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EP2064342A1 - Procédé pharmacogénétique pour prédire l'efficacité d'une monothérapie par méthotrexate dans le traitement d'une arthrite récente - Google Patents

Procédé pharmacogénétique pour prédire l'efficacité d'une monothérapie par méthotrexate dans le traitement d'une arthrite récente

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Publication number
EP2064342A1
EP2064342A1 EP07808553A EP07808553A EP2064342A1 EP 2064342 A1 EP2064342 A1 EP 2064342A1 EP 07808553 A EP07808553 A EP 07808553A EP 07808553 A EP07808553 A EP 07808553A EP 2064342 A1 EP2064342 A1 EP 2064342A1
Authority
EP
European Patent Office
Prior art keywords
responsiveness
subject
polymorphism
das
clinical
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP07808553A
Other languages
German (de)
English (en)
Inventor
Hendrik Jan Guchelaar
Tom Willem Johannes Huizinga
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Leids Universitair Medisch Centrum LUMC
Original Assignee
Leids Universitair Medisch Centrum LUMC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Leids Universitair Medisch Centrum LUMC filed Critical Leids Universitair Medisch Centrum LUMC
Priority to EP07808553A priority Critical patent/EP2064342A1/fr
Publication of EP2064342A1 publication Critical patent/EP2064342A1/fr
Withdrawn legal-status Critical Current

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Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/156—Polymorphic or mutational markers

Definitions

  • the current invention relates to the field of medicine, in particular the fields of methotrexate monotherapy in recent-onset arthritis and the pharmacogenetic diagnostics and prognostics thereof.
  • RA rheumatoid arthritis
  • MTHFR methylene tetrahydrofolate reductase
  • AMPDl adenosine monophosphate deaminase
  • ATIC amino imidazole carboxamide ribonucleotide transformylase
  • IPA inosine triphosphate pyrophosphatase
  • the present invention relates to methods for determining a predicted clinical responsiveness to antifolate therapy in a subject afflicted with, or at risk of developing, arthritis, such as rheumatoid arthritis (RA).
  • RA rheumatoid arthritis
  • the methods described herein are applied to individuals that present with a recent-onset arthritis.
  • the methods described herein are applied to individuals with recent-onset undifferentiated arthritis or recent-onset rheumatoid arthritis.
  • Undifferentiated arthritis (UA) is herein defined as arthritis for which with the available classification criteria no diagnosis can be made, e.g. using the American College of Rheumatology (ACR) 1987 classification criteria for RA (see e.g.
  • RA is herein defined as arthritis for which with the available classification criteria the diagnosis can be made, e.g. using these American College of Rheumatology (ACR) 1987 classification criteria for rheumatoid arthritis.
  • ACR American College of Rheumatology
  • An individual with recent-onset arthritis is herein defined as an individual with complaints dating from less than one year, (e.g., less than 6 months).
  • An individual with recent-onset RA is herein defined as an individual with complaints dating from less than two years (e.g., less than one year).
  • the methods described herein may also be applied to individuals that present with persistent RA, preferably to individuals wherein primary antifolate therapy and/or anti-TNF therapy has failed.
  • One embodiment provides a method for determining a predicted responsiveness to methotrexate (MTX) responsiveness in a mammal afflicted with, or at risk of developing, arthritis (e.g., RA) by determining one or more polymorphisms in one or more of the following genes: methylenetetrahydro folate dehydrogenase (MTHFDl), adenosine monophosphate deaminase (AMPDl), amino imidazole carboxamide ribonucleotide transformylase (ATIC), and inosine triphosphate pyrophosphatase (ITPA), wherein the presence of the polymorphism is indicative of clinical responsiveness to the antifolate therapy.
  • MTHFDl methylenetetrahydro folate dehydrogenase
  • AMPDl adenosine monophosphate deaminase
  • ATIC amino imidazole carboxamide ribonucleotide transformylase
  • ITPA ino
  • the subject may be any mammal, including a human, ape, dog horse, cow, pig, rabbit and the like.
  • the method of the invention is performed in vitro on a sample obtained from a subject to be tested.
  • the in vitro method may be performed on nucleic acid present in a sample from the subject, which may be any sample containing nucleic acids such as blood, serum, plasma, saliva, tissue, or a buccal swab.
  • Nucleic acids which can be analyzed using the present methods include genomic DNA, genomic RNA, mRNA and cDNA.
  • Figure 1 shows a Receiver Operating Curve for predicting methotrexate response, including clinical and pharmacogenetic factors.
  • Incorporated factors in the pharmacogenetic model are gender, Disease Activity Score (DAS) at baseline, rheumatoid factor (RF) status, smoking status, and genotypes for ATIC, AMPDl, ITPA and MTHFDl.
  • Factors in the non-genetic model are gender, DAS at baseline, RF status, and smoking status.
  • Figure 2 shows a schematic example of an embodiment of a computer that may be used in one or more of the embodiments described.
  • Figure 3 schematically depicts a flow diagram of a procedure that may be executed by the computer of Figure 2 according to an embodiment of the invention.
  • the term "antifolate” means a molecule that acts as a folate antagonist against one or more folate-dependent enzymes (e.g., thymidylate synthase and dihydrofolate reductase) and which may also be structurally similar to folate. These compounds result in reduction of de novo purine and pyrimidine synthesis.
  • One antifolate, methotrexate is also used for treatment of arthritis and rheumatoid arthritis.
  • methotrexate analog means a molecule having structural and functional similarity to methotrexate. Methotrexate analogs are functionally characterized, in part, by their inhibitory activity against dihydrofolate reductase.
  • polymorphism refers to the occurrence of two or more genetically determined alternative sequences or alleles in a population.
