KR20130100640A - Snp markers for abdominal obesity and use thereof - Google Patents

Abstract

PURPOSE: A single nucleotide polymorphism (SNP) marker which is specific to the type of Sasang constitutional medicine is provided to accurately and objectively diagnose and predict the risk of abdominal obesity. CONSTITUTION: An SNP for predicting or diagnosing Sasang constitutional type-specific abdominal obesity contains one or more polynucleotides selected among polynucleotides having 5-100 continuous bases with 101th base in polynucleotides of sequence numbers 1-28, or complementary polynucleotides thereof. A composition for predicting or diagnosing Sasang constitutional type-specific abdominal obesity contains a probe for detecting the SNP marker or an agent for amplifying the SNP marker. A kit for predicting or diagnosing Sasang constitutional type-specific abdominal obesity contains the composition. [Reference numerals] (AA) Cardiovascular metabolic disease; (BB) Obesity & diabetes; (CC) Hyperlipidemia & hypertension; (DD) Osteoporosis; (EE) Blood corpuscle disorder; (FF) GWAS(genome-wide association) SNP selecting; (GG) R^2 among SNPs < 0.80 (strong linkage SNPs excluding); (HH) Minor allele frequency >= 0.05; (II) Prior to Affymetrix SNP; (JJ) Analyze correlation between each SNP per each physical condition; (KK) Object: physical condition determined object; (LL) Analyze correlation with abdominal obesity; (MM) Exclude non-specific physical condition SNP; (NN) Duplicated correlation between physical conditions; (OO) Contradiction correlation within physical conditions; (PP) Establish physical condition-specific SNP set; (QQ) Establish specific SNP of each physical condition; (RR) Combination correlation with abdominal obesity

Description

SNP markers for abdominal obesity prediction and their use {SNP markers for abdominal obesity and use about}

The present invention relates to a single nucleotide polymorphism (SNP) marker for predicting or diagnosing filamentous specific abdominal obesity. A composition comprising, a kit or microarray comprising the composition, a method for providing information for predicting or diagnosing filamentous specific abdominal obesity using the marker, and a method for selecting a SNP for predicting or diagnosing filamentous specific abdominal obesity will be.

The main risk predictors of cardiovascular metabolic diseases such as hypertension, hyperlipidemia, stroke and diabetes that threaten the health of modern people are associated with waist circumference (WC) or waist-hip ratio (WHR). Phenotype associated with the same abdominal obesity. Therefore, if the risk for abdominal obesity can be measured in advance, it is expected that the cardiovascular disease can be effectively prevented. Therefore, many studies are being conducted to measure the risk in advance.

Sasang constitution categorizes people into four constitutions: Sunin, Taeinin, Soyangin, and Soinin. These four constitutions are known not only for their responsiveness to drugs but also for their appearance, body type, personality, cog function, and diet. . In addition, the incidence rate for cardiovascular metabolic disease is also different, and compared to the other three constitutions except for the very few sun persons, it is known that the incidence is higher in order of noise, Soyangin, and Taeinin. As such, one of the main causes of different incidences depending on the constitution is that the difference in diet and activity varies by constitution. That is, Taeumin generally eats a lot but has a small amount of activity, while Soyin eats at least a small amount of activity, while Soyangin eats a lot of activity, as mentioned above.

However, in addition to these environmental factors, genetic differences by constitution are thought to be another factor for the difference in disease incidence. Because ideological constitution is inherently determined that it is accepted that the constitution does not change throughout life. In other words, because the constitution determined at birth does not change throughout life, constitution and genetic differences are highly related. Individual genetic differences have been shown to influence the development of cardiovascular metabolic disease in population genetic studies. Similarly, genetic differences between constitutions are expected to affect disease differences.

Genetic group association studies in personalized medicine are known to be effective in identifying genetic disease susceptibility by conducting group association studies separately by race because of the unique differences among the three races of yellow, white and black. This is because the dietary culture and genetic tendencies (reflected in body type, appearance, physiology, etc.) are different for each race, so it is difficult to statistically separate the above-mentioned differences between actual disease susceptibility and race. Similarly, if a person's genetic predisposition is different for each constitution, conducting a constitutional analysis of constitution groups, even within a race, would be more effective in identifying the genetic susceptibility of the disease.

Recent genome-wide association studies (GWAS) have been associated with obesity, hypertension, and hyperlipidemia-related phenotypes such as body mass index (BMI), WC, WHR, blood pressure, and lipid levels (triglyceride, cholesterol). A number of SNPs (single nucleotide polymorphisms) have been identified, and a number of subsequent SNPs have been published to assure reproducibility of associations. These studies have also been conducted with whites, yellows, and blacks. However, constitution-specific group studies have yet to be done with these cardiovascular diseases. So far, the genetics of predicting cardiovascular metabolic diseases that are clearly related to filamentous constitution have not been identified by using the filamentous heredity.

There are several phenotypes associated with each cardiovascular disease, as listed above, but one of the major risk factors common to many cardiovascular diseases is the abdominal phenotype. This marker is known to be more effective in predicting cardiovascular metabolism than BMI.

Against this backdrop, the present inventors have tried to find markers that can accurately predict the incidence of abdominal obesity. The study was conducted with GWAS SNP. The present inventors have identified a set of abdominal obesity-specific SNPs among the GWAS SNPs related to four diseases of obesity, hyperlipidemia, hypertension, and hematopoiesis, targeting abdominal obesity and related phenotypes, which are the major predictors of cardiovascular metabolic disease.

One object of the present invention is to provide a single nucleotide polymorphism (SNP) marker for predicting or diagnosing filamentous constitution specific abdominal obesity.

Another object of the present invention is to provide a composition for predicting or diagnosing filamentous constitution specific abdominal obesity, comprising a probe capable of detecting or predicting a filamentous specific abdominal obesity predictive or diagnostic SNP marker. .

It is another object of the present invention to provide a kit or microarray for filamentous constitution specific abdominal obesity prediction or diagnosis comprising the filamentous specific abdominal obesity prediction or diagnostic composition.

It is another object of the present invention to provide a method for providing information for predicting or diagnosing filamentous constitution specific abdominal obesity, comprising determining a polymorphic site of the SNP marker.

It is another object of the present invention to provide a method for selecting SNP markers for predicting or diagnosing filamentous constitution specific abdominal obesity.

As one aspect for achieving the above object, the present invention provides a single nucleotide polymorphism (SNP) marker that is a monobasic polymorphism for predicting or diagnosing filamentous constitution specific abdominal obesity.

Preferably at least one polynucleotide selected from the polynucleotides consisting of SEQ ID NOs: 1 to 28, comprising a 101 base of each sequence in the SNP position and consisting of 5 to 100 consecutive bases, or It may be a single nucleotide polymorphism (SNP) marker for predicting or diagnosing filamentous specific abdominal obesity, including complementary polynucleotides.

In the present invention, the term "polymorphism" refers to a case where two or more alleles exist in one locus. Of the polymorphic sites, only a single base differs from a polymorphism region to a single base polymorphism (single nucleotide polymorphism, SNP). Preferred polymorphic markers have two or more alleles with a frequency of occurrence of 1% or more, more preferably 5% or 10% or more in the selected population.

The term "allele " in the present invention refers to various types of genes that exist on the same locus of a homologous chromosome. Alleles are also used to represent polymorphisms, for example, SNPs have two kinds of bialles.

In the present invention, the term "rs_id" refers to rs-ID, which is an independent marker assigned to all SNPs initially registered by NCBI, which began accumulating SNP information since 1998. In the present invention, it is described in the form of rs6265. Rs_id described in such a table means an SNP marker which is a polymorphic marker of the present invention. Those skilled in the art will be able to easily identify the position and sequence of the SNP using the rs_id. The specific sequence corresponding to the NCBI's The Single Nucleotide Polymorphism Database (rS_id) number, rs_id, may change slightly over time. It will be apparent to those skilled in the art that the scope of the present invention also applies to such altered sequences.

