Health Risk Assessment Methods

Abstract

The present invention provides a method for assessing health risks. [Solution] The health risk assessment method includes the following steps: creating a microRNA expression database for a healthy population; analyzing the microRNA expression levels in a subject's plasma sample; comparing the subject's microRNA expression data with the microRNA expression levels in the microRNA database for a healthy population to identify microRNAs in the subject's plasma that are overly or underexpressed, and assessing the subject's health risk.

Description

[Technical Field]

[0001] The present invention relates to a health risk assessment method, and in particular to a health risk assessment method using microRNA (miRNA) expression analysis. [Background technology]

[0002] MicroRNAs (microRNAs) are non-coding RNAs approximately 18–25 nucleotides in length that are highly conserved throughout evolution and play crucial roles in intracellular regulation. MicroRNAs were first discovered in Caenorhabditis elegans in 1993. Subsequently, many more microRNAs have been discovered in humans and other species. Currently, there are approximately 2,500 known microRNAs in human cells, and it has been demonstrated that these microRNAs can control more than 50% of messenger RNA (mRNA) expression. Furthermore, abnormal microRNA expression has been shown to be associated with the development of numerous diseases, including cancer, chronic diseases, and autoimmune disorders.

[0003] Over the past few years, microRNAs have been widely praised and considered a novel molecular detection target. It has now been demonstrated that microRNAs are secreted from cells into the bloodstream and are resistant to degradation by ribonucleases (RNases) by forming protein-RNA complexes. These characteristics are also highly valuable, making it easier to obtain cell-free microRNAs in the blood. Cell-free miRNA expression profiling, for example, can be used to detect early disease diagnosis. For example, it has been demonstrated that different types of cancer each have unique cell-free microRNA expression profiles, otherwise known as miRNA signatures, which can be used to detect early cancer diagnosis.

[0004] A convenient, non-invasive disease detection method with a high diagnostic yield has been a goal pursued by the medical community. Taking cancer as an example, this goal can be achieved by conducting cancer screening to detect potentially undetected, early-stage asymptomatic cancer. Cancer screening refers to the process of identifying whether or not a person has cancer using tests, examinations, or other methods.

[0005] Currently, patients can detect whether they have cancer through a variety of symptoms and test results, but the most reliable method of diagnosing malignant tumors is for a pathologist to perform a biopsy on living tissue or a pathological test on tissue extracted during surgery to verify the presence of cancer cells, which is an invasive detection method.

[0006] Tumor marker detection refers to the detection of changes in specific proteins associated with malignant tumor cells to determine whether a patient has cancer. However, tumor marker detection lacks sensitivity and specificity, and is often unable to detect tumors until they have grown significantly or have already metastasized to other organs.

[0007] As described above, the development of non-invasive early assessment methods for health risk and real-time monitoring of health risks of disease as early as possible are currently important research topics. Summary of the Invention [Problem to be solved by the invention]

[0008] The present invention provides a health risk assessment method for monitoring health risks in real time by analyzing the expression levels of microRNAs. [Means for solving the problem]

[0009] The health risk assessment method of the present invention includes the following steps: First, a microRNA expression database for a healthy population is created, and then the microRNA expression levels in the subject's plasma sample are analyzed. The subject's microRNA expression data is then compared with the microRNA expression levels in the microRNA database for the healthy population to identify microRNAs in the subject's plasma that are overly or underexpressed, and the subject's health risk is assessed.

[0010] In one embodiment of the present invention, the health risk determination includes cancer or diabetes.

[0011] In one embodiment of the present invention, microRNAs are classified into H-type, M-type, L-type, or Cn-type based on their expression levels in a microRNA database of a healthy population. H-type indicates that the expression level of that type of microRNA is detected at a frequency of more than 60% in a healthy population, M-type indicates that the expression level of that type of microRNA is detected at a frequency of 20% to 60% in a healthy population, L-type indicates that the expression level of that type of microRNA is detected at a frequency of less than 20% in a healthy population, and Cn-type indicates that the expression of that type of microRNA was not detected in a healthy population.

