Composition for predicting sulfonylurea dependence using THADA marker and prediction method thereof

Abstract

The present invention relates to compositions and methods that can predict the dependency of diabetic patients on sulfonylureas by identifying variations: a first variation, at least one type selected from the group consisting of a variation (A allele) of a base at the 43801878 site, a variation (T allele) of a base at the 43801909 site, a variation (C allele) of a base at the 43776463 site, a variation (C allele) of a base at the 43625187 site, a variation (C allele) of a base at the 43520160 site, and a variation (G allele) of a base at the 43805692 site in a chromosome 2 of GRCH37 / hg19 of THADA; or the second variation reduces the function of THADA protein, and the allele frequency is 5% or less.

Description

Technical Field

[0001] The present invention relates to a composition for predicting sulfonylurea dependence and a method for predicting sulfonylurea dependence. Background Art

[0002] Compared with the research on markers related to the sensitivity of diabetes onset, the research on markers related to the effect of diabetes therapeutic agents is very little. Therefore, there is no competitive technology for using clinically significant genetic markers for diabetes therapeutic agents, and there is no experience of medical staff and prescription based on the clinical characteristics of patients.

[0003] There are currently nine series of diabetes treatment agents used clinically. There are recommended prescription guidelines by societies in the United States, Europe, including Korea (Standards of Medical Care in Diabetes. Diabetes Care Jan 2022, Korean Diabetes Society Diabetes Diagnosis and Treatment Guidelines 2021), but these guidelines are not based on predictions of blood sugar-lowering effects and are not helpful for predictions.

[0004] Sulfonylureas are the most powerful hypoglycemic agents with the longest history. Compared with other series of drugs, they not only have a higher risk of hypoglycemia, but also have a lower overall prescription priority as other oral hypoglycemic agents with proven cardiovascular protective effects are developed. However, it has been confirmed that some patient groups tend to rely heavily on sulfonylureas to regulate blood sugar. In these specific patients, sulfonylureas need to be used preferentially, but clinical characteristics or markers that can predict this are still unknown.

[0005] Therefore, there is a need to discover markers associated with sulfonylurea dependence for diabetes treatment and to develop a technique for confirming sensitivity to sulfonylureas based on the markers. Summary of the invention

[0006] Technical issues

[0007] The present invention provides a composition for predicting sulfonylurea dependence by discovering genes that determine sulfonylurea dependence.

[0008] The present invention provides a method for providing information useful for predicting sulfonylurea dependence.

[0009] Technical Solution

[0010] 1. A composition for predicting sulfonylurea dependence in a diabetic patient, comprising an agent for confirming the following mutations: a first mutation, at least one selected from the group consisting of a mutation at base 43801878 (A allele), a mutation at base 43801909 (T allele), a mutation at base 43776463 (C allele), a mutation at base 43625187 (C allele), a mutation at base 43520160 (C allele) and a mutation at base 43805692 (G allele) of chromosome 2 of GRCH37 / hg19 of THADA (THADA armadillo repeat containing); or a second mutation, which reduces the function of THADA protein and has an allele frequency of 5% or less.

[0011] 2. In the composition for predicting sulfonylurea dependence in a diabetic patient according to 1 above, the second variation is a missense mutation, a frameshift mutation, a nonsense mutation or a splice site mutation.

[0012] 3. In the composition for predicting sulfonylurea dependence in a diabetic patient according to 1 above, the agent is a primer or a probe that specifically binds to the THADA gene.

[0013] 4. In the composition for predicting sulfonylurea dependence in a diabetic patient according to 1 above, the second variation is selected from the group consisting of a variation at base 43230964 (C allele), a variation at base 43231141 (A allele), a variation at base 43231295 (T allele), a variation at base 43231306 (A allele), a variation at base 43231306 (C allele), a variation at base 43231323 (T allele), a variation at base 43232797 (G allele), a variation at base 43232820 (A allele), a variation at base 4323296 (T allele), a variation at base 4323297 (C allele), a variation at base 4323283 (T allele), a variation at base 4323296 (G allele), a variation at base 4323297 (H allele), a variation at base 4323296 (H allele), a variation at base 4323296 (T allele), a variation at base 4323296 (H allele), a variation at base 4323296 (A allele), a variation at base 4323296 (T allele), a variation at base 4323296 (H allele), a variation at base 4323296 ( Mutation at base 32850 (T allele), mutation at base 43232874 (C allele), mutation at base 43232880 (ACT mutation to A allele), mutation at base 43279821 (A allele), mutation at base 43279824 (C allele), mutation at base 43279840 (T allele), mutation at base 43279855 (C allele), mutation at base 43279867 (G allele), mutation at base 43279875 (G allele), mutation at base 43286968 (T allele), mutation at base 43286970 (G allele), mutation at base 43286987 (G allele), mutation at base 43286971 (G allele), mutation at base 43286980 (T allele), mutation at base 43286983 (G allele), mutation at base 43286984 (T allele), mutation at base 43279855 (C allele), mutation at base 43279867 (G allele), mutation at base 43279875 (G allele), mutation at base 43286968 (T allele), mutation at base 43286970 (G allele), mutation at base 43286971 (G allele), mutation at base 43286987 (G allele), mutation at base 43286988 (T allele), mutation at base 43286970 (G allele), mutation at base 43279855 (C allele), mutation at base 43279867 (G allele), mutation at base 43279875 (G allele), mutation at base 43286968 (T allele), mutation at base 43286970 (G allele (C allele), mutation at base 43286995 (A allele), mutation at base 43286998 (T allele), mutation at base 43287058 (C allele), mutation at base 43291749 (A allele), mutation at base 43292125 (G allele), mutation at base 43292130 (T allele), mutation at base 43292144 (T allele), mutation at base 43292201 (C allele), mutation at base 43292983 (A allele), mutation at base 43293195 (G allele), mutation at base 433204 Mutation at base 75 (G allele), mutation at base 43344122 (G allele), mutation at base 43344138 (A allele), mutation at base 43397971 (G allele), mutation at base 43397976 (C allele), mutation at base 43398003 (A allele), mutation at base 43398005 (T allele), mutation at base 43398030 (A allele), mutation at base 43398105 (C allele), mutation at base 43428128 (C allele), mutation at base 43428130 (A allele),The mutation at base 43428131 (A allele), the mutation at base 43428134 (C allele), the mutation at base 43428194 (C allele), the mutation at base 43430242 (A allele), the mutation at base 43430259 (A allele), the mutation at base 43430261 (C allele), the mutation at base 43430265 (T allele), the mutation at base 43430277 (A allele), the mutation at base 43430288 (C allele), the mutation at base 43485283 (C allele), the mutation at base 43485286 (C allele). mutation at base 43485321 (T allele), mutation at base 43485322 (A allele), mutation at base 43498843 (A allele), mutation at base 43498867 (A allele), mutation at base 43498868 (A allele), mutation at base 43498876 (A allele), mutation at base 43498877 (G allele), mutation at base 43498912 (T allele), mutation at base 43498913 (A allele), mutation at base 43498915 (A allele), mutation at base 43498930 (A allele), (A allele), mutation at base 43498937 (A allele), mutation at base 43498941 (AT mutation to A allele), mutation at base 43505722 (A allele), mutation at base 43508647 (A allele), mutation at base 43508653 (C allele), mutation at base 43508657 (C allele), mutation at base 43508676 (T allele), mutation at base 43508677 (C allele), mutation at base 43508683 (C allele), mutation at base 43508688 (T allele), mutation at base 435 Mutation at base 08710 (C allele), mutation at base 43508751 (A allele), mutation at base 43520160 (C allele), mutation at base 43527891 (C allele), mutation at base 43527894 (T allele), mutation at base 43527898 (A allele), mutation at base 43527934 (T allele), mutation at base 43527966 (G allele), mutation at base 43527970 (C allele), mutation at base 43541167 (T allele), mutation at base 43541237 (A allele),Mutation at base 43541254 (C allele), mutation at base 43541296 (T allele), mutation at base 43541298 (CAT mutation to C allele), mutation at base 43549266 (C allele), mutation at base 43549356 (T allele), mutation at base 43549363 (T allele), mutation at base 43551812 (G allele), mutation at base 43551815 (T allele), mutation at base 43551906 (T allele), mutation at base 43552202 (T allele), mutation at base 43552203 (G allele), mutation at base 43552203 (G allele), mutation at base 43552246 (T allele), mutation at base 43552255 (G allele), mutation at base 43552256 (C allele), mutation at base 43552279 (G allele), mutation at base 43552285 (A allele), mutation at base 43552311 (G allele), mutation at base 43552312 (G allele), mutation at base 43552316 (A allele), mutation at base 43556356 (C allele), mutation at base 43556467 The mutation at base 43556467 (G allele), the mutation at base 43556495 (A allele), the mutation at base 43556522 (T allele), the mutation at base 43560299 (A allele), the mutation at base 43560334 (C allele), the mutation at base 43560359 (A allele), the mutation at base 43566712 (C allele), the mutation at base 43566745 (A allele), the mutation at base 43566760 (A allele), the mutation at base 43566766 (T allele), the mutation at base 4356678 Mutation at base 43570390 (C allele), mutation at base 43570392 (C allele), mutation at base 43570471 (G allele), mutation at base 43570490 (G allele), mutation at base 43571736 (A allele), mutation at base 43571736 (G mutation to GCA allele), mutation at base 43571742 (T allele), mutation at base 43571757 (C allele),The mutation at base 43571759 (T allele), the mutation at base 43571760 (C allele), the mutation at base 43571762 (C allele), the mutation at base 43571766 (G allele), the mutation at base 43571775 (G allele), the mutation at base 43571804 (A allele), the mutation at base 43571822 (T allele), the mutation at base 43571858 (T allele), the mutation at base 43572900 (T allele), the mutation at base 43572911 (A allele), the mutation at base 43572949 (G allele). mutation at base 43574347 (A allele), mutation at base 43574378 (C allele), mutation at base 43574429 (C allele), mutation at base 43574432 (T allele), mutation at base 43574440 (A allele), mutation at base 43574473 (T allele), mutation at base 43574474 (C allele), mutation at base 43574477 (A allele), mutation at base 43574551 (G allele), mutation at base 43574606 (G allele), mutation at base 43574690 (G allele), (G allele), mutation at base 43574693 (A allele), mutation at base 43574714 (A allele), mutation at base 43574729 (A allele), mutation at base 43574745 (G allele), mutation at base 43574800 (C allele), mutation at base 43574824 (G allele), mutation at base 43574838 (T allele), mutation at base 43574849 (T allele), mutation at base 43574860 (C allele), mutation at base 43574861 (A allele), mutation at base 43574875 Mutation at base 43574878 (C allele), mutation at base 43574881 (C allele), mutation at base 43574882 (G allele), mutation at base 43574901 (C allele), mutation at base 43574929 (A allele), mutation at base 43574962 (G allele), mutation at base 43575013 (A allele), mutation at base 43575019 (C allele), mutation at base 43575025 (AT mutation to A allele), mutation at base 43577064 (C allele),The mutation of base 43577122 (CCT mutation is C allele), the mutation of base 43577151 (C allele), the mutation of base 43577166 (T allele), the mutation of base 43578565 (G allele), the mutation of base 43578577 (T allele), the mutation of base 43578583 (T allele), the mutation of base 43581834 (A allele), Mutation at base 43586411 (T allele), mutation at base 43586884 (C allele), mutation at base 43586893 (C allele), mutation at base 43586897 (G allele), mutation at base 43586909 (C allele), mutation at base 43586941 (C allele), mutation at base 43586965 (G allele), mutation at base 4359082 The mutation of base 4 (G allele), the mutation of base 43590888 (G allele), the mutation of base 43590947 (C allele), the mutation of base 43590951 (CAATCTAT mutation to C allele), the mutation of base 43591954 (C allele), the mutation of base 43591986 (A allele), the mutation of base 43591998 (A allele), One or more mutations selected from the group consisting of a mutation at base 92040 (T allele), a mutation at base 43592328 (G allele), a mutation at base 43592335 (T allele), a mutation at base 43592390 (T allele), a mutation at base 43625187 (C allele), a mutation at base 43625278 (A allele), and a mutation at base 43818077 (C allele).

