JP2007222134A - Method for detecting genetic risk of hypertension - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a gene detection method, etc., to acquire a material for judging the genetic risk of hypertension. <P>SOLUTION: The method for detecting risk of hypertension comprises the use of 14 gene polymorphisms and gender difference on specific gene polymorphisms and established factors (age, sex, smoking habit and BMI) as evaluation factors, the calculation of onset risk by multiplying odds ratio to each evaluation factor, the classification of the onset risks into multiple groups according to the average and the dispersion or percent section, and the detection of the onset risk on each group. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a method for detecting a genetic risk of hypertension and the like.

  The success of the Human Genome Project is bringing significant benefits to clinical medicine, including the identification of genes that affect common diseases. One of the methods for identifying such a gene is a method of searching for an appropriately selected gene polymorphism while paying attention to a specific disease. This is because such a gene is known to encode a protein involved in the onset and progression of the disease and exists in a chromosomal region linked to the disease.

  Hypertension is a disease in which many factors are involved in a complex manner, and is thought to develop due to the interaction of an individual's genetic characteristics and many environmental factors (Non-patent document 1: For related documents, the end of the description) It is shown together in the following). Because hypertension is a major risk factor for coronary artery disease, cerebrovascular disorder, and severe kidney damage, preventing hypertension is medically and socially important. One of the methods for selecting an optimal treatment method for preventing hypertension according to an individual is to identify genes involved in the disease.

  Genetic linkage analysis (Non-Patent Documents 2 to 6) and candidate gene analysis (Non-Patent Documents 2 and 7 to 10) suggest that some candidate genes are involved in hypertension. However, the genetic cause of hypertension remains unclear.

  This invention is made | formed in view of said situation, The objective is to provide the gene detection method etc. for obtaining one material for judging the genetic risk about hypertension.

  The present inventor conducted a large-scale study on 150 polymorphisms of 128 genes in 4853 Japanese people regarding hypertension. The purpose of this study is to identify genetic polymorphisms involved in hypertension, and to give useful information to a person to avoid hypertension based on this finding.

  As a result of the above analysis, the risk detection method for hypertension according to the first invention is ITGA2 1648A → G, GCK −30G → A, PTGIS 1117C → A, SAH A → G (−7 from exon 13), -1989T → G of ESR1, 242C → T of CYBA, -1306C → T of MMP2, 3857G → A of ABCC8, -863C → A of TNF, 2136C → T of THBD, -603A → G of F3, -588C of GCLM → T, NOS3 −786T → C, PAI1 A → G (Tyr243Cys) at least one or more gene polymorphisms and sex difference were used as evaluation factors, and the odds ratio of each evaluation factor was multiplied The risk of onset is calculated, three or more groups are created according to the mean, variance, or percentage category, and the risk of onset is determined for each group. And detecting the.

  At this time, as a variance used when forming a group, a statistical variance value, a standard deviation value (SD), a percentage division, or the like can be used. Note that the gene polymorphism is not necessarily limited to the above 14 but any 1 to 13 of these 14 polymorphisms, or other 14 polymorphisms shown in the present specification. It is also possible to carry out with 15 or more including.

  In this specification, the description method of a polymorphism is as follows. In principle, each gene is described in the order of “position where polymorphism occurs, base registered in database (A: adenine, G: guanine, C: cytosine, T: thymine) → polymorphic base”. . For example, “1648A → G of ITGA2” means a polymorphism in which A at position 1648 is G for the ITGA2 gene. In addition, the polymorphism for which no location is designated can be easily understood from the dbSNP access numbers described in Tables 1 to 5. Note that the polymorphism retrieved from the dbSNP access number may not match the polymorphism described in Tables 1 to 5. In that case, it means that the reading direction is different. For example, even if it is read in the forward strand and recorded as an A / G polymorphism, it will be a T / C polymorphism if it is read in the reverse strand. Thus, when the polymorphism described in the dbSNP database is not the same as the polymorphism in the table, it means that the reading direction is reversed.

  In general, it is known that polymorphisms have different types and frequencies for different groups (for example, Japanese group, Western group, etc.). For this reason, even if the polymorphism has been pointed out to be related to hypertension in a non-Japanese population, such a relationship is not necessarily observed in the Japanese population. For this reason, conventional reports do not necessarily support the association between polymorphisms and hypertension in Japanese if the country or disease is different. However, the same tendency is likely to be observed in groups close to the Japanese group, such as Korean and Chinese groups.

