WO2014012043A1 - Urinary triaosylceramide (gb3) as a risk factor in non-fabry heart disease subjects - Google Patents

Abstract

A mortality risk factor based on urinary triaosylceramide (Gb3) in heart disease subjects is provided. In certain aspects, methods are provided for measuring urinary glycosphingo lipids and calculating a mortality risk relative to healthy subjects. In other aspects, screening for the presence of heart disease based on one or more urinary glycosphingolipids is described.

Description

DESCRIPTION

URINARY TRIAOSYLCERAMIDE (GB3) AS A RISK FACTOR IN NON-FABRY

HEART DISEASE SUBJECTS

[0001] The invention was made in part with government support under Grant No. U54 NS065768 awarded by the National Institutes of Health. The government has certain rights in the invention.

CROSS REFERENCE TO RELATED APPLICATION

[0002] This application claims benefit of priority to U.S. Provisional Application Serial No. 61/671,556, filed July 13, 2012, the entire contents of all are hereby incorporated by reference.

BACKGROUND

1. Field of the Invention

[0003] The present invention relates generally to the field of medicine and medical diagnostics. More particularly, it concerns methods for determining the risk of death in a cardiac subject by determining the levels of urinary globotriaosylceramide.

2. Description of Related Art

[0004] In the United States there are more than 27 million people who are not in hospitals but have been diagnosed with heart disease. This accounts for almost 12 percent of the adult U.S. population. Around 600,000 people die every year from heart disease, which is the leading cause of death. While there are a number of risk factors known to be associated with mortality rate for heart disease, improved methodology for evaluating risk factors and even evaluating mortality risk would improve the ability to treat subjects.

[0005] Although the number of potential cardiovascular biomarkers continues to grow, many provide only limited improvement over established metrics because they participate in pathways that are already known to be associated with cardiovascular disease. Persistent increase in blood levels of biomarkers such as troponin or natriuretic peptide concentrations are especially known to have prognostic value in post-myocardial infarction subjects. However, all known biomarker in heart disease are circulating factors that are released by cardiovascular tissue in response to mechanical or pathological stress.. SUMMARY OF THE INVENTION

[0006] In a first embodiment, there is provided a method for evaluating a subject with a cardiac disease or who may be at risk of cardiac disease by measuring the level of one or more glycolipids in a biological sample (e.g., a urine sample) from a subject; comparing the level relative to a reference level and calculating a mortality risk factor using an algorithm based on comparisons between measured and reference levels. For example, the one or more glycolipids can one or more glycosphingo lipids. In some aspects, the glycolipid can be Globotriaosylceramide (Gb3, trihexosylceramide, THC, GL-3, ceramide trihexoside), Globotriaosylspingosine, Lactosyl ceramide, Galactosyl ceramide, Glucosylceramide, Trihexosylceramide, Dihexosylceramide, Cholesterol, Sphingosine, Phosphatidic acid, lyso- Phosphatidic acid, pyro-Phosphatidic acid, cyclic-Phosphatidic acid, Phosphatidylglycerol, Cardiolipin (diphosphatidylglycerol), Phosphatidylethanolamine (PE), lyso-PE, N-acyl-PE, methyl-PE, dimethyl-PE, Phosphatidylcholine, lyso-Phosphatidylcholine, Phosphatidylserine (PS), N-acyl-PS, lyso-PS, phosphatidylthreonine, Phosphatidylinositol, Polyphosphoinositides, Bis(monoacylglycero)phosphate, Cytidine diphosphate diacylglycerol, Phosphonolipids, Platelet-activating factor,

Glycosylphosphatidylinositol(GPI)-anchored proteins, Phosphatidylinositol mannosides, Ceramides, Sphingomyelin, Sphingosine phosphorylcholine, ceramide phosphorylethanolamine, Sphingosine- 1 -phosphate, Ceramide- 1 -phosphate, Monoglycosylceramides (cerebrosides), psychosine, Oligoglycosylceramides, lactosylceramide, Gangliosides, Glycosphingolipid sulfates, Ceramide phosphorylinositol, or their isoforms.

[0007] In a further embodiment, there is provided a method for measuring a glycolipid, such as a glycosphingolipid, comprising extracting the glycolipid(s) from a sample, separating the glycolipids contained therein and detecting the glycolipids present. In some aspects, the method used to separate the glycolipid may be liquid chromatography. In further aspects, the method used to detect the separated glycolipid may be mass spectrometry. For example, separated glycolipids may be measured by electrospray ionization mass spectrometry (ESI-MS), matrix-assisted laser desorption/ionization (MALDI-MS) or atmospheric pressure chemical ionization (APCI-MS). In a yet further aspect, extracted and separated glycolipids may be measured by using nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry. [0008] In a further aspect of the embodiment, glycolipids may be measured in situ by mass spectrometry, electrospray ionization mass spectrometry (ESI-MS), matrix-assisted laser desorption/ionization (MALDI-MS), atmospheric pressure chemical ionization (APCI- MS), nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry.

[0009] In some embodiments, the urinary sample is whole urine. In certain other embodiments, the urinary sample may be processed such that urine sediments are separated out from the rest of the urine. For instance, a urine sample may be centrifuged prior to measuring the level of one or more glycolipids. The supernatant may be evaluated. In other embodiments, a urine sample may be filtered prior to measuring one or more glycolipids.

[0010] In another embodiment, glycolipids may be detected by antibodies that specifically recognize the a particular glycolipid. Antibodies may be polyclonal or monoclonal and may be raised in mouse, rat, guinea-pig, hamster, rabbit, sheep, goat, chicken, donkey, pig, cat, dog, horse or other animal capable of generating substrate specific antibodies.

[0011] In a further aspect of the embodiment, glycolipids may be detected by primary detection methods (primary antibody conjugation of chemical groups capable of detection by fluorescent or chemical means; e.g., horse radish peroxidase, Alexa Fluor dyes, etc.). Additionally, glycolipids may be detected by secondary detection methods wherein a primary antibody is recognized by secondary antibody that is species-specific for the primary antibody.

[0012] In yet still another embodiment, antibodies specifically recognizing glycolipids may be utilized for the detection of glycolipids in either pure or processed (components separated) biological samples or for the in situ detection of glycolipids in tissues.

[0013] In a further embodiment a method is provided for calculating a mortality risk factor using an algorithm based on two, three, four, five or more comparisons between the measured and reference levels of glycolipids, such as glycosphingo lipids. The algorithm may rely in part, or completely, on a proportional hazards model, which may be a Cox proportional hazards model. Approximations of the proportional hazards model may be made using Poisson models based on Poisson regression. [0014] Certain aspects of the embodiments concern reporting the mortality to risk. In certain aspects the mortality risk may be reported to a health care provider or health care professional, health care entity or to the subject. In some aspects, the report can be a written, electronic or oral report. Aspects of the embodiments concern reporting the mortality risk for a specific time window. In certain aspects, the embodiment may concern reporting the mortality risk for a time period comprising 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36 or more months.

[0015] Certain aspects of the embodiments concern a method where the reference level of one or more glyco lipids in a biological sample from one or more healthy subjects may comprise a range of values, a mean value, a median value or a set of values bounded by an upper and lower limit.

[0016] In a certain aspects of the embodiments the cardiac disease of a subject may be one or more of hypertrophic cardiomyopathy, rhythm and conduction defects, coronary artery disease, arrhythmia, conduction blocks or valvular disease. [0017] In still further embodiments a method is provided where a subject may be treated with a therapeutic agent (e.g., a cardiotherapeutic agent) knowing the calculated mortality risk factor.

[0018] In a further embodiment a method for treating a cardiac disease or cardiac condition (or of treating a subject identified to have a risk of such a condition or a risk of death from such a condition) is provided where a subject is identified as having a need for treatment against a cardiac disease or cardiac condition and treated with a composition comprised from the class of beta blockers, anti-hypertensives, cardiotonics, anti-thrombotics, vasodialators, hormone antagonists, inotropes, diuretics, endothelin antagonists, calcium channel blockers, phosphodiesterase inhibitors, ACE inhibitors, agiontensin type 2 antagonists, cytokine blockers and HDAC inhibitors. These therapeutic agents may be, specifically, Acebutolol, Alprenolol, Atenolol, Betaxolol, Bisoprolol, Bucindolol, Butaxamine, Carteolol, Carvedilol, Celiprolol, Esmolol, Eucommia bark, ICI- 1 18,551 , Labetalol, Metoprolol, Nadolol, Nebivolol, Oxprenolol, Penbutolol, Pindolol, Propranolol, Sotalol, SR 5923 OA Timolol, Berberine, Calcium, Levosimendan, Omecamtiv, Catecholamines, Dopamine, Dobutamine, Dopexamine, Epinephrine (adrenaline), Isoprenaline (isoproterenol), Norepinephrine (noradrenaline), Digoxin, Digitalis, Eicosanoids, Prostaglandins, Enoximone, Milrinone, Amrinone, Theophylline, Glucagon, Quinidine, Procainamide, disopyramide, Flecainide, Captopril, Zofenopril, Enalapril, Ramipril, Quinapril, Perindopril, Lisinopril, Benazepril, Imidapril, Zofenopril, Trandolapril, Fosinopril, Casokinins, or lactokinin. [0019] In a still further embodiment there is provided a method for screening for the presence of cardiac disease or a cardiac condition by determining the level a glucosylceramide in a urine sample from a subject and identifying the subject as having an increased risk for cardiac disease or a cardiac condition by determining the level of glucosylceramide relative to a reference level. [0020] In certain aspects of the embodiments the level of glucosylceramide may be determined by a protocol involving extraction of glucosylceramide from the urine sample, separation of glucosylceramide from other lipids and glycolipids and detection of glucosylceramide .

[0021] In a certain aspects, a method of the embodiments comprises determining the level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in the urine sample of a subject. Thus, in a further embodiment, there is provided a method where the presence of cardiac disease or a cardiac condition is screened by determining the level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in the urine sample of a subject and comparing to a reference level.

[0022] In a still further embodiment the level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in the urine sample of a subject may be determined by separated by liquid chromatrography and measured by mass spectrometry. [0023] In a yet still further embodiment measuring of the level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in the urine sample of a subject may comprise electrospray ionization mass spectrometry (ESI-MS), matrix-assisted laser desorption/ionization (MALDI- MS), atmospheric pressure chemical ionization (APCI-MS), nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry. [0024] In certain aspects of the embodiments, the risk of cardiac diseases comprising, but not limited to, hypertrophic cardiomyopathy, rhythm and conduction defects, coronary artery disease, arrhythmia, conduction blocks or valvular disease may be measured by measuring the level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in the urine sample of a subject and comparing to a reference level.

[0025] In still further aspects, a method of treating a subject determined to have an increased risk of death from a cardiac disease comprising administering a cardiac therapeutic agent composition comprised from the class of beta blockers, anti-hypertensives, cardiotonics, anti-thrombotics, vasodialators, hormone antagonists, inotropes, diuretics, endothelin antagonists, calcium channel blockers, phosphodiesterase inhibitors, ACE inhibitors, agiontensin type 2 antagonists, cytokine blockers and HDAC inhibitors. These therapeutic agents may be, specifically, Acebutolol, Alprenolol, Atenolol, Betaxolol, Bisoprolol, Bucindolol, Butaxamine, Carteolol, Carvedilol, Celiprolol, Esmolol, Eucommia bark, ICI- 1 18,551 , Labetalol, Metoprolol, Nadolol, Nebivolol, Oxprenolol, Penbutolol, Pindolol, Propranolol, Sotalol, SR 59230A Timolol, Berberine, Calcium, Levosimendan, Omecamtiv, Catecholamines, Dopamine, Dobutamine, Dopexamine, Epinephrine (adrenaline), Isoprenaline (isoproterenol), Norepinephrine (noradrenaline), Digoxin, Digitalis, Eicosanoids, Prostaglandins, Enoximone, Milrinone, Amrinone, Theophylline, Glucagon, Quinidine, Procainamide, disopyramide, Flecainide, Captopril, Zofenopril, Enalapril, Ramipril, Quinapril, Perindopril, Lisinopril, Benazepril, Imidapril, Zofenopril, Trandolapril, Fosinopril, Casokinins, or lactokinin, wherein the subject has been tested for a level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in the urine sample of a subject and comparing to a reference level.

