JP5973181B2 - Asthma inspection method, inspection apparatus, and program - Google Patents

Description

  The present invention relates to a test method, a test apparatus, and a program for asthma.

  Asthma is a respiratory disease that causes excessive secretion of mucus and airway constriction due to chronic inflammation of airway (bronchial) hypersensitivity. Asthmatic patients are characterized by symptoms such as paroxysmal wheezing, shortness of breath, cough, and dyspnea. The number of patients is said to be over 100 million worldwide.

  However, it is known that asthma often has multiple factors and symptoms intertwined, making it difficult to diagnose. For this reason, guidelines for diagnosis and treatment have been proposed in various countries, including the global initiative GINA (Global Initiative for Asthma).

  However, such guidelines provide diagnostic criteria that depend solely on symptoms and the like, and the use of these guidelines does not necessarily make a definitive diagnosis. For example, in GINA, the incidence of asthma is determined according to qualitative criteria based on subjective symptoms such as seizure frequency and quantitative criteria such as measurements after administration of bronchodilators (respiratory hypersensitivity and airway reversibility test). The presence or absence (degree of severity) is judged. When using such diagnostic criteria, it is difficult to make a diagnosis for patients who do not have typical symptoms. Therefore, there is a possibility that the patient cannot receive appropriate diagnosis and treatment at an early stage. In addition, asthma has a different treatment policy depending on the severity, so if an ambiguous classification is used, the burden and risk of the patient increases. However, asthma has not yet established a definitive diagnostic standard, and the actual diagnosis and judgment of severity depend on these guidelines.

  Therefore, in recent years, diagnostic methods based on gene-level approaches have been developed. For example, Reference 1 discloses a method for measuring the expression level of an indicator gene related to differentiation / proliferation of airway epithelial cells into goblet cells.

JP 2004-121218 A

  By the way, there is chronic obstructive pulmonary disease (COPD) as a disease exhibiting symptoms similar to bronchial asthma. Originally, COPD is defined as airflow obstruction caused by chronic bronchitis, emphysema, or a combination of both, and bronchial asthma and COPD are simply categorized by whether airway obstruction is irreversible. However, since the patient's pathology is often complicated by the merger of the two, the judgment is extremely difficult, and bronchial asthma and COPD cannot be clearly separated even by the method described above.

  Thus, it is desired to develop an excellent test method that is a clear guideline for determining the presence or absence of asthma and its severity.

  Therefore, an object of the present invention is to provide a test method for determining the presence or absence of asthma and its severity.

  As a result of intensive studies in order to solve the above-mentioned problems, the present inventors have found a leukocyte migration dynamic characteristic of particularly asthmatic patients, and have completed the present invention based on this finding.

That is, the test method for asthma according to the present application is a test method for asthma for obtaining an index of asthma diagnosis, and measures the average value of the migration speed of each leukocyte collected from the subject with respect to the chemotactic factor ( indomethacin) . A step of taking a distribution of the average value of the traveling speed, and a step of detecting an average value of the traveling speed at a predetermined percentage point of the distribution.

  It is possible to provide a test method for determining the presence or absence of asthma and its severity.

1 is a schematic configuration diagram of an inspection system 1. FIG. 2 is a perspective view of a silicon wafer 112. FIG. It is a schematic explanatory drawing of the cell information table 2220. 5 is a schematic explanatory diagram of reference information 2230. FIG. 4 is a flowchart showing a flow of processing of a control unit 21 of the inspection device 20. It is a graph which shows the kinetics of eosinophil migration for each patient and healthy subject for indomethacin. It is a graph which shows the approximate curve of the kinetics of the eosinophil of an affected group of each GINA step, and a healthy subject group. It is a graph which shows the kinetics of eosinophil migration for each patient and healthy subject for prostaglandins. 3 is a block diagram showing an electrical configuration of the inspection apparatus 20. FIG.

  The test method for asthma according to the present invention includes a step of measuring an average value of the migration speed of each leukocyte collected from a subject with respect to a chemotaxis factor, a step of taking a distribution of the average value of the migration speed, a predetermined value of the distribution Detecting an average value of the traveling speed at the percentage point.

  In addition to the above steps, the step of determining whether or not the detected average value of the migration speed at the predetermined percentage point is included in a predetermined range determined according to the presence or absence of asthma in the subject. including.

