Method for predicting mortality from liver disease using lipoprotein LP-Z

Abstract

This article describes a method for determining mortality in patients with alcoholic hepatitis by NMR spectroscopy in biological samples, and more specifically, a method for determining a Z-index score based on the lipoprotein component LP-Z in plasma and serum.

Description

[0001] Related Applications

[0002] This application claims the benefit of priority to U.S. Provisional Patent Application Serial No. 62 / 757,505, filed on November 8, 2018, the contents of which are incorporated herein by reference as if fully set forth herein. Technical Field

[0003] Described herein are methods and systems for determining components in plasma and serum, and more particularly for determining lipoprotein components in plasma and serum. Background Art

[0004] In the United States, alcoholic hepatitis (AH) is a common reason for hospital admission for patients with liver disease. Among the spectrum of alcoholic liver disease, AH causes the most acute manifestations, with a mortality rate of 5-10% in all patients and as high as 30-50% in severe forms. Unlike other forms of liver failure, AH manifestations are characterized by severe coagulation defects (coagulopathy) and accumulation of bile (cholestasis), which can occur without significant hepatocyte loss or advanced fibrosis. The mechanisms of this profound hepatocellular dysfunction in severe AH remain poorly understood. Conventional AH treatment is limited to abstinence from alcohol, nutritional support, and corticosteroids in selected patients for potential short-term benefits. Liver transplantation may be used for selected AH patients. Disease risk stratification is a key challenge in the clinical management of AH, and it remains difficult to predict the outcome of patients with liver failure and select appropriate patient candidates for liver transplantation.

[0005] Several prediction strategies for AH have been studied, including Maddrey discriminant function (DF), Glasgow alcoholic hepatitis score (GAHS), age, serum bilirubin, INR and serum creatinine (ABIC) score and Lillie model. However, these scores cannot reliably predict mortality and guide clinical decision-making about liver transplantation. Another scoring system for assessing the severity of chronic liver disease is the model for end-stage liver disease (MELD). MELD is a score calculated by the international normalized ratio (INR) of serum creatinine, total bilirubin, prothrombin time and sodium concentration. MELD is usually a good predictor of 90-day mortality in cirrhotic patients caused by various forms of chronic liver disease, and is commonly used to select liver transplant patients and to grade patients on the liver transplant waiting list.

[0006] Despite having a high MELD score, a significant proportion of AH patients recover with alcohol abstinence and supportive care, unlike patients with decompensated cirrhosis where spontaneous recovery rarely occurs. A reliable prediction method could help identify AH patients who would be candidates for organ transplantation.

[0007] One of the essential functions of the liver is to regulate lipid and lipoprotein metabolism. The secretion of very low density lipoprotein particles (VLDL), a lipoprotein rich in triglycerides, is one way that hepatocytes can export triglycerides that have accumulated within the cell. VLDL is metabolized to low density lipoprotein (LDL), a particle rich in cholesterol esters. The conversion of circulating VLDL to LDL depends on a series of enzymes produced by the liver.

[0008] Recent data suggest that nuclear magnetic resonance (NMR) spectroscopy can be used to identify and quantify LDL and abnormal lipoproteins, including LP-X and LP-Z. By accurately determining the presence and amount of lipoproteins in a biological sample, and correlating lipoprotein levels with patient outcomes, improved prognostic methods can be achieved, ultimately improving patient care. Therefore, there is a need for methods and systems for assays that accurately determine lipoproteins in plasma or serum samples and predict patient mortality. This article describes new methods and systems for accurately detecting and quantifying the amount of LP-Z in a biological sample using NMR spectroscopy, and correlating the amount of LP-Z with patient mortality. Summary of the invention

[0009] Described herein are methods and systems for accurately determining the presence and amount of LP-Z in a biological sample using NMR spectroscopy and generating a Z-index score to predict patient mortality. The present invention can be embodied in a variety of ways. In certain embodiments, the methods and systems include determining LP-Z in a subject or patient. In some embodiments, the methods can predict a patient's response to therapy or the patient's likelihood of death within 90 days.

