Biomarkers for improved blood pressure diagnostics

Abstract

Biomarkers of hypertension are described for use in diagnosis, prognosis and to support standard inflatable cuff measurements for improved blood pressure measurement certainty.

Description

[0001] BIOMARKERS FOR IMPROVED BLOOD PRESSURE DIAGNOSTICS

[0002] BACKGROUND

[0003] Blood pressure is a critical health status indicator. High blood pressure affects a quarter of adults and is a risk factor for numerous life-threatening conditions including heart disease, heart attacks, stroke, heart failure, peripheral arterial disease, aortic aneurysms, kidney disease and vascular dementia. Regulation is mainly effected by the cardiovascular, neuroendocrine and renal systems, water and sodium management by the kidneys ensuring systemic fluid balance and long-term blood pressure homeostasis while magnitude is determined by the amount of blood pumped out of heart into the arteries, the resistance of the arteries and the rate at which blood flows out of the arteries. High blood pressure or hypertension is categorised as essential (primary) and non-essential (secondary), the former being hypertension lacking an identifiable cause and represents approximately 95% of all hypertension cases. A sphygmomanometer, an electronic or mechanical device linked to an inflatable cuff which is normally attached to the upper arm, is the standard measurement means from which systolic and diastolic blood pressure values are derived using the auscultatory or oscillometric methods. The devices are provided by numerous manufactures constructed to different specifications (notably the inflatable cuff) and this diverse construction configuration results in a degree of variation in inter-device measurement reading and output. Principal measurement uncertainty include inconsistencies in cuff attachment, cuff size relative to arm size, soft tissue compressibility and fluctuations in blood pressure, including stress- induced transient increases in blood pressure which can be provoked by a clinic environment or the act of taking a blood pressure reading (Palatini 2018). It is estimated that unstandardized blood pressure measurement leads to between a 20 and 45 percent error rate in clinical management decisions (Padwal 2019). In addition, authoritative medical organisations describe different blood pressure measurement values and non-standardised guidelines for its measurement (Brouwers 2021 ). The UK National Health Service (NHS) guidelines provide several blood pressure values and ranges depending upon blood pressure category, age and location. The British Heart Foundation (BHF) describes two categories of normal blood pressure: for individuals 80 years of age and under normal blood pressure is usually considered to be between 90 to 120 mm Hg systolic and between 60 to 80 mm Hg diastolic while high-normal blood pressure or pre-hypertension is considered to be between 120 to 140 mm Hg systolic and between 80 to 90 mm Hg diastolic. High blood pressure is greater than 140 mm Hg systolic and greater than 90 mm Hg diastolic and is composed of three categories. The BHF has further adjustments for home-based measurements. The American College of Cardiology (ACC) and the American Heart Association (AHA) divide blood pressure into four general categories; ideal blood pressure is categorized as normal and is systolic blood pressure < 120 mm Hg and diastolic blood pressure < 80 mm Hg, elevated blood pressure is systolic blood pressure 120 to 129 mm Hg and diastolic blood pressure < 80 mm Hg, stage I hypertension systolic blood pressure is 130 to 139 mm Hg diastolic blood pressure is 80 to 89 mm Hg and stage II hypertension is > 140 mm Hg or diastolic blood pressure is > 90 mm Hg. The various blood measurement categories proposed by different healthcare institutions also incorporate a different range of values for the elderly. Management and treatment of hypertension can be based on lifestyle modification including exercise, weight loss and a low salt diet and more commonly medication. Hypertension medication is critical to prevent lifethreatening conditions although there are shortcomings. Approximately 20 percent of medicated individuals do not achieve their blood pressure goals (treatment-resistant hypertension), side-effects are common and there is an economic downside when anti-hypertensive drugs are prescribed to non-hypertensive (normotensive) individuals. Intervention to stabilise or reverse abnormal blood pressure is most likely to succeed at the early stages of the onset of blood pressure rises when behavioural management alone can be an effective therapy. Identifying the early stages of hypertension also has financial benefits by reducing the possibility of an adverse event and the associated healthcare costs and by minimising drug prescribing. The measurement of biochemicals derived from biological samples is an alternative approach to the detection of hypertension. Protein biomarkers from platelets have been proposed in DE102008063290A1 for use in determining a high blood pressure of >149 / 90 mmHg. Shere (2017) provides a review of biomarkers related to pathophysiology and essential hypertension categorised according to vascular dysfunction, inflammation and oxidative stress and hypertension prediction. Given the importance of accurate and consistent blood pressure monitoring there is a need to reduce the uncertainty associated with standard blood pressure measurement especially at the onset of hypertension.

[0004] References

[0005] Brouwers S. et al. (2021 ). Arterial Hypertension. Lancet, 398:249-261.

[0006] Padwal R.et al. (2019). Optimizing observer performance of clinic blood pressure measurement: a position statement from the Lancet Commission on Hypertension group. J. Hypertens., 37: 1737-1745.

[0007] Palatini P. and Asmar R. (2018). Cuff challenges in blood pressure management. J. Clin. Hypertens., 20(7):1100-1103.

[0008] Shere A. et al. (2017). Circulating blood biomarkers in essential hypertension: a literature review. J. Lab Precis. Med., 2:99.

[0009] SUMMARY OF THE INVENTION

[0010] The current disclosure relates to the use of blood biomarkers to identify hypertension, increased risk of hypertension or to support the diagnosis of hypertension in males. The biomarkers can be used independently, or they can be used with traditional blood pressure measurement methods. The biomarkers used in the methods are associated with diverse biological systems and are chosen from alanine aminotransferase (ALT), anti-streptolysin O (ASO), aspartate aminotransferase (AST), calcium (Ca), chloride (Cl), free thyroxine (FT4), haematocrit count (Het), immunoglobulin A (IgA), potassium (K), small dense low- density lipoprotein (smLDL) and thyroid stimulating hormone (TSH). The methods incorporate the measurement of the concentration of at least two of the biomarkers in at least one biological sample of an individual and the measurement values obtained are used to highlight possible hypertension in the individual and to support decisions relating to hypertension management. The disclosure also describes a method of hypertension biomarker identification based on cohort-specific selection which omits individuals with elevated blood pressure. In a first aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension comprising measuring the concentration of at least two biomarkers in an in vitro biological sample of an individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual has hypertension or an increased likelihood of hypertension, the at least two biomarkers being chosen from at least one of IgA and ASO, and at least one of chloride, calcium and potassium. In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension comprising measuring the concentration of at least three biomarkers in an in vitro biological sample of an individual and inputting each of the measured amounts into a statistical model whose output value indicates has hypertension or an increased likelihood of hypertension, the at least three biomarkers being chosen from at least one of ASO and IgA, at least one of chloride, calcium and potassium, and at least one of AST, ALT, FT4 and TSH .

