ES2644582A1 - A prognostic method and kit for the identification of the risk of development of albuminuria, risk of renal damage and cardiovascular risk in a hipperenso human subject (Machine-translation by Google Translate, not legally binding) - Google Patents

Abstract

A prognostic method and kit to identify the risk of albuminuria development, risk of kidney damage and cardiovascular risk in a hypertensive human subject. The method comprises the evaluation of the urine concentration of at least one compound selected from glutamate, glycerate, guanidoacetate, pantothenate, oxaloacetate, 3-ureidopropionate, 3-hydroxybutyrate, malate and pyruvate, the determination of whether at least one of the markers it is above or below the standard values in healthy subjects, in which said markers are the concentration of compounds and panels composed of several compounds, and the identification of risks in said human subject. (Machine-translation by Google Translate, not legally binding)

Description

FIELD OF THE INVENTION

The invention relates to a prognostic method for the identification of the risk of development of albuminuria, risk of renal damage and cardiovascular risk in a hypertensive human subject. The invention relates to a prognostic method comprising the evaluation of the concentration of at least one of the compounds selected from the group consisting of glutamate, glycerate, guanidoacetate, pantothenate, oxaloacetate, 3-ureidopropionate, 3hydroxybutyrate, malate and pyruvate in a sample urine and the determination of one of the markers or group of markers (panels) that is above or below the values of healthy subjects.

BACKGROUND OF THE INVENTION

Hypertension is a multi-factor disease of increasing prevalence and an important risk factor for cardiovascular mortality even in the presence of a seemingly adequate treatment. Albuminuria has been clearly shown to be a marker of cardiovascular damage.

Chronic suppression of the renin-angiotensin system (RAS) has been shown to facilitate blood pressure control (BP), prevents the development of newly occurring albuminuria and decreases the amount of urinary albumin in patients with persistence of high albuminuria. or too high However, in a relevant subgroup of patients under chronic suppression of RAS there is high albuminuria, either maintained (MHA) or developed de novo (dnA). De novo albuminuria develops up to 16.1% of normoalbuminuric patients during the three years following the start of treatment (Cerezo et al. Microalbuminuria breakthrough under chronic renin-angiotensin-aldosterone system suppression. J Hypertens 2012; 30: 204 -209).

This group of patients probably represents those with the highest risk of progression of CV and kidney disease. The discovery of predictors of progression or development of albuminuria during chronic suppression RAS is guaranteed as a useful tool to detect where drug therapy should be intensified and also where new drugs should be primarily tested.

The metabolome is made up of the low molecular weight final products of the body's metabolism, representing the definitive body's response to a certain condition (for example, disease) and complementing genetic and protein studies very well. Urine represents a rich source for investigating molecular alterations associated with renal physiology and kidney diseases. The metabolome was previously investigated in cardiovascular and kidney diseases. However, very few studies have been carried out in the context of hypertension and those related to human samples are particularly scarce and focused on the progression of kidney disease in diabetic individuals.

DESCRIPTION OF THE INVENTION

A first aspect of the present invention is a prognostic method for identifying the risk of albuminuria development, risk of renal damage and cardiovascular risk in a hypertensive human subject, comprising: a) the evaluation of the concentration of at least one of the compounds selected from the group consisting of glutamate, glycerate, guanidoacetate, pantothenate, oxaloacetate, 3ureidopropionate, 3-hydroxybutyrate, malate and pyruvate in a urine sample obtained from said human subject, b) the determination of whether at least one of the markers is by above or below the standard values of healthy subjects, in which said markers are selected from the group consisting of glutamate concentration, glycerate concentration, guanidoacetate concentration, pantothenate concentration, oxaloacetate concentration, concentration of 3 -ureidopropionate, 3-hydroxybutyrate concentration, malate concentration, concentration pyruvate, the panel consisting of glutamate concentration, guanidoacetate concentration and pantothenate concentration, panel consisting of guanidoacetate concentration, pantothenate concentration, glutamate concentration, glycerate concentration, oxaloacetate concentration , the concentration of 3-ureidopropionate and the concentration of pyruvate and the panel consisting of the concentration of 3-hydroxybutyrate and the concentration of pyruvate and c) the identification of the risk in said human subject evaluating the result of step b).

