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WO2012094366A1 - Microarn circulants utilisés comme biomarqueurs pour les coronaropathies - Google Patents

Microarn circulants utilisés comme biomarqueurs pour les coronaropathies Download PDF

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Publication number
WO2012094366A1
WO2012094366A1 PCT/US2012/020140 US2012020140W WO2012094366A1 WO 2012094366 A1 WO2012094366 A1 WO 2012094366A1 US 2012020140 W US2012020140 W US 2012020140W WO 2012094366 A1 WO2012094366 A1 WO 2012094366A1
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mir
hsa
subject
dataset
cad
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Heng Tao
Philip Beineke
James A. Wingrove
Steven Rosenberg
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CardioDX Inc
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CardioDX Inc
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    • 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
    • C12Q2600/156—Polymorphic or mutational markers
    • 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
    • C12Q2600/158—Expression markers
    • 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
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the invention relates to methods of identifying subjects at risk of coronary artery disease (CAD) based on MicroRNA (miRNA) marker expression data; and to computer systems, kits, and software for their implementation.
  • CAD coronary artery disease
  • miRNA MicroRNA
  • CAD chronic coronary artery disease
  • chronic stable angina affects 16.5 million patients in the United States and is diagnosed in approximately 500,000 new patients annually (1). Even more new patients are evaluated for chest pain or other symptoms that suggest CAD, but CAD is ultimately diagnosed in less than one-half of these (2- 4).
  • the clinical evaluation of patients with suspected CAD varies and includes diagnostic tests with varying levels of accuracy, reproducibility, ease of use, and potential for patient morbidity (5). Many patients who present with symptoms suggesting CAD are tested with invasive diagnostic coronary angiography despite the widespread availability of noninvasive diagnostic methods, but are not diagnosed as having CAD (6).
  • a method for diagnosing CAD coupling good diagnostic accuracy with low patient burden would thus be beneficial.
  • Coronary artery disease has a strong inflammatory component, and it is likely that the changes in gene expression observed are in response to inflammatory processes occurring at the site of inflammation, e.g., the coronary lesion.
  • Inflammatory signals e.g., chemokines or other proteins
  • circulating cells may directly interact with arterial cells at the lesion, resulting in gene expression changes.
  • miRNAs are small (e.g., 21-22 nucleotide) RNAs involved in regulating gene expression in a variety of tissues. miRNAs have been shown to be present in the circulation and can act as diagnostic markers for a variety of diseases (7). Thus, it is possible that circulating miRNAs are also diagnostic for CAD; as such we investigated whether or not we could detect changes in RNA expression levels of circulating miRNAs in response to the presence of CAD.
  • CAD coronary artery disease
  • a method for identifying a subject at risk of coronary artery disease comprising: obtaining a first dataset associated with a sample obtained from the subject, wherein the first dataset comprises quantitative expression data for a MicroRNA (miRNA) marker selected from Table 8; and analyzing the first dataset to determine the expression level of the miRNA marker, wherein the expression level of the miRNA marker positively or negatively correlates with an increased risk of CAD in the subject.
  • miRNA MicroRNA
  • the first dataset comprises quantitative expression data for at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more miRNA markers selected from Table 8.
  • the analysis further comprises comparing the first dataset to a second dataset associated with a control sample, wherein the second dataset comprises quantitative expression data for a control miRNA marker, and wherein a statistically significant difference between expression of the miRNA marker and expression of the control miRNA marker indicates an increased risk of CAD in the subject.
  • the control sample is associated with a control subject or with a control population.
  • expression of the miRNA marker is significantly decreased compared to expression of the control miRNA marker.
  • expression of the miRNA marker is significantly increased compared to expression of the control miRNA marker.
  • the statistically significant difference is determined using linear regression analysis.
  • the control sample is associated with a control subject or a control population characterized by absence of stenosis in any major coronary artery.
  • the expression level of the miRNA marker positively correlates with an increased risk of CAD in the subject. In some embodiments, the expression level of the miRNA marker negatively correlates with an increased risk of CAD in the subject.
  • the subject is male. In some embodiments, the subject is female.
  • the method is implemented on one or more computers.
  • the first dataset is obtained stored on a storage memory.
  • obtaining the first dataset associated with the sample comprises obtaining the sample and processing the sample to experimentally determine the first dataset.
