BACKGROUND

Angina pectoris, chest pain caused by reduced blood flow to the heart, commonly represents the earliest stage of symptomatic atherothrombotic disease and is a risk factor for myocardial infarction or heart attack. The slow, progressive nature of atherosclerosis means that when angina manifests, the status of the atherosclerotic plaques may be at a stage at which clinical intervention such as stent administration or heart surgery is required. Ideally, such plaque deposit build-up would be identified prior to the requirement for extreme physical intervention and therefore reduce the impact on the patient and the cost associated with surgery and recovery. Angina can also be the result of vasospastic pathophysiology, and this contributes to the complex clinical picture that a clinician must unravel when presented with a patient with intermittent chest pain. A further complication is the occurrence of chest pain caused by non-cardiac medical conditions which include musculoskeletal chest wall pain, anxiety, gastroesophageal reflux disease and oesophageal disorders. The current gold standard of obstructive coronary artery disease diagnosis is the invasive coronary angiogram. Other diagnostic techniques used when a patient presents with intermittent chest pain can include the electrocardiogram (ECG), chest X-ray and echocardiography. Additional simplistic and less invasive diagnostic tools that can be used in support clinical investigation are always being sought. A simple and cost- effective method of identifying disease is through the detection and quantification of protein and small molecule biomarkers in biological samples such as blood, urine and saliva.

SUMMARY OF INVENTION

The invention describes the use of standard clinical biomarkers for use to support the diagnosis of angina and sub-clinical atherosclerosis. It has been found that the measurement in blood of immunoglobulin G (IgG) in combination with one or more of aspartate aminotransferase (AST), platelet count, immunoglobulin E (IgE) and vitamin B ₁₂ can support the diagnosis of angina and sub-clinical atherosclerosis. The combination of IgG and AST with either platelet count and/or IgE, represent the strongest combinations for diagnosis. By using these novel biomarker combinations a cheap, facile and patient-friendly method to support angina diagnosis and sub- clinical atherosclerosis is provided.

Figures

Figure 1. ROC curve corresponding to multiple logistic regression analysis (MLR) of IgG + AST concentrations in angina and age-matched healthy male cohorts.

