JPWO2007052789A1 - Lipoprotein analysis method for distinguishing macrovascular disorders - Google Patents

Abstract

Provided is a simple and low-cost testing method capable of testing the risk of macrovascular disorders in diabetic patients. Separating multiple classes of lipoproteins in a test sample collected from a diabetic patient by liquid chromatography, detecting a signal derived from cholesterol contained in the separated lipoproteins, and at least a low-density lipoprotein particle size And calculating the approximate waveform consisting of peaks corresponding to each subclass using the detected signal, and based on the obtained approximate waveform, In the peak corresponding to specific gravity lipoprotein, a step of calculating the total amount of cholesterol contained in subclasses having an average particle size equal to or lower than the low specific gravity lipoprotein, and a step of comparing the calculated total amount of cholesterol with a reference value Including.

Description

  The present invention relates to a lipoprotein analysis method for discriminating macrovascular disorders.

  The chromatogram obtained in the method of separating the lipoprotein contained in the test sample by gel filtration liquid chromatography method depending on the particle size and then quantifying the cholesterol and triacylglycerol contained in the separated lipoprotein Disclosed in Japanese Patent Laid-Open No. 9-15225 (Patent Document 1) is a method for fractionating the protein into chylomicron, ultra-low density lipoprotein, low density lipoprotein and high density lipoprotein by waveform processing such as Gaussian distribution curve approximation. Has been.

  In a method of separating lipoproteins contained in a test sample depending on the particle size by gel filtration liquid chromatography, and then quantifying the components contained in the separated lipoproteins, the lipoproteins are separated into 20 subclasses. Non-Patent Document 1 discloses a method for performing this.

  By the way, it is known that many of the complications of diabetes are related to vascular diseases. Diabetic nephropathy, diabetic retinopathy, etc. are mainly caused by disorders of relatively small blood vessels such as arterioles and capillaries. They are called diabetic microangiopathy and are characteristic lesions of diabetes. It is thought that there is.

  On the other hand, relatively large arteries are often damaged by diabetes, which is called diabetic macrovascular disorder. This macrovascular disorder is considered to have a relatively large effect such as hyperlipidemia, which often accompanies diabetes. It is known that an angina or myocardial infarction is likely to occur when a blood vessel that sends blood to the heart is damaged by a macrovascular disorder, and a stroke is likely to occur if a blood vessel to the brain is damaged.

Currently, as shown in Non-Patent Document 2, carotid echocardiography is known as a method for determining a macrovascular disorder. According to this carotid echocardiography, the carotid intima-media thickness (hereinafter referred to as IMT) can be measured, and the risk of macrovascular injury can be determined. However, the carotid echocardiography to measure this IMT is non-invasive but needs to restrain the subject in time and place and requires a high-performance ultrasonic tomography device. And it cannot be said that it is a low cost inspection. Moreover, it is necessary to frequently know the risk of macrovascular disorders in diabetic patients, and it can be said that there is a craving for an alternative to carotid echocardiography.
Japanese Patent Laid-Open No. 9-15225 Identification of Unique Lipoprotein Subclasses for Visceral Obesity by Component Analysis of Cholesterol Profile in High-Performance Liquid Chromatography (Arterioscler Thromb Vasc Biol. 2005; 25: 1-8) “Hyperlipidemia Navigator” p232-233, Medical Review

  In view of the above, the present invention has an object to provide a simple and low-cost inspection method that can inspect the risk of macrovascular disorders.

  The present invention includes the following.

  (1) A lipoprotein analysis method for discriminating macrovascular disorders by analyzing a small particle size low specific gravity lipoprotein contained in a test sample.

  (2) The analysis method according to (1), wherein the test sample is collected from a diabetic patient.

  (3) The analysis of the small particle size low specific gravity lipoprotein is a step of separating the lipoprotein contained in the test sample by liquid chromatography and detecting a signal derived from a component contained in the separated lipoprotein; Assuming that at least low-density lipoprotein is composed of a plurality of subclasses defined by the particle size, and using the detected signal, calculating an approximate waveform consisting of peaks corresponding to each subclass, and Based on the approximate waveform, the step of calculating the total amount of the above components contained in the small particle size low density lipoprotein in the peak corresponding to the low density lipoprotein, and comparing the calculated total amount with the reference value The analysis method of (1) characterized by including the process.

  (4) The analysis method according to (3), wherein the small particle size low specific gravity lipoprotein is a subclass having an average particle size equal to or smaller than the low specific gravity lipoprotein calculated from the signal.

  (5) The analysis method according to (4), wherein the lipoprotein has an average particle size of 25.5 nm.

  (6) The low specific gravity lipoprotein has a peak with an elution position of 28.0-28.61 nm, a peak with an elution position of 25.4-25.64 nm, a peak with an elution position of 22.9-23.1 nm, and an elution position in the above approximate waveform. The analysis method according to (3), which is assumed to consist of a peak at 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm, and a peak at an elution position of 16.6-16.8 nm.

  (7) The small particle size low specific gravity lipoprotein has a peak at an elution position of 22.9-23.1 nm, a peak at an elution position of 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm and The analysis method according to (6), which is a subclass corresponding to a peak at an elution position of 16.6-16.8 nm.

  (8) In the above approximate waveform, the small particle size low specific gravity lipoprotein has a peak at an elution position of 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm, and a peak at an elution position of 16.6-16.8 nm. The analysis method according to (6), which is a corresponding subclass.

  (9) The analysis method according to (3), wherein the component contained in the lipoprotein is cholesterol and / or triglyceride.

  (10) The approximate waveform is a peak whose elution position is larger than 90 nm, a peak whose elution position is 75 nm, a peak whose elution position is 64 nm, a peak whose elution position is 53.6 nm, and an elution position of 44.5 nm Peak, elution position 36.56-36.8m peak, elution position 31.3-32.17nm peak, elution position 28.0-28.61nm peak, elution position 25.4-25.64nm peak, elution position 22.9 -23.1nm peak, elution position 20.6-20.8nm peak, elution position 18.5-18.7nm peak, elution position 16.6-16.8nm peak, elution position 14.9-15.1nm peak , Peak at elution position 13.4-13.6 nm, peak at elution position 12.0-12.2 nm, peak at elution position 10.8-11.0 nm, peak at elution position 9.7-9.9 nm, elution position 8.7- (3) characterized by comprising a peak at 8.9 nm and a peak at an elution position of 7.46-7.6 nm Analytical methods listed.

