CN115094130A - Detection primer and evaluation model for risk genes of recurrent abortion caused by thrombosis - Google Patents

Abstract

The invention relates to a detection primer and an evaluation model for recurrent abortion risk genes caused by thrombosis, belonging to the fields of molecular biology and bioinformatics, and specifically comprising the following steps: and detecting a plurality of SNPs (single nucleotide polymorphisms) based on multiple PCR amplification and capillary electrophoresis, endowing different weights to the incorporated SNP sites through the construction of a regression prediction model, scoring, and finally classifying and evaluating the thrombus risk of the sample to be detected. The invention discloses a gene for risk of recurrent abortion caused by thrombosis, which comprises 11 gene names, 12 corresponding sites and primers corresponding to the 12 sites. The invention also discloses an evaluation model of the gene for risk of recurrent abortion caused by thrombosis and a use method of the corresponding evaluation model.

Description

Detection primer and evaluation model for risk genes of recurrent abortion caused by thrombosis

Technical Field

The invention belongs to the field of molecular biology and bioinformatics, and particularly relates to a method for detecting multiple SNPs (single nucleotide polymorphisms) based on multiple PCR (polymerase chain reaction) amplification and capillary electrophoresis, endowing different weights to incorporated SNP sites through construction of a regression prediction model, scoring, and finally classifying and evaluating thrombus risks of a sample to be detected.

Background

Recurrent Spontaneous Abortion (RSA) refers to spontaneous abortion occurring 2 or more times continuously, and the cause of spontaneous abortion is complicated, and currently, the more definite causes include genetic factors, endocrine factors, immune factors, prothrombotic state (PTS), anatomical factors, etc., but it is difficult to make an accurate diagnosis of the cause clinically because of lack of specific expression, and some related factors are easily ignored, thereby affecting the productivity. The habitual abortion of unknown cause not only causes serious trauma to the spirit and body of a patient, but also causes great pain to families.

At present, the research on the etiology of the immune genetics of the habitual abortion with unknown reasons is increasing, various researchers are dedicated to searching susceptibility genes of the habitual abortion, and the screening of the susceptibility genes is mainly focused on genes related to risk factors of the habitual abortion. Studies have shown that habitual abortion is caused by abnormal endocrine, metabolic and immune factors in the mother.

Homozygous mutations in the MTHFR gene are a common cause of hyperhomocysteinemia. Hyperhomocysteinemia causes damage and dysfunction of endothelial structures, stimulates hyperplasia of vascular smooth muscle cells, destroys the balance of blood coagulation and fibrinolysis systems of organisms, influences lipid metabolism, enables the organisms to be in a hypercoagulable state and is easy to form thrombus. Hyperhomocysteinemia is associated with early placental peeling, fetal growth restriction, low birth weight infants and the occurrence of preeclampsia. MTHFR plays an important role in hyperhomocysteine metabolism, a common variant of the MTHFR gene is MTHFR677T, carriers of the variant gene are often accompanied by slight high homocysteine level increase, the MTHFR677T gene is quite common in the Caucasian population, homozygote carriers account for 10 percent of the total population, but the high homocysteine level is slightly increased, so that the influence of MTHFR gene mutation on thrombus risk is difficult to estimate. Nelen and the like perform case contrast research on 10 multicenter clinical data, and the probability of recurrent abortion of patients with hyperhomocysteinemia is increased by 3-4 times. The homozygous MTHFR C677T and A1298C have polymorphism distributions of 10% -16% and 4% -6% in Europe, respectively. However, no clear findings, whether in pregnant or non-pregnant women, suggest that mutations in the MTHFR gene increase the risk of venous thrombosis. Although hyperhomocysteinemia has been reported to be a moderate risk factor for venous thrombosis, recent studies have shown that elevated levels of hyperhomocysteine are only a minor risk factor for venous thrombosis.

Plasminogen activator inhibitor-1 (PAI-1)) is a member of the serine protease inhibitor superfamily, and is the main physiological control factor of urokinase-type plasminogen activator and tissue-type plasminogen activator, and the level of PAI-1 is increased and is associated with arterial thrombosis, and the PAI-1 concentration is increased, so that the plasminogen is converted into plasmin to be reduced, and fibrin and fibrinogen in the blood circulation are accumulated, blood hypercoagulability and thrombosis are caused. The research shows that the PAI-1 level is related to the polymorphism of the 4G \5G gene.