[0011] In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension comprising measuring the concentration of at least three biomarkers in an in vitro biological sample of an individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual likely has hypertension, the at least three biomarkers being chosen from at least one of ASO and IgA, at least one of chloride, calcium and potassium, and at least one of AST, ALT, FT4, TSH and Het.

[0012] In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension comprising measuring the concentration of at least three biomarkers in an in vitro biological sample of an individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual likely has hypertension, the at least three biomarkers being chosen from at least one of ASO and IgA, at least one of chloride, calcium and potassium, and at least one of AST, ALT, FT4, TSH, Het and smLDL.

[0013] In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension comprising measuring the concentration of a biomarker in an in vitro biological sample of an individual and inputting the measured amount into a statistical model whose output indicates whether the individual likely has hypertension, the construction of the statistical model being supported by measurements obtained from two cohorts of individuals, one cohort which has individuals of normal blood pressure and one cohort which has individuals with hypertension in which normal blood pressure is <120 mm Hg systolic blood pressure and high blood pressure is >129 mm Hg systolic blood pressure. By using these cohorts and omitting measurements from the central-lying hypertensive cohort (systolic blood pressure 120-129 mm Hg ) more accurate data-sets are used to derive biochemical correlates of normal blood pressure and hypertension.

[0014] When the described biomarker method is used ‘to support the diagnosis of hypertension’ an assessment of one or more systolic and diastolic blood pressure measurement values of the individual is incorporated in the method. The blood pressure measurement values of the individual used to support the diagnosis of hypertension can be obtained using any suitable blood pressure analytical method, but they are preferably obtained using a sphygmomanometer

[0015] In a further aspect there is described a method of identifying an individual at increased risk of hypertension or increased risk of developing hypertension comprising measuring the concentration of two or more biomarkers chosen from ASO, IgA, calcium, chloride, potassium in in vitro samples of the individual obtained at two different time points and establishing whether a change in the concentration in two or more of the biomarkers is indicated between the two different time points in which an increase in the concentration of IgA, an increase in the concentration of calcium, a decrease in the concentration of chloride, a decrease in the concentration of ASO and a decrease in the concentration of potassium between first and second time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension the at least two biomarkers being chosen from at least one of IgA and ASO, and at least one of chloride, calcium and potassium. One or more of ALT and AST can also be measured at two different time points and an increase in concentration of ALT and an increase in concentration of AST between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension. One or more of FT4 and TSH can also be measured at two different time points and a decrease in concentration of FT4 and an increase in concentration of TSH between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension. Het can also be measured at two different time points and an increase in concentration of Het between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension. smLDL can also be measured at two different time points and an increase in concentration of smLDL between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension. This method of monitoring a concentration change between two time points benefits from being readily and easily interpretable by both the clinician and the patient.

[0016] In a further aspect there is described a method of supporting the assessment of the efficacy of an anti-hypertensive drug in decreasing high blood pressure in an individual who has been prescribed an anti-hypertensive drug comprising measuring the concentration of two or more biomarkers in an in vitro sample of the individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual has normal blood pressure, the at least two biomarkers being chosen from at least one of IgA and ASO, and at least one of chloride, calcium and potassium.

[0017] In a further aspect there is described a method of supporting the assessment of the efficacy of an anti-hypertensive drug in decreasing high blood pressure in an individual comprising measuring the concentration of two or more biomarkers chosen from ASO, IgA, calcium, chloride, potassium in in vitro samples of the individual obtained at two different time points and establishing whether a change in the concentration in two or more of the biomarkers is indicated between the two different time points, in which at the first time point the individual is not being prescribed the anti-hypertensive drug and at the second time-point the individual is being prescribed the anti-hypertensive drug, in which a decrease in the concentration of IgA, a decrease in the concentration of calcium, an increase in the concentration of chloride, an increase in the concentration of ASO and an increase in the concentration of potassium between the two time points is indicative that the antihypertensive drug has decreased the blood pressure of the individual. One or more of ALT and AST can also be measured at two different time points and an increase in concentration of ALT and an increase in concentration of AST between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension. One or more of FT4 and TSH can also be measured at two different time points and a decrease in concentration of FT4 and an increase in concentration of TSH between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension. Het can also be measured at two different time points and an increase in concentration of Het between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension. smLDL can also be measured at two different time points and an increase in concentration of smLDL between the two time points is indicative that the individual is at an increased risk of hypertension or at an increased risk of developing hypertension.

[0018] Figures

[0019] Figure 1 Schematic depicting the patient data sources for preliminary biomarker selection. Population cohorts represented by i. unmedicated healthy males who recorded a systolic blood pressure (BP) measurement value corresponding to stage I or stage II hypertension ii. unmedicated healthy males who recorded a BP measurement value corresponding to normotensive. Population data from unmedicated healthy males who recorded a BP measurement value corresponding to an elevated systolic blood pressure does not contribute to preliminary biomarker selection.

[0020] Figure 2 Biomarkers of the disclosure grouped by biological system. Upward facing arrow indicates that the biomarker concentration is greater in HT individuals compared to normotensive individuals, downward facing arrow indicates that the biomarker concentration is lower in HT individuals compared to normotensive individuals.

[0021] Figure 3 Representative statistical methodology showing multiple logistic regression graph of normotensive and hypertensive (HT) cohorts. Each cohort is represented by healthy, unmedicated males aged 30-60 years of matched BML The hypertensive individuals were categorised as such upon registering an inflatable cuff systolic BP measurement of >129 mm Hg or normotensive upon registering an inflatable cuff systolic BP measurement of <120 mm Hg when attending a Randox Health clinic for biomarker blood sampling and analysis. Figure 4 Representative statistical methodology showing how the use of increases / decreases in a sub-set of the hypertension biomarkers can indicate the blood pressure trajectory of an individual. Time-point 1 represents the normalised baseline concentrations of AST, Ca, Cl, Het and IgA measured in a blood sample. Time-point 2 shows the relative concentrations of the biochemicals relative to the baseline concentrations measured in a blood sample obtained 6-months later. Even if the individual’s blood pressure reading indicates normotensive, an increase in the concentrations of each of AST (aspartate aminotransferase), Ca, Het and IgA and a decrease in the concentration of Cl over time indicates a trajectory towards a hypertensive state. The lower diagram also suggests an individual on a trajectory towards hypertension.

