CN113373209B - Methylation of blood skeleton protein gene as potential marker for early diagnosis of stroke - Google Patents

Abstract

The invention discloses blood skeleton protein gene methylation as a potential marker for early diagnosis of stroke. The invention provides the application of the methylated ACTB gene as a marker in the preparation of products; the product has any of the following functions: (1) auxiliary diagnosis of stroke; (2) early warning of stroke before clinical symptoms. The present invention proves that ACTB methylation in peripheral blood can be used as a potential marker for early diagnosis of stroke. The invention has important scientific significance and clinical application value for improving the early diagnosis and treatment effect of cerebral apoplexy and reducing the mortality rate.

Description

Blood cytoskeleton gene methylation as a potential marker for early diagnosis of stroke

Technical Field

The present invention relates to the medical field, and in particular to blood skeleton protein gene methylation as a potential marker for early diagnosis of stroke.

Background Art

In today's world, stroke has become the second leading cause of death in most countries [Collaborators GBD CoD. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: A systematic analysis for the global burden of diseases study 2016. Lancet. 2017; 390: 1151-1210]. Disability-adjusted life years caused by stroke account for almost 5% of all disability-adjusted life years [Feigin VL, Norrving B, Mensah GA. Global burden of stroke. Circ Res. 2017; 120: 439-448]. In 2016, the lifetime risk of stroke in people aged 25 and above was about 25% worldwide, with the highest estimated risk in China at 39.3%, including 41.1% for men and 36.7% for women [Collaborators GBDLRoS, Feigin VL, Nguyen G, Cercy K, Johnson CO, Alam T, et al. Global, regional, and country-specific lifetime risks of stroke, 1990 and 2016. N Engl J Med. 2018; 379: 2429-2437]. At present, stroke has become the leading cause of death among Chinese residents. The "China Cardiovascular Disease Report 2018" pointed out that the current number of people suffering from cardiovascular disease in my country is about 290 million, of which 13 million are stroke [Summary of "China Cardiovascular Disease Report 2018". Chinese Journal of Circulation. 34: 6-17]. Stroke has extremely high disability and mortality rates. It is of great significance to carry out research on early identification and diagnosis of stroke and population prevention and control.

Stroke is a complex disease caused by the combined effects of genetics and the environment [Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, et al. Heart disease and stroke statistics-2017 update: A report from the american heart association. Circulation. 2017; 135: e146-e603]. Vascular remodeling is the main pathological basis of cardiovascular disease. Atherosclerosis and vascular remodeling lead to reduced cerebral blood supply and changes in cerebral arterial hemodynamics, thereby increasing the risk of stroke [Qi YX, Han Y, Jiang ZL. Mechanobiology and vascular remodeling: From membrane to nucleus. Adv Exp Med Biol. 2018; 1097: 69-82]. Epigenetics is a heritable gene expression regulation method that does not involve changes in DNA sequence and can be passed on to the next generation [Nicoglou A, Merlin F. Epigenetics: A way to bridge the gap between biological fields. Stud Hist Philos Biol Biomed Sci. 2017; 66: 73-82]. DNA methylation is one of the important ways of epigenetic regulation, which refers to the covalent bond of a methyl group to the 5' carbon position of cytosine in genomic CpG dinucleotides under the action of DNA methyltransferase [Bird A. Perceptions of epigenetics. Nature. 2007; 447: 396-398]. A large number of studies have shown that DNA methylation can cause changes in chromatin structure, DNA conformation, DNA stability and the way DNA interacts with proteins, thereby controlling gene expression [Moore LD, LeT, Fan G. DNA methylation and its basic function. Neuropsychopharmacology. 2013; 38: 23-38]. Cytoskeletal actin β (β-actin, ACTB) is widely distributed in eukaryotic cells, regulates the polymerization and depolymerization of actin, participates in maintaining the morphology of cells and tissues, and promotes cell migration, division, growth and signal transduction [Chen G, Zou Y, Zhang X, Xu L, Hu Q, Li T, et al. Beta-actin protein expression differs in the submandibular glands of male and female mice. Cell biology international. 2016; 40: 779-786. Herman IM. Actin isoforms. Curr Opin Cell Biol. 1993; 5: 48-55]. Animal studies have shown that excessive actin polymerization can promote the synthesis of the cytoskeleton and stress fibers, increase the thickness of the vascular wall, change the mechanical force of blood flow, induce vascular hypertrophy and hypertension, further lead to reduced cerebral blood supply and changes in cerebral arterial hemodynamics, promote cerebral artery remodeling, and thus increase the risk of stroke [Ibrahim J, McGee A, Graham D, McGrath JC, Dominiczak AF. Sex-specific differences in cerebral arterial myogenic tone in hypertensive and normotensive rats. Am J Physiol Heart Circ Physiol. 2006; 290: H1081-1089. Legrand MC, Benessiano J, Levy BI. Endothelium, mechanical compliance, and cgmp content in the carotid artery from spontaneously hypertensive rats. J Cardiovasc Pharmacol. 1993; 21 Suppl 1: S26-30]. At present, there are no reports on the relationship between ACTB gene methylation in peripheral blood and stroke in the population, and there are no reports on the relationship between ACTB methylation and ischemic stroke and hemorrhagic stroke. In addition, no one has reported the relationship between ACTB methylation and stroke in animal models including mice and cell lines.

Summary of the invention

The purpose of the present invention is to provide peripheral blood ACTB methylation as a potential marker for early diagnosis of stroke.

In a first aspect, the present invention claims the use of a methylated ACTB gene as a marker in the preparation of a product; the product has any of the following functions:

(1) Assist in the diagnosis of stroke;

(2) Warning of stroke before clinical symptoms occur.

In a second aspect, the present invention claims the use of a substance for detecting the methylation level of the ACTB gene in preparing a product; the product has any of the following functions:

(1) Assist in the diagnosis of stroke;

(2) Warning of stroke before clinical symptoms occur.

In a third aspect, the present invention claims the use of a substance for detecting the methylation level of the ACTB gene and a medium storing a method for establishing a mathematical model and/or a method for using the mathematical model in preparing a product; the product has any of the following functions:

(1) Assist in the diagnosis of stroke;

(2) Warning of stroke before clinical symptoms occur.

The mathematical model is obtained according to a method comprising the following steps:

(A1) The methylation levels of ACTB gene were detected in n1 stroke samples and n2 control samples;

(A2) Taking the ACTB gene methylation level data of all samples obtained in step (A1), a mathematical model was established by binary logistic regression method according to the classification of stroke samples and control samples.

Wherein, n1 and n2 in (A1) can both be positive integers greater than 50.

The method for using the mathematical model comprises the following steps:

(B1) detecting the methylation level of the ACTB gene of the sample to be tested;

(B2) Substituting the ACTB gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index and the threshold, and determining whether the sample to be tested is from or is a candidate to be from a stroke patient based on the comparison result.

The threshold value can be determined according to the maximum Youden index, and can be determined as a certain value such as 0.5 according to actual conditions. Values greater than the threshold value are classified into one category, values less than the threshold value are classified into another category, and values equal to the threshold value are classified as an uncertain gray area.

In a fourth aspect, the present invention claims protection for the use of the "medium storing the method for establishing a mathematical model and/or the method for using the mathematical model" in the third aspect above in the preparation of a product; the product has any of the following functions:

(1) Assist in the diagnosis of stroke;

(2) Warning of stroke before clinical symptoms occur.

In a fifth aspect, the present invention claims a kit.

The kit claimed in the present invention comprises a substance for detecting the methylation level of ACTB gene; the purpose of the kit is at least one of the following:

(1) Assist in the diagnosis of stroke;

(2) Warning of stroke before clinical symptoms occur.

Furthermore, the kit also contains the medium storing the mathematical model establishment method and/or use method as described above.

In a sixth aspect, the present invention claims a system.

The system claimed in the present invention comprises:

(D1) Reagents and/or instruments for detecting the methylation level of ACTB gene;

(D2) A device comprising unit A and unit B.

The unit A is used to establish a mathematical model, including a data acquisition module, a data analysis and processing module and a model output module.

The data acquisition module is used to acquire (D1) the ACTB gene methylation level data of n1 stroke samples and n2 control samples detected.

The data analysis and processing module can establish a mathematical model through a binary logistic regression method based on the ACTB gene methylation level data of n1 stroke samples and n2 control samples collected by the data collection module according to the classification method of the stroke samples and the control samples.

Wherein, n1 and n2 in (A1) can both be positive integers greater than 50.

The model output module is used to output the mathematical model established by the data analysis and processing module.

The unit B is used to determine whether the sample to be tested comes from or is a candidate for a stroke patient, and includes a data input module, a data calculation module, a data comparison module and a conclusion output module.

The data input module is used to input (D1) the ACTB gene methylation level data of the subject obtained by the test.

The data calculation module is used to substitute the ACTB gene methylation level data of the subject into the mathematical model to calculate the detection index.

The data comparison module is used to compare the detection index with a threshold.

The threshold value can be determined according to the maximum Youden index, or can be determined as a certain value such as 0.5 according to actual conditions. Values greater than the threshold value are classified into one category, values less than the threshold value are classified into another category, and values equal to the threshold value are classified as an uncertain gray area.

The conclusion output module is used to output a conclusion of whether the sample to be tested comes from or is a candidate to come from a stroke patient according to the comparison result of the data comparison module.

In addition, the present invention also claims a method for detecting whether a sample to be tested is from or is a candidate for being from a stroke patient (i.e., a method for assisting in the diagnosis of stroke or a method for warning of stroke before clinical symptoms). The method may include the following steps:

(A) A mathematical model may be established according to a method comprising the following steps:

(A1) The methylation levels of the ACTB gene were detected in n1 stroke samples and n2 control samples (training set);

(A2) Taking the ACTB gene methylation level data of all samples obtained in step (A1), a mathematical model was established by binary logistic regression method according to the classification of stroke samples and control samples.

Wherein, n1 and n2 in (A1) can both be positive integers greater than 50.

(B) determining whether the sample to be tested is from or is a candidate to be from a stroke patient can be performed according to a method comprising the following steps:

(B1) detecting the methylation level of the ACTB gene of the sample to be tested;

(B2) Substituting the ACTB gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index and the threshold, and determining whether the sample to be tested is from or is a candidate to be from a stroke patient based on the comparison result.

The threshold value can be determined according to the maximum Youden index, or can be determined as a certain value such as 0.5 according to actual conditions. Values greater than the threshold value are classified into one category, values less than the threshold value are classified into another category, and values equal to the threshold value are classified as an uncertain gray area.

In the above aspects, the ACTB gene methylation level is the methylation level of all or part of the CpG sites in the fragments shown below (e1)-(e5) in the ACTB gene;

The methylated ACTB gene is a gene in which all or part of the CpG sites in the fragments shown below (e1) to (e5) in the ACTB gene are methylated;

(e1) a DNA fragment represented by SEQ ID No. 1 or a DNA fragment having 80% or more identity thereto;

(e2) a DNA fragment represented by SEQ ID No. 2 or a DNA fragment having 80% or more identity thereto;

(e3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment having 80% or more identity thereto;

(e4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment having 80% or more identity thereto;

(e5) A DNA fragment represented by SEQ ID No. 5 or a DNA fragment having 80% or more identity thereto.

