| Part I: BCL3-PVRL2-TOMM40 SINGLE NUCLEOTIDE POLYMORPHISMS,GENE-GENE AND GENEENVIRONMENT INTERACTIONS ON DYSLIPIDEMIABackground: With the continuous improvement of living standards,the incidence of cardiovascular diseases has increased year by year,and it has become the leading cause of death among the people in the world,and bringing enormous economic burden and social burden to the people of all countries in the world.The main cause of cardiovascular disease is arteriosclerosis,and dyslipidemia is an important cause of arteriosclerosis.Effective prevention and treatment of dyslipidemia is of decisive significance in reducing arteriosclerosis and even cardiovascular disease prevention and control.According to recent research,serum lipid levels are affected by a variety of factors,among which environmental factors,genetic factors,and environmental-genetic factors cannot be ignored.As the research progressed further,several large genome-wide association analyses mapped some new genes that may be related to serum lipid levels,but the relationship between these genes and serum lipid levels needs further verification.Among them,the B cell leukemia/lymphoma-3 gene(BCL3 [MIM109560]),the poliovirus receptor-associated gene-2(PVRL2 [MIM600798])and the outer mitochondrial membrane gene transposase gene(TOMM40 MIM [608061])were found.It is closely related to the levels of total cholesterol(TC),low density lipoprotein cholesterol(LDL-C)and high-density lipoprotein cholesterol(HDL-C).There are 55 ethnic minorities in China,and Maonan is one of them.It is also one of several ethnic minorities unique to Guangxi Zhuang Autonomous Region.The geographical environment,living characteristics,living habits and dietary traditions of the Maonan people are quite different from those of the Han people living in the area.The customs of intra-ethnic intermarriages have been passed down from generation to generation,thus distinguishing their genetic background from the local Han nationality.It is a perfect group for studying genetic effects,environmental influences,gene-gene and gene-environment interactions.We selected 12 single nucleotide polymorphisms(SNPs)that were confirmed to be associated with lipids in previous studies in the European population,all of the SNPs located within the BCL3-PVRL2-TOMM40 gene cluster.Through genotyping,the influence of gene-gene,gene-environment interaction on serum lipid levels in Maonan ethnic group was determined,and the causes of dyslipidemia were discussed,which is of great significance for further prevention and treatment of arteriosclerosis and even cardiovascular disease.Objectives: To understand the distribution and differences in blood lipid levels in Maonan population in Huanjiang Maonan Autonomous County,Guangxi,and to analyze the relationship between BCL3-PVRL2-TOMM40 SNPs and their haplotypes and serum lipid levels in normal and dyslipidemia groups. The effects of gender,age,environmental effects,genetic factors and environmental-genetic factors on the prevalence of dyslipidemia were also explored.Methods: According to the survey method of international epidemiologists,the stratified(sex and age)random sampling of Maonan residents living in the Shangnan,Zhongnan and Xia'nan mountainous areas of the Huanjiang Maonan Autonomous County in northwestern Guangxi was conducted to study the residents of the Maonan ethnic group.The subjects recorded information such as eating habits,height and weight,and conducted research related questionnaires and physical examinations.Systolic blood pressure(SBP)and diastolic blood pressure(DBP)levels were recorded.Fasting venous blood sample was obtained,and serum was separated to determine total cholesterol(TC),triglyceride(TG),high-density lipoprotein cholesterol(HDL-C),low-density lipoprotein cholesterol(LDL-C),apolipoprotein(Apo)A1 and Apo B.Body mass index(BMI),the Apo A1/Apo B ratio,and pulse pressure(PP)difference were calculated.Extract whole blood DNA samples.In this study,1962 people from Maonan nationality