[0022] DETAILED DESCRIPTION OF THE INVENTION

[0023] Hypertension is a common medical condition and a risk factor for multiple pathologies including stroke, coronary artery disease and kidney disease and its reliable diagnosis is critical to enable its reversal and management through medication and behavioural interventions. However, its common method of measurement, the inflatable cuff, is prone to measurement imprecision and inaccuracy. This unreliability is especially impactful at the early stages of high blood pressure onset, the point at which behavioural intervention is most effective and the desirable avoidance of long-term medication is most likely. The current disclosure describes a biochemical approach to identify high blood pressure which can be used independently to identify a hypertensive individual or support the standard inflatable cuff blood pressure measurement method to produce more precise and accurate diagnoses. It has been found that the measurement of novel combinations of standard clinical biochemicals can be used to reduce the uncertainty of blood pressure measurement values obtained using an inflatable cuff. Furthermore, as biochemicals in biological samples such as blood are not subject to the measurement uncertainty associated with the hand-attached inflatable cuff of blood pressure measurement devices by using population blood pressure measurements obtained using an inflatable cuff together with biochemical measurements, biochemical profiles can be matched to blood pressure measurement ranges and can be used to define a more accurate blood pressure status of an individual. There is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension in an individual comprising measuring the amount of at least two biomarkers in an in vitro biological sample of the individual and inputting each of the measured amounts into a statistical model whose output or output value indicates whether the individual has an increased likelihood of hypertension or has hypertension, the at least two biomarkers being chosen from ALT, ASO, AST, Ca, Cl, FT4, Het, IgA, K, smLDL and TSH. Following a comparative study of normotensive and hypertensive cohorts in which a multitude of biochemicals, many of which were standard clinical biochemicals as they are routinely tested in diagnostic healthcare for biological homeostatic dysfunction and disease identification, ALT, ASO, AST, Ca, Cl, FT4, Het, IgA, K, smLDL and TSH were found to be at different concentrations in normotensive individuals compared to hypertensive individuals. The term ‘biomarker’ as used herein refers to a protein or physiological indicator in a biological sample obtained from an individual the concentration or value of which of which may be indicative of a pathological state. An individual having an ‘increased likelihood’ or ‘increased risk’ of hypertension means the individual has a greater probability of being hypertensive than normotensive. The term supporting the diagnosis of hypertension implies that biochemical measurements are a secondary indicator of blood pressure status and that standard sphygmomanometer blood pressure readings are the primary diagnostic tool for identifying hypertension, hence both biochemical measurement values and blood pressure measurement values of an individual are used to assess the individual’s blood pressure; ranges for the different blood pressure categories can be interpreted using any recognised blood pressure guideline such as those of the European Society of Hypertension (ESH), the NHS, the British Heart Foundation, the AHA, and the ACC. When used as support for hypertension diagnosis, a blood pressure measurement of the individual is taken using a sphygmomanometer at the time at which a biological sample is obtained. By utilising two indicators of blood pressure status, biochemical levels and sphygmomanometer readings, a more reliable and accurate blood pressure status of the individual can be ascertained allowing improved clinical management decisions to be made. Hypertension is considered a multi-factorial disease and the findings of the study support this as the identified biochemicals are typically associated with diverse biological systems (Figure 2). ASO and IgA are immune system related. ASO or anti-streptolysin O, are antibodies produced to the streptolysin O toxin produced by streptococcal bacteria whose increased concentration can be indicative of a recent or current infection.

[0024] Immunoglobulin A (IgA) is active predominantly in mucosal areas of the body such as the mouth, lungs and intestines. The electrolytes chloride, calcium and potassium, commonly associated with kidney function, have multi-functional physiological roles including regulating osmotic pressure, acid-base homeostasis, muscle contraction and nerve conduction. Calcium has also been implicated in cardiovascular disease. AST and ALT are enzymes used in amino acid metabolism which are commonly used clinically as indicators of liver health. FT4 and TSH are associated with the thyroid gland and are involved in metabolism regulation. Haematocrit count represents the percentage of total blood volume occupied by red blood cells and is commonly used in the diagnosis of anaemia. smLDL, a sub-type of low-density lipoprotein (LDL), is a lipoprotein and cholesterol transport protein and is a risk factor of cardiovascular disease.

