KR101546058B1 - SNP markers for metabolic syndrome and use thereof - Google Patents

Abstract

The present invention relates to a single nucleotide polymorphism (SNP) marker for predicting or diagnosing a metabolic syndrome specific to a sasang constitution. More specifically, the present invention relates to a method for predicting or diagnosing a metabolic syndrome such as Taeumin, Soyangin, A kit or microarray comprising the composition, a method for providing information for predicting or diagnosing a sasang constitution-specific metabolic syndrome using the marker, and a method for selecting a SNP for predicting or diagnosing a sasang constitution-specific metabolic syndrome will be.

Description

SNP markers for the prediction of metabolic syndrome and their uses {SNP markers for metabolic syndrome and use thereof}

The present invention relates to a single nucleotide polymorphism (SNP) marker for predicting or diagnosing a metabolic syndrome specific to a sasang constitution. More specifically, the present invention relates to a method for predicting or diagnosing a metabolic syndrome such as Taeumin, Soyangin, A kit or microarray comprising the composition, a method for providing information for predicting or diagnosing a sasang constitution-specific metabolic syndrome using the marker, and a method for selecting a SNP for predicting or diagnosing a sasang constitution-specific metabolic syndrome will be.

Metabolic syndrome refers to a condition with three or more of the five risk factors: abdominal obesity, hypertension, hypertriglyceridemia, low density (HDL) cholesterol, and hyperglycemia. Cardiovascular diseases such as diabetes and coronary artery disease, which threaten the health of modern people, are closely related to the metabolic syndrome and the prevalence of the metabolic syndrome is 23.7%.

On the other hand, in Sasang Constitution, people are classified into four constitutions: Taenin, Taeinin, Soyangin, and Soeumin. These four constitutions differ not only in response to drugs but also in appearance, body type, personality, book function and diet . In addition, the incidence rate of various cardiovascular metabolic diseases including metabolic syndrome is also different among the constitutional groups, and it is known that the incidence is higher in the order of noise, soybean, have.

These differences in disease susceptibility by constitution are thought to be due to differences in diet and activity. In other words, Tae-In has a high appetite and a lot of activity but a small amount of activity. Soo-ine eat at least a small amount of activity, and Soyangin has high activity even if it eats a lot of high appetite.

In addition, genetic differences by constitution are expected to play a role in the incidence of disease incidence, and it is considered that the constitution of sasang constitution does not change the constitution for a lifetime if it is inherited, and the constitution ratio in the population is Taeumin: Soyangin: : 2, since the theory of Sasang Constitution has been claimed, it has remained almost unchanged for more than 100 years. In the study of the inheritance of the constitutions of twins and households, it was found that the genetic inheritance of each constitution was around 50%.

Thus, because the constitution determined in the mother is not changed over the course of a lifetime, somatic formation and genetic differences are considered to be highly correlated. Individual genetic differences affect the onset of cardiovascular metabolic diseases, and genetic differences between constitutions are expected to affect disease severity, as is evidenced by recent population genetics studies.

Therefore, as in the case of recognizing the racial differences according to body shape, appearance, dietary life, genetic tendency among the Hwang, Caucasian, and black people from individualized medical viewpoint and performing group research by separating the genetic susceptibility identification by race, If the genetic varieties are different, performing association analysis of constitutional groups in one race will be more effective in revealing the genetic susceptibility of the disease.

In a recent genome-wide association study (GWAS), obesity and abdominal obesity such as body mass index, waist-to-hip circumference, blood pressure, triglyceride, cholesterol level, A number of SNPs (single nucleotide polymorphisms) have been identified that are associated with hypertension, hyperlipidemia, and diabetes-related phenotypes, and SNPs with reproducible reproducibility of association through a number of subsequent population studies have been published for each phenotype . However, there has not yet been a single SNP study in metabolic syndrome-related populations, and it is possible to identify genes that can predict the metabolic syndrome, which is significantly associated with sasang constitution, No indicator was found.

Under these circumstances, the inventors of the present invention conducted a study on the metabolic syndrome and major risk factors such as abdominal obesity, hypertension, hypertriglyceridemia, hypocholesterolemia and hyperglycemia in order to find a marker capable of effectively predicting the incidence of metabolic syndrome. SNP studies were carried out to identify the SNPs that predict the genetic risk of developing the metabolic syndrome by sasang constitution, thus completing the present invention.

One object of the present invention is to provide a single nucleotide polymorphism (SNP) marker for predicting or diagnosing a somatic sex specific metabolic syndrome.

Another object of the present invention is to provide a composition for predicting or diagnosing sagittal constitution-specific metabolic syndrome, which comprises a probe capable of detecting SNP markers for predicting or diagnosing the socio-structural-specific metabolic syndrome or an agent capable of amplifying .

It is another object of the present invention to provide a kit or microarray for predicting or diagnosing systolic-specific metabolic syndrome comprising a composition for predicting or diagnosing systolic blood pressure-specific metabolic syndrome.

Another object of the present invention is to provide a method for providing information for predicting or diagnosing a metabolic syndrome specific to a sasang constitution comprising the step of determining a polymorphic site of the SNP marker.

It is another object of the present invention to provide a method for screening SNP markers for predicting or diagnosing a somatic somatic-specific metabolic syndrome.

The present invention provides a single nucleotide polymorphism (SNP) marker, which is a single nucleotide polymorphism for predicting or diagnosing a sasang constitution-specific metabolic syndrome.

The marker preferably comprises, in the polynucleotides of SEQ ID NOS: 1 to 51, at least one polynucleotide selected from a polynucleotide comprising the 101st base of each sequence which is the SNP position and composed of 5 to 100 consecutive bases , Or a complementary polynucleotide of the same, or a marker for predicting or diagnosing a metabolic syndrome specific to a metabolic syndrome.

The term "polymorphism " used in the present invention refers to the case where two or more alleles exist in one locus, and among the polymorphic sites, It is called 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.

As used herein, the term "allele" refers to various types of a gene present at the same gene locus on a homologous chromosome. Alleles are also used to represent polymorphisms, for example, SNPs have two kinds of bialles.

The term " rs_id " used in the present invention means an independent marker rs-ID assigned to all SNPs initially registered by the NCBI that has started to accumulate SNP information since 1998. [ In the present invention, it is described in the same form as rs13130484. The rs_id shown in the above table means the SNP marker which is the polymorphism marker of the present invention. Those skilled in the art will readily be able to ascertain the location and sequence of the SNP using the rs_id. The specific sequence corresponding to rs_id, the number of the NCBI's Single Nucleotide Polymorphism Database (dbSNP), may change slightly over time. It will be apparent to those skilled in the art that the scope of the present invention also affects the altered sequence.

The above "SEQ ID NOS: 1 to 51" 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.

The SNP markers of the present invention are the markers shown in Table 2. When the polymorphic site of an SNP marker of an individual is an allele having an effect allele, the risk of the metabolic syndrome is high, You can do it. In the present invention, "effect allele" may be used in combination with "risk allele ".

The term " sasang constitution "used in the present invention means that the constitution of a human being is classified into four types, namely, a sun person, a soy lion, a taeeumin, and a noise person. . It is anticipated that more precise disease prediction or diagnosis will be possible if the disease incidence is different according to the constitution and it is possible to provide a sasang constitution-specific disease marker. Therefore, the inventors of the present invention for the first time found that metabolic syndrome SNP markers for prediction or diagnosis. For the purposes of the present invention, the metabolic syndrome provides SNP markers specific for Taeyein, Soyangin, and Soeum except for those with very low frequency in Koreans.

As used herein, the term "metabolic syndrome" can be used as a phenotypic marker for predicting cardiovascular metabolic diseases. The metabolic syndrome may increase the incidence of abdominal obesity, hypertension, low-density cholesterol, high neutropenia or hyperglycemia have. The SNP markers provided in the present invention can accurately predict the risk of metabolic syndrome expressing the phenotype of abdominal obesity, hypertension, low HDL cholesterol, high neutropenia or hyperglycemia, and furthermore, to determine the risk of cardiovascular metabolic diseases .

