KR20220027690A - Method for providing information for metabolic syndrome disease and kits using the same - Google Patents

Abstract

In the present specification, provided is a method for providing information for metabolic syndrome including a step of detecting a single nucleotide polymorphism (SNP) genotype for at least one gene region of APOA5, LPL, CDKAL1, CETP, GCKR, and NID2 from a biological sample isolated from an individual, and a step of determining the risk of developing metabolic syndrome of the individual based on detected genotype. According to the present invention, a treatment improving effect can be ensured.

Description

Method for providing information on metabolic syndrome and kit using the same

The present invention relates to a biomarker capable of predicting and diagnosing metabolic syndrome from a biological sample isolated from an individual.

Obesity is well known as a significant risk factor for the development of various cancers, including type 2 diabetes, cardiovascular disease and metabolic disease (metabolic syndrome). Currently, body mass index is used as a method of assessing obesity. However, obesity simply based on body mass index has many limitations in predicting the risk for metabolic diseases and cardiovascular diseases.

For example, in obese patients, 10 to 20% appear to have a body mass index obese but metabolically healthy Metabolically Healthy Obesity (MHO). Conversely, in the case of normal persons with a body mass index of less than 25 kg/m ² , 5 to 15% appear to be Metabolically Obese Normal Weight (MONW) with a normal body mass index but a metabolic disease. As described above, it is difficult to discriminate the difference between these metabolic diseases by body mass index.

In this regard, adipose tissue is an active endocrine organ, and various adipokines secreted from adipose tissue regulate fat metabolism, energy homeostasis, and insulin sensitivity, and have an important effect on the development of obesity-related metabolic diseases. The effect of adipose tissue on metabolic diseases is different depending on the location of visceral fat and subcutaneous tissue. Abdominal visceral fat increases the concentration of free fatty acids in the blood and promotes the secretion of metabolically harmful adipokines. On the other hand, the subcutaneous fat of the thigh has high activity of lipoprotein lipase and low activity of hormone sensitive lipase, so it lowers blood triglyceride levels and increases HDL cholesterol levels. It works to buffer or improve the effects of fat.

As such, depending on the composition of body composition and distribution of body fat, the presence or absence of metabolic abnormalities may vary even within the same body mass index. However, although the body mass index currently used as a diagnostic criterion for obesity is widely used due to its ease of use, it does not reflect the distribution characteristics of body fat as described above, so it cannot accurately evaluate the metabolic risk of obesity. Accordingly, there is a need to discover new indicators that can accurately predict and diagnose the risk of metabolic diseases in relation to body mass.

The description underlying the invention has been prepared to facilitate understanding of the invention. It is not to be construed as an admission that the matters described in the background technology of the invention exist as prior art.

Meanwhile, genome-wide association studies (GWAS) are being conducted worldwide to discover disease-causing genetic factors for the realization of genome-based personalized medicine. Although the genetic factors related to a large number of metabolic diseases have been revealed through this, the difference in influence may appear differently due to various group genetic differences such as race and region, and thus it is not effective for all. In particular, there are almost no studies targeting domestic groups.

Accordingly, the inventors of the present invention paid attention to genetic mutations (biomarkers) that can have effective predictive and diagnostic power in the domestic population in order to solve the above-mentioned problem. In particular, the inventors of the present invention paid more attention to single nucleotide polymorphism (SNP), which is a single nucleotide substitution in a DNA sequence, among genetic variations affecting disease. More specifically, the human genes are 99% identical to each other, and individual differences are shown by the remaining 1% of the different genes. SNPs account for most of the genetic variation included in this 1% portion. In SNP, on average, about one nucleotide sequence mutation per 100 to 300 genomic nucleotide sequences is observed, and as the frequency of appearance is high, it is known as a highly reliable genetic mutation.

Accordingly, the inventors of the present invention performed SNP analysis to accurately identify the location of genes contributing to the onset susceptibility of metabolic diseases, and, accordingly, tried to discover base mutations for obesity and metabolic diseases specific to Koreans.

Accordingly, the inventors of the present invention analyzed SNPs to clarify the location of genetic mutations contributing to the susceptibility of metabolic syndrome according to body mass, and accordingly, base mutations for metabolic syndrome according to body mass in Koreans found

Furthermore, the inventors of the present invention have recognized that by detecting and confirming a genetic mutation that can cause metabolic syndrome according to body mass, it is possible to determine an individual more susceptible to the onset of metabolic syndrome. Accordingly, the individual may be aware of the induced risk, and nutritional management appropriate therefor may be performed.

In other words, through mutations that are related to body mass and the traits of metabolic syndrome, it is possible to differentiate the constitutional characteristics of an individual, and to identify each pathological characteristic to prevent obesity, metabolic syndrome, and various diseases such as cardiovascular diseases. can

As a result, the problem to be solved by the inventors of the present invention is to provide a genetic mutation, that is, a marker that can predict and diagnose metabolic syndrome according to body mass, and has a statistically significant and high correlation to Koreans.

The problems of the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

In order to solve the above problems, the present invention provides a single nucleotide polymorphism (SNP) genotype for at least one gene region of APOA5, LPL, CDKAL1, CETP, GCKR, and NID2 from a biological sample isolated from an individual. A method of providing information on metabolic syndrome is provided, comprising determining a risk of developing metabolic syndrome for an individual based on the steps and the detected genotype.

According to a feature of the present invention, the step of detecting the genotype may include detecting at least one of the base of rs651821 in the APOA5 gene region, the base of rs325 in the LPL gene region, and the base of rs138420022 in the CDKAL1 gene region.

According to another feature of the present invention, in the step of determining the risk of developing metabolic syndrome, when the base of rs651821 is C, the base of rs325 is C, or the base of rs138420022 is A, the individual is at high risk for metabolic syndrome. It may include the step of determining.

According to another feature of the present invention, the step of detecting the genotype may include detecting at least one of the base of rs651821 in the APOA5 gene region, the base of rs325 in the LPL gene region, and the base of rs821840 in the CETP gene region. there is.

According to another feature of the present invention, the step of determining the risk of developing metabolic syndrome, when the base of rs651821 is C, the base of rs325 is C, or the base of rs821840 is G, the subject is BMI 25 kg/m ² In the case of abnormality, it may include the step of determining as a high-risk group for metabolic syndrome.

According to another feature of the present invention, the step of detecting the genotype includes the base of rs651821 in the APOA5 gene region, the base of rs325 in the LPL gene region, the base of rs138420022 in the CDKAL1 gene region, the base of rs821840 in the CETP gene region, and the GCKR gene. detecting at least one of a base of rs6547692 in the region and a base of rs75766425 in the NID2 gene region.

According to another feature of the present invention, the step of determining the risk of developing metabolic syndrome, the base of rs651821 is C, the base of rs325 is C, the base of rs138420022 is A, the base of rs821840 is G, or the base of rs6547692 When the base is A or the base of rs75766425 is C, even if the BMI is less than 25 kg/m ² , determining the subject as a high-risk group for metabolic syndrome.

According to another feature of the present invention, the subject may include at least one of obesity and metabolic syndrome, wherein obesity may mean that the subject's BMI is 25 kg/m ² or more. Furthermore, the metabolic syndrome may include at least one of abdominal obesity, hypertension, blood sugar disorders, high triglycerides and low HDL.

According to another feature of the present invention, the step of detecting the genotype comprises: sequencing analysis, hybridization by microarray, allele specific PCR, dynamic allele-specific hybridization , DASH), PCR extension analysis, PCR-single strand conformation polymorphism (PCR-SSCP), PCR-restriction fragment length polymorphism (PCR-RFLP), and TaqMan techniques.

