Method for analyzing disease / physical constitution, system for analyzing disease / physical constitution, program, and computer-readable recording medium

Abstract

To provide an analytical method capable of analyzing an onset risk of a disease using samples collected by a simple method.SOLUTION: A method includes the steps of: extracting exosomes from a sample collected by non-invasive means; quantifying at least one of miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, and miR-3976, miR-4306, miR-17-5p, miR-19a, miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p of microRNAs present in the exosomes; and analyzing a state of a specific disease and / or a specific constitution based on an amount of the quantified microRNA.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a method for analyzing a disease / predisposition, a system for analyzing a disease / predisposition, a program, and a computer-readable recording medium. [Background technology]

[0002] Lifestyle-related diseases refer to "a group of diseases in which lifestyle habits such as dietary habits, exercise habits, rest, smoking, and drinking are involved in the onset and progression of the disease," and examples of such diseases include non-insulin-dependent diabetes mellitus, obesity, hyperlipidemia (excluding familial), hyperuricemia, cardiovascular disease (excluding congenital), colon cancer (excluding familial), and periodontal disease. Furthermore, the prevention of lifestyle-related diseases has become an urgent issue. Therefore, it is also important to test for the risk of lifestyle-related diseases before they develop.

[0003] One test for predicting the risk of lifestyle-related diseases is to measure the concentration of amino acids in the blood (see, for example, Patent Document 1). In this test, the concentration of amino acids in the blood is used to evaluate the state of indicators of lifestyle-related diseases according to predetermined criteria. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2014 / 168125 Summary of the Invention [Problem to be solved by the invention]

[0005] However, this test uses blood and is not a non-invasive test that does not place a burden on the body.

[0006] Therefore, genetic testing is being considered as a method of easily collecting samples. Genetic testing includes DNA testing and RNA testing, but DNA is a gene that does not change throughout a person's life, and even if there is a gene that indicates a high risk of developing a disease, it does not necessarily mean that the person will actually develop the disease.

[0007] On the other hand, RNA testing is a test that analyzes at the genetic level the risk of developing lifestyle-related diseases that increase due to acquired factors, and is thought to be suitable for testing the risk of developing lifestyle-related diseases that occur when genes mutate due to acquired factors such as lifestyle, environment, stress, and aging.

[0008] Furthermore, RNA testing, which can examine acquired factors, would make it possible to grasp the current state of the body, and it may be possible to improve the condition or prevent the onset of disease through lifestyle, environment, diet, and the intake of supplements.

[0009] An object of the present invention is to provide a disease / predisposition analysis method, a disease / predisposition analysis system, a program, and a computer-readable recording medium that can analyze the risk of developing diseases such as lifestyle-related diseases using samples collected by a simple method. [Means for solving the problem]

[0010] As a result of extensive research aimed at solving the above problems, the present inventors discovered that the above object could be achieved by using a specimen collected by a non-invasive means, and thus completed the present invention. That is, according to the present invention,

[0011] (1) Among the microRNAs present in exosomes extracted from samples collected by non-invasive means, the following were identified: miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, miR-3976, miR-4306, miR-17-5p, miR-19a, miR-146a, miR-718, and miR-375 a measuring device having a measuring unit for quantifying at least one of miR-1290, miR-101, miR-373, miR-320, and miR-574-3p, and a transmitting unit for transmitting the amount of microRNA quantified by the measuring unit to an analyzing device; and an analyzing device having a receiving unit for receiving the amount of microRNA transmitted from the measuring device, and an analyzing unit for analyzing the state of a specific disease and / or a specific physical condition based on the amount of microRNA. (2) Among the microRNAs present in exosomes extracted from samples collected by non-invasive means, the following were identified: miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, miR-3976, miR-4306, and miR-17 a means for obtaining data on the amount of microRNA obtained by quantifying at least one of miR-5p, miR-19a, miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p; and a program for functioning as a means for analyzing the state of a specific disease and / or a specific constitution based on the data on the amount of microRNA; (3) Among the microRNAs present in exosomes extracted from samples collected by non-invasive means, the following were identified: miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, miR-3976, miR-4306, miR-17-5p, and miR-19a a means for obtaining data on the amount of microRNA obtained by quantifying at least one of miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p; and a computer-readable recording medium having a program recorded thereon for functioning as a means for analyzing the state of a specific disease and / or a specific constitution based on the data on the amount of microRNA. is provided. Effect of the Invention

[0012] According to the present invention, it is possible to provide a disease / predisposition analysis method, a disease / predisposition analysis system, a program, and a computer-readable recording medium, which are capable of analyzing the risk of developing diseases such as lifestyle-related diseases using samples collected by a simple method. [Brief description of the drawings]

[0013] [Figure 1] 1 is a block diagram showing a system configuration of a disease / constitution analyzing system according to a first embodiment of the present invention. [Diagram 2] 1 is a flowchart showing a disease / constitution analyzing method using a disease / constitution analyzing system according to a first embodiment of the present invention. [Diagram 3] FIG. 2 is a diagram showing an example of an analysis result of disease and constitution according to the first embodiment of the present invention. [Figure 4] 10 is a flowchart showing a disease / constitution analyzing method using a disease / constitution analyzing system according to a second embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, a disease / constitution analyzing method according to a first embodiment of the present invention will be described with reference to the drawings.