Furthermore, the “all or part of the CpG sites” may specifically be any of the following:

(f1) the CpG site at positions 128-129 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 180-181 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 231-232 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 313-314 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 362-363 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 367-368 from the 5' end of the DNA fragment shown in SEQ ID No.1, or the CpG site at positions 428-429 from the 5' end of the DNA fragment shown in SEQ ID No.1;

(f2) the CpG site at positions 53-54 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 57-58 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 125-126 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 232-233 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 260-261 from the 5' end of the DNA fragment shown in SEQ ID No.2, or the CpG site at positions 283-284 from the 5' end of the DNA fragment shown in SEQ ID No.2;

(f3) the CpG site at positions 61-62 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 87-88 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 103-104 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 147-148 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 171-172 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 186-187 from the 5' end of the DNA fragment shown in SEQ ID No.3, or the CpG site at positions 238-239 from the 5' end of the DNA fragment shown in SEQ ID No.3;

(f4) the CpG site at positions 39-40 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 41-42 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 69-70 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 107-108 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 110-111 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 139-140 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 185-186 from the 5' end of the DNA fragment shown in SEQ ID No.4, or the CpG site at positions 275-276 from the 5' end of the DNA fragment shown in SEQ ID No.4;

(f5) the CpG site at positions 44-45 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 175-176 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 266-267 from the 5' end of the DNA fragment shown in SEQ ID No.5, or the CpG site at positions 300-301 from the 5' end of the DNA fragment shown in SEQ ID No.5;

(f6) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2;

(f7) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3;

(f8) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4;

(f9) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f10) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3;

(f11) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4;

(f12) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f13) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4;

(f14) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f15) 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f16) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3;

(f17) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4;

(f18) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f19) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4;

(f20) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f21) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f22) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4;

(f23) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f24) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f25) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4;

(f26) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5;

(f27) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5;

(f28) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5;

(f29) 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5;

(f30) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5;

In (f6)-(f30), the 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 are: SEQ ID No.1 From the 5' end, the CpG site at positions 128-129 (ACTB_A_1); the CpG site at positions 180-181 (ACTB_A_3); the CpG site at positions 203-204 (ACTB_A_4); the CpG site at positions 231-232 (ACTB_A_5); the CpG site at positions 313-314 (ACTB_A_6); the CpG site at positions 338-339 (ACTB_A_7); the CpG sites at positions 362-363 and 367-368 (ACTB_A_8.9); the CpG site at positions 406-407 (ACTB_A_10); the CpG site at positions 428-429 (ACTB_A_12);

The 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.2 are: CpG sites shown at positions 53-54 and 57-58 from the 5' end of SEQ ID No.2 (ACTB_B_2.3); CpG sites shown at positions 96-97 and 101-102 (ACTB_B_4.5); CpG sites shown at positions 125-126 (ACTB_B_6); CpG sites shown at positions 232-233 (ACTB_B_8); CpG sites shown at positions 260-261 (ACTB_B_9); CpG sites shown at positions 283-284 (ACTB_B_10); and CpG sites shown at positions 335-336 (ACTB_B_12);

The 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 are SEQ ID No.3 from the 5' end, the CpG sites shown at positions 25-26, 27-28, 29-30, 32-33 and 45-46 (ACTB_C_1.2.3.4.5); the CpG site shown at positions 61-62 (ACTB_C_6); the CpG sites shown at positions 63-64, 66-67 and 81-82 (ACTB_C_8.9.10); the CpG sites shown at positions 87-88 and 103-104 (ACTB_C_11.12); the CpG sites shown at positions 105-106, 109-110 and 119-120 (ACTB_C_14.15.16); the CpG sites shown at positions 147-148 G site (ACTB_C_17); CpG sites shown at positions 149-150 and 165-166 (ACTB_C_19.20); CpG site shown at positions 171-172 (ACTB_C_24); CpG site shown at positions 186-187 (ACTB_C_25); CpG sites shown at positions 192-193, 194-195, 198-199 and 201-202 (ACTB_C_27.28.29.30); CpG sites shown at positions 211-212 and 216-217 (ACTB_C_31.32); CpG site shown at positions 238-239 (ACTB_C_34);

The 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.4 are the CpG sites shown at positions 39-40 and 41-42 (ACTB_D_2.3) from the 5' end of SEQ ID No.4; the CpG sites shown at positions 61-62 and 65-66 (ACTB_D_4.5); the CpG sites shown at positions 69-70 (ACTB_D_6); the CpG sites shown at positions 77-78 and 81-82 (ACTB_D_7.8); the CpG sites shown at positions 107-108 and 110-111 (ACTB_D_9.10); The CpG site shown at positions 122-123 (ACTB_D_11); the CpG site shown at positions 139-140 (ACTB_D_12); the CpG site shown at positions 185-186 (ACTB_D_14); the CpG sites shown at positions 213-214 and 219-220 (ACTB_D_15.16); the CpG site shown at positions 275-276 (ACTB_D_17); the CpG site shown at positions 304-305 (ACTB_D_18);

The five distinguishable CpG sites of the DNA fragment shown in SEQ ID No.5 are: the CpG site shown at positions 44-45 from the 5' end of SEQ ID No.5 (ACTB_E_1); the CpG site shown at positions 175-176 (ACTB_E_2); the CpG site shown at positions 266-267 (ACTB_E_3); the CpG site shown at positions 292-293 (ACTB_E_4); and the CpG site shown at positions 300-301 (ACTB_E_5).

In the above aspects, the substance for detecting the methylation level of ACTB gene comprises (or is) a primer combination for amplifying the full length or partial fragment of ACTB gene. The reagent for detecting the methylation level of ACTB gene comprises (or is) a primer combination for amplifying the full length or partial fragment of ACTB gene.

Further, the partial fragment may be at least one of the following fragments:

(g1) a DNA fragment represented by SEQ ID No. 1 or a DNA fragment contained therein;

(g2) the DNA fragment shown in SEQ ID No. 2 or a DNA fragment contained therein;

(g3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein;

(g4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment contained therein;

(g5) a DNA fragment represented by SEQ ID No. 5 or a DNA fragment contained therein;

(g6) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 1 or a DNA fragment contained therein;

(g7) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 2 or a DNA fragment contained therein;

(g8) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein;

(g9) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 4 or a DNA fragment contained therein;

(g10) A DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 5 or a DNA fragment contained therein.

Furthermore, the primer combination is primer pair A and/or primer pair B and/or primer pair C and/or primer pair D and/or primer pair E.

The primer pair A is a primer pair consisting of primer A1 and primer A2; the primer A1 is a single-stranded DNA represented by nucleotides 11-35 of SEQ ID No.6 or SEQ ID No.6; the primer A2 is a single-stranded DNA represented by nucleotides 32-58 of SEQ ID No.7 or SEQ ID No.7.

The primer pair B is a primer pair consisting of primer B1 and primer B2; the primer B1 is a single-stranded DNA represented by nucleotides 11-34 of SEQ ID No.8 or SEQ ID No.8; the primer B2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.9 or SEQ ID No.9.

The primer pair C is a primer pair consisting of primer C1 and primer C2; the primer C1 is a single-stranded DNA represented by SEQ ID No.10 or nucleotides 11-35 of SEQ ID No.10; the primer C2 is a single-stranded DNA represented by SEQ ID No.11 or nucleotides 32-51 of SEQ ID No.11.

The primer pair D is a primer pair consisting of primer D1 and primer D2; the primer D1 is a single-stranded DNA represented by nucleotides 11-37 of SEQ ID No.12; the primer D2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.13 or SEQ ID No.13.

The primer pair E is a primer pair consisting of primer E1 and primer E2; the primer E1 is a single-stranded DNA represented by nucleotides 11-37 of SEQ ID No.14; the primer E2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.15 or SEQ ID No.15.

In the above aspects, the subject for the auxiliary diagnosis of stroke and/or the assessment of the risk of stroke is a stroke patient or a normal person (who has not suffered a stroke) who meets at least one of the following conditions:

(h1) Aged less than 65 years;

(h2) drinking alcohol;

(h3) Drinking alcohol and low methylation level of the ACTB gene.

Furthermore, the stroke patient is a stroke patient whose onset time is less than 2 years, less than 1.5 years, less than 1.32 years or less than 1 year.

In the present invention, the definition of drinking is drinking ≥ 2 times/week currently or in the past and continuing drinking for half a year.

Any of the above mathematical models may vary in practical applications depending on the detection method and fitting method of DNA methylation. It should be determined based on the specific mathematical model without the need for agreement.

In an embodiment of the present invention, the model is specifically log(y/(1-y))=b0+b1x1+b2x2+b3x3+…+bnXn, wherein y is the dependent variable, i.e., the detection index obtained after substituting the methylation value of one or more methylation sites of the test sample into the model, b0 is a constant, x1~xn are independent variables, i.e., the methylation value of one or more methylation sites of the test sample (each value is a value between 0-1), and b1~bn are the weights assigned to the methylation value of each site by the model.

In an embodiment of the present invention, the establishment of the model can also add known parameters such as age, gender, white blood cell count, body mass index, smoking, drinking, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG to improve the discrimination efficiency. A specific model established in an embodiment of the present invention is a model for assisting in distinguishing stroke patients with an onset time of less than 2 years and control samples, and the model is specifically: log(y/(1-y))=-2.937-0.810*ACTB_D_2.3+0.916*ACTB_D_4.5-1.573*ACTB_D_6-3.181*ACTB_D_7.8+0.931*ACTB_D_9.10+0.882*

ACTB_D_11+3.763*ACTB_D_12-2.570*ACTB_D_14+1.142*ACTB_D_15.16+0.221*ACTB_D_17+1.285*ACTB_D_18+0.013*Age-0.072*Sex (male is assigned 1, female is assigned 0)+0.302*White blood cell count+0.034*BMI+0 .025*Smoking (smoking is assigned to 1, non-smoking is assigned to 0)-0.055*Drinking (drinking is assigned to 1, non-drinking is assigned to 0)+0.035*History of hypertension (history of hypertension is assigned to 1, no history of hypertension is assigned to 0)-0.030*(history of diabetes is assigned to 1, no history of diabetes is assigned to 0)+0.009*HDL-C+0.351*LDL-C-0.170*TC-0.013*TG. The ACTB_D_2.3 is the methylation level of the CpG sites shown at positions 39-40 and 41-42 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_4.5 is the methylation level of the CpG sites shown at positions 61-62 and 65-66 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_6 is the methylation level of the CpG sites shown at positions 69-70 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_7.8 is the methylation level of the CpG sites shown at positions 77-78 and 81-82 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_9.10 is the methylation level of the CpG sites shown at positions 107-108 and 110-111 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_11 is the methylation level of the CpG sites shown at positions 107-108 and 110-111 from the 5' end of the DNA fragment shown in SEQ ID The methylation level of the CpG site shown at positions 122-123 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_12 is the methylation level of the CpG site shown at positions 139-140 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_14 is the methylation level of the CpG site shown at positions 185-186 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_15.16 are the methylation levels of the CpG sites shown at positions 213-214 and 219-220 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_17 is the methylation level of the CpG site shown at positions 275-276 from the 5' end of the DNA fragment shown in SEQ ID No.4; the ACTB_D_18 is the methylation level of the CpG site shown at positions 304-305 from the 5' end of the DNA fragment shown in SEQ ID No.4. The threshold of the model is a diagnostic threshold of 0.36 obtained by the maximum Youden index. Candidates for subjects whose detection index calculated by the model is less than 0.36 are stroke patients, and candidates for subjects whose detection index is greater than 0.36 are non-stroke patients.

In the above aspects, the detecting of the methylation level of ACTB gene is detecting the methylation level of ACTB gene in blood.

The present invention adopts a nested case-control study, collects new stroke patients within 2 years after the community cohort is selected as the case group (the case group has no disease at the time of blood sample collection, and has a stroke within 2 years after blood collection), and matches the age and gender to those who have not had a stroke during the follow-up as the control group, to explore the relationship between peripheral blood ACTB methylation and stroke in the Chinese population. Studies have shown that peripheral blood ACTB methylation can be used as a potential marker for early warning and early diagnosis of stroke. The present invention has important scientific significance and clinical application value for improving the diagnosis and treatment of stroke.

DETAILED DESCRIPTION

Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

Unless otherwise specified, the materials and reagents used in the following examples can be obtained from commercial sources.

Example 1: Primer design for detecting methylation sites of ACTB gene

The ACTB gene has 6 exons with a total length of 3454bp (chr7:5566779-5570232). After a large number of sequence and functional analyses, this test covers the CpG sites on the ACTB gene promoter region and exon 1 (ACTB_A, ACTB_B), exon 2 and intron 2 (ACTB_C), exons 3, 4, 5 and introns 3, 4, 5 (ACTB_D), exon 6 and intron 6 (ACTB_E) to analyze the correlation between methylation levels and stroke.

The ACTB_A fragment (SEQ ID No. 1) is located in the hg19 reference genome chr7:5570155-5571232, antisense strand.

The ACTB_B fragment (SEQ ID No. 2) is located in the hg19 reference genome chr7:5570155-5571232, positive strand.

The ACTB_C fragment (SEQ ID No. 3) is located at chr7:5569032-5570100 of the hg19 reference genome, positive strand.

The ACTB_D fragment (SEQ ID No. 4) is located at chr7:5567000-5569000 of the hg19 reference genome, positive strand.

The ACTB_E fragment (SEQ ID No. 5) is located in the hg19 reference genome chr7:5565779-5566988, positive strand.

The CpG site information in the ACTB_A fragment is shown in Table 1.

The CpG site information in the ACTB_B fragment is shown in Table 2.

The CpG site information in the ACTB_C fragment is shown in Table 3.

The CpG site information in the ACTB_D fragment is shown in Table 4.

The CpG site information in the ACTB_E fragment is shown in Table 5.