were randomly selected from the specimens established in the previous stratified random sample survey.They were divided into two groups according to whether they met the diagnostic criteria for dyslipidemia.There was no statistical difference in age and gender between the two groups.Twelve single nucleotide polymorphisms of BCL3-PVRL2-TOMM40 gene cluster were detected by polymerase chain reaction and restriction fragment length polymorphism(PCR-RFLP).They included BCL3 rs2965101,rs4803748,rs2965169 and r s8100239;PVRL2 rs10402271,rs3810143,rs519113,rs6859 and rs283810;and TOMM40 rs157580,rs2070650 and rs439401 SNPs.They were tested and genotyped,and Sanger sequencing was used to verify the genotype results of the PCR products.The distribution of genotypes and allele of BCL3-PVRL2-TOMM40 SNPs in the two groups,gender and their relationship with serum lipid levels were analyzed.The genotypes,alleles,and some environmental factors were correlated with serum lipid levels in both groups.Haploview 4.2 software was used to analyze linkage disequilibrium(LD)between each point,estimate D' or r2 values,and haplotypes.The generalized multi-factor dimensionality reduction analysis method(GMDR)was used to investigate the effects of gene-gene and geneenvironment interactions on dyslipidemia.Results: After comparison of serum lipid levels,the two groups of people were obtained,normal and dyslipidemia groups.The values of BMI,the numbers of who was smoking and drinking,fasting blood glucose,serum TC,TG and LDL-C levels were higher in dyslipidemia than in normal groups,whereas HDLC levels and the ratio of Apo A1 to Apo B were lower in dyslipidemia than in normal groups(P < 0.05-0.001).No differences were observed between the two groups in terms of age,gender,height,BMI,waist circumference(WC),SBP,DBP,PP,Apo A1,and Apo B(P > 0.05).The genotype and allele frequencies were different between the two groups(P < 0.05-0.001),and all gene mutations were consistent with the Hardy-Weinberg equilibrium(HWE,P > 0.05).Further analysis of the effects of genetic models on the pathogenesis of dyslipidemia found that the dominant model of rs8100239 and rs157580 SNPs had protective effects on dyslipidemia,while the dominant models of rs10402271,rs3810143,rs519113 and rs6859 SNPs showed increased morbidity(P < 0.05-0.001).At the same time,mutations in some SNPs can cause corresponding changes in serum lipid levels.The relationship in the dyslipidemia group is: TC(rs2965101,rs4803748,rs2965169,rs8100239,rs519113,rs6859,rs157580,rs2075650,and rs439401);TG(rs2965101,rs8100239,rs10402271,rs3810143,rs6859,rs283810 and rs157580);LDLC(rs2965101);whereas the correlation observed in normal blood lipid group is: TC(rs2965169,rs519113 and rs157580);TG(rs2965101,rs8100239,rs6859 and rs157580)(P < 0.004-0.001).Multiple intergenic linkage disequilibrium(LD)clarified the statistical non-independence between the test sites in both groups.Among them,the most common haplotypes were BCL3 AC-A-T,PVRL2 A-A-G-G-A and TOMM40 T-A-T(> 30% ratio).The BCL3 A-T-C-A,BCL3 A-T-C-T,PVRL2 A-A-C-A-A,PVRL2 A-A-C-A-C,PVRL2 A-A-G-G-A,PVRL2 C-G-C-A-A,PVRL2 C-G-C-A-C,TOMM40 C-A-C,TOMM40 C-A-T and TOMM40 T-A-T haplotypes present in a ratio difference between dyslipidemia and the normal population.At the same time,the BCL3 AT-C-A,PVRL2 A-A-C-A-C,PVRL2 A-A-G-G-A and TOMM40 T-A-T haplotypes can reduce the incidence of dyslipidemia,and the BCL3 A-T-C-T,PVRL2 A-A-C-A-A,PVRL2 C-G-C-A-A,PVRL2 C-G-C-A-C,TOMM40 C-A-C and TOMM40 C-A-T haplotypes were displayed to increase morbidity(P < 0.05-0.001).Further study of gene-gene interactions revealed that the most common form of interaction was A-C-A-T-A-A-G-G-A-T-A-T(> 15% ratio).In the two groups,there was a different haplotype interaction between A-C-A-T-A-A-G-A-A-T-A-T,A-C-A-T-A-A-G-G-A-C-A-C,A-C-AT-A-A-G-G-A-C-A-T,A-C-A-T-A-A-G-G-A-T-A-T,A-T-C-A-A-AG-G-A-T-A-T,G-T-C-A-A-A-G-A-A-C-A-C,G-T-C-A-A-A-G-GA-C-A-C and G-T-C-A-A-A-G-G-A-T-A-T.At the same time,the A-C-A-T-A-A-G-A-A-T-A-T,A-T-C-A-A-A-G-G-A-T-A-T and