"SEQ ID NOS 1 to 28" is a polymorphic sequence including a polymorphic site. A polymorphic sequence means a sequence comprising a polymorphic site comprising a SNP in a polynucleotide sequence. The polynucleotide sequence may be DNA or RNA.

SNP marker of the present invention is a marker shown in Table 2, when the polymorphic site of the individual SNP marker is an allele indicated as an effect allele, the risk of abdominal obesity is determined to be high or high risk of abdominal obesity You can do it. In the present invention, "effect allele" may be used interchangeably with "danger allele."

In the present invention, the term "ideological constitution" refers to the classification of the human constitution by the ideology of the sun, Soyangin, Taeumin, and Soinin four constitutions are congenital and do not change over a lifetime biologically genetic characteristics It can be seen as having. Since the disease incidence varies according to constitutions, it is expected that more accurate disease prediction or diagnosis can be made if the disease marker specific disease markers can be provided. Or a diagnostic SNP marker. For the purposes of the present invention, abdominal obesity provides SNP markers specific for the luniumin, yangyangin and mussein except for a few sun persons. This is because the constitution of the sun is very low in Koreans.

In the present invention, the term "abdominal obesity" may be used as a phenotypic marker for predicting cardiovascular metabolic disease, and the incidence of hypertension, hyperlipidemia, stroke, diabetes, hematopoiesis, osteoporosis or obesity may be increased by abdominal obesity. SNP markers provided by the present invention can accurately predict the risk of abdominal obesity can be determined whether the risk of cardiovascular metabolic disease.

As used herein, the term "prediction or diagnosis" includes all types of analyzes used to predict disease occurrence and determine or derive risk of disease occurrence, and preferably determine whether or not to be obese to diagnose or diagnose the risk of development. It may be to predict.

Preferably, the SNP marker is a specific abdominal obesity predictive or diagnosable SNP marker, which is the rs29943 described in SEQ ID NO: 1 of the polynucleotides consisting of SEQ ID NOs: 1 to 8, wherein the 101 st base is A or G 101 A polynucleotide consisting of 5 to 100 consecutive bases comprising the first base, or a complementary polynucleotide thereof; The polynucleotide of rs987237, set forth in SEQ ID NO: 2, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is A or G; The polynucleotide of rs6717858, set forth in SEQ ID NO: 3, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is T or C; The polynucleotide of rs1822438 described in SEQ ID NO: 4, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is C or A; The polynucleotide of rs6544366 of SEQ ID NO: 5, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is T or G; The rs1716685 of SEQ ID NO: 6, comprising: a polynucleotide consisting of 5 to 100 contiguous bases comprising the 101 st base wherein the 101 st base is C or T; or a complementary polynucleotide thereof; The polynucleotide of rs632057, set forth in SEQ ID NO: 7, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is T or G; And a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is A or G, or a complementary polynucleotide thereof according to rs6581830 described in SEQ ID NO: 8 It may be a polynucleotide or more. More preferably two or more, more preferably three or more, four or more, five or more, six or more, seven or more, most preferably all eight SNP marker sets. The marker may be judged to have a high risk of specific abdominal obesity, which is the lupus when the 101th base of each SNP marker is the effect allele base of Table 2, and the risk of specific abdominal obesity, which is lunar if the effect allele base is not This may be determined to be low, and the greater the number of SNP markers in an individual, the higher the accuracy may be.

Preferably, the SNP marker is a specific abdominal obesity predictive or diagnostic SNP marker, and in rs17817449 as set forth in SEQ ID NO: 9, with 5 to 100 consecutive bases including the 101 st base where the 101 st base is T or G Polynucleotides comprised, or complementary polynucleotides thereof; The polynucleotide of rs1424233 set forth in SEQ ID NO: 10, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is A or G; The polynucleotide of rs9482771 of SEQ ID NO: 11, comprising a polynucleotide consisting of 5 to 100 contiguous bases comprising a 101 st base wherein the 101 st base is G or C; or a complementary polynucleotide thereof; The polynucleotide of rs6717858 of SEQ ID NO: 12, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is T or C; or a complementary polynucleotide thereof; The polynucleotide of rs4149270 set forth in SEQ ID NO: 13, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is C or T; or a complementary polynucleotide thereof; The polynucleotide of rs1919484 of SEQ ID NO: 14, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is G or A; or a complementary polynucleotide thereof; The polynucleotide of rs1566732 of SEQ ID NO: 15, comprising a polynucleotide consisting of 5 to 100 contiguous bases comprising a 101 st base wherein the 101 st base is A or C; or a complementary polynucleotide thereof; The polynucleotide of rs857721 of SEQ ID NO: 16, which comprises a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is T or A; And at least one selected from the group consisting of 5 to 100 consecutive bases comprising the 101st base wherein the 101st base is A or T, or a complementary polynucleotide thereof according to rs649729 as set forth in SEQ ID NO: 17; It may be a polynucleotide. More preferably two or more, more preferably three or more, four or more, five or more, six or more, seven or more, eight or more, most preferably all nine SNP marker sets . The marker may be judged to have a high risk of specific abdominal obesity when the 101th base of each SNP marker is the effect allele base of Table 2, and the risk of specific abdominal obesity that is cultivated when the effect allele base is not This may be determined to be low, and the greater the number of SNP markers in an individual, the higher the accuracy may be.

Preferably, the SNP marker is a specific abdominal obesity predictive or diagnostic SNP marker that is noisy. In rs6265 described in SEQ ID NO: 18, the base is composed of 5 to 100 consecutive bases including the 101 st base 101 G or A Polynucleotides comprised, or complementary polynucleotides thereof; The polynucleotide of rs7561317 set forth in SEQ ID NO: 19, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is G or A; or a complementary polynucleotide thereof; The polynucleotide of rs13130484 of SEQ ID NO: 20, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T; The polynucleotide of rs29943 of SEQ ID NO: 21, comprising a polynucleotide consisting of 5 to 100 contiguous bases comprising the 101 st base wherein the 101 st base is A or G; The polynucleotide of rs1424233 set forth in SEQ ID NO: 22, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is A or G; The polynucleotide of rs2074356 of SEQ ID NO: 23, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T; The polynucleotide of rs4149270 set forth in SEQ ID NO: 24, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T; The polynucleotide of rs6544366 of SEQ ID NO: 25, wherein the polynucleotide is composed of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is T or G; or a complementary polynucleotide thereof; The polynucleotide of rs17315646 of SEQ ID NO: 26, consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is C or G; or a complementary polynucleotide thereof; The polynucleotide of rs4667570 of SEQ ID NO: 27, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T; And at least one selected from the group consisting of 5 to 100 consecutive bases comprising the 101st base wherein the 101st base is G or A, or a complementary polynucleotide thereof according to rs12485738 as set forth in SEQ ID NO: 28; It may be a polynucleotide. More preferably 2 or more, more preferably 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, most preferably 11 May be all SNP marker sets. The marker may be judged to have a high risk of noise-specific abdominal obesity when the 101st base of each SNP marker is the effect allele base of Table 2, and the risk of specific abdominal obesity, which is noise when the effect allele base is not This may be determined to be low, and the greater the number of SNP markers in an individual, the higher the accuracy may be.

The present inventors confirmed that the SNP is a marker for predicting or diagnosing filamentous specific abdominal obesity. Specifically, SNPs with repeated reproducibility of four chronic diseases, such as obesity, hyperlipidemia, hypertension, and hematopoietic disorder, were obtained from those who responded to Sasang Constitutional Herbs and confirmed statistical constitution. As a result, 57 relevant SNPs were selected (Table 1), and specific SNPs related to the abdomen were selected for each constitution (Table 2). Constitution specificity was performed as follows. For example, the SNP set related to the abdominal obesity phenotype in the Taeumin people was analyzed by other constitutions, Soyangin, and Soinin, and the indicators of cardiovascular metabolic diseases such as WC, WHR, upper and lower abdominal circumference, blood pressure, lipid, and translocation If no association is found for the blood cell phenotype, it can be termed a specific SNP set, which is the lunium. In other words, although there were nine associated abdominal obesity SNP sets initially selected, one specific SOB set of eight abdominal obesity was constructed by excluding one SNP that associates with the phenotype in another constitution. In the case of a specific abdominal obesity SNP set, which is a soyangin and a noise, 3 and 4 SNPs were excluded through the specificity, respectively, so that 9 Syang and 11 noise SNP sets were finally formed. By measuring the GRS (genetic risk score) of the SNPs (Tables 3 and 4), SNPs having significance in abdominal obesity by filamentous constitution were identified, and such SNPs were first identified by the present inventors.

