WO2016133375A1 - Procédé de sélection d'un agent thérapeutique contre l'ostéoporose sur la base d'informations sur une personne relatives aux dommages protéiques pour empêcher des effets secondaires de l'agent thérapeutique contre l'ostéoporose - Google Patents

Procédé de sélection d'un agent thérapeutique contre l'ostéoporose sur la base d'informations sur une personne relatives aux dommages protéiques pour empêcher des effets secondaires de l'agent thérapeutique contre l'ostéoporose Download PDF

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WO2016133375A1
WO2016133375A1 PCT/KR2016/001632 KR2016001632W WO2016133375A1 WO 2016133375 A1 WO2016133375 A1 WO 2016133375A1 KR 2016001632 W KR2016001632 W KR 2016001632W WO 2016133375 A1 WO2016133375 A1 WO 2016133375A1
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drug
osteoporosis
sequence variation
individual
score
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Korean (ko)
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김주한
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싸이퍼롬, 인코퍼레이티드
김주한
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids

Definitions

  • the present invention relates to a method for selecting an osteoporosis therapeutic agent based on individual protein damage information using individual genome sequencing to prevent side effects of the osteoporosis therapeutic agent.
  • Pharmacogenetics predicts genetic differences in metabolism and reactions of drugs or chemicals in the general population or in individuals. In some individuals, reactions other than the expected drug response to the drug may be present. These drug side effects may be related to the severity of the disease being treated, drug interactions, the patient's age, nutritional status, liver and kidney function, climate, or food. Although it may be due to factors, genetic differences related to drug metabolism, for example, polymorphism of drug enzyme genes, may be affected.
  • anti-osteoabsorbents a type of therapeutic agent for osteoporosis
  • drugs that affect bone metabolism and are drugs that maintain bone density by inhibiting osteoclasts.
  • Bisphosphonate an anti-osteoabsorbent, has been shown to be effective in inhibiting bone loss and preventing fractures, and is currently being used as a primary treatment for treating osteoporosis, and its use is increasing widely with the increasing prevalence of osteoporosis with aging. According to a previous study, bisphosphonate was the most used osteoporosis-related agent in Korea in 2008, with 68%.
  • the pharmacogenomics mentioned above may be used as a method for predicting side effects of drugs before drug administration.
  • Existing studies have shown that the risk of side effects, such as bisphosphonate-related maxillary necrosis, is associated with genotypes.
  • the ratio of rs17024608, an SNP present in the intron region of the RBMS3 gene was significantly higher in the BRONJ patient group (p-value ⁇ 7x10-8; odds ratio, 5.8; 95% confidence interval, 3.1). -11.1) (Paola N. et al., 2012).
  • the present invention has been devised in view of the above, and analyzes individual genome sequence variation information, calculates individual protein damage scores from gene sequence variation information involved in pharmacodynamics or pharmacokinetics of osteoporosis therapeutics, and then By calculating the individual drug scores in association with the correlation between the protein and the protein, it is intended to provide a method for predicting the possibility of side effects of the osteoporosis treatment and providing information for selecting the treatment for the osteoporosis treatment.
  • the present invention comprises the steps of determining from the individual genomic sequence information one or more gene sequence variation information involved in the pharmaco-dynamics or pharmaco-kinetics of the therapeutic agent for osteoporosis; Calculating an individual protein damage score using the gene sequence variation information; And correlating the individual protein damage scores with the interaction between the drug and the protein to calculate the individual drug scores, thereby providing a method for providing information for selecting a therapeutic agent for osteoporosis using the personal genomic sequence variation.
  • the present invention provides a database capable of searching for or extracting information related to a gene or protein related to the osteoporosis therapeutic agent, which can be applied to an individual; A communication unit accessible to the database; A first calculation module configured to calculate one or more gene sequence variation information related to pharmacodynamics or pharmacokinetics of the osteoporosis therapeutic agent based on the information; A second calculation module for calculating an individual protein damage score using the gene sequence variation information; A third calculating module that calculates an individual drug score by associating the individual protein damage score with a correlation between a drug and a protein; And a display unit for displaying the calculated value calculated by the calculating module.
  • the present invention comprises the steps of obtaining from the individual genome sequence information gene sequence variation information involved in the pharmacodynamics or pharmacokinetics of the osteoporosis therapeutic agent; Calculating an individual protein damage score using the gene sequence variation information; And correlating the individual protein damage score with a correlation between the drug and the protein to calculate the individual drug score, wherein the execution module executes a processor to perform the operation. .
  • the method and system for selecting an individual osteoporosis therapeutic agent based on the individual genome sequence variation information of the present invention is a specific drug, that is, a specific drug, that is, through sequence analysis of an exon region of a gene encoding various proteins involved in the pharmacodynamics or pharmacokinetics of the osteoporosis therapeutic agent. It is highly reliable as a technology that can predict responsiveness to the treatment of osteoporosis.