  • obtaining the first dataset associated with the sample comprises receiving the first dataset directly or indirectly from a third party that has processed the sample to experimentally determine the first dataset.
  • the method includes rating CAD risk as low, medium, or high based on the analysis.
  • the quantitative expression data is obtained from a nucleotide -based assay. In some embodiments, the quantitative expression data is obtained from an RT-PCR assay, a sequencing-based assay, or a microarray assay.
  • the subject is a human subject.
  • the method further includes assessing an mRNA marker in the subject; and combining the assessment with the analysis of the first dataset to identify risk of CAD in the subject.
  • the mRNA marker is selected from the group consisting of: AF161365, HNRPF, ACBD5, TFCP2, DDX18, AF289562, CD248, CD79B, CD19, SPIB, BLK, CD3D, LCK, TMC8, CCT2, S100A12, MMP9, CLEC4E, ALOX5AP, S100A8, NAMPT, RPL28, SSRP1, AQP9, GLT1D1, NCF4, NCF2, CASP5, H3F3B, IL18RAP, TXN, TNFAIP6, PLAUR, IL8RB, BCL2A1, TNFRSF10C, PTAFR, KCNE3, LAMP2, TLR4, TYROBP, SLAMF7, CX3CR1, KLRC4, and CD8
  • the method further includes assessing a SNP marker in the subject; and combining the assessment with the analysis of the first dataset to identify risk of CAD in the subject.
  • the method further includes assessing a clinical factor in the subject; and combining the assessment with the analysis of the first dataset to identify risk of CAD in the subject.
  • the clinical factor is selected from the group consisting of: age, gender, chest pain type, neutrophil count, ethnicity, disease duration, diastolic blood pressure, systolic blood pressure, a family history parameter, a medical history parameter, a medical symptom parameter, height, weight, a body-mass index, resting heart rate, and smoker/non-smoker status.
  • Also described herein is a method for determining CAD risk in a subject, comprising: obtaining a sample from the subject, wherein the sample comprises a miRNA marker selected from Table 8; contacting the sample with a reagent; generating a complex between the reagent and the miRNA marker; detecting the complex to obtain a first dataset associated with the sample, wherein the first dataset comprises quantitative expression data for the miRNA marker; and analyzing the first dataset to determine the expression level of the miRNA marker, wherein the expression level of the miRNA marker positively or negatively correlates with an increased risk of CAD in the subject.
  • the first dataset comprises quantitative expression data for at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more miRNA markers selected from Table 8.
  • a computer-implemented method for identifying a subject at risk of a CAD comprising: storing, in a storage memory, a first dataset associated with a sample obtained from the subject, wherein the first dataset comprises quantitative expression data for a miRNA marker selected from Table 8; and analyzing, by a computer processor, the first dataset to determine the expression level of the miRNA marker, wherein the expression level of the miRNA marker positively or negatively correlates with an increased risk of CAD in the subject.
  • the first dataset comprises quantitative expression data for at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more miRNA markers selected from Table 8.
  • the computer-implemented method can be used to implement a method for identifying a subject at risk of CAD described herein.
  • a system for quantifying CAD risk in a subject comprising: a storage memory for storing a first dataset associated with a sample obtained from the subject, wherein the first dataset comprises quantitative expression data for a miRNA marker selected from Table 8; and a processor communicatively coupled to the storage memory for analyzing the first dataset to determine the expression level of the miRNA marker, wherein the expression level of the miRNA marker positively or negatively correlates with an increased risk of CAD in the subject.
  • the first dataset comprises quantitative expression data for at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more miRNA markers selected from Table 8.
  • the system can be used to implement a method for identifying a subject at risk of CAD described herein.
  • a computer-readable storage medium storing computer- executable program code, the program code comprising: program code for storing a first dataset associated with a sample obtained from a subject, wherein the first dataset comprises quantitative expression data for a miRNA marker selected from Table 8; and program code for analyzing the first dataset by comparing the first dataset to determine the expression level of the miRNA marker, wherein the expression level of the miRNA marker positively or negatively correlates with an increased risk of CAD in the subject.
  • the computer-readable storage medium can be used to implement a method for identifying a subject at risk of CAD described herein.
