WO2015079060A2

WO2015079060A2 - Mirnas as advanced diagnostic tool in patients with cardiovascular disease, in particular acute myocardial infarction (ami)

Info

Publication number: WO2015079060A2
Application number: PCT/EP2014/076069
Authority: WO
Inventors: Andreas Keller; Benjamin Meder; Jan Haas; Britta VOGEL; Hugo A. Katus; Jan Kirsten; Cord Friedrich Stähler
Original assignee: Siemens Aktiengesellschaft
Priority date: 2013-11-29
Filing date: 2014-12-01
Publication date: 2015-06-04
Also published as: WO2015079060A3

Abstract

MiRNAs as advanced diagnostic tool in patients with cardiovascular disease, in particular acute myocardial infarction (AMI) In its most general terms, the invention relates to a collection of miRNA markers useful for the diagnosis of cardiovascular disease, in particular, acute myocardial infarction (AMI). The invention further relates to a kit for the diagnosis of cardiovascular disease and a computer program product useful for performing a method of diagnosis of cardiovascular disease. In particular, the methods of the present invention are useful for differentiating between AMI and non-ischemic chest pain as well as for differentiating between ACS and a non-pathological heart condition.

Description

MiRNAs as advanced diagnostic tool in patients with cardio^¬ vascular disease, in particular acute myocardial infarction (AMI)

The invention relates to a method of diagnosis of cardiovas^¬ cular disease, in particular, acute myocardial infarction (AMI), a kit for the diagnosis of cardiovascular disease and a computer program product useful for performing a method of diagnosis of cardiovascular disease.

Background of the invention Very recently, molecular diagnostics has increasingly gained in importance. It has found an entry into the clinical diag^¬ nosis of diseases (inter alia detection of infectious patho^¬ gens, detection of mutations of the genome, detection of dis^¬ eased cells and identification of risk factors for predispo- sition to a disease) .

In particular, through the determination of gene expression in tissues, nucleic acid analysis opens up very promising new possibilities in the study and diagnosis of disease.

Nucleic acids of interest to be detected include genomic DNA, expressed mRNA and other RNAs such as MicroRNAs (abbreviated miRNAs) . MiRNAs are a new class of small RNAs with various biological functions. They are short (average of 20-24 nucle- otide) ribonucleic acid (RNA) molecules found in eukaryotic cells. Several hundred different species of microRNAs (i.e. several hundred different sequences) have been identified in mammals. They are important for post-transcriptional gene- regulation and bind to complementary sequences on target mes- senger RNA transcripts (mRNAs) , which can lead to transla- tional repression or target degradation and gene silencing. As such they can also be used as biologic markers for re^¬ search, diagnosis and therapy purposes. Acute myocardial infarction (AMI) is one of the predominant cardiovascular diseases in western countries. The pathogene^¬ sis of acute myocardial infarction (AMI) is complex and in- eludes a series of events being involved. Contingent rupture of an unstable atherosclerotic plaque is followed by thrombus formation and occlusion of a coronary vessel, leading to ischemia and hence necrosis of the downstream myocardium. It is well known that patients' outcome correlates with the time from the onset of symptoms to re-opening of the occluded cor^¬ onary artery. Hence, affected patients significantly benefit from early diagnosis and treatment.

The diagnosis of AMI is mainly based on patients' symptoms, i.e. typical thoracic pain (e.g. angina pectoris), altera^¬ tions on electrocardiography (ECG) and elevated blood based markers of cardiac necrosis. Based here on, patients with AMI can be divided into patients with non-ST-elevation myocardial infarction (NSTEMI), as well as ST-elevation myocardial in- farction (STEMI), all of which show elevated levels of bi- omarkers for cardiac necrosis. Together with those patients with instable angina pectoris (iAP) (no ECG alterations and normal biomarker values) they belong to the group of patients with "acute coronary syndrome" (ACS) . Patients having insta- ble angina pectoris (iAP) have a significantly increased risk of developing AMI .

In a typical clinical scenario a patient will present with chest pain to the doctor or hospital. It is important to quickly determine whether the patient suffers from AMI, iAP or other thoracic symptoms out of non-ischemic reasons (e.g. chest pains of pulmonary or traumatic origin) , in order to make acute care decisions and select further required thera^¬ peutic and diagnostic measures while avoiding unnecessary procedures.

In the diagnostic pathway of AMI patients, cardiac biomarkers have gained importance. Today's gold standard biomarkers for cardiomyocyte death are cardiac troponins. Troponins can be detected after their release from cardiomyocytes in human blood samples with antibody-dependent diagnostic tools. Over the past decades, such assays have been reworked, modified, enhanced and consequently improved regarding their analytical performance. Such assays now indicate myocardial injury with high sensitivity. Generally, troponin levels of below 14 pg/ml are indicative of a low likelihood of AMI. Troponin levels of between 14 pg/ml and 50 pg/ml are indicative of moderate likelihood of AMI and indicate further monitoring of the patient. Troponin levels of between higher than 50 pg/ml are indicative of a high likelihood of AMI. However, they lack specificity regarding AMI diagnosis if taken as single values. Troponin levels might also be altered in response to other cardiovascular diseases like pulmonary embolism, myocarditis, acute tachycardia or heart failure, making AMI diagnosis more complex. Differentiating true AMI patients from patients with elevated troponins due to non-ischemic causes, is nowadays one of the great challenges in

cardiovascular medicine. It is further a challenge to

differentiate between patients suffering from AMI vs. other cardiovascular conditions with similar symptoms or other patients with chest pain. As AMI requires specific therapies and patient care, a quick and reliable diagnosis of AMI improves patient outcome and reduces costs for unnecessary other procedures.

