RU2293990C1 - Method for predicting genetically deterministic human diseases - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: method involves determining patient acetylation phenotype and predicting disease from table data built in advance. The table has correlation coefficients between rapid and slow acetylation phenotype reoccurrence frequency in various countries, morbidity coefficients for predicting diseases under prognosis and mortality rates caused by the diseases in various age-specific human life intervals. The risks are predicted in the cases when patient has rapid acetylation phenotype, only if said coefficient values corresponding to patient phenotype and sex are positive, and in slow acetylation phenotype cases when the coefficients are negative. The risks are predicted in the cases when said correlation coefficient values have authenticity level equal to or less than 0.05. Prognosed diseases risks and lethal outcome risks caused by those diseases in given age intervals are determined from the values of the correlation coefficients in the range from -1 to +1. Clinical course severity is additionally estimated for particular patient in said age intervals depending on acetylation degree settled when determining patient phenotype. Acetylation degree is taken into consideration.

EFFECT: high accuracy of prognosis.

6 cl, 2 tbl

Description

The invention relates to medicine and can be used to predict the genetically determined diseases of an individual person throughout his life.

The urgent task of modern biology and medicine is to establish factors of an individual's individual predisposition to various diseases. In connection with the decoding of the human genome, work has recently been intensively carried out to search for genes by mutation of which a disease prognosis can be made. Many methods have been developed for predicting various diseases based on gene mutations.

A known method for the diagnosis and prognosis of cancer based on mutations in the gene of a multifunctional tumor suppressor (MTS). By mutations in the MTS gene in the germ line, one can diagnose a predisposition to such forms of cancer as melanoma, ocular melanoma, leukemia, astrocytoma, glioblastoma, lymphoma, glioma, sarcoma, etc. (1, 2).

A known method for predicting the risk of cancer, based on the determination of coordination disorders between alleles in isolated cells compared with coordination in cells of a healthy person (3).

The predisposition of people to various diseases is also associated with the individual activity of a genetically determined xenobiotic detoxification enzyme system. These include enzymes P-450, NAT1, NAT2, etc., varying in a wide range, due to genetic polymorphism.

A known method for the diagnosis of diseases such as cardiovascular disease, cancer, gastrointestinal diseases, inflammation, hematological diseases, neurological diseases, diseases of reproductive function and urological diseases, based on the determination of impaired activity of the NAT1 enzyme (4).

The advantage of these methods is the high accuracy of the forecast.

However, they do not specify the age of the patient at which there is a risk of a predictable disease, the severity of the course of the disease and the possibility of death from him are unknown. This does not allow the timely implementation of preventive measures to reduce the severity of diseases and, in particular, to avoid death.

The genetically determined enzyme NAT2 (N-acetyltrasferase) takes part in the biotransformation of exogenous and endogenous substrates (lipids, hormones, neurotransmitters, immune factors, inflammation factors).

According to the activity of the genetic enzyme NAT2, all human populations are divided into two groups: with the phenotype of fast and slow acetylation (fast and slow acetylators). At the same time, no physiological advantage was found in these phenotypes. The number of fast and slow acetylators in different ethnic populations varies over a wide range.

The connection between the N-acetylation metabolism system and a person’s predisposition to a number of diseases is known. For example, patients with diabetes mellitus, eczema, adhesive disease and nephropathy have the phenotype of rapid acetylation (5), and patients with some infectious diseases have the phenotype of slow acetylation (6). Based on this regularity by the acetylation phenotype, one can predict the patient's predisposition to these diseases in advance, as well as select a drug therapy for a particular patient.

For example, there is a method for establishing the predisposition of patients with rheumatoid arthritis to the risk of side effects when taking sulfazalazine, a well-known and widely used drug for the treatment of rheumatoid arthritis (7). Prediction of side effects by this method is based on the determination of the patient’s NAT2 gene configuration diplotype, since it was found that side effects occur only in slow acetylators.

However, despite the fact that the connection between the acetylation phenotype and the phenotype predisposition to a number of diseases is known, there are no known methods for predicting these diseases with an exact age at which such diseases are at risk, the prognosis of the severity of the course of the disease at different age intervals of a person’s life and the possibility of death from the predicted diseases is unknown. .

The objective of the invention is the ability to predict genetically determined human diseases with the specification of the age of their development, with an assessment of the severity and risk of death.

