KR101673148B1 - Biomarker for predicting of sensitivity to exercise - Google Patents

Abstract

The present invention relates to a method for predicting aerobic exercise sensitivity using a marker, a method for providing information for predicting aerobic exercise sensitivity using the marker, and a method for predicting aerobic exercise sensitivity using a marker, The present invention relates to a kit for predicting aerobic exercise sensitivity comprising a composition for predicting aerobic exercise sensitivity comprising a probe capable of detecting a marker. The present invention also provides a method for predicting anaerobic exercise sensitivity using a marker, a method for providing information for predicting anaerobic exercise sensitivity using the marker, And a probe capable of detecting the marker. The present invention also relates to a kit for predicting anaerobic exercise sensitivity, comprising the composition for predicting anaerobic exercise sensitivity. According to the present invention, the oil / anaerobic exercise sensitivity of an individual can be predicted, and an exercise program suitable for the characteristics of an individual before or during the exercise can be presented.

Description

Biomarker for predicting of sensitivity to exercise}

The present invention is a single nucleotide polymorphic marker capable of predicting aerobic exercise sensitivity as a biomarker, a method of predicting aerobic exercise sensitivity using the marker, a method of providing information to predict aerobic exercise sensitivity using the marker, and It relates to a kit for predicting aerobic exercise sensitivity comprising a composition for predicting aerobic exercise sensitivity including a probe capable of detecting the marker.

The present invention also provides a single nucleotide polymorphic marker capable of predicting anaerobic exercise sensitivity as a biomarker, a method of predicting anaerobic exercise sensitivity using the marker, and a method of providing information to predict anaerobic exercise sensitivity using the marker It relates to a kit for predicting anaerobic exercise sensitivity comprising a composition for predicting anoxic exercise sensitivity including a probe capable of detecting the marker.

With the development of science and the spread of computers, the physical activity of modern people has decreased, and modern people have suffered from lack of exercise. Lack of exercise is known to be an important risk factor for all adult diseases such as hypertension, diabetes, obesity, heart disease, hyperlipidemia, etc., causing a decrease in immunity as well as stamina. Accordingly, the importance of exercise has begun to be emphasized in order to maintain and improve health, and in fact, many modern people feel the necessity of exercise to reinforce physical strength. Exercise is becoming important not only to promote health, but also to develop a beautiful body. In fact, there is a growing trend of people looking for exercise to lose weight.

Since the effect of such exercise can be obtained by steadily performing exercise over a certain period of time, modern people are investing a lot of time and money in exercise.

Meanwhile, even when the same time and effort are invested, the exercise effect may vary according to the physical characteristics of the exerciser. Therefore, in order to obtain an effective exercise effect, the necessity of prediction of exercise sensitivity according to the physical characteristics of each exerciser is emerging.

International Patent Publication No. 2010-028256 discloses a biomarker for predicting exercise sensitivity expressed by such maximum oxygen intake.

International Publication Patent No. 2010-028256

An object of the present invention is to provide a single base polymorphic marker capable of effectively predicting the sensitivity of exercise to aerobic/anaerobic exercise.

The present invention predicts the sensitivity of aerobic exercise of an individual, comprising identifying the base of a polymorphic site of one or more single nucleotide polymorphic markers selected from single nucleotide polymorphic markers shown in Tables 1 and 2 from a nucleic acid sample isolated from an individual. Provides a way of providing information to do so.

The present invention also includes identifying the base of the polymorphic site of one or more single nucleotide polymorphic markers selected from the single nucleotide polymorphic markers shown in Tables 7 and 8 from a nucleic acid sample isolated from the subject. It provides a method of providing information to predict.

The present invention also predicts aerobic exercise sensitivity including a probe capable of detecting one or more single nucleotide polymorphic markers selected from single nucleotide polymorphic markers shown in Tables 1 and 2 or a primer capable of amplifying the single nucleotide polymorphic marker. It provides a kit for predicting aerobic exercise sensitivity, including a composition for use.

The present invention also predicts anaerobic exercise sensitivity including a probe capable of detecting one or more single nucleotide polymorphic markers selected from single nucleotide polymorphic markers shown in Tables 7 and 8 or a primer capable of amplifying the single nucleotide polymorphic marker. It provides a kit for predicting anaerobic exercise sensitivity, including a composition for use.

According to the present invention, since it is possible to predict the sensitivity of an individual's oxygen/anaerobic exercise, it is possible to present an exercise program suitable for the characteristics of the individual before or during exercise.

1 shows the main SNP extraction process of the exercise sensitivity prediction model.
2 shows a process of building and evaluating a model for predicting aerobic exercise sensitivity.
3 shows a model construction and evaluation process for predicting anaerobic exercise sensitivity.

The present inventors assume that if the exercise effect according to the individual's genetic characteristics can be predicted in advance, it is assumed that a personalized exercise program capable of achieving excellent exercise effect in time and cost-effective manner can be presented, and the results of this study, The present invention was completed by discovering a specific single nucleotide polymorphism marker having a significant correlation with the sensitivity to anoxic/oxygen movement.

Accordingly, the present invention provides the use of a single nucleotide polymorphic marker capable of predicting exercise sensitivity in aerobic/ anoxic exercise.

The present invention relates to a marker for predicting exercise sensitivity, including one or more single-base polymorphic markers selected from single-base polymorphic markers capable of predicting exercise sensitivity, in aerobic/anaerobic exercise, and a method for predicting exercise sensitivity using the marker , Provides a kit for predicting the sensitivity of an anoxic exercise, including a method of providing information to predict exercise sensitivity using the marker, and a composition for predicting anoxic exercise sensitivity including a probe capable of detecting the marker do.

Specifically, the present invention comprises identifying the base of the polymorphic site of one or more single nucleotide polymorphic markers selected from the single nucleotide polymorphic markers of the present invention from a nucleic acid sample isolated from the subject, predicting the sensitivity of aerobic exercise in an individual. Provides a way to provide information for the purpose.

The present invention also includes identifying the base of the polymorphic site of one or more single nucleotide polymorphic markers selected from the single nucleotide polymorphic markers of the present invention from a nucleic acid sample isolated from the subject, Provides a way to present information.

The term'polymorphism' refers to the coexistence of one or more forms in a nucleic acid including exons and introns, or a portion thereof. 'Single Nucleotide Polymorphism'or'SNP' refers to a case in which two or more single bases exist at a specific position in a gene. Most SNPs have two alleles. For one allele of the polymorphism, having two identical alleles is called homozygous for the allele (having the same base at the SNP position), and having two different alleles is heterozygous for the allele (SNP Have different bases at the position). Preferred SNPs have two or more alleles exhibiting an incidence of at least 1%, more preferably at least 10% or 20% in the selected population. In the present invention, the SNP name is represented by rs ID or kgp ID. Rs ID refers to the official SNP (Reference SNP, rs) ID assigned to each unique SNP in the National Center for Biotechnological Information (NCBI) . Kgp ID refers to the SNP included in the human omni 2.5M 8 BeadChip kit manufactured and marketed by Illumina, Inc., USA, a SNP chip manufacturer. Is shown. In the present invention, the SNP expressed in kgp was analyzed based on hg19 (human genome version 19).

The term'allele' refers to an alternative form of a gene comprising introns, exons, intron/exon junctions and 3'and/or 5'untranslated regions associated with a gene or a portion thereof. In general, an allele refers to several types of a gene that exist at the same locus on a homologous chromosome. Alleles of a particular gene may differ by a single nucleotide or several nucleotides from each other and may include substitutions, deletions and insertions of nucleotides.

The term “marker”, “polymorphic marker” or “single nucleotide polymorphic marker” refers to a genomic polymorphic site of a gene. Each polymorphic marker has two or more sequence variations characteristic of a particular allele at the polymorphic site.

In this specification, the sequence list was prepared according to the Korean Intellectual Property Office Notice No. 2013-01 [Nucleate group sequence list or amino acid sequence list preparation standard]. In the nucleic acid sequence, the symbol r represents g (guanine) or a (adenine), and the symbol y represents t (thymine)/u (uracil) or c (cytosine). The symbol m represents a or c, and k represents g or t/u. The symbol s represents g or c, and the symbol w represents a or t/u.