  • a "polymorphic site” refers to the locus at which divergence occurs. Preferred polymorphic sites have at least two alleles, each occurring at a frequency of greater than 1%. In other embodiments, each of the at least two alleles occurs at a frequency of greater than 10% or 20% of a selected population.
  • a polymorphic locus may be as small as one base pair (single nucleotide polymorphism, or SNP).
  • Polymorphic markers include restriction fragment length polymorphisms, variable number of tandem repeats (VNTRs), hypervariable regions, minisatellites, dinucleotide repeats, trinucleotide repeats, tetranucleotide repeats, simple sequence repeats, insertion elements such as AIu, deletions and differences in gene copy number.
  • the first identified allele is arbitrarily designated as the reference allele and other alleles are designated as alternative or "variant alleles.”
  • the alleles occurring most frequently in a selected population may be referred to as the "wild-type" allele.
  • Diploid organisms may be homozygous or heterozygous for the variant alleles.
  • the variant allele may or may not produce an observable physical or biochemical characteristic ("phenotype") in an individual carrying the variant allele.
  • phenotype observable physical or biochemical characteristic
  • a variant allele may alter the enzymatic activity of a protein encoded by a gene of interest.
  • SNP single nucleotide polymorphism
  • a SNP occurs at a polymorphic site occupied by a single nucleotide, which is the site of variation between allelic sequences. The site is usually preceded by and followed by highly conserved sequences of the allele (e.g., sequences that vary in less than 1/100 or 1/1000 members of the populations).
  • a SNP usually arises due to substitution of one nucleotide for another at the polymorphic site.
  • a transition is the replacement of one purine by another purine or one pyrimidine by another pyrimidine.
  • a transversion is the replacement of a purine by a pyrimidine or vice versa.
  • Single nucleotide polymorphisms can also arise from a deletion of a nucleotide or an insertion of a nucleotide relative to a reference allele.
  • the method comprises detecting the presence of a polymorphism in the methylenetetrahydrofolate dehydrogenase (MTHFDl) gene, wherein the presence of the polymorphism is indicative of clinical responsiveness to the antifolate therapy.
  • Methylenetetrahydrofolate dehydrogenase (EC 1.5.1.15) is encoded by the MTHFDl gene (accession number for the human gene: NM_005956).
  • the polymorphism in the MTHFDl gene is a polymorphism that results in an amino acid change with respect to the amino acid sequence of SEQ ID NO: 1.
  • MTHFDl single nucleotide polymorphism 1958G>A (rsl7850560).
  • a genotype that is indicative of clinical responsiveness to the antifolate therapy is a MTHFDl G-allele carrier.
  • the genotype "MTHFDl 1958 G-allele carrier” is understood to mean a genotype that is homozygous or heterozygous for the MTHFDl 1958 G-allele.
  • polymorphisms in one or more genes involved in the adenosine release pathway are determined, wherein the presence of the polymorphism is indicative of clinical responsiveness to the antifolate therapy.
  • Genes involved in the adenosine release pathway for detection of polymorphism that are indicative of clinical responsiveness to the antifolate therapy include one or more of the following genes: adenosine monophosphate deaminase (AMPDl), aminoimidazole carboxamide ribonucleotide transformylase (ATIC), and inosine triphosphate pyrophosphatase (ITPA).
  • Adenosine monophosphate deaminase (EC 3.5.4.6) is encoded by the AMPDl gene (accession number for the human gene: NM_000036).
  • the polymorphism in the AMPDl gene is a polymorphism that results in an amino acid change with respect to the amino acid sequence of SEQ ID NO: 2.
  • One particular polymorphism in the AMPDl gene for detection in the methods of the invention is the single nucleotide polymorphism 34C>T (rs 17602729).
  • an AMPDl genotype that is indicative of clinical responsiveness to the antifolate therapy is an AMPDl 34 T-allele carrier.
  • Aminoimidazole carboxamide ribonucleotide transformylase (EC 6.3.2.6) is encoded by the ATIC gene (accession number for the human gene: NM_004044).
  • the polymorphism in the ATIC gene is a polymorphism that results in an amino acid change with respect to the amino acid sequence of SEQ ID NO: 3.
  • One particular polymorphism in the ATIC gene for detection in the methods described herein is the single nucleotide polymorphism 347 C>G (rs2372536).
  • One particular ATIC genotype that is indicative of clinical responsiveness to the antifolate therapy is the ATIC 347 CC genotype.
  • the "ATIC 347 CC genotype” is understood to mean the genotype that is homozygous for the ATIC 347 C allele.
  • Inosine triphosphate pyrophosphatase (EC 3.6.1.19) is encoded by the ITPA gene (accession number for the human gene: NM_033453).
  • the polymorphism in the ITPA gene is a polymorphism that results in an amino acid change with respect to the amino acid sequence of SEQ ID NO: 4.
  • One particular polymorphism in the ITPA gene for detection in the methods of the invention is the single nucleotide polymorphism 94 C>A (rs 1127354).
  • an ITPA genotype that is indicative of clinical responsiveness to the antifolate therapy is the ITPA 94 CC genotype.
  • adenosine is thought to mediate the antirheumatic effects of MTX via adenosine receptor signaling. Binding of this compound to specific receptors enhances the anti-inflammatory properties of methotrexate.
  • the AMPDl 34C>T mutation generates an AMP-deaminase enzyme with lower activity.
  • AMPDl catalyzes the conversion of adenosine-monophosphate (AMP) to inosine- monophosphate (IMP).
  • AMP is converted to adenosine.
  • deficiency of AMPDl could enhance adenosine release.
  • ITPA inosine triphosphate
  • the method comprises detecting the presence of a polymorphism in each of the genes encoding methylenetetrahydrofolate dehydrogenase (MTHFDl) gene, adenosine monophosphate deaminase (AMPDl), aminoimidazole carboxamide ribonucleotide transformylase (ATIC), and inosine triphosphate pyrophosphatase (ITPA) wherein the presence of a polymorphism in at least one of these four genes is indicative of clinical responsiveness to the antifolate therapy, whereby, the polymorphisms for each of the four genes may be as defined hereinabove.