Table 1 CpG site information in ACTB_A fragment

CpG sites The location of the CpG site in the sequence ACTB_A_1 SEQ ID No.1 from 5' end 128-129 ACTB_A_3 SEQ ID No.1 from 5' end 180-181 ACTB_A_4 SEQ ID No.1 from 5' end 203-204 ACTB_A_5 SEQ ID No.1 from 5' end 231-232 ACTB_A_6 SEQ ID No.1 from 5' end 313-314 ACTB_A_7 SEQ ID No.1 from 5' end 338-339 ACTB_A_8 SEQ ID No.1 from 5' end 362-363 ACTB_A_9 SEQ ID No.1 from 5' end 367-368 ACTB_A_10 SEQ ID No.1 from 5' end 406-407 ACTB_A_12 SEQ ID No.1 from 5' end 428-429

Table 2 CpG site information in ACTB_B fragment

Table 3 CpG site information in ACTB_C fragment

CpG sites The location of the CpG site in the sequence ACTB_C_1 SEQ ID No.3 from 5' end 25-26 ACTB_C_2 SEQ ID No.3 from 5' end 27-28 ACTB_C_3 SEQ ID No.3 from 5' end 29-30 ACTB_C_4 SEQ ID No.3 from 5' end 32-33 ACTB_C_5 SEQ ID No.3 from 5' end 45-46 ACTB_C_6 SEQ ID No.3 from 5' end 61-62 ACTB_C_8 SEQ ID No.3 from 5' end 63-64 ACTB_C_9 SEQ ID No.3 from 5' end 66-67 ACTB_C_10 SEQ ID No.3 from 5' end 81-82 ACTB_C_11 SEQ ID No.3 from 5' end 87-88 ACTB_C_12 SEQ ID No.3 from 5' end 103-104 ACTB_C_14 SEQ ID No.3 from 5' end 105-106 ACTB_C_15 SEQ ID No.3 from 5' end 109-110 ACTB_C_16 SEQ ID No.3 from 5' end 119-120 ACTB_C_17 SEQ ID No.3 from 147 to 148 at the 5' end ACTB_C_19 SEQ ID No.3 from 149 to 150 at the 5' end ACTB_C_20 SEQ ID No.3 from 5' end 165-166 ACTB_C_24 SEQ ID No.3 from 5' end 171-172 ACTB_C_25 SEQ ID No.3 from 186 to 187 at the 5' end ACTB_C_27 SEQ ID No.3 from 192 to 193 at the 5' end ACTB_C_28 SEQ ID No.3 from 194 to 195 at the 5' end ACTB_C_29 SEQ ID No.3 from 5' end 198-199 ACTB_C_30 SEQ ID No.3 from 5' end 201-202 ACTB_C_31 SEQ ID No.3 from 5' end 211-212 ACTB_C_32 SEQ ID No.3 from 5' end 216-217 ACTB_C_34 SEQ ID No.3 from 5' end 238-239

Table 4 CpG site information in ACTB_D fragment

Table 5 CpG site information in ACTB_E fragment

CpG sites The location of the CpG site in the sequence ACTB_E_1 SEQ ID No.5 from 5' end 44-45 ACTB_E_2 SEQ ID No.5 from 175 to 176 at the 5' end ACTB_E_3 SEQ ID No.5 from 5' end 266-267 ACTB_E_4 SEQ ID No.5 from 5' end 292-293 ACTB_E_5 SEQ ID No.5 from 5' end 300-301

Specific PCR primers were designed for the five fragments (ACTB_A fragment, ACTB_B fragment, ACTB_C fragment, ACTB_D fragment and ACTB_E fragment), as shown in Table 6. Among them, SEQ ID No.6, SEQ ID No.8, SEQ ID No.10, SEQ ID No.12 and SEQ ID No.14 are forward primers, and SEQ ID No.7, SEQ ID No.9, SEQ ID No.11, SEQ ID No.13 and SEQ ID No.15 are reverse primers; from the 1st to the 10th position of SEQ ID No.6, SEQ ID No.8, SEQ ID No.10, SEQ ID No.12 and SEQ ID No.14 from the 5' end are non-specific tags, and from the 11th to the 35th position of SEQ ID No.6 and SEQ ID No.10, from the 11th to the 34th position of SEQ ID No.8, and from the 11th to the 37th position of SEQ ID No.12 and SEQ ID No.14 are specific primer sequences; from the 1st to the 31st position of SEQ ID No.7, SEQ ID No.9, SEQ ID No.11, SEQ ID No.13 and SEQ ID No.15 from the 5' end are non-specific tags, and from the 1st to the 31st position of SEQ ID No.7, positions 32 to 58, SEQ ID No.9, SEQ ID No.13 and SEQ ID No.15, positions 32 to 56, and SEQ ID No.11, positions 32 to 51 are specific primer sequences. The primer sequences do not contain SNP and CpG sites.

Table 6 ACTB methylation primer sequences

Amplified fragment Primer number Primer sequence (5'-3') ACTB_A SEQ ID No.6 aggaagagagGTTTTGAAAGTAGGGGTTTGAGGATT ACTB_A SEQ ID No.7 cagtaatacgactcactatagggagaaggctCCTCCAAATAATCTAAAAAAACAATTC ACTB_B SEQ ID No.8 aggaagagagTAGATGGTTTGGGAGGGTAGTTTA ACTB_B SEQ ID No.9 cagtaatacgactcactatagggagaaggctCCCTAAAAACAAAACCTAAAAACCT ACTB_C SEQ ID No.10 aggaagagagGGAAGGAAAGGATAAGAAGTTTTGA ACTB_C SEQ ID No.11 cagtaatacgactcactatagggagaaggctACTACCCCACCCAACCAACT ACTB_D SEQ ID No.12 aggaagagagGGGATTTGATTGATTATTTTATGAAGA ACTB_D SEQ ID No.13 cagtaatacgactcactatagggagaaggctACCACAAAACTCCATACCTAAAAAA ACTB_E SEQ ID No.14 aggaagagagGGGTTTTGTAGAATAATGAGAATTTGA ACTB_E SEQ ID No.15 cagtaatacgactcactatagggagaaggctTCCTACCTATTCATCCAAACAAAAA

Example 2: ACTB gene methylation detection and result analysis

1. Research Sample

Using epidemiological cluster sampling, a survey of community residents aged 18 years and above in 16 towns in Jurong City, Jiangsu Province was conducted from October to December 2015, with a total of 11,151 people in the baseline survey. This study was reviewed by the Ethics Committee of Nanjing Medical University, and all respondents signed informed consent.

The baseline survey included collecting the general demographic information of the subjects, such as gender, age, place of origin, and ethnicity; asking about medical history, medication history, family history, etc., mainly including cardiovascular disease, diabetes, kidney disease, and dyslipidemia; collecting smoking status and drinking status. Smoking was defined as smoking more than 20 cigarettes per week and continuous smoking for more than 3 months per year. Drinking was defined as drinking ≥2 times per week and drinking for half a year. Anthropometric indicators included weight, blood pressure, height, and waist circumference. Weight measurement required the respondents to wear light clothes and the readings were accurate to 0.1kg. When measuring blood pressure, the respondents were required to fast in the morning, not engage in strenuous exercise, and sit quietly for 5 minutes. A mercury sphygmomanometer was used to measure the blood pressure of the right brachial artery. Each respondent repeated the blood pressure measurement three times, with an interval of more than 30 seconds each time. If the difference between the three systolic or diastolic blood pressure measurements was ≥8mmHg, an additional measurement was required. When measuring height, a tape measure was fixed on the wall. All respondents took off their shoes and hats, put their heels together and stood upright on the tape measure. The right angle side of the large triangle was used for reading, accurate to 0.1 cm. When measuring waist circumference, a soft tape measure was placed around the skin 1 cm above the navel to read the reading. Body mass index (BMI) is equal to body weight (kg)/height squared (m ² ). In addition, respondents were required to draw blood on an empty stomach in the morning. A total of two tubes of peripheral venous blood (1 tube each of anticoagulant and procoagulant) were collected for the detection of biochemical indicators, mainly including the proportion of leukocyte subtypes, fasting blood glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C).

Information on the incidence and mortality of cardiovascular and cerebrovascular diseases is recorded annually through the chronic disease management system of local hospitals, CDCs, routine chronic disease registration projects of community health service centers and workstations, and reimbursement data of social security centers. The start time of the cohort was the baseline survey date, and the outcome variable was the onset of stroke. The follow-up time for subjects who were lost to follow-up was uniformly calculated as half of the end time of follow-up. As of the follow-up date of July 13, 2018, a total of 234 new strokes occurred. We selected patients with new stroke within 2 years after cohort enrollment as the case group, a total of 139 cases. After age and gender matching, those who did not have a stroke during the follow-up period were selected as controls, a total of 147 cases.

The average age of stroke cases was 67.64±9.51 years, and the average age of controls was 67.59±9.11 years. There was no significant difference in age between the two groups (P>0.05). There was no significant difference in gender, BMI, SBP, DBP, smoking, drinking, history of hypertension, history of diabetes, TC, TG, HDL-C, LDL-C, glucose, white blood cell count, neutrophil ratio, monocyte, eosinophil and basophil ratio between the two groups (P>0.05). The median follow-up time (time from blood draw to follow-up deadline) of all subjects was 2.65 years, and the median onset time (time from blood draw to stroke diagnosis) of stroke cases was 1.32 years. Detailed results are shown in Table 7.

Table 7 Distribution of general demographic and clinical characteristics of the subjects

Note: BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; Glucose, fasting blood glucose; TG, triglycerides; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.

2. Methylation Detection

1. Extract total DNA from blood samples.

2. Treat the total DNA of the blood sample prepared in step 1 with bisulfite (refer to the instructions of the Qiagen DNA methylation kit). After bisulfite treatment, unmethylated cytosine (C) is converted into uracil (U), while methylated cytosine remains unchanged, that is, the C base of the original CpG site is converted into C or U after bisulfite treatment.

3. Using the DNA treated with bisulfite in step 2 as a template, PCR amplification was performed using the 5 pairs of specific primers in Table 6 by DNA polymerase according to the reaction system required for conventional PCR reaction. The 5 pairs of primers all used the same conventional PCR system, and the 5 pairs of primers were amplified according to the following procedure.

The PCR reaction program was: 95°C, 4 min → (95°C, 20 s → 56°C, 30 s → 72°C, 2 min) 45 cycles → 72°C, 5 min → 4°C, 1 h.

4. Take the amplified product of step 3 and perform DNA methylation analysis by time-of-flight mass spectrometry. The specific method is as follows:

(1) Add 2 μl of shrimp alkaline phosphate (SAP) solution (0.3 ml SAP [0.5 U] + 1.7 ml H ₂ O) to 5 μl of PCR product and then incubate in a PCR instrument according to the following program (37°C, 20 min → 85°C, 5 min → 4°C, 5 min);

(2) Take out 2 μl of the SAP-treated product obtained in step (1), add it to 5 μl of T-Cleavage reaction system according to the instructions, and then incubate at 37°C for 3 h;

(3) Take the product of step (2), add 19 μl of deionized water, and then incubate with 6 μg of Resin on a rotary shaker for 1 h for deionization;

(4) Centrifuge at 2000 rpm for 5 min at room temperature, and load a small amount of supernatant onto 384 SpectroCHIP using a Nanodispenser robot;

(5) Time-of-flight mass spectrometry analysis; the data were collected using SpectroACQUIRE v3.3.1.3 software and visualized using MassArray EpiTyper v1.2 software.

Analyzer Chip Prep Module 384，型号：41243；上述数据分析软件为检测仪器自带软件。The reagents used in the above-mentioned time-of-flight mass spectrometry detection are all from the kit (T-Cleavage MassCLEAVEReagent Auto Kit, catalog number: 10129A); the detection instrument used in the above-mentioned time-of-flight mass spectrometry detection is

Analyzer Chip Prep Module 384, model: 41243; the above data analysis software is the software provided by the testing instrument.

3. Quality Control

On-site investigation: formulate rigorous questionnaires and unify measurement standards; uniformly train and assess investigators before the investigation; conduct preliminary investigations before the formal investigation to promptly identify and summarize problems; questionnaires are quality-controlled on-site by dedicated quality control personnel, and questionnaires with unqualified quality are returned to the investigators for re-investigation of the research subjects; questionnaire data are entered on two tracks and consistency is tested; blood samples collected on-site are sent for inspection in a timely manner. Strictly follow the experimental operation requirements, regularly disinfect the operating environment with ultraviolet light; conduct preliminary experiments before formal experiments; randomly select 5% of the samples for repeated time-of-flight mass spectrometry detection to ensure that the consistency rate of the results is more than 99%. Two people interpret the experimental results, organize the methylation data, and ensure the authenticity and accuracy of the data. Through the mass spectrometry experiment, a total of 44 distinguishable G peaks were obtained. SpectroACQUIRE v3.3.1.3 software was used to calculate the methylation level based on the comparison of the G-containing peak and the A peak area (SpectroACQUIRE v3.3.1.3 software can automatically obtain the methylation level of each sample at each CpG site by calculating the peak area).

Statistical Analysis

Normally distributed quantitative data were expressed as mean ± standard deviation, and count data were expressed as rate. Group t-test or chi-square test was used to compare the distribution of general demographic data between the case group and the control group. Non-normally distributed quantitative data were expressed as median (interquartile range), and Mann-Whitney U test was used to compare the differences between the case group and the control group. Unconditional logistic regression model was used for the association analysis between ACTB methylation and stroke. The odds ratio (OR) and 95% confidence interval (CI) were calculated for every 10% methylation increment after adjusting for covariates such as leukocyte subtype ratio, gender, age, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG. Spearman rank correlation coefficient was used to evaluate the statistical correlation between two variables. Logistic regression and receiver operating characteristic curve (ROC) were used to evaluate the value of the combination of multiple CpG sites for early warning and early diagnosis of stroke. The difference was considered statistically significant when the bilateral P value was less than 0.05. All data were analyzed using SPSS 24.0.

