KR102475259B1 - MicroRNA biomarker for predicting drug response to diabetes treatment and use thereof - Google Patents

Abstract

The present invention relates to a microRNA biomarker for predicting drug response to a therapeutic agent for diabetes and its use.
In the present invention, miR-337-3p, miR-369-3p, and miR-376a-3p, which are predictive drug responsiveness markers, were selected by comparing the miRNA profile of the normal group and the diabetic group before and after administration of SGLT2 inhibitor, an antidiabetic drug. It was confirmed that the selected markers had different expression patterns in the normal group and the diabetic patient group, but it was confirmed that the expression pattern was restored similarly to that of the normal group by taking the SGLT2 inhibitor, a diabetic drug. It can be usefully used as a predictive marker of reactivity.

Description

MicroRNA biomarker for predicting drug response to diabetes treatment and use thereof {MicroRNA biomarker for predicting drug response to diabetes treatment and use thereof}

The present invention relates to a microRNA (microRNA) biomarker for predicting drug response to antidiabetic agents and its use, and more particularly, in the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p. A biomarker composition for predicting drug responsiveness to an antidiabetic drug comprising at least one selected, a composition for predicting drug responsiveness to an antidiabetic drug comprising an agent for measuring the expression level of the biomarker, and a drug for the antidiabetic drug using the biomarker It relates to a method of providing information on reactivity.

Diabetes mellitus is a metabolic disease characterized by hyperglycemia caused by defects in insulin secretion or action, caused by insulin deficiency or reduced biological effects of insulin in target cells, resulting in long-lasting complications such as renal failure. It is a chronic degenerative disease with

In particular, type 2 diabetes is an acquired factor such as lack of exercise, obesity, or stress, and occurs when insulin secretion is smoothly controlled but blood sugar control fails because insulin does not function properly.

Due to changes in dietary life following rapid economic development, the prevalence of diabetes is increasing year by year, reaching about 5 to 10% in Korea. Based on statistics in 2005, the number of diabetes patients exceeded 4 million, accounting for 83 out of 100 population, and by 2025 It is estimated that the number will increase to about 6.8 million in 2005 (Korean Diabetes Information Center, 2005) Diabetes is the 3rd most serious disease worldwide and the 4th leading cause of death in Korea. somewhat shortened.

Currently known type 2 diabetes treatments can be classified into four major categories: sulfonylurea drugs that induce insulin secretion, and acetabolic drugs that move sugar to muscle cells and inhibit sugar synthesis in the liver. Anide (biguanides), alpha-glucosidase inhibitor that inhibits glucose-generating enzymes in the small intestine, thiazolidione that activates PPAR (Peroxisome proliferator-activated receptors)-γ related to adipocyte differentiation (TZD, thiazolidinedione) drugs, etc. (Amir Babikerand Mohammed Al Dubayee et al., Sudan J Paediatr, 17(2): 11-20, 2017). Recently, SGLT2 (sodium glucose cotransporter 2) inhibitors control blood sugar by suppressing glucose reabsorption in the kidney and excreting glucose in the urine.

However, these oral hypoglycemic drugs induce hypoglycemia (sulfonylurea drugs), kidney toxicity (biguanide drugs), lactic acidosis (biguanide drugs), diarrhea and upset stomach (alpha-glucosidase inhibitors), weight loss, etc. There are problems accompanying many side effects.

Therefore, in the present invention, as a result of diligent efforts to select biomarkers for predicting drug reactivity to antidiabetic drugs so that side effects of drugs can be predicted by predicting drug reactivity to antidiabetic drugs and drugs with excellent effects can be selected and treated, miR-337 -3p, miR-369-3p and miR-376a-3p markers were selected. Although it was confirmed that the expression patterns of these markers were different between the normal group and the diabetic patient group, it was confirmed that the expression patterns were recovered similar to those of the normal group by taking an SGLT2 inhibitor, a treatment for diabetes, and the present invention was completed.

An object of the present invention is to provide a biomarker for predicting drug response to antidiabetic agents.

