an individual having polymyositis or dermatomyositis, a substance that lowers the expression may be a candidate substance for the treatment of polymyositis or dermatomyositis.

The agent for detecting the expression level of gene NAPA may be within the range exemplified above.

The composition for screening of the present invention can be used to check whether there is a change in the expression level of the gene after the subject material is treated to an individual, an organism-derived tissue or cultured cells thereof, and the expression level of the gene is decreased after the treatment of the subject material If so, the target substance can be selected as a candidate substance for the treatment of polymyositis or dermatomyositis.

The composition for screening of the present invention may further include an agent for detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3.

The composition for screening of the present invention may further include an agent for detecting the expression level of at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1.

The composition for screening of the present invention may further include an agent for detecting at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579.

Hereinafter, examples will be given to describe the present invention in detail.

Experimental method

1. Data Collection

The public database EBI-ArrayExpress (E-MTAB-2141: https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-2141/;E-MEXP-2681: https://www.ebi. Among the data uploaded to ac.uk/arrayexpress/experiments/E-MEXP-2681/;E-GEOD-46239: https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-46239), Data that included both polymyositis or dermatomyositis patients and control data were used.

The selected data were E-MTAB-2141, E-MEXP-2681, and E-GEOD-46239, and included data from 3, 6, and 48 patient samples and 4, 5, and 4 control data, respectively. For consistency of results, data such as polymyositis and inclusion body myositis other than dermatomyositis were excluded from the analysis.

2. Preprocessing and meta-analysis

Pre-processing and normalization of the data were performed using Oligo, a bioconductor package. Each data was separately normalized using the robust multiarray average method, a package built-in function. Then, in order to reduce the deviation between individual data, meta-analysis was performed using normalized data using GeneMeta, a bioconductor package. Statistics for discriminating overexpressed and underexpressed differentially expressed genes (DEGs) were calculated through the GeneMeta package, and the false discovery rate (FDR) and z-value were used. All analysis processes were performed using R (version 3.4.3), a statistical programming language.

3. Gene set enrichment analysis (GSEA)

Analysis was performed using the pre-ranked method of the GSEA program. The entire gene list was analyzed using a file arranged according to the z value, and the hallmark gene list uploaded to the molecular signatures database (MsigDB http://software.broadinstitute.org/gsea/msigdb) was used.

4. Network visualization and analysis

A network was constructed using the core enrichment gene corresponding to the protein secretion and unfolded protein response derived as a result of GSEA analysis as the apex. The network connected each vertex using a search tool for the retrieval of interacting genes (STRING, https://string-db.org/) database. The interaction of each gene was connected by adjusting the confidence level to the maximum value of 0.9, and points not connected to any vertices were deleted. Finally, a network using Cytoscape (version 3.7.0) was constructed by synthesizing the network constructed using STRING and the results of meta-analysis. Network analysis and sub-network analysis were performed using Cytoscape's NetworkAnalyzer tool. To mark transcription factors on the network, the transcriptional regulatory relationships unraveled by sentence-based text mining database (TRRUST, version 2.0, https://www.grnpedia.org/trrust/) was used.

5. cis-eQTL and trans-eQTL analysis

cis-eQTL and trans-eQTL analysis was performed to confirm the effect of DNA sequence mutation on gene expression level.

A gene affected near the location of the genetic mutation is called an essential gene (eGene), and this genetic mutation is called cis-eQTL. Some cis-eQTLs located in the transcriptional regulatory region can control the expression level of genes located more distantly or on other chromosomes, and this genetic variation is called trans-eQTL. Considering both cis-eQTL and trans-eQTL may enable a deeper understanding of the transcriptome data.

A generalized analysis of molecular variance for mixed-model analysis (GAMMA) was performed using the expression information of overexpressed DEGs. The assay was repeated 1E+6 times. For the analysis, the muscle of the genotype-tissue expression (GTEx, version 6.0, https://gtexportal.org/), and the skin exposed to sunlight and the skin without exposure were used. The cis-relationship between genetic variation and genes was judged based on ±1 Mb distance. Database for annotation, visualization and integrated discovery (DAVID, http://david.ncif.org/) were used to classify the functions of eGenes obtained as a result of analysis.

Experiment result

1. DEG acquisition through data collection and meta-analysis

A total of three microarray data were acquired from EBI-ArrayExpress (see Table 2). Next, the DEG between polymyositis and dermatomyositis patients (patient group) and control group was analyzed using the GeneMeta package. As a result, 600 genes were determined to be DEG (FDR < 0.01; overexpression: z value > 0, underexpression: z value). Of the total 600 genes, 317 genes were overexpressed and 283 genes were underexpressed.