V. Results Analysis

1. Analysis of the association between ACTB methylation and stroke

The present invention performed association analysis on stroke cases according to different clinical onset times. The results showed that in stroke cases with clinical onset time ≤ 1.5 years, six sites of ACTB_A fragment [CpG_1 (0.30 vs. 0.35), CpG_3 (0.21 vs. 0.24), CpG_5 (0.27 vs. 0.32), CpG_6 (0.25 vs. 0.30), CpG_8.9 (0.21 vs. 0.25), CpG_12 (0.39 vs. 0.43)], five sites of ACTB_B fragment [CpG_2.3 (0.59 vs. 0.63), Cp G_6 (0.61 vs. 0.64), CpG_8 (0.41 vs. 0.45), CpG_9 (0.31 vs. 0.35), CpG_10 (0.27 vs. 0.33)], 6 sites of ACTB_C fragment [CpG_6 (0.32 vs. 0.35), CpG_11.12 (0.21 vs. 0.25), CpG_17 (0.46 vs. 0.50), CpG_24 (0.31 vs. 0.34), CpG_25 (0.32 vs. 0.35), CpG_34 (0.36 vs. 0.40)], ACT The 6 sites of B_D fragment [CpG_2.3 (0.43 vs. 0.47), CpG_6 (0.39 vs. 0.43), CpG_9.10 (0.32 vs. 0.36), CpG_12 (0.25 vs. 0.30), CpG_14 (0.46 vs. 0.51), CpG_17 (0.45 vs. 0.50)] and the 4 sites of ACTB_E fragment [CpG_1 (0.30 vs. 0.34), CpG_2 (0.31 vs. 0.35), CpG_3 (0.30 vs. 0.35), CpG_5 (0.39 vs. .0.43)] were significantly lower than those in the control group; logistic regression results showed that after adjusting for covariates such as leukocyte subtype ratio, gender, age, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG, the ORs (95% CIs) for each +10% methylation were ACTB_A [CpG_1: 0.820 (0.650-0.907), P = 0.007; CpG_3: 0.778 (0.603-0.904), P = 0.003; CpG_5: 0.711 (0.600-0.921), P = 0.002; CpG_6: 0.700 (0.602-0.901), P = 0.001; CpG_8.9: 0.729 (0.607-0.905), P = 0.005; CpG_12: 0.751 (0.617-0.913), P = 0.006], ACTB_B [CpG_2.3: 0.715 (0.618-0.903), P=0.004; CpG_6: 0.722 (0.603-0.910), P=0.008; CpG_8: 0.715 (0.605-0.896), P=0.00 7; CpG_9: 0.712 (0.607-0.900), P = 0.007; CpG_10: 0.702 (0.608-0.872), P = 0.009], ACTB_C [CpG_6: 0.738 (0.619-0.909), P = 0.006; CpG_11.12: 0.7 45 (0.605-0.906), P=0.003; CpG_17: 0.807 (0.704-0.913), P=0.001; CpG_24: 0.786 (0.695-0.910), P=0.002; CpG_25: 0.774 (0.684-0.909), P = 0.005; CpG_34: 0.796 (0.688-0.907), P = 0.002], ACTB_D [CpG_2.3: 0.780 (0.683-0.908), P = 0.008; CpG_6: 0.775 (0 .678-0.917), P=0.004; CpG_9.10: 0.738 (0.646-0.902), P=0.004; CpG_12: 0.739 (0.656-0.901), P=0.002; C CpG_14: 0.763 (0.649-0.897), P = 0.001; CpG_17: 0.775 (0.631-0.905), P = 0.003], ACTB_E [CpG_1: 0.788 (0.672-0.906), P = 0.002; CpG_2: 0.773 (0.649-0.894), P = 0.001; CpG_3: 0.774 (0.646-0.908), P = 0.004; CpG_5: 0.779 (0.659-0.901), P = 0.003], see Table 8 for specific results. Interestingly, the methylation levels of the above CpG sites in stroke cases with clinical onset time ≤1.32 years and clinical onset time ≤1 year were more significantly different from those in controls. The methylation levels of the above CpG sites in stroke cases with clinical onset time ≤1.32 years and controls were 6 sites in ACTB_A fragment [CpG_1 (0.25 vs. 0.35), CpG_3 (0.15 vs. 0.24), CpG_5 (0.22 vs. 0.32), CpG_6 (0.20 vs. 0.30), CpG_8.9 (0.16 vs. 0.25), CpG_12 (0.34 vs. 0.43)], 5 sites in ACTB_B fragment [CpG_2. 3 (0.53 vs. 0.63), CpG_6 (0.55 vs. 0.64), CpG_8 (0.36 vs. 0.45), CpG_9 (0.25 vs. 0.35), CpG_10 (0.23 vs. 0.33)], 6 sites in the ACTB_C fragment [CpG_6 (0.26 vs. 0.35), CpG_11.12 (0.14 vs. 0.25), CpG_17 (0.40 vs. 0.50), CpG_24 (0.25 vs. 0.34 ）、CpG_25(0.28vs.0.35）、CpG_34(0.31vs.0.40)]、6 sites of ACTB_D fragment [CpG_2.3(0.37vs.0.47）、CpG_6(0.34vs.0.43）、CpG_9.10(0.26vs.0.36）、CpG_12(0.20vs.0.30）、CpG_14(0.39vs.0.51）、CpG_17(0.40vs.0.50)] and ACTB_E fragment The results of logistic regression showed that after adjusting for covariates such as leukocyte subtype ratio, gender, age, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG, the ORs (95% CIs) for each +10% methylation were ACTB_A[ CpG_1:0.610(0.506-0.747); CpG_3:0.608(0.493-0.789); CpG_5:0.611(0.500-0.779); CpG_6:0.606(0.502-0.776); CpG_8.9:0.602(0.489-0. 715);CpG_12:0.598(0.476-0.713)], ACTB_B[CpG_2.3:0.607(0.508-0.739 ; .496-0.769); CpG_11.12:0.604(0.505-0.755); CpG_17:0.607(0.504-0. 713); CpG_24:0.616(0.505-0.730); CpG_25:0.614(0.504-0.739); CpG_34:0.615(0.508-0.727)], ACTB_D[CpG_2.3:0.608(0.503-0.708); CpG_6: 0.601(0.497-0.707); CpG_9.10:0.607(0.496-0.722); CpG_12:0.609(0. 505-0.719); CpG_14: 0.613 (0.501-0.750); CpG_17: 0.615 (0.500-0.744)], ACTB_E [CpG_1: 0.611 (0.492-0.769); CpG_2: 0.613 (0.506-0.749); Cp G_3:0.606(0.503-0.738); CpG_5:0.602(0.498-0.709)], P values are all <0.001 (Table 9). The methylation levels of the above CpG sites in stroke cases with clinical onset time ≤ 1 year and controls were 6 sites in ACTB_A fragment [CpG_1 (0.18 vs. 0.35), CpG_3 (0.13 vs. 0.24), CpG_5 (0.20 vs. 0.32), CpG_6 (0.18 vs. 0.30), CpG_8.9 (0.14 vs. 0.25), CpG_12 (0.32 vs. 0.43)], 5 sites in ACTB_B fragment [CpG_2.3 ( 0.51vs.0.63)、CpG_6(0.53vs.0.64)、CpG_8(0.34vs.0.45)、CpG_9(0.23vs.0.35)、CpG_10(0.20vs.0.33)]、6 sites of ACTB_C fragment [CpG_6(0.24vs.0.35)、CpG_11.12(0.12vs.0.25)、CpG_17(0.38vs.0.50)、CpG_24(0.23vs.0.34)、 CpG_25 (0.26 vs. 0.35), CpG_34 (0.29 vs. 0.40)], 6 sites of ACTB_D fragment [CpG_2.3 (0.35 vs. 0.47), CpG_6 (0.32 vs. 0.43), CpG_9.10 (0.24 vs. 0.36), CpG_12 (0.18 vs. 0.30), CpG_14 (0.37 vs. 0.51), CpG_17 (0.38 vs. 0.50)] and 4 sites of ACTB_E fragment. The logistic regression results showed that after adjusting for covariates such as leukocyte subtype ratio, gender, age, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG, the ORs (95% CIs) for each +10% methylation were ACTB_A [Cp G_1:0.410(0.306-0.647); CpG_3:0.408(0.293-0.689); CpG_5:0.411(0.300-0.679); CpG_6:0.406(0.302-0.667); CpG_8.9:0.412(0.298-0.65 7);CpG_12:0.398(0.277-0.613)], ACTB_B[CpG_2.3:0.407(0.308-0.639) ;CpG_6:0.412(0.313-0.661);CpG_8:0.405(0.306-0.668);CpG_9:0.417(0.307-0.670);CpG_10:0.407(0.311-0.647)], ACTB_C[CpG_6:0.409(0 .296-0.639); CpG_11.12:0.404(0.305-0.655); CpG_17:0.407(0.304-0.6 13); CpG_24:0.426(0.305-0.630); CpG_25:0.424(0.304-0.639); CpG_34:0.451(0.310-0.657)], ACTB_D[CpG_2.3:0.428(0.315-0.647); CpG_6: 0.416(0.297-0.607); CpG_9.10:0.407(0.296-0.602); CpG_12:0.409(0.3 05-0.619); CpG_14: 0.424 (0.296-0.606); CpG_17: 0.415 (0.300-0.604)], ACTB_E [CpG_1: 0.411 (0.292-0.596); CpG_2: 0.413 (0.306-0.594); CpG_ 3:0.406(0.303-0.606); CpG_5:0.402(0.298-0.609)], P values are all <0.001 (Table 10).

Table 8 Comparison of methylation levels of ACTB gene CpG sites in 91 stroke cases (clinical onset time ≤ 1.5 years) and 147 controls

Note: IQR, interquartile range; OR: odds ratio; CI: confidence interval; ACTB_A: promoter region and exon 1; ACTB_B: promoter region and exon 1; ACTB_C: exon 2 and intron 2; ACTB_D: exons 3, 4, 5 and introns 3, 4, 5; ACTB_E: exon 6 and intron 6; *Adjusted for the proportion of leukocyte subtypes, sex, age, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG.

Table 9 Comparison of methylation levels of ACTB gene CpG sites in 67 stroke cases (clinical onset time ≤ 1.32 years) and 147 controls

Note: IQR, interquartile range; OR: odds ratio; CI: confidence interval; ACTB_A: promoter region and exon 1; ACTB_B: promoter region and exon 1; ACTB_C: exon 2 and intron 2; ACTB_D: exons 3, 4, 5 and introns 3, 4, 5; ACTB_E: exon 6 and intron 6; *Adjusted for the proportion of leukocyte subtypes, sex, age, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG.

Table 10 Comparison of methylation levels of CpG sites of ACTB gene in 35 stroke cases (clinical onset time ≤ 1 year) and 147 controls

Note: IQR, interquartile range; OR: odds ratio; CI: confidence interval; ACTB_A: promoter region and exon 1; ACTB_B: promoter region and exon 1; ACTB_C: exon 2 and intron 2; ACTB_D: exons 3, 4, 5 and introns 3, 4, 5; ACTB_E: exon 6 and intron 6; *Adjusted for the proportion of leukocyte subtypes, sex, age, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG.

2. Correlation analysis between ACTB methylation and clinical onset time of stroke

The correlation analysis between ACTB methylation and stroke onset time was performed on stroke cases with clinical onset time ≤ 1.5 years, 1.32 years and 1 year. The results showed that 6 sites of ACTB_A fragment (CpG_1, CpG_3, CpG_5, CpG_6, CpG_8.9, CpG_12), 5 sites of ACTB_B fragment (CpG_2.3, CpG_6, CpG_8, CpG_9, CpG_10), 6 sites of ACTB_C fragment (CpG_6, CpG_11.12, CpG_17, CpG_24, CpG_25, C The methylation levels of six sites (CpG_2.3, CpG_6, CpG_9.10, CpG_12, CpG_14, and CpG_17) in the ACTB_D fragment and four sites (CpG_1, CpG_2, CpG_3, and CpG_5) in the ACTB_E fragment were positively correlated with the onset time of stroke (Tables 11-13); especially for stroke cases with clinical onset time within 1.32 years and 1 year, the methylation levels of the above CpG sites were strongly correlated with the clinical onset time (Spearman rank correlation coefficients were all >0.534, Tables 12-13).

