KR20250088845A - Method for diagnosis of mutant genotype of genes related to therapeutic response or side effects of tuberculosis treatment - Google Patents

Abstract

The present invention relates to a method for predicting individual treatment responsiveness to a tuberculosis treatment agent or the risk of occurrence of side effects by rapidly detecting mutations present in human AADAC, human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT-RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A and human UGT2B7 genes. The present invention enables faster and cheaper identification of specific mutations in genes related to side effects of tuberculosis treatment agents, and exhibits high accuracy. Therefore, the present invention can not only predict treatment responsiveness to tuberculosis treatment agents in advance, but also prevent side effects in advance. Therefore, the present invention can be usefully used to increase the effectiveness and success rate of treatment by administering alternative drugs.

Description

Method for diagnosis of mutant genotype of genes related to therapeutic response or side effects of tuberculosis treatment

The present invention relates to a method for predicting or diagnosing the risk of occurrence of treatment response or side effects to an anti-tuberculosis drug by rapidly detecting a mutation genotype of a gene associated with treatment response or side effects of an anti-tuberculosis drug.

Tuberculosis (TB) is a disease that has been threatening human health for decades and has been a challenge in global health management. Since the tuberculosis bacteria can survive for a long time in the human body, drug treatment is required for at least 6 months to completely eradicate the bacteria, and in some cases, drug treatment is required for a longer period. It is known that patients who do not respond well to treatment may fail treatment or develop drug resistance.

Moreover, antituberculosis drugs are known to have side effects such as gastrointestinal toxicity, hepatotoxicity, cardiotoxicity, nephrotoxicity, and central nervous system toxicity. It is known that first-line antituberculosis drugs such as isoniazid (INH), Rifampin (RIF), and pyrazinamide (PZA) cause hepatotoxicity. Second-line antituberculosis drugs (aminoglycosides, cycloserine, linezolid, etc.) that are more toxic than first-line antituberculosis drugs cause a wide range of adverse drug reactions (ADRs), and these adverse reactions can last for a long time, sometimes threatening life. In particular, in the case of tuberculosis patients who have other diseases, there is a possibility that antituberculosis treatment drugs can cause drug interactions with antiretroviral drugs or other drugs, which can cause serious problems.

It is very important to identify genetic factors in predicting an individual's response to these antituberculosis drugs and the risk of side effects. Meanwhile, with the completion of the human genome map and the development of genome-based technologies such as next-generation sequencing (NGS), and basic and clinical research-based technologies leading to translational and clinical research, personalized medicine is becoming a reality. In particular, pharmacogenomics is attracting attention as a key research field that enables effective and safe personalized drug treatment by predicting drug responses based on each individual's genetic/environmental factors.

With the growth of such pharmacogenomics research, many pharmacogenomic biomarkers are being clinically verified through many studies, and the Food and Drug Administration in the United States and Europe is including the content of “valid pharmacogenomics biomarkers” in the drug labeling (including 408 drugs and 175 biomarkers by 2023) to explain the diversity of drug responses or warn of treatment failure/adverse drug reactions (Table of Pharmacogenomic Biomarkers in Drug Labeling. US Food and Drug Administration. Available at http://www.fda.gov/Drugs (last accessed 2 February 2016)). It is clear that genetic diversity between individuals leads to differences in drug toxicity and efficacy, so considering the effect of genetic diversity of such pharmaceutically important proteins in the early stage of drug development is an important factor that can reduce the risk of drug development failure.

The application of pharmacogenetic discoveries to clinical practice is becoming more common, but many challenges remain, including evolving regulatory requirements, clinical test uniformity, provider education, and ongoing evaluation of clinical utility and cost effectiveness. Currently, various technologies such as NGS, microarray, high-performance liquid chromatography (HPLC), and SNaPshot analysis are being used to develop accurate genotyping analysis. Among them, next-generation sequencing (NGS) provides high-throughput sequencing and can detect multiple genetic variants in many samples. However, it requires large-scale data storage capabilities, complex bioinformatics systems, and high-speed data processing infrastructure, which is very expensive. Microarrays provide high-throughput screening, but their resolution is limited and their analysis is complex, so sophisticated methods to control various factors are required to implement them. High-performance liquid chromatography (HPLC) is a technology that can replace next-generation sequencing (NGS) due to its high sensitivity and low price. However, it is not suitable for general laboratories because it requires a lot of expertise and complex techniques to perform HPLC properly. Finally, the SNaPshot assay is a cost-effective fluorescence-based assay that can detect specific genetic markers, including single nucleotide polymorphisms (SNPs) and insertions or deletions, in one day, making it an ideal analytical method for target SNP detection in clinical settings.

An object of the present invention is to provide a biomarker composition for predicting or diagnosing drug treatment response or side effects.

Another object of the present invention is to provide a set of multiple single-nucleotide primers for predicting or diagnosing drug treatment responsiveness or side effects.

Another object of the present invention is to provide a composition comprising a primer for predicting or diagnosing drug treatment responsiveness or side effects.

Another object of the present invention is to provide a kit for predicting or diagnosing drug treatment response or side effects.

Another object of the present invention is to provide a method for providing pharmacogenetic information for implementing personalized drug treatment.

Another object of the present invention is to provide a method for identifying a drug causing an adverse drug reaction.

To achieve the above purpose, the present invention provides a biomarker composition for predicting or diagnosing drug treatment response or side effect , comprising a mutation in any one gene selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3, human MT-RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A, and human UGT2B7 .

In addition, the present invention provides a composition for predicting or diagnosing drug treatment response or side effect, comprising an agent that detects a site where a mutation exists in any one gene selected from the group consisting of human AADAC, human ABCB1, human CYP1A2, human CYP2E1, human FMO3, human MT-RNR1, human MT-RNR2, human NAT2, human SLCO1B1, human SLC22A2 (OCT2), human UGT1A, and human UGT2B7.

In order to achieve the other objects described above, the present invention provides a multiplex single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, comprising a primer comprising one or more base sequences selected from the group consisting of SEQ ID NO: 39 to SEQ ID NO: 69.

In order to achieve the above another object, the present invention provides a composition for predicting or diagnosing drug treatment responsiveness or side effects, comprising a single base primer comprising at least one base sequence selected from the group consisting of SEQ ID NO: 39 to SEQ ID NO: 69.

In addition, to achieve the above another object, the present invention provides a biomarker composition for predicting or diagnosing drug treatment responsiveness or side effects according to the present invention, a composition for predicting or diagnosing drug treatment responsiveness or side effects comprising the biomarker composition, a primer set for predicting or diagnosing drug treatment responsiveness or side effects, or a kit for predicting or diagnosing drug treatment responsiveness or side effects comprising a composition for predicting or diagnosing drug treatment responsiveness or side effects comprising the primer set.

In addition, in order to achieve the above another object, the present invention provides a method for providing pharmacogenetic information for implementing a personalized drug treatment regimen, comprising the following steps: (a) a step of extracting nucleic acid from a biological sample collected from a human; (b) a step of performing PCR using the nucleic acid of step (a) as a template and a primer capable of amplifying any one or a fragment thereof selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT-RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 ; and (c) a step of confirming the presence or absence of a genetic mutation in the base sequence of the PCR product obtained in step (b).