ArrayExpress ID PMID Source Platform Organism PM DM Control Total E-MTAB-2141 24462217 Muscle Biopsy Affymetrix GeneChip Human Exon 1.0 ST Array version 2 Human 3 - 4 7 E-MEXP-2681 - Muscle Biopsy Affymetrix GeneChip Human Genome HG-U133A Human 4 2 5 11 E-GEOD-46239 - Skin Biopsy Affymetrix GeneChip Human Genome U133 Plus 2.0 Human - 48 4 52 Total - - - - 7 50 13 70

When comparing the number of DEGs derived from the individual data and the combined data, it was confirmed that the meta-analysis using the combined data discovered new genes that could not be found in the individual data and at the same time, it was possible to derive reliable results. (See Figures 1A and 1B). The difference between the results of meta-analysis and individual data analysis suggests that the error was reduced with more improved statistical power through meta-analysis (see FIGS. 1C and 1D ).

1A is a comparison of the meta-analysis result and the number of DEGs for each z value of single data under the condition of FDR < 0.05, and FIG. 1B is a comparison of the number of DEGs for each z value under the condition of FDR < 0.01. 1C is a Venn diagram of the meta-analysis result and overexpressed DEG in single data, and FIG. 1D is a Venn diagram of the meta-analysis result and underexpressed DEG in single data.

Most of the DEGs shown in the individual data were found only in E-MEXP-2681, but the DEGs derived from meta-analysis showed high reliability results, including many previously known genetic markers of polymyositis and dermatomyositis. For example, RIG-1 (z value: 3.44, FDR: 0.00) and TLR-2 (z value: 3.31, FDR: 0.00) were included in the overexpressed genes as a result of meta-analysis.

Meta-analysis The top 10 overexpressed genes are shown in Table 2 below.

Gene Symbol Full Name Entrez ID z-score FDR TMSB10 thymosin beta 10 9168 5.62 0.00 SPCS3 signal peptidase complex subunit 3 60559 5.58 0.00 BST2 bone marrow stromal cell antigen 2 684 5.31 0.00 A2M alpha-2-macroglobulin 2 5.14 0.00 PECAM1 platelet and endothelial cell adhesion molecule 1 5175 5.07 0.00 IGF1 insulin-like growth factor 1 3479 5.07 0.00 SERPING1 serpin family G member 1 710 4.95 0.00 SLC25A24 solute carrier family 25 member 24 29957 4.84 0.00 CD163 CD163 molecule 9332 4.84 0.00 TM4SF1 transmembrane 4 L six family member 1 4071 4.83 0.00

As a result of meta-analysis, the top 10 overexpressed genes were verified using FDR and z values, and as a result, 6 of them were known to be involved in inflammatory and immune responses. Six genes known to be involved in inflammatory and immune responses are bone marrow stomal cell antigen 2 (BST2), alpha-2-macroglobulin (A2M), platelet and endothelial cell adhesion molecule 1 (PECAM1), and insulin-like growth factor 1 (IGF1), serpin family G member 1 (SERPING1) and CD164 molecule (CD163). By detecting genes involved in inflammation and immune response, it was confirmed that the meta-analysis results were in good agreement with the existing research results.

2. Biological pathway analysis using GSEA

In order to understand the biological significance of the gene expression patterns of polymyositis and dermatomyositis patients, analysis using GSEA was performed. This method calculates the weight for each expression value by using a list sorted by expression amount of all genes, and it is possible to analyze not only DEG but also the overall gene expression pattern. This is very useful for analyzing the overall expression pattern in a way that minimizes the loss of information. 10,032 genes of the combined data were analyzed using the z value of the GeneMeta package as a weight.

The analysis was performed using hallmark genes, which classified the functions of genes in a large range. As a result of the analysis, it was confirmed that 25 pathways were overexpressed under a significance level of FDR < 0.01 (see FIG. 2A ). Most of them were pathways involved in immune or inflammatory responses as previously known, such as interferon alpha and gamma responses. Under the same significance level, only three underexpressed pathways were derived. These were “KRAS signaling down”, “estrogen response early” and “estrogen response late”. This result agrees well with the result detected as one of the overexpressed pathways in the “KRAS signaling up” pathway. Excluding this, only pathways related to the estrogen response were found to be underexpressed, and it was judged that it was difficult to derive a biological meaning from this alone, so only the overexpressed pathways were used in the subsequent analysis.

Among the overexpressed pathways, the top two pathways based on normalized enrichment score (NES) were interferon gamma response (FIG. 2B, FDR: 0.00, normalized enrichment score, NES: 3.54), and interferon alpha response (FIG. 2C, FDR: 0.00, NES: 3.34). In addition, it was confirmed that two novel pathways were overexpressed: protein secretion (FIG. 2D, FDR: 0.00, NES: 2.24) and unfolded protein reaction (FIG. 2E, FDR: 0.00, NES: 1.97). The NES value is a relative index that evaluates the degree of concentration compared to other gene sets.