  • NGS Next Generation Sequencing
  • the method of the present invention can be used in tens to hundreds.
  • Molecular-level research and analysis of proteins related to pharmacokinetics and pharmacodynamics related to the drug can be applied directly to the selection of therapeutic agents for osteoporosis, so that they can be applied without being influenced by differences among population groups, and compared to using fractional markers. Has the advantage of being high.
  • osteoporosis therapeutics applied to an individual by predicting the side effects or risks for the treatment of osteoporosis, for example, bisphosphonates. It can lead to the prevention of side effects through the administration of an appropriate dose in osteoporosis patients.
  • osteoporosis therapeutics such as bisphosphonates
  • it can be easily added and applied to the methods of the present invention, which will be further improved by the accumulation of future findings.
  • a customized treatment method can be provided.
  • FIG. 1 is a flowchart illustrating each step of a method for providing information for selecting an agent for treating osteoporosis using an individual genome sequence variation according to an embodiment of the present invention.
  • FIG. 2 is a schematic block diagram of a system for selecting osteoporosis therapeutics using personal genome sequence variation according to an embodiment of the present invention (DB: database).
  • DB database
  • 3A and 3B are flowcharts illustrating a receiver operating curve (ROC) curve for verification of a method for selecting an osteoporosis therapeutic agent using genome sequence variation according to an embodiment of the present invention.
  • ROC receiver operating curve
  • the present invention is based on the discovery that individual drugs can be selected for high-safety drugs and doses / uses in the treatment of individual osteoporosis drugs by analyzing individual genome sequence variation information.
  • the present invention comprises the steps of determining from the individual genomic sequence information one or more gene sequence variation information involved in the pharmaco-dynamics or pharmaco-kinetics of the therapeutic agent for osteoporosis; Calculating an individual protein damage score using the gene sequence variation information; And correlating the individual protein damage scores with the correlation between the drug and the protein to calculate the individual drug scores.
  • the present invention relates to a method for providing information for selecting a therapeutic agent for osteoporosis using a personal genomic sequence variation.
  • the therapeutic agent for osteoporosis includes, but is not limited to, all substances that exhibit the same and similar pharmacological activity, such as drugs belonging to the drug class disclosed in Table 1, derivatives thereof, and pharmaceutically acceptable salts thereof.
  • DrugBank http://www.drugbank.ca/
  • KEGG Drug http://www.genome.jp/kegg/drug/
  • PharmGKB It can be obtained from a database such as https://www.pharmgkb.org/), preferably FGFR4, IGHMBP2, ARHGEF26, HBXIP, CD1A, ZNF57, LAMA4, SIPA1, GPC4, PSMD9, AKNA, ANKRD50, DUSP13, PIK3R1 , C4orf14, GPR174, CHDH, AC018682.6, SLC12A4, ADARB2, CD3G, ZFYVE20, ASZ1, ARHGEF4, FAT4, OR2M5, HPS1, ZNF235, P4HB, ATP11C, SYNE1, ADCY3, PGLYRP3, M187RT4, M187A4 , SERPINI
  • the genes involved in the pharmacokinetics or pharmacokinetics of the therapeutic agent for osteoporosis in the present invention are FGFR4, IGHMBP2, ARHGEF26, HBXIP, CD1A, ZNF57, LAMA4, SIPA1, GPC4, PSMD9, AKNA, ANKRD50, DUSP13, PIK3R1, C4or14 CHDH, AC018682.6, SLC12A4, ADARB2, CD3G, ZFYVE20, ASZ1, ARHGEF4, FAT4, OR2M5, HPS1, ZNF235, P4HB, ATP11C, SYNE1 and ADCY3, and preferably selected from the group consisting of More than one selected from the group consisting of PGLYRP3, MAGEA12, TMEM187, OR4S1, KRTAP5-4, SERPINI2, BTNL2, CXorf1, PRG4, VAMP8, CSAG1, C1orf27, C1orf229, LRRTM3, SPDEF, GZ
  • the genes / proteins are expressed according to the nomenclature of the HUGO Gene Nomenclature Committee (HGNC) (Gray KA, Daugherty LC, Gordon SM, Seal RL, Wright MW, Bruford EA.genenames.org: the HGNC resources in 2013. Nucleic Acids Res. 2013 Jan; 41 (Database issue): D545-52. Doi: 10.1093 / nar / gks1066. Epub 2012 Nov 17 PMID: 23161694).
  • HGNC HUGO Gene Nomenclature Committee
  • Gene sequence variation used as one information in the present invention refers to a variation or polymorphism of the individual gene sequence.
  • the gene sequence mutation or polymorphism is not limited to those occurring at gene regions, particularly exon regions, which encode proteins associated with pharmacodynamics or pharmacokinetics of osteoporosis therapeutics.