Prothrombin (factor II) is a vitamin K-dependent protein with a molecular weight of 72kD and consists of 579 amino acid residues; the prothrombin gene is located at 11p 11-q 12, has a total length of 21kb and comprises 14 exons and 13 introns. The prothrombin gene G20210A mutation is a relatively weaker risk factor for Venous Thromboembolism (VTE) than the Leiden mutation in the coagulation factor V gene. In 1996, Poort et al found that guanine at position 20210 in the 3' non-transcribed region of the prothrombin gene was mutated to adenine (G-A), which increased plasma prothrombin levels and increased the risk of venous thrombosis. The incidence of mutations in women with normal pregnancy ranges from 1% to 3% and in women with poor outcome pregnancy ranges around 10%, and is associated with the occurrence of fetal growth restriction, preeclampsia, recurrent miscarriage, premature birth and premature placental stripping.

Different genetic thrombosis causes correspond to different treatment and intervention measures, such as folic acid supplement, vitamin B6 and B12 for patients with homocysteinemia caused by abnormal expression of methylenetetrahydrofolate reductase (MTHFR) gene. For example, heparin anticoagulant therapy is considered during pregnancy of patients with factorVLeiden gene mutation, protein S or protein C deficiency. Therefore, the genetic thrombus risk assessment is carried out on the pregnant women who suffer from abortion of unknown reasons or who have pathological findings of thrombus, and the genetic thrombus risk assessment has an important role in treatment and reproduction.

The traditional researches are generally single-factor analysis, but the accuracy and the positive rate of the prediction or the review of recurrent abortion are low according to single factors. There is therefore a need for improvements in the prior art.

The CN201610940238.1 patent only detects 2 genes of key enzymes of folic acid metabolism, and 3 polymorphic sites are used for predicting thrombosis; patent CN201310461481.1 only detected one gene of MTHFR, 1 site was used to predict thrombosis; in the CN109055368B patent, two genes PAI-1 and F5 are detected, and 2 polymorphic sites are totally used for predicting thrombosis. In the prior art, only one typing result is given, but risks cannot be informed, so that a standardized judgment standard is lacked; the judgment deviation under the human factor is easy to occur.

The CN201710309444.7 patent, although the content of the detection is very much, includes 18 genes of all exons and three gene specific polymorphisms, although the detection genes are many, the final result only gives a list of mutations in such multiple genes, and does not give any clinical reference value. Any one of the ordinary people detects such multiple genes, and in such a multi-region, a plurality of mutation sites can be found, and if 1 mutation site is found, even if the risk is high, all people are high-risk. This neglects the weight of the gene and results in different physicians understanding of the thrombus caused by different mutations, leading to differences in the therapeutic intervention.

Disclosure of Invention

The invention aims to provide a detection primer and an evaluation model for a recurrent abortion risk gene caused by thrombosis.

In order to solve the problems, the invention provides a recurrent abortion risk gene caused by thrombosis, which is characterized in that according to the gene weight, the set gene name, the corresponding locus and the rs number are as follows:

name of Gene	Site of the body	rs number
			F2	G20210A	rs1799963
F5	G1691A	rs6025
			IL10	c.-149+2211A>G	rs1800871
PAI-1	-675 4G/5G	rs1799768
			MTHFR	A1298C	rs1801131
MTHFR	C677T	rs1801133
			MTRR	A66G	rs1801394
PROC	C169T	rs757583846
			VEGFA	-1154G/A	rs1570360
PROS	A586G	rs121918474
			SERPINC1	C218T	rs121909551
THBD	G1209T	rs398122807

。

Improvement of the gene for risk of recurrent abortion caused by thrombosis of the present invention: primers corresponding to 12 loci for 11 genes were as follows:

wt represents wild type, mt represents mutant type.

The invention also provides an evaluation model of the gene for risk of recurrent abortion caused by thrombosis, which utilizes the gene as described above, and the specific assignment table is as follows:

the formula for the RSA risk value is:

2×{2.8×rs1799963+3×rs6025+(3+rs1570360+rs121918474+rs121909551+rs398122807)×(1+rs1799768)+[(1+rs1801131)×(1+rs1801133)+1]^(2 ^rs1801394 )+2×rs757583846}×3 ^rs1800871 ；

the judgment threshold value is 60-65.