[0012] In one embodiment of the present invention, microRNAs are classified into U-type, D-type, N-type, or En-type based on the expression level of a subject's microRNA expression level data. Type U indicates that the expression level of that type of microRNA in the subject is higher than the reference range of the expression level of that type of microRNA in a healthy population. Type D indicates that the expression level of that type of microRNA in the subject is lower than the reference range of the expression level of that type of microRNA in a healthy population. Type N indicates that the expression level of that type of microRNA in the subject is within the reference range of the expression level of that type of microRNA in a healthy population. Type En indicates that the expression of that type of microRNA in the subject was not detected.

[0013] In one embodiment of the present invention, each microRNA of a subject is classified into group 1, group 2, group 3, group 4, or group 5. When each microRNA belongs to group 1, group 2, group 3, group 4, or group 5, it is shown with one red dot, where group 1 indicates that the microRNA of that type simultaneously belongs to both H type and U type, group 2 indicates that the microRNA of that type simultaneously belongs to both M type and U type, group 3 indicates that the microRNA of that type simultaneously belongs to both Cn type and U type, group 4 indicates that the microRNA of that type simultaneously belongs to both H type and D type, and group 5 indicates that the microRNA of that type simultaneously belongs to both M type and D type.

[0014] In one embodiment of the present invention, a number of red dots greater than or equal to 5 indicates that the subject may be at health risk. [Effects of the Invention]

[0015] As described above, a non-invasive early assessment method for health risk assessment is provided, which analyzes the expression level of microRNA in the plasma of a subject and then compares it with a microRNA database of a healthy population, thereby enabling real-time and efficient assessment of health risks and further improving the convenience and diagnostic rate of existing health risk screening.

[0016] In order to make the above-mentioned features and advantages of the present invention more comprehensible, the present invention will be described in detail below with reference to the following embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0017] The present invention provides an improved method for measuring nucleic acid samples, which includes the following steps: first, creating a database of microRNA expression levels for a healthy population; then, analyzing the microRNA expression levels in a subject's plasma sample; then, comparing the subject's microRNA expression level data with the microRNA expression levels in the microRNA database for a healthy population to identify microRNAs with overly or underexpressed levels in the subject's plasma and assess the subject's health risk.

[0018] In this embodiment, the method for creating a microRNA database for a healthy population is as follows: First, a disease-related microRNA information database is created based on more than 30,000 literature documents, and 167 microRNAs highly associated with the disease are filtered out. More than 300 healthy subjects (those who have not been diagnosed by a doctor as suffering from cancer, diabetes, or other major diseases) are recruited. After being evaluated by a doctor as having no risk of tumor, plasma samples are collected and the expression levels of 167 microRNAs in the plasma samples are detected. The mean and standard deviation of each microRNA expression level in the healthy population are calculated, and based on this, the normal range of each microRNA expression level in the healthy population is statistically determined. A database for the expression levels of these 167 microRNAs in the healthy population is created.

[0019] In this embodiment, the 167 filtered microRNAs highly associated with diseases are as shown in Table 1 below.

[0020] [Table 1]

[0021] In this embodiment, the method for detecting microRNA in plasma includes the following steps.

[0022] 1. Collect a blood sample

[0023] The blood collection site on the donor's skin is wiped with alcohol, and a tourniquet is tied using the slipknot technique 5 to 15 cm above the collection site. 10 ml of whole blood is drawn into a K2EDTA BD Vacutainer tube using a 19G to 22G needle. Once the blood has flowed into the tube, the tourniquet is immediately untied. Immediately after the blood collection is complete, gently invert the tube upside down and mix it 5 to 8 times to ensure the anticoagulant has fully taken effect. The blood collection tube should be stored at room temperature, and the plasma separation step should be completed within one hour of collection.