In the present specification, the term'aerobic exercise' refers to an exercise in which oxygen is supplied to the muscles by continuing at a relatively low intensity. Examples of aerobic exercise include walking, jogging, aerobics, jumping rope, swimming, biking, mountain climbing, and the like. 'Anaerobic exercise' refers to an exercise of sufficient intensity to trigger lactic acid formation in the absence or lack of oxygen. Examples of anaerobic exercises include push-ups, weight lifting, squats, and the like.

The term'sensitivity to exercise' refers to the ability of a living body to respond to exercise, and refers to the responsiveness of a living body to exercise. For example, when the exercise sensitivity is high, the level of changes in the living body that occurs in response to exercise such as maximum oxygen intake or increase in muscle strength is high, and on the contrary, when the exercise sensitivity is low, the level of changes in the living body in response to exercise is low. 'Aerobic exercise sensitivity' is an exercise sensitivity to aerobic exercise, but is not limited thereto, but may be expressed as aerobic capacity and/or maximum oxygen intake. The'anaerobic exercise sensitivity' is an exercise sensitivity to anoxic exercise, but is not limited thereto, but may be expressed as an anoxic ability and/or an increase in muscle strength.

'Aerobic capacity' refers to the ability to convert energy during aerobic processes in the process of energy conversion, and is related to the ability to carry oxygen such as breathing, circulation, and blood, or to the use of oxygen by tissues, and is closely related to systemic endurance. There is. Decreased aerobic capacity can lead to fatigue and ischemic heart disease. Aerobic capacity can be raised through aerobic exercise and can generally be assessed as maximum oxygen intake. 'Maximal oxygen consumption (maximal oxygen uptake; VO2max)' refers to the maximum oxygen consumption in a unit of time measured during exercise. The maximum oxygen intake is used as an index to determine aerobic capacity or cardiopulmonary endurance.

'Anaerobic capacity' is a concept that contrasts with aerobic capacity, and refers to the ability to convert energy in an anaerobic process without using oxygen. Anaerobic ability can be raised through anaerobic exercise, and can be evaluated as an increase in muscle strength. The'muscle strength increase' refers to an increase in muscle strength (muscle strength) caused by muscle contraction, and may be expressed as a peak torque. Torque means the force that rotates an object, and'peak torque' means the maximum torque value.

The term'subject' refers to a subject for predicting the exercise sensitivity of aerobic/anaerobic exercise, and'nucleic acid sample' refers to a sample containing a nucleic acid (DNA or RNA) obtained from an individual. Nucleic acid samples include blood, urine, hair, amniotic fluid, cerebrospinal fluid collected from an individual; Or skin, muscle, oral mucosa or conjunctival mucosa; It can be obtained from any source containing nucleic acids, such as tissue samples from the placenta, gastrointestinal tract or other organs. Methods for obtaining a nucleic acid sample from an individual are well known in the art, and known methods can be used without limitation.

From a nucleic acid sample isolated from an individual, a polymorphic site of a single nucleotide polymorphic marker may be amplified or hybridized with a probe capable of detecting a single nucleotide polymorphic marker to identify the base of the polymorphic site.

For example, polymorphic sites can be amplified using PCR, ligase chain reaction (LCR), transcription amplification, self-maintained sequence replication, and nucleic acid-based sequence amplification (NASBA).

The identification of the base of the polymorphic site is sequencing analysis, hybridization by microarray, allele specific PCR, dynamic allele-specific hybridization (DASH), PCR extension analysis, SSCP, PCR-RFLP analysis, TaqMan technique, SNPlex platform (Applied Biosystems), mass spectrometry (e.g. Sequenom's MassARRAY system), mini-sequencing method, Bio-Plex system (BioRad), CEQ and SNPstream systems (Beckman), Molecular Inversion Probe array technology (eg, Affymetrix GeneChip), and BeadChip (HumanOmni2.5-8 from Illumina), and the like, but are not limited thereto. For example, the base of the polymorphic site can be identified using a SNP chip. The SNP chip refers to one of the DNA microarrays that can identify each base of hundreds of thousands of SNPs at once.

The TaqMan method includes the steps of (1) designing and producing a primer and a TaqMan probe to amplify a desired DNA fragment; (2) labeling probes of different alleles with FAM dyes and VIC dyes (Applied Biosystems); (3) using the DNA as a template and performing PCR using the primers and probes; (4) after the PCR reaction is completed, analyzing and confirming the TaqMan assay plate with a nucleic acid analyzer; And (5) determining the genome types of the polynucleotides of step (1) from the analysis result.

Sequencing analysis may be performed using a conventional method for determining the base sequence, and may be performed using an automated genetic analyzer. In addition, allele-specific PCR refers to a PCR method for amplifying a DNA fragment in which the SNP is located with a primer set including a primer designed with a base in which the SNP is located as the 3'end. The principle of the method is, for example, when a specific base is substituted from A to G, a primer containing A as a 3'end base and a reverse primer capable of amplifying a DNA fragment of an appropriate size are designed and PCR In the case of performing the reaction, when the base at the SNP position is A, the amplification reaction is normally performed and a band at the desired position is observed. When the base is substituted with G, the primer can complementarily bind to the template DNA. This is due to the fact that the amplification reaction is not performed properly because the 3'end cannot perform complementary bonding. DASH may be performed by a conventional method, and preferably may be performed by a method by a prince or the like.

In PCR extension analysis, a DNA fragment containing a base in which a single base polymorphism is located is first amplified with a primer pair, and then all nucleotides added to the reaction are dephosphorylated to inactivate, and a SNP-specific extension primer, dNTP mixture , Didioxynucleotide, reaction buffer, and DNA polymerase are added to perform a primer extension reaction. At this time, the extension primer uses the base immediately adjacent to the 5'direction of the base where the SNP is located as the 3'end, and the dNTP mixture excludes nucleic acids having the same base as the didioxynucleotide, and the didioxynucleotide represents the SNP. It is selected from one of the base types. For example, when there is a substitution from A to G, when a mixture of dGTP, dCTP and TTP and ddATP are added to the reaction, the primer at the base where the substitution occurs is extended by DNA polymerase, and after several bases, A Primer extension reaction is terminated by ddATP at the position where the base first appears. If the substitution has not occurred, since the extension reaction is terminated at that position, it is possible to determine the type of base representing the SNP by comparing the length of the extended primers.

At this time, as a detection method, in the case of fluorescently labeled extension primers or dodioxynucleotides, the SNP can be detected by detecting fluorescence using a genetic analyzer (eg, ABI's Model 3700, etc.) used for general nucleotide sequence determination. The SNP can be detected by measuring the molecular weight using a matrix assisted laser desorption ionization-time of flight (MALDI-TOF) technique in the case of using a non-labeled extension primer and a dodioxynucleotide.

The single nucleotide polymorphism markers for predicting exercise sensitivity of the present invention are shown in Tables 1, 2, 7 and 8 below. The single nucleotide polymorphic markers shown in Table 1 are markers capable of classifying reactive groups and non-responding groups in aerobic exercise. The single nucleotide polymorphism markers shown in Table 2 are markers capable of discriminating high and low sensitivity according to the intensity of the reaction among the aerobic exercise reaction groups. For example, the single nucleotide polymorphic markers shown in Table 2 are markers capable of classifying a normal aerobic exercise responder, a high aerobic exercise responder, and a very high aerobic exercise response group according to the intensity of the reaction. The single nucleotide polymorphism markers shown in Table 7 are markers that can classify the reactive group and the non-reactive group in anoxic exercise, and the single nucleotide polymorphism markers shown in Table 8 are sensitive according to the reaction intensity among the anaerobic exercise reactive groups. It is a marker that can discriminate high and low of. For example, the single nucleotide polymorphic markers shown in Table 8 are markers capable of classifying an anoxic exercise normal response group, an anoxic exercise high response group, and an anaerobic exercise very high response group according to the intensity of the reaction.