In addition, in order to achieve the above another object, the present invention provides a method for identifying a drug causing a side effect, comprising the following steps: (a) a step of extracting nucleic acid from a sample treated with a drug; (b) a step of performing PCR using the nucleic acid of step (a) as a template and a primer capable of amplifying any one or a fragment thereof selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT -RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A, and human UGT2B7 ; (c) a step of checking whether there is a genetic mutation in the base sequence of the PCR product obtained in step (b); and (d) a step of determining that the drug treated in step (a) causes the side effect if there is a genetic mutation.

The present invention produces a genotyping panel capable of efficiently detecting mutations in human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT-RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A and human UGT2B7 genes associated with anti-tuberculosis drug responsiveness or side effects, and since the genetic mutations can be identified more quickly and accurately through snapshot (SNaPshot) analysis, the responsiveness to anti-tuberculosis drugs can be predicted or diagnosed in advance, and further, side effects can be predicted in advance, so that it can be usefully used to increase the effectiveness and success rate of treatment by administering alternative drugs.

Figure 1 shows the results of confirming the presence of a mutation in a specific gene by performing a snapshot (SNaPshot) analysis using panel 1 (TB-PGx1) among the genotyping analysis panels according to the present invention.
Figure 2 shows the results of confirming the presence of a mutation in a specific gene by performing a snapshot (SNaPshot) analysis using panel 2 (TB-PGx2) among the genotyping analysis panels according to the present invention.
Figure 3 shows the results of confirming the presence of a mutation in a specific gene by performing a snapshot (SNaPshot) analysis using panel 3 (TB-PGx3) among the genotyping analysis panels according to the present invention.
Figure 4 shows the results of confirming the presence of a mutation in a specific gene by performing a snapshot (SNaPshot) analysis using panel 4 (TB-PGx4) among the genotyping analysis panels according to the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. In the following description, detailed descriptions of well-known techniques to those skilled in the art may be omitted. In addition, when describing the present invention, if it is determined that a specific description of a related known function or configuration may unnecessarily obscure the gist of the present invention, the detailed description thereof may be omitted. In addition, the terminology used in this specification is a terminology used to appropriately express preferred embodiments of the present invention, and may vary depending on the intention of the user or operator or the customs of the field to which the present invention belongs.

Therefore, the definitions of these terms should be based on the contents of the entire specification. Throughout the specification, when a part is said to "include" a certain component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise specifically stated.

The present invention provides a biomarker composition for predicting or diagnosing drug treatment response or side effect, comprising a mutation in any one gene selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT-RNR1 , human MT -RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 .

In the present invention, the mutation may mean a single nucleotide polymorphism (SNP). ‘Genetic polymorphism’ refers to a case where a genetic mutation appears at a frequency of at least 1% in a population, and among these, a case where an insertion, deletion, or substitution of a single nucleotide in DNA occurs is called a SNP.

The term "polymorphism" above refers to the arrangement of a gene's sequence that varies within a population. A polymorphism consists of different "alleles". The arrangement of such a polymorphism can be identified by its position in the gene and the different amino acids or bases found therein. Such an amino acid variation is the result of two different alleles, two possible variant bases, C and T. Since a genotype consists of two different, distinct alleles, any of the several possible variants can be observed in any one individual (e.g., CC, CT or TT in this example). An individual polymorphism is also assigned a unique identifier (a "reference SNP", "refSNP" or "rs#"), which is well known to those skilled in the art and is used, for example, in the Single Nucleotide Polymorphism Database (dbSNP) of Nucleotide Sequence Variation available on the NCBI website.

More preferably, the mutation of the gene is selected from human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human It may be at least one selected from the group consisting of human CYP2E1 rs6413432 and human CYP1A2 rs2069526.

The present invention has a technical feature of accurately and quickly identifying the genetic mutation and predicting or diagnosing the therapeutic response or side effects of a drug, preferably an anti-tuberculosis drug.

The above-mentioned anti-tuberculosis treatment agent is not limited to any agent known in the art for preventing or treating tuberculosis, but may be at least one selected from the group consisting of, for example, rifapentine, moxifloxacin, rifampin, ethambutol, isoniazid, efavirenz, ethionamide, streptomycin, amikacin, kanamycin, cycloserine, linezolid, para-aminosalicyclic acid (PAS), rifabutin, and pyrazinamide.

In addition, the present invention provides a composition for predicting or diagnosing drug treatment response or side effect, comprising an agent that detects a site where a mutation exists in any one gene selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3, human MT-RNR1, human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2), human UGT1A, and human UGT2B7.

In the diagnostic composition of the present invention, the agent may be at least one selected from the group consisting of an antisense oligonucleotide, a primer, and a probe that specifically binds to a site where a mutation of the gene exists.

In the present invention, "diagnosis" means confirming the existence or characteristics of a pathological condition. The diagnosis can provide objective basic information necessary for monitoring not only the onset but also the prognosis, progress, and stage, and excludes the clinical judgment or opinion of a doctor. For the purpose of the present invention, diagnosis means diagnosing the possibility of individual treatment responsiveness to an anti-tuberculosis agent or side effects thereof, such as hepatotoxicity, ototoxicity, lactic acidosis, peripheral neuropathy, mitochondrial toxicity, optic neuropathy, myelosuppression, QT prolongation, depression, skin discoloration, etc.

In the present invention, the composition may further comprise one or more other component compositions, solutions or devices suitable for the analysis method.

In addition, the present invention provides a multiple single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, comprising a primer comprising one or more base sequences selected from the group consisting of SEQ ID NO: 39 to SEQ ID NO: 69.

In the present invention, nucleic acids are written in a 5'→3' orientation from left to right. Numerical ranges recited within the specification include the numbers defining the range and include each integer or any non-integer fraction within the defined range.

The above nucleic acid refers to a polynucleotide or oligonucleotide such as deoxyribonucleic acid (DNA), and, where appropriate, ribonucleic acid (RNA). The term also equally includes analogs of either RNA or DNA prepared from nucleotide analogs (e.g., peptide nucleic acids), and single (sense or antisense) and double-stranded polynucleotides. In the present invention, the terms 'nucleic acid' and 'nucleotide' are used interchangeably.

The primer according to the present invention is characterized in that it can amplify a mutation region of any one gene selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT -RNR1, human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 .

In the multiple single-base primer set for predicting or diagnosing drug treatment responsiveness or side effects of the present invention, the primer including the base sequence represented by SEQ ID NO: 39 to the primer including the base sequence represented by SEQ ID NO: 46 are characterized in that they detect a mutation in at least one gene selected from the group consisting of human NAT2 and human SLCO1B1 .

More preferably, the primer comprising the base sequence represented by SEQ ID NO: 39 to the primer comprising the base sequence represented by SEQ ID NO: 46 is characterized in that it detects at least one selected from the group consisting of human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, and human SLCO1B1 rs4149056.

In addition, in the multiple single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects of the present invention, the primer including the nucleotide sequence represented by SEQ ID NO: 47 to the primer including the nucleotide sequence represented by SEQ ID NO: 55 are characterized in that they detect a mutation in any one or more genes selected from the group consisting of human UGT2B7 , human OCT2 , human ABCB1 , human UGT1A1 , and human AADAC .

More preferably, the primer including the base sequence represented by SEQ ID NO: 47 to the primer including the base sequence represented by SEQ ID NO: 55 is characterized by detecting at least one selected from the group consisting of human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, and human AADAC rs1803155.