[0010] In some embodiments, a method for predicting mortality in a subject with AH comprises the steps of obtaining an NMR spectrum of a plasma or serum sample obtained from the subject, and programmatically determining the presence of LP-Z and total apoB-containing lipoproteins in the sample based on the NMR spectrum of the sample. In some embodiments, the NMR spectrum of the sample may include normal lipoproteins and all subclasses of abnormal lipoproteins LP-X, LP-Y, and LP-Z. In certain embodiments, the method further comprises calculating a Z-index score. In some cases, a Z-index greater than 0.6 may be associated with mortality from alcoholic hepatitis within 90 days or less.

[0011] Still other embodiments relate to an NMR analyzer. The NMR analyzer may include an NMR spectrometer, a probe in communication with the spectrometer, and a controller in communication with the spectrometer, the controller being configured to obtain an NMR signal defining a single peak region of an NMR spectrum associated with LP-Z of a fluid sample in the probe and generate a patient report providing a LP-Z level. In some embodiments, the probe may be a flow probe.

[0012] The controller may include or communicate with at least one local or remote processor, wherein the at least one processor is configured to: (i) obtain a composite NMR spectrum of a fitted region of an in vitro plasma biological sample; and (ii) deconvolute the composite NMR spectrum using a defined deconvolution model to generate a LP-Z level. In certain embodiments, the deconvolution model includes at least one of a high-density lipoprotein (HDL) component, a low-density lipoprotein (LDL) component, a VLDL (very low density lipoprotein) / chylomicron component, LP-X and / or LP-Y and LP-Z.

[0013] A person of ordinary skill in the art will understand other features, advantages and details of the present invention when reading the drawings and the following detailed description of the preferred embodiments, and such descriptions are merely illustrative of the present invention. Features described with respect to one embodiment may be combined with other embodiments, although not specifically discussed therewith. That is, it should be noted that aspects of the present invention described with respect to one embodiment may be incorporated into different embodiments, even without being specifically described therewith. That is, all embodiments and / or features of any embodiment may be combined in any manner and / or combination. Therefore, the applicant reserves the right to change any originally submitted claims or to submit any new claims, including the right to be able to modify any originally submitted claims to be subordinate to and / or incorporated into any features of any other claims (although not originally claimed in this manner). The above and other aspects of the present invention are explained in detail in the specification set forth below. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present disclosure may be better understood with reference to the accompanying drawings, in which embodiments of the present invention are shown. However, the present invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the present disclosure will be thorough and complete and will fully convey the scope of the invention to those skilled in the art.

[0015] Figure 1 An exemplary NMR spectrum of human serum is shown.

[0016] Figure 2 Exemplary NMR spectra of VLDL, LDL or HDL subclasses are shown.

[0017] Figure 3 An exemplary plasma analysis using the LP-X deconvolution model including reference signals for LP-X and LP-Z is shown.

[0018] Figure 4 Exemplary LP-Z concentrations of healthy patients and patients with liver disease as determined by NMR analysis are shown.

[0019] Figure 5Example Kaplan Meier curve showing the Z-index to predict 90-day survival in severe alcoholic hepatitis.

[0020] Figure 6 Exemplary repeated measures of the Z-index are shown to predict 90-day survival in severe alcoholic hepatitis.

[0021] Figure 7 Shown is an exemplary lipoprotein profile in alcoholic hepatitis compared to healthy subjects.

[0022] Figure 8 The chemical structures of lipids and triglycerides are shown.

[0023] Fig. 9 is a schematic diagram showing lipoprotein metabolism in healthy subjects.

[0024] Fig.10 An exemplary lipoprotein profile of LP-X and LP-Z in alcoholic hepatitis is shown.

[0025] Fig.11 is a schematic diagram of a system for analyzing patient risk using a Z-index module and / or circuit according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In this application, the relationship between LP-Z as determined by NMR spectroscopy was studied on plasma samples from alcoholic hepatitis (AH) patients, and the mortality of AH patients was followed. A new method is described herein to accurately predict the mortality of AH patients based on the amount of LP-Z in biological samples using NMR spectroscopy. The present invention can be embodied in various ways.