Table 11 Correlation between ACTB gene methylation and clinical onset time of stroke (91 stroke cases with clinical onset time ≤ 1.5 years)

Table 12 Correlation between ACTB gene methylation and clinical onset time of stroke (clinical onset time of 67 stroke cases ≤ 1.32 years)

Table 13 Correlation between ACTB gene methylation and clinical onset time of stroke (clinical onset time of 35 stroke cases ≤ 1 year)

3. Correlation between ACTB methylation and age

The association between ACTB methylation and stroke was analyzed by stratification according to the age of the subjects. The results showed that in people aged less than 65 years, 6 sites of ACTB_A fragment [CpG_1 (0.29 vs. 0.35), CpG_3 (0.21 vs. 0.27), CpG_5 (0.28 vs. 0.33), CpG_6 (0.25 vs. 0.29), CpG_8.9 (0.19 vs. 0.23), CpG_12 (0.37 vs. 0.43)], 5 sites of ACTB_B fragment [CpG_2.3 (0.56 vs. 0.64), CpG_6 (0.57 vs. 0.61), CpG_8 (0.35vs.0.48), CpG_9(0.24vs.0.35), CpG_10(0.23vs.0.34)], 6 sites in ACTB_C fragment [CpG_6(0.25vs.0.35), CpG_11.12(0.14vs.0.24), CpG_17(0.39vs.0.49), CpG_24(0.25vs.0.33), CpG_25(0.29vs.0.36), CpG_34(0.31vs.0.39)], 6 sites in ACTB_D fragment [CpG_2.3(0 The methylation levels of four sites in the ACTB_E fragment [CpG_1 (0.26 vs. 0.33), CpG_2 (0.24 vs. 0.35), CpG_3 (0.23 vs. 0.33), CpG_5 (0.32 vs. 0.41)] were significantly lower than those in the CpG_1 fragment [0.36 vs. 0.45), CpG_6 (0.32 vs. 0.45), CpG_9.10 (0.26 vs. 0.35), CpG_12 (0.18 vs. 0.29), CpG_14 (0.40 vs. 0.50), CpG_17 (0.37 vs. 0.49)] Compared with the control group, the logistic regression results showed that after adjusting for covariates such as the proportion of leukocyte subtypes, gender, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG, the ORs (95% CIs) per +10% methylation were ACTB_A [CpG_1: 0.615 (0.416-0.916), P = 0.004; CpG_3: 0.611 (0.413-0.946), P = 0.006; CpG_5: 0.592 (0.373-0.882), P = 0.001; CpG_6: 0.6 08 (0.431-0.939), P = 0.002; CpG_8.9: 0.566 (0.467-0.906), P = 0.003; CpG_12: 0.548 (0.364-0.903), P = 0.001], ACTB_B [CpG_2.3: 0.594 (0.375-0. 902), P=0.006; CpG_6:0.518(0.307-0.891), P＜0.001; CpG_8:0.517(0.302-0.889), P＜0.001; CpG_9:0.5 11 (0.315-0.891), P < 0.001; CpG_10: 0.509 (0.364-0.902), P < 0.001], ACTB_C [CpG_6: 0.518 (0.382-0.901), P = 0.002; CpG_11.12: 0.522 (0.39 2-0.909), P=0.004; CpG_17: 0.526 (0.394-0.870), P=0.002; CpG_24: 0.504 (0.342-0.876), P<0.001; CpG_25:0 .507 (0.385-0.892), P = 0.005; CpG_34: 0.506 (0.392-0.901), P = 0.001], ACTB_D [CpG_2.3: 0.538 (0.311-0.903), P = 0.002; CpG_6: 0.548 (0.346-0. 899), P < 0.001; CpG_9.10: 0.537 (0.366-0.897), P = 0.002; CpG_12: 0.546 (0.385-0.901), P = 0.001; CpG_14 :0.528(0.374-0.900), P＜0.001; CpG_17:0.537(0.358-0.903), P＝0.001], ACTB_E[CpG_1:0.557(0.366-0.913), P＝0.006; CpG_2:0.546(0.370-0.906), P＝0.005; CpG_3:0.563(0.409-0.908), P＝0.005; CpG_5:0.545(0.424-0.904), P＝0.003], the specific results are shown in Table 14.

The results of the correlation analysis between ACTB methylation and age showed that in the control population, 6 sites of ACTB_A fragment (CpG_1, CpG_3, CpG_5, CpG_6, CpG_8.9, CpG_12), 5 sites of ACTB_B fragment (CpG_2.3, CpG_6, CpG_8, CpG_9, CpG_10), and 6 sites of ACTB_C fragment (CpG_6, CpG_11.12, CpG_1 The methylation levels of six sites (CpG_2.7, CpG_24, CpG_25, CpG_34), six sites (CpG_2.3, CpG_6, CpG_9.10, CpG_12, CpG_14, CpG_17) in the ACTB_D fragment and four sites (CpG_1, CpG_2, CpG_3, CpG_5) in the ACTB_E fragment were negatively correlated with age (the absolute values of the Spearman rank correlation coefficients were all >0.501, Table 15).

Table 14 Comparison of methylation levels of ACTB gene CpG sites in stratified analysis of 139 stroke cases and 147 controls

Note: IQR, interquartile range; OR: odds ratio; CI: confidence interval; ACTB_A: promoter region and exon 1; ACTB_B: promoter region and exon 1; ACTB_C: exon 2 and intron 2; ACTB_D: exons 3, 4, 5 and introns 3, 4, 5; ACTB_E: exon 6 and intron 6; *Adjusted for the proportion of leukocyte subtypes, sex, drinking, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG.

Table 15 Correlation between ACTB gene methylation and age (147 controls)

4. Correlation between ACTB methylation and alcohol consumption

Studies have shown that in addition to genetic mechanisms, environmental factors (such as drinking) may lead to changes in DNA methylation patterns. The subjects were stratified according to their drinking status to analyze the association between ACTB methylation and stroke. The results showed that among drinkers, stroke cases had 6 sites in the ACTB_A fragment [CpG_1 (0.29 vs. 0.36), CpG_3 (0.19 vs. 0.26), CpG_5 (0.27 vs. 0.32), CpG_6 (0.24 vs. 0.30), CpG_8.9 (0.19 vs. 0.24), CpG_12 (0.34 vs. 0.44)], and 5 sites in the ACTB_B fragment [CpG_2.3 (0.58 vs. 0.68), CpG_6 (0.57 vs. 0.64), CpG_8 (0.34 vs.0.48), CpG_9 (0.25vs.0.33), CpG_10 (0.23vs.0.33)], 6 sites in ACTB_C fragment [CpG_6 (0.25vs.0.32), CpG_11.12 (0.15vs.0.23), CpG_17 (0.38vs.0.46), CpG_24 (0.25vs.0.33), CpG_25 (0.28vs.0.36), CpG_34 (0.31vs.0.40)], 6 sites in ACTB_D fragment [CpG_2.3 (0.35vs.0.32), CpG_11.12 (0.15vs.0.23), CpG_17 (0.38vs.0.46), CpG_24 (0.25vs.0.33), CpG_25 (0.28vs.0.36), CpG_34 (0.31vs.0.40)]. The methylation levels of CpG_1 (0.24 vs. 0.34), CpG_2 (0.24 vs. 0.34), CpG_3 (0.22 vs. 0.32), CpG_5 (0.31 vs. 0.41)] and four sites of ACTB_E fragment [CpG_1 (0.24 vs. 0.34), CpG_2 (0.24 vs. 0.34), CpG_3 (0.22 vs. 0.32), CpG_5 (0.31 vs. 0.41)] were significantly lower than those of the control. ; The results of logistic regression showed that after adjusting for covariates such as leukocyte subtype ratio, gender, age, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG, the ORs (95% CIs) per +10% methylation were ACTB_A [CpG_1: 0.616 (0.466-0.912), P = 0.006; CpG_3: 0.625 (0.447-0.913), P = 0.005; CpG_5: 0.619 (0.437-0.918), P = 0.006; CpG_6: 0.609 (0.413-0.938), P=0.003; CpG_8.9:0.626 (0.411-0.906), P=0.004; CpG_12: 0.609 (0.406-0.903), P=0.001], ACTB_B[CpG_2.3:0.594 (0.405-0.899 ), P＝0.001; CpG_6: 0.634 (0.437-0.911), P＝0.006; CpG_8: 0.618 (0.416-0.901), P＜0.001; CpG_9: 0.609 (0.405-0.913), P=0.001; CpG_10:0.594 (0.406-0.892), P<0.001], ACTB_C[CpG_6:0.618 (0.407-0.914), P=0.007; CpG_11.12:0.623 (0.412-0.9 08), P=0.006; CpG_17: 0.566 (0.394-0.879), P<0.001; CpG_24: 0.618 (0.424-0.913), P=0.003; CpG_25: 0. 617(0.418-0.912), P＝0.002; CpG_34:0.607(0.412-0.907), P＝0.001], ACTB_D[CpG_2.3:0.578(0.393-0.883), P＜0.001; CpG_6:0.585(0.397-0 .891), P＜0.001; CpG_9.10:0.572(0.362-0.882), P＜0.001; CpG_12:0.576(0.392-0.891), P＜0.001; CpG_14 :0.594(0.387-0.882), P＜0.001; CpG_17:0.575(0.376-0.883), P＜0.001], ACTB_E[CpG_1:0.572(0.360-0.843), P＜0.001; CpG_2:0.584(0.370-0.863), P＜0.001; CpG_3:0.594(0.377-0.855), P＜0.001; CpG_5:0.545(0.337-0.846), P＜0.001], the specific results are shown in Table 16.

The results of the correlation analysis between ACTB methylation and drinking showed that in the stroke population, 6 sites of ACTB_A fragment (CpG_1, CpG_3, CpG_5, CpG_6, CpG_8.9, CpG_12), 5 sites of ACTB_B fragment (CpG_2.3, CpG_6, CpG_8, CpG_9, CpG_10), and 6 sites of ACTB_C fragment (CpG_6, CpG_11.12, CpG_ The methylation levels of six sites (CpG_2.3, CpG_6, CpG_9.10, CpG_12, CpG_14, CpG_17, CpG_24, CpG_25, CpG_34) in the ACTB_D fragment and four sites (CpG_1, CpG_2, CpG_3, CpG_5) in the ACTB_E fragment were negatively correlated with the amount of alcohol consumed (the absolute values of the Spearman rank correlation coefficients were all >0.542, Table 17).

In order to better illustrate the relationship between methylation and drinking, we divided the population into low methylation group and high methylation group based on the median methylation of CpG sites. The results showed that 6 sites (CpG_1, CpG_3, CpG_5, CpG_6, CpG_8.9, CpG_12) of ACTB_A fragment, 5 sites (CpG_2.3, CpG_6, CpG_8, CpG_9, CpG_10) of ACTB_B fragment, and 6 sites (CpG_6, CpG_11.12, CpG_17, CpG_24, CpG_25, CpG_10) of ACTB_C fragment were significantly higher than those of ACTB_A fragment. Among the people with low methylation of 6 sites (CpG_2.3, CpG_6, CpG_9.10, CpG_12, CpG_14, CpG_17) in ACTB_D fragment and 4 sites (CpG_1, CpG_2, CpG_3, CpG_5) in ACTB_E fragment, drinking alcohol increased the risk of stroke compared with non-drinking (OR values were all >1.287, P values were all <0.007, Table 18).

In addition, this study evaluated the joint effect of the above CpG methylation levels (low vs. high) and drinking (yes vs. no) on stroke, and used the high methylation, non-drinking group as the reference group to evaluate the methylation level, drinking and their interaction. The results showed that 6 sites of ACTB_A fragment (CpG_1, CpG_3, CpG_5, CpG_6, CpG_8.9, CpG_12), 5 sites of ACTB_B fragment (CpG_2.3, CpG_6, CpG_8, CpG_9, CpG_10), 6 sites of ACTB_C fragment (CpG_6, CpG_11.12, CpG_17, CpG_24, CpG_ There was a synergistic effect between hypomethylation of 6 sites (CpG_2.3, CpG_6, CpG_9.10, CpG_12, CpG_14, CpG_17) in ACTB_D fragment and 4 sites (CpG_1, CpG_2, CpG_3, CpG_5) in ACTB_E fragment and drinking (OR interaction was all >2.618, P values were all <0.001, Table 19).

The above results suggest that drinking may lead to stroke by affecting the methylation level of ACTB gene. Drinking is one of the most common lifestyle habits among Chinese people. Combined with the results of this study, quitting drinking may significantly reduce the risk of stroke.

Table 16 Comparison of methylation levels of ACTB gene CpG sites in 139 stroke cases and 147 controls according to whether or not they drank alcohol

Note: IQR, interquartile range; OR: odds ratio; CI: confidence interval; ACTB_A: promoter region and exon 1; ACTB_B: promoter region and exon 1; ACTB_C: exon 2 and intron 2; ACTB_D: exons 3, 4, 5 and introns 3, 4, 5; ACTB_E: exon 6 and intron 6; *Adjusted for the proportion of leukocyte subtypes, sex, age, smoking, BMI, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG.

Table 17 Correlation between ACTB gene methylation and drinking (139 cases)

Table 18 Relationship between drinking and stroke at different methylation levels

Table 19 Combined effects of methylation and drinking on stroke

5. The value of ACTB gene methylation in early warning and early diagnosis of stroke

The mathematical model for assisting stroke diagnosis established by the present invention can achieve the following purposes:

(1) Distinguish between stroke patients and non-stroke controls;

(2) Provide early warning of stroke.