In addition, in the multiple single-base primer set for predicting or diagnosing drug treatment responsiveness or side effects of the present invention, the primer including the base sequence represented by SEQ ID NO: 56 to the primer including the base sequence represented by SEQ ID NO: 63 are characterized in that they detect a mutation in at least one gene selected from the group consisting of human MT-RNR1 and human MT-RNR2 .

More preferably, the primer including the base sequence represented by SEQ ID NO: 56 to the primer including the base sequence represented by SEQ ID NO: 63 is characterized in that it detects at least one selected from the group consisting of human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306 , human MT -RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, and human MT-RNR1 rs267606619.

In addition, in the multiple single-base primer set for predicting or diagnosing drug treatment responsiveness or side effects of the present invention, the primer including the base sequence represented by SEQ ID NO: 64 to the primer including the base sequence represented by SEQ ID NO: 69 are characterized in that they detect a mutation in any one or more genes selected from the group consisting of human FMO3 , human CYP2E1 , and human CYP1A2 .

More preferably, the primer including the base sequence represented by SEQ ID NO: 64 to the primer including the base sequence represented by SEQ ID NO: 69 is characterized in that it detects at least one selected from the group consisting of human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human CYP2E1 rs6413432, and human CYP1A2 rs2069526.

In the present invention, the term "primer" means a short nucleic acid sequence having a short free 3' hydroxyl group, which can form base pairs with a complementary nucleic acid template and serves as a starting point for strand copying of the nucleic acid template. The primer can initiate DNA synthesis in the presence of a reagent for polymerization reaction (i.e., DNA polymerase or reverse transcriptase) and four different nucleoside triphosphates in an appropriate buffer and temperature.

When designing the above primers, there are several restrictions, such as the A, G, C, and T content ratio of the primers, prevention of primer dimer formation, and prohibition of repeating the same base sequence more than three times. In addition, for the single PCR reaction conditions, the amount of template DNA, concentration of primers, concentration of dNTP, concentration of Mg2 ⁺ , reaction temperature, and reaction time must be appropriate.

The length of the above primer is generally closely related to the temperature at which a stable hybrid is formed with the template, and generally, the longer the length, the higher the temperature. Although it may vary depending on the intended use, it is usually 15 to 30 nucleotides, preferably 15 to 25 nucleotides, but is not limited thereto. The primer sequence does not need to be completely complementary to the template, but should be sufficiently complementary to hybridize with the template.

The above primers may incorporate additional features that do not change the basic properties, i.e. the nucleic acid sequence may be modified by many means known in the art. Examples of such modifications include methylation, capping, substitution of one or more homologues of the nucleotides, and modification of the nucleotides with uncharged linkers such as phosphonates, phosphotriesters, phosphoramidates or carbamates, or with charged linkers such as phosphorothioates or phosphorodithioates. The nucleic acids may also have one or more additional covalently bonded moieties, such as nucleases, toxins, antibodies, signal peptides, proteins such as poly-L-lysine, intercalators such as acridine or psoralens, chelating agents such as metals, radioactive metals, iron oxide metals, and alkylating agents.

Additionally, the primer sequence of the present invention may be modified using a label capable of directly or indirectly providing a detectable signal. The primer may include a label capable of being detected using spectroscopic, photochemical, biochemical, immunochemical or chemical means.

The primers of the present invention can be chemically synthesized using any other well-known method, including cloning of appropriate sequences and restriction enzyme digestion and direct chemical synthesis methods such as the phosphotriester method of Narang et al. (1979, Meth, Enzymol. 68:90-99), the diethylphosphoramidite method of Beaucage et al. (1981, Tetrahedron Lett. 22: 1859-1862), and the solid support method of U.S. Pat. No. 4,458,066.

The base sequences represented by SEQ ID NOS: 1 to 69 included in the primer set of the present invention are not limited thereto, and homologs of the base sequences are included within the scope of the present invention. Specifically, the primer set may include base sequences having a sequence homology of 70% or more, preferably 80% or more, more preferably 90% or more, and most preferably 95% or more with the base sequences of SEQ ID NOS: 1 to 69, respectively. The "% of sequence homology" for a polynucleotide is determined by comparing a comparison region with two optimally aligned sequences, and a part of the polynucleotide sequence in the comparison region may include additions or deletions (i.e., gaps) compared to a reference sequence for the optimal alignment of the two sequences (which does not include additions or deletions).

In addition, the present invention provides a composition for predicting or diagnosing drug treatment responsiveness or side effects, comprising a single-base primer comprising at least one base sequence selected from the group consisting of SEQ ID NO: 39 to SEQ ID NO: 69.

The composition according to the present invention is characterized by being capable of accurately and rapidly detecting a specific genetic mutation, thereby predicting or diagnosing individual treatment responsiveness to a tuberculosis treatment agent or side effects thereof associated with the genetic mutation.

The present invention also provides a biomarker composition for predicting or diagnosing drug treatment responsiveness or side effects according to the present invention, a diagnostic composition comprising the biomarker composition, a multiple single-nucleotide primer set, or a kit for predicting or diagnosing drug treatment responsiveness or side effects comprising a diagnostic composition comprising the primer set.

The kit for predicting or diagnosing drug treatment responsiveness or side effects according to the present invention can be prepared in the form of a lyophilized biomarker composition according to the present invention, a diagnostic composition comprising the biomarker composition, a multiple single-base primer set, or a diagnostic composition comprising the primer set. In addition, the reagent for performing the amplification reaction is not particularly limited as long as it is a reagent that can be typically added to the amplification reaction, but preferably includes DNA polymerase, dNTPs, or a buffer. In addition, a suitable carrier, a label capable of generating a detectable signal, a solubilizer, a detergent, etc. can be further included as a reagent and tool, but is not limited thereto.

In addition, the kit may take the form of a bottle, a tub, a sachet, an envelope, a tube, an ampoule, and the like, which may be formed partly or wholly from plastic, glass, paper, foil, wax, and the like. The container may be equipped with a completely or partly detachable stopper, which may initially be part of the container or may be attached to the container by mechanical, adhesive, or other means. The container may also be equipped with a stopper, the contents of which may be accessed by a syringe needle. In addition, the kit of the present invention may further include a user guide describing optimal reaction performance conditions. The guide is a printed matter explaining how to use the kit, for example, a method for preparing a PCR buffer, reaction conditions presented, etc. The guide includes instructions in the form of a pamphlet or leaflet, a label attached to the kit, and a description on the surface of a package containing the kit. In addition, the guide includes information disclosed or provided through electronic media, such as the Internet.

As a specific example, the present invention produces a genotyping panel including a multiplex single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects according to the present invention. The genotyping panel is characterized by including the multiplex single-nucleotide primer set according to the present invention divided into four groups. According to one embodiment of the present invention, in the gene set of the present invention, panel 1 including a primer including a base sequence represented by SEQ ID NO: 39 to a primer including a base sequence represented by SEQ ID NO: 46 is characterized by detecting at least one selected from the group consisting of human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931 , human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, and human SLCO1B1 rs4149056. In addition, panel 2 comprising a primer comprising a base sequence represented by SEQ ID NO: 47 to a primer comprising a base sequence represented by SEQ ID NO: 55 is characterized by detecting at least one selected from the group consisting of human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874 , human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, and human AADAC rs1803155. In addition, panel 3 comprising a primer comprising a base sequence represented by SEQ ID NO: 56 to a primer comprising a base sequence represented by SEQ ID NO: 63 is characterized by detecting at least one selected from the group consisting of human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306 , human MT -RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, and human MT-RNR1 rs267606619. In addition, panel 4 comprising a primer comprising a base sequence represented by SEQ ID NO: 64 to a primer comprising a base sequence represented by SEQ ID NO: 69 is characterized by detecting at least one selected from the group consisting of human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human CYP2E1 rs6413432, and human CYP1A2 rs2069526.