[0027] In some embodiments, the methods and systems include determining LP-Z in a subject or patient. In some embodiments, the methods can predict a patient's response to therapy or the patient's likelihood of death within 90 days.

[0028] In some embodiments, a method for predicting mortality in a subject with AH comprises the steps of obtaining an NMR spectrum of a plasma or serum sample obtained from the subject, and programmatically determining the presence of LP-Z and apoB-containing lipoproteins in the sample based on the NMR spectrum of the sample, wherein the NMR spectrum of the sample includes LP-X and LP-Z. In some embodiments, the NMR spectrum of the sample also includes LP-Y. In certain embodiments, the method further comprises calculating a Z-index score. In some cases, a Z-index greater than 0.6 may be associated with AH mortality within 90 days or less.

[0029] Lipoprotein Z (LP-Z) is a low-density lipoprotein (LDL) sample particle. As LDL, LP-Z carries a copy of apolipoprotein B (apoB), has amphipathic lipids on its surface, and has hydrophobic lipids in the particle core. The species referred to herein as LP-Z has previously been described as "highly triglyceride-rich LDL" (Kostner GM et al., Biochem J. 1976; 157: 401-407). Lipoprotein X (LP-X) is an abnormal multilamellar vesicle particle rich in phospholipids and unesterified cholesterol, which can be quantitatively measured by nuclear magnetic resonance (NMR) spectroscopy. Conventional lipid groups (lipid panel) may not detect the presence of LP-X or LP-Z.

[0030] Terms and Definitions

[0031] The same numbers refer to the same elements throughout. In the accompanying drawings, the thickness of certain lines, layers, components, elements or features may be exaggerated for clarity. Unless otherwise specified, dashed lines illustrate optional features or operations.

[0032] The terms used herein are only used to describe the specific embodiment purpose, and are not intended to limit the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms "one", "a kind of" and "said" are also intended to include plural forms. It should also be understood that when used in this specification, the terms "comprising" and / or "including" indicate that there are stated features, integers, steps, operations, elements and / or components, but do not exclude the existence or increase of one or more other features, integers, steps, operations, elements, components and / or their groups. As used herein, the term "and / or" includes any and all combinations of one or more related listed items. As used herein, phrases such as "between X and Y" and "between about X and Y" should be interpreted as including X and Y. As used herein, phrases such as "between about X and Y" refer to "between about X and about V", and as used herein, phrases such as "about X to Y" refer to "about X to about Y".

[0033] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention belongs. It should be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having meanings consistent with their meanings in the context of this specification and the relevant art, and should not be interpreted in an idealized or overly formal sense unless explicitly defined herein. For the sake of brevity and / or clarity, well-known functions or structures may not be described in detail.

[0034] The term "programmed" means performed using operations directed by a computer program and / or software, a processor, or an ASIC. The term "electronic" and its derivatives refer to automatic or semi-automatic operations performed using devices having circuits and / or modules rather than via mental steps, and generally refer to operations performed in a programmed manner. The terms "automated" and "automated" mean that operations can be performed with minimal or no manual labor or input. The term "semi-automated" means that some input or activation by an operator is allowed, but calculations and signal acquisition and calculation of concentrations of one or more ionized components are performed electronically (usually programmatically) without the need for manual input. The term "approximately" refers to a specific value or number of + / - 10% (mean or average).

[0035] The term "biological sample" refers to an in vitro sample of blood, plasma, serum, CSF, saliva, lavage fluid, sputum, urine or tissue of a human or animal. Embodiments of the present invention may be particularly suitable for evaluating human plasma or serum biological samples. The plasma or serum sample may be fasting or non-fasting.

[0036] The term "patient" or "subject" is used broadly and refers to an individual who provides a biological sample for testing or analysis.

