A method for predicting liver disease mortality using lipoprotein LP-Z.

Abstract

To provide methods and systems for assays that accurately determine lipoproteins in a plasma or serum sample and predict patient mortality, in contrast to conventional lipid panels incapable of detecting the presence of LP-X or LP-Z.SOLUTION: Described herein are methods for the determination of patient mortality from alcoholic hepatitis in biosamples by NMR spectroscopy, and more specifically, methods for the determination of a Z index score based on lipoprotein constituent LP-Z in blood plasma and serum.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] (Related Application) This application claims the benefit of priority of U.S. Provisional Patent Application No. 62 / 757,505, filed on November 8, 2018, the content of which is incorporated herein by reference in its entirety as if fully set forth herein.

[0002] This specification describes methods and systems for determining components in plasma and serum, more specifically, methods and systems for determining lipoprotein components in plasma and serum.

Background Art

[0003] Alcoholic hepatitis (AH) is a common cause of hospitalization for liver disease in the United States. Among the spectrum of alcoholic liver diseases, AH causes the most acute symptoms, with a mortality rate of 5% - 10% among all patients and 30% - 50% in its severe form. Unlike other forms of liver failure, the symptoms of AH are characterized by severe defects in blood clotting (coagulopathy) and bile stagnation (cholestasis) that can occur without significant hepatocyte loss or advanced fibrosis. The mechanisms underlying this severe hepatocyte dysfunction in severe AH remain largely unclear. Conventional treatment of AH is limited to abstinence from alcohol, nutritional support, and corticosteroids in selected patients for potential short-term effects. Liver transplantation may be possible for selected AH patients. Stratification of disease risk is an important issue in the clinical management of AH, and it remains difficult to predict outcomes and select appropriate patient candidates for liver transplantation among patients with liver failure.

[0004] Several prognostic strategies in AH have been studied, including the Maddrey discriminant function (DF), the Glasgow Alcoholic Hepatitis Score (GAHS), age, serum bilirubin, INR, and serum creatinine (ABIC) scores, and the Lillie model. However, these scores do not reliably predict mortality or guide clinical decisions regarding liver transplantation. Another scoring system used to assess the severity of chronic liver disease is the End-Stage Disease Model (MELD). MELD is a score calculated from serum creatinine, total bilirubin, the international normalized ratio (INR) of prothrombin time, and sodium concentration. MELD is generally a good predictor of 90-day mortality in patients with cirrhosis resulting from various forms of chronic liver disease and has traditionally been used to select patients for liver transplantation and to rank patients on the liver transplant waiting list.

[0005] Unlike patients with decompensated cirrhosis, where spontaneous recovery is rare, a significant proportion of patients with acute hemorrhagic heart disease (AH) can recover with abstinence and supportive care, even with high MELD scores. Highly reliable prognostic methods may help identify AH patients who are candidates for organ transplantation.

[0006] One of the essential functions of the liver is to regulate lipid and lipoprotein metabolism. The secretion of very low-density lipoprotein particles (VLDL), which are triglyceride-rich lipoproteins, is one pathway by which liver cells can remove triglycerides accumulated within the cells. VLDL is metabolized into low-density lipoprotein (LDL), which are cholesterol ester-rich particles. The conversion of VLDL to LDL in circulation depends on a series of enzymes produced by the liver.

[0007] Recent data suggest that nuclear magnetic resonance (NMR) spectroscopy can be used to identify and quantify abnormal lipoproteins, including LDL, LP-X, and LP-Z. Accurately determining the presence and quantity of lipoproteins in biological samples and correlating lipoprotein levels with patient outcomes can improve prognosis prediction and ultimately improve 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 specification describes a novel method and system for accurately detecting and quantifying LP-Z levels in biological samples using NMR spectroscopy and correlating LP-Z levels with patient mortality. [Overview of the Initiative] [Means for solving the problem]

[0008] This specification describes a method and system for accurately determining the presence and amount of LP-Z in a biological sample using NMR spectroscopy, creating a Z-index score, and predicting patient mortality. The present invention can be embodied in various ways. In certain embodiments, the method and system include determining LP-Z in a subject or patient. In some embodiments, the method can predict the accuracy of the patient's response to therapy or the patient's mortality within 90 days.