In still another aspect, the present invention provides a composition for predicting or diagnosing filamentous constitution specific abdominal obesity, comprising a probe capable of detecting the abdominal obesity prediction or diagnostic marker for each filamentous constitution or amplifying agent.

 In the present invention, the term "probe that can detect the abdominal obesity prediction or diagnostic marker for each constitutional constitution" is specifically identified through the hybridization reaction with the polymorphic site of the gene to predict specific filamentous constitution and abdominal obesity or It refers to a composition that can be diagnosed, and the specific method of such a gene analysis is not particularly limited, and may be by any gene detection method known in the art.

In the present invention, the term "agent that can amplify the abdominal obesity predictive or diagnostic marker for each constitution" refers to the polymorphic site of the gene through amplification to predict or diagnose specific filamentous constitution and abdominal obesity. It means a composition, preferably means a primer capable of specifically amplifying the polynucleotide of the marker for predicting or diagnosing the abdominal obesity according to the filamentous constitution.

The primers used for amplifying the polymorphic markers are template-directed DNA under appropriate conditions (e.g., four other nucleoside triphosphates and polymerizers such as DNA, RNA polymerase or reverse transcriptase) in appropriate buffers and at appropriate temperatures. It refers to a single stranded oligonucleotide that can act as a starting point for synthesis. The appropriate length of the primer may vary depending on the intended use, but is usually 15 to 30 nucleotides. Short primer molecules generally require a lower temperature to form a stable hybrid with the template. The primer sequence need not be completely complementary to the template, but should be sufficiently complementary to hybridize with the template.

As used herein, the term "primer" refers to a base sequence having a short free 3 'hydroxyl group, which can form complementary templates and base pairs and is a starting point for template strand copying. By a short sequence that functions as a point. The primer can initiate DNA synthesis in the presence of reagents and four different nucleoside triphosphates for polymerization reactions (i.e., DNA polymerase or reverse transcriptase) at appropriate buffer solutions and temperatures. PCR amplification can be used to predict the sagittal specific abdominal obesity through the production of the desired product. The PCR conditions, the lengths of the sense and antisense primers can be modified based on what is known in the art.

Probes or primers of the invention can be chemically synthesized using phosphoramidite solid support methods, or other well known methods. Such nucleic acid sequences may also be modified using many means known in the art. Non-limiting examples of such modifications include methylation, "capsulation", substitution of one or more homologs of natural nucleotides, and modifications between nucleotides, such as uncharged linkages such as methyl phosphonate, phosphoester, Phosphoramidate, carbamate, and the like) or charged linkers (eg, phosphorothioate, phosphorodithioate, etc.).

In another aspect, the present invention provides a kit for predicting or diagnosing filamentous specific abdominal obesity, comprising the composition for predicting or diagnosing filamentous specific abdominal obesity.

The kit may be an RT-PCR kit or a kit for DNA analysis (eg, DNA chip).

The kit of the present invention can predict or diagnose filamentous specific abdominal obesity by confirming SNP markers, which are predictive or diagnostic markers for filamentous specific abdominal obesity, or confirming the expression level of mRNA. have. As a specific example, the kit for measuring the mRNA expression level of filamentous specific abdominal obesity prediction or diagnostic marker in the present invention may be a kit containing the necessary elements necessary to perform RT-PCR. In addition to each primer pair specific for the gene of a filamentous specific abdominal obesity predictive or diagnostic marker, the RT-PCR kit can be used in a test tube or other appropriate container, reaction buffer (pH and magnesium concentrations vary), Enzymes such as deoxynucleotides (dNTPs), Taq-polymerases and reverse transcriptases, DNases, RNAse inhibitors, DEPC-water, sterile water and the like. It may also contain a primer pair specific for the gene used as a quantitative control. Also preferably, the kit of the present invention may be a kit for predicting or diagnosing filamentous constitution specific abdominal obesity including essential elements necessary for performing a DNA chip. DNA chip kits are those in which nucleic acid species are attached in a gridded array on a generally flat solid support plate, typically a glass surface not larger than a slide for a microscope, and nucleic acids are uniformly arranged on the chip surface, Hybridization reaction occurs between the nucleic acid on the surface and the complementary nucleic acid contained in the solution treated on the surface of the chip to enable a mass parallel analysis.

In another aspect, the present invention provides a microarray for predicting or diagnosing filamentous specific abdominal obesity comprising the polynucleotide of the filamentous specific abdominal obesity predicting or diagnosing marker.

The microarray may comprise DNA or RNA polynucleotides. The microarray comprises a conventional microarray except that the polynucleotide of the present invention is contained in the probe polynucleotide.

Methods for producing microarrays by immobilizing probe polynucleotides on a substrate are well known in the art. The probe polynucleotide means a polynucleotide capable of hybridizing, and means an oligonucleotide capable of binding to the complementary strand of the nucleic acid in a sequence-specific manner. The probe of the present invention is an allele-specific probe in which a polymorphic site exists in a nucleic acid fragment derived from two members of the same species and hybridizes to a DNA fragment derived from one member but does not hybridize to a fragment derived from another member . In this case, the hybridization conditions show a significant difference in the intensity of hybridization between alleles, and should be sufficiently stringent to hybridize to only one of the alleles. This can lead to good hybridization differences between different allelic forms. The probe of the present invention can be used for detecting alleles and predicting or diagnosing filamentous specific abdominal obesity. The prediction or diagnostic method includes detection methods based on hybridization of nucleic acids such as Southern blot and the like, and may be provided in a form that is pre-bound to the substrate of the DNA chip in a method using a DNA chip. The hybridization can usually be performed under stringent conditions, for example, a salt concentration of 1 M or less and a temperature of 25 ° C or higher. For example, conditions of 5 × SSPE (750 mM NaCl, 50 mM Na Phosphate, 5 mM EDTA, pH 7.4) and 2530 ° C. may be suitable for allele specific probe hybridization.

Immobilization of a probe polynucleotide on a substrate associated with filamentous specific abdominal obesity prediction or diagnosis of the present invention can also be readily prepared using this prior art. In addition, hybridization of nucleic acids on a microarray and detection of hybridization results are well known in the art. The detection can be accomplished, for example, by labeling the nucleic acid sample with a labeling substance capable of generating a detectable signal comprising a fluorescent material, such as Cy3 and Cy5, and then hybridizing on the microarray and generating The hybridization result can be detected.

In another aspect, the present invention provides a method for producing a polymorphism, comprising the steps of: (a) amplifying a polymorphic site of said SNP marker or hybridizing with a probe from DNA of an isolated sample; And (b) determining the base of the amplified or hybridized polymorphic site of step (a), thereby providing information for predicting or diagnosing filamentous specific abdominal obesity.

DNA of the isolated sample can be obtained from a sample separated from the individual.

As used herein, the term "individual" refers to a subject for predicting or diagnosing filamentous constitution-specific abdominal obesity, wherein the filamentous specific abdominal obesity can be determined whether it is a specific abdominal obesity, which is a lunar, ulcer or noise. In the sample, DNA may be obtained from a sample such as hair, urine, blood, various body fluids, isolated tissues, isolated cells, or saliva, but is not limited thereto.

The step of amplifying the polymorphic site of the SNP marker from the DNA of step (a) or hybridizing with the probe may be performed by any method known to those skilled in the art. For example, the target nucleic acid can be obtained by PCR amplification and purification thereof. Other ligase chain reaction (LCR) (Wu and Wallace, Genomics 4, 560 (1989), Landegren et al., Science 241, 1077 (1988)), transcription amplification (Kwoh et al., Proc. Natl. Acad. Sequence amplification based on nucleic acids (NASBA) can be used as well as self-sustaining sequence replication (Guatelli et al., Proc. Natl. Acad. Sci. USA 87, 1874 (1990)).

