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

Abstract

The present invention predicts sulfonylurea-based dependencies in diabetic patients by identifying mRNA levels of GIPR, levels or activity of GIPR protein, or levels or activity inhibitory mutations of GIPR, and relates to compositions and methods for modulating such dependencies by modulating them.

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 mRNA level of GIPR (gastric inhibitory polypeptide receptor), the level or activity of GIPR protein, or a mutation that inhibits the level or activity of GIPR.

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

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

[0013] 4. In the composition for predicting sulfonylurea dependence in diabetic patients according to 1 above, the mutation is selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs779198689, rs1271 one or more single nucleotide variations (SNVs) in the group consisting of rs638992, rs775963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419 and rs757704281.

[0014] 5. A composition for regulating sulfonylurea dependence in diabetic patients, comprising an agent for regulating the mRNA level of GIPR, the level or activity of GIPR protein, or for inducing a mutation that inhibits the level or activity of GIPR.

[0015] 6. In the composition for regulating sulfonylurea dependence in diabetic patients according to 5 above, the mutation of GIPR is selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs779198689, One or more single nucleotide variations in the group consisting of rs1271638992, rs775963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419 and rs757704281.

[0016] 7. A method for providing information for predicting sulfonylurea dependence in a diabetic patient, comprising the step of confirming the mRNA level of GIPR, the level or activity of GIPR protein, or a mutation of GIPR in a biological sample isolated from an individual.

[0017] 8. In the method for providing information for predicting sulfonylurea dependence of a diabetic patient according to 7 above, the mutation is a missense mutation, a frameshift mutation, a nonsense mutation or a splice site mutation.

[0018] 9. In the method for providing information for predicting sulfonylurea dependence in a diabetic patient according to 7 above, the agent is a primer or a probe that specifically binds to the GIPR gene.

[0019] 10. In the method for providing information for predicting sulfonylurea dependence in a diabetic patient according to 7 above, the mutation of GIPR is selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs77919868 9. One or more single nucleotide variations in the group consisting of rs1271638992, rs775963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419 and rs757704281.

[0020] 11. In the method for providing information for predicting sulfonylurea dependence of a diabetic patient according to 7 above, the method further comprises the step of providing information that an individual having the mutation is sulfonylurea dependent.

[0021] 12. In the method for providing information for predicting sulfonylurea dependence of a diabetic patient according to 7 above, the method further comprises the step of providing information that if the level or activity is lower than that of a control group, the possibility of having sulfonylurea dependence is higher than that of the control group.

[0022] Effects of the Invention

[0023] The GIPR of the present invention can be used as a marker to predict whether a diabetic patient has an excellent blood sugar lowering effect of sulfonylureas, and information useful therefor can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A diagram showing a schematic diagram of a method for deriving sulfonylurea dependency-associated variants of the present invention.

[0025] DM: diabetes mellitus; FPG: fasting plasma glucose; MAF: minor allele frequency; SNV: single nucleotide variant; SU: sulfonylurea; WES: whole exome sequencing.

[0026] Figure 2 This is a graph to check the blood concentration of HbA1c (glycosylated hemoglobin) or FPG (fasting blood glucose) after stopping the use of sulfonylureas.

[0027] Values ​​are expressed as mean ± SD.

[0028] ***: p<0.001, between the 2 groups by 2-way repeated measures ANOVA.

[0029] FPG: fasting blood glucose; peak: highest measures within 6 months after SU discontinuation; SU: sulfonylurea.

[0030] Figure 3a and Figure 3b The graphs show the expression level of GIPR following siGipr treatment and the extent of insulin secretion stimulated by GIP.

[0031] INS1 mouse insulinoma cells were injected with 80-nM siRNA for Gipr and negative control. (a) Quantitative real-time polymerase chain reaction (RT-PCR): Gipr mRNA corrected by 18s expression was downregulated by siGipr. (b) Western blotting: GIPR protein levels corrected by tubulin expression were also reduced by siGipr. (c) Enzyme-linked immunosorbent assay (ELISA): Insulin secretion by GIP treatment (50 nM within 1 hour) was also slowed by siGipr.