The mathematical model is established as follows:

(A) Data source: Methylation levels of target CpG sites (a combination of one or more of those in Tables 1-5) in ex vivo blood samples of 139 patients with new stroke within 2 years after enrollment in the community cohort listed in step 1 and 147 patients who did not develop stroke during follow-up (detection method is the same as step 2).

The data can be added with known parameters such as age, gender, white blood cell count, body mass index, smoking, drinking, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG according to actual needs to improve the discrimination efficiency.

(B) Model building

According to the need, any two different types of patient data, namely the training set (for example: stroke patients with onset time <2 years and controls, stroke patients with onset time ≤1.5 years and controls, stroke patients with onset time ≤1.32 years and controls, stroke patients with onset time ≤1 year and controls, stroke patients with age <65 years and controls <65 years, stroke patients with age ≥65 years and controls with age ≥65 years, stroke patients who drink alcohol and controls who drink alcohol, stroke patients who do not drink alcohol and controls who do not drink alcohol) are selected as the data for building the model, and the mathematical model is established by formula using the statistical method of binary logistic regression using statistical software such as SAS, R, and SPSS. The value corresponding to the maximum Youden index calculated by the mathematical model formula is the threshold value or 0.5 is directly set as the threshold value. After the test sample is tested and substituted into the model calculation, the detection index obtained is greater than the threshold value and is classified into one category (category B), less than the threshold value and is classified into another category (category A), and equal to the threshold value as an uncertain gray area. When predicting a new sample to be tested to determine which category it belongs to, firstly, the methylation level of one or more CpG sites on the ACTB gene of the sample to be tested is detected by a DNA methylation determination method, and then the data of these methylation levels are substituted into the above-mentioned mathematical model to calculate the detection index corresponding to the sample to be tested, and then the detection index corresponding to the sample to be tested is compared with the threshold, and the category of the sample to be tested is determined according to the comparison result.

For example: The data of the methylation level of a single CpG site of the ACTB gene in the training set or the methylation level of a combination of multiple CpG sites are used to establish a mathematical model for distinguishing between Class A and Class B using a binary logistic regression formula using statistical software such as SAS, R, and SPSS. The mathematical model is a binary logistic regression model, specifically: log(y/(1-y))=b0+b1x1+b2x2+b3x3+…+bnXn, where y is the dependent variable, i.e., the detection index obtained after substituting the methylation value of one or more methylation sites of the sample to be tested into the model, b0 is a constant, x1~xn are independent variables, i.e., the methylation value of one or more methylation sites of the test sample (each value is a value between 0 and 1), and b1~bn are the weights assigned to the methylation value of each site by the model. In specific applications, a mathematical model is first established based on the methylation degree (x1~xn) of one or more DNA methylation sites of the samples that have been tested in the training set and their known classification (class A or class B, y is assigned 0 and 1 respectively), thereby determining the constant b0 of the mathematical model and the weights b1~bn of each methylation site, and the numerical value corresponding to the maximum Youden index calculated by the mathematical model is used as the threshold or 0.5 is directly set as the threshold for division. The detection index obtained after the test sample is tested and substituted into the model calculation, that is, the y value is greater than the threshold and is classified as class B, less than the threshold and classified as class A, and equal to the threshold as an uncertain gray area. Among them, class A and class B are two corresponding categories (the grouping of the two categories, which group is class A and which group is class B, should be determined according to the specific mathematical model, and no agreement is made here). When predicting the sample of the subject to determine which category it belongs to, first collect the blood of the subject, and then extract DNA from it. After the extracted DNA is converted by bisulfite, the methylation level of a single CpG site of the subject's ACTB gene or the methylation level of a combination of multiple CpG sites is detected by a DNA methylation determination method, and then the methylation data obtained by the detection is substituted into the above-mentioned mathematical model. If the value calculated by substituting the methylation level of one or more CpG sites of the subject's ACTB gene into the above-mentioned mathematical model, i.e., the detection index, is greater than the threshold value, the subject is determined to belong to the same category (category B) as the subjects in the training set whose detection index is greater than the threshold value; if the value calculated by substituting the methylation level data of one or more CpG sites of the subject's ACTB gene into the above-mentioned mathematical model, i.e., the detection index, is less than the threshold value, the subject is determined to belong to the same category (category A) as the subjects in the training set whose detection index is less than the threshold value; if the value calculated by substituting the methylation level data of one or more CpG sites of the subject's ACTB gene into the above-mentioned mathematical model, i.e., the detection index, is equal to the threshold value, it cannot be determined whether the subject is in category A or category B.

Example: The methylation of all CpG sites of ACTB_D (ACTB_D_2.3, ACTB_D_4.5, ACTB_D_6, ACTB_D_7.8, ACTB_D_9.10, ACTB_D_11, ACTB_D_12, ACTB_D_14, ACTB_D_15.16, ACTB_D_17 and ACTB_D_18) and the application of mathematical modeling in detecting stroke patients 2 years in advance (early warning of stroke): the training set of stroke patients with onset time less than 2 years and controls (here: 139 stroke patients with onset time less than 2 years and 147 controls) are used. The data on the methylation levels of all CpG sites of ACTB_D that have been detected in the experiment, as well as the patients' age, gender (male was assigned a value of 1, female was assigned a value of 0), white blood cell count, body mass index, smoking (smoking was assigned a value of 1, non-smoking was assigned a value of 0), drinking (drinking was assigned a value of 1, non-drinking was assigned a value of 0), history of hypertension (history of hypertension was assigned a value of 1, no history of hypertension was assigned a value of 0), history of diabetes (history of diabetes was assigned a value of 1, no history of diabetes was assigned a value of 0), HDL-C, LDL-C, TC and TG were used to establish a mathematical model for detecting stroke patients 2 years in advance (early warning of stroke) using the formula of binary logistic regression using SPSS software or R software. The mathematical model here is a two-class logistic regression model, which determines the constant b0 of the mathematical model and the weights b1~bn of each methylation site, which are specifically as follows in this example: log(y/(1-y))=-2.937-0.810*ACTB_D_2.3+0.916*ACTB_D_4.5-1.573*ACTB_D_6-3.181*ACTB_D_7.8+0.931*ACTB_D_9.10+0.882*ACTB_D_11+3.763*ACTB_D_12-2.570*ACTB_D_14+1.142*ACTB_D_15.16+0.221*ACTB_D_17+1.285*ACTB_D_18+0.013*age-0.072*gender (male is assigned 1, female is assigned to 0)+0.302*number of white blood cells+0.034*body mass index+0.025*smoking (smoking is assigned to 1, non-smoking is assigned to 0)-0.055*drinking (drinking is assigned to 1, non-drinking is assigned to 0)+0.035*history of hypertension (history of hypertension is assigned to 1, no history of hypertension is assigned to 0)-0.030*(history of diabetes is assigned to 1, no history of diabetes is assigned to 0)+0.009*HDL-C+0.351*LDL-C-0.170*TC-0.013*TG, where y is the dependent variable, that is, the methylation value of all CpG sites of ACTB_D of the sample to be tested, as well as age, gender, white blood cell count, body mass index, smoking, drinking, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG are substituted into the model to obtain the detection index. The diagnostic threshold (0.36) obtained by the maximum Youden index, the methylation level of all CpG sites of ACTB_D of the sample to be tested is substituted into the model for calculation together with the information of age, gender, white blood cell count, body mass index, smoking, drinking, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG. The detection index obtained, that is, the y value less than the threshold is classified as a stroke patient, greater than the threshold is classified as a non-stroke control, and equal to the threshold, it is uncertain whether it is a stroke patient or a control. The area under the curve (AUC) of this model is calculated as 0.76 (Table 20). The specific subject judgment method is exemplified as follows, blood is collected from two subjects (A, B) to extract DNA, and the extracted DNA is converted by bisulfite, and the methylation level of all CpG sites of ACTB_D of the subject is detected by the DNA methylation determination method. Then the methylation level data obtained by the test were substituted into the above mathematical model together with the subject's age, gender, white blood cell count, body mass index, smoking, drinking, history of hypertension, history of diabetes, HDL-C, LDL-C, TC and TG information. If the value calculated by the mathematical model for subject A is 0.35 less than 0.36, then subject A is determined to be a stroke patient; if the methylation level data of all CpG sites of ACTB_D of subject B are substituted into the above mathematical model and the calculated value is 0.58 greater than 0.36, then subject B is determined to have no stroke.

(C) Model effect evaluation

According to the above method, mathematical models for detecting stroke patients 1 year, 1.32 years, 1.5 years and 2 years in advance were established, and their effectiveness was evaluated by receiver operating characteristic curve (ROC curve). The larger the area under the curve (AUC) obtained by the ROC curve, the better the discrimination of the model and the more effective the molecular marker. The evaluation results after the mathematical model was constructed using different CpG sites are shown in Table 20. In Table 20, 1 CpG site represents the site of any CpG site in the ACTB_A/ACTB_B/ACTB_C/ACTB_D/ACTB_E amplified fragment, 2 CpG sites represent the combination of any 2 CpG sites in ACTB_A/ACTB_B/ACTB_C/ACTB_D/ACTB_E, 3 CpG sites represent the combination of any 3 CpG sites in ACTB_A/ACTB_B/ACTB_C/ACTB_D/ACTB_E, and so on. The values in the table are the range values of the evaluation results of different site combinations (that is, the results of any combination of CpG sites are within this range).

The results of this study showed that the areas under the ROC curve of ACTB gene methylation (all CpG sites) for early detection of stroke were 0.91, 0.89, 0.85, and 0.81, respectively, for 1 year, 1.32 years, 1.5 years, and 2 years, respectively. The sensitivities corresponding to the diagnostic thresholds obtained by the maximum Youden index were 86.2%, 85.3%, 83.3%, and 79.1%, respectively, and the specificities were 90.2%, 86.8%, 85.9%, and 80.2%, respectively, indicating that ACTB gene methylation has a good warning and early diagnosis effect on stroke. In addition, we further analyzed the diagnostic value of ACTB gene methylation for stroke in different ages and drinking status. The results showed that the areas under the ROC curve of ACTB gene methylation (all CpG sites) for diagnosing stroke in people aged <65 years and ≥65 years were 0.88 and 0.79, and the corresponding sensitivities of the diagnostic thresholds obtained by the maximum Youden index were 84.6% and 79.8%, and the specificities were 88.4% and 80.1%; the areas under the ROC curve of ACTB gene methylation (all CpG sites) for diagnosing stroke in drinking and non-drinking status were 0.88 and 0.80, and the corresponding sensitivities of the diagnostic thresholds obtained by the maximum Youden index were 83.6% and 78.6%, and the specificities were 87.1% and 80.3%, indicating that ACTB gene methylation has a better diagnostic effect on stroke in people under 65 years old and drinkers (Table 20).

Table 20 Value of ACTB gene methylation for early warning and early diagnosis of stroke

<110> Nanjing Medical University

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Claims (22)

