KR101873303B1 - Age Predicting method using DNA Methylation level in saliva - Google Patents
Age Predicting method using DNA Methylation level in saliva Download PDFInfo
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- KR101873303B1 KR101873303B1 KR1020170010915A KR20170010915A KR101873303B1 KR 101873303 B1 KR101873303 B1 KR 101873303B1 KR 1020170010915 A KR1020170010915 A KR 1020170010915A KR 20170010915 A KR20170010915 A KR 20170010915A KR 101873303 B1 KR101873303 B1 KR 101873303B1
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Abstract
Description
The present invention relates to an age estimation method using DNA methylation in saliva. More particularly, the present invention relates to a method for predicting the age of a test subject by measuring the level of methylation (DNA methylation and non-methylation ratio) of a target gene in a saliva sample to be tested to a specific CpG site .
In the field of forensic science and forensic medicine, various biological evidence found in crime scenes can be used to obtain evidence that is legally valid, to set the course of investigation, to identify the cause and type of death, to estimate postmortem time, It plays a role. However, in cases where the suspect is not specified, even if the DNA genotypic results are effectively obtained from the evidence, if the suspects do not appear in the analysis and the DNA database, the incident remains untreated. Thus, in order to obtain additional information related to criminal suspects from evidence, methods have been developed in Europe and elsewhere in the West to estimate suspects through the analysis of color genetic information such as skin, hair, and iris, and some countries use it for investigation . However, it is impossible to apply it effectively in the Asian region including Korea.
In recent years, many studies have been conducted because estimating the age and narrowing the range of suspects can be applied regardless of race or ethnicity. So far, the most effective biomarker for age estimation is known as DNA methylation marker.
The method of predicting the age by methylation measurement of a gene is mainly for blood samples (Non-Patent Document 1), and it is required to analyze methylation in 70 or more genes in various tissues (Non-Patent Document 2 ). As a relatively simple method compared to blood or tissue analysis, the method of predicting age by saliva or oral epithelium analysis is based on the method of predicting the age of the test subject by measuring methylation in three gene markers (Non-Patent Documents 3 and 4) The accuracy is not high.
Therefore, there is a need for a method of quickly and accurately predicting the age by analyzing the minimum gene marker required for age prediction or the selection of a specific CpG site in the gene and the methylation of the marker.
SUMMARY OF THE INVENTION It is an object of the present invention to provide a method and apparatus for measuring methylation level and non-methylation level at a specific CpG position in a saliva sample from a test subject, And to provide an age prediction kit or a method for predicting the age of the subject.
However, the technical problem to be solved by the present invention is not limited to the above-mentioned problems, and other matters not mentioned can be clearly understood by those skilled in the art from the following description.
In order to solve the above problems, the inventors of the present invention have found that the kind of CpG to be analyzed in a saliva sample to be inspected is selected, and the ratio of DNA methylation and unmethylation of the selected marker is measured, Prediction method.
Hereinafter, various embodiments described herein will be described with reference to the drawings. In the following description, for purposes of complete understanding of the present invention, various specific details are set forth, such as specific forms, compositions and processes, and the like. However, certain embodiments may be practiced without one or more of these specific details, or with other known methods and forms. In other instances, well-known processes and techniques of manufacture are not described in any detail, in order not to unnecessarily obscure the present invention. Reference throughout this specification to "one embodiment" or "embodiment" means that a particular feature, form, composition, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Accordingly, the appearances of the phrase " in one embodiment "or" an embodiment "in various places throughout this specification are not necessarily indicative of the same embodiment of the present invention. In addition, a particular feature, form, composition, or characteristic may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise in the application, all scientific and technical terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
An object of the present invention is to provide a saliva sample which can be used as a sample for oral administration to a patient in need thereof, which comprises PTPN7 (protein tyrosine phosphatase), SST (somatostatin), CNGA3 (cyclic nucleotide gated channel alpha 3), KLF14 (cg18384097, cg00481951, cg19671120, cg14361627, cg08928145, cg12757011, and the like) containing the testis specific serine kinase 6, TBR1 (T-box, brain 1) and SLC12A5 (solute carrier family 12 member 5) cg07547549), and to provide a kit for predicting the age of the subject or a kit for predicting the age of the subject to be examined.