The term "prediction or diagnosis" as used herein includes all types of analyzes used to predict disease outbreaks and disease outbreaks, preferably to determine whether they are metabolic syndromes, It may be to predict the risk.

Preferably, the SNP marker is a SNP marker for predicting or diagnosing a metabolic syndrome specific to bait, wherein, among the polynucleotides consisting of SEQ ID NOS: 1 to 17, rs13130484 represented by SEQ ID NO: 1, wherein the 101st base is C A polynucleotide consisting of 5 to 100 contiguous bases comprising a second base, or a complementary polynucleotide thereof; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, in rs1424233 described in SEQ ID NO: 2; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or C, or a complementary polynucleotide thereof, in rs17782313 described in SEQ ID NO: 3; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is G or C, or a complementary polynucleotide thereof, in rs6235 described in SEQ ID NO: 4; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is T or G, or a complementary polynucleotide thereof, in rs1294421 represented by SEQ ID NO: 5; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is G or A, or a complementary polynucleotide thereof, in rs2605100 described in SEQ ID NO: 6; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is G or A, or a complementary polynucleotide thereof, in rs17249754 described in SEQ ID NO: 7; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is G or A, or a complementary polynucleotide thereof, in rs1133323 represented by SEQ ID NO: 8; A polynucleotide consisting of 5 to 100 consecutive bases comprising the 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, in rs6589566 described in SEQ ID NO: 9; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is T or G, or a complementary polynucleotide thereof, in rs6544366 described in SEQ ID NO: 10; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or G, or a complementary polynucleotide thereof, in rs10402271 described in SEQ ID NO: 11; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or C, or a complementary polynucleotide thereof, in rs3846663 described in SEQ ID NO: 12; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is A or T, or a complementary polynucleotide thereof, in rs2156552 represented by SEQ ID NO: 13; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is C or A, or a complementary polynucleotide thereof, in rs6586891 represented by SEQ ID NO: 14; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or C, or a complementary polynucleotide thereof, in rs5215 represented by SEQ ID NO: 15; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is C or T, or a complementary polynucleotide thereof, in rs163171 described in SEQ ID NO: 16; And rs7593730 described in SEQ ID NO: 17, a polynucleotide consisting of 5 to 100 consecutive bases comprising the 101st base having the 101st base of C or T, or a complementary polynucleotide thereof Or more polynucleotide.

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, 11 or more, 12 or more , At least 13, at least 14, at least 15, at least 16, and most preferably at least 17 SNP marker sets. The marker may be considered to be a high risk of a specific metabolic syndrome that is a bait if the 101st base of each SNP marker is the effect allelic base of Table 3. If it is not an effective allele base, Can be judged to be low, and the greater the number of SNP markers of an individual, the higher the accuracy can be.

Preferably, the SNP marker is SNP markers for predicting or diagnosing specific metabolic syndrome which is noise, wherein, in the polynucleotide consisting of SEQ ID NOs: 18 to 32, rs8050136 of SEQ ID NO: 18, wherein the 101st base is C A polynucleotide consisting of 5 to 100 contiguous bases comprising a base, or a complementary polynucleotide thereof; A rs4712652 described in SEQ ID NO: 19, wherein the polynucleotide is a polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or G, or a complementary polynucleotide thereof, in rs1294421 described in SEQ ID NO: 20; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is C or T, or a complementary polynucleotide thereof, in rs6005975 as set forth in SEQ ID NO: 21; 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, according to rs17249754 described in SEQ ID NO: 22; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is T or C, or a complementary polynucleotide thereof, according to rs4409766 described in SEQ ID NO: 23; A polynucleotide consisting of 5 to 100 consecutive bases comprising the 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, in rs17367504 described in SEQ ID NO: 24; 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, as set forth in SEQ ID NO: 25; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is C or T, or a complementary polynucleotide thereof, according to rs4149270 described in SEQ ID NO: 26; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is A or C, or a complementary polynucleotide thereof, in rs10889353 set forth in SEQ ID NO: 27; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, according to rs6589566 set forth in SEQ ID NO: 28; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is C or G, or a complementary polynucleotide thereof, in rs17315646 described in SEQ ID NO: 29; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or C, or a complementary polynucleotide thereof, in rs5215 described in SEQ ID NO: 30; 31. A rs163171 according to SEQ ID NO: 31, wherein the polynucleotide is 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; And rs7927129 described in SEQ ID NO: 32, polynucleotides composed of 5 to 100 consecutive bases comprising the 101st base having the 101st base of T or G, or complementary polynucleotides thereof, Polynucleotide < / RTI >

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, 11 or more, 12 or more Or more, 13 or more, 14 or more, and most preferably 15 SNP marker sets. The markers can be judged to be a high risk of noise-specific metabolic syndrome when the 101st base of each SNP marker is the effect allele base of Table 3. If the non-effector allele base is not a specific allelic base, Can be judged to be low, and the greater the number of SNP markers of an individual, the higher the accuracy can be.

Preferably, the SNP marker is a SNP marker for predicting or diagnosing a soybean-specific metabolic syndrome, wherein, in the polynucleotide of SEQ ID NO: 33 to 51, rs13130484 of SEQ ID NO: 33, wherein the 101st base is C A polynucleotide consisting of 5 to 100 contiguous bases comprising a second base, or a complementary polynucleotide thereof; A polynucleotide consisting of 5 to 100 consecutive bases comprising the 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, in rs1424233 described in SEQ ID NO: 34; 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, in rs7561317 described in SEQ ID NO: 35; 36. A polynucleotide according to rs2605100 as set forth in SEQ ID NO: 36, wherein the polynucleotide is composed of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is G or A, or a complementary polynucleotide thereof; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is C or T, or a complementary polynucleotide thereof, in rs4149270 described in SEQ ID NO: 37; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, according to rs6589566, set forth in SEQ ID NO: 38; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, according to rs4420638 set forth in SEQ ID NO: 39; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is G or A, or a complementary polynucleotide thereof, in rs261332 set forth in SEQ ID NO: 40; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is A or C, or a complementary polynucleotide thereof, in rs1566732 set forth in SEQ ID NO: 41; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is T or C, or a complementary polynucleotide thereof, according to rs6129647 described in SEQ ID NO: 42; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, according to rs10903129 set forth in SEQ ID NO: 43; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is G or A, or a complementary polynucleotide thereof, in rs1436955 described in SEQ ID NO: 44; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is G or C, or a complementary polynucleotide thereof, in rs7754840 described in SEQ ID NO: 45; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or C, or a complementary polynucleotide thereof, according to rs7767391 described in SEQ ID NO: 46; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is T or C, or a complementary polynucleotide thereof, in rs6475606 described in SEQ ID NO: 47; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base in which the 101st base is G or T, or a complementary polynucleotide thereof, in rs4402960 as set forth in SEQ ID NO: 48; A polynucleotide consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is A or G, or a complementary polynucleotide thereof, in rs864745 described in SEQ ID NO: 49; A polynucleotide consisting of 5 to 100 consecutive bases comprising the 101st base, wherein the 101st base is T or C, or a complementary polynucleotide thereof, in rs5215 described in SEQ ID NO: 50; And rs163171 set forth in SEQ ID NO: 51, polynucleotides consisting of 5 to 100 consecutive bases comprising a 101st base, wherein the 101st base is C or T, or complementary polynucleotides thereof, Polynucleotide < / RTI >

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, 11 or more, 12 or more Or more, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, and most preferably at least 19 SNP marker sets. The marker may be considered to be a high risk of Soyangin-specific Metabolic Syndrome when the 101st base of each SNP marker is the effect allelic base of Table 3. In case of non-effective allelic base, the risk of Soyangin-specific Metabolic Syndrome Can be judged to be low, and the greater the number of SNP markers of an individual, the higher the accuracy can be.

In the present invention, the metabolic syndrome refers to a phenotype associated with three or more risk factors among abdominal obesity, hypertension, hypertriglyceridemia, low HDL cholesterol, and hyperglycemia. Abdominal obesity means waist circumference greater than 90 cm for males and greater than 85 cm for females. Hypertension is defined as a systolic blood pressure greater than 130 mm Hg, diastolic blood pressure greater than 85 mm Hg, , And hypertriglyceridemia refers to a state in which triglyceride is greater than or equal to 150 mg / dL. Low HDL cholesterol has a high HDL cholesterol level of less than 40 mg / dL in males In women, and less than 50 mg / dL in women. Hyperglycemia refers to fasting blood glucose levels greater than 110 mg / dL or blood glucose control drugs.