The prognostic method of the first aspect of the present invention is useful for identifying the risk of albuminuria development, the risk of renal damage and cardiovascular risk in a hypertensive human subject who is or is not under an anti-hypertension treatment. If said human subject is under treatment for hypertension, said treatment could be based on renin-angiotensin system inhibitors or could be based on any other compounds suitable for anti-hypertensive treatments.

Other compounds suitable for anti-hypertension treatments include, but are not limited to, calcium antagonists, diuretics, mineralocorticoid receptor antagonists, alpha blockers, beta blockers and sympathetic nervous system blockers.

In a particular aspect, the invention is the method of prognosis of the first aspect of the invention, wherein said hypertensive human subject is under treatment with renin-angiotensin system inhibitors.

The examples of the present invention showed significant differences for a total of nine meta urinary pellets: glutamate, glycerate, guanidoacetate, pantothenate, oxaloacetate and 3-ureidopropionate with decreased values compared to healthy individuals, and 3-hydroxybutyrate, malate and pyruvate, with a increased response in hypertension with the inhibition of RAS and / or albuminuria condition.

The risk identification is considered positive if the concentrations of glutamate and / or glycerate and / or guanidoacetate and / or pantothenate and / or oxaloacetate and / or 3-ureidopropionate are lower than the standard values of healthy subjects and / or concentrations of Healthy hydroxybutyrate and / or malate and / or pyruvate are higher than the standard values of healthy subjects.

The examples of the present invention confirmed that guanidoacetate, glutamate and pantothenate showed significantly higher levels in patients still in the condition of normoalbuminuria, but who will develop albuminuria in the future.

The panel consisting of glutamate concentration, guanidoacetate concentration and pantothenate concentration, also called met-dnA panel in the present application, is a molecular panel for the identification of patients even in the normoalbuminuria condition, but which will develop albuminuria in the future. This panel identifies patients with a cardiovascular risk, but they will not be correctly identified using state-of-the-art techniques, since these patients have normal levels of albuminuria. The identification of these patients allows an early personalized treatment. Such early treatment will prevent irreversible kidney damage and cardiovascular damage.

The panel consisting of guanidoacetate concentration, pantothenate concentration, glutamate concentration, glycerate concentration, oxaloacetate concentration, 3-ureidopropionate concentration and pyruvate concentration is a molecular panel for identification of responding patients to hypertension (HTN) with

or without albuminuria.

The panel consisting of the 3-hydroxybutyrate concentration and the pyruvate concentration, also called the met-MHA panel in the present application, is a molecular panel for the identification of patients with maintained high albuminuria (MHA).

Another aspect is the forecast method of the first aspect of the invention, in which the concentrations of step (b) are quantified by a technique selected from the group consisting of nuclear magnetic resonance, immunoassay, chromatography, electrochemical sensors, microarray and mass spectrometry. ° any combination thereof.

A second aspect is a kit for carrying out the method of the first aspect of the invention, comprising suitable reagents for the quantification of the concentration of at least one of the compounds selected from the group consisting of glutamate, glycerate, guanidoacetate, pantothenate, oxaloacetate, 3 -ureidopropionate, 3-hydroxybutyrate, malate and pyruvate in a urine sample obtained from said human subject.

BRIEF DESCRIPTION OF THE FIGURES

Figure 1. Urine metabolites that respond to HTN. Declining trends were observed in chronically suppressed RAS hypertensive patients for glutamate (A), glycerate (B), guanidoacetate (C), pantothenate (D), oxaloacetate (E) and 3-ureidopropionate (F) in response to HTN. The graphs represent the SRM-LC-MS I MS analysis of urinary metabolites in a cohort of 68 patients and 14 healthy subjects (Table 1). The individual signals were normalized based on the total ionic current (TIC) and the areas of the normalized peaks were calculated for the inter-group comparison. The non-Mann-Whitney metric technique was applied with a 95% confidence level. For clarity, the important details are included in Table 2 and more details are included in the statistical analysis section. C: control, N: normoalbuminuria, dnA: de novo albuminuria, MHA: maintained high albuminuria.