  • base sequence variation information used in the present invention means information about the substitution, addition or deletion of the base constituting the exon of the gene. Substitution, addition, or deletion of such bases can occur for a variety of reasons, for example, by structural differences including mutations, truncation, deletions, duplications, inversions and / or translocations of chromosomes.
  • nucleotide polymorphism refers to differences between individuals of nucleotide sequences present in the genome, and the largest number of nucleotide polymorphisms is Single Nucleotide Polymorphism (SNP), and A, T, C, There is a difference between individuals in one base of the base sequence consisting of G.
  • Sequence polymorphism is a form of polyalleic variation including single nucleotide variation (SNV), short tandem repeat polymorphism (STRP), or variable number of tandem repeat (VNTR) and copy number variation (CNV), including SNPs. May appear.
  • Sequence variation or polymorphism information found in the genome of an individual in the method of the present invention is collected in association with a protein associated with the pharmacokinetics or pharmacokinetics of the therapeutic agent for osteoporosis. That is, the nucleotide sequence information used in the method of the present invention is one or more genes involved in the pharmacokinetics or pharmacokinetics of the therapeutic agent of osteoporosis among the obtained genomic sequence information of the individual, for example, a target protein, drug associated with the drug Mutation information found in the exon region, in particular, but not limited to, genes encoding enzyme proteins, transporter proteins or carrier proteins involved in metabolism.
  • the genome sequence information of an individual used in the present invention may be determined using a known sequence decoding method, and services such as Complete Genomics, BGI (Beijing Genome Institute), Knome, Macrogen, DNALink, etc., which provide commercially available services. May be used, but is not limited thereto.
  • Gene sequence variation information present in the genome sequence of an individual in the present invention can be extracted using a variety of methods, a sequence comparison program with a genomic sequence of a reference group, for example HG19, for example, ANNOVAR ( Wang et al., Nucleic Acids Research, 2010; 38 (16): e164), Sequence Variant Analyzer (SVA) (Ge et al., Bioinformatics. 2011; 27 (14): 19982000), Break Dancer (Chen et al., Nat Methods.2009 Sep; 6 (9): 677-81) and the like.
  • the gene sequence variation information may be received / obtained through a computer system, and in this aspect, the method of the present invention may further include receiving the genetic variation information into a computer system.
  • the computer system used in the present invention relates to a gene involved in the pharmacokinetics or pharmacokinetics of the therapeutic agent for osteoporosis, for example, a target protein associated with a drug, an enzyme protein involved in drug metabolism, a transporter protein or a carrier protein. It may include or be accessible to one or more databases containing information.
  • Such databases include, for example, DrugBank (http://www.drugbank.ca/), KEGG Drug (http://www.genome.jp/kegg/drug/), PharmGKB (http://www.pharmgkb.org /) May include, but is not limited to, public or private databases or knowledge bases that provide information about genes / proteins / drug-protein interactions, and the like.
  • the osteoporosis therapeutic agent may be information input from a database including information input by a user, information input from a prescription (pre), or information on the osteoporosis therapeutic agent.
  • the prescription includes, but is not limited to, electronic prescription.
  • pharmaco-kinetics or pharmacokinetic parameters refers to the properties of a drug that is associated with absorption, migration, distribution, conversion, and excretion of the drug in the body over a period of time.
  • pharmacodynamics or pharmacodynamic parameters refers to the characteristics related to the physiological and biochemical action of the drug on the living body and its mechanism of action, ie the reaction or effect of the living body of the drug.
  • the term “gene sequence variation score” refers to an amino acid sequence variation (substitution or addition) of a protein encoded by the gene when the genome sequence variation is found in the exon region of the gene encoding the protein. Or deletion) or a score that quantifies the extent to which transcriptional control mutations result, thereby causing significant changes or damage to the structure and / or function of the protein, wherein the gene sequence variation score is the evolution of amino acids on the genome sequence It can be calculated in consideration of the degree of preservation and the degree of change in the structure or function of the protein according to the physical properties of the modified amino acid.
  • the method of calculating the gene sequence variation score may be performed using a method known in the art. See, eg, SIFT (Sorting Intolerant From Tolerant, Pauline C et al., Genome Res. 2001 May; 11 (5): 863874; Pauline C et al., Genome Res. 2002 March; 12 (3): 436446; Jing Hul et al., Genome Biol. 2012; 13 (2): R9), PolyPhen, PolyPhen-2 (Polymorphism Phenotyping, Ramensky V et al., Nucleic Acids Res.
  • fathmm (Shihab et al., Functional Analysis through Hidden Markov Models, Hum Mutat 2013; 34 : 57-65, http://fathmm.biocompute.org.uk/) may be used to calculate the gene sequence variation score from the gene sequence variation information, but is not limited thereto.
  • the purpose of the algorithms described above is to determine how each gene sequence mutation affects protein function, how this damage damages the protein, or whether there is little effect. They have a common point in that they determine the impact of individual gene sequence variations on the structure and / or function of the protein in consideration of the changes that will result in the amino acid sequence of the protein encoded by the gene.