Improvement of the evaluation model of the gene for risk of recurrent abortion caused by thrombosis of the present invention:

when the judgment threshold is 65, the corresponding result judgment criteria are:

when the RSA risk value is more than or equal to 65, the risk of thrombus is high;

when the RSA risk value is less than or equal to 55, the risk of thrombus is low;

RSA risk values in the [55,65] interval are indicative of risk in thrombosis.

The invention also provides a use method of the evaluation model of the gene for risk of recurrent abortion caused by thrombosis, which comprises the following steps:

carrying out PCR amplification on a sample to be detected to obtain types corresponding to 12 bit points of 11 genes of the sample to be detected;

obtaining an RSA risk value according to an assignment table and a calculation formula of the RSA risk value;

and finally, carrying out corresponding risk judgment.

Improvement of the method of use as an evaluation model of the gene for risk of recurrent abortion caused by thrombosis of the present invention:

extracting the genome DNA of a sample to be detected by using a DNA extraction kit, and then performing multiplex PCR amplification by using a PCR primer;

reaction system:

the wild type amplification system is as follows: 2 XPCR amplification premix solution 12.5ul, wild type upstream primer mixture 2ul, downstream primer mixture 2ul, DNA template 100ng-500ng, make up to 25ul with water without ribozyme;

the mutant amplification system is as follows: 2 XPCR amplification premix solution 12.5ul, mutant upstream primer mixture 2ul, downstream primer mixture 2ul, DNA template 100ng-500ng, make up to 25ul with water without ribozyme;

the 2 XPCR amplification premix was 25mM Tris-HCl (pH8.0),125mM KCl,6.5mM Mg ²⁺ 0.6mM dNTP; the balance of deionized water;

PCR amplification procedure: 95 ℃ for 2 min- > (94 ℃ for 30 sec; 60 ℃ for 60 sec; 72 ℃ for 60 sec; 30 cycles) - >72 ℃ for 10 min- >4 ℃.

The invention also provides a method for acquiring the disease potential associated gene based on multi-site information fusion, which is a recurrent abortion risk gene caused by thrombosis, and comprises the following steps:

step 1: based on non-relevant literature knowledge, inquiring the genetic locus of the recurrent abortion related to the easy thrombosis reported at home and abroad at present, wherein the frequency of the genetic locus exceeds one in a thousand in Chinese population;

thereby setting the corresponding gene locus;

step 2: designing and synthesizing primers for the set gene loci, and detecting;

and step 3: through clinical tests, detecting pregnant women with recurrent abortion related to the known thrombosis susceptibility and people who are clinically diagnosed with no recurrent abortion by using the primers in the step 2;

and 4, step 4: carrying out normalization processing on the result of the step 3, then utilizing computer tools such as biological information and the like to construct a decision tree, and obtaining a calculation model, namely a corresponding calculation formula;

and 5: and (4) setting a threshold value for the sample, and evaluating the sensitivity, specificity, accuracy and the like under the threshold value.

The disease potential related gene based on multi-site information fusion is obtained by firstly inquiring recurrent abortion gene sites related to easy thrombosis based on non-related documents, then simultaneously detecting the gene sites through a gene chip hybridization technology, determining the incorporated gene sites through a regression prediction model algorithm, simultaneously endowing corresponding weights to the sites, scoring, and finally classifying and evaluating the thrombus risk of a sample to be detected.

The invention detects 12 SNP risk sites of 11 genes with high incidence in Chinese population by a medium flux mode, and then forms an easy thrombosis evaluation model related to recurrent abortion, which is used for evaluating thrombosis risk, thereby predicting recurrent abortion and guiding the treatment of high risk population.

Description of the invention: thrombosis, which is a very important cause of recurrent abortion, can treat, for example, MTHFR-related thrombosis, which may reduce the risk of folate uptake, while PAI-1-related thrombosis can be avoided by injection of small-molecule heparin sodium. For low risk populations, these treatments are not recommended. Natural pregnancy should be selected. Namely, the risk of thrombus is evaluated first, whether the thrombus is easy to cause thrombus or not is judged, the easy thrombus causes a plurality of problems (such as myocardial infarction, stroke, recurrent abortion and the like), the risk of recurrent abortion of people with high risk of thrombus is high, and different treatment modes correspond to different genes.