  The predetermined percentage point and the predetermined range are determined by measuring, as control sample data, the migration kinetics of leukocytes collected from a plurality of groups of asthma patients and healthy groups in advance for chemotactic factors. can do. In the present invention, these were derived by using leukocytes derived from the group of asthma patients and the group of healthy individuals at each step whose severity was evaluated based on GINA. In the present invention, the inspection method of the present invention can be performed on leukocytes collected from a subject after setting at least the predetermined percentage point.

  The predetermined range (hereinafter referred to as a reference range) is a range of leukocyte migration speeds used for determination of the presence and severity of asthma. That is, in the test method of the present invention, the severity is quantitatively determined based on the migration rate of leukocytes.

  In the present specification, asthma patients classified by severity are asthma patients evaluated in the so-called GINA step defined in GINA (revised edition). According to the GINA step, the severity of asthma patients can be as follows: “Minor intermittent type (Step 1)”, “Mild type persistent type (Step 2)”, “Moderate persistent type (Step 3)”, “Severe persistent type (Step 4) ”.

  In GINA step 1 intermittent asthma, symptoms usually appear less than once a week. In general, GINA step 1 asthma patients do not need to be administered daily, but only when there is an increase in eosinophils in the blood and sputum and when there are slightly asthma symptoms (eg 1-2 times a month) When there is an increase in eosinophils in the middle or sputum, administration of any one of an inhaled steroid drug (low dose), a theophylline sustained-release preparation, a leukotriene receptor antagonist, DSCG, or an antiallergic drug is considered.

  In GINA step 2 mild persistent asthma, symptoms appear from once a week to about once a day. The recommended main medication is treatment with inhaled steroids (low doses). When this is insufficient, the combined use of any one of theophylline sustained-release preparation, leukotriene receptor antagonist, long-acting β2 stimulant, DSCG, and antiallergic agent is considered.

  In GINA step 3 moderate persistent asthma, symptoms appear daily. Recommended main pharmacotherapy is continuous use of medium-dose inhaled steroids and theophylline sustained-release preparations, leukotriene receptor antagonists, long-acting inhaled β2-stimulants, or a combination of several .

GINA step 4 severe persistent asthma appears daily and is often exacerbated even under treatment. The recommended main pharmacological therapy includes continuous use of high-dose inhaled steroids and any one of theophylline sustained-release preparations, leukotriene receptor antagonists, long-acting inhaled β2-stimulants, and Th ₂ cytokine inhibitors Or a combination of several. If this is still poorly managed, oral steroids are added.

  In the present specification, chemotaxis refers to a phenomenon in which leukocytes, particularly eosinophils, move in a certain direction according to the concentration gradient of chemotactic factors. Leukocyte chemotactic factor secretion is essential for leukocyte migration. In many cases, leukocytes recognize the concentration of a factor via a receptor, migrate in a deep direction, and gather at an inflammatory site.

  As used herein, migration refers to the migration of white blood cells, particularly eosinophils.

In the present specification, eosinophils refer to granulocytes that occupy about 5% or less of leukocytes in peripheral blood and that are filled with condylar acidophilic granules in the cytoplasm. Eosinophils generally have migratory and phagocytic properties and control allergic reactions.
<First Embodiment>
Hereinafter, a method for measuring the migration rate of leukocyte chemotaxis factors according to the present application will be described.

  In the present invention, first, using the test system 1, measurement is performed by an asthma patient group of each severity and a group of healthy persons according to the GINA step or other asthma guidelines. Then, the percent point, class and reference range necessary for the test of the subject are set.

(Sample adjustment)
First, biological samples are collected from a group of asthma patients of each severity according to the GINA step or other asthma guidelines, and a group of healthy individuals. As long as the biological sample is a sample from which white blood cells can be collected, such as body fluids such as whole blood, sputum, nasal discharge, saliva, spinal fluid, and other tissues, the type and collection method thereof are not limited.

  Next, eosinophils are separated from the collected biological sample. As a method for extracting eosinophils from these samples, any method known in the art may be used. For example, when the biological sample is whole blood, erythrocytes are precipitated from the sample by centrifugation, and a leukocyte fraction is taken out. Further, granulocyte (basophil, neutrophil, eosinophil) components are separated from the leukocyte fraction by centrifugation, and the remaining erythrocytes are hypotonically dissolved and washed, and then the erythrocyte membrane is removed. Thereafter, if a commercially available extraction kit is used, unnecessary cells can be removed and only eosinophils can be easily extracted. Of course, the eosinophils may be extracted by any method other than the above.