As a result of performing a snapshot analysis on 50 random samples using the genotyping analysis panel according to the present invention, it was confirmed that all panels showed 100% accuracy compared to the existing standard method.

Therefore, the genotyping panel, which is a specific example of the present invention, can more quickly identify specific genetic mutations and exhibit high accuracy, so that it can predict individual treatment responsiveness to anti-tuberculosis drugs in advance, or prevent side effects thereof in advance, and thus can be usefully used to increase the effectiveness and success rate of treatment by administering alternative drugs as needed.

In addition, the present invention provides a method for providing pharmacogenetic information for implementing personalized drug treatment, comprising the following steps: (a) extracting nucleic acid from a biological sample; (b) performing PCR using the nucleic acid of step (a) as a template and a primer set capable of amplifying any one or a fragment thereof selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT -RNR1 , human MT-RNR2, human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 ; and (c) confirming the presence or absence of a genetic mutation in the base sequence of the PCR product obtained in step (b).

In one embodiment, the pharmacogenetic type can provide information for predicting pharmacokinetics, drug therapeutic effects, and drug adverse reactions, and for implementing personalized drug treatment regimens by taking these into consideration. The present invention can provide information for implementing personalized drug therapy for tuberculosis.

The above biological sample can preferably be collected from a subject or patient suffering from tuberculosis. The above 'subject' or 'patient' refers to any single entity requiring treatment, including humans, cows, dogs, guinea pigs, rabbits, chickens, insects, etc. In addition, any subject participating in a clinical research trial that does not show any clinical findings of the disease, a subject participating in an epidemiological study, or a subject used as a control group is included as a subject. In one embodiment of the present invention, a human was used as the subject.

The above biological sample means a collection of similar cells obtained from a tissue of a subject or patient, by 'tissue or cell sample (sample)'. The source of the tissue or cell sample may be a fresh, frozen and/or preserved organ or tissue sample or solid tissue from a biopsy or aspirate; blood or any blood component; cells from any point in the subject's pregnancy or development. The tissue sample may also be a primary or cultured cell or cell line.

The biological samples specifically include tissue, whole blood, plasma, serum, sputum, tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, leukocytes, peripheral blood mononuclear cells, buffy coat, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid, and joint aspirate. The subject matter may be any one or more selected from the group consisting of, but is not limited to, body fluids, blood, urine, and excretions, including but not limited to, bodily fluids (e.g., urine, blood, urine samples, aspirate), organ secretions, cells, cell extracts, and cerebrospinal fluid.

The primers of the step (b) are characterized in that they are a primer set for amplifying a region including a genetic mutation, including at least one base sequence selected from the group consisting of SEQ ID NOs: 1 to 38, and the presence or absence of a genetic mutation in the step (c) is characterized in that they are confirmed through a snapshot (SNaPshot) analysis using multiple single-base primers including at least one base sequence selected from the group consisting of SEQ ID NOs: 39 to 69. In one embodiment of the present invention, the genetic mutation (SNP) was analyzed by the SNaPshot analysis method using multiple single-base primers according to the present invention in step (c) using the amplified product of the region including a genetic mutation amplified in the step (b), and the genotype was confirmed by analyzing the highest point for the single nucleotide polymorphism (SNP) for the generated product.

In one embodiment of the present invention, it is possible to determine in advance whether a patient 's therapeutic response to a drug or the risk of developing side effects is high based on the human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1, human FMO3 , human MT-RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 genotypes and phenotypes.

In addition, the above genetic variants are human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human It is characterized by at least one selected from the group consisting of human CYP2E1 rs6413432 and human CYP1A2 rs2069526.

In the method for providing pharmacogenetic information of the present invention, a more detailed description of the multiple single-nucleotide primer set is as described above.

In addition, the present invention provides a method for identifying a drug causing a side effect, comprising the following steps: (a) extracting nucleic acid from a sample treated with the drug; (b) performing PCR using the nucleic acid of step (a) as a template and primers capable of amplifying any one or a fragment thereof selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT- RNR1 , human MT-RNR2, human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 ; (c) checking whether there is a genetic mutation in the base sequence of the PCR product obtained in step (b); and (d) determining that the drug treated in step (a) causes the side effect if there is a genetic mutation.

In the present invention, the drug refers to an anti-tuberculosis treatment agent. That is, the method for identifying a drug causing a side effect of the drug of the present invention refers to a method for identifying an anti-tuberculosis treatment agent that can cause a side effect.

In the method for identifying a drug causing a side effect of the present invention, the genetic mutation is selected from the group consisting of human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 It is characterized by at least one selected from the group consisting of rs3813867, human CYP2E1 rs6413432, and human CYP1A2 rs2069526.

The primer of the step (b) is characterized in that it is a primer set for amplifying a region including a genetic mutation, which includes at least one base sequence selected from the group consisting of sequence numbers 1 to 38, and the presence or absence of a genetic mutation of the step (c) is characterized in that it is confirmed through a snapshot (SNaPshot) analysis using multiple single-base primers, which include at least one base sequence selected from the group consisting of sequence numbers 39 to 69.

Hereinafter, the present invention will be described in more detail by way of examples. These examples are only intended to explain the present invention more specifically, and it will be apparent to those skilled in the art that the scope of the present invention is not limited to these examples.

<Example 1> Production of PCR products containing SNPs using multiplex polymerase chain reaction (multiplex PCR)

To amplify specific fragments containing SNPs associated with adverse drug reactions in seven metabolic genes ( AADAC, CYP1A2, CYP2E1, FMO3, NAT2, UGT1A, UGT2B7), three drug transporter genes (ABCB1, SLCO1B1, SLC22A2 ), and two mitochondrial genes ( MT-RNR1, MT-RNR2 ), primers for each gene were designed. To increase the amplification efficiency of multiple sequences, heterologous primers were designed using Primer3 software, focusing on the conserved regions within the signature and the flanking regions of the selected SNPs (see Table 1).

The pharmacogenetic panel contained fragments with high homology to CYP2E1 -Rsal/Pst variants, which were tested with various additional primer pairs to obtain specific amplification. Multiple amplification conditions using different genes were tested to obtain optimal products of expected size without non-specific amplification. The concentrations of primer pairs were adjusted from 0.05 μM to 0.75 μM to achieve equilibrium of PCR products for the next genotyping step. Genotyping was performed using a low input DNA of 20 ng, which generated sufficient signal for variant detection.

In summary, six multiplex PCRs and two single-strand PCRs were designed and optimized for efficient amplification of all target genes. SNP primer concentrations were adjusted to preserve genotyping signals of at least >1000 raw intensities and to achieve similar SNP signals across the panel.