  Further, the genetic risk detection method for hypertension according to the second invention includes ITGA2 1648A → G, GCK −30G → A, PTGIS 1117C → A, SAH A → G (−7 from exon 13), ESR1. -1989T → G, 242C → T of CYBA, -1306C → T of MMP2, 3857G → A of ABCC8, -863C → A of TNF, 2136C → T of THBD, -603A → G of F3, -588C of GCLM → It is characterized by detecting at least one gene polymorphism of T, NOS3 −786T → C, and PAI1 A → G (Tyr243Cys).

  According to the present invention, a detection method and the like for determining a genetic risk and an onset risk for hypertension are provided. By using this invention, it becomes possible to prevent hypertension, and as a result, by reducing the occurrence of myocardial infarction, cerebrovascular disorder, renal failure, etc. caused by high blood pressure, the healthy life extension of the elderly, QOL improvement, It can greatly contribute to medical and social issues such as prevention of stickiness and reduction of medical expenses in the future.

  Next, embodiments of the present invention will be described with reference to the drawings. However, the technical scope of the present invention is not limited by these embodiments, and various forms can be made without changing the gist of the invention. Can be implemented. Further, the technical scope of the present invention extends to an equivalent range.

<Test method>
Study subjects The study subjects were 4853 Japanese (2688 men, 2165 women) Japanese. They are located in one of six research facilities (Gifu Prefectural Gifu Hospital, Gifu Prefectural Tajimi Hospital, Gifu Prefectural Gero Onsen Hospital, Hirosaki University Hospital, Reimeikyo Rehabilitation Hospital, and Yokohama General Hospital) from October 2002 to March 2005. He had been hospitalized or hospitalized by the month. 2818 hypertensive patients (1677 men, 1141 women) who meet the criteria for systolic blood pressure 140 mmHg or higher or diastolic blood pressure 90 mmHg or higher (or both) or take antihypertensive drugs It was a person who had been. Those with secondary hypertension due to valvular heart disease, congenital malformations of the heart or blood vessels, kidney or endocrine disease were excluded from the study.

  2035 controls (1011 males and 1024 females) were those who visited the hospital for annual health examinations. They had normal blood pressure (systolic blood pressure <140 mmHg and diastolic blood pressure <90 mmHg), no history of hypertension, and were not taking antihypertensive drugs. The blood pressure was measured at least twice in a state of sitting for 10 minutes or more and resting. The blood pressure was measured by a skilled doctor in accordance with American Heart Association guidelines (Non-patent Document 11). The research protocol was approved by the Mie University School of Medicine, Hirosaki University School of Medicine, Gifu International Institute for Biotechnology, and the ethics committee of participating hospitals in accordance with the Declaration of Helsinki. Written informed consent was obtained for each participant.

Selection of polymorphisms Through the use of public databases and the inventor's intensive studies, the biology of blood vessels, the biology of platelets and leukocytes, the cascade of coagulation and fibrinolysis, neurological factors, lipid / glucose / homocysteine metabolism, Based on a comprehensive overview of other metabolic factors, 128 candidate genes that could be associated with hypertension were selected. The inventor selected 150 polymorphisms for these 128 genes. Many of these polymorphisms are located in many promoter regions, exons, intron splicing donor or acceptor sites, and polymorphisms may alter the function or expression of the encoded protein. Thought to get. These polymorphisms are shown in Tables 1-5. In the table, the locus (Locus), gene name (Gene), simple description (Symbol), polymorphism (Polymorphism), and polymorphism database registration number (dbSNP) are shown in order from the left column. In addition, when there was no polymorphism database registration number, the number registered in NCBI gene bank was shown.

Detection method of gene polymorphism 7 mL of venous blood was collected in a tube containing 50 mmol / L EDTA (disodium salt), and genomic DNA was separated using a kit (Genomics). The 150 polymorphic genotypes were determined by a method using PCR and sequence-specific oligonucleotide probes in combination with Suspension Array Technology (SAT: Luminex 100) (G & G Science Inc.). The primer, probe, and other conditions are shown in Table 6 below. In the table, from left to right, the gene symbol (Gene Symbol), polymorphism (Polymorphism), sense primer (Sense primer), antisense primer (Antisense primer), probe 1 (Probe 1), probe 2 (Probe 2), annealing Temperature (Annealing) and number of cycles (Cycles) are shown. The detailed method was based on the previously reported one (Non-Patent Document 12) and the amplification conditions were changed appropriately. In addition, description was abbreviate | omitted about the conditions for detecting the polymorphism by which the relationship with hypertension was not recognized.