In one embodiment of the present invention, there is provided a method for providing information about a subject's age prediction, comprising a methylation assay step for a specific CpG marker of a gene in a sample obtained from a subject, PTPN7 (protein tyrosine phosphatase, non-receptor type 7), SST (somatostatin), CNGA3 (cyclic nucleotide gated channel alpha 3), KLP14 (Kruppel like factor 14), TSSK6 (testis specific serine kinase 6), TBR1 , brain 1), and SLC12A5 (solute carrier family 12 member 5). The present invention provides a method for providing information on the age prediction of a subject.
In this embodiment, the CpG marker is cg18384097 for PTPN7, cg00481951 for SST, cg19671120 for CNGA3, cg14361627 for KLF14, cg08928145 for TSSK6, cg12757011 for TBR1 and cg07547549 for SLC12A5, Is a measure of the K value as a ratio of methylation and unmethylation levels in each CpG marker,
In another embodiment of the present invention, there is provided an age prediction kit for a subject comprising a primer set for methylation analysis of a CpG marker in a gene group including PTPN7, SST, CNGA3, KLF14, TSSK6, TBR1 and SLC12A5 Respectively. In this embodiment, the primer set comprises a PCR primer set of SEQ ID NOS: 1 to 14 for amplifying a fragment comprising a methylated portion of a CpG marker and a single base extension (SBE) primer for PCR products amplified by the primer set, Wherein the CpG marker is selected from the group consisting of cg18384097 for PTPN7, cg00481951 for SST, cg19671120 for CNGA3, cg14361627 for KLF14, cg08928145 for TSSK6, TBR1 CG12757011 for SLC12A5, and cg07547549 for SLC12A5. In this embodiment, the subject-derived sample is any one selected from the group consisting of body fluids, hair follicles, blood, plasma, serum and saliva, A kit for predicting the age of the subject was provided.
In another embodiment of the present invention, an analysis unit for measuring the methylation level of a gene in a sample obtained from a subject; And a calculation unit for calculating the age of the subject from the measurement result of the methylation level, wherein the gene is one or more genes selected from the group consisting of PTPN7, SST, CNGA3, KLF14, TSSK6, TBR1, and SLC12A5 Of age. In this embodiment, the CpG marker is cg18384097 for PTPN7, cg00481951 for SST, cg19671120 for CNGA3, cg14361627 for KLF14, cg08928145 for TSSK6, cg12757011 for TBR1, and cg07547549 for SLC12A5, The methylation level measurement measures the K value as a ratio of methylation and non-methylation levels in each CpG marker,
In the present invention, the term "biological sample" refers to all samples that can confirm the genetic information of the subject. Preferably, the sample can be blood, plasma, serum, saliva and the like.
The term "DNA methylation" in the present invention refers to a process for methylating a base at a specific position on a DNA sequence, which occurs in a CpG nucleotide sequence in which cytosine and guanine are consecutively present in a base sequence constituting a gene sequence 5), the methylation of the CpG nucleotide sequence is formed by DNA methyltransferase. In addition, bisulfite converted DNA refers to single-stranded DNA in which unmethylated cytosine is converted to uracil by sodium bisulfite treatment. The cytosine methylated by sodium bisulfite treatment remains cytosine as it is, but the unmethylated cytosine is converted to uracil, so methylation of the DNA can be detected by performing a single nucleotide polymorphism test on bisulfite converted DNA.