Meanwhile, in order to solve the above problems, the present invention includes a SNP (single nucleotide polymorphism) site for at least one gene region of APOA5, LPL, CDKAL1, CETP, GCKR, and NID2 from a biological sample isolated from an individual. It is possible to provide a composition for providing information on metabolic syndrome, comprising a probe or primer agent configured to amplify or detect a polynucleotide that is

At this time, according to a feature of the present invention, the probe or primer is A, T or C, which is the base of rs651821 in the APOA5 gene region, T or C, the base of rs325 in the LPL gene region, and the base of rs138420022 in the CDKAL1 gene region Amplify T or A, base A or G at rs821840 in the CETP gene region, G, C, T or A at base rs6547692 in the GCKR gene region, and G or C at base rs75766425 in the NID2 gene region or configured to detect.

In addition, in order to solve the problems as described above, the present invention may provide a kit for providing information on the metabolic syndrome comprising the composition for providing information on the aforementioned metabolic syndrome.

At this time, according to the features of the present invention, the kit may be at least one of RT-PCR, ddPCR, microarray chip and DNA chip kit, but is not limited thereto, and all kits that can be performed using the above-described composition may include

According to another feature of the present invention, the kit may further include a display means configured to indicate an individual's susceptibility to the onset of metabolic syndrome according to the genotype of the SNP for the measured gene, wherein the display means is abdominal obesity , hypertension, blood sugar disorder, high triglyceride, and low HDL may indicate the onset susceptibility to at least one disease, but is not limited thereto, and all information that can be derived through the method of providing information on metabolic syndrome All of them can be indicated.

Hereinafter, the present invention will be described in more detail through examples. However, since these examples are only for illustrative purposes of the present invention, the scope of the present invention should not be construed as being limited by these examples.

In the present invention, a single nucleotide polymorphism (SNP) genotype is detected for at least one of CBX8 and CBX4 (intergenic), LPL, CDKAL1, CETP, GCKR and NID2 gene regions from a biological sample isolated from an individual, and thus the individual can provide information on the risk of developing metabolic syndrome for

Furthermore, the present invention provides not only prediction and diagnosis of metabolic syndrome for an individual, but also information on obesity that can induce or aggravate metabolic syndrome, thereby identifying the cause of the individual and promoting nutritional management accordingly. It can promote prevention and treatment of metabolic diseases.

Furthermore, according to the present invention, by predicting and diagnosing the onset of a disease in advance according to the constitution of the individual, that is, body mass, the individual can more identify and manage risk factors for themselves.

Furthermore, the present invention provides markers with high correlation in the domestic population, unlike conventional markers for metabolic syndrome, so that predictive and diagnostic power for the domestic population may be higher than that of conventional markers.

Furthermore, since the present invention is a genotype that appears specifically in patients with obesity and metabolic syndrome and rarely appears in normal people, it is possible to effectively diagnose the presence or risk of obesity and metabolic syndrome at an early stage, thereby enhancing the effectiveness of treatment. can

Accordingly, the present invention can effectively predict the onset susceptibility of obesity and metabolic syndrome to prevent diseases at an early stage, thereby reducing the burden on the patient's psychological and medical expenses.

The effect according to the present invention is not limited by the contents exemplified above, and more various effects are included in the present specification.

1A is a flowchart of a method for providing information on metabolic syndrome according to an embodiment of the present invention.
2 is a schematic diagram exemplarily illustrating a selection process for an analysis group in a method for providing information on metabolic syndrome according to an embodiment of the present invention.
3 is a general characteristic result of the analysis group in the method for providing information on metabolic syndrome according to an embodiment of the present invention.
4A and 4C are results of metabolic disease-related SNPs according to body mass in the method for providing information on metabolic syndrome according to an embodiment of the present invention.
5A and 5B are SNP results according to MHO and MONW in a method for providing information on metabolic syndrome according to an embodiment of the present invention.
6 is a result of SNP in the method for providing information on metabolic syndrome according to an embodiment of the present invention.

Advantages and features of the present invention and methods of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be embodied in various different forms, and only these embodiments allow the disclosure of the present invention to be complete, and common knowledge in the art to which the present invention pertains It is provided to fully inform those who have the scope of the invention, and the present invention is only defined by the scope of the claims.

As used herein, the term “and/or” will be understood to indicate that one or both of the items linked by the term herein are included. In other words, in this specification, the term may mean "one or the other or both".

As used herein, the term “prediction or diagnosis” includes any type of analysis used to predict the occurrence of a disease, determine or derive the risk of developing a disease and susceptibility to the disease, preferably may include, but is not limited to, making a diagnosis by determining whether or not metabolic syndrome according to body mass or predicting the risk of developing obesity and metabolic syndrome.

As used herein, the term "susceptibility" means that an individual tends to develop a particular phenotype (disease, trait, condition), or is capable of resisting a particular phenotype more than the average individual. means weak. Susceptibility includes both increased susceptibility and decreased susceptibility. That is, a particular allele of a polymorphic marker of the present invention is characterized by a metabolic syndrome characterized by a relative risk (RR) or odds ratio (OR) greater than one and/or an increased susceptibility (i.e. increased risk) of the metabolic syndrome. can be done with

As used herein, the term "allele" refers to several types of a gene that exist on the left and right sides of the same gene on a homologous chromosome, for example, SNP has two types of alleles. Allele frequencies can be used to indicate genetic polymorphisms within a particular population.

As used herein, the term “rs_id” may refer to an independent marker assigned to all SNPs initially registered by the NCBI, which has been accumulating SNP information since 1998. In the present specification, it is described in the same form as rs (number), which may mean a polymorphic marker SNP in the method for providing information on metabolic syndrome according to an embodiment of the present invention, and those skilled in the art use rs-id Thus, the position and sequence of the SNP can be easily confirmed through NCBI. Furthermore, NCBI's dbSNP (The Single Nucleotide Polymorphism Database) number of rs_id and specific information on it may be slightly changed over time (according to the Genome Reference Consortium human genome build version), but the scope of the present invention It will be apparent to those skilled in the art that also affects the altered sequence.

As used herein, the term “polynucleotide or nucleic acid” may refer to single- or double-stranded DNA or RNA. DNA consists of four bases: adenine (A), guanine (G), cytosine (C), and thymine (T). RNA has uracil (U) instead of thymine . In a nucleic acid double strand, A forms a hydrogen bond with T or U, and C forms a hydrogen bond with a G base, and the relationship between these bases is called complementary. Furthermore, as used herein, the term "genomic DNA" is the total nucleotide sequence of an individual's gene, and may refer to DNA containing almost complete genetic information. Furthermore, as used herein, the term “protein” refers to a polymer of amino acid residues, and may be used interchangeably with a polypeptide or a peptide.

As used herein, "one letter (three letters) of amino acids" may refer to the following amino acids according to standard abbreviation rules in the field of biochemistry. A(Ala): alanine, C(Cys): cysteine, D(Asp): aspartic acid, E(Glu): glutamic acid, F(Phe): phenylalanine, G(Gly): glycine, H(His): histidine, I(IIe): isoleucine, K(Lys): lysine, L(Leu): leucine, M(Met): methionine, N(Asn): asparagine, O(Ply): pyrrolysine, P(Pro): Proline, Q(Gln): Glutamine, R(Arg): Arginine, S(Ser): Serine, T(Thr): Threonine, U(Sec): Selenocysteine, V(Val): Valine, W (Trp): tryptophan and Y (Tyr): tyrosine.