The invention has the following beneficial effects: and (3) assigning values according to different risks by detecting 12 easy-to-tie risk factors, and obtaining a quantitative risk value by utilizing an algorithm on a final result. The standardization of different laboratories in different regions is facilitated. According to the judgment threshold value, the judgment mode is visual.

The invention carries out assignment and calculation simulation on the result of 12 sites of 100 samples, namely a data matrix of 100 multiplied by 12 by a dichotomy to obtain a calculation formula which can distinguish the 50 known low-risk groups from the 50 known recurrent abortion groups.

Drawings

The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.

FIG. 1 is a capillary electrophoresis diagram of QFPCR primer amplification standard;

in FIG. 1, the top is a capillary electrophoresis of 12 homozygous wild-type samples detected by using the primers of the present invention, and the bottom is a capillary electrophoresis of 12 homozygous mutant samples detected by using the primers of the present invention.

FIG. 2 is a QFPCR capillary electrophoresis diagram of 12 sites of a practical sample.

Detailed Description

The invention will be further described with reference to specific examples, but the scope of the invention is not limited thereto:

example 1 acquisition of a Gene at risk of recurrent abortion caused by thrombosis:

step 1: based on non-relevant literature knowledge, inquiring the genetic locus of recurrent abortion related to thrombosis related reported at home and abroad, wherein the search range comprises expert consensus, medical guidelines and the like, and Chinese keywords: easy thrombus, recurrent abortion, SNP; english keywords: thrombophilia, RSA, SNP

And through Chinese common frequency filtration, the following 12 sites (as shown in Table 1) are found:

TABLE 1, 12 bit points

Step 2: aiming at 12 loci in the step 1, aiming at wild type and mutant, QF-PCR primers are respectively designed, and the design rule is as follows: the primer length is 20-22bp, the TM value is 40-60, and the GC content is 35% -65%. The downstream primer is a universal primer, and the 5 end of the downstream primer is provided with a FAM fluorescent label. The upstream primers are two, and respectively correspond to a wild type and a mutant type, the mutant type upstream primer is two bp more at the 5' end than the wild type upstream primer (mainly used for distinguishing the size of a product), meanwhile, the last base is different, the 3-end base of the wild type upstream primer is complementary with a wild type sequence, and the 3-end base of the mutant type upstream primer is complementary with a mutant type sequence. The lengths of the two products are different by more than 1 bp. Primers for the 12 sites are shown in table 2 below:

TABLE 2

-wt for wild type, -mt for mutant, all primers were synthesized in Shanghai Biotechnology Ltd, the downstream primers were universal, and the 5' ends were fluorescently labeled with FAM, all primers were configured with nuclease-free water to a working concentration of 10pmole/ul for use. All wild type forward primers were mixed in equal proportion to a wild type forward primer mixture. All the mutant upstream primers are mixed into a mutant upstream primer mixture in equal proportion. All the downstream primers with fluorescent modification are mixed into a downstream primer mixture in equal proportion.

And step 3:

3.1), extracting genome DNA of a sample (including a sample to be detected) by using a DNA extraction kit, and then performing multiplex PCR amplification by using the PCR primer in the step 2;

and (3) PCR reaction system:

the wild-type amplification system is: 2 x PCR amplification premix solution 12.5ul, wild type upstream primer mixture 2ul, downstream primer mixture 2ul, DNA template 100ng-500ng, the remainder is made up to 25ul with water without ribozyme.

The mutant amplification system is as follows: 2 XPCR amplifications premix solution 12.5ul, mutant upstream primer mixture 2ul, downstream primer mixture 2ul, DNA template 100ng-500ng, the deficiency, with no ribozyme water to make up to 25 ul.

The final concentration of the wild type upstream primer mixture/the mutant type upstream primer mixture in the system is 40nmole/L respectively, and the final concentration of the downstream primer mixture in the system is 80 nmole/L.

The 2 XPCR amplification premix had the composition of 25mM Tris-HCl (pH8.0),125mM KCl,6.5mM Mg ²⁺ 0.6mM dNTP; the balance of deionized water;

PCR amplification procedure: 95 ℃ for 2 min- > (94 ℃ for 30 sec; 60 ℃ for 60 sec; 72 ℃ for 60 sec; 30 cycles) - >72 ℃ for 10 min- >4 ℃.