In the present invention, the term "kit" means a device for examining a CpG marker having a correlation with an age prediction target and providing information necessary for age prediction. The DNA methylation rate of the CpG marker from the biological sample There is no limit to the type that can be confirmed. Preferably a probe or a primer set having a complementary sequence to the bisulfite converted DNA sequence of the gene containing the CpG marker, wherein the "probe" or "primer" The oligonucleotide having a complementary sequence capable of specifically binding to the bisulfite converted DNA sequence of the gene including the CpG markers cg18384097, cg00481951, cg19671120, cg14361627, and cg08928145, which are necessary for the age prediction model of the present invention, , cg12757011, and cg07547549. In the present invention, the term "diagnostic device" predicts the age of the subject from the measurement of the methylation level of CpG marker (cg18384097, cg00481951, cg19361127, cg08928145, cg12757011 and cg07547549) of the gene in the saliva sample obtained from the subject. There is no restriction as long as it can measure the methylation level of the CpG marker in the subject-derived sample and predict the age of the subject.
In the present invention, "PCR (Polymerase Chain Reaction)" is a simple and convenient method for exponentially amplifying a DNA sequence at a specific site using only a small amount of DNA, And DNA amplification is performed by repeatedly performing denaturation, annealing, and extension using a stable Taq DNA polymerase at high temperatures. The detection of the target gene using PCR is performed by amplifying and confirming the gene using a primer recognizing the gene.
In the present invention, "Multiplex PCR" is intended to perform an experimental reaction in a single tube by inserting primers of several loci into a single PCR reaction. If a multiplex PCR system is used, (PCR reaction enzyme) used in the analysis, and the cost of the genotype capillary automatic analyzer can be minimized, thereby reducing the cost. In particular, the gene methylation analysis using DNA methylation analysis has a merit that the budget saving effect can be considerably taken in consideration that the commercially available expensive reaction reagents are consumed. In this way, researches have been actively conducted to establish a multiplex PCR system suitable for the local reality in advanced countries such as the United Kingdom and the United States leading to gene identification due to the utility value of the multiplex PCR system.
The term " multiplex snapshot reaction "in the present invention refers to a primer-based single base extension (SBE) method developed for SNP analysis, in which a single primer is used per SNP and analysis is performed from a multiplex reaction to several SNPs can do. The term " single nucleotide polymorphism " (SNP) is the most common type of human gene mutation. One of the nucleotide sequences consisting of A, T, C and G on the genome is changed to another nucleotide sequence . Two-thirds of these SNPs are known to be mutations in the nucleotide sequence between C and T, and it is known that SNP mutations usually occur once per 1000 nucleotides in the genomic sequence. In addition, SNPs account for about 90% of mutations in human genomes, and people with similar traits or families have the same or similar SNP patterns, so clinical susceptibility to disease in individuals And can also be used as an indicator for predicting the effects and side effects of drugs.
In the present invention, "determination" includes quantitative and / or qualitative analysis, including detection of presence and absence and concentration measurement, and such methods are well known in the art, and those skilled in the art will appreciate that suitable methods You will be able to choose. In the present invention, "discrimination" means to measure the methylation level and the non-methylated level of the CpG marker of the gene target in the saliva sample from the test subject to distinguish the expected age for the test subject.
The age of the test subject can be predicted by measuring the level of DNA methylation in the saliva sample from the test subject and analyzing the methylation ratio using the age prediction method according to the present invention.
In particular, the number of markers to be analyzed is reduced to seven and the accuracy of age estimation is improved compared with the method using three CpG markers in saliva, compared with the conventional method of predicting DNA methylation in human body fluid samples . The age prediction method according to the present invention is less expensive than the conventional various methylation analysis methods and can reduce the error range of the measured age predicted value and can quickly and accurately measure the age of the test subject.
Figure 1 relates to the results of measuring methylation and non-methylation levels of specific CpG positions in seven gene targets according to the present invention.
FIG. 2 is a flowchart for deriving an age prediction formula from the methylation data to be tested in the present invention.
Figure 3 relates to variables in an age prediction model using methylation and unmethylation ratios of specific CpG positions in seven gene targets according to the present invention.
FIG. 4 is a result of comparing the estimated age of the test subject calculated using the age prediction model according to the present invention with the actual age of the test subject.