This problem is solved by the proposed method, which is carried out as follows. The patient determines the acetylation phenotype and predicts the risk of genetically determined diseases according to a previously prepared table. To compile a table according to world statistics, for example, the World Health Organization (WHO), morbidity and mortality rates from various diseases are revealed, which are given annually by WHO for different countries of the world separately for men and women, indicating the following age intervals (years): up to a year , 1-4, 5-15, 15-24, 25-34, 35-44, 45-54, 55-64, 65-74, 75 and older. Calculate the average annual values of these coefficients for the indicated age intervals, taking into account the data given for 10-20 years.

According to scientific statistics (articles, reviews), the frequency of occurrence of phenotypes of fast and slow acetylation (% of fast or slow acetylators of the total population of the country) is revealed for the same countries. Then, using the array of this data and the well-known mathematical method of statistical data processing, the correlation coefficient “a” and coefficient “b” (according to Spearman) are calculated.

The coefficient “a” is the correlation coefficient between the ratios of phenotypes of fast and slow acetylation and the incidence rates of specific diseases in different countries. The coefficient "b" is the correlation coefficient between the ratios of the same phenotypes and mortality rates from these diseases in the same countries. In this case, the risk of each predicted disease and the risk of death from it in the indicated age ranges are determined by the coefficients “a” and “b” corresponding to the patient’s gender and phenotype with a positive sign of these coefficients for a patient with a rapid acetylation phenotype and a negative sign for a patient with phenotype of slow acetylation, with the reliability of these coefficients (p) equal to or less than 0.05, and the degree of risk of identified diseases and the degree of risk of death from them is determined by the values of ffitsientov «a» and «b» in the range of their values from -1 to +1.

The patient acetylation phenotype can be determined by methods known to those skilled in the art. In one of the methods, the phenotype is determined by the genotype of the patient. At the same time, venous blood is sampled from the patient, DNA is extracted from the nuclei of lymphocytes and the alleles of the NAT2 gene are determined using primers. When one of the alleles NAT2 * 4, NAT2 * 12A and NAT2 * 12C is detected, the rapid acetylation phenotype is established, and when two alleles are found from NAT2 * 5, NAT2 * 6, NAT2 * 7, NAT2 * 10, NAT2 * 11, NAT2 * 13 NAT2 * 14 establish the phenotype of slow acetylation (8).

The patient acetylation phenotype can be determined by another known method (9). In accordance with this method, in the morning on an empty stomach, the patient is given a test preparation inside, which is used as sulfadimezin at a dose of 7 mg / kg of body weight or caffeine at a dose of 4 mg / kg of body weight and its amount is determined after 6 hours in urine. In this case, the phenotype of rapid acetylation at a degree of acetylation of the test preparation is 70-100%, and the phenotype of slow acetylation at a degree of acetylation of less than 70%.

According to the claimed method, in each identified age range of predictable diseases, the severity of diseases for a particular patient is estimated taking into account the direct dependence of the parameters “acetylation degree - disease severity” for fast acetylators and the inverse relationship of these parameters for slow acetylators.

To carry out the forecast for the proposed method, the patient undergoes one or two medical procedures - taking a urine sample after administration of the test drug or taking peripheral venous blood to determine its acetylation phenotype.

Table (1) is prepared in advance, with the help of which forecasting will be carried out. To compile such a table from articles, reviews, scientific monographs and other scientific literature, the percentage ratio of phenotypes of fast and slow acetylation among the population of different countries of the world is revealed. Such data are presented in Table 2. For illustration, table 2 shows the phenotype ratio for 56 countries.

According to the World Health Organization ( WHO Statistics ), for each of these countries, they search for morbidity and mortality rates, which are published every year, indicating sex and age group, separately for each genetically determined disease. All data for each specific disease is subjected to statistical processing. The rates of morbidity (CV) and mortality (COP) are given in WHO in the form of standardized values of the number of diseases and deaths per 100 thousand standardized by age groups of the population. Separate data are provided for men and women. Moreover, WHO data are presented for the following age intervals (years): - up to 1, 1-4, 5-14, 15-24, 25-34, 45-54, 55-64, 65-74, 75 and older.

