KR101724130B1 - Biomarkers for Diagnosing Intestinal Behcet's Disease and Uses Thereof - Google Patents

Abstract

The present invention relates to a biomarker for the diagnosis of Jejobetich's disease and a use thereof. According to the present invention, the biological sample comprises a single base polymorphism site of NAALADL2 gene, a single base polymorphism site of YIPF7 gene, a single base polymorphism site of DCAF12 gene, a single base polymorphism site of PLCB1 gene, a single base polymorphism site of SCHIP1 gene, Wherein the biological sample comprises a single nucleotide polymorphic site of a gene selected from the group consisting of a single nucleotide polymorphism site of the genome of the bacterium. Thus, the kit and method of the present invention can be used very effectively and easily to predict the diagnosis or risk of Jejobetich's disease.

Description

[0001] Biomarkers for Diagnosis of Intestinal Behcet's Disease and Uses Thereof [0002]

The present invention relates to a biomarker for the diagnosis of Jejobetich's disease and a use thereof.

Behcet's disease (BD) is a rare chronic, inflammatory, and multisystem disease commonly associated with unknown factors in the environment and genes in countries across the Middle East and the Mediterranean, including the Far East and the Silk Road in Far East Asia. ^1-3 Although many of these genetic variants are not known, many gene risk factors may contribute to disease susceptibility. The Genome Wide Association Study (GWAS) is a genome wide association study of the human leukocyte antigens genes encoding B ^* 51 ( HLA-B ^* 51 ) and major histocompatibility complex ( MHC ) class I ( interleukin ) 10, and the IL23 receptor ( IL23R ) -IL12 receptor beta2 ( IL12RB2 ). Recently, GWAS studies have also shown that several other non-HLA gene locations and CC chemokine receptor 1 gene ( CCR1 ), signal transduction and transcription activator ( STAT4 ), gene encoding killer cell lectin-like receptor family members ( KLRC4- KLRK1 ) And an ER-1 gene ( ERAP1 ). ^2-6

Chapter BD (BD containing bowel) is generally diagnosed as a clinical diagnostic criteria for ulcers and BD, typical of the gastrointestinal tract. ⁷ Interestingly, BD BD patient is in the Mediterranean, including chapter rarely appear (0-3%), ^8,9 East Asian patients BD occurs frequently relatively (5-25%). ^10-12

Taking into account the regional and ethnic differences in the incidence of BD and BD that do not contain a chapter, BD shows the pathogenesis pathway that can be distinguished from a BD that does not contain a BD, and a unique genetic susceptibility position specifically associated with BD BD It is assumed that there is. Recently, GWAS studies on several BD patients have been widely known for their genetic susceptibility to BD-related sites. ^2-6 However, all of these studies focus on BD itself, and Chang BD is a very rare disease and there is no study to evaluate genetic factors related to BD. In addition, the effects of genes associated with some phenotypic duplications (inflammation in the eyes, skin and intestines), MHC class I domains, IL10 , and IL23R , and tumor necrosis factor (TNF) -a blockade regimens have been reported between BD and inflammatory bowel disease It is included in the shared pathogenic pathway. ^13,14 In particular, IBD and chapters BD is shared by a number of clinical phenotypes in terms of Chapter symptoms, treatment applied, and clinical course may share a genetic susceptibility between Chapter ¹⁴ and BD IBD. Otherwise, it may be regarded as two different diseases due to a specific genetic marker for the intestinal BD, not against intestinal IBD.

In the present study, the present inventors used GWAS in a Korean population to identify a specific gene sensitive marker for BD, which can be defined as a limited genetic marker for a BD containing a GW. The present inventors have also studied the functional consequences of genetic factors affecting disease susceptibility and phenotype of BD and BD that do not contain enterovirus.

The present inventors have tried to develop a biomarker for rapid diagnosis and prediction of prognosis of Intestinal Behcet's Disease. As a result, the present inventors have identified a single nucleotide polymorphism (SNP) specific to Jejobez disease through a GWAS (Genome Wide Association Study) on biological samples obtained from patients with Jejobet's disease, The present invention can be effectively used for diagnosis of diseases.

Accordingly, the present invention is to provide a kit for diagnosis and risk prediction of Jejobelet disease.

It is another object of the present invention to provide a method for diagnosing Jean-Berthets disease.

Other objects and advantages of the present invention will become more apparent from the following detailed description of the invention, claims and drawings.

According to one aspect of the present invention, the present invention provides a single nucleotide polymorphism (SNP) region of an N-acetylated alpha-linked acidic dipeptidase-like 2 ( NAALADL2 ) gene at position 501 (GenBank SNP database rs3914501) (GenBank SNP database rs68848171), the YIPF7 (Yip1 domain family, member 7) gene at position 501 of Sequence Listing No. 2 (GenBank SNP database rs6838327), DCAF12 DDB1 and CUL4 associated factor 12) gene as a single nucleotide polymorphic site of the PLCB1 (phospholipase C, beta 1) gene at position 201 of the Sequence Listing 4 (GenBank SNP database rs10441723) (GenBank SNP database rs6086653), the single nucleotide polymorphic site of the SCHIP1 (schwannomin interacting protein 1) gene as the 501 (GenBank SNP database rs16830581) and the PRKCH (protein kinase C, eta) gene as a single nucleotide polymorphic site of the gene selected from the group consisting of SEQ ID NO: A primer or a probe that specifically binds to 10-100 consecutive nucleotide sequences containing the nucleotide sequence of SEQ ID NO:

The present inventors have sought to find a novel biomarker capable of rapidly and accurately diagnosing Jejobet's disease (Jeon BD). As a result, we found a series of SNPs associated with intestinal BD at the genomic locus containing NAALADL2 .

Chang BD is a gastrointestinal disorder associated with Behcet's disease (BD), a chronic inflammatory disease that can invade multiple organs. It rarely occurs in BD patients in the Mediterranean, but is relatively common in Behcet's disease patients in East Asia. These intestinal BD are diagnosed on the basis of endoscopy and clinical diagnosis of BD, which confirms a typical form of ulcer.

We have analyzed the genotypes of a total of 756 Genome Wide Association Study (GWAS) subjects and 724 repeated study subjects and found strong evidence that some SNPs are associated with the intestinal BD. According to the present invention, one SNP located in the YIPF7 (Yip1 domain family, member 7) gene, two SNPs located in the NA-acetylated alpha-linked acidic dipeptidase-like 2 (NAALADL2) gene, DCAF12 (DDB1 and CUL4 associated one SNP located in the gene of PLCB1 (phospholipase C, beta 1), one SNP located in the SCHIP1 (schwannomin interacting protein 1) gene, and PRKCH (protein kinase C, eta) We found that one SNP located in the gene is associated with the BD. The kit of the present invention can predict the diagnosis and risk of human JEVH using a primer or a probe that specifically binds to 10-100 consecutive nucleotide sequences of each gene sequence containing the above SNPs.

(GenBank SNP database rs16848171) or the YIPF7 (Yip1 domain family, member (s)) of the second sequence of the sequence listing as a single nucleotide polymorphism (SNP) region of the NAALADL2 (N-acetylated alpha-linked acidic dipeptidase- 7) primer or probe that specifically binds to 10-100 contiguous nucleotide sequences comprising a single nucleotide polymorphic site of the 501 th position of Sequence Listing 3 (GenBank SNP database rs6838327) as a single nucleotide polymorphic site of the gene, The risk of Behcet's disease and oral ulcers can be predicted at the same time. It is also known that a single nucleotide polymorphism site of the PRKCH (protein kinase C, eta) gene is specific for 10-100 consecutive nucleotide sequences containing a single nucleotide polymorphic site at the 501 th position of Sequence Listing 7 sequence (GenBank SNP database rs12433533) Primers or probes that bind to a target gene can simultaneously predict the risk of Jejobetich's disease and eye disease.

As used herein, the term " association "means a statistically significant relationship between the polymorphism of a particular gene and the phenotype of an individual having the gene, and more specifically, the presence of a specific SNP and colonoscopy The p -value ( p -value) of the statistical results indicating the relationship between the BDs diagnosed by the test and clinical characteristics is 5 × 10 ^-4 or less. A total of 7 SNPs listed above are GWAS The results show that the small p - value of less than 5 × 10 ^{-4 is} associated with the intestinal BD (Tables 1 to 4), and especially the p - values of the two highly correlated rs3914501 and rs6838327 are 3.5 × 10 ^-4 and 3.4 10 ^-4 .

As used herein, the term " nucleotide " is a deoxyribonucleotide or ribonucleotide present in single or double stranded form and includes analogs of natural nucleotides unless otherwise specifically indicated (Scheit, Nucleotide Analogs, John Wiley, New York (1980); Uhlman and Peyman, Chemical Reviews, 90: 543-584 (1990)).

As used herein, the term " single nucleotide polymorphism (SNP) " refers to the occurrence of a single nucleotide (A, T, C or G) in the genome that is different between members of a species or between individual chromosomes DNA sequence identity. For example, if three DNA fragments of different entities (eg, AAGT [A / A] AG, AAGT [A / G] AG, and AAGT [G / It is called two alleles (C or T), and almost all SNPs generally have two alleles. Within a population, SNPs can be assigned to a minor allele frequency (MAF; the lowest allele frequency in locus found in a particular population). There are variations in the human population, and one common SNP allele in the geological or ethnic group is very rare. Single bases can be changed (substituted), removed (deleted), or added (inserted) to the polynucleotide sequence. The SNP can cause a change in the translation frame. Single nucleotide polymorphisms can be included in coding sequences of genes, non-coding regions of genes, or in intergenic regions between genes. SNPs in the coding sequence of a gene do not necessarily cause changes in the amino acid sequence of the target protein due to the degeneracy of the genetic code. SNPs that form the same polypeptide sequence are called synonymous (also called silent mutations) and SNPs that form other polypeptide sequences are said to be non-synonymous. Non-consensual SNPs can be missense or nonsense, and mismatch changes produce other amino acids while nonsense changes form non-mature termination codons. SNPs that are not in the protein-coding region can induce gene silencing, transcription factor binding, or non-coding RNA sequences. Human DNA sequence variability can affect disease outbreaks and how humans respond to pathogens, chemicals, drugs, vaccines and other reagents. In addition, SNP is considered to be a key enabler for realizing the concept of customized medicines. Above all, SNPs, which are actively being developed as markers in recent years, are most important in biomedical research to diagnose disease by comparing genomic sites between groups with or without disease. SNPs are the most abundant variants of the human genome and are presumed to exist at a SNP ratio of 1.9 kb (Sachidanandam et al., 2001). SNPs are highly stable genetic markers, sometimes directly affecting phenotypes, and are well suited for automated genotyping systems (Landegren et al., 1998; Isaksson et al., 2000). SNP studies are also important in grain and livestock breeding programs.

As used herein, the term " primer " means an oligonucleotide in which the synthesis of a primer extension product complementary to a nucleic acid chain (template) is induced, that is, the presence of a polymerizing agent such as a nucleotide and a DNA polymerase, It can act as a starting point for synthesis at suitable temperature and pH conditions. Specifically, the primer is a deoxyribonucleotide and a single strand. The primers used in the present invention may include naturally occurring dNMPs (i.e., dAMP, dGMP, dCMP and dTMP), modified nucleotides or non-natural nucleotides. In addition, the primers may also include ribonucleotides.

The primer of the present invention may be an extension primer that is annealed to a target nucleic acid and forms a sequence complementary to the target nucleic acid by a template-dependent nucleic acid polymerase, which extends to a position where the immobilization probe is annealed, It occupies the area that is annealed.

The extension primer used in the present invention comprises a hybridization nucleotide sequence complementary to the first position of the target nucleic acid. The term " complementary " means that under certain annealing or hybridization conditions the primer or probe is sufficiently complementary to hybridize selectively to the target nucleic acid sequence and is substantially complementary and perfectly complementary It is meant to be inclusive, and specifically to be completely complementary. As used herein, the term " substantially complementary sequence " as used in connection with a primer sequence is intended to encompass a complete sequence as well as a sequence that is comparable to that of the sequence to be compared, Inconsistent sequences are also included.

The primer should be long enough to be able to prime the synthesis of the extension product in the presence of the polymerizing agent. The suitable length of the primer is determined by a number of factors, such as the temperature, the application, and the source of the primer, but is typically 15-30 nucleotides. Short primer molecules generally require lower temperatures to form a sufficiently stable hybrid complex with the template. The term " annealing " or " priming " means that the oligodeoxynucleotide or nucleic acid is apposited to the template nucleic acid, which polymerizes the nucleotide to form a complementary nucleic acid molecule to the template nucleic acid or a portion thereof .

The sequence of the primer does not need to have a sequence completely complementary to a partial sequence of the template, and it is sufficient if the primer has sufficient complementarity within a range capable of hybridizing with the template and acting as a primer. Therefore, the primer of the present invention does not need to have a perfectly complementary sequence to the above-mentioned nucleotide sequence which is a template, and it is sufficient that the primer has sufficient complementarity within a range capable of hybridizing with the gene sequence and acting as a primer. The design of such a primer can be easily carried out by those skilled in the art with reference to the nucleotide sequence described above, for example, by using a program for primer design (e.g., PRIMER 3 program).