Hereinafter, the present invention will be described in detail with reference to the following examples. However, the following examples are illustrative of the present invention, and the contents of the present invention are not limited by the following examples.
In the present invention, a sample derived from an object to be examined used in the age prediction may be blood or saliva as a sample capable of DNA methylation analysis, but is not limited thereto.
Analysis target ( CpG Marker ) Selection
Analysis of the methylation and non-methylation mutations of more than 450,000 CpG markers by Illumina's HumanMethylation 450 Beadchip array was performed on saliva DNA from 54 subjects of various ages and correlated with actual age and correlation ) Were selected as 62 CpG marker candidates. For constructing the age estimation model, stepwise linear regression analysis was performed on these 62 CpGs. Four CpG markers with statistical significance were selected first. Among the candidate markers, Two markers and one CpG marker, which was previously used to distinguish between blood and saliva, were additionally selected. In the case of the cell type division marker (cg18384097), it was selected with reference to the previously reported document (Non-Patent Document 6). As a result, a total of seven CpG markers including six age-related CpG markers and one cell type-specific CpG marker in saliva were determined (see Table 1).
Multiplex PCR
2.1 Experimental Material
Multiplex PCR was performed to verify whether it could be used to predict the age of the subject by simultaneous analysis of the seven gene targets selected by the above method.
Experimental materials required for multiplex PCR include bisulfite converted DNA (PCR template), 5X primer mix, polymerase (purchased from AmpliTaq Gold ® DNA Polymerase (Applied Biosystems, Foster City, CA) Gold ST * R 10X Buffer, purchased from Promega, Madicine, Wis.).
The sequences of the CpG markers to be analyzed in the seven gene targets were identified and primer hybridization temperature and PCR product size (100 to 200 bp) were determined using the Methprimer program and the Pyromark 2.0 program for the sequences. Similar conditions were selected to design the primer sequence.
The sequence and composition of the 5X primer mixture for carrying out the multiplex PCR are shown in Table 2 below.
designation
(5 '- >3')
(μM)
size
(bp)
number
2.2 Experimental Method
The composition of the PCR mixture for carrying out the multiplex PCR is shown in Table 3 below.
Conditions for carrying out the multiplex PCR are shown in Table 4 below.
35
PCR Post-reaction treatment
3.1 Enzyme purification of multiplex PCR products
The components and reaction conditions necessary for the purification of the enzyme (SAP or CIP) of the multiplex PCR product are shown in Table 5 below.
(USB, Cleveland, OH)
3.2 Multiplexed Snapshot (SNaPshot)
Materials required for the reaction is a three kinds of 10X SBE Primer Mix, 5X Sequencing buffer_BigDye Termination (Applied Biosystems, Foster City, CA), SNaPshot TM Kit (Applied Biosystems, Foster City, CA) and, 10X SBE is marking composition of the primer mixture 6.
In order to prepare a primer sequence for SBE for the product prepared according to Example 3.1 above, a primer sequence was designed by selecting similar conditions for the primer hybridization temperature using the BatchPrimer3 program.
designation
number
The composition and reaction conditions of the reaction mixture for the SBE reaction are shown in Table 7 below.
10X SBE Primer Mix
5X Sequencing Buffer
SNaPshot Reaction Mix
Purified PCR Product
One
2
One
> 1
25
SBE (Single Base Extension) Post-reaction processing
4.1 Treatment of enzymes (SAP or CIP)
The composition and reaction conditions of the enzyme-treated reaction product for the SBE reaction products are shown in Tables 8 and 9 below.
(USB, Cleveland, OH)
4.2 Capillary Electrophoresis
Materials necessary for the implementation of capillary electrophoresis are a dry heating block, a water bath or thermal cycler, a 3130 capillary (33 cm x 50 μm; Applied Biosystems, Foster City, Calif.), (DS-02'dR110, dR6G, dTAMRA 占 dROX 占 LIZ 占 Dyes'; Applied Biosystems, Foster City, Calif.), Run Module GS STR POP4 (1 mL) E5, GeneScan TM 120 LIZ TM Size Standard, and Hi-Di TM Formamide (Applied Biosystems, Foster City, CA).