Specifically, the marker capable of discriminating between the aerobic and non-reactive groups is a sequence of 5 to 100 consecutive nucleic acids including the 8,408,552 nucleotide, wherein the 8,408,552 nucleotide of the human chromosome 9 is A or C. A polynucleotide consisting of or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 93,796,029 nucleotide, wherein the 93,796,029 nucleotide of human chromosome 11 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 26,737,544 nucleotide, wherein the 26,737,544 nucleotide of the human chromosome 22 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 87,101,649th base, wherein the 87,101,649th base of human chromosome 1 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 11,988,839 nucleotide, wherein the 11,988,839 nucleotide of the human chromosome 11 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 14,526,538 bases, wherein the 14,526,538 bases of the human chromosome 3 are A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 72,101,495 base, wherein the 72,101,495 base of the human chromosome 1 is C or T, or a polynucleotide complementary thereto; And a polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 190,359,804 th base, wherein the 190,359,804 th base of the human chromosome 3 is A or G, or a polynucleotide complementary thereto.

In the above, the 8,408,552 th base of human chromosome 9 is A; The 93,796,029 th base of human chromosome 11 is C; Base 26,737,544 of human chromosome 22 is G; Base 87,101,649 of human chromosome 1 is G; Base 11,988,839 of human chromosome 11 is T; Base 14,526,538 of human chromosome 3 is G; Base 72,101,495 of human chromosome 1 is T; Alternatively, when the 190,359,804 th base of human chromosome 3 is G, the base may be an indicator of high aerobic exercise sensitivity as compared to the case of having other bases on the allele.

In addition, in the above, the 8,408,552 th base of human chromosome 9 is C; Base 93,796,029 of human chromosome 11 is T; The 26,737,544 base of human chromosome 22 is A; Base 87,101,649 of human chromosome 1 is A; The 11,988,839th base of human chromosome 11 is C; The 14,526,538th base of human chromosome 3 is A; Base 72,101,495 of human chromosome 1 is C; Alternatively, when the 190,359,804 th base of human chromosome 3 is A, the base may be an indicator of low aerobic exercise sensitivity as compared to the case of having another base on the allele.

In one embodiment, the single nucleotide polymorphism marker capable of discriminating between the aerobic and non-reactive groups may be polynucleotides represented by SEQ ID NOs: 1 to 8 or complementary polynucleotides thereto.

SEQ ID NO: 1: tttaagtaaamttgattaata

SEQ ID NO: 2: gttctgcccygcccactctg

SEQ ID NO: 3: ttaaactccartccatctatc

SEQ ID NO: 4: gcagatgtcargttgctgatc

SEQ ID NO: 5: ggggtcagaayctggaaaaat

SEQ ID NO: 6: cgacggggccrcggctttcct

SEQ ID NO: 7: aaagtgttaaygatgtcatgg

SEQ ID NO: 8: gtcccaggctracctgtggca

Among the aerobic exercise reaction groups, markers capable of discriminating high and low sensitivity groups, such as normal, high and very high responders, according to the intensity of the reaction, are the 132,075,759 bases of human chromosome 3 C or T, a polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 132,075,759 th base, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences comprising the 138,556,052 base, wherein the 138,556,052 base of the human chromosome 9 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 125,108,977 nucleotide, wherein the 125,108,977 nucleotide of the human chromosome 8 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 50,907,179th base, wherein the 50,907,179th base of human chromosome 18 is A or C, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 238,462,725 base, wherein the 238,462,725 base of the human chromosome 2 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 156,883,493 nucleotide, wherein the 156,883,493 nucleotide of human chromosome 1 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 83,945,288 th base, wherein the 83,945,288 th base of human chromosome 16 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 141,462,748 th base, wherein the 141,462,748 th base of human chromosome 3 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 55,000,949th base, wherein the 55,000,949th base of human chromosome 20 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 151,538,412 base, wherein the 151,538,412 base of human chromosome 1 is A or G, or a polynucleotide complementary thereto; And a polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 71,433,572 base, wherein the 71,433,572 base of the human chromosome 2 is C or T, or a polynucleotide complementary thereto.

In the above, the 132,075,759 th base of human chromosome 3 is T; Base 138,556,052 of human chromosome 9 is G; Bases 125,108,977 of human chromosome 8 are C; The 50,907,179th base of human chromosome 18 is A; Base 238,462,725 of human chromosome 2 is T; Base 156,883,493 of human chromosome 1 is G; Base 83,945,288 of human chromosome 16 is G; The 141,462,748th base of human chromosome 3 is A; The 55,000,949th base of human chromosome 20 is A; The 151,538,412th base of human chromosome 1 is A; Alternatively, when the 71,433,572th base of human chromosome 2 is C, the base may be an index of high aerobic exercise sensitivity as compared to the case of having other bases on the allele.

In addition, in the above, the 132,075,759 th base of human chromosome 3 is C; The 138,556,052th base of human chromosome 9 is A; Bases 125,108,977 of human chromosome 8 are T; C; bases 50,907,179 of human chromosome 18; Base 238,462,725 of human chromosome 2 is C; The 156,883,493th base of human chromosome 1 is A; The 83,945,288th base of human chromosome 16 is A; Base 141,462,748 of human chromosome 3 is G; The 55,000,949th base of human chromosome 20 is G; Base 151,538,412 of human chromosome 1 is G; Alternatively, when the 71,433,572 th base of human chromosome 2 is T, the base may be an indicator of low aerobic exercise sensitivity as compared to the case of having other bases on the allele.

In one embodiment, among the aerobic exercise reaction groups, the single nucleotide polymorphism marker capable of discriminating between the normal response group, the high response group and the very high response group is a polynucleotide represented by SEQ ID NO: 9 to SEQ ID NO: 19 or complementary thereto. It can be a polynucleotide.

SEQ ID NO: 9: gtagctgcccytctcagggca

SEQ ID NO: 10: cagatgacctratcggattaa

SEQ ID NO: 11: gggtgaacatyacagagataa

SEQ ID NO: 12: tattcttatamagttacaagt

SEQ ID NO: 13: ttagacatccyacaagtgact

SEQ ID NO: 14: gggagcagccrctggaccgaa

SEQ ID NO: 15: caaaaggtacrgaaaaagtca

SEQ ID NO: 16: tttggttctaraaggcatttc

SEQ ID NO: 17: tgctatacttraaaagcatca

SEQ ID NO: 18: ctcatggaacrtagaaatctt

SEQ ID NO: 19: tgggaaagctycaaccctgtt

For example, in Table 1, when the base pair of the polymorphic site of the single nucleotide polymorphism marker is a homozygous marked as GoodGeno, the homozygous may be an index indicating that aerobic exercise sensitivity is high compared to the homozygous marked with BadGeno. .

Similarly, in Table 2, when the base pair of the polymorphic site of the single nucleotide polymorphism marker is a homozygous marked as GoodGeno, the homozygous may be an index indicating that aerobic exercise sensitivity is high compared to the homozygous marked with BadGeno.

Markers capable of discriminating between anaerobic and non-reactive groups are polynucleotides consisting of 5 to 100 consecutive nucleic acid sequences including the 71,709,614 th base, wherein the 71,709,614 th base of human chromosome 10 is A or G. Or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 2,756,407th base, wherein the 2,756,407th base of human chromosome 3 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 34,256,377 nucleotide, wherein the 34,256,377 nucleotide of human chromosome 11 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 14,591,736 nucleotide, wherein the 14,591,736 nucleotide of the human chromosome 8 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 5,545,532 nucleotides in which the 5,545,532 nucleotides of human chromosome 7 are C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 2,759,187 th base, wherein the 2,759,187 th base of human chromosome 3 is G or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 8,831,123th base, wherein the 8,831,123th base of human chromosome 17 is A or G, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 129,845,547 base, wherein the 129,845,547 base of the human chromosome 10 is A or C, or a polynucleotide complementary thereto; And a polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 42,192,083 nucleotide in which the 42,192,083 nucleotide of the human chromosome 20 is A or G, or a polynucleotide complementary thereto.

