CN114908153A - Reagent kit for screening plateau pneumochysis susceptible population based on 39 SNP loci - Google Patents

Abstract

The invention discloses a reagent kit for screening plateau pneumochysis susceptible population based on 39 SNP loci. The invention provides application of 39 SNPs as detection targets in developing products; the product has the following functions: screening susceptible individuals of plateau pulmonary edema; the subjects were assessed for risk of developing high altitude pulmonary edema. Rs number of 39 SNPs: 12733147, 2941757, 56240659, 28843785, 4836498, 79522289, 59140633, 12569857, 241970, 11620394, 12148912, 740873, 919197, 6009184, 938355, 9932581, 6194, 9592406, 2297441, 4762, 2397218, 12462380, 699, 11896604, 12655827, 130293, 2486736, 41417552, 5768002, 40305, 11962222, 2009196, 2148582, 1008438, 10929728, 820336, 6888553, 6010621, and 6882447. The invention can be used to avoid or reduce the occurrence of high altitude pulmonary edema.

Description

Reagent kit for screening plateau pneumochysis susceptible population based on 39 SNP loci

Technical Field

The invention belongs to the field of gene detection, and relates to a reagent kit for screening plateau pneumochysis susceptible population based on 39 SNP loci.

Background

High Altitude Pulmonary Edema (HAPE) means that the patient feels hypodynamia or reduced mobility when the patient reaches the plateau (generally, the altitude is more than 3000 m, and a small amount is less than 3000 m), and the patient suffers from dyspnea, chest distress, chest oppression, cough, white or pink sputum foam at rest. The plateau pulmonary edema is a plateau idiopathic disease, is mostly seen in high altitude areas with more than 3000 m, and is mainly characterized by acute disease, great harm and high disease death rate.

In recent years, a series of studies have been made on the occurrence of HAPE at home and abroad, and the disease has a remarkable tendency of genetic susceptibility and is a result of combined action of heredity and environment. The incidence of disease in hypoxic environment is closely related to individual susceptibility genes, so the susceptibility genes may be an important molecular marker for preventing and diagnosing diseases, evaluating the severity of diseases and providing an effective treatment method.

Disclosure of Invention

The invention aims to provide a reagent kit for screening plateau pneumochysis susceptible population based on 39 SNP loci.

The invention provides application of 39 SNPs as detection targets in product development.

The invention also provides a product comprising means for detecting the genotype of a subject based on 39 SNPs.

Illustratively, the means for detecting the genotype of the subject for the 39 SNPs is a primer set; the primer group consists of 117 primers which are sequentially shown as a sequence 1 to a sequence 117 in a sequence table.

The primer is a single-stranded DNA molecule.

The product also comprises a carrier in which the prediction model is recorded.

The product also comprises a carrier which is recorded with the establishment method of the prediction model and the application method of the prediction model.

The product also comprises a carrier which is recorded with a building method of a prediction model, an evaluation method of the prediction model and an application method of the prediction model.

The invention also provides the application of the substance for detecting the genotype of the subject based on 39 SNPs in the preparation of products.

Illustratively, the means for detecting the genotype of the subject for the 39 SNPs is a primer set; the primer group consists of 117 primers which are sequentially shown as a sequence 1 to a sequence 117 in a sequence table.

The primer is a single-stranded DNA molecule.

The function of any one of the products is as follows (a) or (b):

(a) screening susceptible individuals of plateau pulmonary edema;

(b) the subject is assessed for risk of developing high altitude pulmonary edema.

Any of the 39 SNPs described above are as follows: rs12733147, rs2941757, rs56240659, rs28843785, rs4836498, rs79522289, rs59140633, rs12569857, rs241970, rs11620394, rs12148912, rs740873, rs919197, rs6009184, rs938355, rs9932581, rs6194, rs9592406, rs2297441, rs4762, rs2397218, rs12462380, rs 118699, rs11896604, rs12655827, rs130293, rs2486736, rs 417552, rs5768002, rs40305, rs11962222, rs2009196, rs2148582, rs1008438, rs10929728, rs 82826, rs6888553, rs 6016016016881 and rs 2468847.