The present inventors have confirmed through the following proof that the SNP is a marker for predicting or diagnosing a socio-trait specific metabolic syndrome. This study was designed to investigate the effects of metabolic syndrome on hypertension, hypertension, hypertriglyceridemia, hypercholesterolemia, hyperglycemia, and hypertension. After securing these established SNPs, 74 SNPs were selected (Table 2), and specific SNPs associated with the metabolic syndrome phenotype were selected for each constitution (Table 3). The specificity of each constitution was given as follows. For example, when a statistical analysis of a SNP set related to a metabolic syndrome phenotype in Taein, the other constitution, Soyangin, and Sooin, the metabolic syndrome and its five risk factors, abdominal obesity, hypertension, hypertriglyceridemia, Low-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and hyperglycemia. The genetic risk score (GRS) of the SNP was measured (Table 4), and the SNP having significance in the metabolic syndrome according to the sasang constitution was identified. Such SNPs were first identified by the present inventors.

As another embodiment of the present invention, there is provided a composition for predicting or diagnosing sagittal constitution-specific metabolic syndrome, which comprises a probe capable of detecting a marker for predicting or diagnosing metabolic syndrome by sagittal constitution or an agent capable of amplifying.

As used herein, the term " probe capable of predicting the metabolic syndrome or predicting metabolic syndrome according to the constitution of the present invention "refers to a specific sperm constitution and metabolic syndrome by specifically hybridizing with the polymorphic site of the above- And the specific method of such gene analysis is not particularly limited and may be by any gene detection method known in the art to which this invention belongs.

As used herein, the term "agent capable of amplifying a marker for predicting or diagnosing metabolic syndrome by sasang constitution" means that the polymorphic site of the above-mentioned gene is amplified to predict or diagnose a specific sasang constitution and metabolic syndrome Refers to a composition capable of specifically amplifying a polynucleotide of a marker for predicting or diagnosing metabolic syndrome according to the sasang constitution.

The primers used for the polymorphic marker amplification can be amplified by PCR using appropriate conditions in suitable buffers (e.g., four different nucleoside triphosphates and polymerase such as DNA, RNA polymerase or reverse transcriptase) and template-directed DNA Refers to a single stranded oligonucleotide that can serve 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, capable of forming a base pair with a complementary template, Quot; means a short sequence functioning as a starting point for < / RTI > The primers 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 socio-structural-specific metabolic syndrome through the production of desired products. The PCR conditions, the lengths of the sense and antisense primers can be modified based on what is known in the art.

The probes or primers of the present invention can be chemically synthesized using the phosphoramidite solid support method, 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, but are not limited to, methylation, "capping ", replacement of natural nucleotides with one or more homologues, and modifications between nucleotides, such as uncharged linkers, such as methylphosphonate, Phosphoamidates, carbamates, etc.) or charged linkages (e.g., phosphorothioates, phosphorodithioates, etc.).

In another embodiment, the present invention provides a kit for predicting or diagnosing a systolic blood sugar-specific metabolic syndrome comprising a composition for predicting or diagnosing a systolic blood sugar-specific metabolic syndrome.

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

The kit of the present invention can predict or diagnose a sasang constitution-specific metabolic syndrome by confirming SNP markers, which are predictive or diagnostic markers of sasang constitution-specific metabolic syndrome, or confirming the expression level of SNP markers with mRNA expression level have. As a specific example, in the present invention, a kit for measuring the level of mRNA expression of a sagittal constitution-specific metabolic syndrome prediction marker or a diagnostic marker may be a kit containing necessary elements necessary for performing RT-PCR. The RT-PCR kit includes a test tube or other appropriate container, a reaction buffer (pH and magnesium concentration varying), a test tube or other appropriate container, as well as a respective pair of primers specific for the gene of a sagittal constitution-specific metabolic syndrome prediction or diagnostic marker. Enzymes such as deoxynucleotides (dNTPs), Taq polymerase and reverse transcriptase, DNase, 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 a metabolic syndrome specific to a sasang constitution comprising 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 yet another embodiment, the present invention provides a microarray for predicting or diagnosing a sirtuinic-specific metabolic syndrome comprising polynucleotides of the sirtuinic-specific-specific metabolic syndrome prediction or diagnostic 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 predicting or diagnosing a metabolic syndrome specific to a sasang constitution by detecting an allele. The prediction or diagnosis method includes detection methods based on hybridization of nucleic acids such as Southern blot, and may be provided in a form pre-bonded to the substrate of a 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 5x SSPE (750 mM NaCl, 50 mM Na Phosphate, 5 mM EDTA, pH 7.4) and 2530 [deg.] C may be suitable for allele-specific probe hybridization.

The process of immobilizing the probe polynucleotide on the substrate associated with the prediction or diagnosis of the sagittal constitution-specific metabolic syndrome of the present invention can also be easily manufactured using this conventional technique. 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 embodiment, the present invention provides a method of amplifying a polynucleotide comprising: (a) amplifying or hybridizing a polymorphic site of the SNP marker from DNA of a separate sample; And (b) determining the base of the amplified or hybridized polymorphic site of step (a). The present invention also provides a method for providing information for predicting or diagnosing a metabolic syndrome.

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

The term "individual" of the present invention refers to a person who is predicting or diagnosing a socio-structural-specific metabolic syndrome, wherein the socio-structural-specific metabolic syndrome can determine whether a specific metabolic syndrome is Taeiin, Soyangin or Silent. DNA can be obtained from the 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.

The term "SNP chip" used in the present invention means one of DNA microarrays capable of confirming each base of several hundred thousand SNPs at a time.

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, and the nucleic acid having the same base as the dodecoxynucleotide is excluded in the dNTP mixture, and the dodecoxynucleotide indicates the SNP Base type. For example, when dGTP, dCTP and TTP mixture and ddATP are added to the reaction in the presence of substitution from A to G, the primer is extended by the DNA polymerase in the base in which the substitution has occurred, The primer extension reaction 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 the step (b), in the case of rs13130484 described in SEQ ID NO: 1, the 101st base is T; In rs1424233 described in SEQ ID NO: 2, when the 101st base is G; In rs17782313 described in SEQ ID NO: 3, when the 101st base is C; In rs6235 described in SEQ ID NO: 4, when the 101st base is G; In rs1294421 described in SEQ ID NO: 5, when the 101st base is T; In rs2605100 described in SEQ ID NO: 6, when the 101st base is G; In rs17249754 described in SEQ ID NO: 7, when the 101st base is G; In rs1133323 described in SEQ ID NO: 8, when the 101st base is G; In rs6589566 described in SEQ ID NO: 9, when the 101st base is G; In rs6544366 described in SEQ ID NO: 10, when the 101st base is T; In rs10402271 described in SEQ ID NO: 11, when the 101st base is G; In rs3846663 described in SEQ ID NO: 12, when the 101st base is T; In rs2156552 described in SEQ ID NO: 13, when the 101st base is T; In rs6586891 described in SEQ ID NO: 14, when the 101st base is C; In rs5215 described in SEQ ID NO: 15, when the 101st base is C; In rs163171 described in SEQ ID NO: 16, when the 101st base is C; And rs7593730 described in SEQ ID NO: 17, when the 101st base is T, it can be judged to be the obesity-specific metabolic syndrome obesity in sasang constitution. The polymorphic site is considered to be a risk allele, and the higher the frequency of the allele, the higher the risk of a specific metabolic syndrome.