G-TC-A-A-A-G-G-A-T-A-T,A-C-A-T-A-A-G-G-A-C-A-C,A-C-A-TA-A-G-G-A-C-A-T,A-C-A-T-A-A-G-G-A-T-A-T,G-T-C-A-A-A-G-A-A-C-A-C and G-T-C-A-A-A-G-G-A-C-A-C haplotypes were shown to increase the incidence of dyslipidemia(P <0.01-0.001).To assess the effects of gene-gene and gene-environment interactions on dyslipidemia,the GMDR model was used for analysis,and after adjusting for covariates(including age,gender,BMI,blood pressure,blood glucose,smoking,and alcohol consumption),the results were analyzed.It is known that there is a SNP-SNP interaction between rs296510,rs157580 and rs439401 SNPs,and there were potential SNP-environment interactions between rs2965101,rs8100239 SNP and BMI > 24 kg/m2.Further analysis showed that haplotype-the interaction(PVRL2 A-A-G-G-A,TOMM40 C-A-C and TOMM40 T-A-T)and haplotype-environment interactions(TOMM40 C-A-C,TOMM40 T-A-T and BMI> 24 kg/m2,P < 0.001).Similarly,in the two populations can also find gene-gene interactions(A-C-A-T-A-A-G-G-A-C-A-C,A-C-A-T-A-A-G-G-A-T-AT and G-T-C-A-A-A-G-G-A-T-A-T)and gene-environment interactions(G-T-C-A-A-A-G-G-A-T-A-T,age > 75 and BMI > 24 kg/m2).To clarify the effects of these interactions on the pathogenesis of dyslipidemia,we used logistic regression to analyze their interactions.We found that,compared with the carrying rs157580 CC and rs439401 TT genotype,rs157580 CT/TT and rs439401 CC/CT genotype of the population with the lowest risk of dyslipidemia(adjusted OR = 0.54,95% CI = 0.32-0.93,P < 0.001).When considering SNP-environment interactions,we found to carry rs2965101 AC/CC genotype and BMI > 24 kg/m2 dyslipidemia subject increased risk of disease(adjusted OR = 1.08,95% CI = 0.84-1.44,P = 0.0015).However,when analyzing the haplotype-haplotype and haplotype-environment interactions,and we can find PVRL2 A-A-C-A-A,TOMM40 C-A-C carriers(adjusted OR = 5.47,95% CI = 3.64-7.73,P <0.001) and TOMM40 T-A-T carriers and BMI > 24 kg/m2 population(adjusted OR = 1.08,95% CI = 0.75-1.54,P <0.001)with an increased risk of dyslipidemia.When the gene-gene and gene-environment interactions were analyzed,we found that the A-C-A-T-A-A-G-G-A-T-A-T,G-T-C-A-A-A-G-G-A-T-A-T carriers can reduce the risk of dyslipidemia(adjusted OR = 0.88,95% CI = 0.62-1.02,P < 0.001),and the G-T-C-A-A-A-G-G-A-T-A-T carriers-BMI > 24 kg/m2(adjusted OR = 1.13,95% CI = 0.85-1.49,P < 0.001)increased the risk of onset of dyslipidemia.Conclusions: There was different in serum lipid levels between dyslipidemia and normal groups.Serum lipid levels were closely related to age,gender,waist circumference,blood pressure,glucose,smoking and drinking.The genotypes and allele carrying frequencies of SNPs in the BCL3-PVRL2-TOMM40 gene cluster of Maonan nationality are related to dyslipidemia.The haplotypes carrying status is different from dyslipidemia and normal groups,and SNPs,haplotypes and environment interaction of factors also has an important impact on the risk of disease.Part II:WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS IDENTIFIES SPECIFIC MODULES AND HUB GENES RELATED TO HYPERLIPIDEMIABackground and purpose: Cardiovascular disease is currently one of the leading causes of death in patients worldwide.In the recent years,with the improvement of living standards,the incidence of the disease has increased year by year.Hyperlipidemia is one of the key factors affecting its development,and prevention of hyperlipidemia plays an important role in the control of cardiovascular diseases.According to existing research,the occurrence and development of hyperlipidemia is affected by environmental factors,genetic factors and environmental-genetic interactions.This study attempts to find potential genes and pathogenesis of hyperlipidemia through data mining,and to explore possible mechanisms related to it.Methods: Recently,with the continuous development of gene chip technology,research applications are very extensive.The most important research projects include: gene expression profiling,biomarker detection,DNA sequencing,genomic library mapping and