  • a Sorting Intolerant From Tolerant (SIFT) algorithm was used to calculate an individual gene sequence variation score.
  • SIFT Sorting Intolerant From Tolerant
  • gene sequence variation information is input to a VCF (Variant Call Format) format file, and each gene sequence variation is scored for damaging the gene.
  • VCF Variant Call Format
  • the method of the present invention calculates individual protein damage scores based on the gene sequence variation scores described above in the next step.
  • protein damage score means that two or more significant sequence mutations are found in a gene region encoding one protein, so that one protein has two or more gene sequence mutation scores. Refers to a score calculated by combining the gene sequence variation score. If there is a significant sequence variation in a gene region encoding a protein, the gene sequence variation score and the protein damage score are the same. In this case, when there are two or more gene sequence mutations encoding a protein, the protein damage score is calculated as an average value of the gene sequence variation scores calculated for each variation, and the average value is, for example, a geometric mean, an arithmetic mean, or a harmonic mean.
  • Arithmetic geometric mean, arithmetic harmonic mean, geometric harmonic mean, Pythagorean mean, quadrant mean, quadratic mean, cutting mean, windsorized mean, weighted mean, weighted geometric mean, weighted arithmetic mean, weighted harmonic mean, function mean, ⁇ average Can be computed as a generalized f-means, percentiles, maximums, minimums, modes, medians, median ranges, measures of central tendency, simple products or weighted products, or as a function of these calculations. This is not restrictive.
  • the protein damage score was calculated by Equation 1 below, and Equation 1 may be variously modified and is not limited thereto.
  • Equation 1 Sg is the protein damage score of the protein encoded by the gene g, n is the number of the nucleotide sequence analysis of the nucleotide variation of the gene g, vi is the gene sequence variation score of the i-th gene sequence variation And p is a nonzero real number.
  • p when the value of p is 1, it is an arithmetic mean, and when the value of p is -1, it is a harmonic mean, and in the extreme case where the value of p is close to 0, it is a geometric mean.
  • the protein damage score was calculated by Equation 2 below, and Equation 2 may be variously modified and is not limited thereto.
  • Equation 2 Sg is the protein damage score of the protein encoded by the gene g, n is the number of the nucleotide sequence analysis of the nucleotide sequence variation of the gene g, vi is the gene sequence variation score of the i-th gene sequence variation , wi is a weight given to vi. When all weights wi have the same value, the protein damage score Sg becomes the geometric mean value of the gene sequence variation score vi.
  • the weight may be given in consideration of the type of the protein, the pharmacokinetic or pharmacodynamic classification of the protein, the pharmacokinetic parameters of the drug enzyme protein, and the population or race distribution.
  • the term “pharmacokinetic parameters of drug enzyme protein” includes Vmax, Km, Kcat / Km and the like.
  • Vmax is the maximum enzyme reaction rate when the substrate concentration is very high
  • Km is the concentration of the substrate that causes the reaction to reach 1/2 Vmax.
  • Km can be seen as an affinity between the enzyme and the substrate. The smaller the Km, the stronger the bond between the enzyme and the substrate.
  • Kcat also called the enzyme's metabolic rate, refers to the number of substrate molecules that are metabolized at one second per enzyme active site when the enzyme is active at its maximum rate, and how fast the enzyme reaction actually occurs.
  • the method of the present invention calculates the individual drug score by correlating the protein damage score described above in the next step with the correlation between the drug and the protein.
  • drug score means a given protein, eg, a target protein involved in the pharmacodynamics or pharmacokinetics of a given drug, an enzyme protein involved in drug metabolism, a transporter protein or a carrier, given a drug, such as an osteoporosis therapeutic agent.
  • the proteins are found, the protein damage scores of the proteins are calculated, and the results are summed to give the calculated value for one drug.
  • the drug score is calculated as an average value of the protein damage scores when the damage of the protein involved in the pharmacokinetics or pharmacokinetics of the osteoporosis therapeutic agent is two or more, and the average value is, for example, geometric mean, arithmetic mean, harmonic mean, arithmetic Geometric mean, arithmetic harmonic mean, geometric harmonic mean, Pythagorean mean, quadrant mean, quadratic mean, cutting mean, windsor mean, weighted mean, weighted geometric mean, weighted arithmetic mean, weighted harmonic mean, function mean, power average, generalization Can be calculated by a calculated f-means, percentiles, maximums, minimums, modes, medians, median ranges, measures of central tendency, simple products or weighted products, or a function operation of the calculations. It is not limited.
  • the drug score may be calculated by adjusting the weights of the drug, that is, the target protein involved in the pharmacodynamics or pharmacokinetics of the osteoporosis therapeutic agent, the enzyme protein involved in the drug metabolism, the transporter protein, and the carrier protein in consideration of pharmacological properties.