  Examples of chemotactic factors include indomethacin and prostaglandins, and are selected from protein / peptide chemotactic factors and lipid chemotactic factors.

  About the sample adjusted in this way, the migration kinetics with respect to the chemotactic factor of an eosinophil is each measured using the following test | inspection systems.

(Measurement of chemotaxis)
FIG. 1 shows a schematic configuration diagram of the inspection system 1. The inspection system 1 includes an observation device 10 for observing cells and an inspection device 20 for analyzing cell migration dynamics from images observed by the observation device 10.

  The observation device 10 includes a holder 11 for accommodating a sample, an imaging device 12 for measuring cell migration dynamics, and a sample injector 13.

  The holder 11 constitutes a square sample storage space 111 partitioned by a partition 11a and a partition 11b. The silicon wafer 112 and the glass plate 113 can be detachably fitted in the bottom of the sample storage space 111 without any gap. In addition, a hole that allows the imaging device 12 to directly observe the glass plate 113 is provided on the bottom surface of the holder 11.

  Here, the silicon wafer 112 will be described in detail. FIG. 2 shows a perspective view of the silicon wafer 112.

  A rectangular groove 112 a is formed in the silicon wafer 112. At the time of observation, the glass plate 113 is put on the opening side of the groove 112a, and the silicon wafer 112 is set on the holder 111 with the glass plate 113 side down (see FIG. 1).

  A terrace 112b is provided in the center of the groove 112a to divide the groove 112a in the short direction. The terrace 112b has a height lower than the edge of the groove 112a (for example, about 20 μm), and the sample filled in the groove 112a can move on the terrace 112b. On the terrace 112b, a plurality of minute blocks 112c having a height to the edge of the groove 112a (that is, about 20 μm) are arranged. By covering the silicon wafer 112 with the glass plate 113, the terrace 112b A channel (flow path) is formed between the glass plate 113 and the glass plate 113. The shape of the channel is not limited to this, and by changing the height and width of the terrace 112b and the size and position of the block 112c, a channel having the size and shape most suitable for the cell to be observed may be freely formed. .

  A well 112d, which is a through hole, is formed on the bottom surface on both sides of the groove 112a across the terrace 112b. When the well 112 d is set in the holder 11, it communicates with the sample storage space 111. Although FIG. 2 shows a silicon wafer having 12-wells, it may have a structure having any number of wells.

  The imaging device 12 is a camera 122 to which a microscope 121 is attached, and images the terrace 112b of the silicon wafer 112 set on the holder 11 through the glass plate 113 at every predetermined timing. The imaging interval can be freely set by the user. Note that the image captured by the imaging device 12 is output to the inspection device 20.

  The sample injector 13 injects a sample into the well 112d. The sample is, for example, a solution containing cells to be observed or a solution containing chemotactic factors.

  According to such an observation apparatus 10, the cell accommodating space 111 and the silicon wafer 112 are filled with a liquid that does not affect cell chemotaxis (for example, a buffer solution), and then the sample injector 13 is filled in one well. By injecting the chemotactic factor in (1), a concentration gradient of the chemotactic factor can be formed in the channel (flow path). Thereafter, the cells are injected into the other well paired with the well into which the chemotactic factor has been injected, and the channel (flow channel) is time-lapse imaged with the imaging device 12 for a predetermined time, so that Chemotactic migration dynamics can be observed.

  The observation device 10 has a temperature adjustment function that allows the user to keep the temperature in the holder 11 at a set value by setting an arbitrary temperature via the input unit 24 of the inspection device 20 described later. Have. Further, it is assumed that a position adjustment function for moving the holder 11 and the imaging device 12 to a position set by the user is also provided.

(Analysis of migration dynamics)
The inspection apparatus 20 determines the presence or absence of asthma and its severity from a series of images obtained by time-lapse observation.

  The inspection device 20 includes a control unit 21 that controls the inspection device 20, a storage unit 22 that stores captured images and information required for processing, a display unit 23 that displays information to the user, and various settings from the user. And an input / output interface unit (hereinafter referred to as I / F unit) 25 that enables input / output of information.

  The display unit 23 is a marking device such as an LCD (Liquid Crystal Display), and displays an image based on the supplied image signal.

  The input unit 24 is a user interface such as a keyboard and a mouse, for example, and accepts various settings and instructions from the user.