Figure 2. Urine metabolites that respond to albuminuria. Increasing trends were observed in chronically suppressed RAS hypertensive patients for 3-hydroxybutyrate (A), malate (B) and pyruvate (C) in response to albuminuria. The graphs represent the SRM-LC-MS I MS analysis of urinary metabolites in a cohort of 68 patients and 14 healthy subjects (Table 1). Individual signals were normalized based on total ionic current (ICT) and areas of normalized peaks were calculated for intergroup comparison. The non-parametric Mann-Whitney test was applied with a 95% confidence level. For clarity, the important details are included in Table 2 and more details are included in the statistical analysis section. C: control, N: normoalbuminuria, dnA: de novo albuminuria, MHA: maintained high albuminuria.

Figure 3. Urinary metabolites with predictive potential. A specific panel composed of three metabolites (guanidoacetate, glutamate and pantothenate) predicts the development of albuminuria when analyzed in patients' urine even under normoalbuminuria conditions. The graphs represent the SRM-LC-MS! MS of the urinary metabolites in a cohort of 35 normo-albuminuric patients (Table 1, confirmation cohort) who remained as N or progressed to dnA during the follow-up of at least one year from taking urine samples. Individual signals were normalized based on total ionic current (ICT) and areas of normalized peaks were calculated for intergroup comparison. The non-parametric Mann-Whitney test was applied with a 95% confidence level. C: control, N: normoalbuminuria, dnA: de novo albuminuria, MHA: maintained high albuminuria. ****: P value <0.0001, ***: P value <0.001, *: p value <0.05.

Figure 4. Multi-molecular panels defined according to their response to either hypertension (met-HTA), maintained high albuminuria (met-MHA) or de novo albuminuria (metdnA). The upper panels show the ROC curves (AUC: area under the curve, 95% confidence interval) and the lower panels show the graphs of predictive probability classes showing clusters according to their clinical status. MetHTN is composed of guanidoacetate, pantothenate, 3-ureidopropionate, oxaloacetate and pyruvate. Met-MHA is composed of 3-hydroxybutyrate and pyruvate. Met-dnA is composed of guanidoacetate, glutamate and pantothenate. ROC curves were generated by Monte-Cario cross-validation (MCCV) using balanced subsampling. "Random forest" was selected as the classification method used and the probability prediction diagram of classes was obtained using the best classifier (based on the AUC).

Figure 5. The positive correlation between the prediction accuracy of the panels and the number of features included

EXAMPLES OF THE INVENTION

Materials and methods

Classification and selection of patients

Patient selection was based on an earlier study showing the development of de novo albuminuria in patients during chronic suppression of the reninaangiotensin system (RAS) (Cerezo et al. Microalbuminuria breakthrough under chronic reninangiotensin-aldosterone system suppression. J Hypertens 2012; 30: 204-209). In a nutshell, in that study, the evolution of 1533 patients of the Hypertension Unit - Hospital 12 de Octubre, who had been under chronic suppression of RAS for at least 5 years (2 before arrival at the Unit and three of the follow up later). After a period of 3 months of stabilization, during which the best possible control of cardiovascular risk factors was attempted, and the RAS suppression dose was increased to the maximum tolerated, the reference data were obtained. From the beginning, 1141 patients remained normoalbuminuric, while the remaining 392 (27.3%) had persistent albuminuria. BP was estimated by using a semi-automatic OMRON validated device under standardized conditions and the presence of secondary forms of arterial hypertension was excluded. From the beginning, the patients were subsequently followed for a minimum period of 3 years in which the progression of albuminuria was evaluated every six months. The suppression of RAS was maintained throughout the duration of the follow-up. Of the normoalbuminuric patients at the beginning of the study, 16.1% developed de novo albuminuria (that is, absent at the beginning of the study and subsequently developed) during the 3-year period. The development of albuminuria de novo was defined as any new occurrence of high albuminuria (albumincreatinine ratio of 20 to 200 mg / g creatinine in men and 30-300 mg / g creatinine in women) confirmed on at least a second occasion between semiannual determinations made on three samples of morning urine or very high albuminuria (> 200 mg I 9 of creatinine in men and> 300 mg / g of creatinine in women).