Another object of the present invention is to provide a composition for predicting drug responsiveness to an antidiabetic agent comprising an agent for measuring the expression level of a biomarker and a method for providing information on drug responsiveness to an antidiabetic agent using the biomarker have.

Another object of the present invention is to provide a method for screening antidiabetic agents using the biomarker.

In order to achieve the above purpose,

The present invention provides a biomarker composition for predicting drug response of an antidiabetic agent comprising at least one microRNA selected from the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p.

In a preferred embodiment of the present invention, miR-337-3p is the nucleotide sequence of SEQ ID NO: 1, miR-369-3p is the nucleotide sequence of SEQ ID NO: 2, miR-376a-3p is the nucleotide sequence of SEQ ID NO: 3 sequence can be displayed.

In another preferred embodiment of the present invention, the antidiabetic agent may be a sodium glucose cotransporter 2 (SGLT2) inhibitor.

In another preferred embodiment of the present invention, the diabetes may be type 2 diabetes.

to achieve other purposes,

The present invention is for predicting drug response to a therapeutic agent for diabetes, including an agent for measuring the expression level of one or more microRNAs selected from the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p composition is provided.

In a preferred embodiment of the present invention, miR-337-3p is the nucleotide sequence of SEQ ID NO: 1, miR-369-3p is the nucleotide sequence of SEQ ID NO: 2, miR-376a-3p is the nucleotide sequence of SEQ ID NO: 3 sequence can be displayed.

In another preferred embodiment of the present invention, the antidiabetic agent may be a sodium glucose cotransporter 2 (SGLT2) inhibitor.

In another preferred embodiment of the present invention, the agent for measuring the expression level may be sense and antisense primers or probes that complementarily bind to microRNA.

In addition, the present invention provides a diagnostic kit for predicting drug response to an antidiabetic agent comprising the composition for predicting drug reactivity to the antidiabetic agent.

In addition, the present invention (a) measures the expression level of one or more microRNAs selected from the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p in a biological sample derived from a subject before and after administration of an antidiabetic agent step; and (b) comparing microRNA expression levels before and after administration of the antidiabetic agent.

In a preferred embodiment of the present invention, miR-337-3p is the nucleotide sequence of SEQ ID NO: 1, miR-369-3p is the nucleotide sequence of SEQ ID NO: 2, miR-376a-3p is the nucleotide sequence of SEQ ID NO: 3 sequence can be displayed.

In another preferred embodiment of the present invention, the agent for measuring the expression level may be sense and antisense primers or probes that complementarily bind to microRNA.

In another preferred embodiment of the present invention, the expression level is determined by next generation sequencing (NGS), polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase It can be measured through one or more methods selected from the group consisting of Real-time PCR, RNase protection assay (RPA), microarray, and northern blotting. .

In another preferred embodiment of the present invention, the antidiabetic agent may be a sodium glucose cotransporter 2 (SGLT2) inhibitor.

In a preferred embodiment of the present invention, when the expression of miR-337-3p, miR-369-3p or miR-376a-3p increases after administration of the antidiabetic agent, it can provide information that the antidiabetic agent has a therapeutic effect. have.

In the present invention, miR-337-3p, miR-369-3p, and miR-376a-3p, which are predictive drug responsiveness markers, were selected by comparing the miRNA profile of the normal group and the diabetic group before and after administration of SGLT2 inhibitor, an antidiabetic drug. It was confirmed that the selected markers had different expression patterns in the normal group and the diabetic patient group, but it was confirmed that the expression pattern was restored similarly to that of the normal group by taking the SGLT2 inhibitor, a diabetic drug. It can be usefully used as a predictive marker of reactivity.