[0015] The method for analyzing a disease / predisposition according to a first embodiment of the present invention includes an extraction step of extracting RNA from a sample collected by non-invasive means, a step of quantifying mRNA present in the RNA that is associated with the onset of a specific disease and / or a specific predisposition, and an analysis step of analyzing the state of the specific disease and / or the specific predisposition based on the quantified amount of mRNA.

[0016] Furthermore, the disease / constitution analysis system according to the first embodiment of the present invention includes a measuring device having a measuring unit that quantifies an amount of mRNA associated with the onset of a specific disease and / or a specific constitution from RNA extracted from a sample collected by non-invasive means, and a transmitting unit that transmits the amount of mRNA quantified by the measuring unit to an analytical device, and an analytical device having a receiving unit that receives the amount of mRNA transmitted from the measuring device, and an analytical unit that analyzes the state of the specific disease and / or the specific constitution based on the amount of mRNA.

[0017] Fig. 1 is a block diagram showing the system configuration of a disease / predisposition analysis system according to a first embodiment of the present invention. As shown in Fig. 1, a disease / predisposition analysis system 2 includes a quantitative PCR device 4 as a measurement device, and a PC (personal computer) 6 as an analysis device.

[0018] The quantitative PCR device 4 also includes a control unit 8 that performs overall control of each part of the quantitative PCR device 4. The control unit 8 is connected to an input unit 10 that accepts input operations such as measurement conditions and measurement start, a measurement unit 12 that amplifies and quantifies mRNA using predetermined primers, and a transmission unit 14 that transmits data on the amount of mRNA measured by the measurement unit 12 to the PC 6.

[0019] The PC 6 also has a CPU 16, to which are connected a receiving unit 18 that receives the mRNA amount data transmitted from the quantitative PCR device 4, a memory unit 20 that stores the mRNA amount data, an analysis unit 22 that analyzes the disease state based on the mRNA amount data, and an operation unit 24 that specifies the data to be used in the analysis of the disease state and inputs instructions to start disease analysis, etc. Next, a method for analyzing diseases and constitutions using the disease analyzing system according to the embodiment of the present invention will be described with reference to the flowchart shown in FIG.

[0020] First, in the present invention, a specimen collected by a non-invasive means is used, and RNA is extracted from the specimen (step S1). Although known methods such as centrifugation, suction filtration, and methods using extraction reagents and extraction kits can be used as methods for extracting RNA, it is preferable to perform a treatment for stably storing RNA, or to use dry filter paper that has been treated so that RNA can be extracted and stably stored, and it is more preferable to use dry filter paper that has been treated so that RNA can be extracted and stably stored. An example of a treatment for stably storing RNA is treatment of a collected specimen with RNAlater (registered trademark) or the like.

[0021] An example of such a dry filter paper is RNASound RNA Sampling / Extracting Card (manufactured by Metammune). Furthermore, samples collected by non-invasive means include saliva, oral mucosa, urine, etc., with saliva and oral mucosa being preferred, and saliva being more preferred.

[0022] Therefore, after pouring the above-mentioned sample onto a dry filter paper that has been treated to extract and stably store RNA, such as an RNASound RNA Sampling / Extracting Card, to allow it to adhere or be adsorbed onto the filter paper, the sample can be easily transported in this state (hereinafter referred to as "sample-adhered filter paper").

[0023] When centrifugation, suction filtration, or a method using an extraction reagent is used as a method for extracting RNA, the container in which the sample was collected must be transported in a liquid state to the testing institution or laboratory. However, when dry filter paper that has been treated to extract and stably store RNA, such as RNASound RNA Sampling / Extracting Card, is used, the card or paper of the RNASound RNA Sampling / Extracting Card can be used as a medium to transport to the testing institution or laboratory, which is preferable in terms of ease of transportation, such as the ability to transport at room temperature, and transportation costs. When transporting the sample-attached filter paper, it may be transported in a designated bag or the like from the standpoint of odor prevention, etc.

[0024] Next, the amount of mRNA associated with the onset of a specific disease among the extracted RNAs is quantified using the quantitative PCR device 4 (step S2). When performing quantification, first, the RNA extracted in step S1 is set in the measurement unit 12. Then, when an instruction to start quantification is input by the operator from the input unit 10, the control unit 8 starts the quantification of mRNA for the RNA set in the measurement unit 12. Here, in the quantitative PCR device 4, it is preferable to perform measurement by real-time PCR, which measures amplification by polymerase chain reaction (PCR) over time. Also, amplification can be performed using primers designed for each of the mRNAs associated with the onset of a specific disease and / or a specific constitution. Also, a housekeeping gene such as GAPDH is used as a control for the analysis of the expression level of mRNA.

[0025] In this embodiment, specific diseases include cancer, arteriosclerosis, cerebral infarction, myocardial infarction, diseases related to immune function, autoimmune diseases, type 1 diabetes, type 2 diabetes, hyperlipidemia, thrombosis, binge eating, sweet intake, obesity, metabolic syndrome, diseases related to cholesterol, diseases related to neutral fat, liver cirrhosis, kidney stones, gallstones, urinary tract stones, emphysema, nicotine dependence, bone diseases, inflammation, rheumatism, arthritis, gout, lower back pain, duodenal ulcer, anemia, rhinitis, restless legs syndrome, cluster headache, migraine, age-related macular degeneration, glaucoma, astigmatism, skin aging, atopy, sunburn freckles, freckles, fatigue, chronic fatigue, alopecia areata, etc. Specific constitutions such as detoxification, drug resistance, alcohol metabolism, caffeine metabolism, exercise therapy, sleep time, and longevity can also be analyzed.