[0014] 5. A method for providing information for predicting sulfonylurea dependence in a diabetic patient, comprising the step of confirming the following variation in a biological sample isolated from an individual: a first variation, at least one selected from the group consisting of a variation at base 43801878 (A allele), a variation at base 43801909 (T allele), a variation at base 43776463 (C allele), a variation at base 43625187 (C allele), a variation at base 43520160 (C allele) and a variation at base 43805692 (G allele) of chromosome 2 of GRCH37 / hg19 of THADA; or a second variation, which reduces the function of THADA protein and has an allele frequency of 5% or less.

[0015] 6. In the method for providing information for predicting sulfonylurea dependence in a diabetic patient according to 5 above, the second variation is a missense mutation, a frameshift mutation, a nonsense mutation or a splice site mutation.

[0016] 7. In the method for providing information for predicting sulfonylurea dependence in a diabetic patient according to 5 above, the agent is a primer or a probe that specifically binds to the THADA gene.

[0017] 8. In the method for providing information for predicting sulfonylurea dependence in a diabetic patient according to 5 above, the second variation is selected from the group consisting of a variation at base 43230964 (C allele), a variation at base 43231141 (A allele), a variation at base 43231295 (T allele), a variation at base 43231306 (A allele), a variation at base 43231306 (C allele), a variation at base 43231323 (T allele), a variation at base 43232797 (G allele), a variation at base 43232820 (A allele), and a variation at base 4323283 (T allele). Mutation at base 43232850 (T allele), mutation at base 43232874 (C allele), mutation at base 43232880 (ACT mutation to A allele), mutation at base 43279821 (A allele), mutation at base 43279824 (C allele), mutation at base 43279840 (T allele), mutation at base 43279855 (C allele), mutation at base 43279867 (G allele), mutation at base 43279875 (G allele), mutation at base 43286968 (T allele), mutation at base 43286970 Mutation at base 43286995 (C allele), mutation at base 43286998 (T allele), mutation at base 43287058 (C allele), mutation at base 43291749 (A allele), mutation at base 43292125 (G allele), mutation at base 43292130 (T allele), mutation at base 43292144 (T allele), mutation at base 43292201 (C allele), mutation at base 43292983 (A allele), mutation at base 43293195 (G allele), mutation at base 43320 Mutation at base 475 (G allele), mutation at base 43344122 (G allele), mutation at base 43344138 (A allele), mutation at base 43397971 (G allele), mutation at base 43397976 (C allele), mutation at base 43398003 (A allele), mutation at base 43398005 (T allele), mutation at base 43398030 (A allele), mutation at base 43398105 (C allele), mutation at base 43428128 (C allele), mutation at base 43428130 (A allele),The mutation at base 43428131 (A allele), the mutation at base 43428134 (C allele), the mutation at base 43428194 (C allele), the mutation at base 43430242 (A allele), the mutation at base 43430259 (A allele), the mutation at base 43430261 (C allele), the mutation at base 43430265 (T allele), the mutation at base 43430277 (A allele), the mutation at base 43430288 (C allele), the mutation at base 43485283 (C allele), the mutation at base 43485286 (C allele). mutation at base 43485321 (T allele), mutation at base 43485322 (A allele), mutation at base 43498843 (A allele), mutation at base 43498867 (A allele), mutation at base 43498868 (A allele), mutation at base 43498876 (A allele), mutation at base 43498877 (G allele), mutation at base 43498912 (T allele), mutation at base 43498913 (A allele), mutation at base 43498915 (A allele), mutation at base 43498930 (A allele), (A allele), mutation at base 43498937 (A allele), mutation at base 43498941 (AT mutation to A allele), mutation at base 43505722 (A allele), mutation at base 43508647 (A allele), mutation at base 43508653 (C allele), mutation at base 43508657 (C allele), mutation at base 43508676 (T allele), mutation at base 43508677 (C allele), mutation at base 43508683 (C allele), mutation at base 43508688 (T allele), mutation at base 435 Mutation at base 08710 (C allele), mutation at base 43508751 (A allele), mutation at base 43520160 (C allele), mutation at base 43527891 (C allele), mutation at base 43527894 (T allele), mutation at base 43527898 (A allele), mutation at base 43527934 (T allele), mutation at base 43527966 (G allele), mutation at base 43527970 (C allele), mutation at base 43541167 (T allele), mutation at base 43541237 (A allele),Mutation at base 43541254 (C allele), mutation at base 43541296 (T allele), mutation at base 43541298 (CAT mutation to C allele), mutation at base 43549266 (C allele), mutation at base 43549356 (T allele), mutation at base 43549363 (T allele), mutation at base 43551812 (G allele), mutation at base 43551815 (T allele), mutation at base 43551906 (T allele), mutation at base 43552202 (T allele), mutation at base 43552203 (G allele), mutation at base 43552203 (G allele), mutation at base 43552246 (T allele), mutation at base 43552255 (G allele), mutation at base 43552256 (C allele), mutation at base 43552279 (G allele), mutation at base 43552285 (A allele), mutation at base 43552311 (G allele), mutation at base 43552312 (G allele), mutation at base 43552316 (A allele), mutation at base 43556356 (C allele), mutation at base 43556467 The mutation at base 43556467 (G allele), the mutation at base 43556495 (A allele), the mutation at base 43556522 (T allele), the mutation at base 43560299 (A allele), the mutation at base 43560334 (C allele), the mutation at base 43560359 (A allele), the mutation at base 43566712 (C allele), the mutation at base 43566745 (A allele), the mutation at base 43566760 (A allele), the mutation at base 43566766 (T allele), the mutation at base 4356678 Mutation at base 43570390 (C allele), mutation at base 43570392 (C allele), mutation at base 43570471 (G allele), mutation at base 43570490 (G allele), mutation at base 43571736 (A allele), mutation at base 43571736 (G mutation to GCA allele), mutation at base 43571742 (T allele), mutation at base 43571757 (C allele),The mutation at base 43571759 (T allele), the mutation at base 43571760 (C allele), the mutation at base 43571762 (C allele), the mutation at base 43571766 (G allele), the mutation at base 43571775 (G allele), the mutation at base 43571804 (A allele), the mutation at base 43571822 (T allele), the mutation at base 43571858 (T allele), the mutation at base 43572900 (T allele), the mutation at base 43572911 (A allele), the mutation at base 43572949 (G allele). mutation at base 43574347 (A allele), mutation at base 43574378 (C allele), mutation at base 43574429 (C allele), mutation at base 43574432 (T allele), mutation at base 43574440 (A allele), mutation at base 43574473 (T allele), mutation at base 43574474 (C allele), mutation at base 43574477 (A allele), mutation at base 43574551 (G allele), mutation at base 43574606 (G allele), mutation at base 43574690 (G allele), (G allele), mutation at base 43574693 (A allele), mutation at base 43574714 (A allele), mutation at base 43574729 (A allele), mutation at base 43574745 (G allele), mutation at base 43574800 (C allele), mutation at base 43574824 (G allele), mutation at base 43574838 (T allele), mutation at base 43574849 (T allele), mutation at base 43574860 (C allele), mutation at base 43574861 (A allele), mutation at base 43574875 Mutation at base 43574878 (C allele), mutation at base 43574881 (C allele), mutation at base 43574882 (G allele), mutation at base 43574901 (C allele), mutation at base 43574929 (A allele), mutation at base 43574962 (G allele), mutation at base 43575013 (A allele), mutation at base 43575019 (C allele), mutation at base 43575025 (AT mutation to A allele), mutation at base 43577064 (C allele),The mutation of base 43577122 (CCT mutation is C allele), the mutation of base 43577151 (C allele), the mutation of base 43577166 (T allele), the mutation of base 43578565 (G allele), the mutation of base 43578577 (T allele), the mutation of base 43578583 (T allele), the mutation of base 43581834 (A allele), Mutation at base 43586411 (T allele), mutation at base 43586884 (C allele), mutation at base 43586893 (C allele), mutation at base 43586897 (G allele), mutation at base 43586909 (C allele), mutation at base 43586941 (C allele), mutation at base 43586965 (G allele), mutation at base 4359082 The mutation of base 4 (G allele), the mutation of base 43590888 (G allele), the mutation of base 43590947 (C allele), the mutation of base 43590951 (CAATCTAT mutation to C allele), the mutation of base 43591954 (C allele), the mutation of base 43591986 (A allele), the mutation of base 43591998 (A allele), One or more mutations selected from the group consisting of a mutation at base 92040 (T allele), a mutation at base 43592328 (G allele), a mutation at base 43592335 (T allele), a mutation at base 43592390 (T allele), a mutation at base 43625187 (C allele), a mutation at base 43625278 (A allele), and a mutation at base 43818077 (C allele).