As used herein, "genome wide association study (GWAS)" is an analysis method for discovering genetic variation related to a specific trait (disease), SNP or Association studies with a specific trait (disease) are performed using a marker that can represent genetic variation, and the results of the association study show that a specific genetic variation is frequent in a specific trait group (disease group) between a specific trait group (disease group) and a normal group If it appears, it can be said that there is a correlation.

As used herein, the term “subject” may refer to a subject for predicting or diagnosing a specific trait, ie, obesity or metabolic syndrome. Furthermore, it may be a subject comprising obesity and/or metabolic syndrome for making a prediction or diagnosis for obesity and/or metabolic syndrome. Accordingly, by obtaining DNA from a biological sample isolated from an individual, it is possible to predict or diagnose the above-described specific trait of the individual. In this case, the biological sample may include, but is not limited to, hair, urine, blood, various body fluids, isolated tissues, isolated cells, and saliva, and may include any material from an individual from which DNA can be extracted. there is.

As used herein, the term "metabolic syndrome" refers to several diseases such as diabetes (impaired glucose tolerance and type 2 diabetes), hypertension, hyperlipidemia, obesity, and cardiovascular atherosclerosis due to chronic metabolic disorders. It can mean appearing in an individual, and can be used synonymously with metabolic disease.

Method for providing information on metabolic syndrome and kit accordingly

Hereinafter, a method for providing information on metabolic syndrome and a kit according thereto according to an embodiment of the present invention will be described in detail with reference to FIG. 1A. At this time, for convenience of description, it will be described with reference to FIG. 1B.

Referring to FIG. 1A , a flowchart of a method for providing information on metabolic syndrome according to an embodiment of the present invention is shown. In a method for providing information on metabolic syndrome according to an embodiment of the present invention, a single nucleotide polymorphism (SNP) genotype of at least one of APOA5, LPL, CDKAL1, CETP, GCKR, and NID2 is obtained from a biological sample isolated from an individual. It may include the step of detecting (S110) and determining the risk of developing metabolic syndrome for the individual based on the detected genotype (S120).

At this time, SNP (single nucleotide polymorphism), that is, single nucleotide polymorphism, means that only a single base is different from among polymorphic sites in which two or more alleles exist at one locus. SNPs are relatively high in frequency and stable, and are distributed throughout the genome, so they can generate genetic diversity in individuals. In addition, SNPs are generally accompanied by single nucleotide polymorphisms and may include changes in phenotype, and the SNPs of the present invention may indicate obesity, metabolic syndrome, and differences in the onset of metabolic syndrome according to body mass. Furthermore, in the present specification, “SNP” may be used interchangeably with “mutation” and “SNP marker”.

First, in the step (S110) of detecting the SNP (single nucleotide polymorphism) genotype of at least one of APOA5, LPL, CDKAL1, CETP, GCKR and NID2 from DNA of a biological sample isolated from an individual, rs651821, rs325, rs138420022 , at least one SNP of rs821840, rs6547692 and rs75766425 may be detected.

In this case, the SNP of rs651821 may be all or part of the polynucleotide including the 101th base in the polynucleotide of SEQ ID NO: 1 for the APOA5 gene region. Furthermore, the 101th base in the polynucleotide of SEQ ID NO: 1 is A, T, or C, and rs651821 may be a polynucleotide consisting of 5 to 300 consecutive bases including the same or a polynucleotide complementary thereto. It is not limited.

Then, the SNP of rs325 may be all or part of a polynucleotide including the 101th base in the polynucleotide of SEQ ID NO: 2 for the LPL gene region. Furthermore, the 101th base in the polynucleotide of SEQ ID NO: 2 is T or C, and rs325 may be a polynucleotide consisting of 5 to 300 consecutive bases including the same or a polynucleotide complementary thereto, but is limited thereto it is not

Then, the SNP of rs138420022 may be all or part of a polynucleotide including the 101th base in the polynucleotide of SEQ ID NO: 3 for the CDKAL1 gene region. Furthermore, in the polynucleotide of SEQ ID NO: 3, the base corresponding to the 101st is T or A, and rs138420022 may be a polynucleotide consisting of 5 to 300 consecutive bases including the same or a polynucleotide complementary thereto, but is limited thereto it is not

Then, the SNP of rs821840 may be all or part of a polynucleotide including the 101th base in the polynucleotide of SEQ ID NO: 4 for the CETP gene region. Furthermore, the 101th base in the polynucleotide of SEQ ID NO: 4 is A or G, and rs821840 may be a polynucleotide consisting of 5 to 300 consecutive bases including the same or a polynucleotide complementary thereto, but is limited thereto it is not

Then, the SNP of rs6547692 may be all or part of a polynucleotide including the 101th base in the polynucleotide of SEQ ID NO: 5 for the GCKR gene region. Furthermore, the 101th base in the polynucleotide of SEQ ID NO: 5 is G, C, T or A, and rs6547692 may be a polynucleotide consisting of 5 to 300 consecutive bases including the same or a polynucleotide complementary thereto. , but is not limited thereto.

Finally, the SNP of rs75766425 may be all or part of the polynucleotide including the 101th base in the polynucleotide of SEQ ID NO: 6 for the NID2 gene region. Furthermore, the 101th base in the polynucleotide of SEQ ID NO: 6 is G or C, and rs75766425 may be a polynucleotide consisting of 5 to 300 consecutive bases including the same or a polynucleotide complementary thereto, but is limited thereto it is not

In addition, the nucleotide sequence for the SNP, that is, SEQ ID NOs: 1 to 6 used in the method for providing information on metabolic syndrome according to an embodiment of the present invention, is the sequence described in the sequence list and the It may also include sequences exhibiting substantial identity. At this time, the substantial identity (substantial identity) is to align the sequence in the method for providing information on metabolic syndrome according to an embodiment of the present invention and any other sequence to the maximum extent, and is commonly used in the art. When the aligned sequence is analyzed using an algorithm, it may mean a sequence exhibiting a homology of at least 60%, preferably 70%, more preferably 80%, still more preferably 90%. Therefore, the SNP used in the method for providing information on metabolic syndrome according to an embodiment of the present invention is a nucleotide sequence having high homology with the nucleotide sequence represented by SEQ ID NOs: 1 to 6 including the aforementioned SNP, for example, , the nucleotide sequence having a high homology of 70% or more, preferably 80% or more, and most preferably 90% or more, may be included.

Further, in the step of detecting the SNP (single nucleotide polymorphism) genotype of at least one of APOA5, LPL, CDKAL1, CETP, GCKR and NID2 from DNA of a biological sample isolated from an individual (S110), sequencing analysis , hybridization by microarray, allele specific PCR (allele specific PCR), dynamic allele-specific hybridization (DASH), PCR extension analysis, PCR-SSCP (PCR-single strand conformation polymorphism), PCR -It may be performed by at least one method of PCR-restriction fragment length polymorphism (RFLP) and TaqMan technique, but is not limited thereto, and various methods available to those skilled in the art to determine the base sequence can include all of them.

More specifically, the detection of the SNP genotype may be performed using a PCR method of amplifying the DNA fragment in which the SNP is located using a primer set including a primer designed with the 3' end of the base at which the SNP is located.

For example, to detect when a specific base is substituted from A to G, a PCR reaction can be performed by designing a primer containing A as a 3' end base and an opposite primer capable of amplifying a DNA fragment of an appropriate size. there is. Accordingly, when the base at the above-described SNP position is A, the amplification reaction is normally performed and a band at the desired position is observed. Bands may not be observed due to the inability to perform complementary binding at the ends and the amplification reaction is not performed properly.

Furthermore, PCR extension analysis first amplifies a DNA fragment containing a base in which the single nucleotide polymorphism is located with a pair of primers, and then inactivates all nucleotides added to the reaction by dephosphorylating, and here a SNP-specific extension primer; It can be accomplished by performing a primer extension reaction by adding a dNTP mixture, didioxynucleotide, reaction buffer and DNA polymerase.