In the above, the 71,709,614th base of human chromosome 10 is G; Base 2,756,407 of human chromosome 3 is C; Bases 34,256,377 of human chromosome 11 are T; Base 14,591,736 of human chromosome 8 is T; Base 5,545,532 of human chromosome 7 is T; The 2,759,187th base of human chromosome 3 is T; Base 8,831,123 of human chromosome 17 is G; Base 129,845,547 of human chromosome 10 is C; Alternatively, when the 42,192,083 base of human chromosome 20 is G, the base may be an indicator of high anaerobic sensitivity as compared to the case of having other bases on the allele.

In addition, in the above, the 71,709,614th base of human chromosome 10 is A; The 2,756,407th base of human chromosome 3 is T; Bases 34,256,377 of human chromosome 11 are C; C; base 14,591,736 of human chromosome 8; Base 5,545,532 of human chromosome 7 is C; Base 2,759,187 of human chromosome 3 is G; The 8,831,123th base of human chromosome 17 is A; The 129,845,547th base of human chromosome 10 is A; Alternatively, when the 42,192,083 base of human chromosome 20 is A, the base may be an indicator of low anaerobic exercise sensitivity as compared to the case of having other bases on the allele.

In one embodiment, the single nucleotide polymorphism marker capable of discriminating between the anaerobic exercise reactive group and the non-reactive group may be a polynucleotide represented by SEQ ID NO: 20 to SEQ ID NO: 28 or a polynucleotide complementary thereto.

SEQ ID NO: 20: gaaaaggtctrgtgcatgcag

SEQ ID NO: 21: aggaaaatgtytcgtttattt

SEQ ID NO: 22: gaagcacttaycagagattat

SEQ ID NO: 23: gattatattgyttatcaagat

SEQ ID NO: 24: gtttcactatyttgtccaggc

SEQ ID NO: 25: tttcctccagkttcactccat

SEQ ID NO: 26: tctctgaatgrttggtgtcat

SEQ ID NO: 27: actttacaaamatagtttggg

SEQ ID NO: 28: ctcatcactgrtttggcacat

Among the anaerobic exercise reactive groups, markers capable of discriminating high and low sensitivity groups, for example, normal, high and very high responders according to the intensity of the reaction, are the 56,271,880 bases of human chromosome 20. C or T, a polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 56,271,880 th base, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 76,128,521 nucleotide, wherein the 76,128,521 nucleotide of the human chromosome 5 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 40,739,349th base, wherein the 40,739,349th base of human chromosome 2 is C or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 10,777,812 base, wherein the 10,777,812 base of the human chromosome 6 is G or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 134,158,790 nucleotide, wherein the 134,158,790 nucleotide of the human chromosome 2 is G or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 122,887,805 base, wherein the 122,887,805 base of human chromosome 6 is G or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 94,862,577 nucleotides, wherein the 94,862,577 nucleotides of human chromosome 11 are A or C, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 82,353,762 nucleotide, wherein the 82,353,762 nucleotide of human chromosome 4 is G or T, or a polynucleotide complementary thereto; A polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 208,275,210 base, wherein the 208,275,210 base of the human chromosome 1 is C or T, or a polynucleotide complementary thereto; And a polynucleotide consisting of 5 to 100 consecutive nucleic acid sequences including the 344,535 nucleotide in which the 344,535 nucleotide of the human chromosome 9 is A or G, or a polynucleotide complementary thereto.

In the above, bases 56,271,880 of human chromosome 20 are C; Base 76,128,521 of human chromosome 5 is C; Base 40,739,349 of human chromosome 2 is T; Base 10,777,812 of human chromosome 6 is G; Base 134,158,790 of human chromosome 2 is G; Base 122,887,805 of human chromosome 6 is T; Bases 94,862,577 of human chromosome 11 are C; Base 82,353,762 of human chromosome 4 is G; Base 208,275,210 of human chromosome 1 is C; Alternatively, when the 344,535 th base of human chromosome 9 is G, the base may be an index having high anaerobic sensitivity compared to the case of having other bases on the allele.

In addition, in the above, the 56,271,880 th base of human chromosome 20 is T; Base 76,128,521 of human chromosome 5 is T; Base 40,739,349 of human chromosome 2 is C; Base 10,777,812 of human chromosome 6 is T; Base 134,158,790 of human chromosome 2 is T; Base 122,887,805 of human chromosome 6 is G; A of bases 94,862,577 of human chromosome 11; Base 82,353,762 of human chromosome 4 is T; Base 208,275,210 of human chromosome 1 is T; Alternatively, when the 344,535 th base of human chromosome 9 is A, the base may be an indicator of low anaerobic motion sensitivity as compared to the case of having other bases on the allele.

In one embodiment, among the anaerobic exercise reaction groups, the single nucleotide polymorphism marker capable of discriminating a normal reaction group, a high reaction group and a very high reaction group is a polynucleotide represented by SEQ ID NO: 29 to SEQ ID NO: 38 or complementary thereto. It can be a polynucleotide.

SEQ ID NO: 29: gagctcaagaytctgtggaga

SEQ ID NO: 30: acaggaaccayagatcctcta

SEQ ID NO: 31: agtcactagcycaacctattt

SEQ ID NO: 32: tttttttaagkttttaaagta

SEQ ID NO: 33: ttgaggttctkcaggttggtg

SEQ ID NO: 34: ctgccttcctkcttccttcct

SEQ ID NO: 35: tacaccatggmgctattccaa

SEQ ID NO: 36: aattacctaakatgtataagg

SEQ ID NO: 37: gcccagggccyttgcacagag

SEQ ID NO: 38: aaaattggcarctgactaagt

For example, in Table 7, when the base pair of the polymorphic site of the single nucleotide polymorphism marker is a homozygous marked with GoodGeno, the homozygous can be an index indicating that the anaerobic motion sensitivity is high compared to the homozygous marked with BadGeno. .

Likewise, in Table 8, when the base pair of the polymorphic site of the single nucleotide polymorphism marker is a homozygous marked with GoodGeno, the homozygous can be an index indicating that the anaerobic motion sensitivity is high compared to the homozygous marked with BadGeno.

In addition, based on the indicators indicated by the base form of the polymorphic site of each marker, the exercise sensitivity of the individual was determined again among the exercise-responsive group, non-responder group, and specifically, the reactive group, again in the normal responder group, high responder group, and very high response group. Criteria for classifying into groups were established. Specifically, as described in Example 2 below, for aerobic exercise sensitivity, an exercise sensitivity score was scored according to the base type of the polymorphic site of the marker, and the weights according to the genomic type were summed, and the cutoff value ( C1, C2, C3) were set. According to the set C1 value, it is possible to predict the sensitivity of an individual to aerobic exercise. For example, if the genomic type score of a specific individual is C1 or higher, it can be predicted as an aerobic exercise reactive group, and if it is less than C1, it can be predicted as aerobic exercise non-responsive group. In addition, if the genomic type score of a specific individual is C1 or more and less than C2, it can be predicted as a normal aerobic exercise responder, if it is C2 or more and less than C3, a highly aerobic response group, and C3 or more, a very high aerobic response group. This can be applied equally to the anaerobic exercise sensitivity (see Example 4).

One of the single nucleotide polymorphic markers may be used, one or more of the markers may be used in combination, or all of the markers may be used in combination. As the number of markers to be combined increases, the discriminant ability of predicting exercise sensitivity improves.

In one embodiment, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, or all of the above single nucleotide polymorphic markers may be used in combination.

For example, in the aerobic exercise sensitivity experiment, among the 8 polymorphic markers that can discriminate between the reactive group and the non-responder group, the discriminant power of each marker was about 59 to 79%, but when all 8 were used, about 89 To 90% of the discriminant was obtained (see Example 2). The results were similar in the anaerobic exercise sensitivity experiment. In the anaerobic exercise sensitivity experiment, of the 9 polymorphic markers that can discriminate between the reactive group and the non-reactive group, the discriminant power of each marker was about 53 to 87%, but when all 9 were used, about 94 to 96% Discriminant ability was obtained (see Example 4).

In addition, with respect to the sensitivity of aerobic exercise, the sensitivity of aerobic exercise was 78, when all markers were combined, among the reactive groups, the normal response group, the high response group, and the very high response group. To 84%, the anaerobic exercise sensitivity was 85 to 88% (see Example 2 and Example 4).