Any of the above prediction models is the prediction model glm (PHONTYPE-PS).

The method for establishing the prediction model glm (Phentopy-PS) is as follows:

(1) preparing two matrices (matrices), one including genotype information for the 39 SNPs for each subject of the training set, and the other including effector value information for the 39 SNPs; the two matrices are multiplied, and the PS value of each subject is calculated according to the calculation formula of the multi-gene risk score, and is stored into an additional data box, wherein the phenotype value (the phenotype value refers to a patient with high pulmonary edema or a normal person) and the PS value of each subject are included.

(2) Establishing a formula: phenotype-PS; performing logistic regression on the formula, and selecting a function glm, wherein the input data of the regression is the data frame obtained in the step (1); obtaining a prediction model glm (Phentopy-PS);

the method for establishing the prediction model specifically comprises the following steps.

(1) Preparing two matrices (matrices), one including genotype information for the 39 SNPs for each subject of the training set, and the other including effector value information for the 39 SNPs; the two matrices are multiplied, and the PS value of each subject is calculated according to the calculation formula of the multi-gene risk score, and is stored into an additional data box, wherein the phenotype value (the phenotype value refers to a patient with high pulmonary edema or a normal person) and the PS value of each subject are included.

(2) Establishing a formula: phenotype-PS; performing logistic regression on the formula, and selecting a function glm, wherein the input data of the regression is the data frame obtained in the step (1); a prediction model glm (Phentopy-PS) was obtained.

The evaluation method of the prediction model is as follows: inputting the genotype information of 39 SNPs of each subject in the verification set into a prediction model glm (PHONTYPE-PS), selecting a predict function, and obtaining the prediction result of the subject (the prediction result is a patient with high altitude pulmonary edema or a normal person).

The application method of the prediction model is as follows: inputting the genotype information of 39 SNPs of the person to be tested into a prediction model glm (Phentopy-PS), selecting a prediction function, and obtaining the prediction result of the person to be tested (the prediction result is a patient with high altitude pulmonary edema or a normal person).

The formula for the multigenic risk score (PS) is as follows:

in the calculation formula, Gi is the number of the effective alleles (value is 0 or 1 or 2) in the genotype of the subject based on a certain SNP, β i is the effective value of a certain SNP in the association analysis, and n is the number of SNPs included in the calculation (the number of SNPs is 39, and the information of 39 SNPs is shown in table 1). The effect alleles and effect values of the individual SNPs are shown in Table 3. In Table 3, BETA is the effect value (. beta.i).

Any of the above training sets consists of statistically significant patients with high altitude pulmonary edema and normal persons.

Any of the above verification sets consists of statistically significant patients with high altitude pulmonary edema and normal persons.

Any of the above products may be a kit.

Any of the above subjects may be Chinese.

Any of the above subjects may be chinese han nationality.

Any of the above subjects may be chinese han-nationality men.

Any of the subjects described above may be Chinese in plain.

Any of the above subjects may be chinese han population in plain region.

Any of the above subjects may be chinese han men in plain regions.

Any of the subjects described above may be Chinese from a plain area to a plateau area.

Any of the subjects described above may be chinese han population arriving at plateau from plain.

Any of the above subjects may be a chinese han male who arrives at the plateau from the plain region.

Any of the subjects described above may be Chinese expected to go to plateau from plain.

Any of the subjects described above may be chinese Han nationality predicted to go to plateau from plain areas.

Any of the above subjects may be chinese men expected to go to plateau from plain.

Any one of the above plateau regions may be a Tibet plateau region.

Any one of the above plateau regions may be the rasa region of tibetan plateau.