In this case, the extension primer uses the 3' end of the base immediately adjacent to the 5' direction of the base on which the SNP is located, the dNTP mixture excludes nucleic acids having the same base as the dideoxynucleotide, and the dideoxynucleotide binds the SNP It is selected from one of the base types shown. For example, in the case of A to G substitution, if a mixture of dGTP, dCTP and TTP and ddATP are added, the primer is extended by DNA polymerase, and after a few bases, the A base is first appeared by ddATP. The primer extension reaction may be terminated. At this time, if the substitution of the base does not occur, the extension reaction is terminated at that position, and thus the type of the base representing the SNP can be determined by comparing the lengths of the extended primers.

Furthermore, in the detection method, when the extension primer or didioxynucleotide is fluorescently labeled, the SNP can be detected by detecting the fluorescence of a gene analyzer used for general sequencing, and the unlabeled extension primer and didioxynucleotide In the case of using , the SNP can be detected by measuring the molecular weight using the MALDITOF (matrix assisted laser desorption ionization-time of flight) technique. However, the above-described method is an exemplary SNP detection method, and is not limited thereto, and various methods may be used to perform the SNP detection method.

Next, in the step of determining the risk of developing metabolic syndrome for the individual based on the detected genotype (S120), the risk of developing metabolic syndrome and cardiovascular disease of the individual through the specific base of the SNP detected by the above method is determined. can decide More specifically, according to each SNP for at least one gene region of APOA5, LPL, CDKAL1, CETP, GCKR and NID2, that is, the 101st base in the polynucleotide of SEQ ID NOs: 1 to 6, the pathogenesis of metabolic syndrome A high-risk group or a high-risk group for metabolic syndrome according to body mass may be determined.

For example, in the step of determining the risk of developing metabolic syndrome for an individual based on the detected genotype (S120), rs651821 base is C in the APOA5 gene region measured by the above step, and rs325 base is C in the LPL gene region And when the base of rs138420022 in the CDKAL1 gene region is at least one of A, the individual may be determined as a high-risk group for metabolic syndrome.

In addition, in the step (S120) of determining the risk of developing metabolic syndrome for an individual based on the detected genotype, rs651821 base is C in the APOA5 gene region measured by the above step, and rs325 base is C and CETP in the LPL gene region When the base of rs821840 in the gene region is at least one of G, if the individual has a BMI of 25 kg/m ² or more, it can be determined as a high-risk group for metabolic syndrome.

In addition, in the step of determining the risk of developing metabolic syndrome for an individual based on the detected genotype ( S120 ), rs651821 base is C in the APOA5 gene region measured by the above step, rs325 base is C in the LPL gene region, and CDKAL1 If the base of rs138420022 is A in the gene region, the base of rs821840 is G in the CETP gene region, the base of rs6547692 is A in the GCKR gene region, and the base of rs75766425 in the NID2 gene region is C. Even if it is less than m ² , it can be determined as a high-risk group for metabolic syndrome. Accordingly, the individual may be lean and obese, with a high probability of suffering from metabolic syndrome even though the body mass is normal.

Accordingly, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, it is possible to predict and diagnose an individual's risk and susceptibility of metabolic syndrome according to body mass by the above-described method.

Furthermore, the present invention may provide a composition based on the above-described method for providing information on metabolic syndrome and a kit comprising the same.

First, the composition for providing information on metabolic syndrome according to an embodiment of the present invention provides a single SNP (single) gene region for at least one of APOA5, LPL, CDKAL1, CETP, GCKR, and NID2 from DNA of a biological sample isolated from an individual. A probe or primer agent configured to amplify or detect a polynucleotide containing a nucleotide polymorphism site may be included.

In this case, the probe may refer to a polynucleotide fragment such as RNA or DNA having a length of several to hundreds of base pairs capable of specifically binding to mRNA, cDNA (complementary DNA), DNA, etc. of a specific gene, As a labeling factor such as fluorescence or radiation is additionally attached to the 5' or 3' end of the probe so that it can be recognized with the naked eye, it is possible to check the presence or absence of the mRNA or cDNA of the binding target, the amount of expression, etc. there is. For example, a probe may comprise a sequence complementary to a polynucleotide sequence capable of binding to or recognizing a SNP, ie, a polynucleotide sequence comprising the SNP. Furthermore, the probe may be in the form of an oligonucleotide probe, a single stranded DNA probe, a double stranded DNA probe, an RNA probe, and the like,

In this case, the selection and hybridization conditions of these probes may be appropriately selected according to techniques known in the art. Furthermore, the probe may be used in a diagnostic method for detecting alleles (or alleles, alleles). In this case, diagnostic methods include detection methods based on hybridization of nucleic acids, such as Southern blot, and may be provided in a form previously bound to a substrate of a DNA chip in a method using a DNA chip, but is not limited thereto.

Furthermore, the primer may refer to a short single-stranded oligonucleotide serving as a starting point of DNA synthesis. A primer specifically binds to a polynucleotide as a template under suitable buffer and temperature conditions, and DNA polymerase adds a nucleoside triphosphate having a base complementary to the template DNA to the primer. DNA is synthesized by linking. A primer generally consists of a sequence of 15 to 30 bases, and the melting temperature (Tm) at which it binds to the template strand may vary depending on the base composition and length. The sequence of the primer does not need to have a completely complementary sequence to a part of the base sequence of the template, but it is sufficient if it hybridizes with the template and has sufficient complementarity within the range to perform the intrinsic function of the primer. The primer for the amplification reaction (polymerase chain reaction, PCR) is the template (or sense) and the opposite side (antisense, antisense) of both ends (5' end or 3' end) of a specific section of the polynucleotide to be amplified. ) may be composed of a pair (set) that are each complementary to each other. Furthermore, those skilled in the art can easily design a primer pair by referring to the nucleotide sequence of cDNA or genetic DNA for the SNP site of SEQ ID NOs: 1 to 6 described above.

In addition, according to the present invention, the probe or primer of the composition based on the method for providing information on metabolic syndrome can be chemically synthesized using a phosphoramidite solid support method or other well-known methods. Such nucleic acid sequences may also be modified using a number of means known in the art. Here, non-limiting examples of modifications include methylation, “capping”, substitution of one or more homologues of natural nucleotides, and modifications between nucleotides, such as uncharged linkages (eg, methyl phosphonates, phosphotriesters). , phosphoroamidate, carbamate, etc.) or a charged linkage (eg, phosphorothioate, phosphorodithioate, etc.), and the like.

Accordingly, in the present invention, the probe or primer of the composition based on the method for providing information on metabolic syndrome is the 101st (rs651821) base in SEQ ID NO: 1 for the APOA5 gene region, A, T or C, SEQ ID NO for the LPL gene region 2 to 101 (rs325) base T or C, SEQ ID NO: 3 to 101 (rs138420022) base T or C for the gene region of CDKAL1, SEQ ID NO: 4 to 101 (rs821840) base for the gene region of CETP A or G, G, C, T or A, which is the 101st (rs6547692) base in SEQ ID NO: 5 for the gene region of GCKR, and G or C, which is the 101st (rs75766425) base in SEQ ID NO: 6 for the NID2 gene region can be amplified or detected.

Next, according to the present invention, a kit comprising a composition based on a method for providing information on metabolic syndrome may be at least one of RT-PCR, ddPCR, microarray chip and DNA chip kit, and SNPs of SEQ ID NOs: 1 to 6 described above By detecting through amplification of or by detecting the expression level of SNP, information on metabolic syndrome according to body mass of an individual can be determined.