Therefore, there exists an unmet need for an efficient, simple, reliable diagnostic test for of cardiovascular dis- ease, in particular, acute myocardial infarction (AMI, which can differentiate between AMI and other cardiovascular conditions .

Definitions

Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The term "diagnosis" of a disease, as used herein, relates to all aspects of diagnosing a disease, including determining whether a patient is suffering from said disease, screening for the likelihood to develop said disease, prediction of an outcome of said disease, and monitoring a therapy of said disease

The term "predicting an outcome" of a disease, as used here- in, is meant to include both a prediction of an outcome of a patient undergoing a given therapy and a prognosis of a pa^¬ tient who is not treated.

An "outcome" within the meaning of the present invention is a defined condition attained in the course of the disease. This disease outcome may e.g. be a clinical condition such as "re^¬ lapse of disease", "remission of disease", "response" to therapy", "survival", "curation", a disease stage or grade or the like.

A "risk" is understood to be a probability of a subject or a patient to develop or arrive at a certain disease outcome. The term "risk" in the context of the present invention is not meant to carry any positive or negative connotation with regard to a patient's wellbeing but merely refers to a proba^¬ bility or likelihood of an occurrence or development of a given event or condition.

The term "clinical data" relates to the entirety of available data and information concerning the health status of a patient including, but not limited to, age, sex, weight, meno- pausal/hormonal status, etiopathology data, anamnesis data, data obtained by in vitro diagnostic methods such as blood or urine tests, data obtained by imaging methods, such as x-ray, computed tomography, MRI, PET, spect, ultrasound, electro^¬ physiological data, genetic analysis, gene expression analy^¬ sis, biopsy evaluation, intraoperative findings. The term "classification of a sample" of a patient, as used herein, relates to the association of said sample with at least one of at least two categories. These categories may be for example "high risk" and "low risk", high, intermediate and low risk, wherein risk is the probability of a certain event occurring in a certain time period, e.g. occurrence of disease, progression of disease, etc. It can further mean a category of favorable or unfavorable clinical outcome of dis^¬ ease, responsiveness or non-responsiveness to a given treat- ment or the like. Classification may be performed by use of an algorithm, in particular a discrimant function. A simple example of an algorithm is classification according to a first quantitative parameter, e.g. expression level of a nu^¬ cleic acid of interest, being above or below a certain threshold value. Classification of a sample of a patient may be used to predict an outcome of disease or the risk of de^¬ veloping a disease. Instead of using the expression level of a single nucleic acid of interest, a combined score of sever^¬ al nucleic acids of interest of interest may be used. Fur- ther, additional data may be used in combination with the first quantitative parameter. Such additional data may be clinical data from the patient, such as sex, age, weight of the patient, disease grading etc. A "discriminant function" is a function of a set of variables used to classify an object or event. A discriminant function thus allows classification of a patient, sample or event into a category or a plurality of categories according to data or parameters available from said patient, sample or event. Such classification is a standard instrument of statistical analy^¬ sis well known to the skilled person. E.g. a patient may be classified as "high risk" or "low risk", "in need of treatment" or "not in need of treatment" or other categories ac^¬ cording to data obtained from said patient, sample or event. Classification is not limited to "high vs. low", but may be performed into a plurality of categories, grading or the like. Examples for discriminant functions which allow a clas^¬ sification include, but are not limited to discriminant func- tions defined by support vector machines (SVM) , k-nearest neighbors (kNN) , (naive) Bayes models, or piecewise defined functions such as, for example, in subgroup discovery, in de^¬ cision trees, in logical analysis of data (LAD) an the like.

The term "expression level" refers, e.g., to a determined level of expression of a nucleic acid of interest. The term "pattern of expression levels" refers to a determined level of expression compared either to a reference nucleic acid, e.g. from a control, or to a computed average expression val^¬ ue, e.g. in DNA-chip analyses. A pattern is not limited to the comparison of two genes but is also related to multiple comparisons of genes to reference genes or samples. A certain "pattern of expression levels" may also result and be deter- mined by comparison and measurement of several nucleic acids of interest disclosed hereafter and display the relative abundance of these transcripts to each other, for example for purposes of normalization. Expression levels may also be as^¬ sessed relative to expression in different tissues, patients versus healthy controls, etc.

A "reference pattern of expression levels", within the meaning of the invention shall be understood as being any pattern of expression levels that can be used for the comparison to another pattern of expression levels. In a preferred embodi^¬ ment of the invention, a reference pattern of expression levels is, e.g., based on an average pattern of expression lev^¬ els observed in a group of healthy or diseased individuals, serving as a reference group. In particular, a reference pat- tern of expression levels is, e.g., based on an average pat^¬ tern of expression levels observed in a cohort or population belonging to a defined patient population based on disease (e.g. patients with iAP) or having defined clinical data such as a patient population wherein specific marker is absent, present, elevated or reduced (e.g. troponin positive pa^¬ tients) . In the context of the present invention a "sample" or a "bio^¬ logical sample" is a sample which is derived from or has been in contact with a biological organism. Examples for biologi^¬ cal samples are: cells, tissue, body fluids, biopsy speci- mens, blood, urine, saliva, sputum, plasma, serum, cell cul^¬ ture supernatant, and others.