  (11) The reference value is an average value of the total of the components contained in the small particle size low density lipoprotein among the peaks corresponding to the low density lipoprotein measured in the healthy subject group. The analysis method according to (3).

  (12) The analysis method according to (3), wherein the component contained in the lipoprotein is cholesterol, and the reference value is 20 mg / dl.

  (13) The analysis method according to (1), wherein the macrovascular disorder is a disorder or disease associated with an increase in carotid intima-media thickness.

  (14) The analysis method according to (13), wherein the disorder is cerebrovascular disorder and / or peripheral neuropathy, and the disease is ischemic heart disease and / or coronary artery disease.

  (15) Liquid chromatography for separating a plurality of classes of lipoproteins contained in a test sample, detection means for detecting a signal derived from a component contained in the lipoproteins separated by the liquid chromatography, and at least low specific gravity lipo Assuming that the protein is composed of a plurality of subclasses defined by the particle size, using the detected signal, approximate waveform calculation means for calculating an approximate waveform consisting of peaks corresponding to each subclass, and obtained Based on the approximate waveform, among the peaks corresponding to low density lipoprotein, a total amount calculation means for calculating the total amount of components contained in the small particle size low density lipoprotein, and the calculated total value is compared with the reference value. And a lipoprotein analyzer for discriminating macrovascular disorders in diabetic patients.

  (16) The total amount calculating means calculates the total amount using a subclass having a particle size equal to or smaller than the average particle size of the low specific gravity lipoprotein calculated from the signal as the small particle size low specific gravity lipoprotein (15). ) The analytical device described.

  (17) The analyzer according to (16), wherein the total amount calculating means sets the average particle size of the lipoprotein to 25.5 nm.

  (18) The approximate waveform calculating means includes the low specific gravity lipoprotein, a peak at an elution position of 28.0-28.61 nm, a peak at an elution position of 25.4-25.64 nm, a peak at an elution position of 22.9-23.1 nm, An approximate waveform is calculated on the assumption that the elution position consists of a peak at 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm, and a peak at an elution position of 16.6-16.8 nm (15 ) The analytical device described.

  (19) The total amount calculating means comprises a small particle diameter low specific gravity lipoprotein having a peak at an elution position of 22.9-23.1 nm, a peak at an elution position of 20.6-20.8 nm, and an elution position of 18.5- The analytical apparatus according to (18), wherein the total amount is calculated by defining that the peak is 18.7 nm and the subclass corresponding to the peak whose elution position is 16.6-16.8 nm.

  (20) The total amount calculating means comprises a small particle size low specific gravity lipoprotein having a peak at an elution position of 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm and an elution position of 16.6- The analysis apparatus according to (18), wherein the total amount is calculated by defining the subclass corresponding to a peak of 16.8 nm.

  (21) The analysis according to (15), wherein the detection means includes a cholesterol reaction part for quantifying cholesterol contained in the lipoprotein and a triglyceride reaction part for quantifying triglyceride contained in the lipoprotein. apparatus.

  (22) The approximate waveform calculation means includes the above-described lipoprotein, the peak at which the elution position is greater than 90 nm, the peak at which the elution position is 75 nm, the peak at which the elution position is 64 nm, the peak at which the elution position is 53.6 nm, Peak at elution position 44.5 nm, peak at elution position 36.56-36.8 nm, peak at elution position 31.3-32.17 nm, peak at elution position 28.0-28.61 nm, elution position 25.4-25.64 nm A peak with an elution position of 22.9-23.1 nm, a peak with an elution position of 20.6-20.8 nm, a peak with an elution position of 18.5-18.7 nm, a peak with an elution position of 16.6-16.8 nm, and an elution position 14.9-15.1 nm peak, elution position 13.4-13.6 nm peak, elution position 12.0-12.2 nm peak, elution position 10.8-11.0 nm peak, elution position 9.7-9.9 nm Peak, peak where elution position is 8.7-8.9nm and peak where elution position is 7.46-7.6nm And calculates the assumed approximate waveform Ranaru ones (15) Analysis device according.

  (23) In the comparison processing means, among the peaks corresponding to the low density lipoprotein measured in the healthy subject group, the average value of the total of the components contained in the small particle size low density lipoprotein is defined as the reference value. (15) The analyzer according to (15).

  (24) The analyzer according to (15), wherein the component contained in the lipoprotein is cholesterol, and the comparison processing means sets 20 mg / dl as the reference value.

  ADVANTAGE OF THE INVENTION According to this invention, in a diabetic patient, the simple and low-cost analysis method which can test | inspect the risk of a macrovascular disorder can be provided.

  This specification includes the contents described in the specification and / or drawings of Japanese Patent Application No. 2005-321327, which is the basis of the priority of the present application.

It is a system block diagram of the lipoprotein analyzer which quantifies TC and TG contained in serum lipoprotein. FIG. 5 is a characteristic diagram in which a chromatogram for TC and a chromatogram for TG are superimposed and displayed with the horizontal axis as the elution time (min) and the vertical axis as the detection value (mV). It is a characteristic view which shows the data used as a basis when defining as an anchor peak obtained using the TSKgel LipopropalXL column (made by Tosoh Corporation). It is a characteristic view which shows the data used as the basis at the time of defining as an anchor peak obtained using Superose 6HR 10/30 column (made by Amersham Pharmacia).

  Hereinafter, the present invention will be described in detail.

  A lipoprotein analyzer to which the present analysis method is applied includes, for example, a column 1 for separating a lipoprotein component contained in a test sample and a lipoprotein eluted from the column 1, as shown in FIG. The splitter 2 that distributes the eluent in two, the first flow path 3 and the second flow path 4 distributed by the splitter 2, and the cholesterol (hereinafter referred to as “TC”) reaction section 5 disposed in the first flow path 3. A triglyceride (hereinafter referred to as “TG”) reaction section 6 disposed in the second flow path 4, a TC detection section 7 disposed downstream of the TC reaction section 5 in the first flow path 3, and a second flow Connected to the TG detection unit 8 disposed downstream of the TG reaction unit 6 in the path 4, a system controller 9 to which signals are input from the operation control and TC detection unit 7 of the apparatus and the TG reaction unit 8, and the system controller 9 Computing device Device 10. Here, the test sample is not particularly limited, and means a sample containing biological fluid samples such as serum, plasma spinal fluid, tissue fluid and lymph fluid, and secretory particles derived from a cell culture system.