The metabolomic investigation was carried out at the end of the third year of follow-up. A group of 118 hypertensive patients were selected as a representative cohort (75 non-diabetics and 43 diabetics). Diabetes was diagnosed based on a fasting blood glucose> 126 mg I di, a serum glucose level> 198 mg I di after an oral glucose tolerance test, or the use of oral antidiabetic drugs (present in 32 patients) . The 118 patients were classified into three groups as follows: a) patients who remained normoalbuminuric during the 3-year follow-up (N); b) patients who developed albuminuria novo during follow-up (dnA); c) patients with persistent albuminuria from the beginning and during follow-up (MHA). A control group of urine samples from 30 healthy normotensive subjects (C), matched by sex and age was included to assess the differences attributable to hypertension itself. This study is carried out with the requirements for an omic study in terms of sample group size and technical workflow. The entire group of 118 patients and 30 controls was divided into two different cohorts for the discovery phase and the confirmation phase. The first phase of discovery was carried out in a cohort of 50 hypertensive patients and 16 controls. Variations identified at the metabolome level were further evaluated in an independent confirmation cohort of 68 hypertensive patients and controls. The clinical characteristics of these patients recruited for the study and included in the discovery cohort or confirmation cohort are summarized in Table 1.

Table 1. Characteristics and medication of the reference patients. Values expressed as the mean ± the standard deviation (SD), or percentages (%). The

Statistical differences between the three groups using the non-parametric KruskalWailis test (P-value <0.05 was considered significant). BMI: body mass index; HDL: high density lipoprotein cholesterol; LDL: low density lipoprotein cholesterol. N: normoalbuminuria; dnA: de novo albuminuria; MHA: high albuminuria

5 maintained. ACEI: angiotensin converting enzyme inhibitors; ARB: angiotensin receptor blockers.

COHORT OF N (n 17) INITIAL DISCOVERY Age (years) 61 ± 4 Sex (male), 47% BMI (kg / m2) 29 ± 4 Smoking at the present time. % Total cholesterol 193 ± 31 (mg / dl) Triglycerides (mg / dl) 114 ± 53 HDL cholesterol 52 ± 9 (mg / dl) LDL cholesterol 118 ± 28 (mg / dl) Blood glucose (mg / dl) 106 ± 25 Acid uric (mg / dl) 4.6 ± 1.6 95 ± 28 creatinine clearance (mg / ml) eGFR 81 ± 10 (ml / min / 1.73m2) Blood pressure 135 ± 16 systolic (mmHg) 135 Blood pressure 83 ± 11 diastolic (mmHg ) ACR (mg / g) 7 ± 9 Diabetes Mellitus. % 18

dnA (n 18) 66 ± 6 67 29 ± 5 22 162 ± 21 124 ± 62 52 ± 12 84 ± 14 122 ± 28 6.1 ± 1J 92 ± 53 72 ± 20 132 ± 16 80 ± 12 230 ± 404 50 MHA (n 15) 65 ± 8 60 32 ± 5 20 164 ± 23 121 ± 86 45 ± 13 98 ± 19 109 ± 24 5.9 ± 1.6 91 ± 35 74 ± 24 134 ± 16 81 ± 9 215 ± 379 33 P-value 0.023 0.499 0.219 0.707 0.005 0.886 0.183 0.001 0.066 0.032 0.691 0.551 0.968 0.676 <0.0001 0.1015

Antihypertensives,%

ACEi

24 22 13 0.7436

ARB

59 67 73 0.7967

Diuretic

59 44 53 0.696

Calcium channel blocker

35 fifty 60 0.3765

Beta blocker

12 33 40 0.1758

Alpha blocker

12 33 twenty 0.3055

Other treatments,%

Anticoagulant

12 44 33 0.1071

Lipid Reduction Treatment

77 78 67 0.7428

Antidiabetic agent

18 44 33 0.2411

Antialdosteronic

6 17 27 0.2838

CONFIRMATION COHORT

N (n-39) dnA (n-13) MHA (n-16) P-value

Age (years)

65 ± 12 68 ± 11 63 ± 14 0.581

Sex (male) %

36 62 69 0.052

BMI (kg / m2) 3

30 ± 5 31 ± 4 29 ± 4 0.505

Smoking today%

10 fifteen 13 0.881

Total cholesterol (mg / dl)

184 ± 29 168 ± 27 184 ± 36 0.261

Triglycerides (mg / dl)

120 ± 49 129 ± 66 146 ± 58 0.308

HDL cholesterol (mg / dl)

55 ± 14 50 ± 12 49 ± 12 0.186

LDL cholesterol (mg / dl)

104 ± 28 93 ± 20 107 ± 27 0.352

Glycemia (mg / dl)

11 5 ± 33 11 6 ± 27 123 ± 39 0.894

Uric acid (mg / dl)