[0009] In some embodiments, a method for predicting the mortality rate of a subject with AH includes 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 examples, the NMR spectrum of the sample may include all subclasses of normal lipoproteins, as well as abnormal lipoproteins LP-X, LP-Y, and LP-Z. In certain embodiments, the method further includes calculating a Z-index score. In some cases, a Z-index greater than 0.6 may correlate with alcoholic hepatitis mortality within 90 days.

[0010] Further embodiments relate to NMR analyzers. An NMR analyzer may comprise an NMR spectrometer, a probe communicating with the spectrometer, and a control unit communicating with the spectrometer, which are configured to acquire the NMR signal of a specified single-peak region of the NMR spectrum associated with the LP-Z of a fluid sample in the probe, and to produce a patient report providing the LP-Z level. In some examples, the probe may be a flow probe.

[0011] The control device may include or communicate with at least one local or remote processor, wherein at least one processor is configured to (i) acquire a composite NMR spectrum of a fitting region of an in vitro plasma biological sample, and (ii) deconvolve the composite NMR spectrum using a defined deconvolution model to generate LP-Z levels. In certain embodiments, the deconvolution model includes at least one of a high-density lipoprotein (HDL) component, a low-density lipoprotein (LDL) component, a very low-density lipoprotein (VLDL) / chylomicron component, LP-X, and / or LP-Y and LP-Z.

[0012] Further features, advantages, and details of the present invention will be understood by those skilled in the art by reading the drawings and the detailed description of the following preferred embodiments, which are merely illustrative of the invention. Features described in relation to one embodiment may be incorporated with other embodiments even if they are not specifically discussed therein. That is, it should be noted that aspects of the invention described in relation to one embodiment may be incorporated into different embodiments even if they are not specifically described in relation thereto. That is, features of all embodiments and / or any embodiments may be combined in any way and / or in any combination. The applicant has the right to modify any claims initially filed or to file any new claims, including the right to amend any claims initially filed to make them dependent on and / or incorporated with any features of any other claims, even if they were not initially claimed that way. The above and other aspects of the present invention are described in detail in the specification shown below.

[0013] This disclosure can be better understood by referring to the accompanying drawings illustrating embodiments of the present invention. However, the present invention can be embodied in many different ways and should not be construed as being limited to the embodiments shown herein. Rather, these embodiments are presented to make this disclosure thorough and complete and to fully convey the scope of the invention to those skilled in the art. [Brief explanation of the drawing]

[0014] [Figure 1] This figure shows an exemplary NMR spectrum of human serum. [Figure 2] This figure shows an example of a VLDL, LDL, or HDL subclass in an NMR spectrum. [Figure 3] This figure shows an exemplary analysis of plasma using an LP-X deconvolution model that includes reference signals for LP-X and LP-Z. [Figure 4] This figure shows exemplary LP-Z concentrations in healthy patients and patients with liver disease, as determined by NMR analysis. [Figure 5] This figure shows an example Kaplan-Meier curve of the Z index predicting 90-day survival in severe alcoholic hepatitis. [Figure 6] This figure shows an example of repeated measures of the Z index for predicting 90-day survival in severe alcoholic hepatitis. [Figure 7] This figure shows exemplary lipoprotein profiles in alcoholic hepatitis compared to healthy subjects. [Figure 8] This is a diagram showing the chemical structures of lipids and triglycerides. [Figure 9] This is a schematic diagram illustrating lipoprotein metabolism in healthy subjects. [Figure 10] This figure shows exemplary lipoprotein profiles for LP-X and LP-Z in alcoholic hepatitis. [Figure 11] This 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. [Modes for carrying out the invention]

[0015] This application investigates the relationship between LP-Z, determined by NMR spectroscopy, in plasma samples from alcoholic hepatitis (AH) patients and tracks the mortality rate of AH patients. This specification describes a novel method for accurately predicting the mortality rate of AH patients based on the amount of LP-Z in a biological sample using NMR spectroscopy. The present invention can be embodied in various ways.

[0016] In some embodiments, the method and system include determining the LP-Z in a subject or patient. In some embodiments, the method can predict the likelihood of a patient's response to therapy or the patient's mortality rate within 90 days.