[0026] Examples of mRNA related to the onset of cancer include p53, a gene that suppresses various cancers; BRAF, a precursor to oncogenes; K-RAS, a sarcoma virus oncogene; Cytokeratin-7, which is related to lung cancer, stomach cancer, and ovarian cancer; Cytokeratin-19, which is related to lung cancer, breast cancer, and thyroid cancer; Cytokeratin-20, which is related to stomach cancer, colon cancer, and pancreatic cancer; MAGE-A1, a tumor-specific antigen found in melanoma cells and related to lung cancer, stomach cancer, and liver cancer; and melanoma cell Examples of such antigens include MAGE-A3, a tumor-specific antigen discovered in tumor cells and associated with lung cancer, gastric cancer, breast cancer, etc.; MAGE-A12, a tumor-specific antigen discovered in melanoma cells and associated with esophageal cancer and breast cancer; HnRNP, an intranuclear lipoprotein mainly associated with lung cancer but also with breast cancer; Mucin-1, a mucus glycoprotein associated with esophageal cancer, colon cancer, pancreatic cancer, etc.; and the mRNA of CEA, which is used as a tumor marker and is expressed in fetal cell adhesion, colon cancer, lung cancer, pancreatic cancer, etc.

[0027] Examples of mRNA related to arteriosclerosis include endothelin, the production of which increases with the onset of cardiovascular diseases such as hypertension and arteriosclerosis; VCAM-1, an adhesion molecule found in arteriosclerotic lesions and thought to be essential for the onset of arteriosclerosis through inflammation of the cell wall and the accompanying adhesion of leukocytes to vascular endothelial cells; ICAM-1, a receptor involved in the adhesion mechanism of monocytes and lymphocytes to vascular endothelium and a molecule that causes strong adhesion; P-selectin, which is involved in the reaction system when macrophages become foam cells and form plaques due to the unlimited uptake of oxidized LDL, which is produced when LDL is oxidized on vascular endothelial cells, by macrophages; M-CSF, which is deeply involved in the early stages of the development of arteriosclerosis; LOX-1, which may play an important role in the mechanism by which various risk factors for arteriosclerosis lead to organ damage; and thrombin R mRNA, which is involved in the onset and progression of many vascular diseases such as arteriosclerosis, restenosis after angioplasty, cerebral vasospasm after subarachnoid hemorrhage, vasculitis, Buerger's disease, and pulmonary hypertension. Furthermore, examples of mRNA related to the onset of cerebral infarction include the mRNA of NINJ2, a gene involved in the onset of cerebral infarction and the cerebrovascular system.

[0028] In addition, examples of mRNAs related to the onset of myocardial infarction include CDKN2B-AS1 mRNA, which is present in the CDKN2B-CDKN2A gene cluster on chromosome 9 and which has been reported to function in cell proliferation and to be strongly associated with familial cardiovascular disorders.

[0029] Furthermore, examples of mRNA related to the onset of diseases related to immune function include TNF-α mRNA, which can determine whether or not a person has a genetic tendency toward high immunity.

[0030] In addition, examples of mRNA related to the onset of autoimmune diseases include the mRNAs for IL-6, NF-κB, FKBP5, KLF5, and Foxp3, which belong to a group of genes involved in the reaction in which the immune system judges substances that make up one's own body to be foreign and triggers a rejection reaction.

[0031] Furthermore, examples of mRNAs related to the onset of diabetes (type 1 and type 2) include the mRNAs of PPARgamma, Glucokinase, HNF-4α, Adiponectin, and TNF-α, which belong to gene groups involved in sugar metabolism and fat metabolism.

[0032] Examples of mRNAs related to the onset of type 2 diabetes include the mRNAs of SORBS1, LMNA, and UCP2, which belong to a group of genes involved in pancreatic functions such as insulin secretion and carbohydrate metabolism.

[0033] In addition, examples of mRNAs related to the onset of hyperlipidemia include the mRNAs for PCSK9, which has been reported to be the third causative gene for familial hypercholesterolemia, CETP, which is a cholesteryl ester transfer protein, and LCAT, which is involved in primary hyperlipoproteinemia, obesity, diabetes, and nephrotic syndrome. Furthermore, examples of mRNA related to the onset of thrombosis include mRNA for ABO, a gene involved in blood coagulation. Furthermore, examples of mRNAs related to the onset of hyperphagia include RUFY1 mRNA, which is involved in the transport of lipids and proteins within cells.

[0034] In addition, examples of mRNA related to the onset of sweet intake include genes that receive adrenaline and increase blood sugar levels, and ADRA2A mRNA, which can determine whether or not someone tends to consume a lot of sweets.

[0035] In addition, mRNAs related to the onset of obesity include the mRNAs for β3AR, a thrifty gene called the β3-adrenergic receptor gene, UCP1, a thermogenic protein that burns fat, and β2AR, a thrifty gene called the β2-adrenergic receptor gene.

[0036] Furthermore, examples of mRNA related to the onset of metabolic syndrome include the mRNA of APOE, a gene related to whether or not a person is at high risk of dyslipidemia, and the mRNA of ACE, a gene related to whether or not a person is at high risk of hypertension.

[0037] Furthermore, examples of mRNAs related to the onset of cholesterol-related diseases such as hypercholesterolemia include the mRNA of ABCG8, a gene involved in the metabolism of bad cholesterol (LDL).