1. Use of methylated ACTB gene as a marker in the preparation of a product; the product has any of the following functions: (1) Assist in the diagnosis of stroke; (2) Warning of stroke before clinical symptoms occur. 2. The use according to claim 1, characterized in that: the methylated ACTB gene is the methylation of all or part of the CpG sites in the fragments shown in the following (e1)-(e5) in the ACTB gene; (e1) the DNA fragment shown in SEQ ID No. 1; (e2) the DNA fragment shown in SEQ ID No. 2; (e3) the DNA fragment shown in SEQ ID No. 3; (e4) the DNA fragment shown in SEQ ID No. 4; (e5) The DNA fragment shown by SEQ ID No.5. 3. The use according to claim 2, characterized in that: the "all or part of the CpG sites" are any of the following: (f1) the CpG site at positions 128-129 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 180-181 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 231-232 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 313-314 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 362-363 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 367-368 from the 5' end of the DNA fragment shown in SEQ ID No.1, or the CpG site at positions 428-429 from the 5' end of the DNA fragment shown in SEQ ID No.1; (f2) the CpG site at positions 53-54 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 57-58 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 125-126 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 232-233 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 260-261 from the 5' end of the DNA fragment shown in SEQ ID No.2, or the CpG site at positions 283-284 from the 5' end of the DNA fragment shown in SEQ ID No.2; (f3) the CpG site at positions 61-62 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 87-88 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 103-104 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 147-148 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 171-172 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 186-187 from the 5' end of the DNA fragment shown in SEQ ID No.3, or the CpG site at positions 238-239 from the 5' end of the DNA fragment shown in SEQ ID No.3; (f4) the CpG site at positions 39-40 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 41-42 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 69-70 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 107-108 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 110-111 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 139-140 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 185-186 from the 5' end of the DNA fragment shown in SEQ ID No.4, or the CpG site at positions 275-276 from the 5' end of the DNA fragment shown in SEQ ID No.4; (f5) the CpG site at positions 44-45 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 175-176 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 266-267 from the 5' end of the DNA fragment shown in SEQ ID No.5, or the CpG site at positions 300-301 from the 5' end of the DNA fragment shown in SEQ ID No.5; (f6) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2; (f7) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f8) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f9) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f10) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f11) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f12) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f13) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f14) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f15) 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f16) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f17) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f18) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f19) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f20) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f21) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f22) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f23) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f24) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f25) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f26) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f27) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f28) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f29) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f30) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; In (f6)-(f30), the 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.1 are: the CpG site shown at positions 128-129 from the 5' end of SEQ ID No.1; the CpG site shown at positions 180-181; the CpG site shown at positions 203-204; the CpG site shown at positions 231-232; the CpG site shown at positions 313-314; the CpG site shown at positions 338-339; the CpG sites shown at positions 362-363 and 367-368; the CpG site shown at positions 406-407; and the CpG site shown at positions 428-429; The 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 are: the CpG sites shown at positions 53-54 and 57-58 from the 5' end of SEQ ID No. 2; the CpG sites shown at positions 96-97 and 101-102; the CpG site shown at positions 125-126; the CpG site shown at positions 232-233; the CpG site shown at positions 260-261; the CpG site shown at positions 283-284; and the CpG site shown at positions 335-336; The 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.3 are the CpG sites shown at positions 25-26, 27-28, 29-30, 32-33 and 45-46 from the 5' end of SEQ ID No.3; the CpG site shown at positions 61-62; the CpG site shown at positions 63-64, 66-67 and 81-82; the CpG site shown at positions 87-88 and 103-104; the CpG site shown at positions 105-106, 109-110 and 119-120; the CpG site shown at positions 147 -148; CpG sites shown at positions 149-150 and 165-166; CpG sites shown at positions 171-172; CpG sites shown at positions 186-187; CpG sites shown at positions 192-193, 194-195, 198-199, and 201-202; CpG sites shown at positions 211-212 and 216-217; CpG sites shown at positions 238-239; The 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.4 are the CpG sites shown at positions 39-40 and 41-42 from the 5' end of SEQ ID No.4; the CpG sites shown at positions 61-62 and 65-66; the CpG sites shown at positions 69-70; the CpG sites shown at positions 77-78 and 81-82; the CpG sites shown at positions 107-108 and 110-111; the CpG sites shown at positions 122-123; the CpG sites shown at positions 139-140; the CpG sites shown at positions 185-186; the CpG sites shown at positions 213-214 and 219-220; the CpG sites shown at positions 275-276; and the CpG sites shown at positions 304-305; The five distinguishable CpG sites of the DNA fragment shown in SEQ ID No.5 are: the CpG sites shown at positions 44-45 from the 5' end of SEQ ID No.5; the CpG sites shown at positions 175-176; the CpG sites shown at positions 266-267; the CpG sites shown at positions 292-293; and the CpG sites shown at positions 300-301. 4. Use of a substance for detecting the methylation level of the ACTB gene and a medium storing a mathematical model in preparing a product; the product has any of the following functions: (1) Assist in the diagnosis of stroke; (2) Warning of stroke before clinical symptoms occur; The mathematical model is obtained according to a method comprising the following steps: (A1) The methylation levels of ACTB gene were detected in n1 stroke samples and n2 control samples; (A2) taking the ACTB gene methylation level data of all samples obtained in step (A1), and establishing a mathematical model by binary logistic regression method according to the classification of stroke samples and control samples; The method for using the mathematical model comprises the following steps: (B1) detecting the methylation level of the ACTB gene of the sample to be tested; (B2) Substituting the ACTB gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index and the threshold, and determining whether the sample to be tested is from or is a candidate to be from a stroke patient based on the comparison result. 5. Use of a medium storing a mathematical model in the preparation of a product; the product having any of the following functions: (1) Assist in the diagnosis of stroke; (2) Warning of stroke before clinical symptoms occur; The mathematical model is obtained according to a method comprising the following steps: (A1) The methylation levels of ACTB gene were detected in n1 stroke samples and n2 control samples; (A2) taking the ACTB gene methylation level data of all samples obtained in step (A1), and establishing a mathematical model by binary logistic regression method according to the classification of stroke samples and control samples; The method for using the mathematical model comprises the following steps: (B1) detecting the methylation level of the ACTB gene of the sample to be tested; (B2) Substituting the ACTB gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index and the threshold, and determining whether the sample to be tested is from or is a candidate to be from a stroke patient based on the comparison result. 6. The use according to claim 4 or 5, characterized in that: the methylation level of the ACTB gene is the methylation level of all or part of the CpG sites in the fragments shown in the following (e1)-(e5) in the ACTB gene; (e1) the DNA fragment shown in SEQ ID No. 1; (e2) the DNA fragment shown in SEQ ID No. 2; (e3) the DNA fragment shown in SEQ ID No. 3; (e4) the DNA fragment shown in SEQ ID No. 4; (e5) The DNA fragment shown by SEQ ID No.5. 7. The use according to claim 6, characterized in that: the "all or part of the CpG sites" are any of the following: (f1) the CpG site at positions 128-129 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 180-181 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 231-232 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 313-314 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 362-363 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 367-368 from the 5' end of the DNA fragment shown in SEQ ID No.1, or the CpG site at positions 428-429 from the 5' end of the DNA fragment shown in SEQ ID No.1; (f2) the CpG site at positions 53-54 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 57-58 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 125-126 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 232-233 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 260-261 from the 5' end of the DNA fragment shown in SEQ ID No.2, or the CpG site at positions 283-284 from the 5' end of the DNA fragment shown in SEQ ID No.2; (f3) the CpG site at positions 61-62 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 87-88 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 103-104 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 147-148 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 171-172 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 186-187 from the 5' end of the DNA fragment shown in SEQ ID No.3, or the CpG site at positions 238-239 from the 5' end of the DNA fragment shown in SEQ ID No.3; (f4) the CpG site at positions 39-40 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 41-42 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 69-70 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 107-108 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 110-111 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 139-140 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 185-186 from the 5' end of the DNA fragment shown in SEQ ID No.4, or the CpG site at positions 275-276 from the 5' end of the DNA fragment shown in SEQ ID No.4; (f5) the CpG site at positions 44-45 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 175-176 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 266-267 from the 5' end of the DNA fragment shown in SEQ ID No.5, or the CpG site at positions 300-301 from the 5' end of the DNA fragment shown in SEQ ID No.5; (f6) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2; (f7) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f8) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f9) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f10) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f11) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f12) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f13) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f14) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f15) 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f16) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f17) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f18) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f19) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f20) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f21) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f22) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f23) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f24) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f25) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f26) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f27) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f28) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f29) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f30) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; In (f6)-(f30), the 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.1 are: the CpG site shown at positions 128-129 from the 5' end of SEQ ID No.1; the CpG site shown at positions 180-181; the CpG site shown at positions 203-204; the CpG site shown at positions 231-232; the CpG site shown at positions 313-314; the CpG site shown at positions 338-339; the CpG sites shown at positions 362-363 and 367-368; the CpG site shown at positions 406-407; and the CpG site shown at positions 428-429; The 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 are: the CpG sites shown at positions 53-54 and 57-58 from the 5' end of SEQ ID No. 2; the CpG sites shown at positions 96-97 and 101-102; the CpG site shown at positions 125-126; the CpG site shown at positions 232-233; the CpG site shown at positions 260-261; the CpG site shown at positions 283-284; and the CpG site shown at positions 335-336; The 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.3 are the CpG sites shown at positions 25-26, 27-28, 29-30, 32-33 and 45-46 from the 5' end of SEQ ID No.3; the CpG site shown at positions 61-62; the CpG site shown at positions 63-64, 66-67 and 81-82; the CpG site shown at positions 87-88 and 103-104; the CpG site shown at positions 105-106, 109-110 and 119-120; the CpG site shown at positions 147 -148; CpG sites shown at positions 149-150 and 165-166; CpG sites shown at positions 171-172; CpG sites shown at positions 186-187; CpG sites shown at positions 192-193, 194-195, 198-199, and 201-202; CpG sites shown at positions 211-212 and 216-217; CpG sites shown at positions 238-239; The 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.4 are the CpG sites shown at positions 39-40 and 41-42 from the 5' end of SEQ ID No.4; the CpG sites shown at positions 61-62 and 65-66; the CpG sites shown at positions 69-70; the CpG sites shown at positions 77-78 and 81-82; the CpG sites shown at positions 107-108 and 110-111; the CpG sites shown at positions 122-123; the CpG sites shown at positions 139-140; the CpG sites shown at positions 185-186; the CpG sites shown at positions 213-214 and 219-220; the CpG sites shown at positions 275-276; and the CpG sites shown at positions 304-305; The five distinguishable CpG sites of the DNA fragment shown in SEQ ID No.5 are: the CpG sites shown at positions 44-45 from the 5' end of SEQ ID No.5; the CpG sites shown at positions 175-176; the CpG sites shown at positions 266-267; the CpG sites shown at positions 292-293; and the CpG sites shown at positions 300-301. 8. The use according to claim 4, characterized in that: the material for detecting the methylation level of the ACTB gene comprises a primer combination for amplifying the full length or partial fragment of the ACTB gene. 9. The use according to claim 8, characterized in that the partial fragment is at least one of the following fragments: (g1) a DNA fragment represented by SEQ ID No. 1 or a DNA fragment contained therein; (g2) the DNA fragment shown in SEQ ID No. 2 or a DNA fragment contained therein; (g3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein; (g4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment contained therein; (g5) The DNA fragment shown by SEQ ID No. 5 or a DNA fragment contained therein. 10. The use according to claim 8, characterized in that: the primer combination is primer pair A and/or primer pair B and/or primer pair C and/or primer pair D and/or primer pair E; The primer pair A is a primer pair consisting of primer A1 and primer A2; the primer A1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No.6; the primer A2 is a single-stranded DNA represented by nucleotides 32 to 58 of SEQ ID No.7 or SEQ ID No.7; The primer pair B is a primer pair consisting of primer B1 and primer B2; the primer B1 is a single-stranded DNA represented by nucleotides 11 to 34 of SEQ ID No.8; the primer B2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No.9 or SEQ ID No.9; The primer pair C is a primer pair consisting of primer C1 and primer C2; the primer C1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No. 10; the primer C2 is a single-stranded DNA represented by nucleotides 32 to 51 of SEQ ID No. 11 or SEQ ID No. 11; The primer pair D is a primer pair consisting of primer D1 and primer D2; the primer D1 is a single-stranded DNA represented by nucleotides 11 to 37 of SEQ ID No. 12; the primer D2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No. 13 or SEQ ID No. 13; The primer pair E is a primer pair consisting of primer E1 and primer E2; the primer E1 is a single-stranded DNA represented by nucleotides 11-37 of SEQ ID No.14; the primer E2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.15 or SEQ ID No.15. 11. A kit comprising a substance for detecting the methylation level of ACTB gene; the kit is used for at least one of the following purposes: (1) Assist in the diagnosis of stroke; (2) Warning of stroke before clinical symptoms occur; The kit also contains the medium storing the mathematical model as described in claim 3 or 4. 12. The kit according to claim 11, characterized in that: the methylation level of the ACTB gene is the methylation level of all or part of the CpG sites in the fragments shown in (e1)-(e5) in the ACTB gene; (e1) the DNA fragment shown in SEQ ID No. 1; (e2) the DNA fragment shown in SEQ ID No. 2; (e3) the DNA fragment shown in SEQ ID No. 3; (e4) the DNA fragment shown in SEQ ID No. 4; (e5) The DNA fragment shown by SEQ ID No.5. 