[0024] 2. Plasma separation method

[0025] Place the blood collection tubes in a swinging-bucket rotor and centrifuge at 1200 x g for 10 minutes at room temperature. After centrifugation, transfer the supernatant to a new 15 ml centrifuge tube. Pipette up and down the 15 ml tube five times to ensure complete mixing, then divide equally between 1.5 ml DNase / RNase-free Eppendorf tubes and centrifuge at 1200 x g for 10 minutes at room temperature. After centrifugation, transfer the supernatant to a new 15 ml centrifuge tube, being careful not to collect the white precipitate at the bottom of the 1.5 ml Eppendorf tube. Pipette up and down the supernatant five times to ensure complete mixing, then divide into 1.5 ml DNA LoBind tubes (Eppendorf, 22431021) and immediately store in a -80°C refrigerator.

[0026] 3. MicroRNA extraction method

[0027] The plasma sample was removed from the -80°C refrigerator and placed on ice to thaw. After thawing, the experiment was carried out according to the operating instructions provided with the Qiagen miRNeasy Serum / Plasma kit, and the sample was reconstituted in 30 μl of nuclease-free water.

[0028] 4. cDNA synthesis

[0029] An appropriate amount of microRNA is extracted and reverse-transcribed using Quarkbio's microRNA Universal RT kit to synthesize cDNA.

[0030] 5. qPCR Experiment

[0031] An appropriate amount of cDNA is extracted and a qPCR experiment is performed according to the operating manual provided by Quarkbio's miRSCAN Panelchip®.

[0032] In this embodiment, the health risk assessment includes cancer or diabetes, but the present invention is not limited thereto, and may include risk factors that cause other diseases or adverse effects on health.

[0033] In this embodiment, microRNAs are classified into H-type, M-type, L-type, or Cn-type based on their expression levels in a microRNA database of a healthy population. H-type indicates that the expression level of that type of microRNA is detected at a frequency higher than approximately 60% in a healthy population, M-type indicates that the expression level of that type of microRNA is detected at a frequency of approximately 20% to 60% in a healthy population, L-type indicates that the expression level of that type of microRNA is detected at a frequency lower than approximately 20% in a healthy population, and Cn-type indicates that the expression of that type of microRNA was not detected in a healthy population.

[0034] In this embodiment, the microRNA expression level data of a subject is divided into U, D, N, or En types based on the expression level. Type U indicates that the expression level of that type of microRNA in the subject is higher than the reference range of the expression level of that type of microRNA in a healthy population. Type D indicates that the expression level of that type of microRNA in the subject is lower than the reference range of the expression level of that type of microRNA in a healthy population. Type N indicates that the expression level of that type of microRNA in the subject is within the reference range of the expression level of that type of microRNA in a healthy population. Type En indicates that the expression of that type of microRNA in the subject was not detected.

[0035] In this embodiment, each microRNA of a subject is classified into group 1, group 2, group 3, group 4, or group 5. When each microRNA belongs to group 1, group 2, group 3, group 4, or group 5, it is represented by one red dot. Group 1 indicates that the microRNA of that type simultaneously belongs to both H type and U type, group 2 indicates that the microRNA of that type simultaneously belongs to both M type and U type, group 3 indicates that the microRNA of that type simultaneously belongs to both Cn type and U type, group 4 indicates that the microRNA of that type simultaneously belongs to both H type and D type, and group 5 indicates that the microRNA of that type simultaneously belongs to both M type and D type. A number of red dots greater than or equal to five indicates a possible health risk for the subject.

[0036] The health risk assessment method according to the above-described embodiment will be described in detail below with reference to experimental examples, which, however, are not intended to limit the present invention.

[0037] Experimental example

[0038] To prove that the health risk assessment method proposed in this invention can assess health risks in real time and efficiently, the following experimental examples were specifically carried out.

[0039] Example 1: Risk assessment for cancer

[0040] 198 subjects who were already known to be in the low-risk group and the cancer group (determined by a doctor) were analyzed, and the number of red dots for each subject was determined using the discrimination method mentioned in the above embodiment, and the results are shown in Table 2 below. In Table 2, the low-risk group refers to subjects who have not yet been diagnosed with any major disease, and none of the cancer group have yet been treated. Among the 198 test samples, the accuracy rate of successfully identifying the high-risk group with potential health risks was approximately 73%.