3.2) performing capillary electrophoresis on the amplification products by using ABI 3100 or ABI 3730XL to obtain an electrophoresis diagram of 24 amplification products of 12 sites in one sample, and finally confirming 12 types corresponding to 11 genes according to the amplification result; the capillary electrophoresis of QF-PCR is a conventional technology for judging the amplification product. As shown in fig. 1.

FIG. 1 shows the results of electrophoresis obtained from 12 plasmids all of which are homozygous wild-type plasmids, and the top shows the results of electrophoresis obtained from 12 plasmids all of which are homozygous mutant-type plasmids, using a standard plasmid as a template. Thus fig. 1 is a reference peak: 12 samples, standard peak of 24 sites of wild type and mutant type.

In fig. 1: the ordinate is the fluorescence signal value and the abscissa is the time to peak. The upper graph in FIG. 1 shows the peak-off time of the wild type peak at 12 sites, and the lower graph in FIG. 1 shows the peak-off time of the mutant type peak at 12 sites. Shows no miscellaneous peak, no cross among products and high specificity. Meanwhile, the invention adds an ALDH2 gene locus as an internal reference for quality control and does not participate in analysis.

Step 4, interpretation of results of clinical samples:

obtaining DNA of a clinical sample, and performing detection according to the step 3 to obtain a detection result as shown in FIG. 2, wherein the clinical sample can be judged by combining the peak emergence times of the wild type and the mutant type in FIG. 1, wherein one site of F2, PROC, PAI, THBD, SERPINC1, IL10, PROS and MTHFR is a single peak, and the peak emergence time is consistent with the standard peak emergence time of the wild type, thus the clinical sample is judged to be homozygous wild type, while the other site of VEGFA and MTHFR is homozygous mutant, F5 and MTRR are heterozygous. The QFPCR interpretation method is a conventional technique.

And 5: and (4) weighting and scoring the SNP detection result obtained in the step (3) by combining risk OR values of different sites. Homozygous wild-type were normalized to 0, and heterozygous and homozygous mutant assignments were as follows in table 3: (reference https:// www.reddit.com/r/SNPedia)

TABLE 3 assignment Table

Site number	Name of Gene	rs number	Heterozygote type	Homozygous mutant	Homozygous wild type
						1	F2	rs1799963	2.8	7	0
2	F5	rs6025	4.1	11.4	0
						3	IL10	rs1800871	-0.5	-0.5	0
4	PAI-1	rs1799768	4	6.4	0
						5	MTHFR	rs1801131	2.2	2.8	0
6	MTHFR	rs1801133	2.1	2.5	0
						7	MTRR	rs1801394		0	1.4	0
8	PROC	rs757583846	5	9	0
						9	VEGFA	rs1570360	3	3	0
10	PROS	rs121918474	5	5	0
						11	SERPINC1	rs121909551	3.5	5	0
12	THBD	rs398122807	2.1	4	0

And 6: taking the 12 sites of the sample of fig. 2 as an example, rs1570360 of VEGFA is homozygous mutant, rs1801131 of MTHFR, rs6025 of F5, rs1801394 of MTRR is heterozygous, and the others are wild type, and according to the settings of table 3, the sample is assigned as table 4:

TABLE 4

Site number	Name of Gene	rs number	Score value
				1	F2	rs1799963		0
2	F5	rs6025	4.1
				3	IL10	rs1800871		0
4	PAI-1	rs1799768	0
				5	MTHFR	rs1801131	2.2
6	MTHFR	rs1801133						0
				7	MTRR	rs1801394			0
8	PROC	rs757583846						0
				9	VEGFA	rs1570360	3
10	PROS	rs121918474	0
				11	SERPINC1	rs121909551		0
12	THBD	rs398122807							0

And 7: the RSA risk value for this sample is calculated according to the following formula:

the calculation formula is as follows:

＝2×{2.8×rs1799963+3×rs6025+(3+0.4×rs757583846+0.5×rs1570360+0.3×rs12191847+0.35×rs12190955+0.5×rs398122807)×(1+rs1799768)+[(1+rs1801131)×(1+rs1801133)+1]^2 ^rs1801394 }×3 ^rs1800871

taking the sample assignments of table 4 as an example, the substitution formula is:

2×{2.8×0+3×4.1+(3+0.4×0+0.5×3+0.3×0+0.35×0+0.5×0)×(1+0)+[(1+2.2)×(1+0)+1]^2 ⁰ }×3 ⁰ ＝42。

and (4) judging a result standard:

when the RSA risk value is more than or equal to 65, the risk of thrombus is high;

when the RSA risk value is less than or equal to 55, the risk of thrombus is low;

when the RSA risk value is in the interval of [55,65], the risk is in thrombus;

taking 42 obtained from the calculation formula of the sample in Table 4 as an example, the sample is low risk thrombus according to the judgment standard.