hybridization sequencing,mutation detection,disease classification and polymorphism analysis.There are several commonly used gene chip databases in the world: the Gene Expression Omnibus(GEO)database established by the National Center for Bioinformatics(NCBI),the Internet-based gene expression database established by the National Genome Center's resources,and the European biology.Arryexpress public database was established by the Informatics Center.These databases receive and store biochip data submitted by researchers around the world.Researchers can selectively download the raw data of other chips for further scalability analysis based on the research content,and become one of the sources of information for big data mining.In this study,the GSE3059 chip data were downloaded from the GEO database,which contained 13 known hyperlipidemia samples.The gene co-expression network is a method for finding a gene having a synergistic expression effect by a scale-free method,and a component coexpressing a network regulation module.The method can cluster a group of genes with similar functions,or simultaneously appearing in a specific biological pathway,and form a module.Researchers can infer the function of the gene based on the gene of an unknown function,and further expand the inter-regulation relationship between the genes with the same function in the module.The relationship between inquiry and external phenotype is linked.The weighted gene co-expression networks analyzed(WGCNA)algorithm is a typical biological algorithm that is widely used in the field of international biology to construct a gene co-expression network.Further analysis of the genes gathered by this module,the Gene Ontology annotation(GO)and the Kyoto Encyclopedia of Genes and Genomes(KEGG)were performed by using the cluster Profiler and DOSE packages in the R language.Pathway enrichment analyzed).A proteinprotein interaction(PPI)network was built using Cytoscape software and an important module was analyzed using the MCODE plug-in.Finally,functional verification of the core gene was performed by RT-PCR.Results: This study analyzed the relationship between the 13-sample gene-phenotypes by WGCNA and found that the genes were in the salmon-central granulocyte count(R2 = 0.78,P < 0.01)and midnight blue-glucose metabolism(R2 = 0.67,P = 0.01).Both modules have the highest correlation.GO and KEGG analysis of the genes in these two modules revealed that there were 23 meaningful functional analyses and 9 metabolic related pathways in the Salmon module;the Midnight blue module had 11 meaningful functional analyses and 3 metabolic related pathways.After analysis by PPI and MCODE,five genes were synthesized(histone deacetylase 4,HDAC4;F2R trypsin analog was-1,F2RL1;hydrolase domain-2,ABHD2;transmembrane-4-Six families into-1,TM4SF1;and family sequence similarity 13-member-A,FAM13A),these five genes were of great significance in the development of hyperlipidemia.The relative expression of HDAC4 was lower when verified by RT-q PCR,but F2RL1,ABHD2,TM4SF1 and FAM13 A were higher in hyperlipidemia than in the normal control groups(P < 0.05-0.01).Subgroup analysis showed that the relative expression of HDAC4 in Maonan was lower,whereas the expression of F2RL1 and ABHD2 was higher than that in Han(P < 0.05).Conclusions: HDAC4 has the function of deacetylating histones.Combined with bioinformatics analysis,epigenetic effects(histone modifications)affect the development of hyperlipidemia in addition to genetic factors and environmental exposure.The occurrence of hyperlipidemia in the Maonan population may be related to histone modification(epigenetic regulation)and needs further confirmation and verification.Part III:CIRCULATING MIR-3659 MAY BE A POTENTIAL BIOMARKER OF DYSLIPIDEMIA IN PATIENTS WITH OBESITYBackground/Objective: Obesity is an unavoidable topic in the development of modern society.With the deep research on obesity,it is currently considered to be a chronic metabolic disease and caused by multiple factors,including