The matrix was prepared using the ABI PRISM®SnaPshot ™ Multiplex Kit according to the manufacturer's manual.
The configuration and thermal cycling conditions required for capillary electrophoresis are shown in Tables 10 and 11 below.
Capillary electrophoresis was performed under the conditions described in Table 12 below.
The electrophoresis results were verified using 3130 data acquisition software.
Analysis
5.1 Electrophorogram
As shown in FIG. 1, the multiplex methylated SNaPshot product according to the present invention was subjected to electrophoresis by electrophoresis to determine methylation and non-methylation levels in the target gene. Since all SBE primers were produced in reverse orientation, the blue peak represents nucleotide G as a methylated signal and the green peak represents nucleotide A as an unmethylated signal (see FIG. 1).
5.2 Deriving Formulas for Age Forecasting
Through the Multiplex SNaPshot procedure, methylation data for 7 CpGs were obtained from 226 saliva samples. A set of 226 randomly divided test subjects was divided into a training set to derive formulas and a set to be tested to verify derived formulas (see Table 13).
(chromological age)
For reference, only the results for 15 persons are shown in Table 13. Training set Multivariate linear regression analysis was performed on DNA methylation data from aged 113 subjects and 7 CpG markers using SPSS 23.0 from IBM (see FIG. 2), and the results were summarized Reference).
To verify the accuracy of the model equation obtained from the training set, the age was estimated using DNA methylation data from 113 testing sets and compared with the actual age. At this time, the mean absolute deviation from chronological age (MAD) of both the training set and the testing set was around 3 years old.
5.3 Age Prediction Model
The results of the methylation and non-methylation analysis according to Example 5.1 and the procedure of Example 5.2 were used to construct an age prediction model as shown in Table 15 below (see red mark in FIG. 2).
(Coefficient)
+ (-29.088) x cg18384097
+ 9.285 × cg00481951
+ 46.992 x cg19671120
+ 86.268 x cg14361627
+ 32.211 x cg08928145
+ 58.699 x cg12757011
+ 56.384 × cg07547549
± 2 RMSE
In Table 15, B indicates the height of the blue peak indicating methylation, and G indicates the height of the green peak indicating unmethylated (see Fig. 1). Values such as B or G are in the range of 0 to 1. The CpG marker (e.g., cg18384097) described in the predicted age calculation has a corresponding methylation value
The age prediction model shown in Table 13 was applied to 226 samples to be inspected in Example 5.2, and the age was calculated and analyzed (see FIG. 4). In Fig. 4, the left side is a set used to derive an age prediction model equation as a training set. The horizontal axis represents the actual age, the vertical axis represents the estimated age, and the diagonal line is a straight line of y = x, which means that the closer to the diagonal line the closer the actual age to the estimated age. The training set has a mean absolute deviation (MAD) of 3.13 years and a RMSE of 4.16 years. In Fig. 4, the right side is a testing set for verifying the model, and the composition of the graph is the same as the left side. In the testing set, the MAD is 3.15 and the error is 4.34, which is similar to the training set.
In the present invention, an age prediction model is constructed as shown in Table 15 by measuring methylation and non-methylation levels of seven markers that are less than the CpG marker used in the conventional age prediction method. Using the age prediction method according to the present invention, it is possible to predict the age of the test subject accurately and with an improved error rate and a lower cost than the existing age prediction method (e.g., Pyrosequencing).
All references, articles, publications and patents and patent applications cited herein are hereby incorporated by reference in their entirety. Accordingly, the spirit and scope of the following claims should not be limited to the description of the preferred embodiments described above.