[0026] In still a further embodiment there is provided a tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising (a) receiving information corresponding to a level of one or more glycolipid (e.g., a glycosphingolipid) in a sample, such as a urine sample, from a subject with a cardiac disease or at risk for a cardiac disease; and (b) determining a relative level of one or more glycolipid relative to a reference level for the one or more glycolipid. For example, the computer-readable code that can causes the computer to perform operations comprising (a) receiving information corresponding to a level of expression of one or more glycolipid in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease; and (b) determining a relative level of one or more glycolipid relative to a reference level for the one or more glycolipid, wherein elevated level of one or more glycolipid relative to a reference level for the one or more glycolipid indicates the presence of a mortality risk factor. In certain aspects, the computer-readable code further causes the computer to receive information corresponding to a reference level of one or more glycolipid in a sample from a healthy subject. In further aspects, the computer-readable medium comprises a reference level stored in said medium. [0027] In still further aspects, a computer-readable medium comprises code for performing one or more additional operations comprising: sending information corresponding to the relative level one or more glycolipid, to a tangible data storage device and/or calculating a diagnostic score (e.g., a mortality risk factor) for the sample, wherein the diagnostic score is indicative of the probability that the sample is from a subject having a mortality risk. In still further aspects, computer-readable medium comprises code for receiving information corresponding to a level of globotriaosylceramide, globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide, glucosylceramide, globotriaosylceramide (GB3), albumin, cystatin C, or creatinine in a sample from a subject.

[0028] A processor or processors can be used in performance of the operations driven by the example tangible computer-readable media disclosed herein. Alternatively, the processor or processors can perform those operations under hardware control, or under a combination of hardware and software control. For example, the processor may be a processor specifically configured to carry out one or more those operations, such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). The use of a processor or processors allows for the processing of information (e.g., data) that is not possible without the aid of a processor or processors, or at least not at the speed achievable with a processor or processors. Some embodiments of the performance of such operations may be achieved within a certain amount of time, such as an amount of time less than what it would take to perform the operations without the use of a computer system, processor, or processors, including no more than one hour, no more than 30 minutes, no more than 15 minutes, no more than 10 minutes, no more than one minute, no more than one second, and no more than every time interval in seconds between one second and one hour. [0029] Some embodiments of the present tangible computer-readable media may be, for example, a CD-ROM, a DVD-ROM, a flash drive, a hard drive, or any other physical storage device. Some embodiments of the present methods may include recording a tangible computer-readable medium with computer-readable code that, when executed by a computer, causes the computer to perform any of the operations discussed herein, including those associated with the present tangible computer-readable media. Recording the tangible computer-readable medium may include, for example, burning data onto a CD-ROM or a DVD-ROM, or otherwise populating a physical storage device with the data. In certain aspects, a tangible computer-readable media can be included in a kit of the embodiments. [0030] As used herein the specification, "a" or "an" may mean one or more. As used herein in the claim(s), when used in conjunction with the word "comprising", the words "a" or "an" may mean one or more than one.

[0031] The use of the term "or" in the claims is used to mean "and/or" unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and "and/or." As used herein "another" may mean at least a second or more.

[0032] Throughout this application, the term "about" is used to indicate that a value includes the inherent variation of error for the device, the method being employed to determine the value, or the variation that exists among the study subjects. [0033] Other objects, features and advantages of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein. [0035] FIG. 1: A graph showing the concentration distribution of Gb3 in all available urine specimens of cardiac subjects enrolled in the study of the present invention (N=294). Cardiac subjects data were analyzed with the software Systat and expressed as ng of Gb3 /card (mL of urine).

[0036] FIG. 2: A graph showing the concentration distribution of Gb3 in the subject set shown in FIG. 1, but the outliers (Gb3 > 700 ng/card) were excluded in order to clearly show the concentration distribution.

[0037] FIG. 3: A plot showing the concentration distribution of Gb3 in the same subject set, but limited to subjects with Gb3 < 400 ng/card in order to clearly show the concentration distribution.

[0038] FIG. 4: A graph showing the concentration distribution of Gb3 in normal control population (N= 157).

[0039] FIG. 5: A combination plot of Gb3 concentration distribution in healthy controls (N = 157) and cardiac subjects (N = 294).

[0040] FIG. 6: A box plot showing urine globotriaosylceramide distribution in cardiac subjects (N=993) and healthy controls (N=169).

[0041] FIG. 7: A graph showing distribution of urine globotriaosylceramide levels of male and female cardiac subjects (N=651; N=341, respectively) and healthy controls (N=69; N=100, respectively).

[0042] FIG. 8: A box plot showing urine globotriaosylceramide distribution of subjects with various types of heart disease (Arrhythmias/Conduction defects, N=461; CAD/MI, N=617; Cardiomyopathy, N=69; Valvular, N=174) and healthy controls (N=169).

[0043] FIG. 9: Survival probability functions for urinary globotriaosylceramide values of 100 ng/mL, 200 ng/mL, 300 ng/mL, 500 ng/mL and lOOOng/mL in cardiac subjects are presented.

[0044] FIG. 10: Graphs show total trihexosylceramide levels (left graph) or individual trihexosylceramide isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0045] FIG. 11: Graphs show total ceramide levels (left graph) or individual ceramide isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0046] FIG. 12: Graphs show total glucosylceramide levels (left graph) or individual glucosylceramide isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0047] FIG. 13: Graphs show total dihexosylceramide levels (left graph) or individual dihexosylceramide isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls. [0048] FIG. 14: Graphs show total phosphatidylcholine levels (left graph) or individual phosphatidylcholine isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0049] FIG. 15: Graphs show total sphingomyelin levels (left graph) or individual sphingomyelin isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0050] FIG. 16: Graphs show total phosphatidylinositol levels (left graph) or individual phosphatidylinositol isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0051] FIG. 17: Graphs show total phosphatidylserine levels (left graph) or individual phosphatidylserine isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0052] FIG. 18: Graphs show total phosphatidylethanolamine levels (left graph) or individual phosphatidylethanolamine isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0053] FIG. 19: Graphs show total bis monoacylglycerol phosphate levels (left graph) or individual bis monoacylglycerol phosphate isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0054] FIG. 20: Graphs show total phosphatidylglycerol levels (left graph) or individual phosphatidylglycerol isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls. [0055] FIG. 21: Graphs show total lyso phosphatidylcholine levels (left graph) or individual lyso phosphatidylcholine isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0056] FIG. 22: Graphs show total lyso phosphatidylethanolamine levels (left graph) or individual lyso phosphatidylethanolamine isoform levels (right graph) in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0057] FIG. 23: Graph shows cholesterol levels in urine of cardiac subjects with elevated urine globotriaosylceramide, cardiac subjects with not elevated urine globotriaosylceramide, Fabry disease subjects, and healthy controls.

[0058] FIG. 24: Bar graphs showing mean sphingomyelin isoform levels (left graph) and mean cholesterol level (right graph) in heart tissue of subjects with coronary artery disease (N=10) and control subjects (N=10). [0059] FIG. 25A - 25F: 3D Scatter Plot and 90% Coverage Contour Ellipsoids of Fabry and high Gb3 heart disease patients in spaces spanned by top 3 principal components of MHC, PC, SM, PS and PE isoforms. Red dots represent heart disease patients with elevated urinary Gb3 and green dots patients with Fabry disease. MHC: monohexosylceramide; PC: phosphatidylcholine; SM: sphingomyelin; PS: phosphatidylserine; PE: phosphatidylethanolamine

[0060] FIG. 26 A - 26B: Gb3 and sphingomyelin levels in the left ventricle of failing ischemic hearts. A. Heart Gb3 levels in control versus CAD. N=20 per group. B. Heart sphingomyelin (SM) levels in control versus CAD. N=10 per group. In both panels, *p<0.05, ***p<0.001 by Welch's t-test.

[0061] FIG. 27A - 27B: 3D 90% contour plots of MHC expressed as per unit of urine volume (A) or per mg of creatinine (B) of Fabry and high Gb3 heart disease patients. Red dots represent heart disease patients with elevated urinary Gb3 and green dots patients with Fabry disease.

[0062] FIG. 28A - 28C: (A)-Exploratory neutral loss scan of 88 to detect PS in human urine; (B) Chromatogram of detected PS in pooled normal human urine; (C) Chromatogram in pool 1 cardiac patients urine.

[0063] FIG.29: Scatter 3D plot and 90% 3D Contour plot of all Glucosylceramide isoforms in urine.

[0064] FIG. 30: 3D Contour plot of all Glucosylceramide isoforms in creatinine. DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

I. Gb3, Other Glycolipids, and Mortality Risk

[0065] Embodiments concern detection of elevated urinary Globotriaosylceramide (Gb3, trihexosylceramide, THC, GL-3, ceramide trihexoside) levels, which is a risk factor for a variety of acquired cardiac abnormalities in the general population (non-Fabry diseased) and a risk factor for cardiac death. This suggests the screening of high risk subjects for cardiac disease by measuring urinary Gb3 levels and calculating a mortality risk. [0066] Gb3 is a glycosphingolipid that accumulates in Fabry disease and is thought to be the main offending metabolite. Fabry disease is X-linked and is caused by a deficiency of lysosomal enzyme a-galactosidase A resulting in accumulation of Gb3 in all organs (particularly in heart and kidney) and many cell types and in the urine. This disease is associated particularly with a marked increased risk for stroke, cardiac disease (hypertrophic cardiomyopathy, rhythm and conduction defects, coronary artery disease and valvular abnormalities), and chronic proteinuric renal insufficiency.

[0067] Although Fabry disease is rare, the cardiac complications, progressive renal disease and stroke described above are similar in nature to those commonly seen in the general population. Globotriaosylsphingosine or Lyso-Gb3 may also be a Fabry-related offending metabolite and may be increased in urine of Fabry subjects and subjects with cardiac disease.

[0068] The inventors therefore screened a large population of subjects with a variety of cardiac abnormalities for Fabry disease. These cardiac subjects are screened using urinary Gb3 (known to be elevated in Fabry disease), a-galactosidase A activity in blood and sequencing of GLA gene (the gene of Fabry disease).

[0069] The inventors found that subjects with cardiac disease have higher than expected urinary Gb3 even though they do not have mutations in the GLA gene or reduction in α-galactosidase A activity (are not Fabry disease subjects) suggesting that Gb3 and its metabolism are involved in cardiac disease in general. The Gb3 abnormality is not associated with lower than normal α-galactosidase A activity.

[0070] 1421 consecutive subjects with a variety of acquired cardiac abnormalities (including coronary artery disease, arrhythmia, conduction blocks and valvular disease) were recruited. Thirteen subjects were excluded because of variants in the GLA gene (data not shown). Urinary Gb3 in cardiac subjects was 136±150 ng/niL (N=981) and 94±39 ng/niL (N=166) in the controls (p=0.002; age and sex adjusted) - Gb3 upper limit of normal (99th percentile) is 200 ng/mL. Urinary Gb3 was elevated in 15% of cardiac subjects and overlapped with levels seen in Fabry disease subjects. No Gb3 abnormalities were found in plasma of these subjects (data not shown). There was no difference in α-galactosidase A activity between subjects with heart disease and healthy controls. When the distribution of urinary Gb3 levels in the cardiac and healthy control populations are compared, it is clear that the cardiac population is significantly different from the healthy controls.