A "gene" is a set of segments of nucleic acid that contains the information necessary to produce a functional RNA product in a controlled manner. A "gene product" is a biological mol^¬ ecule produced through transcription or expression of a gene, e.g. an mRNA or the translated protein.

A "miRNA" is a short, naturally occurring RNA molecule and shall have the ordinary meaning understood by a person skilled in the art. A "molecule derived from an miRNA" is a molecule which is chemically or enzymatically obtained from an miRNA template, such as cDNA. The term "array" refers to an arrangement of addressable lo^¬ cations on a device, e.g. a chip device. The number of loca^¬ tions can range from several to at least hundreds or thou^¬ sands. Each location represents an independent reaction site. Arrays include, but are not limited to nucleic acid arrays, protein arrays and antibody-arrays. A "nucleic acid array" refers to an array containing nucleic acid probes, such as oligonucleotides, polynucleotides or larger portions of genes. The nucleic acid on the array is preferably single stranded. A "microarray" refers to a biochip or biological chip, i.e. an array of regions having a density of discrete regions with immobilized probes of at least about 100/cm2.

A "PCR-based method" refers to methods comprising a polymer^¬ ase chain reaction PCR. This is a method of exponentially am- plifying nucleic acids, e.g. DNA or RNA by enzymatic replica^¬ tion in vitro using one, two or more primers. For RNA amplification, a reverse transcription may be used as a first step. PCR-based methods comprise kinetic or quantitative PCR (qPCR) which is particularly suited for the analysis of ex^¬ pression levels, ) . When it comes to the determination of ex^¬ pression levels, a PCR based method may for example be used to detect the presence of a given mRNA by (1) reverse tran- scription of the complete mRNA pool (the so called

transcriptome) into cDNA with help of a reverse transcriptase enzyme, and (2) detecting the presence of a given cDNA with help of respective primers. This approach is commonly known as reverse transcriptase PCR (rtPCR) . The term "PCR based method" comprises both end-point PCR applications as well as kinetic/real time PCR techniques applying special fluorophors or intercalating dyes which emit fluorescent signals as a function of amplified target and allow monitoring and quanti^¬ fication of the target. Quantification methods could be ei- ther absolute by external standard curves or relative to a comparative internal standard.

The term "next generation sequencing" or "high throughput sequencing" refers to high-throughput sequencing technologies that parallelize the sequencing process, producing thousands or millions of sequences at once. Examples include Massively Parallel Signature Sequencing (MPSS) Polony sequencing, 454 pyrosequencing, Illumina (Solexa) sequencing, SOLiD sequencing, Ion semiconductor sequencing, DNA nanoball sequencing, Helioscope (TM) single molecule sequencing, Single Molecule SMRT(TM) sequencing, Single Molecule real time (RNAP) se^¬ quencing, Nanopore DNA sequencing.

The term "antibody", as used herein, refers to an immuno- globulin protein or a fragment thereof, said fragment being capable of specifically binding an antigen. An antibody, in^¬ cluding an antibody fragment, suitable for the invention may be monoclonal, polyclonal, of any host organism source, recombinantly expressed or otherwise artificially produced and of any immunoglobuline type. In the context of the inven^¬ tion, the antibody is able to bind an antigen comprising a hybrid of a nucleic acid molecule of interest and a nucleic acid probe. The term "immunoassay", as used herein, refers to the detec^¬ tion or quantification of an analyte - such as a nucleic acid of interest - comprising an immune reaction between an anti- body and an antigen. In the context of the invention the analyte to be detected or quantified comprises a nucleic acid of interest.

A "pathologic heart condition" is a heart condition which re- quires a defined level of therapeutic intervention such as invasive surgical intervention (e.g. bypass surgery, minimal invasive intervention such as treatment by catheter, place^¬ ment of stents and the like) or treatment with a pharmacolog^¬ ically active substance (e.g. beta-blocker, nitroglycerine, and others) . A "non-pathologic heart condition" is a heart condition which does not require immediate therapeutic inter^¬ vention, although a patient with a non-pathologic heart con^¬ dition may be advised to undergo further diagnostic measures such as periodic monitoring.

The term "marker" or "biomarker" refers to a biological mole^¬ cule, e.g., a nucleic acid, peptide, protein, hormone, etc., whose presence or concentration can be detected and correlat^¬ ed with a known condition, such as a disease state, or with a clinical outcome, such as response to a treatment.

Object of the invention

The technical problem underlying the present invention is to provide biological markers allowing diagnosis of cardiovascu^¬ lar disease, in particular, acute myocardial infarction (AMI) and ACS.

Summary of the invention

Before the invention is described in detail, it is to be un^¬ derstood that this invention is not limited to the particular component parts of the process steps of the methods described as such methods may vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only, and is not intended to be limit^¬ ing. It must be noted that, as used in the specification and the appended claims, the singular forms "a, " "an" and "the" include singular and/or plural referents unless the context clearly dictates otherwise. It is also to be understood that plural forms include singular and/or plural referents unless the context clearly dictates otherwise. It is moreover to be understood that, in case parameter ranges are given which are delimited by numeric values, the ranges are deemed to include these limitation values.