When the starting material in the kit of the present invention is gDNA, the separation of gDNA can be carried out according to conventional methods known in the art (Rogers & Bendich (1994)).

When the starting material is mRNA, the total RNA is isolated by a conventional method known in the art (see Sambrook, J. et al., Molecular Cloning, A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (1987) and Chomczynski, et al., ≪ RTI ID = 0.0 > Ausubel, < / RTI > FM et al., Current Protocols in Molecular Biology, John Willey & P. et al., Anal. Biochem. 162: 156 (1987)). The isolated total RNA is synthesized by cDNA using reverse transcriptase. Since the total RNA is isolated from a human (for example, obesity or diabetic patients), it has a poly-A tail at the end of mRNA and can easily synthesize cDNA using oligo dT primers and reverse transcriptase using such sequence characteristics (1988); Libert F, et al., Science, 244: 569 (1989); and Sambrook, J. et al., Molecular Cloning, A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (2001)).

In the kit of the present invention, identification of the specific sequence can be performed by applying various methods known in the art. For example, techniques that may be applied to the present invention include fluorescence in situ hybridization (FISH), direct DNA sequencing, PFGE analysis, Southern blot analysis, single-strand conformational analysis (SSCA, Orita et al., PNAS, USA 86: 2776 (1989)), RNase protection analysis (Finkelstein et al., Genomics, 7: 167 (1990)), dot blot analysis, denaturing gradient gel electrophoresis (DGGE, Wartell et al., Nucl. Acids Res. , 18: 2699 (1990)), a protein WartE recognizing a nucleotide mismatch. The mutS protein ucl.Ac of E. coli includes, but is not limited to, the method (Modrich, Ann. Rev. Genet., 25: 229-253 (1991)), and allele-specific PCR. Sequence changes result in differences in base-linkage within the single-stranded molecule, leading to the appearance of different bands of mobility, and SSCA detects this band. DGGE analysis uses a denaturing gradient gel to detect sequences that represent wild type sequences and other mobility.

Other techniques generally use probes or primers complementary to sequences comprising the SNPs of the invention. For example, in an RNase protection assay, a riboprobe complementary to a sequence comprising the SNPs of the present invention is used. The riboprobe is hybridized with DNA or mRNA isolated from human, and then cleaved with an RNase A enzyme capable of detecting a mismatch. If there is a mismatch and RNase A recognizes, a smaller band is observed.

In the analysis using a hybridization signal, a probe complementary to the sequence containing the SNP of the present invention is used. In this technique, hybridization signals of the probe and the target sequence are detected to determine whether DM or MS is directly detected.

As used herein, the term " probe " means a linear oligomer having a natural or modified monomer or linkage comprising a deoxyribonucleotide and a ribonucleotide that can hybridize to a particular nucleotide sequence.

Specifically, probes are single strands for maximum efficiency of hybridization. More specifically, the probe is a deoxyribonucleotide.

As the probe used in the present invention, a sequence complementary to the sequence including the SNP may be used, but a sequence substantially complementary to the sequence that does not interfere with the specific hybridization is used It is possible. Specifically, the probe used in the present invention includes a sequence that can be hybridized to a sequence comprising 10 to 30 contiguous nucleotide residues including the SNP of the present invention. More specifically, the 3'-end or the 5'-end of the probe has a base complementary to the SNP base. Generally, the stability of the duplex formed by hybridization tends to be determined by the agreement of terminal sequences, so that in a probe having a base complementary to the SNP base at the 3'-terminal or 5'-terminal, If the part is not hybridized, such a duplex can be disassembled under stringent conditions.

Suitable conditions for hybridization include, but are not limited to, Nucleic Acid Hybridization, A Practical Approach, Hayes, BD, et al., Molecular Cloning, A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, IRL Press, Washington, DC (1985). ≪ / RTI > The stringent condition used for hybridization can be determined by controlling the temperature, the ionic strength (buffer concentration) and the presence of a compound such as an organic solvent, and the like. This stringent condition can be determined differently depending on the sequence to be hybridized.

As used herein, the term " diagnosing " is intended to include determining the susceptibility of an object to a particular disease or disorder, determining whether an object currently has a particular disease or disorder (e.g., Determining the prognosis of an object that has suffered a particular disease or disorder, or including therametrics (e.g., monitoring the status of an object to provide information about the therapeutic efficacy) do. According to the present invention, when SNPs of the present invention are identified as multiple markers and their presence is confirmed through the above-described method, it is judged that the risk of intestinal BD is high.

According to one embodiment of the invention, humans with a single base polymorphic site of the invention have an increased risk of intestinal disease.

According to a more specific embodiment of the present invention, the intestinal BD was diagnosed by colonoscopy and clinical characteristics (Table 5).

According to another aspect of the present invention, there is provided a method for detecting a single nucleotide polymorphism (SNP) of a NAALADL2 (N-acetylated alpha-linked acidic dipeptidase-like 2) gene in a biological sample of a human, (GenBank SNP database rs3914501) and the 501th position (GenBank SNP database rs16848171) of the second sequence of the sequence listing and the YIPF7 (Yip1 domain family, member 7) gene as a single nucleotide polymorphic site (GenBank SNP database rs6838327), PLCB1 (GenBank SNP database rs6838327), DCB2 (DDB1 and CUL4 associated factor 12) gene locus at position 501 of Sequence Listing No. 3 (GenBank SNP database rs10441723) (GenBank SNP database rs6086653), SCHIP1 (schwa (SEQ ID NO: 1)) in the 5th sequence of the Sequence Listing as a single base polymorphic site of the phospholipase C, (GenBank SNP database rs16830581) and the PRKCH (protein kinase C, eta) gene as the single nucleotide polymorphic site of the nnomin interacting protein 1) gene as a single nucleotide polymorphic site of SEQ ID NO: Position (GenBank SNP database rs12433533) of a gene selected from the group consisting of a single nucleotide polymorphism site and a nucleotide polymorphism site.

The method of the present invention has the above-mentioned primer as an essential component, and the detailed description of the primer also applies to the primer used in the method of the present invention. Therefore, the description thereof will be omitted in order to avoid the excessive complexity of the present specification according to the repetitive description.

Because there is no definitive symptom and test result in the diagnosis of BD, classification criteria consisting of high diagnostic value among endoscopy or various clinical symptoms of BD are used. In particular, Chang BD is an ulcer of the gastrointestinal tract in Korea and in East Asia including Japan, and symptoms such as abdominal pain, diarrhea and stool occur, but various vasculitis and central nervous system diseases may precede other symptoms. it's difficult.

The inventors of the present invention have found a method of detecting the intestinal BD in a convenient and precise manner only by a specific genetic test in order to solve this problem.

As used herein, the term " biological sample " refers to all materials of an organism, including nucleic acids.

According to one embodiment of the present invention, the biological sample of the present invention is a biological sample separated from a human, and is used as a blood sample, blood plasma, serum, tissue, cell, lymph, bone marrow fluid, saliva, ocular fluid, And more specifically includes blood, plasma, serum, tissues, cells, lymphatic fluid, bone marrow fluid, cell tissue fluid and cell culture fluid, and more specifically blood, plasma, serum, And more particularly, blood, plasma, serum, tissue, and lymph, and most specifically blood, plasma, and serum.

In the present specification, the term " nucleic acid molecule " has the meaning inclusive of DNA (gDNA and cDNA) and RNA molecules, and the nucleotide, which is a basic constituent unit in the nucleic acid molecule, includes not only natural nucleotides, (Scheit, Nucleotide Analogs, John Wiley, New York (1980); Uhlman and Peyman, Chemical Reviews, 90: 543-584 (1990)).

The single nucleotide polymorphic sites for detecting Jejobetich's disease of the present invention are the same as the single nucleotide polymorphic sites used in the BD BD diagnostic kit of the present invention. Therefore, the description thereof will be omitted in order to avoid the excessive complexity of the present specification according to the repetitive description.

When the method of the present invention is applied to a PCR amplification process, the method of the present invention may optionally comprise the steps of adding a reagent, such as a buffer, a DNA polymerase (e.g., Thermus aquaticus (Taq), Thermus thermophilus filiformis, Thermis flavus, Thermococcus literalis or Pyrococcus furiosus (Pfu)), DNA polymerase joins and dNTPs. The method of the present invention can be made with a number of separate packaging or compartments containing the reagent components described above.

According to one embodiment of the present invention, the method of the present invention is carried out through a gene amplification reaction or a microarray. Specifically, the amplification reaction of the present invention is carried out according to a polymerase chain reaction (PCR).

The amplification reaction refers to a reaction for amplifying a silver nucleic acid molecule. A variety of amplification reactions have been reported in the art, including polymerase chain reaction (PCR) (US Pat. Nos. 4,683,195, 4,683,202 and 4,800,159), reverse-transcription polymerase chain reaction (RT-PCR) (Sambrook et al., Molecular Cloning. (LCR) (see, for example, A Laboratory Manual, 3rd Ed. Cold Spring Harbor Press (2001)), Miller, HI (WO 89/06700) and Davey, C. et al (EP 329,822) 17,18), Gap-LCR (WO 90/01069), repair chain reaction (EP 439,182), transcription-mediated amplification (TMA) 19 (WO 88/10315) (US Ser. No. 6,410, 276), self-sustained sequence replication (20) (WO 90/06995), selective amplification of target polynucleotide sequences (US Patent No. 6,410,276), consensus sequence priming polymerase chain Consensus sequence primed polymerase chain reaction (CPPCR) (U.S. Patent No. 4,437,975), (US Pat. Nos. 5,413,909 and 5,861, 245), nucleic acid sequence based amplification (NASBA) (US Pat. No. 5,130,238, 5,409,818, 5,554,517, and 6,063,603), strand displacement amplification (21,22), and loop mediated isothermal amplification. (LAMP) 23, but is not limited thereto. Other amplification methods that may be used are described in U.S. Patent Nos. 5,242,794, 5,494,810, 4,988,617 and U.S. Patent No. 09 / 854,317.

PCR is the most well-known nucleic acid amplification method, and many variations and applications thereof have been developed. For example, touchdown PCR, hot start PCR, nested PCR and booster PCR have been developed by modifying traditional PCR procedures to enhance the specificity or sensitivity of PCR. In addition, real-time PCR, differential display PCR (DD-PCR), rapid amplification of cDNA ends (RACE), multiplex PCR, inverse polymerase chain reaction chain reaction (IPCR), vectorette PCR and thermal asymmetric interlaced PCR (TAIL-PCR) have been developed for specific applications. For more information on PCR see McPherson, M.J., and Moller, S.G. PCR. BIOS Scientific Publishers, Springer-Verlag New York Berlin Heidelberg, N.Y. (2000).

When the method of the present invention is carried out using a primer, the nucleotide sequence of the marker of the present invention is analyzed by performing a gene amplification reaction. Since the present invention detects the nucleotide sequence of the marker of the present invention, it can be determined by determining the nucleotide sequence of the marker of the present invention in a sample (for example, genomic DNA) to be analyzed.

The method of the present invention may be implemented in a microarray manner. When the method of the present invention is based on the microarray method, the probe is immobilized on the solid-phase surface of the microarray.

The probe used in the method of the present invention has a sequence complementary to 10-100 consecutive nucleotide sequences on each gene comprising the above-mentioned SNPs of the present invention.

* The nucleotide sequence of the marker of the present invention to be referred to in the production of the probe can be confirmed by GenBank.

For example, the nucleotide sequence of Sequence Listing 1, which is one of the markers of the present invention, is the GenBank SNP database rs3914501, the nucleotide sequence of Sequence Listing 2 is the GenBank SNP database rs16848171, the nucleotide sequence is disclosed, can do.

In the microarray of the present invention, the probe is used as a hybridizable array element and immobilized on a substrate. Specific gases include, for example, membranes, filters, chips, slides, wafers, fibers, magnetic beads or non-magnetic beads, gels, tubing, plates, polymers, microparticles and capillaries, as suitable rigid or semi-rigid supports. The hybridization array elements are arranged and immobilized on the substrate. Such immobilization is carried out by a chemical bonding method or a covalent bonding method such as UV. For example, the hybridization array element may be bonded to a glass surface modified to include an epoxy compound or an aldehyde group, and may also be bound by UV on a polylysine coating surface. In addition, the hybridization array element may be coupled to the gas through a linker (e.g., ethylene glycol oligomer and diamine).

On the other hand, the sample DNA to be applied to the microarray of the present invention can be labeled and hybridized with the array elements on the microarray. Hybridization conditions can be varied. The detection and analysis of the hybridization degree can be variously carried out according to the labeling substance.