Preferably, in the base sequence determined in the step (b), in the case of rs8050136 of SEQ ID NO: 18, when the 101st base is C; In rs4712652 described in SEQ ID NO: 19, when the 101st base is A; In rs1294421 described in SEQ ID NO: 20, when the 101st base is T; In rs6005975 described in SEQ ID NO: 21, when the 101st base is C; In rs17249754 described in SEQ ID NO: 22, when the 101st base is A; In rs4409766 described in SEQ ID NO: 23, when the 101st base is T; In rs17367504 described in SEQ ID NO: 24, when the 101st base is G; In rs1716685 described in SEQ ID NO: 25, when the 101st base is T; In rs4149270 described in SEQ ID NO: 26, when the 101st base is C; In rs10889353 described in SEQ ID NO: 27, when the 101st base is A; In rs6589566 described in SEQ ID NO: 28, when the 101st base is G; In rs17315646 described in SEQ ID NO: 29, when the 101st base is C; In rs5215 described in SEQ ID NO: 30, when the 101st base is C; In rs163171 described in SEQ ID NO: 31, when the 101st base is C; Or rs7927129 of SEQ ID NO: 32, if the 101st base is T, it can be judged to be a noise-specific metabolic syndrome in sasang constitution. The polymorphic site is judged to be a risk allele, and the higher the frequency of the allele gene, the higher the risk of the noise specific metabolic syndrome. More preferably at least one polymorphic site of SEQ ID NOS: 18 to 32, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 Or more, more than 11, more than 12, more than 13, and more than 14 are risk alleles, the risk allele of the risk allele is most preferably 15, which is considered to be a higher risk of noise specific metabolic syndrome. If the 101 < th > base is not the base of the effect allele of Table 3, it can be judged that the risk of metabolic syndrome is low.

Preferably, in rs13130484 of SEQ ID NO: 33 among the nucleotide sequences determined in the step (b), when the 101st base is T; In rs1424233 described in SEQ ID NO: 34, when the 101st base is A; In rs7561317 described in SEQ ID NO: 35, when the 101st base is G; In rs2605100 described in SEQ ID NO: 36, when the 101st base is A; In rs4149270 described in SEQ ID NO: 37, when the 101st base is T; In rs6589566 described in SEQ ID NO: 38, when the 101st base is G; In rs4420638 described in SEQ ID NO: 39, when the 101st base is G; In rs261332 described in SEQ ID NO: 40, when the 101st base is G; In rs1566732 described in SEQ ID NO: 41, when the 101st base is A; In rs6129647 described in SEQ ID NO: 42, when the 101st base is C; In rs10903129 described in SEQ ID NO: 43, when the 101st base is G; In rs1436955 described in SEQ ID NO: 44, when the 101st base is A; In rs7754840 described in SEQ ID NO: 45, when the 101st base is C; In rs7767391 described in SEQ ID NO: 46, when the 101st base is T; In rs6475606 described in SEQ ID NO: 47, when the 101st base is T; In rs4402960 described in SEQ ID NO: 48, when the 101st base is T; In rs864745 described in SEQ ID NO: 49, when the 101st base is A; In rs5215 described in SEQ ID NO: 50, when the 101st base is C; Or in the case of rs163171 described in SEQ ID NO: 51, when the 101st base is C, it can be judged as a Soyangin-specific metabolic syndrome in sasang constitution. The polymorphic site is considered to be a risk allele, and the higher the frequency of the allele, the higher the risk of a soybean-specific metabolic syndrome. More preferably at least one polymorphic site of SEQ ID NOS: 18 to 28, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 And more preferably at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, and at least 18 of the risk alleles, The risk of metabolic syndrome is high. If the 101 < th > base is not the base of the effect allele of Table 3, it can be judged that the risk of metabolic syndrome is low.

As yet another embodiment, the present invention provides a method for screening a SNP for predicting or diagnosing a somatic sex specific metabolic syndrome.

(A) selecting SNPs that are associated with a phenotype of abdominal obesity, hypertension, hypertriglyceridemia, low HDL cholesterol, or hyperglycemia; (b) selecting SNPs associated with the metabolic syndrome phenotype using multiple regression analysis among the selected SNPs of step (a); (c) selecting SNPs that are constitutionally related to the metabolic syndrome phenotype using multiple regression analysis among SNPs selected in step (b); And (d) calculating a genetic risk score (GRS) of the SNPs selected in the step (c), and performing multiple regression analysis on the SNPs as independent variables to select specific SNPs specific to the constitution. Syndrome prediction or diagnostic SNP screening method.

Non-limiting examples of phenotypes of abdominal obesity, hypertension, hypertriglyceridemia, low HDL cholesterol, or hyperglycemia in step (a) include obesity phenotypes such as body mass index, waist circumference, waist-to-hip circumference ratio, Lipid phenotype such as high density cholesterol, low density cholesterol, triglyceride; Blood pressure phenotypes such as systolic blood pressure, diastolic blood pressure, and hypertension; Fasting blood glucose, type 2 diabetes, and the like.

The metabolic syndrome phenotype of step (b) means that the at least three phenotypes of abdominal obesity, hypertension, hypertriglyceridemia, low-density cholesterol, or hyperglycemia are present. According to one embodiment of the present invention, 74 SNP sets were selected by performing the above-mentioned steps (a) and (b) (Table 2).

Although the step (c) is not limited thereto, it is preferable to select the SNPs having a correlation of the P <0.05 with the five phenotypes of the metabolic syndrome, and analyze the association of the selected SNPs with the metabolic syndrome It is possible to exclude SNPs whose orientation is different from that of individual factors.

The GRS calculation in the step (d) is not limited thereto. For example, when the non-risk allele is 2, the heterozygosity is 1, The simple count method for calculating all genotypes of selected SNPs and the beta coefficients of multiple regression analysis for each SNP multiplied by the genotype score are all added and the genotype score is divided by the maximum total score multiplied by the beta coefficient It may be a GRS determined by a weighted count method of multiplying the maximum risk allele number. Regression analysis is performed on the metabolic syndrome and the related phenotype using the GRS as the independent variable, and it is possible to select the maximum constitution specific SNP that guarantees specificity by constitution. In the embodiment of the present invention, 17 cases of Taeumin, 15 cases of Sohin, and 19 cases of Soyangin were selected (Table 3).

The screening method of the present invention is advantageous in that SNPs showing more specificity can be selected by constitution without predicting the genetic risk for the metabolic syndrome in the whole population.

The SNP markers of the present invention are specific SNP markers for predicting or diagnosing a sasang constitution-specific metabolic syndrome, so that the risk prediction can be more accurate and objective diagnosis and risk prediction can be predicted.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 shows a simplified flow diagram of a method for selecting SNPs of the present invention.
Fig. 2 shows the detailed phenotype distribution of the metabolic syndrome according to the present invention.

Hereinafter, the present invention will be described in more detail by way of examples. It should be understood, however, that these examples are for illustrative purposes only and are not to be construed as limiting the scope of the invention.

Example  1: Selection of subjects and phenotype standard for metabolic syndrome

(1) Selection of subjects

The subjects were 3,117 people collected from 22 oriental medicine clinics from 2006 to 2012, and those who had confirmed their constitution by watching the reaction of oriental medicine to Sasang Constitutional Herbal Medicine. The confirmation of the spermatogenesis prescribes those who do not have side effects when the spermatozoa prescription basically consumes 60 tablets (usually one month's intake) and the improvement response to the constitution is pronounced. (However, But it is also applicable when the constitution is determined through a recently developed Sasang Constitutional Analysis Tool (SCAT). The subjects agreed in writing to the study and underwent a study ethics review by the institution.

The clinical characteristics of the subjects were as follows. As shown in Table 1 below, Soyangin (SY) and Soybean (TE) were significantly higher than Soein (SE) And the prevalence of metabolic syndrome was high. This is consistent with the characteristics of each constitution, that is, Taeumin has a strong energy storage function, has a tendency to have a high appetite and intake, has a static tendency, Soyangin is known to have a strong digestive function, , And noise is consistent with each characteristic known to have a tendency to lower appetite and intake due to its static and weak digestive function.

In the following Table 1, clinical characteristic values are expressed as mean ± standard deviation, or%.

(2) Metabolic syndrome and detailed phenotypic criteria setting

The metabolic syndrome was defined by the guidelines of the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) for five risk factors: abdominal obesity (including obesity), hypertension, hypertriglyceridemia, low HDL cholesterol and hyperglycemia. Based on the modified Korean version, it was set to have 3 or more risk factors among 5 risk factors.