  An I / F (input / output interface) unit 25 connects the control unit 21 to other functional units, devices, and networks so as to be able to transmit and receive data.

  The storage unit 22 includes an image information storage area 221, a cell information storage area 222, and a determination criterion information storage area 223.

  The image information storage area 221 stores frame images captured by the imaging device 12 at predetermined timings in chronological order.

  The cell information storage area 222 stores a cell information table 2220 as shown in FIG. The cell information table 2220 stores a cell ID storage area 2221 for storing an identifier for identifying each cell existing on a frame image constituting a series of time-lapse images, and an identifier for identifying each frame image. A frame image ID storage area 2222 and a cell coordinate position storage area 2223 in which the coordinate position of the center of gravity in each frame image of each cell is stored. From such a cell information table 2220, it is possible to grasp which cell is located at which coordinate in which frame image.

  The criterion information storage area 223 stores criterion information 2230 as shown in FIG. 4 that serves as a criterion for determining the presence or absence of asthma and its severity. This includes a percent point storage area 2231 that represents a reference percent point in the cell distribution described later, the presence / absence of asthma and its severity class, and the range of eosinophil migration speed according to the class. And a determination table 2232 in which a reference range to be expressed is associated and stored. For reference, FIG. 4 illustrates which GINA step the class corresponds to, but each class does not necessarily correspond to the GINA step, and it is not necessary. Details will be described later.

  The control unit 21 analyzes the frame image and tracks each cell in the image, the statistical processing unit 212 for deriving a distribution relating to the migration speed of the cells, the percent point, the class, and the reference range from the sample data. It comprises an analysis processing unit 213 to be set, and a determination processing unit 214 for determining the presence or absence of asthma and the severity of the subject.

  The image analysis unit 211 acquires 1 to f frame images output from the imaging device 12 at predetermined timings for a predetermined time, stores them in the storage unit 22, recognizes each cell, and outlines the cell. The center of gravity and the like are detected, and the cell information table 2220 is created.

  Specifically, when receiving the frame image, the image analysis unit 211 first performs a cell recognition process of extracting an image region corresponding to each cell from each frame image. Any method may be used for the cell recognition process. As an example, first, an image is binarized with a threshold value that changes intermittently, and an edge is extracted at each stage. Next, the contour image of the cell is created by superimposing such edges, and the outline of the cell is extracted from the contour image to identify the cells (1 to m) in the image. As another method, for example, each cell region is detected by dividing an image with a predetermined mesh and binarizing each mesh value with a predetermined threshold, and then detecting a region where a predetermined gradation continues. There is a way.

  Next, the image analysis unit 211 detects the position of the center of gravity of each cell region. The position of the center of gravity can be calculated by, for example, extracting a plurality of coordinates on the contour of the cell region at predetermined intervals and taking the coordinate average value.

  Then, when the frame image is the first frame image (first frame), the image analysis unit 211 assigns a unique cell ID to each cell. A cell ID storage area 2221 for identifying the cell ID, a frame image ID storage area 2222 for storing a frame image ID for identifying the number of frames 1 to f captured during the observation time, and each cell A new cell information table 2220 having a cell coordinate position storage area 2223 in which the coordinates of the center of gravity in the nucleus frame image of the image are stored and stored in the cell information storage area 222 of the storage unit 22 (see FIG. 3). .

  On the other hand, when the frame image is not the first frame image (the 2nd to fth frames), the image analysis unit 211 inputs the value of the center of gravity into the cell information table 2220 of the time lapse image to which the frame belongs.

  Specifically, first, the image analysis unit 211 determines which cell in the previous frame image has moved from each cell in the frame image. For example, the image analysis unit 211 compares the barycentric coordinates of each cell in the frame image with the barycentric coordinates of each cell in the previous frame image, and the cells having the nearest (small difference) barycentric coordinates are compared. Are stored in the cell coordinate position storage area 2223 of the corresponding record, and the coordinates of the center of gravity of each cell are stored.

  Then, the image analysis unit 211 outputs an analysis request to the statistical processing unit 212 when the above processing is completed up to the last frame image (fth frame).

  The statistical processing unit 212 calculates the movement amount TD and the average speed V of each cell in a predetermined continuous frame using the created cell information table 2220. Specifically, first, the statistical processing unit 212 obtains the vertical (Y) direction movement amount Δy and the horizontal (X) direction movement amount Δx of each cell between the frames from the displacement of the barycentric coordinates, and The average movement amount for each frame in the vertical and horizontal directions is calculated (see the following formulas (1) and (3)).