[0032] siGipr: siRNA for Gipr; siNS: siRNA for negative control; siRNA: small interfering mRNA; NS: no significant difference.

[0033] Figure 4 The graphs show changes in insulin secretion induced by low-concentration SU stimulation in insulinoma cells in which GIPR expression is suppressed.

[0034] INS1 mouse insulinoma cells were injected with siGipr and siNS (80 nM) and then stimulated with low dose SU (50 nM glimepiride within 30 min). Insulin secretion was measured using an ELISA kit. (a): physiological state, (b): simulated diabetic state and pretreated with 15-mM glucose and 150-uM palmitic acid for 24 h (glycolipid toxicity).

[0035] Values ​​are expressed as mean ± SD.

[0036] *, p<0.05, by Two-way ANOVA.

[0037] Figure 5 The graphs show the amount of intracellular and extracellular adenosine triphosphate (ATP) in insulinoma cells in which GIPR expression is suppressed.

[0038] After injection of siGipr and siNS into INS1 cells, ATP levels in cell lysates (part (a)) and culture medium (part (b)) were measured over 24 hours according to the presence or absence of glycolipid toxicity.

[0039] *, p<0.05, by Two-way ANOVA

[0040] Figure 6 This is a graph showing the amount of intracellular Vdac1 mRNA in insulinoma cells in which GIPR expression was suppressed.

[0041] After siGipr and siNS were injected into INS1 cells, Vdac1 mRNA was corrected at 18s expression level according to the presence or absence of glycolipid toxicity and compared within 24 hours.

[0042] *, p < 0.05, by Kruskal-Wallis test

[0043] Figure 7 This figure confirms the changes in insulin secretion stimulated by low concentration of SU in insulinoma cells in which GIPR function is inhibited.

[0044] After treating INS1 mouse insulinoma cells with a GIPR inhibitor (rat GIP (3-30), 100 nM, 24 hours (h)), it was confirmed whether insulin secretion was inhibited by GIP. Low dose SU (50 nM glimepiride in 30 minutes) was used to stimulate insulin secretion. Insulin secretion was measured using an ELISA kit. DETAILED DESCRIPTION

[0045] 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.

[0046] The present invention relates to a composition for predicting sulfonylurea dependence of a diabetic patient, comprising an agent for confirming the mRNA level of GIPR, the level or activity of GIPR protein, or a mutation that inhibits the level or activity of GIPR.

[0047] 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.

[0048] 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 detecting the GIPR mRNA level, the level or activity of the GIPR protein, or a GIPR level or activity inhibitory mutation. Specifically, in the case of a patient who has induced diabetes due to low levels or activities of GIPR mRNA or protein, or mutations that inhibit its function, activity or level, it can be predicted that the patient has high sulfonylurea dependence. However, the present invention is not limited to this.

[0049] In the present invention, as long as the mutation of the gene is not the addition, deletion or change of the base sequence of the gene, 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.

[0050] The GIPR gene, mRNA, and protein may have a sequence in the prediction target. The sequences for each species are known. For example, in the case of humans, the gene may be Gene ID: 2696, the mRNA may be a sequence having SEQ ID NO: 1, and the protein may be a sequence having SEQ ID NO: 2.

[0051] The mutation of the GIPR gene of the present invention may include, without limitation, a situation where the GIPR gene cannot perform its function or has a reduced function, for example, a mutation selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs7791 98689, rs1271638992, rs775963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419 and rs757704281. However, it is not limited thereto.

[0052] GIPR: variants and stop-gain variants derived in SU-dependent patients.