For example, in Japan for 1997, the following WHO data for primary liver cancer are presented:

Coef. floor Age intervals (years) Up to 1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75+ KZ M 0.86 0.96 0.41 0.42 2,5 14.8 83,2 304.6 584.8 553.6 F 0.12 0.51 0.21 0.36 0.82 3.6 12,2 66,2 189.2 292.7 The cop M 0.2 0.2 0.1 0.1 0.6 3,7 22.5 84.8 167.1 173.0 F 0,0 0.1 0,0 0.1 0.2 0.9 3.3 18,4 54.0 79.0 KZ - incidence rate KS - mortality rate

For Finland, the same data for 1997 have the following meaning:

Coef. floor Age intervals (years) Up to 1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75+ KZ M 0.04 0.11 1.3 0.04 1.3 0.2 14.3 43.6 106.0 170.8 F 0,03 0.12 0.04 0.04 5.1 1,2 2,3 29.2 65.1 140.2 The cop M 0,0 0,0 0.3 0,0 0.3 0,0 3,5 10.6 27.9 48.8 F 0,0 0,0 0,0 0,0 1,2 0.3 2,3 7.4 17.6 43.9

In the same way, information about other diseases is revealed. To calculate the average annual values of the coefficients of the indicators KZ and KS use an array of data for each country for 10-20 years. As a result, a very large data set is used to compile the table, including world statistics on KZ and CS for all diseases separately for men and women in the indicated age ranges for different countries of the world and data on the same countries on the frequency of occurrence of phenotypes of fast and slow acetylation. Using an array of these data and the well-known mathematical method of statistical data processing, two types of correlation coefficients are calculated: “a” - between the frequency of occurrence of each of the two phenotypes and incidence rates of the predicted disease and “b” - between the frequency of occurrence of the same phenotypes and mortality rates from the predicted diseases.

Having compiled such a table, forecasting by the proposed method is not particularly difficult for a specialist. To predict each disease in the table, it is enough to find the patient's gender. Then follow the signs and values of the correlation coefficients “a” and “b” in the various age ranges presented for this disease, which correspond to the patient’s gender. In addition, it is necessary to pay attention to the reliability of the values of the coefficients “a” and “b”, i.e. by the p values shown in table 1. In the event that p is less than or equal to 0.05, then the values of “a” and “b” are reliable indicators and can be used to predict the degree of risk of disease and death from them. If p is more than 0.05, the forecast in this age range is not carried out.

The values of the coefficients "a" and "b" are in the range from -1 to +1. As indicated above, the sign of these coefficients - or + is important for prediction. For the rapid acetylation phenotype, the + sign of the coefficients “a” and “b” indicates a predisposition to the predicted disease, and the sign indicates the absence of a predisposition to this phenotype. For the slow acetylation phenotype, on the contrary, the predisposition to the disease is indicated by the sign - at the coefficients “a” and “b”, and the + sign indicates the lack of predisposition to this disease.

If necessary, an assessment can be made of the severity of the predicted disease in the identified age-related intervals for the risk of the disease. This can be done taking into account the phenotype of the patient and specific data on the degree of acetylation of the test drug in%, obtained when establishing its phenotype. In the event that the patient is a fast acetylator, the assessment of the severity of the disease is made directly proportional to the degree of acetylation. For slow acetylators, the severity of the disease is assessed inversely with the degree of acetylation.

The reliability of the proposed forecasting method was confirmed for patients being treated in a hospital. Moreover, blood or urine was taken from patients with various diagnoses established on the basis of a comprehensive examination to establish the acetylation phenotype according to the methods described above. Then, the same disease was predicted according to Table 1. For this, the same disease was found in the table and signs for the patient's gender were looked at the coefficients “a” and “b”. Based on the signs facing the coefficients “a” and “b”, a conclusion was made about the presence or absence of a predictable disease. In the event that the sign indicated a predisposition to the predicted disease, the values of the coefficients “a” and “b” and their reliability (p) were analyzed. By the value of the reliable coefficients “a” and “b”, the degree of risk of the predicted disease in the patient's age range was established. After that, the severity of the disease was assessed taking into account the above patterns.

In addition, the patient made a forecast regarding the risk of other diseases with an assessment of their severity, including those that were predicted by the proposed method for an earlier age of the patient. This information was compared with the data contained in the patient's medical history.

Such predictions were made on a representative group of patients (400 people) for whom various diseases were established after a comprehensive examination in a hospital.

In all cases, the forecasts made by the proposed method coincided with the diagnoses made on the basis of data from a medical examination of patients.