  • MTHFDl methylenetetrahydrofolate dehydrogenase
  • AMPDl adenosine monophosphate deaminase
  • ATIC aminoimidazole carboxamide ribonucleotide transformylase
  • ITPA inosine triphosphate pyrophosphatase
  • polymorphisms in any of the MTHFDl, AMPDl, ATIC, and ITPA genes may also be used.
  • the polymorphism has a frequency in a population of 1%, 5%, 10%, 20 % or more, and results in an amino acid change resulting in a functional change for the gene product or enzyme, such as an amino acid change with respect to the amino acid sequences of SEQ ID NO: 1 - 4, respectively.
  • functional changes may include e.g. biochemical activity, stability/half-life and interaction with other proteins or compounds.
  • Such methods include, but are not limited to, DNA sequencing, allele specific PCR, PCR amplification followed by an allele/mutant specific restriction digestion, oligonucleotide ligation assays, primer hybridization and primer extension assays, optionally combined with or facilitated by microarray analysis.
  • Alternative methods for determining allelic variants and gene polymorphisms are readily available to the skilled person in the art of molecular diagnostics.
  • Another embodiment is oligonucleotides capable of hybridizing to sequences in or flanking genes (e.g., polymorphic regions) involved in adenosine metabolism, and the use of these oligonucleotides for performing these methods.
  • Primers may be designed to amplify (e.g., by PCR) at least a fragment of a gene encoding an adenosine metabolism- associated enzyme.
  • a polymorphism may be present within the amplified sequence and may be detected by, for example, a restriction enzyme digestion or hybridization assay.
  • the polymorphism may also be located at the 3' end of the primer or oligonucleotide, thus providing means for an allele or polymorphism specific amplification, primer extension or oligonucleotide ligation reaction, optionally with a labeled nucleotide or oligonucleotide.
  • the label may be an enzyme (e.g., alkaline phosphatase, horseradish peroxidase), radiolabel ( 32 P, 33 P, 3 H, 125 1, 35 S etc.), a fluorescent label (Cy3, Cy5, GFP, EGFP, FITC, TRITC and the like) or a hapten/ligand (e.g., digoxigenin, biotin, HA, etc.).
  • the detection is carried out using oligonucleotides physically linked to a solid support, and may be performed in a microarray format.
  • kits comprising one or more oligonucleotides capable of hybridizing to, or adjacent to, any of the polymorphic sites in any of the MTHFDl, AMPDl, ATIC, and ITPA genes as defined hereinabove.
  • the oligonucleotide(s) may be provided in solid form, in solution or attached on a solid carrier such as a DNA microarray.
  • the kit may provide detection means, containers comprising solutions and/or enzymes and a manual with instructions for use.
  • the method further comprises the step of: a) determining the clinical responsiveness to the antifolate therapy by correlating the presence of a polymorphism as defined hereinabove with a predefined responsiveness value associated with each particular polymorphism.
  • a responsiveness score is calculated as the sum of the responsiveness values for each polymorphism.
  • the method further comprises the step of : b) determining a set of clinical parameter values comprising at least one of: i) the gender of the subject and optionally the pre- or postmenopausal status of a female subject; ii) DAS at baseline, wherein DAS is disease activity score as defined by the European League against Rheumatism; iii) the presence or absence of Rheumatoid factor; and, iv) smoking status; and c) determining the predicted clinical responsiveness to the antifolate therapy by correlating the values determined in steps a) and b) with a predefined responsiveness value associated with each particular polymorphism and parameter value.
  • the DAS28 may be used, which is the disease activity score as defined by the European League against Rheumatism based on a swollen joint count of 28 joints.
  • the DAS44 is used, which is a more extensive disease activity score that is based on a swollen joint count of 44 joints.
  • a responsiveness score is calculated as the sum of the responsiveness values for each polymorphism and for each parameter value.
  • the individual responsiveness values for the polymorphisms and clinical parameters may be defined as between 50% and 150%, between 75% and 125%, between 80% and 120% or between 90% and 110% of the values in a) - i): a) 0 for male gender; 1 for female gender; b) 0 for DAS at baseline ⁇ 3.8 ;
  • the individual responsiveness values for the polymorphisms and clinical parameters are defined as between 75% and 125%, between 80% and 120%, between 90% and 110% of the values in a) - i): a) 0 for male gender; 1 for female gender; b) 0 for DAS at baseline ⁇ 3.8 ;
  • a subset of the clinical parameters a) to i) may also be used, in which case it will be understood that the maximum responsiveness score is calculated as the sum of the responsiveness values for each polymorphism and for each parameter value in the subset.
  • a responsiveness score of a subject of 6 or more may indicate that the subject is not responsive to antifolate therapy. Subjects with a responsiveness score of 6 or more are not eligible for antifolate monotherapy and are instead given a combination therapy. A responsiveness score of a subject less than 6 indicates that the subject is eligible for antifolate monotherapy.
  • a subject with a responsiveness score of more than 3.5 but less than 6 indicates that the subject has an intermediate responsiveness to antifolate therapy.
  • Subjects with an intermediate responsiveness to antifolate therapy may be started on antifolate therapy, for example with a weekly dose of about 15 mg MTX or equivalent thereto. After some period of time (e.g.
  • the DAS of the subjects may be established and: a) if a decrease in DAS of more than 1.2 is measured, antifolate monotherapy is continued but the dosage is increased to about 25 mg weekly; or b) if a decrease in DAS of 1.2 or less is measured, antifolate monotherapy is discontinued and combination therapy is started.