  Next, the statistical processing unit 212 calculates the total movement amount TD of each cell from the average movement amount, and calculates the average speed V of each cell from the total movement amount TD and the frame unit time T (the following mathematical formula (5)). (See (6)).

  Further, the vertical dispersion Vy and the horizontal dispersion Vx may be calculated (see the following formulas (2) and (4)).

  Then, the statistical processing unit 212 creates a graph showing the distribution of migration dynamics by taking the average velocity TD on the vertical axis and the distribution normalized by the range of 0 to 1 by sorting each cell in ascending order on the horizontal axis. To be displayed on the display unit 23. Here, the graph showing the distribution of migration dynamics is, for example, a scatter diagram as shown in FIGS.

  Next, the analysis processing unit 213 sets a percentage point, a class, and a reference range from the distribution of the migration dynamics. That is, this process is performed to create the reference information 2230 (see FIG. 4) from the sample data. Therefore, it is not executed when measuring the sample of the subject, and in this case, only the determination process executed by the determination processing unit 214 is performed.

  The percent point, class, and reference range may be set automatically by the analysis processing unit 213, or a setting screen that allows the user to arbitrarily set the setting point may be displayed on the display unit 23. In that case, the user can freely set these based on data accumulated in the past, medical findings, experiences, and the like. The setting contents are stored in the criterion information storage area 223 as the criterion information 2230 shown in FIG.

  As shown in FIG. 7, the inspection method of the present invention uses the difference in the average value of the migration speeds seen between patients with different severity and healthy subjects. Therefore, it is desirable to select a distribution point in which a difference appears remarkably as a percentage point (a specific example is shown in Example 1).

  Such percentage points differ optimally depending on the definition and class of each group that obtained the sample as a sample. Therefore, any distribution point may be set as a percentage point as long as the difference can be used.

  For example, when the sample group and the class are only affected and unaffected, the percentage point at which the difference of the average speed V is the largest in both groups can be set as a suitable percentage point for the classification of affected and unaffected. In this case, the average of the average speed V of healthy subjects at the percent point is taken as a standard value ± 2S. D. As a result, the presence or absence of asthma can be determined.

  On the other hand, the affected sample group is classified into multiple groups according to symptoms such as GINA, and if the class is classified according to severity, if the difference in average speed between each group is not more than a certain level, Cannot be determined. Therefore, for example, a point where the difference in average speed between groups is equal to or larger than a certain threshold and the difference between groups is the largest can be set as a percentage point. In addition, the difference between the groups may be set to a value that is equal to or less than a certain threshold.

  In this way, the analysis processing unit 213 calculates a percent score using a predetermined calculation method according to the definition and class of each group.

  As shown in FIG. 4, the class is obtained by dividing the average eosinophil velocity at a percentage point into classes for each range, and from this, the presence or absence of disease and the severity are determined. In other words, the class is not uniquely determined because it represents only the average speed. The user can arbitrarily set this from medical findings, experience, and accumulated data. Of course, a combination of predetermined classes may be stored in the storage unit 22, and the analysis processing unit 213 may allow the user to select this.

  The reference range is a numerical range for dividing the value of the average velocity of eosinophils into the above classes. For example, the analysis processing unit 213 can divide the average speed between groups at a predetermined percentage point by an intermediate value, and set this as a reference range (a specific example is shown in Example 1). Of course, it may be set by any other method and may be set arbitrarily by the user.

  The determination processing unit 214 performs processing that is executed only when measuring the sample of the subject. Specifically, the percentage point set from the percentage point storage area 2231 stored in the determination information storage area 223 is read out, and the average speed V at the percentage point is extracted from the distribution and displayed on the display unit 23. Further, it is detected which reference range of the determination table 2232 the average speed V belongs to, and a class corresponding to the range is read out. Then, the display unit 23 displays the contents of the class indicating the presence or absence of asthma and the severity.

  In this way, the test system 1 determines the presence or absence of asthma and the severity of the subject when suffering from the average value of the migration speed of the eosinophil stimulation factor.

  Here, the hardware configuration of the inspection apparatus 20 will be described. FIG. 9 is a block diagram showing an electrical configuration of the inspection apparatus 20.