[0025] In an embodiment of the disclosure there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension in an individual comprising measuring the amount of at least two biomarkers in an in vitro biological sample of the individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual has an increased likelihood of hypertension or has hypertension or supports the diagnosis of hypertension, the at least two biomarkers being chosen from at least one of ASO and IgA, and at least one of chloride, calcium and potassium. When two or more biomarkers are used in the biochemical method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension, a suitable mathematical or statistical model based on multiple variable analysis, such as a logistic regression equation, can be derived from biomarker measurements of a group of individuals and the model used to categorise a single individual as more likely being hypertensive or normotensive. The significance of the levels of the biomarkers, i.e. categorisation of the individual as either hypertensive or normotensive (normal blood pressure) can be established by inputting the biomarker concentration values into a model. Such a classification model may be chosen from one capable of analysing multiple variables (two or more variables), such as decision trees (aka ‘classification trees’), K-nearest neighbour, artificial neural networks, regression methods such as logistic regression, random forests, principal component analysis, support vector machine or any other similar classification method known in the art. The output of the models used indicates whether an individual possesses or is more likely (has an increased likelihood) to possess a hypertensive biochemical phenotype or a normotensive biochemical phenotype. Such an output could be a numerical value, for example a number representing a probability, an odds value, an odds ratio value, a risk ratio / relative risk value or categorical output such as ‘yes’ or ‘no’ or ‘high risk’, ‘low risk’, ‘more likely’ or ‘less likely’ etc. Multiple logistic regression is a statistical model that can be used in the described diagnostic methods. The diagnostic accuracy of a logistic regression model for various biomarker combinations is described by the area under the curve value (AUC) which can take values from 0.5 to 1 .00. A high degree of diagnostic accuracy is usually ascribed to a test or assay when an AUC value is greater than about 0.800, preferably greater than about 0.850 and more preferably greater than about 0.900. The logistic regression equation computed from the data can be used to predict whether an individual, following biochemical analysis and data collection, is more probable or more likely to be of a normotensive biochemical phenotype or of a hypertensive biochemical phenotype. A further method that can be used to identify an increased likelihood of hypertension or to monitor progression towards or away from hypertension is to track the concentration fluctuation of two or more individual biomarkers by taking and analysing samples from an individual at different time points. Measuring biomarker concentrations in an individual at different time-points can also be referred to as individual serial testing or measurement and could be incorporated into a decision tree statistical methodology. If two or more of the biomarkers displays a concentration trend in the direction consistent with a hypertensive biochemical phenotype over two or more consecutive time-points, this indicates an undesirable trend and preventative measures can be initiated to arrest or reverse the trend. In this method, the initial measured individual biomarker concentrations at time-point 1 can each be classed as a control value, to which ensuing measurements at time-points 2,3,4 etc, can be compared; subsequent timepoint measurements can also be compared to each other. A pictorial representation is provided Figure 4. The biomarkers IgA, calcium, AST, ALT, HcT, smLDL and TSH would show an increasing concentration trend in the transition towards a hypertensive biochemical phenotype, and ASO, chloride, potassium and FT4 would display a decrease. The different time points could be separated by weeks, months or years depending upon the analytical granularity required by the individual or as recommended by a clinician. For example, an individual at a first time-point has a blood sample taken and numerous biochemicals analysed and has a blood pressure reading of 119 / 79 mmHg and each of the hypertension biomarkers of the described methods were within the population normal reference range i.e. no pathology is indicated. Six months later the individual has a blood pressure reading of 128 / 80 mmHg and a further blood sample is taken and the same biochemicals are analysed which show that compared to the previous biochemical analysis IgA, calcium and AST each increase in concentration and ASO, potassium and chloride both decrease in concentration whilst remaining within the population normal reference range. This suggests that the individual has an increased likelihood of hypertension or is a increased risk of developing hypertension. Thus, an advantage of this method is that even though hypertension biomarker concentrations are within recognised healthy ranges, hypertension or developing hypertension could be present and by highlighting this a hypertension management program initiated. In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension in an individual comprising measuring the amount of at least three biomarkers in an in vitro biological sample of the individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual has an increased likelihood of hypertension or has hypertension or supports the diagnosis of hypertension, the at least three biomarkers being chosen from at least one of ASO and IgA, at least one of chloride, calcium and potassium and at least one of AST or ALT.

[0026] In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension in an individual comprising measuring the amount of at least four biomarkers in an in vitro biological sample of the individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual has an increased likelihood of hypertension or has hypertension or supports the diagnosis of hypertension, the at least four biomarkers being chosen from at least one of ASO and IgA, at least one of chloride, calcium and potassium, at least one of AST or ALT and at least one of TSH and FT4 .

[0027] In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension in an individual comprising measuring the amount of at least five biomarkers in an in vitro biological sample of the individual and inputting each of the measured amounts into a statistical model whose output value indicates whether the individual has an increased likelihood of hypertension or has hypertension or supports the diagnosis of hypertension, the at least five biomarkers being chosen from at least one of ASO and IgA, at least one of chloride, calcium and potassium, at least one of AST or ALT, at least one of FT4 and TSH and at least one of haematocrit count and smLDL. It has been found that by increasing the number of biomarkers the diagnostic accuracy of the statistical model can be increased as exemplified by an increase in the AUC (Table 2). An example of a statistical model for identifying a male normotensive biochemical phenotype vs a hypertensive biochemical phenotype uses multiple logistic regression (MLR). Using the biomarker combination of calcium, IgA and ASO based on the sample cohorts described in the Methods and Results section, the MLR equation is:

[0028] Y= -31 .07 + 13.51 [calcium] + 9.880[log 1 olg A] - 2.929[log ASO] with a classification cut-off of 0.5 (AUC for this combination is 0.8636 - see Table 2). Following input of the concentration values for calcium, IgA and ASO measured in an in vitro blood sample of an individual, if Y is above zero for the individual then the presence of a hypertensive biochemical phenotype in the individual is supported, whereas if Y is below zero the presence of a normotensive biochemical phenotype is supported. The probability of an individual having hypertension can be computed from the above equation using 1 / (1 + eY). This data can be supported by or be supportive of a blood pressure measurement using a sphygmomanometer. The biomarker coefficients of the equation will show variation with a different classification cut-off or if data from additional individuals is added to the model over time. Such minor modification of the coefficients would apply whichever statistical methodology was applied but this does not diminish the utility of the identified biomarkers to identify hypertension independently or as a support to inflatable cuff measurements. Although multiple logistic regression is exemplified, use of similar- suited statistical methodologies can be used to categorise an individual as being of a normotensive or hypertensive biochemical phenotype using the identified biomarkers. In a further aspect there is described a method of diagnosing or identifying an increased likelihood of hypertension, or supporting the diagnosis of hypertension in an individual comprising measuring the amount of a biomarker in an in vitro biological sample of the individual and inputting the measured amounts into a statistical model whose output value indicates whether the individual has hypertension, in which the statistical model is derived using measurements obtained from two cohorts of unmedicated individuals, one cohort which has individuals of normal blood pressure and one cohort which has individuals with hypertension in which normal blood pressure is <120 mm Hg systolic blood pressure and hypertension is >129 mm Hg systolic blood pressure (Figure 1 ). Systolic blood pressure is clinically considered to be the main indicator of high blood pressure and this measure was the main driver of cohort categorisation. By using population blood pressure measurements corresponding to normotensive and high blood pressure, unmedicated, self-reported healthy cohorts only and omitting measurements from the central-lying elevated blood pressure cohort of systolic BP of 120-129 mm Hg, more accurate data-sets are used to derive biochemical correlates of normal blood pressure and hypertension. Given the variation inherent to inflatable-cuff-based blood pressure measurement which can be as much as 10 mm Hg for systolic blood pressure, omission of data in the model building phase from the central-lying elevated blood pressure cohort which ranges from 120 mm Hg to 129 mm Hg, provides for a more robust model using the hypertensive and normotensive datasets. That is, for the method, the data used to train the statistical methodology used to discriminate between normotensive and hypertensive (but otherwise healthy and unmedicated) males to identify biomarkers of hypertension was derived from a healthy normotensive male cohort of systolic BP <120 mm Hg and an unmedicated hypertensive male cohort without co-morbidities of systolic BP >129 mm Hg.