Abdominal obesity is defined as waist circumference greater than 90 cm for males and greater than 85 cm for females. Hypertension is defined as systolic blood pressure greater than 130 mm Hg, diastolic blood pressure greater than 85 mm Hg, Hypertriglyceridemia is more than 150 mg / dL in hypertriglyceridemia, low HDL cholesterol level is lower than 40 mg / dL in men and 50 mg / / dL, and hyperglycemia refers to a state in which fasting blood glucose is at least 110 mg / dL or a blood sugar controlling drug.

Example  2: SNP  Conflicting genotyping

The five risk factors for metabolic syndrome, which are also risk factors for cardiovascular metabolic disease, are the body mass index (BMI), waist circumference, waist-hip Obesity phenotype such as circumference ratio; Lipid phenotype such as high density cholesterol, low density cholesterol, triglyceride; Blood pressure phenotypes such as systolic blood pressure, diastolic blood pressure, and hypertension; (SNPs) that have been established through repetitive reproducibility genome-wide association studies (GWAS) for diabetic phenotypes such as fasting plasma glucose and type 2 diabetes. In Asian populations, only one SNP with a minor allele frequency of less than 5% and a strong linkage (r ² ≥ 0.8) in the same locus in LD (linkage disequilibrium) analysis was selected, Respectively.

Of the total of 3,117 subjects, 954 subjects who had allelic genotypes determined by the Affymetrix Genome-Wide Human SNP array 5.0 (Affymetrix Santa Clara, CA, USA) were selected as SNPs that existed in Affymetrix (proxy SNP: r ² &gt; 0.6).

A total of 74 SNPs (Table 2) were collected for 954 individuals, and the remaining 2,163 SNP allele genotypes were determined. In this case, the genotyping method used is a method of determining through unlabeled oligonucleotide probe (UOP). When the temperature of the complementary DNA strand at the SNP position is gradually increased in a real-time PCR apparatus called LightCycler 480, The DNA strand separation is performed at a relatively high temperature. As a result, the melting pattern through UOP genotyping has three patterns according to major homozygote, heterozygote and minor homozygote, and SNP allele genotype can be determined accordingly.

Example  3: Statistical association analysis

Correlation variables were analyzed by multiple logistic regression analysis. Gender, age, daily food intake (categorical type), daily activity (categorical type), and presence or absence of chronic diseases were used. Among the subjects, 690 had hypertension, hyperlipidemia, and one or more of diabetes mellitus, which may affect the metabolic syndrome association analysis.

The genetic risk score (GRS) was measured by a weighted count method that measures the effect size on the metabolic syndrome. First, genotype scores for individual SNPs were calculated to be 0 for two nonrisk alleles, 1 for hetero and 2 for risk allele (effect allele in Table 3). Assuming that 10 SNP sets were selected, the weighted count method multiplies the genetic score by multiple regression analysis of the metabolic syndrome of each SNP obtained for each constitution, adds the allele genotype score of 10 SNPs, Is multiplied by the beta coefficient, divided by the maximum possible score, and then multiplied by 20, the maximum risk allele number. In this way, we can obtain the GRS for each constitution reflecting the weight value of each SNP uniquely obtained for each constitution, and the logistic regression analysis for the metabolic syndrome and the related phenotype is performed in the same manner as described above, using the obtained GRS as an independent variable Respectively. Statistical significance was P <0.05 for the association analysis of individual SNPs for the five detailed phenotypes of the metabolic syndrome. For the SNP set, P <0.005 for the whole group analysis, P &lt; 0.05 for comparative analysis.

Example  4: Screening for association of metabolic syndrome with 5 risk factors associated with constitution

After all the allele genotypes of 74 SNPs were determined in a total of 3,117 subjects, SNPs that did not deviate from the Hardy - Weinberg equilibrium were analyzed for constitutional factors by metabolic syndrome and 5 related risk factors. First, after screening SNPs that are related to the five risk factors of metabolic syndrome (P <0.05) by constitution, the association of selected SNPs with metabolic syndrome was analyzed and the direction of the association was different from that of individual risk factors SNPs (eg, OR> 1 for individual risk factors or OR <1 for metabolic syndrome) were excluded. As a result, for the analysis to calculate the genetic risk score (GRS), 17 SNPs were selected for Tae - In, 15 SNs, and 19 SNs. Table 3 below shows the selection of SNPs with specificity-specific associations for the metabolic syndrome phenotype, and the above series of studies are shown in Fig.

Example  5: Metabolic syndrome by constitution SNP  set GRS Association analysis

(1) GRS analysis by constitution for metabolic syndrome

Each constitutional group is divided into four subgroups (quartile) according to the GRS, followed by the remaining three groups based on the lowest quartile, with the highest GRS being the lowest quartile Of the metabolic syndrome.

The range of GRS of Taeumin was 4.15 ~ 26.04 and the mean value of GRS was 11.51 ~ 27.17, the mean value was 20.44 and the range of GRS of Soyangin was 7.68 ~ 30.25 and the mean value was 18.03. The OR value of GRS for each subgroup compared to the lowest group tended to increase as the GRS value increased for all three constituents (Table 4). Therefore, from the comparison of the highest quartile to the lowest quartile showing the maximum OR value, the taeeumin was 2.80 times (P = 4.78 × 10 ^-8 ), the noise was 2.37 times (P = 1.87 × 10 ^-2 ) (P = 4.67 × 10 ^-5 ), the risk of developing metabolic syndrome was increased. However, in the case of the so-called noise, the genetic risk for the metabolic syndrome was remarkably exhibited only in the highest group, as in the clinical characteristics of the above Table 1, the lowest metabolic syndrome prevalence and related phenotype values.

According to the GRS, GRS itself is divided into consecutive numbers and the genetic risk of the metabolic syndrome is calculated as 1.14 times (P = 1.24 × 10 ^-9 ) and 1.18 times (P = 1.20 × 10 ^-3 ), and Soyangin was 1.16 times (P = 1.30 × 10 ^-8 ), indicating an increased risk of metabolic syndrome (Table 4).

(2) GRS distribution trends of five risk factors of metabolic syndrome

A detailed phenotypic analysis was performed to examine the differences in the five risk factors associated with the distribution of GRS in the metabolic syndrome, namely, abdominal obesity, hypertriglyceridemia, low HDL cholesterol, hypertension and hyperglycemia (FIG. 2).

As expected, the association of the five risk factors of metabolic syndrome was stronger in all constitutional groups than in the GRS lowest group, but there was a difference in the type of risk factors . Specifically, in the case of taeumin, the lowest group vs. In the middle and lower group, only low-density-cholesterol was associated with GRS, hypertriglyceridemia and low HDL-cholesterol were strongly associated with abdominal obesity in the mid-upper gastrointestinal group, In addition, hypertension was strongly correlated with hyperglycemia. Therefore, the major risk factors for metabolic syndrome in Taein are hypertriglyceridemia and low HDL cholesterol.

Interestingly, hyperglycemia is the lowest group. There was strong association from the middle to the top group. In addition, hypertriglyceridemia was more strongly associated with abdominal obesity than with hypertriglyceridemia. Therefore, hyperglycemia and hypertriglyceridemia can be considered as major risk factors for metabolic syndrome.

Finally, in Soyangin, the lowest group vs. In the middle and lower group, abdominal obesity and low HDL cholesterol were weakly related, and in the hyperlipidemic group, hyperglycemia was strongly associated with hypertriglyceridemia. Therefore, the major risk factors for metabolic syndrome in Soyangin are abdominal obesity, low HDL cholesterol, and hyperglycemia.

Based on the above examples, SNPs that have been linked to the trait related to the metabolic syndrome through various GWAS studies from the present invention were constructed to constitute a genetic risk (GRS) prediction SNP set of constitutionally specific metabolic syndrome And the prevalence of metabolic syndrome was also found to increase with increasing GRS.

The risk factors for the metabolic syndrome were hypertriglyceridemia and low-density-cholesterolemia, and the risk factors for metabolic syndrome were hyperglycemia and hypercholesterolemia. Hypertriglyceridemia, hypertriglyceridemia, hyperglycemia, and hyperglycemia were the major risk factors for major metabolic syndrome. Therefore, it is important to determine which subgroup (quartile) the individual GRS belongs to after the preliminary diagnosis of constitution for prevention of personalized cardiovascular metabolic diseases.