  The lipoprotein analyzer also includes a sampler 11 for supplying a serum sample to the column 1, a first pump 12 for supplying an eluent to the column 1, and a gas from the eluent supplied to the column 1 by the first pump 12. And a degasser 13 for removing the.

  In the lipoprotein analyzer, the column 1 is not particularly limited, but it is particularly preferable to use a column filled with a gel filtration filler. In particular, the column 1 can be exemplified by a column having a filler having an average pore diameter of 800 to 1200 angstroms. With fillers with an average pore size of less than 800 angstroms, lipoproteins with large molecular sizes such as CM and VLDL are difficult to enter into the pores, whereas with fillers with an average pore size of more than 1200 angstroms, molecules such as LDL and HDL Since separation of small-sized lipoproteins deteriorates, those having an average pore diameter of 800 to 1200 angstroms are preferable as described above. Among them, a filler having an average pore diameter of 900 to 1100 angstroms is excellent in resolution, so that it is possible to finally analyze a lipoprotein with higher accuracy.

  In addition, it is necessary to select a filler having a mechanical strength that can sufficiently withstand use in liquid chromatography. Examples of such fillers include those based on silica gel, polyvinyl alcohol, polyhydroxymethacrylate and other hydrophilic resins (for example, TSKgel Lipopropak, trade name, manufactured by Tosoh Corporation). .

  Examples of the eluent include phosphate buffer, Tris buffer, and bis-Tris buffer, but are not particularly limited as long as they can separate lipoproteins. The buffer concentration is 20 to 200 mM, particularly preferably 50 to 100 mM. This is because if the concentration of the buffer solution is less than 20 mM, the buffer capacity is small, and if it exceeds 200 mM, the reaction between the enzyme reagent described below and TC or TG may be inhibited. The pH of the buffer is 5-9, particularly preferably 7-8. This is because if the pH of the buffer solution is less than 5 or more than 9, the reaction with the enzyme reagent may be inhibited as described above. However, this is not the case when measuring TC and / or TG without using an enzyme.

  The TC reaction unit 5 is connected via a second pump 15 to a TC reagent tank 14 provided with a reagent for quantifying TC contained in the eluent containing lipoprotein eluted from the column 1. Here, the reagent for quantifying TC is not particularly limited, and examples thereof include enzymes such as cholesterol esterase, cholesterol oxidase, peroxidase, and N-ethyl-N- (3-methylphenyl) -N′-succinyl. An enzyme-dye reagent in combination with a dye such as ethylenediamine, 4-aminoantipyrine, N-ethyl-N- (3-sulfopropyl) -m-anisidine can be used. As the reagent, for example, commercially available Determiner L TCII (Kyowa Medex Co., Ltd.), L type CHO.H (Wako Pure Chemical Industries, Ltd.) reagent can be suitably used. These reagents react with TC to give reaction products having fluorescence and absorption that can be detected by a spectroscope such as a fluorescence detector or an ultraviolet-visible detector.

  The TG reaction unit 6 is connected to a TC reagent tank 16 provided with a reagent for quantifying TG contained in the eluent containing lipoprotein eluted from the column 1 via the second pump 15. Here, the reagent for quantifying TG is not particularly limited. For example, enzymes such as ascorbate oxidase, glycerol kinase, glycerol-3-phosphate oxidase, lipoprotein lipase and peroxidase, and quinone coloring dyes are used. An enzyme-dye reagent in combination with the above dye can be used. As quinone coloring dyes, oxidative condensation of N-ethyl-N- (3-methylphenyl) -N'-succinylethylenediamine or N-ethyl-N- (3-sulfopropyl) -m-anisidine and 4-antiaminopyrine. The body is mentioned. As the reagent, for example, commercially available Determiner L TGII (Kyowa Medex Co., Ltd.), L type TG • H (Wako Pure Chemical Industries, Ltd.) reagent can be suitably used.

  The TC reaction unit 5 and the TG reaction unit 6 are each provided with a reaction coil for controlling the reaction temperature between the above-described reagent and TC or TG. In the TC reaction unit 5 and the TG reaction unit 6, the reaction temperature between the above-described reagent and TC or TG is 35 to 50 ° C, preferably 45 to 50 ° C. If the reaction temperature is less than 35 ° C, the reaction tends to be insufficient, and if it exceeds 50 ° C, the enzyme may be deteriorated during the reaction.

  The TC detection unit 7 includes, for example, an ultraviolet-visible light detector for detecting the absorbance of the reaction product generated by the reaction of TC and the reagent in the TC reaction unit 5. The TG detector 8 includes, for example, an ultraviolet-visible light detector for detecting the absorbance of the reaction product generated by the reaction of TG and the reagent in the TG reaction unit 6. For example, when a quinone coloring pigment is used as the reagent described above, the measurement wavelength of the ultraviolet-visible detector may be 540 to 560 nm.

  The system controller 9 has a function of receiving output signals from the TC detection unit 7 and the TG detection unit 8 and outputting a TC chromatogram and a TG chromatogram as a result based on the signals. As the chromatogram output from the system controller 9, for example, as shown in FIG. 2, the horizontal axis is the elution time (min) and the vertical axis is the detection value (mV), and the chromatogram for TC and the chromatogram for TG. Can be displayed in a superimposed manner.

  As the arithmetic unit 10, for example, a computer in which an analysis program to be described later is installed can be used. The computing device 10 is connected to the system controller 9, processes the data of the chromatogram output from the system controller 9 by an analysis program, separates lipoproteins contained in the test sample into, for example, 20 subclasses, and TC. It has a function to calculate the amount and TG amount. The arithmetic device 10 may be connected to the system controller 9 via an information communication network such as the Internet, a LAN, or an intranet.