[0071] Consequently, some methods involve comparing the level or amount of at least one biomarker glycolipid to the level or amount of a comparative glycolipid (the same glycolipid as the measured glycolipid in the urinary sample). In some embodiments, methods involve comparing the level of at least one biomarker glycolipid to the standardized level or the level of that biomarker glycolipid in a standardized sample; in either case, the level is or represents the level in a non-cardiac subject or multiple non-cardiac subjects. An increase or decrease in the level can be determined based on a comparative value. In some embodiments, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28,

29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 comparative markers (or any range derivable therein) may be used in comparisons or compared to the level of a biomarker or of a biomarker glycolipid. In other embodiments at least or at most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 comparative markers are measured. In particular embodiments, at least or at most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,

30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 comparative markers are compared to one or more biomarker glycolipids. A "comparative marker" refers to a glycolipid whose expression level is used to evaluate the level of a glycolipid in the sample. A subject may be determined to have a high mortality risk, where "high" is based on a threshold mortality risk value or number. A subject may be determined to have a low mortality risk, where "low" is based on a threshold mortality risk value or number. What qualifies as high or low risk can be set based on the relative mortality risk of a population of subjects with a certain profile of characteristics, such as gender, age, smoking status, activity level, etc.

[0072] In certain embodiments, methods involving measuring or assaying the level of one or more of the following glycolipids: Globotriaosylceramide (Gb3), Globotriaosylspingosine, Lactosyl ceramide, Galactosyl ceramide, Glucosylceramide, Trihexosylceramide, Dihexosylceramide, Cholesterol, Sphingosine, Phosphatidic acid, lyso- Phosphatidic acid, pyro-Phosphatidic acid, cyclic-Phosphatidic acid, Phosphatidylglycerol, Cardiolipin (diphosphatidylglycerol), Phosphatidylethanolamine (PE), lyso-PE, N-acyl-PE, methyl-PE, dimethyl-PE, Phosphatidylcholine, lyso-Phosphatidylcholine, Phosphatidylserine (PS), N-acyl-PS, lyso-PS, phosphatidylthreonine, Phosphatidylinositol, Polyphosphoinositides, Bis(monoacylglycero)phosphate, Cytidine diphosphate diacylglycerol, Phosphonolipids, Platelet-activating factor, Glycosylphosphatidylinositol(GPI)-anchored proteins, Phosphatidylinositol mannosides, Ceramides, Sphingomyelin, Sphingosine phosphorylcholine, ceramide phosphorylethanolamine, Sphingosine- 1 -phosphate, Ceramide- 1 -phosphate,

Monoglycosylceramides (cerebrosides), psychosine, Oligoglycosylceramides, lactosylceramide, Gangliosides, Glycosphingolipid sulfates, Ceramide phosphorylinositol, and their iso forms.

[0073] In some embodiments, the urinary sample is whole urine. In certain other embodiments, the urinary sample may be processed such that urine sediments are separated out from the rest of the urine. For instance, a urine sample may be centrifuged prior to measuring the level of one or more glycolipids. The supernatant may be evaluated. In other embodiments, a urine sample may be filtered prior to measuring one or more glycolipids.

II. Assaying for Glycolipids

[0074] In some embodiments of mass spectrometry, tandem mass spectrometry (MS/MS) with a collision cell between the mass spectrometers may be used. Sample introduction may utilize electrospray ionization. In some embodiments no pre-separation may be used. Two types of scans may be used to obtain polar lipid profiles. One type of scan is the precursor scan; the other type of scan is the neutral loss scan. Scans may be specific to the particular lipid classes. Some classes are analyzed with precursor scans while others are analyzed with neutral loss scans.

[0075] The sample may be introduced by continuous infusion in solvent into the electrospray ionization source, where lipid molecular ions are produced from the lipid molecules. In some method, phosphatidylcholine (PC), lyso-PC, sphingomyelin (SM), phoPS, phophatidylethanolamme (PE) and lysoPE are analyzed as singly-charged positive [M+H]+ ions. In yet another method, MGDG, DGDG, PG, PI, PA, and PS are analyzed as singly-charged [M + NH4]+ ions, and lysoPG as negative [M-H] - ions. The ions that are available for analysis depend on the solution in which the lipids are dissolved and on the source voltage. The ions enter the mass spectrometer in the gas phase. [0076] Inside a quadrupole mass spectrometer, the ions are in an electrical field. At a certain electrical field strength, ions of a particular mass/charge ratio will move straight toward the detector at the end of the tandem mass spectrometer ion path. Scanning, or systematically varying the electrical field strength, produces a plot of signal vs. mass/charge (correlated with electrical field strength).

[0077] In the case of lipids, the charge is almost always 1 , so mass/charge = mass. Scanning of the ions in a tissue or cell extract with one quadrupole mass spectrometer produces many peaks, with some peaks representing several molecular species of lipids (i.e., different lipid molecular species with the same mass). Precursor or neutral loss scans allow specific detection of species within particular head group classes and allow identification and quantification of individual lipid molecular species.

[0078] The molecular species are identified by (1) the presence of a specific head group fragment and (2) the mass. The mass generally allows us to assign a specific number of acyl carbons and number of double bonds. [0079] For "precursor" spectra (scans), the second mass spec is set at a (constant) electrical field that allows only ions with a mass that corresponds to a characteristic charged fragment generated from the polar lipid head group to move to the detector. Subsequently the first mass spectrometer will scan. The second mass spec effectively acts as a "filter" so only a "hit" at the detector is detected when a molecular ion from the first mass spec produces the characteristic head group fragment. Thus, the spectra show only the lipids that have that head group fragment. Usually this corresponds to the lipids in one head group class.

[0080] A neutral loss spectrum also shows the lipids in a single class, but this type of spectrum is obtained when the charge does not localize to the lipid head group after fragmentation. In these lipids, the diacylglycerol ions produced vary in mass as a function of the molecular ion acyl composition, but the difference in mass between the molecular ion and the charged DAG fragments is constant (corresponding to the head group). Therefore, the second mass spectrometer scans in sync with the first mass spectrometer with an electrical field offset that corresponds to the mass of the neutral head group fragment. Similar to precursor scanning, only a hit at the detector is detected when the first mass spectrometer is at a field strength that corresponds to a mass generating the characteristic neutral loss of the head group. [0081] Corrections are applied to the data for "isotopic overlap". This phenomenon is due to the approximately 1% natural abundance of 13C. This means that a molecular ion with 50 carbons, for example, will produce not one, but a series of peaks: (1) a peak at the "nominal" mass, A; (2) a peak at A+l, from the species containing one 13C atom, with 56% of the signal of the A peak; (3) a peak at A+2, from the species containing two 13C atoms, with 15% of the signal of the A peak; (4) a peak at A+3, from the species containing three 13C atoms, with 3% of the signal of the A peak. Since the presence/absence of a double bond in a lipid species causes a difference of just two mass units, the A+2 peak of one species will produce a signal at the same mass as the A peak of another (more saturated) species. The contribution of A+2 species to the signal of the second peak must be subtracted.

[0082] After corrections peaks on the spectra are quantified in comparison to a group of internal standards. Generally, two internal standards of each head group class are used. Signal that may be due to low levels of contaminants in a internal standard mixture may be subtracted. [0083] The precursor and neutral loss methodologies may be supplanted by the more typically used "product" ion scans in which the first mass spec is held at a constant electrical field, corresponding to a particular molecular ion mass, while scanning is performed with the second mass spectrometer to detect the fragments made in the collision cell. Product ion scans can be used to determine the head group or other fragments that are produced. Product ion scans can be used to identify the fatty acyl groups in particular polar lipid molecular species, when this additional analysis is required.

[0084] Ultra Performance Liquid Chromatography (UPLC) tandem mass spectrometry (MS/MS) may be used for quantitative determination of glycolipid and glycosphingolipids and their isoforms with different fatty acid components. In some embodiments, samples may be in urine dried on filter paper cards. Subsequently, one milliliter of urine dried on a 5 x 5 cm square of filter paper is extracted with methanol. For example, for detection of Gb3, C17-Gb3 may be used as internal standard. Ten microliters are injected into an Acquity UPLC for chromatographic separation of Gb3 isoforms using a fast methanol/water gradient with a C8 BEH, 1 x 50 mm, 1.7 μιη UPLC column at 60 C, with a total run time of 3 minutes, including column re-equilibration. Gb3 is analyzed with a Quattro Premier MS/MS using positive electrospray ionization. Multiple reaction monitoring transitions are m/z 1060→898 for C17-Gb3 internal standard and ml 1046 →884, 1074→912, 1102→940, 1128→966, 1130→968, 1156→994, 1158→996, 1174→1012 to encompass eight major Gb3 isoforms. The peak areas of the MRM chromatograms for the isoforms are used with standard curves to calculate nanograms of Gb3 per ml of urine.

[0085] In another embodiment, glycolipids may be detected by antibodies that specifically recognize a particular glycolipid. Antibodies may be polyclonal or monoclonal and may be raised in mouse, rat, guinea-pig, hamster, rabbit, sheep, goat, chicken, donkey, pig, cat, dog, horse or other animal capable of generating substrate specific antibodies.

[0086] In a further aspect of the embodiment, glycolipids may be detected by primary detection methods (primary antibody conjugation of chemical groups capable of detection by fluorescent or chemical means; e.g., horse radish peroxidase, Alexa Fluor dyes, etc.). Additionally, glycolipids may be detected by secondary detection methods wherein a primary antibody is recognized by secondary antibody that is species-specific for the primary antibody.

[0087] In yet still another embodiment, antibodies specifically recognizing glycolipids may be utilized for the detection of glycolipids in either pure or processed (components separated) biological samples or for the in situ detection of glycolipids in tissues.

III. Mortality Risk Calculation

[0088] The levels of one or more glycolipids in a subject's urinary sample provides quantitative information that can be used to calculate the subject's risk of mortality. Risk of mortality is an estimate of the likelihood of death for a subject. Information regarding amounts or levels of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more different glycolipids in the urinary sample can be the basis for determining a value that represents the subject's mortality risk. As shown below, the rate of death increases by 60% for every increase of 200 units of Gb₃. Survival functions for Gb₃ values of 100, 200, 300, 500, and 1000 are presented in FIG. 9 and described below. An algorithm would be based on this observation and it can be employed to calculate a mortality risk based on one or more data points, such as the subject's urinary Gb3 value or the value of one or more other urinary glycolipids, In some embodiments, an algorithm takes into account other factors such as age, gender, familial cardiac history, stress test results, blood pressure, heart rate, cholesterol level, weight, body mass index, and/or smoking status. [0089] A mortality risk value may be calculated, determined or evaluated using one or more mathematical formulas or algorithms. The algorithm may include data from or values representative of the mortality risks of a plurality of subjects, which may be non-cardiac subjects, cardiac subjects, or both. This data or representative values will reflect or embody urinary glycolipid levels, such as the level of Gb3. In some embodiments, the value is calculated, determined or evaluated using computer software.

[0090] Any of the methods described herein may be implemented on tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform one or more operations. In some embodiments, there is a tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: a) receiving information corresponding to the levels of one or more glycolipids in a urinary sample; b) comparing those levels to control or reference levels for one or more of those glycolipids; and c) calculating or determining a mortality risk value for the subject based on one or more comparisons.