[0038] Furthermore, examples of mRNAs related to the onset of diseases related to neutral fat include APOA5, a gene involved in the decomposition of neutral fat, and GCKR, a gene involved in sugar and lipid metabolism.

[0039] Examples of mRNA related to the onset of cirrhosis include the mRNA of TNPO3, which is a gene for primary biliary cirrhosis, which occurs when the bile duct is destroyed and bile refluxes into the liver. Furthermore, examples of mRNAs related to the development of kidney stones include DGKH mRNA.

[0040] Furthermore, examples of mRNA related to the development of gallstones include the mRNA for ADRB3, a gene that acts as a keyhole to turn on the lipolysis switch and is related to the susceptibility to visceral fat accumulation. Furthermore, examples of mRNAs related to the development of urinary stones include the mRNA of UMOD, a gene involved in calcium deposition in the urinary system. Examples of mRNAs related to the onset of emphysema include the mRNAs of CSMD1 and BICD1, an emphysema susceptibility gene. Furthermore, examples of mRNAs related to the onset of nicotine dependence include mRNAs for CHRNA3, a gene involved in nicotine reactivity and metabolism.

[0041] In addition, examples of mRNAs related to the onset of bone diseases include the mRNAs for VDR, a nuclear receptor for vitamin D and a gene related to bone metabolism, and BGLAP, a non-collagenous bone protein involved in bone formation by osteocalcin.

[0042] Furthermore, examples of mRNA related to the onset of inflammation include mEPHX1 mRNA, which can determine whether an inflammatory substance is likely to cause inflammation in the body.

[0043] In addition, mRNA related to the onset of rheumatism includes the mRNA for PADI4, a group of genes that cause severe pain and swelling in joints throughout the body, including the hands and feet. Furthermore, examples of mRNA related to the onset of arthritis include DVWA mRNA. Furthermore, examples of mRNA related to the onset of gout include the mRNA of SLC2A9, a gene involved in the excretion of uric acid. Furthermore, examples of mRNAs related to the onset of lower back pain include the mRNA for CILP, a gene involved in cartilage repair. Furthermore, examples of mRNAs related to the development of duodenal ulcers include the mRNA of PSCA, a gene involved in the mucous membranes of the stomach and small intestine. Furthermore, examples of mRNAs related to the onset of anemia include the mRNA of IGL, a gene involved in iron transport in blood.

[0044] In addition, examples of mRNA related to the onset of rhinitis include GSDMB mRNA, which is involved in nasal congestion and has been reported to be involved in the risk of onset of asthma. In addition, examples of mRNAs related to the onset of restless legs syndrome include the mRNA of BTBD9, a gene involved in symptoms such as itching and pain in the legs. Furthermore, examples of mRNAs related to the onset of cluster headache include HCRtr2 mRNA. Furthermore, examples of mRNAs related to the onset of migraine include PRDM16 mRNA. Furthermore, an example of mRNA associated with the onset of age-related macular degeneration is CFH. Furthermore, examples of mRNA related to the onset of glaucoma include the mRNA of CDKN2B, which belongs to a group of genes related to intraocular pressure and the function of the lens. Furthermore, examples of mRNAs related to the onset of astigmatism include PDGFRA mRNA, which is highly expressed in people with corneal astigmatism.

[0045] Further, examples of mRNA related to the onset of skin aging include the mRNA for MMP1, an enzyme that breaks down collagen; GPX1, a gene that filters harmful substances and is involved in the detoxification of harmful substances that affect skin aging; and SOD2, a stress metabolism gene that is involved in the removal of reactive oxygen species that affect skin aging. Examples of mRNAs related to the onset of atopy include the mRNAs of FLG, SPINK5, and ZNF365, which belong to the immune system gene group. Furthermore, examples of mRNAs related to the development of sunburn freckles include the mRNA of ASIP, a gene involved in melanin production. Furthermore, examples of mRNA related to the development of freckles include the mRNA of IRF4, a gene that is believed to be able to determine the susceptibility to developing freckles.

[0046] Furthermore, examples of mRNA related to the onset of fatigue include the mRNA for NQO1, a gene involved in the production of ubiquinone (coenzyme Q10), which burns energy in the body. Furthermore, examples of mRNA related to the onset of chronic fatigue include the mRNA of TPH2, a gene involved in the production of the neurotransmitter serotonin. Furthermore, examples of mRNA related to the onset of alopecia areata include the mRNA of CTLA4, which is believed to be one of the causative genes related to hair loss resulting from autoimmune diseases. Furthermore, examples of mRNAs related to detoxification include the mRNA of GPX1, a gene involved in the treatment of reactive oxygen species. Furthermore, examples of mRNA associated with drug resistance include mRNA for multidrug resistance protein.

[0047] Examples of mRNA related to alcohol metabolism include PEPCK, and the mRNAs of aldehyde dehydrogenase and acetaldehyde dehydrogenase, which are genes for enzymes involved in alcohol metabolism.

[0048] Furthermore, examples of mRNAs related to caffeine metabolism include CYP1A2 mRNA, which can determine whether or not caffeinated drinks have a large impact on one's constitution.

[0049] Examples of mRNAs related to exercise therapy include the mRNAs of AMP kinase, GLUT4, and PGC-1α, which are genes involved in insulin resistance, glucose metabolism, and fat burning in mitochondria.