  According to the lipoprotein analyzer described above, first, various lipoproteins are separated by the column 1 depending on the particle size, and then TC and TG contained in the eluate eluted from the column 1 are quantified. Therefore, according to the lipoprotein analyzer, TC and TG can be quantified for each subclass of lipoprotein depending on the resolution of the column 1.

  Lipoproteins are classified into several classes depending on differences in properties such as particle size, hydration density, and electrophoretic mobility. In this analyzer, lipoproteins are separated into subclasses based on particle size. Specifically, the subclasses are larger than 90 nm (> 90 nm), 64-90 nm, 53.6-75 nm, 44.5-64 nm, 36.8-53.6 nm, 31.3-44.5 nm, 28.6-36.8 nm, 25.5-31.3 nm, 23- 28.6nm, 20.7-25.5nm, 18.6-23nm, 16.7-20.7nm, 15-18.6nm, 13.5-16.7nm, 12.1-15nm, 10.9-13.5nm, 9.8-12.1nm, 8.8-10.9nm, 7.6-9.8nm And 20 subclasses smaller than 8.8 (<8.8). The subclass is preferably larger than 82.5 nm (> 90 nm), 69.5-82.5 nm, 58.8-69.5 nm, 49.05-58.8 nm, 40.65-49.05 nm, 34.05-40.65 nm, 29.95-34.05 nm, 27.05- 29.95nm, 24.25-27.05nm, 21.85-24.25nm, 19.65-21.85nm, 17.65-19.65nm, 15.85-17.65nm, 14.25-15.85nm, 12.8-14.25nm, 11.5-15-12.8nm, 10.35-11.5nm, 9.3- There are 20 subclasses consisting of 10.35 nm, 8.2-9.3 nm and smaller than 8.2 (<8.2). Further, the subclass is more preferably greater than 90 nm (> 90 nm), 75 nm, 64 nm, 53.6 nm, 44.5 nm, 36.56-36.8 nm, 31.3-32.17 nm, 28.0-28.61 nm, 25.4-25.64 nm, 22.9- 23.1nm, 20.6-20.8nm, 18.5-18.7nm, 16.6-16.8nm, 14.9-15.1nm, 13.4-13.6nm, 12.0-12.2nm, 10.8-11.0nm, 9.7-9.9nm, 8.7-8.9nm and 7.46- There are 20 subclasses of 7.6 nm.

  In the lipoprotein analyzer, TC and TG contained in each of the 20 subclasses are quantified by data processing of the chromatogram output from the system controller 9 by an analysis program.

  The analysis program will be described below. The analysis program controls the arithmetic device 10 according to the flowchart consisting of step 1 and step 2.

  First, in step 1, the chromatogram output from the system controller 9 is input as an input signal via the input means of the arithmetic unit 10. That is, in step 1, the analysis program causes the computer to execute as detection means for inputting the chromatogram output from the system controller 9 as an input signal.

  Step 1 will be described in detail. First, when the chromatogram relating to TC and the chromatogram relating to TG as shown in FIG. 2 are input via the input means of the arithmetic unit 10, for example, the memory inherent in the arithmetic unit 10 is stored. These chromatograms and / or numerical data on which the chromatograms are based are stored in a recording medium that can be recorded by the apparatus or the arithmetic unit 10.

  Next, in step 2, the input chromatogram is subjected to waveform processing and separated into 20 subclasses, and a Gaussian approximate waveform is calculated. That is, in step 2, the analysis program causes the computer to execute as waveform processing means for calculating a Gaussian approximate waveform. The chromatogram input in step 1 can be separated into 20 independent peaks by the waveform processing means. In the following description, 20 independent peaks are referred to as G1 to G20 in descending order of size, and each peak is referred to as a component peak. G1 and G2 are component peaks corresponding to chylomicron (CM), G3 to G7 are component peaks corresponding to very low specific gravity (specific gravity) lipoprotein (VLDL), and G8 to G13 are low specific gravity lipoprotein (LDL). ), And G14 to G20 are component peaks corresponding to high-density lipoprotein (HDL). Among the component peaks corresponding to VLDL, G3 to G5 are large VLDL, G6 is medium VLDL, and G7 is small VLDL. Among the component peaks corresponding to LDL, G8 is large LDL, G9 is medium LDL, G10 is small LDL, and G11 to G13 are very small LDL. Among the component peaks corresponding to HDL, G14 and G15 are very large HDL, G16 is large HDL, G17 is medium HDL, G18 is small HDL, and G19 and G20 are very small HDL. .

  The waveform processing means in step 2 is means for separating the chromatogram or numerical data input in step 1 into 20 component peaks and causing the arithmetic unit 10 to execute processing for calculating a Gaussian approximate waveform including G1 to G20. is there. Here, the 20 component peaks are classified according to the size of the lipoprotein.

  Each peak position of the 20 component peaks is defined as follows. For the 20 peaks consisting of G1 to G20, the peak position (elution time) of the reference peak (referred to as an anchor peak) is first determined, and then the peak excluding the anchor peak (extra essential peaks) Peak position) is determined. Specifically, as an example, G5, G6, G7, G9, G10, G15, G17 and G18 are anchor peaks, and G1 to G4, G8, G11 to G14, G16, G19 and G20 are extra essential peaks. FIG. 3 shows an example of data that is the basis for defining G5, G6, G7, G9, G10, G15, G17, and G18 as anchor peaks.

  Since the VLDL size, LDL size, and HDL size are distributed over a certain range in the population of healthy middle-aged men (30-40 years old), the elution positions of G6, G9, and G17 of the anchor peaks are determined (Fig. 3 (a)). More specifically, the chromatogram for TC and the chromatogram for TG as shown in FIG. 2 are obtained using a collected serum sample for a plurality of healthy middle-aged men (30 to 40 years old). In the acquired chromatogram, peaks corresponding to VLDL, LDL, and HDL as major categories appear in this order. Calculate the average value of peak positions corresponding to VLDL, LDL, and HDL in chromatograms obtained for multiple healthy middle-aged men, and elute the average VLDL size, average LDL size, and average HDL size into G6, G9, and G17, respectively. Defined as position (particle size).

  In cases where lipoprotein lipase activity is absent or very low, TG-rich lipoprotein triglycerides are not degraded and VLDL remains large in the blood. Thus, the population of cases with no or very low lipoprotein lipase activity has a significantly larger VLDL size than healthy men and is distributed within a predetermined size range. The average elution position of VLDL is defined as the elution position of G5 in the anchor peak (see FIG. 3 (b)).