[0041] [Table 2]

[0042] Example 2: Risk assessment for diabetes

[0043] 56 subjects who were already known to be in the low-risk group and the diabetic group (determined by a doctor) were analyzed, and the number of red dots for each subject was determined using the discrimination method mentioned in the above embodiment, and the results shown in Table 3 below were obtained. In Table 3, the low-risk group refers to subjects who have not yet been diagnosed with any major disease. In the 56 test samples, the accuracy rate of successfully identifying the high-risk group with potential health risks was approximately 70%.

[0044] [Table 3]

[0045] As described above, the present invention provides a non-invasive early assessment method for health risk assessment, which analyzes the expression levels of microRNAs associated with health risk factors in the plasma of a subject and then compares the results with a microRNA database of healthy individuals, thereby enabling real-time and efficient assessment of health risks. Furthermore, the present invention can improve the convenience and diagnostic yield of existing cancer screening methods and provide personalized and specialized health risk monitoring.

[0046] As described above, this invention has been disclosed by way of an embodiment, but of course, this is not intended to limit this invention. As can be easily understood by a person skilled in the art, appropriate changes and modifications can naturally be made within the scope of the technical idea of ​​this invention, and therefore the scope of patent protection must be determined based on the scope of the claims and the equivalents thereto.

Claims

[Claim 1] Creating a database of microRNA expression levels for a healthy population; Analyzing microRNA expression levels in a plasma sample from the subject; Comparing the microRNA expression level data of the subject with the microRNA expression level in the microRNA database of the healthy population to find microRNAs in the plasma of the subject that are overly or underexpressed, and assessing the health risk of the subject; Including, In the step of creating a microRNA expression level database for the healthy subject population, each microRNA is classified into H type, M type, L type, or Cn type based on the detection frequency of each microRNA expression in the microRNA database for the healthy subject population, where H type indicates a detection frequency higher than 60%, M type indicates a detection frequency of 20% to 60%, L type indicates a detection frequency lower than 20%, and Cn type indicates that expression of this type of microRNA could not be detected; In the step of assessing the health risk of the subject, the microRNA expression level data of the subject is divided into U-type, D-type, N-type, or En-type based on the expression level, where U-type indicates that the expression level of that type of microRNA in the subject is higher than the reference range of the expression level of that type of microRNA in the healthy population, D-type indicates that the expression level of that type of microRNA in the subject is lower than the reference range of the expression level of that type of microRNA in the healthy population, N-type indicates that the expression level of that type of microRNA in the subject is within the reference range of the expression level of that type of microRNA in the healthy population, and En-type indicates that the expression of that type of microRNA in the subject could not be detected; In the step of assessing the health risk of the subject, each microRNA of the subject is classified into a first group, a second group, a third group, a fourth group, or a fifth group, and when each microRNA belongs to the first group, the second group, the third group, the fourth group, or the fifth group, one red dot is shown, the first group indicates that the microRNA of that type simultaneously belongs to H type and U type, the second group indicates that the microRNA of that type simultaneously belongs to M type and U type, the third group indicates that the microRNA of that type simultaneously belongs to Cn type and U type, the fourth group indicates that the microRNA of that type simultaneously belongs to H type and D type, and the fifth group indicates that the microRNA of that type simultaneously belongs to M type and D type, and when the number of red dots is greater than or equal to 5, it indicates that there is a health risk in the subject; In the step of creating a database of microRNA expression levels for the healthy population, plasma samples from the healthy population are collected, and the expression levels of 167 microRNAs in the plasma samples are detected. The average value and standard deviation of each microRNA expression level in the healthy population are calculated, and based on the average value and standard deviation, a reference range of each microRNA expression level in the healthy population is calculated. A database of the expression levels of these 167 microRNAs in the healthy population is created, and the 167 microRNAs are as shown in Table 1 below: The health risk assessment method, wherein the assessment of health risk is a risk assessment for cancer or diabetes. 【Table 1】

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