[0050] Furthermore, examples of mRNA related to sleep time include NRSR1 mRNA, which can genetically determine whether or not a person has a biological clock, particularly a tendency to go to bed later.

[0051] Examples of mRNAs related to longevity include the mRNAs for Mitochondria and FOXO3, which are involved in energy consumption such as mitochondria within cells and body temperature elevation. That is, examples of mRNA to be quantified in the present invention include those mentioned above.

[0052] Next, the control unit 8 of the quantitative PCR device 4 transmits data on the amount of mRNA obtained by quantification to the PC 6 via the transmission unit 14 (step S3), and the PC 6 receives the data on the amount of mRNA obtained by quantification via the reception unit 18 (step S4). Here, communication between the transmission unit 14 of the quantitative PCR device 4 and the reception unit 18 of the PC 6 may be performed by wired communication such as a wired LAN, or may be performed by wireless communication such as a wireless LAN or Bluetooth (registered trademark).

[0053] Next, the CPU 16 of the PC 6 stores the mRNA amount data received via the receiving unit 18 in the storage unit 20 (step S5). Here, the storage unit 20 stores the mRNA amount data in association with, for example, a specimen ID, a measurement date and time, a measurement number, etc.

[0054] Then, when data to be analyzed is designated via the operation unit 24 and an instruction to start the analysis is input, the CPU 16 causes the analysis unit 22 to analyze the state of the specific disease / constitution (step S6). When analyzing the state of the specific disease / constitution, the CPU 16 reads out the data of the mRNA amount stored in the memory unit 20 that is designated as the data to be analyzed, and causes the analysis unit 22 to analyze the state of the specific disease / constitution. An example of the analysis result is shown in FIG. 3.

[0055] Here, the amount of mRNA quantified using the quantitative PCR device 4 can be analyzed by statistical processing, but it is preferable to analyze the data obtained by the comparative Ct method by statistical processing. For example, by continuously quantifying mRNA extracted from a sample from a specific individual, data can be collected under normal circumstances, and when there is a change in the amount of mRNA, it can be analyzed to indicate a risk of developing a specific disease or a tendency to develop a specific physical constitution. The amount of mRNA is determined by the cycle number at which it can be detected by quantitative PCR, and is corrected based on the expression level of GAPDH.

[0056] In the analysis of the state of a specific disease or physical constitution by the analysis unit 22, for example, by using data continuously collected for a specific individual, it is possible to analyze that there is a risk of developing a specific disease when the amount of mRNA related to the onset of a specific disease or a specific physical constitution fluctuates by comparing it with the continuously collected data, and it is also possible to analyze that there is a tendency to develop a specific physical constitution.

[0057] Furthermore, when analyzing the state of a specific disease or constitution, a predetermined threshold value may be used. In this case, a threshold value for analyzing the onset of a specific disease or a specific constitution is calculated in advance by statistically processing the mRNA amount related to the onset of a specific disease or a specific constitution from all data or randomly extracted data of the mRNA amount stored in the memory unit 20. Then, by setting this threshold value as the threshold value for analyzing the state of a specific disease or a specific constitution, it is possible to analyze whether or not specific data is in a state of a specific disease or a specific constitution.

[0058] In the above-mentioned analysis of the state of a specific disease / specific constitution, data such as outliers and missing values ​​may be removed before analyzing the state of a specific disease / specific constitution.

[0059] According to the disease / predisposition analyzing method and disease / predisposition analyzing system of the first embodiment of the present invention, the risk of developing diseases such as lifestyle-related diseases can be analyzed using samples collected by a simple method.

[0060] In the above-mentioned first embodiment, the PC 6 is used as an example of the analytical device, but a tablet terminal or the like may be used as the analytical device. Also, the disease / predisposition analytical system 2 is described as having two devices, the quantitative PCR device 4 and the PC 6, but the analytical system can be configured with one device, for example, by incorporating the function of the analytical device into the quantitative PCR device 4.

[0061] In addition, in the first embodiment, data on the amount of mRNA is transmitted from the quantitative PCR device 4, which is a measuring device, to the PC 6, which is an analyzing device. However, in cases where communication between the quantitative PCR device 4 and the PC 6 is not possible, the data on the amount of mRNA may be transferred from the quantitative PCR device 4 to the PC 6 via a recording medium such as a USB memory or an SD card.

[0062] In the above-mentioned first embodiment, the data to be analyzed is designated via the operation unit 24, and when an instruction to start the analysis is input, the PC 6 analyzes the state of a specific disease or specific constitution. However, an analysis program for analyzing the state of a specific disease or specific constitution based on data on the amount of mRNA related to a specific disease or specific constitution among the mRNA extracted from a sample may be downloaded via a network such as the Internet and incorporated into the computer, thereby causing the computer to function so as to perform the above-mentioned analysis process. Here, this analysis program may read data on the amount of mRNA related to the onset of a specific disease and / or a specific constitution stored on the network or in the computer, and use it to analyze the state of a specific disease or specific constitution.

[0063] The program may be recorded on a computer-readable recording medium such as a flexible disk, a CD-ROM, a DVD, etc. In other words, the program may be read from the computer-readable recording medium and installed in a computer to cause the computer to function so as to analyze the state of the specific disease or physical constitution described above.