The substance for detecting the genotype of the subject based on the 39 SNPs may be a substance for detecting the genotype of the subject based on the 39 SNPs based on any one of the following techniques: DNA sequencing, restriction enzyme fragment length polymorphism, single-strand conformation polymorphism, denaturing high performance liquid chromatography, SNP chip, etc. The SNP chip may include a chip based on a nucleic acid hybridization reaction, a chip based on a single base extension reaction, a chip based on an allele-specific primer extension reaction, a chip based on a "one-step" reaction, a chip based on a primer ligation reaction, a chip based on a restriction enzyme reaction, a chip based on a protein DNA binding reaction, a chip based on a fluorescent molecule DNA binding reaction, and the like.

Any of the above-described substances for detecting the genotype of a subject based on 39 SNPs includes a primer set. The primer set consists of all the primers for detecting 39 SNPs (for example, the primer set for detecting each SNP consists of 3 primers, and then the primer set for detecting 39 SNPs consists of 117 primers). The primer set for detecting each SNP consists of three primers, one of which is a single-base extension primer, and the other two of which are used for amplifying a DNA fragment including the SNP. The two amplification primers are not particularly limited in sequence as long as they can amplify a genomic DNA fragment including the SNP. The single base extension primer can be designed according to the upstream or downstream (excluding the SNP site) of the SNP in the human genome, and the extended nucleotide of the single base extension primer corresponds to the SNP in the human genome, namely, the 3' terminal nucleotide of the single base extension primer corresponds to the adjacent nucleotide (namely, the former nucleotide or the latter nucleotide of the SNP) of the SNP in the human genome.

Any of the above-mentioned materials for detecting a subject's genotype based on a certain SNP may further include PCR reagents, DNA sequencing reagents, DNA sequencers, and the like.

Any of the above-described substances for detecting the genotype of a subject based on 39 SNPs includes a primer set. The primer set consists of all the primers for detecting 39 SNPs (for example, the primer set for detecting each SNP consists of 2 primers, and then the primer set for detecting 39 SNPs consists of 78 primers). The pair for detecting each SNP consists of two primers for amplifying a DNA fragment including the SNP. The two primers are not particularly limited in sequence, as long as they can amplify a genomic DNA fragment including the SNP.

The combination of 39 SNPs provided by the invention can be used for screening individuals susceptible to high altitude pulmonary edema, predicting the susceptibility of people to high altitude pulmonary edema, screening individuals carrying genes susceptible to high altitude pulmonary edema of people and evaluating the risk of suffering from high altitude pulmonary edema.

The invention can be used for avoiding or reducing the occurrence of the plateau pulmonary edema and has great application and popularization values for plateau areas.

Detailed Description

The present invention is described in further detail below with reference to specific embodiments, which are given for the purpose of illustration only and are not intended to limit the scope of the invention. The examples provided below serve as a guide for further modifications by a person skilled in the art and do not constitute a limitation of the invention in any way. The experimental procedures in the following examples, unless otherwise indicated, are conventional and are carried out according to the techniques or conditions described in the literature in the field or according to the instructions of the products. Materials, reagents and the like used in the following examples are commercially available unless otherwise specified. Ethical statement: each subject signed an informed consent, which was approved by the seventh medical center of the liberty military and the medical ethics committee of the general hospital of the tibetan liberty military. The plateau pulmonary edema patients are all patients diagnosed in hospitals, and the diagnosis standard is shown in documents: naming, typing and diagnosing standards of the altitude diseases in China; volume 20, stage 1 of the journal of plateau medicine 2010; 9-11. The normal person in the present invention refers to a patient with non-high altitude pulmonary edema.

Example 1 screening for SNPs associated with risk of high altitude pulmonary edema

The matched population consists of a population of patients with high altitude pulmonary edema and a corresponding normal population.