For example, when a kit comprising a composition based on a method for providing information on metabolic syndrome according to an embodiment of the present invention is a kit necessary to perform RT-PCR or dd-PCR, each specific for SNP In addition to probes or primer pairs, test tubes or other suitable containers, reaction buffers, deoxynucleotides (dNTPs), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNAse inhibitors, DEPC-water, It may include sterile water and the like, but is not limited thereto. In addition, a pair of primers specific to a gene used as a control may be included.

Furthermore, referring to FIG. 1B , the kit including the composition based on the method for providing information on metabolic syndrome according to an embodiment of the present invention may be a kit for performing a DNA chip or/and a DNA chip including a sensor. A DNA chip is a method in which nucleic acid species are attached in a gridd array to the surface of a generally flat solid support plate, in which nucleic acids are uniformly arranged on the surface of the chip. It is an analysis tool that allows multiple hybridization reactions between specific nucleic acids to enable massively parallel analysis, but is not limited thereto.

Furthermore, the kit including the composition based on the method for providing information on metabolic syndrome according to an embodiment of the present invention may be a kit for performing a microarray chip. In the case of a kit for performing a microarray chip, a kit comprising a composition based on the method for providing information on metabolic syndrome according to an embodiment of the present invention is a nucleic acid comprising at least one SNP of SEQ ID NOs: 1 to 6 immobilized It may include a microarray having a substrate formed thereon. The microarray may be composed of a conventional microarray except that the polynucleotide, primer or probe of the present invention is included. Hybridization of nucleic acids on microarrays and detection of hybridization results are well known in the art. In this case, detection is, for example, labeling a nucleic acid sample with a labeling factor capable of generating a detectable signal including a fluorescent material such as Cy3 and Cy5, then hybridizing on a microarray, and detecting the signal generated from the labeling material. By detecting, the hybridization result can be detected.

Furthermore, according to the genotype of the SNP for the measured gene region, the kit comprising the composition based on the method for providing information on metabolic syndrome according to an embodiment of the present invention, the metabolic syndrome and the susceptibility to the onset of metabolic syndrome of the individual Display means configured to indicate may be further included. More specifically, the display means, according to the SNP of SEQ ID NOs: 1 to 6, that is, the 101st base, at least one of abdominal obesity, hypertension, blood sugar disorders, high triglycerides and low HDL disease susceptibility to at least one disease However, the present invention is not limited thereto, and various information that can be derived through the method for providing information on metabolic syndrome according to an embodiment of the present invention may be displayed.

Through the above process, the method for providing information on metabolic syndrome according to an embodiment of the present invention, a composition based thereon, and a kit including the same can predict and diagnose a disease for an individual, that is, metabolic syndrome through gene detection and confirmation. can In addition, it is possible to further predict and diagnose the metabolic syndrome according to the body mass of the individual, and reduce the metabolic syndrome of the individual through nutritional management based thereon.

Hereinafter, with reference to FIGS. 2 to 6 , the SNP of the method for providing information on metabolic syndrome according to an embodiment of the present invention will be described.

2 is a schematic diagram exemplarily illustrating a selection process for an analysis group in a method for providing information on metabolic syndrome according to an embodiment of the present invention.

In order to select a genetic mutation optimized for the Korean genome, the inventors of the present invention, first, include diseases other than metabolic syndrome, such as cancer, thyroid disease, stroke and myocardial infarction in the sample, body mass index (BMI), waist circumference Participants with missing values for , blood pressure, fasting blood sugar, triglyceride (TG), and blood lipoprotein-cholesterol data were excluded.

Then, the selected population was subjected to exclusion criteria, according to the presence or absence of obesity and metabolic syndrome, with a normal weight and without metabolic syndrome (MHNW), with normal weight and with metabolic syndrome (Metabolically obese normal weight, MONW). , were divided into groups without obesity and metabolic syndrome (Metabolically healthy obese, MHO) and with obesity and metabolic syndrome (Metabolically obese obese, MOO). Then, by comparing them with MHNW and MONW (Model 1) and MHO and MOO (Model 2), respectively, the genetic factors that can determine whether or not obesity, that is, metabolic syndrome according to body mass, were selected. Then, by comparing MONW and MHO (Model 3), genetic factors that can induce metabolic syndrome were selected even with a normal weight.

Accordingly, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, it is possible to diagnose and predict metabolic syndrome according to body mass through genetic factors selected as Model 1, Model 2, and Model 3.

At this time, obesity was determined as a case of 25 kg/m ² or more based on the body mass index (BMI) of the guidelines for the Asia-Pacific region set by the World Health Organization. Furthermore, metabolic syndrome was determined based on guidelines set by the National Cholesterol Education Program Adult Treatment Panel and the Korean Society for the Study of Obesity. More specifically, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, when the waist circumference is above a certain value (90 cm or more for men, 85 cm or more for women), and when systolic and diastolic blood pressures are 130 and 85 mmHg or more (including patients diagnosed with high blood pressure and taking blood pressure medications), fasting blood sugar of 100 mg/dL or more (including patients diagnosed with diabetes and taking diabetes medications), blood triglycerides of 150 mg/dL or more, and high-density lipoprotein-cholesterol ( HDL-C) was less than a certain value (less than 40 mg/dL for men, less than 50 mg/dL for women), the subject was determined as a patient with metabolic syndrome.

At this time, the genetic data for each participant was provided by The Korean Genome and Epidemiology Study (KoGES), and the SNP genotypes of each group were extracted using the array (KoreanChip) of the Korean National Biobank. Furthermore, in order to confirm the association between SNP and metabolic syndrome according to metabolic syndrome, the error ratio (Odds Ratio, OR) and 95% confidence intervals (CI) were calculated and displayed using logistic regression analysis.

Accordingly, the final obtained population data can easily identify genes that can cause metabolic syndrome depending on body mass as the aforementioned exclusion criteria are applied, and furthermore, there is an effect of selecting genes optimized for Koreans.

Furthermore, referring to FIG. 3 , a general characteristic result of the analysis group selected by the above-described process is shown.

First, the body mass index (BMI) was found to be the most significantly high in the MOO group, which is an obese individual including the metabolic syndrome, at 27.7 kg/m ² , followed by the MHO, MONW, and MHNW in the order of the body mass index (BMI). P<0.001).

Furthermore, the waist circumference (WC), like the body mass index, was found to be the most significantly high in the MOO group at 91.0 CM, followed by the MHO, MONW, and MHNW in the order of waist circumference being significantly higher (P<0.001).

Then, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly higher in the MONW and MOO groups with metabolic syndrome than in the MHNW and MHO groups without metabolic syndrome (P<0.001).

Then, fasting blood glucose (FPG) and triglycerides (TG) were similar to systolic blood pressure (SBP) and diastolic blood pressure (DBP), the MONW and MOO groups, subjects with metabolic syndrome, and the MHNW and MHO groups, without metabolic syndrome. appeared to be significantly higher (P<0.001).

Then, blood high-density lipoprotein-cholesterol (HDL-C) was significantly lower in the MONW and MOO groups with metabolic syndrome than in the MHNW and MHO groups without metabolic syndrome (P<0.001).

That is, the above-mentioned indicators appear to be clearly distinguished according to the presence or absence of metabolic syndrome.

Then, the prevalence of hypertension and diabetes mellitus was significantly higher in the MHNW and MHO groups than in the MONW and MOO groups (P<0.001).

4A and 4C , metabolic disease-related SNP results according to body mass in the method for providing information on metabolic syndrome according to an embodiment of the present invention are shown.