[0018] 9. In the method for providing information for predicting sulfonylurea dependence of a diabetic patient according to 5 above, the method further comprises the step of providing information that an individual having the first variation or the second variation has sulfonylurea dependence.

[0019] Effects of the Invention

[0020] By using the THADA of the present invention as a marker, it is possible to predict whether or not a patient is excellent in the hypoglycemic effect of sulfonylureas, and information useful therefor can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Schematic diagram of the method for deriving sulfonylurea dependency-associated variants of the present invention.

[0022] DM: diabetes mellitus; FPG: fasting plasma glucose; MAF: minor allele frequency; SNV: single nucleotide variant; SU: sulfonylurea; WES: whole exome sequencing.

[0023] Figure 2 This is a graph showing the blood concentration of HbA1c (glycosylated hemoglobin) or FPG (fasting blood glucose) after discontinuation of sulfonylurea administration in a retrospective study.

[0024] Values ​​are expressed as mean ± SD.

[0025] ***: p<0.001, between the 2 groups by 2-way repeated measures ANOVA.

[0026] FPG: fasting blood glucose; peak: highest measures within 6 months after SU discontinuation; SU: sulfonylurea.

[0027] Figure 3 A diagram schematically illustrating a method for prospectively testing THADA candidate variants of the present invention.

[0028] FPG: fasting plasma glucose; SU: sulfonylurea; WES: whole exome sequencing

[0029] Figure 4 This is a graph showing the blood concentration of HbA1c (glycosylated hemoglobin) or FPG after discontinuation of sulfonylurea administration in a prospective study.

[0030] Values ​​are expressed as mean ± SD.

[0031] **: p < 0.01, the differences between the two groups were compared by two-way repeated measures ANOVA.

[0032] FPG: fasting blood glucose; peak: highest measures within 20 weeks after SU discontinuation; SU: sulfonylurea.

[0033] Figure 5 Schematic representation of the method used to extract THADA variants from UK Biobank registries for testing the present invention in a large population.

[0034] eGFR: estimated glomerular filtration calculated by the CKD-EPI method; SU: sulfonylurea

[0035] Figure 6 Schematic diagram of the method for extracting variants from public gene databases in order to test the THADA variants of the present invention in a large population.

[0036] SU: sulfonylurea; WES: whole exome sequencing.

[0037] dbNSFP v4.(http: / / database.liulab.science / dbNSFP)

[0038] genomAD exomes v2.1.1(https: / / gnomad.broadinstitute.org) DETAILED DESCRIPTION

[0039] The present invention is described in detail below. Unless otherwise defined, the meanings of all terms in this specification are the same as the common meanings of the relevant terms understood by ordinary technicians in the technical field to which the present invention belongs. If there is a conflict with the meaning of the terms used in this specification, the meaning used in this specification shall prevail.

[0040] The present invention relates to a composition for predicting sulfonylurea dependence in a diabetic patient, comprising an agent for confirming the following mutations: a first mutation, at least one selected from the group consisting of a mutation at base 43801878 (A allele), a mutation at base 43801909 (T allele), a mutation at base 43776463 (C allele), a mutation at base 43625187 (C allele), a mutation at base 43520160 (C allele) and a mutation at base 43805692 (G allele) of chromosome 2 of GRCH37 / hg19 of THADA; or a second mutation, which reduces the function of THADA protein and has an allele frequency of 5% or less.

[0041] In the present invention, the sulfonylurea dependence refers to the degree to which the diabetic patient can only rely on sulfonylureas to lower blood sugar or should take sulfonylureas in priority to other drugs. That is, it means that when taking conventionally known hypoglycemic agents that are not sulfonylureas, such as metformin, gliptin, pioglitazone, etc., blood sugar is not lowered or the effect is not as expected, and only when taking sulfonylureas can the expected blood sugar effect be shown, so sulfonylureas should be taken in priority.

[0042] In the present invention, the composition for predicting sulfonylurea dependence is a composition that can predict whether a diabetic patient has the sulfonylurea dependence by a preparation for confirming the following mutations: a first mutation, at least one selected from the group consisting of a mutation at base 43801878 (A allele), a mutation at base 43801909 (T allele), a mutation at base 43776463 (C allele), a mutation at base 43625187 (C allele), a mutation at base 43520160 (C allele) and a mutation at base 43805692 (G allele) of chromosome 2 of GRCH37 / hg19 of THADA; or a second mutation, which reduces the function of THADA protein and has an allele frequency of 5% or less.

[0043] The second variation is a variation that reduces the function of the THADA protein and has an allele frequency of 5% or less. As long as it is such a variation, its type, variation position, variation base, etc. are not limited. The variation that reduces the protein function can be, for example, a variation that predicts a functional change by a known method such as SIFT or Polyphen. Many variations of THADA are known (dbNSFP, gnomAD, etc.) together with the variation frequency and the effect of the variation type, and the prediction results of the protein function are therefore easily confirmed to be the second variation.

[0044] In the present invention, as long as the base sequence of the gene is added, deleted or changed, it can be included in the scope of the present invention without limitation. For example, it can be a missense mutation, a frameshift mutation, a nonsense mutation or a splice site mutation, and preferably, it can be a case of inducing a mutation that affects the function of the gene protein of the present invention. But it is not limited to this.