[0064] Next, a disease / predisposition analysis method according to a second embodiment of the present invention will be described with reference to the drawings. Note that the disease / predisposition analysis method according to the second embodiment is modified to use microRNA instead of mRNA used in the first embodiment. Therefore, detailed description of the same configuration as the first embodiment will be omitted, and only the different parts will be described in detail.

[0065] The method for analyzing a disease or predisposition according to the second embodiment of the present invention includes an extraction step of extracting exosomes from a specimen collected by a non-invasive means, and an extraction step of detecting microRNAs present in the exosomes, such as miR-141, miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-246, miR-248, miR-250, miR-260, miR-270, miR-280, miR-290, miR-300, miR-310, miR-320, miR-331, miR-340, miR-350, miR-360, miR-370, miR-380, miR-390, miR-400, miR-410, miR-420, miR-430, miR-440, miR-450, miR-460, miR-470, miR-480, miR-490, miR-500, miR-510, miR-520, miR-530, miR-540, miR-550, miR-560, miR-570, miR-580, miR-590, miR-600, miR-610, miR-620, miR-630, miR-640, miR-650, miR-700, miR-800, miR-900, miR-900, miR-1000, miR-1000, miR-1000, miR-1000, miR-10 and quantifying at least one of miR-3a, miR-4644, miR-3976, miR-4306, miR-17-5p, miR-19a, miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p; and analyzing the onset of a specific disease and / or a specific constitutional state based on the quantified amount of microRNA.

[0066] In addition, the disease / predisposition analysis system according to the second embodiment of the present invention detects and analyzes the following microRNAs present in exosomes extracted from a specimen collected by a non-invasive means: miR-141, miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, miR-3976, miR-4306, miR-17-5p, miR-1 The present invention also includes a measuring device having a measuring unit that quantifies at least one of miR-9a, miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p and a transmitting unit that transmits the amount of microRNA quantified by the measuring unit to an analyzing device, a receiving unit that receives the amount of microRNA transmitted from the measuring device, and an analyzing unit that analyzes the state of a specific disease and / or a specific physical constitution based on the amount of microRNA.

[0067] Furthermore, the method for analyzing a disease / predisposition according to the second embodiment of the present invention includes an extraction step of extracting exosomes from a saliva sample, a step of quantifying miR-103, miR-21 and / or miR-19 among the microRNAs present in the exosomes, and an analysis step of analyzing the state of a specific disease and / or a specific predisposition based on the amounts of microRNA miR-103, miR-21 and / or miR-19.

[0068] Furthermore, a disease / predisposition analysis system according to a second embodiment of the present invention includes a measurement device having a measurement unit that quantifies the amounts of microRNA, miR-103, miR-21 and / or miR-19, among microRNAs present in exosomes extracted from a saliva sample, and a transmission unit that transmits the amounts of microRNA, miR-103, miR-21 and / or miR-19, quantified by the measurement unit to an analysis device, an analysis device having a receiving unit that receives the amounts of microRNA transmitted from the measurement device, and an analysis unit that analyzes the state of a specific disease and / or a specific predisposition based on the amounts of microRNA.

[0069] The disease / predisposition analysis system according to the second embodiment uses the analysis system shown in FIG. 1 used in the first embodiment. Next, a method for analyzing diseases and constitutions using the disease analyzing system according to the embodiment of the present invention will be described with reference to the flowchart shown in FIG.

[0070] First, in the present invention, a specimen collected by a non-invasive means is used, and exosomes are extracted from the specimen (step S11). Methods for extracting exosomes include ultracentrifugation, ultrafiltration, gel filtration, HPLC, and methods using extraction reagents, and it is preferable to use filter paper that has been treated to trap exosomes.

[0071] Examples of such filter paper include FTA Microcard (manufactured by GE Healthcare) (see, for example, U.S. Patent Nos. 5,496,562, 5,756,126, 5,807,527, 5,972,386, and 5,985,327). The FTA Microcard has a filter paper in which a composition comprising a weak base such as trishydroxymethylmethane, a chelating agent such as ethylenediaminetetraacetate, an anionic surfactant such as sodium dodecyl sulfate, and a free radical trap such as uric acid or a urate salt is adsorbed or incorporated into cellulose-based paper.

[0072] The filter paper that makes up the FTA microcard is designed to entangle and trap nucleic acids, and the inventors' studies have found that when a sample is poured onto or attached to the FTA microcard, exosomes are trapped.

[0073] Therefore, after a urine sample is poured onto filter paper that has been treated to trap exosomes, such as an FTA microcard, to allow the exosomes to adhere or be adsorbed, the sample can be easily transported in this state (hereinafter referred to as "sample-adhered filter paper").

[0074] When ultracentrifugation, ultrafiltration, gel filtration, HPLC, or methods using extraction reagents are used as a method for extracting exosomes, the sample needs to be transported to the testing institution or laboratory in the liquid state of the container in which it was collected. However, when filter paper treated to trap exosomes is used, the sample can be transported to the testing institution or laboratory on a card such as an FTA microcard or paper as a medium, which is preferable in terms of ease of transportation, such as the ability to transport the sample at room temperature, and transportation costs. When transporting the sample-attached filter paper, it may be transported in a designated bag or the like from the standpoint of odor prevention, etc. Furthermore, samples collected by non-invasive means include saliva, urine, etc., with saliva being more preferred.

[0075] Next, in the extraction step, exosomes are extracted from the specimen, and then microRNA is extracted from the exosomes (step S12). The method for extracting microRNA from exosomes is not particularly limited, and various commercially available extraction kits can be used. For example, the miRCURY RNA Isolation Kit (Product# 300110; EXIQON) can be used.