DETAILED DESCRIPTION OF INVENTION

The invention has highlighted five standard clinical biomarkers, that can be used to support the diagnosis of angina (also referred to as ‘angina pectoris’, in which angina includes stable angina and unstable angina) and sub-clinical atherosclerosis. In a first aspect of the invention is a method of supporting the diagnosis of angina in a patient who has experienced chest pain which comprises measuring in an ex vivo biological sample of the individual the concentration of at least one biomarker chosen from immunoglobulin G (IgG), aspartate aminotransferase (AST), platelet count, immunoglobulin E (IgE) and vitamin B ₁₂ and establishing whether the at least one biomarker is at a concentration/level that indicates angina. This can be established using several methods including comparing the measurements to one or more reference values. A biomarker, also referred to as an analyte herein, is a biological system measurement that can indicate whether a biological system is operating at a level expected of a healthy biological system or one that is operating at a sub-optimal level and that may therefore imply a diseased or dysfunctional biological system. To ascertain whether the measurement represents a possible diseased, damaged, dysfunctional or healthy biological system, the measurement is usually compared to a reference measurement or value. The biological system can a whole organism, usually a mammal, and in the context of the current invention, homo sapiens, or can be a sub-system of the whole organism such as a tissue, organ or a cell. A reference value/levels or normal value/level is a measurement (usually the concentration) of the corresponding analyte or biomarker (IgG, IgE, AST, platelet count or vitamin B ₁₂ ) derived from a suitable control. For example, an individual suspected of having angina has, for example, IgG measured in an in vitro or ex vivo sample and this measurement is compared to an IgG reference value (‘the corresponding analyte’) derived from a control, and the increase or decrease in concentration of IgG in the patient’s sample established. The greater the decrease (IgG, platelet count and vitamin B ₁₂ ) or increase (AST and I g E) of the analyte in the patient sample compared to the reference value, the more supportive the measurement is of a positive diagnosis of angina. The suitable control can be a cohort or group of individuals that does not have angina and/or does not have sub- clinical atherosclerosis. The control is preferably a healthy population without any underlying disease, from which analyte/biomarker measurements are taken to derive the reference level. The individual’s and the population measurements can then be compared as part of the angina diagnosis process. This comparison can take the form a direct comparison of the patient’s measurement values for each individual analyte, with the corresponding individual analytes from the population in which the population measurement values for each individual analyte have been converted to a statistical measure of central tendency e.g. the mean or median or the comparison can utilise both the mean and median. As a hypothetical example, the measurement value of the patient’s IgG obtained from a blood sample is compared to the mean and/or median measurement value(s) of IgG calculated from 50 healthy individual IgG measurements (the reference). If the patient’s IgG value is less than the mean and/or median IgG value(s) calculated for the 50 healthy individuals, then this would support a diagnosis of angina in the patient. If in addition to the patient’s IgG concentration being lower than the mean and/or mean IgG value(s) calculated for the 50 healthy individuals, the patient’s measured concentration of AST is greater than the mean and/or median AST concentration value(s) of the 50 healthy individuals, then this adds further support to a diagnosis of angina in the patient. This approach can be applied to the other analytes; a patient mean and/or median I g E concentration which is greater than mean and/or median reference IgE concentration value(s) supports the diagnosis of angina; a patient mean and/or median platelet count value which is less than the mean and/or median reference platelet count value(s) supports the diagnosis of angina; a patient mean and/or median vitamin B ₁₂ value which is less than the mean and/or median reference vitamin B ₁₂ value(s) supports the diagnosis of angina. The more biomarkers supportive of a diagnosis of angina increases the likelihood that the patient or individual has angina. In a further aspect of the invention is the method of supporting the diagnosis of angina in a patient comprising measuring in an ex vivo biological sample of the individual the concentration of the analyte immunoglobulin G (IgG) and at least one further analyte chosen from aspartate aminotransferase (AST), platelet count, immunoglobulin E (IgE) and vitamin B ₁₂ , wherein each analyte concentration in the ex vivo biological sample of the individual is compared to a reference value of the corresponding analyte to establish an increase or decrease, and in which a decrease in the concentration of IgG, a decrease in the concentration of platelet count, a decrease in the concentration of vitamin B ₁₂ , an increase in the concentration of IgE and an increase in the concentration of AST supports the diagnosis of angina. As an alternative to the use of a comparison of individual patient analyte measurements to a population analyte measurement of statistical central tendency, a suitable mathematical or machine learning classification model based on multiple variable analysis, such as a multiple logistic regression equation, can be derived from existing biomarker measurements of individuals and the derived model used to categorise an individual as having or not having angina and/or sub-clinical atherosclerosis or being healthy. Further examples of multivariate techniques are decision trees, artificial neural networks, random forests, principal component analysis and support vector machine learning. These various multivariate statistical techniques are also referred to herein as ‘statistical methodologies’. When using a statistical methodology as part of the methods of the invention an output value is produced. The output value of the statistical methodology either supports a diagnosis of angina or does not support a diagnosis of angina. For example, for ‘Disease X’ diagnosis, when using MLR as the statistical methodology, a cut-off value is applied to the model and depending on whether the MLR output is greater or less than the cut-off value determines whether or not a diagnosis of ‘Disease X’ is supported. The output value or output of the statistical methodology can comprise any symbol or alphanumerical character, but usually comprises or consists of numerical characters. ROC curve analysis using the AUC statistic is a method of assessing the multiple logistic regression model diagnostic power. The AUC, the area under the curve of a receiver operating characteristic curve (ROC curve), is deemed to have adequate diagnostic power if at a level of 0.70 or greater, of 0.75 or greater, preferably 0.80 or greater, more preferably 0.85 or greater. Examples of biomarker combinations for use in the invention include IgG + AST + platelet count (also referred to as ‘platelets’ herein) + IgE + VitBi ₂ , IgG + AST + platelets + IgE, IgG + AST + platelets + VitBi ₂ , IgE + AST + platelets + VitBi ₂ , IgG + platelets + IgE + VitBi ₂ , IgG + AST + IgE + VitBi ₂ , IgG + AST + platelets, IgG + AST + IgE, IgG + AST + VitBi ₂ , IgG + IgE + VitBi ₂ , IgG + platelets + IgE, IgG + platelets + VitBi ₂ , AST + IgE + platelets, AST + IgE + VitBi ₂ , AST + IgE + VitBi ₂ , AST + platelets + VitBi ₂ , IgE + platelets + VitBi ₂ , IgG + AST, IgG + platelets, IgG + IgE, IgG + VitBi ₂ , AST + IgE, AST + platelets, AST + VitBi ₂ , platelets + IgE, platelets + VitBi ₂ , lgE+ VitBi ₂ . Preferred biomarker combinations are shown in Table 3. The reference value can also be one or more biomarker measurement values taken from the individual who has or who is suspected of having angina derived from the individual at an earlier time-point when the individual did not have angina; the one or more biomarker measurement values can also be multiple measurements from same analyte which are compared individually to the suspected angina measurement value or can be grouped together and compared as a measure of central tendency e.g. the mean or median to the suspected angina measurement value. It has been found that a decrease in the concentration of IgG, platelet count and vitamin B ₁₂ and an increase in the concentration of IgE and AST compared to one or more reference values supports the diagnosis of angina. The biological sample can be any ex vivo biological sample from which the levels of biomarkers can be determined. Preferably, the sample isolated from the patient is a whole blood, plasma or serum sample. Most preferably, the sample is a serum sample. The determination of the level of biomarkers may be carried out on one or more samples obtained from the patient. The use of the polyclonal antibody for IgG measurement (anti-IgG pAb was derived by immunising a goat with human IgG) means that the pAb used in the assay likely detects all four isoforms of IgG in serum and that the decrease detected in IgG in the angina cohort could be to a decrease in one or more of I gG 1 , I gG2, lgG3 and lgG4. In a further aspect, there is described the use of IgG in combination with AST as a biomarker of angina. IgG in combination with AST means that the concentration values of both IgG and AST measured in an in vitro sample taken from an individual suspected of having angina, at risk of having angina or known to have angina, are used to assess whether the individual has angina or to confirm that the individual has angina.