Accordingly, the present invention identifies the base of the polymorphic site of one or more single nucleotide polymorphic markers selected from the single nucleotide polymorphic markers shown in Tables 1 and 2, from a nucleic acid sample isolated from an individual; It provides a method of providing information to predict the exercise sensitivity of an individual, comprising identifying the base of the polymorphic site of one or more single base polymorphic markers selected from the single base polymorphic markers shown in Tables 7 and 8.

In the present invention, the provision of information for predicting the exercise sensitivity may be performed through a computer program. For example, the result of base identification of the polymorphic site of the single base polymorphic marker of the target individual is output through a computer-readable program, and as a result, in the case of an individual with high aerobic exercise sensitivity, an appropriate aerobic exercise program can be presented. In the case of individuals with high sensitivity to anaerobic exercise, an appropriate anaerobic exercise program can be suggested. Accordingly, by presenting a personalized exercise program according to the genetic characteristics of each individual, it is possible to maximize the exercise effect.

The present invention also includes a probe capable of detecting one or more single nucleotide polymorphic markers selected from the single nucleotide polymorphic markers shown in Tables 1 and 2, or a primer capable of amplifying the polymorphic marker, for predicting aerobic exercise sensitivity. It provides a kit for predicting aerobic exercise sensitivity, including the composition.

The present invention also includes a probe capable of detecting one or more single nucleotide polymorphic markers selected from the single nucleotide polymorphic markers shown in Tables 7 and 8, or a primer capable of amplifying the polymorphic marker, for predicting anaerobic exercise sensitivity. It provides a kit for predicting anaerobic exercise sensitivity, including the composition.

The present invention also predicts aerobic exercise sensitivity including a probe capable of detecting one or more single nucleotide polymorphic markers selected from single nucleotide polymorphic markers shown in Tables 1 and 2 or a primer capable of amplifying the single nucleotide polymorphic marker. Dragon composition; And a probe capable of detecting one or more single nucleotide polymorphic markers selected from single nucleotide polymorphic markers shown in Tables 7 and 8 or a primer capable of amplifying the single nucleotide polymorphic marker. It provides a kit for predicting exercise sensitivity.

In the present specification, the term'probe' refers to a substance capable of predicting the sensitivity of the aerobic/anaerobic exercise by specifically hybridizing with a polymorphic site of a gene, and the specific method of such genetic analysis is not particularly limited. It may be by any method for detecting genes known in the art to which the invention belongs.

In the present specification, the term'primer' is a material capable of specifically amplifying a polynucleotide of a single nucleotide polymorphism marker, and a template complementary to a base sequence having a short free 3'terminal hydroxyl group (free 3'hydroxyl group). ) Refers to a short sequence that can form a base pair and serves as a starting point for template strand copying. Primers can initiate DNA synthesis in the presence of a reagent for polymerization (ie, DNA polymerase or reverse transcriptase) and four different nucleoside triphosphates at an appropriate buffer and temperature. By performing PCR amplification, the sensitivity of exercise can be predicted through whether the desired product is produced. The PCR conditions, the length of the sense and antisense primers can be modified based on those known in the art. The appropriate length of the primer may vary depending on the purpose of use, and may be, for example, 15 to 30 nucleotides. The primer sequence need not be completely complementary to the template, but must be sufficiently complementary to hybridize to the template.

Probes or primers can be chemically synthesized using the phosphoramidite solid support method, or other well known methods. Such nucleic acid sequences can also be modified using a number of means known in the art. Non-limiting examples of such modifications include methylation, encapsulation, substitution of one or more homologs of natural nucleotides, and modifications between nucleotides, e.g., uncharged linkers (e.g., methyl phosphonate, phosphorester, phosphoro Amidates, carbamates, etc.) or with charged linkers (eg phosphorothioate, phosphorodithioate, etc.).

In the present invention, the kit may be used without limitation as long as it is a kit capable of detecting or identifying a single nucleotide polymorphism marker. For example, the kit may be a DNA chip kit or a real time-polymerase chain reaction (RT-PCR) kit. The RT-PCR kit includes, in addition to each primer pair specific for the gene of the polymorphic marker, a test tube or other suitable container, reaction buffer (varies in pH and magnesium concentration), deoxynucleotides (dNTPs), Taq-polymerase and Enzymes such as reverse transcriptase, DNase, RNAse inhibitors, DEPC-water, sterile water, and the like may be included. In addition, a primer pair specific to a gene used as a quantitative control may be included. Using an RT-PCR kit, polymorphic markers can be identified by measuring the mRNA expression level of a single base polymorphic marker. A DNA chip kit is a gridded array of nucleic acid species attached to a generally flat solid support plate, typically a glass surface that is not larger than a microscope slide, in which nucleic acids are uniformly arranged on the chip surface. It is a tool that enables mass-parallel analysis by causing multiple hybridization reactions between the nucleic acid on the image and the complementary nucleic acid contained in the solution treated on the surface of the chip.

The kit of the present invention also includes a microarray. The microarray may include DNA or RNA polynucleotides. The microarray may be formed of a conventional microarray, except that the polynucleotide of the polymorphic marker of the present invention is included in the probe polynucleotide.

A method of preparing a microarray by immobilizing a probe polynucleotide on a substrate is well known in the art. The probe polynucleotide refers to a polynucleotide capable of hybridizing, and refers to an oligonucleotide capable of sequence-specific binding to a complementary strand of a nucleic acid. The probe of the present invention is an allele-specific probe, and a polymorphic site exists in a nucleic acid fragment derived from two members of the same species, and hybridizes to a DNA fragment derived from one member, but does not hybridize to a fragment derived from another member. . In this case, hybridization conditions show a significant difference in hybridization strength between alleles, and must be sufficiently stringent to hybridize to only one of the alleles. This can lead to good hybridization differences between different allelic types.

As the microarray, a known microarray may be used without limitation, and a method of manufacturing a microarray is well known in the art. In addition, hybridization of nucleic acids on microarrays and detection of hybridization results are also well known in the art. For example, the result of hybridization may be detected by labeling a nucleic acid sample with a labeling substance capable of generating a detectable signal such as a fluorescent substance, hybridizing on a microarray, and detecting a signal generated from the labeling substance.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Hereinafter, the present invention will be described in detail through examples. The following examples are merely illustrative of the present invention, and the scope of the present invention is not limited to the following examples. The present embodiments are provided to complete the disclosure of the present invention and to fully inform the scope of the invention to those of ordinary skill in the art to which the present invention pertains, and the present invention will be defined by the scope of the claims. Only.

[ Example ]

[ Example 1] Establishment of aerobic exercise sensitivity prediction model and major SNP extraction

In order to predict the aerobic exercise sensitivity of an individual, an aerobic exercise sensitivity prediction model, which is a mathematical model capable of predicting aerobic exercise sensitivity according to the difference in single nucleotide polymorphism observed in an individual, was established, and the SNP was calculated according to the process shown in FIG. Extracted. Subjects are healthy adult males and females aged 30 to 60 years old at the time of the experiment, and among those who have not experienced regular exercise for the last 3 months, their weight is 45 kg or more and within ±20% of their ideal body weight. After hearing sufficient explanations for this clinical trial, among those who have had a decision to voluntarily participate in this clinical trial, it was limited to those who agreed in writing to comply with the precautions. Ideal weight is defined as = (height cm-100) x 0.9.

The following is the criteria for exclusion of subjects based on medical judgment.