<110> YONSEI UNIVERSITY <120> Age Predicting method using DNA Methylation level in saliva <130> DPB167058 <160> 21 <170> KoPatentin 3.0 <210> 1 <211> 25 <212> DNA <213> Artificial Sequence <220> <223> human cg18384097_PTPN7-F <400> 1 ttgttttagt aagtatttga agggg 25 <210> 2 <211> 25 <212> DNA <213> Artificial Sequence <220> <223> human cg18384097_PTPN7-R <400> 2 catcaaatct ataaacaccc atacc 25 <210> 3 <211> 29 <212> DNA <213> Artificial Sequence <220> <223> human cg00481951_SST-F <400> 3 aggtgagttt ttatttggta tttaagaaa 29 <210> 4 <211> 25 <212> DNA <213> Artificial Sequence <220> <223> human cg00481951_SST-R <400> 4 tttaaattac ccctttaccc taatc 25 <210> 5 <211> 24 <212> DNA <213> Artificial Sequence <220> <223> human cg19671120_CNGA3-F <400> 5 ggagagggag gttataggtt tttt 24 <210> 6 <211> 26 <212> DNA <213> Artificial Sequence <220> <223> human cg19671120_CNGA3-R <400> 6 tccttaccct accaaaattt aaactt 26 <210> 7 <211> 23 <212> DNA <213> Artificial Sequence <220> <223> human cG14361627_KLF14-F <400> 7 aggttgttgt aatttagaag ttt 23 <210> 8 <211> 30 <212> DNA <213> Artificial Sequence <220> <223> human cG14361627_KLF14-R <400> 8 atatttaaca acctcaaaaa ttatcttatc 30 <210> 9 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> human cg08928145_TSSK6-F <400> 9 agggaagygg aagggaaaaa g 21 <210> 10 <211> 30 <212> DNA <213> Artificial Sequence <220> <223> human cG08928145_TSSK6-R <400> 10 actaaaaacc raataattcc aaccattcct 30 <210> 11 <211> 24 <212> DNA <213> Artificial Sequence <220> <223> human cg12757011_TBR1-F <400> 11 gggtgggttt aggttttaga gtta 24 <210> 12 <211> 25 <212> DNA <213> Artificial Sequence <220> <223> human cg12757011_TBR1-R <400> 12 ataaaattat cctcctacaa ttccc 25 <210> 13 <211> 23 <212> DNA <213> Artificial Sequence <220> <223> human cg07547549_SLC12A5-F <400> 13 ggtttagtta atttaagtta gtt 23 <210> 14 <211> 25 <212> DNA <213> Artificial Sequence <220> <223> human cg07547549_SLC12A5-R <400> 14 aaactcaact ccattaaaat actcc 25 <210> 15 <211> 24 <212> DNA <213> Artificial Sequence <220> <223> human PTPN7_cg18384097-SBE <400> 15 cataccccaa ccaaacacta taac 24 <210> 16 <211> 24 <212> DNA <213> Artificial Sequence <220> <223> human SST_cg00481951-SBE <400> 16 ccaaaatcaa caccaaaaat aaac 24 <210> 17 <211> 22 <212> DNA <213> Artificial Sequence <220> <223> human CNGA3_cg19671120-SBE <400> 17 ctaccaaaat ttaaacttct cc 22 <210> 18 <211> 29 <212> DNA <213> Artificial Sequence <220> <223> human KLF14_cg14361627-SBE <400> 18 ttaacaacct caaaaattat cttatctcc 29 <210> 19 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> human TSSK6_cg08928145-SBE <400> 19 ccaaaaacac taaaccaaaa c 21 <210> 20 <211> 27 <212> DNA <213> Artificial Sequence <220> <223> human TBR1_cg12757011-SBE <400> 20 acctaaacaa tcctatcaaa caacaac 27 <210> 21 <211> 27 <212> DNA <213> Artificial Sequence <220> <223> human SLC12A5_cg07547549-SBE <400> 21 craacrctat ccaaaatact aaaatac 27
Claims (19)
These genes include PTPN7 (protein tyrosine phosphatase, non-receptor type 7), SST (somatostatin), CNGA3 (cyclic nucleotide gated channel alpha 3), KLP14 (Kruppel like factor 14), TSSK6 (testis specific serine kinase 6) T-box, brain 1), and SLC12A5 (solute carrier family 12 member 5)
The CpG marker provides information about the subject's age prediction, which is cg18384097 for PTPN7, cg00481951 for SST, cg19671120 for CNGA3, cg14361627 for KLF14, cg08928145 for TSSK6, cg12757011 for TBR1, and cg07547549 for SLC12A5 How to.