[0017] In some embodiments, a method for predicting the mortality of a subject with AH includes obtaining an NMR spectrum of a plasma sample or a 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 including LP-X and LP-Z. In some embodiments, the NMR spectrum of the sample further includes LP-Y. In certain embodiments, the method further includes calculating a Z-index score. In some cases, a Z-index greater than 0.6 may correlate with AH mortality within 90 days.

[0018] Lipoprotein Z (LP-Z) is an LDL-like particle. Similar to LDL, LP-Z has an amphipathic lipid on its surface and one copy of apolipoprotein B (apoB) with hydrophobic lipids in the core of the particle. The species referred to herein as LP-Z has previously been described as "highly triglyceride enriched LDL" (by Kostner GM et al, Biochem J. 1976; Vol. 157: pp. 401-407). Lipoprotein X (LP-X) is an abnormal multilamellar vesicle particle rich in phospholipids and unesterified cholesterol that can be quantified by nuclear magnetic resonance (NMR) spectroscopy. Conventional lipid panels cannot detect the presence of LP-X or LP-Z.

[0019] Terms and Definitions Like numbers refer to like elements throughout. In the drawings, for clarity, certain lines, layers, components, elements, or features may be exaggerated. Dashed lines indicate optional features or operations unless otherwise specified.

[0020] The terms used in this specification are for the sole purpose of describing particular embodiments and are not intended to limit the present invention. When used in this specification, the singular forms ("a", "an", and "the") are intended to include the plural forms as well, unless the context clearly dictates otherwise. As used herein, the terms "comprises" and / or "comprising" specify the presence of the stated feature, integer, step, operation, element, and / or component, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items. As used herein, phrases such as "between X and Y" and "substantially between X and Y" should be construed to include X and Y. As used herein, phrases such as "substantially between X and Y" mean "between about X and about Y". As used herein, "substantially X to Y" means "about X to about Y".

[0021] Unless otherwise defined, all terms (including technical and scientific terms) used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, terms defined in commonly used dictionaries should be interpreted to have a meaning that coincides with their meaning in the context of this specification and the related art, and should not be interpreted in an idealized or overly formal sense unless explicitly defined herein. Well-known functions or configurations may not be described in detail for the sake of brevity and / or clarity.

[0022] The term "programmatically" means that the operation is performed using a computer program and / or software, processor, or ASIC. The term "electronic" and its derivatives refer to automated or semi-automated operations performed using devices with electrical circuits and / or modules, without human arrangement, and typically refer to operations performed by a program. The terms "automated" and "automatic" mean that the operation can be performed with minimal or no manual intervention or input. The term "semi-automated" means that the operator is required to make some inputs or activations, but the calculations and signal acquisition, and the calculation of the concentration of ionized components (including multiple components) are performed electronically, typically by a program, without requiring manual input. The term "approximately" means ±10% (mean or average) of a specified value or number.

[0023] The term "biological sample" refers to an in vitro blood sample, plasma sample, serum sample, CSF sample, saliva sample, lavage sample, sputum sample, urine sample, or tissue sample from a human or animal. Embodiments of the present invention may be particularly suitable for evaluating biological samples of human plasma or serum. Plasma or serum samples may be fasted or not fasted.

[0024] The terms "patient" or "subject" are widely used to refer to individuals who provide biological samples for testing or analysis.

[0025] The term “clinical condition” refers to a risky medical condition that may indicate the appropriateness of medical intervention, therapy, adjustment of therapy, or exclusion and / or monitoring of a particular therapy (e.g., a drug). By identifying the likelihood of a clinical condition, clinicians can treat, delay, or suppress the onset of the condition accordingly. Examples of clinical conditions, but not limited to, include 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 conditions associated with immunodeficiency, abnormalities in biological function in protein sorting, immunity and receptor recognition, inflammation, pathogenicity, metastasis, and other cellular processes.

[0026] Method for determining the Z index by measuring LP-Z This specification describes a novel method (i.e., an assay) for diagnosing or detecting pulmonary hypertension (AH) in a subject by characterizing LP-Z in a biological sample using NMR. In some embodiments, this method can predict mortality in AH patients. The method can be embodied in various ways.