[0037] The term "clinical disease state" means a medical condition at risk, which may indicate that medical intervention, therapy, therapy adjustment or exclusion of a therapy (e.g., drug) and / or monitoring is appropriate. The identification of the possibility of a clinical disease state may allow a clinician to treat the condition accordingly, delay or inhibit the onset of the condition. Examples of clinical disease states include, but are not limited to, CHD, CVD, stroke, type 2 diabetes, prediabetes, dementia, Alzheimer's disease, cancer, arthritis, rheumatoid arthritis (RA), kidney disease, liver disease, lung disease, COPD (chronic obstructive pulmonary disease), peripheral vascular disease, congestive heart failure, organ transplant reactions and / or medical conditions associated with immunodeficiency, protein sorting, immune and receptor recognition, inflammation, pathogenicity, metastasis and other cellular processes in biological dysfunction.

[0038] Method for measuring LP-Z to determine the Z index

[0039] New methods (ie, assays) for diagnosing or detecting AH in a subject using NMR characterization of LP-Z in a biological sample are described herein. In some embodiments, the methods can predict mortality in AH patients. The methods can be embodied in a variety of ways.

[0040] NMR spectroscopy has been used to simultaneously measure the full spectrum of circulating lipoproteins, including very low density lipoprotein (VLDL), low density lipoprotein (LDL) and high density lipoprotein (HDL) particle subclasses from in vitro plasma or serum samples, as well as abnormal lipoprotein particles such as LP-X and LP-Z. See, U.S. Patent No. 4,933,844, U.S. Patent No. 6,617,167, U.S. Patent Application No. 16 / 188,435 filed on November 13, 2018, the contents of which are incorporated herein by reference as if fully described herein. In some embodiments, the sample may be blood, serum, plasma, cerebrospinal fluid, or urine.

[0041] Generally, to assess lipoproteins in plasma and / or serum samples, the amplitudes of multiple NMR spectra derived signals in the chemical shift region of the NMR spectra are derived by deconvolution of the composite methyl signal envelope to yield subclass concentrations. Figure 1 An exemplary NMR spectrum of human serum is shown with lipid methyl groups highlighted. Subclasses are represented by a number (typically more than 60) of discrete contributing subclass signals that are associated with NMR frequencies and lipoprotein diameters. NMR evaluation can decompose the measured plasma NMR signals to yield the concentrations of different lipoprotein subpopulations of VLDL, LDL, and HDL. These subpopulations can be further characterized as, for example, Figure 2 The specific size ranges within the VLDL, LDL or HDL subclasses shown in Figure 2 As shown in , the subclass signals are combined to produce the measured signal. The subclass signal amplitudes derived by deconvolution can provide the concentration of each subclass.

[0042] In the past, "advanced" lipoprotein test panels (such as the NMRLIPOPROFILE® lipoprotein test) available from LapCorp, Burlington, NC, typically included a total HDL particle (HDL-P) measurement that sums the concentrations of all HDL subclasses and a total LDL particle (LDL-P) measurement that sums the concentrations of all LDL subclasses. The LDL-P number represents the concentration of those corresponding particles expressed in concentration units such as nmol / L. The HDL-P number represents the concentration of those corresponding particles expressed in concentration units such as μmol / L.

[0043] Recently, NMR analysis using a refined deconvolution model has been used to determine the concentrations of LP-X and LP-Z in biological samples. Figure 3 Shown is an example of a good fit and small residual signal resulting from analysis of plasma from a patient with high bilirubin when using the LP-X deconvolution model including reference signals of LP-X, LP-Y, and LP-Z.

[0044] NMR spectroscopy can be used to identify and quantify LP-Z in patients in which LP-Z accumulates, such as patients with alcoholic hepatitis (AH). Figure 4 As shown in, recent testing of plasma samples from AH patients using an NMR-based method developed by LabCorp to quantify the distribution of circulating lipoproteins in biological samples showed that exemplary AH patients carry significantly elevated levels of the abnormal lipoprotein LP-Z. Specifically, the levels of LP-Z can be significantly higher in AH patients compared to healthy individuals (HC) or patients with other forms of chronic liver disease. In order to reliably use NMR for AH patient prognosis, the relationship of LP-Z determined by NMR to patient mortality must be understood.