  • the weight may be given in consideration of pharmacokinetic parameters, population groups or race distributions of the corresponding drug enzyme protein.
  • the protein damage scores of proteins that do not interact directly with the drug but interact with precursors of the drug or metabolites of the drug, such as proteins that participate in pharmacological pathways are also synthesized. Drug scores can be calculated.
  • the combined drug scores may be calculated by considering the protein damage scores of the proteins that significantly interact with the proteins involved in the pharmacodynamics or pharmacokinetics of the drug.
  • protein damage scores of the proteins that significantly interact with the proteins involved in the pharmacodynamics or pharmacokinetics of the drug For information on proteins that participate in the pharmacological pathway of the drug, significantly interact with the proteins, or participate in its signaling pathway, see PharmGKB (Whirl-Carrillo et al., Clinical Pharmacology & Therapeutics 2012; 92).
  • the drug score was calculated by the following Equation 3, and the following Equation 3 may be variously modified, but is not limited thereto.
  • Equation 3 Sd is a drug score of drug d, n is a protein directly involved in the pharmacodynamics or pharmacokinetics of drug d or interacts with a precursor of the drug or metabolites of the drug, for example, a pharmacological pass.
  • the number of proteins encoded by one or more genes selected from the group of genes participating in the way, gi is a protein that directly participates in the pharmacodynamics or pharmacokinetics of drug d or interacts with precursors or metabolites of the drug, eg
  • p when the value of p is 1, it is an arithmetic mean, and when the value of p is -1, it is a harmonic mean, and in the extreme case where the value of p is close to 0, it is a geometric mean.
  • the drug score was calculated by Equation 4 below, and Equation 4 may be variously modified, and is not limited thereto.
  • Sd is a drug score of drug d
  • n is a protein directly involved in the pharmacodynamics or pharmacokinetics of drug d or interacts with a precursor of the drug or metabolites of the drug, eg, a pharmacological pass.
  • the number of proteins encoded by one or more genes selected from the group of genes constituting the way, gi are proteins that directly participate in the pharmacodynamics or pharmacokinetics of drug d or interact with precursors or metabolites of the drug, eg
  • the protein damage score of the protein encoded by one or more genes selected from the gene group constituting the pharmacological pathway, wi is the weight given to the gi.
  • the drug score Sd becomes the geometric mean value of the protein damage score gi when all weights wi have the same value.
  • the weight may be given in consideration of the type of the protein, the pharmacokinetic or pharmacodynamic classification of the protein, the pharmacokinetic parameters of the drug enzyme protein, and the population or race distribution.
  • the weights are equally given regardless of the characteristics of the drug-protein association, but as in the other embodiment of the present invention, It is possible to calculate the drug score by assigning weights in consideration of each feature to have. For example, different scores may be assigned to the drug's target protein and the drug's transporter protein.
  • the drug enzyme protein may be weighted with its pharmacokinetic parameters Km, Vmax, and Kcat / Km to calculate the drug score.
  • the target protein may be given a higher weight because it is considered more important in pharmacological action than the transporter protein, and the transporter protein or the carrier protein may be given a high weight for the concentration-sensitive drug.
  • Weights can be closely adjusted according to the correlation between drug and drug-related proteins, and the nature of drug-protein interactions. For example, a sophisticated algorithm can be used that assigns a weight to the nature of the drug-protein interaction, such as giving the target protein two points and the transporter protein one point.
  • the protein interacts with the precursor of the drug or metabolites of the drug, and is involved in the pharmacodynamics or pharmacokinetics of the drug. It is possible to improve the predictive power of the formula by utilizing the protein that interacts significantly with the protein, and the related protein information participating in the signaling pathway. In other words, the protein-protein interaction network or pharmacological pathway information can be utilized to use the information of various proteins involved in it.
  • the mean value (eg, geometric mean) of the protein damage scores of related proteins participating in the same signaling pathway may be used as a drug score calculation instead of the protein damage score of the protein.
  • the individual drug score may be calculated for all drugs for which information on one or more related proteins can be obtained or for some selected drugs.
  • individual drug scores can be converted into rank (rank).
  • the method of the present invention may further include determining whether to use a drug applied to the individual, that is, a treatment for osteoporosis, by using the aforementioned individual drug score.
  • the individual drug scores of the present invention can be applied individually to all drugs, but are more useful when applied between classes of drugs, such as disease, clinical characteristics, or mode of action.
  • Drug classification systems that can be used in the present invention are, for example, the ATC (Anatomical Therapeutic Chemical Classification System) code, the top 15 frequently prescribed drug classes during 2005-2008 in the United States (Health, United States, 2011, Centers for Disease Control and Prevention), a list of drugs that have been released from the market due to known pharmacogenomic markers that may affect drug action information on the drug label, or side effects. It may include.
  • the method of the invention may further comprise calculating a prescription score.