1) Those who show symptoms of suspected acute disease 28 days before the start of the test (administration of investigational drug)

2) Those with clinically significant and active gastrointestinal tract, cardiovascular system, respiratory system, kidney, endocrine system, hematology, digestive system, central nervous system, mental illness, or malignant tumor

3) A person who is judged to be unsuitable as a subject through a health checkup (disease history, physical examination, ECG, clinical pathology examination, etc., screening items) within 28 days of the initiation of the test (administration of investigational drugs)

4) Those who have a history of gastric ulcer or duodenal ulcer in the past or have active gastric duodenal ulcer

5) A person who shows any of the following results in the clinical laboratory test

a. AST(SGOT) or ALT(SGPT)> 1.25 times the upper limit of the normal range

b. Total bilirubin> 1.5 times the upper limit of the normal range

6) Those with clinically significant allergic disease (except for mild allergic rhinitis that does not require medication)

7) Those who participated in other clinical studies as subjects within 30 days of the start of the test

8) Those with systolic blood pressure> 150 mmHg, diastolic blood pressure> 100 mmHg

9) People with increased intraocular pressure, glaucoma, urinary retention, or other diseases

10) Those who have eaten abnormal meals

11) A person who donated whole blood within 60 days of initiation of the test (administration of investigational drug) or a person who donated component blood within 30 days of initiation of the test

12) Continuously caffeine (caffeine> 5 cups/day), alcoholic beverages (alcohol> 30 g/day) or excessive smokers (cigarettes> 20 cigarettes/day)

13) A person who judges that the investigator is unsuitable for participation in the clinical trial due to laboratory test results and other reasons

14) Those who cannot read letters or have limited such ability (illiterate)

Below are the exclusion criteria for exercise fitness test.

1) Those who voluntarily stop the test within 6 minutes of the exercise load test

2) Those who stopped the test because they reached the target heart rate within 6 minutes in the exercise load test.

A total of 79 people (52 men, 27 women) who satisfies the above criteria were subjected to a high intensity training (HIT) exercise experiment, and blood samples were collected before starting the exercise for these subjects, and then sold by Illumina. Using the human omni 2.5M 8 beadchip kit, personal genome types for a total of 2,391,739 single nucleotide mutations (SNPs) were extracted, and the following data preprocessing was performed.

Of the total 2,391,730 SNPs, the number of SNPs (monormorphic SNPs) in which only one genotype was detected in 79 samples was 1,000,738, accounting for 41.8% of the total SNPs, which were excluded from future analysis.

In a sample of 79 people, 2,120 SNPs with more than 20% missing values were all, accounting for 0.089% of the total SNPs, and all of these SNPs were excluded from future analysis. In the case of missing values of less than 20%, it was replaced with the observed genome type.

Among the observed alleles, 48,433 SNPs with a frequency of less than 1% were all, accounting for 2.0% of all SNPs, and all of these SNPs were excluded from future analysis.

There were 64,394 SNPs seriously out of the Hardy-Weinberg Equilibrium (p value <0.001), accounting for 2.7% of all SNPs, and all of these SNPs were excluded from future analysis.

As a result of data preprocessing, 1,276,054 (53.4%) of the total 2,391,739 SNPs were used to construct a future exercise sensitivity prediction model.

The HIT exercise experiment was conducted three times a week, and exercise was performed for 3 minutes and 40 seconds per day (after warming up of 40 seconds, 3 times of 20 seconds high intensity cycling and 40 seconds rest).

Cardio maximum oxygen uptake in the sensitivity evaluation parameters were determined by selecting the (maximal oxygen consumption; maximal oxygen uptake ;; VO2max units of mL / kg / min), oil responders and non-responders according to D _i values of the formula 1 Classified. D _i means the ratio of the increase in the maximum oxygen intake at the 9th week of exercise compared to the i-th person who performed high intensity training (HIT) exercise before the start of exercise.

[Equation 1]

In Equation 1 _{, a group with D i} ≤ O was classified as a non-reactive group, and a group with D _i > 0 was classified as a reactive group. _{In addition, three initial values (S1: min (D i} ), S2: median (D _i ), S3: max (D _i )) for applying the 3-means clustering algorithm were set for the reactive group. Clustering was performed using the 3-means algorithm using the above initial values, and as a result, people clustered around S1 were usually responders, those clustered around S2 were high responders, and those clustered around S3 were very high responders. Classified as.

As a result, the aerobic exercise sensitivity response group was found to be 60 out of 79 patients (75.9%), and the non-responder group (19 out of 79) (24.1%). The average responder was 34 out of 60 respondents (56.7%), the high responder (19 out of 60) was 31.7%, and the very high responder was 7 out of 60 (11.7%).

Among the two alleles found in each SNP, a trait with a larger Di value is defined as a trait that has a good effect on the increase in the maximum oxygen uptake (allele A), and the trait that does not have a negative effect on an increase in the maximum oxygen intake (allele) After defining as B), among the three genotypes consisting of traits A and B, BB was converted into 0, AB into 1, and AA into 2, and then used for model construction.

Linear regression analysis, binary logistic regression analysis, and multinomial logistic regression analysis ( multinomial logistic regression analysis) was performed. When performing regression analysis, all were corrected by sex, age, and maximum oxygen intake at the beginning of exercise.

More specifically, the sensitivity of continuous exercise was determined through linear regression analysis corrected by gender, age, and maximum oxygen uptake at the beginning of exercise after setting Di as a response variable as a response variable and the genome type of each SNP as an independent variable. 13,032 SNPs influencing were selected (p value <0.01). In addition, the exercise sensitivity group divided into two types of aerobic non-responsive group and aerobic reaction group was set as a response variable, and the genome type of each SNP was set as an independent variable, and then corrected by sex, age, and maximum oxygen intake at the beginning of exercise. Through the classification logistic regression analysis, 6,971 SNPs affecting the exercise sensitivity divided into two types were selected (p value <0.01).

Lastly, the aerobic reaction group was divided into three types of aerobic response group, high response group, and very high response group as the response variable, and the genome type of each SNP was set as an independent variable, followed by sex, age, and exercise. Through a multinomial logistic regression analysis corrected by the initial maximum oxygen intake, 17,506 SNPs that affect exercise sensitivity classified into three-minute types were selected (p value <0.01).

Among these selected SNPs, 1,181 SNPs that have a common effect on continuous motion sensitivity and two-minute motion sensitivity were selected, and among them, SNP 343 in which all three genotypes and those belonging to the DNA region functioning as genes were observed. Dogs were selected and used as candidate SNPs constituting prediction model A.

In addition, after selecting 724 SNPs that have a common influence on the continuous motion sensitivity and the three-minute motion sensitivity, among them, 57 SNPs belonging to the DNA region that function as genes and in which all three genotypes are observed were selected. It was used as a candidate SNP constituting the prediction model B.

Prediction model A refers to a prediction model including SNPs that can classify aerobic exercise sensitivity into reactive and non-responsive groups. The prediction model is most stable by applying the backward stepwise regression method to 343 candidate SNPs. SNPs judged to be constituted were selected as the primary. After applying the forward stepwise regression method again targeting the SNPs selected in this way, 8 SNPs were finally selected.

Prediction model B refers to a predictive model that includes SNPs that can reclassify people classified as aerobic reaction groups through predictive model A into normal, high and very high responders, with 57 candidates. SNPs judged to be the most stably constructing the prediction model by applying the backward stepwise regression method to the SNPs were selected as the first order. After applying the forward stepwise regression method again targeting the SNPs selected in this way, 11 SNPs were finally selected.

The Backward stepwise regression method is a method of finding the independent variable with the optimal model fit by first adding all the independent variables to the model, calculating the goodness-of-fit, and excluding the independent variables one by one. On the other hand, the forward stepwise regression method is a method of finding an independent variable with an optimal model fit while adding independent variables one by one to an empty model with nothing, and the backward and forward stepwise regression methods are widely used in statistics.

SNPs extracted from prediction model A are shown in Table 1 below, and SNPs extracted from prediction model B are shown in Table 2 below.

[ Example 2] Evaluation of aerobic exercise sensitivity prediction model

Using the aerobic exercise sensitivity prediction models A and B established in Example 1, the cut-off value (C1) for discriminating the reactive group and the non-responder group, and the normal and high responders within the reactive group are discriminated. A cut-off value (C2) for determining and a cut-off value (C3) for discriminating a high response group and a very high response group were set, and the discrimination accuracy was calculated. The specific process is shown in FIG. 2. In summary, discriminant power was calculated using KNN (K-nearest neighbor), SVM (support vector machine), LDA (linear discriminant analysis) and ROC curve model as the discriminant algorithm, and then the discriminant difference for each algorithm was compared. The sum of the calculated genomic score and the ROC curve model were used to derive the final cutoff value for classifying the responders.