The label of the probe may provide a signal to detect hybridization, which may be linked to an oligonucleotide. Suitable labels include fluorescent moieties (e.g., fluorescein, phycoerythrin, rhodamine, lissamine, and Cy3 and Cy5 (Pharmacia)), chromophores, chemiluminescent moieties, magnetic particles, (Such as P32 and S35), mass labels, electron dense particles, enzymes (alkaline phosphatase or horseradish peroxidase), joins, substrates for enzymes, heavy metals such as gold and antibodies, streptavidin, biotin , Digoxigenin, and haptens with specific binding partners such as chelating groups. Markers can be generated using a variety of methods routinely practiced in the art such as the nick translation method, the Multiprime DNA labeling systems booklet (Amersham, 1989) and the kaination method (Maxam & Gilbert, Methods in Enzymology, 65: 499 (1986)). The label provides signals that can be detected by fluorescence, radioactivity, color measurement, weighing, X-ray diffraction or absorption, magnetism, enzymatic activity, mass analysis, binding affinity, hybridization high frequency, and nanocrystals.

The nucleic acid sample to be analyzed can be prepared using mRNA obtained from various biological targets. Instead of the probe, the cDNA to be analyzed may be labeled and subjected to a hybridization reaction-based analysis.

When a probe is used, the probe is hybridized with the cDNA molecule. In the present invention, suitable hybridization conditions can be determined by a series of procedures by an optimization procedure. This procedure is performed by a person skilled in the art in a series of procedures to establish a protocol for use in the laboratory. Conditions such as, for example, temperature, concentration of components, hybridization and washing time, buffer components and their pH and ionic strength depend on various factors such as probe length and GC amount and target nucleotide sequence. Detailed conditions for hybridization are described in Joseph Sambrook, et al., Molecular Cloning, A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N. Y. (2001); And M.L.M. Anderson, Nucleic Acid Hybridization, Springer-Verlag New York Inc .; N.Y. (1999).

After the hybridization reaction, a hybridization signal generated through the hybridization reaction is detected. The hybridization signal can be carried out in various ways depending on, for example, the type of label attached to the probe. For example, when a probe is labeled with an enzyme, the substrate of the enzyme can be reacted with the result of hybridization reaction to confirm hybridization. Combinations of enzymes / substrates that may be used include, but are not limited to, peroxidases (such as horseradish peroxidase) and chloronaphthol, aminoethylcarbazole, diaminobenzidine, D-luciferin, lucigenin (bis- Acetyl-3,7-dihydroxyphenox), HYR (p-phenylenediamine-HCl and pyrocatechol), TMB (tetramethylbenzidine), ABTS (2) , 2'-Azine-di [3-ethylbenzthiazoline sulfonate]), o-phenylenediamine (OPD) and naphthol / pyronine; (BCIP), nitroblue tetrazolium (NBT), naphthol-AS-B1-phosphate, and ECF substrate; alkaline phosphatase and bromochloroindoleyl phosphate; Glucose oxidase and t-NBT (nitroblue tetrazolium) and m-PMS (phenzaine methosulfate). When the probe is labeled with gold particles, it can be detected by a silver staining method using silver nitrate. Therefore, by analyzing the intensity of the hybridization signal by the hybridization process, the present invention is diagnosed to have a high risk of BD when the hybridization signal for the nucleotide sequence of the marker of the present invention in the sample is stronger than that of the control.

According to the present invention, the BD BD diagnosis and detection kit using the gene polymorphism site specific for BD BD enables the diagnosis and detection of BD BD in a convenient and accurate manner only by specific genetic test.

The features and advantages of the present invention are summarized as follows:

(a) The present invention relates to a Jean-Berthetti bottle biomarker and its use.

(b) According to the present invention, the biological sample is a single nucleotide polymorphism (SNP) region of the N-acetylated alpha-linked acidic dipeptidase-like 2 (NAALADL2) gene at position 501 (GenBank SNP database rs3914501) And the 501th position (GenBank SNP database rs688327) of the 3rd sequence of Sequence Listing (GenBank SNP database rs6838327) as the single nucleotide polymorphic site of YIPF7 (Yip1 domain family, member 7) (GenBank SNP database rs10441723) and the PLCB1 (phospholipase C, beta 1) gene as the single nucleotide polymorphic site of the DDB1 and CUL4 associated factor 12 gene in SEQ ID NO: (GenBank SNP database rs6086653), the single nucleotide polymorphic site of SCHIP1 (schwannomin interacting protein 1) gene, as the 501 (GenBank SNP database rs16830581) and the PRKCH (protein kinase C, eta) gene as a single nucleotide polymorphic site of the gene selected from the group consisting of SEQ ID NO: , The biological sample has a very high risk of Jejobetz disease.

(c) Thus, the kit and method of the present invention can be used to diagnose Jeff-Bethel's disease very easily and easily.

Figure 1 shows the results of cumulative probability of surgery according to SNP genotype in patients with Jejobetz disease. Blue represents a risk allele.
2A and 2B show gene expression results in colon tissues according to disease and SNP genotype. Immunohistochemistry of colon tissues was performed on NAALADL2, YIPF7, and GSTT1. (A) NAALADL2 (rs3914501), (B) YIPF7 (rs6838327), (C) GSTT1 (rs17856199). The right side shows the intensity of dyeing. * P <0.05. CTL, *** P <0.005 vs. CTL. CTL, control CD, colonic disease BD, Behcet's disease.
FIG. 3 shows gene expression results by LPS stimulation in HT-29 cells. (A) NAALADL2, (B) YIPF7, (C) GSTT1.
Figure 4 shows the flow of the research work.
Figures 5A-5B show the results of principal component analysis (PCA). Figure 5a shows the PCA results for the entire subject sample (199 BD case and 597 control group) including the samples referenced in the 1000 genome project. The BD case is red, the control is green, the purple is blue, and the blue and the yellow, respectively, in the northern and western European systems, and the Yuubah in Nigeria. Figure 5b shows the PCA results for the 199 BD case and 597 control samples not in the 1000 genome project samples. The BD case was red and the control was green.
FIGS. 6A to 6C show cumulative probability results according to SNP genotypes in patients with BD. Figure 6a shows the cumulative probability of hospitalization according to SNP genotype in patients with BD. Figure 6b shows cumulative probability results of corticosteroid use according to SNP genotype in patients with BD. Figure 6c shows cumulative probability results of immunosuppressive drug use according to SNP genotype in patients with BD. The risk allele was indicated by the blue line.
Figures 7a-7k show Cis expression quantitative characterization results of related SNPs. FIG. 7A is a graph showing the relationship between rs3914501 in NAALADL2. Fig. 7b shows the results of the comparison of YPF7 to rs6838327. Figure 7c shows ERP1 to rs17482078. 7d shows ERP1 to rs2927615. 7E shows IL10 to rs1554286. Fig. 7f shows the results of rs1518111. FIG. 7g shows rs1805110 in TGFBR3. Figure 7h shows rs430208 at COG7. Figure 7i shows DCAF12 at rs10441723. 7J shows SCHIP1 in rs16830581. Figure 7h shows STAT4 in rs7574070. The results were compared with the results of HapMap3 (CEU, CHB, GIH, JPT, LWK, MEX, MKK, YRI) (Stranger et al., 2012), Geneva Gencord (Dimas et al. ) &Lt; / RTI &gt; located at the cis-probes of each SNP. Chr., Chromosome; eQTL, expression quantitative property location; LD, connection imbalance; Position, chromosomal location (hg19); rSNP, regulated SNP; F, fibroblast; T, T-cells; S, skin; F, fat; L, lymphocytic cell line.

Materials and methods

Research subjects and DNA extraction

A total of 533 Korean BD subjects, including 238 BD subjects and 295 BD BD subjects, were included in the BD Clinic in Korea, Seoul, Yonsei University, and Severance Hospital between June 2006 and August 2013. Registered. Chang BD was diagnosed according to criteria established on the basis of colonoscopy characteristics and clinical characteristics. ⁷ Only those patients who were finally classified as "definite" or "certain" were included in the study. The statistical and clinical characteristics of the study subjects are summarized in Table 5. We obtained phenotypic results from 600 healthy individuals who were randomly selected from 10,000 healthy Koreans in the Korean Association of Resource Projects using the same platform. This study was approved by the institutional review board of Yonsei University, Severance Hospital and written consent provided by all patients and controls. Genomic DNA was extracted from whole blood samples using Qiagen (Hilden, Germany) DNA blood maxikits.

Genotype and quality management in GWAS

A total of 199 BD patients (100 BD patients without bowel and 99 BD patients) received the Affymetrix Whole-Blood test to see the final> 95% call rates entering the case-control analysis on all samples. Genome-Wide Human SNP Array 6.0. (Affymetrix, Santa Clara, Calif.). A case-control analysis was conducted on 557 control samples from 600 Koreans, with control, matched, and potentially relevant subjects excluded from> 95% collation.

Quality control, or if the case is not on a chromosome with the control group, <1% minority allele mapping (mapping) the gene frequency or P value of the control group ^{(value) <1 × 10 -7} Hardy-Weinberg equilibrium (HWE), SNPs are P Value < 1 x 10 &lt; ^-4 &gt; The quantilequantile plot (QQ plot) was obtained to assess the overall significance of genome-wide associations and the potential implications of population stratification. Healthy Control vs Filtering Progression, healthy versus 651,605 SNPs on all BD Patients, healthy versus 652,294 SNPs versus BD BD Patients, BD Patients not containing 646,355 SNPs versus healthy controls, BD patients 637,816 SNPs do not include large bowel BD patients were used for final GWAS analysis.

Principal component analysis (PCA) was used to identify population stratification as a factor of bishop using basic parameters and parameter software package EIGENSTRAT v.5.0.1 ¹⁵ . For the initiation PCA, 199 BD cases were analyzed with 597 controls. In addition, Korean samples (199 cases and 597 controls) were assigned to the 1000 genome project (phase1_release_v3.20101123) using 391.001 markers labeled with> 95% collate,> 5% MAF, and collate> 95%, and 0.05 HWE p (CEU) and African (YRI).

Imputation

For the purpose of evaluating the reliability of the analysis and substitution methods for finding the mutation association in the present invention, the missing genotype was divided into 1000 genome-phage I integrated mutation sets and IMPUTE (v.2.0) (https: //mathgen.stats.ox .ac.uk / impute / impute_2.html) and GWAS samples containing genotyping. For qualitative management, 31 SNPs (posterior probability score of <0.90), or <0.05% of the minor allele frequency (MAF) to the low substitution quality is the P value of Hardy-Weinberg equilibrium (HWE) <0.0001 or It was escaped except for the collet <95%. SNPs were excluded from the relevant analysis at Rsq <3.0. A total of 779,465 replaced SNPs were included in the genome-wide association analysis. A total of 5,093,113 replated SNPs were passed qualitative control tests and 571,238 genotypic SNPs were combined for analysis.

SNP selection and repeated study

Genome-wide search in accordance with the analysis, P <1 × 10 ^-4 SNPs and BD 237 BD 295 does not include a chapter and one chapter can use the 70 SNPs (39 loci) DNA comprising the SNPs reported in the prior art and one A non-duplicate set of 391 controls was selected for repeated study. (BioMark TM HD system (Fluidigm, CA, USA) was used for identification of rs17856199, rs1800871, and rs4500591, according to manufacturer's protocol and recommended qualitative management measures, TaqMan genotype analysis (Applied Biosystems, CA, USA) Were used. The concordance rate between the genotypes determined by Affymetrix Whole-Genome-Wide Human SNP Array 6.0 and TaqMan genotyping assays or BioMark ™ HD systemj was> 99.9% among duplicate samples in 44 SNPs, indicating negligible genotype errors.

Haplotypic analysis

To clarify the sensitive area and narrow the candidate area, haplotype associations are analyzed using the method developed by Lake et al, and R (http://www.r-project.org) And provided estimates and significance of haplotype-related effects on traits compared to haplotype effects. In this study, a haplotype consisting of a combination of major alleles at each gene location was used as a standard.

Cis-expression quantitative trait gene location ( cis-eQTL )

For the cis-eQTL analysis to reveal the gene locus in a control of gene-specific changes, three other data from the eQTL Browser (http://www.sanger.ac.uk/resources/software/genevar/) found. The cis associations of each SNP and its expression and its proxies were found in primary fibroblasts, T-cells, skin, fat and lymphoblastoid cell lines. ^17,18

Regulated SNPs

Regulatory SNPs were investigated in RegulomeDB (http://regulomedb.org). Variations can be categorized into one of four scoring ranges, ranging from 1-6 indicating the estimated function and four RegulomeDB categories.

GWAS Analysis-Oriented Networks and Paths

We analyzed biological pathways using Ingenuity pathway analysis to evaluate biologically meaningful subnetworks by comparing known KEGG pathways and constitutive genes.