5.4 ± 1 .7 6.4 ± 1.7 7. 2 ± 1 .7 0.003

Creatinine clearance (mg / ml)

183 ± 437 96 ± 36 75 ± 42 0238

eGFR (m l / min / 1.73m2)

81 ± 20 72 ± 22 68 ± 28 0.201

Systolic blood pressure (mm Hg) 135

138 ± 18 144 ± 20 144 ± 32 0.618

Diastolic blood pressure (mmHg)

80 ± 10 80 ± 8 84 ± 18 0.71 3

ACR (mg / g)

10 ± 1 3 104 ± 1 22 896 ± 969 <0.0001

Mellitus diabetes. %

33 39 fifty 0.5181

Antihypertensives,%

ACEi

10 8 31 0.1029

ARB

85 70 63 0.1738

Diuretic

54 54 56 0.9861

Calcium channel blocker

62 46 75 0.2877

Beta blocker

36 2. 3 13 0.1993

Alpha blocker

13 2. 3 19 0.6551

Other treatments,%

Anticoagulant agents

46 39 19 0.1691

Lipid Reduction Treatment

80 54 88 0.0861

Antidiabetic agent

2. 3 fifteen 31 0.6162

Antialdosteronic

twenty-one 8 6 02961

Finally, a prospective study was carried out to assess the predictive capacity of de novo albuminuria development for these metabolites that show some response.

related to hypertension or albuminuria. The 35 normoalbuminuric patients in the confirmation cohort (Table 1) could be clinically followed for at least an additional year from the urine sampling. They were classified as non-progressive (remaining as N) or progressive to dnA. The clinical study was accepted by the Ethics Committee of the Hospital October 12 and was carried out in accordance with the principles of the Declaration of Helsinki. All patients signed the written informed consent before inclusion.

Analysis of / metab% ma of urine for 1H NMR and identification of metabolites by NMR 20

A first phase of discovery was addressed by NMR. Individual urine samples were obtained from a total of 50 patients and 16 healthy subjects. Table 1 shows the baseline characteristics of the included patients. The three groups are comparable, with marginal differences for total cholesterol, LDL cholesterol and uric acid. Briefly, the urine samples were centrifuged and the supernatants were frozen at -80 ° C until processing. The frozen samples were thawed and diluted with 0.01 mM sodium trimethylsilyl propionate (TSP) solution (as internal reference for spectral calibration) in D20 buffered with Na2HP04 I NaH2P04 at pH 7.0. All NMR experiments were performed at 277 K on a Bruker ADVANCE 111700 instrument and the spectra were processed using TOPSPIN (version 1.3, Bruker Biospin Ud). The 1 H-NMR spectra were analyzed using AMIX software (version 3.6.8, Bruker Rheinstetten, Germany). Each spectrum was divided into regions and the individual regions were normalized for comparison. The unambiguous identification of specific metabolites with variable response for hypertension and albuminuria was performed using 2D NMR, Metabohunter and HMD (Tulpan D et al. MetaboHunter: an automatic approach for identification of metabolites from 1 H-NMR spectra of complex mixtures. BMCBioinformatics. 2011; 12: 400). To validate the association of metabolites identified with hypertension and albuminuria, metabolites were further measured in an independent cohort by a method based on quantitative mass spectrometry, as described in the next section.

Confirmation of altered metabolite responses by analysis based on mass spectrometry

Urine samples were collected from an independent cohort consisting of 68 patients and 14 healthy subjects. Table 1 shows the baseline characteristics of this confirmation cohort, showing groups without significant differences in any of the variables between patient groups, apart from uric acid. The altered metabolites were analyzed by SRM-LCMS / MS for confirmation in a 6460 Triple Ouadrupol

LC-MS / MS (1200 Series 5, Agilent Technologies) controlled by Mass Hunter software (Agilent Technologies v4.0) as previously published (Martin-Lorenzo M et al. KLK1 and ZG16B proteins andarginine-proline metabolism identified as novel targets to monitor atherosclerosis, acute coronary syndrome and recovery Metabolomics. 2015; 11: 1056-1067). Briefly, the urine proteins were removed by organic precipitation and the separation was performed at 0.4 ml / min in a gradient of acetonitrile. Optimal analysis conditions were previously established by analysis of commercial metabolite standards. Individual signals were normalized based on total ionic current (ICT) and areas of normalized peaks were calculated for intergroup comparison.