In the present invention, since the genome type of each SNP is composed of a combination of two alleles, there are three types of genome type per SNP. When calculating the average of the D _i according to the genome type, 0 points for the homozygous case of the lower genome type, 1 point for the heterozygous case, and 2 points for the homozygous case of the higher _{D i genome type.} The score was calculated. In the prediction model A and the prediction model B, scores different for the SNP genome type are shown in Table 3 below.

Using the scores of each SNP shown in Table 3, the sum of the genome-type scores was calculated according to Equation 2 below.

[Equation 2]

In Equation 2, n: the number of SNPs constituting the prediction model

S _i : The sum of the genotype scores calculated in the i-th person

G _{i , j} : Genomic type score observed at the j-th SNP of the i-th person ∈ {0, 1, 2}

W _j : indicates the weight of the j-th SNP (the ^{use of semi-R 2} of each SNP calculated in the multiple linear regression analysis is basic, and if all are defined as 1, the weight according to the SNP is the same).

Using the sum of the genome-type scores, cutoff values and discriminant power were calculated.

[Example 2-1] Evaluation of predictive model A

1. The results of using all 8 SNPs in the prediction model A were as follows in Table 4 below:

ㆍNumber of SNPs = 8

ㆍR ² = 0.283

ㆍClassification power

-KNN (when k=3): 89.9%

-SVM: 89.9%

-LDA: 88.6%

-ROC curve model: 88.6%

ㆍNon-responder vs. Criteria score for discriminating reaction group

ㆍC1 = 0.773 points

2. The results of using one SNP in the prediction model A were as follows in Table 5 below:

ㆍNon-responder vs. Criteria score for determining reaction

ㆍC1 = 1.0 point (common in all SNPs)

These results suggest that, when each SNP of predictive model A or a combination thereof, the exercise sensitivity in the aerobic exercise response can be predicted.

[Example 2-2] Evaluation of predictive model B

The results when all 11 SNPs were used in the prediction model B were shown in Table 6 below and as follows:

ㆍNumber of SNPs = 11

ㆍR ² = 0.328

ㆍClassification power

-KNN (when k=3): 83.1%

-SVM: 83.1%

-LDA: 78%

-ROC curve model: 83.9%

ㆍMedium response group, high response group, and very high response group discrimination criteria score

-C2 = 1.424

-C3 = 1.634

These results suggest that when the SNPs of predictive model B are combined, exercise sensitivity in aerobic exercise responders can be predicted.

[ Example 3] Establishment of anaerobic exercise sensitivity prediction model and major SNP extraction

In order to predict the sensitivity of an individual to anaerobic exercise, an anaerobic exercise sensitivity prediction model was established in a similar manner as in the aerobic exercise response of Example 1, and SNPs were extracted according to the process shown in FIG. 1.

A high intensity training (HIT) exercise experiment was performed on a total of 79 subjects that were the same as in Example 1, and SNPs for prediction model A and prediction model B were extracted in the same manner.

As the anaerobic exercise sensitivity evaluation parameter, a peak torque value (unit: NM/kg), which is an index indicating muscle strength, was selected and measured, and the reactive group and non-reactive group were classified according to _{the D i value of Equation 3 below.} . D _i denotes the ratio of muscle strength increase (increase of peak torque value) at the 9th week of exercise compared to before the start of exercise of the i-th person who performed high intensity training (HIT) exercise.

[Equation 3]

In Equation 3 _{, a group with D i} ≤ O was classified as a non-reactive group, and a group with D _i > 0 was classified as a reactive group. _{In addition, three initial values (S1: min (D i} ), S2: median (D _i ), S3: max (D _i )) for applying the 3-means clustering algorithm were set for the reactive group. Clustering was performed using the 3-means algorithm using the above initial values, and as a result, those who were clustered around S1 were usually the responders, those clustered around S2 were the high responders, and those clustered around S3 were the very high responders. Classified as.

As a result, the anaerobic exercise sensitivity was found to be 67 out of 79 patients (84.8%), and the non-responder group (12 out of 79) (15.2%). The average responder was 41 out of 67 respondents (61.2%), the high responder was 21 out of 67 (31.3%), and the very high responder was 5 out of 67 (7.5%).

SNPs extracted from prediction model A are shown in Table 7 below, and SNPs extracted from prediction model B are shown in Table 8 below.

[ Example 4] Evaluation of anaerobic exercise sensitivity prediction model

Using the anaerobic exercise sensitivity prediction models A and B established in Example 3, the cut-off value (C1) for discriminating the reactive group and the non-responder group, and the normal and high responders in the reactive group were discriminated. A cut-off value (C2) to be used and a cut-off value (C3) for discriminating a high response group and a very high response group were set, and the discrimination accuracy was calculated. The specific process is shown in FIG. 3.

In summary, after calculating discriminant power using KNN (K-nearest neighbor), SVM (support vector machine), LDA (linear discriminant analysis) and ROC curve model as the discriminant algorithm, the discriminant difference for each algorithm was compared. The sum of the calculated genomic score and the ROC curve model were used to derive the final cutoff value for classifying the responders. In the present invention, since the genome type of each SNP is composed of a combination of two alleles, there are three types of genome type per SNP. When calculating the average of the D _i according to the genome type, 0 points for the homozygous case of the lower genome type, 1 point for the heterozygous type, and 2 points for the homozygous case of the higher _{D i genome type.} The score was calculated. In the predictive model A and the predictive model B, scores different for the genotype of SNP are shown in Table 9 below.

Using the scores of each SNP shown in Table 9, the sum of the genome-type scores was calculated according to Equation 2 below.

[Equation 2]

In the above formula, n: the number of SNPs constituting the prediction model

S _i : The sum of the genotype scores calculated in the i-th person

G _{i , j} : Genomic type score observed at the j-th SNP of the i-th person ∈ {0, 1, 2}

W _j : indicates the weight of the j-th SNP (the ^{use of semi-R 2} of each SNP calculated in the multiple linear regression analysis is basic, and if all are defined as 1, the weight according to the SNP is the same).

Using the sum of the genome-type scores, cutoff values and discriminant power were calculated.

[Example 4-1] Evaluation of predictive model A

1. The results of using all 9 SNPs in the prediction model A were as follows in Table 10 below:

ㆍ Number of SNPs = 9

ㆍ R ² = 0.203

ㆍ Classification power

-KNN (when k=3): 96.2%

-SVM: 93.7%

-LDA: 94.9%

-ROC curve model: 96.2%

ㆍ Non-responder vs. Criteria score for discriminating reaction group

ㆍ C1 = 0.999 points

2. The results of using one SNP in the prediction model A were as follows in Table 11 below:

ㆍ Non-responder vs. Criteria score for determining reaction

ㆍ C1 = 1.0 point (common in all SNPs)

These results suggest that, when each SNP of the prediction model A or a combination thereof, the exercise sensitivity in the anaerobic exercise response can be predicted.

[Example 4-2] Evaluation of predictive model B

The results when all 10 SNPs were used in the prediction model B were shown in Table 12 below and as follows:

ㆍ Number of SNPs = 10

ㆍ R ² = 0.260

ㆍ Classification power

-KNN (when k=3): 87.7%

-SVM: 86.2%

-LDA: 84.8%

-ROC curve model: 87.7%

ㆍ Average, high and very high response group discrimination criteria score

-C2 = 1.159

-C3 = 1.454

These results suggest that when the SNP of predictive model B is combined, the exercise sensitivity in the anaerobic exercise reaction group can be predicted.