Immunodiffusion

For immunohistochemical analysis, formalin-fixed paraffin embedded (FFPE) tissue pieces (21 cancer normal tissues and 29 intestinal BD patient inflammatory tissues were deparaffinized, washed with sterile water, In 10 mM citrate buffer (pH 6.0) for 10 min.The tissue pieces were washed with sterile water and treated with 3% H ₂ O ₂ for 5 min.Tris-buffered saline containing 0.1% Tween-20 After washing with saline (TBST), the slices were blocked with 2.5% normal horse serum in TBST for one hour and incubated overnight at 4 ° C with NAALADL2 antibody (1: 100, Santa Cruz Biotechnology, Santa (1: 100, Santa Cruz) and YIPF7 (1: 100, Novus Biologicals, Littleton, CO, USA). After washing, the slices were incubated with biotin-conjugated IgG (Vector Laboratories, Burlingame, Calif., USA, 1: 500), and then the benzidine material The streptavidin-peroxidase kit (Vector Laboratories) was treated with the reagents. The slices were contrasted with diluted hematoxylin and stained with an optical microscope (Olympus BX41: Olympus Optical , Tokyo, Japan). To quantify gene expression, randomly selected fields were tested for each sample of 100 × magnification and 0-3 range scores.

Cell culture and treatment

HT-29 cells (Korea Cell Line Bank, Seoul, Korea), 10% heat in humid conditions of 5% CO ₂ - inert fetal bovine serum (FBS) and 1% Dulbecco's modified Eagle's medium (DMEM) with antibiotics contain 37 ℃ Respectively. Cells were incubated with LPS (1 [mu] g / ml) for a period of incubation.

The knockdown was performed by transfection of HT-29 cells per well with 6-well plates for 24 hours with short interfering RNA or non-targeted control. To evaluate the inflammatory response, the cell culture medium was replaced with culture medium containing LPS 24 hours after transfection. All samples were obtained 3-72 hours after LPS treatment. Transcript levels were quantified by quantitative PCR and standardized by GAPDH and β-ACTIN.

Quantitative real-time reverse-transcription polymerase chain reaction (RT-PCR)

Total RNA was purified using TRIzol reagent (Invitrogen) and 1 g of RNA was reverse-transcribed using SuperScript First-Strand synthesis kit (Invitrogen) according to the manufacturer-recommended protocol. cDNAs were mixed in each of three using SYBR Green Master Mix (Applied Biosystems, Foster City, CA) and primer pairs (4 pmol of each primer). PCR was performed using primers (AccuTarget qRT-PCR primer) for NAALADL2, YIPF7, TNF-alpha, IL12BIL22 and beta -actin . 40-45 cycles were amplified in StepOne Plus real-time PCR (Applied Biosystems) at 95 ° C for 30 seconds, 6063 ° C for 30 seconds, and 72 ° C for 40 seconds. Finally, the quantitative analysis was performed using the relative comparison curve method, and the results were compared with the relative expression or tolerance, GAPDH or β-actin standardization of transcription level, Respectively.

Statistical analysis

The association of selected SNPs in a subset of diseases or diseases was assessed using the chi-square test (dominant, recessive, and allele models), the Cohchran-Amitage Trend test using SAS 9.1.3 version (SAS institute Inc. Cary NC, USA) Statistical significance determined by parametric methods (non-parametric models) and non-parametric methods Jonckheere-Terpstra (results not shown), and minority alleles between cases and controls were compared and analyzed. In addition, the logistic regression analysis included the odds ratio (OR) for the SNPs selected from four different models (dominant, recessive, dominant, and alleles), the 95% confidence interval (CI) for OR, and it was used to obtain a relative P value compared to the control group. We have created a Manhattan plot of -log10 P using Haploview (V.4.2) (http://www.broadinstitute.org/haploview). Significant P values for association analysis were calculated using the Cochran-Mantel-Haenszel test (Bonferroni correction for 70 tests applied at a statistically significant level P <7.1 × 10 ⁴ ) The CochranArmitage trend test was used to calculate for repeated samples. In the case of a minor allele frequency of 0.4%, our study obtained 80% power to detect a low OR at 1.56% estimated by Quanto (version 1.2.4). For each recorded SNP, the force for detection at a P value of 0.05 was calculated based on reported OR and Korean allele frequency. One gene (GSTT1) was selected by comparing non-long BD and non-long BD using Nexus copy number version 7.0 (Biodiscovery, El Segundo, CA, USA).

The association analysis for the fine-mapping step is performed in Haploview, version 4.1. Linkage disequilibrium analysis (LD).

Predictable effects of amino acid substitution on protein function can be found in SIFT (Sorting Intolerant From Tolerant, http://siftdna.org/www/SIFT_dbSNP.html) or PolyPhen-2 algorithms (polymorphism phenotyping v2) (http: //genetics.bwh. harvard.edu/pph2), and "damage" or "possibly / possible damage" was considered to predict effects on each protein function.

The Mann-Whitney test was used to test for significant differences in immunostaining considering P <0.05 significance.

The cumulative probability of the use of intestinal BD (post-diagnosis surgery, hospitalization, corticosteroid use, and immunosuppression use) is analyzed using the Kaplan-Meier method, where the differences are determined using log-range tests Respectively.

result

Selection of GWAS and SNP for BD patients who do not include BD patients and intestines

A characteristic summary of the BD samples is provided in Table 1. A case-control analysis was initiated with a total of 577 control subjects in a total of 199 BD patients (BD patients not containing 100 chickens, 99 BD patients) and GWAS> 95% call rates. PCA suggests a low likelihood of false positives from mixed populations by comparison with existing Korean IBD GWAS data (Figure 4) ^20,21 . This suggests a genetic heterogeneity due to the disease in the eigenvector 2 data set (Fig. 5). The intermediate variation between the BD case and the control subjects.

After SNP qualitative management, we used a tendency test of logistic regression to further analyze the association between cases and controls. The GWAS analysis provides seven more comparisons at the genome-wide level ( P <1 × 10 ^-4 ) summarized in Support Information 2, which allows for more comprehensive analysis of disease subtypes and shows various SNPs according to subtypes of disease Group: 319 SNPs versus non-healthy healthy controls vs healthy BD-399 SNPs, BD versus non-BD versus healthy versus healthy controls (excluding BD, which are not specifically risky SNPs) Comparison of 342 SNPs versus BD without healthy chickens versus healthy chickens versus BD versus non-chick versus healthy chickens versus healthy controls (except for those that are specifically risky for intestinal BD) Comparing between BD SNPs, 108 SNPs comparing between BDs that do not contain a large BD catheter (no detection risk alone), BD vs. healthy BDs that do not contain meaningful chapters compared to BD versus BD 32 divided by SNPs, and all of BD (BD + does not include a chapter Chapter BD) for 218 SNPs comparison between healthy controls (to assume the total risk of BD).

CD300C / CD300LB ( P <2.0 × 10 ^-6 ) and TNFRSF13B ( P <2.5 × 10 ^-6 ), which have an important association with the onset of intestinal BD in chromosome 17, have been reported to improve the range of specific mutations associated with BD Using genomes Phase I incorporating the mutation set, missing genotypes of autosomal SNPs in 99 GW cases and 557 GWAS clusters of controls were re-identified (Table 6). In addition, other means (Nexus copy number) were used to compare the predictive power among the analytical means from GSTT1 selected as the BD-, BD-related genes that did not contain any significant BD-, Chapter.

Repeated studies to identify genotypes

70 SNPs selected after genome-wide association screening performed an additional repeat study using 196 independent long-BD patients who assess genome-wide association screening, BD patients not containing 137 chickens, and 391 controls. With this analysis, one SNP ( GSTT1 ) from the GWAS analysis using the strongest associated signal or other analysis software, the 8 position (rs12119179 and rs1495965 to IL23R-IL12RB2 , rs1554286, rs1518111 to IL10 , the rs1800871, rs5742906, rs17482078 ERAP1 in CCR1-CCR3 and rs2927615, HLA-F-AS1HLA- a to the rs4713242, KLRC4-KLRK1 the rs2255336, rs12525170, rs7574070 STAT4 in PSORS1C1) ^{2-6, 22} from the 12 SNPs, and checking again 56 SNPs were selected from 37 positions showing one or more significant associations in at least one region of analysis separated by one location of the data ( rs61730133 to CD300C / CD300LB ).

The combined analysis and iterative studies of GWAS showed that the NAALADL2 gene (rs3914501, OR = 1.914, P ) was obtained on chromosome 3, obtained after Bonferroni calibration ( P <2.0 × 10 ³ , = 3.5 × 10 ⁴ , recessive genetic model) with one BD-specific association at the site and a single locus at position PSORS1C1 (rs12525170, OR = 2.210, P = 1.1 × 10 ⁵ dominant genetic model) on chromosome 6 Specific BD-free association. These different genetic risks demonstrate the specific biological importance that exists, including intestines (Tables 1 and 2). Comparisons to BDs that do not contain BDs and chapters are significant at the location of the YIPF7 gene (rs6838327, OR = 1.567, P = 3.4 × 10 ⁴ , allele model) on chromosome 4 containing the post-Bonferroni correction Respectively. Rs61730133 from CD300C / CD300LB selected from re-identified SNPs did not show any genetic variation in this study (Table 3). In addition, the association GSTT1 rs17856199 Chapter BD (OR = 1.918, P = 1.7 × 10 -4, Allele model) and chapter does not include BD (OR = 1.630, P = 3.7 × 10 -3 allele model) , Suggesting that GSTT1 is a novel candidate gene for BD (OR = 1.730, P = 5.2 × 10 ⁵ , allele model) independent of intestine.

Among the previously proven positions in the GWAS study, CCR1-CCR3 (rs5742906), IL23R- IL12RB2 (rs12119179, rs1495965) ^4,5 , HLA-F- AS1HLA-A (rs4713242), and KLRC4-KLRK1 ( rs2255336) and the BD did not see an association that means in any of the sub-type, ERAP1 (rs2927615) showed significantly between BD does not include a chapter BD and Chapter, which proved the role of ERAP1 including Chapter (OR = 2.744, MAF = 0.041, P = 1.6 x 10 ^-2 , allele model). Also, ELMO1 is not including the heads compared with the healthy control group BD (rs10259514, OR = 0.724, MAF = 0.256, P = 1.8 × 10 -2 ball dominant genetic model) than the section BD (rs10259514, OR = 0.706, MAF = ^{0.249, P = 4.8 × 10 -3} , ball dominant genetic model) strong connection and HLA-B is present near PSORS1C1 Bonferroni connection between BD and a healthy control group that does not include a chapter before correction (rs4959053, OR = 1.892, MAF = 0.203, P = 5.6 × 10 ^-5 , allele model). Rs1518111 the IL10 (OR = 0.717, MAF = 0.247, P = 7.5 × 10 3, the ball dominant genetic model), rs1554286 (OR = 0.789, MAF = 0.252, P = 7.3 × 10 -3, , And rs1800871 (OR = 0.730, MAF = 0.245, P = 8.9 × 10 ³ , pseudo-genetic model) were also associated with BD episodes not involving intestinal BD and intestine. There was a significant association between STAT4 and rs7574070 (OR = 1.355, MAF = 0.490, P = 4.2 × 10 ^-2 , dominant gene model) and also between BDs without BDs and BDs and healthy controls. These results are shown.

The data set of this study shows that although there is a limit to the sample size, it has sufficient strength (> 80%) to determine the association to these SNPs.

In addition, not only YIPF7 AFF1 position between genes between (rs4536897, OR = 1.478, MAF = 0.151, P = 4.0 × 10 -2, the allele model), and RPL13AP25 HNF4GP1 (rs11839457, OR = 1.775, MAF = 0.235, P = 2.0 × 10 ^-3 , dominant gene model), NAALADL2 (rs16848171, OR = 3.208, MAF = 0.248, P = 5.0 × ^10-3 , recessive gene model), PEX1 (rs32019, OR = 1.723, MAF = 0.548, P = 9.9 × 10 ^-3, recessive genetic model), PLCB1 (rs6086653, OR = 2.141, MAF = 0.293, P = 1.5 × 10 2, recessive genetic model), PRKCH (rs12433533, OR = 1.614, MAF = 0.178, P = 1.6 × 10 ^2, dominant genetic model), PSORS1C1 (rs12525170, OR = 0.595, MAF = 0.151, P = 5.9 × 10 3, the dominant genetic model), and TGFBR3 (rs284148, OR = 0.638, MAF = 0.381, P = 1.6 × 10 ² , dominant genetic model) shows a good evidence of the association (before the ferroni correction).