We developed, amplified, and tested six multiplex polymerase chain reactions (multiplex PCR), one single-stranded PCR for NAT2 amplification, and one hole-labeled PCR for independent investigation of UGT1A1 rs8175347, a thymine-adenine (TA) dinucleotide repeat variant of the UGT1A1 promoter. In addition, 50 subjects were selected from 1,000 healthy Korean subjects recruited from September 1, 2005 to August 31, 2015, with the support of the Ministry of Health and Welfare to establish a pharmacogenetic database for healthy adults in Korea. The selected subjects were adults aged 19 years or older without any recorded diseases at the time of specimen collection. Three samples were selected and used.

Total DNA was extracted from whole blood using the Blood Genomic DNA Miniprep Kit (Cosmo Genetech, Seoul, Korea) according to the manufacturer's instructions.

For optimization of PCR conditions, 20 μl reaction mixtures containing EF Taq® in 10X EF buffer or 2X multiplex mixture (Solgent, Korea) and 10–100 ng of genomic DNA in 5X Band doctor were performed. To balance the PCR products, the primer mixtures were adjusted manually. The PCR consisted of 35 cycles of initial denaturation step at 95 °C for 2 min, denaturation step at 95 °C for 20 s, annealing step in the range of 55–63 °C for 30 s, extension step at 72 °C for 40 s to 1 min, and final elongation at 72 °C for 5 min (see Table 2). PCR results were evaluated after electrophoresis on a 2% agarose gel.

PCR
gene Primer name Sequence 5’ - 3’ Primer concentration (μM) Amplification (bp) Sequence number PCR1 NAT2 NAT2_F TAG TCA CAC GAG GAA ATC AAA TGC 0.25 989 1 NAT2_R GTG AGT TGG GTG ATA CAT ACA CAA GG 2 PCR2 UGT1A1 UGT1A_1F CTGGCCAGTGATGTGTATGG 0.15 599 3 UGT1A_1R GCTCACCTGAACCAACCAAT 4 UGT2B7 UGT2B7_1F TATTGCATAAGACAGATGGC 0.15 366 5 UGT2B7_1R AGCACCTTTCCACAATTCCC 6 SLC22A2 OCT2_1F CTGATAGCTGGACAGCCAAC 0.3 306 7 OCT2_1R TTAAGGAAGGCAGACTTCTTAGC 8 OCT2_2F TCCATGCATTTTCCACAATC 0.3 283 9 OCT2_2R TCTATTTTGGCAGCGAGGTT 10 ABCB1 ABCB1_1F TGTTGTCTGGACAAGCACTGA 0.3 141 11 ABCB1_1R GCATAGTAAGCAGTAGGGAGTAACAA 12 PCR3 UGT2B7 UGT2B7_2F GAAGAGGTGTATCTGAGTAATGTTC 0.5 560 13 UGT2B7_2R TTGAAACTCCCAAGCAATCCTC 14 AADAC AADAC_F CCAAATCACTCATGGTCAGATTC 0.25 203 15 AADAC_R TTTAGCCAGCTCAGAACTGCC 16 ABCB1 ABCB1_2F GGGTGGTGTCACAGGAAGAG 0.5 113 17 ABCB1_2R CATGCTCCCAGGCTGTTTAT 18 PCR4 MT-RNR1 MT-RNR1_F CAA CCA AAC CCC AAA GAC AC 0.05 1100 19 MT-RNR1_R GCT CAG AGC GGT CAA GTT AAG 20 MT-RNR2 MT-RNR2_F CCC TAA CCG TGC AAA GGT AG 0.05 760 21 MT-RNR2_R CAA TGA GGA GTA GGA GGT TGG 22 PCR5 UGT1A1 UGT1A1_*28_F 6-FAM CTTGGTGTATCGATTGGTTTTTG 0.5 79 23 UGT1A1_*28_R GGCGCCTTTGCTCCTGCCAGAGGTTCG 24 PCR6 CYP2E1 CYP2E1_1F CTGCTGCTAATGGTCACTTG 0.25 688 25 CYP2E1_1R GGAGTTCAAGACCAGCCTAC 26 CYP2E1_2F CTGAAGCCTCTGCCAGAGGC 0.75 433 27 CYP2E1_2R CAGACCCTCTTCCACCTTCTATG 28 PCR7 FMO3 FMO3_1F ATCTGCCAAAACCATTTGCT 0.25 639 29 FMO3_1R ACGAGAGTCACCCGAGTACC 30 FMO3_2F TCCAATAATTGTCTCTGTTTTCCA 0.5 423 31 FMO3_2R TTCATCTTCGCAATCCATGA 32 CYP1A2 CYP1A2_F TGGAAGCTAGTGGGGACA 0.5 168 33 CYP1A2_R TTGTGCTAAGGGGGAAGC 34 PCR8 SLCO1B1 SLCO1B1_1F GGTGCAAATAAAGGGGAATATTTCTC 0.1 285 35 SLCO1B1_1R CAATTTTTAGAGATGTAATTAAATGTATAC 36 SLCO1B1_2F CCCAGTCTCAGGTATGTATT 0.05 308 37 SLCO1B1_2R TGTAAGAAAGCCCCAATGGTA 38

PCR Gene PCR mixture PCR conditions Component Unit 1 NAT2 DNA 20 ng 95℃ 2 minutes, (95℃ 20 seconds, 61℃ 30 seconds, 72℃ 45 seconds) *35 cycles, 72℃ 5 minutes 10x EF-taq buffer 2 μl dNTP 2.5mM 2 μl Primer mixture x μl EF-taq 0.2 μl D.W up to 20 μl 2 UGT1A1, UGT2B7, OCT2, ABCB1 DNA 20 ng 95℃ 2 minutes, (95℃ 20 seconds, 57℃ 30 seconds, 72℃ 40 seconds) *35 cycles, 72℃ 5 minutes 10x EF-taq buffer 2 μl dNTP 2.5mM 2 μl 5x Band doctor 1 μl Primer mixture x μl EF-taq 0.2 μl D.W up to 20 μl 3 UGT2B7, AADAC, ABCB1 DNA 20 ng 95℃ 2 minutes, (95℃ 20 seconds, 61℃ 30 seconds, 72℃ 40 seconds) *35 cycles, 72℃ 5 minutes 10x EF-taq buffer 2 μl dNTP 2.5mM 2 μl 5x Band doctor 1 μl Primer mixture x μl EF-taq 0.2 μl D.W up to 20 μl 4 MT-RNR1, MT-RNR2 DNA 20 ng 95℃ 2 minutes, (95℃ 20 seconds, 57℃ 30 seconds, 72℃ 1 minute) *35 cycles, 72℃ 5 minutes 10x EF-taq buffer 2 μl dNTP 2.5mM 2 μl 5x Band doctor 1 μl Primer mixture x μl EF-taq 0.2 μl D.W up to 20 μl 5 UGT1A1 DNA 20 ng 95℃ 15 minutes, (95℃ 20 seconds, 63℃ 30 seconds, 72℃ 40 seconds) *35 cycles, 72℃ 5 minutes 2x EF-taq buffer 10 μl Primer mixture x μl D.W up to 20 μl 6 CYP2E1 DNA 20 ng 95℃ 2 minutes, (95℃ 20 seconds, 61℃ 30 seconds, 72℃ 40 seconds) *35 cycles, 72℃ 5 minutes 10x EF-taq buffer 2 μl dNTP 2.5mM 2 μl 5x Band doctor 1 μl Primer mixture x μl EF-taq 0.2 μl D.W up to 20 μl 7 FMO3, CYP1A2 DNA 20 ng 95℃ 2 minutes, (95℃ 20 seconds, 57℃ 30 seconds, 72℃ 40 seconds) *35 cycles, 72℃ 5 minutes 10x EF-taq buffer 2 μl dNTP 2.5mM 2 μl 5x Band doctor 1 μl Primer mixture x μl EF-taq 0.2 μl D.W up to 20 μl 8 SLCO1B1 DNA 20 ng 95℃ 15 minutes, (95℃ 20 seconds, 55℃ 30 seconds, 72℃ 40 seconds) *35 cycles, 72℃ 5 minutes 2x EF-taq buffer 2 μl Primer mixture x μl D.W up to 20 μl