[0053] Table 1

[0054]

[0055]

[0056] In the present invention, the preparation for confirming the level of mRNA, protein, protein activity or mutation can be used without limitation of its type as long as it can confirm DNA, mRNA sequence, protein sequence, protein activity, etc. For example, it can be a primer, a probe, an antibody or an antisense nucleic acid, but is not limited thereto. The nucleic acid sequence having an allele in the mutation position can be amplified or its presence can be confirmed by using the primer, probe or antisense nucleic acid, and the amount of protein encoded by the gene can also be measured using the antibody.

[0057] 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.

[0058] Furthermore, the present invention relates to a composition for regulating sulfonylurea dependence in diabetic patients, comprising an agent for regulating the mRNA level of GIPR, the level or activity of GIPR protein, or for inducing mutation of GIPR.

[0059] As mentioned above, sulfonylurea dependence refers to the extent to which a diabetic patient can only rely on sulfonylureas to lower blood sugar or should take sulfonylureas in preference to other drugs. The mRNA level of GIPR, the level or activity of GIPR protein, and its mutation are related to sulfonylurea dependence, and sulfonylurea dependence can be regulated by regulating them. For example, the dependence on sulfonylureas can be increased by inhibiting the mRNA level of GIPR, the level or activity of GIPR protein, or inducing mutation.

[0060] The mutation of the GIPR gene of the present invention may include, without limitation, a situation where the GIPR gene cannot perform its function or has a reduced function, for example, a mutation selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs7791 98689, rs1271638992, rs775963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419 and rs757704281. However, it is not limited thereto.

[0061] In the present invention, agents for regulating GIPR mRNA levels, GIPR protein levels or activities, or inducing GIPR level or activity suppressive mutations can be used without limitation in type as long as they can achieve the above effects, for example, antibodies, antisense nucleic acids, natural substances, compounds, etc., but are not limited thereto.

[0062] Furthermore, the present invention relates to a method for providing information for predicting sulfonylurea dependence of a diabetic patient, comprising the step of confirming the mRNA level of GIPR, the level or activity of GIPR protein, or the mutation of GIPR in a biological sample isolated from an individual.

[0063] 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 performing DNA amplification and sequencing analysis on 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.

[0064] Furthermore, the information providing method of the present invention may further include the step of providing information that the individual having the mutation has sulfonylurea dependence. Specifically, the individual is an individual having the aforementioned mutation, more specifically, the individual is an individual having a gene selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs779198689, rs1271638992, rs When an individual has one or more mutations selected from the group consisting of rs775963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419 and rs757704281, information on sulfonylurea dependence can be provided.

[0065] Furthermore, the information providing method of the present invention may further include the step of providing information that if the level is lower than that of the control group, the possibility of having sulfonylurea dependence is higher than that of the control group.

[0066] In the present invention, the control group refers to a diabetic patient who lowers blood sugar by other hypoglycemic agents other than sulfonylureas, for example, a diabetic patient who lowers blood sugar by the aforementioned metformin, gliptin, pioglitazone, or a non-patient who does not suffer from diabetes. In addition, the control group can be a single individual or a group of two or more people. If the control group is a group of two or more people, the level of the control group can refer to the average value, median value, etc. of the level of the individual individuals belonging to the control group. Therefore, in the case of a diabetic patient whose level is lower than that of the control group, information that the probability of having sulfonylurea dependence is higher than that of the control group can be provided.

[0067] Hereinafter, in order to specifically illustrate the present invention, it will be described in detail through examples.

[0068] Experimental Example 1. Screening of SU-dependent patients through retrospective case query

[0069] 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.

[0070] 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% at risk of hypoglycemia; (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.

[0071] 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.

[0072] 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 2), and thus, the responsiveness to SU was indistinguishable before SU discontinuation.

[0073] Comparison of clinical characteristics before SU discontinuation and diabetes preparations after discontinuation

[0074] Table 2

[0075]

[0076] Data are expressed as mean ± standard deviation or median (range).