Figure 1 is a comparative analysis of the expression level of microRNA in exosomes isolated from the serum of the normal group and the diabetic group before taking the SGLT2 inhibitor. Alternatively, it is a heat map result of performing hierarchical clustering according to the increased expression level of microRNA, and (B) is a volcano plot of the expression level of microRNA to confirm the difference in expression level between the normal group and the diabetic group before taking the SGLT2 inhibitor. ) is the result represented by
Figure 2 compares and analyzes the expression level of microRNA in exosomes isolated from the serum of a diabetic patient group before taking the SGLT2 inhibitor and a patient group after taking the SGLT2 inhibitor. (A) is compared to the patient group before taking the SGLT2 inhibitor This is the heat map result of hierarchical clustering according to the expression level of microRNAs whose expression was significantly decreased or increased by more than 2 times. This is the result of expressing the expression level of microRNA as a volcano plot.
Figure 3 compares and analyzes the expression level of microRNA in exosomes isolated from the serum of the normal group and the patient group after taking the SGLT2 inhibitor, (A) is significantly more than twice as high in the patient group after taking the SGLT2 inhibitor This is a heat map result of hierarchical clustering according to the decreased or increased microRNA expression level, and (B) is a volcano plot (volcano plot) to confirm the difference in expression level between the normal group and the patient group after taking the SGLT2 inhibitor. This is the result shown in plot).
Figure 4 measures the expression levels of miR-337-3p, miR-369-3p and miR-376a-3p between the normal group (HV), the diabetic patient group before taking the SGLT2 inhibitor (Before) and the patient group after taking the SGLT2 inhibitor (After) This is the result of comparison.

Hereinafter, the present invention will be described in detail.

From a consistent point of view, the present invention relates to a biomarker composition for predicting drug response of an antidiabetic agent containing at least one microRNA selected from the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p. it's about

In the present invention, the diabetes may be type 2 diabetes.

In the present invention, the miR-337-3p may be represented by the nucleotide sequence of SEQ ID NO: 1, and 70% or more, preferably 80% or more, more preferably 90% or more of the nucleotide sequence represented by SEQ ID NO: 1 , and most preferably, a base sequence having 95% or more sequence homology.

The miR-369-3p may be represented by the nucleotide sequence of SEQ ID NO: 2, and 70% or more, preferably 80% or more, more preferably 90% or more, most preferably 90% or more of the nucleotide sequence represented by SEQ ID NO: 2 may include a nucleotide sequence having 95% or more sequence homology.

The miR-376a-3p may be represented by the nucleotide sequence of SEQ ID NO: 3, and 70% or more, preferably 80% or more, more preferably 90% or more of the nucleotide sequence represented by SEQ ID NO: 3, most preferably may include a nucleotide sequence having 95% or more sequence homology.

In the present invention, the antidiabetic agent may be a sodium glucose cotransporter 2 (SGLT2) inhibitor.

In a specific embodiment of the present invention, an attempt was made to select a marker for predicting drug reactivity to an antidiabetic agent, and an SGLT2 inhibitor was used as an antidiabetic agent, and a normal group, a diabetic patient group before taking the SGLT2 inhibitor, and a diabetic patient group after taking the SGLT2 inhibitor The expression level of microRNA in exosomes isolated from each serum was confirmed.

In order to select microRNA markers for predicting drug response, as shown in FIGS. 1 to 3, a normal group and a diabetic patient group before taking the SGLT2 inhibitor; diabetic patients before taking SGLT2 inhibitors and diabetic patients after taking SGLT2 inhibitors; Divided into the normal group and the diabetic group after taking the SGLT2 inhibitor, the expression levels of microRNAs whose expression was significantly reduced or increased by more than 2 times were visualized with a heat map and analyzed with a volcano plot.

As a result, as shown in Table 2, microRNAs whose expression levels were different between the normal group and the diabetic patients before taking the SGLT2 inhibitor and whose expression patterns were restored to a level similar to that of the normal group by taking the SGLT2 inhibitor were finally selected.

Analysis of the expression levels of selected miR-337-3p, miR-369-3p and miR-376a-3p by dividing them into normal group (HV), diabetic group before taking SGLT2 inhibitor (Before), and patient group after taking SGLT2 inhibitor (After) As a result, significant differences in expression levels were observed between the normal group and the diabetic patient group before taking antidiabetic drugs for miR-337-3p, miR-369-3p, and miR-376a-3p, and the expression levels were similar to those of the normal group by taking the SGLT2 inhibitor. It was confirmed that the level was restored.