  • kits for use in quantifying CAD risk in a subject comprising: a set of reagents comprising a plurality of reagents for determining from a sample obtained from the subject quantitative expression data for a miRNA marker selected from Table 8; and instructions for using the plurality of reagents to determine quantitative expression data from the sample and analyzing the first dataset by comparing the first dataset to determine the expression level of the miRNA marker, wherein the expression level of the miRNA marker positively or negatively correlates with an increased risk of CAD in the subject.
  • the instructions further comprise instructions for conducting a nucleotide-based assay.
  • the quantitative expression data comprises data for at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more miRNA markers selected from Table 8.
  • the kit can be used to implement a method for identifying a subject at risk of CAD described herein.
  • kits for use in quantifying CAD risk in a subject comprising: a set of reagents consisting essentially of a plurality of reagents for determining from a sample obtained from the subject quantitative expression data for a miRNA marker selected from Table 8; and instructions for using the plurality of reagents to determine quantitative expression data from the sample.
  • the instructions further comprise instructions for conducting a nucleotide-based assay.
  • the quantitative expression data comprises data for at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more miRNA markers selected from Table 8.
  • the kit can be used to implement a method for identifying a subject at risk of CAD described herein.
  • acute coronary syndrome encompasses all forms of unstable coronary artery disease.
  • coronary artery disease or "CAD” encompasses all forms of atherosclerotic disease affecting the coronary arteries.
  • Ct refers to cycle threshold and is defined as the PCR cycle number where the fluorescent value is above a set threshold. Therefore, a low Ct value corresponds to a high level of expression, and a high Ct value corresponds to a low level of expression.
  • Cp refers to the crossing point and is defined as the intersection of the best fit of the log-linear portion of a standard's amplification curve in a real time PCR instrument such as, e.g., a LightCycler, and the noise band (set according to background fluorescence measurements).
  • marker encompass, without limitation, miRNAs, lipids, lipoproteins, proteins, cytokines, chemokines, growth factors, polypeptides, nucleic acids, RNA, DNA, genes, and oligonucleotides, together with their related complexes, metabolites, mutations, variants, polymorphisms, modifications, fragments, subunits, degradation products, elements, and other analytes or sample-derived measures.
  • a marker can also include mutated proteins, mutated nucleic acids, variations in copy numbers, and/or transcript variants.
  • a marker is a miRNA marker.
  • highly correlated miRNA marker expression or “highly correlated marker expression” refer to two or more marker expression values that have a sufficient degree of correlation to allow their interchangeable use in some embodiments of methods for identifying subjects at risk of CAD.
  • highly correlated marker y having expression value Y can be substituted for miRNA marker x in a straightforward way readily apparent to those having ordinary skill in the art and the benefit of the instant disclosure.
  • Highly correlated markers can be identified using methods known in the art, e.g., a Pearson correlation.
  • highly correlated marker or “highly correlated substitute marker” refer to markers that can be substituted with the original marker of interest based on, e.g., the above criteria.
  • a highly correlated substitute marker can be used, e.g., by substitution of the highly correlated substitute marker(s) for the original marker(s) of interest.
  • mammal encompasses both humans and non-humans and includes but is not limited to humans, non-human primates, canines, felines, murines, bovines, equines, and porcines.
  • human generally refers to Homo sapiens.
  • myocardial infarction refers to an ischemic myocardial necrosis. This is usually the result of abrupt reduction in coronary blood flow to a segment of the myocardium, the muscular tissue of the heart. Myocardial infarction can be classified into ST-elevation and non-ST elevation MI (also referred to as unstable angina). Myocardial necrosis results in either classification. Myocardial infarction, of either ST-elevation or non- ST elevation classification, is an unstable form of atherosclerotic cardiovascular disease.
  • sample can include an RNA, a single cell or multiple cells or fragments of cells or an aliquot of body fluid, taken from a subject, by means including venipuncture, excretion, swabbing, ejaculation, massage, biopsy, needle aspirate, lavage sample, scraping, surgical incision, or intervention or other means known in the art.
  • subject encompasses a cell, tissue, or organism, human or non-human, whether in vivo, ex vivo, or in vitro, male or female.
  • expression data refers to a value that represents a direct, indirect, or comparative measurement of the level of expression of a nucleotide (e.g., RNA or DNA) or polypeptide.
  • expression data can refer to a value that represents a direct, indirect, or comparative measurement of the RNA expression level of a miRNA marker of interest.
