Epigenetic methylation marker for predicting metabolic syndrome, and kit using same

Abstract

The present invention relates to an epigenetic methylation marker for predicting metabolic syndrome, and a kit for predicting metabolic syndrome using same. Enabling specific prediction of disease risk rates for each condition within metabolic syndrome, the biomarker of the present invention is expected to be actively applicable in the medical and healthcare fields.

Description

Epigenetic methylation markers for predicting metabolic syndrome and kits using the same

[0001] The present invention relates to an epigenetic methylation marker for predicting metabolic syndrome, and a kit for predicting metabolic syndrome using the same. The kit for predicting metabolic syndrome may include a preparation for measuring the methylation level of the epigenetic methylation marker for predicting metabolic syndrome presented in the present invention.

[0002] With the recent rapid advancements in research based on next-generation sequencing (NGS), it is becoming increasingly clear that the genetic information contained in DNA inherited from parents can be differentially regulated in its expression patterns by various postnatal factors. This is called epigenetics, and the major factors known to be involved in the epigenetic mechanism include the actions of tissue-specific transcription factors, DNA methylation, histone modification, the actions of non-coding RNA, and signals from outside the cell. Furthermore, epigenetic alterations caused by these major factors are continuously being reported to be associated with the development of various diseases, including cancer. In particular, DNA methylation in the human genome is a crucial clue to epigenetics and is dynamically regulated during development. Because these phenomena are essential for the study of intracellular biological processes and gene regulation, it is expected that understanding the structure and function of key factors in epigenetic mechanisms will broaden the possibilities for treating human diseases.

[0003] Meanwhile, metabolic syndrome, which is called a modern disease, refers to a group of metabolic abnormalities such as hyperglycemia (fasting blood sugar), hypertension, hypertriglyceridemia, low level of HDL cholesterol, and increased waist circumference due to central obesity. Metabolic syndrome is known to increase the risk of developing metabolic diseases such as cardiovascular disease and diabetes. If three or more diseases are present in the five risk factors above, it is diagnosed as metabolic syndrome. Therefore, metabolic syndrome is not a single disease, but a comprehensive disease that occurs through a complex relationship between genetic predisposition and environmental factors.

[0004] The prevalence of metabolic syndrome has exploded in recent years, posing a significant problem. The prevalence of metabolic syndrome in adults worldwide is reported to be 20-25%, with rates reaching 35% in the US and 30% in Korea. If left untreated, metabolic syndrome can lead to serious complications, but there is currently no technology capable of accurately predicting the condition.

[0005] Accordingly, the present invention was conceived to address the aforementioned issues and relates to a biomarker for predicting metabolic syndrome. Since the biomarker of the present invention can specifically predict the risk of developing each metabolic syndrome disease, it is expected to find widespread use in the medical and healthcare fields.

[0006] The present invention has been devised to solve the above-mentioned problems in conventional technology, and relates to an epigenetic methylation marker as a biomarker for predicting metabolic syndrome.

[0007] In one aspect, the present invention provides a method for predicting or diagnosing the onset of metabolic syndrome.

[0008] In another aspect of the present invention, a composition for predicting or diagnosing the onset of metabolic syndrome is provided.

[0009] In another aspect of the present invention, a kit for predicting or diagnosing the onset of metabolic syndrome is provided.

[0010] As another aspect of the present invention, a device for predicting or diagnosing the onset of metabolic syndrome is provided.

[0011] However, the technical problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned can be clearly understood by those skilled in the art from the description below.

[0012] Hereinafter, various embodiments described herein will be described with reference to the drawings. In the following description, various specific details, such as specific configurations, compositions, and processes, are set forth to provide a thorough understanding of the present invention. However, certain embodiments may be practiced without one or more of these specific details, or in conjunction with other known methods and configurations. In other instances, well-known processes and manufacturing techniques have not been described in specific detail so as not to unnecessarily obscure the present invention. Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, configuration, composition, or characteristic described in connection with the embodiment is included in one or more embodiments of the present invention. Thus, the appearances of "in one embodiment" or "an embodiment" in various places throughout this specification do not necessarily refer to the same embodiment of the present invention. Additionally, the particular features, configurations, compositions, or characteristics may be combined in any suitable manner in one or more embodiments.

[0013] Unless otherwise specifically defined in the specification, all scientific and technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0014] Throughout the specification, whenever a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise stated.

[0015] The term "metabolic syndrome" in the present invention refers to a condition in which an individual has three or more of five risk factors (hypertension, hyperglycemia, hypertriglyceridemia, low high-density lipoprotein cholesterol, and abdominal obesity) that increase the risk of health problems, including heart disease, diabetes, and stroke. Hyperglycemia, hypertension, hyperlipidemia, obesity, and cardiovascular disease are increasing explosively in relation to the metabolic syndrome. Since metabolic syndrome can cause serious complications if left untreated for a long time, it is important to predict whether an individual is at high risk of developing metabolic syndrome before the onset of the disease, as well as to diagnose it early. However, the development of technology to predict metabolic syndrome using epigenetics is still insufficient.

[0016] The above epigenetics refers to specific traits acquired regardless of the genetic base sequence and passed on to offspring, and refers to changes in gene function that occur without changes in the DNA base sequence, i.e., genetic mutations. The specific traits are gene expression patterns established as cells differentiate in each cell type, and occur through a complex interaction of tissue-specific transcription factor actions, DNA methylation, histone modifications, and extracellular signals. In particular, DNA methylation is a representative epigenetic change that directly alters gene function without changing the genetic code, can be passed on to offspring cells, and is known to be related to gene expression suppression and tumorigenesis.

[0017] Accordingly, the present invention relates to an epigenetic marker that shows a high predictive value for metabolic syndrome and specific diseases that constitute metabolic syndrome.