After transferring the products of the polymerase chain reaction to an ice bucket, 2 μl of PCR product, 1 μl of 6X loading buffer, 1-2% agarose gel, 2 μl of 100 bp Mixed DNA ladder, and 0.5X TBE buffer were mixed on parafilm and electrophoresis was run at 100 V for 30 minutes. Afterwards, the 1% agarose gel was stained with gel red containing a fluorescent material to confirm the DNA size. After confirming the size of the PCR product, in order to remove the primers and dNTPs that did not undergo PCR reaction in the sample, in the case of panel TB-PGx1, a mixture of 3.5 μl of PCR1 product and 2 μl of PCR 8 product was treated with 2.5 μl of ExoSAP-IT. For panel TB-PGx2, a mixture of 2.5 μl of PCR2 product and 2.5 μl of PCR3 product was treated with 3.5 μl of ExoSAP-IT. For panel TB-PGx3, 4 μl of PCR4 product was treated with 2.5 μl of ExoSAP-IT. For panel TB-PGx4, a mixture of 2.5 μl of PCR6 product and 2.5 μl of PCR7 product was treated with 3.5 μl of ExoSAP-IT. All were mixed with ExoSAP-IT and reacted at 37°C for 30 minutes and 80°C for 15 minutes to inactivate the remaining enzyme. The polymerase chain reaction products produced through the above reactions were used as templates for the subsequent SNaPshot analysis.

<Example 2> Design of a pharmacogenetic panel related to side effects of antituberculosis drugs

<Example 2-1> SNP-specific primer design and pharmacogenetic panel production

The primers designed for the multiplex single-based primer extension (SNaPshot assay) are shown in Table 3. The 3' ends of the primers were designed to align with the nucleotide immediately preceding each genetic SNP. In addition, in order to cover all 32 target SNPs, the primers were grouped into four groups, and four genotyping panels (TB-PGx1 to TB-PGx4) were developed.

Panel Gene rsID/SNP Primer sequence (5'-3') Primer concentration (μM) order
number TB-PGx1 NAT2 rs1041983 TATTTGTTAACTGGAGGGAT 0.51 39 NAT2 rs1208 TTTTTTTTTTTTTTAGAGGGTTGAAGAAGTGCTGA 0.1 40 NAT2 rs1799931 TTTTTTTTTTTTTTTTTTTTTTTTAGAAATCTCGTGCCCAAACCTGGTGATG 0.01 41 NAT2 rs1799930 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCATAGACTCAAAATCTTCAATTGTT 0.26 42 NAT2 rs1801279 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCACATTGTAAGAAGAAACC 0.51 43 NAT2 rs1801280 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGACAATGTAATTCCTGCCGTCA 0.15 44 SLCO1B1 rs2306283 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGTCGATGTTGAATTTTCTGATGAAT 0.1 45 SLCO1B1 rs4149056 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGTTTAAAGGAATCTGGGTCATACATGTGGATATATG 0.05 46 TB-PGx2 UGT2B7 rs7668282 TAAGTCAAAGTACATACAAT 0.99 47 UGT2B7 rs10028494 TTTTTTGAAGGGAGTCAAACAGAAGG 0.3 48 OCT2 rs316019 TTTTTTTTTGGAGGTGGTTGCAGTTCACAGTT 0.02 49 OCT2 rs201919874 TTTTTTTTTTTTTTTTTTTTCTCATGGCCATTTCCCCAA 0.07 50 OCT2 rs145450955 TTTTTTTTTTTTTTTTCCTTGGATTAAGCGAAAAATTAACATCCAC 0.03 51 ABCB1 rs2032582 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTAGTTTGACTCACCTTCCCCAG 0.1 52 ABCB1 rs1045642 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGCCTCCTTTGCTGCCCTCAC 0.04 53 UGT1A1 rs3755319 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGCTCATCTTTCCCTTTTGACTTCAA 0.15 54 UGT1A1 rs3064744 - - AADAC rs1803155 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGCAGGGAACTCCAATTAA 0.74 55 TB-PGx3 MT-RNR2 m.2706A>G GCCCGTGAAGAGGCGGGCAT 0.07 56 MT-RNR2 rs3928306 TTTTTTTTATGTTGGATCAGGACATCCC 0.07 57 MT-RNR1 rs267606618 TTTTTTTTTCTGGGATTAGATACCCCACTATGCT 0.13 58 MT-RNR2 m.3197T>C TTTTTTTTTTTTTTTTTTTTTTGGGTGGGTGTGGGTATAAT 0.07 69 MT-RNR1 rs267606617 TTTTTTTTTTTTTTTTTTTTTTAACCCCTACGCATTTATATAGAGGAG 0.26 60 MT-RNR1 m.827A>G TTTTTTTTTTTTTTTTTTTTTTTTGCTTAGTTAAAACTTTCGTTTATTGCTAAAGG 0.2 61 MT-RNR1 m.1291T>C TTTTTTTTTTTTTTTTTTTTTTTTTTTTTAACGTCTTTACGTGGGTACTTGCGCTTACTTTGT 0.07 62 MT-RNR1 rs267606619 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGGCCCTGAAGCGCGTACACACCGCCCGTCAC 0.07 63 TB-PGx4 FMO3 rs2266782 GGCCTTACCTGGAAAGGACT 0.2 64 CYP2E1 rs2031920 TTTTTTTTTGTTCTTAATTCATAGGTTGCAATTTT 0.49 65 FMO3 rs2266780 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGTAAAGCCTAACGTGAAGGAATTCACAG 0.07 66 CYP2E1 rs3813867 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCGCCCCTTCTTGGTTCAGGAGAG 0.15 67 CYP2E1 rs6413432 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCCACCACACCCAGCTGATTAAAAATT 0.49 68 CYP1A2 rs2069526 TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCGGGGAGCCTGGGCTAGGTGTAGGGG 0.1 69

<Example 3-2> Confirmation of the presence or absence of SNP using multiplex single-based primer extension reaction (SNaPshot assay)