  • Subjects with a responsiveness score of 3.5 or less may be started on antifolate monotherapy (e.g., about 15 mg MTX weekly or equivalent thereto), and if necessary (DAS >2.4) after some period of time (e.g. about 3 months) the dosage may be increased to about 25 mg weekly.
  • FIG. 2 shows a schematic example of an embodiment of a computer 10 that may be used in one or more of the embodiments described herein.
  • the computer 10 comprises a processor 12 for performing mathematical operations.
  • the processor 12 is connected to memory units that may store instructions and data, such as a tape unit 13, hard disk 14, a Read Only Memory (ROM) 15, Electrically Erasable Programmable Read Only Memory (EEPROM) 16 and a Random Access Memory (RAM) 17.
  • the processor 12 is also connected to one or more input devices, such as a keyboard 18 and a mouse 19, one or more output devices, such as a display 20 and a printer 21 , and one or more reading units 22 to read, for example, floppy disks 23 or CD ROMs 24.
  • the computer system 10 comprises program lines readable and executable by the processor 12.
  • the computer 10 shown in Figure 2 may also comprise an input output device (I/O) 26 arranged to communicate with other computer systems (not shown) via a communication network 27.
  • sample analyzer 32 is in data communication with the network 27.
  • a local sample analyzer 30 is located proximate the computer 10 and a remote sample analyzer 32 is positioned remote the computer 10 and may be in communication with the computer 10 via the network 27.
  • any number of sample analyzers 30, 32 may be in communication with the computer 10.
  • the system does not include a local sample analyzer 30, but comprises multiple remote sample analyzers 32.
  • a server 40 is also in data communication with the network 27.
  • the server 40 stores data received from the sample analyzer 30,32 and provides this data to the computer 10.
  • the server 40 and/or the sample analyzer 30,32 are configured to perform operations on data determined by the sample analyzer 30,32 in order to determine the predicted responsiveness to antifolate therapy of an subject, such as by using the systems and methods described below.
  • the following description refers to the computer 10 as the device that performs calculations in order to determine the predicted responsiveness of a subject to antifolate therapy.
  • any other computing device such as the sample analyzer 30,32 or the server 40 may also be configured to perform these operations and determine the predicted responsiveness of an subject to antifolate therapy.
  • the computer 10 accesses information and software executing on the server 40 via a graphical user interface, such as a web browser, that is displayed on the display device 20.
  • a graphical user interface such as a web browser
  • the computer 10 provides an interface for viewing, such as by a physician, data from the sample analyzer 30 that is stored on the server 40.
  • the user interface that is displayed on the display device 20 may include data received from the sample analyzer 30 via the network 27.
  • the computer 10 comprises more and/or other memory units, input devices and read devices than are illustrated in Figure 2. Moreover, one or more of them may be physically located remote from the processor 12, if required.
  • the exemplary processor 12 is shown as one box, but may comprise several processing units functioning in parallel or controlled by one main processor unit that may be located remote from one another, as is known to persons skilled in the art.
  • the computer 10 is shown as a computer system, but can be any signal processing system with analog and/or digital and/or software technology arranged to perform the functions discussed herein.
  • the detailed description as given above for the computer 10 may refer to several kind of devices, such as personal computers, servers, laptops, personal digital assistance (PDA), palmtops. All of these devices are different kinds of computer systems.
  • PDA personal digital assistance
  • the memory units 13, 14, 15, 16, 17 may comprise program lines readable and executable by the processor 12.
  • the programming lines may be such that they provide the computer 10 with the functionality to perform one or more of the methods described below.
  • the computer 10 may be connected to a sample analyzer 30, 32 by a communication link.
  • the sample analyzer 30, 32 may be arranged to receive a blood sample, or other biological sample, from an individual and perform measurements on this blood sample.
  • the sample analyzer 30, 32 may, for example, be arranged to determine a set of clinical parameter values from the blood sample including: i) the gender of the subject and, optionally, the pre- or postmenopausal status of a female subject; ii) DAS at baseline, wherein DAS is disease activity score as defined by the European League against Rheumatism; the presence or absence of Rheumatoid factor; iii) smoking status; iv) the presence or absence of Rheumatoid factor; and/or v) one or more the polymorphisms/genotypes defined hereinabove.
  • the computer 10 is arranged for receiving data-signals relating to measurements of a blood sample from the sample analyzer 30, 32 so as to determine clinical parameter values for a set of clinical parameters, such as the parameters i) - v) noted above.
  • the connection between the computer 10 and the sample analyzer 30 comprises a wired and/or wireless two-way communication link, such as via a direct wired or wireless connection 32 or via the network 27.
  • the computer 10 may also comprise multiple connections, each to one of the different sample analyzers 30.
  • the computer 10 may be arranged to read the at least one clinical parameter as determined by the sample analyzer 30, 32, and store the at least one clinical parameter in the memory units 13, 14, 15, 16, 17.
  • the computer 10 may also determine the at least one clinical parameter by reading the at least one clinical parameter from memory 13, 14, 15, 16, 17, or from input devices, such as keyboard 18 and mouse 19, or from one or more reading units 22 to read for instance floppy disks 23 or CD ROMs 24.
  • fewer or additional further clinical parameters may be received by the computer 10 and used to determine the predicted responsiveness to antifolate therapy.
  • the further clinical parameter values are entered into the computer 10 using one or more input devices, such as a keyboard and/or a mouse, in response to information displayed in a graphical user interface that is displayed on the display device 20.
  • a graphical user interface may be configured to prompt a user to enter each of a plurality of clinical parameter values.
  • each of the entered clinical parameter values is used to determine the predicted responsiveness to antifolate therapy.
  • selected clinical parameter values are used to determine the predicted responsiveness to antifolate therapy.