  Furthermore, triglyceride is passed from VLDL to LDL by the action of cholesterol ester transfer protein present in the blood, and cholesterol ester is passed from LDL to VLDL instead. LDL becomes triglyceride-rich particles, and triglycerides in LDL are degraded by hepatic lipase, and LDL becomes smaller. The size of this miniaturized LDL is significantly smaller than the LDL size of healthy men and distributed within a certain size range in a population of cases with no or very low lipoprotein lipase activity. Therefore, the average elution position of LDL is defined as the elution position of G10 among the anchor peaks (see FIG. 3 (b)).

  Furthermore, in cases where lipoprotein lipase activity is absent or very low, triglycerides are passed from LDL or VLDL to HDL, and cholesterol esters are passed from HDL to LDL or VLDL instead. As a result, HDL becomes rich in triglycerides, triglycerides in HDL are decomposed by hepatic lipase, and HDL is reduced in size. Thus, in a population of cases with no or very low lipoprotein lipase activity, the size of HDL is significantly smaller than that of healthy males, and the size is also distributed within a certain range. Therefore, the average elution position of HDL is defined as the elution position of G18 in the anchor peak (see FIG. 3 (b)).

  Furthermore, cholesterol ester transfer protein deficiency passes cholesterol ester from HDL to LDL or VLDL, but cannot receive triglycerides from LDL or VLDL instead, so HDL becomes cholesterol ester rich and its size increases. Especially in cholesterol ester transfer protein complete deficiency, there is almost no triglyceride in HDL. The HDL size of cholesterol ester transfer protein deficiency is significantly larger than that of healthy men and distributed within a certain size range. Therefore, the average elution position of HDL is defined as the elution position of G15 in the anchor peak (see FIG. 3 (d)).

  Furthermore, in the case of type III hyperlipidemia of ApoE2 / 2, substitution of 158th Arg of ApoE to Cys results in the LDL receptor (ApoB / E), which is apoE ligand, and LDL receptor related protein. The conformational mutation in the binding region with the VLDL-receptor reduces the uptake of small VLDL (remnant), increases the component corresponding to small VLDL in the blood, and a specific peak is observed. Therefore, the average elution position of VLDL in this case group is defined as the elution position of G7 among the anchor peaks (see FIG. 3 (c)).

  The data shown in FIG. 3 is data obtained using a TSKgel Lipopropal XL column (manufactured by Tosoh Corporation), but other columns are used as the data used as the basis for defining the anchor peak. You may use the data obtained.

  For example, as shown in FIG. 4, data can be similarly obtained using a Superose 6HR 10/30 column (manufactured by Amersham Pharmacia), and an anchor peak can be defined based on this data. In this case, the elution positions of G9 and G17 can be defined from the profile of healthy middle-aged men (30-40 years old) (FIG. 4 (a)). From the profile of cases with no or very low lipoprotein lipase activity, the elution positions of G10 and G18 can be defined (FIG. 4 (b)). The elution position of G7 can be defined from the profile of ApoE2 / 2 type III hyperlipidemia case (FIG. 4 (c)). The elution position of G15 can be defined from the complete defect profile of cholesterol ester transfer protein (FIG. 4 (d)).

  As described above, the elution positions are defined with G5, G6, G7, G9, G10, G15, G17 and G18 as anchor peaks.

  Next, for extra essential peaks, the position and width of the peak are determined mathematically. Extra essential peaks are necessary for analyzing component peaks by Gaussian approximation with fixed component peak size and distribution (time and width fixed). The distribution width of the lipoprotein subclass corresponding to extra essential peaks is assumed to be approximately the same in LDL and HDL, and the anchor peaks are filled at approximately equal intervals. Four extra essential peaks (G11-14) are set between G10 and G15, one extra essential peak (G8) is set between G7 and G9, and 1 between G15 and G17. Two extra essential peaks (G16) are set, and two extra essential peaks (G19 and G20) are set after G18. In addition, the position of extra essential peaks (G16-20) belonging to HDL can be defined with reference to the correspondence between the peak observation frequency of the healthy population and the experimental value by rechromatography in the analysis using another HDL dedicated column. .

  In addition, the component peaks G8 to G20 were determined so that their positions were almost equally spaced and equal in width. Furthermore, component peaks G2, G3, and G4 are necessary for Gaussian approximation between Void G1 and anchor peak G5, and were determined from the rules of peak interval and width.

  Furthermore, the minimum value of the component peak width can be defined as the FG (particle size of a single molecular weight 92) width obtained by the analysis system, and the maximum value can be defined as twice the interval between adjacent peaks.

  For 20 component peaks, the peak width can be set as a numerical value represented by SD (minutes) = half-width of peak (seconds) ÷ 143 * 60. Specifically, the peak width of 20 component peaks is 0.33 min for G01, 0.40 min for G02, 0.55 min for G03, 0.55 min for G04, 0.55 min for G05, 0.50 min for G06, 0.40 min for G07, G08 0.38 min for G09, 0.38 min for G10, 0.38 min for G11, 0.38 min for G12, 0.33 min for G13, 0.33 min for G14, 0.33 min for G15, 0.38 min for G16, 0.38 min for G17, G18 0.38 min for G19, 0.38 min for G19, and 0.48 min for G20 are input or preset.

  The waveform processing means in step 2 can be executed by applying a Gaussian waveform processing calculation algorithm, for example. According to the Gaussian waveform processing calculation algorithm, it can be separated into 20 component peaks as follows.

That is, first, assuming that the shape of a single peak on the chromatogram is symmetric gaussian distribution, the peak height h (t) at time t uses the peak position T and the width (standard deviation) σ.
h (t) = H × exp (-(tT) ² / 2σ ² )
(H is the maximum peak height). Other peak shapes are (1) Peason VII, (2) Lorentzian, (3) exponentially modified Gaussian, (4) Weibull, (5) bi-Gaussian, (6) poisson, (7) Gram-Charlier, (8) combination of Gauss and Cauchy functions, (9) combination of statistical moments, (10) cam-driven analog peak, etc. are known and assumed to be in any form of (1)-(8) It is also possible to do.