The details of the PCR-SSOP-Luminex method are as described in Non-Patent Document 12. Below, the outline | summary of this method is demonstrated.
FIG. 1 shows the microstructure and characteristics of microbeads detected by Luminex 100 flow cytometry. Microbeads (symbol (A) in the figure) have a diameter of about 5.5 μm and are made of polystyrene. A probe that recognizes a specific base sequence is bound to the bead surface. One type of probe is bound to each bead. By changing the ratio of the red dye and the infrared dye to this microbead, the identification of each bead can be performed in a state where a maximum of 100 kinds are mixed, as indicated by the symbol (B) in the figure. It can be done. Microbeads with multiple types of probes (however, only one type of probe for each microbead) were mixed at an appropriate ratio to prepare a bead mix of 100 beads / μL (reference in the figure). (C)).

In FIG. 2, the outline | summary of the procedure of PCR-SSOP-Luminex method was shown.
<Amplification>
In the PCR reaction for amplifying the target DNA, a primer labeled with biotin at the 5 'end was used. A 1 × PCR solution containing 1.5 mM magnesium chloride (50 mM KCl, 10 mM Tris-HCl, pH 8.3), 2% DMSO, 0.2 mM dNTPs, and 0.1 μM to 10 μM primer set were mixed, and Taq DNA polymerase (50 U / mL) and 50 ng to 100 ng of genomic DNA were added to make 25 μL. The PCR reaction was treated at 95 ° C. for 10 minutes, followed by denaturation at 94 ° C. for 20 seconds, annealing at 60 ° C. for 30 seconds, and extension at 72 ° C. for 30 seconds, and this was repeated 50 cycles. A GeneAmp9700 thermal cycler (Applied Biosystems) was used as the instrument.

<Hybridization>
The amplified DNA was denatured and then hybridized with the bead mix. In each well of a 96-well plate, 5 μL of amplified PCR solution, 5 μL of bead mix, and 40 μL of hybridization buffer (3.75 M TMAC, 62.5 mM TB (pH 8.0), 0.5 mM) EDTA, 0.125% N-lauroylsarcosine) was added to a total volume of 50 μL. The 96-well plate to which this mixed solution had been added was subjected to denaturation at 95 ° C. for 2 minutes and hybridization at 52 ° C. for 30 minutes (using a GeneAmp 9700 thermal cycler).
FIG. 2 shows a state in which only beads (1) having a probe that recognizes amplified DNA bind to DNA.

<Streptavidin-phycoerythrin reaction (SA-PE Reaction)>
Next, the bead mix-DNA was reacted with SA-PE. After the hybridization reaction, 100 μL of PBS-Tween (1 × PBS (pH 7.5), 0.01% Tween-20) was added to each well, centrifuged at 1000 × g for 5 minutes, and the supernatant was removed. The microbeads were washed. To each microbead remaining in each well, 70 μL of SA-PE solution (commercially available product (G & G Science Co., Ltd.) diluted 100-fold with PBS-Tween) was added and mixed, and then at 52 ° C. for 15 minutes. (A GeneAmp9700 thermal cycler was used.)
FIG. 2 shows that biotinylated DNA is bound only to the probe of the bead (1), and thus SA-PE is bound to the biotin.

<Measurement>
Next, the sample after the reaction used Luminex 100 to identify the bead type and determine whether PE is bound to the bead. The measurement was performed using two types of lasers, the type of beads was identified by a 635 nm laser, and PE fluorescence was quantified using a 532 nm laser. For the DNA bound to the oligo beads, at least 50 beads were measured per measurement, and the quantified median fluorescence intensity (MFI) of PE was used.
In FIG. 2, since each bead (1) to (3) was identified and PE was measured only on the bead (1), the DNA recognized by the probe bound to the bead (1) was amplified. The situation is shown.

Statistical analysis Clinical data were compared between the hypertension patient group and the control group by the unpaired Student t test. Qualitative data were compared by chi-square test. Allele frequencies were estimated by the gene count method, and the chi-square test was used to determine if the Hardy-Weinberg equilibrium was met. The genotype distribution in each autosome was compared between hypertensive patients and controls by chi-square test (3 × 2). For gene polymorphisms on the X chromosome, allele frequencies were compared by chi-square test (2 × 2).