[0091] In additional embodiments the medium further comprises computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising: sending information corresponding to the differential value between the measured urinary glycolipid and the reference or control to a tangible data storage device. In specific embodiments, it further comprises computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising: sending information corresponding to the differential value to a tangible data storage device. In certain embodiments, receiving information comprises receiving from a tangible data storage device information corresponding to a level of one or more glycolipids, such as Gb3, in the urinary sample of the subject. It is contemplated that any of the methods described above may be implemented with tangible computer readable medium that has computer readable code, that when executed by a computer, causes the computer to perform operations related to the measuring, comparing, and/or calculating a mortality risk value related to the probability of the subject's death. [0092] A processor or processors can be used in performance of the operations driven by the example tangible computer-readable media disclosed herein. Alternatively, the processor or processors can perform those operations under hardware control, or under a combination of hardware and software control. For example, the processor may be a processor specifically configured to carry out one or more those operations, such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). The use of a processor or processors allows for the processing of information (e.g., data) that is not possible without the aid of a processor or processors, or at least not at the speed achievable with a processor or processors. Some embodiments of the performance of such operations may be achieved within a certain amount of time, such as an amount of time less than what it would take to perform the operations without the use of a computer system, processor, or processors, including no more than one hour, no more than 30 minutes, no more than 15 minutes, no more than 10 minutes, no more than one minute, no more than one second, and no more than every time interval in seconds between one second and one hour.

[0093] Some embodiments of the present tangible computer-readable media may be, for example, a CD-ROM, a DVD-ROM, a flash drive, a hard drive, or any other physical storage device. Some embodiments of the present methods may include recording a tangible computer-readable medium with computer-readable code that, when executed by a computer, causes the computer to perform any of the operations discussed herein, including those associated with the present tangible computer-readable media. Recording the tangible computer-readable medium may include, for example, burning data onto a CD-ROM or a DVD-ROM, or otherwise populating a physical storage device with the data. [0094] Summary statistics are presented by death status in Table 2. Means with standard deviations and frequencies with percents are given for continuous and categorical variables respectively. Missing data were imputed using the expectation-maximization algorithm. A Cox proportional-hazards model with inverse probability weights (IPWs) was generated to assess the association between Gb₃ and death. The IPWs were used to standardize the populations of subjects with Gb₃ values less than or equal to 63, 63 to 211, and greater than 211 using the variables listed in Table 2 other than Gb₃ and follow-up. Of the 1406 subjects with cardiovascular disease, 75 died during the follow-up period. The median follow-up time and time to death was 17 and 7 months respectively. There was a statistically significant association between GB₃ and risk of death (P<0.0001) after correction for multiple variables and confounders listed in Table 2. The rate of death increases by 60% for every increase of 200 units of GB₃. Survival functions for Gb₃ values of 100, 200, 300, 500, and 1000 ng/niL are presented in FIG 9. [0095] A reference level may represent a level from a healthy, non-cardiac diseased subject or be representative of a level in a non-cardiac diseased subject. In some embodiments, the reference level may represent a mean value of a group of healthy, non- cardiac disease subjects. In specific embodiments, a reference level may be a level from a subject with Fabry disease or be representative of a level in a Fabry disease subject. Alternatively, the reference level may be the level in a subject who has a cardiac disease but does not have Fabry disease. A person of ordinary skill in the art would understand how to use different controls to evaluate one or more levels from a subject being evaluated.

IV. Therapeutic Administration

[0096] Some embodiments concern treating a subject after the subject has been assessed for one or more urinary glycolipids and been determined to have or be at risk for a cardiac disease. In certain embodiments, the mortaility risk of the subject has been assessed based on the levels of urinary Gb3 and other glycolipids. In certain embodiments, methods concern providing to a cardiac subject or a subject at risk for a cardiac disease pharmaceutical cardiac therapies which may belong to one of the following classes: beta blockers, antihypertensives, cardiotonics, anti-thrombotics, vasodialators, hormone antagonists, inotropes, diuretics, endothelin antagonists, calcium channel blockers, phosphodiesterase inhibitors, ACE inhibitors, agiontensin type 2 antagonists, cytokine blockers and HDAC inhibitors. Cardio therapeutics and varying methods of administration are well-known; these are disclosed in U.S. Pat. No. 8,093,286, which is incorporated by reference herein.

[0097] Cardiac therapeutics belonging to the beta blocker class may of, but are not limited to, one of the following : Acebutolol, Alprenolol, Atenolol, Betaxolol, Bisoprolol, Bucindolol, Butaxamine, Carteolol, Carvedilol, Celiprolol, Esmolol, Eucommia bark, ICI- 118,551, Labetalol, Metoprolol, Nadolol, Nebivolol, Oxprenolol, Penbutolol, Pindolol, Propranolol, Sotalol, SR 59230A Timolol.

[0098] Cardiac therapeutics belonging to the inotrope class may be of, but are not limited to, one of the following : Berberine, Calcium, Levosimendan, Omecamtiv, Catecholamines, Dopamine, Dobutamine, Dopexamine, Epinephrine (adrenaline), Isoprenaline (isoproterenol), Norepinephrine (noradrenaline), Digoxin, Digitalis, Eicosanoids, Prostaglandins, Enoximone, Milrinone, Amrinone, Theophylline, Glucagon, Quinidine, Procainamide, disopyramide, Flecainide. [0099] Cardiac therapeutics belonging to the ACE inhibitor class may be of, but are not limited to, one of the following : Captopril, Zofenopril, Enalapril, Ramipril, Quinapril, Perindopril, Lisinopril, Benazepril, Imidapril, Zofenopril, Trandolapril, Fosinopril, Casokinins, lactokinins. [00100] In another aspect, a cardiac disease or a cardiac condition may be treated by administering a composition of migalastat hydrochloride or eliglustat and one or more optional pharmaceutically acceptable excipients in a concentration sufficient to treat the cardiac disease or the cardiac condition.

[00101] In still another aspect, administration of a therapeutic may be combined with enzyme reaplacement therapy (ERT). ERT may be co-administered with the therapeutic in question or administered separately.

[00102] In yet another embodiment, a cardiac disease or a cardiac condition may be treated by substrate reduction therapies as detailed in, Park et al Pharmacological Research 58 (2008) 45-51, Park et al Circulation. 2004;110:3465-3471, Li et al Biochimica et Biophysica Acta 1791 (2009) 297-306, Bietrix, F. et al. Arterioscler Thromb Vase Biol 2010;30:931-937, the contents of which are incorporated by reference herein.

V. Principal Component Analysis

[00103] Principal component analysis (PCA) is a multivariate dimension reduction procedure that linearly convert multiple correlated variables (lipids isoforms) into a set of linearly uncorrected variables called principal components, among which the first principal component accounts for the largest variability, and each succeeding component accounts for the highest variance possible under the constraint that it be orthogonal to (i.e., uncorrected with) the preceding components. PCA is often used to supply a lower- dimensional picture of the data, typically 3D scatterplot with axes being the top 3 principal components.

[00104] If sample data collected on variables are highly skewed, log transformation is a standard procedure to be applied prior to principal components. This is because the PC calculations are susceptible to outliers when the covariance matrix is used. PCA can also be implemented on correlation matrix, which is more robust to skewed distributions. Eigenvectors and eigenvalues of the covariance/correlation matrix are calculated, for which the eigenvector associated with the largest eigenvalue is the first principal component, and the second largest eigenvalue's corresponding eigenvector is the second principal component and etc.

[00105] The original data of a subject is a vector (a series of lipid isoform measurements) and can be imagined as a point in a high-dimensional space. Principal components can be utilized to visualize data with the most information retained. The corresponding coordinates of that subject in the 3D space are calculated as linear transformation of the original vector by coefficients of the top 3 PCs, separately.

[00106] Normal elliptical contour is often employed to estimate the center and radius of the population that a group of sample comes from. If two 90% coverage contours are separated from each other in a 3D scatterplot, there is likely to be a distinction between the corresponding populations, and this type of exploratory analysis result has a positive indication of good power for further statistical inference to discriminate these two populations. VI. Examples

[00107] The following examples are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples which follow represent techniques discovered by the inventor to function well in the practice of the invention, and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention.

Example 1 - Association of Urinary Globotriaosylceramide Levels with Risk of Death in Subjects with Heart Disease

[00108] Clinical study— A subject population with all forms of heart disease was screened for Fabry disease (ClinicalTrials.gov Identifier: NCT01019629). Subjects were 18 years of age or older and were seen at Baylor Healthcare System heart hospitals. Healthy controls with no history of heart disease were recruited in parallel from volunteers and friends and relatives of subjects visiting the heart hospitals. Screening was performed by measuring urinary Gb3 in randomly collected samples of whole urine using ultra high pressure chromatography-tandem mass spectrometry (UPLC-MS/MS), measuring a-galactosidase A activity in dried blood spots by flow injection analysis-tandem mass spectrometry (FIA- MS/MS),and looking for GLA gene mutations by parallel sequencing of the whole gene inpooled genomic DNA samples. Conventional Sanger sequencing was used to further analyze individual samples from selected subject DNA pools. Death (all causes) of a subject was determined by accessing the Social Security Death Index.

[00109] Gb₃ analysis in urine by mass spectrometry— Urinary Gb3 was measured by UPLC-MS/MS, the analytical method was based on a published method (Auray-Blais, et al, 2007) and modified based on the specific circumstances and observations to fit the needs of the present study (Duffey, et al, 2010). 25 μΐ, of C17-Gb3 at a concentration of 50 μg/mL was added to one milliliter of urine dried on 5x5 cm filter paper square and was extracted with 4 mL of methanol. 10 were injected into the UPLC-MS/MS system.

Chromatography with a fast methanol/water gradient was performed using a C8 BEH, 1x50 mm, 1.7 μιη UPLC column, at 60°C, with a total run time of 3 minutes, including column re- equilibration. Gb3 was detected with a Quattro Premier Tandem mass spectrometer, in positive ion mode. Multiple reaction monitoring (MRM) transitions were: m/z 1060.6^898.6 for C17-Gb3 and 1046.6 ^884.6 for C16:0, 1074^912.6 for C18:0, 1102^940.6 for C20:0, 1128^966.6 for C22: l, 1130^968.6 for C22:0, 1156^994.6 for C24: l, 1158^996.6 for C24:0, 1174^ 1012.6 for C24:0(OH) for a total of eight Gb3 isoforms. Concentrations of urinary Gb3 were expressed as ng/mL.