The height hn (t) of the nth peak is determined by using the position Tn of the nth peak and the width (standard deviation) σn.
hn (t) = Hn × exp (-(t-Tn) ² / 2σn ² )… I
(Hn is the n-th peak maximum value (height)).

Where exp (-(t-Tn) ² / 2σn ² ) = Gn (t)
hn (t) = Hn × Gn (t)… II
Can be written.

Assuming that the N peaks are independent, the combined waveform A (t) at time t is
A (t) = h1 (t) + h2 (t) + ... + hn-1 (t) + hn (t)
= H1 × G1 (t) + H2 × G2 (t) + ・ ・ ・ ・ + Hn-1 × Gn-1 (t) + Hn × Gn (t)… III
It becomes.

  If the number of data points is m, the formula III is multiplied by m as shown below.

A (t1) = H1 × G1 (t1) + H2 × G2 (t1) + ・ ・ ・ ・ + Hn-1 × Gn-1 (t1) + Hn × Gn (t1)
A (t2) = H1 × G1 (t2) + H2 × G2 (t2) + ・ ・ ・ ・ + Hn-1 × Gn-1 (t2) + Hn × Gn (t2)
...
A (tm) = H1 × G1 (tm) + H2 × G2 (tm) + ・ ・ ・ ・ + Hn-1 × Gn-1 (tm) + Hn × Gn (tm)
If the actual chromatogram waveform at time t is R (t), the number of peaks n, the peak position T, and the width (standard deviation) σ such that R (t) = A (t) is obtained. fitting method. Actually, R (t) = A (t) does not become true at all times by the non-linear least-squares method, so a parameter that minimizes the sum of (R (t) −A (t)) 2 is obtained.

  In addition to the curve fitting method, for example, an iterative method (Fletcher Powell, Marquardt, Newton-Raphson, Simplex minimization, Box-Complex method, etc.) can also be applied. However, in methods other than the curve fitting method, the initial value affects the calculation result, the waveform (Gaussian or Lorentzian) must be assumed in advance, and the number of peaks is large (4 or more) The difficulty is that it is difficult to converge. Therefore, how to find an initial value close to the true value is the point, and peak separation methods to clear these drawbacks are (1) factor analysis, (2) moments analysis, (3) orthogonal polynominal analysis, ( 3) Inverse diffusion models have been recently reported and can be applied to this algorithm.

Here, since ti (i = 1, 2,..., M) is a constant, any Gn (ti) is also a constant. Then, the above formula III is
A (t1) = H1 × G1 (t1) + H2 × G2 (t1) + ・ ・ ・ ・ + H19 × Gn-1 (t1) + H20 × G20 (t1)
A (t2) = H1 × G1 (t2) + H2 × G2 (t2) + ・ ・ ・ ・ + H19 × Gn-1 (t2) + H20 × G20 (t2)
...
A (tm) = H1 × G1 (tm) + H2 × G2 (tm) + ・ ・ ・ ・ + H19 × G19 (tm) + H20 × G20 (tm)
You can make m. If R (t) = A (t), m primary expressions composed of 20 unknowns H1, H2,..., H19, H20 can be formed. If m = 20, the solution can be found by solving the linear simultaneous equations.

  In actual data, the number of data points is not 20, but in this algorithm, 20 points that are easy to calculate for high-speed processing (for example, 20 peak positions in 20 subcrumbs) are selected for convenience. To do. In this algorithm, the number of data points can be determined by the least square method without selecting 20 points.

  According to the flowchart consisting of Step 1 and Step 2 described above, an approximate waveform consisting of peaks corresponding to 20 subclasses is calculated from the chromatogram output from the system controller 9 (for example, the chromatogram shown in FIG. 2). can do.

  In the analysis method according to the present invention, based on the approximate waveform obtained by the above analysis program, the amount of cholesterol contained in the small particle size low density lipoprotein in the peak corresponding to the low density lipoprotein is then determined. Calculate the total. Here, the small particle size low specific gravity lipoprotein means a low specific gravity lipoprotein having a relatively small particle size among the low specific gravity lipoproteins. More specifically, the small particle diameter low specific gravity lipoprotein means a subclass having an average particle diameter of the low specific gravity lipoprotein or less. In the example described above, the peak corresponding to the low density lipoprotein is a peak of G08 to G13, and the average particle diameter of the low density lipoprotein can be 25.5 nm. That is, in the above-described example, the small particle size low specific gravity lipoprotein corresponds to the peak of G10 to G13. Moreover, as a small particle diameter low specific gravity lipoprotein, you may define as a peak of G11-G13.

  Here, the total amount of cholesterol contained in each subclass can be calculated by an arithmetic processing means having an integration circuit using the numerical data of the approximate waveform calculated as described above as an input value.

  Next, in the analysis method according to the present invention, the total amount of cholesterol calculated in the above step is compared with a reference value. Here, as a reference value, as an example, among the peaks corresponding to the low specific gravity lipoprotein measured in the group of healthy subjects, the subclass (G10 to G13 peak or G11 to G10 It can be the average value of the total amount of cholesterol contained in the peak of G13). As an example, 20 mg / dl can be used as the reference value as the average value. By setting the value calculated in this way as an average value, it is possible to compare the amount of total cholesterol contained in subclasses having an average particle size of the low specific gravity lipoprotein or less between the healthy subject group and the diabetic patient group. As a result of the comparison, in the test sample derived from the diabetic patient to be tested, whether the total cholesterol amount contained in the subclass of the average particle size of the low specific gravity lipoprotein is below the reference value or above the reference value. Can be determined.

  With the analysis method according to the present invention, information for determining the risk of macrovascular disorder in a diabetic patient can be acquired. In other words, for diabetics whose total cholesterol content in the subclasses of the low-density lipoprotein less than the average particle size exceeds the reference value, there is a possibility of causing a major vascular disorder or shifting to a major vascular disorder Can be determined to be high.

  Here, the macrovascular disorder can be paraphrased as a disorder or disease associated with an increase in IMT (carotid intima-media thickness). Generally, IMT is a value measured by carotid echocardiography, and is conventionally used to determine the risk of macrovascular disorders. Examples of the disorder associated with an increase in IMT include cerebrovascular disorder and peripheral neuropathy. Examples of the disorder associated with an increase in IMT include ischemic heart disease and coronary artery disease.