Since the acetylator phenotype is genetically determined and stable throughout a person’s life, the proposed method allows predicting diseases before the onset of clinical symptoms of these diseases. Moreover, the acetylation phenotype can be determined already at an early age (up to 1 year) and entered into the patient’s medical record to use this information throughout his life.

Thus, the proposed method allows the timely prevention of predictable diseases.

In addition, the method allows for medical and genetic counseling, give dietary and pharmacological recommendations, advice on lifestyle and employment. This cannot be done by known forecasting methods, which make it possible to establish a diagnosis in the early stages of the development of the disease, when preventive measures are already useless.

The invention is illustrated by examples.

Example 1. Primary liver cancer.

A 68-year-old patient G. complained of weakness, a feeling of heaviness on the right, a periodic increase in body temperature, loss of appetite, weight, nausea and vomiting, a feeling of heaviness and constant pain in the right hypochondrium, progressive deterioration. An examination of the patient revealed: the liver is enlarged, painful, dense, bumpy, its lower edge comes out of the hypochondrium. Laboratory studies found hypochromic anemia, leukocytosis, accelerated ESR, increased activity of transaminases and alkaline phosphatase. A comprehensive examination of the patient established the diagnosis of primary liver cancer.

A test drug sulfadimesin was administered to a patient on an empty stomach in a dose of 7 mg / kg body weight. 6 hours after taking the drug, a urine sample was taken from the patient and its analysis was made for the content of sulfadimezin in it. The amount of sulfadimesin in the urine was 15%. Consequently, 85% of the test preparation was acetylated. By this indicator, the patient was assigned to fast acetylators.

In addition, the established phenotype of the patient was confirmed by determining the acetylation genotype. To determine the acetylation genotype, blood was taken from a vein to isolate DNA from lymphocytes. Using the PCR reaction, the patient's genotype was determined - NAT2 * 4 / NAT2 * 4, which determines the phenotype of rapid acetylation.

In table 1, find the disease: primary liver cancer in men (M) and look at the signs in front of the correlation coefficients "a" and "b". The table shows that the coefficients "a" and "b" in all age intervals have a positive value. Since patient G. is a fast acetylator, the + sign of the coefficients “a” and “b” indicates that this patient is predisposed to this disease. Analyze the significance of the given correlation coefficients in all age intervals. It can be seen that the values of the coefficients are reliable, since p has values less than 0.05. Therefore, the prognosis for this disease for a given patient can be made for all age intervals shown in the table. The risk of this disease in patient G. existed at all age intervals. Patient G. at the time of prediction of 68 years, it refers to the age range of 65-74 years. In this interval, the coefficients “a” and “b” have values of +0.75, which indicates a high degree of risk of primary liver cancer.

Assessment of the severity of the course of the disease in patient G. is carried out taking into account the direct dependence of the parameters "the value of the degree of acetylation - the severity of the disease", i.e. severity increases with increasing degree of acetylation.

The table shows that for patient G. at the age of 68 years (degree of acetylation of 85%), the average severity of the course of the disease with primary liver cancer is characteristic. This is consistent with the clinical symptoms and laboratory findings of this patient.

Table The degree of acetylation (%) 71-80 81-90 91-100 Severity + ++ +++ Note: + - mild severity; ++ - moderate severity; +++ - severe.

In addition, to illustrate the invention for this patient, prediction was carried out for other diseases, in accordance with the proposed method according to table 1, for phlebitis, atherosclerosis and cerebrovascular pathologies.

From table 1 it is seen that the reliable values of the coefficients "a" and "b" with phlebitis and atherosclerosis have a negative sign. This means that patient G. has no predisposition to phlebitis and atherosclerosis, which is confirmed by the history of the disease, in which there is no information about these diseases.

Regarding the predisposition to morbidity and mortality from cerebrovascular pathologies from the data presented in table 1, the following can be seen. The correlation coefficients "a" and "b" have a positive sign and high reliable values from 0 to 64 years, which indicates a great predisposition to this disease in this patient. In the age group from 65 to 74 years, a forecast is impossible, since the values of the coefficients “a” and “b” are unreliable.

From the data of the anamnesis it was found that patient G. aged 50-52 years complained of headaches, dizziness, partial loss of vision, periodic increase in blood pressure, which is confirmed by the proposed method.