As a result of the overall GSEA analysis, it was confirmed that the gene expression patterns of polymyositis and dermatomyositis were similar to well-known autoimmune diseases or inflammation-based diseases, and that protein-related mechanisms related to ER-stress were abnormally activated.

3. Construction of gene network involved in protein secretion and unfolded protein response

Following the GSEA analysis, network analysis using core enrichment genes that play an important role in protein secretion and unfolded protein response was performed (see FIG. 3 ). Of the total 150 core enrichment genes, 107 genes with probes in the used microarray platform were used to construct a network. As a result of the construction, it was confirmed that the two pathways of protein secretion and unfolded protein reaction were linked by interaction between the MAPK1 gene and the EIF4EBP1 gene.

Next, genes valuable as new biomarkers were selected from among the top genes in the network over two steps. First, a gene that is both overexpressed DEG and present on the gene network was selected. Then, genes belonging to the above-described top 10 overexpressed genes (see Table 1) or having the most active interaction with other genes were selected ( FIGS. 3A and 3B ). By these criteria, three genes, which had not been mentioned in previous studies, and which recorded a high order in the network were preferentially selected. The three selected genes were YKT6 v-SNARE homolog (YKT6, z-value: 3.48, FDR: 0.00, order: 29), NSF attachment protein alpha (NAPA, z-value: 3.38, FDR: 0.00, order: 34), coatomer protein complex subunit beta-2 (COPB2, z-value: 3.33, FDR: 0.01, order: 24). In addition, signal peptidase complex subunit 3 (SPCS3, z-value: 5.58, FDR: 0.00, order: 4), which is a gene included in the network, was also selected from among the top 10 overexpressed genes described above. The four selected genes were indicated by double circles on the constructed network (see Fig. 3C). These genes are all genes that are importantly involved in protein secretion or unfolded protein response, and they are statistically significantly overexpressed (FDR < 0.01). In addition, since these genes have not been paid attention to in previous studies, they can be suggested as new biomarkers for polymyositis and dermatomyositis.

3A is a scatter plot expressing the order of genes, and the top 10 genes are indicated by red dots. 3B shows information on the top 10 genes with high order and their order, and the higher the order, the closer to red. 3C is a visualized gene network, in which higher expression levels are expressed in red, and lower expression levels are expressed in blue. In FIG. 3C, the size of the apex means the order size of each vertex, the transcription factor is indicated by a diamond, and the proposed potential biomarker is indicated by a double circle.

4. Potential eQTL Locus Analysis

To analyze the genetic mutations involved in polymyositis and dermatomyositis lesions, the GAMMA tool, an algorithm based on multiple regression analysis, was used to estimate genetic mutations potentially affecting the expression of specific phenotypes or genes. .

Since polymyositis and dermatomyositis are diseases in which major lesions occur in the muscles or skin, information between genes and genetic variations was obtained using data on muscle, sun-exposed skin, and non-sun-exposed skin data from the GTEx database. GAMMA analysis was conducted using the above information and 317 overexpressed DEGs. Forty genetic mutations and 40 eGenes were obtained, and 154 potential genetic mutations and 27 eGenes were obtained from unexposed skin. Since the analysis using GAMMA was repeated to calculate significance up to the -5 power of 10, the significance between the gene and SNP was set to 1E-4 at the GTEx p value and 5E-4 at the p value of GAMMA. The p-value of GTEx indicates the correlation between genes and SNPs, and the p-value of GAMMA indicates the influence of SNPs on the expression levels of DEGs used in the analysis. These two figures suggest that SNPs could potentially influence overexpression of 317 genes.

To analyze the causal relationship between SNPs and eGenes on DEG overexpression in each tissue, functional clustering of DAVID was used. Among the clusters of eGenes obtained from each tissue, the cluster containing the most genes was selected and the meaning was interpreted. As a result, clusters that appeared to be biologically significant were obtained in muscle tissue and sun-exposed skin tissue, but even the highest cluster in non-sun-exposed skin tissue did not have biological significance. In muscle tissue, the cluster involved in transcriptional regulation appeared as the highest cluster including 7 SNPs and 4 eGenes, and on chromosomes 1, 6, and 16, rs587638658, rs115256213, rs12925855, and chromosome 11, respectively. rs61916118, rs59992343, rs11221871, and rs11221861 affecting NFRκB were found to be SNPs involved in this cluster (see Table 3).

The SNP variant ids in Tables 3 and 4 describe SNP information as "chromosome number_base number_base before mutation_base_version information after mutation". For example, re61916118 means that cytosine, base 129707902 of chromosome 11, is mutated to adenine.