[0045] The above AH test further determined that in AH patients, the levels of both LP-Z and total apoB-containing lipoproteins are inversely correlated with liver synthetic function, as measured by INR. Although the levels of LP-Z and total apoB-containing lipoproteins may not be robustly associated with the mortality of patients with AH, these two parameters can predict mortality mutually. LP-Z and total apoB-containing lipoproteins (VLDL, LDL and LP-Z) can be used to simultaneously predict mortality. LP-Z can be positively correlated with mortality, while total apoB-containing lipoproteins can be negatively correlated with mortality. The novel biomarker Z index described herein utilizes these associations with patient mortality. The Z index can be calculated by the following equation:

[0046]

[0047] The concentration unit of lipoprotein components is nmol / L.

[0048] The Z index represents the proportion of abnormal lipoprotein LP-Z in apoB-containing lipoproteins and reflects the degree of liver damage that leads to the disorder of circulating lipoproteins in AH. The Z index is highly predictive of short-term mortality within 90 days. Figure 5 As shown in the exemplary KaplanMeier curve of , the Z index can be robustly associated with 90-day mortality. For every 1% increase in the Z index, the risk of death increased by 5% (95% CI 1.02-1.08, p = 0.001). The threshold of the Z index was determined to be 0.6. When the Z index is less than 0.6, only about 5% of patients may die within 90 days of LP-Z identification (in Figure 5 In contrast, when the Z index is greater than 0.6, nearly 40% of patients can be expected to die within 90 days of LP-Z identification (in Figure 5 In the data shown in , 21 of the 53 test subjects died within 90 days).

[0049] The Z index may be a more reliable predictor than the MELD score, which is the current standard for predicting outcomes in patients with liver failure. As shown in Table 1, the Z index was significantly better than the MELD score in predicting 90-day mortality in patients with AH.

[0050] Table 1. Multivariable Cox Proportional Hazards Regression

[0051] method HR 95% CI P-value Z index (>0.6) 8.4 1.9-36.4 0.004 MELD 1.0 0.9-1.2 0.5

[0052] The Z-index may also be a more reliable predictor than other components for predicting AH outcomes, as shown in Table 2.

[0053] Table 2. Comparison of confidence levels for various strategies

[0054] Z Index ≤0.6 ＞0.6 P-value quantity 38 53 INR 2.0±0.5 1.9±0.4 0.4 Bilirubin 21.5±9.3 25.3±8.1 0.04 Creatinine 0.8±0.5 1.2±0.8 0.01

[0055] The Z index can be calculated using the concentrations of LP-Z and total apoB-containing lipoproteins measured by NMR and can be used to effectively risk stratify patients with severe AH. Effective risk stratification can be particularly useful in helping to distinguish patients at low risk of death from those at high risk of death within 90 days. Figure 6 As shown in, for example, the Z index can be used as a repeated measure to predict outcome. The Z index in those who survived decreased by day 14, while the Z index in those who died remained stable.

[0056] Although the disclosure herein discloses LP-Z and apoB-containing lipoproteins by NMR spectroscopy, those skilled in the art understand that the Z index is not unique to NMR spectroscopy. For example, the concentration of LP-Z can be estimated using agarose gel electrophoresis in conjunction with lipid staining using Sudan Black and Filipin. The concentration of ApoB can be measured by ELISA. Figure 7 The exemplary lipoprotein profile in AH was shown to be unique compared to exemplary healthy subjects (HC) in both Sudan Black and Filipin tests.

[0057] Figure 8 Lipoprotein structures are shown, as well as the chemical structures of phospholipids (PL), cholesterol esters (CE), and triglycerides (TG), as well as free cholesterol (FC). Fig. 9 The pathways of lipids in lipoprotein metabolism in healthy subjects are shown. Most individuals (i.e., "normal" healthy subjects) have very low or no levels of LP-X or LP-Z. In contrast, variable amounts of LP-Y are found in both healthy and diseased individuals. In subjects that exhibit the presence of LP-X or LP-Z (e.g., subjects with obstructive jaundice or AH), LP-Z levels may be elevated to varying degrees.