  • the term “prescription score” refers to the drug score determined for each drug when two or more drugs are administered at the same time or at intervals short enough to significantly affect each other's pharmacological action. Refers to the score calculated in aggregate.
  • the prescription score may be calculated by combining the drug scores determined for each drug when two or more drugs determined by the priority between the drugs and simultaneous administration are required. The calculation of the prescription score can be calculated by simply averaging, summing or multiplying the drug scores of the plurality of drugs, for example, when no protein interacts in common with the plurality of drugs. If there are proteins that interact in common with the plurality of drugs, the drug damage scores of the common interacting protein are weighted twice, for example, to calculate each drug score and then the corresponding drug scores are calculated. By summing up, the prescription score can be calculated.
  • Prescription scores are intended to determine the adequacy or risk of a multi-drug prescription that is included in the prescription applied to an individual, beyond the effects of individual drugs.
  • the method of the present invention may further comprise determining the appropriateness or risk of the prescription (pre) applied to the individual.
  • the method of the present invention includes, but is not limited to being carried out for the purpose of preventing the side effects of osteoporosis therapeutics.
  • FIG. 1 is a flowchart illustrating each step of a method for providing information for selecting an agent for treating osteoporosis using an individual genome sequence variation according to an embodiment of the present invention.
  • the step of providing a pharmacogenomic calculation process and the basis for calculating the drug scores by providing information such as pictures, charts and explanations to help the prescriber's judgment It may further comprise. That is, the method according to the present invention provides one or more information of the gene sequence variation information, the gene sequence variation score, the protein damage score, the drug score, and the information used for the calculation on which the drug ranking of the present invention is based. It may further comprise the step.
  • the present invention provides a database for osteoporosis therapeutics that can be applied to an individual, a database capable of searching for or extracting information related to genes or proteins related to the osteoporosis therapeutics; A communication unit accessible to the database; A first calculation module configured to calculate one or more gene sequence variation information related to pharmacodynamics or pharmacokinetics of the osteoporosis therapeutic agent based on the information; A second calculation module for calculating an individual protein damage score using the gene sequence variation information; A third calculating module that calculates an individual drug score by associating the individual protein damage score with a correlation between a drug and a protein; And it relates to a osteoporosis therapeutic agent selection system using a personal genome sequence variation comprising a display unit for displaying the calculated value calculated by the calculation module.
  • the module may mean a functional and structural combination of hardware for performing the technical idea according to the present invention and software for driving the hardware.
  • the module may mean a logical unit of a predetermined code and a hardware resource for performing the predetermined code, and does not necessarily mean a physically connected code or a kind of hardware. Will be apparent to those skilled in the art.
  • the term “output module” refers to the gene sequence variation score, protein damage score, drug score, and information on which the gene is calculated, for the osteoporosis therapeutic agent and gene to be analyzed according to the method of the present invention, and It may mean a logical unit of a predetermined code for calculating each score based on the information and a hardware resource for performing the predetermined code, and necessarily means a physically connected code or a kind of hardware. It does not mean.
  • the system according to the present invention may further include a fourth calculation module for determining whether to use an osteoporosis therapeutic agent applied to the individual by using the individual drug score calculated in the third calculation module.
  • the system according to the present invention further includes a fifth calculation module for calculating the prescription score by combining the drug scores determined for each drug when two or more drugs determined by the priority between drugs are required. It may include.
  • the system according to the present invention inputs a list of osteoporosis treatments by the user, or accesses a database including information on the treatment of osteoporosis, extracts relevant information, and calculates and provides a drug score of the drug accordingly. It may further include.
  • the system according to the present invention may further include a display unit for further displaying a calculation process in which a value calculated in each calculation module or a priority between drugs is determined, and information on which the calculation or calculation is based.
  • the server including the database or its access information, the calculated information and the user interface device connected thereto may be used in conjunction with each other.
  • the system according to the invention can be updated immediately when new pharmacological / biochemical information on drug-protein interactions is produced and can be used for further osteoporosis therapeutic selection.
  • the gene sequence variation information, gene sequence variation score, protein damage score, drug score and information on which the basis of the calculation stored in each calculation module Is updated.
  • System 10 of the present invention is a database (DB) 100, the communication unit 200, the user interface or terminal 300, the calculation unit 400 and the search for or extract information related to genes or proteins related to osteoporosis therapeutics and
  • the display unit 500 may be configured to be included.
  • the user interface or the terminal 300 may request, receive and / or store the osteoporosis therapeutic agent selection process using a personal genome sequence variation from a server, and may be a smart phone, a personal computer (PC), or a tablet PC. It may be configured as a terminal having a mobile communication function having a computing capability by mounting a microprocessor, such as a personal digital assistant (PDA), a web pad, or the like.
  • a microprocessor such as a personal digital assistant (PDA), a web pad, or the like.