Determination of bases in the polymorphic site of step (b) of the above method can be carried out by sequencing, hybridization by microarray, allele specific PCR, dynamic allele-specifichybridization, DASH), PCR extension analysis, PCR-SSCP, PCR-RFLP analysis or TaqMan technique, SNPlex platform (Applied Biosystems), mass spectrometry (e.g. MassenRAY system of Sequenom), mini- But are not limited to, the BioRad system, the CEQ and SNPstream system (Beckman), the Molecular Inversion Probe array technology (e.g. Affymetrix GeneChip), and BeadArray Technologies (e.g. Illumina GoldenGate and Infinium analysis) Do not. One or more alleles in a polymorphic marker, including microsatellite, SNP or other types of polymorphic markers, can be identified by such methods or by other methods available to those skilled in the art to which this invention pertains. The base of such a polymorphic site can be determined preferably through a SNP chip.

As used herein, the term "SNP chip" refers to one of the DNA microarray capable of identifying each base of several hundred thousand SNPs at once.

The TaqMan method comprises the steps of: (1) designing and constructing a primer and a TaqMan probe to amplify a desired DNA fragment; (2) labeling probes of different alleles with FAM dyes and VIC dyes (Applied Biosystems); (3) performing PCR using the DNA as a template and using the primer and the probe; (4) after completion of the PCR reaction, analyzing and confirming the TaqMan assay plate with a nucleic acid analyzer; And (5) determining the genotype of the polynucleotides of step (1) from the analysis results.

In the above, the sequencing analysis can be performed using a conventional method for determining the nucleotide sequence, and can be performed using an automated gene analyzer. The allele-specific PCR means a PCR method in which a DNA fragment in which the SNP is located is amplified with a primer set including a primer designed with the base at the 3 'end at which the SNP is located. The principle of the above method is that, for example, when a specific base is substituted by A to G, an opposite primer capable of amplifying a primer containing the A as a 3 'terminal base and a DNA fragment of an appropriate size is designed, In the case where the base at the SNP position is A, the amplification reaction is normally performed and a band at a desired position is observed. When the base is substituted with G, the primer can be complementarily bound to the template DNA, And the amplification reaction is not performed properly due to the inability of complementary binding at the terminal. DASH can be performed by a conventional method, preferably by a method such as Prince et al.

On the other hand, in the PCR extension analysis, first, a DNA fragment containing a base in which a single base polymorphism is located is amplified by a pair of primers, and all nucleotides added to the reaction are deactivated by dephosphorylation, and SNP- specific extension primers, a dNTP mixture, a digoxin nucleotide, a reaction buffer, and a DNA polymerase to perform a primer extension reaction. At this time, the extension primer has a base immediately adjacent to the 5 'direction of the base in which the SNP is located at the 3' terminus, the nucleic acid having the same base as the didyxin nucleotide is excluded in the dNTP mixture, and the didyoxynucleotide indicates the SNP Base type. For example, if there is a substitution from A to G, when a mixture of dGTP, dCTP and TTP and ddATP is added to the reaction, the primer is extended by DNA polymerase at the base where the substitution has occurred, and after several bases A The primer extension is terminated by ddATP at the position where the base first appears. If the substitution has not occurred, the extension reaction is terminated at the position, so that it is possible to discriminate the type of the base representing the SNP by comparing the lengths of the extended primers.

As the detection method, when the extension primer or the dioxynucleotide is fluorescently labeled, the SNP is detected by detecting fluorescence using a gene analyzer (for example, Model 3700 of ABI Co., Ltd.) used for general nucleotide sequence determination And when the unlabeled extension primer and the didyxin nucleotide are used, the SNP can be detected by measuring the molecular weight using MALDI-TOF (matrix assisted laser desorption ionization-time of flight) technique.

Preferably, in the base sequence determined in step (b), in rs29943 described in SEQ ID NO: 1, when the 101st base is G; The rs987237 set forth in SEQ ID NO: 2, wherein the 101 st base is A; The rs6717858 set forth in SEQ ID NO: 3, wherein the 101 st base is T; The rs1822438 set forth in SEQ ID NO: 4, wherein the 101 st base is C; The rs6544366 set forth in SEQ ID NO: 5, wherein the 101 st base is T; The rs1716685 set forth in SEQ ID NO: 6, wherein the 101 st base is C; In rs632057 set forth in SEQ ID NO: 7, wherein the 101st base is G; Alternatively, in rs6581830 described in SEQ ID NO: 8, when the 101 st base is A, it can be determined as a specific abdominal obesity, which is the lunar phase in filamentous constitution. The polymorphic site may be determined as a risk allele, and the higher the frequency of the allele, the higher the risk of specific abdominal obesity. More preferably, at least one, at least two, at least three, at least four, at least five, at least six, and at least seven of the polymorphic sites of SEQ ID NOs: 1 to 8 are most preferred, In all eight risk alleles, the higher the risk of specific abdominal obesity, which is Taeum. When the 101 st base is not the base of the effect allele of Table 2, it can be determined that the risk of abdominal obesity is low.

Preferably, in rs17817449 as set forth in SEQ ID NO: 9 of the base sequence determined in step (b), the 101 st base is G; The rs1424233 set forth in SEQ ID NO: 10, wherein the 101 st base is A; The rs9482771 set forth in SEQ ID NO: 11, wherein the 101 st base is G; The rs6717858 set forth in SEQ ID NO: 12, wherein the 101 st base is C; The rs4149270 set forth in SEQ ID NO: 13 wherein the 101 st base is T; The rs1919484 set forth in SEQ ID NO: 14 when the 101 st base is G; The rs1566732 set forth in SEQ ID NO: 15, wherein the 101 st base is A; The rs857721 set forth in SEQ ID NO: 16, wherein the 101 st base is T; Alternatively, in rs649729 as set forth in SEQ ID NO: 17, when the 101 st base is A, it can be determined as a specific abdominal obesity that is a minority in filamentous constitution. The polymorphic site is determined as a risk allele, and the higher the frequency of the allele, the higher the specific abdominal obesity risk. More preferably, when at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight of the polymorphic sites in SEQ ID NOs: 9 to 17 are dangerous alleles, Most preferably, all nine risk alleles may determine that the risk of specific abdominal obesity is higher. When the 101 st base is not the base of the effect allele of Table 2, it can be determined that the risk of abdominal obesity is low.

Preferably, in the base sequence determined in step (b), in rs6265 described in SEQ ID NO: 18, when the 101 st base is A; The rs7561317 set forth in SEQ ID NO: 19, wherein the 101 st base is G; The rs13130484 set forth in SEQ ID NO: 20, wherein the 101 st base is T; The rs29943 set forth in SEQ ID NO: 21, wherein the 101 st base is A; The rs1424233 set forth in SEQ ID NO: 22, wherein the 101 st base is G; The rs2074356 set forth in SEQ ID NO: 23, wherein the 101 st base is C; The rs4149270 set forth in SEQ ID NO: 24 wherein the 101 st base is C; The rs6544366 set forth in SEQ ID NO: 25, wherein the 101 st base is G; The rs17315646 set forth in SEQ ID NO: 26 wherein the 101st base is C; The rs4667570 set forth in SEQ ID NO: 27, wherein the 101 st base is C; Alternatively, in rs12485738 as set forth in SEQ ID NO: 28, when the 101 st base is G, it can be determined as a specific abdominal obesity that is noise in filamentous constitution. The polymorphic site is determined as a risk allele, and the higher the frequency of the allele, the higher the risk of specific abdominal obesity, which is noise. More preferably, one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more polymorphic sites in SEQ ID NOs: 18 to 28 In the case where the abnormal allele is a risk allele, it is most preferable that all 11 risk alleles have a higher risk of abdominal obesity. When the 101 st base is not the base of the effect allele of Table 2, it can be determined that the risk of abdominal obesity is low.