Therefore, the markers selected in the present invention can be used for predicting drug reactivity to antidiabetic agents, a composition for predicting drug reactivity to antidiabetic agents, and a method for providing information on drug reactivity of antidiabetic agents.

Furthermore, since the microRNA marker of the present invention was confirmed to show a significant difference in expression level between the normal group and the diabetic patient group, it can be used as a marker for diabetic diagnosis as well as a predictive marker for drug response.

From another point of view, the present invention relates to an antidiabetic agent comprising an agent for measuring the expression level of one or more microRNAs selected from the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p. It relates to a composition for predicting drug response.

The composition for predicting drug reactivity to the antidiabetic agent confirms the expression level of the predictive marker of drug reactivity to the antidiabetic agent of the present invention, and the specific details are as described above.

In the present invention, the agent for measuring the expression level may be a pair of primers or probes that complementarily bind to microRNA.

As used herein, the term "primer" is a fragment that recognizes a target gene sequence, and includes a forward and reverse primer pair, but is preferably a primer pair that provides analysis results having specificity and sensitivity.

The term "probe" used in the present invention means a substance that can specifically bind to a target substance to be detected in a sample, and means a substance that can specifically confirm the presence of a target substance in a sample through the binding. do. The type of probe is not limited as a material commonly used in the art, but preferably may be peptide nucleic acid (PNA), locked nucleic acid (LNA), peptide, polypeptide, protein, RNA or DNA, and most preferably Most likely it is PNA.

In another aspect, the present invention relates to a diagnostic kit for predicting drug reactivity to an antidiabetic agent, including the composition for predicting drug reactivity to the antidiabetic agent.

The kit may be prepared by a conventional manufacturing method known in the art. The kit may include, for example, a freeze-dried antibody, a buffer, a stabilizer, and an inactive protein.

The kit may further include a detectable label. The term "detectable label" means an atom or molecule that allows specific detection of a molecule containing a label among molecules of the same kind without a label. The detectable label may be attached to an antibody, interacting protein, ligand, nanoparticle, or aptamer that specifically binds to the protein or fragment thereof. The detectable label may include a radionuclide, a fluorophore, or an enzyme.

The kit uses next generation sequencing (NGS), polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), and real-time polymerase chain reaction (Real-time polymerase chain reaction) to analyze microRNA expression levels. It can be used according to methods such as PCR), RNase protection assay (RPA), and microarray.

For example, the kit of the present invention may be a kit including a primer set specific for the marker gene of the present invention, an appropriate amount of DNA polymerase, a dNTP mixture, a PCR buffer, and water to perform PCR. The PCR buffer may contain KCl, Tris-HCl and MgCl2. In addition, the kit of the present invention may additionally include components necessary for performing electrophoresis to confirm whether or not the PCR product is amplified.

In addition, the kit of the present invention may be a kit containing essential elements necessary for performing RT-PCR. The RT-PCR kit contains, in addition to each primer pair specific for a marker gene, a test tube or other suitable container, reaction buffer, deoxynucleotides (dNTPs), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNase inhibitors, DEPC -Water (DEPC-water), sterilized water, etc. may be included. It may also include a primer pair specific to a gene used as a quantitative control.

In another aspect of the present invention, (a) the expression level of one or more microRNAs selected from the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p in a biological sample derived from a subject before and after administration of an antidiabetic agent measuring; and

(b) It relates to a method for providing information on predicting drug response of an antidiabetic agent, comprising the step of comparing microRNA expression levels before and after administration of the antidiabetic agent.

In the above method, "biological sample" refers to a sample such as tissue, cell, blood, serum, plasma, saliva, cerebrospinal fluid or urine in which microRNA expression levels differ due to diabetes, and is preferably blood , Plasma or serum, more preferably refers to exosomes contained in serum.

The expression level of step (a) is determined by Next generation sequencing (NGS), polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), and real-time polymerase chain reaction (Real-time PCR). ), RNase protection assay (RPA), microarray, and northern blotting.