[0076] Next, the amount of the extracted microRNA is quantified using the quantitative PCR device 4 (step S13). When performing quantification, first, the microRNA extracted in step S12 is set in the measurement unit 12. Then, when an instruction to start quantification is input by the operator from the input unit 10, the control unit 8 starts the quantification of the microRNA set in the measurement unit 12. Here, in the quantitative PCR device 4, it is preferable to perform the measurement by real-time PCR, which measures amplification by polymerase chain reaction (PCR) over time. Furthermore, amplification can be performed using primers designed for each microRNA associated with the onset of a specific disease and / or a specific constitution. Furthermore, a specific microRNA or the like can be used as a control (control) for the analysis of the expression level of the microRNA.

[0077] In the second embodiment, examples of the specific disease or specific constitution include cancers such as ovarian cancer, colon cancer, pancreatic cancer, cervical cancer, liver cancer, prostate cancer, pharyngeal squamous cell carcinoma, breast cancer, glioma, and glioblastoma multiforme.

[0078] MicroRNAs associated with the development of ovarian cancer include miR-21, miR-141, miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, and miR-373.

[0079] In addition, microRNAs related to the development of colorectal cancer include let-7a, miR-1229, miR-1246, miR-150, miR-21, miR-223, miR-23a, miR-19a, etc. In addition, microRNAs associated with the development of pancreatic cancer include miR-1246, miR-4644, miR-3976, miR-4306, and miR-21. MicroRNAs related to the development of cervical cancer include miR-21 and miR-146a. In addition, examples of microRNAs related to the development of liver cancer include miR-21 and miR-718.

[0080] In addition, microRNAs related to the development of prostate cancer include miR-375, miR-141, and miR-1290. In addition, microRNAs related to the development of pharyngeal squamous cell carcinoma include miR-21. In addition, examples of microRNAs related to the development of breast cancer include miR-101 and miR-373. Furthermore, examples of microRNAs related to the development of glioma include miR-21. In addition, examples of microRNAs associated with the development of glioblastoma multiforme include miR-320 and miR-574-3p.

[0081] In this embodiment, the microRNAs to be quantified may be miR-103, miR-21, and / or miR-19, which are microRNAs present in exosomes extracted from a saliva sample.

[0082] Here, miR-103 is stably expressed in serum / plasma, urine, and exosomes in cerebrospinal fluid (see, for example, Table 6 (page 25) of http: / / www.exiqon.com / ls / Documents / Scientific / microRNA-serum-plasma-guidelines.pdf).

[0083] In addition, miR-21 is a microRNA found in a wide variety of cancers, such as ovarian cancer, colon cancer, pancreatic cancer, cervical cancer, liver cancer, pharyngeal squamous cell carcinoma, and glioma, as a disease-specific molecule contained in exosomes extracted from serum or cerebrospinal fluid, etc. In other words, it is a type of microRNA that is secreted in large amounts from a wide variety of cancer cells.

[0084] Here, while there are types of microRNAs that are stably expressed in exosomes in serum / plasma, saliva, and cerebrospinal fluid, such as the above-mentioned miR-103, there are also microRNAs that are not stably expressed (as above, for example, see Table 6 (page 25) in http: / / www.exiqon.com / ls / Documents / Scientific / microRNA-serum-plasma-guidelines.pdf). Therefore, just because a type of microRNA is expressed as a type of microRNA contained in exosomes extracted from serum, cerebrospinal fluid, etc., does not mean that it is expressed as a type of microRNA contained in exosomes extracted from saliva or urine. In other words, there is no complete correlation between the type of microRNA contained in exosomes extracted from serum, cerebrospinal fluid, etc. and the type of microRNA contained in exosomes extracted from saliva.

[0085] In addition, miR-19 is a type of microRNA whose secretion is suppressed from a wide range of cancer cells, and its expression level is low as a type of microRNA contained in exosomes extracted from the serum or cerebrospinal fluid of cancer patients.

[0086] Next, the control unit 8 of the quantitative PCR device 4 transmits data on the amount of microRNA obtained by quantification to the PC 6 via the transmission unit 14 (step S14), and the PC 6 receives the data on the amount of microRNA obtained by quantification via the reception unit 18 (step S15). Here, communication between the transmission unit 14 of the quantitative PCR device 4 and the reception unit 18 of the PC 6 may be performed by wired communication such as a wired LAN, or may be performed by wireless communication such as a wireless LAN or Bluetooth (registered trademark).

[0087] Next, the CPU 16 of the PC 6 stores the microRNA amount data received via the receiving unit 18 in the storage unit 20 (step S16). Here, the storage unit 20 stores the microRNA amount data in association with, for example, a specimen ID, a measurement date and time, a measurement number, etc.

[0088] Then, when data to be analyzed is designated via the operation unit 24 and an instruction to start the analysis is input, the CPU 16 causes the analysis unit 22 to analyze the state of the specific disease and / or specific constitution (step S17). When analyzing the state of the specific disease and / or specific constitution, the CPU 16 reads out the data of the microRNA amount stored in the storage unit 20 that is designated as the data to be analyzed, and causes the analysis unit 22 to analyze the state of the specific disease and / or specific constitution.