The clinician needs to judge the risk of the recurrent abortion of the sample according to the high risk condition of the thrombus, the pregnancy week, the current medicine taking and other comprehensive factors.

In order to verify the effectiveness of the invention, several groups of the invention performed the following verification experiments:

experimental case 1:

the cooperative hospital of the applicant is responsible for collecting and providing 50 clinically and pathologically diagnosed thrombosis-associated recurrent pregnant women with abortion and 50 definite recurrent pregnant women with abortion and normal fertility; after DNA extraction, the primers designed in step 2 were used to perform the operation according to step 4, and the following 100 samples were obtained for the detection results of 12 SNP sites, which are shown in Table 5 below:

table 5: results of 12 SNP detections in 50 patients compared with 50 normal controls

Description of the drawings: "4G/5G" represents a heterozygous type, "4G/4G" represents a homozygous mutant type, and "5G/5G" represents a homozygous wild type.

The results obtained in table 5 are put into the assignment table in table 3 to obtain the assignment of the patient to 12 genes, and then put into the calculation formula in step 7 to calculate the RSA score, and the risk is judged according to the score criteria, with the results as in table 6-1 below:

TABLE 6-1

According to Table 6-1, the statistical results are shown in Table 6-2 below in combination with the gold standard;

TABLE 6-2

		High risk	Middle risk	Low risk
					Gold standard (pathology) positive	50	43	2	5
Negative gold standard	50	5	5	40
					Total of	100	48	7	45

Based on the above statistical results, the statistical results of tables 6-3 were further obtained. The calculation was carried out, and the results obtained were: according to the principle of the 2-point method, if the intermediate risk is classified into a risk range, the specificity is 88.8%, the sensitivity is 81.8%, and the accuracy is 85%, and if the intermediate risk is classified into a risk-free range, the specificity is 86.5%, the sensitivity is 89.6%, and the accuracy is 88%.

Tables 6 to 3

Comparative example 1

The other steps are the same as those of the experimental case 1, but the final judgment of the risk standard is different, and if the conventional heterozygous (4G/5G) and homozygous 4G/4G of PAI-1 are used as the medium-high risk in the comparative case 1, the following consistency results are obtained.

That is, conventional PAI-1 is determined to be at high risk when "PAI-1" in Table 5 is 4G/4G, is determined to be at medium risk when 4G/5G, and is determined to be at low risk when "PAI-1" is 5G/5G.

The results obtained are shown in Table 7-1 below.

TABLE 7-1

According to Table 7-1, the risk statistics obtained are given in Table 7-2 below;

TABLE 7-2

		High risk	Middle risk	Low risk
					Gold standard (pathology) positive	50	21	21	8
Negative standard gold (normal person)	50	12	32	6
					In total	100	33	53	14

Then: further statistics are given based on the above statistics to obtain the results of tables 7-3, which are: if the medium risk is classified as risky, specificity 42.8%, sensitivity 48.8%, accuracy 48%, if the medium risk is classified as low risk specificity 56.7%, sensitivity 63.6%, accuracy 59%.

7-3

The results show that the conventional PAI-1 heterozygous (4G/5G) and homozygous 4G/4G are poorer in risk, specificity, sensitivity and accuracy than the algorithm of the invention.

Comparative example 2

Other experimental steps are the same as the experimental case 1, and the homozygous wild type is judged to be low risk, the heterozygous type is medium risk, the homozygous mutant type is high risk according to the common MTHFR C677T on the market at present according to the later judgment standard, and the medium risk is also included in the high risk.

That is, "C677T of MTHFR" is determined to be at high risk when "rs 1801133" in table 5 is a homozygous mutant type, "is determined to be at intermediate risk when" rs1801133 "is a heterozygous type," and is determined to be at low risk when "rs 1801133" is a homozygous wild type.