[0018] In one embodiment of the present invention, FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like) 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), The present invention provides a composition for predicting or diagnosing metabolic syndrome, comprising a preparation for measuring the methylation level of a CpG site of one or more genes selected from the group consisting of SNX8 (Sorting Nexin 8). At this time, the CpG sites are chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374,chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227, chr7:2314651, chr7:2314652, chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, It may be at least one CpG site selected from the group consisting of chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033,The above metabolic syndrome may include at least one selected from the group consisting of hyperglycemia, abdominal obesity, hypertension, and non-alcoholic fatty liver disease.

[0019] As a more preferred specific example, when the metabolic syndrome includes hyperglycemia, the CpG site may include at least one CpG site selected from the group consisting of chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:220974, chr7:220975, chr7:223592, and chr7:545084, and when the metabolic syndrome includes abdominal obesity, the CpG site may include chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402,chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, It may include any one or more CpG sites selected from the group consisting of chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033, and when the metabolic syndrome includes hypertension, the CpG site may include chr7:2289889, and when the metabolic syndrome includes non-alcoholic fatty liver disease, the CpG site may include any one or more CpG sites selected from the group consisting of chr7:2298227, chr7:2314651, and chr7:2314652, but is not limited thereto.

[0020] In the composition for predicting or diagnosing metabolic syndrome of the present invention, the agent for measuring the methylation level of the CpG site of the gene may include at least one selected from the group consisting of bisulfite or a salt thereof, a methylation-sensitive restriction enzyme, a primer specific for a methylated sequence of the CpG site of the gene promoter, a primer specific for an unmethylated sequence, a methylated CpG binding domain, and an antibody specifically binding to methylcytosine, and the methylation-sensitive restriction enzyme may include at least one selected from the group consisting of SmaI, SacII, EagI, HpaII, MspI, BssHII, BstUI, and NotI.

[0021] In another embodiment of the present invention, the present invention is FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like) 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), A kit for predicting or diagnosing metabolic syndrome is provided, comprising a preparation for measuring the methylation level of a CpG site of one or more genes selected from the group consisting of SNX8 (Sorting Nexin 8). In this case, the kit preferably includes the above-described prediction or composition for metabolic syndrome. Therefore, description of specific diseases within metabolic syndrome and CpG sites matching them are omitted to prevent excessive complexity of the specification.In addition, the kit of the present invention may be a qRT-PCR kit, a PCR kit, a methylation-specific PCR kit, a real-time methylation-specific PCR kit, a PCR kit using a methylated DNA-specific binding protein, a DNA microarray kit, a MALDITOFF kit, a MassARRAY kit, a MethyLight kit, a QAMA kit, an ERMA kit, a HeavyMethyl kit, a QBSUPT kit, a MS-SNuPE kit, a MethylQuant kit, a quantitative PCR sequencing kit, and an oligonucleotide-based microarray kit, and the like, and any kit commonly used in the art may be used without limitation.

[0022] In another specific embodiment of the present invention, the present invention provides a method for isolating FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like 1), CUX1 (Cut Like Homeobox 1), IFRD1 (Interferon Related Developmental Regulator 1), PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2), NOXA1 (NADPH Oxidase Activator 1), FAM102A ((Myc-DDK-tagged)-Human family with sequence similarity 102, member A), NACC2 (NACC Family Member 2), NUDT1 (Nudix Hydrolase 1), A method for providing information for predicting or diagnosing metabolic syndrome is provided, comprising the step of measuring the methylation level of a CpG site of any one or more genes selected from the group consisting of SNX8 (Sorting Nexin 8). At this time, the CpG sites are chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925,<h2 style=";text-align:left;direction:ltr">chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227, chr7:2314651, chr7:2314652, chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196,and chr7:112087033, and the metabolic syndrome may include at least one selected from the group consisting of hyperglycemia, abdominal obesity, hypertension, and non-alcoholic fatty liver disease. In addition, the method for providing information for predicting or diagnosing metabolic syndrome of the present invention includes chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536,Any one or more CpG sites selected from the group consisting of chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227, chr7:2314651, and chr7:2314652 are hypermethylated, or chr7:220974, chr7:220975, chr7:223592, chr7:545084, The method may further include a step of predicting that the subject has a high risk of developing metabolic syndrome, or diagnosing that the subject has already developed metabolic syndrome, when any one or more CpG sites selected from the group consisting of chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033 are hypomethylated.

[0023] As a more preferred embodiment, when the metabolic syndrome includes hyperglycemia, the method may include a step of measuring the methylation level of a CpG site, including any one or more CpG sites selected from the group consisting of chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:220974, chr7:220975, chr7:223592, and chr7:545084, wherein any one or more CpG sites selected from the group consisting of chr9:6328440, chr9:36949608, chr9:136545908, and chr9:136549044 are hypermethylated, or chr7:220974, The method may further include a step of predicting that the subject will have a high risk of developing hyperglycemia, or diagnosing that the subject has already developed hyperglycemia, when any one or more CpG sites selected from the group consisting of chr7:220975, chr7:223592, and chr7:545084 are hypomethylated. In case the above metabolic syndrome includes abdominal obesity, the above method is chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713,chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, It may include a step of measuring the methylation level of a CpG site, including any one or more CpG sites selected from the group consisting of chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033, wherein the chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926,chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, Any one or more CpG sites selected from the group consisting of chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, and chr9:138911484 are hypermethylated, or chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, When one or more CpG sites selected from the group consisting of chr7:2106607, chr7:2121196, and chr7:112087033 are hypomethylated, the subject is predicted to have a high risk of developing abdominal obesity, orOr, the method may further include a step of diagnosing that the subject has already developed hypertension. In the case where the metabolic syndrome includes hypertension, the method may further include a step of measuring the methylation level of the CpG site including chr7:2289889, and in this case, when the chr7:2289889 region is hypermethylated, the method may further include a step of predicting that the subject has a high risk of developing hypertension, or diagnosing that the subject has already developed hypertension. Alternatively, when the metabolic syndrome includes non-alcoholic fatty liver disease, the method may further include a step of measuring the methylation level of a CpG site, including any one or more CpG sites selected from the group consisting of chr7:2298227, chr7:2314651, and chr7:2314652, and wherein when any one or more CpG sites selected from the group consisting of chr7:2298227, chr7:2314651, and chr7:2314652 are hypermethylated, the method may further include a step of predicting that the subject has a high risk of developing non-alcoholic fatty liver disease, or diagnosing that the subject has already developed the disease. In this case, the subject means a subject for which the risk of developing metabolic syndrome is to be predicted or the development of the disease is to be diagnosed, and the subject may include, without limitation, any animal that can develop metabolic syndrome, including humans, dogs, horses, cows, rats, goats, and rabbits. In addition, the sample isolated from the above-mentioned individual may be a DNA or nucleic acid extracted from the above-mentioned tissue, etc. as a biological sample capable of detecting the presence or level of methylation. In particular, any nucleic acid capable of detecting the presence of CpG at a methylated CpG site may be used, but is not limited thereto, and any nucleic acid in purified or unpurified form may be used, and any nucleic acid containing or suspected of containing a nucleic acid sequence containing a target site (e.g., CpG-containing nucleic acid) may be used. Specifically, the nucleic acid used to detect the methylation of a CpG site may be DNA,In particular, but not limited to, genomic DNA;