[0058] The methyl lipid signals from LP-X, LP-Y, and LP-Z each have a unique spectral shape and position in the NMR spectrum that is different from those of "normal" lipoprotein particles. A unique pattern of circulating lipoproteins may be present in AH, characterized by the accumulation of abnormal lipoproteins LP-X and LP-Z. Fig.10 An exemplary unique lipoprotein profile in AH patients is shown. As determined by NMR analysis, elevated LP-X and LP-Z concentrations can distinguish healthy patients from patients with liver disease. These lipoproteins can be effective biomarkers for risk stratification of severe alcoholic hepatitis. The assays described herein utilize these unique spectral line shapes to detect and quantify LP-X, LP-Y, and LP-Z in serum or plasma samples.

[0059] In some embodiments, the method further comprises the step of generating a report listing the concentrations of lipoprotein components present in the sample and the probability of death. In some embodiments, the method for diagnosing the presence of LP-Z in a subject comprises the steps of obtaining an NMR spectrum of a plasma or serum sample obtained from the subject and programmatically determining the presence of LP-Z in the sample based on the NMR spectrum of the sample, wherein the NMR spectrum of the sample comprises LP-X, LP-Y, and LP-Z. In some embodiments, the acquisition step of the method comprises (a) generating a measured lipid signal line shape for the NMR spectrum of the plasma or serum sample obtained from the subject; and (b) generating a calculated line shape for the sample, the calculated line shape being based on the derived concentrations of lipoprotein components that may be present in the sample, wherein the lipoprotein components comprise LP-X, LP-Y, and LP-Z, the derived concentration of each lipoprotein component being a function of a reference spectrum of the component and a calculated reference coefficient, wherein the three lipoprotein components for which the concentrations are calculated are LP-X, LP-Y, and LP-Z.

[0060] In some embodiments, the method further comprises (c) determining a correlation between an initial calculated line shape of the sample and a measured line shape of the sample; and (d) determining the presence of LP-Z based on the calculated line shape if the correlation between the calculated line shape and the measured line shape of the sample is above a predetermined threshold. In some embodiments, step (b) of the method comprises calculating a reference coefficient for the calculated line shape based on a linear least squares fitting technique. In some embodiments, the sample may be blood, serum, plasma, cerebrospinal fluid, or urine.

[0061] Reference now Fig.11 It is expected that most, if not all, measurements may be performed on or using a system 10 that is in communication with or at least partially loaded upon an NMR clinical analyzer 22 such as described, for example, in U.S. Pat. No. 8,013,602, the contents of which are incorporated herein by reference as if fully set forth herein.

[0062] The system 10 may include a Z-index risk module 370 to collect data suitable for determining the Z-index. The system 10 may include an analysis circuit 20 including at least one processor 20p that may be loaded on the analyzer 22 or at least partially remote from the analyzer 22. If the latter, the module 370 and / or the circuit 20 may be located in whole or in part on the server 150. The server 150 may be provided using cloud computing, which includes providing computing resources on demand via a computer network. The resources may be embodied as various infrastructure services (e.g., computers, storage, etc.) as well as applications, databases, file services, email, etc. In the traditional computing model, both data and software are usually completely contained in the user's computer; in cloud computing, the user's computer may contain very little software or data (perhaps an operating system and / or a web browser) and may only serve as a display terminal for processes occurring on an external computer network. Cloud computing services (or an aggregation of multiple cloud resources) may generally be referred to as "clouds". Cloud storage may include a model of networked computer data storage in which data is stored on multiple virtual servers rather than being hosted on one or more dedicated servers. Data transmission may be encrypted and may be accomplished over the Internet using any appropriate firewall to comply with industry or regulatory standards such as HIPAA. The term "HIPAA" refers to the United States law defined by the Health Insurance Portability and Accountability Act. Patient data may include an accession number or identifier, gender, age, and test data.

[0063] The results of the analysis can be sent to the patient, clinician site 50, health insurance agency 52 or pharmacy 51 via a computer network (such as the Internet), via email, etc. The results can be sent directly from the analysis site or can be sent indirectly. The results can be printed out and sent by regular mail. This information can also be sent to the pharmacy and / or health insurance company, or even the patient, which monitors prescriptions or drug use that may increase the risk of adverse events, or issues medical alerts to prevent the prescription of contradictory medicaments. The results can be sent to the patient by emailing to a "home" computer or a popular computing device (such as a smart phone or laptop, etc.). For example, the results can be sent as an email attachment to the entire report or as a text message alert.