First, referring to FIG. 4A , a Manhattan plot result for metabolic disease-related SNPs according to body mass index is shown. At this time, the Manhattan plot is a diagram visualized by displaying the statistical value, that is, the p-value, of each SNP as a scatter plot according to the location of the SNP in the genome. SNPs showing significance above or near the threshold at the corresponding locus may appear in clusters.

Genes (MHNW vs MONW) of metabolic disease-related SNP loci according to metabolic syndrome at normal body weight are CDKAL1, LPL, and APOA5, and they appear to have statistical significance with a p value of 5x10 ^-8 or less (P<5X10 ^{- 8} ). That is, as the SNP included in the above-described gene shows a high significance above the threshold on the Manhattan plot, it may mean that it is a marker having high predictive power and diagnostic power in metabolic syndrome of normal weight.

More specifically, referring to FIG. 4B , APOA5 includes rs651821, a metabolic disease-related SNP according to the presence or absence of metabolic syndrome at normal body weight, and rs651821 is a C genotype (base) of 116,663,707 bp (11q23.3 site) of chromosome 11. ) can be At this time, the frequency of the C genotype (minor allele freqeuency, maf) is 0.30. Furthermore, the odds ratio of rs651821 is 1.47, and the 95% confidence interval is 1.39 to 1.55, which does not include 1, which may mean that rs651821 can increase the risk of metabolic syndrome. That is, when an individual contains rs651821, it may mean that the incidence rate for metabolic syndrome is 1.47 times higher than that of an individual of normal weight that does not include it (P=2.64E-45).

In this case, APOA5 including rs651821 is a lipid synthetase-related gene, and may be involved in lipid metabolism, in particular, neutral fat and lipoprotein metabolism containing abundantly.

LPL includes rs325, a metabolic disease-related SNP according to the presence or absence of metabolic syndrome at normal weight, and rs325 may be the C genotype (base) of chromosome 8 at 19,819,328 bp (8p21.3 site). At this time, the frequency of the C genotype (minor allele freqeuency, maf) is 0.12. Furthermore, the odds ratio of rs325 is 0.78, and the 95% confidence interval is 0.72 to 0.84, which does not include 1, so it may mean that rs325 has a significant effect on the incidence of metabolic syndrome for normal weight (P=1.68). E-09).

At this time, LPL including rs325 is a lipolytic enzyme-related gene, and because it regulates the delivery of free fatty acids (FFA) to muscle, adipose tissue and blood vessel wall macrophages, insulin resistance and atherosclerosis can be decided

CDKAL1 includes rs138420022, a metabolic disease-related SNP according to the presence or absence of metabolic syndrome at normal weight, and rs138420022 may be the A genotype (base) of chromosome 6 at 20,693,697 bp (6p22.3 site). At this time, the frequency (minor allele freqeuency, maf) of the A genotype is 0.47. Furthermore, the odds ratio of rs138420022 is 1.20, and the 95% confidence interval is 1.14 to 1.26, which does not contain 1, which may mean that rs138420022 can increase the risk of metabolic syndrome. That is, when an individual contains rs138420022, it may mean that the incidence rate for metabolic syndrome is significantly higher than that of an individual of normal weight that does not include it by 1.14 times (P=6.61E-13).

In this case, CDKAL1 containing rs138420022 is a gene associated with an increased risk of developing type 2 diabetes and obesity, and may be involved in proinsulin conversion and insulin response in glucose metabolism. Furthermore, CDKAL1 may be involved in the maintenance of mitochondrial morphology and function in adipose tissue.

According to the above results, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, rs651821 for the APOA5 gene region, rs325 for the LPL gene region, and rs138420022 for the CDKAL1 gene region correlated with the metabolic syndrome incidence rate at normal body weight. Having an association, it can determine the high-risk group for metabolic syndrome in normal-weight individuals.

Again, referring to FIG. 4a, the genes (MHO vs MOO) of the metabolic disease-related SNP locus according to the presence or absence of metabolic syndrome in obesity are LPL, APOA5, and CETP, which have statistical significance of p value 5x10 ^-8 or less. appears to be That is, as the SNP included in the above-described gene shows a high significance above the threshold in the Manhattan plot, it may mean that it is a marker having high predictive power and diagnostic power in the metabolic syndrome of obesity.

More specifically, referring to FIG. 4C , APOA5 includes rs651821, which is a metabolic disease-related SNP according to whether or not metabolic syndrome in obesity, and rs651821 is a C genotype (base) of 116,662,579 bp (11q23.3 site) of chromosome 11. can be At this time, the frequency (minor allele freqeuency, maf) of the C genotype is 0.30. Furthermore, the odds ratio of rs651821 is 1.40, and the 95% confidence interval is 1.33 to 1.47, which does not include 1, which may mean that rs651821 can increase the risk of metabolic syndrome. That is, when an individual includes rs651821, it may mean that the incidence rate for metabolic syndrome is 1.40 times higher than that of an obese individual who does not include it (P=6.17E-37).

LPL includes rs325, a metabolic disease-related SNP according to the presence or absence of metabolic syndrome at normal weight, and rs325 may be the C genotype (base) of chromosome 8 at 19,826,701 bp (8p21.3 site). At this time, the frequency of the C genotype (minor allele freqeuency, maf) is 0.12. Furthermore, the odds ratio of rs325 is 0.79, and the 95% confidence interval is 0.74 to 0.85, which does not include 1, so it may mean that rs325 has a significant effect on the incidence of metabolic syndrome for obesity (P=4.39E) -10).

On the other hand, in Figure 4b, it appears that rs651821 for the APOA5 gene region and rs325 for the LPL gene region, which are metabolic disease-related SNPs according to the presence or absence of metabolic syndrome in obesity, are included, but their respective positions are different. Accordingly, they may each be a different genotype mutation, but is not limited thereto. For example, they may be identical mutations at the same position, which may be SNPs with the same association for various traits.

CETP includes rs821840, which is a metabolic disease-related SNP according to the presence or absence of metabolic syndrome at normal body weight, and rs821840 may be the G genotype (base) at the position of 56,993,886 bp (16p13 site) of chromosome 16. At this time, the frequency (minor allele freqeuency, maf) of the G genotype is 0.17. Furthermore, the odds ratio of rs821840 is 0.80, and the 95% confidence interval is 0.75 to 0.85, which does not include 1, so it may mean that rs821840 has a significant effect on the incidence of metabolic syndrome for obesity (P=2.41E) -12).

In this case, CETP including rs821840 is a gene related to lipid metabolism of triglycerides and HDL cholesterol, and HDL cholesterol variation according to race may be related thereto.

According to the above results, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, rs651821 for the APOA5 gene region, rs325 for the LPL gene region, and rs821840 in the CETP gene region were correlated with the metabolic syndrome incidence rate in obesity. As a result, it is possible to determine a high-risk group for metabolic syndrome in obese individuals.

5A and 5B, SNP results according to MHO and MONW in the method for providing information on metabolic syndrome according to an embodiment of the present invention are shown.

First, referring to FIG. 5A , the Manhattan plot results for SNPs according to MHO and MONW are shown. The genes of the SNP locus associated with MHO and MONW are GCKR, CDKAL1, LPL, APOA5, NID2 and CETP, and they appear to have a statistical significance of less than or equal to p value 5x10 ^-8 (P<5X10 ^-8 ). That is, as the SNP included in the above-described gene shows a high significance above the threshold in the Manhattan plot, it may mean that it is a marker having high predictive power and diagnostic power in determining MHO and MONW.