In its most general terms, the invention relates to a collec- tion of miRNA markers useful for the diagnosis of cardiovas^¬ cular disease, in particular, acute coronary syndrome (ACS) , in particular acute myocardial infarction (AMI).

In particular, the invention relates to a method of classify- ing a sample of a patient suffering from or at risk of devel^¬ oping acute coronary syndrome (ACS) , in particular acute myo^¬ cardial infarction (AMI), said method comprising the steps of:

a) determining in said sample from said patient, an expres- sion level of at least one miRNA selected from the group con^¬ sisting of the miRNA species No. 1 to 81 as listed in tables 1 to 4 or from a miRNA species which has at least 80% se^¬ quence identity with a miRNA species selected from the group consisting of the miRNA species No. 1 to 81 as listed in ta- bles 1 to 4 ;

b) comparing the pattern of expression level (s) determined in step a) with one or several reference pattern (s) of ex^¬ pression levels; and

c) classifying the sample of said patient from the outcome of the comparison in step b) into one of at least two clas^¬ ses . It is noted that miRNA species No. 1 to 81 correspond to the miRNA species having the SEQ ID NO: 1 to 81

Said one of at least two classes can be a class indicative of a risk of suffering from or risk of developing acute myocardial infarction.

A reference pattern of expression levels may, for example, be obtained by determining in at least one healthy subject the expression level of at least one miRNA species used in the methods of the invention.

A reference pattern of expression levels may , for example, further be obtained by determining in at least one patient having a diagnosed acute myocardial infarction the expres^¬ sion level of at least one miRNA species used in the methods of the invention.

It is within the scope of the invention to assign a numerical value to an expression level of the at least one miRNA deter^¬ mined in step a) .

It is further within the scope of the invention to mathemati^¬ cally combine expression level values to obtain a pattern of expression levels in step (b) , e.g. by applying an algorithm to obtain a normalized expression level relative to a refer^¬ ence pattern of expression level (s) .

In a further aspect the invention relates to a method for di- agnosing acute coronary syndrome (ACS) , in particular acute myocardial infarction (AMI) in a patient, said method com^¬ prising the steps of:

a) determining in a sample from said patient, an expression level of at least one miRNA selected from the group consist- ing of miRNA sequences having the SEQ ID NO: 1 to 81 or from a miRNA species which has at least 80% sequence identity with a miRNA species selected from the group consisting of the miRNA species No. 1 to 81 as listed in tables 1 to 4; b) comparing the pattern of expression level (s) determined in step a) with one or several reference pattern (s) of ex^¬ pression levels; and

c) diagnosing acute myocardial infarction from the out- come of the comparison in step b) .

According to an aspect of the invention, the sample is se^¬ lected from the group consisting of blood sample, serum sam^¬ ple, and plasma sample.

According to an aspect of the invention, the cardiovascular disease is acute myocardial infarction (AMI) .

According to an aspect of the invention, the one or several reference pattern (s) of expression levels are based one or several reference pattern (s) of expression levels of a sub^¬ ject selected from the group consisting of

- a subject having a predefined range of blood concentration of troponin;

- a subject having chest pain;

- a subject not suffering from cardiovascular disease;

- a subject suffering from instable angina pectoris;

- a subject suffering from NSTEMI; and

- a Subject suffering from STEMI .

According to an aspect of the invention, the step (a) comprises determining the expression level of at least 2, 3, 4, 5, 10, 15, or 20 miRNA species. According to an aspect of the invention, the step (b) of com^¬ paring comprises determining a probability of the pattern of expression level (s) belonging to one of at least two classes.

According to an aspect of the invention, the step (b) of com- paring comprises applying a discriminant function.

According to an aspect of the invention, the expression levels of a plurality of miRNAs are determined as expression level values and step (b) comprises mathematically combining the expression level values of said plurality of miRNAs .

The miRNA species No. 1 to 81 as listed in tables 1 to 4 or from a miRNA species are also listed without duplicates in table 5 and the attached sequence listing as SEQ ID NO: 1 to 81.

It is within the scope of the invention to apply an algorithm to the numerical value of the expression level of the at least one miRNA determined in step a) to obtain a disease score to allow classification of the sample or diagnosis, prognosis or prediction of the risk of cardiovascular disease, in particular AMI. A non-limiting example of such an algorithm is to compare the the numerical value of the ex^¬ pression level against a threshhold value in order to classi^¬ fy the result into one of two categories, such as high risk/low risk, diseased/healthy or the like. A further non- limiting example of such an algorithm is to combine a plural- ity of numerical values of expression levels, e.g. by summa^¬ tion, to obtain a combined score. Individual summands may be normalized or weighted by multiplication with factors or nu^¬ merical values representing the expression level of an miRNA, numerical values representing clinical data, or other fac- tors.

It is within the scope of the invention to apply a discrimi^¬ nant function to classify a result, diagnose disease, predict an outcome or a risk.

According to an aspect of the invention, the determination of the expression level in step (a) is obtained by use of a method selected from the group consisting of a Sequencing- based method, an array based method, a PCR based method, and an immunoassay method.