[0045] For example, the second variation may be a variation at base 43230964 (C allele), a variation at base 43231141 (A allele), a variation at base 43231295 (T allele), a variation at base 43231306 (A allele), a variation at base 43231306 (C allele), a variation at base 43231323 (T allele), a variation at base 43232797 (G allele), a variation at base 43232820 (A allele), a variation at base 43232850 (T allele), a variation at base 43232874 of chromosome 2 of GRCH37 / hg19. (C allele), mutation at base 43232880 (ACT mutation to A allele), mutation at base 43279821 (A allele), mutation at base 43279824 (C allele), mutation at base 43279840 (T allele), mutation at base 43279855 (C allele), mutation at base 43279867 (G allele), mutation at base 43279875 (G allele), mutation at base 43286968 (T allele), mutation at base 43286970 (C allele), mutation at base 43286995 (A allele), mutation at base 43286 Mutation at base 4329998 (T allele), mutation at base 43287058 (C allele), mutation at base 43291749 (A allele), mutation at base 43292125 (G allele), mutation at base 43292130 (T allele), mutation at base 43292144 (T allele), mutation at base 43292201 (C allele), mutation at base 43292983 (A allele), mutation at base 43293195 (G allele), mutation at base 43320475 (G allele), mutation at base 43344122 (G allele), mutation at base 4334423 (G allele), mutation at base 433443 Mutation at base 344138 (A allele), mutation at base 43397971 (G allele), mutation at base 43397976 (C allele), mutation at base 43398003 (A allele), mutation at base 43398005 (T allele), mutation at base 43398030 (A allele), mutation at base 43398105 (C allele), mutation at base 43428128 (C allele), mutation at base 43428130 (A allele), mutation at base 43428131 (A allele), mutation at base 43428134 (C allele),The mutation at base 43428194 (C allele), the mutation at base 43430242 (A allele), the mutation at base 43430259 (A allele), the mutation at base 43430261 (C allele), the mutation at base 43430265 (T allele), the mutation at base 43430277 (A allele), the mutation at base 43430288 (C allele), the mutation at base 43485283 (C allele), the mutation at base 43485286 (C allele), the mutation at base 43485321 (T allele), the mutation at base 43485322 (A allele). The mutation at base 43498843 (A allele), the mutation at base 43498867 (A allele), the mutation at base 43498868 (A allele), the mutation at base 43498876 (A allele), the mutation at base 43498877 (G allele), the mutation at base 43498912 (T allele), the mutation at base 43498913 (A allele), the mutation at base 43498915 (A allele), the mutation at base 43498930 (A allele), the mutation at base 43498937 (A allele), the mutation at base 43498941 (T allele), the mutation at base 43498943 (A allele), the mutation at base 43498947 (A allele), the mutation at base 43498948 (A allele), the mutation at base 43498949 (A allele), the mutation at base 43498940 (A allele), the mutation at base 43498941 (A allele), the mutation at base 43498943 (A allele), the mutation at base 43498944 (A allele), the mutation at base 43498945 (A allele), the mutation at base 43498946 (A allele), the mutation at base 43498947 (A allele), the mutation at base 43498948 ...9 (A allele), the mutation at base 43498941 (A allele), the mutation at base 43498943 (A allele), the mutation at base 43 The mutation at base 43505722 (A allele), the mutation at base 43508647 (A allele), the mutation at base 43508653 (C allele), the mutation at base 43508657 (C allele), the mutation at base 43508676 (T allele), the mutation at base 43508677 (C allele), the mutation at base 43508683 (C allele), the mutation at base 43508688 (T allele), the mutation at base 43508710 (C allele), the mutation at base 43508751 (A allele), the mutation at base 43508660 (T allele), the mutation at base 43508661 (C allele), the mutation at base 43508662 (C allele), the mutation at base 43508663 (C allele), the mutation at base 43508664 (C allele), the mutation at base 43508665 (C allele), the mutation at base 43508666 (T allele), the mutation at base 43508667 (C allele), the mutation at base 43508668 (C allele), the mutation at base 43508669 (C allele), the mutation at base 43508670 (C allele), the mutation at base 43508671 (C allele), the mutation at base 43508672 (C allele), the mutation at base 43508673 (C allele), the mutation at base 43508674 (C allele), the mutation at base 43508675 (A allele), Mutation at base 20160 (C allele), mutation at base 43527891 (C allele), mutation at base 43527894 (T allele), mutation at base 43527898 (A allele), mutation at base 43527934 (T allele), mutation at base 43527966 (G allele), mutation at base 43527970 (C allele), mutation at base 43541167 (T allele), mutation at base 43541237 (A allele), mutation at base 43541254 (C allele), mutation at base 43541296 (T allele),Mutation at base 43541298 (CAT mutation to C allele), mutation at base 43549266 (C allele), mutation at base 43549356 (T allele), mutation at base 43549363 (T allele), mutation at base 43551812 (G allele), mutation at base 43551815 (T allele), mutation at base 43551906 (T allele), mutation at base 43552202 (T allele), mutation at base 43552203 (G allele), mutation at base 43552203 (G allele), mutation at base 43552246 (G allele), mutation at base 43552247 (G allele), mutation at base 43552260 (G allele), mutation at base 43552270 (G allele), mutation at base 43552280 (G allele), mutation at base 43552290 (G allele), mutation at base 43552291 (G allele), mutation at base 43552292 (G allele), mutation at base 43552293 (G allele), mutation at base 43552294 (G allele), mutation at base 43552296 (G allele), mutation at base (T allele), mutation at base 43552255 (G allele), mutation at base 43552256 (C allele), mutation at base 43552279 (G allele), mutation at base 43552285 (A allele), mutation at base 43552311 (G allele), mutation at base 43552312 (G allele), mutation at base 43552316 (A allele), mutation at base 43556356 (C allele), mutation at base 43556467 (G allele), mutation at base 43556467 (T allele), mutation at base 43556495 (G allele), mutation at base 43556496 (G allele), mutation at base 43556497 (G allele), mutation at base 43556498 (G allele), mutation at base 4355649 ...9 (G allele), mutation at base 43556499 (G allele), mutation at base 43556499 (G allele), mutation at base 43556311 (G allele), mutation at base 43556312 (G allele), mutation at base 43556316 (A allele), mutation at base The mutation at base 43566522 (A allele), the mutation at base 43560299 (A allele), the mutation at base 43560334 (C allele), the mutation at base 43560359 (A allele), the mutation at base 43566712 (C allele), the mutation at base 43566745 (A allele), the mutation at base 43566760 (A allele), the mutation at base 43566766 (T allele), the mutation at base 43566785 (T allele), the mutation at base 43566791 (G allele), the mutation at base 43566680 Mutation at base 8 (A allele), mutation at base 43570390 (C allele), mutation at base 43570392 (C allele), mutation at base 43570471 (G allele), mutation at base 43570490 (G allele), mutation at base 43571736 (A allele), mutation at base 43571736 (G mutation to GCA allele), mutation at base 43571742 (T allele), mutation at base 43571757 (C allele), mutation at base 43571759 (T allele), mutation at base 43571760 (C allele),Mutation at base 43571762 (C allele), mutation at base 43571766 (G allele), mutation at base 43571775 (G allele), mutation at base 43571804 (A allele), mutation at base 43571822 (T allele), mutation at base 43571858 (T allele), mutation at base 43572900 (T allele), mutation at base 43572911 (A allele), mutation at base 43572949 (G allele), mutation at base 43574347 (A allele), mutation at base 43574378 (C allele) ), mutation at base 43574429 (C allele), mutation at base 43574432 (T allele), mutation at base 43574440 (A allele), mutation at base 43574473 (T allele), mutation at base 43574474 (C allele), mutation at base 43574477 (A allele), mutation at base 43574551 (G allele), mutation at base 43574606 (G allele), mutation at base 43574690 (G allele), mutation at base 43574693 (A allele), mutation at base 43574714 (A allele), mutation at base 43574729 (A allele), mutation at base 43574745 (G allele), mutation at base 43574800 (C allele), mutation at base 43574824 (G allele), mutation at base 43574838 (T allele), mutation at base 43574849 (T allele), mutation at base 43574860 (C allele), mutation at base 43574861 (A allele), mutation at base 43574875 (C allele), mutation at base 43574878 (G allele), mutation at base 43574881 ( hetero (C allele), mutation at base 43574882 (G allele), mutation at base 43574901 (C allele), mutation at base 43574929 (A allele), mutation at base 43574962 (G allele), mutation at base 43575013 (A allele), mutation at base 43575019 (C allele), mutation at base 43575025 (AT mutation to A allele), mutation at base 43577064 (C allele), mutation at base 43577122 (CCT mutation to C allele), mutation at base 43577151 (C allele),The mutation at base 43577166 (T allele), the mutation at base 43578565 (G allele), the mutation at base 43578577 (T allele), the mutation at base 43578583 (T allele), the mutation at base 43581834 (A allele), the mutation at base 43586411 (T allele), the mutation at base 43586884 ( C allele), mutation at base 43586893 (C allele), mutation at base 43586897 (G allele), mutation at base 43586909 (C allele), mutation at base 43586941 (C allele), mutation at base 43586965 (G allele), mutation at base 43590824 (G allele), mutation at base 43590888 The mutation of base 43590947 (G allele), base 43590951 (CAATCTAT mutation to C allele), base 43591954 (C allele), base 43591986 (A allele), base 43591998 (A allele), base 43592040 ...54 (CAATCTAT mutation to C all (T allele), mutation at base 43592328 (G allele), mutation at base 43592335 (T allele), mutation at base 43592390 (T allele), mutation at base 43625187 (C allele), mutation at base 43625278 (A allele), mutation at base 43818077 (C allele), etc., but are not limited to these.

[0046] The THADA gene may have a sequence in the prediction target. The sequence of each species is known. For example, in the case of humans, the gene may be Gene ID: 63892.

[0047] In the present invention, the preparation for confirming the mutation (first mutation or second mutation) can be used without limitation in type as long as it can confirm its sequence, the presence or absence of the mutation, etc. For example, it can be a primer, a probe or an antisense nucleic acid, but is not limited thereto. The primer, probe or antisense nucleic acid can be used to amplify the nucleic acid sequence of a specific allele at the mutation position or to confirm its presence.

[0048] In the present invention, the diabetic patient may be included in the scope of the present invention regardless of the type of diabetes, and may preferably be type 2 diabetes mellitus (T2DM), but is not limited thereto.

[0049] Furthermore, the present invention relates to a method for providing information for predicting sulfonylurea dependence in a diabetic patient, comprising the step of confirming the following variation in a biological sample isolated from an individual: a first variation, at least one selected from the group consisting of a variation at base 43801878 (A allele), a variation at base 43801909 (T allele), a variation at base 43776463 (C allele), a variation at base 43625187 (C allele), a variation at base 43520160 (C allele) and a variation at base 43805692 (G allele) of chromosome 2 of GRCH37 / hg19 of THADA; or a second variation, which reduces the function of THADA protein and has an allele frequency of 5% or less.

[0050] The second variation may be the aforementioned variation.