[0027] NMR spectroscopy is used to simultaneously measure the entire range of circulating lipoproteins, including very low-density lipoprotein (VLDL), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) subclasses, as well as abnormal lipoprotein particles such as LP-X and LP-Z, derived from in vitro plasma or serum samples. See U.S. Patent No. 4,933,844, U.S. Patent No. 6,617,167, and U.S. Patent Application No. 16 / 188,435 filed November 13, 2018 (these are incorporated herein by reference as if they were all enumerated herein). In some embodiments, the sample may be blood, serum, plasma, cerebrospinal fluid, or urine.

[0028] In summary, to evaluate lipoproteins in plasma and / or serum samples, subclass concentrations are obtained by deconvolving the envelope of a composite methyl signal by deriving the amplitudes of signals from multiple NMR spectroscopic methods within the chemical shift region of the NMR spectrum. Figure 1 shows an exemplary NMR spectrum of human serum, with lipid methyl groups highlighted. Subclasses are represented by the signals of numerous (typically more than 60) distinct contributing subclasses, associated with NMR frequencies and lipoprotein diameters. NMR evaluation can decompose the measured plasma NMR signal to generate concentrations of different lipoprotein subsets for VLDL, LDL, and HDL. These subsets can be further characterized as relating to specific size ranges within the VLDL, LDL, or HDL subclasses, for example, as shown in Figure 2. As shown in Figure 2, concatenating the subclass signals generates the measured signal. The amplitudes of the subclass signals derived by deconvolution may indicate the concentration of each subclass.

[0029] In the past, "advanced" lipoprotein test panels, such as the NMR LIPOPROFILE® lipoprotein test available from LapCorp in Burlington, North Carolina, typically included total HDL particle (HDL-P) measurements, which summed the concentrations of all HDL subclasses, and total LDL particle (LDL-P) measurements, which summed the concentrations of all LDL subclasses. The LDL-P count expresses the concentration of each particle in units such as nmol / L. The HDL-P count expresses the concentration of each particle in units such as μmol / L.

[0030] NMR analysis using sophisticated deconvolution models has recently been used to determine the concentrations of LP-X and LP-Z in biological samples. Figure 3 shows an example of good fit and small residual signal obtained from the analysis of patient-derived plasma with high bilirubin levels using an LP-X deconvolution model that includes reference signals for LP-X, LP-Y, and LP-Z.

[0031] NMR spectroscopy can be used to identify and quantify LP-Z in patients with LP-Z accumulation, such as those with alcoholic hepatitis (AH). As shown in Figure 4, recent studies on plasma samples from AH patients using an NMR-based methodology developed by LabCorp to quantify circulating lipoprotein profiles in biological samples revealed that exemplary patients with AH have significantly higher levels of the abnormal lipoprotein LP-Z. In particular, LP-Z levels may be significantly higher in patients with AH compared to healthy individuals (HC) or patients with other forms of chronic liver disease. To reliably use NMR for prognostic diagnosis in AH patients, the relationship between NMR-determined LP-Z and patient mortality must be understood.

[0032] The above AH study further confirmed that, among AH patients, levels of both LP-Z and total apoB-containing lipoproteins were inversely correlated with liver synthesis function as measured by INR. While neither LP-Z nor total apoB-containing lipoprotein levels may have a robust correlation with mortality in patients with AH, these two parameters can inversely predict mortality. Mortality can be predicted using LP-Z and total apoB-containing lipoproteins (VLDL, LDL, and LP-Z) simultaneously. LP-Z may have a positive correlation with mortality, while total apoB-containing lipoproteins may have a negative correlation. The novel biomarker Z index described herein utilizes these correlations with patient mortality. The formula is as follows: Z index=([LPZ]) / ([VLDL]+[LDL]+[LPZ]) The Z coefficient can be calculated using the following formula, where the concentration unit for the lipoprotein component is nmol / L.