It is within the scope of the invention to determine the ex^¬ pression level of a miRNA marker by immunoassay detection. Detection of a specific nucleic acid molecule of interest is achieved by using a nucleic acid probe which hybridizes to the nucleic acid molecule of interest. For example, immunoas^¬ say detection can be achieved by using a solid-phase bound antibody specific for the hybrid formed by hybridization of the nucleic acid probe to the nucleic acid molecule of inter^¬ est. This is described e.g. in the document WO2013/135581A1 which is incorporated herein in its entirety by reference. According to an aspect of the invention, step (c) comprises differentiating between a classification or diagnosis of AMI and at least one of the conditions selected from

- non-ischemic chest pain

- non-ischemic chest pain and increased troponin concentra- tion

- increased troponin concentration.

In this regard, the markers described herein allow to deter^¬ mine, whether a patient with chest pain and/or increased tro- ponin concentration is suffering from or is at risk of suffering from AMI .

According to a further aspect of the invention according to the above aspect of the invention, a troponin concentration of >14pg/ml is an increased troponin concentration.

According to a further aspect of the invention according to this above aspect of the invention, wherein a troponin concentration of >50pg/ml is an increased troponin concentra- tion.

According to an aspect of the invention, step (c) comprises differentiating between a classification or diagnosis of AMI and/or instable angina pectoris (iAP) and a non-pathologic heart condition.

In this regard, the markers described herein allow to differ^¬ entiate whether a patient is suffering from or at risk of suffering from AMI or iAP versus not having a pathologic heart condition. Thereby it is possible to identify patients having acute coronary syndrome. In a further aspect the invention relates to a kit for diag^¬ nosing acute myocardial infarction ,

- determining in said sample from said patient, an expression level of at least one miRNA selected from the group con^¬ sisting of the miRNA species No. 1 to 81 as listed in ta- bles 1 to 4 or from a miRNA species which has at least 80% sequence identity with a miRNA species selected from the group consisting of the miRNA species No. 1 to 81 as listed in tables 1 to 4, and

- at least one reference pattern of expression levels for comparing with the expression level of the at least one miRNA from said sample.

The means for determining the expression level of said at least one miRNA may comprise an oligonucleotide probe for de- tecting or amplifying said at least one miRNA, means for determining the expression level based on an array-based method, a PCR based method, a sequencing based method or any oth^¬ er suitable means for determining the expression level. According to an aspect of the invention, the kit further comprises at least one reference pattern of expression levels for comparing with the expression level of the at least one miRNA from said sample. The reference pattern of expression may include at least one digital or numerical information and may be provided in any readable or electronically readable form, including, but not limited to printed form, electronically stored form on a computer readable medium, such as CD, smart card, or provided in downloadable form, e.g. in a com^¬ puter network such as the internet.

In a further aspect the invention relates to a computer program product, useful for performing the method according to any of claims 1 to 9, comprising - means for receiving data representing an expression level of at least one miRNA selected from the group consisting of the miRNA species No. 1 to 81 as listed in tables 1 to 4 or from a miRNA species which has at least 80 % seguenee identity with a miRNA species selected from the group con^¬ sisting of the miRNA species No. 1 to 81 as listed in ta^¬ bles 1 to 4,

- means for receiving data representing at least one reference pattern of expression levels for comparing with the expression level of the at least one miRNA from said sam^¬ ple,

- means for comparing said data representing the expression level of the at least one miRNA in a patient sample, and

- means for determining a diagnosis of acute myocardial in- farction from the outcome of the comparison in step b) .

The computer program product may be provided on a storable electronic medium, such as a solid state memory, disk, CD or other. It may be stored locally on a computer. It may be im- plemented as network-based program or application, including a web- or internet-based application. It may be implemented in a diagnostic device, such as an analyzer instrument. It may be operably connected to a device for outputting infor^¬ mation, such as a display, printer or the like.

Detailed description of the invention

Additional details, features, characteristics and advantages of the object of the invention are further disclosed in the following description and figures of the respective examples, which, in an exemplary fashion, show preferred embodiments of the present invention. However, these examples should by no means be understood as to limit the scope of the invention. The use of new biomarkers based on miRNAs for diagnosis of

AMI according to the invention can circumvent limitations of exisiting diagnostic tests and add precision to the diagnosis of AMI, especially by enhancing test specificity. Further- more, blood-borne miRNAs also bear the potential of a faster diagnosis as compared to cardiac troponin, which is released as a consequence of pathogenic processes in the heart. Here, the abundance of miRNAs in blood samples of AMI

patients, in particular STEMI and NSTEMI patientss has been compared against healthy controls, against patients suffering from other cardiovascular disorders, against patients