excessive energy intake and energy less consumption.With the continuous improvement of people's living standards,the lifestyle and diet structure have changed a lot compared with the past.Epidemiological studies suggest that the proportion and number of overweight and obese people are increasing year by year.Obesity not only affects the appearance of the body,but more importantly,it is also a risk factor for cardiovascular and cerebrovascular diseases,causing metabolic diseases such as dyslipidemia,hypertension,coronary heart disease,and diabetes.Effective prevention of obesity and the development of dyslipidemia can reduce the incidence and mortality of cardiovascular and cerebrovascular diseases.Recent studies have shown that obesity can be regulated by epigenetic effects,so this study sought to identify key genes that potentially cause dyslipidemia in obese people,and to predict and regulate micro RNAs related to the gene through bioinformatics prediction.This study aimed to explore its predictive value for the development of dyslipidemia in obese people.Methods: Recently,huge data mining has gradually become a hot technology for disease research.Gene chip technology can provide more information on the gene spectrum of diseases,and is an important technology for the impact of genes related to disease research.With the continuous development of gene chip technology,it can provide research projects including: gene expression profiling,biomarker detection,DNA sequencing,genomic library mapping and hybridization sequencing,mutation detection,disease classification and polymorphism analysis and etc.Usually after the completion of the chip sequencing,the corresponding data will be uploaded to the designated database for later research to further research and analysis,in addition to saving relevant funds,but also to ensure the continuity of the subject.The current gene chip database can be downloaded and used,including the Gene Expression Omnibus(GEO)database established by the National Center for Bioinformatics(NCBI)the Internet-based gene expression database established by the National Genomics Center,and the European Bioinformatics in the UK.The Arryexpress public database was established by the center.The establishment of these databases has greatly expanded the source of information data and has gradually become an indispensable tool for huge data mining.There are also many methods for the analysis of the chip data that can be mined.The researchers can choose according to their own research needs,and the gene co-expression network is a method for finding the genes with synergistic expression through scale-free search,and the components co-express the network control module.The core idea of the method is to integrate a set of functions that are close to each other,or to focus on a specific biological effect pathway,by building a scale-free correlation link.Ther esearcher use these modules and related phenotypes.Corresponding links speculate on the function of these genes,and even a way to predict whether these genes have corresponding regulatory relationships.The weighted gene coexpression networks analyzed(WGCNA)algorithm is one of the typical bioinformatics algorithms,which can construct a co-expression network based on the weight of gene and phenotypic functions without scale.In the field of international biology,in the GEO database,this study downloads chip data for GSE66676,which contains 67 known obese individuals with different serum lipid levels.Through analysis,these genes that cause changes in blood lipid phenotype in obese people are clustered in a module,and the genes in the module are further analyzed.The gene function annotation(Gene Ontology annotation,GO)is completed using the cluster Profiler and DOSE packages in the R language.And Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed.A protein-protein interaction(PPI)network was built using Cytoscape software and an important module was analyzed using the MCODE plug-in.After selecting the key genes,bioinformatic