  EXAMPLES Hereinafter, although an Example demonstrates this invention in detail, the technical scope of this invention is not limited to a following example.

[Example 1]
In this example, blood samples collected from 45 diabetic patients with hyperlipidemia (26 males, 19 females, average age 53.2 years old) undergoing outpatient treatment as a diabetic patient group were collected. In addition, blood samples collected from 299 medical checkup subjects (186 men, 113 women, average age 46.3 years) were collected as a group of healthy subjects.

  For each of these groups, the clinical indices of age, disease duration, and body mass index (BMI) were investigated. For each of these groups, fasting blood glucose levels (FPG) and glycated hemoglobin concentrations (HbA1c) were measured as biochemical tests. For fasting blood glucose level (FPG), use fully automatic glucose measuring device GA-1160 (ARKRAY Co., Ltd.), and for glycohemoglobin concentration (HbA1c), use fully automatic glycohemoglobin measuring device HA-8150 (ARKRAY CO., LTD.). And measured.

In addition, using the analyzer shown in FIG. 1, each of these groups was analyzed for lipoproteins, and the total cholesterol level (TC) in blood, the total triglyceride level (TG) in blood, and the high specific gravity lipoprotein in blood. The total cholesterol content (HDL-C) contained in the protein and the total cholesterol content (LDL-C) contained in the low density lipoprotein in the blood were measured. Further, the profile obtained by the analyzer is divided into 20 subclasses by the analysis program described above, and calculated from the component peaks of G11 to G13. The total cholesterol amount (chol) contained in the diameter LDL) was measured. Furthermore, the average particle diameter of the low specific gravity lipoprotein was measured from the elution position of the low specific gravity lipoprotein using the profile obtained by the analyzer shown in FIG. The results are shown in Table 1. In Table 1, * is p <0.001, and ** is p <0.01.

  From the results shown in Table 1, it was revealed that in the diabetic patient group, the total amount of cholesterol contained in the small particle size LDL was significantly larger than that in the healthy subject group. Therefore, the diabetic patient group is divided into a group in which the total amount of cholesterol contained in the small particle size LDL is 20 mg / dl or more and a group in which the total is less than 20 mg / dl, and the average of the maximum value of IMT in each group Values were calculated and compared.

  IMT was measured using an ultrasonic diagnostic apparatus Logiq7 (Yokogawa GE Medical) according to the instrument usage manual.

The results are shown in Table 2. In Table 2, * is p <0.001, and ** is p <0.01.

  From the results shown in Table 2, in the group in which the total amount of cholesterol contained in the small particle size LDL is 20 mg / dl or more, the maximum value of IMT is significant compared to the group in which the total is less than 20 mg / dl. It was great.

Moreover, from the results shown in Table 1, in the diabetic patient group, it became clear that the average particle size of the low specific gravity lipoprotein is significantly smaller than that in the healthy subject group. Therefore, the diabetic patient group is divided into a group in which the average particle size of low-density lipoprotein is 25 nm or more and a group in which the average particle size is less than 25 nm, and the average value of the maximum value of IMT in each group is calculated and compared . The results are shown in Table 3. In Table 3, * is p <0.001, and ** is p <0.05.

  From the results shown in Table 3, in the group in which the average particle size of the low specific gravity lipoprotein was less than 25 nm, the maximum value of IMT was significantly larger than that in the group in which the average particle size was 25 nm or more. .

In addition, the diabetic patient group is divided into a group in which the maximum value of IMT is less than 1.0 mm and a group in which the maximum value is 1.0 mm or more, and the total and low amount of cholesterol contained in the small particle diameter LDL in each group. The average particle size of specific gravity lipoprotein was compared. The results are shown in Table 4. In Table 4, * is p <0.01, and ** is p <0.05.

  From the results shown in Table 4, in the diabetic patient group in which the maximum value of IMT is 1.0 mm or more, the small particle diameter LDL is included in the diabetic patient group in which the maximum value is less than 1.0 mm. It was revealed that the total amount of cholesterol was significantly large, and the average particle size of low density lipoprotein was significantly small. From the above results, for the diabetes patient to be examined, an approximate waveform divided into 20 subclasses by the above-described analysis program is calculated, and the total amount of cholesterol contained in the subclasses having an average particle size of the low specific gravity lipoprotein or less. Was found to correlate with the maximum value of IMT. Therefore, according to the present example, the new knowledge that the risk of macrovascular damage that has been conventionally determined by the maximum value of IMT can be determined by the total amount of cholesterol contained in subclasses having an average particle size of low specific gravity lipoprotein or less. I was able to get it.

  All publications, patents and patent applications cited herein are incorporated herein by reference in their entirety.

Claims (24)