suffering from chest pain and against patients having a predetermined blood concentration of troponin. This approach involved extraction of miRNA from blood samples and a massive effort of sequencing miRNAs from respective samples by next generation sequencing (NGS) . Further, the use of blood samples as a source of expression information of miRNA markers has several tangible advances which are not available in other sample sources such as serum or tissue, such as ease of sample procurement and handling, sample preparation, and robustness and consistency of expression patterns. The experimental approach was aimed at identifying miRNAs that allow discrimination of AMI (STEMI and NSTEMI) patients, which were troponin positive, from patients that also showed elevated troponin levels, but due to other non-ischemic caus^¬ es (Table 1 and 2) . In a study on over 200 patients collected from the Chest Pain Unit, several single miRNAs were identi^¬ fied as candidates to discriminate between these groups with high specificity and report likewise signatures that allow for improved diagnostics of AMI . Based on these data it was possible to differentiate between AMI (STEMI and NSTEMI) patients, which were troponin positive, and patients with thoracic symptoms (e.g. chest pain) out of non-ischemic reasons (Table 1 and 2) . The same data set also allowed for identification of other clinically relevant data sets with related clinical need. These include the differentiation between acute coronary syndrome (ACS) (incl. NSTEMI, STEMI and instable angina pector- is) patients and controls (Table 3) and between AMI (NSTEMI, STEMI) and patients with thoracic symptoms out of non^¬ ischemic reasons (Table 4) . Classification of patients into the NSTEMI group, STEMI group, iAP group, group of thoracic symptoms out of non^¬ ischemic reasons, and control group were based on further di^¬ agnostic tests including a high sensitivity Troponin T assay (hsTnT) , ECG, and angiography. Controls were subjects who had elective angiography, but did not show any symptoms for ACS and had otherwise normal heart function.

Tables 1 and 2 show miRNA expression data shown as number of reads per 2 million reads in a NGS approach and the siginicance of differential expression between AMI (STEMI and NSTEMI) patients, which were troponin positive, and patients with thoracic symptoms out of non-ischemic reasons which were also troponin positive, the troponin cutoff being 14 pg/ml (table 1) and 50pg/ml (table 2) . The markers described herein allow to determine, whether a patient with chest pain and/or increased troponin concentration is suffering from or is at risk of suffering from AMI.

Table 1 NSTEMI + STEMI: TnT-positive vs. TS 3 + TS 4,

Troponin cutoff 14 pg/ml

No. miRNA Sequence Expression Significance

1 hsa-miR-181c-5p AACAUUCAACCUGUCGGUGAGU 410,6 7,49E-05

2 hsa-miR-425-3p AUCGGGAAUGUCGUGUCCGCCC 125,9 7,53E-05

3 hsa-miR-146a-5p UGAGAACUGAAUUCCAUGGGUU 786,5 9,59E-05

4 hsa-miR-548ah-3p CAAAAACUGCAGUUACUUUUGC 62,9 0,000349911

5 hsa-miR-29b-2-5p CUGGUUUCACAUGGUGGCUUAG 12,2 0,000361095

6 hsa-miR-2110 UUGGGGAAACGGCCGCUGAGUG 54,5 0,00059564

7 hsa-miR-664b-3p UUCAUUUGCCUCCCAGCCUACA 38,3 0,000838702

8 hsa-miR-185-5p UGGAGAGAAAGGCAGUUCCUGA 3396,1 0,000904265

9 hsa-miR-4286 ACCCCACUCCUGGUACC 48,4 0,001001705

10 hsa-miR-30c-5p UGUAAACAUCCUACACUCUCAGC 6191,9 0,001469859

11 hsa-let-7i-3p CUGCGCAAGCUACUGCCUUGCU 198 0,001989775

12 hsa-miR-4772-3p CCUGCAACUUUGCCUGAUCAGA 7,5 0,002051503 -

Table 2 NSTEMI + STEMI : TnT-positive vs. TS 3 + TS 4,

Troponin cutoff 14 pg/ml

Table 3 shows miRNA expression data shown as number of reads per 2 million reads in a NGS approach and the significance of differential expression between acute coronary syndrome (ACS) patients ( incl . patients having NSTEMI, STEMI and instable an^¬ gina) and healthy individuals. The markers described herein allow to differentiate whether a patient is suffering from or at risk of suffering from AMI or iAP versus not having a pathologic heart condition. Thereby it is possible to identi^¬ fy patients having acute coronary syndrome. Table 3 NSTEMI + STEMI + iAP vs. Controls

Table 4 shows miRNA expression data shown as number of reads per 2 million reads in a NGS approach and the significance of differential expression between AMI (NSTEMI, STEMI) and patients with thoracic symptoms out of non-ischemic reasons

Table 4 NSTEMI + STEMI (alle) vs. TS 1-4

No. miRNA Sequence Expression Significance

61 hsa-let-7i-3p CUGCGCAAGCUACUGCCUUGCU 198 7,45E-07

62 hsa-miR-15a-5p UAGCAGCACAUAAUGGUUUGUG 10652,5 l,05E-05

63 hsa-miR-185-5p UGGAGAGAAAGGCAGUUCCUGA 3396,1 l,41E-05 64 hsa-miR-425-3p AUCGGGAAUGUCGUGUCCGCCC 125,9 4,06E-05