Establishing a plurality of groups of paired groups, performing a large amount of whole genome sequencing and sequence comparison analysis work, and obtaining a large amount of differential SNPs. The allele frequencies and genotype frequencies of each differential SNP in the plateau pneumochysis patient population and the corresponding normal population were verified in turn for association analysis. And (3) trying a plurality of SNP combination forms and respectively establishing a model and a verification model preliminarily. By a large number of performance comparisons, a combination of 39 SNPs was finally screened.

The information of 39 SNPs is shown in Table 1. In table 1, chromosomal locations are for grch37.p 13.

TABLE 1

Example 2 method for establishing genotype of test subject based on individual SNP

The subjects were each tested for genotype based on each SNP (39 SNPs in total, information in Table 1).

1. The peripheral blood of the subject was collected and genomic DNA was extracted.

2. And (3) performing PCR amplification by using the genomic DNA extracted in the step (1) as a template and adopting a specific primer pair.

The specific primer pair consists of a primer F and a primer R.

PCR amplification was performed in 384-well plates, one reaction system per well.

Composition of reaction system for PCR amplification (5. mu.L): 0.5. mu.L of 10 XPCR buffer, 0.4. mu.L of 25mM MgCl ₂ The volume of the solution, 0.1. mu.L of 25mM dNTP mix, genomic DNA, HotStart Taq DNA polymerase, primer F, and primer R was made up with ultrapure water. In the 5. mu.L system, the content of genomic DNA was 20 to 50ng, the content of HotStar Taq enzyme was 0.5U, the content of primer F was 0.5pmol, and the content of primer R was 0.5 pmol.

Reaction procedure for PCR amplification: 4 minutes at 94 ℃; at 94 ℃ for 20 seconds, at 56 ℃ for 30 seconds, at 72 ℃ for 1 minute, for 45 cycles; 3 minutes at 72 ℃; keeping at 4 ℃.

3. Alkaline phosphatase treatment was performed (in order to remove free dNTPs from the system).

Taking the 384-well plate which completes the step 2, preparing a reaction system and then carrying out reaction.

Composition of reaction system (7. mu.L): mu.L of the product solution obtained in step 2, 0.3. mu.L of SAP, 0.17. mu.L of 10 XSAP buffer, and 1.53. mu.L of ultrapure water.

SAP (shrimp alkaline phosphatase ): the product specification is 1.7U/mu L; agena corporation, cat # 10002.1. The 10 × SAP buffer is the matched buffer of SAP.

Reaction conditions are as follows: 40 minutes at 37 ℃; 5 minutes at 85 ℃; maintaining the temperature at 4 ℃.

4. Single base extension was performed.

Taking the 384-well plate which completes the step 3, preparing a reaction system and then carrying out single-base extension reaction.

Composition of reaction System for Single base extension (10. mu.L): 7. mu.L of the product solution obtained in step 3, 0.3. mu.L of the single-base extension reaction enzyme, 0.17. mu.L of the 10 Xsingle-base extension reaction buffer, 1. mu.L of the single-base extension primer, and 1.53. mu.L of ultrapure water.

Single base extension reaction enzyme: the product specification is 1.7U/mu L; agena, cat. No. 1432. The 10 Xsingle-base extension reaction buffer is the matched buffer of the single-base extension reaction enzyme.

The reaction procedure for single base extension is as follows:

firstly, 94 ℃ for 30 seconds;

② 94 ℃ for 5 seconds;

③ 5 cycles of 5 seconds at 52 ℃ and 5 seconds at 80 ℃;

fourthly, 40 cycles of 5 seconds at 94 ℃, 5 seconds at 52 ℃ and 5 seconds at 80 ℃;

fifthly, the temperature is 72 ℃ for 3 minutes;

maintaining at 4 deg.c.

5. Resin purification is performed.

Taking the 384-well plate which completes the step 4, adding 16 mu l of water into each well, then adding Clean Resin (Sequenom corporation, USA) into each well, sealing the membrane, vertically rotating at a low speed for 30 minutes to fully contact the Resin with the reactant, then centrifuging to sink the Resin into the bottom of the well, and obtaining the supernatant which is the extension product after the Resin is purified.