[0024] In the method for providing information for predicting or diagnosing the metabolic syndrome of the present invention, the agent for measuring the methylation level of the CpG site of the gene may include at least one selected from the group consisting of bisulfite or a salt thereof, a methylation-sensitive restriction enzyme, a primer specific for a methylated sequence of the CpG site of the gene promoter, a primer specific for an unmethylated sequence, a methylated CpG binding domain, and an antibody specifically binding to methylcytosine, and the methylation-sensitive restriction enzyme may include at least one selected from the group consisting of SmaI, SacII, EagI, HpaII, MspI, BssHII, BstUI, and NotI.

[0025] More specifically, the method for providing information for predicting or diagnosing the metabolic syndrome of the present invention will be described step by step. The step of measuring the methylation level of the CpG site may include: (a) treating genomic DNA in the separated sample with bisulfite or a salt thereof, or a methylation-sensitive restriction enzyme; and (b) amplifying the treated DNA by PCR using primers capable of amplifying the target CpG site. At this time, various amplification methods may be used to measure the methylation level of the CpG site. For example, it may be performed through PCR (Polymerase Chain Reaction), methylation-specific PCR, real-time methylation-specific PCR, PCR using a methylated DNA-specific binding protein, DNA microarray, pyrosequencing, and bisulfite sequencing. Amplification methods other than PCR include, but are not limited to, ligase chain reaction (LCR), transcription amplification, selective amplification of target sequences, PCR using conserved sequences, PCR using random primers, nucleic acid-based sequence amplification (NASBA), and nick replacement amplification. Other methods for measuring methylation levels include, but are not limited to, MALDITOFF, MassARRAY, MethyLight, quantitative analysis of ethylated alleles (QAMA), enzymatic regional methylation assay (ERMA), HeavyMethyl, QBSUPT, MS-SNuPE, MethylQuant, quantitative PCR sequencing, and oligonucleotide-based microarrays. Probes, primers, etc. used to detect methylation status work by hybridizing with the target nucleic acid.Hybridization conditions can be determined based on the specific experimental purpose, the characteristics of the nucleic acids used in the reaction, etc. For example, the length of the nucleic acids in the hybridization region, the degree of homology, the nucleotide sequence composition (e.g., GC / AT composition ratio), and the nucleic acid type (e.g., RNA, DNA) are considered in the selection of hybridization conditions. In general, the optimal conditions for increasing specificity vary depending on the hybridization reaction and can be determined experimentally. PCR primers for detecting the methylation level of CpG sites can be designed in various ways depending on the detection method. For example, in the case of bisulfite analysis, COBRA (Called Combined Bisulfite Restriction Analysis), or Ms-SNuPE (Methylation-sensitive single nucleotide primer extension) analysis, the primers themselves are designed to not cover or hybridize to DNA methylation sites and potential sites, and the sequence variation in the differentially methylated site is located between a pair of primers. Alternatively, primers may be designed to specifically hybridize to methylated or non-methylated sites after compound treatment, and may be designed to include additional sequences, such as restriction enzyme sites, ligand binding sites, linkers, or repeat sequences, provided that the binding complementarity is sufficient so as not to interfere with hybridization. In addition, probes that can specifically bind to a specific product for detection of modified or non-modified DNA may be used, and such probes may bind directly to the modified product or to the amplified product of the modified product, and may be labeled with various known substances for detection, such as fluorescent substances, radioactive substances, bioluminescent substances, luminescent substances, chemiluminescent substances, enzymes, receptors, or ligands. Labeling methods are widely known in the art and can be performed by conventional methods. Alternatively, the methylation level of a CpG site can be measured by Bisulfite Amplicon Sequencing (BSAS).The above BSAS can be performed by various methods known in the art, for example, methylation can be measured by labeling methylated DNA with a fluorescent dye and hybridizing it to a DNA chip on which complementary probes are integrated.

[0026] In another embodiment of the present invention, the present invention is FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like) 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), And a device for predicting or diagnosing metabolic syndrome, including a test unit for measuring the methylation level of a CpG site of at least one gene selected from the group consisting of SNX8 (Sorting Nexin 8); and a judgment unit for determining whether the CpG site is hypomethylated or hypermethylated. In this case, the device may be configured to operate the test unit according to the method for providing information for predicting or diagnosing metabolic syndrome of the present invention using the composition for predicting or diagnosing metabolic syndrome of the present invention. Therefore, descriptions of diseases within specific metabolic syndrome, CpG sites matching them, and judgment methods based on high / low expression of specific diseases within metabolic syndrome and CpG sites combined therewith are omitted in order to prevent excessive complexity of the specification.