[0077] eGFR, estimated glomerular filtration rate; SU, sulfonylurea; T2DM, type 2 diabetes mellitus.

[0078] *: Analyzed by Student's t-test, Mann Whitney test, and Fisher's exact test.

[0079] Experimental Example 2. Whole-exome sequencing (WES)

[0080] 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.

[0081] Experimental Example 3. Deriving candidate mutations ( Figure 1 )

[0082] 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).

[0083] 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 3).

[0084] Table 3

[0085]

[0086]

[0087]

[0088]

[0089] Example. After inhibiting Gipr gene expression in insulin-secreting cells, the response to SU was examined. Among the 70 genes screened, three mutations (Nos. 31 to 33) were observed in GIPR, among which No. 33 GIPR: NM_000164: exon9: c.C843A mutation was a stop codon mutation that obtained a stop codon, terminating the translation at position 281 of the GIPR peptide consisting of 462 amino acids (p.Y281X). Such premature stop codons are known to inhibit mRNA transcription of related genes through a mechanism called nonsense-mediated decay (NMD) (J Biol Chem. 2022 Nov; 298 (11): 102592). That is, No. 33 mutation has a theoretical background for inhibiting GIPR expression. Another GIPR variant, 31, was also predicted to affect protein function in computer simulations using Polyphen and SIFT (Table 4).

[0090] Table 4

[0091]

[0092] EAS: East Asian; MAF: minor allele frequency.

[0093] *In silico prediction by Polyphenand SIFT

[0094] Furthermore, the GIPR protein is a cell membrane receptor that transmits the incretin hormone GIP (gastric inhibitory polypeptide) signal. It has been reported that DPP-4 inhibitors, which are diabetes medications based on incretin effects, induce hypoglycemia by interacting with SU, and that inhibition of GIPR expression affects the SU responsiveness of pancreatic β cells. Therefore, the correlation with SU dependence was examined by an in vitro experiment of inhibiting gene expression.

[0095] The expression inhibition test of the rat Gipr gene, which has the same gene sequence as human GIPR, was conducted in mouse insulinoma cells. The expression of Gipr mRNA and protein was confirmed to be significantly inhibited by siRNA ( Figure 3a ), which induces insulin secretion via GIP, i.e., functional inhibition of GIPR ( Figure 3b ).

[0096] Then, the SU responsiveness based on Gipr inhibition was confirmed. Under physiological conditions, Gipr inhibition had no effect on insulin secretion regardless of SU stimulation ( Figure 4 In the diabetic state, i.e., chronic exposure to high concentrations of glucose and fatty acids (glycolipid toxicity), insulin secretion is increased by low doses of SU ( Figure 4 (b) of the Regulations).

[0097] Since SU-induced insulin secretion depends on intracellular ATP, the effect of Gipr inhibition on ATP was evaluated. It was confirmed that under physiological conditions, there was no change in ATP content due to Gipr inhibition, but it increased under diabetic conditions ( Figure 5 In contrast, ATP released from cells was severely reduced under diabetic conditions due to the inhibition of Gipr expression ( Figure 5 The results suggest that if Gipr expression is inhibited, ATP release is inhibited in the diabetic state, thereby increasing the intracellular content and enhancing the SU response.

[0098] In addition, it has been reported that in insulin-secreting cells, the amount of ATP in the cell is regulated by the voltage-dependent anion channel 1 (VDAC1) (Cell Metab. 2019 Jan 8; 29 (1): 64). Specifically, the expression of VDAC1, which is located in the outer membrane of mitochondria under normal conditions, increases and moves to the cell membrane under diabetic conditions, thereby promoting the extracellular release of ATP, resulting in the inhibition of insulin secretion. Therefore, the results of analyzing the expression of the Vdac1 gene in mouse insulinoma cells showed that the expression of Vdac1 increased under diabetic conditions, and the inhibition of Gipr suppressed its increased expression ( Figure 6 ).