  As shown in FIG. 9, the inspection apparatus 20 is a general computer on which a program operates, for example, a personal computer or a workstation.

  As shown in FIG. 9, the inspection apparatus 20 includes a CPU (Central Processing Unit) 901 that centrally controls each unit, a memory 902 that stores various data in a rewritable manner, various programs, data generated by the programs, and the like. An external storage device 903 for storing the data, a display device 904, and a bus 905 for connecting them. The inspection device 20 can be realized, for example, by reading a predetermined program stored in the external storage device 903 into the memory 902 and executing it by the CPU 901.

  In addition, in order to make an understanding of the structure of the inspection apparatus 20 easy, each above-mentioned component is classified according to the main processing content. The present invention is not limited by the name. The processing performed by the inspection device 20 can be classified into more components depending on the processing content. Moreover, it can also classify | categorize so that one component may perform more processes.

  Each functional unit may be constructed by hardware (such as an ASIC). Further, the processing of each functional unit may be executed by one hardware or may be executed by a plurality of hardware.

  The processing of the inspection apparatus 20 as described above will be described with reference to FIG. FIG. 5 is a flowchart showing a process flow of the control unit 21 of the inspection apparatus 20. Here, the processing when the control unit 21 determines whether or not the subject has asthma and its severity will be described. This flow is started when the input unit 24 receives an instruction from the user.

  The image analysis unit 211 acquires frame images output from the imaging device 12 at predetermined timings for a predetermined time, and stores them in the storage unit 22 (step S11).

  Next, the image analysis unit 211 recognizes each cell present in the image (step S13) and detects the coordinates of the center of gravity (step S13). Then, it is determined whether or not the image is the first frame image (first frame) (step S14). If it is the first frame image (YES), the process proceeds to step S15. If it is not the first frame image (NO), the process proceeds to step S16.

  If it is the first frame image (YES in step S14), the image analysis unit 211 newly creates the cell information table 2220 (step S15), and returns to step S11.

  When it is not the first frame image (NO in step S14), the image analysis unit 211 tracks which cell in the previous frame image has moved from each cell in the frame image, and cell information The coordinates of the center of gravity of each cell are written in the table 2220 (step S16).

  Then, the image analysis unit 211 determines whether or not the image is the last (f-th frame) image (step S17). If it is the last frame image (YES), the image analysis unit 211 outputs an analysis request to the statistical processing unit 212 and proceeds to step S18. If it is not the last frame image (NO), the processing from step S11 is repeated.

  When it is the last frame image (YES in step S17), the statistical processing unit 212 that has received the analysis request uses the created cell information table 2220 to move the amount of each cell in a predetermined continuous frame. TD and average speed V are calculated (step S18).

  Next, the statistical processing unit 212 creates a graph showing the distribution of migration dynamics by taking the average velocity TD on the vertical axis and the distribution normalized by the range of 0 to 1 by sorting each cell in ascending order on the horizontal axis. And it is made to display on the display part 23 (step S19).

  The determination processing unit 214 extracts the value of the average speed V at a predetermined percentage point 2231 stored in the determination information storage area 223 and determines the class to which the average speed V belongs. Then, the presence or absence of asthma and the class content indicating the severity are displayed on the display unit 23 (step S20), and the process is terminated.

  Each processing unit of the flow described above is divided according to the main processing contents in order to facilitate understanding of the processing of the inspection apparatus 20. The invention of the present application is not limited by the way of classifying the components or their names. The configuration of the inspection apparatus 20 can be divided into more components depending on the processing content. Moreover, it can also classify | categorize so that one component may perform more processes.

  In addition, said embodiment intends to illustrate the summary of this invention, and does not limit this invention.

  Next, an example of setting the percentage point, class, and reference range using the system as described above for asthma patients of each severity using the GINA step and a group of healthy persons will be described.

Example 1 of chemotaxis measurement and migration dynamic analysis for each group is shown below.
<Example 1>
(Sample adjustment)
In this example, RPMI (Roswell Park Memorial Institute) 1640 medium (manufactured by Sigma-Aldrich) was used as the medium, and indomethacin (manufactured by Sigma-Aldrich) was used as the chemotactic factor.