In the above method, when the expression of miR-337-3p, miR-369-3p or miR-376a-3p increases after administration of the antidiabetic agent, the drug response to the antidiabetic agent is excellent, providing information that the antidiabetic agent has a therapeutic effect. can do. Preferably, when the SGLT2 inhibitor is administered as a therapeutic agent for diabetes, when the expression of miR-337-3p, miR-369-3p, and miR-376a-3p is increased by the administration of the SGLT2 inhibitor, the drug response to the SGLT2 inhibitor is excellent. can provide

Specifically, in the diabetic patient group after administration of the antidiabetic drug compared to the diabetic patient group before administration of the antidiabetic drug, the miR-337-3p expression level increased 2 to 3 times, preferably 2.2 to 2.5 times; 1.5 to 2.5 fold increase in miR-369-3p expression level, preferably 2 to 2.4 fold increase; Alternatively, when the expression level of miR-376a-3p increases by 2.5 to 3.5 times, preferably by 3 to 3.4 times, it can be seen that the drug has a therapeutic effect on diabetes.

In addition, depending on the purpose, before directly administering the drug to the patient, cells derived from the patient's tissue, preferably cells related to diabetes, are isolated, and the isolated cells are treated with the drug, and then changes in the microRNA expression level are confirmed to make the patient more effective. A suitable antidiabetic agent with excellent drug response can be selected.

Furthermore, another aspect of the present invention is (a) measuring the expression level of one or more microRNAs selected from the group consisting of miR-337-3p, miR-369-3p and miR-376a-3p in a biological sample derived from a diabetic patient step; and

(b) comparing the microRNA expression level of a normal control group; to a method for providing information on whether or not a therapeutic agent for diabetes is administered.

The antidiabetic agent may be a sodium glucose cotransporter 2 (SGLT2) inhibitor, and when the expression of miR-337-3p, miR-369-3p, and miR-376a-3p in diabetic patients is reduced compared to the normal control group, the SGLT2 inhibitor is administered. can provide information.

Hereinafter, the present invention will be described in more detail through examples.

These examples are only for exemplifying the present invention, and it will be apparent to those skilled in the art that the scope of the present invention is not to be construed as being limited by these examples.

Patient selection and sequencing performed

1-1: Patient selection

In the present invention, in order to select biomarkers for predicting drug response to antidiabetic drugs, 20 normal subjects and 20 diabetic patients whose diabetic symptoms were improved by administration of an SGLT2 inhibitor among 20 diabetic patients who had never taken an SGLT2 inhibitor (SLGT2 inh dose) group) was selected, and the SLGT2 inh taking group was analyzed by collecting serum samples before and after taking the SGLT2 inhibitor.

The clinical characteristics of the patients are shown in Table 1 below, and the numbers in parentheses indicate the number of samples.

Patient's Clinical Information normal (20) SLGT2 inh dosage group (20) gender (m/f) 0/20 12/8 age 53.00±4.24 56.20±10.62 height 157.68±5.55 164.43±9.84 weight 54.26±6.00 73.09±10.62 BMI 21.75±1.38 27.02±2.96 waist 72.91±4.05 92.45±10.21 FBS 86.90±3.73 147.05±30.89 HbA1c 5.27±0.22 7.60±0.86 WBC 5.74±1.29(10) 6.89 ± 1.49 (19) AST 23.05±5.37 24.89 ± 10.59 (19) ALT 15.05±6.80 26.68±13.29(19) BUN 14.38±3.70(8) 13.68±3.77(19) Creatinie 0.66±0.10 0.80±0.20(19) LDL 116.96±30.48 113.60±40.39 (18) M/C ratio -(0) 36.78±68.74(18) eGFR 93.46±16.20 (18) 93.78±20.72 (19) HOMA-IR 0.32±0.36 3.09±3.30(15) SBP 118.60±17.55 126.50±20.69 DBP 75.15±7.81 80.05±16.70

1-2 RNA isolation and sequencing performed from serum

Analysis was performed by isolating RNA from the serum of the normal group and the SLGT2 inh taking group selected in Example 1-1, and serum samples were taken from the SLGT2 inh taking group before and after taking the SGLT2 inhibitor for analysis.