[0051] In the present invention, the method for providing information for predicting sulfonylurea dependence of diabetic patients may further include the step of obtaining genotype information of the individual by DNA amplification and sequencing analysis in a biological sample separated from the individual. The DNA amplification, sequencing analysis and genotype information obtaining methods may be used without limitation as long as they are well-known methods in the technical field to which the present invention belongs.

[0052] Furthermore, the information providing method of the present invention may further include the step of providing information that the individual having the first variation or the second variation has sulfonylurea dependence.

[0053] Hereinafter, in order to specifically illustrate the present invention, it will be described in detail through examples.

[0054] Experimental Example 1. Screening of SU-dependent patients through retrospective case query

[0055] This was a retrospective observational study of adult patients with type 2 diabetes who discontinued low-dose sulfonylurea (SU, glimepiride equivalents ≤ 2 mg / day) therapy at Seoul National University Hospital from 2009 to 2015.

[0056] SU dependence was defined as the group that met all the following criteria: (1) HbA1c (glycosylated hemoglobin) ≤7.0% for at least 6 months during low-dose SU (glimepiride equivalent ≤2 mg / day), or HbA1c ≤7.5% with risk of hypoglycemia for at least 6 months; (2) HbA1c increased by ≥1.2% within 3 months or ≥1.5% within 6 months after discontinuation of SU preparation, regardless of whether other oral diabetes therapeutic agents were added or administered; (3) SU was restarted; (4) HbA1c decreased by ≥0.8% or fasting blood glucose decreased by ≥40 mg / dL within 3 months after restarting SU.

[0057] Patients with HbA1c that remained less than 7.5% after SU discontinuation and who had not resumed SU use until the final data collection in 2019 were considered SU-independent. A SU-independent control group was selected from patients with diabetes for more than 10 years and was clinically consistent with SU-dependent patients based on age, sex, and antidiabetic agents. Renal dysfunction (serum creatinine >1.4 mg / dL or estimated glomerular filtration rate (eGFR) <50 mL / min / 1.73 m 2 ), clinically significant liver disease, taking medications such as glucocorticoids that may affect blood sugar regulation, and patients with serious medical problems during changes in SU use were excluded from the analysis.

[0058] As a result, 21 patients who showed SU dependence were selected, and 19 controls who did not show SU dependence were selected. The SU-dependent patients showed a significant increase in blood sugar after SU discontinuation (HbA1c increased from 6.6±0.4% to 8.8±1.0% after 20 weeks) and a significant decrease in blood sugar after SU re-administration (HbA1c was 6.9±0.5% after 12 weeks). The fasting blood sugar also showed the same trend, and a drug responsiveness significantly different from that of the SU-independent control group was confirmed ( Figure 2 ). However, the two groups were similar in clinical characteristics and administration of antidiabetic agents before SU discontinuation (Table 1), and thus, the responsiveness to SU was indistinguishable before SU discontinuation.

[0059] Comparison of clinical characteristics before SU discontinuation and diabetes preparations after discontinuation

[0060] Table 1

[0061]

[0062]

[0063] Data are expressed as mean ± standard deviation or median (range).

[0064] eGFR, estimated glomerular filtration rate; SU, sulfonylurea; T2DM, type 2 diabetes mellitus.

[0065] *: Analyzed by Student's t-test, Mann Whitney test, and Fisher's exact test.

[0066] Experimental Example 2. Whole-exome sequencing (WES)

[0067] Therefore, the genetic characteristics of SU-dependent patients will be analyzed. Due to the small sample size, exon sequencing is intended to be performed in the full length in order to find rare variants with large effect size. Among the 21 SU-dependent patients, blood samples for DNA extraction were collected from 17 patients who voluntarily provided written consent. The relevant studies were conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice, and the institutional review board approved the relevant studies (#1407-103-596). Exon sequencing was performed at Macrogen (Seoul, South Korea). Briefly, DNA was extracted from blood leukocytes, exome capturing was performed using SureSelect v4 + UTR (Agilent Technologies, Santa Clara, CA, USA), and sequenced using the HiSeq 2,000 sequencing system (Illumina Inc., San Diego, CA, USA) at 100x coverage. Sequence reads were aligned to UCSC genome assembly hg19 data using BWA, and variants were called and matched using SAMtoll and ANNOVAR software.

[0068] Experimental Example 3. Deriving candidate mutations ( Figure 1 )

[0069] For gene-based analysis, 260 target genes reported to be associated with β-cell function and β-cell mass were selected, and single nucleotide variants (SNVs) that change the amino acid sequence in these genes were selected based on the results of whole exome sequencing. Type 2 diabetes is not only a complex disease that is greatly affected by rare variants (Am J Hum Genet. 2001; 69: 124), but also limited to uncommon variants (minor allele frequency <5%, 1000 Genomes Phase 1) due to the small number of samples in this study as mentioned above. On the other hand, it is known that the variation of drug response genes varies greatly among different ethnic groups (Genome Med. 2017; 9(1): 117.), and the use of SU is more common in East Asians (EAS), which can be seen as a good response of SU in East Asian patients (Diabetes Obes Metab. 2023Jan; 25(1): 208). Compared with the average frequency worldwide, the minor allele frequency screened out higher variation in East Asians (EAS) (Genome Aggregation Database (gnomAD, v2.1.1).

[0070] Then, in order to select variants that are densely distributed in SU-dependent patients, two control groups, East Asians (gnomAD_EAS) and Koreans with T2DM (SNUH project, http: / / / koex.snu.ac.kr), were compared to screen for variants with an odds ratio of 2 or more. As a result, 94 single nucleotide variants in 70 genes were selected as candidates for SU-dependent related variants (Table 2).

[0071] Table 2

[0072]

[0073]

[0074]

[0075]

[0076]

[0077]

[0078]

[0079] Example 1. Testing of THADA candidate variants in prospectively confirmed SU-dependent patients

[0080] In contrast to the fact that most of the 70 genes screened contained 1 to 2 candidate variants, 6 candidate variants (Nos. 83 to 88) were observed in THADA in 5 of the 17 patients. Therefore, in order to examine whether the THADA candidate variants are associated with SU responsiveness, a clinical study for genetic examination of patients showing SU dependence was prospectively screened (IRB No. H1906 070 1041).

[0081] It was calculated that about 20% of the patients registered in Experimental Example 1 showed SU dependence. Therefore, in order to screen out 10 SU-dependent patients, 50 patients were required, but considering the 15% failure rate, 58 patients were planned to be recruited. The registration criteria are as follows: patients with type 2 diabetes who take low-dose SU (glimepiride equivalent ≤ 2 mg / day or less) and HbA1c ≤ 7.5% during the period of taking for more than 6 months. After obtaining the patient's written consent for the study, SU was discontinued and replaced with other oral diabetes therapeutic agents (glitine or glitazone preparations), and blood glucose and HbA1c were observed for up to 20 weeks to determine SU dependence. If blood glucose significantly worsens (one of the following: HbA1c increases by 1% or more within 12 weeks, HbA1c increases by 1.5% or more within 20 weeks, and fasting blood glucose increases by 80 mg / dL or more within 20 weeks), the patient is determined to be SU-dependent and SU is resumed. As a result of the study, 2 patients were excluded due to withdrawal of study consent, 7 patients showed SU dependence, and 43 did not show it. The remaining 6 patients did not resume SU during the 20-week observation period, but resumed SU later (the average time of SU discontinuation was 40 weeks), so the dependence was unclear ( Figure 3 ). As in the retrospective study, there were no statistically significant differences in the clinical characteristics of the prospectively confirmed SU-dependent patients (Tables 1 and 3). Figure 4 shown.

[0082] Clinical characteristics of SU-dependent patients confirmed by prospective clinical study

[0083] Table 3

[0084]

[0085]

[0086] When exome sequencing (Macrogen, Korea; see Experimental Example 2) was performed on 7 prospectively confirmed SU-dependent patients to analyze whether candidate mutations of THADA (Table 2, Nos. 83 to 88) were observed, Nos. 85, 86, and 88 were confirmed in 2 patients. Considering that these mutations are rare mutations with a rate of about 0.1% in East Asians (Table 4), from the retrospective study ( Figure 1 ) to prospective studies ( Figure 3 ), which was repeatedly observed in a small number of SU-dependent patients and was considered to be significantly associated with SU dependence.

[0087] Sorting out Example 1, when confirming candidate variants of THADA in 7 patients who restarted SU within 20 weeks due to worsening blood sugar levels after replacing low-dose SU with other diabetes preparations, 3 out of 6 candidate variants were observed, which can be interpreted as being related to SU dependence considering the frequency of related variants.

[0088] THADA variants associated with SU dependence were observed

[0089] Table 4

[0090]

[0091]

[0092] a: frameshift, stop-gained, splice donor, splice acceptor, or functional prediction by either Polyphen or SIFT

[0093] b: dbNSFP v4.(http: / / database.liulab.science / dbNSFP) and genomAD exomesv2.1.1(https: / / gnomad.broadinstitute.org)

[0094] EAS: East Asian; EUR: European; MAF: minor allele frequency (genomAD exomes v2.1.1); N: not predicted by either Polyphen or SIFT; NA: not applicable; ND: not detected; P: predicted function; UKBB: UK Biobank.