[0027] In another specific embodiment of the present invention, the present invention provides a method for isolating FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like 1), CUX1 (Cut Like Homeobox 1), IFRD1 (Interferon Related Developmental Regulator 1), PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2), NOXA1 (NADPH Oxidase Activator 1), FAM102A ((Myc-DDK-tagged)-Human family with sequence similarity 102, member A), NACC2 (NACC Family Member 2), NUDT1 (Nudix A method for predicting or diagnosing metabolic syndrome is provided, comprising a step of measuring the methylation level of a CpG site of any one or more genes selected from the group consisting of SNX8 (Sorting Nexin 8), SNX1 (Sorting Nexin 1), and SNX2 (Sorting Nexin 8). In the method, descriptions of a specific disease in metabolic syndrome, a CpG site matching the disease, and a determination method according to high / low expression of the specific disease in metabolic syndrome and the CpG site combined therewith are the same as the definition in the method for providing information for predicting or diagnosing metabolic syndrome described above, and therefore are omitted to prevent excessive complexity of the specification.

[0028] In another embodiment of the present invention, the present invention is FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like) 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), And SNX8 (Sorting Nexin 8) provides a preparation capable of measuring the methylation level of a CpG site of one or more genes selected from the group consisting of a disease in the metabolic syndrome and a CpG site matching the disease, and a method for determining the disease in the metabolic syndrome and the high / low expression of the CpG site combined therewith, since the description is the same as the definition in the method for providing information for predicting or diagnosing the metabolic syndrome described above, it is omitted to prevent excessive complexity of the specification.

[0029] By using the epigenetic methylation marker of the present invention, the possibility of developing metabolic syndrome or the onset of metabolic syndrome can be predicted or the onset can be diagnosed through correlation analysis of DNA methylation and expression values ​​even with a small amount of sample, thereby making it possible to predict metabolic syndrome or its risk level and facilitate customized treatment and management of patients with metabolic syndrome.

[0030] Figure 1 is a schematic diagram showing an analysis process for confirming the methylation status between a metabolic disease group and a normal control group according to one specific example of the present invention.

[0031] Figure 2 shows the results of comparing methylation patterns in the 7th chromosome region between a metabolic disease group and a normal control group according to one specific example of the present invention.

[0032] Figure 3 shows the results of comparing methylation patterns in the 9th chromosome region between a metabolic disease group and a normal control group according to one specific example of the present invention.

[0033] NEBNext with enzyme treatment ® Using Enzymatic Methyl-seq (EM-seqTM; TWIST Bioscience), we analyzed the methylation status of genomic DNA extracted from blood (3cc of whole blood) of metabolic disease or normal subjects. We identified DNA methylation hotspots specific to specific metabolic diseases on chromosomes 7 and 9. Specifically, metabolic syndrome was associated with methylation of the FAM20C, PDGFA, TPD52L3, PAX5, SARDH, MAD1L1, CUX1, IFRD1, PTPRN2, NOXA1, FAM102A, NACC2, NUDT1, or SNX8 genes.

[0034] Hereinafter, the present invention will be described in more detail through examples. These examples are intended solely to illustrate the present invention more specifically, and it will be apparent to those skilled in the art that the scope of the present invention is not limited by these examples, in accordance with the gist of the present invention.

[0035] Throughout the specification, whenever a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise stated.

[0036] [Research Method]

[0037] 1. Methylation detection.

[0038] A traditional method for detecting DNA methylation involved chemically converting unmethylated cytosine to uracil using bisulfite treatment, thereby identifying methylated cytosine residues. Using this method, unmethylated cytosine is read as thymine after PCR, and methylated cytosine is read as cytosine. However, bisulfite treatment often causes DNA breaks, ultimately leading to failure in methylation detection.

[0039] Therefore, in the present invention, NEBNext using an enzyme treatment method ® Using Enzymatic Methyl-seq (EM-seq™; TWIST Bioscience), we demonstrated a method that achieves the same conversion results as conventional methods without the need for chemical conversion via bisulfite. Ultimately, we achieved results that were significantly more reliable than those obtained with conventional methods.

[0040] 2. DNA methylation test.

[0041] 2-1. DNA methylation

[0042] After preparing 200 ng of genomic DNA extracted from blood (3 cc of whole blood), fragmentation was performed using Qsonica to shear to an average length of 240 ± 290 bp. The sample DNA was end prepped to attach dA-Tailing, and then adapters were attached enzymatically. The adapter-attached DNA was reacted with TET2 to oxidize the 5mC and 5hmC regions, using an Fe(II) solution. After 1 hour of reaction, impurities were removed using beads. The oxidized DNA library was denatured using 0.1 N NaOH, and unmethylated cytosine was converted to thymine, so cytosine was deaminated using APOBEC enzyme to protect the 5mC and 5hmC regions. After removing impurities using beads, the purified deaminated library was amplified by PCR.

[0043] 2-2. Amplification of methylated DNA

[0044] The DNA library prepared in the previous step was mixed with the methylation panel, dried at room temperature, and hybridized. Hybridization was performed at 60°C for 2 hours with the hybridization material and DNA well mixed. The hybridization material was quickly and carefully washed using beads and a high-temperature (65°C) washing solution. Care was taken to ensure that the temperature of the hybridization sample did not drop below 60°C. The washed sample was homogenized with clean water and beads, and PCR amplification was performed in the homogenized state. After removing impurities, the concentration of the final library was measured. The final library was sequenced using the Illumina NGS (NextSeq 550) system, and the average yield was 12 Gbp, and the average on-target ratio was 41.6x.

[0045] 3. Methylation pattern analysis

[0046] The analysis process for confirming methylation status is shown in Figure 1. First, the quality of the generated base sequences was assessed to remove base sequences in low-quality regions (FastQC v0.11.9), and then methylated / unmethylated cytosine base sequences were identified and mapped to the reference sequence (bwameth v0.2.4). Since there were reads with duplicate sequences produced with the same sequence among the mapped reads, these were removed and the data quality control was confirmed (Picard v2.26.10). At this time, the depth of the target region was calculated using samtool (v1.14). Since bias may occur at both ends of the reads when methylation has occurred, a process to confirm this is necessary, and the location and level of methylation were analyzed using the methyldackel (v0.6.1) analysis tool.