  • the server is a means for providing access to the database 100 for osteoporosis therapeutics, gene mutations or drug-protein correlations, and is connected to the user interface or the terminal 300 through the communication unit 200. It is configured to exchange various information.
  • the communication unit 200 may communicate in the same hardware, as well as a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), the Internet, 2G, 3G, 4G mobile communication network, Wi-Fi (Wi-Fi), Wibro (Wibro) and the like can be included, and the communication method is wired, wireless, any communication method.
  • the database 100 may also be connected to various life science databases accessible through the Internet as well as being installed directly on the server.
  • the calculation unit 400 calculates one or more gene mutation information related to pharmacokinetics or pharmacokinetics of the osteoporosis therapeutic agent by using the collected / inputted information as described above. It may be configured to include a second calculation module 420 for calculating the protein damage score, a third calculation module 430 for calculating the individual drug score.
  • a storage medium includes any medium for storage or delivery in a form readable by a device such as a computer.
  • a computer readable medium may include read only memory (ROM); Random access memory (RAM); Magnetic disk storage media; Optical storage media; Flash memory devices and other electrical, optical or acoustic signaling media, and the like.
  • the present invention comprises the steps of obtaining from the individual genome sequence information gene sequence variation information involved in the pharmacodynamics or pharmacokinetics of the osteoporosis therapeutic agent; Calculating an individual protein damage score using the gene sequence variation information; And an execution module for associating the individual protein damage score with the correlation between the drug and the protein to execute a processor to perform an operation comprising calculating the individual drug score.
  • the processor may further include determining whether to use an osteoporosis therapeutic agent applied to the individual by using the individual drug score.
  • the present invention provides a biomarker composition for predicting side effects of an osteoporosis therapeutic agent.
  • Genes that may be included in the biomarker composition according to the present invention include FGFR4, IGHMBP2, ARHGEF26, HBXIP, CD1A, ZNF57, LAMA4, SIPA1, GPC4, PSMD9, AKNA, ANKRD50, DUSP13, PIK3R1, C4orf14, GPR174, CHDH, AC018682.
  • Osteoporosis refers to a condition in which the overall bone can be easily destroyed due to a decrease in bone density and changes in the microstructure in the bone tissue. Patients are often diagnosed with osteoporosis along with fractures. In patients with osteoporosis, vertebral compression fractures or hip fractures usually occur. Osteoporosis in postmenopausal women is the most common manifestation of increased osteoclast function and decreased osteoblast function due to estrogen reduction. In addition, osteoporosis may occur due to the decrease of osteoblast function due to aging and lack of calcium in the body, and other secondary causes such as nephrotic urinary tract syndrome, Cushing syndrome, androgen insensitivity syndrome, inflammatory bowel disease, and bone metastasis of malignant tumors. It may appear.
  • bisphosphonate a type of therapeutic agent for osteoporosis
  • Bisphosphonates have been shown to be effective in inhibiting bone loss and preventing fractures, and are currently being used as a primary treatment for the treatment of osteoporosis.
  • the use of bisphosphonates increases widely with the increasing prevalence of osteoporosis with aging. According to a previous study, bisphosphonate was the most used osteoporosis-related agent in Korea in 2008, with 68%.
  • the pharmacogenomics mentioned above may be used as a method for predicting side effects of drugs before drug administration.
  • Existing studies have revealed that genotypes are associated with the risk of side effects such as bisphosphonate-relate OsteoNecrosis of the Jaw (BRONJ).
  • BRONJ bisphosphonate-relate OsteoNecrosis of the Jaw
  • the ratio of rs17024608, an SNP present in the intron region of the RBMS3 gene was significantly higher in the BRONJ patient group (p-value ⁇ 7x10-8; odds ratio, 5.8; 95% confidence interval, 3.1). -11.1) (Paola N. et al., 2012).
  • sequence fragments analyzed were sequence alignment map (SAM) and binary alignment map (BAM) files aligned with human reference sequence (eg, HG19) through data cleaning and quality check.
  • SAM sequence alignment map
  • BAM binary alignment map
  • the output was in format.
  • the clean alignment result is detected using a software tool such as SAMTools: pileup, SAMTools: mpileup, GATK: recalibration, GATK: realignment, and the like to detect mutations such as single nucleotide variations (SNVs, Single Nucleotide Variants) and InDels. It was output to a file in VCF (Variant Calling Format) format.
  • VCF Variariant Calling Format
  • the above-described gene sequence variation score vi value was calculated for each variation by using the SIFT algorithm, and the individual protein damage score Sg was calculated using Equation 2. Subsequently, the individual protein damage scores were compared for each gene in 38 cases in which the side effects appeared and in 30 cases of the health control group. Fifty genes showing statistically significant differences in the adverse event group and the control group were selected as follows, and 32 genes with higher statistical significance were selected as the first group based on the p-value. The following genes correspond to genes of high relevance to the pharmacokinetics or pharmacokinetics of bisphosphonates and their metabolites.