  Polymorphisms associated with hypertension (P <0.06) were analyzed by multinomial logistic regression analysis with confounding factors. At this time, regarding confounding factors, age (age), sex difference (sex: female = 0, male = 1), body mass indes (BMI), smoking status (smoking: non-smoker = 0, smoker = 1) and each genotype was an independent variable, and hypertension was a dependent variable. Each genotype was evaluated according to dominant, recessive, and two addition (addition 1 and 2) genetic models, and P values, odds ratios, and 95% confidence intervals were calculated.

  Each genetic model consists of two groups. The dominant model is “mutant homozygous and heterozygous binding group” vs. “wild type homozygous”, the recessive model is “mutant homozygous” vs. “wild type homozygous and heterozygous” The “body binding group”, the addition 1 model is “heterozygote” vs. “wild type homozygote”, and the addition 2 model is “mutant homozygote” vs. “wild type homozygote”. To analyze the combined genotype, a multinomial logistic regression analysis was performed with age, gender, body mass index, smoking status, and combination genotype as independent variables and hypertension as a dependent variable. Each genotype used a dominant or recessive model based on statistical dominance. Each combined genotype was also compared to the combined genotype that gave the highest genetic risk for hypertension. Furthermore, in order to confirm the effect of genotype or other confounding factors on hypertension, analysis was performed by the stepwise variable increment method. The reference level for inclusion in the model was 0.25, and the reference level for exclusion from the model was 0.1.

  In obtaining hypertension and genotype multiple comparison results, strict criteria of statistical significance (P <0.01) were adopted to avoid type I errors. For other clinical background data, a risk rate of less than 5% (P <0.05) was considered statistically significant. Statistical significance was tested by a two-sided test. Statistical analysis was performed with JMP software version 5.1 (SAS Institute).

<Test results>
Table 7 shows the basic data for the 4853 subjects. The features (Characteristics), hypertension patient group (hypertension), and control group (Controls) are shown in order from the left column. In addition, in the feature column, the number of persons (No. of subjects), age (Age), gender (male / female), body mass index, current or past Smoking rates (Current or former smoker), Diabetes mellitus, Hypercholesterolemia, Systolic blood pressure, and Diastolic blood pressure.

The age and body mass index are expressed as mean ± SD. Regarding the smoking rate, smoking was defined as the case where 10 or more cigarettes were smoked per day. As for diabetes, the fasting blood glucose level was 6.93 mmol / L (126 mg / dL) or more, hemoglobin A1c was 6.5% or more, or a person who was taking a therapeutic drug for diabetes. For high cholesterol, the total serum cholesterol was 5.72 mmol / L (220 mg / dL) or higher, or a person taking a lipid-lowering drug. In the table, “*” means that a significant difference of P <0.001 was observed between the control group and the control group.
In the hypertensive patient group, age, the proportion of men, BMI, and the prevalence of diabetes / hypercholesterolemia were higher than those in the control group.

<High blood pressure risk diagnosis system>
Table 8 provides details on the hypertension risk diagnostic system. In the table, the factor (Variable), P value (P value), and odds ratio (95% confidence interval) (OR (95% CI)) are shown in order from the left column. The bottom row shows the total risk multiplied by the odds ratio of the conventional risk factors and the genetic risk factors found in this study.

  The genetic polymorphism group whose risk factor was less than 0.05 (P <0.05) and the age, sex, smoking, and BMI as independent factors (confounding factors) and hypertension as a dependent factor. Logistic regression analysis was performed. Therefore, these factors are independent, and the overall risk of developing hypertension can be predicted by multiplying the odds ratio. As a result of multinomial logistic regression analysis, sex (higher risk for men) was related to the development of hypertension as a conventional risk factor. In addition, as a genetic factor, ITGA2, GCK, PTGIS, SAH, ESR1, CYBA, MMP2, ABCC8, TNF, THBD, F3, GCLM, NOS3, and PAI1 gene polymorphisms were associated with the development of hypertension. . Conventional risk factors have a minimum odds ratio of 1.00 and a maximum odds ratio of 1.53, and genetic factors have a minimum odds ratio of 0.04 and a maximum odds ratio of 9.23. Therefore, when the conventional risk factors and the genetic factors found this time were combined, the minimum odds ratio was 0.04 and the maximum odds ratio was 14.12, showing a difference of 353 times.