[0047] Meanwhile, methylation information extracted from the metabolic disease group and the normal control group was analyzed for pattern differences between the two groups. Specifically, methylation call information was identified using the methylKit package (v1.24.0) included in the R program (v4.1.2), regions with depths <10 were removed, and methylation call regions of the analysis target samples were merged to analyze pattern similarity. Methylation patterns between the two groups were compared using the Pheatmap package included in the R program.

[0048] [Research Results]

[0049] 1. Comparison of clinical data between metabolic disease group and normal control group

[0050] The basic clinical data for the metabolic disease group (n=20) and the control group classified as normal (n=20) are shown in Table 1. The two groups showed significant differences in systolic blood pressure, blood sugar, and triglycerides (p=2.2x10 -6 , p=1.3x10 -5 , p=2.5x10 -6 ), age, weight, waist circumference, BMI, diastolic blood pressure, HDL, LDL, and γ-GTP also showed statistically significant differences (p<0.05). The comparison of methylation patterns between the groups of the present invention was performed with reference to the above clinical data. However, there was no difference between the two groups in kidney, total cholesterol, aspartate lyase, alanine aminoase, creatinine, and glomerular filtration rate.

[0051] Clinical indicators, Control group, Metabolic syndrome, P value, No. of study participants, 2020, Age (years), 42.0±9.9, 54.5±11.1, 6.0×10 -4 Height (cm)160.3±5.4157.7±6.20.1593Weight (kg)56.5±6.862.9±10.83.0×10 -2 Waist measurement (cm)73.5±6.282.3±9.03.0×10 -4 BMI (kg / ㎡)22.1±3.125.2±3.12.5×10 -3 SBP (mmHg)110.0±8.9127.7±11.12.2×10 -6 DBP (mmHg)70.3±8.476.2±8.53.5×10 -2 Blood glucose (mg / dL)87.3±6.5104.5±13.91.3×10 -5 Total cholesterol (mg / dL)194.0±19.6210.4±31.00.0526HDL cholesterol (mg / dL)76.7±16.557.1±19.01.2×10 -3 LDL cholesterol (mg / dL)103.4±20.2123.4±33.62.8×10-3 Triglyceride (mg / dL)77.6±28.8156.3±56.72.5×10 -6 AST (U / L)21.7±8.822.8±4.70.6399ALT (U / L)18.0±11.021.9±8.90.2232γ-GTP (U / L)15.6±8.827.0±18.41.6×10 -2 Serum creatinine (mg / dL)0.7±0.10.7±0.10.2432GFR (mL / min / 1.73㎡)96.7±21.785.6±18.00.1654Values ​​are shown as mean ± SD.BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein cholesterol; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, γ-glutamyltranspeptidase; GFR, glomerular filtration rate.

[0052] 2. Comparison of methylation patterns between metabolic disease groups and normal controls

[0053] All samples, including metabolic disease groups and normal controls, were analyzed for methylation status against the reference sequence, and this information was used to compare and analyze methylation patterns between metabolic disease groups and normal controls. Statistical significance was calculated as the P value using Fisher's exact test or logistic regression. The P value was adjusted using Bonferroni correction, and the Q value was calculated using a sliding linear model (SLIM). From this, the adjusted P value < 5 x 10 -8And the region where the differential methylation value increased by 25% or more (Hypermethylation) or decreased by 25% or more (Hypomethylation) was extracted, and 464 regions where methylation differences appeared were investigated as a heatmap. At this time, the region where methylation increased by 25% or more compared to the reference sequence for the entire sample was marked in red (Hypermethylation), and the region where methylation decreased by 25% or more was marked in blue (Hypomethylation). As a result, a clear methylation difference between the normal control group and the metabolic disease group was confirmed, especially in the regions of chromosome 7 and chromosome 9 among the entire autosomal regions. The results of the comparison of the methylation pattern in chromosome 7 are shown in Figure 2, and the results of the comparison of the methylation pattern in chromosome 9 are shown in Figure 3, and DNA methylation hotspots specific to specific metabolic diseases in chromosomes 7 and 9 are shown in Tables 2 to 5. In Tables 2 to 5, P values ​​were adjusted with Bonferroni correction, and Hyper-M indicates Hypermethylation and Hypo-M indicates Hypomethylation.

[0054] 고혈당(Hyperglycemia)과 관련된 특이적인 DNA methylation hotspotsGenesCpG idChrPosition_startPosition_endfunctionsDifferential methylation(M)P valueQ valueFAM20Cchr7220974220974intronicHypo-M1.24E-141.24E-08FAM20Cchr7220975220975intronicHypo-M2.41E-132.41E-07FAM20Ccg11896151chr7223592223592intronicHypo-M1.58E-481.58E-42PDGFAchr7545084545084intronicHypo-M9.18E-179.18E-11TPD52L3chr963284406328440exonicHyper-M2.05E-252.05E-19PAX5chr93694960836949608intronicHyper-M2.27E-152.27E-09SARDHchr9136545908136545908intronicHyper-M6.26E-556.26E-49SARDHchr9136549044136549044intronicHyper-M1.40E-241.40E-18