  • the term "obtaining a dataset associated with a sample” or "obtaining a first dataset associated with a sample” encompasses obtaining a set of data determined from at least one sample. Obtaining a dataset encompasses obtaining a sample, and processing the sample to experimentally determine the data. The phrase also encompasses receiving a set of expression data directly or indirectly, e.g., from a third party that has processed the sample to experimentally determine the dataset. Additionally, the phrase encompasses mining data from at least one database or at least one publication or a combination of databases and publications. A dataset can be obtained by one of skill in the art via a variety of known ways including accessing a dataset stored on a storage memory.
  • Clinical factor refers to a measure of a condition of a subject, e.g., disease activity or severity.
  • “Clinical factor” encompasses all markers of a subject's health status, including non-sample markers, and/or other characteristics of a subject, such as, without limitation, age and gender.
  • a clinical factor can be a score, a value, or a set of values that can be obtained from evaluation of a sample (or population of samples) from a subject or a subject under a determined condition.
  • a clinical factor can also be predicted by markers and/or other parameters such as marker expression surrogates.
  • the invention includes identifying a subject at risk of coronary artery disease CAD, comprising obtaining a first dataset associated with a sample obtained from the subject, wherein the first dataset comprises quantitative expression data for a miRNA marker selected from Table 8.
  • the invention further includes analyzing the first dataset to determine the expression level of the miRNA marker, wherein the expression level of the miRNA marker positively or negatively correlates with an increased risk of CAD in the subject.
  • the analysis includes comparing the first dataset to a second dataset associated with a control sample, wherein the second dataset comprises quantitative expression data for a control miRNA marker, and wherein a statistically significant difference between expression of the miRNA marker and expression of the control miRNA marker indicates an increased risk of CAD in the subject.
  • the analysis includes assessing an mRNA marker in the subject and combining the assessment with the analysis of the first dataset to identify risk of CAD in the subject.
  • an mRNA marker is AF161365, HNRPF, ACBD5, TFCP2, DDX18, AF289562, CD248, CD79B, CD19, SPIB, BLK, CD3D, LCK, TMC8, CCT2, S100A12, MMP9, CLEC4E, ALOX5AP, S100A8, NAMPT, RPL28, SSRP1, AQP9, GLT1D1, NCF4, NCF2, CASP5, H3F3B, IL18RAP, TXN, TNFAIP6, PLAUR, IL8RB, BCL2A1, TNFRSF10C, PTAFR, KCNE3, LAMP2, TLR4, TYROBP, SLAMF7, CX3CR1, KLRC4, and/or CD8A.
  • the first dataset includes one or more mRNA markers.
  • an mRNA can be included within a dataset, e.g., the first dataset.
  • the analysis includes assessing a SNP marker in the subject and combining the assessment with the analysis of the first dataset to identify risk of CAD in the subject.
  • the first dataset includes one or more SNP markers.
  • a SNP can be included within a dataset, e.g., the first dataset.
  • the quantity of one or more markers of the invention can be indicated as a value.
  • a value can be one or more numerical values resulting from evaluation of a sample under a condition.
  • the values can be obtained, for example, by experimentally obtaining measures from a sample by an assay performed in a laboratory, or alternatively, obtaining a dataset from a service provider such as a laboratory, or from a database or a server on which the dataset has been stored, e.g., on a storage memory.
  • the quantity of one or more markers can be one or more numerical values associated with RNA expression levels of miRNAs shown in the Tables below, e.g., resulting from evaluation of a sample under a condition.
  • miRNAs are in accordance with guidelines provided by HGNC. Gene symbols and GenBank accession numbers based on these guidelines are given Table 2B. Sequence(s) for a given miRNA can be obtained from the NCBI GenBank website using the accession numbers referenced in Table 2B as of December 30, 2010.
  • a condition can include one clinical factor or a plurality of clinical factors.
  • the invention can include assessing a clinical factor in a subject and combining the assessment with an analysis of the first dataset (see above) to identify risk of CAD in the subject.
  • a clinical factor can be included within a dataset, e.g., the first dataset.
  • a dataset can include one or more, two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, sixteen or more, seventeen or more, eighteen or more, nineteen or more, twenty or more, twenty-one or more, twenty-two or more, twenty-three or more, twenty-four or more, twenty-five or more, twenty-six or more, twenty-seven or more, twenty-eight or more, twenty-nine or more, or thirty or more overlapping or distinct clinical factor(s).