[0064] Illustrative embodiments of methods, systems, and analyzers

[0065] As used below, any reference to a method, system, or analyzer will be understood to be a reference to each of those methods, systems, or analyzers individually (e.g., "illustrative embodiments 1-4" will be understood to be "illustrative embodiments 1, 2, 3, or 4").

[0066] Illustrative embodiment 1 is a method for predicting mortality in a patient with alcoholic hepatitis, comprising: acquiring an NMR spectrum of a biological sample obtained from a subject; programmatically determining the concentrations of LP-Z and total apoB-containing lipoproteins in the sample based on the NMR spectrum of the sample, wherein the NMR spectrum of the sample includes LP-X and LP-Z; and calculating a Z-index score.

[0067] Illustrative embodiment 2 is the method of any preceding or subsequent embodiment, wherein the acquiring step of the method comprises: generating measured lipid signal line shapes for an NMR spectrum of a biological sample obtained from a subject; and generating calculated line shapes for the sample.

[0068] Illustrative embodiment 3 is the method of any preceding or subsequent embodiment, wherein the calculated linearity is based on derived concentrations of lipoprotein components including LP-X and LP-Z.

[0069] Illustrative embodiment 4 is the method of any preceding or subsequent embodiment, wherein the derived concentration of each of the lipoprotein components is a function of a reference spectrum and a calculated reference coefficient for the component.

[0070] Illustrative embodiment 5 is the method of any preceding or subsequent embodiment, wherein the generating step comprises calculating reference coefficients for the calculated line shape based on a linear least squares fitting technique.

[0071] Illustrative embodiment 6 is a method of any preceding or subsequent embodiment, further comprising: determining a correlation between an initial calculated line shape of the sample and a measured line shape of the sample; and determining the presence of LP-Z based on the calculated line shape if the correlation between the calculated line shape and the measured line shape of the sample is higher than a predetermined threshold.

[0072] Illustrative embodiment 7 is the method of any preceding or subsequent embodiment, wherein the Z-index score comprises the concentrations of lipoproteins LP-Z, LDL, and VLDL.

[0073] Illustrative embodiment 8 is the method of any preceding or subsequent embodiment, wherein the Z index is the ratio of the LP-Z concentration to the total ApoB-containing lipoprotein concentration.

[0074] Illustrative embodiment 9 is the method of any preceding or subsequent embodiment, wherein the Z index is calculated by the following equation:

[0075] Z index = ([ LP-Z ]) / ([ VLDL ] + [ LDL ] + [ LP-Z ]).

[0076] Illustrative embodiment 10 is the method of any preceding or subsequent embodiment, wherein a Z-index greater than 0.6 predicts that patient death will occur within 90 days or less.

[0077] Illustrative embodiment 11 is the method of any preceding or subsequent embodiment, wherein the method predicts the likelihood of death of the patient within 90 days.

[0078] Illustrative embodiment 12 is the method of any preceding or subsequent embodiment, wherein the method predicts the likelihood of survival or the patient's response to treatment.

[0079] Illustrative embodiment 13 is the method of any preceding or subsequent embodiment, further comprising, prior to programmatically determining,

[0080] The subject's sample is placed in an NMR spectrometer;

[0081] deconvoluting the NMR spectrum; and

[0082] NMR-derived measures of multiple selected lipoprotein parameters are calculated based on the deconvoluted NMR spectra.

[0083] Illustrative embodiment 14 is the method of any preceding or subsequent embodiment, further comprising generating a report listing the concentration of the lipoprotein components present in the sample and the probability of death.

[0084] Illustrative embodiment 15 is the method of any preceding embodiment, wherein the biological sample is one of blood, serum, plasma, cerebrospinal fluid, or urine.