6. And (4) spotting the chip.

The MassARRAYANodeipenser RS1000 Spotter (SEQUENOM) was started and the resin-purified extension product was transferred to a 384-well SpectroCHIP (Sequenom) chip (SEQUENOM).

7. And (4) detecting by mass spectrometry.

The spotted SpectroCHIP chip is analyzed by MALDI-TOF, and the detection result is typed by TYPER 4.0 software (sequenom) and output.

The primers F, R and single-base extension primers for detecting the genotype of the subject based on each SNP are shown in Table 2.

TABLE 2

Example 3 establishment of Risk assessment model

Calculation formula of one-gene and multi-gene risk scores

The formula for the multigene risk score (PS) is as follows:

in the calculation formula, Gi is the number of the effective alleles (value is 0 or 1 or 2) in the genotype of the subject based on a certain SNP, β i is the effective value of a certain SNP in the association analysis, and n is the number of SNPs included in the calculation (the number of SNPs is 39, and the information of 39 SNPs is shown in table 1). The effect alleles and effect values of the individual SNPs are shown in Table 3. In Table 3, BETA is the effect value (. beta.i).

TABLE 3

In the case of rs12733147, the polymorphic form is A/G, and the effector allele is A; if the genotype of the subject is AA, then the number of effector alleles is 2; if the genotype of the subject is GG, then the number of its effector alleles is 0; if the subject's genotype is AG, then the number of its effector alleles is 1.

Secondly, establishing a prediction model (logistic regression model)

The subject population consisted of several patients with high altitude pulmonary edema and several normal individuals. Each subject was individually tested for genotype based on each SNP (39 SNPs in total) according to the method of example 2.

Samples were taken 1000 times from the subject population. At each sampling time, 80% of the subjects in the subject population consisted of high altitude pulmonary edema patients and 80% of the normal individuals in the subject population, and the remaining 20% of the subjects consisted of high altitude pulmonary edema patients and 20% of the normal individuals in the subject population.

The R language is used for establishing the model, evaluating the model and applying the model.

The steps of establishing the model are as follows:

(1) preparing two matrices (matrices), one including genotype information for the 39 SNPs for each subject of the training set, and the other including effector value information for the 39 SNPs; multiplying the two matrixes, calculating the PS value of each subject according to the calculation formula of the multi-gene risk score, and storing the PS value into an additional data box, wherein the PS value and the phenotype value of each subject are included (the phenotype value refers to a patient with high altitude pulmonary edema or a normal person).

(2) Establishing a formula: phenotype-PS; performing logistic regression on the formula, and selecting a function glm, wherein the input data of the regression is the data frame obtained in the step (1); obtaining a prediction model glm (Phentopy-PS);

the procedure for evaluating the model is as follows: inputting the genotype information of 39 SNPs of each subject in the verification set into a prediction model glm (PHENOTYPE-PS), selecting a prediction function, and obtaining the prediction result of the subject (the prediction result is a patient with high altitude pulmonary edema or a normal person).

The model is evaluated based on the consistency of the predicted outcome and actual phenotype of the subjects in the validation set. Sampling is carried out for 1000 times, and the average AUC is more than 0.95, which shows that the classification effect of the model is good.

The steps of applying the model are as follows: inputting the genotype information of 39 SNPs of the person to be tested into a prediction model glm (Phentopy-PS), selecting a prediction function, and obtaining the prediction result of the person to be tested (the prediction result is a patient with high altitude pulmonary edema or a normal person).