Haplotype analysis

In order to evaluate the better genetic linkage, we selected 11 gene positions from GWAS results and selected CAF12, ERAP1, IL10, IL23R-IL12RB2, SCHIP1, KCNJ16, NAALADL2, PLCB1, PRKCH , PSORS1C1, and TGFBR3 horseshoe-shaped and proximal SNPs from additional sites. IL10, NAALADL2, PLCB1, PRKCH, and TGFBR3 were consistently associated with intestinal BD outbreaks in repeated outcomes in haplotype analysis , although IL23R-IL12RB2, SCHIP1, and KCN did not correlate with any subtype of BD: DCAF12 CA, OR = 0.619, P = 2.4 × 10 3, Chapter BD vs. healthy controls), IL10 (GCC, OR = 0.712, P = 7.3 × 10 3, Chapter BD vs. healthy controls), NAALADL2 (TG, OR = 0.473, P = 1.7 × 10 ^2, Chapter BD vs. healthy controls; TG, OR = 0.347, P = 7.3 × 10 3, pages that do not include the chapter BD for BD), PLCB1 (CCTTG, OR = 1.465, P = 1.5 × 10 ² , BD vs. healthy control), SCHIP1 (GC, OR = 1.613, P = 3.2 × 10 ³ , BD versus healthy control), PRKCH (TG, OR = 1.587, P = 1.8 × 10 ² , BD), and TGFBR3 (CCG, OR = 1.481, P = 2.2 × 10 ² , BD versus healthy control), suggesting that these genes are potentially causative mutations affecting BD BD 4). On the other hand, PSORS1C1 is a BD-free healthy control group that does not contain BD (GGG, OR = 0.511, P = 1.5 x 10 ⁵ , BD containing no chapter; GGG, OR = 1.619, P = 9.4 x 10 ³ , BDs that do not contain BD titles), and may be negative regulators to include chapters.

Clinical phenotypes and results according to genotype

This study assessed whether the SNPs found affect the clinical signs, including systemic organ involvement, intestinal complications, and prognosis, such as surgery, hospitalization, use of corticosteroids and use of immunosuppressive agents in patients with BD. In Chang BD, NAALADL2 (rs16848171), PRKCH (rs1957895), PEX1 (rs32019), and YIPF7 (rs6838327) are associated with the development of oral ulcers and TGFBR3 (rs1805110 and rs284148) are associated with the development of genital ulcers. PRKCH (rs12433533) and IL10 (rs1518111, rs1554286, and rs1800871 ) is to include the eyes, IL23R-IL12RB2 (rs12119179 and rs1495965 ) is and HLA-F-AS1HLA-A ( rs4713242) that includes a skin arthralgia / arthritis . In relation to intestinal complications, ERAP1 (rs17482078 and rs2927615) and HLA-F-AS1HLA-A (rs4713242) are associated with intestinal perforation. ELMO1 (rs10259514) and DCAF12 (rs10758242) are associated with intestinal stenosis (Table 6). In terms of clinical outcome, AFF1 (rs4536897), NAALADL2 (rs3914501), and TGFBR3 (rs1805110 and rs17882828) are associated with high cumulative probability of surgery, while PSORS1C1 (rs12525170) and STAT4 (rs7574070) (Fig. 1). KCNJ16 (rs1013996 and rs2108440), NAALADL2 (rs16848171 and rs3914501), and COG7 (rs430208) are associated with a high cumulative probability of hospital admission. NAALADL2 (rs16848171 and rs3914501), PTPRD (rs12003392), PRKCH (rs12433533 and rs1957895), COG7 (rs430208), and IL23R (rs1495965) is associated with a high cumulative probability of the use of corticosteroids and PTPRD (rs12003392) and between RPL13AP25 and HNF4GP1 (Rs11839457) is associated with a high cumulative probability of use of immunosuppressive agents (Fig. 6), suggesting a worse prognosis.

The present study also assessed whether the SNPs found had an effect on the clinical signs of BD that did not contain a chapter. PSORS1C1 (rs12525170 and rs4959053) and IL10 (rs1554286) are associated with HLA-B51 positive, while AFF1 (rs4536897) and YIPF7 (rs6838327) are associated with the onset of genital ulcers. IL10 (rs1554286 and rs1957895) are associated with inclusion of the skin and HLA-F-AS1HLA-A (rs4713242) with vascular involvement. PSORS1C1 (rs12525170 and rs4959053) are associated with the inclusion of the central nervous system (Table 7).

Gene function analysis

To confirm the functional outcome of disease-associated SNPs, the present study explored possible functional outcomes of selected 70 SNPs, centering on eQTLs and missense. Lymphocyte subsets (LCLs) have proven to be useful model systems for the genetic control of gene expression ²³ . eQTL analysis shows significant positions associated with mRNA expression after the ferronicking: DCTN5, EARS2 and GGA2 with COG7 and rs430208 at COG7; The CAST and ERAP1 including ERAP1 rs17482078 and rs2927615; SCHIP1 to rs16830581; Rs7574070 to STAT4 and STAT4; NUDT2 and r910441723 and rs10758242 to C9orf131 and DCAF12; IL19, C1orf186 , and rs1554286 and rs1518111 to MAPKAPK2 and IL10 ; Rs1805110 to TGFBR3 and KIAA1107 ; GUF1 and GNPDA2 and YIPF7 to rs6838327 (Fig. 7). Furthermore, candidate SNPs were tested for potential regulatory functions using the Regulome DB annotated with reference to experimentally supported regulatory elements. Scores and corresponding functional evidence were recorded in Supported Information 6. Two of the three SNPs representing a relatively high level of evidence for the potential regulatory function (low RegulomeDB scores) were genome-wide, meaningful SNPs ( rs2927615 in ERAP1- ERAP2, score = 1f; rs1518111 in IL10 , score = 3a) (Rs17882828 on TGFBR3 , score = 2b).

Miss sense to YIPF7 (p.Gln92 *) for generating a mutation as well as rs192398919 rs9866564 (p.Pro622Arg) and rs144202170 (p.Arg52Gly) on chromosome 9 in the PTPRD rs17482078 (p.Arg725Gln) and NAALADL2 in ERAP1 on chromosome 5 We predicted the possibility of damage to silico analysis. In addition, rs17856199 (p.Phe45Cys) on GSTT1 on chromosome 22 was found to be very deleterious and destructive to protein structure in previous studies ²⁴ .

Significant SNPs were applied to PANOGA to identify biological pathways to genes responsive to disease susceptibility.

For additional findings, three proteins ( NAALADL2, YIPF7 , and GSTT1 ) in the colon tissues of intestinal BD patients and normal cancer tissues in intestinal cancer patients were analyzed by one or more methods There was a meaningful connection. Protein expression of NAALADL2, YIPF7, and GSTT1 decreased in the colonic tissues of IBD and BD patients compared to control tissue (Fig. 2). Other unknown mutations in the region of high LD in the locus found may alter protein expression, or regulation of protein translation and degradation ^25,26 .

Comparisons between healthy controls and patients with Jean-Bethel disease SNP MA location
(Locus) Nearby genes GWAS P
Model Cloned
a P value model Combined
(combined)
a P value model OR
(95% CI) Combined P model MAF
Healthy control MAF
Chang BD rs3914501 G Chr.3:
174564668 NAALADL2 5.7 x 10 ^-5
zeal 1.6 × 10 ^-2
zeal 3.8 × 10 ^-4
zeal 1.914 (1.338-2.738) 3.5 × 10 ^-4
zeal 0.459 0.537 rs16848171 C Chr.3:
175181067 NAALADL2 1.4 x 10 ^-5
zeal 9.2 x 10 ^-2
zeal 7.0 × 10 ^-3
zeal 2.462 (1.279 - 4.739) 5.6 x 10 ^-3
zeal 0.219 0.248 rs32019 C Chr.5:
66702373 CD180 1.8 x 10 ^-3
Bongsung 4.4 × 10 ^-2
Bongsung 4.0 × 10 ^-3
Bongsung 1.265 (1.023-1.563) 3.8 × 10 ^-3
Bongsung 0.487 0.548 rs6086653 A Chr.20:
8838343 PLCB1 3.5 × 10 ^-5
dominant 6.2 x 10 ^-1
dominant 4.3 × 10 ^-2
dominant 0.729 (0.537-0.99) 4.3 × 10 ^-2
dominant 0.312 0.293 rs284148 T Chr.1:
92277843 TGFBR3 4.8 × 10 ^-5
dominant 3.5 x 10 ^-1
dominant 1.2 × 10 ^-2
dominant 0.667 (0.486-0.916) 1.2 × 10 ^-2
dominant 0.425 0.381 rs12525170 ^* A Chr.22:
31099761 PSORS1C1 4.7 x 10 ^-2
Opposition 4.7 x 10 ^-2
Opposition 8.5 × 10 ^-2
Opposition 1.318 (0.962-1.805) 8.5 × 10 ^-2
Opposition 0.119 0.151 rs121917820 T Chr.6:
31084794 PSORS1C1 No mutation No mutation No mutation No mutation rs7742033 G Chr.6:
31085226 PSORS1C1 6.4 x 10 ^-1
Bongsung 6.4 x 10 ^-1
Bongsung 8.4 x 10 ^-1
Bongsung 1.323 (0.082-21.241) 8.4 x 10 ^-1
Bongsung 0.001 0.002 rs4959053 ^* A Chr.6:
31099577 PSORS1C1 7.6 x 10 ^-2
Opposition 7.7 x 10 ^-1
Opposition 1.2 x 10 ^-1
Opposition 1.285 (0.937-1.760) 1.2 x 10 ^-1
Opposition 0.119 0.148 rs5742906 ^* T Chr.3:
46306765 CCR-CCR3 No mutation No mutation No mutation No mutation rs10259514 G Chr.3:
36829705 ELMO1 7.7 × 10 ^-6
Opposition 1.4 x 10 ^-1
Opposition 4.8 × 10 ^-3
Opposition 0.706 (0.554-0.899) 4.8 × 10 ^-3
Opposition 0.320 0.249 rs17482078 ^* T Chr.5:
96118866 ERAP1 1.6 x 10 ^-1
zeal 9.9 x 10 ^-1
zeal 9.9 x 10 ^-1
zeal ∞
(0-∞) 2.5 x 10 ^-1
zeal 0.046 0.048 rs2927615 ^* A Chr.5:
96198202 ERAP1-ERAP2 1.6 x 10 ^-1
zeal 9.9 x 10 ^-1
zeal 9.9 x 10 ^-1
zeal ∞
(0-∞) 2.5 x 10 ^-1
zeal 0.032 0.041 rs4713242 ^* A Chr.6:
29718220 HLA-F-AS1-HLA-A 9.2 x 10 ^-1
zeal 9.2 x 10 ^-1
zeal 5.3 × 10 ^-1
zeal 1.141 (0.757-1.720) 5.3 × 10 ^-1
zeal 0.391 0.399 rs1554286 ^* G Chr.1:
206944233 IL10 4.7 x 10 ^-1
dominant 4.0 × 10 ^-3
Bongsung 2.1 x 10 ^-1
Bongsung 0.717 (0.562-0.915) 7.3 × 10 ^-3
Bongsung 0.318 0.252 rs1800871 ^* C Chr.1:
206946634 IL10 5.8 × 10 ^-3
Bongsung 2.1 x 10 ^-1
Bongsung 0.730 (0.563-0.948) 8.9 × 10 ^-3
Bongsung 0.309 0.245 rs1518111 ^* C Chr.1:
206944645 IL10 1.4 x 10 ^-5
Bongsung 5.6 x 10 ^-3
Bongsung 7.8 × 10 ^-3
Bongsung 0.717 (0.562-0.916) 7.5 × 10 ^-3
Bongsung 0.313 0.247 rs12119179 ^* C Chr.1:
67747415 IL23R-IL12RB2 8.8 × 10 ^-3
zeal 9.5 x 10 ^-1
zeal 3.3 x 10 ^-1
zeal 1.196 (0.832-1.722) 3.3 x 10 ^-1
zeal 0.478 0.489 rs1495965 ^* C Chr.1:
67753508 IL23R-IL12RB2 4.0 x 10 ^-1
zeal 1.7 x 10 ^-1
zeal 1.283 (0.901-1.828) 1.7 x 10 ^-1
zeal 0.494 0.514 rs2255336 ^* T Chr.12:
10532326 KLRC4-KLRK1 4.2 x 10 ^-1
dominant 2.7 x 10 ^-1
Bongsung 1.8 x 10 ^-1
Bongsung 0.828 (0.630-1.088) 1.8 x 10 ^-1
Bongsung 0.214 0.185 rs7574070 ^* A Chr.2:
192010488 STAT4 3.6 x 10 ^-1
dominant 8.0 x 10 ^-2
dominant 7.3 x 10 ^-2
dominant 1.370 (0.971-1.934) 7.3 x 10 ^-2
dominant 0.459 0.491 rs6838327 A Chr.4:
44626846 YIPF4 4.5 x 10 ^-3
dominant 1.2 x 10 ^-1
zeal 6.4 × 10 ^-3
zeal 1.654 (1.152-2.376) 6.2 × 10 ^-3
zeal 0.468 0.519 rs7245731 A Chr.19:
29975118 LOC284395 6.6 x 10 ^-1
dominant 9.9 x 10 ^-1
zeal 9.9 x 10 ^-1
zeal - 2.5 x 10 ^-1
zeal 0.133 0.127