  The clinical significance of this research result is described below. At the hospital, clinic or health check-up center, the applicant will be tested for the existing risk factors and the current genetic factors to predict the risk of developing hypertension. The degree of risk is divided into three or more levels (for example, five levels) from the distribution of the conventional product of risk factors and odds ratios of all genetic factors. For example, an average ± 1SD range is an average risk group, an average + 1SD to an average + 2SD is a slightly high risk group, and an average + 2SD is a high risk group. Moreover, let average -1SD-average -2SD be a slightly low-risk group, and let a thing smaller than average -2SD be a low-risk group. Although no significant association was found in this embodiment, since smoking, obesity, and aging are generally considered as risk factors for hypertension, these factors can be taken into account.

  In fact, in this study, the distribution of risk values was 14.3% in the hypertension group and 3.7% in the control group in the high-risk group, and 33.1% in the hypertension group in the high-risk group and the control group. In the 15.7% group, the average risk group is 49.2% in the hypertension group and 65.8% in the control group, the group in the low risk group is 3.4% in the hypertension group and 14.4% in the control group In the low group, the hypertension group was 0% and the control group was 0.4%. As another method, the control group is divided into 5%, 20%, 50%, 20%, and 5% in descending order of risk value, and the group with the highest risk value of 5% 20% group is a slightly higher risk group, the next 50% group is an average risk group, the next 20% group is a slightly lower risk group, and the 5% group with the lowest risk value is a lower risk group A group. In fact, the distribution of the hypertension group in this study was 18.4% for the high-risk group (5.0% for the control group), 38.3% for the group with slightly higher risk (20.0% for the control group), The average risk group is 35.8% (control group is 50.0%), the low risk group is 6.6% (control group is 20.0%), and the low risk group is 0.8% ( The control group was 5.0%).

  The results will be counseled, including the judgment of qualified personnel such as doctors, and will improve lifestyle habits (quite smoking, diet, ie salt restriction, exercise therapy Actively promote primary prevention of hypertension by reducing obesity, stress, and sleep. Lifestyles and obesity such as smoking, excessive salt intake, lack of exercise, overstress, and lack of sleep are generally considered to cause high blood pressure, so the genetic risk of developing hypertension is predicted to be higher than average. If so, explain to clients to reduce their risk of developing hypertension by improving their lifestyle habits. It is especially effective for people with a family history of high blood pressure, myocardial infarction, or cerebrovascular disorder. This system enables tailor-made prevention of hypertension, and as a result, by reducing the incidence of myocardial infarction, cerebrovascular disorder, renal failure, etc. caused by high blood pressure, the healthy life extension of elderly people, QOL improvement, ne It can greatly contribute medically and socially, such as preventing burnout and reducing medical costs in the future.

<Statistical analysis>
Next, the results of statistical analysis that led to the development of the risk judgment system will be described.
By chi-square test, 17 gene polymorphisms showed an association with hypertension (P <0.06). Details are shown in Table 9. In the table, gene notation (Gene symbol), polymorphism (Polymorphism), and risk factor (P) are shown in order from the left column.

These polymorphisms were analyzed in more detail for their association with hypertension. A multinomial logistic regression analysis corrected for age, gender difference, body mass index, and smoking rate revealed that the 1648A → G polymorphism of the integrin α2 gene (ITGA2) was found in the recessive model and the glucokinase gene (GCK) in the dominant model. -30G → A polymorphism of A), the A → G polymorphism of the hypertension-associated SA rat homolog of gene (SAH), and the prostaglandin I ₂ synthase gene (PTGIS) The 1117C → A polymorphism was significantly (P <0.01) associated with the prevalence of hypertension. At this time, the 1648G allele of ITGA2 was a risk factor for hypertension, whereas the −30A allele of GCK, the G allele of SAH, and the 1117A allele of PTGIS were protective against hypertension. It was working. Details are shown in Table 10. In the table, data with a risk factor of less than 0.01 (P <0.01) are shown in bold.