  • a clinical factor can be, for example, the condition of a subject in the presence of a disease or in the absence of a disease.
  • a clinical factor can be the health status of a subject.
  • a clinical factor can be age, gender, chest pain type, neutrophil count, ethnicity, disease duration, diastolic blood pressure, systolic blood pressure, a family history parameter, a medical history parameter, a medical symptom parameter, height, weight, a body-mass index, resting heart rate, and smoker/non-smoker status.
  • Clinical factors can include whether the subject has stable chest pain, whether the subject has typical angina, whether the subject has atypical angina, whether the subject has an anginal equivalent, whether the subject has been previously diagnosed with MI, whether the subject has had a revascularization procedure, whether the subject has diabetes, whether the subject has an inflammatory condition, whether the subject has an infectious condition, whether the subject is taking a steroid, whether the subject is taking an immunosuppressive agent, and/or whether the subject is taking a chemo therapeutic agent.
  • a marker's associated value can be included in a dataset associated with a sample obtained from a subject.
  • a dataset can include the marker expression value of two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, sixteen or more, seventeen or more, eighteen or more, nineteen or more, twenty or more, twenty-one or more, twenty-two or more, twenty-three or more, twenty-four or more, twenty-five or more, twenty-six or more, twenty-seven or more, twenty-eight or more, twenty-nine or more, or thirty or more marker(s).
  • the invention includes obtaining a sample associated with a subject, where the sample includes one or more markers.
  • the sample can be obtained by the subject or by a third party, e.g., a medical professional. Examples of medical
  • a sample can include RNA.
  • a sample can also include one or more cells.
  • the sample can be obtained from any bodily fluid, for example, amniotic fluid, aqueous humor, bile, lymph, breast milk, interstitial fluid, blood, blood plasma, cerumen (earwax), Cowper's fluid (pre-ejaculatory fluid), chyle, chyme, female ejaculate, menses, mucus, saliva, urine, vomit, tears, vaginal lubrication, sweat, serum, semen, sebum, pus, pleural fluid, cerebrospinal fluid, synovial fluid, intracellular fluid, and vitreous humour.
  • the sample is obtained by a blood draw, where the medical professional draws blood from a subject, such as by a syringe.
  • the bodily fluid can then be tested to determine the value of one or more markers using an assay, such as an assay described in the Examples section below.
  • the value of the one or more markers can then be evaluated by the same party that performed the assay using the methods of the invention or sent to a third party for evaluation using the methods of the invention.
  • assays for one or more markers include sequencing assays, microarrays, polymerase chain reaction (PCR), RT-PCR, Southern blots, Northern blots, antibody-binding assays, enzyme-linked immunosorbent assays (ELISAs), flow cytometry, protein assays, Western blots, nephelometry, turbidimetry, chromatography, mass
  • immunoassays including, by way of example, but not limitation, RIA, immunofluorescence, immunochemiluminescence, immunoelectrochemiluminescence, or competitive immunoassays, immunoprecipitation, and the assays described in the Examples section below.
  • the information from the assay can be quantitative and sent to a computer system of the invention.
  • the information can also be qualitative, such as observing patterns or fluorescence, which can be translated into a quantitative measure by a user or
  • the subject can also provide information other than assay information to a computer system, such as race, height, weight, age, gender, eye color, hair color, family medical history and any other information that may be useful to a user, such as a clinical factor described herein.
  • exemplary markers identified in this application by name, accession number, or sequence included within the scope of the invention are all variant sequences having at least 50, 60, 70, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% or greater identity to the exemplified marker sequences.
  • the percentage of sequence identity may be determined using algorithms well known to those of ordinary skill in the art, including, e.g., BLASTn, and BLASTp, as described in Stephen F. Altschul et al, J. Mol. Biol.
  • a computer comprises at least one processor coupled to a chipset. Also coupled to the chipset are a memory, a storage device, a keyboard, a graphics adapter, a pointing device, and a network adapter. A display is coupled to the graphics adapter. In one embodiment, the functionality of the chipset is provided by a memory controller hub and an I/O controller hub. In another embodiment, the memory is coupled directly to the processor instead of the chipset.