  • a confidence level in the predicted responsiveness increases as the number of clinical parameter values that are entered into the graphical user interface, and are processed by the computer 10, increases.
  • the confidence level of the predicted responsiveness may increase as additional clinical parameter values are received and considered in determining the predicted responsiveness.
  • the computer 10 may be arranged to read these further parameter values from memory 13, 14, 15, 16, 17, from input devices, such as keyboard 18 and mouse 19, or from one or more reading units 22 to read, for example, floppy disks 23 or CD ROMs 24.
  • the computer 10 may be arranged to determine the predicted responsiveness of an subject to antifolate therapy by correlating at least two of the clinical parameter values with a predefined responsiveness value associated with each particular parameter value.
  • the responsiveness score may be outputted by the computer 10 using one or more output devices, such as display 20 and printer 21.
  • computer 10 may be arranged for transmission of the predicted responsiveness value over the network 27 to another computer system (not shown).
  • the predicted responsiveness is transmitted to a remote computing system and displayed to a user via a graphical user interface.
  • the predicted responsiveness is transmitted via e-mail to the individual, a physician, and/or another computing system.
  • the predicted responsiveness may be transmitted via facsimile or printed and delivered to the individual and/or physician.
  • the responsiveness values associated with each of the clinical parameter values and the total responsiveness value or score for the individual are also transmitted from the computer 10 to another computing device.
  • the predicated responsiveness is stored on the server 40 and is accessible to users with proper authorization to view the predicted responsiveness, such as the subject and the subject's healthcare providers.
  • Figure 3 schematically depicts a flow diagram of a procedure as may be executed by computer 10, or other computing device, according to an embodiment described herein. Depending on the embodiment, certain of the actions described below may be removed, others may be added, and the sequence of actions may be altered. [0054] In a first action 100, the computer 10 starts executing the procedure. This action may be triggered, for example, by input from a user into a graphical user interface displayed on the display device 20.
  • the computer 10 determines at least one clinical parameter using sample analyzer 30, 32.
  • This action may comprise the steps of 101a) the processor 12 requesting the sample analyzer 30, 32 to output data-signals relating to the measured values of a blood sample to the processor 12; 101b) the processor 12 receiving the data-signals, and 101c) the processor 12 (optionally) storing the data-signals relating to the measured values in memory 13, 14, 15, 16, 17.
  • the data-signals that are received from the sample analyzer 30, 32 comprise parameter values associated with each of one or more clinical parameters, such as, for example, a parameter value indicating a polymorphism or genotype as defined hereinabove and a parameter value indicating the presence or absence of Rheumatoid factor in the sample (e.g., blood sample).
  • action 101a) may also comprise that the processor 12 requests the sample analyzer 30, 32 to perform certain measurements on the sample (e.g., blood sample) relating to determining a set of clinical parameter values, such as clinical parameters values for clinical parameters i) - v) discussed above before transmitting the data- signals.
  • the processor 12 determines at least one of the further clinical parameter values using one or more input devices as described above, or alternatively, from associated data already stored in memory 13, 14, 15, 16, 17.
  • the further clinical parameter values may be entered into a computing device, such as computer 10, via a graphical user interface.
  • the further clinical parameter values are entered into the computer 10 by a caregiver in response to comments from the individual.
  • a user interface is accessible to the individual via a computer in communication with the network, so that the individual may enter the further clinical parameter values for use in this method.
  • the computer 10 determines the predicted responsiveness of a subject to antifolate therapy by correlating each of at least two of the clinical parameter values and further clinical parameter values determined in action 101 and 102 above with predefined responsiveness values that are associated with each particular parameter value. These responsiveness values may then be combined in order to determine a total responsiveness value or score for the individual. Finally, the total responsiveness value or score may be associated with the predicted responsiveness of a subject to antifolate therapy.
  • ranges of values for each of the clinical parameter values are associated with particular responsiveness values.
  • responsiveness values for particular clinical parameters are determined according to formulas specific to each clinical parameter.
  • the total responsiveness value or responsiveness score is the sum of each of the responsiveness values that have been associated with the clinical parameter values. In other embodiments, the total responsiveness value may be calculated using only a portion of the responsiveness values.
  • ranges of total responsiveness values are each associated with the responsiveness of the subject to antifolate therapy.
  • the number of ranges of total responsiveness values and the granularity of the predicted responsiveness associated with the ranges may vary depending on the application. For example, in one embodiment only two ranges of total responsiveness values are used, where total responsiveness values that are within a first range are associated with predicted responsiveness indicating that an individual is likely to respond to antifolate therapy, and total responsiveness values that are within a second range are associated with predicted responsiveness indicating that the individual is not likely to respond to antifolate therapy. In another embodiment, total responsiveness values are associated with one of three predicted responsivenesses, such as low, intermediate, and high responsiveness to antifolate therapy.
  • total responsiveness values are each associated with one of a plurality, such as 5, 10, 15, or 20, for example, of different predicted responsiveness scores.
  • the predicted responsiveness scores are expressed as a percentage chance that the individual will respond to antifolate therapy.
  • the predicted responsiveness is determined based on a formula in which the total responsiveness value is a factor.
  • ranges of total responsiveness values may not be necessary as each total responsiveness value may result in a different predicted responsiveness.
  • the predefined responsiveness values associated with parameter values, or ranges of parameter values may be stored in memory 13, 14, 15, 16, 17 and retrieved from memory 13, 14, 15, 16, 17 by the processor 12, or may be received using input devices as described above.
  • the computer 10 outputs the computed predicted responsiveness of a subject to antifolate therapy using one or more output devices, such as display 20 and printer 21, or by transmission of the computed predicted responsiveness to another computer system (not shown), such as via email or storage of the predicted responsiveness on a server that is accessible to other users. Also, the computer 10 may store the computed predicted responsiveness, and/or the responsiveness values and total responsiveness values, in memory 13, 14, 15, 16, 17 or on the server 40.