[00110] a-Galactosidase A activity evaluation by tandem mass spectrometry—

The analytical procedure was based on the "Triplex" method (Duffey, et al, 2010). A 3-mm dried blood spot punch was incubated for 18 hours at 37°C in a single assay buffer with substrate and internal standard. Fabry internal standard (a-galactosidase A [GLAJ-IS) and Fabry substrate were from Drs. H. Zhou and V. De Jesus (CDC, Atlanta, Georgia, USA). The samples were processed by a simple liquid-liquid extraction by using ethyl acetate. The extracts were dried and resuspended in 80/20 v/v acetonitrile/water with 0.2% formic acid for injection into the tandem mass spectrometer. Products and internal standard were monitored by multiple reaction monitoring (MRM) (Duffey, et al, 2010). Samples were processed in a 96-well plate and each plate included 6 blank samples and quality controls in duplicate. Quality control DBS samples (low, medium, and high) were obtained from Drs. H. Zhou and V. De Jesus at the CDC in Atlanta. 20 were injected for flow injection analysis - tandem mass spectrometry using a Micromass (Waters) Quattro LC triple quadrupole. The flow rate was 40 μΙ7ηώι. MRM transitions were m/z 489.3^389.3 for [GLA]-IS and m/z 483.3 -» 383.3 for GLA product. [00111] Gb3 analysis on heart tissue by mass spectrometry— Human heart tissue

(left ventricular tip, full wall thickness) was obtained at the time of transplantation from patients with end-stage heart failure due to ischemic heart disease. Control samples from subjects without heart failure were obtained from hearts harvested for transplantation, but unutilized for non-cardiac reasons. Both patients and controls were randomly selected. Tissue was flash frozen in liquid nitrogen according to methods previously described. To perform heart tissue Gb3 quantitation, homogenates were prepared by adding 16 μΐ, of ice cold deionized water per mg of heart tissue. 50:50 acetone :methanol was added to the homogenate (ratio 20 : 1), the mixture was vortexed, rehomogenized, and centrifuged at 10600g for 10 minutes at room temperature. A 50

aliquot of each supernatant was transferred to a 13 ml silanized glass tube and prepared for solid phase extraction (SPE); successive additions of 200 μΕ DMSO, 150 μΕ of 1 :20 water: (1 :1 acetone: methanol), 50 μΕ C17-CTH internal standard (from porcine red blood cell (RBC); (Matreya, LLC, Pleasant Gap, PA)) at a final concentration of 1 μg/mL, and 600

of water: methanol (13:87) were briefly vortexed and loaded onto a pre-conditioned Varian Bond Elut 40 μιη, 100 mg C-18 column (Varian Inc, Palo Alto, CA). After elution, the column was washed with 67:23: 10 methanol:acetone:water. Gb3 was eluted from the column with 1 mL of 9: 1 acetone :methanol into silanized glass tubes containing 300 O. Samples were evaporated to the DMSO layer at 40 °C for 10 min and vortexe

were injected into a LC-MS/MS system (LC: Shimadzu Corporation, Kyoto, Japan; MS/MS: 4000QTRAP LC/MS/MS, Applied Biosystems, Foster City, CA) at room temperature. The separation was carried out on a C18 analytical column (Phenomenex Aqua 3 μιη 100 x 3.0 mm, 125 A; Phenomenex, Torrance, CA) under gradient elution with acetone/methanol/acetonitrile with sodium acetate binary mobile phase system at a flow rate of 0.5 mL/min. MS/MS analysis was performed in positive ion mode (ESI+): ionspray voltage of +5500 V, a source temperature of 400 °C, a curtain gas flow of 20 psi, a Gasl flow of 60 psi, a Gas2 flow of 40 psi, a de-clustering potential (DP) in the [+251 - +336] V range, and a collision energy (CE) in the [+83 - + 93] V range. The following 12 transitions were monitored: m/z 1046.70→m/z 884.7 for C16:0; m/z 1074.8→m z 912.8 for C18:0; m z 1102.8→m/z 940.8 for C20:0; m/z 1128.8→m/z 966.8 for C22: l; m/z 1130.9→m/z 968.8 for C22:0; m/z 1144.9→m/z 982.8 for C23:0; m/z 1146.9→m z 984.8 for C22:0(2OH); m z 1154.9→m/z 992.8 for C24:2; m/z 1156.9→m/z 994.8 for C24: l; m/z 1158.9→m/z 996.9 for C24:0; m/z 1172.9→m/z 1010.8 for C24: 1(20H); m/z 1174.9→m/z 1012.8 for C24:0(2OH); and m/z 1060.7→m/z 898.6 for the C17-CTH internal standard. : The ratio of the total Gb3 area counts (sum of 12 iso forms) to that of the internal standard was used to calculate the concentration of Gb3 in each sample based on a linear equation fitted with the weighting factor 1/x². Total Gb3 measurements were normalized to wet tissue weight.

[00112] Lipid profiling of urine and heart tissue— Pieces of heart tissue were thawed and homogenized in 1 mL 0.5 M NaCl, 20 mM Tris, pH 7, using a Microson Ultrasonic Cell Disruptor, and total protein was determined by the Lowry method (Lowry, et al, 1951). Lipids were extracted from 0.1 mg of protein by the method of Folch method (Folch, et al, 1957) and from 1.5 ml of urine by the Bligh and Dyer method (Bligh & Dyer, 1959) with the inclusion of 400 pmol of the following internal standards: bis (monoacylglycero) phosphate (BMP) 14:0/14:0, ceramide 18: 1/17:0, dihexosylceramide (DHC) 18: 1/16:0 (d3), monohexosylceramide (MHC) 18: 1/16:0 (d3), phosphatidylethanolamine (PE) 17:0/17:0, phosphatidylglycerol (PG) 14:0/14:0, phosphatidyinositol (PI) 16:0/16:0, phosphatidylserine (PS) 17:0/17:0, cholesteryl heptadecanoate 17:0 and 100 pmol of lysoPC 13:0 and lyso PE 14:0. Dried lipid extracts were resuspended in 0.2 mL of methanol containing 10 mM NH₄COOH and 20

were injected onto a 3 μιη Alltima CI 8 column (50 x 2.1 mm) at a flow rate of 0.2 μΕ/ηιίη in 70% mobile phase A (30% tetrahydrofuran/20%CH₃OH/10%H₂O in 5 mM NH4COOH). This was then linearly converted to 100% mobile phase B (70% tetrahydrofuran/20%CH₃OH/10%H₂O in 5 mM NH₄COOH) over 7 min and maintained for 3 min prior to the next injection. A divert valve was used for the first 1.6 minutes. Following chromatography, individual species of ceramide, MHC, DHC, SM, PC, PI, PE, PS and cholesterol were quantified by ESI- MS/MS as described (Hein, et al, 2008), and BMP and PG as described (Meikle, et al, 2008). LysoPC and lysoPE were quantified in positive and negative ion in the MRM mode, respectively. For lysoPC the ion spray voltage was +5500, source temperature 200 C, curtain gas, gasl and 2 flow lOpsi, DP 106, CE 37, and 16 isoforms were measured using the m/z product ion of 184 corresponding to the phosphocholine head group. For lysoPE the ion spray voltage was -4500, source temperature 200°C, curtain gas flow 10 psi, gasl flow 16 psi and gas 2 flow lOpsi, DP -70, CE -33, and 12 isoforms were measured using the m/z product ion of 196 corresponding to the dilyso-H₂0. Concentrations of individual species were calculated by relating the AUC to that for the corresponding internal standard. The total amount of each lipid was determined by summing each of the isoforms.

[00113] Determination of urine pellet size— 1.5 mL of thawed frozen urine was aliquoted into an Eppendorf vial in duplicate for each sample. The specimens were centrifuged at low speed (1000 g) at 4 C for 10 minutes in order to precipitate salts and inorganic matter. The supernatant was transferred into a second pre -weighed vial. The samples were spun at maximum speed (13500 rpm) for 30 minutes. The supernatant was removed and discarded. The pellet was dried overnight in a rotary evaporator. The vial containing the dry residue was weighted again and the weight of the dry residue was calculated.

Statistical Methods

[00114] Comparison of urinary Gb3 levels with controls— The two categories investigated for this analysis were cardiac patients and healthy controls. Summary statistics are presented by disease status in Tables 1. Medians with first and third quartiles and frequencies with percentages are given for continuous and categorical variables respectively. Because Gb3 distributions in patients with heart disease and control groups may not have had equal variances, a statistical model allowing for unequal variances among groups (variance component) was used to test for differences in mean Gb3 values (log base 10 transformed). Age, gender, ethnicity, race, known risk factors for heart disease (Table 1) and medications were accessed as potential confounders.

[00115] Assessing the associate between Gb3 and death in heart disease patients — Summary statistics of patients with heart disease are presented by death status in Table 2. Means with standard deviations and frequencies with percentages are given for continuous and categorical variables respectively. Missing data were imputed using the expectation- maximization algorithm. A Cox proportional hazards model with inverse probability weights (IPWs) was generated to assess the relationship between Gb3 and death. The IPWs were used to standardize the populations of subjects with Gb3 values less than or equal to 63 ng/ml (calculated first decile from sample), 63 to 211 ng/ml, and greater than 211 (calculated ninth decile from sample) using the demographic, clinical, and medication variables presented in Table 2. [00116] Urinary lipid profiling comparison in patient with heart disease, Fabry disease and controls— In order to ascertain that patients with heart disease and high urinary Gb3 have a different lipid pattern from Fabry disease patients, the applicants applied principal component analysis (PCA). Data that was log transformed prior to the first PCA was applied on the correlation matrixes of all lipid isoforms. The lipid groups that showed a separation pattern between Fabry and high Gb3 groups using 90% coverage normal contours ellipsoids were pooled for the second PCA. In order to evaluate individual isoforms and the top 3 principal components for their ability to separate the urinary lipid profile of Fabry disease patients from that of heart disease patients with high Gb3, Receiver-Operating Characteristic (ROC) Curves were plotted. To quantify the differential expression of each isoform between the Fabry group and the group of heart disease patients with elevated urine Gb3, two independent sample t-test and Wilcoxon test were applied on all the isoforms simultaneously, and multiple comparison corrections (Benjamini & Hochberg) were imposed on p-values returned by these two tests.

Table 1 . Summary statistics by disease status, age, urinary Gb3 levels (ng/ml) and ethnic background.

'Urinary Gb₃ was independent of age Table 2. Summary statistics for 1408 heart disease subjects by death status.

Alive (ISM 333) Deceased (N=75) N(%) N(%)

Female 473 (35.5%) 20 (26.7%)

Ethnicity Hispanic 55 (4.1 %) 0 (0.0%)

Non-Hispanic 1271 (95.9%) 75 (100.0%) Race Black 85 (6.4%) 6 (8.0%)

White/Caucasian 1213 (91 .3%) 69 (92.0%)

Other 31 (2.3%) 0 (0.0%)

Variable N Mean (Std Dev) N Mean (Std Dev)

Age (yrs) 1331 63.2 (12.7) 75 69.5 (9.1 )

Follow-up (months) 1331 17.1 (10.7) 75 9.7 (8.5)

Gb₃ 1331 122.3 (87) 75 187.2 (308.8)

AlphaGAL 1302 6 (3.9) 74 6.2 (5)

Main Diagnosis

CAD 859 (64.5%) 59 (78.7%)

Cardiomyopathy 1 17 (8.8%) 1 1 (14.7%)

Valvular Disease 186 (14.0%) 12 (16.0%)

Arrhythmia/conduction 604 (45.4%) 39 (52.0%)

Risk Factors

BMI 1331 29.9 (6.8) 75 28 (5.8)

Ejection Fraction 917 49.4 (15.1 ) 59 39.5 (17.7) eGFR 1288 69.3 (25.5) 74 53.2 (25.3)

HDL 1079 45.4 (17.9) 57 38.6 (12.5)

LDL 1084 96.5 (35.5) 58 92 (44.4)

Proteinuria 130 (9.8%) 4 (5.3%)

Diabetes 191 (14.4%) 17 (22.7%)

Onset < age 40 67 (5.0%) I (1 .3%)

Medications

ACE 536 (40.3%) 31 (41.3%)

ARB 261 (19.6%) 20 (26.7%)

Analgesic 842 (63.4%) 50 (66.7%)

Antihyperlidemic 947 (71.3%) 55 (73.3%)

Antiplatelet_agent 412 (31.0%) 28 (37.3%)

Beta_Blocker 444 (33.4%) 23 (30.7%)

Anticoagulant 330 (24.8%) 28 (37.3%)

Calcium Channel Block. 222 (16.7%) 13 (17.3%)

Cardiac glycoside 96 (7.2%) 14 (18.7%)

Antiarrhythmics 215 (16.2%) 22 (29.3%)

Vasodilator 196 (14.7%) I I (14.7%)

Diuretics 280 (21.1 %) 35 (46.7%)

Potassium replacement 197 (14.8%) 24 (32.0%) Table 3. Eigen Value and Eigenvectors on the top 3 principal components