Example 4 Risk assessment on subjects

Peripheral blood samples were obtained from the general hospital of the liberty military, tibet. 166 peripheral blood samples were obtained from 166 high altitude pulmonary edema patients, and 142 peripheral blood samples were obtained from 142 normal persons (non-high altitude pulmonary edema patients). 166 patients with high altitude pulmonary edema and 142 normal persons were Han nationalities of Chinese male unrelated in blood margin, both lived in plain areas for a long time (long term means more than 1 year) and received peripheral blood after arriving at Lhasa (altitude 3658 m). All people had no history of smoking and drinking, and no autoimmune related diseases (e.g. vitiligo, psoriasis, type I diabetes etc.) and no history of high altitude trips before.

The procedure was followed as in example 2. Detecting the genotype of the subject based on the 39 SNPs.

The PS values for each subject were calculated according to the formula for the multigene risk score in example 3. The average PS value in the normal group (142 cases) was-3.85, and the average PS value in the high altitude pulmonary edema group (166 cases) was 1.99.

According to the procedure of applying the model in example 3, the subject was substituted into the prediction model glm (PHENOTYPE-PS) based on the genotypes of the 39 SNPs, and the prediction function was selected to obtain the prediction result of the subject (the prediction result was a patient with high altitude pulmonary edema or a normal person).

The predicted outcome (predicted as a high altitude pulmonary edema patient or normal person) and the actual phenotype (actual phenotype is a high altitude pulmonary edema patient or normal person) are fitted. The results showed that AUC was 0.95, indicating that the model was able to achieve excellent prediction ability with a sensitivity of 85.2%, specificity of 9.0%, and positive and negative predictive values of 0.88 and 0.88. The model accuracy index is shown in table 2. The confusion matrix is shown in table 3.

TABLE 2 accuracy of the binary prediction model based on 39 SNPs (N ═ 308)

N	AUC	Sensitivity of the device	Degree of specificity	Negative predictive value	Positive predictive value
						39	0.95	0.852	0.09	0.88	0.88

TABLE 3 confusion matrix for predicting high-altitude pulmonary edema based on 39 SNPs sites (N ═ 308)

The above results show that the risk model composed of 39 susceptibility genes associated with high altitude pulmonary edema can better realize the prediction of diseases. The method can be used for screening individuals susceptible to the high altitude pulmonary edema, predicting the susceptibility of people to the high altitude pulmonary edema, screening individuals carrying genes susceptible to the high altitude pulmonary edema of people and evaluating the risk of the high altitude pulmonary edema.

The present invention has been described in detail above. It will be apparent to those skilled in the art that the invention can be practiced in a wide range of equivalent parameters, concentrations, and conditions without departing from the spirit and scope of the invention and without undue experimentation. While the invention has been described with reference to specific embodiments, it will be appreciated that the invention can be further modified. In general, this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. The use of some of the essential features is possible within the scope of the claims attached below.

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<213> Artificial Sequence (Artificial Sequence)