65 hsa-miR-3143 AU AACAU UG UAAAGCGCU U CU U U CG 17 9,98E-05

66 hsa-miR-454-3p UAGUGCAAUAUUGCUUAUAGGGU 405,3 0,000120547

67 hsa-miR-150-5p UCUCCCAACCCU UGUACCAGUG 3253,8 0,00015084

68 hsa-miR-30c-5p UGUAAACAUCCUACACUCUCAGC 6191,9 0,000163937

69 hsa-miR-532-5p CAUGCCUUGAGUGUAGGACCGU 2892,7 0,000195016

70 hsa-miR-193a-5p UGGGUCU UUGCGGGCGAGAUGA 22,5 0,000198102

71 hsa-miR-145-5p GUCCAGUUUUCCCAGGAAUCCCU 95,4 0,00021691

72 hsa-miR-92b-3p UAUUGCACUCGUCCCGGCCUCC 44258,1 0,000317213

73 hsa-miR-186-5p CAAAGAAUUCUCCUUUUGGGCU 32013,5 0,000697863

74 hsa-miR-4286 ACCCCACUCCUGGUACC 48,4 0,000732354

75 hsa-miR-1284 UCUAUACAGACCCUGGCUUUUC 10,1 0,000840383

76 hsa-miR-223-3p UGUCAGUUUGUCAAAUACCCCA 5807,4 0,001206971

77 hsa-miR-23b-3p AUCACAUUGCCAGGGAUUACC 978,4 0,00135927

78 hsa-miR-628-3p UCUAGUAAGAGUGGCAGUCGA 20,7 0,001360549

79 hsa-miR-5701 UUAUUGUCACGUUCUGAUU 23,2 0,001401099

80 hsa-miR-769-5p UGAGACCUCUGGGUUCUGAGCU 286,5 0,001719981

81 hsa-miR-199a-3p ACAGUAGUCUGCACAUUGGUUA 37 0,00179258

The methods of the invention fulfill unmet clinical needs in the diagnosis of AMI, assessing the risk of developing AMI and differentiating between AMI and non-ischemic chest pain.

In particular, the methods of the present invention and the markers described herein are useful for differentiating be^¬ tween AMI and non-ischemic chest pain as well as for differ^¬ entiating between ACS and a non-pathological heart condition