[0099] On the other hand, when the GIPR inhibitor (rat GIP (3-30), 100 nM, 24 h) was used, which is a substance that directly inhibits the function of the GIPR protein rather than directly inhibits the expression of the GIPR gene, it was confirmed that the insulin secretion by SU was increased even under the condition of non-diabetes ( Figure 7 ).

[0100] In the embodiment, GIPR expression is reduced and its function is inhibited (Figure 3, Figure 7 ) inhibits the expression of VDAC1 induced by diabetes ( Figure 6 ), which prevents ATP from being released outside the cell ( Figure 5 (b) of the study), thereby increasing the intracellular ATP content ( Figure 5 The SU effect is dependent on cellular ATP, and thus the increase in ATP caused by decreased GIPR expression could be interpreted as contributing to the increased insulin secretion via SU ( Figure 4 , Figure 7 ).

[0101] In summary, if Figure 1 As shown, candidate variants were extracted from patients with significantly different clinical conditions (Table 3). Among them, in the case of GIPR, variant 33 has the possibility of inhibiting transcription through NMD. Based on this, the results of inhibiting GIPR transcription or function in cell lines verified that the insulin secretion response to SU was enhanced. Therefore, it is predicted that other SNVs that have the possibility of inhibiting GIPR transcription through NMD will also increase the response to SU (GIPR stop-gain variants; source: gnomAD v2.1.1. https: / / gnomad.broadinstitute.org / ) (Table 1).

[0102] 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 (SNVs) associated with responsiveness to SU were discovered in type 2 diabetes, which will help predict SU response through genetic analysis.

Claims

1. A composition for predicting sulfonylurea dependence in diabetic patients, characterized in that: The invention also includes an agent for determining the level of GIPR mRNA, the level or activity of GIPR protein, or a mutation that inhibits the level or activity of GIPR.

2. The composition for predicting sulfonylurea dependence in diabetic patients according to claim 1, characterized in that: The mutation 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 GIPR gene.

4. The composition for predicting sulfonylurea dependence in diabetic patients according to claim 1, characterized in that: The mutation is selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs779198689, rs1271638992, rs775 one or more single nucleotide variations in the group consisting of rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419 and rs757704281.

5. A composition for regulating sulfonylurea dependence in diabetic patients, characterized in that: The invention also includes agents for regulating the mRNA level of GIPR, the level or activity of GIPR protein, or for inducing mutation of GIPR.

6. The composition for regulating sulfonylurea dependence in diabetic patients according to claim 5, characterized in that: The mutation of GIPR is selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs779198689, rs1271638992, rs7 or more single nucleotide variations in the group consisting of rs75963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419, and rs757704281.

7. A method for providing information for predicting sulfonylurea dependence in a diabetic patient, characterized in that The method comprises the step of determining the level of GIPR mRNA, the level or activity of GIPR protein, or a mutation of GIPR in a biological sample isolated from an individual.

8. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 7, characterized in that: The mutation is a missense mutation, a frameshift mutation, a nonsense mutation or a splice site mutation.

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

10. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 7, characterized in that: The mutation of GIPR is selected from rs550405192, rs13306403, rs13306402, rs554179666, rs1194979043, rs149510000, rs759654048, rs764005735, rs935395843, rs755629061, rs749728382, rs779198689, rs1271638992, rs7 or more single nucleotide variations in the group consisting of rs75963892, rs778756249, rs146268621, rs753645152, rs771165150, rs771830344, rs144328094, rs1159478274, rs1292381802, rs550405192, rs747395645, rs1183524419, and rs757704281.

11. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 7, characterized in that: Also included is the step of providing information that the individual having the mutation is sulfonylurea dependent.

12. The method for providing information for predicting sulfonylurea dependence in a diabetic patient according to claim 7, characterized in that: The step of providing information that if the level or activity is lower than that of the control group, the possibility of having sulfonylurea dependence is higher than that of the control group is also included.

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