In another aspect, the present invention provides a method for selecting SNPs for predicting or diagnosing filamentous constitution specific abdominal obesity.

The method specifically includes the steps of: (a) selecting SNPs that are associated with phenotypes of obesity, hyperlipidemia, hypertension, and hemophilia; (b) selecting SNPs associated with the abdominal phenotype using multiple regression analysis among the selected SNPs of step (a); (c) selecting SNPs that are related to the constitution by abdominal phenotype and abdominal obesity using multiple regression analysis among the SNPs selected in step (b); And (d) calculating a genetic risk score (GRS) of the SNP selected in step (c) and performing multiple regression analysis as independent variables, thereby selecting specific constitution specific SNPs. SNP screening method for predicting or diagnosing obesity.

Obesity of the step (a), hyperlipidemia, hypertension and hemophilia phenotype is not limited thereto, for example, obesity is BMI, WC, WHR; Hyperlipidemia includes HDL cholesterol, LDL cholesterol, triglyceride; Hypertension includes systolic blood pressure, diastolic blood pressure; Hemocytosis may be white blood cell count, red blood cell count, hematocrit, hemoglobin concentration, and the like.

The abdominal phenotype of step (b) is not limited thereto, but may be, for example, a ratio between abdominal obesity, upper abdomen, waist, lower abdomen, and each hip circumference. According to an embodiment of the present invention, the 57 SNP sets were selected by performing the steps (a) and (b) (Table 1).

Step (c) is not limited thereto, but preferably, the case of abdominal obesity is P <0.1 and the abdominal phenotype is P <0.05. Can be excluded. In one embodiment of the present invention, as a step before specificity analysis, 9 SNPs for Taeinin, 12 for Soyangin, and 15 SNPs for Soinin were selected.

The GRS calculation of step (d) is not limited thereto. For example, the GRS calculation is calculated as a genotyping score of 0 for only two non-hazard alleles, 1 for hetero, and 2 for only two risk alleles. A simple count method that calculates the genotyping scores of the selected SNPs, plus all the beta coefficients of multiple regression analysis for abdominal obesity for each SNP, multiplied by the genotyping scores, divided by the maximum total score multiplied by the genotyping scores. It may be a GRS determined by multiplying the maximum number of risk alleles. Regression analysis is performed on abdominal obesity and related phenotypes using GRS as an independent variable to select the largest constitution-specific SNP that ensures constitution specificity. In one embodiment of the present invention, eight for Taeinin, nine for Soyangin, and 11 for Soinin were selected (Table 2).

The screening method of the present invention has the advantage of selecting SNPs showing more specificity by constitution by not predicting the genetic risk for abdominal obesity in the entire population.

The SNP marker of the present invention is a specific SNP marker for predicting or diagnosing filamentous constitution specific abdominal obesity, and the risk prediction may be more accurate to allow objective diagnosis and risk prediction.

1 shows a simplified flowchart of a method for screening SNPs of the present invention.

Hereinafter, the present invention will be described in more detail with reference to the following examples. These examples are only for illustrating the present invention, and the scope of the present invention is not to be construed as being limited by these examples.

Example 1: Subject Selection and Abdominal Related Phenotypes and Abdominal obesity  Measure

The subjects of the present invention were 2279 people collected from 25 oriental medical centers from 2006 to 2010, and those who confirmed the constitution after seeing the response to Sasang Constitutional Herbs. The constitution confirmer selected people with no side effects with clear response to constitution when they ate 60 tablets (usually a month). Subjects agreed to the study and went through research ethics. Numerous clinical epidemiologic and molecular genetic studies have already been performed on these constitution confirmers, and their results have been published in several overseas SCI journals (Evidence-based Complementary and Alternative Medicine, Journal of Alternative and Complementary Medicine, European Journal of Integrative Medicine). Has been reported.

There are three continuous phenotypes of abdominal-related phenotypes, including the upper and lower abdomen, the circumference of the hips and the circumference of the hips. The upper circumference measured the horizontal circumference (cm) passing through the upper and lower left and right 7-8 rib cartilage junctions, and the waist circumference (WC) measured the circumference of the navel area (cm), and the lower abdomen circumference passed the left and right anterior superior iliac spines. The circumference (cm) was measured. For each abdominal to hip circumference ratio, the upper abdominal to hip circumference is divided by the upper abdominal circumference to the hip circumference. Will be divided around the hips. The hip circumference is the horizontal circumference (cm) passing above the pubic bone. Abdominal obesity was selected when the waist circumference was 90 cm or more in men and 85 cm or more in women. This criterion is based on Korean abdominal obesity.

Example 2: Statistical Correlation Analysis

Correlation analysis was performed by multiple regression analysis. When the dependent variable was linear, linear regression analysis was performed. The calibration variables were gender, age, and chronic disease. Among the subjects, hypertension, hyperlipidemia, diabetes mellitus and paralysis among the subjects could affect abdominal obesity.

Example 3: Specific Constitution SNP ( Single nucleotide polymorphism ) Three The  Selection

<3-1> associated with abdominal phenotype SNP  selection

Phenotypes associated with four chronic diseases: obesity, hyperlipidemia, hypertension, and hemophilia (obesity: BMI, WC, WHR; hyperlipidemia: HDL cholesterol, LDL cholesterol, triglyceride; hypertension: systolic blood pressure, diastolic blood pressure; Water, hematocrit, hemoglobin concentration, etc.) to obtain SNPs with established repeatability. Among Asians, the minor allele frequency was less than 5%, and SNPs with strong linkage (r ² ≥ 0.8) were excluded from the linkage disequilibrium (LD) analysis. A statistical analysis was performed on some subjects (40% of the total subjects) who were genotyped with Affymetrix SNP chip. 57 relevant SNPs were selected (Table 1).

<3-2> the abdominal relationship by constitution SNP  Selection

In Example <3-1>, a total of 57 SNP genotypes were determined in 2279 subjects, and correlation analysis was performed for each of the abdominal related phenotypes (WC, WHR) and abdominal obesity. Abdominal obesity was selected when P <0.1, and other abdominal phenotypes were selected when P <0.05. Along with the constitution, SNPs that showed specific association with the belly-related abdominal related variables were excluded.

As a result, the analysis of calculating the GRS (genetic risk score) used 9 SNPs for Taeumin, 12 for Soyangin, and 15 SNPs for Soinin.

<3-3> GRS (Genetic risk score ) Calculation

Genetic risk for abdominal obesity (abdominal GRS) is described by Chloe YY, et al. And Cornelis MC, et al. Measured by two disclosed methods (Chloe YY, et al. Obesity Susceptibility Genetic Variants Identified from Recent Genome-Wide Association Studies: Implications in a Chinese Population. J Clin Endocrinol Metab. 2010; 95 (3) 1395-1403., Cornelis MC, et al. Joint Effects of Common Genetic Variants on the Risk for Type 2 Diabetes in US Men and Women of European Ancestry.Annn Intern Med. 2009; 50 (8): 541-550). First, the genotyping score for each SNP was set to 0 for only two nonrisk alleles, 1 for heteros, and 2 for only two risk alleles. Assuming that 10 SNP sets are selected, one method is a simple count method that adds all 10 SNP genotyping scores, allowing for a minimum of 0 to 20 GRS. The other is the weighted count method, where the beta coefficient of multiple regression analysis for abdominal obesity of each SNP is multiplied by the genotyping score, the score of 10 SNPs is divided by the maximum total score multiplied by the beta coefficient, and then the maximum number of risk alleles. It is a way to multiply by 20. Regression analysis was performed on abdominal obesity and related phenotypes using GRS as an independent variable to select the largest constitution specific SNP set that ensures specific constitution.

The specificity of each constitution was analyzed by considering other abdominal variables (circumference of upper and lower abdomen), blood pressure, lipid and whole blood cell phenotype, in addition to abdominal obesity and related phenotypes WC and WHR. Therefore, it was considered to have constitution specificity for various phenotypes related to cardiovascular metabolic disease as well as specificity for abdominal obesity in the navel area.