  • action 105 the execution of procedure ends. If needed, the procedure may be resumed at action 101 to execute once more.
  • the sample analyzer 30, 32 and/or the server 40 comprises a computer, having the components such as those described above with reference to computer 10, that is configured to perform the procedure described in Figure 3.
  • the sample analyzer 30, 32 and/or server 40 are capable of computing the antifolate responsiveness score of a subject by correlating at least two of the clinical parameter values determined above with a predefined responsiveness value associated with each particular parameter value.
  • One embodiment relates to a method for determining a predicted responsiveness of a subject to antifolate therapy, the method comprising: a) receiving characteristics of a subject, the characteristics comprising at least two of: a polymorphism as defined in hereinabove, and an indicator of a presence or absence of Rheumatoid factor in a blood sample from the subject; b) assigning a responsiveness value to each of the characteristics; and, c) determining a predicted responsiveness of the subject to antifolate therapy, the predicted responsiveness being determined based at least partly on the determined responsiveness values.
  • at least some of the characteristics may be received from a blood sample analyzer.
  • the received characteristics include indicators of least one of: i) the gender of the subject and optionally the pre- or postmenopausal status of a female subject; ii) DAS at baseline, wherein DAS is disease activity score as defined by the European League against Rheumatism; and, iii) smoking status.
  • at least some of the characteristics are entered into a user interface that communicates the characteristics via one or more networks.
  • the method may further comprise transmitting the predicted responsiveness via email, and may further comprise transmitting the predicted responsiveness to a server that is accessible to authorized users.
  • the authorized users may comprise at least one of the subject and a healthcare provider for the subject.
  • the assigning may comprise accessing data in a computer memory associating responsiveness values with characteristics. In the method, the determined predicted responsiveness is expressed as a percentage chance that the subject responds to antifolate therapy.
  • Another embodiment relates to a system for determining a predicted responsiveness of an subject to antifolate therapy, comprising: a) means for receiving characteristics of a subject, the characteristics comprising at least two polymorphisms described herein, and an indicator of a presence or absence of Rheumatoid factor in a blood sample from the subject; b) means for assigning a responsiveness value to each of the characteristics; and, c) means for determining a predicted responsiveness of the subject to antifolate therapy, the predicted responsiveness being determined based at least partly on the determined responsiveness values.
  • a system for determining a predicted responsiveness of an subject to antifolate therapy comprising: a) a blood sample analyzer configured to analyze a blood sample provided by the individual and determine at least two polymorphisms as described herein, and an indicator of a presence or absence of Rheumatoid factor in a blood sample from the subject; and, b) a computing device configured to assign a responsiveness value to each of the indicators determined by the blood sample analyzer, wherein the computing device accesses data stored in a memory associating ranges of values for each of the indicators with respective responsiveness values, the computing device further configured to determine a predicted responsiveness of the subject to antifolate therapy based at least partly on the assigned responsiveness values.
  • the blood sample analyzer may be located remote from or proximate to the computing device and the indicators may be transmitted to the computing device via a network communication link.
  • the computing device may be further configured to transmit one or more electronic messages indicating the determined predicted responsiveness.
  • the computing device may receive the indicators via a web interface in data communication with the computing device.
  • the computing device may be further configured to assign a risk value to indicators indicating at least one of: i) the gender of the subject and optionally the pre- or postmenopausal status of a female subject; ii) DAS at baseline, wherein DAS is disease activity score as defined by the European League against Rheumatism; and iii) smoking status.
  • the 205 patients enrolled in this study comprised a subcohort of the 508 patients who participated in the BeSt study.
  • Responders were defined as patients with a DAS of ⁇ 2.4 (good clinical response) based on EULAR response criteria and using MTX at 6 months (24; 25).
  • Non- responders were defined as patients with a DAS of >2.4 at the 6-month follow up visit and using MTX.
  • 19 patients were missing for efficacy analyses; 2 patients moved, 1 patient refused to take MTX after short usage without having adverse drug events (ADEs), 5 patients did not have their DAS assessed, 1 patient started on sulfasalazine before evaluation, 10 patients had discontinued MTX permanently after experiencing ADEs. Consequently, 186 remained eligible for MTX efficacy evaluation at 6 months. Patients experiencing ADEs, but still treated with MTX at 6 months, were included in the analysis.
  • Baseline variables possibly influencing the patient's disease state and MTX response were selected on the basis of literature.(10-18; 21; 22; 26; 27). The following factors were identified: gender; rheumatoid factor status; age; duration of joint complaints; alcohol consumption; smoking; body mass index; menopausal status; hormone supplementation; VAS for physician's assessment of disease activity, for pain, for patient's assessment of disease activity, for patient's assessment of global health, for morning stiffness; Health assessment questionnaire (HAQ); ESR; C-reactive protein (CRP); DAS; SJC; RAI; kidney function (defined as creatinine clearance); anti-cyclic citrullinated peptide status (CCP); NSAID use and the existence of co-morbidity based on drug use (other than RA disease- related drugs). The CCP assay was not performed for all patients at the time of inclusion in the BeSt study. As CCP status is unlikely to change with treatment (27), the CCP status after beginning treatment was also used. Selection of
  • SNPs single nucleotide polymorphisms in 13 candidate genes related to MTX mechanism of action, purine and pyrimidine synthesis (28-30), were selected taking the following criteria into consideration (31; 32): validated SNP, SNP -preferably- causes non- synonymous amino acid change, indications for clinical relevance from previous publications and a preferred minimal genotype frequency of approximately 10%. (19-21; 33- 46)
  • Genotyping techniques, success rates and genotype frequencies of 10 out of the 17 SNPs in this population together with their association with MTX response were previously reported (19; 20). These SNPs were in genes encoding adenosine monophosphate deaminase (AMPDl), aminoimidazole carboxamide ribonucleotide transformylase (ATIC), inosine triphosphate pyrophosphatase (ITPA), methionine synthase (MTR), and methionine synthase reductase (MTRR), dihydrofolate reductase (DHFR), methylenetetrahydrofolate reductase (MTHFR) and the reduced folate carrier (RFC).