A comparison between healthy controls and BD patients without bowel disease SNP MA location
(Locus) Nearby genes GWAS P
Model Cloned
a P value model Combined
(combined)
a P value model OR
(95% CI) Combined P model MAF
Healthy control MAF
BDs that do not contain chapters rs3914501 G Chr.3:
174564668 NAALADL2 8.7 x 10 ^-5
Bongsung 7.8 × 10 ^-2
Bongsung 3.4 x 10 ^-1
Bongsung 1.122 (0.886-1.422) 3.4 x 10 ^-1
Bongsung 0.459 0.487 rs16848171 C Chr.3:
175181067 NAALADL2 6.2 x 10 ^-1
zeal 4.1 x 10 ^-1
zeal 5.7 x 10 ^-1
zeal 0.768 (0.308-1.911) 5.7 x 10 ^-1
zeal 0.219 0.217 rs32019 C Chr.5:
66702373 CD180 2.4 x 10 ^-1
zeal 3.3 x 10 ^-1
zeal 3.9 x 10 ^-2
zeal 0.658 (0.442-0.98) 3.9 x 10 ^-2
zeal 0.487 0.483 rs6086653 A Chr.20:
8838343 PLCB1 2.8 x 10 ^-1
Bongsung 1.9 x 10 ^-1
Bongsung 7.9 x 10 ^-2
Bongsung 0.792 (0.610-1.028) 7.9 x 10 ^-2
Bongsung 0.312 0.266 rs284148 T Chr.1:
92277843 TGFBR3 4.4 x 10 ^-1
zeal 8.4 x 10 ^-1
zeal 3.0 x 10 ^-1
zeal 1.25 (0.823-1.897) 3.0 x 10 ^-1
zeal 0.425 0.446 rs12525170 ^* A Chr.6:
31207740 PSORS1C1 1.1 x 10 ^-3
dominant 1.3 x 10 ^-5
dominant 2.210 (1.546-3.157) 1.0 x 10 ^-5
dominant 0.119 0.212 rs121917820 T Chr.6:
31084794 PSORS1C1 No mutation No mutation No mutation rs7742033 G Chr.6:
31085226 PSORS1C1 2.0 x 10 ^-1
Bongsung 7.2 x 10 ^-1
Bongsung 1.648 (0.103-26.477) 7.2 x 10 ^-1
Bongsung 0.001 0.002 rs4959053 ^* A Chr.6:
31099577 PSORS1C1 2.2 x 10 ^-5
Opposition 7.7 x 10 ^-2
Opposition 5.6 x 10 ^-5
Opposition 1.892 (1.383-2.589) 5.6 x 10 ^-5
Opposition 0.119 0.203 rs5742906 ^* T Chr.3:
46306765 CCR-CCR3 No mutation No mutation No mutation No mutation rs10259514 G Chr.3:
36829705 ELMO1 6.8 x 10 ^-2
Bongsung 1.7 x 10 ^-2
Bongsung 1.7 x 10 ^-2
Bongsung 0.724 (0.556-0.944) 1.7 x 10 ^-2
Bongsung 0.320 0.256 rs17482078 ^* T Chr.5:
96118866 ERAP1 5.3 × 10 ^-2
Bongsung 2.1 x 10 ^-1
Bongsung 0.669 (0.358-1.251) 2.1 x 10 ^-1
Bongsung 0.046 0.032 rs2927615 ^* A Chr.5:
96198202 ERAP1-ERAP2 5.0 x 10 ^-2
Bongsung 7.5 × 10 ^-2
Bongsung 0.468 (0.199-1.100) 7.5 × 10 ^-2
Bongsung 0.032 0.016 rs4713242 ^* A Chr.6:
29718220 HLA-F-AS1-HLA-A 6.4 x 10 ^-1
dominant 5.7 x 10 ^-1
dominant 1.104 (0.788-1.548) 5.7 x 10 ^-1
dominant 0.391 0.397 rs1554286 ^* G Chr.1:
206944233 IL10 1.4 x 10 ^-1
Bongsung 5.7 x 10 ^-1
Bongsung 8.5 × 10 ^-2
Bongsung 0.801 (0.621-1.032) 8.5 × 10 ^-2
Bongsung 0.318 0.272 rs1800871 ^* C Chr.1:
206946634 IL10 4.6 × 10 ^-3
dominant 1.0 x 10 ^-1
dominant 0.806 (0.622-1.044) 1.0 x 10 ^-1
dominant 0.309 0.266 rs1518111 ^* C Chr.1:
206944645 IL10 3.2 × 10 ^-3
dominant 1.0 x 10 ^-1
dominant 0.758 (0.545-1.055) 1.0 x 10 ^-1
dominant 0.313 0.278 rs12119179 ^* C Chr.1:
67747415 IL23R-IL12RB2 1.1 x 10 ^-1
zeal 2.2 x 10 ^-1
zeal 1.0 x 10 ^-1
zeal 1.369 (0.938-2.000) 1.0 x 10 ^-1
zeal 0.478 0.515 rs1495965 ^* C Chr.1:
67753508 IL23R-IL12RB2 8.2 x 10 ^-1
zeal 2.0 x 10 ^-1
zeal 1.276 (0.877-1.855) 2.0 x 10 ^-1
zeal 0.494 0.523 rs2255336 ^* T Chr.12:
10532326 KLRC4-KLRK1 3.3 x 10 ^-1
Opposition 1.2 x 10 ^-1
Opposition 2.7 x 10 ^-1
Opposition 0.85 (0.637-1.134) 2.7 x 10 ^-1
Opposition 0.214 0.188 rs7574070 ^* A Chr.2:
192010488 STAT4 4.0 x 10 ^-1
dominant 8.7 x 10 ^-2
dominant 1.2 x 10 ^-1
dominant 1.337 (0.924-1.933) 1.2 x 10 ^-1
dominant 0.459 0.487 rs6838327 A Chr.4:
44626846 YIPF4 3.9 × 10 ^-4
dominant 3.6 x 10 ^-1
dominant 1.0 x 10 ^-2
dominant 0.630 (0.442-0.897) 1.0 x 10 ^-2
dominant 0.468 0.408 rs7245731 A Chr.19:
29975118 LOC284395 1.9 × 10 ^-9
zeal 9.9 x 10 ^-1
zeal 6.3 × 10 ^-4
zeal - 6.3 × 10 ^-4
zeal 0.133 0.1399

Comparisons were made between patients with Behcet's disease and those without Behcet's disease SNP MA location
(Locus) Nearby genes GWAS P
Model Cloned
a P value model Combined
(combined)
a P value model OR
(95% CI) Combined P model MAF
BDs that do not contain chapters MAF
Chang BD rs3914501 G Chr.3:
174564668 NAALADL2 1.1 x 10 ^-1
Opposition 1.1 x 10 ^-1
Opposition 1.1 x 10 ^-1
Opposition 1.303 (0.88-1.928) 1.1 x 10 ^-1
Opposition 0.487 0.537 rs16848171 C Chr.3:
175181067 NAALADL2 5.0 x 10 ^-3
zeal 5.0 x 10 ^-3
zeal 5.0 x 10 ^-3
zeal 3.208 (1.367-7.529) 5.0 x 10 ^-3
zeal 0.217 0.248 rs32019 C Chr.5:
66702373 CD180 9.9 × 10 ^-3
zeal 9.9 × 10 ^-3
zeal 9.9 × 10 ^-3
zeal 1.723 (1.137-2.610) 9.9 × 10 ^-3
zeal 0.483 0.548 rs6086653 A Chr.20:
8838343 PLCB1 1.5 x 10 ^-2
zeal 1.5 x 10 ^-2
zeal 1.5 x 10 ^-2
zeal 2.141 (1.144-4.007) 1.5 x 10 ^-2
zeal 0.266 0.293 rs284148 T Chr.1:
92277843 TGFBR3 1.6 × 10 ^-2
dominant 1.6 × 10 ^-2
dominant 1.6 × 10 ^-2
dominant 0.638 (0.442-0.921) 1.6 × 10 ^-2
dominant 0.446 0.381 rs12525170 ^* A Chr.22:
31099761 PSORS1C1 5.8 × 10 ^-3
dominant 5.8 × 10 ^-3
dominant 5.8 × 10 ^-3
dominant 0.595 (0.410-0.862) 5.8 × 10 ^-3
dominant 0.212 0.151 rs121917820 T Chr.6:
31084794 PSORS1C1 No mutation No mutation No mutation No mutation rs7742033 G Chr.6:
31085226 PSORS1C1 8.8 × 10 ^-1
Bongsung 8.8 × 10 ^-1
Bongsung 8.8 × 10 ^-1
Bongsung 0.801 (0.050-12.879) 8.8 × 10 ^-1
Bongsung 0.002 0.002 rs4959053 ^* A Chr.6:
31099577 PSORS1C1 1.1 × 10 ^-2
dominant 1.1 × 10 ^-2
dominant 1.1 × 10 ^-2
dominant 0.619 (0.425-0.9) 1.1 × 10 ^-2
dominant 0.204 0.148 rs5742906 ^* T Chr.3:
46306765 CCR-CCR3 No mutation No mutation No mutation No mutation rs10259514 G Chr.3:
36829705 ELMO1 5.5 × 10 ^-1 enthusiasm 5.5 × 10 ^-1 enthusiasm 5.5 × 10 ^-1 enthusiasm 1.256 (0.596-2.645) 5.5 × 10 ^-1 enthusiasm 0.256 0.250 rs17482078 ^* T Chr.5:
96118866 ERAP1 1.9 × 10 ^-1 1.9 × 10 ^-1 1.9 × 10 ^-1 1.529 (0.807-2.897) 1.9 × 10 ^-1 0.032 0.048 rs2927615 ^* A Chr.5:
96198202 ERAP1-ERAP2 1.6 × 10 ^-2
Opposition 1.6 × 10 ^-2
Opposition 1.6 × 10 ^-2
Opposition 2.744 (1.172-6.427) 1.6 × 10 ^-2
Opposition 0.016 0.041 rs4713242 ^* A Chr.6:
29718220 HLA-F-AS1-HLA-A 4.0 x 10 ^-1
zeal 4.0 x 10 ^-1
zeal 4.0 x 10 ^-1
zeal 1.227 (0.763-1.971) 4.0 x 10 ^-1
zeal 0.398 0.399 rs1554286 ^* G Chr.1:
206944233 IL10 4.2 x 10 ^-1
zeal 4.2 x 10 ^-1
zeal 4.2 x 10 ^-1
zeal 0.758 (0.381-1.505) 4.2 x 10 ^-1
zeal 0.272 0.252 rs1800871 ^* C Chr.1:
206946634 IL10 4.1 x 10 ^-1
dominant 4.1 x 10 ^-1
dominant 4.1 x 10 ^-1
dominant 0.865 (0.611-1.223) 4.1 x 10 ^-1
dominant 0.266 0.245 rs1518111 ^* C Chr.1:
206944645 IL10 4.1 × 10 ^-1 opposition 4.1 × 10 ^-1 opposition 4.1 x 10 ^-1
Opposition 0.889 (0.669-1.18) 4.1 × 10 ^-1 opposition 0.269 0.247 rs12119179 ^* C Chr.1:
67747415 IL23R-IL12RB2 4.1 x 10 ^-1
Bongsung 4.1 x 10 ^-1
Bongsung 4.1 x 10 ^-1
Bongsung 0.902 (0.705-1.154) 4.1 x 10 ^-1
Bongsung 0.5150 0.489 rs1495965 ^* C Chr.1:
67753508 IL23R-IL12RB2 5.9 x 10 ^-1
dominant 5.9 x 10 ^-1
dominant 5.9 x 10 ^-1
dominant 0.894 (0.593-1.347) 5.9 x 10 ^-1
dominant 0.521 0.514 rs2255336 ^* T Chr.12:
10532326 KLRC4-KLRK1 6.6 x 10 ^-1
zeal 6.6 x 10 ^-1
zeal 6.6 x 10 ^-1
zeal 0.801 (0.296-2.169) 6.6 x 10 ^-1
zeal 0.188 0.185 rs7574070 ^* A Chr.2:
192010488 STAT4 8.9 x 10 ^-1
Bongsung 8.9 x 10 ^-1
Bongsung 8.9 x 10 ^-1
Bongsung 1.025 (0.685-1.535) 8.9 x 10 ^-1
Bongsung 0.491 0.487 rs6838327 A Chr.4:
44626846 YIPF4 3.4 × 10 ^-4
Opposition 3.4 × 10 ^-4
Opposition 3.4 × 10 ^-4
Opposition 1.567 (1.225-2.005) 3.4 × 10 ^-4
Opposition 0.408 0.519 rs7245731 A Chr.19:
29975118 LOC284395 1.4 x 10 ^-2
zeal 1.4 x 10 ^-2
zeal 1.4 x 10 ^-2
zeal 0.113 (0.014-0.925 1.4 x 10 ^-2
zeal 0.139 0.127