Statistic analysis

To identify significant differences in clinical characteristics or medications, the three groups (N, ndA and MHA) were compared using the non-parametric KruskalWailis test with a 95% confidence level. To calculate statistically significant differences in metabolite levels between the groups, we first applied the ROUT method to detect outliers based on the False Discovery Rate (FDR), adjusting the O to 5%. Next, the non-parimetric Mann-Whitney test was carried out with a 95% confidence level. The analyzes were performed using GraphPad Prism software (version 6.01). To assess the performance of individual or panel markers, ROC curves were constructed using the Metaboanalyst web server (version 3.0) (Xia J et al. MetaboAnalyst 3.0 - making moremeaningful metabolomics. Nucleic Acids Res. 2015; 43: W251- W257). ROC curves were generated by cross-validation of Monte-Carla (MCCV) using balanced subsampling. Univariate ROC curves were first calculated with optimal cut points defined as those closest to the upper left corner. Then the multivariate ROC analysis was performed by combining these metabolites with similar response. "Random fores!" It was the classification method used and the probability prediction diagram of classes was obtained using the best classifier (based on the AUC). In the results section, the specific meta balls that make up each panel are detailed.

Example 1. A meta bolito fingerprint responds to the condition of hypertension and albuminuria

Metabolites were initially identified as potential responders to hypertension with inhibition of RAS and albuminuria, based on NMR analysis performed on an initial discovery cohort (see Table 1). For the confirmation and final selection of metabolic signatures, the metabolites were analyzed in an independent cohort (confirmation cohort) (see Table 1), using a highly specific and quantitative methodology based on the measurement of specific masses corresponding to the metabolite of interest (SRM-LC-MS I MS) and as previously published (MartinLorenzo M et al. KLK1 and ZG16B proteins andarginine-proline metabolism identified as novel targets to monitor atherosclerosis, acute coronary syndrome and recovery. Metabolomics. 2015; 11: 1056- 1067). Significant differences were confirmed for a total of nine urinary metabolites: glutamate, glycerate, guanidoacetate, pantothenate, oxaloacetate and 3-ureidopropionate with decreased values compared to healthy individuals (Figure 1), and 3-hydroxybutyrate, malate and pyruvate, with a increased response in hypertension with the condition of inhibition of RAS or albuminuria (Figure 2). Table 2 shows the statistical comparison between groups for metabolites that respond, either to hypertension alone, or to hypertension with dnA or MHA. Table 2. Metabolites showing significant alteration in the response to hypertension (AHT), de novo albuminuria (dnA) and maintained high albuminuria (MHA). The Pvalues are displayed. Statistical differences between each two groups were assessed using the non-parametric Mann-Whitney test (P-value <0.05 was considered significant). C: control. N: normoalbuminuric. ns: not significant.

METABOLLTO C / N C / dnA C / MHA N / dnA N / MHA dnAlMHA

LleDdeDCia ~

Glutamate! 0.0034 0.0128 <0.0001 ns <0.0001 0.0005 Glycerate! <0.0001 0.0005 <0.0001 ns 0.0068 0.0318 3-Ureidopropionate! <0.0001 <0.0001 <0.0001 ns ns ns 3-Hydroxybutyrate r ns ns <0.0001 ns <0.0001 <0.0001 Pyruvate r <0.0001 <0.0001 <0.0001 0.0299 <0.0001 0.0001 Guanidoacetate! <0.0001 <0.0001 <0.0001 ns <0.0001 0.0150 Oxalacetate! <0.0001 <0.0001 <0.0001 0.0226 <0.0001 0.0062 Pantothenate! 0.0004 0.0002 <0.0001 ns <0.0001 <0.0001 Malato) 0.0058 0.003 <0.0001 ns <0.0001 <0.0001

Figure 1 shows how glutamate (Figure 1A), glycerate (Figure 18), guanidoacetate (Figure 1C), pantothenate (Figure 1D) and oxaloacetate (Figure 1 E) significantly decrease in the urine of hypertensive patients compared to healthy subjects and ,

5 even more, in MHA. 3-Ureidopropionate also decreases significantly in response to HTN (Figure 1 F), but without showing a worsening effect with MHA

With an opposite tendency, 3-hydroxybutyrate (Figure 2A) and malate (Figure 28) respond significantly to MHA, while pyruvate increases progressively with hypertension, dnA and MHA (Figure 2C).