13. The kit according to claim 12, characterized in that: the "all or part of the CpG sites" are any of the following: (f1) the CpG site at positions 128-129 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 180-181 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 231-232 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 313-314 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 362-363 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 367-368 from the 5' end of the DNA fragment shown in SEQ ID No.1, or the CpG site at positions 428-429 from the 5' end of the DNA fragment shown in SEQ ID No.1; (f2) the CpG site at positions 53-54 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 57-58 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 125-126 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 232-233 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 260-261 from the 5' end of the DNA fragment shown in SEQ ID No.2, or the CpG site at positions 283-284 from the 5' end of the DNA fragment shown in SEQ ID No.2; (f3) the CpG site at positions 61-62 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 87-88 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 103-104 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 147-148 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 171-172 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 186-187 from the 5' end of the DNA fragment shown in SEQ ID No.3, or the CpG site at positions 238-239 from the 5' end of the DNA fragment shown in SEQ ID No.3; (f4) the CpG site at positions 39-40 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 41-42 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 69-70 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 107-108 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 110-111 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 139-140 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 185-186 from the 5' end of the DNA fragment shown in SEQ ID No.4, or the CpG site at positions 275-276 from the 5' end of the DNA fragment shown in SEQ ID No.4; (f5) the CpG site at positions 44-45 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 175-176 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 266-267 from the 5' end of the DNA fragment shown in SEQ ID No.5, or the CpG site at positions 300-301 from the 5' end of the DNA fragment shown in SEQ ID No.5; (f6) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2; (f7) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f8) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f9) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f10) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f11) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f12) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f13) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f14) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f15) 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f16) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f17) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f18) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f19) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f20) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f21) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f22) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f23) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f24) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f25) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f26) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f27) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f28) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f29) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f30) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; In (f6)-(f30), the 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.1 are: the CpG site shown at positions 128-129 from the 5' end of SEQ ID No.1; the CpG site shown at positions 180-181; the CpG site shown at positions 203-204; the CpG site shown at positions 231-232; the CpG site shown at positions 313-314; the CpG site shown at positions 338-339; the CpG sites shown at positions 362-363 and 367-368; the CpG site shown at positions 406-407; and the CpG site shown at positions 428-429; The 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 are: the CpG sites shown at positions 53-54 and 57-58 from the 5' end of SEQ ID No. 2; the CpG sites shown at positions 96-97 and 101-102; the CpG site shown at positions 125-126; the CpG site shown at positions 232-233; the CpG site shown at positions 260-261; the CpG site shown at positions 283-284; and the CpG site shown at positions 335-336; The 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.3 are the CpG sites shown at positions 25-26, 27-28, 29-30, 32-33 and 45-46 from the 5' end of SEQ ID No.3; the CpG site shown at positions 61-62; the CpG site shown at positions 63-64, 66-67 and 81-82; the CpG site shown at positions 87-88 and 103-104; the CpG site shown at positions 105-106, 109-110 and 119-120; the CpG site shown at positions 147 -148; CpG sites shown at positions 149-150 and 165-166; CpG sites shown at positions 171-172; CpG sites shown at positions 186-187; CpG sites shown at positions 192-193, 194-195, 198-199, and 201-202; CpG sites shown at positions 211-212 and 216-217; CpG sites shown at positions 238-239; The 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.4 are the CpG sites shown at positions 39-40 and 41-42 from the 5' end of SEQ ID No.4; the CpG sites shown at positions 61-62 and 65-66; the CpG sites shown at positions 69-70; the CpG sites shown at positions 77-78 and 81-82; the CpG sites shown at positions 107-108 and 110-111; the CpG sites shown at positions 122-123; the CpG sites shown at positions 139-140; the CpG sites shown at positions 185-186; the CpG sites shown at positions 213-214 and 219-220; the CpG sites shown at positions 275-276; and the CpG sites shown at positions 304-305; The five distinguishable CpG sites of the DNA fragment shown in SEQ ID No.5 are: the CpG sites shown at positions 44-45 from the 5' end of SEQ ID No.5; the CpG sites shown at positions 175-176; the CpG sites shown at positions 266-267; the CpG sites shown at positions 292-293; and the CpG sites shown at positions 300-301. 14. The kit according to claim 11, characterized in that: the material for detecting the methylation level of the ACTB gene comprises a primer combination for amplifying the full length or partial fragment of the ACTB gene. 15. The kit according to claim 14, characterized in that: the partial fragment is at least one of the following fragments: (g1) the DNA fragment shown in SEQ ID No. 1 or a DNA fragment contained therein; (g2) the DNA fragment shown in SEQ ID No. 2 or a DNA fragment contained therein; (g3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein; (g4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment contained therein; (g5) The DNA fragment shown by SEQ ID No. 5 or a DNA fragment contained therein. 16. The kit according to claim 14, characterized in that: the primer combination is primer pair A and/or primer pair B and/or primer pair C and/or primer pair D and/or primer pair E; the primer pair A is a primer pair consisting of primer A1 and primer A2; the primer A1 is a single-stranded DNA represented by SEQ ID No.6 or nucleotides 11-35 of SEQ ID No.6; the primer A2 is a single-stranded DNA represented by SEQ ID No.7 or nucleotides 32-58 of SEQ ID No.7; The primer pair B is a primer pair consisting of primer B1 and primer B2; the primer B1 is a single-stranded DNA represented by nucleotides 11 to 34 of SEQ ID No.8; the primer B2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No.9 or SEQ ID No.9; The primer pair C is a primer pair consisting of primer C1 and primer C2; the primer C1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No. 10; the primer C2 is a single-stranded DNA represented by nucleotides 32 to 51 of SEQ ID No. 11 or SEQ ID No. 11; The primer pair D is a primer pair consisting of primer D1 and primer D2; the primer D1 is a single-stranded DNA represented by nucleotides 11 to 37 of SEQ ID No. 12; the primer D2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No. 13 or SEQ ID No. 13; The primer pair E is a primer pair consisting of primer E1 and primer E2; the primer E1 is a single-stranded DNA represented by nucleotides 11-37 of SEQ ID No.14; the primer E2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.15 or SEQ ID No.15. 17. Systems, including: (D1) Reagents and/or instruments for detecting the methylation level of ACTB gene; (D2) a device comprising a unit A and a unit B; The unit A is used to establish a mathematical model, including a data acquisition module, a data analysis and processing module and a model output module; The data acquisition module is used to acquire (D1) the ACTB gene methylation level data of n1 stroke samples and n2 control samples detected; The data analysis and processing module can establish a mathematical model through a binary logistic regression method based on the ACTB gene methylation level data of n1 stroke samples and n2 control samples collected by the data collection module according to the classification method of the stroke samples and the control samples; The model output module is used to output the mathematical model established by the data analysis and processing module; The unit B is used to determine whether the sample to be tested is from or is a candidate for being from a stroke patient, and includes a data input module, a data calculation module, a data comparison module and a conclusion output module; The data input module is used to input (D1) the ACTB gene methylation level data of the subject to be tested obtained by detection; The data calculation module is used to substitute the ACTB gene methylation level data of the subject into the mathematical model to calculate the detection index; The data comparison module is used to compare the detection index with a threshold value; The conclusion output module is used to output a conclusion of whether the sample to be tested comes from or is a candidate to come from a stroke patient according to the comparison result of the data comparison module. 18. The system according to claim 17, characterized in that: the ACTB gene methylation level is the methylation level of all or part of the CpG sites in the fragments shown in (e1)-(e5) in the ACTB gene; (e1) the DNA fragment shown in SEQ ID No. 1; (e2) the DNA fragment shown in SEQ ID No. 2; (e3) the DNA fragment shown in SEQ ID No. 3; (e4) the DNA fragment shown in SEQ ID No. 4; (e5) The DNA fragment shown by SEQ ID No.5. 19. The system according to claim 18, wherein the "all or part of the CpG sites" are any of the following: (f1) the CpG site at positions 128-129 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 180-181 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 231-232 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 313-314 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 362-363 from the 5' end of the DNA fragment shown in SEQ ID No.1, the CpG site at positions 367-368 from the 5' end of the DNA fragment shown in SEQ ID No.1, or the CpG site at positions 428-429 from the 5' end of the DNA fragment shown in SEQ ID No.1; (f2) the CpG site at positions 53-54 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 57-58 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 125-126 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 232-233 from the 5' end of the DNA fragment shown in SEQ ID No.2, the CpG site at positions 260-261 from the 5' end of the DNA fragment shown in SEQ ID No.2, or the CpG site at positions 283-284 from the 5' end of the DNA fragment shown in SEQ ID No.2; (f3) the CpG site at positions 61-62 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 87-88 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 103-104 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 147-148 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 171-172 from the 5' end of the DNA fragment shown in SEQ ID No.3, the CpG site at positions 186-187 from the 5' end of the DNA fragment shown in SEQ ID No.3, or the CpG site at positions 238-239 from the 5' end of the DNA fragment shown in SEQ ID No.3; (f4) the CpG site at positions 39-40 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 41-42 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 69-70 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 107-108 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 110-111 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 139-140 from the 5' end of the DNA fragment shown in SEQ ID No.4, the CpG site at positions 185-186 from the 5' end of the DNA fragment shown in SEQ ID No.4, or the CpG site at positions 275-276 from the 5' end of the DNA fragment shown in SEQ ID No.4; (f5) the CpG site at positions 44-45 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 175-176 from the 5' end of the DNA fragment shown in SEQ ID No.5, the CpG site at positions 266-267 from the 5' end of the DNA fragment shown in SEQ ID No.5, or the CpG site at positions 300-301 from the 5' end of the DNA fragment shown in SEQ ID No.5; (f6) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2; (f7) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f8) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f9) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f10) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f11) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f12) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f13) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f14) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f15) 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4 and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f16) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3; (f17) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f18) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f19) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f20) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f21) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f22) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f23) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f24) 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f25) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, and 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4; (f26) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f27) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 2, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f28) 9 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 1, 12 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown by SEQ ID No. 5; (f29) 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; (f30) 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 1, 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2, 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 3, 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 4, and 5 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 5; In (f6)-(f30), the 9 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.1 are: the CpG site shown at positions 128-129 from the 5' end of SEQ ID No.1; the CpG site shown at positions 180-181; the CpG site shown at positions 203-204; the CpG site shown at positions 231-232; the CpG site shown at positions 313-314; the CpG site shown at positions 338-339; the CpG sites shown at positions 362-363 and 367-368; the CpG site shown at positions 406-407; and the CpG site shown at positions 428-429; The 7 distinguishable CpG sites of the DNA fragment shown in SEQ ID No. 2 are: the CpG sites shown at positions 53-54 and 57-58 from the 5' end of SEQ ID No. 2; the CpG sites shown at positions 96-97 and 101-102; the CpG site shown at positions 125-126; the CpG site shown at positions 232-233; the CpG site shown at positions 260-261; the CpG site shown at positions 283-284; and the CpG site shown at positions 335-336; The 12 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.3 are the CpG sites shown at positions 25-26, 27-28, 29-30, 32-33 and 45-46 from the 5' end of SEQ ID No.3; the CpG site shown at positions 61-62; the CpG site shown at positions 63-64, 66-67 and 81-82; the CpG site shown at positions 87-88 and 103-104; the CpG site shown at positions 105-106, 109-110 and 119-120; the CpG site shown at positions 147 -148; CpG sites shown at positions 149-150 and 165-166; CpG sites shown at positions 171-172; CpG sites shown at positions 186-187; CpG sites shown at positions 192-193, 194-195, 198-199, and 201-202; CpG sites shown at positions 211-212 and 216-217; CpG sites shown at positions 238-239; The 11 distinguishable CpG sites of the DNA fragment shown in SEQ ID No.4 are the CpG sites shown at positions 39-40 and 41-42 from the 5' end of SEQ ID No.4; the CpG sites shown at positions 61-62 and 65-66; the CpG sites shown at positions 69-70; the CpG sites shown at positions 77-78 and 81-82; the CpG sites shown at positions 107-108 and 110-111; the CpG sites shown at positions 122-123; the CpG sites shown at positions 139-140; the CpG sites shown at positions 185-186; the CpG sites shown at positions 213-214 and 219-220; the CpG sites shown at positions 275-276; and the CpG sites shown at positions 304-305; The five distinguishable CpG sites of the DNA fragment shown in SEQ ID No.5 are: the CpG sites shown at positions 44-45 from the 5' end of SEQ ID No.5; the CpG sites shown at positions 175-176; the CpG sites shown at positions 266-267; the CpG sites shown at positions 292-293; and the CpG sites shown at positions 300-301. 20. The system according to claim 17, wherein the reagent for detecting the methylation level of the ACTB gene comprises a primer combination for amplifying the full length or partial fragment of the ACTB gene. 21. The system according to claim 20, wherein the partial segment is at least one of the following segments: (g1) a DNA fragment represented by SEQ ID No. 1 or a DNA fragment contained therein; (g2) the DNA fragment shown in SEQ ID No. 2 or a DNA fragment contained therein; (g3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein; (g4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment contained therein; (g5) The DNA fragment shown by SEQ ID No. 5 or a DNA fragment contained therein. 22. The system according to claim 20, characterized in that: the primer combination is primer pair A and/or primer pair B and/or primer pair C and/or primer pair D and/or primer pair E; the primer pair A is a primer pair consisting of primer A1 and primer A2; the primer A1 is a single-stranded DNA represented by nucleotides 11-35 of SEQ ID No.6 or SEQ ID No.6; the primer A2 is a single-stranded DNA represented by nucleotides 32-58 of SEQ ID No.7 or SEQ ID No.7; The primer pair B is a primer pair consisting of primer B1 and primer B2; the primer B1 is a single-stranded DNA represented by nucleotides 11 to 34 of SEQ ID No.8; the primer B2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No.9 or SEQ ID No.9; The primer pair C is a primer pair consisting of primer C1 and primer C2; the primer C1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No. 10; the primer C2 is a single-stranded DNA represented by nucleotides 32 to 51 of SEQ ID No. 11 or SEQ ID No. 11; The primer pair D is a primer pair consisting of primer D1 and primer D2; the primer D1 is a single-stranded DNA represented by nucleotides 11 to 37 of SEQ ID No. 12; the primer D2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No. 13 or SEQ ID No. 13; The primer pair E is a primer pair consisting of primer E1 and primer E2; the primer E1 is a single-stranded DNA represented by nucleotides 11-37 of SEQ ID No.14; the primer E2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.15 or SEQ ID No.15.