<400> 44

acgttggatg aatatccagc cactgccttg 30

<210> 45

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 45

atatttgcag aagcacagca tgta 24

<210> 46

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 46

acgttggatg aaacagaaaa acggcggagg 30

<210> 47

<211> 29

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 47

acgttggatg tggaatggtg gcaggagtg 29

<210> 48

<211> 17

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 48

acggaggccg gaggcag 17

<210> 49

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 49

acgttggatg tgcagtaggg tcatttggtc 30

<210> 50

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 50

acgttggatg gaagagtgtt gcctcatacc 30

<210> 51

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 51

cccagggtca tttggtcatc cag 23

<210> 52

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 52

acgttggatg tggatatgtg tcatgacggg 30

<210> 53

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 53

acgttggatg tacctgtgac aacagcatcg 30

<210> 54

<211> 18

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 54

gtgatgccat ttcacaca 18

<210> 55

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 55

acgttggatg gtgtccactt ttaatcaggg 30

<210> 56

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 56

acgttggatg aactccctgt ccctcaactc 30

<210> 57

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 57

ggggacaggg ctctctaata aa 22

<210> 58

<211> 29

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 58

acgttggatg tgtacagggc ctgctagtg 29

<210> 59

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 59

acgttggatg acaaacggct gcttcaggtg 30

<210> 60

<211> 15

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 60

agctgctgct gtcca 15

<210> 61

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 61

acgttggatg ccttcctagg catctgctaa 30

<210> 62

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 62

acgttggatg tcagaggaat ccagataagg 30

<210> 63

<211> 26

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 63

aaatttatac agataaactc atacag 26

<210> 64

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 64

acgttggatg taagtgctct tcccaacctc 30

<210> 65

<211> 29

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 65

acgttggatg ggcacacagg aacactccc 29

<210> 66

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 66

ggggtcaacc tctcggatca cac 23

<210> 67

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 67

acgttggatg acgtaggtgt tgaaagccag 30

<210> 68

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 68

acgttggatg gattgacagg ttcatgcagg 30

<210> 69

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 69

cccccgtcca cactggctcc c 21

<210> 70

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 70

acgttggatg tactaccaag gacagtgacg 30

<210> 71

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 71

acgttggatg tcctttgtct ctgacctagc 30

<210> 72

<211> 19

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 72

tgacgggtct gagatttac 19

<210> 73

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 73

acgttggatg ggtgcacagc tcattccatc 30

<210> 74

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 74

acgttggatg gatgtggtct ggtgtcaatc 30

<210> 75

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 75

aaccggggca tgtggttcca ag 22

<210> 76

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 76

acgttggatg taaaccagat caccaagcac 30

<210> 77

<211> 31

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 77

acgttggatg caagactttt ccctatgcta c 31

<210> 78

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 78

ctgaggattc tattagcagg ggac 24

<210> 79

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 79

acgttggatg gaggttttca ttcacttcgg 30

<210> 80

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 80

acgttggatg ggccagtctt agcaacttac 30

<210> 81

<211> 16

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 81

tcacttcggt aggtga 16

<210> 82

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 82

acgttggatg gatctgcaaa ttccaattcc 30

<210> 83

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 83

acgttggatg caaggtgctg catatgtgtg 30

<210> 84

<211> 17

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 84

tccatatgct cctctcc 17

<210> 85

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 85

acgttggatg gcagcgactg gagacaatag 30

<210> 86

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 86

acgttggatg tacctgatat gacaagcgag 30

<210> 87

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 87

acaatagata tattttcttg cttttaa 27

<210> 88

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 88

acgttggatg aaatgggacc cctgtgtatg 30

<210> 89

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 89

acgttggatg tgtagccaag aatgacgctg 30

<210> 90

<211> 20

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 90

tggcacgacc taccatccac 20

<210> 91

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 91

acgttggatg cgagtgcagc actcagtgtt 30

<210> 92

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 92

acgttggatg ccccatttcg tgatagcaag 30

<210> 93

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 93

gaatcactca gtgttgagac c 21

<210> 94

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 94

acgttggatg tgagaagagc tggatagacc 30