As a result, the final screened specific SNP set consisted of eight for Taeinin, nine for Soyangin, and 11 for Soinin (Table 2).

Example 4: Constitution Specific SNP  three The GRS Association Analysis of

<4-1> Simple count method

Each constitution group was divided into four subgroups according to the GRS, and then the OR (odds ratio) of abdominal obesity of the remaining three groups was calculated based on the lowest GRS subgroup. The lunar GRS ranges from 5 to 15, with the highest number of people at 10, and the Soyangin has a GRS range of 4 to 15, with the largest subgroup at 9, and the noise group has a GRS range of 7 to 20 and 13 days. When the subgroup was the largest. The OR value of the GRS of each subgroup tended to increase in the case of the subgroup in which all three constitutions had increased GRS values. So, the risk of abdominal obesity was increased up to 2.9 times (GRS 5 ~ 8 vs. GRS 13 ~ 15) for Taeumin, 4.7 times (GRS 4 ~ 7 vs. GRS 12 ~ 15) for Soyangin, and up to 4.6 times (GRS 7) for Soyangin. ~ 11 vs. GRS 16-20) showed an increased risk of abdominal obesity (Table 3).

The linear regression analysis of the abdominal phenotypes WC or WHR showed specific associations and strong associations with each constitution. In the case of a specific SNP set that is Taeum, WC increased 0.69 cm (P <0.0001) per point of GRS, 0.0047 (P <0.0001) for WHR, and 0.86 cm (P <WC) for a specific point of GRS. 0.0001), WHR was 0.0054 ((P <0.0001), and for the noise-specific SNP set, the increase per point of GRS was 0.73 cm (P <0.0001) for WC and 0.0064 (P <0.0001) for WHR (Table 4).

<4-2> Weighted count method

The OR value of GRS for abdominal obesity may be slightly higher than that of the simple count method of Example <4-1>, but it has been shown to have almost the same value. ~ 9.5 vs. GRS 13.5 ~ 15.6) Increased risk of abdominal obesity, up to 6.1 times for Soyangyang (GRS 4.3 ~ 7.5 vs. GRS 11.5 ~ 14.8), up to 5.8 times for Noise Noise (GRS 6.5 ~ 12.5 vs. GRS 16.5 ~ 21.0) It was confirmed that the risk of abdominal obesity increased (Table 3).

For the abdominal phenotype, WC or WHR, the results of linear regression were similar to those of the simple count method. WC showed 0.62 cm (P <0.0001) increase per point of GRS, WHR showed 0.0041 (P <0.0001), and WC showed 0.86 cm (P <0.0001) for GRS. ), WHR was 0.0052 ((P <0.0001), and for the noise-specific SNP set, the increase per point of GRS was 0.61 cm (P <0.0001) for WC and 0.0050 (P <0.0001) for WHR (Table 4).

These results suggest that the constitution-specific SNP marker selected in the present invention can predict the genetic risk for each constitution for abdominal obesity following the objective constitution diagnosis.