[0029] In a further aspect is a method of supporting the assessment of the efficacy of an anti-hypertensive drug in decreasing high blood pressure in an individual comprising measuring the concentration of two or more biomarkers chosen ALT, ASO, AST, calcium, chloride, FT4, IgA, potassium, haematocrit count, smLDL and TSH in vitro samples of the individual obtained at two different time points whereat the first time point the individual is not being prescribed the anti-hypertensive drug and at the second time-point the individual is being prescribed the anti-hypertensive drug; and establishing whether there is a change in the concentration in each of the two or more of biomarkers between the two different time points, in which a decrease in the concentration of IgA, a decrease in the concentration of calcium, an increase in the concentration of chloride, an increase in the concentration of ASO, an increase in the concentration of potassium, a decrease in the concentration of AST, a decrease in the concentration of ALT, an increase in the concentration of FT4, a decrease in the concentration of TSH, a decrease in the concentration of smLDL and a decrease in concentration of Het between the first and second time points is indicative that the anti-hypertensive drug has decreased the blood pressure of the individual. For each of the disclosed methods, where applicable, the first time point chronologically precedes the second time point. Being prescribed the antihypertensive drug means that the individual, due to high blood pressure, is taking the drug as instructed by the GP or clinician; not being prescribed the anti-hypertensive drug means that the individual does not have or is not considered to have high blood pressure and is not taking anti-hypertensive medication. Monitoring whether the biomarker concentrations are following the expected medication trajectory allows for the treatment regimen to be adjusted or changed if unexpected results are observed. The terms biochemical and biomarker are used interchangeably herein. The biological sample obtained from the individual is preferably a blood sample, and the sample analysed is preferably blood, serum or plasma. As used herein, the term ‘in vitro’ has its usual meaning in the art and refers to a sample that has been removed from an individual’s body. When a blood sample is taken from the individual’s body it can be analysed using several analytical methodologies including mass spectroscopy linked to a pre-separation technique such as chromatography. The preferred methodologies use clinical chemistry analysers (described in the Methods and Results section) which are based on immuno and enzymatic reagents.

[0030] In the context of the present invention, a “control value” or simply “control” is understood to be the mean or median concentration of a particular biomarker typically found in healthy individuals of blood pressure <120 / 80 mm Hg. In certain contexts the control value can also be the first biomarker measurement value of an individual who undergoes serial testing for the biomarker; if such a usage is intended this can be gauged from the context. The terms model, methodology, algorithm, formula in the current description can be used interchangeably and represent a statistical equation or method / technique, mathematical equation, algorithmic, analytical or programmed process, that takes one or more continuous or categorical inputs and calculates or produces an output value. Unless otherwise stated, the term “blood pressure” when referring to a measurement, measured value or a measured state e.g. high, low, elevated, normal, implies that the measurement was obtained using a sphygmomanometer, the measurement units being mm Hg unless otherwise stated. The biochemical-based measurement methods described can be used to support traditional inflatable cuff blood pressure measurement(s). Alternatively, the biochemical-based measurement methods described can be used independently of traditional inflatable cuff blood pressure measurement. By using both standard blood pressure measurements and biochemical-based blood pressure categorisation, greater confidence in the diagnosis of hypertension is achieved. For example a standard blood pressure measurement of <120 / 80 mm Hg and a biochemical categorisation of normotensive for an individual is suggestive of normal blood pressure, whereas a standard blood pressure measurement of >130 / 80 mm Hg and a hypertensive biochemical categorisation for an individual is suggestive of hypertension. Of particular use in assigning a biochemical blood pressure category is if an individual has a systolic blood pressure in the range of 120 to129 mm Hg or so- called ‘elevated blood pressure’ - this intermediate range which is neither normal or high blood pressure (stage I or stage II hypertensive as per the AHA guidelines) will be given more certainty by the biochemical categorisation whether this categorisation is by way of a mathematical / statistical methodology or by of an increase / decrease in two or more of ALT, ASO, AST, calcium, chloride, FT4, IgA, potassium, haematocrit count, smLDL and TSH in biological sample measurements of an individual’s biological samples taken at two different time-points (see Figure 4 for an example of the latter). If an individual is normotensive based on an inflatable cuff measurement and hypertensive based on biochemical measurements then follow-up clinical investigation can be pursued which could include further biochemical testing and inflatable cuff measurements, using the same pressuremeasuring device and / or a different pressure-measuring device. If an individual is hypertensive based on an inflatable cuff measurement and normotensive based on biochemical measurements then follow-up clinical investigation can be pursued which could include further inflatable cuff measurements, using the same pressuremeasuring device and / or a different pressure-measuring device. A similar approach can be applied if the individual has an elevated blood pressure i.e. 120-129 mm Hg systolic BP and < 80 mmHg diastolic BP - it is within this blood pressure range which most uncertainty lies as the measured BP values could potentially reside above or below the actual measured values, in the stage I or stage II hypertensive category and normotensive category respectively, and for which the described biochemical measurement methods potentially have most utility. The biochemicals described herein are not restricted to being used in the context of the UK BHA or ACC / AHA blood pressure classification systems and their measurement can used to support blood pressure measurements using other blood pressure classification systems.

[0031] Methods and Results

[0032] Patients

[0033] The individuals taking part in the study had fasted for at least 12 hours and were self-reported healthy males (aged 30 to 60 years) of similar BMI, not taking medication and with no known morbidities. Populations of healthy males with normal blood pressure (systolic BP <120 mm Hg) versus high blood pressure (systolic BP >129 mm Hg) were initially compared; the ages and BMI values of the two cohorts were not significantly different (Table 1). Blood pressure values were obtained by a nurse using a blood monitoring device (OMRON HBP-1320) by taking measurements of each arm and using the average of the two values if the two readings differed by < 5 mm Hg; if the two readings where > 5 mm Hg the individual’s data was not used in the study.