Specifically, exosomes were isolated from serum samples collected from normal groups, diabetic patients before taking SGLT2 inhibitors, and diabetic patients after taking SGLT2 inhibitors using Exoquick (SBI, USA), and from the isolated exosomes, Qiagen Total RNA was extracted using the miRNeasy kit, and the quality of the extracted total RNA was measured using an Agilent RNA Bioanalyzer according to the manufacturer's instructions. Then, using the isolated RNA, a library was prepared using the Takara SMARTer smRNA for illumina kit from Macrogen, and then microRNA was detected by next-generation sequencing (NGS) using the Hiseq 2500.

Screening biomarkers for predicting drug responsiveness to antidiabetic drugs

2-1: MicroRNA analysis of the difference in expression level between the normal group and the diabetic group before taking SGLT2 inhibitor

First, in order to identify microRNAs (miRNAs) with different expression levels in the blood-derived exosomes of the 20 normal group and the 20 diabetic patients before taking the SGLT2 inhibitor, each subject was tested according to the method of Example 1-2. Exosomes were isolated from serum collected from the field and NGS analysis was performed on the extracted total RNA. As a result of the analysis, 523 miRNAs were detected, and the expression levels of the detected miRNAs were further compared.

As a result, as shown in Figure 1a, among the 523 miRNAs, 105 miRNAs whose expression decreased more than twice (p < 005) in the diabetic patient group (Before) before taking the SGLT2 inhibitor compared to the normal group (HV), and the expression increased 75 miRNAs appeared. In addition, the result of the volcano plot according to the expression level of the miRNAs showing the significant expression change is shown in FIG. 1B.

2-2 : MicroRNA analysis of the difference in expression levels of diabetic patients before taking SGLT2 inhibitor vs diabetic patients after taking SGLT2 inhibitor

In order to identify miRNAs with different expression levels in the blood-derived exosomes of 20 diabetic patients before taking the SGLT2 inhibitor and 20 diabetic patients after taking the SGLT2 inhibitor, the total RNA in exosomes obtained by the same method as above NGS analysis was performed. As a result of the analysis, 523 miRNAs were detected, and the expression levels of the detected miRNAs were further compared.

As a result, as shown in FIG. 2a, among 523 miRNAs, 14 miRNAs whose expression was reduced more than twice (p < 005) in the diabetic patient group after taking the SGLT2 inhibitor (After) compared to the diabetic patient group before taking the SGLT2 inhibitor (Before) , 28 miRNAs with increased expression were found. In addition, the result of the volcano plot according to the expression level of the miRNA showing the significant expression change is shown in FIG. 2B.

2-3: microRNA analysis of the difference in expression levels of the normal group vs. the diabetic group after taking SGLT2 inhibitors

The present inventors performed NGS analysis on total RNA in exosomes obtained in the same manner as above to identify miRNAs with different expression levels in the blood-derived exosomes of the 20 normal group and 20 diabetic patients after taking the SGLT2 inhibitor. did As a result of the analysis, 523 miRNAs were detected, and the expression levels of the detected miRNAs were further compared.

As a result, as shown in Figure 3a, among the 523 miRNAs, 103 miRNAs whose expression decreased by more than 2 times (p < 005) in the diabetic patient group (After) after taking the SGLT2 inhibitor compared to the normal group (HV), and the expression increased 77 miRNAs appeared. In addition, the result of the volcano plot according to the expression level of the miRNA showing the significant expression change is shown in FIG. 3B.

2-4: Selection of biomarkers for predicting drug responsiveness

Referring to the results of FIGS. 1 to 3, microRNAs whose expression levels were different between the normal group and diabetic patients before taking the SGLT2 inhibitor and whose expression patterns were restored to a level similar to that of the normal group by taking the SGLT2 inhibitor were finally selected, Selected markers and sequence information are shown in Tables 2 and 3 below.