Wherein the methylation analysis step measures the K value as a ratio of methylation and unmethylation levels of each CpG marker,
The methylation analysis step may be carried out by measuring the K value for each CpG marker (
The calculating step calculates the K value for the formula "N 1 + N 2 x cg18384097 (
Wherein N 1 is -27 through -28, and the N 2 is -28.5 to -29.5, and said N 3 is 9 to 10, and N 4 is the 46.5 to 47.5 and the N 5 is 86 to 87 and the N is 6 to 32 33, wherein N 7 is from 58 to 59, N 8 is from 56 to 57, and the RMSE is from 4 to 5.
Wherein the sample obtained from the subject is any one selected from the group consisting of body fluids, hair follicles, blood, plasma, serum, and saliva.
Wherein the CpG marker is a subject's age prediction kit, wherein the CpG marker is cg18384097 for PTPN7, cg00481951 for SST, cg19671120 for CNGA3, cg14361627 for KLF14, cg08928145 for TSSK6, cg12757011 for TBR1, and cg07547549 for SLC12A5. .
The primer set includes a PCR primer set of SEQ ID NOS: 1 to 14 for amplifying a fragment containing a methylated portion of a CpG marker, and a PCR primer set for amplifying a PCR product amplified by the primer set using a single base extension A kit for predicting the age of a subject, which is a primer set of SEQ ID NOS: 15 to 21.
Wherein the body fluid-derived sample is any one selected from the group consisting of body fluids, hair follicles, blood, plasma, serum, and saliva.
And an arithmetic unit for calculating an age of the subject from the result of the methylation level measurement,
These genes are PTPN7, SST, CNGA3, KLF14, TSSK6, TBR1, and SLC12A5 genes,
Wherein the CpG marker is cg18384097 for PTPN7, cg00481951 for SST, cg19671120 for CNGA3, cg14361627 for KLF14, cg08928145 for TSSK6, cg12757011 for TBR1, and cg07547549 for SLC12A5.
The methylation level measurement measures the K value as a ratio of methylation and unmethylation levels of each CpG marker,
The methylation level measurement is based on the K value for each CpG marker (
Wherein N 1 is -27 through -28, and the N 2 is -28.5 to -29.5, and said N 3 is 9 to 10, and N 4 is the 46.5 to 47.5 and the N 5 is 86 to 87 and the N is 6 to 32 33, wherein N 7 is 58 to 59, N 8 is 56 to 57, and the RMSE is 4 to 5.
Wherein the sample obtained from the subject is any one selected from the group consisting of body fluids, hair follicles, blood, plasma, serum, and saliva.
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| KR20200101084A (en) * | 2019-02-19 | 2020-08-27 | 바이오코아 주식회사 | Age estimation method using body fluids |
| KR20220008133A (en) * | 2020-07-13 | 2022-01-20 | 대한민국(관리부서: 행정안전부 국립과학수사연구원장) | Method for bone age predeiction and marker thereof |
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| WO2022058980A1 (en) | 2020-09-21 | 2022-03-24 | Insilico Medicine Ip Limited | Methylation data signatures of aging and methods of determining a methylation aging clock |
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| US20150259742A1 (en) * | 2012-11-09 | 2015-09-17 | The Regents Of The University Of California | Methods for predicting age and identifying agents that induce or inhibit premature aging |
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| KR102170423B1 (en) * | 2019-02-19 | 2020-10-27 | 바이오코아 주식회사 | Age estimation method using body fluids |
| KR20220008133A (en) * | 2020-07-13 | 2022-01-20 | 대한민국(관리부서: 행정안전부 국립과학수사연구원장) | Method for bone age predeiction and marker thereof |
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