More specifically, referring to FIG. 5B , APOA5 includes rs651821, which is a related SNP of MHO and MONW, and rs651821 may be a C genotype (base) of 116,662,579 bp (11q23.3 site) of chromosome 11. At this time, the frequency of the C genotype (minor allele freqeuency, maf) is 0.30. Furthermore, the odds ratio of rs651821 is 1.63, and the 95% confidence interval is 1.54 to 1.74, which does not contain 1, so rs651821 is an obese individual without metabolic syndrome, MHO, and MONW, a normal individual containing metabolic syndrome. It can mean that it has a significant influence on the decision (P=2.64E-45). That is, MHO and MONW can be determined through rs651821 included in the APOA5 gene region.

LPL includes rs325, which is a related SNP of MHO and MONW, and rs325 may be a C genotype (base) of 19,819,328 bp (8p21.3 site) of chromosome 8. At this time, the frequency of the C genotype (minor allele freqeuency, maf) is 0.12. Furthermore, the odds ratio of rs325 is 0.73, and the 95% confidence interval is 0.67 to 0.80, which does not contain 1, so rs325 is the trait of MHO, an obese individual without metabolic syndrome, and MONW, a normal individual with metabolic syndrome. It can mean that it has a significant influence on the decision (P=1.68E-09). That is, MHO and MONW can be determined through rs325 included in the LPL gene region.

CDKAL1 contains rs138420022, a related SNP of MHO and MONW, and rs138420022 may be the A genotype (base) of chromosome 6 at 20,693,697 bp (6p22.3 site). At this time, the frequency (minor allele freqeuency, maf) of the A genotype is 0.47. Furthermore, the odds ratio of rs138420022 is 1.26, and the 95% confidence interval is 1.19 to 1.33, which does not contain 1, so rs138420022 is an obese individual without metabolic syndrome, MHO, and a normal individual, MONW, containing metabolic syndrome. It can mean that it has a significant influence on the decision (P= 2.27E-15). That is, MHO and MONW can be determined through rs138420022 included in the CDKAL1 gene region.

CETP includes rs821840, which is a related SNP of MHO and MONW, and rs821840 may be a G genotype (base) of 56,993,886 bp (16p13 site) of chromosome 16. At this time, the frequency (minor allele freqeuency, maf) of the G genotype is 0.47. Furthermore, the odds ratio of rs821840 is 0.78, and the 95% confidence interval is 0.69 to 0.81, which does not contain 1, so rs821840 is an obese individual without metabolic syndrome, MHO, and a normal individual, MONW, containing metabolic syndrome. It can mean that it has a significant influence on the decision (P=1.29E-13). That is, MHO and MONW can be determined through rs821840 included in the CETP gene region.

GCKR includes rs6547692, which is a related SNP of MHO and MONW, and rs6547692 may be the A genotype (base) of chromosome 2 at 27,734,972 bp (2p23.3 site). At this time, the frequency (minor allele freqeuency, maf) of the A genotype is 0.46. Furthermore, the odds ratio of rs6547692 is 0.84, and the 95% confidence interval is 0.80 to 0.89, which does not contain 1, so rs6547692 is an obese individual without metabolic syndrome and MONW, a normal individual containing metabolic syndrome. It can mean that it has a significant influence on the decision (P=5.47E-09). That is, MHO and MONW can be determined through rs6547692 included in the GCKR gene region.

At this time, GCKR including rs6547692 is a gene involved in glucosekinase activity, glucose balance, and glucose-stimulated insulin secretion regulation.

NID2 includes rs75766425, a related SNP of MHO and MONW, and rs75766425 may be a C genotype (base) of 52,511,911 bp (14q22.1 site) of chromosome 14. At this time, the frequency (minor allele freqeuency, maf) of the C genotype is 0.16. Furthermore, the odds ratio of rs75766425 is 0.80, and the 95% confidence interval is 0.74 to 0.87, which does not contain 1, so rs75766425 is an obese individual without metabolic syndrome, MHO, and a normal individual, MONW, containing metabolic syndrome. It can mean that it has a significant influence on the decision (P=2.53E-08). That is, MHO and MONW can be determined through rs75766425 included in the NID2 gene region.

At this time, NID2 including rs6547692 is a gene related to the maintenance of basement membrane structure and may be involved in the development of malignant tumors.

According to the above results, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, rs651821 for the APOA5 gene region, rs325 for the LPL gene region, rs138420022 for the CDKAL1 gene region, rs821840 in the CETP gene region, and the GCKR gene As rs6547692 for the region and rs75766425 for the NID2 gene region have associations with MHO and MONW traits, it is possible to determine, that is, select, predict, and diagnose an individual as MHO or MONW.

Referring to FIG. 6 , the results for SNP in the method for providing information on metabolic syndrome according to an embodiment of the present invention are shown.

As a result, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, the 101st base in SEQ ID NO: 1 for rs651821 of the APOA5 gene region is C, and the 101st base in SEQ ID NO: 2 for rs325 of the LPL gene region When the 101st base in SEQ ID NO: 3 for rs138420022 of the C and CDKAL1 gene region is at least one of A, the individual may be determined as a high-risk group for metabolic syndrome. Furthermore, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, when the SNP of SEQ ID NOs: 1, 2, 3 is not the above-described base, the individual can be further determined as a low-risk group for metabolic syndrome.

In addition, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, the 101st base in SEQ ID NO: 1 for rs651821 of the APOA5 gene region is C, and the 101st base in SEQ ID NO: 2 for rs325 of the LPL gene region is If the 101st base in SEQ ID NO: 4 for rs821840 of the C and CETP gene regions is at least one of G, the individual has a BMI of 25 kg/m ² or more, it can be determined as a high-risk group for metabolic syndrome. Furthermore, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, when the SNP of SEQ ID NOs: 1, 2, and 4 is not the aforementioned base, the individual has a BMI of 25 kg/m ² or more, the metabolic syndrome It can be further determined as a low-risk group.

In addition, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, the 101st base in SEQ ID NO: 1 for rs651821 of the APOA5 gene region is C, and the 101st base in SEQ ID NO: 2 for rs325 of the LPL gene region is C, the 101st base in SEQ ID NO: 3 for rs138420022 of the CDKAL1 gene region is A, the 101st base in SEQ ID NO: 4 to rs821840 of the CETP gene region is G, the 101st base in SEQ ID NO: 5 for rs6547692 of the GCKR gene region When the 101st base in SEQ ID NO: 6 for rs75766425 of the A and NID2 gene region is at least one of C, even if the individual has a BMI of less than 25 kg/m ² , it can be determined as a high-risk group for metabolic syndrome. Furthermore, in the method for providing information on metabolic syndrome according to an embodiment of the present invention, when the SNPs of SEQ ID NOs: 1, 2, 3, 4, 5 and 6 are not the above-described bases, the subject is BMI 25 kg/m ² or less case, it can be further determined as a low-risk group for metabolic syndrome.

Accordingly, the method for providing information on metabolic syndrome according to an embodiment of the present invention can predict and diagnose the risk of onset of metabolic syndrome of an individual according to body mass through the SNPs of rs651821, rs325, rs138420022, rs821840, rs6547692 and rs75766425. there is. Furthermore, the method for providing information on metabolic syndrome according to an embodiment of the present invention can provide nutrition, exercise, and pharmaceutical prescription more suitable to the individual by selecting the constitution of the individual, that is, MONW and/or MHO.

Although the embodiments of the present invention have been described in more detail with reference to the accompanying drawings, the present invention is not necessarily limited to these embodiments, and various modifications may be made within the scope without departing from the spirit of the present invention. Therefore, the embodiments disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain, and the scope of the technical spirit of the present invention is not limited by these embodiments. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. The protection scope of the present invention should be construed by the following claims, and all technical ideas within the scope equivalent thereto should be construed as being included in the scope of the present invention.