[0085] Illustrative embodiment 16 is an NMR analyzer comprising:

[0086] NMR spectrometer;

[0087] a probe in communication with the spectrometer; and

[0088] A controller in communication with the spectrometer is configured to obtain an NMR signal defining a single peak region of an NMR spectrum associated with LP-Z of the fluid sample in the probe and generate a patient report providing a level of LP-Z.

[0089] Illustrative embodiment 17 is the analyzer of any preceding or subsequent embodiment, wherein the controller is in communication with at least one local or remote processor, wherein the at least one processor is configured to:

[0090] (i) obtaining a composite NMR spectrum of a fitted region of the fluid sample; and

[0091] (ii) Deconvoluting the composite NMR spectrum using a defined deconvolution model to generate LP-Z levels.

[0092] Illustrative embodiment 18 is an analyzer of any preceding or subsequent embodiment, wherein the deconvolution model includes at least one of a high-density lipoprotein (HDL) component, a low-density lipoprotein (LDL) component, a VLDL (very low density lipoprotein) / chylomicron component, LP-X, LP-Y, and LP-Z.

[0093] Illustrative embodiment 19 is the analyzer of any preceding or subsequent embodiment, wherein the probe is a flow probe.

[0094] Illustrative embodiment 20 is the analyzer of any preceding or subsequent embodiment, wherein the fluid sample is an in vitro plasma biological sample.

[0095] Illustrative embodiment 21 is the analyzer of any preceding embodiment, wherein the fluid sample is a biological sample of blood, serum, plasma, cerebrospinal fluid, or urine.

Claims

1. A system for predicting mortality of patients with alcoholic hepatitis, wherein the system is used to implement the following steps: acquiring an NMR spectrum of a biological sample obtained from a subject; programmatically determining the concentration of LP-Z and the concentration of total apoB-containing lipoproteins in the biological sample based on an NMR spectrum of the biological sample, wherein the NMR spectrum of the biological sample includes LP-X and LP-Z, and the total apoB-containing lipoproteins consist of LP-Z, LDL, and VLDL; and A Z-index score is calculated based on the ratio of LP-Z to total apoB-containing lipoproteins, wherein a Z-index score greater than 0.6 predicts the likelihood of patient death within 90 days, and wherein the biological sample is blood, serum or plasma.

2. The system of claim 1, wherein said obtaining step comprises: Producing measured lipid signal line shapes for NMR spectra of biological samples obtained from subjects; as well as Generate calculated line shapes for biological samples.

3. The system of claim 2, wherein the calculated linearity is based on derived concentrations of lipoprotein components including LP-X and LP-Z.

4. The system of claim 3, wherein the derived concentration of each of the lipoprotein components is a function of a reference spectrum and a calculated reference coefficient for the component.

5. The system of claim 2, wherein said generating step comprises calculating reference coefficients for said calculated line shape based on a linear least squares fitting technique.

6. The system of claim 2, wherein said steps further comprise: determining a correlation between a calculated linear shape of the biological sample and a measured linear shape of the biological sample; as well as If the correlation between the calculated line shape and the measured line shape of the biological sample is higher than a predetermined threshold, the presence of LP-Z is determined based on the calculated line shape.

7. The system of claim 1, wherein the Z-index score is the ratio of LP-Z concentration to total ApoB-containing lipoprotein concentration.

8. The system of claim 1, wherein the Z-index score is calculated by the following equation: Z-index = ([LP-Z]) / ([VLDL]+[LDL]+[LP-Z]), where [LP-Z] is the LP-Z concentration, [VLDL] is the VLDL concentration, and [LDL] is the LDL concentration.

9. The system of claim 1, wherein the system predicts the likelihood of survival or a patient's response to treatment.

10. The system of claim 1, wherein said step further comprises, prior to programmatically determining, placing a biological sample from the subject in an NMR spectrometer; deconvoluting the NMR spectrum; and NMR-derived measures of multiple selected lipoprotein parameters are calculated based on the deconvoluted NMR spectra.

11. The system of claim 1, wherein said step further comprises generating a report listing the concentrations and probability of mortality of lipoprotein components present in said biological sample.

12. The system of claim 1, wherein the biological sample is blood.

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