[0095] Example 2. Testing the effect of SU drugs with THADA mutation in a large population

[0096] Next, in order to analyze whether the candidate variants of THADA are related to SU response in a large population, UK Biobank data were used. UK Biobank is a regional social group in the UK that registered approximately 500,000 people from 2006 to 2010 (Nucleicacids research 47.D1(2019):D1005-D1012). Among them, there were 23,104 patients coded as type 2 diabetes. In order to exclude type 1 diabetes or youth-onset diabetes (youth-onset diabetes) with atypical course, patients under the age of 30 were excluded. Including cases without genetic information, a total of 1,991 people were excluded. In addition, 1,213 patients with impaired renal function (GFR less than 40 ml / min / 1.73 m 2 ) of patients, and 19,900 ( Figure 5 ).

[0097] Since the candidate variants derived in Experimental Example 3 are specific variants screened in East Asians, only 9 out of 19,900 people in the UK Biobank, which is mainly composed of European Caucasians, retain 6 THADA candidate variants (Table 4). In addition, considering the low frequency of candidate variant characteristics, it is expected that there will be unscreened THADA variants in the candidate variants derived from a small number of Korean patients. Therefore, THADA SNVs predicted to affect protein function were screened in dbNSFP (GenomeMedicine. (2020) 12:103), a public SNV database. The screening criteria are that changes in protein function are predicted in computer simulation predictions using Polyphen or SIFT while the variation frequency is less than 5%. Additionally, pLoF (predicted loss of function) variants were screened in gnomAD v2.1.1 browser, which included not only SNVs but also many nucleotide variants, and the following variations were found: transcript ablation, splice acceptor variant, splice donor variant, stop codon gain variant, and frameshift variant. Among the variants screened in the two databases (7548 and 153 in the former and the latter, respectively) and the 6 candidate variants confirmed in Korean SU-dependent patients, 928 variants were extracted from UK Biobank, and among these variants, 197 variants were found in 1335 subjects ( Figure 6 , Table 7).

[0098] Then, 1335 variant holders (test group) were compared with the remaining 18565 patients (control group) (Table 5). The age and diagnosis age of the test group were significantly lower than those of the control group. Even when correcting for age, sex, and BMI using propensity score matching (PSM, 1:10), the diagnosis age of the test group was lower, indicating that variant holders are at high risk of developing diabetes.

[0099] Clinical features according to whether the variant is selected in THADA

[0100] Table 5

[0101]

[0102] BMI: body mass index; PSM: propensity score matching

[0103] Mean ± SD

[0104] At the time of registration in UK Biobank, the order of common drug use in Europe was metformin, sulfonylureas, and insulin. It is difficult to determine whether the influence of genes is reflected in the use of drugs in the early stage of diagnosis. However, as the duration of illness increases, the prescription status also varies with the difference in blood sugar response to the drug. That is, it can be inferred that as the duration of illness increases, the feedback of the drug effect is reflected, so that the prescription status is matched with the genetic susceptibility. Therefore, if the variant holder has a good blood sugar response to SU, the use rate of SU will increase as the duration of illness increases, blood sugar will improve, and the use rate of insulin will be reduced. Therefore, the subject patients were grouped based on the 72-month duration of illness to compare the drug prescription status and blood sugar regulation between the experimental group and the control group (Table 6).

[0105] Clinical characteristics of THADA mutation at different stages of diabetes

[0106] Table 6

[0107]

[0108]

[0109] BMI: body mass index; eGFR: estimated glomerular filtration rate; MTF: metformin; SU: sulfonylurea; PSM: propensity score matching

[0110] Mean ± SD

[0111] In the case of a short duration of illness, the ratio of glycated hemoglobin to metformin users was significantly higher in variant holders, even after correction for age, sex, BMI, duration of illness, and renal function (eGFR) using propensity score matching (1:10). Variant holders, who are at high risk for diabetes (Table 5), also had poor blood glucose regulation, which can be explained by the faster prescription of metformin as a primary agent.

[0112] In cases where the duration of illness was 72 months or longer (median 114 months), the proportion of SU use increased by more than two times (about 15% vs 40%) compared to cases where the duration of illness was less than 72 months (median 30 months). Among them, the proportion of glycated hemoglobin and metformin users in the experimental group did not differ from that in the control group, but the proportion of SU users was significantly higher. When propensity score matching (1:10) was used to adjust for age, gender, BMI, duration of illness, and renal function (eGFR), the statistical significance disappeared, but the proportion of SU users was still high (41.3 vs 45.7%, P = 0.0746). In other words, it can be explained that when SU ​​is added as a secondary drug due to long-term diabetes, the blood sugar difference between the variant holder and the control group gradually disappears as the use of SU is further prolonged.

[0113] In particular, the proportion of starting insulin prescription after SU treatment failure showed a tendency to be low in variant holders regardless of the duration of illness (Table 6). When the total duration of illness was adjusted for age, gender, BMI, duration of illness, i.e., renal function, the proportion was 9.51% in the experimental group and 11.43% in the control group, showing a significant difference (p=0.0387). In other words, it can be explained that variant holders have a good response to SU and good blood sugar regulation, so insulin prescription is delayed.

[0114] Summarizing the contents of Example 2, the results of analyzing the characteristics of THADA screening variant holders using UK Biobank data showed that these were high-risk groups for diabetes, with poor blood sugar regulation, and most of them used metformin as a primary agent in the early stage. However, at the time point when sulfonylureas were added during the long illness period, blood sugar regulation was similar. On the other hand, the use rate of additional insulin when sulfonylureas failed was low, so this can be regarded as a good response of THADA variant holders to sulfonylureas.

[0115] In summary, most candidate variants in THADA derived from retrospectively screened SU-dependent patients ( Figure 1 , Figure 2 , Table 2), three THADA gene mutations with a frequency of about 0.1% were verified in 7 patients who were typically confirmed to be SU-dependent (Example 1: Figure 3 , Figure 4 , Table 4). In addition, when the UK Biobank data were analyzed by adding the variant predicted to change the protein function of the THADA gene, it was observed that when the genetic susceptibility to drugs was reflected in the prescription status due to the long illness period and the use of 2SU as a secondary drug increased, the blood sugar of the THADA variant holders was similar to that of the control group, and the insulin use rate was low (Example 2: Figure 5 , Figure 6 , Table 6, Table 7).

[0116] Although pharmacogenetics of T2DM has not yet been clinically applied, it is an area that can be applied in downstream groups such as SU-dependent patients. Through this study, single nucleotide variants associated with responsiveness to SU were discovered in type 2 diabetes, which will help predict SU response through genetic analysis.

[0117] Table 7

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125]

Claims

1. A composition for predicting sulfonylurea dependence in diabetic patients, characterized in that: Contains preparations for confirming the following variants: The first mutation is at least one selected from the group consisting of a mutation at base 43801878 (A allele), a mutation at base 43801909 (T allele), a mutation at base 43776463 (C allele), a mutation at base 43625187 (C allele), a mutation at base 43520160 (C allele), and a mutation at base 43805692 (G allele) of chromosome 2 of GRCH37 / hg19 of THADA; or The second variant reduces the function of the THADA protein, with an allele frequency of less than 5%.

2. The composition for predicting sulfonylurea dependence in diabetic patients according to claim 1, characterized in that: The second variation is a missense mutation, a frameshift mutation, a nonsense mutation or a splice site mutation.

3. The composition for predicting sulfonylurea dependence in diabetic patients according to claim 1, characterized in that: The preparation is a primer or a probe that specifically binds to the THADA gene.