Platelet count and/or IgE can be added to combination of IgG and AST and the resultant combinations be used as biomarkers of angina. In all the methods and uses described it is likely that there will be accompanying clinicial results and information relating to the individual that will support a diagnosis relating to angina. That atherosclerosis up until the onset of initial symptoms, as manifest through angina, is represented by a continuum of plaque build-up, the biomarkers disclosed herein would also likely be present at a level similar to that seen following the onset of angina and the instance prior to an episode of angina and could also find application in identifying sub-clinical atherosclerosis. Age is a risk factor in the development of atherosclerosis; the median levels of the analytes used in the methods of the invention to support the diagnosis of angina can be seen to be greater in the healthy older cohort compared to the healthy younger cohort (T able 1 ), further supporting their use to diagnose sub-clinical atherosclerosis. Thus, in a further aspect of the invention each of the biomarker combinations described previously to be used to support the diagnosis of angina, can also be used to diagnose sub-clinical atherosclerosis, sub-clinical atherosclerosis being atherosclerosis that has yet to be diagnosed. By identifying sub-clinical atherosclerosis in an individual more acute clinical pathologies related to atherosclerosis such as heart attack and stroke can be avoided through medication and/or behavioural changes. There are various instances in which the biomarkers could have application. An individual without chest pain undergoes a routine blood test and the biomarkers of the invention indicate sub- clinical atherosclerosis; the individual is then alerted to possible disease and can then acquire clinical advice and further testing to assess whether atherosclerosis is present and if positive can respond to the findings. An individual with intermittent chest pain undergoes a blood test and the biomarkers indicate that angina could be present; this is followed up by clinical assessment and advice, and possible further alternative diagnostic testing, prescribed medication and/or recommended behavioural adaptation. A clinician suspects an individual is subject to angina; the clinician orders a blood test to assess if the biomarkers support the diagnosis of angina.