The present invention provides a method for screening a SNP for metabolic syndrome by measuring the SNP associated with metabolic syndrome by selecting SNPs that are related to the five risk factors of the metabolic syndrome without limiting the prevalence of the metabolic syndrome to the metabolic syndrome And that the individual SNPs used to predict genetic risk for the metabolic syndrome are highly valued and highly correlated with respect to the cardiovascular metabolic disease phenotype in several populations Since it has been reproduced, it is less likely to contain false positives.

The strategic methodology used in the present invention is highly utilized because it can be used to diagnose constitutional problems of a sasang constitutional specialist as well as to determine a constitution over a certain level even if the drug is not used in conjunction with an objective constitutional diagnosis tool (SCAT) , Which is expected to constitute a more reliable set of metabolic syndrome SNPs for more constitutional populations.

<110> Korea Institute of Oriental Medicine <120> SNP markers for metabolic syndrome and use thereof <130> PA130915 / KR <160> 51 <170> Kopatentin 2.0 <210> 1 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 1 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> 2 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 2 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> 3 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = T or C <400> 3 tctacctacc atgttcttgg aagcaggaaa accagaatat atgtgagcat ctttaatgac 60 tacaacatta tagaagttta aagcaggaga gattgtatcc ygatggaaat gacaagaaaa 120 gcttcagggg gaaggtgaca tttaagttgg aatattattg aggagtatca ttttagcatc 180 tgggattgag gtagctttgt g 201 <210> 4 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> S = G or C <400> 4 gagttggagg agggagcccc ttcccaggcc atgctgcgac tcctgcaaag tgctttcagt 60 aaaaactcac cgccaaagca atcaccaaag aagtccccaa stgcaaagct caacatccct 120 tatgaaaact tctacgaagc cctggaaaag ctgaacaaac cttcccagct taaagactct 180 gaagacagtc tgtataatga c 201 <210> 5 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> K = T or G <400> 5 ctgagagtta accgagttag gagccacagc ctttacagaa aagatggatg aaagctggag 60 atgaacctga catacataag gtaccaggac tgaatcctat kcatttgaca gatgcaaaca 120 gtcttcatcc aggctctgct ggaaggcaac cagtggaggc ttacctggct ccagtgcagg 180 gctcagcagc aaacctggac c 201 <210> 6 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 6 tgcagacttc caggagtgaa ataacagaaa acaaccagtg actcaccgtg acactggaaa 60 tggctgtgaa gaacgcagaa tgctgagagc caactgtcca rtggatgaac atgagaaaga 120 actaagacaa cccctcgatt tcctaaatat gccaaaggaa agcctccctt ggggaatggc 180 tgatgcttgg aatatagatg g 201 <210> 7 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 7 tccatcagaa ttttttctca gtcatatatg atccacggac atatctctaa cttcctgtca 60 tgttcctctt tcaattccaa gaccttctta aattactcca rctctttcca gggtcctcaa 120 gtctgctcca agaccttgct tccttgattg ccactgcaag ctaccaccac ttccatcccc 180 tttctcttgg tttcctcaga c 201 <210> 8 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 8 tttaaaagtg gtcactgaga tagtcttgag gatgtgctat gcagtagcca agccctctta 60 cggtgtgttc ctctcttagt gcccctttcc tttcctacct rttcttccct tgcagtggtg 120 tattagcctt ggacattaaa acatttgctt tgtaaatttg gaggcattct gattaaacag 180 ctgagtaaaa caaatcctgc t 201 <210> 9 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 9 gtggaaggtc ccagaaattt tatttcccat gcactttttc ccaggaagct actggagaag 60 atgctctaac aaaataaggg agaaaaacaa gaaagaagac rtggaatata gaaaaccaga 120 agagggccag gtgcggtggc tcacgcctgt aatcccagca ctttgggaag cccaggcagg 180 cagatcacga ggtcaggagt t 201 <210> 10 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> K = T or G <400> 10 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> 11 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> K = T or G <400> 11 ggtttagaac aagcaggcac aagaattcca tagagacaca ctgtgatgga ggttgtcata 60 tctgcacagt ccattcattg gaggtgtggg gatcagtagc ktgggtcaag tagtttgtat 120 ctatctagct gtcccataca gagatggtcc catacaggag gaggtgagat aaagctgata 180 ccttgatcaa ctccagtaag a 201 <210> 12 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = T or C <400> 12 atattatgtt agctatggta ttatgcactg tcaggtgtgg ctgtcaagtc ttggaaagtt 60 agtgcttcca gtggagtcta gttctattct gatgccatta yagttgccct gtttttagtt 120 gatttagtaa gaaattggtc atgattttaa gggtgaatct tgttgtgtct ctccctggct 180 acagatgcta ggtgttcaag g 201 <210> 13 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> W = A or T <400> 13 cttggggagg acaactctga tctgttttct gaggctggac gcaacatgaa ggaggtctta 60 gaacatttta accaattaaa gagctgaaag gagaagtcag wtacaatggc aagcagctac 120 ctgggtgata acgaaatcca cgcacaatca agatattcca ccttcgtagc agggatgtct 180 ggaggggctg cagagtcccc c 201 <210> 14 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> M = C or A <400> 14 cacagaagga cattctgtaa aatgatgatc ctggatcctt aaaacatgtc agtatcatga 60 aagacaaaaa gaggctggga taccagatta aagaagccta maatatcatg acaactaaat 120 gcagtgcatg atccttgatt ggatcttgat ctaaacatat atatacatat atatgacatt 180 attgatacaa ctggagaaat t 201 <210> 15 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> N = T or C <400> 15 ttgcgcaggg gcccgcgggc tgaggcgagg gtcagagctt ccagtaggct gtggtcctca 60 tcaagctggc gggccgtgca gagtggtgtg ggcactttga nggtgttgcc aaacttggag 120 tagtccacag agtaacgtcc gtcctcctca gctacaatgg gcacaaagcg ctggccccac 180 aggatctcat cggccaggta g 201 <210> 16 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 16 tttgatttgc caggagcaga atttctgggt tggaatcggg aacatttaga ggagcttctc 60 agtagagttg tacagagtgg aaatgagtcg gcaggctgca yggggggttc cagtcacagc 120 acagagggtg tgtgttttcg gtgcctgccc tcctgagctc caagtgtccc acgcctgccc 180 gtcagtcctc atgtctacct g 201 <210> 17 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 17 tggatgtttt tttagacatc tgttgtccat gctaacacgc aacaaagctc tgtggataca 60 cacacaggca tgtacatgca caaactctct ctctctcata yagtttcagc aggtcataaa 120 tgagaaccca gctacaatga aatgatacaga cttttactga tggatattta agttttttcc 180 ttcaattttg ctattgtcaa c 201 <210> 18 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> M = C or A <400> 18 atcactttaa actcggtatt tgatttcctt ttccctggga cctgtgacag tgccagcttc 60 atagcctagt ctaggcatgc cagttgccca ctgtggcaat maatatctga gcctgtggtt 120 tttgccttag gtaaactgta gagatggact catggaatgc ttggaaaatt tttcagttta 180 tgataatgtg taaatgtcga g 201 <210> 19 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 19 gtctttcttc agtatccctg cttggacagt ggttttgccc ccattgtgca caacactttt 60 ccaaaaagcc tttcaacatt aattatggct ggagctgact rctttcctca gaccatcatg 120 cttctcctaa tacaataaat gtttctcttg ctgggcaggt ggatgattgg attgatgaat 180 ggatgcatg ggatgggcag g 201 <210> 20 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> K = T or G <400> 20 ctgagagtta accgagttag gagccacagc ctttacagaa aagatggatg aaagctggag 60 atgaacctga catacataag gtaccaggac tgaatcctat kcatttgaca gatgcaaaca 120 gtcttcatcc aggctctgct ggaaggcaac cagtggaggc ttacctggct ccagtgcagg 180 gctcagcagc aaacctggac c 201 <210> 21 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 21 tgggcgacag agctgtctca aaagaaagaa aaggaaggga aagaaggaag gaaataggga 60 accatagcct gaatataaaa catctgcttt atctgtcagg ycttttccta cctggaagac 120 taagagactc tcaaggcctt ggaggaaaaa tattccaagc atctaccctt caaaattacc 180 taatcatgag tggagaggga c 201 <210> 22 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 22 tccatcagaa ttttttctca gtcatatatg atccacggac atatctctaa cttcctgtca 60 tgttcctctt tcaattccaa gaccttctta aattactcca rctctttcca gggtcctcaa 120 gtctgctcca agaccttgct tccttgattg ccactgcaag ctaccaccac ttccatcccc 180 tttctcttgg tttcctcaga c 201 <210> 23 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = T or C <400> 23 cttggcttta cattacaaca gcccctgcct tcaaggcaac cacaactccc attgagtctg 60 ttttctaaat gtctcacaaa tcctttgttt ctttttttct yggctacttc tgtgtttcag 120 gccatcctca ttccttgctt agagtactgc tgtgtcatcc taaccaatct ctctgcctca 180 ttccccactc tagtccacct g 201 <210> 