The results obtained are shown in Table 8-1 below.

TABLE 8-1

According to the table 8-1, the obtained results are further statistically generated to the following table 8-2;

TABLE 8-2

		High risk	Middle risk	Low risk
					Gold standard (pathology) positive	50	8	24	18
Negative standard of gold	50	12	25	13
					Total of	100	20	49	31

Further statistics are given from the results obtained above to generate tables 8-3, which are calculated as follows: if the intermediate risk is classified as risky, the specificity is 41.9%, the sensitivity is 42.4%, and the accuracy is 45%. If the medium risk is assigned to low risk, the specificity is 47.5%, the sensitivity is 40%, and the accuracy is 46%.

Tables 8 to 3

A comparison of the three examples is shown below:

TABLE 9

The result shows that the method is more accurate than the traditional single-factor prediction method in specificity, sensitivity or accuracy through the joint detection of a plurality of indexes and the regression prediction risk calculation formula.

Comparative example 3

The calculation formula and the threshold judgment of the invention are both learned by a machine, various test simulations are carried out among different thresholds, and a state of relatively balanced specificity and sensitivity is achieved, other steps are the same as the embodiment 1, if the judgment threshold in the embodiment 1 is adjusted to be 60, and the medium risk is [55,60] and other invariants, the result of the embodiment 1 is as the following table 10-1:

TABLE 10-1

		High risk	Middle risk	Low risk
					Gold standard (pathology) positive	50	45	0	5
Negative standard of gold	50	9	1	40
					Total of	100	54	1	45

The comparison results are shown in Table 10-2 below:

table 10-2:

the results show differences in specificity, sensitivity and accuracy, but still maintain a high accuracy.

Finally, it is also noted that the above-mentioned lists merely illustrate a few specific embodiments of the invention. It is obvious that the invention is not limited to the above embodiments, but that many variations are possible. All modifications which can be derived or suggested by the person skilled in the art from the present disclosure are to be considered within the scope of the present invention.

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<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 17

aagctgcgtg atgatgaaat cga 23

<210> 18

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 18

ctcgccttga acaggtggag g 21

<210> 19

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 19

gcaaaggcca tcgcagaaga aata 24

<210> 20

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 20

aaaggccatc gcagaagaaa tg 22

<210> 21

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 21

cacttcccaa ccaaaattct tcaaagc 27

<210> 22

<211> 20

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 22

ccgtcacagc agcctggagc 20

<210> 23

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 23

ctccgtcaca gcagcctgga gt 22

<210> 24

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 24

gtcatccaca ttttggaaaa tttcctt 27

<210> 25

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 25

ggacaggcga gcctcagccc t 21

<210> 26

<211> 19

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 26

acaggcgagc ctcagcccc 19

<210> 27

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 27

gcttcactga gcgtccgcag ag 22

<210> 28

<211> 28

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 28

tcctgctctt acctttacaa tctttctt 28

<210> 29

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 29

tccctcaaat ataaatggag gttgc 25

<210> 30

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 30

tccctcaaat ataaatggag gttgc 25

<210> 31

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 31

gagggctcag aacagaagat ccc 23

<210> 32

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 32

atgagggctc agaacagaag atcct 25

<210> 33

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 33

tctgccaggt gctgatagaa agtg 24

<210> 34

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 34

gtctggttgc aaaacatctg gcac 24

<210> 35

<211> 26

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 35

cagtctggtt gcaaaacatc tggcaa 26

<210> 36

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 36

agcccctgaa ccaaactagc tacct 25

Claims (7)

1. A gene at risk of recurrent abortion caused by thrombosis, characterized in that: according to the weight of the gene, the set gene name, the corresponding locus and the rs number are as follows:

name of Gene Site of the body rs number F2 G20210A rs1799963 F5 G1691A rs6025 IL10 c.-149+2211A>G rs1800871 PAI-1 -675 4G/5G rs1799768 MTHFR A1298C rs1801131 MTHFR C677T rs1801133 MTRR A66G rs1801394 PROC C169T rs757583846 VEGFA -1154G/A rs1570360 PROS A586G rs121918474 SERPINC1 C218T rs121909551 THBD G1209T rs398122807

。

2. The gene for risk of recurrent abortion caused by thrombosis according to claim 1, wherein: primers corresponding to 12 loci of 11 genes were as follows:

wt represents wild type, mt represents mutant type.