[0055] <h2 style=";text-align:left;direction:ltr">복부비만(Central obesity)과 관련된 특이적인 DNA methylation hotspotsGenesCpG idChrPosition_startPosition_endfunctionsDifferential methylation(M)P valueQ valueMAD1L1chr718659211865921intronicHypo-M1.01E-191.01E-13MAD1L1chr718659221865922intronicHypo-M3.04E -243.04E-18MAD1L1chr718806991880699intronicHyper-M6.27E-426.27E-36MAD1L1chr718807001880700intronicHyper r-M2.93E-332.93E-27MAD1L1chr718807371880737intronicHypo-M1.06E-261.06E-20MAD1L1chr718812651881265intronicHypo-M2.79E-472.79E-41MAD1L1chr718812661881266intronicHypo-M7.04E-357.04E-29MAD1L1chr718813691881369 intronicHyper-M7.00E-397.00E-33MAD1L1chr718813701881370intronicHyper-M6.34E-336.34E-27MAD1L1chr7188506 91885069intronicHyper-M1.80E-401.80E-34MAD1L1chr718850701885070intronicHyper-M6.63E-376.63E-31MAD1L1chr 718851141885114intronicHyper-M3.17E-333.17E-27MAD1L1chr718851151885115intronicHyper-M1.75E-241.75E-18M AD1L1chr718851191885119intronicHyper-M5.09E-325.09E-26MAD1L1chr718852211885221intronicHyper-M6.89E-286.<h2 style=";text-align:left;direction:ltr">89E-22MAD1L1chr718869371886937intronicHyper-M3.06E-273.06E-21MAD1L1chr718869381886938intronicHyper-M2.61E-242.61E-18MAD1L1chr718873611887361intronicHyper-M1.16E-351.16E-29MAD1L1chr718873621887362intronicHyper-M9.26E-519.26E-45MAD1L1chr718895201889520 intronicHyper-M8.87E-308.87E-24MAD1L1chr718895211889521intronicHyper-M2.20E-192.20E-13MAD1L1chr718909251890925intronicHyper-M2.23E-502.23E-44MAD1L1chr718909261890926intronicHyper-M2.79E-312.79E-25MAD1L1chr719103741910374intronicHyper-M2.58E-582.58E-5 2MAD1L1chr719104501910450intronicHyper-M5.20E-415.20E-35MAD1L1chr719120561912056intronicHyper-M1.72E-311.72E-25MAD1L1chr71912 0571912057intronicHyper-M1.12E-511.12E-45MAD1L1chr719147571914757intronicHyper-M1.21E-161.21E-10MAD1L1chr719147581914758intro nicHyper-M4.73E-674.73E-61MAD1L1cg12169700chr719236951923695intronicHyper-M9.05E-229.05E-16MAD1L1chr719236961923696intronicHy per-M3.13E-343.13E-28MAD1L1chr719386551938655intronicHyper-M6.83E-276.83E-21MAD1L1chr719386561938656intronicHyper-M3.96E-503.<h2 style=";text-align:left;direction:ltr">96E-44MAD1L1chr719397651939765intronicHyper-M9.16E-279.16E-21MAD1L1chr719397661939766intronicHyper-M1.62E-391.62E-33MAD1L1chr719487121948712intronicHyper-M6.90E-386.90E-32MAD1L1chr719487131948713intronicHyper-M2.33E-472.33E-41MAD1L1cg16178271chr7194 87551948755intronicHyper-M3.02E-403.02E-34MAD1L1chr719487561948756intronicHyper-M1.58E-511.58E-45MAD1L1chr719489481948948intronicHypo-M6.71E-246.71E-18MAD1L1chr719506151950615intronicHypo-M3.89E-243.89E-18MAD1L1chr719682271968227intronicHypo-M2.89E- 622.89E-56MAD1L1chr719735791973579intronicHyper-M1.16E-211.16E-15MAD1L1chr719735801973580intronicHyper-M1.61E-291.61E-23MAD1L1cg03075889chr719764571976457exonicHyper-M3.72E-283.72E-22MAD1L1chr719768621976862intronicHyper-M5.55E-275.55E-21MAD1L1chr71 9779061977906intronicHyper-M2.08E-372.08E-31MAD1L1chr719899461989946intronicHyper-M2.27E-182.27E-12MAD1L1chr720129962012996intronicHyper-M2.04E-602.04E-54MAD1L1chr720129972012997intronicHyper-M1.08E-471.08E-41MAD1L1chr720174452017445intronicHypo-M1.62E-381.62E-32MAD1L1chr720174462017446intronicHypo-M4.72E-534.72E-47MAD1L1chr720198752019875intronicHyper-M1.01E-871.01E-81MAD1L1chr720209942020994intronicHyper-M1.23E-731.23E-67MAD1L1chr720209952020995intronicHyper-M4.60E-434.60E-37MAD1L1chr720273 232027323intronicHyper-M3.51E-573.51E-51MAD1L1chr720273242027324intronicHyper-M2.11E-372.11E-31MAD1L1chr720273542027354intronic nicHyper-M1.44E-631.44E-57MAD1L1chr720273552027355intronicHyper-M6.32E-466.32E-40MAD1L1chr720468302046830intronicHyper-M1.11E -371.11E-31MAD1L1chr720468312046831intronicHyper-M1.05E-431.05E-37MAD1L1cg27286614chr720504012050401intronicHyper-M4.28E-524.28E-46MAD1L1chr720504022050402intronicHyper-M6.04E-476.04E-41MAD1L1chr720601272060127intronicHypo-M9.98E-399.98E-33MAD1L1chr 720825242082524intronicHypo-M7.58E-287.58E-22MAD1L1chr720825362082536intronicHyper-M7.88E-367.88E-30MAD1L1chr721066072106607 intronicHypo-M1.13E-241.13E-18MAD1L1chr721211962121196intronicHypo-M1.17E-581.17E-52MAD1L1chr721720662172066intronicHypo-M6.64E-176.64E-11MAD1L1chr721954432195443intronicHyper-M3.97E-233.97E-17CUX1chr7101917140101917140intronicHyper-M1.28E-281.28E-22IFRD1chr7112087033112087033intronicHypo-M3.67E-283.67E-22PTPRN2chr7157448562157448562intronicHyper-M1.76E-231.76E-17PTPRN2chr7157455211157455211intronicHyper-M6.48E-526.48E-46PTPRN2chr7157455296157455296intronicHyper-M2.80E-252.80E-19NOXA1chr9140322640140322640intronicHyper-M9.91E-429.91E-36FAM102Achr9130703789130703789exonicHyper-M9.46E-399.46E-33NACC2chr9138911484138911484intronicHyper-M1.11E-311.11E-25.