[0033] The Z index can represent the proportion of abnormal lipoprotein LP-Z in apoB-containing lipoproteins and reflect the degree of liver dysfunction that impairs circulating lipoproteins in AH. The Z index can highly predict short-term mortality within 90 days. As shown in the exemplary Kaplan-Meier curve in Figure 5, the Z index can have a robust correlation with 90-day mortality. For every 1% increase in the Z index, the hazard ratio for mortality increases by 5% (95% CI 1.02~1.08, p=0.001). A threshold of 0.6 for the Z index was determined. At a Z index below 0.6, only about 5% of patients may die within 90 days of LP-Z identification (2 out of 38 subjects in the data shown in Figure 5). In contrast, if the Z index exceeds 0.6, approximately 40% of patients may be expected to die within 90 days of LP-Z identification (in the data shown in Figure 5, 21 out of 53 subjects died within 90 days).

[0034] The Z-index may be a more reliable predictor than the MELD score, a recent standard for predicting outcomes in patients with hepatic hepatitis. As shown in Table 1, the Z-index significantly outperforms the MELD score in predicting 90-day mortality among patients with pulmonary hepatitis (AH). [Table 1]

[0035] As shown in Table 2, the Z index can also be a more reliable predictor than other components when predicting outcomes in AH. [Table 2]

[0036] The Z-index can be calculated using the concentrations of LP-Z and total apoB-containing lipoproteins measured by NMR, and this can be used to effectively risk stratify patients with severe AH. Effective risk stratification can be particularly useful in distinguishing between patients with a low risk of death within 90 days and those with a high risk of death. For example, as shown in Figure 6, the Z-index can be used as a repeated measure to predict outcomes. The Z-index among survivors decreased until day 14, while the Z-index for those who died remained constant.

[0037] While this specification discloses LP-Z and apoB-containing lipoproteins via NMR spectroscopy, those skilled in the art will understand that the Z index is not specific to NMR spectroscopy. For example, the concentration of LP-Z could be estimated using agarose gel electrophoresis combined with lipid staining using Sudan Black and Philippine. The concentration of apoB could be measured by ELISA. Figure 7 shows that exemplary lipoprotein profiles in AH are distinctive compared to the profiles of exemplary healthy subjects (HC) in both the Sudan Black and Philippine tests.

[0038] Figure 8 shows the lipoprotein and chemical structures of phospholipids (PL), cholesterol esters (CE), triglycerides (TG), and free cholesterol (FC). Figure 9 shows the lipid pathway in lipoprotein metabolism in healthy subjects. Most individuals (i.e., "normal" healthy subjects) have very low levels of LP-X or LP-Z, or no LP-Z at all. In contrast, varying amounts of LP-Y are found in both healthy and affected individuals. In subjects showing the presence of LP-X or LP-Z, such as those with obstructive jaundice or avian heart disease (AH), LP-Z levels can be elevated to varying degrees.

[0039] The methyllipid signals from LP-X, LP-Y, and LP-Z each exhibit unique spectral shapes and positions in NMR spectroscopy, distinct from "normal" lipoprotein particles. In AH, a unique pattern of circulating lipoproteins can be observed, characterized by the accumulation of abnormal lipoproteins LP-X and LP-Z. Figure 10 shows an exemplary characteristic lipoprotein profile in an AH patient. Elevated LP-X and LP-Z concentrations, as determined by NMR analysis, can distinguish between healthy patients and those with liver disease. These lipoproteins can serve as effective biomarkers for risk stratification of severe alcoholic hepatitis. The assays described herein utilize these unique spectral characteristics to detect and quantify LP-X, LP-Y, and LP-Z in serum or plasma samples.

[0040] In some embodiments, the method further includes the step of generating a report listing the concentrations of lipoprotein components present in the sample and the probability of death. In some embodiments, a method for diagnosing a subject for the presence of LP-Z includes 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 containing LP-X, LP-Y, and LP-Z. In some embodiments, the steps obtained by the method include (a) generating a linearized measured lipid signal for the NMR spectrum of a plasma or serum sample obtained from the subject, and (b) creating a calculated linearized line for the sample based on the derived concentrations of lipoprotein components that may be present in the sample, wherein the lipoprotein components include LP-X, LP-Y, and LP-Z, and the derived concentration of each lipoprotein component is a function of the reference spectrum and calculated reference coefficient for that component, and the three lipoprotein components whose concentrations are calculated are LP-X, LP-Y, and LP-Z.