24 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 24 aagttccctc aaagaataca gtgtgagaat caacattttt aacccattga agagtgtgtc 60 taaaatacct tgacactgtg gagggacttt tacaggcaac rgagaagttg cagatcagat 120 gacccactct gccttctcct tcctgccccc tccggctgct tttttctgcc gggttaaagg 180 gcagcccagc ctcagggctg a 201 <210> 25 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 25 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> 26 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 26 cccaagtccc ctctatgtct gagagctgag gctggctgtc aaagaggaac taaggatgcc 60 agggactttc tgcttaggac ccctctcatc acttctccaa ygctggtatc atgaacccca 120 ttctacagat gatgtccact agattaagaa tggcatgtga ggccaagttt ccacctgaga 180 gtcagtttta ttcagaagag 201 <210> 27 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> M = A or C <400> 27 atgcccctat attccaatcc tgactactct attttttggt ttgtgggatc tcagagaagt 60 tacctaacta ctctgagcct gagccacctt atctgttaaa mccttaaatg agatgagtgc 120 aaagtgccca ataaaatgcc cagcacacaga taaacccata aatgttaatt ctcttatcct 180 cttgcctaaa ccaaggttaa c 201 <210> 28 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 28 gtggaaggtc ccagaaattt tatttcccat gcactttttc ccaggaagct actggagaag 60 atgctctaac aaaataaggg agaaaaacaa gaaagaagac rtggaatata gaaaaccaga 120 agagggccag gtgcggtggc tcacgcctgt aatcccagca ctttgggaag cccaggcagg 180 cagatcacga ggtcaggagt t 201 <210> 29 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> S = C or G <400> 29 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> 30 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> N = T or C <400> 30 ttgcgcaggg gcccgcgggc tgaggcgagg gtcagagctt ccagtaggct gtggtcctca 60 tcaagctggc gggccgtgca gagtggtgtg ggcactttga nggtgttgcc aaacttggag 120 tagtccacag agtaacgtcc gtcctcctca gctacaatgg gcacaaagcg ctggccccac 180 aggatctcat cggccaggta g 201 <210> 31 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 31 tttgatttgc caggagcaga atttctgggt tggaatcggg aacatttaga ggagcttctc 60 agtagagttg tacagagtgg aaatgagtcg gcaggctgca yggggggttc cagtcacagc 120 acagagggtg tgtgttttcg gtgcctgccc tcctgagctc caagtgtccc acgcctgccc 180 gtcagtcctc atgtctacct g 201 <210> 32 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> K = T or G <400> 32 aggtggtgag gctataggtg ttagatgtgg caggatgcaa gccagggcct gctgccttta 60 aagagccaca gcagagacac catcccagtc ccaagagctg ktctaaggaa gtggttgtca 120 tctgcggtgc cccccagggg acatatggca atgtctggag atatttttgg ctatcatgac 180 tatgggagaa ttactaatat c 201 <210> 33 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 33 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> 34 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 34 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> 35 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 35 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> 36 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 36 tgcagacttc caggagtgaa ataacagaaa acaaccagtg actcaccgtg acactggaaa 60 tggctgtgaa gaacgcagaa tgctgagagc caactgtcca rtggatgaac atgagaaaga 120 actaagacaa cccctcgatt tcctaaatat gccaaaggaa agcctccctt ggggaatggc 180 tgatgcttgg aatatagatg g 201 <210> 37 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 37 cccaagtccc ctctatgtct gagagctgag gctggctgtc aaagaggaac taaggatgcc 60 agggactttc tgcttaggac ccctctcatc acttctccaa ygctggtatc atgaacccca 120 ttctacagat gatgtccact agattaagaa tggcatgtga ggccaagttt ccacctgaga 180 gtcagtttta ttcagaagag 201 <210> 38 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 38 gtggaaggtc ccagaaattt tatttcccat gcactttttc ccaggaagct actggagaag 60 atgctctaac aaaataaggg agaaaaacaa gaaagaagac rtggaatata gaaaaccaga 120 agagggccag gtgcggtggc tcacgcctgt aatcccagca ctttgggaag cccaggcagg 180 cagatcacga ggtcaggagt t 201 <210> 39 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 39 gaggtgaagt tacttgtata aggtcacaca gccaggaagt agagaactgg aactagattg 60 aaccctcagc ctagcaatgt cactatgcta cacttttcct rgtgtggtct acccgagatg 120 aggggctgag gttttttttt gtttttgttt ctgttttgag gcagactcac tctctccccc 180 aggatggagt acagtggtgc g 201 <210> 40 <211> 199 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 40 tattatgtga gatatcaata tttccttcat tagaaattaa aactgagaaa tctttaaaat 60 ctgctaacac tttttaaaat gataataaac ccttgcatrt taacacatat aatgtaattt 120 tatgaaaaat aacttgtatt ttccaaataa gttttaaatg gagaagagtg acattgtttt 180 acaaagaaat gttgcaaat 199 <210> 41 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> M = A or C <400> 41 ttcatcatac ccacccagat ttttagccct gtgtgtgcat acctgttgga aacaaagacc 60 acatttccca gctcccatgg agctagatgt tgcaatgtga mtaagttttg ctcaacgaag 120 catgagcaga ggtactgggt gacttctagg aagtgtcctt taagggtggg gcacaacctt 180 ctgcccttcc tccttcttat 201 <210> 42 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = T or C <400> 42 ggcccttctc aataggttac tatttatagg aacatacaca gagttgctgt acccagacat 60 gtgagcccca gtgatgagat ttctggtcca gtggaaacat ytgaaagtcg ttacttaaaa 120 tgttaccaag acagccacag gcaggctctg tatgtgccct cagtcaacaa aatcttcccc 180 accctcctct aagactctaa g 201 <210> 43 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 43 ttgccattac tgagaggaca ggaaagctgg gattgagatg gatggctact agcagagcca 60 gtaaaatatt ccacagactc atttctgtag tgaggaccaa rtgaactaaa tggccattag 120 tctgcctagg gaaaaggtca ggtactaagg attgatggcc agctggtggt aattgtgtgg 180 gctccagaaa atgatctaga t 201 <210> 44 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = G or A <400> 44 cggaagtaca cttgggggtt gtcaccttgc cagcatgagg gaacacatca tcacagcaca 60 ggtatgcact gcgttaatga tggaaagctt ccttctcatc rtacacaagc ttcaggtctt 120 ccatttgggg ggcaatgtag agcagagatt acttgcacat gaggacataa aattgccccc 180 accccaaatg atcaggactt g 201 <210> 45 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> S = G or C <400> 45 tgtccagatt tgagagtgag caaaatacac cagatatacc accaaaattg aaaaaaaaat 60 caactgcttg ctgttgggga agaagtagta atgttggaaa sgttgacttg atagaggatt 120 ttgtaagatg agtgaaaaag atctaaaagg acagtgatgt ctctgttatt gactgaggta 180 tccttggtct ctagaatagt g 201 <210> 46 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> N = T or C <400> 46 agaatgtaaa tttcttcctt ccctacccca gaatgtagat gcatgtcctc atttaatttt 60 agtcattctt ggcgaatgtg ataattaggg taaagtgcaa ngagatttgc aaattggatg 120 gtgaattcac taaatgtaac agctgatcag ggcttctctt ctcagtgtca ctttattaag 180 gtcttcggat atactgatat a 201 <210> 47 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = T or C <400> 47 tccccatctg gcacccaatc ttttacagtg ttatgaaaaa tagggaaaat gtagaaagga 60 agaacatggc acccaatcct taatggacac tcagtgaaag ytggctatca tcatcatttt 120 tggggttgtt gtgttctaca aatgtatttt cccaggagtt ttttttactc tgtctcctct 180 ttccttcata tacccccagc c 201 <210> 48 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> K = G or T <400> 48 tggaaccctg gaattccaag attcccagtc ttggaatcta acagctctat ggagttttgg 60 ccctgcctgg ggagcagtaa ggtaggatgg acagtagatt kaagatactg attgtgtttg 120 caaacatgcc ccagataagg aatggtcaaa gcagattcct tttttttttt ttttttttga 180 gacggagtct tgctctgtcg c 201 <210> 49 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> R = A or G <400> 49 tatgctgtga atgagtttca cattgccacc agatattcac agctgtaaag ttctttctgc 60 gttaaaacat tgaacatttc ctacaaccat tcaaaacatt rtaacagttc aaattatatt 120 tgagcatcac ttatatggct cttacggaac ttatgtaaag ttcttgaagt cagtgatttt 180 aagaaattgt gcttggaata t 201 <210> 50 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> N = T or C <400> 50 ttgcgcaggg gcccgcgggc tgaggcgagg gtcagagctt ccagtaggct gtggtcctca 60 tcaagctggc gggccgtgca gagtggtgtg ggcactttga nggtgttgcc aaacttggag 120 tagtccacag agtaacgtcc gtcctcctca gctacaatgg gcacaaagcg ctggccccac 180 aggatctcat cggccaggta g 201 <210> 51 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <101> <223> Y = C or T <400> 51 tttgatttgc caggagcaga atttctgggt tggaatcggg aacatttaga ggagcttctc 60 agtagagttg tacagagtgg aaatgagtcg gcaggctgca yggggggttc cagtcacagc 120 acagagggtg tgtgttttcg gtgcctgccc tcctgagctc caagtgtccc acgcctgccc 180 gtcagtcctc atgtctacct g 201