Using the polymerase chain reaction products produced in the above Example 1 as templates, multiplex single-nucleotide primer extension reactions and SNaPshot analysis were performed using four genotyping panels including the primers of Table 3, which were designed to have different lengths for single-nucleotide polymorphism sites. Specifically, each reaction product produced in Example 1 was treated with ExoSAP-IT™ PCR Product Cleanup Reagent (ThermoFisher, USA) at 37°C for 30 minutes, and enzyme inactivation was performed at 85°C for 15 minutes. Thereafter, the SNaPshot reaction was performed using 1.2 μl of the SNaPshot Multiplex Kit (Applied Biosystems, Foster City, California, USA). At this time, 0.7 μl of each primer of Table 3 was used according to each concentration. In order to strengthen the signals of all SNPs tested in the same panel, various primer mixtures were tested. PCR conditions consisted of 40 cycles of denaturation at 96°C for 10 s, followed by annealing at 50°C for 5 s, and extension at 60°C for 30 s. For genotyping, the product was treated with 1 U of Shrimp Alkaline Phosphatase (USB, USA) at 37°C for 60 min and 65°C for 15 min. Detection was performed using 1 μl of SNaPshot product mixed with 8.5 μl of HiDi™ formamide and 0.5 μl of GeneScan-120LIZ size standard (Applied Biosystems, USA). In particular, the labeled amplicon of UGT1A1 *28 was directly pooled into the final mixture for genotyping. After obtaining the extension reaction products in which the fluorescently labeled ddNTP complementary to each single nucleotide polymorphism position was placed at the 3' end of each primer, each peak for each SNP was analyzed. Genotyping was performed on a 3500 Genetic Analyser (Applied Biosystems, Foster City, California, USA) equipped with a 36 cm long capillary and POP-7™ polymer, and analyzed using GeneMapperTM software version 3.7 (Thermo Fisher Scientific).

Based on the analysis results, human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 were randomly selected from three samples. rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human The genotypes of CYP2E1 rs6413432 and human CYP1A2 rs2069526 were confirmed (Figs. 1 to 4).

<Example 3> Validation of a pharmacogenetic panel related to side effects of antituberculosis drugs

DNA samples from 50 healthy Korean subjects pre-selected from the biobank of the Pharmacogenomics Research Center of Inje University were used for the validation phase. The selected subjects were 19 years of age or older without any diseases recorded at the time of sample collection and provided written consent to participate in genotyping. Blood samples were collected at the time of recruitment and frozen at -80°C. DNA genomes were extracted from whole blood using the Blood Genomic DNA Miniprep Kit (Cosmogenetech, Seoul, Republic of Korea) according to the manufacturer's instructions. DNA purity and concentration were measured using a NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific, USA). The accuracy of tuberculosis genotyping in variant calling was validated through Sanger sequencing for most genes (excluding mitochondrial genes using previously known next-generation sequencing data (Pham et al. BMC Medical Genomics (2022) 15:3 Note). Sequencing was performed with 3500 Genetic Analyzer software (Applied Biosystems, Foster City, California, USA) and analyzed using FinchTV 1.4.0 software (Geospiza, lnc.; Seattle, WA, USA; http://www.geospiza.com).

Gene Genetic polymorphism
Genotype Number of samples Gene Genetic polymorphism
Genotype Number of samples
AADAC rs1803155 (G>A) GG 7 MT-RNR2


m.2706A>G (A>G) GG 50 GA 28 m.3010G>A (G>A) GG 35 AA 15 AA 15 ABCB1 rs2032582 (G>A/T) GG 13 m.3197T>C (T>C) TT 50 GA 9 NAT2 rs1041983 (C>T) CC 13 GT 12 CT 31 AT 4 TT 6 TT 11 rs1208 (A>G) AA 48 AA 1 AG 2 rs1045642 (C>T) CC 22 rs1799930 (G>A) GG 28 CT 16 GA 20 TT 12 AA 2 CYP1A2 rs2069526 (T>G) TT 44 rs1799931 (G>A) GG 35 TG 6 GA 15 CYP2E1 rs2031920 (C>T) CC 33 rs1801279 (G>A) GG 50 CT 16 rs1801280 (T>C) TT 48 TT 1 TC 2 rs3813867 (G>C) GG 34 OCT2 rs316019 (C>A) CC 41 GC 14 CA 8 CC 2 AA 1 rs6413432 (T>A) TT 25 rs201919874 (C>T) CC 50 TA 24 rs145450955 (G>A) GG 50 AA 1 SLCO1B1 rs2306283 (A>G) AA 7 FMO3 rs2266782 (G>A) GG 32 AG 19 GA 18 GG 24 rs2266780 (A>G) AA 35 rs4149056 (T>C) TT 40 AG 14 TC 10 GG 1 UGT1A1 rs3755319 (A>C) AA 24 MT-RNR1




m.827A>G (A>G) AA 47 AC 20 GG 3 CC 6 m.1095T>C (T>C) TT 49 rs8175347 (TA6>TA7) TA6TA6 38 CC 1 TA6TA7 12 m.1291T>C (T>C) TT 50 UGT2B7 rs7668282 (T>C) TT 39 m.1494C>T (C>T) CC 50 TC 11 m.1555A>G (A>G) AA 50 rs10028494 (A>C) AA 44 AC 3 CC 3

As a result, the 4-panel approach according to the present invention succeeded in genotyping by accurately detecting 32 SNPs selected for 50 healthy subjects. In particular, the genotyping results showed an accuracy score of 100% in all panels compared to the existing standard method (see Table 4). In addition, the electrophoresis results confirmed that there was sufficient signal to distinguish three different alleles of a complex variant ( ABCB1 rs2032582) into six distinct genotypes (see Table 4), clearly confirming the efficiency and appropriateness of the panel performance.

Attach electronic file of sequence list

Claims (31)