  • AMPDl adenosine monophosphate deaminase
  • ATIC aminoimidazole carboxamide ribonucleotide transformylase
  • IPA inosine triphosphate pyrophosphatase
  • MTR methionine
  • MTHFR 677OT (rsl801133), MTHFR 1298A>C (rsl801131), DHFR -473 G>A (DNA alignment, rsl650697), DHFR 35289A>G (DNA alignment, rsl232027), RFC 80G>A (rslO51266), MTRR 66A>G (rsl801394), MTR 2756A>G (rsl805087), AMPDl 34C>T (rsl7602729), ITPA 94C>A (rsl 127354) and ATIC 347OG (rs2372536).
  • SNPs were de novo genotyped for this analysis in our population. These SNPs were in genes encoding methylenetetrahydrofolate dehydrogenase (MTHFDl), serine hydroxymethyltransferase (SHMTl), folylpolyglutamate synthase (FPGS), gamma- glutamyl hydrolase (GGH) and thymidylate synthetase (TYMS).
  • MTHFDl methylenetetrahydrofolate dehydrogenase
  • SHMTl serine hydroxymethyltransferase
  • FPGS folylpolyglutamate synthase
  • GGH gamma- glutamyl hydrolase
  • TYMS thymidylate synthetase
  • the SNPs were MTHFDl 1958G>A (rsl 7850560), SHMTl 1420OT (rsl 7829445), TYMS 28bp-tandem repeat polymorphism in the promoter region, FPGS 114G>A (rsl0760502), FPGS 1994A>G (DNA alignment, rsl0106), GGH 452OT (rsl 1545078) and GGH 16T>C (rsl800909).
  • PCR Real-time polymerase chain reaction using the Taqman technique were used in genotyping MTHFDl and SHMTl. Both assays were performed according to protocols provided by the manufacturer (Taqman, Applied Biosystems, Foster City, CA).
  • FPGS and GGH SNPs were genotyped using the Pyrosequencer method and protocols (Uppsala, Sweden). Double (2R2R) or triple (3R3R) 28bp-tandem repeats in the promoter region of the TYMS gene were visualized on agarose gels directly after the PCR reaction.
  • Genotype distributions for MTHFDl 1958G>A were: 29%GG, 50%GA, 22%AA; for SHMTl: 1420OT 54%CC, 42%CT, 4%TT; for FPGS: 114G>A 49%GG, 45%GA, 6%AA; for FPGS: 1994A>G 31%AA, 48%GA, 21%GG; for GGH: 452C>T 83%CC, 17%CT; for GGH: 16T>C 53%TT, 39%CT, 7%CC; and for TYMS 28-bp repeats: 31% 3R3R, 48% 2R3R, 21% 2R2R, 0.4% 2R6R, respectively.
  • the exponential of the regression coefficient, eB is an estimate of the adjusted odds ratio.
  • the estimated probability for response was calculated for each individual patient with a set of variable values.
  • a receiver-operating characteristic (ROC) curve was derived to evaluate the discriminative performance of the model. Cross-validation was performed to control for overfitting (48).
  • Weighted scores for the simplified model were assigned by rounding the regression coefficients in the final model to the nearest number ending in .5 or .0. Negative regression coefficients were inverted to obtain only positive weighted scores. Categories within a variable were grouped if regression coefficients led to identical scores. The calculated scores per individual were compared with the observed responses to MTX. Higher calculated scores reflect higher probability of non-response to MTX. Several clinical score cutoff levels that represent approximately >0.80 or ⁇ 0.20 probability of response were chosen to classify patients as nonresponders, intermediate or responders. The true positive rate and true negative response rates were calculated. All statistical analyses were performed using SPSS 11.5 software (SPSS Inc., Chicago, IL). Results
  • Rf positive and Rf negative patients were divided into 2 additional groups by smoking status. Between age and gender no significant interaction was found. However, gender and menopausal status were combined into a new variable with three categories based on a biological rationale: male, premenopausal female and postmenopausal female. Therefore, the total number of non-genetic variables selected for the multivariate analysis was 15.
  • Table 2 displays the comparison of wild type and/or mutant allele carriers for the de novo genotyped SNPs between responders and nonresponders. Only MTHFDl 1958A>G, which compared the G-allelic carriers versus the homozygous mutant AA genotypes, showed a difference between responders and nonresponders. In addition, 3 out of the 10 previously genotyped SNPs were associated with MTX good clinical response at 6 months. These SNPs were AMPDl 34C>T, ITPA 94C>A and ATIC 347OG (20). Specifically, the AMPDl 34T-allele carriers, the ITPA CC genotyped and the ATIC 347 CC genotyped were more likely to achieve good clinical response. Thus, 4 SNPs were selected for the subsequent multivariate analysis. Multivariate Analysis Of Baseline Variables In Relation To MTX Monotherapy Efficacy
  • the independent predicting variables resulting from stepwise selection procedure were gender; Rf status; smoking; DAS at baseline; SJC; HAQ; and 4 polymorphisms in AMPDl, ATIC, ITPA and MTHFDl genes. Since the SJC is a composite measure of the DAS, there is a large correlation between these two variables. Adding DAS at baseline and SJC variables in the model yielded, due to colinearity, coefficients which are difficult to interpret. The HAQ also showed coefficients which are difficult to interpret. This is likely to be due to the strong correlations between HAQ and DAS as described previously (49). These coefficients did not allow HAQ and SJC to be entered simultaneously with DAS at baseline in the model.