Assessment of the severity of the course of the disease with cerebrovascular pathologies of patient G. is carried out taking into account the direct dependence of the parameters "the degree of acetylation - the severity of the disease", i.e. severity increases with increasing degree of acetylation.

The table shows that for patient G. at the age of 68 years (the degree of acetylation of 85%), the average severity of the course of the disease is characteristic. This is consistent with the history and clinical symptoms of this patient.

Table The degree of acetylation (%) 71-80 81-90 91-100 Severity + ++ +++ Note: + - mild severity; ++ - moderate severity;
+++ - severe.

Example 2. Primary liver cancer.

Patient A., 47 years old, complained of progressive weakness, adynamia, loss of appetite, weight, frequent nausea and vomiting, fever, feeling of heaviness and constant pain in the right hypochondrium, progressive worsening of the condition. An examination of the patient revealed: the liver is enlarged, its lower edge is determined at the level of the navel, on palpation it is painful, dense, bumpy. Laboratory studies found hypochromic anemia, leukocytosis, accelerated ESR, increased activity of transaminases and alkaline phosphatase. Using targeted biopsy of the liver, the presence of tumor cells in the liver parenchyma was established. Based on clinical, biochemical and histological studies, a diagnosis of primary liver cancer was made.

Patient A. in the morning on an empty stomach was administered a test drug sulfadimezin at a dose of 7 mg / kg body weight. 6 hours after taking the drug, a urine sample was taken from the patient and her analysis was made for the content of sulfadimezin in it. The amount of sulfadimesin in the urine was 22%. Therefore, 78% of the test drug was acetylated. By this indicator, the patient was assigned to fast acetylators.

In addition, the patient's established phenotype was confirmed by determining the acetylation genotype. To determine the acetylation genotype, blood was taken from a vein to isolate DNA from lymphocytes. According to the PCR reaction, the patient's genotype was determined - NAT2 * 4 / NAT2 * 12A, which determines the fast phenotype.

In table 1, find the disease: primary liver cancer in women (G) and look at the signs facing the correlation coefficients "a" and "b". The table shows that the coefficients "a" and "b" in all age intervals have a positive value. As patient A. is a fast acetylator, the + sign of the coefficients “a” and “b” indicates that this patient is predisposed to this disease. The reliability of the given correlation coefficients in all age intervals is analyzed. It can be seen that the values of the coefficients are reliable, since p is less than or equal to 0.05. Therefore, the prognosis for this disease for this patient can be made for all age intervals listed in the table. The risk of this disease in patient A. existed at all age intervals. Patient A. at the time of prediction of 47 years, she refers to the age interval of 45-54 years. In this interval, the coefficients “a” and “b” have values of +0.56 and +0.57, respectively, which indicates a high degree of risk for her disease of primary liver cancer. Assessment of the severity of the course of the disease in patient A. is carried out taking into account the direct dependence of the parameters "the value of the degree of acetylation - the severity of the disease" severity increases with increasing degree of acetylation.

Table The degree of acetylation (%) 71-80 81-90 91-100 Severity + ++ +++ Note: + - mild severity; ++ - moderate severity; +++ - severe.

The table shows that for the patient A. at the age of 47 years (the degree of acetylation of 78%), the course of the disease is characterized by mild to moderate primary liver cancer, as evidenced by her medical history.

In addition, to illustrate the invention for this patient, forecasting for other diseases was carried out in accordance with the proposed method according to table 1, for phlebitis, atherosclerosis and cerebrovascular pathologies.

Table 1 shows that in women, the reliable values of the coefficients “a” and “b” for phlebitis and atherosclerosis have a negative sign. This means that patient A. has no predisposition to phlebitis and atherosclerosis, which is confirmed by the history of the disease, in which there is no information about these diseases.

Regarding the predisposition to morbidity and mortality from cerebrovascular pathologies from the data presented in table 1, the following can be seen. The correlation coefficients "a" and "b" have a positive sign and high reliable values from 0 to 64 years, which indicates a great predisposition to this disease of this patient. In the age group from 65 to 74 years, a forecast is impossible, since the values of the coefficients “a” and “b” are unreliable.

From the anamnesis data, it was found that patient A., aged 40, complained of headaches, vasospasms, dizziness, periodic increase in blood pressure, which she still has at present, which indicates her predisposition to cerebrovascular pathologies.

The severity of the disease of patient A., taking into account the direct dependence of the parameter “degree of acetylation - disease severity”, is estimated according to the table.