A biomarker composition for predicting or diagnosing drug treatment response or side effect, comprising a mutation in any one gene selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT - RNR1 , human MT-RNR2, human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 .
In paragraph 1,
The mutations in the above genes are human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human A biomarker composition for predicting or diagnosing drug treatment response or side effect, characterized by at least one selected from the group consisting of CYP2E1 rs6413432 and human CYP1A2 rs2069526.
In paragraph 1,
A biomarker composition for predicting or diagnosing drug treatment response or side effects, characterized in that the drug is a tuberculosis treatment agent.
A composition for predicting or diagnosing drug treatment response or side effect, comprising an agent that detects a site where a mutation exists in any one gene selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT-RNR1, human MT-RNR2, human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7.
In paragraph 4,
A composition for predicting or diagnosing drug treatment responsiveness or side effects, characterized in that the preparation comprises at least one selected from the group consisting of antisense oligonucleotides, primers and probes that specifically bind to a site where a mutation of the gene exists.
A multiplex single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, comprising a primer comprising one or more nucleotide sequences selected from the group consisting of SEQ ID NO: 39 to SEQ ID NO: 69.
In paragraph 6,
A multiplex single -nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects , characterized in that the above primers can amplify a mutation region of any one gene selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1 , human FMO3 , human MT-RNR1, human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A, and human UGT2B7.
In Article 7,
The mutations in the above genes are human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human A multiple single nucleotide primer set for predicting or diagnosing drug treatment response or side effect, characterized in that at least one is selected from the group consisting of human CYP2E1 rs6413432 and human CYP1A2 rs2069526.
In paragraph 6,
A multiplex single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, characterized in that the drug is an anti-tuberculosis drug.
In Article 9,
A multiplex single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, characterized in that the above-mentioned anti-tuberculosis agent is at least one selected from the group consisting of Rifapentine, Moxifloxacin, Rifampin, Ethambutol, Isoniazid, Efavirenz, Ethionamide, Streptomycin, Amikacin, Kanamycin, Cycloserine, Linezolid, Para-aminosalicyclic acid (PAS), Rifabutin, and Pyrazinamide.
In paragraph 6,
A multiple single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, characterized in that the primer including the base sequence represented by the above sequence number 39 to the primer including the base sequence represented by the above sequence number 46 detects a mutation in at least one gene selected from the group consisting of human NAT2 and human SLCO1B1 .
In Article 11,
A multiplex single nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effect, characterized in that the genetic mutation is at least one selected from the group consisting of human NAT2 rs1041983, human NAT2 rs1208 , human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280 , human SLCO1B1 rs2306283, and human SLCO1B1 rs4149056.
In paragraph 6,
A multiplex single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, characterized in that the primer including the base sequence represented by the above sequence number 47 to the primer including the base sequence represented by the above sequence number 55 detects a mutation in any one or more genes selected from the group consisting of human UGT2B7 , human OCT2 , human ABCB1 , human UGT1A1 , and human AADAC.
In Article 13,
A multiplex single nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effect , characterized in that the genetic mutation is at least one selected from the group consisting of human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019 , human OCT2 rs201919874 , human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, and human AADAC rs1803155.
In paragraph 6,
A multiple single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, characterized in that the primer including the base sequence represented by the above sequence number 56 to the primer including the base sequence represented by the sequence number 63 detects a mutation in at least one gene selected from the group consisting of human MT-RNR1 and human MT-RNR2 .
In Article 15,
A multiplex single nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effect, characterized in that the genetic mutation is at least one selected from the group consisting of human MT -RNR2 m.2706A >G, human MT-RNR2 rs3928306 , human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, and human MT-RNR1 rs267606619.
In paragraph 6,
A multiple single-nucleotide primer set for predicting or diagnosing drug treatment responsiveness or side effects, characterized in that the primer including the base sequence represented by the above sequence number 64 to the primer including the base sequence represented by the above sequence number 69 detects a mutation in at least one gene selected from the group consisting of human FMO3 , human CYP2E1 , and human CYP1A2 .
In Article 17,
A multiplex single nucleotide primer set for predicting or diagnosing drug treatment response or side effect, characterized in that the genetic mutation is at least one selected from the group consisting of human FMO3 rs2266782, human CYP2E1 rs2031920 , human FMO3 rs2266780, human CYP2E1 rs3813867, human CYP2E1 rs6413432, and human CYP1A2 rs2069526.
A composition for predicting or diagnosing drug treatment responsiveness or side effects, comprising a single nucleotide primer comprising at least one nucleotide sequence selected from the group consisting of SEQ ID NO: 39 to SEQ ID NO: 69.
A kit for predicting or diagnosing drug treatment response or side effect, comprising a biomarker composition for predicting or diagnosing drug treatment response or side effect according to claim 1, a composition for predicting or diagnosing drug treatment response or side effect according to claim 4, a single nucleotide primer set for predicting or diagnosing drug treatment response or side effect according to claim 6, or a composition for predicting or diagnosing drug treatment response or side effect according to claim 19.
A method for providing pharmacogenetic information for implementing personalized drug therapy, comprising the following steps:
(a) a step of extracting nucleic acid from a biological sample;
(b) a step of performing PCR using the nucleic acid of step (a) as a template and primers capable of amplifying at least one gene or fragment thereof selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1, human FMO3 , human MT -RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 ; and
(c) A step of confirming the presence or absence of a genetic mutation in the base sequence of the PCR product obtained in step (b).
In Article 21,
The above biological samples include tissue, whole blood, plasma, serum, sputum, tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, leukocytes, peripheral blood mononuclear cells, buffy coat, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid, and joint aspirate. A method for providing pharmacogenetic information, wherein the pharmacogenetic information is at least one selected from the group consisting of aspirate, organ secretions, cells, cell extracts, and cerebrospinal fluid.
In Article 21,
A method for providing pharmacogenetic information, characterized in that the primer of step (b) is a primer set for amplifying a region including a genetic mutation, the primer including at least one base sequence selected from the group consisting of sequence numbers 1 to 38.
In Article 21,
The above genetic variants are human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human A method for providing pharmacogenetic information, characterized in that at least one type is selected from the group consisting of CYP2E1 rs6413432 and human CYP1A2 rs2069526.
In Article 21,
A method for providing drug genotype information, characterized in that the drug is a tuberculosis treatment drug.
In Article 21,
A method for providing pharmacogenetic information, characterized in that the presence or absence of a genetic mutation in the step (c) is confirmed through a snapshot (SNaPshot) analysis using multiple single-base primers including one or more base sequences selected from the group consisting of sequence numbers 39 to 69.
A method for identifying a drug causing an adverse drug reaction, comprising the steps of:
(a) a step of extracting nucleic acid from a drug-treated sample;
(b) a step of performing PCR using the nucleic acid of step (a) as a template and primers capable of amplifying at least one gene or fragment thereof selected from the group consisting of human AADAC , human ABCB1 , human CYP1A2 , human CYP2E1, human FMO3 , human MT -RNR1 , human MT-RNR2 , human NAT2 , human SLCO1B1 , human SLC22A2 ( OCT2 ), human UGT1A , and human UGT2B7 ;
(c) a step of checking whether there is a genetic mutation in the base sequence of the PCR product obtained in step (b); and
(d) A step for determining that the drug treated in step (a) causes side effects if a genetic mutation exists.
In Article 27,
A method for identifying a drug causing adverse drug reactions, wherein the drug is a tuberculosis treatment drug.
In Article 27,
The above genetic variants are human NAT2 rs1041983, human NAT2 rs1208, human NAT2 rs1799931, human NAT2 rs1799930, human NAT2 rs1801279, human NAT2 rs1801280, human SLCO1B1 rs2306283, human SLCO1B1 rs4149056, human UGT2B7 rs7668282, human UGT2B7 rs10028494, human OCT2 rs316019, human OCT2 rs201919874, human OCT2 rs145450955, human ABCB1 rs2032582, human ABCB1 rs1045642, human UGT1A1 rs3755319, human UGT1A1 rs3064744, human AADAC rs1803155, human MT-RNR2 m.2706A>G, human MT-RNR2 rs3928306, human MT-RNR1 rs267606618, human MT-RNR2 m.3197T>C, human MT-RNR1 rs267606617, human MT-RNR1 m.827A>G, human MT-RNR1 m.1291T>C, human MT-RNR1 rs267606619, human FMO3 rs2266782, human CYP2E1 rs2031920, human FMO3 rs2266780, human CYP2E1 rs3813867, human A method for identifying a drug causing an adverse drug reaction, characterized in that the drug is at least one selected from the group consisting of CYP2E1 rs6413432 and human CYP1A2 rs2069526.
In Article 27,
A method for identifying a drug causing an adverse drug reaction, characterized in that the primer of step (b) is a primer set for amplifying a region including a genetic mutation, the primer including at least one base sequence selected from the group consisting of sequence numbers 1 to 38.
In Article 27,
A method for providing pharmacogenetic information, characterized in that the presence or absence of a genetic mutation in the step (c) is confirmed through a snapshot (SNaPshot) analysis using multiple single-base primers including one or more base sequences selected from the group consisting of sequence numbers 39 to 69.