[0056] 고혈압(Hypertension)과 관련된 특이적인 DNA methylation hotspotsGenesCpG idChrPosition_startPosition_endfunctionsDifferential methylation(M)P valueQ valueNUDT1chr722898892289889intronicHyper-M5.64E-235.64E-17

[0057] Specific DNA methylation hotspots associated with non-alcoholic fatty liver disease Genes CpG id Chr Position_start Position_end functions Differential methylation (M) P value Q value SNX8chr722982272298227 intronicHyper-M5.27E-315.27E-25 SNX8chr723146512314651 intronicHyper-M1.71E-371.71E-31 SNX8chr723146522314652 intronicHyper-M1.05E-471.05E-41

[0058] Analyzing the above results, metabolic syndrome is classified as FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), and MAD1L1 (Mitotic Arrest Deficient 1 Like). 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2), NUDT1(Nudix Hydrolase 1), or SNX8(Sorting Nexin 8) was associated with methylation of the gene. Looking at specific DNA methylation hotspots, chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057,chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, Hypermethylation of any one or more regions of chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227, chr7:2314651, and chr7:2314652, or chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, When one or more of the following regions were hypomethylated: chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033, the risk of developing metabolic syndrome was found to be high.

[0059] When analyzed by specific diseases within metabolic syndrome, hyperglycemia was found to be associated with methylation of the FAM20C, PDGFA, TPD52L3, PAX5, or SARDH genes. Looking at specific DNA methylation hotspots, the risk of developing hyperglycemia was found to be high when one or more regions among chr9:6328440, chr9:36949608, chr9:136545908, and chr9:136549044 were hypermethylated, or when one or more regions among chr7:220974, chr7:220975, chr7:223592, and chr7:545084 were hypomethylated.

[0060] Abdominal obesity was associated with methylation of the MAD1L1, CUX1, IFRD1, PTPRN2, NOXA1, FAM102A, or NACC2 genes. Looking at specific DNA methylation hotspots, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789,When one or more regions among chr9:138911484 were hypermethylated, or when one or more regions among chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033 were hypomethylated, the risk of developing abdominal obesity was found to be high.

[0061] Hypertension was associated with methylation of the NUDT1 gene. Specifically, hypermethylation of the chr7:2289889 region was associated with a higher risk of developing hypertension.

[0062] Nonalcoholic fatty liver disease (NAFLD) was associated with methylation of the SNX8 gene. Specifically, hypermethylation of one or more of the following DNA methylation hotspots—chr7:2298227, chr7:2314651, and chr7:2314652—was associated with a higher risk of developing NAFLD.

[0063] Therefore, by analyzing the methylation pattern of the above DNA methylation hotspots, it is expected that it will be possible to predict the risk of developing metabolic syndrome, specifically hyperglycemia, abdominal obesity, hypertension, or non-alcoholic fatty liver disease, and manage the disease.

[0064] While specific aspects of the present invention have been described in detail above, it should be apparent to those skilled in the art that these specific descriptions are merely preferred embodiments and do not limit the scope of the present invention. Therefore, the substantial scope of the present invention is defined by the appended claims and their equivalents.

[0065] Since the biomarker of the present invention can specifically predict the risk of developing each metabolic syndrome disease, it is expected to be actively utilized in the medical and health fields.

Claims

1. FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like 1), CUX1 (Cut Like Homeobox) 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), and SNX8 (Sorting Nexin A composition for predicting or diagnosing metabolic syndrome, comprising a preparation for measuring the methylation level of a CpG site of one or more genes selected from the group consisting of 8).

2. In paragraph 1, CpG 부위는 chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227,chr7:2314651, chr7:2314652, chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and A composition for predicting or diagnosing metabolic syndrome, wherein the composition comprises at least one CpG site selected from the group consisting of chr7:112087033.

3. In paragraph 1, A composition for predicting or diagnosing metabolic syndrome, wherein the metabolic syndrome includes at least one selected from the group consisting of hyperglycemia, abdominal obesity, hypertension, and non-alcoholic fatty liver disease.

4. In paragraph 3, If the above metabolic syndrome includes hyperglycemia, A composition for predicting or diagnosing metabolic syndrome, wherein the CpG site comprises at least one CpG site selected from the group consisting of chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:220974, chr7:220975, chr7:223592, and chr7:545084.

5. In paragraph 3, If the above metabolic syndrome includes abdominal obesity, CpG 부위는 chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948,A composition for predicting or diagnosing metabolic syndrome, comprising at least one CpG site selected from the group consisting of chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033.

6. In paragraph 3, If the above metabolic syndrome includes hypertension, A composition for predicting or diagnosing metabolic syndrome, wherein the CpG site comprises chr7:2289889.

7. In paragraph 3, If the above metabolic syndrome includes non-alcoholic fatty liver disease, A composition for predicting or diagnosing metabolic syndrome, wherein the CpG site comprises at least one CpG site selected from the group consisting of chr7:2298227, chr7:2314651, and chr7:2314652.

8. In paragraph 1, A preparation for measuring the methylation level of the CpG site of the above gene is A composition for predicting or diagnosing metabolic syndrome, comprising at least one selected from the group consisting of bisulfite or a salt thereof, a methylation-sensitive restriction enzyme, a primer specific for a methylated sequence of a CpG site of the gene promoter, a primer specific for an unmethylated sequence, a methylated CpG binding domain, and an antibody specifically binding to methylcytosine.

9. In paragraph 8, A composition for predicting or diagnosing metabolic syndrome, wherein the methylation-sensitive restriction enzyme comprises at least one selected from the group consisting of SmaI, SacII, EagI, HpaII, MspI, BssHII, BstUI, and NotI.

10. A kit for predicting or diagnosing metabolic syndrome, comprising a composition according to any one of claims 1 to 9.

11. From samples isolated from individuals, FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like) 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), A method for providing information for predicting or diagnosing metabolic syndrome, comprising the step of measuring the methylation level of a CpG site of any one or more genes selected from the group consisting of SNX8 (Sorting Nexin 8).

12. In paragraph 11, CpG 부위는 chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227,chr7:2314651, chr7:2314652, chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and A method for providing information for predicting or diagnosing metabolic syndrome, wherein the information is at least one CpG site selected from the group consisting of chr7:112087033.