[0041] In some embodiments, the method further includes (c) determining the correlation between an initial calculated linearity of the sample and a measured linearity of the sample, and (d) determining the presence of LP-Z based on the calculated linearity if the correlation between the calculated linearity of the sample and the measured linearity exceeds a predetermined threshold. In some embodiments, step (b) of the method includes calculating a reference coefficient for the calculated linearity based on a linear least squares fitting method. In some embodiments, the sample may be blood, serum, plasma, cerebrospinal fluid, or urine.

[0042] Referring here to Figure 11, it is conceivable that most, if not all, of the measurements can be performed on or using a system 10 that communicates with, or at least partially incorporates, an NMR clinical analyzer 22, for example, U.S. Patent No. 8,013,602 (the contents of which are incorporated herein by reference as if they were all enumerated herein).

[0043] System 10 may include a Z-index risk module 370 that collects data suitable for determining the Z-index. System 10 may also include an analysis circuit 20 that includes at least one processor 20p, which may be mounted on the analyzer 22 or at least partially separate from the analyzer 22. In the latter case, the module 370 and / or the circuit 20 may reside entirely or partially on a server 150. The server 150 may be provided using cloud computing, which includes providing on-demand computing resources over a computer network. These resources may be embodied as various infrastructure services (e.g., computers, storage devices, etc.), as well as applications, databases, file services, email, etc. In traditional computing models, both data and software are typically housed entirely on the user's computer, whereas in cloud computing, the user's computer houses little to no software or data (and possibly even an operating system and / or web browser), and may only function as a display terminal for processes performed on a network of external computers. Cloud computing services (or a collection of cloud resources) may generally be referred to as the "cloud." Cloud storage can include models of network-connected computer data storage where data is stored on multiple virtual servers rather than being hosted on one or more dedicated servers. Data transfer can be encrypted and conducted over the internet using any appropriate firewall compliant with industry or regulatory standards such as HIPAA. The term "HIPAA" refers to U.S. law as defined by the Health Insurance Portability and Accountability Act. Patient data may include accession numbers or identifiers, sex, age, and test data.

[0044] The analysis results may be transmitted to patients, clinicians 50, health insurance agencies 52, or pharmacies 51 via computer networks such as the internet, or via email. The results may be sent directly or indirectly from the analysis site. The results may be printed out and sent via conventional postal mail. This information may also be transmitted to pharmacies and / or health insurance companies, or even patients, to monitor prescriptions or drug use that may increase the risk of adverse events or to issue medical warnings to prevent inconsistent prescriptions. The results may be sent to patients via email to their "home" computers or to popular computer devices such as smartphones or notepads. The results may be, for example, an email attachment to the full report or a text message warning.

[0045] Exemplary embodiments of methods, systems, and analytical devices Where used below, all references to methods, systems, or analytical devices should be understood alternatively as references to each of those methods, systems, or analytical devices (for example, “Exemplary Embodiments 1-4” should be understood as “Exemplary Embodiments 1, 2, 3, or 4”).

[0046] An exemplary embodiment 1 is a method for predicting patient mortality in alcoholic hepatitis, comprising the steps of: obtaining an NMR spectrum of a biological sample obtained from a subject; determining the concentrations of LP-Z and total apoB-containing lipoprotein in the sample by program based on the NMR spectrum of the sample containing LP-X and LP-Z; and calculating a Z-index score.

[0047] An exemplary embodiment 2 is a method of any earlier or later embodiment in which the acquisition step of the above method includes the steps of generating a measured lipid signal linearity for the NMR spectrum of a biological sample obtained from a subject, and creating a calculated linearity for the sample.

[0048] Exemplary Embodiment 3 is a method of any of the preceding or succeeding embodiments in which the calculated linearity is based on the derived concentrations of lipoprotein components including LP-X and LP-Z.

[0049] Exemplary Embodiment 4 is a method of either a preceding or succeeding embodiment in which the derived concentration of each lipoprotein component is a function of the reference spectrum and calculated reference coefficient for that component.

[0050] Exemplary Embodiment 5 is a method of any of the preceding or succeeding embodiments in which the creation step includes calculating reference coefficients for the calculated linear based on a linear least-squares fitting method.