Analysis of haplotypes of susceptibility genes to Behcet's disease without Jean-Bethel's disease and intestine Closest gene Haplotype Combined P model OR (95% CI) Long BD (n = 295) versus healthy control (n = 391) DCAF12 C - A
TG 2.4 × 10 ^-3 dominant
5.4 x 10 ^-3 enthusiasm 0.619 (0.454-0.843)
1.55 (1.138-2.111) IL10 ATT
G - C - C 1.2 × 10 ^-2
7.3 × 10 ^-3 1.374 (1.073-1.76)
0.712 (0.555-0.913) NAALADL2 C - G
TC
TG 5.5 x 10 ^-2 enthusiasm
6.4 × 10 ^-1 dominant
1.7 × 10 ^-2 dominant 2.079 (0.985-4.388)
1.137 (0.66-1.961)
0.473 (0.255-0.876) PLCB1 CCTTG
G - T - C - C - A 1.5 x 10 ^-3 enthusiasm
9.1 × 10 ^-2 dominant 1.465 (1.077-1.993)
0.768 (0.565-1.044) SCHIP1 CT
G - C 7.3 x 10 ^-3 enthusiasm
3.2 × 10 ^-3 dominant 0.649 (0.473-0.890)
1.613 (1.174-2.217) TGFBR3 CCG
CT- A 2.2 x 10 ^-3 enthusiasm
1.4 × 10 ^-3 dominant 1.481 (1.059-2.070)
0.793 (0.582-1.080) Bd (n = 264) versus healthy control (n = 391) PSORS1C1 G- A - A
GGG

A - A
GG 2.4 × 10 ^-5 confrontation
1.5 × 10 ^-5 opposition
3.7 × 10 ^-5 Confrontation
2.1 × 10 ^-5 Confrontation 1.935 (1.424-2.628)
0.511 (0.377-0.693)

1.917 (1.412-2.602)
0.515 (0.380-0.699) BD (n = 264) that does not include a chapter BD (n = 295) NAALADL2 C- G
T- C
TG 1.7 x 10 ^-2 enthusiasm
4.1 × 10 ^-1 dominant
7.3 × 10 ^-3 dominant 3.401 (1.245-9.296)
0.791 (0.453-1.382)
0.347 (0.16-0.751) PSORS1C1 G- A - A
GGG

A - A
GG 9.7 × 10 ^-3 dominant
9.4 × 10 ^-3 enthusiasm
9.7 × 10 ^-3 dominant
9.6 x 10 ^-3 enthusiasm 0.617 (0.428-0.889)
1.619 (1.125-2.329)

0.617 (0.428-0.889)
1.62 (1.125-2.333)

Clinical and demographic characteristics of patients with Behcet's disease without Jean-Bethel's disease and intestinal disease BDs that do not contain chapters
(n = 238) Chang BD
(n = 295) male(%)
Average age (years)
Average age of diagnosis (years)
Average disease duration (years)
HLA-B51 positive (%)
Clinical characteristics (%)
Oral ulcer
Genital ulcer
Eye disorder
Skin disorder
Arthritis / joint pain
Vascular disorder
Central nervous system disorders
Epididymitis
Intestinal complications
boring
Fist
stricture
boil
Drug use
5-Aminosalicylic acid / Sulfasalazine
Corticosteroid
Azathiopurine / 6-mercaptopurine
Anti-TNF agent
62 (26.1)
41.8 ± 11.8
NA
NA
83 (36.7)

238 (100)
212 (89.1)
76 (31.9)
219 (92.0)
134 (56.3)
10 (4.2)
5 (2.1)
3 (1.3)

NA
NA
NA
NA

NA
NA
NA
NA 135 (45.8)
44.3 + - 12.3
40.1 ± 11.8
7.5 ± 5.7
NA

273 (92.5)
154 (52.2)
52 (17.6)
192 (65.1)
158 (53.6)
11 (3.7)
5 (1.7)
0

28 (9.5)
26 (8.8)
25 (8.5)
13 (4.4)

288 (97.6)
136 (46.1)
107 (36.3)
8 (2.7)

Intestinal complications according to SNP genotype in patients with Jejuredecet disease Phenotype Gene and
rs number Genotype
Or opposition Phenotype
A patient Phenotype
A patient without aOR (95% CI) P value boring






Fist



stricture
ERAP1
rs17482078
ERAP1
rs2927615
HLA-F-AS1-HLA-A
rs4713242
ELMO1
rs10259514
DCAF12
rs10758242
TGFBR3
rs1805110
TGFBR3
rs284148
dominant

dominant

Opposition

Opposition

dominant

dominant

Opposition CC
CT / TT
GG
GA / AA
A
G
G
A
GG
AG / AA
GG
GA / AA
T
C 20 (76.9)
6 (23.1)
20 (76.9)
6 (23.1)
14 (26.9)
38 (73.1)
19 (39.58)
29 (60.42)
19 (79.2)
5 (20.8)
4 (16.0)
21 (84.0)
26 (59.1)
18 (40.9) 244 (92.1)
21 (7.9)
246 (93.5)
17 (6.5)
218 (41.3)
310 (58.7)
123 (23.65)
397 (76.35)
142 (55.7)
113 (44.3)
101 (37.7)
167 (62.3)
192 (36.5)
334 (63.5)
3.49 (1.26-9.62)

4.34 (1.54-12.24)

0.52 (0.28-0.99)

2.12 (1.15-3.90)

0.33 (0.12-0.91)

3.17 (1.06-9.51)

2.51 (1.34-4.70)
0.016

0.05

0.047

0.017

0.033

0.039

0.004

Clinical symptoms according to SNP genotype in patients with Behcet's disease without intestine Phenotype Gene and
rs number Genotype
Or opposition Phenotype
A patient Phenotype
A patient without aOR (95% CI) P value HLA-B51 positive





Genital ulcer



Skin disorder



Central nervous system disorders PSORS1C1
rs12525170
PSORS1C1
rs4959053
IL10
rs1554286
AFF1
rs4536897
YIPF7
rs6838327
IL10
rs1554286

IL10
rs1957895
PSORS1C1
rs12525170
PSORS1C1
rs4959053
dominant

dominant

dominant

Opposition

Opposition

Bongsung


dominant

zeal

zeal GG
AG / AA
GG
AG / AA
AA
GA / GG
G
A
A
G
AA
GA
GG
TT
GT / GG
GG / AG
AA
GG / AG
AA 11 (13.6)
70 (86.4)
11 (11.9)
68 (86.1)
37 (44.6)
46 (55.4)
40 (9.8)
370 (90.2)
177 (42.6)
239 (57.5)
120 (54.8)
84 (38.4)
15 (6.9)
79 (36.1)
140 (63.9)
3 (60.0)
2 (40.0)
3 (60.0)
2 (40.0) 127 (90.1)
14 (9.9)
128 (90.8)
13 (9.2)
81 (57.0)
61 (43.0)
9 (19.6)
37 (80.4)
13 (56.0)
37 (74.0)
6 (33.3)
9 (50.0)
3 (16.7)
13 (72.2)
5 (27.8)
221 (96.5)
8 (3.5)
218 (96.5)
8 (3.5) 56.39 (24.22-131.32)

59.53 (25.26-140.30)

1.75 (1.00-3.05)

0.42 (0.19-0.96)

2.11 (1.08-4.11)

0.47 (0.23-0.99)


4.82 (1.63-14.23)

23.23 (3.05-176.79)

22.91 (3.02-174.09)
&Lt; 0.0O1

<0.001

0.048

0.039

0.029

0.049


0.004

0.002

0.002

references

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13. Moll JM, Haslock I, Macrae IF, et al. Associations between ankylosing spondylitis, psoriatic arthritis, Reiter's disease, intestinal arthropathies, and Behcet's syndrome. Medicine (Baltimore) 1974; 53: 343-64.