Table 5 Listing of miRNA Sequences

SEQ ID NO Sequence

1 AACAUUCAACCUGUCGGUGAGU

2 AUCGGGAAUGUCGUGUCCGCCC

3 UGAGAACUGAAUUCCAUGGGUU

4 CAAAAACUGCAGUUACUUUUGC

5 CUGGU UUCACAUGGUGGCUUAG

6 UUGGGGAAACGGCCGCUGAGUG

7 UUCAUUUGCCUCCCAGCCUACA

8 UGGAGAGAAAGGCAGUUCCUGA

9 ACCCCACUCCUGGUACC UGUAAACAUCCUACACUCUCAGC

CUGCGCAAGCUACUGCCUUGCU

CCUGCAACUUUGCCUGAUCAGA

CAUGCCUUGAGUGUAGGACCGU

UGAGUGUGUGUGUGUGAGUGUGU

UUCUGGAAUUCUGUGUGAGGGA

UCUAUACAGACCCUGGCUUUUC

UAACAGUCUACAGCCAUGGUCG

ACCACUGACCGUUGACUGUACC

ACUGGCUAGGGAAAAUGAUUGGAU

UCCCUGAGACCCUUUAACCUGUGA

AUCGGGAAUGUCGUGUCCGCCC

AACAUUCAACCUGUCGGUGAGU

CAAAAACUGCAGUUACUUUUGC

CUGGU UUCACAUGGUGGCUUAG

UGAGAACUGAAUUCCAUGGGUU

UUGGGGAAACGGCCGCUGAGUG

UUCAUUUGCCUCCCAGCCUACA

ACCCCACUCCUGGUACC

UCUAUACAGACCCUGGCUUUUC

UGAGGUAGUAGGUUGUAUGGUU

AAAAACUGAGACUACUU UUGCA

UCACCAGCCCUGUGUUCCCUAG

UAACAGUCUACAGCCAUGGUCG

UUCUGGAAUUCUGUGUGAGGGA

CUGCGCAAGCUACUGCCUUGCU

AACCAUCGACCGUUGAGUGGAC

UAGCACCAUUUGAAAUCGGUUA

ACCACUGACCGUUGACUGUACC

CCUGCAACUUUGCCUGAUCAGA

ACUGGCUAGGGAAAAUGAUUGGAU

CUCCCACAUGCAGGGUUUGCA

GUCCAGUU UUCCCAGGAAUCCCU

UGUCAGUUUGUCAAAUACCCCA

UAAUCCUUGCUACCUGGGUGAGA

UGAGAUGAAGCACUGUAGCUC

UGUCCUCUAGGGCCUGCAGUCU

AUCACAUUGCCAGGGAUUUCC

AUCCCCAGAUACAAUGGACAA

UGAGGUAGUAGUUUGUACAGUU

UCUCUGGGCCUGUGUCUUAGGC

UAGCAGCGGGAACAGUUCUGCAG AUCGGGAAUGUCGUGUCCGCCC

AAAGUUCUGAGACACUCCGACU

AAACUCUACUUGUCCUUCUGAGU

CACCCGGCUGUGUGCACAUGUGC

CUGACCUAUGAAUUGACAGCC

UCAAGUGUCAUCUGUCCCUAG

AGGGCCCCCCCUCAAUCCUGU

CAAAAACCACAGUUUCUUUUGC

ACUGUAAACGCUUUCUGAUG

CUGCGCAAGCUACUGCCUUGCU

UAGCAGCACAUAAUGGUUUGUG

UGGAGAGAAAGGCAGUUCCUGA

AUCGGGAAUGUCGUGUCCGCCC

AUAACAUUGUAAAGCGCUUCUUUCG

UAGUGCAAUAUUGCUUAUAGGGU

UCUCCCAACCCUUGUACCAGUG

UGUAAACAUCCUACACUCUCAGC

CAUGCCUUGAGUGUAGGACCGU

UGGGUCUUUGCGGGCGAGAUGA

GUCCAGUU UUCCCAGGAAUCCCU

UAUUGCACUCGUCCCGGCCUCC

CAAAGAAUUCUCCUUUUGGGCU

ACCCCACUCCUGGUACC

UCUAUACAGACCCUGGCUUUUC

UGUCAGUUUGUCAAAUACCCCA

AUCACAUUGCCAGGGAUUACC

UCUAGUAAGAGUGGCAGUCGA

UUAUUGUCACGUUCUGAUU

UGAGACCUCUGGGUUCUGAGCU

ACAGUAGUCUGCACAUUGGUUA

Claims

What is claimed is

1. A method of classifying a sample of a patient suffering from or at risk of developing acute coronary syndrome (ACS) , in particular acute myocardial infarction (AMI), said method comprising the steps of:

a) determining in said sample from said patient, an expres^¬ sion level of at least one miRNA selected from the group con^¬ sisting of miRNA sequences having the SEQ ID NO: 1 to 81 or from a miRNA species which has at least 80% sequence identity with a miRNA species selected from the group consisting of miRNA sequences having the SEQ ID NO: 1 to 81;

b) comparing the pattern of expression level (s) determined in step a) with one or several reference pattern (s) of ex- pression levels; and

c) classifiying the sample of said patient from the outcome of the comparison in step b) into one of at least two clas^¬ ses .

2. A method for diagnosing acute coronary syndrome (ACS), in particular acute myocardial infarction (AMI), in a patient, said method comprising the steps of:

a) determining in a sample from said patient, an expression level of at least one miRNA selected from the group consist- ing of miRNA sequences having the SEQ ID NO: 1 to 81 or from a miRNA species which has at least 80% sequence identity with a miRNA species selected from the group consisting of miRNA sequences having the SEQ ID NO: 1 to 81;

c) diagnosing acute myocardial infarction (AMI) from the outcome of the comparison in step b) .

3. The method according to claim 1 or 2, wherein the sample is selected from the group consisting of blood sample, serum sample, and plasma sample.

4. The method according to any of the preceding claims, wherein diagnosis of acute myocardial infarction (AMI) in^¬ cludes diagnosis of iAP .

5. The method according to claim 4, wherein the one or several reference pattern (s) of expression levels are based one or several reference pattern (s) of expression levels of a subject selected from the group consisting of

- a subject having a predefined range of blood concentration of troponin;

- a subject having chest pain;

- a subject not suffering from cardiovascular disease;

- a subject suffering from instable angina pectoris;

- a subject suffering from NSTEMI; and

- a Subject suffering from STEMI .

6. The method according to any of the preceding claims, wherein step (a) comprises determining the expression level of at least 2, 3, 4, 5, 10, 15, or 20 miRNA species.

7. The method according to any of the preceding claims, wherein the step (b) of comparing comprises determining a probability of the pattern of expression level (s) belonging to one of at least two classes.

8. The method according to any of the preceding claims, wherein the step (b) of comparing comprises applying a dis^¬ criminant function.

9. The method according to any of the preceding claims, wherein the determination of the expression level in step (a) is obtained by use of a method selected from the group con^¬ sisting of a Sequencing-based method, an array based method, a PCR based method, and an immunoassay method.

10. The method according to any of the preceding claims,, wherein step (c) comprises differentiating between a classi- fication or diagnosis of AMI and at least one of the condi^¬ tions selected from

- non-ischemic chest pain

- non-ischemic chest pain and increased troponin concentra- tion

- increased troponin concentration.

11. The method according to any of the preceding claims, wherein step (c) comprises differentiating between a classi- fication or diagnosis of AMI and/or instable angina pectoris (iAP) and a non-pathologic heart condition.

12. The method according to any of the preceding claims, wherein a troponin concentration of >14pg/ml is an increased troponin concentration.

13. The method according to any of the preceding claims,, wherein a troponin concentration of >50pg/ml is an increased troponin concentration.

14. A kit for diagnosing acute myocardial infarction (AMI),

- determining in said sample from said patient, an expression level of at least one miRNA selected from the group con^¬ sisting of miRNA sequences having the SEQ ID NO: 1 to 81 or from a miRNA species which has at least 80% sequence iden^¬ tity with a miRNA species selected from the group consist^¬ ing of miRNA sequences having the SEQ ID NO: 1 to 81, and

15. A computer program product, useful for performing the method according to any of claims 1 to 9, comprising

- means for receiving data representing an expression level of at least one miRNA selected from the group consisting of miRNA sequences having the SEQ ID NO: 1 to 81 or from a miRNA species which has at least 80% sequence identity with a miRNA species selected from the group consisting of the miRNA species No. 1 to 81 as listed in tables 1 to 4,

- means for determining a diagnosis of acute myocardial in- farction (AMI) from the outcome of the comparison in step b) .