Table The degree of acetylation (%) 71-80 81-90 91-100 Severity + ++ +++ Note: + - mild severity; ++ - moderate severity; +++ - severe.

The table shows that patient A. aged 47 years (degree of acetylation 78%) may be characterized by a mild to moderate cerebrovascular pathology, as evidenced by her medical history.

Example 3. Phlebitis.

A 45-year-old patient K. complained of a cosmetic defect in his legs, the appearance of dense red cords on the lower extremities, warm to the touch, painful on palpation or spontaneously, fever of the skin, diffuse pain, a feeling of heaviness and bursting, night leg cramps, swelling . The patient often feels general weakness. On examination, redness and slight swelling are determined along the affected area of the vein. On palpation, a painful seal in the form of a rosary is determined. A general blood test showed a slight leukocytosis with a neutrophilic left shift and an acceleration of ESR. On examination of patient K., varicose dilatation of the great saphenous vein and its branches was revealed. The patient was performed angiography. Diagnosis: stem lymphangitis. Surgical treatment is indicated.

Patient K. in the morning on an empty stomach was given a test drug sulfadimezin at a dose of 7 mg per kg of body weight. 6 hours after taking the drug, a urine sample was taken from the patient and an analysis was made for the content of sulfadimezin in it. The amount of sulfadimesin in the urine was 72%. Therefore, 28% of the test drug was acetylated. By this indicator, the patient was assigned to slow acetylators.

In addition, the established phenotype of the patient was confirmed by determining the acetylation genotype. To determine the acetylation genotype, blood was taken from a vein to isolate DNA from lymphocytes. Using the PCR reaction, the patient's genotype was determined - NAT2 * 7 / NAT2 * 10, which determines the phenotype of slow acetylation.

Table 1 shows the phlebitis disease in men (M) and looks at the signs facing the correlation coefficients “a” and “b”. The table shows that the coefficients "a" and "b" in the age ranges from 15 to 75+ have a negative value in these age intervals. Since patient K. is a slow acetylator, the negative sign for the coefficients “a” and “b” indicates that this patient is predisposed to this disease in age ranges from 15 to 75+. Patient K. at the time of prediction of 45 years, he refers to the age interval of 45-54 years. In this interval, the coefficients “a” and “b” have values of -0.58 and -0.54, respectively, which indicates a high degree of risk of phlebitis in these age ranges. The reliability of the values of the correlation coefficients in the age intervals of 45-54 years is analyzed. It can be seen that the values of the coefficients are reliable, since p is less than or equal to 0.05. Therefore, a forecast of the degree of risk to a given disease for a given patient can be made at age intervals of 45-54 years.

The severity of the disease, taking into account the inverse relationship between the parameter “value of the degree of acetylation - severity of the disease” for slow acetylators, increases with decreasing degree of acetylation. The severity of the disease of patient K. is evaluated according to the table.

Table. The degree of acetylation (%) MA 0-30 31-50 51-70 Severity +++ ++ + Note: + - mild severity; ++ - moderate severity; +++ - severe.

The table shows that patient K. aged 45 years (degree of acetylation 28%) is characterized by a severe course of the disease (surgery is necessary), as evidenced by the data on his medical history.

In addition, to illustrate the invention for this patient, prediction was carried out for other diseases: atherosclerosis, cerebrovascular pathologies and primary liver cancer, in accordance with the proposed method.

From table 1 it can be seen that in men, the reliable values of the coefficients “a” and “b” in atherosclerosis have a negative sign in the age ranges from 45 to 75 years and older. The correlation coefficients "a" and "b" in the age range of 45-54 years are -0.17 and -0.19, respectively. This means that the patient K. is 45 years old (the degree of acetylation is 28%), starting from 45 years old, there is a predisposition to atherosclerosis, which will increase with age.

The severity of the disease, taking into account the inverse dependence of the parameter “the value of the degree of acetylation - severity of the disease” for slow acetylators, increases with decreasing degree of acetylation. The severity of the disease of patient K. is estimated according to the table.

The table shows that for the patient K. at the age of 45 years (degree of acetylation of 28%), a severe course of the disease with atherosclerosis may be characteristic.

Table. The degree of acetylation (%) MA 0-30 31-50 51-70 Severity +++ ++ + Note: + - mild severity; ++ - moderate severity; +++ - severe.