Example 2. A specific metabolic pattern predicts the development of albuminuria in normoalbuminuric hypertensive patients.

15 Once the metabolic patterns with altered response in this clinical scenario were identified, a prospective study by SRM-LC-MS / MS was conducted to evaluate a potential predictive response for the development of albuminuria of those nine metabolites found significantly altered. in hypertensive patients. In a subgroup of 35 normoalbuminuric patients who were clinically followed for at least 1

20 years since urine sampling, 26 remained as N, while 9 evolved to dnA. In the latter group guanidoacetate, glutamate and pantothenate showed significantly higher levels before patients could be classified as dnA (Figure 3). This means that these three metabolites already show an alteration in their urinary levels when the clinical situation of the patients is

25 still in the condition of normoalbuminuria.

Example 3. Multi-molecular panels linked to hypertension, maintained albuminuria and progression prediction

In view of the individual metabolite responses showing significant intergroup alterations (Figures 1 and 2), we evaluate the added value of the metabolic panels. Metabolites with similar responses (variation trends) were pooled and the panel performance was evaluated. Multivariate ROC analyzes were performed based on mass spectrometry data and the results are shown in Figure

4. A molecular response panel for hypertension ("met-HTN") can be defined, including responses to guanidoacetate, pantothenate, 3-ureidopropionate, oxaloacetate and pyruvate, and showing an area value under the ROC curve (AUC) of 0.942 (Figure 4A). A panel composed of 3-hydroxybutyrate and pyruvate, called tlMet-MHAtI identifies MHA with AUC value of 0.892 (Figure 48).

In the prospective study, a significant alteration was found in the urine of N patients who later progressed to dnA for guanidoacetate, glutamate and pantothenate (Figure 3). With this data, the combination of these three metabolic responses in a third panel (tlmet_dnAtI) was evaluated, resulting in an AUC value of 0.861 (Figure 4C).

The additive value in the prediction accuracy provided by these prognostic diagnostic panels instead of the one based on the response of an individual marker was demonstrated here. A positive correlation is observed between the prediction accuracy of the panels and the number of features that it includes, increasing sensitivity and specificity (see Figure 5).

Claims (4)

one.

A prognostic method to identify the risk of development of albuminuria, risk of renal damage and cardiovascular risk in a hypertensive human subject, characterized in that it comprises: a) the evaluation of the concentration of at least one of the compounds selected from the group consisting of of glutamate, glycerate, guanidoacetate, pantothenate, 5 oxaloacetate, 3ureidopropionate, 3-hydroxybutyrate, malate and pyruvate in a urine sample obtained from said human subject, b) the determination if at least one of the markers is above or below the standard values of healthy subjects, in which said markers are selected from the group consisting of glutamate concentration, glycerate concentration, guanidoacetate concentration, pantothenate concentration, oxaloacetate concentration, 3-ureidopropionate concentration, 3- concentration hydroxybutyrate, malate concentration, pyruvate concentration, panel consisting of conc glutamate entry, guanidoacetate concentration and pantothenate concentration, panel consisting of guanidoacetate concentration, pantothenate concentration, glutamate concentration, glycerate concentration, oxaloacetate concentration, 3-ureidopropionate concentration and concentration of pyruvate and the panel consisting of the pyruvate concentration and the concentration of 3-hydroxybutyrate and, c) the identification of the risk in said human subject evaluating the result of step b).

2.

Prognosis method according to claim 1, characterized in that said hypertensive human subject is under treatment with reninaangiotensin system inhibitors.

3.

Forecasting method according to claim 1 or 2, characterized in that the concentrations of step (b) are quantified by a technique selected from the group consisting of nuclear magnetic resonance, immunoassay, chromatography, electrochemical sensors, microarray and mass spectrometry ° any combination of the above.

Four.

Kit for carrying out the method according to any of claims 1 to 3, characterized in that it comprises reagents suitable for the quantification of the concentration of at least one of the compounds selected from the group consisting of glutamate, glycerate, guanidoacetate, pantothenate, oxaloacetate, 3 ureidopropionate, 3-hydroxybutyrate, malate and pyruvate in a urine sample obtained from said human subject.