<110> BIO AGE CO., LTD. DAEWOONG PHARMACEUTICAL CO., LTD. <120> Biomarker for predicting of sensitivity to exercise <130> P14E10C1127 <160> 38 <170> KopatentIn 2.0 <210> 1 <211> 21 <212> DNA <213> homo sapiens <400> 1 tttaagtaaa mttgattaat a 21 <210> 2 <211> 20 <212> DNA <213> Homo sapiens <400> 2 gttctgcccy gcccactctg 20 <210> 3 <211> 21 <212> DNA <213> homo sapiens <400> 3 ttaaactcca rtccatctat c 21 <210> 4 <211> 21 <212> DNA <213> homo sapiens <400> 4 gcagatgtca rgttgctgat c 21 <210> 5 <211> 21 <212> DNA <213> homo sapiens <400> 5 ggggtcagaa yctggaaaaa t 21 <210> 6 <211> 21 <212> DNA <213> homo sapiens <400> 6 cgacggggcc rcggctttcc t 21 <210> 7 <211> 21 <212> DNA <213> homo sapiens <400> 7 aaagtgttaa ygatgtcatg g 21 <210> 8 <211> 21 <212> DNA <213> homo sapiens <400> 8 gtcccaggct racctgtggc a 21 <210> 9 <211> 21 <212> DNA <213> homo sapiens <400> 9 gtagctgccc ytctcagggc a 21 <210> 10 <211> 21 <212> DNA <213> homo sapiens <400> 10 cagatgacct ratcggatta a 21 <210> 11 <211> 21 <212> DNA <213> homo sapiens <400> 11 gggtgaacat yacagagata a 21 <210> 12 <211> 21 <212> DNA <213> homo sapiens <400> 12 tattcttata magttacaag t 21 <210> 13 <211> 21 <212> DNA <213> homo sapiens <400> 13 ttagacatcc yacaagtgac t 21 <210> 14 <211> 21 <212> DNA <213> homo sapiens <400> 14 gggagcagcc rctggaccga a 21 <210> 15 <211> 21 <212> DNA <213> homo sapiens <400> 15 caaaaggtac rgaaaaagtc a 21 <210> 16 <211> 21 <212> DNA <213> homo sapiens <400> 16 tttggttcta raaggcattt c 21 <210> 17 <211> 21 <212> DNA <213> homo sapiens <400> 17 tgctatactt raaaagcatc a 21 <210> 18 <211> 21 <212> DNA <213> homo sapiens <400> 18 ctcatggaac rtagaaatct t 21 <210> 19 <211> 21 <212> DNA <213> homo sapiens <400> 19 tgggaaagct ycaaccctgt t 21 <210> 20 <211> 21 <212> DNA <213> homo sapiens <400> 20 gaaaaggtct rgtgcatgca g 21 <210> 21 <211> 21 <212> DNA <213> homo sapiens <400> 21 aggaaaatgt ytcgtttatt t 21 <210> 22 <211> 21 <212> DNA <213> homo sapiens <400> 22 gaagcactta ycagagatta t 21 <210> 23 <211> 21 <212> DNA <213> homo sapiens <400> 23 gattatattg yttatcaaga t 21 <210> 24 <211> 21 <212> DNA <213> homo sapiens <400> 24 gtttcactat yttgtccagg c 21 <210> 25 <211> 21 <212> DNA <213> homo sapiens <400> 25 tttcctccag kttcactcca t 21 <210> 26 <211> 21 <212> DNA <213> homo sapiens <400> 26 tctctgaatg rttggtgtca t 21 <210> 27 <211> 21 <212> DNA <213> homo sapiens <400> 27 actttacaaa matagtttgg g 21 <210> 28 <211> 21 <212> DNA <213> homo sapiens <400> 28 ctcatcactg rtttggcaca t 21 <210> 29 <211> 21 <212> DNA <213> homo sapiens <400> 29 gagctcaaga ytctgtggag a 21 <210> 30 <211> 21 <212> DNA <213> homo sapiens <400> 30 acaggaacca yagatcctct a 21 <210> 31 <211> 21 <212> DNA <213> homo sapiens <400> 31 agtcactagc ycaacctatt t 21 <210> 32 <211> 21 <212> DNA <213> homo sapiens <400> 32 tttttttaag kttttaaagt a 21 <210> 33 <211> 21 <212> DNA <213> homo sapiens <400> 33 ttgaggttct kcaggttggt g 21 <210> 34 <211> 21 <212> DNA <213> homo sapiens <400> 34 ctgccttcct kcttccttcc t 21 <210> 35 <211> 21 <212> DNA <213> homo sapiens <400> 35 tacaccatgg mgctattcca a 21 <210> 36 <211> 21 <212> DNA <213> homo sapiens <400> 36 aattacctaa katgtataag g 21 <210> 37 <211> 21 <212> DNA <213> homo sapiens <400> 37 gcccagggcc yttgcacaga g 21 <210> 38 <211> 21 <212> DNA <213> homo sapiens <400> 38 aaaattggca rctgactaag t 21

Claims (8)

A method of providing information for predicting anaerobic exercise sensitivity of an individual, comprising identifying a base in a polymorphic site of a single base polymorphic marker from a nucleic acid sample isolated from the individual:
Wherein the single nucleotide polymorphism marker comprises:
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the above 56,271,880 base, wherein the 56,271,880 base of the human chromosome 20 is C or T, or a polynucleotide complementary thereto;
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the above 76,128,521 base, wherein the 76,128,521 base of the human chromosome 5 is C or T, or a complementary polynucleotide thereof;
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the 82, 353, 762th bases, wherein the 82,353,762th base of human chromosome 4 is G or T, or a polynucleotide complementary thereto;
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the above 208,275, 210 base, wherein the 208,275, 210 base of the human chromosome 1 is C or T, or a polynucleotide complementary thereto; And
A polynucleotide consisting of 5 to 100 contiguous nucleic acid sequences comprising the 344,535 base sequence, wherein the 344,535th base of human chromosome 9 is A or G, or a complementary polynucleotide thereof,
In the above, the 56,271,880th base of human chromosome 20 is C;
76,128,521 base of human chromosome 5 is C;
The 82,353,762th base of human chromosome 4 is G;
The 208,275,210th base of human chromosome 1 is C; or
When the 344,535th base of human chromosome 9 is G, the oxygen-free movement sensitivity is high,
The anaerobic exercise sensitivity is expressed as an increase in muscle strength.
3. The method of claim 1, further comprising identifying a base in a polymorphic site of a single base polymorphic marker as follows:
Wherein the single nucleotide polymorphism marker comprises:
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the 40,739, 349th nucleotide, wherein the 40,739,349th base of the human chromosome 2 is C or T, or a polynucleotide complementary thereto;
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the above 10,777,812 base, wherein the 10,777,812th base of the human chromosome 6 is G or T, or a polynucleotide complementary thereto;
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the 134th, 158th, and 79th bases, wherein the 134th, 158th, and 790th bases of the human chromosome 2 are G or T, or a complementary polynucleotide thereof;
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the 122,887,805 base, wherein the 122,887,805th base of the human chromosome 6 is G or T, or a polynucleotide complementary thereto; And
A polynucleotide consisting of 5 to 100 consecutive nucleotide sequences comprising the 94,862,577 base sequence, wherein the 94,862,577th base of human chromosome 11 is A or C, or a complementary polynucleotide thereof,
In the above, the 40,739,349th base of the human chromosome 2 is T;
The 10,777,812th base of human chromosome 6 is G;
The 134,158,790th base of human chromosome 2 is G;
The 122,887,805th base of human chromosome 6 is T; or
When C is 94,862,577 base of human chromosome 11, it is an indicator of oxygen-free exercise sensitivity.
2. The method of claim 1, wherein identifying a base of a polymorphic site of at least two monoclonal polymorphic markers is provided for predicting anaerobic exercise sensitivity of an individual.
2. The method of claim 1, wherein identifying a base in a polymorphic site of all five monoclonal polymorphic markers is provided for predicting anaerobic exercise sensitivity of an individual.
3. The method of claim 2, further comprising identifying a base in a polymorphic site of two or more monoclonal polymorphic markers of the additional monoclonal polymorphic markers of claim 2 to provide information to predict the anaerobic motility sensitivity of the individual Way.
3. The method of claim 2, wherein information is provided to predict the anaerobic exercise sensitivity of an individual, including identifying bases at polymorphic sites of all five of the single base polymorphic markers of the additional single base polymorphic markers of claim 2 How to.
A kit for predicting anaerobic exercise sensitivity comprising a probe capable of detecting a single base polymorphic marker according to claim 1 or a primer capable of amplifying said single base polymorphic marker,
Wherein the anaerobic exercise sensitivity is expressed as an increase in muscle strength.
The kit for predicting anaerobic exercise sensitivity according to claim 7, further comprising a probe capable of detecting the single base polymorphism marker according to claim 2 or a primer capable of amplifying the single base polymorphism marker.

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