13. In paragraph 11, A method for providing information for predicting or diagnosing metabolic syndrome, wherein the metabolic syndrome includes at least one selected from the group consisting of hyperglycemia, abdominal obesity, hypertension, and non-alcoholic fatty liver disease.

14. In paragraph 13, If the above metabolic syndrome includes hyperglycemia, A method for providing information for predicting or diagnosing metabolic syndrome, wherein the method comprises measuring the methylation level of a CpG site, including at least one CpG site selected from the group consisting of chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:220974, chr7:220975, chr7:223592, and chr7:545084.

15. In paragraph 13, If the above metabolic syndrome includes abdominal obesity, 상기 방법은 chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615,A method for providing information for predicting or diagnosing metabolic syndrome, comprising measuring the methylation level of a CpG site, including at least one CpG site selected from the group consisting of chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and chr7:112087033.

16. In paragraph 13, If the above metabolic syndrome includes hypertension, The above method is a method for providing information for predicting or diagnosing metabolic syndrome, which comprises measuring the methylation level of a CpG site including chr7:2289889.

17. In paragraph 13, If the above metabolic syndrome includes non-alcoholic fatty liver disease, A method for providing information for predicting or diagnosing metabolic syndrome, wherein the method comprises measuring the methylation level of a CpG site, including at least one CpG site selected from the group consisting of chr7:2298227, chr7:2314651, and chr7:2314652.

18. From samples isolated from individuals, FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like) 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), A test section for measuring the methylation level of a CpG site of one or more genes selected from the group consisting of SNX8 (Sorting Nexin 8); and A device for predicting or diagnosing metabolic syndrome, comprising a judgment unit for determining whether the substance is hypomethylated or hypermethylated.

19. In paragraph 18, CpG 부위는 chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227,chr7:2314651, chr7:2314652, chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and A device for predicting or diagnosing metabolic syndrome, wherein the device is at least one CpG site selected from the group consisting of chr7:112087033.

20. In paragraph 18, A device for predicting or diagnosing metabolic syndrome, wherein the metabolic syndrome includes at least one selected from the group consisting of hyperglycemia, abdominal obesity, hypertension, and non-alcoholic fatty liver disease.

21. From samples isolated from individuals suspected of having metabolic syndrome, FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like) 1),CUX1(Cut Like Homeobox 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), A method for predicting or diagnosing metabolic syndrome, comprising the step of measuring the methylation level of a CpG site of any one or more genes selected from the group consisting of SNX8 (Sorting Nexin 8).

22. In paragraph 21, CpG 부위는 chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227,chr7:2314651, chr7:2314652, chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and A method for predicting or diagnosing metabolic syndrome, wherein the CpG site is at least one selected from the group consisting of chr7:112087033.

23. In paragraph 21, A method for predicting or diagnosing metabolic syndrome, wherein the metabolic syndrome includes at least one selected from the group consisting of hyperglycemia, abdominal obesity, hypertension, and non-alcoholic fatty liver disease. 24.FAM20C (Family with sequence similarity 20, member C), PDGFA (Platelet-derived growth factor subunit A), TPD52L3 (Tumor Protein D52 Like 3), PAX5 (Paired box 5), SARDH (Sarcosine Dehydrogenase), MAD1L1 (Mitotic Arrest Deficient 1 Like 1), CUX1 (Cut Like Homeobox) 1),IFRD1(Interferon Related Developmental Regulator 1),PTPRN2(Protein Tyrosine Phosphatase Receptor Type N2),NOXA1(NADPH Oxidase Activator 1),FAM102A((Myc-DDK-tagged)-Human family with sequence similarity 102, member A),NACC2(NACC Family Member 2),NUDT1(Nudix Hydrolase 1), and SNX8 (Sorting Nexin 8) Use of a preparation capable of measuring the methylation level of a CpG site of one or more genes selected from the group consisting of: predicting or diagnosing metabolic syndrome.

25. In paragraph 24, 상기 제제는 chr9:6328440, chr9:36949608, chr9:136545908, chr9:136549044, chr7:1880699, chr7:1880700, chr7:1881369, chr7:1881370, chr7:1885069, chr7:1885070, chr7:1885114, chr7:1885115, chr7:1885119, chr7:1885221, chr7:1886937, chr7:1886938, chr7:1887361, chr7:1887362, chr7:1889520, chr7:1889521, chr7:1890925, chr7:1890926, chr7:1910374, chr7:1910450, chr7:1912056, chr7:1912057, chr7:1914757, chr7:1914758, chr7:1923695, chr7:1923696, chr7:1938655, chr7:1938656, chr7:1939765, chr7:1939766, chr7:1948712, chr7:1948713, chr7:1948755, chr7:1948756, chr7:1973579, chr7:1973580, chr7:1976457, chr7:1976862, chr7:1977906, chr7:1989946, chr7:2012996, chr7:2012997, chr7:2019875, chr7:2020994, chr7:2020995, chr7:2027323, chr7:2027324, chr7:2027354, chr7:2027355, chr7:2046830, chr7:2046831, chr7:2050401, chr7:2050402, chr7:2082536, chr7:2172066, chr7:2195443, chr7:101917140, chr7:157448562, chr7:157455211, chr7:157455296, chr9:140322640, chr9:130703789, chr9:138911484, chr7:2289889, chr7:2298227,chr7:2314651, chr7:2314652, chr7:220974, chr7:220975, chr7:223592, chr7:545084, chr7:1865921, chr7:1865922, chr7:1880737, chr7:1881265, chr7:1881266, chr7:1948948, chr7:1950615, chr7:1968227, chr7:2017445, chr7:2017446, chr7:2060127, chr7:2082524, chr7:2106607, chr7:2121196, and A method for predicting or diagnosing metabolic syndrome, wherein the methylation level of one or more CpG sites selected from the group consisting of chr7:112087033 can be measured.

26. In paragraph 24, A use for predicting or diagnosing metabolic syndrome, wherein the metabolic syndrome includes at least one selected from the group consisting of hyperglycemia, abdominal obesity, hypertension, and non-alcoholic fatty liver disease.

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