  In the table, in order from the left column, genetic notation (Gene symbol), polymorphism (Polymorphism), dominant model (Dominant) risk rate (P), odds ratio (OR), 95% confidence interval (95% CI), Risk factor (P), odds ratio (OR), 95% confidence interval (95% CI) in recessive model (Recessive), risk factor (P), odds ratio (OR), 95% in additive 1 model (Additive 1) The risk interval (P), odds ratio (OR), and 95% confidence interval (95% CI) for the confidence interval (95% CI) and the additive 2 model (Additive 2) are shown.

Next, the effects of 14 polymorphism genotypes, age, sex, and body mass index on hypertension were analyzed by the stepwise variable increment method. The results are shown in Table 11. In the table, the factor (Variable), P value (P value), and contribution rate (R ² ) are shown in order from the left column.

In descending order of statistical significance, age, gender, body mass index, ITGA2 genotype (recessive model), GCK genotype (dominant model), and PTGIS genotype (dominant model) are very highly significant (P <0.01), each factor was found to affect hypertension independently.
Next, the odds ratio, 95% confidence interval, and P value were calculated for the combined genotypes of the three polymorphisms (ITGA2 1648A → G, GCK −30G → A, and PTGIS 1117C → A). The results are shown in Table 12.

In the table, in order from the left, ITGA2 1648A → G genotype, GCK −30G → A genotype, PTGIS 1117C → A genotype, number ratio of hypertensive patient group / control group in each combination genotype, Odds ratio (95% confidence interval) and P value are shown. Multinomial logistic regression analysis was performed with correction for age, gender difference, body mass index, and smoking rate. By analyzing the combined genotypes of the three polymorphisms, the combined genotype of GG for ITGA2, GG for GCK, and CC for PTGIS is 1.00, and the minimum odds ratio of 0.47 is AA or AG for ITGA2. , GCK for GA or AA and PTGIS for CC combined genotypes.
In addition, the distribution of 4 polymorphic genotypes with high involvement in hypertension (P <0.01) was compared between the hypertension patient group and the control group. The results are shown in Table 13.

  In the table, in order from the left column, gene notation (Gene symbol), polymorphism (Polymorphism), frequency of each genotype in hypertension group (Hypertension) (%), frequency of each genotype in control group (Controls) (% ). For example, in the ITGA2 1648A → G polymorphism, the AA genotype is 0.1%, the AG genotype is 7.4%, and the GG genotype is 92.6% in the hypertension group. The AA genotype was 0.3%, the AG genotype was 9.4%, and the GG genotype was 90.2. The genotype frequencies for these four polymorphisms were in Hardy-Weinberg equilibrium in both the hypertension group and the control group.

<Discussion>
The present inventor conducted research on the relationship between hypertension and 150 polymorphisms out of 128 candidate genes estimated to be involved in hypertension. A large study of 4853 showed that ITGA2 1648A → G polymorphism, GCK −30G → A polymorphism, and PTGIS 1117C → A polymorphism were significantly associated with hypertension in the Japanese population. I found out. As a result of analyzing the combined genotype of these three polymorphisms, 0.47 was obtained as the predisposition to hypertension at the lowest odds ratio.

The integrin α2 chain (ITGA2, platelet glycoprotein Ia) is a major receptor component for collagen (α2β1 integrin). When ITGA2 is deficient, it becomes a hemorrhagic constitution. On the other hand, when the α2β1 integrin concentration is high, the binding between platelets and type I collagen is promoted under conditions of high shearing force. The ITGA2 1648A → G (Lys505Glu) polymorphism is involved in the immunogenic Br ^{a / b} (HPA-5a / b) polymorphism (Non-patent Document 13). Since the Lys505Glu polymorphism is located in the cation binding domain of ITGA2, it may influence the interaction between α2β1 integrin and ligand.

  The ITGA2 1648A → G (Lys505Glu) polymorphism has been shown to be associated with coronary artery disease in the low-risk group, and it has been reported that the frequency of the GG genotype is high in the patient group (Non-patent Document 14). According to our study, this polymorphism is associated with hypertension, and the GG genotype was a risk factor for hypertension. Although the molecular mechanism is unknown, this study is the first finding that ITGA2 polymorphism 1648A → G (Lys505Glu) is involved in hypertension. It is known that platelet function is activated in hypertensive patients. Activated platelets release platelet microparticles. It is known that in patients with severe hypertension, the blood concentration of the microbody is increased, and systolic and diastolic blood pressures are increased. Thus, the impact of ITGA2's 1648A → G (Lys505Glu) polymorphism on platelet function may be the reason for its involvement in hypertension.