<110> Korea Institute of Oriental Medicine <120> SNP markers for abdominal obesity and use <130> PA110783 / KR <160> 28 <170> Kopatentin 2.0 <210> 1 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = A or G <400> 1 gccagcccct gatctccagg tgagggcaag ccctctctct acaaggaaac tcctcctttg 60 ggcggggttg gggtgagcaa agagagccac ccacattctc rtcacacatg tgacaagacc 120 aatattactt ggctgacttg agccttgtgg ctaaacacat tgcctacccc ccttgagatg 180 gccatcaacc tgtgacatcc t 201 <210> 2 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = A or G <400> 2 tatgaattag agtgattggt tgattgatca gggcacctgt tgtaaatcat aactgttcca 60 aacaatcact agccggtgct ttaatttgta aacaaaattc rtgtcactgc agaattgctt 120 tcactgaaga tgagcatttg ggttcctttc taaatgaatc tgttgttatt atgtagggaa 180 gaatggggca cactttaaag a 201 <210> 3 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = T or C <400> 3 acaaacctgc acacatgtac ttcatataaa tacatctata tagggcttca tatcaaaata 60 ttaacagcta tctttggaga ggagagtggg atgctgggga ygaaaaagaa tgtattttat 120 actctatcat atatatgtaa tctgaattat aattttaata ttatataaat aaataacttg 180 attggaggaa agaaggaaaa g 201 <210> 4 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> M = C or A <400> 4 aaaaaagaag aagaagaaag aggaggagga ggtgaagaag aagaaaaagg aaagcctgtg 60 caggctcact actggtgcat tgggacactg gtaagcctaa maaggacctc agttcctgag 120 tgcctgtgag ccctcgtgca gtgcattaaa tatacccaga tttattttgg aggagtatca 180 tgcctggact tatttggata t 201 <210> 5 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> K = T or G <400> 5 atggcagata ttctcaactt ggccaagaca atgcagcccc tgctgtgccc ttcttctgag 60 ccacacagac ccagtgaagg actgggtgtt gcaaagggca ktttcccatt tcctgggctt 120 ggccttatac ctggacaagg aaaggagtca ccttgtcata tggtgtcagt agatgtagag 180 tgccctgctc ccacatctgc c 201 <210> 6 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = C or T <400> 6 tatgtttaag cctaaaggtc tgttgaggta acagttttag aacgattgcc acaatcccac 60 agagaaaaaa caagtgaagg tcggtgaaag ctgcaggttc yaaattacag aatcaagaac 120 agtatttctt gacattcatc acatttaagt aataaaagac attacctcaa caacaggtgt 180 attttcctgg agctcagctg t 201 <210> 7 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> K = T or G <400> 7 ttgcagttac attcgaattt tagataagca aagaataaca tttgagtata actatgtccc 60 aaatatccca atttatgttc caaatatttg ccctacgtcc kctctccaaa tacaatcaag 120 cacaaagtgc catcaatgcc ccaagtattt atattaataa ttccttcata atgattatga 180 tgttggaatg aaacaaagat a 201 <210> 8 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = A or G <400> 8 aaaaaagaaa tgtcattcta attcttccag ccattgacca tcttcgtcta gtttcccaat 60 acacatcaat cagtgagaag tcatggttct gtagccacag raagttccgc attatcaggt 120 tggaagtctg cccttctcaa gaaagtgatc tgacttgtaa caacaaaacc atcttctcac 180 actaatcaat acattttatt t 201 <210> 9 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> K = T or G <400> 9 ggtgaagagg aggagattgt gtaactggag tctcccctta actggtcttt attgttaaag 60 aagagtgatc cctttgtgtt tcagcttggc acacagaaac kgttttaatt taacagtcca 120 gctcctttaa tagatcaatt ctctattgtg gtttgaattt ggtgcactcc caatttactc 180 taaacttcta cgggcttcct t 201 <210> 10 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = A or G <400> 10 gtaccgtgaa aaatggattt gattccattt ttattctcca agtttgacca tagtaactca 60 agatagggac agccagcgag ggtaggagcg acaggaataa rggtttgagc tcaacatgca 120 gtggaatctt gtaacaattg cagcttttat gcagcactat tcaatagaaa aataacatga 180 ggcatacata acaattgtgt a 201 <210> 11 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> S = G or C <400> 11 gagaaggtag actcagaagt taaagacctg ggttccagat ccagcattgc tgctaatgcc 60 tgaataaccc aagaaagtcc ttttactata ccaagctaaa stttttcatc tgcaaaatga 120 ggaggttgat caaaaactta gatctagtga tccctacggt ttcctcaaca tttaatcttt 180 tggtatgaga atataagtca c 201 <210> 12 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = T or C <400> 12 acaaacctgc acacatgtac ttcatataaa tacatctata tagggcttca tatcaaaata 60 ttaacagcta tctttggaga ggagagtggg atgctgggga ygaaaaagaa tgtattttat 120 actctatcat atatatgtaa tctgaattat aattttaata ttatataaat aaataacttg 180 attggaggaa agaaggaaaa g 201 <210> 13 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = C or T <400> 13 cccaagtccc ctctatgtct gagagctgag gctggctgtc aaagaggaac taaggatgcc 60 agggactttc tgcttaggac ccctctcatc acttctccaa ygctggtatc atgaacccca 120 ttctacagat gatgtccact agattaagaa tggcatgtga ggccaagttt ccacctgaga 180 gtcagtttta ttcagaagag a 201 <210> 14 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = G or A <400> 14 catgaaggga cagtgtcatg ctactttagc ttttgctttg acagactttc ctgaaaattc 60 tgatcaagtc acttactgta gactgagcat gaagaagagt rttcaaacag caaaaaattc 120 cagtgggtgg cgagagaaag gttactctcg gacaaattcc ttttcataag tcctgactgt 180 gatttccgtg tgactacagc t 201 <210> 15 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> M = A or C <400> 15 ttcatcatac ccacccagat ttttagccct gtgtgtgcat acctgttgga aacaaagacc 60 acatttccca gctcccatgg agctagatgt tgcaatgtga mtaagttttg ctcaacgaag 120 catgagcaga ggtactgggt gacttctagg aagtgtcctt taagggtggg gcacaacctt 180 ctgcccttcc tccttcttat a 201 <210> 16 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> W = T or A <400> 16 cttctgaaga acctgctcca catcagactc tgaagtctct gagagcaggc atggtagcct 60 caacagtcag aaagtgttaa agtatcaagg gtgatgacta wccaaccaac aagctcggaa 120 tggtgaaatt ttccaagatt cctattttga acttgcctga atgttagtgg cgtctttgta 180 ggattcatca caggctgtgg g 201 <210> 17 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> W = A or T <400> 17 ggcaccttta tctcctcctc cttcaaatgg aatgataatc taggtaattt aaggtactgg 60 ttaaatgctt aacttctgca atgaatttaa tccccagaac wccctgtgag ataggttttc 120 ttattaggtc catttgatga ggaagagcat agtgctgata tcatagtatg tgggaaggtg 180 aaacgagata atccatggaa a 201 <210> 18 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = G or A <400> 18 ggcctaccca ggtgtgcgga cccatgggac tctggagagc gtgaatgggc ccaaggcagg 60 ttcaagaggc ttgacatcat tggctgacac tttcgaacac rtgatagaag agctgttgga 120 tgaggaccag aaagttcggc ccaatgaaga aaacaataag gacgcagact tgtacacgtc 180 cagggtgatg ctcagtagtc a 201 <210> 19 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = G or A <400> 19 gctcactgtg gacacttccc agccccttcc cagaggtgag gtctcctgct agcactggct 60 tagaagatgt aggcagagat gacaagtgac acttcctgtc rtctgcctac aagttcccaa 120 agatcctccc ctttcttgct ctgttttcac ctccagaata agcgtgaatg agccctggaa 180 gatgcacggt ctggacagat g 201 <210> 20 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = C or T <400> 20 ttttggtgca cattgtggta gaagaattca tagatctgca ttcactgctt ccatcatttg 60 gcagctttct tcagtcaggg gagtatttac ccagtcatgg yagaggcaat gcagtgctct 120 gttcactgat tttctgattt ggaaacaagt tttcttgggc aggaaaagga tgcttcagag 180 gacatgatac tttagagaag c 201 <210> 21 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = A or G <400> 21 gccagcccct gatctccagg tgagggcaag ccctctctct acaaggaaac tcctcctttg 60 ggcggggttg gggtgagcaa agagagccac ccacattctc rtcacacatg tgacaagacc 120 aatattactt ggctgacttg agccttgtgg ctaaacacat tgcctacccc ccttgagatg 180 gccatcaacc tgtgacatcc t 201 <210> 22 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = A or G <400> 22 gtaccgtgaa aaatggattt gattccattt ttattctcca agtttgacca tagtaactca 60 agatagggac agccagcgag ggtaggagcg acaggaataa rggtttgagc tcaacatgca 120 gtggaatctt gtaacaattg cagcttttat gcagcactat tcaatagaaa aataacatga 180 ggcatacata acaattgtgt a 201 <210> 23 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = C or T <400> 23 tgcttgtcaa tttagctgaa tattttgggt tgatgggctg ctgcagtgaa gctggagtgg 60 ttatactggg aaactctgtg gtctggtggt taacagttca yatctgaagt catactgttt 120 accagctgtg tggacttgag aaaattactt aacatctctg ggctttcccc atctttaaaa 180 tggaatatgt gctctgcaag g 201 <210> 24 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = C or T <400> 24 cccaagtccc ctctatgtct gagagctgag gctggctgtc aaagaggaac taaggatgcc 60 agggactttc tgcttaggac ccctctcatc acttctccaa ygctggtatc atgaacccca 120 ttctacagat gatgtccact agattaagaa tggcatgtga ggccaagttt ccacctgaga 180 gtcagtttta ttcagaagag a 201 <210> 25 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> K = T or G <400> 25 atggcagata ttctcaactt ggccaagaca atgcagcccc tgctgtgccc ttcttctgag 60 ccacacagac ccagtgaagg actgggtgtt gcaaagggca ktttcccatt tcctgggctt 120 ggccttatac ctggacaagg aaaggagtca ccttgtcata tggtgtcagt agatgtagag 180 tgccctgctc ccacatctgc c 201 <210> 26 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> S = C or G <400> 26 tctacctatt ctgaaagaga ggcttaaaac taaagtcctg gttagttgag gatcagatgt 60 gtcatacttt tctcagaggg gaggggacgg tcactttgct staagtttgg gccatgaggt 120 ccacactgag cctacatggg gtagggggaa accgtgaagt gtgcagtgac ctgagggtgc 180 cagatcaccc cgagccgttg t 201 <210> 27 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> Y = C or T <400> 27 actgattaaa tcaaccaaat ggaagccaaa cattccacaa agaaatgtct attgctattc 60 acacagataa acggatacac ccactggcaa ggccaaaagg yacaagtgtc ctggtttgaa 120 tatgtatgct gtggtggtgg cttctgattc cttactgctt caacctcaag ccacctgtaa 180 atgggaaggg ctctatatgc a 201 <210> 28 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> R = G or A <400> 28 gaagcaatct ttggtttcca tctgtcattc agttattatg aggcctggta atcagagatg 60 atctcttccc agcacactgg tgtgtacgtt cagaaaacat ratcaacatt ttaagaaagg 120 tcaaggtctt ctgtccagtt ccacatcaac cagttaccat gttgacagaa acagaaatgg 180 ctctcttcca tttttttctg g 201

Claims (16)