[0089] Here, the amount of microRNA quantified using the quantitative PCR device 4 can be analyzed by statistical processing, but it is preferable to analyze the data obtained by the comparative Ct method by statistical processing. For example, by continuously quantifying the microRNA contained in exosomes extracted from a specimen of a specific person, data at normal times (for example, when the person is not cancerous) can be collected, and when a change is observed in the amount of microRNA, it can be analyzed that there is a risk of developing a specific disease, or that there is a tendency to develop a specific constitution. For example, when the amounts of miR-21 and miR-19 are used as the amount of microRNA, the amount of miR-21 and the amount of miR-19 are analyzed by using values ​​compared with the amount of miR-103.

[0090] In the analysis of the state of a specific disease and / or a specific physical constitution by the analysis unit 22, for example, by using data continuously collected for a specific individual, it is possible to analyze that there is a risk of developing a specific disease when the amount of mRNA related to the onset of a specific disease / specific physical constitution fluctuates by comparing it with the continuously collected data, and also to analyze that there is a tendency to develop a specific physical constitution.

[0091] Furthermore, when analyzing the state of a specific disease and / or a specific constitution, a predetermined threshold may be used for the analysis. In this case, a threshold for analyzing the onset of a specific disease or a specific constitution is calculated in advance by statistically processing the amount of microRNA related to the onset of a specific disease or a specific constitution from all data or randomly extracted data of the amount of microRNA stored in the storage unit 20. Then, by setting this threshold as the threshold for analyzing the state of a specific disease or a specific constitution, it is possible to analyze whether or not specific data is in a state of a specific disease or a specific constitution.

[0092] In addition, in the analysis of the above-mentioned specific disease / specific constitution state, data such as outliers and missing values ​​may be removed before analyzing the cancer state.

[0093] According to the disease / predisposition analyzing method and disease / predisposition analyzing system of the second embodiment of the present invention, the risk of developing diseases such as lifestyle-related diseases can be analyzed using samples collected by a simple method.

[0094] In the above-mentioned second embodiment, the PC 6 is used as an example of the analytical device, but a tablet terminal or the like may be used as the analytical device. Also, the disease / predisposition analytical system 2 is described as having two devices, the quantitative PCR device 4 and the PC 6, but the analytical system can be configured with one device, for example, by incorporating the function of the analytical device into the quantitative PCR device 4.

[0095] In addition, in the second embodiment, data on the amount of microRNA is transmitted from the quantitative PCR device 4, which is a measuring device, to the PC 6, which is an analyzing device. However, in cases where communication between the quantitative PCR device 4 and the PC 6 is not possible, the data on the amount of microRNA may be transferred from the quantitative PCR device 4 to the PC 6 via a recording medium such as a USB memory or an SD card.

[0096] In the above embodiment, the data to be analyzed is designated via the operation unit 24, and when an instruction to start the analysis is input, the PC 6 analyzes the state of a specific disease or specific constitution. However, an analysis program for analyzing the state of a specific disease or specific constitution based on data on the amount of mRNA associated with a specific disease or specific constitution among microRNAs present in exosomes extracted from a specimen may be downloaded via a network such as the Internet and incorporated into a computer, thereby causing the computer to function so as to perform the above-mentioned analysis process. Here, this analysis program may read data on the amount of microRNA associated with the onset of a specific disease and / or a specific constitution stored on the network or computer, and use it to analyze the state of a specific disease or specific constitution.

[0097] The program may be recorded on a computer-readable recording medium such as a flexible disk, a CD-ROM, a DVD, etc. In other words, the program may be read from the computer-readable recording medium and installed in a computer to cause the computer to function so as to analyze the state of the specific disease or physical constitution described above. [Explanation of symbols]

[0098] 2...Disease / physical analysis system, 4...quantitative PCR device, 6...PC, 8...control unit, 12...measuring unit, 16...CPU, 20...storage unit, 22...analysis unit

Claims

1. A measuring unit that quantifies at least one of the following microRNAs present in exosomes extracted from a sample collected by a non-invasive means: miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, miR-3976, miR-4306, miR-17-5p, miR-19a, miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p; a transmitting unit that transmits the amount of microRNA quantified by the measuring unit to an analyzing device; A measuring device comprising: A receiving unit that receives the amount of microRNA transmitted from the measuring device; an analysis unit that analyzes a specific disease and / or a specific physical condition based on the amount of the microRNA; An analysis device comprising: A disease / constitution analysis system including:

2. Computer A means for quantifying at least one of the microRNAs present in exosomes extracted from a specimen collected by a non-invasive means, which is selected from the group consisting of miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, miR-3976, miR-4306, miR-17-5p, miR-19a, miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p, to obtain data on the amount of microRNA; Means for analyzing a specific disease and / or a specific physical condition based on the data on the amount of microRNA A program to function as a

3. Computer A means for quantifying at least one of the microRNAs present in exosomes extracted from a specimen collected by a non-invasive means, which is selected from the group consisting of miR-200a, miR-200c, miR-200b, miR-203, miR-205, miR-214, let-7a, miR-1229, miR-1246, miR-150, miR-223, miR-23a, miR-4644, miR-3976, miR-4306, miR-17-5p, miR-19a, miR-146a, miR-718, miR-375, miR-1290, miR-101, miR-373, miR-320, and miR-574-3p, to obtain data on the amount of microRNA; Means for analyzing a specific disease and / or a specific physical condition based on the data on the amount of microRNA A computer-readable recording medium having a program recorded thereon for causing the device to function as a

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