<110> Theragen Bio Co. <120> METHOD FOR PROVIDING INFORMATION FOR METABOLIC SYNDROME DISEASE AND KITS USING THE SAME <130> DP-2020-0736 <160> 6 <170> KoPatentIn 3.0 <210> 1 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> n = A, T or C <400> 1 gccagcctcc acccacaccc ccacgttgaa gtcagggtcg gagacccacc tgaaagaaga 60 gccagagccc aggtgagcac ggcagccatg cttgccatta nctgctctga gaagacaggt 120 ggagggaggc ctggttaggg gaagaaggag acgaagggac atggcgcagg ggacttgccc 180 aggggggcctc tgcaggggca a 201 <210> 2 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> n = T or C <400> 2 aaagatcttg gggatggaaa tgttataaag aatctttttt acactagcaa tgtctagctg 60 aaggcagatg ccctaattcc ttaatgcaga tgctaagaga nggcagagtt gatcttttat 120 catctcttgg tgaaagccca gtaacataag actgctctag gctgtctgca tgcctgtcta 180 tctaaattaa ctagcttggt t 201 <210> 3 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> n = T or A <400> 3 ccagttgaaa taagataatt cttttattca attccaggac tctgaaatcc tctgagacca 60 aacttataga actgtcagtt gtctggactt tttgtgtgca ntttatcaag agggagaaga 120 acagttactt tctcccttcc ctcaaaacag ggcaaatgac agaattctat ttccagatag 180 atatgtttct ttcagggaca a 201 <210> 4 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> n = A or G <400> 4 ggaggggagg ggagggaagg gagagagaaa gaagaaagag aaagaaagga agaaagaaaa 60 agaaggaaag aaagaaagaa agaaagaaag aaagaaagaa ngaaagaaag aaagaaagaa 120 agaaagaaag aaaagagtga acccaggaac gaaagatcac acacactgta tgactctatt 180 tacatgaaat gttcagagta g 201 <210> 5 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> n = G, C, T or A <400> 5 ccaaggcagg cagatcacaa ggtcaggagt tcgagaccag cctgatcaac atggtgaaac 60 ctgatctcta ctaaaaatac aaaaattagc caggcgtggt ngcttggacc tgtaatcaca 120 actactcagg aggctgaggc agaagaatcg cttgaacctg ggaggcagag gttgcagtga 180 gctgagatca taccactgca c 201 <210> 6 <211> 201 <212> DNA <213> Homo sapiens <220> <221> variation <222> (101) <223> n = G or C <400> 6 atcatgagca ctagattagg ggtcaccaca tgtctggggt taatcagcac agacttcaag 60 tataattcga gtcatacttt ataaactggg tttaatggta naagcaagca gggaagatta 120 tcgagatgac tattacagca tgttgaaaaa cagcacaggt aagaaatgag agtagcagca 180 gcggcattag cttttgaaca g 201

Claims (17)

detecting a single nucleotide polymorphism (SNP) genotype for at least one of APOA5, LPL, CDKAL1, CETP, GCKR, and NID2 from a biological sample isolated from an individual; and
A method for providing information on metabolic syndrome, comprising determining a risk of developing metabolic syndrome for the individual based on the detected genotype. The method of claim 1,
The step of detecting the genotype,
the base of rs651821 in the APOA5 gene region;
the base of rs325 in the LPL gene region, and
A method for providing information on metabolic syndrome, comprising the step of detecting at least one of the bases of rs138420022 in the CDKAL1 gene region. 3. The method of claim 2,
Determining the risk of developing the metabolic syndrome comprises:
The base of rs651821 is C,
The base of rs325 is C,
When the base of rs138420022 is A,
A method for providing information on metabolic syndrome, comprising determining the subject as a high-risk group for metabolic syndrome. The method of claim 1,
The step of detecting the genotype,
the base of rs651821 in the APOA5 gene region;
the base of rs325 in the LPL gene region, and
A method for providing information on metabolic syndrome, comprising the step of detecting at least one of the bases of rs821840 in the CETP gene region. 5. The method of claim 4,
Determining the risk of developing the metabolic syndrome comprises:
The base of rs651821 is C,
The base of rs325 is C,
When the base of rs821840 is G,
If the subject is BMI 25 kg / m ² or more, comprising the step of determining a high-risk group for metabolic syndrome, information providing method for metabolic syndrome. The method of claim 1,
The step of detecting the genotype,
the base of rs651821 in the APOA5 gene region;
the base of rs325 in the LPL gene region;
the base of rs138420022 in the CDKAL1 gene region;
the base of rs821840 in the CETP gene region;
the base of rs6547692 in the GCKR gene region, and
A method for providing information on metabolic syndrome, comprising the step of detecting at least one of the bases of rs75766425 in the NID2 gene region. 7. The method of claim 6,
Determining the risk of developing the metabolic syndrome comprises:
The base of rs651821 is C,
The base of rs325 is C,
The base of rs138420022 is A,
The base of rs821840 is G,
The base of rs6547692 is A,
When the base of rs75766425 is C,
Even if the subject is less than 25 kg / m ² BMI, comprising the step of determining a high-risk group for metabolic syndrome, information providing method for metabolic syndrome. The method of claim 1,
The object is
A method of providing information on metabolic syndrome, comprising at least one of obesity and metabolic syndrome. 9. The method of claim 8,
The obesity is
A method for providing information on metabolic syndrome, wherein the subject's BMI is 25 kg/m ² or more. The method of claim 1,
The metabolic syndrome is
A method of providing information on metabolic syndrome comprising at least one of abdominal obesity, hypertension, glycemic disorders, high triglycerides and low HDL. The method of claim 1,
The step of detecting the genotype,
Sequencing analysis, hybridization by microarray, allele specific PCR (allele specific PCR), dynamic allele-specific hybridization (DASH), PCR extension analysis, PCR-SSCP (PCR-single strand) Conformation polymorphism), PCR-restriction fragment length polymorphism (PCR-RFLP), and a method of providing information on metabolic syndrome, performed by at least one method of TaqMan technique. A probe or primer configured to amplify or detect a polynucleotide comprising a single nucleotide polymorphism (SNP) site for at least one gene region of APOA5, LPL, CDKAL1, CETP, GCKR and NID2 from a biological sample isolated from an individual (primer) comprising the agent, a composition for providing information on metabolic syndrome. 12. The method of claim 11,
The probe or primer,
A, T or C, which is the base of rs651821 in the gene region of APOA5;
T or C, which is the base of rs325 in the gene region of LPL,
T or A, which is the base of rs138420022 in the CDKAL1 gene region,
A or G, which is the base of rs821840 in the gene region of CETP,
G, C, T or A, which is the base of rs6547692 in the gene region of GCKR, and
A composition for providing information on metabolic syndrome, configured to amplify or detect G or C, which is the base of rs75766425, in the gene region of NID2. A kit for providing information on metabolic syndrome, including claim 13 or 14. 16. The method of claim 15,
The kit is
A kit for providing information on metabolic syndrome, which is at least one of RT-PCR, ddPCR, microarray chip and DNA chip kit. 16. The method of claim 15,
15. A composition comprising the composition of any one of claims 13 or 14,
The kit is
According to the measured genotype of the SNP for the gene, further comprising a display means configured to indicate the susceptibility to at least one of obesity and metabolic syndrome of the individual, the kit for providing information on metabolic syndrome. 16. The method of claim 15,
The display means,
An informational kit for metabolic syndrome, indicating susceptibility to the development of at least one of abdominal obesity, hypertension, impaired blood sugar, high triglycerides and low HDL.

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