[0051] An exemplary embodiment 6 is a method of any earlier or later embodiment, further comprising determining the correlation between an initial calculated linearity of the sample and a measured linearity of the sample, and determining the presence of LP-Z based on the calculated linearity if the correlation between the calculated linearity of the sample and the measured linearity exceeds a predetermined threshold.

[0052] An exemplary embodiment 7 is a method of any of the preceding or subsequent embodiments in which the Z-index score includes the concentrations of lipoprotein LP-Z, LDL, and VLDL.

[0053] Exemplary embodiment 8 is a method of any of the preceding or subsequent embodiments in which the Z index is the ratio of the LP-Z concentration to the total apoB-containing lipoprotein concentration.

[0054] In exemplary embodiment 9, the Z-exponent is given by the following formula: Z index=([LP-Z]) / ([VLDL]+[LDL]+[LP-Z]) This is a method of either a preceding or succeeding embodiment, calculated by [the formula shown].

[0055] Exemplary embodiment 10 is a method of either a preceding or succeeding embodiment in which patient mortality is predicted to occur within 90 days based on a Z index greater than 0.6.

[0056] Exemplary embodiment 11 is a method of either a preceding or succeeding embodiment for predicting the certainty of patient mortality within 90 days.

[0057] Exemplary embodiment 12 is a method of either a preceding or succeeding embodiment for predicting the likelihood of survival or the response of a patient to treatment.

[0058] Exemplary embodiment 13 is a method of any preceding or subsequent embodiment, further comprising, before programmatic determination, placing a subject's sample into an NMR spectrometer, deconvolving the NMR spectrum, and calculating NMR-derived measurements of several selected lipoprotein parameters based on the deconvolved NMR spectrum.

[0059] Exemplary embodiment 14 is a method of any earlier or later embodiment, further comprising generating a report listing the concentrations of lipoprotein components present in the sample and the likelihood of death.

[0060] Exemplary embodiment 15 is a method of any of the preceding embodiments, wherein the biological sample is one of blood, serum, plasma, cerebrospinal fluid, or urine.

[0061] An exemplary embodiment 16 is an NMR analyzer comprising an NMR spectrometer, a probe communicating with the spectrometer, and a control device communicating with the spectrometer, which are configured to acquire an NMR signal of a specified single-peak region of the NMR spectrum associated with the LP-Z of a fluid sample in the probe, and to produce a patient report providing the LP-Z level.

[0062] An exemplary embodiment 17 is an analytical apparatus of any earlier or later embodiment in which the control device communicates with at least one local or remote processor, wherein at least one processor is configured to (i) acquire a composite NMR spectrum of a fitting region of a fluid sample, and (ii) deconvolve the composite NMR spectrum using a defined deconvolution model to generate LP-Z levels.

[0063] An exemplary embodiment 18 is an analytical instrument of any earlier or later embodiment in which the deconvolution model includes at least one of the following: high-density lipoprotein (HDL) components, low-density lipoprotein (LDL) components, very low-density lipoprotein (VLDL) / chylomicron components, LP-X, LP-Y, and LP-Z.

[0064] An exemplary embodiment 19 is an analyzer of any of the preceding or succeeding embodiments, wherein the probe is a flow probe.

[0065] Exemplary embodiment 20 is an analyzer of any of the preceding or succeeding embodiments, wherein the fluid sample is an in vitro plasma biological sample.