Prinl Prin2 Prin3

Eigen Value 29.00 1.35 0.61

Percent of Variation 90.6% 4.2% 1.9%

Eigen Vector

GC.C18.1.16.0 0. 16878 -0.22969 0.34193

GC.C18.1.20.0 0. 15490 -0.37029 0.40592

GC.C18.1.22.0 0. 16710 -0.29992 0.32164

GC.C18.1.24.0 0. 17468 -0.16814 0.33222

PC.C32.0 0. 18357 0.00830 0.04633

PC.C32.1 0. 18296 0.06891 -0.02844

PC.C34.1 0. 18366 0.04696 0.01634

PC.C34.2 0. 17742 0.01040 -0.07155

PC.C36.2 0. 17950 0.13986 0.00732

PC.C36.4 0. 17582 0.01796 -0.10695

PC.C38.4 0. 17449 -0.0841 1 -0.18098

SM.C18.0.20.0 0. 18358 0.05705 0.01530

SM.C18.1.16.0 0. 18495 -0.05186 -0.03634

SM.C18.1.16.1 0. 17442 -0.16272 -0.26107

SM.C18.1.18.0 0. 18332 -0.08620 -0.05964

SM.C18.1.18.1 0. 17851 -0.09876 -0.22643

SM.C18.1.22.0 0. 17894 0.14567 0.01782

SM.C18.1.24.0 0. 18120 -0.12693 -0.0221 1

SM.C18.1.24.1 0. 17899 -0.17291 -0.17461

PS.C18.0.18.2 0. 18305 0.01671 0.02929

PS.C18.0.20.4 0. 17774 -0.10889 -0.17537

PS.C18.1.18.0 0. 18076 0.06609 0.11805

PS.C18.1.18.1 0. , 18141 0.09424 0.04303

PE.C16.0.22.4 0. 17982 -0.071 14 -0.20636

PE.C18.0.18.2 0. 18062 0.09980 -0.06485

PE.C18.0.20.4 0. 18165 -0.05554 -0.17645

PE.C18.1.16.0 0. 16224 0.36519 0.23054

PE.C18.1.16.1 0. 15487 0.42350 0.06496

PE.C18.1.18.0 0. 17857 0.20499 0.11338

PE.C18.1.18.1 0. 16484 0.35987 0.17578

PE.C18.1.18.2 0. 18026 0.07402 -0.1 1517

PE.C18.1.20.4 0. 17869 -0.08820 -0.23740

Table 4. AUC for each isoform and the top 3 Principal components in

ROC curve

ROC Variable AUC

PC1 1.000

PC2 0.643

PC3 0.500

GC.C18.1.16.0 0.952

GC.C18.1.20.0 0.810

GC.C18.1.22.0 0.929

GC.C18.1.24.0 1.000

PC.C32.0 1.000

PC.C32.1 1.000

PC.C34.1 1.000

PC.C34.2 1.000

PC.C36.2 1.000

PC.C36.4 1.000

PC.C38.4 0.976

SM.C18.0.20.0 1.000

SM.C18.1.16.0 1.000

SM.C18.1.16.1 0.905

SM.C18.1.18.0 1.000

SM.C18.1.18.1 0.929

SM.C18.1.22.0 1.000

SM.C18.1.24.0 1.000

SM.C18.1.24.1 0.905

PS.C18.0.18.2 1.000

PS.C18.0.20.4 0.964

PS.C18.1.18.0 1.000

PS.C18.1.18.1 1.000

PE.C16.0.22.4 0.964

PE.C18.0.18.2 1.000

PE.C18.0.20.4 1.000

PE.C18.1.16.0 1.000

PE.C18.1.16.1 0.976

PE.C18.1.18.0 1.000

PE.C18.1.18.1 1.000

PE.C18.1.18.2 1.000

PE.C18.1.20.4 0.988

Table 5. P-value of top 3 PC, individual isoform and lipid group summation value in MHC, PC, SM, PS and PE after correction of multiple comparisons (Benjamini & Hochberg)

P-value Lipids after summation P-

ROC Variable

correction value after correction

PC1 0.003

PC2 0.471

PC3 1.000

MHC 0.025

GC.C18.1.16.0 0.018

GC.C18.1.20.0 0.1 14

GC.C18.1.22.0 0.024

GC.C18.1.24.0 0.01 1

PC 0.003

PC.C32.0 0.01 1

PC.C32.1 0.010

PC.C34.1 0.01 1

PC.C34.2 0.010

PC.C36.2 0.01 1

PC.C36.4 0.010

PC.C38.4 0.011

SM 0.003

SM.C18.0.20.0 0.010

SM.C18.1.16.0 0.010

SM.C18.1.16.1 0.027

SM.C18.1.18.0 0.0 1

SM.C18.1.18.1 0.018

SM.C18.1.22.0 0.01 1

SM.C18.1.24.0 0.01 1

SM.C18.1.24.1 0.027

PS 0.003

PS.C18.0.18.2 0.01 1

PS.C18.0.20.4 0.016

PS.C18.1.18.0 0.01 1

PS.C18.1.18.1 0.010

PE 0.003

PE.C16.0.22.4 0.016

PE.C18.0.18.2 0.010

PE.C18.0.20.4 0.01 1

PE.C18.1.16.0 0.01 1

PE.C18.1.16.1 0.014

PE.C18.1.18.0 0.011

PE.C18.1.18.1 0.01 1

PE.C18.1.18.2 0.010

PE.C18.1.20.4 0.014 Results

[00117] Patient population— 1421 consecutive patients were recruited. Thirteen patients were excluded because of detected variations in the GLA gene (data not shown). The patients' characteristics are further described in Table 1. Urinary Gb3 is elevated in patients with heart disease status was statistically significant in the model (numerator degrees of freedom=2, denominator degrees of freedom =1642, F=47095.6, p<0.0001). Specifically, there was a significant difference in Gb3 between the healthy controls and the cardiac patients (log (base 10) difference=0.09, 95% confidence intervals=0.05 and 0.13, and p<0.0001). Age, gender, ethnicity, and race (with and without their interactions with disease status), risk factors and medications (Table 2) were not statistically significant when included in the model. Furthermore, the estimates for disease status did not show a meaningful change with and without these variables being included in the model, indicating they are not confounders in this analysis. Urinary Gb3 levels in healthy controls were independent of age. [00118] Levels of other lipids are abnormal in the urine of patients with heart disease— In order to investigate whether other lipids besides Gb3 are elevated in the urine of patients with heart disease, the applicants performed lipid profiling on randomly collected whole urine and plasma samples on a total of 23 representative samples of urine belonging to patients with heart disease and elevated (478-886 ng/ml; n=6) or low (55-72 ng/ml; n=5) Gb3, patients with Fabry disease (351-9344 ng/ml; n=7) and healthy controls (57-105 ng/ml; n=5). The upper limit of normal (99th percentile) urinary Gb3 was 200 ng/ml. Principal component analysis (PCA) showed the isoforms of MHC PC, SM, PS and PE produced the separation shown using 90% contours between Fabry disease and heart disease with high urinary Gb3 (FIG. 25). These isoforms were pooled together for PCA analysis and the 3D contour plots are shown in FIG. 25. The first Eigen vector has all its coefficients non- negative and accounts for 90.6% of the variation. The coefficients of the top 3 principal components are listed in Table 3. ROC was assessed by AUC on the top 3 principal components and each lipid isoform is shown (Table 4). The first principal component has an AUC of 1 - a perfect separation between the Fabry and high Gb3 groups. Some isoforms also had an AUC of 1 (Table 4). However, due to the limited sample size, the applicants cannot assess whether the first principal component is better than other individual isoforms in terms of discriminating between urine from Fabry patients and that of patients with heart disease and elevated Gb3. Multiple comparisons for lipid group summation values and individual iso forms confirmed that urinary MHC, SM, and PE were significantly different between patients with Fabry disease and those with heart disease and elevated urinary Gb3 levels (Table 5, FIGs. 10 - 18, FIGs. 20 - 24). No significant differences in lipid profiling were found in plasma from these two patient groups (data not shown).

[00119] Confirmation of sphingolipid abnormalities in heart disease patients— In order to verify our initial lipid profiling findings described above the applicants studied urinary MHC, SM and lactosylceramide (LC) in 8 heart disease patients with elevated urinary Gb3 randomly selected to represent the full spectrum of Gb3 values, and 6 randomly selected patients from each of the following: heart disease with normal urine Gb3, and patients with overt Fabry disease, the applicants confirmed that MHC levels separated Fabry patients from the heart disease high Gb3 group (FIG. 27). Importantly, expression of lipid levels per unit of volume or per mg creatinine gave consistent result. Urinary Gb3 levels are independent of the size of the membrane pellet In order to determine whether the variation of urinary Gb3 and other lipids in patients with heart disease reflects the amount of sloughed cellular debris rather than membrane lipid composition, the applicants measured the size of the pellet in previously frozen urine samples of 22 patients with heart disease and 6 patients with Fabry disease. Urine Gb3 in those samples ranged from undetectable to 478 ng/ml. There was no significant correlation (p=0.15) between the size of the pellet and the Gb3 concentration in urine of patients with heart disease.

[00120] Lipid abnormalities in failing ischemic heart— In order to determine whether lipid abnormalities seen in urine reflect an abnormal lipid profile in the heart itself, the applicants performed lipid profiling on samples of the left ventricle of 20 patients with end- stage ischemic heart failure (Ambardekar et al., 2011) Gb3 levels were significantly decreased in these hearts compared to 20 controls ( FIG. 26A) while sphingomyelin levels were significantly higher compared to controls (FIG. 26B).

[00121] Gb3 levels are significantly associated with the risk of near-term death—

Of the 1408 patients with cardiovascular disease, 75 died during the follow-up period (Table 2). The average follow-up time and time to death was 17 and 10 months, respectively. An unadjusted analysis was conducted using Kaplan-Meier estimates for rate of death by Gb3 status. Gb3 was categorized into four groups based on the quartiles from the observed data (78, 100, and 138). The differences in rates of death were not significant (p=0.0581 by log- rank test). In order to adjust the analysis for demographic, clinical, and medication variables listed in Table 2, a Cox proportional hazard analysis was used. In this analysis there was a significant association between urinary Gb3 levels and risk of death (HR=1.59 for increase in Gb3 of 200, 95% confidence intervals=1.36 and 1.87, and PO.0001). The rate of death increases by 60%> for every increase of 200 units of urinary Gb3. Based on this survival analysis, the risk estimates for death over time are presented in FIG. 9 using urine Gb3 values of 100, 200, 300, 500, and 1000 ng/ml.

[00122] The Cox proportional hazard model determined a statistically significant association between Gb3 and mortality for patients with heart disease. The results of this analysis will be used to plan and power future studies. These longitudinal studies will be conducted to assess the predictive capability of GB3 for heart disease related outcomes. Commonly used statistical techniques (logistic regression, linear discriminant analysis, etc.) will be used to develop classifier algorithms. The results (accuracy, sensitivity, and specificity) will be validated using internal methods such as leave-one-out cross validation. Furthermore, the results will be validated in an independent cohort.

Example 2 - Quantitative Targeted Lipidomics in Urine: Phosphatidylserine and other Phospholipids by UPLC-MS/MS

Methods

[00123] Sample preparation: 2 mL of whole urine, liquid-liquid extraction with 10 mLMTBE, 3 mL methanol and 2.5 mL water. Mix and collect top layer. Dry and reconstitute in 400 \iL of IPA/ACN/water (2: 1 : 1)

[00124] Chromatography: Separation with a Waters CSH-C 18 column 2.1X100 mm, 1.7μιη and a guard column with the same stationary phase. The column oven heated at 60 °C. Mobile phase A :acetonitrile/ water 60/40 (v/v) Mobile phase B: isopropanol /acetonitrile 90/10 (v/v), both with 10 mM ammonium formate and 0.05% ammonium hydroxide. Injection volume 20 μί.