Methods and Results

Patients

The angina cohort (N= 15) is represented by non-smoking males aged 47-73 years who have been clinically diagnosed with angina and who do not have obstructive coronary artery disease. The angina cohort incorporates individuals with either stable angina or unstable angina, the former being chest pain usually associated with exertion or stress, the latter unexpected chest pain usually occurring while resting. Most individuals in this cohort were taking statin and/or blood pressure medication. The control cohorts were i. non-smoking males aged 47-73 years (N=300) and ii. non-smoking males aged 21-29 years (N=100), each cohort with no reported underlying conditions and no reported medication regime. All males were resident in Northern Ireland at the time of blood draw. Samples were taken and analysed over the period 2017-2019 at Randox Laboratories RCLS. The patient attended a Randox Health clinic and urine and blood samples were collected from the patient, a physical examination conducted and a health report form completed. Blood samples were stored at 2-8°C until same-day analysis. The physical examination included measuring weight, height, blood pressure, body fat measurements, reflex measurements and reflex tests. The samples were processed and analysed using Randox clinical analysers and other analysers from various manufacturers. The individuals of the angina cohort were each subject to statin therapy and just over half of the cohort were also on blood pressure medication. The statins were found to significantly lower LDL and total cholesterol in the angina cohort. A previous study (GB application number 2116132.8) found that statins and blood pressure medication did not affect blood levels of AST, platelet count, vitamin B ₁₂ and IgE in males, while IgG levels were found to increase slightly in males on blood pressure medication.

Analyte analysis

The biomarkers analysed comprised a comprehensive set of over 150 clinical analytes and tests including: haemoglobin, haematocrit, mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), red blood cell mean volume (MCV), red blood cell count, basophil count, eosinophil count, lymphocyte count, monocyte count, neutrophil count, white blood cell count, platelet count, iron, ferritin, total iron binding capacity (TIBC), transferrin, transferrin saturation, total cholesterol, LDL cholesterol, HDL cholesterol, total cholesterol:HDL cholesterol ratio, triglycerides, apolipoprotein A-l, apolipoprotein B, apolipoprotein B:A-I ratio, apolipoprotein Cll, apolipoprotein CHI, apolipoprotein E, small LDL cholesterol, lipoprotein (a), high sensitivity C-reactive protein (hs-CRP), cardiovascular risk score, heart-type fatty acid binding protein (hFABP), HbA1c, insulin, glucose, triglycerides, HbA1c, insulin, C-peptide, leptin, adiponectin, resistin, creatinine, estimated glomerular filtration rate (eGFR), cystatin C, calcium, chloride, magnesium, phosphate, potassium, sodium, urea, uric acid, total bilirubin, ketones, nitrites, protein, red blood cells, calcium adjusted, urobilinogen, white blood cells (WBC), alanine aminotransferase (ALT), alkaline phosphatase (ALP), aspartate aminotransferase (AST), gamma-glutamyltransferase (GGT), albumin, pancreatic amylase, lipase, H. pylori, antitissue transglutaminase antibodies, total antioxidant status, (TAS), folic acid, vitamin B ₁₂ , vitamin D, creatinine kinase, rheumatoid factor, parathyroid hormone (PTH), immunoglobulin E (IgE), C-reactive protein (CRP), complement component 3 (Comp C3), complement component 4 (Comp C4), immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), antistreptolysin O (ASO), thyroid stimulating hormone (TSH), free thyroxine (FT4), free tri-iodothyronine (FT3), anti-thyroglobulin antibody (Anti-Tg), antithyroid peroxidase antibody (Anti-TPO), oestradiol, follicle stimulating hormone (FSH), luteinising hormone, progesterone, prolactin, testosterone, sex hormone binding globulin (SHBG), free androgen index (FAI), total prostate specific antigen (TPSA), interleukin-6 (IL-6), interleukin-1 beta (IL-1 ), tumour necrosis factor alpha (TNF-a), monocyte chemoattractant protein 1 (MCP-1), macrophage inflammatory protein 1 alpha (Ml P-1 a). A full list of analytes measured can be obtained by referring to Everyman, Everywoman and Signature biomarker analysis tests, Randox Health, Crumlin, County Antrim, Northern Ireland, UK. The immunoglobulin G (IgG) immunoturbidimetric assay (Randox Laboratories, catalogue number IG8044) was run on a Randox Modena automated analyzer according to the manufacturer’s instructions and uses purified goat anti-human IgG polyclonal antibody. Tests showed the purified antibody to be specific to the Fc portion of human IgG with no cross-reactivity towards the light chain of human IgG or other human immunoglobulins IgA, IgE, IgM and IgD. The immunoglobulin E (IgE) immunoturbidimetric assay (Randox Laboratories, catalogue number IE7308) was run on a Randox Imola automated analyzer according to the manufacturer’s instructions and uses a mouse monoclonal anti-human IgE antibody attached to latex particles. The aspartate aminotransferase (AST) assay was run on the Randox Imola according to the manufacturer’s instructions (Randox Laboratories, catalogue number AS 3804). The platelet count assay was part of a full blood count assay run on a Sysmex XN-550 haematology analyzer according to the manufacturer’s instructions. The Roche Elecsys vitamin B12 II assay was run a cobas analyzer according to the manufacturer’s instructions. Statistical Analysis