Refsnp ID SNP variant id GAMMA
p value GTEX
p value ENSEMBL ID Gene Symbol Description rs61916118 11_129707902_C_A_b37 9.00E-05 2.06E-06 ENSG00000170322 NFRκB nuclear factor related to kappaB binding protein rs59992343 11_129710515_C_T_b37 9.00E-05 3.60E-06 rs11221871 11_129708766_C_G_b37 1.01E-05 1.42E-06 rs11221861 11_129686195_G_A_b37 1.09E-05 3.88E-06 rs115256213 6_30436560_A_G_b37 2.10E-05 5.00E-08 ENSG00000204644 ZFP57 ZFP57 zinc finger protein rs12925855 16_10494325_T_G_b37 2.40E-05 6.10E-05 ENSG00000166669 ATF7IP2 activating transcription factor 7 interacting protein 2 rs587638658 1_120148215_GC_G_b37 3.10E-05 9.95E-05 ENSG00000143067 ZNF697 zinc finger protein 697

The SNPs included in the muscle tissue clusters listed in Table 3 were shown to play a role as trans-eQTLs in the expression of DEGs and the phenotypes of polymyositis and dermatomyositis via eGene. In addition, in the sun-exposed skin tissue, the immunoglobulin domain cluster containing 3 SNPs and 7 eGenes was found at the highest level, and in this cluster, rs9269294 and rs75364579 located on chromosome 6 affect HLA genes. rs397600 located on chromosome 19 was found to affect the LILRB2 gene (see Table 4).

Refsnp ID SNP variant id GAMMA
p value GTEX
p value ENSEMBL ID Gene Symbol Description rs397600 19_54791788_A_G_b37 6.20E-05 5.47E-07 ENSG00000131042 LILRB2 Leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 2 rs9269294 6_32539473_C_A_b37 2.50E-04 3.77E-06 ENSG00000204305 AGE Advanced glycosylation end product-specific receptor 4.13E-14 ENSG00000196735 HLA-DQA1 Major histocompatibility complex, class II, DQ alpha 1 3.53E-11 ENSG00000223534 HLA-DQB1-AS1 HLA-DQB1 antisense RNA 1 1.35E-12 ENSG00000179344 HLA-DQB1 Major histocompatibility complex, class II, DQ beta 1 1.54E-22 ENSG00000196126 HLA-DRB1 Major histocompatibility complex, class II, DR beta 1 rs75364579 6_32481655_C_T_b37 3.30E-04 2.82E-05 ENSG00000179344 HLA-DQB1 Major histocompatibility complex, class II, DQ beta 1

Since the eGenes obtained from the sun-exposed skin tissue described in Table 4 are directly involved in immune and inflammatory responses, the SNPs in Table 3 can be interpreted as cis-eQTL.

Claims (13)

A composition for diagnosing polymyositis or dermatomyositis, comprising an agent for detecting the expression level of gene NAPA.
The composition for diagnosing polymyositis or dermatomyositis according to claim 1, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3.
The method for diagnosing polymyositis or dermatomyositis according to claim 1, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1 composition.
The method for diagnosing polymyositis or dermatomyositis according to claim 1, further comprising an agent for detecting at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579. .
A kit for diagnosing polymyositis or dermatomyositis comprising the composition of any one of claims 1 to 4.
An information providing method for diagnosing polymyositis or dermatomyositis, comprising the step of detecting the expression level of the gene NAPA from a sample isolated from an individual.
The method of claim 6, further comprising: detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2, and SPCS3 from the sample; further comprising, information providing method for diagnosing polymyositis or dermatomyositis.
The method according to claim 6, TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and detecting the expression level of at least one gene selected from the group consisting of TM4SF1 from the sample; further comprising, polymyositis or A method of providing information for the diagnosis of dermatomyositis.
The method according to claim 6, further comprising the step of detecting at least one SNP selected from the group consisting of rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294 and rs75364579 from the sample. A method of providing information for the diagnosis of myositis.
A composition for screening polymyositis or dermatomyositis drug candidates, comprising an agent for detecting the expression level of gene NAPA.
The composition according to claim 10, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of YKT6, COPB2 and SPCS3, for screening polymyositis or dermatomyositis treatment candidates.
The therapeutic agent for polymyositis or dermatomyositis according to claim 10, further comprising an agent for detecting the expression level of at least one gene selected from the group consisting of TMSB10, BST2, A2M, PECAM1, IGF1, SERPING1, SLC25A24, CD163 and TM4SF1 A composition for screening candidate substances.
11. The method according to claim 10, rs61916118, rs59992343, rs11221871, rs11221861, rs115256213, rs12925855, rs587638658, rs397600, rs9269294, and rs75364579, which further comprises an agent for detecting at least one SNP selected from the group consisting of polymyositis or dermatomyositis candidates A composition for screening a substance.

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