  A lipoprotein analysis method for discriminating a large blood vessel disorder by analyzing a small particle size low specific gravity lipoprotein contained in a test sample.   The analysis method according to claim 1, wherein the test sample is collected from a diabetic patient. Analysis of the above small particle size low specific gravity lipoprotein
Separating the lipoprotein contained in the test sample by liquid chromatography and detecting a signal derived from a component contained in the separated lipoprotein;
Assuming that at least low-density lipoprotein is composed of a plurality of subclasses defined by the particle diameter, using the detected signal, calculating an approximate waveform consisting of peaks corresponding to each subclass;
Based on the obtained approximate waveform, among the peaks corresponding to the low density lipoprotein, calculating the total amount of the above components contained in the small particle size low density lipoprotein,
Comparing the calculated total amount with a reference value;
The analysis method according to claim 1, further comprising:   The analysis method according to claim 3, wherein the small particle size low specific gravity lipoprotein is a subclass having an average particle size equal to or smaller than the low specific gravity lipoprotein calculated from the signal.   The analysis method according to claim 4, wherein the lipoprotein has an average particle diameter of 25.5 nm.   The low-density lipoprotein has a peak at an elution position of 28.0-28.61 nm, a peak at an elution position of 25.4-25.64 nm, a peak at an elution position of 22.9-23.1 nm, and an elution position of 20.6-20.8 in the approximate waveform. 4. The analysis method according to claim 3, wherein the analysis method is assumed to consist of a peak at nm, a peak at an elution position of 18.5-18.7 nm, and a peak at an elution position of 16.6-16.8 nm.   In the above approximate waveform, the small particle size low specific gravity lipoprotein has a peak at an elution position of 22.9-23.1 nm, a peak at an elution position of 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm, and an elution position. The analysis method according to claim 6, which is a subclass corresponding to a peak of 16.6-16.8nm.   The small particle size low specific gravity lipoprotein is a subclass corresponding to the peak having an elution position of 20.6-20.8 nm, the peak having an elution position of 18.5-18.7 nm, and the peak having an elution position of 16.6-16.8 nm in the above approximate waveform. The analysis method according to claim 6, wherein:   The analysis method according to claim 3, wherein the component contained in the lipoprotein is cholesterol and / or triglyceride.   The approximate waveform above shows a peak with an elution position greater than 90 nm, a peak with an elution position of 75 nm, a peak with an elution position of 64 nm, a peak with an elution position of 53.6 nm, a peak with an elution position of 44.5 nm, and an elution Peak at position 36.56-36.8m, peak at elution position 31.3-32.17nm, peak at elution position 28.0-28.61nm, peak at elution position 25.4-25.64nm, elution position 22.9-23.1nm Peak, elution position 20.6-20.8 nm, elution position 18.5-18.7 nm peak, elution position 16.6-16.8 nm peak, elution position 14.9-15.1 nm peak, elution position Is a peak at 13.4-13.6 nm, a peak at an elution position of 12.0-12.2 nm, a peak at an elution position of 10.8-11.0 nm, a peak at an elution position of 9.7-9.9 nm, and an elution position of 8.7-8.9 nm The component according to claim 3, characterized in that it consists of a peak and a peak whose elution position is 7.46-7.6 nm. Analysis method.   The reference value is an average value of the total of the components contained in the small particle size low density lipoprotein among the peaks corresponding to the low density lipoprotein measured in the healthy subject group. 3. The analysis method according to 3.   4. The analysis method according to claim 3, wherein the component contained in the lipoprotein is cholesterol, and the reference value is 20 mg / dl.   The analysis method according to claim 1, wherein the macrovascular disorder is a disorder or disease associated with an increase in carotid intima-media thickness.   The analysis method according to claim 13, wherein the disorder is a cerebrovascular disorder and / or a peripheral neuropathy, and the disease is an ischemic heart disease and / or a coronary artery disease. Liquid chromatography for separating multiple classes of lipoproteins contained in a test sample;
Detection means for detecting a signal derived from a component contained in the lipoprotein separated by the liquid chromatography;
Assuming that at least low specific gravity lipoprotein is composed of a plurality of subclasses defined by the particle diameter, and using the detected signal, approximate waveform calculating means for calculating an approximate waveform consisting of peaks corresponding to each subclass; ,
Based on the obtained approximate waveform, among the peaks corresponding to the low density lipoprotein, a total amount calculating means for calculating the total amount of components contained in the small particle size low density lipoprotein,
A comparison processing means for comparing the calculated total value with a reference value,
A lipoprotein analyzer for distinguishing macrovascular disorders in diabetic patients.   16. The total amount calculating means according to claim 15, wherein the total amount is calculated by setting a subclass having a particle size equal to or less than an average particle size of the low specific gravity lipoprotein calculated from the signal as the small particle size low specific gravity lipoprotein. Analysis equipment.   The analyzer according to claim 16, wherein the total amount calculating means sets the average particle size of the lipoprotein to 25.5 nm.   The approximate waveform calculating means includes the low-density lipoprotein, a peak at an elution position of 28.0-28.61 nm, a peak at an elution position of 25.4-25.64 nm, a peak at an elution position of 22.9-23.1 nm, and an elution position The approximate waveform assumed to be composed of a peak at 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm, and a peak at an elution position of 16.6-16.8 nm is calculated. Analysis equipment.   The above total amount calculation means comprises a small particle size low specific gravity lipoprotein having a peak at an elution position of 22.9-23.1 nm, a peak at an elution position of 20.6-20.8 nm, and an elution position of 18.5-18.7 nm in the above approximate waveform. 19. The analyzer according to claim 18, wherein the total amount is calculated by defining that the peak is a subclass corresponding to a peak whose elution position is 16.6-16.8 nm.   The total amount calculating means comprises a small particle size low specific gravity lipoprotein having a peak at an elution position of 20.6-20.8 nm, a peak at an elution position of 18.5-18.7 nm and an elution position of 16.6-16.8 nm in the approximate waveform. 19. The analyzer according to claim 18, wherein the total amount is calculated by defining that the subclass corresponds to a certain peak.   The analyzer according to claim 15, wherein the detection means includes a cholesterol reaction unit that quantifies cholesterol contained in the lipoprotein and a triglyceride reaction unit that quantifies triglyceride contained in the lipoprotein.   The approximate waveform calculation means includes the lipoprotein, a peak with an elution position greater than 90 nm, a peak with an elution position of 75 nm, a peak with an elution position of 64 nm, a peak with an elution position of 53.6 nm, and an elution position The peak at 44.5 nm, the peak at elution position 36.56-36.8 nm, the peak at elution position 31.3-32.17 nm, the peak at elution position 28.0-28.61 nm, the peak at elution position 25.4-25.64 nm, Peak at elution position 22.9-23.1 nm, peak at elution position 20.6-20.8 nm, peak at elution position 18.5-18.7 nm, peak at elution position 16.6-16.8 nm, elution position 14.9-15.1 Peak at nm, peak at elution position 13.4-13.6 nm, peak at elution position 12.0-12.2 nm, peak at elution position 10.8-11.0 nm, peak at elution position 9.7-9.9 nm, elution It consists of a peak whose position is 8.7-8.9nm and a peak whose elution position is 7.46-7.6nm. Analyzer according to claim 15, wherein the calculating the assumed approximate waveform as.   The comparison processing means uses, as a reference value, an average value of the total of the components contained in the small particle size low density lipoprotein among the peaks corresponding to the low density lipoprotein measured in the healthy subject group. The analyzer according to claim 15, characterized in that:   16. The analyzer according to claim 15, wherein the component contained in the lipoprotein is cholesterol, and the comparison processing means sets 20 mg / dl as the reference value.

Images