[00125] Mass Spectrometry: Desolvation gas 350 L/h, cone gas OL/h, desolvation temperature 600 °C, additional mass spectrometer conditions in Table 6, including ESI as positive or negative. [00126] Detection of phosphatidylserine occurs with ESI in negative ion mode using a UPLC-Xevo TQMS. Exploratory analysis neutral loss scan of 88 to detect PS in human urine.; Spectrum of neutral loss scan of 88 in FIG. 28; Phosphatidyl inositol in negative mode, exploratory analysis by parent ion scan of 241 and 223. Detected MRMs for phosphatidylserine and phosphatidylinositol and semi quantitative differences between pooled urine from cardiac patients with high Gb3 compared to pooled urine from cardiac patients with normal Gb3 in table 7. Detected MRMs for phosphatidyl choline parent ion scan of 184, selected MRMs in table 8 and phosphatidylethanolamine neutral loss scan of 141 , selected MRMs in table 8.

[00127] Samples: Normal pooled urine; Cardiac pool 1 = pooled urine of cardiac patients with elevated globotriaosylceramide; Cardiac Pool 2= pooled urine of cardiac patients with normal globotriaosylceramide; Cardiac patients with any type of heart disease were enrolled for a screening study for Fabry disease; these cardiac patients do not have Fabry, but have increased levels of globotriaosylceramide usually associated with this disease.

Table 6. Mass Spectrometry Conditions

Capillary Collision

V k¥ V

Phosphatidylserine - 50 2.8 25

Phospatidy nos!to! - 60 2.8 40

Phosphatidylcholine + 80 35

Phosphaiidylethanoiamsne 4- 35 3.2 20

Table 7. MRM of PS and PI

Phosphatidylsenne in Pooled Human Urine

Phosphatidylinositol in Pooied Human Urine

close to detection ^T t not present Table 8. MRM for PC and PE

Phosphatidylcholine MRM in Phosphatidy!eihanolamine pooled human urine MRM in pooled human urine

4 :733.00 > 184.00 1 : 716.50 > 575,50

5 : 734,00 > 184.00 2 : 718.50 > 577.50

10 ^■ 747.50 > 184.00 3 : 720.50 > 579 50

12 : 748.50 > 184.00 6 : 740.50 > 600.50

13 ^• 759.50 > 184,00 7 : 744.50 > 603.50

15 ^' 761.50 > 184.00 8 : 745.50 > 604.50

18 . 762.50 > 184.00 1 1 747.50 > 606.50

17 . 763.50 > 184.00 19 764.50 > 621 50

18 ^• 764.50 > 184.00

20 768.50 > 625.50

23 ^• 783.50 > 184.00

21 769.50 > 626.50

24 . 787.50 > 184.00

22 770.50 > 627.50

26 : 789.50 > 184.00

26 27

^• 790.50 > 184,00 792.50 > 651.50

31 ^■ 866.80 > 184.00 28 793.50 > 652.50

32 . 882.50 184.00 29 794.50 > 653,50

30 795.50 > 654.50

[00128] Results— Liquid/Liquid extraction with MTBE was found to be very effective for each phospholipids class tested.. Chromatography with C18 and CI 8 CSH was tested; C18 CSH offers more flexibility and hopefully more chances to fine tune separation. Two different types of mobile phases were tested; initially the aim was to optimize sensitivity with a water/ acetonitrile (A) and methanol/isopropanol and acetonitrile (B) mixtures , both containing 0.05% ammonium hydroxide and lmM ammonium formate.

[00129] Superior separation and peak shape was achieved with a high ionic strength, mobile phase : mobile phase A consists of acetonitrile/ water 60/40 (v/v) and mobile phase B is isopropanol /acetonitrile 90/10 (v/v), both with 10 mM ammonium formate and 0.05% ammonium hydroxide.

[00130] Data on phosphatidylserine show that a comprehensive quantitative method for human urinary phospholipids is achievable.

Example 3 - Sphingomyelin, Glucosylceramide, and Lactosylceramide urine PC A analysis

[00131] Methods— PCA analysis was performed on data collected from urine of 20 patients by two types of measurement approaches (amount per creatinine vs. amount per volume) on Sphingomyelins, Glucosylceramides, Lactosylceramide and their isoforms. The 20 patients are divided into three groups: cardiac patients low GB3, cardiac patients high Gb3 and Fabry patients.

PCA analysis objectives

1. To decompose multivariate data into low dimensional principle components

2. To visualize low Gb3 group, high Gb3 group and fabry group in 3D space that having the top 3 Principle components as its coordinates. Low Gb3 group and high Gb3 group are all cardiac patients and are compared to the Fabry patients.

[00132] PCA analysis is done on the correlation matrixes of all lipid isoforms pooled together and on each lipid by measurement combo.

[00133] FIGs. 31-32 show the 3D scatter plots with axes being the top 3 principle components. Low GB3 group light blue color dots with blue 90%> coverage contour; high GB3 group red dots with green 90% coverage contour; fabry group green color dots with pink 90%) coverage contour.

Results [00134] PCA on Glucosylceramide isoforms in urine— PCA analysis was done on all the Glucosylceramide isoforms in urine pooling together. FIG. 29 shows the 3D scatter plot. Low GB3 group light blue color dots with blue 90%> coverage contour; high GB3 group red dots with green 90%> coverage contour; fabry group green color dots with pink 90%> coverage contour. The 90% fabry pink contour with green dots has no overlap with neither high GB3 green contour nor low GB3 blue contour.

[00135] The eigenvectors and the percentage of variation explained of the principle components are provided in Table 1. The first component explains more than 90% of the variation of the normalized log transformed data and its coefficients on each variable are all positive. The second component explains 8% of the variation and has its coefficients all negative except for Glucosylceramide 24 : 1.

Table 9. Top 3 principle components of all Glucosylceramide isoforms in urine

Num

.0Q01* .08Sf ,0801* .0801*

C 8:8 Gfec»s¾ C¾!¾R¾Se 842286 ^ ΛΑ:>Μ -0.45832 D .22340 45.78020 -5.2 0 0

C 18:8 Gl cos SCer3R¾S8 8 2686 4 81606 D ; 2i^;¾2 0.58668 0.53003 4s.22662

C2% ®im$≠ %n 8.42451 α θίϊ ί ΐίϊ -8.45684 -0.48366 0.2266;; 0,58038

CZS.O GfccosylCersrnKfe 8.42410 ·ί^;.02477^' 8.20424 -0.6142? 0 02:22; 4= 578 IB

S ucssy Csj¾r ¾de 2 8 6.41808 -6.7 80'; 0.68890 0 70404 .0,.2¾270 0.45886 e u¾SSViC«ramsd§ 2 :1 6.32813 6.63521 0 0O202 : 4077

[00136] PCA on Glucosylceramide isoforms in Creatinine— PCA analysis was done on all the Glucosylceramide isoforms in creatinine pooling together. FIG. 30 shows the 3D scatter plot. Low GB3 group light blue color dots with blue 90%> coverage contour; high GB3 group red dots with green 90%> coverage contour; fabry group green color dots with pink 90% coverage contour.. The 90% fabry pink (green dots) has no overlap with either the low Gb3 blue contour or the high Gb3 green contour (red dots).

[00137] Eigenvectors and the percentage of variation explained are provided in Table 2. The first component explains 83% of the variation and its coefficients on each variable are all positive. The second component explains 14% of the variation and its coefficients are all negative or close to zero except for Glucosylceramide 24: 1. The eigenvectors of Glucosylceramide in urine is similar to creatinine.

Table 10. Top 3 principle components of all Glucosylceramide isoforms in creatinine gress* ¾e m Cum ercem

4.3388 82.730 202.911 11.183 «,οοοτ 0.8161 13,602 J 96382 13,511 *.08or 0.108? 1-828 mm 34.055 8.820 ^« 0001^*

1.232 §§.442 24.813 4.928 0.0001^*

0.8203 0.488 §8.640 12.6® 1JS8 6.001S" 0.6033 o.oeo 106,600 0 000

Prfcrt Prtn2 Ptfttt n pt mm

C1¾ SiucasylCers 2 9.4300? 2?.03 ^'33^r 3133131 -0.74738 .2 60

C18:0SI »s«IC¾amii «2 0,43173 3^;.33333 -0.13313 030427 0.58808 35.23330

C20:0«?ucosy1C¾rsml<St2 0,43001 3 333-:i: 3 S883 -0,41349 3 33213 0.01344

C22.-0Olucos^Csrar^<J«2 0.43321 : : : : : ^¾ : 8.33S73 •0 32?20 6 353 3 -0 3 0

C24;0OlucosylC^n&fe 0 42649 -0.21330 0 3096? 323353 3 12323 6.44031

s3!«C S5ⁱICe?ams< tS4:1 2 3233 * 034333 0.03333 0.13343 01133

* * *

[00138] All of the methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the compositions and methods of this invention have been described in terms of preferred embodiments, it will be apparent to those of skill in the art that variations may be applied to the methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit and scope of the invention. More specifically, it will be apparent that certain agents which are both chemically and physiologically related may be substituted for the agents described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the invention as defined by the appended claims.

REFERENCES

The following references, to the extent that they provide exemplary procedural or other details supplementary to those set forth herein, are specifically incorporated herein by reference.

Ambardekar, et al, Circ Heart Fail. 4:425-432, 2011.

Auray-Blais, et al, J Inherit Metab Dis. 30: 106, 2007.

Bligh & Dyer, Can J Biochem Physiol. 37:91 1-7, 1959.

Duffey, et al, Clin Chem. 56: 1854-61, 2010.

Folch, et al, J Biol Chem. 226:497-509, 1957.

Fuller, et al, Clin Chem. 51 :688-94, 2005.

Hein et al, J Lipid Res. 49: 1725-34, 2008.

Lowry, et al, J Biol Chem. 193:265-275, 1951.

Meikle, et al, Biochem J. 411 :71-8, 2008.

U.S. Patent No. 8,093,286

Claims

1. A method for evaluating a subject with a cardiac disease or at risk for a cardiac disease comprising:

(a) measuring the level of one or more glycosphmgolipids in a urine sample;

(b) comparing the level of one or more glycosphmgolipids relative to a reference level for the one or more glycosphmgolipids;

(c) calculating a mortality risk factor using an algorithm based one or more comparisons between the measured levels and the reference levels.

2. The method of claim 1, wherein at least one glycosphingolipid is a globotriaosylceramide (GB3).

3. The method of claims 1 or 2, measuring the glycosphingolipid level comprises extracting, separating, and/or detecting the glycosphmgolipids.

4. The method of any of claims 1-3, wherein measuring the level of one or more glycosphmgolipids comprises using liquid chromatography (LC) or mass spectrometry (MS).

5. The method of any of claims 1-3, wherein measuring the level of one or more glycosphmgolipids comprises using electrospray ionization mass spectrometry (ESI-MS), matrix-assisted laser desorption/ionization (MALDI-MS) or atmospheric pressure chemical ionization (APCI-MS).

6. The method of any of claims 1-3, wherein measuring the level of one or more glycosphmgolipids comprises using nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry.

7. The method of any of claims 1-3, wherein measuring the level of one or more glycosphmgolipids comprises using one or more antibodies that specifically recognize the one or more glycosphmgolipids.

8. The method of claim 7, wherein the antibodies are polyclonal or monoclonal.

9. The method of claim 7, wherein the antibodies are detected by a functional group conjugated to a primary antibody or by a secondary antibody or tertiary antibody to which detectable functional groups are conjugated.