  Glucokinase is expressed in pancreatic β cells and hepatocytes, and its expression is regulated by two organ-specific promoters. Pancreatic glucokinase acts as a glucose sensor and regulates insulin secretion. It has been reported that 10% to 50% of young adult-onset diabetes depends on GCK mutations. The −30G → A polymorphism of GCK is located in a β-cell specific promoter, and in Japanese, it is involved in a decrease in β-cell function and abnormal glucose tolerance (Non-patent Documents 15 and 16). This polymorphic A allele increased the risk of coronary artery disease, and its association with coronary artery disease remained unchanged after correcting for the presence or absence of type 2 diabetes (Non-patent Document 17).

  The risk of coronary artery disease due to the A allele is greater in patients with type 2 diabetes than in non-diabetes. In this study, the −30G → A polymorphism of GCK was involved in hypertension, and at this time the A allele acted protectively. Regarding the mechanism that the A allele increases the risk of coronary artery disease (Non-Patent Document 17), decreases the function of β-cells and causes glucose intolerance (Non-Patent Documents 15 and 16), and reduces the risk of hypertension. Is currently unknown. The -258G → A polymorphism located in the liver-specific GCK promoter is known to be associated with hypertension in Taiwanese (Non-patent Document 18).

Prostaglandin I ₂ (prostacyclin) has a strong vasodilatory effect, and in addition to inhibiting the proliferation of smooth muscle cells, it exhibits the strongest platelet aggregation inhibitory effect as a body component. For this reason, it is thought that the mutation of PTGIS that regulates the synthesis of prostacyclin may play an important role in the pathology of cardiovascular diseases. Iwai et al. Found a polymorphism in the promoter region of PTGIS that affects promoter activity (Non-patent Document 19). They found in a general population survey that genotypes with low transcriptional activity were associated with higher pulse pressures across the population (especially noticeable in women) and higher systolic blood pressure in the elderly. It was. The 1117C → A polymorphism in exon 8 of PTGIS has been reported to be associated with the prevalence of myocardial infarction, and CC genotype is a risk factor (Non-patent Document 20). The CC genotype was also involved in high systolic blood pressure, but it was a borderline with statistical significance. In this study, it was found that the PTGIS 1117C → A polymorphism was significantly involved in hypertension, and the C polymorphism was a risk factor. Since the 1117C → A polymorphism does not involve an amino acid mutation (Arg373Arg), it is unlikely to directly affect PTGIS expression or prostaglandin I ₂ synthase activity (Non-patent Document 20). This polymorphism may be a genetic marker in linkage disequilibrium with other polymorphisms of PTGIS or polymorphisms of other genes involved in hypertension in the vicinity.
As described above, according to the present embodiment, a detection method and the like for determining a genetic risk and an onset risk for hypertension are provided. By using this invention, it becomes possible to prevent hypertension, and can greatly contribute medically and socially, such as extending the healthy life of the elderly, improving QOL, preventing stickiness, and reducing medical costs in the future.

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It is a figure which shows the fine structure and characteristic of a microbead detected with Luminex100. It is a figure which shows the outline | summary of the procedure of PCR-SSOP-Luminex method.

Claims (2)

ITGA2 1648A → G, GCK −30G → A, PTGIS 1117C → A, SAH A → G (−7 from exon 13), ESR1 −1989T → G, CYBA 242C → T, MMP2 −1306C → T, ABCC8 3857G → A, TNF -863C → A, THBD 2136C → T, F3 -603A → G, GCLM -588C → T, NOS3 -786T → C, PAI1 A → G (Tyr243Cys) The risk of onset is calculated by multiplying the odds ratio of each evaluation factor by using at least one or more genetic polymorphisms and gender differences as evaluation factors, and the risk is determined according to the average and variance or percentage category. A method for detecting a risk of hypertension, comprising preparing a plurality of groups of 3 or more and detecting a risk of onset according to each group. ITGA2 1648A → G, GCK −30G → A, PTGIS 1117C → A, SAH A → G (−7 from exon 13), ESR1 −1989T → G, CYBA 242C → T, MMP2 −1306C → T, ABCC8 3857G → A, TNF -863C → A, THBD 2136C → T, F3 -603A → G, GCLM -588C → T, NOS3 -786T → C, PAI1 A → G (Tyr243Cys) A genetic risk detection method for hypertension, comprising detecting at least one gene polymorphism of at least one gene.