In table 1, find the disease: primary liver cancer in men (M) and look at the signs in front of the correlation coefficients "a" and "b". The table shows that the coefficients "a" and "b" in all age intervals have a positive value, which indicates a great predisposition to this disease of fast acetylators. Since patient G. is a slow acetylator, he has no predisposition to the disease with primary liver cancer.

Regarding the predisposition to morbidity and mortality from cerebrovascular pathologies from the data presented in table 1, the following can be seen. The correlation coefficients “a” and “b” in men have a positive sign and high reliable values from 0 to 64 years, which indicates a great predisposition to rapid acetylators to this disease. Since patient K. is a slow acetylator, he does not have a predisposition to these diseases.

Information sources

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10. Hein D.W. "Molecular genetics and function of NAT1 and NAT2: role in aromatic amine metabolism and carcinogenesis", "Mutat. Res. ", 2002, v. 506-507, p. 65-77.

Table 1 Diseases Floor Coef. correlations Age intervals 0-1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75+ Primary liver cancer M but +0.55 +0.33 +0.72 +0.36 +0.72 +0.81 +0.72 +0.75 +0.75 +0.75 R 0.00 0.02 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 b +0.55 +0.33 +0.72 +0.36 +0.72 +0.81 +0.72 +0.75 +0.75 +0.75 p 0.00 0.02 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 F but +0.20 +0.44 +0.57 +0.41 +0.34 +0.52 +0.56 +0.68 +0.62 +0.62 p 0.05 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 b +0.23 +0.44 +0.56 +0.43 +0.33 +0.52 +0.57 +0.67 +0.63 +0.63 p 0.05 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 Phlebitis M but -0.86 -0.08 -0.08 -0.01 -0.30 -0.60 -0.58 -0.64 -0.72 -0.75 p 0.88 0.35 0.95 0.01 0,000 0,000 0,000 0,000 0,000 0,000 b -0.86 -0.07 -0.09 -0.01 -0.24 -0.59 -0.54 -0.65 -0.71 -0.76 p 0.88 0.35 0.95 0.01 0,000 0,000 0,000 0,000 0,000 0,000 F but -0.09 -0.02 -0.06 -0.36 -0.42 -0.51 -0.55 -0.62 -0.67 -0.67 p 0.34 0.89 0.41 0.001 0.001 0,000 0,000 0,000 0,000 0,000 b -0.08 -0.02 -0.06 -0.30 -0.34 -0.47 -0.54 -0.60 -0.65 -0.65 p 0.29 0.87 0.41 0.001 0.001 0,000 0,000 0,000 0,000 0,000

Continuation of table 1 Diseases Floor Coef. correlations Age intervals 0-1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75+ Atherosclerosis M but -0.02 -0.02 -0.05 -0.16 -0.09 -0.03 -0.17 -0.39 -0.37 -0.40 R 0.82 0.73 0.60 0.09 0.19 0.76 0,03 0.00 0.00 0.00 b -0.02 -0.03 -0.05 -0.15 -0.11 -0.03 -0.19 -0.39 -0.38 -0.41 R 0.82 0.73 0.61 0.09 0.20 0.77 0,03 0.00 0.00 0.00 F but -0.03 -0.051 -0.02 -0.06 -0.07 -0.02 -0.08 -0.36 -0.39 -0.37 R 0.004 0.01 0,000 0.08 0.06 0.1 0.19 0,000 0,000 0,000 b 0,03 0.05 0.02 0.06 0.08 0.02 -0.09 -0.38 -0.40 -0.36 p 0.003 0.01 0,000 0.08 0.16 0.3 0.09 0,000 0,000 0,000 Cerebrovascular pathology M but +0.51 +0.38 +0.47 +0.54 +0.44 +0.45 +0.51 +0.29 +0.06 -0.23 p 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0.340 0.001 b +0.52 +0.38 +0.48 +0.55 +0.43 +0.45 +0.55 +0.28 +0.07 -0.24 p 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0.370 0.001 F but +0.54 +0.43 +0.53 +0.54 +0.32 +0.43 +0.52 +0.32 +0.08 -0.36 p 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0.23 0,000 b +0.54 +0.43 +0.54 +0.55 +0.33 +0.44 +0.52 +0.33 +0.08 -0.37 p 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0.25 0,000