Claims (16)

A polynucleotide comprising the nucleotide sequence of SEQ ID NOS: 1 to 17 or a complementary polynucleotide set thereof,
The base sequence includes the 101st base as a SNP,
The 101st base of SEQ ID NO: 1 is T, the 101st base of SEQ ID NO: 2 is G, the 101st base of SEQ ID NO: 3 is C, the 101st base of SEQ ID NO: 4 is G, 7 is G, the 101st base of SEQ ID NO: 7 is G, the 101st base of SEQ ID NO: 7 is G, the 101st base of SEQ ID NO: 8 is G, the 101st base of SEQ ID NO: The 101st base of SEQ ID NO: 10 is T, the 101st base of SEQ ID NO: 11 is G, the 101st base of SEQ ID NO: 12 is T, the 101st base of SEQ ID NO: 13 is T, The base is C, the 101st base of SEQ ID NO: 15 is C, the 101st base of SEQ ID NO: 16 is C, and the 101st base of SEQ ID NO: 17 is T, Array.
delete delete delete The microarray according to claim 1, wherein the metabolic syndrome is a risk factor for abdominal obesity, hypertension, hypertriglyceridemia, low HDL cholesterol, or hyperglycemia.
2. The microarray according to claim 1, wherein the prediction or diagnosis is for diagnosing a metabolic syndrome or for predicting risk.
A polynucleotide comprising the nucleotide sequence of SEQ ID NOS: 1 to 17, or a probe capable of detecting a complementary polynucleotide set thereof or a primer capable of specifically amplifying,
The 101st base of SEQ ID NO: 1 is T, the 101st base of SEQ ID NO: 2 is G, the 101st base of SEQ ID NO: 3 is C, the 101st base of SEQ ID NO: 4 is G, 7 is G, the 101st base of SEQ ID NO: 7 is G, the 101st base of SEQ ID NO: 7 is G, the 101st base of SEQ ID NO: 8 is G, the 101st base of SEQ ID NO: The 101st base of SEQ ID NO: 10 is T, the 101st base of SEQ ID NO: 11 is G, the 101st base of SEQ ID NO: 12 is T, the 101st base of SEQ ID NO: 13 is T, Wherein the base is C, the 101st base of SEQ ID NO: 15 is C, the 101st base of SEQ ID NO: 16 is C, and the 101st base of SEQ ID NO: 17 is T, a composition for predicting or diagnosing a specific metabolic syndrome .
A kit for predicting or diagnosing a Taeumin specific metabolic syndrome among sasang constitution comprising the composition of claim 7.
9. The kit of claim 8, wherein the kit is an RT-PCR kit or a DNA chip kit.
delete (a) amplifying or hybridizing a polynucleotide consisting of the nucleotide sequence of SEQ ID NOS: 1 to 17, or a polymorphic site of the complementary polynucleotide set thereof, which is a polymorphic site of the 101st base sequence, with the probe, from the DNA of the isolated sample; And
(b) determining the base of the amplified or hybridized polymorphic site of step (a); And
(c) the nucleotide sequence determined in the step (b)
In rs13130484 described in SEQ ID NO: 1, when the 101st base is T;
In rs1424233 described in SEQ ID NO: 2, when the 101st base is G;
In rs17782313 described in SEQ ID NO: 3, when the 101st base is C;
In rs6235 described in SEQ ID NO: 4, when the 101st base is G;
In rs1294421 described in SEQ ID NO: 5, when the 101st base is T;
In rs2605100 described in SEQ ID NO: 6, when the 101st base is G;
In rs17249754 described in SEQ ID NO: 7, when the 101st base is G;
In rs1133323 described in SEQ ID NO: 8, when the 101st base is G;
In rs6589566 described in SEQ ID NO: 9, when the 101st base is G;
In rs6544366 described in SEQ ID NO: 10, when the 101st base is T;
In rs10402271 described in SEQ ID NO: 11, when the 101st base is G;
In rs3846663 described in SEQ ID NO: 12, when the 101st base is T;
In rs2156552 described in SEQ ID NO: 13, when the 101st base is T;
In rs6586891 described in SEQ ID NO: 14, when the 101st base is C;
In rs5215 described in SEQ ID NO: 15, when the 101st base is C;
In rs163171 described in SEQ ID NO: 16, when the 101st base is C; And
A method for predicting or diagnosing a specific metabolic syndrome in a sasang constitution comprising the step of determining rs7593730 of SEQ ID NO: 17 as a specific metabolic syndrome which is a bait in the sasang constitution when the 101st base is T .
delete delete delete 12. The method according to claim 11, wherein the base crystals of step (b) are selected from the group consisting of sequence analysis, hybridization with a microarray, allele specific PCR, dynamic allele-specific hybridization (DASH) Wherein the detection is performed by one or more methods selected from the group consisting of PCR extension analysis, PCR-single strand conformation polymorphism (PCR-SSCP), PCR-restriction fragment length polymorphism (PCR-RFLP)
(a) selecting SNPs that are associated with a phenotype of abdominal obesity, hypertension, hypertriglyceridemia, low HDL cholesterol, or hyperglycemia;
(b) selecting SNPs associated with the metabolic syndrome phenotype using multiple regression analysis among the selected SNPs of step (a);
(c) selecting SNPs associated with Taeumin in the sasang constitution for the metabolic syndrome phenotype using multiple regression analysis among the SNPs selected in step (b); And
(d) calculating a genetic risk score (GRS) of the selected SNPs in step (c), and performing multiple regression analysis on the SNPs as independent variables to select Taeumin-specific SNPs among the sasang constitutions A method for predicting or diagnosing a specific metabolic syndrome or predicting SNPs for diagnosis.

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