[0034] Collection and Analysis of In Vitro Samples

[0035] Each patient attended a Randox Health clinic and during which urine and blood samples were collected from the patient, a physical examination conducted and a health report form completed. The physical examination included measuring weight, height, blood pressure and body fat measurements. Blood samples were obtained <15 minutes after blood pressure measurement. Once the patient sample was collected, it was analysed on-site or transferred to a Randox Laboratory for analysis. The samples were processed and analysed using Randox test reagents (available from Randox Laboratories Ltd, Crumlin, UK), Randox clinical analysers or other test reagents and analysers from different manufacturers if specified. Biochemicals were analysed at Randox Health Holywood, Randox Health London, Randox Health Liverpool and Randox Clinical Laboratory Services in Antrim. Analysers used for measuring biochemicals were Randox Imola / Monza / Daytona / Modena, Sysmex XN550 and Roche Cobas e801 . ALT, ASO, AST, calcium, chloride, IgA and potassium were analysed using Randox analysers and test reagents; FT4 and TSH were analysed using a Roche analyser and test reagents; haematocrit was analysed using Sysmex analyser and test reagents. Each analyser was used in its standard manner without modification and the biochemicals measured as per the accompanying instruction test reagent sheet / information for use (IFU). Measurement units: Alanine aminotransferase (ALT) units U / l, reference range <31 normal 31-155 raised >155 high; Anti-streptolysin O (ASO) units lU / ml, reference range <200 normal >200 high; Aspartate aminotransferase (AST) units U / l, reference range <31 normal 31 -155 raised >155 high; Calcium (Ca) units mmol / l, reference range <2.20 low 2.20-2.60 normal >2.60 high; Chloride (Cl) units mmol / l, reference range <95 low 95 - 108 normal >108 high; Free Thyroxine (FT4) units pmol / l, reference range <10.30 low 10.30 - 24.50 normal >24.50 high; Hematocrit units units l / l, reference range <0.37 low 0.37 - 0.47 normal >0.47 high; Immunoglobulin A (IgA) units g / l, reference range <0.90 low 0.90 - 4.50 normal >4.50 high; Potassium (K) units mmol / l, reference range <3.5 low 3.5 - 5.3 normal >5.30 high; Small low-density lipoprotein (smLDL) units mg / dl, reference range <64.4 normal >64.4 high; Thyroid stimulating hormone (TSH) units mIU / l, reference range <0.40 low 0.40 - 4.00 normal >4.00 high. The described biomarkers are standard clinical biochemicals which are regularly measured in clinical laboratories and in research organisations and there are numerous tests and analysers available from various manufacturers that can be used for their analysis.

[0036] Statistical Analysis

[0037] Population data: two-tail unpaired t-test, with data transformation where appropriate for normalisation, and Mann-Whitney statistic were used for comparison of the population data guided by an upper threshold of significance of P<0.15. These results helped inform the multi-variable analyses of various biomarker measurement combinations (see Tables for biomarker combinations and results). A threshold of significance of P<0.15 was used to prevent omission of biochemicals that might significantly contribute to the finalised model equation. A default cut-off value of 0.5 was used to derive the ROC curve and AUC values for the multiple logistic regression model for the various biomarker combinations. Population data from a cohort of males aged 30 to 60 years clinically diagnosed hypertensive, exhibiting ongoing high blood pressure and taking anti-hypertensive medication was used to assess whether the individual biomarker concentration levels were different from those measured in the unmedicated hypertensive cohort. All calculations were effected using Graphpad Prism 9.02 software.

[0038] Results

[0039] Step 1 the identification of candidate biomarkers by comparing mean / median systolic BP of the stage I & II hypertensive cohort and the normotensive cohort (N= 21 to 29 and N=16 to 24, respectively) and calculating the % difference between the values and performing a t-test (log transformation applied where applicable) or Mann- Witney statistical test. Biomarkers whose P-value was <0.150 were taken forward for assessment. Of the initial 78 biomarkers; following univariate analysis this was reduced to 15 biomarkers (Table 1 ). This approach was chosen to maximise the probability of delineating higher and lower BP categories by omitting the central category of elevated BP wherein most uncertainty regarding BP measurement values analysis resides i.e. this central band of readings, given the inherent uncertainty with traditional BP measurements, are difficult to place for analysis as they could potentially lie within the stage I & II hypertensive BP category or the normotensive BP category; hence to prevent these values confounding the high vs normal BP analysis they were omitted from the analysis.

[0040] Step 2 Informed by the results of Step 1 , multiple logistic regression models were constructed to assign individuals to normal BP or stage I & II hypertension guided by systolic blood pressure values of the American College of Cardiology (ACC) & American Heart Association (AHA) blood pressure classification system. AUC values of various biomarker combinations are shown in Table 2.

[0041] The ACC and AHA blood pressure-related categories

[0042] A) Normal blood pressure is < 120 / 80 mm Hg or lower

[0043] B) elevated blood pressure ranges from 120 to 129 mm Hg and < 80 mm Hg. Ci) stage I hypertension. Systolic BP 130 to 139 mm Hg or diastolic BP is 80 to 89 mm Hg.

[0044] Cii) stage II hypertension. Systolic BP is > 140 mm Hg or diastolic BP is 90 mm Hg or higher.

[0045] Step 3 biomarker data (see % difference right-hand column of Table 1 ) from a clinically defined high blood pressure cohort, with concurrent high blood pressure, taking anti-hypertensive medication was compared to the corresponding biomarker data of the unmedicated population cohort with a stage I or stage II hypertension BP measurement. It might be expected that blood pressure medication would stabilise / reverse the biomarker concentration trend observed in Step 1 . The % difference column indicates that this was observed for each of the highlighted biomarkers (grey) except for sodium and TIBC further supporting the involvement of the biomarkers of the disclosed methods in hypertension physiology.

[0046] Table 1 Standard physiological and clinical biochemicals (biomarkers) t-test / Mann-Whitney P-value and percentage difference of mean concentrations in two self-reported healthy age- matched male populations separated using blood pressure (BP) measurements. The normal BP cohort (N=16 to 24 per biomarker comparison) had a systolic BP range of <120 mmHg and a hypertensive cohort (N=21 to 29 per biomarker comparison) had a systolic BP of >129 mm Hg. Negative value indicates the hypertensive cohort had lower mean biomarker concentration than normal BP cohort. The % column to the far right compares the percentage difference in biomarker concentration in a medicated cohort with clinically defined high blood pressure and the unmedicated hypertensive cohort (negative value indicates the medicated hypertensive cohort had lower mean biomarker concentration than the unmedicated hypertensive cohort). The age of the two cohorts, normal BP vs HT, was not significantly different P=0.157. HT= hypertensive; diff.=difference. Creatinine 83.71 84.24 0.62 0.8396 3.38

[0047] CRP 1.59 1.24 -27.97 0.8224 43.30

[0048] Cystatin C 0.71 0.74 4.97 0.3986 7.97

[0049] Eosinophil count 0.15 0.14 -7.07 0.6328 30.23 eGFR 93.83 91.25 -2.82 0.6127 -1.98