Table 2.
The ratio of phenotypes of N-acetylation in some ethnic populations (56 populations) a country % fast acetylators % slow acetylators Thailand 93 7 Polynesia 93 7 R. Korea 89 eleven Japan 88 12 Hong Kong 85 fifteen Philippines 80 twenty Bangladezh 79 21 USA - Indians 79 21 Singapore 78 22 Taiwan 78 22 Tahiti 72 28 Mexico 70 thirty Venezuela 70 thirty Chile 70 thirty Ecuador 70 thirty Australia - Aboriginal 63 37 Costa Rica 62 38 Brazil 60 40 South Africa (blacks) 59 41 Moldova 52 48 Nigeria 51 49 Tanzania 51 49 Germany 46 54 France 46 54 Spain 46 54 Belgium 46 54 Portugal 46 54 Russia 45 55 Estonia 45 55 Italy 45 55 Angola 45 55 Norway 44 56 Austria 44 56 USA 43 57 Australia 43 57 N.Zelandia 42 58 Denmark 42 58 Netherlands 42 58 Canada 41 59 Continuation of table 2 Morocco 41 59 Turkey 41 59 Poland 40 60 Egypt 39 63 England 38 62 Ireland 38 62 Zimbabwe 38 62 Israel 37 63 Kuwait 37 63 Finland 36 64 Switzerland 36 64 Sudan 35 65 Greece 34 66 Sweden 32 68 Hawaii 31 59 India 26 74 Czech twenty 80

Claims (6)

1. A method for predicting a person’s genetically determined diseases in different age intervals of his life, which consists in determining the patient’s acetylation phenotype and predicting these diseases using a pre-prepared table, for compiling which, according to world statistics, the incidence rates of predicted diseases and mortality from these diseases per year, in age intervals (years) up to 1, 1-4, 5-14, 15-24, 25-34, 45-54, 55-64, 65-74 and older, separately for men and women, for different countries of the world, and according to scientific statistics, the frequency of occurrence of phenotypes of fast and slow acetylation is determined for the same countries, then using the array of these data and the well-known mathematical method of statistical data processing, two types of correlation coefficients are calculated: “a” - between the frequency of occurrence of each of the two phenotypes and the incidence rates of the predicted disease and "b" - between the frequency of occurrence of the same phenotypes and the mortality rates of the predicted disease and the risk of predictable diseases and the risk of death from them in the indicated age ranges are determined by the coefficients “a” and “b” corresponding to the patient’s gender and phenotype with a positive sign of these coefficients for patients with a rapid acetylation phenotype and a negative sign for patients with the slow acetylation phenotype, with a reliability (p) of these coefficients equal to or less than 0.05, and the degree of risk of identified diseases and the degree of risk of death from them are predicted by the coefficients itsientov «a» and «b» in the range of their values from -1 to +1. 2. The method according to claim 1, wherein the world statistics are the World Health Organization (WHO) database. 3. The method according to claim 1, in which the detected morbidity and mortality rates are the average values of these indicators for the year for each country for 10-20 years. 4. The method according to claim 1, wherein the patient’s acetylation phenotype is determined by the activity of the N-acetyltransferase enzyme, and the test preparation is administered to the patient on an empty stomach in the morning on an empty stomach, using sulfadimesin at a dose of 7 mg / kg body weight or caffeine at a dose of 4 mg / kg of body weight, and determine its amount after 6 hours in the urine, while the phenotype of rapid acetylation is established with the degree of acetylation of the test drug 70-100%, and the phenotype of slow acetylation with the degree of acetylation of less than 70%. 5. The method according to claim 1, in which the severity of diseases for a particular patient is assessed in each identified age range of predictable diseases, taking into account the direct dependence of the parameters, the degree of acetylation is the severity of the disease for fast acetylators and the inverse relationship of these parameters for slow acetylators. 6. The method according to claim 1, wherein the patient’s acetylation phenotype is determined by its genotype, while peripheral venous blood is sampled from the patient, DNA is extracted from the nuclei of lymphocytes and the alleles of the NAT2 gene are determined using primers using the polymerase chain reaction and when one of the alleles NAT2 * 4, NAT2 * 12A and NAT2 * 12C establish the rapid acetylation phenotype, and if there are two alleles, NAT2 * 5, NAT2 * 6, NAT2 * 7, NAT2 * 10, NAT2 * 11, NAT2 * 13 and NAT2 * 14 phenotype of slow acetylation.