  • the storage device is any device capable of holding data, like a hard drive, compact disk read-only memory (CD-ROM), DVD, or a solid-state memory device.
  • the memory holds instructions and data used by the processor.
  • the pointing device may be a mouse, track ball, or other type of pointing device, and is used in combination with the keyboard to input data into the computer system.
  • the graphics adapter displays images and other information on the display.
  • the network adapter couples the computer system to a local or wide area network.
  • a computer can have different and/or other components than those described previously.
  • the computer can lack certain components.
  • the storage device can be local and/or remote from the computer (such as embodied within a storage area network (SAN)).
  • SAN storage area network
  • module refers to computer program logic utilized to provide the specified functionality.
  • a module can be implemented in hardware, firmware, and/or software.
  • program modules are stored on the storage device, loaded into the memory, and executed by the processor.
  • percent "identity,” in the context of two or more nucleic acid or polypeptide sequences, refer to two or more sequences or subsequences that have a specified percentage of nucleotides or amino acid residues that are the same, when compared and aligned for maximum correspondence, as measured using one of the sequence comparison algorithms described below (e.g., BLASTP and BLASTN or other algorithms available to persons of skill) or by visual inspection.
  • sequence comparison algorithms e.g., BLASTP and BLASTN or other algorithms available to persons of skill
  • the percent “identity” can exist over a region of the sequence being compared, e.g., over a functional domain, or, alternatively, exist over the full length of the two sequences to be compared.
  • sequence comparison typically one sequence acts as a reference sequence to which test sequences are compared.
  • test and reference sequences are input into a computer, subsequence coordinates are designated, if necessary, and sequence algorithm program parameters are designated.
  • sequence comparison algorithm then calculates the percent sequence identity for the test sequence(s) relative to the reference sequence, based on the designated program parameters.
  • Optimal alignment of sequences for comparison can be conducted, e.g., by the local homology algorithm of Smith & Waterman, Adv. Appl. Math. 2:482 (1981), by the homology alignment algorithm of Needleman & Wunsch, J. Mol. Biol. 48:443 (1970), by the search for similarity method of Pearson & Lipman, Proc. Nat'l. Acad. Sci. USA 85:2444 (1988), by computerized implementations of these algorithms (GAP, BESTFIT, FASTA, and TFASTA in the Wisconsin Genetics Software Package, Genetics Computer Group, 575 Science Dr., Madison, Wis.), or by visual inspection (see generally Ausubel et al, infra).
  • BLAST algorithm One example of an algorithm that is suitable for determining percent sequence identity and sequence similarity is the BLAST algorithm, which is described in Altschul et al, J. Mol. Biol. 215:403-410 (1990). Software for performing BLAST analyses is publicly available through the National Center for Biotechnology Information.
  • Embodiments of the entities described herein can include other and/or different modules than the ones described here.
  • the functionality attributed to the modules can be performed by other or different modules in other embodiments.
  • this description occasionally omits the term "module" for purposes of clarity and convenience.
  • 'Cases' are defined as subjects with stenosis in one or more major coronary arteries of >70%; and 'Controls' are subjects with no stenosis in any major coronary artery.
  • a pooled-sample approach was used initially to identify circulating miRNAs that are present in a set of PREDICT subjects. Four pools of 10 subjects were created:
  • hsa- miR-337 shows a 3.14 Ct decrease in pool 1 vs pool3, suggesting hsa-miR-337 is down- regulated in the presence of CAD.
  • Table 3 gives the delta Ct values between pools 2 & 4, and pools 1 & 3.
  • Table 4 summarizes the results from this analysis where the delta Ct was greater than one.
  • miRNA was purified from each of the individual 40 samples.
  • the MagMAXTMViral RNA Isolation Kit (Ambion, Austin, TX; cat. no. AM 1939) was used for total plasma RNA (including miRNA) isolation following the manufacturer's instructions with some modifications. 400ul of plasma was thawed on ice and transferred to 96-deep well plate. 400ul of lysis/binding buffer and 40ul of proteinase K solution (20mg/ml) was added to each plasma sample. The plate was incubated at 50°C for 50 min. To allow for normalization of sample-to-sample variation during RNA isolation, synthetic C.
  • elegans miRNAs cel-miR-39 synthetic RNA oligonucleotides synthesized by Integrated DNA Technology
  • RNA oligonucleotides synthesized by Integrated DNA Technology were added (1.2 fmol in a 6ul total volume).