[0050] Ferritin 197 267 26.40 0.7348 -20.69

[0051] Folic acid 8.57 8.21 -4.40 0.5723 9.51

[0052] FAI 34.42 35.09 1.90 0.7884 19.59

[0053] FT4 17.49 16.17 -8.16 0.0656 3.37

[0054] FT3 4.67 4.58 -1.99 0.7456 12.87

[0055] GGT 33.64 39.65 15.17 0.1744 9.60

[0056] Glucose 5.46 5.57 2.01 0.6300 -0.51

[0057] HbA1c 31.71 31.82 0.33 0.9164 2.71

[0058] HDL 1.26 1.26 - 0.5855 1.19

[0059] Haematocrit 0.439 0.449 2.23 0.1481 -0.22

[0060] Haemoglobin 151.00 154.40 2.36 0.2123 -0.29 hFABP 3.18 3.06 -3.92 0.5988 25.55

[0061] H. pylori 1.74 1.24 -36.70 0.0136 56.57

[0062] IgA 2.24 2.97 24.55 0.0087 -17.21 igE 95.48 111.30 14.22 0.8420 18.23 igG 10.74 10.98 2.21 0.7595 3.39

[0063] Insulin 63.17 82.08 23.04 0.2090 18.46

[0064] Iron 20.18 22.49 10.29 0.1852 -9.92

[0065] LDL 3.82 4.19 8.78 0.2934 -9.64

[0066] Leptin 5.04 6.59 23.51 0.2728 27.45

[0067] Lipase 44.28 38.91 -13.81 0.1820 21.62

[0068] Lipoprotein (a) 263 301 12.65 0.9364 -7.56

[0069] Lymphocyte count 1.78 1.74 -2.19 0.9621 6.75

[0070] Magnesium 0.86 0.85 -1.08 0.4558 2.71

[0071] MCH 30.40 30.65 0.79 0.8622 -0.91

[0072] MCHC 343.36 344.35 0.29 0.9594 -1.28

[0073] Monocyte count 0.50 0.50 - 0.9482 9.25

[0074] Neutrophil count 3.29 3.50 6.05 0.8340 7.40

[0075] Pancreatic amylase 35.75 29.13 -22.75 0.0949 10.15

[0076] Phosphate 1.12 1.14 2.01 0.6032 -4.44

[0077] Platelet count 253.30 254.40 0.28 0.9394 -2.04

[0078]

[0079] Alanine aminotransferase (ALT), Alkaline phosphatase (ALP), Antistreptolysin O (ASO), Aspartate aminotransferase (AST), Body mass index (BMI), C-reactive protein (CRP), Free androgen index (FAI), Free androgen index (FAI), Free thyroxine (FT4), Free tri-iodothyroxine (FT3), gammaGlutamyltransferase (GGT), Immunoglobulin A (IgA), Immunoglobulin E (IgE), Immunoglobulin G (IgG), Mean corpuscular hemoglobin (MOV), Mean corpuscular hemoglobin concentration (MCHC), Red blood cell count (RBC), Sex hormone binding globulin (SHBG), Small LDL (smLDL), Thyroid stimulating hormone (TSH), Total iron binding capacity (TIBC), Total antioxidant status (TAS), White blood cell count (WBC)

[0080] Table 2 Biomarker combinations area under the curve (AUC) statistic

[0081] Case Study 1

[0082] A 56-year-old male, self-reported normotensive and not taking medication visited a Randox Health clinic in Northern Ireland and recorded a blood pressure measurement of 118 / 110 mm Hg. Blood analysis and incorporation of measurements of the biochemicals ASO, AST, Ca, Cl, Het and IgA in a multiple logistic regression model ( Y= 370.1 + 9.81 [calcium] - 6.05[logioASO] + 16.60[logio AST] + 37.82[log IgA] - 212.7[log 1 o chloride] + 11 .01 [haematocrit count] ), suggested a hypertensive phenotype. Six months later the individual returned to the Randox Health clinic and reported that he had been diagnosed hypertensive by a clinician and prescribed anti-hypertensive medication.

[0083] Case Study 2

[0084] A 49-year-old male, self-reported normotensive and not taking medication visited a Randox Health clinic in Northern Ireland for a health check. He recorded a blood pressure measurement of 139 / 79 mm Hg and blood analysis and application of the previously described multiple logistic regression model (Case Study 1 ) suggested a hypertensive phenotype. Two subsequent visits to Randox health during the following two years, in which he recorded a BP of 139 / 79 mm Hg on visit 2 (BP measurement data for visit 3 is missing) confirmed a biochemically hypertensive phenotype which appeared to be worsening given the concentration trajectory of each of the biochemicals and the output of the MLR model. The individual returned to the Randox Health clinic 6-months later (visit 4) and reported that he had been diagnosed hypertensive and was on a course of anti-hypertensive medication. Biochemical analysis, although suggesting a hypertensive biochemical phenotype, did indicate an improving blood pressure physiology based on the concentration trajectory of the biochemicals and the model output (Y-value).

[0085] Between visits 3 and 4 each of the intra-biomarker concentrations of AST, Ca, Cl, Het and IgA change in a trajectory that supports an improving blood pressure physiology suggesting the medication was having the desired effect. The comparison of biochemical concentrations between two-time points method to blood pressure analysis provides an alternative algorithm to the MLR model in assessing the efficacy of the anti-hypertensive drug treatment which is more simplistic and readily interpretable by the patient.

[0086] Table 3 Inter-visit, individual biochemical relative measurement values (Case Study 2), the concentration of each individual biomarker being afforded a value of 100 for the first visit. The male was self-reported healthy and not taking medication before each of visits 1 to 3; during visit 4 the individual reported that he was taking medication for high blood pressure having been clinically diagnosed as hypertensive. Y-value represents the multiple logistic regression model output value ( In(odds) of being hypertensive vs normotensive).