In addition, the following reagents were prepared.
・ HEPES (4- (2-hydroxyethyl) -1-piperazine etheric acid) (manufactured by Sigma-Aldrich)
-Fetal bovine serum (FBS) (manufactured by Sigma-Aldrich)
・ Bovine serum albumin (BSA)
Dulbecco phosphate buffer (DPBS) (Invitrogen)
Dextran T500 (manufactured by GE Healthcare)
Ficoll-paque (registered trademark) (manufactured by GE Healthcare)
・ StemSep (registered trademark) Eosinophils Enrichment kit (manufactured by Stem Cell Technologies)
EasySep (registered trademark) T cell Enrichment kit (manufactured by Stem Cell Technologies)
First, biological samples were collected from asthma patient groups of various severity levels and groups of healthy subjects.

  Specifically, 4 groups of 3 asthma patients corresponding to GINA step 1, 3 asthma patients corresponding to GINA step 2, 6 asthma patients corresponding to GINA step 3 and 8 healthy persons, total 20 people Whole blood was collected to obtain a sample. The sample was collected in a vacuum blood collection tube containing EDTA as a blood coagulation inhibitor.

Next, each sample was adjusted as follows. First, dextran was mixed with a whole blood sample to precipitate red blood cells for 15 minutes at room temperature, and a white blood cell fraction was separated. This was centrifuged at 250 × g for 5 minutes together with 5 ml of phosphate buffer, and the leukocyte fraction was suspended in phosphate buffer. Then, Ficoll Pack (registered trademark) was added and centrifuged at 400 × g for 20 minutes at 24 ° C. to separate the granulocyte fraction. From the granulocyte fraction isolated in this manner, eosinophils were separated by negative selection using magnetic nanobeads using StemSep (registered trademark) and EasySep (registered trademark). Then, eosinophils were suspended in RPMI 1640 medium containing HEPES containing 0.1% BSA to prepare a 2 × 10 ⁶ cell / mL eosinophil cell solution.

  If the granulocyte fraction contains a large amount of erythrocyte contamination, it is destroyed by hypotonic hemolysis with 10 times the amount of distilled water, and then osmotic pressure is recovered by further adding phosphate buffer. Ghosts were removed by repeating centrifugation twice at 150 × g for 5 minutes with PBS.

(Measurement of chemotaxis)
About each eosinophil cell solution adjusted in this way, the chemotaxis was measured using the observation apparatus 10. FIG.

  First, a silicon wafer 112 having 12 wells is set in the holder 11 with the glass plate 113 side down, and the RPMI 1640 medium containing HEPES containing 0.1% BSA is contained in the cell accommodation space 111 and the silicon wafer 112. Filled with. Next, indomethacin adjusted to 1.0 M as a chemotactic factor was injected into one well by the sample injector 13 to form a concentration gradient of indomethacin in the channel (flow channel). Then, the eosinophil cell solution prepared above was injected into a well paired with a well into which indomethacin had been injected, and time-lapse observation was performed at a unit time of 30 seconds to obtain a time-lapse image.

(Analysis of migration dynamics)
Based on the above time-lapse image, the following results were obtained from the inspection apparatus 20.

  FIG. 6 is a graph showing the kinetics of eosinophil migration for each patient and healthy person, and FIG. 7 is a graph showing an approximate curve for the kinetics of eosinophils in the affected group and healthy group of each GINA step. is there.

  As shown in FIG. 6, it was found that a sample of a patient having a severe asthma symptom in the classification by the GINA step includes more cells having a higher average speed. This indicates that there is a correlation between the average rate of eosinophils and the severity of asthma symptoms.

  Further, as shown in FIG. 7, it has become clearer that there is a difference in the average speed V in the approximate curve obtained by collecting statistics of a plurality of patients belonging to each GINA step. When the percentage point is 75 to 95%, particularly around 80%, there was a significant difference between each GINA step and healthy subjects.

  Therefore, 80% where a significant difference in the average speed V is seen between groups is set as a percentage point in advance, and from the value of the average speed V at the percentage point, the presence or absence of asthma and the asthma symptoms The severity can be determined. That is, it is predicted that the larger the average speed V, the more severe the symptoms are asthma.

  In addition, by setting a reference range for the average speed V, the severity can be divided into classes and captured. Specifically, in FIG. 7, the average value of the average speed between the healthy person and the GINA1 group at the percent point of 80% is 0.18 μm / s, the intermediate value of GINA1 and GINA2 is 0.23 μm / s, and GINA2 The intermediate value with GINA3 is about 0.31 μm / s. Thus, for example, subjects with average velocity values less than 0.18 are unaffected, subjects with an average velocity of 0.18 or more and less than 0.23 are mildly affected, and subjects with an average velocity of 0.23 or more and less than 0.31 are moderately affected. A class in which 0.31 or more subjects are severely affected can be considered. Of course, the class is not limited to this, and any class may be set based on medical findings and experiences.