  • Each sample was then mixed with 1 ml of isoproponal and 15ul of beads solution.
  • the plate was incubated at room temperature for 10 min. Bead binding and washing steps were performed based on the manufacturer's instructions.
  • the RNA was eluted in 50ul of DEPC water.
  • RNA sample 2.5ul was used in cDNA reaction with TaqMan® MicroRNA Reverse Transcription Kit (Applied Biosystems; part number 4366596) and 2.5ul of the cDNA was used in pre-amp reaction (TaqMan® PreAmp Master Mix Kit; part number 4391128).
  • 47 miRNAs were chosen based on the magnitude of difference between case and control pools; these miRNA are shown in Table 5. Expression values for the 47 miRNA were determined using the 48x48 Expression Chip from Fludigim (part number BMK-M- 48.48); RT-PCR was performed on the Fluidigm BioMark. In addition, as a normalization control we also assessed the levels of the spiked in the C elegans miRNA, cel-miR-39. [0072] Table 6 shows the P values and directionality (T value) of the 47 assays, derived from linear regression, normalizing for age and sex. Linear regression was performed using MiniTab (version 15.1.30.0.).
  • Target Scan Three publically available miRNA target databases (PicTar, Target Scan and miRrecord) were examined for potential mRNA targets of the miRNA. Potential targets were identified for 16 of the 20 significant miRNA (by normalization) in the technical replication experiment; results are shown in Table 7. The top 10 genes (based on their matrix score) were chosen from each database if there were more than 50 predicted targets.
  • Target scan OXSR1 oxidative-stress responsive 1

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Abstract

Cette invention concerne des méthodes d'identification de sujets prédisposés à la coronaropathie, fondées sur des mesures de l'expression de marqueurs de microARN (miARN); l'invention concerne également des systèmes informatiques, des kits et un logiciel permettant leur mise en œuvre.
PCT/US2012/020140 2011-01-06 2012-01-04 Microarn circulants utilisés comme biomarqueurs pour les coronaropathies Ceased WO2012094366A1 (fr)

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WO2013093870A1 (fr) 2011-12-23 2013-06-27 International Centre For Genetic Engineering And Biotechnology - Icgeb Microarn pour la régénération cardiaque par l'intermédiaire d'induction de la prolifération de cardiomyocytes
CN107385093A (zh) * 2017-09-07 2017-11-24 青岛大学 引物组合物及其应用和应用其的产品及产品的使用方法
CN107840877A (zh) * 2016-09-18 2018-03-27 北京奥维亚生物技术有限公司 一种人hnrpf多肽及其抗体制备方法
WO2018170651A1 (fr) * 2017-03-19 2018-09-27 深圳市博奥康生物科技有限公司 Arn tud pour inhiber les expressions des miarn-29 a, mir-140 et mir-152 humain, et application associées
EP4202060A1 (fr) * 2021-12-27 2023-06-28 Fundación Para la Investigación del Hospital Universitario y Politécnico La Fe de la Comunidad Valenciana Arnmi circulants comme biomarqueurs prédictifs du risque d'ischémie cardiaque chez les patients souffrant de douleurs thoraciques

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013093870A1 (fr) 2011-12-23 2013-06-27 International Centre For Genetic Engineering And Biotechnology - Icgeb Microarn pour la régénération cardiaque par l'intermédiaire d'induction de la prolifération de cardiomyocytes
CN107840877A (zh) * 2016-09-18 2018-03-27 北京奥维亚生物技术有限公司 一种人hnrpf多肽及其抗体制备方法
WO2018170651A1 (fr) * 2017-03-19 2018-09-27 深圳市博奥康生物科技有限公司 Arn tud pour inhiber les expressions des miarn-29 a, mir-140 et mir-152 humain, et application associées
CN107385093A (zh) * 2017-09-07 2017-11-24 青岛大学 引物组合物及其应用和应用其的产品及产品的使用方法
EP4202060A1 (fr) * 2021-12-27 2023-06-28 Fundación Para la Investigación del Hospital Universitario y Politécnico La Fe de la Comunidad Valenciana Arnmi circulants comme biomarqueurs prédictifs du risque d'ischémie cardiaque chez les patients souffrant de douleurs thoraciques

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