[0087] Visit Age ASO AST Ca Cl Het IgA Y-value

[0088] 1 49 100 100 100 100 100 100 5.52

[0089] 2 50 76 97 102 100 95 105 6.79

[0090] 3 51 72 121 104 99 103 103 11.52

[0091] 4 52 60 85 98 101 95 99 3.68

[0092] The described approaches use population blood pressure data in unmedicated, healthy individuals with normal (systolic BP <120 mm Hg) and hypertensive (systolic BP >129 mm Hg) blood pressure readings to identify corresponding biochemical profiles. This enables the construction of biochemical-based algorithms to categorise individuals as normotensive or hypertensive and which can be used to support traditional blood pressure measurements and to mitigate the uncertainty of inflatable cuff measurements. Hypertension-related biochemicals associated with diverse organ systems were identified supporting the multi-factorial origin theory of high blood pressure. The case studies highlight the use of biochemicals in identifying hypertensive states either as a support to or independently of inflatable cuff measurements. Highlighting a high blood pressure biochemical phenotype in an individual with an apparently normal blood pressure inflatable cuff reading alerts the clinician to the possibility that the individual may have or be at risk of high blood pressure, thus allowing for increased monitoring including repeat / increased blood pressure monitoring and / or biochemical analysis and the implementation of behavioural modification to prevent hypertension onset and the need for medication. The method can also be used to support the decision to prescribe anti-hypertensive medication, and to monitor the efficacy of prescribed anti-hypertensive medication by confirming that the medication stabilises the biochemical concentrations or directs the biochemical concentrations to a trajectory consistent with a normotensive status.

Claims

CLAIMS1 . A method of diagnosing hypertension, diagnosing an increased likelihood of hypertension or supporting the diagnosis of hypertension in an individual comprising measuring the concentration of at least two biomarkers in an in vitro biological sample of an individual the at least two biomarkers including at least one of i) immunoglobulin A and anti-streptolysin O, and at least one of ii) calcium, chloride and potassium, and inputting the measured concentration values into a statistical model the output of which indicates whether the individual is hypertensive, has an increased likelihood of hypertension or supports the diagnosis of hypertension, the method including the assessment of one or more systolic and diastolic blood pressure measurement values of the individual when the biomarker concentrations are used to support the diagnosis of hypertension.

2. The method of claim 1 in which the concentration of one or both of aspartate aminotransferase and alanine aminotransferase and are also measured.

3. The method of any of claims 1 and 2 in which the concentration of one or both of haematocrit count and small LDL cholesterol are also measured.

4. The method of any of the preceding claims in which the concentration of one or both of free thyroxine and thyroid stimulating hormone are also measured.

5. The method of any of the preceding claims in which measurement values obtained from two cohorts of individuals are used to support the construction of the statistical model, one cohort whose individuals each have blood pressure measurement values of <120 mm Hg systolic blood pressure and a second cohort whose individuals each have blood pressure measurement values of >129 mm Hg systolic blood pressure.

6. A method of identifying an individual having an increased risk of developing hypertension comprising measuring the concentration of two or more biomarkers in in vitro samples of the individual obtained at two different time points, at least one of which is chosen from immunoglobulin A and anti-streptolysin O and at least one of which is chosen from calcium, chloride and potassium and establishing whether a change in the concentration in two or more of the biomarkers is indicated between the two different time points in which an increase in the concentration of immunoglobulin A, an increase in the concentration of calcium, a decrease in theconcentration of chloride, a decrease in the concentration of anti-streptolysin O and a decrease in the concentration of potassium between the first and second time points is indicative that the individual has an increased risk of developing hypertension.

7. The method of claim 6 in which the concentration of one or both of alanine aminotransferase and aspartate aminotransferase is also measured at the two different time points and an increase in concentration of alanine aminotransferase and an increase in concentration of aspartate aminotransferase between the two time points is indicative that the individual has an increased risk of developing hypertension.

8. The method of claims 6 and 7 in which the concentration of one or both of free thyroxine and thyroid stimulating hormone is also measured at the two different time points and a decrease in concentration of free thyroxine and an increase in concentration of thyroid stimulating hormone between the two time points is indicative that the individual has an increased risk of developing hypertension.

9. The method of claims 6 to 8 in which the concentration of one or both of small LDL cholesterol and haematocrit count is also measured at the two different time points and an increase in concentration of small LDL cholesterol and an increase in concentration of haematocrit count between the two time points is indicative that the individual has an increased risk of developing hypertension.

10. A method of assessing whether an anti-hypertensive drug decreases high blood pressure in an individual comprising measuring the concentration of two or more biomarkers chosen from immunoglobulin A, calcium, anti-streptolysin O, chloride, and potassium in in vitro samples of the individual obtained at two different time points whereat the first time point the individual is not being prescribed the antihypertensive drug and at the second time-point the individual is being prescribed the anti-hypertensive drug; and establishing whether there is a change in the concentration in the two or more of the biomarkers between the two different time points, in which a decrease in the concentration of immunoglobulin A, a decrease in the concentration of calcium, an increase in the concentration of chloride, an increase in the concentration of anti-streptolysin O and an increase in theconcentration of potassium between the first and second time points is indicative that the anti-hypertensive drug has decreased the blood pressure of the individual.11 . The method of claim 10 in which the concentration of one or both of alanine aminotransferase and aspartate aminotransferase are also measured at the two different time points and a decrease in concentration of alanine aminotransferase and a decrease in concentration of aspartate aminotransferase between the two time points is indicative that the anti-hypertensive drug has decreased the blood pressure of the individual.

12. The method of claims 10 and 11 in which the concentration of one or both of free thyroxine and thyroid stimulating hormone are also measured at the two different time points and an increase in concentration of free thyroxine and a decrease in concentration of thyroid stimulating hormone between the two time points is indicative that the anti-hypertensive drug has decreased the blood pressure of the individual.

13. The method of claims 10 to 12 in which the concentration of one or both of small LDL cholesterol and haematocrit count are also measured at the two different time points and a decrease in concentration of small LDL cholesterol and a decrease in concentration of haematocrit count between the two time points is indicative that the anti-hypertensive drug has decreased the blood pressure of the individual.

14. A method of assessing whether an anti-hypertensive drug decreases high blood pressure in an individual with hypertension and who is prescribed anti-hypertensive medication comprising measuring the concentration of two or more biomarkers chosen from immunoglobulin A, calcium, chloride, anti-streptolysin O and potassium in an in vitro sample of the individual, the at least two biomarkers including at least one of i) immunoglobulin A and anti-streptolysin O, and at least one of ii) calcium, chloride and potassium; and inputting the measured concentration values into a statistical model the output of which indicates whether the individual has hypertension or is likely to have hypertension.

15. The method of claim 14 in which the concentration of one or both of alanine aminotransferase and aspartate aminotransferase are also measured.

16. The method of claims 14 and 15 in which the concentration of one or both of free thyroxine and thyroid stimulating hormone are also measured.

17. The method of any of claims 14 to 16 in which the concentration of one or both of small LDL and haematocrit are also measured.

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