  • the definite model to obtain a simple pharmacogenetic score for MTX monotherapy efficacy consisted of the independent variables gender, Rf status, smoking status, DAS at baseline and 4 polymorphisms in the AMPDl, ATIC, ITPA and MTHFDl genes. All factors were significantly (p ⁇ 0.05) associated with MTX response at 6 months, and the model had an explained variance (Cox and Snell R2) of 35%.
  • the probability of response was converted into a simplified clinical score.
  • the regression coefficients of the logistic regression model and the assigned points per variable for the simplified prediction are listed in Table 3.
  • the scores in our population ranged between 0 and 9.5, with a lower score reflecting a higher probability of response to MTX.
  • the cutoff values were set at ⁇ 3.5 points for responders and >6 points for nonresponders.
  • the score of ⁇ 3.5 had a true positive rate of 95%.
  • the true positive rate reflects the proportion of patients with a high probability for MTX efficacy that were true responders.
  • a score of >6 had a true negative response rate of 86%.
  • Patients were eligible for the replication cohort if they fulfilled the ACR 1987 criteria for RA, started with MTX monotherapy, had not been treated previously with DMARDs other than antimalarial agents, and had disease duration of less than 2 years. In addition, clinical data comprising the prediction model and DNA samples had to be available.
  • 352 patients were recorded as having received MTX at any time point. Of these 352 patients, only 36 received MTX monotherapy as their primary DMARD for more than 6 months. Twenty- four of these 36 patients were used for validation of the clinical model; the other 12 patients were excluded because no DNA was available, poor quality DNA was available, or prednisone was prescribed as additional therapy in doses ⁇ lO mg.
  • the true positive response rate for this cohort was 70% (7 of 10 patients; 95% CI 35-93%), and the true negative response rate was 72% (13 of 18 patients; 95% CI 47-90%).
  • 28 patients (68%) were categorized as responders and nonresponders, whereas 10 patients (32%) were categorized as intermediate responders.
  • NSAIDs use (%) 100 100 -
  • M2 ⁇ ff ⁇ >l methylenetetrahydro folate dehydrogenase
  • SHMTl serine hydro xymethyltransferase
  • FPGS folylpolyglutamate synthase
  • GGH gamma-glutamyl hydrolase
  • TYMS thymidylate synthetase.
  • B regression coefficient in the definite model
  • OR odds ratio
  • 95%C.I. 95% confidence interval
  • M2 ⁇ ff ⁇ >/ methylenetetrahydro folate dehydrogenase
  • AMPDl adenosine monophosphate deaminase
  • ATIC aminoimidazole carboxamide ribonucleotide transformylase
  • ITPA inosine triphosphate pyrophosphatase. * Higher scores represent higher probability of non-response to MTX.
  • Nonresponders were defined as patients with a DAS of >2.4 with MTX therapy at 6 months, responders were defined as patients with a DAS of ⁇ 2.4 with MTX therapy at 6 months
  • Nonresponders defined as prediction derived score > 6, intermediate responders defined as predicting derived score >3.5, but ⁇ 6.
  • Responders defined as prediction derived score ⁇ 3.5. Cutoff levels were chosen based on the clinical score which represent probabilities of response to MTX of approximately >0.80 and ⁇ 0.20. Two patients are missing since their genotyping was incomplete.
  • Nonresponders were defined as patients with a DAS of >2.4 with MTX therapy at 6 months, responders were defined as patients with a DAS of ⁇ 2.4 with MTX therapy at 6 months.
  • Cutoff levels were chosen based on the clinical score which represent probabilities of response to MTX of approximately >0.80 and ⁇ 0.20.
  • AICA- ribosiduria a novel, neurologically devastating inborn error of purine biosynthesis caused by mutation of ATIC. Am. J. Hum. Genet. 2004; 74(6): 1276-1281.
  • A66G polymorphism is a novel genetic determinant of plasma homocysteine concentrations. Atherosclerosis 2001; 157(2):451-456.

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Abstract

L'invention concerne des procédés pharmacogénétiques permettant de déterminer une réactivité prévue à une thérapie antifolique chez des sujets atteints d'une arthrite indifférenciée récente. Ces procédés reposent sur la détermination d'un ensemble de valeurs de paramètres cliniques et consistent à déterminer une réactivité prévue à une thérapie antifolique par corrélation desdites valeurs de paramètres avec des valeurs de réactivité prédéfinies associées à des plages de valeurs de paramètres. Des valeurs de paramètres déterminantes pour la réactivité à une thérapie antifolique peuvent comprendre des polymorphismes dans le gène de la méthylène tétrahydrofolate déshydrogénase (MTHFD1), ainsi que dans trois gènes impliqués dans la voie de libération d'adénosine, la présence ou l'absence de facteurs rhumatoïdes, le sexe, le statut préménopausique ou postménopausique et/ou le statut de fumeur.
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KRAJINOVIC M ET AL: "PHARMACOGENETICS OF METHOTREXATE", PHARMACOGENOMICS, ASHLEY PUBLICATIONS, GB, vol. 5, no. 7, 1 January 2004 (2004-01-01), pages 819 - 834, XP009075358, ISSN: 1462-2416, DOI: 10.1517/14622416.5.7.819 *
MATSUZAKI HAJIME ET AL: "GENOTYPING OVER 100,000 SNPS ON A PAIR OF OLIGONUCLEOTIDE ARRAYS", NATURE METHODS, NATURE PUBLISHING GROUP, GB, vol. 1, no. 2, 1 November 2004 (2004-11-01), pages 109 - 111, XP009082656, ISSN: 1548-7091, DOI: 10.1038/NMETH718 *
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