<210> 95

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 95

acgttggatg gagttatcca ccttaaaggg 30

<210> 96

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 96

ctcccgatgt aagaccccca aa 22

<210> 97

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 97

acgttggatg tctgggtact acagcagaag 30

<210> 98

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 98

acgttggatg agctcagtta catctgagag 30

<210> 99

<211> 15

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 99

tcagctcctt ctcgg 15

<210> 100

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 100

acgttggatg aatcaccgag ctcgatgagg 30

<210> 101

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 101

acgttggatg tctgattggt ccaaggaagg 30

<210> 102

<211> 18

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 102

ggcgggaata ttccaggg 18

<210> 103

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 103

acgttggatg ataactgggt cccctgcaag 30

<210> 104

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 104

acgttggatg aggtaggaaa acctgagctg 30

<210> 105

<211> 18

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 105

tcccctgcaa gtttttaa 18

<210> 106

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 106

acgttggatg cagcccagaa caagctgtta 30

<210> 107

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 107

acgttggatg ttgatctaag ccccgaagac 30

<210> 108

<211> 20

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 108

ggaacaagct gttagcagga 20

<210> 109

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 109

acgttggatg agcttgttca aactgtaggg 30

<210> 110

<211> 31

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 110

acgttggatg ctgtagttaa attctgaagc c 31

<210> 111

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 111

caggcaaata tgccaaattt a 21

<210> 112

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 112

acgttggatg agcacgagaa cagcaccgag 30

<210> 113

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 113

acgttggatg tgacaacctc ttgacgaccc 30

<210> 114

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 114

ggtgggaaca gcaccgagga aaag 24

<210> 115

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 115

acgttggatg aatgttagga atgggcctgc 30

<210> 116

<211> 30

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 116

acgttggatg tctcagaatt cacaggccag 30

<210> 117

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 117

agcataatta tttcctcaca tcct 24

Claims (5)

1.39 SNPs are used as detection targets in product development; the function of the product is as follows (a) or (b):

(a) screening susceptible individuals of plateau pulmonary edema;

(b) assessing the risk of the subject for developing high altitude pulmonary edema;

the 39 SNPs were as follows: rs12733147, rs2941757, rs56240659, rs28843785, rs4836498, rs79522289, rs59140633, rs12569857, rs241970, rs11620394, rs12148912, rs740873, rs919197, rs6009184, rs938355, rs9932581, rs6194, rs9592406, rs2297441, rs4762, rs2397218, rs12462380, rs 118699, rs11896604, rs12655827, rs130293, rs2486736, rs 417552, rs5768002, rs40305, rs11962222, rs2009196, rs2148582, rs1008438, rs10929728, rs 82826, rs6888553, rs 6016016016881 and rs 2468847.

2. A product comprising a substance for detecting a genotype of a subject based on 39 SNPs; the function of the product is as follows (a) or (b):

(a) screening susceptible individuals of plateau pulmonary edema;

(b) assessing the risk of the subject for developing high altitude pulmonary edema;

the 39 SNPs were as follows: rs12733147, rs2941757, rs56240659, rs28843785, rs4836498, rs79522289, rs59140633, rs12569857, rs241970, rs11620394, rs12148912, rs740873, rs919197, rs6009184, rs938355, rs9932581, rs6194, rs9592406, rs2297441, rs4762, rs2397218, rs12462380, rs699, rs11896604, rs12655827, rs130293, rs2486736, rs 417552, rs5768002, rs40305, rs11962222, rs 2006, 2148582, rs1008438, rs 109728, rs 829196, rs6888553, rs 0626881 and rs 2468847.

3. The product of claim 2, wherein: the substance for detecting the genotypes of the 39 SNPs of the subject is a primer group; the primer group consists of 117 primers which are sequentially shown as a sequence 1 to a sequence 117 in a sequence table.

4. Use of a substance for detecting a genotype of a subject based on 39 SNPs in the manufacture of a product; the function of the product is as follows (a) or (b):

(a) screening susceptible individuals of high altitude pulmonary edema;

(b) assessing the risk of the subject developing high altitude pulmonary edema;

the 39 SNPs were as follows: rs12733147, rs2941757, rs56240659, rs28843785, rs4836498, rs79522289, rs59140633, rs12569857, rs241970, rs11620394, rs12148912, rs740873, rs919197, rs6009184, rs938355, rs9932581, rs6194, rs9592406, rs2297441, rs4762, rs2397218, rs12462380, rs 118699, rs11896604, rs12655827, rs130293, rs2486736, rs 417552, rs5768002, rs40305, rs11962222, rs2009196, rs2148582, rs1008438, rs10929728, rs 82826, rs6888553, rs 6016016016881 and rs 2468847.

5. The use of claim 4, wherein: the substance for detecting the genotypes of the 39 SNPs of the subject is a primer group; the primer group consists of 117 primers which are sequentially shown as a sequence 1 to a sequence 117 in a sequence table.