4. The composition for predicting sulfonylurea dependence in diabetic patients according to claim 1, characterized in that: The second variation is selected from the group consisting of a variation at base 43230964 (C allele) of chromosome 2 of GRCH37 / hg19, a variation at base 43231141 (A allele), a variation at base 43231295 (T allele), a variation at base 43231306 (A allele), a variation at base 43231306 (C allele), a variation at base 43231323 (T allele), a variation at base 43232797 (G allele), a variation at base 43232820 (A allele), a variation at base 43232850 (T allele), and a variation at base 43232874 (C allele), mutation at base 43232880 (ACT mutation to A allele), mutation at base 43279821 (A allele), mutation at base 43279824 (C allele), mutation at base 43279840 (T allele), mutation at base 43279855 (C allele), mutation at base 43279867 (G allele), mutation at base 43279875 (G allele), mutation at base 43286968 (T allele), mutation at base 43286970 (C allele), mutation at base 43286995 (A allele), mutation at base 43286 Mutation at base 4329998 (T allele), mutation at base 43287058 (C allele), mutation at base 43291749 (A allele), mutation at base 43292125 (G allele), mutation at base 43292130 (T allele), mutation at base 43292144 (T allele), mutation at base 43292201 (C allele), mutation at base 43292983 (A allele), mutation at base 43293195 (G allele), mutation at base 43320475 (G allele), mutation at base 43344122 (G allele), mutation at base 4334423 (G allele), mutation at base 433443 Mutation at base 344138 (A allele), mutation at base 43397971 (G allele), mutation at base 43397976 (C allele), mutation at base 43398003 (A allele), mutation at base 43398005 (T allele), mutation at base 43398030 (A allele), mutation at base 43398105 (C allele), mutation at base 43428128 (C allele), mutation at base 43428130 (A allele), mutation at base 43428131 (A allele), mutation at base 43428134 (C allele),The mutation at base 43428194 (C allele), the mutation at base 43430242 (A allele), the mutation at base 43430259 (A allele), the mutation at base 43430261 (C allele), the mutation at base 43430265 (T allele), the mutation at base 43430277 (A allele), the mutation at base 43430288 (C allele), the mutation at base 43485283 (C allele), the mutation at base 43485286 (C allele), the mutation at base 43485321 (T allele), the mutation at base 43485322 (A allele). The mutation at base 43498843 (A allele), the mutation at base 43498867 (A allele), the mutation at base 43498868 (A allele), the mutation at base 43498876 (A allele), the mutation at base 43498877 (G allele), the mutation at base 43498912 (T allele), the mutation at base 43498913 (A allele), the mutation at base 43498915 (A allele), the mutation at base 43498930 (A allele), the mutation at base 43498937 (A allele), the mutation at base 43498941 (T allele), the mutation at base 43498943 (A allele), the mutation at base 43498947 (A allele), the mutation at base 43498948 (A allele), the mutation at base 43498949 (A allele), the mutation at base 43498940 (A allele), the mutation at base 43498941 (A allele), the mutation at base 43498943 (A allele), the mutation at base 43498944 (A allele), the mutation at base 43498945 (A allele), the mutation at base 43498946 (A allele), the mutation at base 43498947 (A allele), the mutation at base 43498948 ...9 (A allele), the mutation at base 43498941 (A allele), the mutation at base 43498943 (A allele), the mutation at base 43 The mutation at base 43505722 (A allele), the mutation at base 43508647 (A allele), the mutation at base 43508653 (C allele), the mutation at base 43508657 (C allele), the mutation at base 43508676 (T allele), the mutation at base 43508677 (C allele), the mutation at base 43508683 (C allele), the mutation at base 43508688 (T allele), the mutation at base 43508710 (C allele), the mutation at base 43508751 (A allele), the mutation at base 43508660 (T allele), the mutation at base 43508661 (C allele), the mutation at base 43508662 (C allele), the mutation at base 43508663 (C allele), the mutation at base 43508664 (C allele), the mutation at base 43508665 (C allele), the mutation at base 43508666 (T allele), the mutation at base 43508667 (C allele), the mutation at base 43508668 (C allele), the mutation at base 43508669 (C allele), the mutation at base 43508670 (C allele), the mutation at base 43508671 (C allele), the mutation at base 43508672 (C allele), the mutation at base 43508673 (C allele), the mutation at base 43508674 (C allele), the mutation at base 43508675 (A allele), Mutation at base 20160 (C allele), mutation at base 43527891 (C allele), mutation at base 43527894 (T allele), mutation at base 43527898 (A allele), mutation at base 43527934 (T allele), mutation at base 43527966 (G allele), mutation at base 43527970 (C allele), mutation at base 43541167 (T allele), mutation at base 43541237 (A allele), mutation at base 43541254 (C allele), mutation at base 43541296 (T allele),Mutation at base 43541298 (CAT mutation to C allele), mutation at base 43549266 (C allele), mutation at base 43549356 (T allele), mutation at base 43549363 (T allele), mutation at base 43551812 (G allele), mutation at base 43551815 (T allele), mutation at base 43551906 (T allele), mutation at base 43552202 (T allele), mutation at base 43552203 (G allele), mutation at base 43552203 (G allele), mutation at base 43552246 (G allele), mutation at base 43552247 (G allele), mutation at base 43552260 (G allele), mutation at base 43552270 (G allele), mutation at base 43552280 (G allele), mutation at base 43552290 (G allele), mutation at base 43552291 (G allele), mutation at base 43552292 (G allele), mutation at base 43552293 (G allele), mutation at base 43552294 (G allele), mutation at base 43552296 (G allele), mutation at base (T allele), mutation at base 43552255 (G allele), mutation at base 43552256 (C allele), mutation at base 43552279 (G allele), mutation at base 43552285 (A allele), mutation at base 43552311 (G allele), mutation at base 43552312 (G allele), mutation at base 43552316 (A allele), mutation at base 43556356 (C allele), mutation at base 43556467 (G allele), mutation at base 43556467 (T allele), mutation at base 43556495 (G allele), mutation at base 43556496 (G allele), mutation at base 43556497 (G allele), mutation at base 43556498 (G allele), mutation at base 4355649 ...9 (G allele), mutation at base 43556499 (G allele), mutation at base 43556499 (G allele), mutation at base 43556311 (G allele), mutation at base 43556312 (G allele), mutation at base 43556316 (A allele), mutation at base The mutation at base 43566522 (A allele), the mutation at base 43560299 (A allele), the mutation at base 43560334 (C allele), the mutation at base 43560359 (A allele), the mutation at base 43566712 (C allele), the mutation at base 43566745 (A allele), the mutation at base 43566760 (A allele), the mutation at base 43566766 (T allele), the mutation at base 43566785 (T allele), the mutation at base 43566791 (G allele), the mutation at base 43566680 Mutation at base 8 (A allele), mutation at base 43570390 (C allele), mutation at base 43570392 (C allele), mutation at base 43570471 (G allele), mutation at base 43570490 (G allele), mutation at base 43571736 (A allele), mutation at base 43571736 (G mutation to GCA allele), mutation at base 43571742 (T allele), mutation at base 43571757 (C allele), mutation at base 43571759 (T allele), mutation at base 43571760 (C allele),Mutation at base 43571762 (C allele), mutation at base 43571766 (G allele), mutation at base 43571775 (G allele), mutation at base 43571804 (A allele), mutation at base 43571822 (T allele), mutation at base 43571858 (T allele), mutation at base 43572900 (T allele), mutation at base 43572911 (A allele), mutation at base 43572949 (G allele), mutation at base 43574347 (A allele), mutation at base 43574378 (C allele) ), mutation at base 43574429 (C allele), mutation at base 43574432 (T allele), mutation at base 43574440 (A allele), mutation at base 43574473 (T allele), mutation at base 43574474 (C allele), mutation at base 43574477 (A allele), mutation at base 43574551 (G allele), mutation at base 43574606 (G allele), mutation at base 43574690 (G allele), mutation at base 43574693 (A allele), mutation at base 43574714 (A allele), mutation at base 43574729 (A allele), mutation at base 43574745 (G allele), mutation at base 43574800 (C allele), mutation at base 43574824 (G allele), mutation at base 43574838 (T allele), mutation at base 43574849 (T allele), mutation at base 43574860 (C allele), mutation at base 43574861 (A allele), mutation at base 43574875 (C allele), mutation at base 43574878 (G allele), mutation at base 43574881 ( hetero (C allele), mutation at base 43574882 (G allele), mutation at base 43574901 (C allele), mutation at base 43574929 (A allele), mutation at base 43574962 (G allele), mutation at base 43575013 (A allele), mutation at base 43575019 (C allele), mutation at base 43575025 (AT mutation to A allele), mutation at base 43577064 (C allele), mutation at base 43577122 (CCT mutation to C allele), mutation at base 43577151 (C allele),The mutation at base 43577166 (T allele), the mutation at base 43578565 (G allele), the mutation at base 43578577 (T allele), the mutation at base 43578583 (T allele), the mutation at base 43581834 (A allele), the mutation at base 43586411 (T allele), the mutation at base 43586884 (C allele), mutation at base 43586893 (C allele), mutation at base 43586897 (G allele), mutation at base 43586909 (C allele), mutation at base 43586941 (C allele), mutation at base 43586965 (G allele), mutation at base 43590824 (G allele), mutation at base 43590888 (G allele), The mutation of base 43590947 (G allele), the mutation of base 43590951 (CAATCTAT mutation to C allele), the mutation of base 43591954 (C allele), the mutation of base 43591986 (A allele), the mutation of base 43591998 (A allele), the mutation of base 43592040 (T Allele), variation at base 43592328 (G allele), variation at base 43592335 (T allele), variation at base 43592390 (T allele), variation at base 43625187 (C allele), variation at base 43625278 (A allele) and variation at base 43818077 (C allele).

5. A method for providing information for predicting sulfonylurea dependence in a diabetic patient, characterized in that The method comprises the steps of identifying the following variants in a biological sample isolated from an individual: The first mutation is at least one selected from the group consisting of a mutation at base 43801878 (A allele), a mutation at base 43801909 (T allele), a mutation at base 43776463 (C allele), a mutation at base 43625187 (C allele), a mutation at base 43520160 (C allele), and a mutation at base 43805692 (G allele) of chromosome 2 of GRCH37 / hg19 of THADA; or The second variant reduces the function of the THADA protein, with an allele frequency of less than 5%.

6. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 5, characterized in that: The second variation is a missense mutation, a frameshift mutation, a nonsense mutation or a splice site mutation.

7. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 5, characterized in that: The preparation is a primer or a probe that specifically binds to the THADA gene.

8. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 5, characterized in that: The second variation is selected from the group consisting of a variation at base 43230964 (C allele) of chromosome 2 of GRCH37 / hg19, a variation at base 43231141 (A allele), a variation at base 43231295 (T allele), a variation at base 43231306 (A allele), a variation at base 43231306 (C allele), a variation at base 43231323 (T allele), a variation at base 43232797 (G allele), a variation at base 43232820 (A allele), a variation at base 43232850 (T allele), and a variation at base 43232874 (C allele), mutation at base 43232880 (ACT mutation to A allele), mutation at base 43279821 (A allele), mutation at base 43279824 (C allele), mutation at base 43279840 (T allele), mutation at base 43279855 (C allele), mutation at base 43279867 (G allele), mutation at base 43279875 (G allele), mutation at base 43286968 (T allele), mutation at base 43286970 (C allele), mutation at base 43286995 (A allele), mutation at base 43286 Mutation at base 4329998 (T allele), mutation at base 43287058 (C allele), mutation at base 43291749 (A allele), mutation at base 43292125 (G allele), mutation at base 43292130 (T allele), mutation at base 43292144 (T allele), mutation at base 43292201 (C allele), mutation at base 43292983 (A allele), mutation at base 43293195 (G allele), mutation at base 43320475 (G allele), mutation at base 43344122 (G allele), mutation at base 4334423 (G allele), mutation at base 433443 Mutation at base 344138 (A allele), mutation at base 43397971 (G allele), mutation at base 43397976 (C allele), mutation at base 43398003 (A allele), mutation at base 43398005 (T allele), mutation at base 43398030 (A allele), mutation at base 43398105 (C allele), mutation at base 43428128 (C allele), mutation at base 43428130 (A allele), mutation at base 43428131 (A allele), mutation at base 43428134 (C allele),The mutation at base 43428194 (C allele), the mutation at base 43430242 (A allele), the mutation at base 43430259 (A allele), the mutation at base 43430261 (C allele), the mutation at base 43430265 (T allele), the mutation at base 43430277 (A allele), the mutation at base 43430288 (C allele), the mutation at base 43485283 (C allele), the mutation at base 43485286 (C allele), the mutation at base 43485321 (T allele), the mutation at base 43485322 (A allele). The mutation at base 43498843 (A allele), the mutation at base 43498867 (A allele), the mutation at base 43498868 (A allele), the mutation at base 43498876 (A allele), the mutation at base 43498877 (G allele), the mutation at base 43498912 (T allele), the mutation at base 43498913 (A allele), the mutation at base 43498915 (A allele), the mutation at base 43498930 (A allele), the mutation at base 43498937 (A allele), the mutation at base 43498941 (T allele), the mutation at base 43498943 (A allele), the mutation at base 43498947 (A allele), the mutation at base 43498948 (A allele), the mutation at base 43498949 (A allele), the mutation at base 43498940 (A allele), the mutation at base 43498941 (A allele), the mutation at base 43498943 (A allele), the mutation at base 43498944 (A allele), the mutation at base 43498945 (A allele), the mutation at base 43498946 (A allele), the mutation at base 43498947 (A allele), the mutation at base 43498948 ...9 (A allele), the mutation at base 43498941 (A allele), the mutation at base 43498943 (A allele), the mutation at base 43 The mutation at base 43505722 (A allele), the mutation at base 43508647 (A allele), the mutation at base 43508653 (C allele), the mutation at base 43508657 (C allele), the mutation at base 43508676 (T allele), the mutation at base 43508677 (C allele), the mutation at base 43508683 (C allele), the mutation at base 43508688 (T allele), the mutation at base 43508710 (C allele), the mutation at base 43508751 (A allele), the mutation at base 43508660 (T allele), the mutation at base 43508661 (C allele), the mutation at base 43508662 (C allele), the mutation at base 43508663 (C allele), the mutation at base 43508664 (C allele), the mutation at base 43508665 (C allele), the mutation at base 43508666 (T allele), the mutation at base 43508667 (C allele), the mutation at base 43508668 (C allele), the mutation at base 43508669 (C allele), the mutation at base 43508670 (C allele), the mutation at base 43508671 (C allele), the mutation at base 43508672 (C allele), the mutation at base 43508673 (C allele), the mutation at base 43508674 (C allele), the mutation at base 43508675 (A allele), Mutation at base 20160 (C allele), mutation at base 43527891 (C allele), mutation at base 43527894 (T allele), mutation at base 43527898 (A allele), mutation at base 43527934 (T allele), mutation at base 43527966 (G allele), mutation at base 43527970 (C allele), mutation at base 43541167 (T allele), mutation at base 43541237 (A allele), mutation at base 43541254 (C allele), mutation at base 43541296 (T allele),Mutation at base 43541298 (CAT mutation to C allele), mutation at base 43549266 (C allele), mutation at base 43549356 (T allele), mutation at base 43549363 (T allele), mutation at base 43551812 (G allele), mutation at base 43551815 (T allele), mutation at base 43551906 (T allele), mutation at base 43552202 (T allele), mutation at base 43552203 (G allele), mutation at base 43552203 (G allele), mutation at base 43552246 (G allele), mutation at base 43552247 (G allele), mutation at base 43552260 (G allele), mutation at base 43552270 (G allele), mutation at base 43552280 (G allele), mutation at base 43552290 (G allele), mutation at base 43552291 (G allele), mutation at base 43552292 (G allele), mutation at base 43552293 (G allele), mutation at base 43552294 (G allele), mutation at base 43552296 (G allele), mutation at base (T allele), mutation at base 43552255 (G allele), mutation at base 43552256 (C allele), mutation at base 43552279 (G allele), mutation at base 43552285 (A allele), mutation at base 43552311 (G allele), mutation at base 43552312 (G allele), mutation at base 43552316 (A allele), mutation at base 43556356 (C allele), mutation at base 43556467 (G allele), mutation at base 43556467 (T allele), mutation at base 43556495 (G allele), mutation at base 43556496 (G allele), mutation at base 43556497 (G allele), mutation at base 43556498 (G allele), mutation at base 4355649 ...9 (G allele), mutation at base 43556499 (G allele), mutation at base 43556499 (G allele), mutation at base 43556311 (G allele), mutation at base 43556312 (G allele), mutation at base 43556316 (A allele), mutation at base The mutation at base 43566522 (A allele), the mutation at base 43560299 (A allele), the mutation at base 43560334 (C allele), the mutation at base 43560359 (A allele), the mutation at base 43566712 (C allele), the mutation at base 43566745 (A allele), the mutation at base 43566760 (A allele), the mutation at base 43566766 (T allele), the mutation at base 43566785 (T allele), the mutation at base 43566791 (G allele), the mutation at base 43566680 Mutation at base 8 (A allele), mutation at base 43570390 (C allele), mutation at base 43570392 (C allele), mutation at base 43570471 (G allele), mutation at base 43570490 (G allele), mutation at base 43571736 (A allele), mutation at base 43571736 (G mutation to GCA allele), mutation at base 43571742 (T allele), mutation at base 43571757 (C allele), mutation at base 43571759 (T allele), mutation at base 43571760 (C allele),Mutation at base 43571762 (C allele), mutation at base 43571766 (G allele), mutation at base 43571775 (G allele), mutation at base 43571804 (A allele), mutation at base 43571822 (T allele), mutation at base 43571858 (T allele), mutation at base 43572900 (T allele), mutation at base 43572911 (A allele), mutation at base 43572949 (G allele), mutation at base 43574347 (A allele), mutation at base 43574378 (C allele) ), mutation at base 43574429 (C allele), mutation at base 43574432 (T allele), mutation at base 43574440 (A allele), mutation at base 43574473 (T allele), mutation at base 43574474 (C allele), mutation at base 43574477 (A allele), mutation at base 43574551 (G allele), mutation at base 43574606 (G allele), mutation at base 43574690 (G allele), mutation at base 43574693 (A allele), mutation at base 43574714 (A allele), mutation at base 43574729 (A allele), mutation at base 43574745 (G allele), mutation at base 43574800 (C allele), mutation at base 43574824 (G allele), mutation at base 43574838 (T allele), mutation at base 43574849 (T allele), mutation at base 43574860 (C allele), mutation at base 43574861 (A allele), mutation at base 43574875 (C allele), mutation at base 43574878 (G allele), mutation at base 43574881 ( hetero (C allele), mutation at base 43574882 (G allele), mutation at base 43574901 (C allele), mutation at base 43574929 (A allele), mutation at base 43574962 (G allele), mutation at base 43575013 (A allele), mutation at base 43575019 (C allele), mutation at base 43575025 (AT mutation to A allele), mutation at base 43577064 (C allele), mutation at base 43577122 (CCT mutation to C allele), mutation at base 43577151 (C allele),The mutation at base 43577166 (T allele), the mutation at base 43578565 (G allele), the mutation at base 43578577 (T allele), the mutation at base 43578583 (T allele), the mutation at base 43581834 (A allele), the mutation at base 43586411 (T allele), the mutation at base 43586884 (C allele), mutation at base 43586893 (C allele), mutation at base 43586897 (G allele), mutation at base 43586909 (C allele), mutation at base 43586941 (C allele), mutation at base 43586965 (G allele), mutation at base 43590824 (G allele), mutation at base 43590888 (G allele), The mutation of base 43590947 (G allele), the mutation of base 43590951 (CAATCTAT mutation to C allele), the mutation of base 43591954 (C allele), the mutation of base 43591986 (A allele), the mutation of base 43591998 (A allele), the mutation of base 43592040 (T Allele), variation at base 43592328 (G allele), variation at base 43592335 (T allele), variation at base 43592390 (T allele), variation at base 43625187 (C allele), variation at base 43625278 (A allele) and variation at base 43818077 (C allele).

9. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 5, characterized in that: Also included is the step of providing information that the individual having the first variation or the second variation has sulfonylurea dependence.

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