Biomarkers for predicting drug response fold change (+/-) Mature miRNAs Before/HV After/Before After/HV ANOVA hsa-miR-337-3p -4.52 2.33 -1.94 *** hsa-miR-369-3p -4.62 2.18 -2.12 *** hsa-miR-376a-3p -7.48 3.28 -2.28 ***

marker sequence information Mature miRNAs sequence sequence number hsa-miR-337-3p CUCCUAUAUGAUGCCUUUCUUC One hsa-miR-369-3p AAUAAUACAUGGUUGAUCUUU 2 hsa-miR-376a-3p AUCAUAGAGGAAAAUCCACGU 3

As shown in Table 2, miR-337-3p, miR-369-3p, and miR-376a-3p markers were finally selected, and the expression level of each marker was measured in the normal group (HV) and the diabetic group before taking the SGLT2 inhibitor (Before ) and after taking the SGLT2 inhibitor, as shown in FIG. 4, a significant difference in the expression level was observed between the normal group and the diabetic patients before taking the antidiabetic drug, and the normal group was taken with the SGLT2 inhibitor. Similarly, it was confirmed that the expression level was restored.

<110> Keimyung University <120> MicroRNA biomarker for predicting drug response to diabetes treatment and use <130> 1067799 <160> 3 <170> KoPatentIn 3.0 <210> 1 <211> 22 <212> RNA <213> artificial sequence <220> <223> hsa-miR-337-3p <400> 1 cuccuauaug augccuuucu uc 22 <210> 2 <211> 21 <212> RNA <213> artificial sequence <220> <223> hsa-miR-369-3p <400> 2 aauaauacau gguugaucuu u 21 <210> 3 <211> 21 <212> RNA <213> artificial sequence <220> <223> hsa-miR-376a-3p <400> 3 aucauagagg aaaauccacg u 21

Claims (10)

A biomarker composition for predicting drug response of a treatment for type 2 diabetes, which is a sodium glucose cotransporter 2 (SGLT2) inhibitor containing all microRNAs of miR-337-3p, miR-369-3p and miR-376a-3p.
The method of claim 1, wherein miR-337-3p is the nucleotide sequence of SEQ ID NO: 1, miR-369-3p is the nucleotide sequence of SEQ ID NO: 2, and miR-376a-3p is represented by the nucleotide sequence of SEQ ID NO: 3. A biomarker composition for predicting drug responsiveness of a therapeutic agent for diabetes, characterized in that.
delete delete A composition for predicting drug response to a treatment for type 2 diabetes mellitus, which is a sodium glucose cotransporter 2 (SGLT2) inhibitor, comprising an agent for measuring the expression level of the biomarker composition of claim 1.
[Claim 6] The composition for predicting drug reactivity for an antidiabetic agent according to claim 5, wherein the agent for measuring the expression level is a sense and antisense primer or probe that complementarily binds to microRNA.
A diagnostic kit for predicting drug response to a treatment for type 2 diabetes, which is a sodium glucose cotransporter 2 (SGLT2) inhibitor, including an agent for measuring the expression level of the biomarker composition of claim 1.
(a) measuring the expression level of the biomarker composition of claim 1 in a biological sample derived from a subject before and after administration of a sodium glucose cotransporter 2 (SGLT2) inhibitor for type 2 diabetes;
(b) comparing microRNA expression levels before and after administration of the antidiabetic agent; and
(c) after administration of the antidiabetic agent, when the expression of miR-337-3p, miR-369-3p and miR-376a-3p increases, the drug response to the antidiabetic agent is excellent, providing information that there is a therapeutic effect for diabetes step;
A method for providing information on drug reactivity of a type 2 diabetes treatment agent that is a sodium glucose cotransporter 2 (SGLT2) inhibitor comprising a.
The method of claim 8, wherein the expression level in step (a) is determined by next generation sequencing (NGS), polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase chain reaction Characterized in that it is measured by one or more methods selected from the group consisting of Real-time PCR, RNase protection assay (RPA), microarray, and northern blotting A method for providing information on drug responsiveness of antidiabetic drugs.
delete

Images