3. An evaluation model of a gene for risk of recurrent abortion caused by thrombosis, characterized in that: use of the gene according to claim 1 or 2, wherein the assignment table is as follows:

name of Gene rs number Heterozygote type Homozygous mutant Homozygous wild type F2 rs1799963 2.8 7 0 F5 rs6025 4.1 11.4 0 IL10 rs1800871 -0.5 -0.5 0 PAI-1 rs1799768 4 6.4 0 MTHFR rs1801131 2.2 2.8 0 MTHFR rs1801133 2.1 2.5 0 MTRR rs1801394 0 1.4 0 PROC rs757583846 5 9 0 VEGFA rs1570360 3 3 0 PROS rs121918474 5 5 0 SERPINC1 rs121909551 3.5 5 0 THBD rs398122807 2.1 4 0

The calculation formula for the RSA risk value is:

2×{2.8×rs1799963+3×rs6025+(3+rs1570360+rs121918474+rs121909551+rs398122807)×(1+rs1799768)+[(1+rs1801131)×(1+rs1801133)+1]^(2 ^rs1801394 )+2×rs757583846}×3 ^rs1800871 ；

the judgment threshold value is 60-65.

4. The model for evaluating a gene for risk of recurrent spontaneous abortion caused by thrombosis as set forth in claim 3, wherein:

when the judgment threshold is 65, the corresponding result judgment criteria are:

when the RSA risk value is more than or equal to 65, the risk of thrombus is high;

when the RSA risk value is less than or equal to 55, the risk of thrombus is low;

an RSA risk value within the [55,65] interval is the risk in thrombosis.

5. The method of using the model for evaluating a gene at risk of recurrent spontaneous abortion as claimed in claim 3 or 4, comprising the steps of:

carrying out PCR amplification on a sample to be detected to obtain types corresponding to 12 bit points of 11 genes of the sample to be detected;

obtaining an RSA risk value according to an assignment table and a calculation formula of the RSA risk value;

and finally, carrying out corresponding risk judgment.

6. The method of using the gene for assessing the risk of recurrent spontaneous abortion caused by thrombosis according to claim 5, wherein the gene comprises:

extracting the genome DNA of a sample to be detected by using a DNA extraction kit, and performing multiple PCR amplification by using a PCR primer;

reaction system:

the wild type amplification system is as follows: 2 XPCR amplification premix solution 12.5ul, wild type upstream primer mixture 2ul, downstream primer mixture 2ul, DNA template 100ng-500ng, make up to 25ul with water without ribozyme;

the mutant amplification system is as follows: 2 XPCR amplification premix solution is 12.5ul, mutant upstream primer mixture is 2ul, downstream primer mixture is 2ul, DNA template is 100ng-500ng, water without ribozyme is used for complementing to 25 ul;

the 2 XPCR amplification premix was 25mM Tris-HCl (pH8.0),125mM KCl,6.5mM Mg ²⁺ 0.6mM dNTP; the balance of deionized water;

PCR amplification procedure: 95 ℃ for 2 min- > (94 ℃ for 30 sec; 60 ℃ for 60 sec; 72 ℃ for 60 sec; 30 cycles) - >72 ℃ for 10 min- >4 ℃.

7. A method for acquiring disease potential associated genes based on multi-site information fusion is characterized in that: a gene for risk of recurrent abortion caused by thrombosis, comprising the steps of:

step 1: based on non-relevant literature knowledge, inquiring the genetic locus of the recurrent abortion related to the easy thrombosis reported at home and abroad at present, wherein the frequency of the genetic locus exceeds one in a thousand in Chinese population;

thereby setting corresponding gene loci;

step 2: designing and synthesizing primers for the set gene loci, and detecting;

and step 3: through clinical tests, detecting pregnant women with recurrent abortion related to the known thrombosis susceptibility and people who are clinically diagnosed with no recurrent abortion by using the primers in the step 2;

and 4, step 4: carrying out normalization processing on the result of the step 3, then utilizing computer tools such as biological information and the like to construct a decision tree, and obtaining a calculation model, namely a corresponding calculation formula;

and 5: and (4) setting a threshold value for the sample, and evaluating the sensitivity, specificity, accuracy and the like under the threshold value.

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