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<110> Industry-Academic Cooperation Foundation, Younsei University <120> Biomarkers for Diagnosing Intestinal Behcet's Disease and Uses          Thereof <130> PN150119 <160> 7 <170> Kopatentin 2.0 <210> 1 <211> 1001 <212> DNA <213> Homo sapiens <400> 1 aggcatttta taatatcatt ttatagagca gatattcctc tttaaatttg gaacttatgt 60 tggttggttg tggccaagaa atcccaggtt ggggtttttt gatcatgcat gcttaatact 120 tgtgagttct ccaagaaata agatatatag gtaaactagg aaagtagggg aaaggtatac 180 acatataaga aatatgggta gagataaatt aaacaagatt cttttgtgct taggtatact 240 ggcccaacat attgtatttt ctctcttctg gatctcagtg ataccattaa cccagctgct 300 agagacagaa acttagaatt tatctttgtt tccaccaaca cattttccag agagtcacca 360 ggtttgataa attctgtgtc ctaactgtca ttgaactcta tcgcctaaac tttccatttc 420 ctctaggtga ggccattttc atctcttgcc tggagaacaa ttccctaaat acagtctttc 480 ttctctctca tctatggtct yatatctcct atagtggtct tcctaaaaca tagcaatcat 540 gccagttcca tgctcacata cgttcaatgg ccccacagcc tgcccaataa tgtcaacatg 600 ttaccagcaa aattttttat cctgctgact ccaaaccctt cattaacatt taactcattt 660 aactcctctg taaaggcttc tctgatgtcc ccaagtgtac ttaatattag aaatctaaga 720 atatatcata catacataat catatttatt tttctatatg tttgtttttt aaaagtcaaa 780 aaaacattga ggcctactca gaactttgca ctgggattga caaaagtatc ctgtagatac 840 tactaactaa acttttaatt ctcttattac ttttttatta tgtggcatac aaaattttaa 900 gaaaattgac attgttagag aacaaggaaa ataactgttt cagagagcta gagtgatgtc 960 agcaagaggc taactagact tatttggctc tcatcccctg a 1001 <210> 2 <211> 1001 <212> DNA <213> homo sapiens <400> 2 ataaacagaa aaattcaaaa aggtagagcg attagtacag atttagaata gaggtaaggg 60 acctacaaac tcagaaataa aaactctaat atatgaaaac atgtacagct ttaagaatat 120 ttatcctttt atgttgtata atgctttatt tatcattttt aaagtgttaa taaaatagtg 180 agtcatactg gaaaggttat tgtccacatg ttctttatct gaaaatagaa aagcattcaa 240 tattctttgg aaatatttta atctattttt ttctgttttt aaaaatatga gttccccaca 300 tctcctgaag gtcttctcaa tgctctcatg atgaacactc attgtagaac tcaatgtaag 360 gtttagaagt gtctatttat ggctctgagg ttcaaagagg ctagcaattg tatcttagtc 420 atcactgcgt aacaaacacc taaaatagaa tctgtacaaa gtattgaata aatatttgtc 480 ggaaaaagta taactggcta yctgagaaca ttcaattctg tggaattctt ttgctgatga 540 tattggataa aataaatttt aagattaaa aaatacaata aaatataaag aagcaaaagt 600 ctttaaattt ttattttttc agaaataaga gtcgtcagca tgcaagttca gacagtcaca 660 aaattgaaaa cagttactaa tgttgttgga tttgtaatgg gcttgacatc tccaggtaag 720 tagggttgaa aatttataat ctacacttta tatgaaacta tacaaggaaa tgctctgtaa 780 taatttaata ttatacttaa atatcctact tgagatataa ctagaaattt gtcccactct 840 tagagtagat aaatttgaaa ctaagaagtg ggtcttcctt ctctttccta ccgtatctct 900 tctaaaataa atcttagtcg ggggagagag agagagagag agagagagag agagagaggt 960 ggggatctct caggaggaga tgaaacaaga aacagagttt a 1001 <210> 3 <211> 1001 <212> DNA <213> homo sapiens <400> 3 gctgggatta caagcatgag ccactgcgcc tggccaaaaa gtgtcagttt taaagataac 60 ttggattaat ttatttttta agtaattgaa gtaagaacag cacctgggcc aaaactaacc 120 tacttttctt aatctatgag tagcttttaa tagccatggt tttcccagtt ccactaccaa 180 aacaatcagg aagggctcaa ctttttcatg gctgtggcaa accttggcta tgattgtgca 240 tgtggggtca ttgagagcac acagacactt actgcagtga aaagaacatg gcgcaaccag 300 acaggatgac catggggagc aggcagtaac ccagcacgct ggccacacag ccgtacgaca 360 cccctgaaga gctcatcagg ttcagcaagg catgaatcac aaggcagcca atggcactca 420 tgccatacac ataaccaaac tgaacttttc ctgcctgaaa cgacgtgaag aaaaaacagt 480 ttgaacacac aatggacacc ragaggaaat ctgaatatca tgaagcagag agcatcttag 540 agtcagttca gtgctgttcc atgtctttgt aggactgtca tcaggagact ggaagttctg 600 ggaaaaacat ggccaatggt ttgaattcag attctgaaaa caaacacttc tgactagagt 660 taggatggga taagcgtgct acaaaaaaga ttgaatattt ctagacttat attttttact 720 ctaaattgtc cattacgagt acaaggcata agtaagacta tattttgttc ccatatttat 780 taaacaaata agtgattgaa cagaggaata aaaaatccaa ttttagtctt ggagatttac 840 aaggcatatt agtaaaatta gcaaacacct acagggttta ccatgtcaga tcccattcta 900 agtgtgctac atatatttat gtaatccaca taacaacctt atgaaatcag tatcattatt 960 acaccaactt tacacatgag gaaactgagg tgcagagatg a 1001 <210> 4 <211> 1549 <212> DNA <213> homo sapiens <400> 4 aaaagcaacc agtggtatgc agatttgatg atcacttcct ccagtatcaa ttcagtcatg 60 gttctgagct ttactttttg cttttttaag tcttagcact aatattacag tttatctgtg 120 tattattgta agagaaaata ttttcctttg atctagtgtg attttacaaa aattggtatc 180 taaaaattcc tcagaatact yctaaattac cacaaacttg gtgggttgtt ttttgttgtt 240 ttttttgaga cggagccttg ctctgtcgcc taggctggag tgcagtggca cgatctcagc 300 tcactgcaac ctccatctct caggttcaag caattctcct gcctcagcct cccgagtagt 360 tgggactata ggtgcatgcc actacgcccg gccaattttt tgtattttta gtagagacgg 420 ggtttcacca tattggtcag gctggtctcg aactcctgag ctcaggcgat ccacccgcct 480 cagcctccca gagtgctggg attagaggca tgagccactg tgcccagcct aacttggtgg 540 gttttaaaac aacagagtca ttctctcata gttttggagt ccagaactct gaaaacaaga 600 cgccaatctc atgcaatgct ctttctcgag gcccaagggg agaatttttt ttttgagacg 660 gagtctcact ctgttgccca ggctggagtg caatggtgtg gtctcggctt tctgcaacct 720 ctgcctcctg ggttcaagcg attctcttgc ctcagcttcc tgagtagctg agattatagg 780 agcacaccac cacgcccggc taatttttgt attttttggt agaggtgggg tttcgccatg 840 ttggccaggc tggtctcaaa ctcctgacct cagatgatct gcccacctcg gcctcccaaa 900 gtgctgggat tacaggtgtg agcagccacg cctagcctat tattattttt tgagacaggg 960 tcttgctctg tcacccaggt tggagtgcag tggcgcaatc atagttcaca gcagcctcaa 1020 actcctgggc tcaaacagtc ttcctgtgca ccatcatgcc tggctaagtt ttcaattttg 1080 tgtagagacc aggtcttgct atattgccca ggctgatctt gagctcctag tatcatgcaa 1140 tctttctgcc ttggcctccc aaagtgctgg gattacaggc atgagccact gcgcctggcc 1200 agtttctttc tttttttttt tttttttgag acagggtcct gctctgttgc ccaggctgga 1260 gtgcagtggc acaatcctgg cgcgctgcag ccttaaactc ctgggctcac gtgatcttcc 1320 tgtctctgcc tcccaagtac ctgggactat aggtgggcat caccatgcaa ggctaattaa 1380 ttatgtgtag aaatggggtc tcactatgtt ggccagattg gtctcaaatt cctggcttca 1440 ggcaatccac cccagcctcc caaagtgttg ggattacagg tgtaagccac tgcacccagc 1500 tcagtttatt ttaaggtatg agttgatcat ctgttttctt cctgtccat 1549 <210> 5 <211> 1001 <212> DNA <213> homo sapiens <400> 5 gagaacaact cagcactgca acagtatcac ttttgtcata tcctattgac aaaacaagtc 60 acaaaagagg agtgaagaat ggtgggtttt tgaaaactca atctaccaca cttctcttat 120 gtgaacttct ctctgtgtac taatgaaaaa aatttaaata aagtatatct aagtataagg 180 tatctatatt gttaaatgtt gctatagttt attttgactt attctattcc atgaatgtat 240 cgcacttatc cattctactg tcagtttgca tttagtgatg tccagttgat tgctgtttta 300 agcagatctg ctgtgaacat gccatctcat atctcctagt atgcaaactc tgtaccagaa 360 gttttcttgg ttgtatacca aactgtggaa ttactgggcc atagggaata tgaatcttcc 420 attttacatg atgatgctaa attgtcttct gaagtaacta taccacttta cactttcttc 480 agcaatatat gaaagactgt rttaccctga cacttgccaa tagttgatat taacgtcaga 540 cttcctaata tttcctacta agatgagtat gaaatgatat ctcaatgtgg tctagatctg 600 cctttttctg atcagtgaag aaactgacca tcccttctat ttagtttgtt tttgttttgc 660 ctttagccac atgttccttc ttaagcaaaa tgcctctttg tatcttttgg taattttttt 720 caattgagtg attggtcttc tcattacttc ataacaattc tttatatatt ctcaatacta 780 ttcttttgtc agatgtgttt gttgtgaaaa tatttgccca gtttatcact tgcttctcac 840 cttattgagg gtgtcatttg aataagtttc ataattttaa gtatttgaat taaattttta 900 tttaattttt attgttagct ttacttgagg cctatttagc caatccttaa ctaccccagg 960 atctgaaata gattaaaggt ttagcagtca aaacataaac t 1001 <210> 6 <211> 1001 <212> DNA <213> homo sapiens <400> 6 agtacttgtt attccaaaag taaacaaggt agaccacaac tctgcatatt gaataatgcc 60 cattaaattc aaattaaaag ctaacttcat tattttacaa aatcacaaga ttatccattt 120 tccttacttt ttcaagtact gtgcttatct tgtgtcattt aacgtataag cattctgcaa 180 cgtgggaaag agactatcag tcaaaaatat tgaacaccta ccatatgcag aaatttgggg 240 gaataaaaac taaagtagac aaaaatcctg cctccaagga tctaacactc tcgtttgagg 300 gaacaaaggc tggaatgaga atatttaact aaatattgat acaccttgat acccctctaa 360 ctgatccctg aaacacagct atacaagcat cccccagaag taaggcagag aacatctgct 420 ttaccaaaca catacaaaca agttgccttg attttatttc ctattttatc taataaatca 480 ttattccagc gggaagaaaa sgtcaatgta gttgttttca cttttagaaa ttcttaagaa 540 ggcaacacaa tccatgtaag ccacagttgg agaagccacg gctctggcac aaacctgaga 600 aaaaccctcc ttcaattaag aacacctcct cccccaggct tgaccctctg atcaggctta 660 tctaaaacaa ggcaggctgc ctattacact caccaacata tccaagctcc ttggggagcc 720 aactagccaa aaagtgctta tcacatcgac tcctgcaaga acagtgggta gaatcttgcc 780 ttatatccta caaaaaagac aactcaaaag gttcttctca gaacaaaatg ataggttact 840 ctcagaataa attccatttt acatgctaga atggatagac tgcttgcaac cttcagaatg 900 accattgtag tctttcaatc gtctacacat tctacctcta ccaggcaccc tctgcgtgta 960 ttggtatctc ctctggcagg agtgcggaga atggattgtg c 1001 <210> 7 <211> 1001 <212> DNA <213> homo sapiens <400> 7 tgagtggatt tatattttac ttttacgtgc gggtgggggg catggcatgt gtggacatac 60 ccatggtaag cagcagccag gttgcaaggg agaggttcat tttgaggcag ttgcagagtt 120 ccaagtaaca agataatgag gacctgaact aagacagtga tggtagggct gatgagaaag 180 gcataagaga taatagcaag taaagctgat aggacttagt atttgggtgg attcagggta 240 aaaaagaaac cggaaatcat ttccaggtgt ttagctagaa ggttgagtgg atggcagtgc 300 cattagctag gagagatcat gtgcctagga agaagtctag gcaaaagagg aagaagtttt 360 agaaaggttg tatgacaggt gcctgaggta tactccagtg gagatgctcc atggataggg 420 gcataggagt ctgaagctca gtaaagagga tgggctgaat taaatatttg gaagtcatca 480 ggacatagct attagttgag rccacgagac tgaatgagat cacccaatag gagtctctta 540 aatggaacag tgtgagtcaa ggacagaacc ctggggaacc agactccatt agaaatctgc 600 ctaaatttgg ctccagggtt atagaaacaa ttggtatgtt catcatttag agtaagtatc 660 cccaaagtgc cagtgtatta aaaatataat tccataaaag tatagaaaaa gatcacttac 720 tttagagtat gtgtgtgacg ctacatatat tcttcctact gaaagaatgc tggacatggt 780 tttcagaagc cctgcatgct agacccagcc ctggtcctgg ggatgtgggc aggttgctga 840 atgcccctag ccctttggcc catctgtaca gtggaggtgc cattgacaca gcttcccagc 900 agggtccttg taaaactcaa atcagatgga agtggaaatg cgaatgcttt ttggaacatg 960 ccgtgtcaat ataagaggtt atctttgcat atgtgctgtc a 1001

Claims (8)

10-100 consecutive nucleotide sequences containing a single nucleotide polymorphism (SNP) site of NAALADL2 (N-acetylated alpha-linked acidic dipeptidase-like 2) gene at position 501 of Sequence Listing 1 (GenBank SNP database rs3914501) A kit for diagnosing or predicting the risk of a Jeff-Bethel disease comprising a specifically binding primer or a probe.
The kit according to claim 1, wherein the kit is a single nucleotide polymorphism (SNP) region of an N-acetylated alpha-linked acidic dipeptidase-like 2 (NAALADL2) gene at position 501 of the Sequence Listing (GenBank SNP database rs16848171) (GenBank SNP database rs6838327), DCAF12 (DDB1 and CUL4 associated factor 12) genes of the Yip1 domain family member 7 gene as a single nucleotide polymorphic site of the Yip1 domain family member 7 gene, (GenBank SNP database rs10441723), the PLCB1 (phospholipase C, beta 1) gene as a single nucleotide polymorphic site at position 501 (GenBank SNP database rs6086653), SCHIP1 (schwannomin interacting protein 1 (GenBank SNP database rs16830581) and the PRKCH (protein kinase C, eta) gene as the single nucleotide polymorphic site of the gene A primer or a probe that specifically binds to 10-100 consecutive nucleotide sequences comprising a single nucleotide polymorphic site of a gene selected from the group consisting of the nucleotide polymorphism site, the 501st position of SEQ ID NO: 7 (GenBank SNP database rs12433533) Wherein the kit further comprises a kit for diagnosing or predicting risk of Jean-Behcet's disease.
3. The method according to claim 2, wherein the single nucleotide polymorphism (SNP) region of the N-acetylated alpha-linked acidic dipeptidase-like 2 (NAALADL2) gene is at position 501 of the Sequence Listing (GenBank SNP database rs16848171) Yip1 domain family member 7) gene as a single nucleotide polymorphic site of the Yip1 domain family, member 7), which specifically binds to 10-100 consecutive nucleotide sequences comprising a single nucleotide polymorphic site at the 501 th position of the Sequence Listing 3 (GenBank SNP database rs6838327) Wherein the primer or the probe is used for simultaneous prediction of the risk of Jejobetz disease and oral ulcer.
3. The method according to claim 2, wherein the single nucleotide polymorphism site of the PRKCH (protein kinase C, eta) gene is 10-100 consecutive sequences comprising a single nucleotide polymorphic site at position 501 of Sequence Listing 7 (GenBank SNP database rs12433533) Wherein the primer or probe specifically binding to the nucleotide sequence is used for simultaneous prediction of the risk of Jean-Bertheth &lt; / RTI &gt;
(NAALADL2) gene of the 501st position (GenBank SNP database rs3914501) of the first sequence of the sequence listing in human biological samples in order to provide information necessary for the diagnosis of Jejobetich's disease Detecting the presence of 10-100 consecutive nucleotide sequences comprising a single nucleotide polymorphism (SNP) site.
6. The method according to claim 5, wherein the method is a single base polymorphism (SNP) region of an N-acetylated alpha-linked acidic dipeptidase-like 2 (NAALADL2) gene at position 501 of the Sequence Listing (GenBank SNP database rs16848171) (GenBank SNP database rs6838327), DCAF12 (DDB1 and CUL4 associated factor 12) genes of the Yip1 domain family member 7 gene as a single nucleotide polymorphic site of the Yip1 domain family member 7 gene, (GenBank SNP database rs10441723), the PLCB1 (phospholipase C, beta 1) gene as a single nucleotide polymorphic site at position 501 (GenBank SNP database rs6086653), SCHIP1 (schwannomin interacting protein 1 (GenBank SNP database rs16830581) and the PRKCH (protein kinase C, eta) gene as the single nucleotide polymorphic site of the gene Further comprising the step of detecting the presence of 10-100 contiguous nucleotide sequences comprising a single nucleotide polymorphic site of a gene selected from the group consisting of the nucleotide polymorphism site and the 501st position of SEQ ID NO: 7 sequence (GenBank SNP database rs12433533) A method for detecting a Jeff-Bethel disease marker.
6. The method according to claim 5, wherein the biological sample is blood, plasma, serum, tissue, cells, lymph, bone marrow fluid, saliva, ocular fluid, multiple fluid, cell tissue fluid or cell culture fluid.
6. The method of claim 5, wherein the detection of the presence of the single nucleotide polymorphic site is performed through a gene amplification reaction, a microarray, or sequencing.

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