In the polynucleotides consisting of SEQ ID NOs: 1 to 28, at least one polynucleotide selected from a polynucleotide comprising the 101 st base of each sequence at the SNP position and consisting of 5 to 100 consecutive bases, or a complementary polynucleotide thereof Single, nucleotide polymorphism (SNP) marker for predicting or diagnosing filamentous specific abdominal obesity, comprising.
According to claim 1, Among the polynucleotide consisting of SEQ ID NO: 1 to 8,
The polynucleotide of rs29943 of SEQ ID NO: 1, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is A or G;
The polynucleotide of rs987237, set forth in SEQ ID NO: 2, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is A or G;
The polynucleotide of rs6717858, set forth in SEQ ID NO: 3, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is T or C;
The polynucleotide of rs1822438 described in SEQ ID NO: 4, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is C or A;
The polynucleotide of rs6544366 of SEQ ID NO: 5, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is T or G;
The rs1716685 of SEQ ID NO: 6, comprising: a polynucleotide consisting of 5 to 100 contiguous bases comprising the 101 st base wherein the 101 st base is C or T; or a complementary polynucleotide thereof;
The polynucleotide of rs632057, set forth in SEQ ID NO: 7, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is T or G; And
At least one selected from the group consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is A or G, or a complementary polynucleotide thereof SNP markers for predicting or diagnosing specific abdominal obesity, which are polynucleotides, which are in the nasal constitution.
According to claim 1, Among the polynucleotide consisting of SEQ ID NOs: 9 to 17,
The polynucleotide of rs17817449 set forth in SEQ ID NO: 9, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is T or G; or a complementary polynucleotide thereof;
The polynucleotide of rs1424233 set forth in SEQ ID NO: 10, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is A or G;
The polynucleotide of rs9482771 of SEQ ID NO: 11, comprising a polynucleotide consisting of 5 to 100 contiguous bases comprising a 101 st base wherein the 101 st base is G or C; or a complementary polynucleotide thereof;
The polynucleotide of rs6717858 of SEQ ID NO: 12, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is T or C; or a complementary polynucleotide thereof;
The polynucleotide of rs4149270 set forth in SEQ ID NO: 13, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is C or T; or a complementary polynucleotide thereof;
The polynucleotide of rs1919484 of SEQ ID NO: 14, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is G or A; or a complementary polynucleotide thereof;
The polynucleotide of rs1566732 of SEQ ID NO: 15, comprising a polynucleotide consisting of 5 to 100 contiguous bases comprising a 101 st base wherein the 101 st base is A or C; or a complementary polynucleotide thereof;
The polynucleotide of rs857721 of SEQ ID NO: 16, which comprises a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is T or A; And
At least one poly selected from the group consisting of 5 to 100 consecutive bases comprising the 101st base wherein the 101st base is A or T, or a complementary polynucleotide thereof SNP markers for predicting or diagnosing specific abdominal obesity, which are nucleotides, which are predominant in filamentous constitution.
According to claim 1, Among the polynucleotide consisting of SEQ ID NO: 18 to 28,
The polynucleotide of rs6265 of SEQ ID NO: 18, wherein the polynucleotide is composed of 5 to 100 consecutive bases comprising the 101st base wherein the 101st base is G or A; or a complementary polynucleotide thereof;
The polynucleotide of rs7561317 set forth in SEQ ID NO: 19, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is G or A; or a complementary polynucleotide thereof;
The polynucleotide of rs13130484 of SEQ ID NO: 20, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T;
The polynucleotide of rs29943 of SEQ ID NO: 21, comprising a polynucleotide consisting of 5 to 100 contiguous bases comprising the 101 st base wherein the 101 st base is A or G;
The polynucleotide of rs1424233 set forth in SEQ ID NO: 22, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is A or G;
The polynucleotide of rs2074356 of SEQ ID NO: 23, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T;
The polynucleotide of rs4149270 set forth in SEQ ID NO: 24, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T;
The polynucleotide of rs6544366 of SEQ ID NO: 25, wherein the polynucleotide is composed of 5 to 100 consecutive bases comprising the 101 st base wherein the 101 st base is T or G; or a complementary polynucleotide thereof;
The polynucleotide of rs17315646 of SEQ ID NO: 26, consisting of 5 to 100 consecutive bases comprising a 101st base wherein the 101st base is C or G; or a complementary polynucleotide thereof;
The polynucleotide of rs4667570 of SEQ ID NO: 27, comprising a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101 st base wherein the 101 st base is C or T; And
At least one poly selected from the group consisting of 5 to 100 contiguous bases comprising the 101 st base wherein the 101 st base is G or A, or a complementary polynucleotide thereof SNP markers for predicting or diagnosing specific abdominal obesity, which are nucleotides and noise in filamentous constitution.
The marker of claim 1, wherein the abdominal obesity is a risk factor for hypertension, hyperlipidemia, obesity, or hemocytosis.
The marker of claim 1, wherein the prediction or diagnosis diagnoses abdominal obesity or predicts risk.
A composition for predicting or diagnosing filamentous constitution specific abdominal obesity, comprising a probe capable of detecting or predicting a filamentous specific abdominal obesity predictive or diagnostic SNP marker according to any one of claims 1 to 6.
Sasang constitution specific abdominal obesity prediction or diagnostic kit comprising the composition of claim 7.
The kit for predicting or diagnosing filamentous constitution specific abdominal obesity according to claim 8, wherein the kit is an RT-PCR kit or a DAN chip kit.
A microarray for predicting or diagnosing filamentous constitution specific abdominal obesity comprising the polynucleotide of any one of claims 1 to 6.
(a) amplifying or hybridizing with a probe the polymorphic site of the SNP marker of any one of claims 1 to 6 from DNA of an isolated sample; And
(b) determining the base of the amplified or hybridized polymorphic site of step (a), the method of providing information for predicting or diagnosing filamentous specific abdominal obesity.
According to claim 11, Of the base sequence determined in the step (b),
The rs29943 set forth in SEQ ID NO: 1, wherein the 101 st base is G;
The rs987237 set forth in SEQ ID NO: 2, wherein the 101 st base is A;
The rs6717858 set forth in SEQ ID NO: 3, wherein the 101 st base is T;
The rs1822438 set forth in SEQ ID NO: 4, wherein the 101 st base is C;
The rs6544366 set forth in SEQ ID NO: 5, wherein the 101 st base is T;
The rs1716685 set forth in SEQ ID NO: 6, wherein the 101 st base is C;
In rs632057 set forth in SEQ ID NO: 7, wherein the 101st base is G; or
The method according to rs6581830, set forth in SEQ ID NO: 8, wherein when the 101 st base is A, it is determined by specific abdominal obesity in the filamentous constitution.
According to claim 11, Of the base sequence determined in the step (b),
The rs17817449 set forth in SEQ ID NO: 9, wherein the 101 st base is G;
The rs1424233 set forth in SEQ ID NO: 10, wherein the 101 st base is A;
The rs9482771 set forth in SEQ ID NO: 11, wherein the 101 st base is G;
The rs6717858 set forth in SEQ ID NO: 12, wherein the 101 st base is C;
The rs4149270 set forth in SEQ ID NO: 13 wherein the 101 st base is T;
The rs1919484 set forth in SEQ ID NO: 14 when the 101 st base is G;
The rs1566732 set forth in SEQ ID NO: 15, wherein the 101 st base is A;
The rs857721 set forth in SEQ ID NO: 16, wherein the 101 st base is T; or
The method according to rs649729 set forth in SEQ ID NO: 17, wherein the 101-st base is A, the specific abdominal obesity determined in filamentous constitution.
According to claim 11, Of the base sequence determined in the step (b),
The rs6265 set forth in SEQ ID NO: 18, wherein the 101 st base is A;
The rs7561317 set forth in SEQ ID NO: 19, wherein the 101 st base is G;
The rs13130484 set forth in SEQ ID NO: 20, wherein the 101 st base is T;
The rs29943 set forth in SEQ ID NO: 21, wherein the 101 st base is A;
The rs1424233 set forth in SEQ ID NO: 22, wherein the 101 st base is G;
The rs2074356 set forth in SEQ ID NO: 23, wherein the 101 st base is C;
The rs4149270 set forth in SEQ ID NO: 24 wherein the 101 st base is C;
The rs6544366 set forth in SEQ ID NO: 25, wherein the 101 st base is G;
The rs17315646 set forth in SEQ ID NO: 26 wherein the 101st base is C;
The rs4667570 set forth in SEQ ID NO: 27, wherein the 101 st base is C; or
The method according to rs12485738 of SEQ ID NO: 28, wherein the 101-th base is G is determined as specific abdominal obesity that is noise in filamentous constitution.
The method of claim 11, wherein the base determination of step (b) is sequence analysis, hybridization by microarray, allele specific PCR, dynamic allele-specific hybridization technique (DASH), And PCR extension analysis, PCR-single strand conformation polymorphism (PCR-SSCP), PCR-restriction fragment length polymorphism (PCR-RFLP), and TagMan techniques.
(a) screening SNPs associated with phenotypes of obesity, hyperlipidemia, hypertension and hemophilia;
(b) selecting SNPs associated with the abdominal phenotype using multiple regression analysis among the selected SNPs of step (a);
(c) selecting SNPs that are related to the constitution by abdominal phenotype and abdominal obesity using multiple regression analysis among the SNPs selected in step (b); And
(d) calculating the GRS (genetic risk score) of the SNP selected in step (c) and performing multiple regression analysis as an independent variable to select specific SNPs for each constitution, filamentous constitution specific abdominal obesity Predictive or Diagnostic SNP Screening Method.

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