10. The method of claim 9, wherein the function group is a peptide, an enzyme, a fluorescent label, a colorimetric label, or a radioisotope.

11. The method of any of claims 1-10, further comprising calculating a mortality risk factor using an algorithm based two, three, four, five or more comparisons between the measured levels and the reference levels.

12. The method of any of claims 1-10, further comprising reporting the mortality risk factor.

13. The method of any of claims 1-12, wherein the mortality risk factor is calculated for a three year time window.

14. The method of any of claims 1-13, wherein the reference level represents the level of one or more glycosphingolipids in a biological sample from one or more healthy subjects.

15. The method any of claims 1-14, wherein one or more glycosphingolipids comprise globotriaosylceramide, globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide, glucosylceramide or combinations thereof.

16. The method any of claims 1-15, wherein the cardiac disease is hypertrophic cardiomyopathy, rhythm and conduction defects, coronary artery disease, arrhythmia, conduction blocks or valvular disease.

17. The method of any of claims 1-16, further comprising treating the subject with a therapeutic agent knowing the calculated mortality risk factor.

18. A method of treating a cardiac disease, a cardiac condition or for mitigating a risk factor for a cardiac condition in a human subject comprising the steps of: identifying a human subject in need for treatment against the cardiac disease, the cardiac condition or for mitigation of the risk factor for the cardiac condition; and administering a composition that belongs, but is not limited, to a class of beta blockers, anti-hypertensives, cardiotonics, anti-thrombotics, vasodialators, hormone antagonists, inotropes, diuretics, endothelin antagonists, calcium channel blockers, phosphodiesterase inhibitors, ACE inhibitors, agiontensin type 2 antagonists, cytokine blockers and HDAC inhibitors and one or more optional pharmaceutically acceptable excipients in a concentration sufficient to treat the cardiac disease, the cardiac condition or for the mitigation of the risk factor for the cardiac condition.

19. A method for screening for the presence of cardiac disease or a cardiac condition in a subject comprising:

(a) determining a level of glucosylceramide in a urine sample from the subject; and

(b) identifying the subject as having an increased risk for cardiac disease or a cardiac condition by determining the level of glucosylceramide relative to a reference level.

20. The method of claim 19, wherein the level of glucosylceramide is determined by a protocol involving extraction or separation or detection.

21. The method of claim 19, further comprising determining a level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in a urine sample from the subject.

22. The method of claim 21, further comprising identifying the subject as having an increased risk for cardiac disease or a cardiac condition by determining the level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide or relative to a reference level.

23. The method of claim 19, wherein the separation or detection of at least one glycosphingolipid is through liquid chromatography (LC) or mass spectrometry (MS).

24. The method of claim 19, wherein the detection step comprises electrospray ionization mass spectrometry (ESI-MS), matrix-assisted laser desorption/ionization (MALDI- MS) or atmospheric pressure chemical ionization (APCI-MS).

25. The method of claim 19, wherein the detection step comprises nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry.

26. The method of claim 19, wherein the cardiac disease is comprises hypertrophic cardiomyopathy, rhythm and conduction defects, coronary artery disease, arrhythmia, conduction blocks and valvular disease.

27. A method of treating a subject determined to have an increased risk of death from a cardiac disease comprising administering a cardiac therapeutic agent, wherein the subject has been tested for a level of glucosylceramide in a urine sample from the subject.

28. A tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: a) receiving information corresponding to a level of one or more glycosphingo lipids in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease; b) comparing the level of one or more glycosphingolipids relative to a reference level for the one or more glycosphingolipids; and c) calculating a mortality risk factor using an algorithm based one or more comparisons between the received levels and the reference levels.

29. The tangible computer-readable medium of claim 28, further comprising receiving information corresponding to a reference level of one or more glycosphingolipids in a urine sample from a healthy subject.

30. The tangible computer-readable medium of claim 28, wherein the reference level is stored in said tangible computer-readable medium.

31. The tangible computer-readable medium of claim 28, wherein the receiving information comprises receiving from a tangible data storage device information corresponding to a level of one or more glycosphingolipids in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease.

32. The tangible computer-readable medium of claim 28, further comprising computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising: sending information corresponding to the relative level of one or more glycosphingolipid to a tangible data storage device.

33. The tangible computer-readable medium of any one of claims 28-32, wherein the receiving information further comprises receiving information corresponding to a level of albumin, cystatin C, or creatinine in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease.

34. The tangible computer-readable medium of any one of claims 28-32, wherein the receiving information further comprises receiving information corresponding to a level of globotriaosylceramide, globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide, glucosylceramide or globotriaosylceramide (GB3) in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease.

35. A tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: a) receiving information corresponding to a level of glucosylceramide in a urine sample from a subject; b) comparing the level of glucosylceramide relative to a reference level for glucosylceramide; and c) calculating a risk factor for a cardiac disease or cardiac condition using an algorithm based one or more comparisons between the received levels and the reference levels.

36. A method for evaluating a subject with a cardiac disease or at risk for a cardiac disease comprising:

(a) measuring the level of one or more glycolipids in a urine sample;

(b) comparing the level of one or more glycolipids relative to a reference level for the one or more glycolipids;

(c) calculating a mortality risk factor using an algorithm based one or more comparisons between the measured levels and the reference levels.

37. The method of claim 36, wherein at least one glycolipid is a globotriaosylceramide (GB3).

38. The method of claims 36 or 37, measuring the glycolipid level comprises extracting, separating, and/or detecting the glycolipids.

39. The method of any of claims 36-38, wherein measuring the level of one or more glycolipids comprises using liquid chromatography (LC) or mass spectrometry (MS).

40. The method of any of claims 36-38, wherein measuring the level of one or more glycolipids comprises using electrospray ionization mass spectrometry (ESI-MS), matrix- assisted laser desorption/ionization (MALDI-MS) or atmospheric pressure chemical ionization (APCI-MS).

41. The method of any of claims 36-38, wherein measuring the level of one or more glycolipids comprises using nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry.

42. The method of any of claims 36-38, wherein measuring the level of one or more glycolipids comprises using one or more antibodies that specifically recognize the one or more glycolipids.

43. The method of claim 42, wherein the antibodies are polyclonal or monoclonal.

44. The method of claim 42, wherein the antibodies are detected by a functional group conjugated to a primary antibody or by a secondary antibody or tertiary antibody to which detectable functional groups are conjugated.

45. The method of claim 44, wherein the function group is a peptide, an enzyme, a fluorescent label, a colorimetric label, or a radioisotope.

46. The method of any of claims 36-45, further comprising calculating a mortality risk factor using an algorithm based two, three, four, five or more comparisons between the measured levels and the reference levels.

47. The method of any of claims 36-45, further comprising reporting the mortality risk factor.

48. The method of any of claims 36-47, wherein the mortality risk factor is calculated for a three year time window.

49. The method of any of claims 36-48, wherein the reference level represents the level of one or more glycolipids in a biological sample from one or more healthy subjects.

50. The method any of claims 36-49, wherein one or more glycolipids comprise globotriaosylceramide, globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide, glucosylceramide or combinations thereof.

51. The method any of claims 36-50, wherein the cardiac disease is hypertrophic cardiomyopathy, rhythm and conduction defects, coronary artery disease, arrhythmia, conduction blocks or valvular disease.

52. The method of any of claims 36-51, further comprising treating the subject with a therapeutic agent knowing the calculated mortality risk factor.

53. A method of treating a cardiac disease, a cardiac condition or for mitigating a risk factor for a cardiac condition in a human subject comprising the steps of: identifying a human subject in need for treatment against the cardiac disease, the cardiac condition or for mitigation of the risk factor for the cardiac condition; and administering a composition that belongs, but is not limited, to a class of beta blockers, anti-hypertensives, cardiotonics, anti-thrombotics, vasodialators, hormone antagonists, inotropes, diuretics, endothelin antagonists, calcium channel blockers, phosphodiesterase inhibitors, ACE inhibitors, agiontensin type 2 antagonists, cytokine blockers and HDAC inhibitors and one or more optional pharmaceutically acceptable excipients in a concentration sufficient to treat the cardiac disease, the cardiac condition or for the mitigation of the risk factor for the cardiac condition.

54. A method for screening for the presence of cardiac disease or a cardiac condition in a subject comprising:

(a) determining a level of glucosylceramide in a urine sample from the subject; and

(b) identifying the subject as having an increased risk for cardiac disease or a cardiac condition by determining the level of glucosylceramide relative to a reference level.

55. The method of claim 54, wherein the level of glucosylceramide is determined by a protocol involving extraction or separation or detection.

56. The method of claim 54, further comprising determining a level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide in a urine sample from the subject.

57. The method of claim 56, further comprising identifying the subject as having an increased risk for cardiac disease or a cardiac condition by determining the level of globotriaosylceramide (GB3), globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide or glucosylceramide or relative to a reference level.

58. The method of claim 54, wherein the separation or detection of at least one glycolipid is through liquid chromatography (LC) or mass spectrometry (MS).

59. The method of claim 54, wherein the detection step comprises electrospray ionization mass spectrometry (ESI-MS), matrix-assisted laser desorption/ionization (MALDI- MS) or atmospheric pressure chemical ionization (APCI-MS).

60. The method of claim 54, wherein the detection step comprises nuclear magnetic resonance spectroscopy, fluorescence spectroscopy or dual polarization interferometry.

61. The method of claim 54, wherein the cardiac disease comprises hypertrophic cardiomyopathy, rhythm and conduction defects, coronary artery disease, arrhythmia, conduction blocks and valvular disease.

62. A method of treating a subject determined to have an increased risk of death from a cardiac disease comprising administering a cardiac therapeutic agent, wherein the subject has been tested for a level of glucosylceramide in a urine sample from the subject.

63. A tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: a) receiving information corresponding to a level of one or more glycolipids in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease; b) comparing the level of one or more glycolipids relative to a reference level for the one or more glycolipids; and c) calculating a mortality risk factor using an algorithm based one or more comparisons between the received levels and the reference levels.

64. The tangible computer-readable medium of claim 63, further comprising receiving information corresponding to a reference level of one or more glycolipids in a urine sample from a healthy subject.

65. The tangible computer-readable medium of claim 63, wherein the reference level is stored in said tangible computer-readable medium.

66. The tangible computer-readable medium of claim 63, wherein the receiving information comprises receiving from a tangible data storage device information corresponding to a level of one or more glycolipids in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease.

67. The tangible computer-readable medium of claim 63, further comprising computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising: sending information corresponding to the relative level of one or more glycolipids to a tangible data storage device.

68. The tangible computer-readable medium of any one of claims 63-67, wherein the receiving information further comprises receiving information corresponding to a level of albumin, cystatin C, or creatinine in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease.

69. The tangible computer-readable medium of any one of claims 63-67, wherein the receiving information further comprises receiving information corresponding to a level of globotriaosylceramide, globotriaosylspingosine, lactosyl ceramide, galactosyl ceramide, glucosylceramide or globotriaosylceramide (GB3) in a urine sample from a subject with a cardiac disease or at risk for a cardiac disease.

70. A tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: a) receiving information corresponding to a level of glucosylceramide in a urine sample from a subject; b) comparing the level of glucosylceramide relative to a reference level for glucosylceramide; and c) calculating a risk factor for a cardiac disease or cardiac condition using an algorithm based one or more comparisons between the received levels and the reference levels.

71. A method of treating a subject determined to have an increased risk of death from a cardiac disease comprising administering migalastat HC1, wherein the subject has been tested for a level of glucosylceramide in a urine sample from the subject.

72. The method of claim 71, wherein glucosylceramide is globotriaosylceramide

(GB3).