  • the drug score for each individual gene group was calculated using the method of the present invention. More specifically, after calculating the gene sequence variation score using the SIFT algorithm from each individual gene sequence variation information, the individual protein damage score for the 50 genes were calculated using Equation 2, Equation 4 Using to calculate the individual drug score for bisphosphonate, statistical analysis for each group. The results are shown in Table 2.
  • the method of the present invention can be used to predict a group of patients with osteoporosis who are more likely to develop side effects in the administration of bisphosphonates, and induce high-risk patients to control the concentration of the drug or to use other alternative treatments or interventions. will be.
  • the personalized drug selection method according to the present invention not only targets all gene sequence mutations, but also does not require expensive case-control design observation studies, and damages individual proteins by pure calculation of genome sequence mutations. Since we propose a method of calculating the score and the individual drug score and applying it, it has the great advantage that it is possible to infer a personalized drug selection for the combination of all genome sequence variations and all drugs.
  • Validity criteria data were extracted from the established knowledge of 987 gene sequence mutation-drug interaction pairs provided by PharmGKB with 650 (65.9%) having at least one link with the 497 drugs.
  • the present invention targets the nucleotide sequence variation of the exon region, overlapping portions between the verification target data and the evaluation reference data are removed for fair evaluation. More specifically, all 36 nucleotide sequence mutations located in the exon region were removed from the 650 pairs, and only a nucleotide sequence variation of the non-coding region was selected to perform a more fair evaluation. In conclusion, we selected 614 pairs as the final gold standard for evaluation.
  • the sensitivity, specificity and area under the receiver operating curve were used. After ranking 497 drugs based on individual drug scores and setting thresholds by rank at 496 splits between each rank, (1) the drug score rank of the drug is above the threshold and the PharmGKB mutation is in the personal genome.
  • D is a set of 497 total drugs
  • GS is a set of personalized PharmGKB drugs that are used as individual gold standards by matching individual genetic sequence mutations with the risk allele of PharmGKB
  • D L is a set of top-ranking drugs The vertical bar brackets indicate the number of elements in the set.
  • ROC curve was calculated by calculating the specificity and and the AUC was calculated. More specifically, first, gene sequence variation scores were calculated using a SIFT algorithm for a total population of 1092 people, and then protein damage scores and drug scores were calculated by applying Equations 2 and 4, respectively.
  • Protein group distribution and average protein damage score calculation Protein family Protein count Related drug count Number of protein-drug pairs Average protein damage score Target protein 440 486 2357 0.798 Carrier Protein 10 50 65 0.728 Metabolic protein 74 330 1347 0.733 Transporter protein 54 176 457 0.733 system 545 497 4201 0.783
  • Table 3 shows the distribution of the protein groups for 497 drugs used in this example, and the number of protein-drug pairs and the average protein damage score were displayed together in each group.
  • Table 4 shows the adequacy of the individual drug scores calculated when calculating the drug score using Equation 4, when the weights for each protein group are not applied (simple geometric mean) and when applied (weighted geometric mean), respectively. It is represented by each protein group, each race.
  • each group of proteins such as target protein, carrier protein, metabolic protein, and transporter protein
  • a result of performing an AUC analysis of individual drug scores by applying weights according to the number of individual races is considered, considering race specificity (bold line).
  • the total AUC of the population was 0.666 (African 0.744, American 0.650, Asian 0.631, European 0.653), without considering race specificity (dotted line).
  • the overall population AUC was 0.633 (African 0.623, American 0.629, Asian 0.64, European 0.636), indicating that the validity of drug score calculation considering race specificity was improved compared to that of the other population.
  • the individual drug score calculation validity AUC of the individual of the present invention is 0.634, and also applied to the weight of each protein group with race specificity ( Bold line), the individual drug score calculation validity AUC of the present invention is 0.667, indicating that the different weights are useful.

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Abstract

La présente invention concerne un procédé et un système pour sélectionner un agent thérapeutique contre l'ostéoporose sur la base d'informations sur une personne relatives aux dommages protéiques à l'aide d'un séquençage du génome d'une personne. Le procédé et le système, selon la présente invention, sont extrêmement fiables et largement applicables à des techniques capables de prévoir des effets ou risques secondaires de médicaments spécifiques, en d'autres termes, d'agents thérapeutiques contre l'ostéoporose, pour chaque personne en une analyse de séquence d'une partie d'un exon d'un gène qui code diverses protéines impliquées dans la pharmacocinétique ou la pharmacodynamique de l'agent thérapeutique contre l'ostéoporose.
PCT/KR2016/001632 2015-02-17 2016-02-17 Procédé de sélection d'un agent thérapeutique contre l'ostéoporose sur la base d'informations sur une personne relatives aux dommages protéiques pour empêcher des effets secondaires de l'agent thérapeutique contre l'ostéoporose WO2016133375A1 (fr)

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