  Thus, it is possible to provide a new index of asthma diagnosis by deriving a percentage point from sample data and giving an arbitrary class to the average speed at the percentage point.

  Here, the vertical axis of the dispersion diagram is the average velocity V. However, when this is the vertical dispersion Vy, the same correlation can be seen, so the longitudinal dispersion Vy may be used for the measurement.

<Example 2>
Next, an example using prostaglandin D2 (PGD2) instead of indomethacin as a chemotactic factor will be described.

(Sample adjustment)
Prostaglandin D2 was prepared as a chemotactic factor.

  Further, in this example, a total of 23 people including 2 asthma patients corresponding to GINA step 1, 6 asthma patients corresponding to GINA step 2, 10 asthma patients corresponding to GINA step 3, and 5 healthy persons. Blood was collected to obtain a sample.

(Examination of chemotaxis)
The prostaglandin D2 was adjusted to 1.0 M, and a concentration gradient was formed in the channel (flow path) of the observation apparatus 10. The other points were all the same as in Example 1.

(Analysis of migration dynamics)
Based on the above time-lapse observation, the following results were obtained from the inspection apparatus 20.

  FIG. 8 is a graph showing cell migration kinetics for each sample.

  As shown in FIG. 8, a sample of a patient whose asthma severity is serious in the classification by the GINA step includes cells having a higher average rate. Thus, it was found that there was a correlation between the migration dynamics of eosinophils against various leukocyte chemotactic factors and the severity of asthma.

  In the foregoing, the presence / absence of asthma using this test system 1 and the method for testing the severity have been described. As described above, the rate of migration kinetics of chemotactic factors in a part of eosinophils is linked to the disease state. Therefore, by using the rate of eosinophils as an index, it becomes possible to test for asthma and to screen for compounds for treatment of the disease.

  In addition, eosinophils from subjects suffering from COPD alone do not show an increase in the rate seen in eosinophils from patients suffering from asthma, so a new clinical diagnosis that distinguishes asthma from chronic obstructive pulmonary disease Usefulness as an index can be expected.

  Furthermore, the test method for asthma provided by the present invention can analyze the migration kinetics of eosinophils as a numerical value. Moreover, since the class indicating the degree of severity depends only on the speed of eosinophils, it can be used as a quantitative and objective diagnostic index. In addition, since analysis can be performed from a biological sample, the invasiveness to a patient is low, and a quick and inexpensive examination is possible.

1: inspection system, 10: observation device, 11: holder, 11a / 11b: partition, 12: imaging device, 13: sample injector, 20: inspection device, 21: control unit, 22: storage unit, 23: display unit 24: input unit, 25: I / F unit, 111: sample storage space, 112: silicon wafer, 113: glass plate, 112a: groove, 112b: terrace, 112c: block, 112d: well.

Claims (4)

An asthma test method for obtaining an index of asthma diagnosis,
Measuring the average migration rate of each leukocyte collected from the subject against indomethacin ,
Taking a distribution about the average value of the traveling speed;
Detecting an average value of the traveling speed at a predetermined percentage of the distribution;
Asthma testing method.   The inspection method according to claim 1, wherein the distribution is obtained by sorting the white blood cells in ascending order of the average value of the migration speeds and normalizing between 0 and 1. An asthma test apparatus for obtaining an index of asthma diagnosis,
Image analysis means for tracking the movement of leukocytes relative to indomethacin and calculating the average value of migration speed from a series of images,
Statistical processing means for taking a distribution about the average value of the traveling speed;
Determination processing means for detecting an average value of the traveling speed at a predetermined percentage point of the distribution;
A test apparatus for asthma, comprising: A program for causing a computer to function as an asthma test apparatus for obtaining an index of asthma diagnosis,
The computer
Image analysis processing that calculates the average value of migration speed by tracking the movement of leukocytes relative to indomethacin from a series of images,
Statistical processing to take a distribution about the average value of the traveling speed;
A determination process for detecting an average value of the traveling speed at a predetermined percentage point of the distribution;
The program characterized by performing.

Images