[0066] Exemplary embodiment 21 is an analytical apparatus of any of the preceding embodiments, wherein the fluid sample is a biological sample of blood, serum, plasma, cerebrospinal fluid, or urine. [Note 1] A method for predicting the mortality rate of patients with alcoholic hepatitis, The process of obtaining the NMR spectrum of a biological sample obtained from a subject, A step of determining the concentration of LP-Z and total apoB-containing lipoprotein in the sample by program based on the NMR spectrum of the sample containing LP-X and LP-Z, The process of calculating the Z-index score, Methods that include... [Note 2] The aforementioned acquisition process is, A step of generating a linear representation of the measured lipid signal for the NMR spectrum of the biological sample obtained from the subject, A step of creating a calculated linear for the aforementioned sample, The method described in Appendix 1, including the method described in Appendix 1. [Note 3] The calculated linearity is based on the derived concentrations of lipoprotein components including LP-X and LP-Z, as described in Appendix 2. [Note 4] The derived concentration of each lipoprotein component is a function of the reference spectrum and calculated reference coefficient for that component, as described in Appendix 3. [Note 5] The method according to Appendix 2, wherein the process of creating the linear line comprises calculating a reference coefficient for the linear line calculated based on a linear least squares fitting method. [Note 6] To determine the correlation between the initially calculated linearity of the sample and the measured linearity of the sample, If the correlation between the calculated linear and the measured linear of the sample exceeds a predetermined threshold, the presence of LP-Z is determined based on the calculated linear. The method described in Appendix 2, further including the above. [Note 7] The Z-index score is the method described in Appendix 1, which includes the concentrations of lipoprotein LP-Z, LDL, and VLDL. [Note 8] The method according to Appendix 1, wherein the Z index is the ratio of the LP-Z concentration to the total apoB-containing lipoprotein concentration. [Note 9] The Z-exponent is given by the following formula: Z index=([LP-Z]) / ([VLDL]+[LDL]+[LP-Z]) The method described in Appendix 1, calculated according to [the specified method]. [Note 10] The method described in Appendix 1, in which a Z index greater than 0.6 predicts that patient mortality will occur within 90 days. [Note 11] The method described in Appendix 1 for predicting the accuracy of patient mortality within 90 days. [Note 12] The method described in Appendix 1 for predicting the likelihood of survival or the patient's response to treatment. [Note 13] Prior to the decision made by the aforementioned program, The subject's sample is placed in an NMR spectrometer, Deconvolution of NMR spectra, Based on the deconvolved NMR spectrum, the NMR-derived measurements of several selected lipoprotein parameters are calculated. The method described in Appendix 1, further including the above. [Note 14] The method according to Appendix 1, further comprising generating a report listing the concentrations of the lipoprotein components present in the sample and the likelihood of death. [Note 15] The method according to Appendix 1, wherein the biological sample is one of blood, serum, plasma, cerebrospinal fluid, or urine. [Note 16] An NMR analyzer, NMR spectrometer and A probe that communicates with the spectrometer, A control device that communicates with the spectrometer, An NMR analyzer comprising, configured to acquire an NMR signal of a specified single-peak region of the NMR spectrum associated with the LP-Z of a fluid sample in the probe, and to produce a patient report providing the LP-Z level. [Note 17] The control device communicates with at least one local processor or remote processor, where the at least one processor is (i) Obtain the composite NMR spectrum of the fitting region of the fluid sample, and (ii) The analytical apparatus described in Appendix 16, configured to deconvolve a composite NMR spectrum using a specified deconvolution model to generate LP-Z levels. [Note 18] The deconvolution model is the analytical apparatus described in Appendix 17, comprising at least one of the following: high-density lipoprotein (HDL) component, low-density lipoprotein (LDL) component, very low-density lipoprotein (VLDL) / chylomicron component, LP-X, LP-Y, and LP-Z. [Note 19] The probe is a flow probe, as described in Appendix 16 of the analytical apparatus. [Note 20] The fluid sample is an in vitro plasma biological sample, as described in Appendix 16 of the analytical apparatus. [Note 21] The analytical apparatus described in Appendix 16, wherein the fluid sample is a biological sample of blood, serum, plasma, cerebrospinal fluid, or urine. [Explanation of symbols]

[0067] 10 Siltem 20 Processor / Analysis Circuits 22 NMR analyzer 50 Clinician 51 Pharmacy 52 Health Insurance Institutions 150 servers 227 Internet 370 Z-Index Risk Module

Claims

[Claim 1] A method for predicting the mortality rate of patients with alcoholic hepatitis, A process for obtaining NMR spectra from biological samples obtained from subjects, The process involves determining the concentrations of LP-Z and total apoB-containing lipoproteins in the sample by program based on the NMR spectrum of the sample, wherein the NMR spectrum of the sample includes LP-X and LP-Z. A step of calculating a Z-index score using the ratio of the concentration of LP-Z in the sample to the concentration of total apoB-containing lipoprotein, wherein the Z-index score represents the mortality rate of patients within 90 days after the determination of the concentration of LP-Z in the biological sample. Methods that include...

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