Population data: two-tail unpaired t-test, with data transformation where appropriate for normalisation, Mann-Whitney and Kruskal-Wallis statistics were used for comparison of the angina and healthy population data for all analytes. These results helped inform multiple logistic regression analyses of various biomarker measurement combinations. The initial statistical analysis of the different male cohorts did not indicate any significant statistical difference in platelet count levels between the different cohorts, hence platelet count was not included as a biomarker during initial model formulation. Platelets were later included in the logistic regression analysis because it was noticed through data inspection that lower IgG levels in the angina cohort were accompanied by lower platelet counts. All calculations were effected using Graphpad Prism 9.02 software; a P-value of less than 0.10 was considered to be statistically significant.

Results

Table 1. Median values of selective analytes in three male cohorts (non-smokers): 1/ males aged 47-73 years with angina 2/ males aged 47-73 years with no reported conditions (healthy) 3/ males aged 21-29 years with no reported conditions.

Analyte units: AST U/l, IgE kll/l, IgG g/l, Vitamin B ₁₂ ng/l, Platelets (count) 10 ⁹ /l

Table 2. Statistical analysis of analytes in different male cohorts. Angina = males aged 47-73 years (yrs); non-Angina age-matched = healthy males aged 47-73 years; and non-Angina 21-29 years = healthy males aged 21-29 years. Numbers represent Kruskal-Wallis statistic (Analyte column) with Dunn’s multiple comparisons (right Cohort columns).

Table 3. ROC curve AUCs for various MLR models and representative sensitivity and specificity values for different combinations of AST, IgE, IgG and vitamin B ₁₂ (Vit B12) in males with angina aged 47-73 years vs healthy males aged 47-73 years.

Table 3 confirms the potential use of a combination of biomarkers for supporting the diagnosis of angina, the biomarker combination incorporating at least one of IgG and AST and one or more of IgE, platelet count (platelets) and vitamin B12 having an acceptable AUC. Biomarker combinations incorporating IgG, and IgG plus AST are shown to have the greatest diagnostic power, having AUCs >0.75. These biomarkers can support a diagnosis of angina or sub-clinical atherosclerosis in a patient. The interpretation of the diagnostic biomarker measurements can be supported by the assessment of a clinician who may also make use of the results of the patient’s clinical history and results from other diagnostic tools such as echocardiography, X-ray analysis, CAT and MRI scans when formulating a diagnosis.