methods were used to predict the mi RNAs that had regulatory effects on the genes.Finally,RT-PCR and ROC curves were used to verify the function of the core mi RNAs and to predict their predictive value for the risk of dyslipidemia.Results: This study analyzed the relationship between the 67-sample genephenotypes by WGCNA and found that the genes had the highest correlation at grey60-triglyceride levels(R2 = 0.98,P < 0.01).GO and KEGG analysis of the genes in this module revealed that the module had 15 meaningful functional analyses and 8 metabolic related pathways.After analysis by PPI and MCODE,it was judged by comprehensive judgment(collagen type I ?1 chain,COL1A1)as a core gene.After bioinformatic prediction,4 mi RNAs(hsa-mi R-3659,hsa-mi R-4658,hsa-mi R-151a-5p and hsa-mi R-151b)were able to specifically bind to the gene 3 'UTR.When RT-q PCR was used to verify normal and abnormal serum lipid levels,only hsa-mi R-3659 and hsa-mi R-151-5p were statistically significant.Further analysis by ROC curve,AUC hsa-mi R-3659 = 80.6% vs.AUC hsami R-151-5p = 76.9%(P < 0.05).Conclusion: COL1A1 is positively correlated with serum triglyceride levels in obese people.Combined with bioinformatic analysis,epigenetic effects(noncoding RNA)can specifically bind to the 3'UTR of the gene,affecting the occurrence of dyslipidemia.Among them,hsa-mi R-3659 has a good predictive effect on dyslipidemia in obese people,but the specific mechanism needs further confirmation and verification.PART ?:INTEGRATED DNA METHYLATION AND GENE EXPRESSION ANALYSIS IN THE PATHOGENESIS OF CORONARY ARTERY DISEASEBackground/Objective: Coronary artery disease(CAD)is still the world's first fatal disease,its main pathological characteristics are atherosclerosis.There are many causes of CAD,including age,sex,race,hypertension,hyperglycemia,dyslipidemia,hyperhomocysteine,obesity,genetic background differences,bad lifestyle,etc.According to World Health Organization statistics,the number of deaths caused by CAD in the world is expected to increase from 47 million in 1990 to 82 million in 2020.Framingham's study in 2010 showed that the incidence of CAD varies with age,with the incidence of 18-44 years old,45-65 years old and over 65 years old being 1.2%,7.1% and 19.8%;respectively.Gender,the incidence of premenopausal women is slightly lower,while the incidence of postmenopausal women is significantly higher.Further studies show that atherosclerotic plaques are rich in lipid foam cells and soft plaques in CAD.This kind of soft plaque progresses rapidly and is easy to rupture,which is the main cause of coronary artery thrombosis.Most patients with coronary heart disease have no precursory symptoms,acute onset,and manifest as acute coronary syndrome,especially acute myocardial infarction,with a high mortality.Normally,whether a cell can perform a specific function is determined by its own gene expression profile.Classical genetics considers that the molecular basis of inheritance is nucleic acid,and genetic information between different life is stored in the nucleotide base sequence.With the continuous progress and development of genetics,the modification of DNA methylation level,histone and chromatin variation level in varying degrees will also cause changes in gene expression mode and quantity,and this change can be inherited.Therefore,epigenetics can be defined as the regulation of gene expression without altering the gene sequence,and the regulation results can be passed on from generation to generation through cell division.Contrary to nucleotide sequence polymorphism,epigenetic variation is specific,dynamic,and even reversible throughout life,and its mechanism is diverse.DNA methylation,histone modification and non-coding RNA(nc RNA)regulation can affect and regulate gene expression,which are the three most important mechanisms of epigenetics.Therefore,epigenetics is considered as a bridge between genotype and individual phenotype.DNA methylation refers to the transfer of methyl groups to the base sequence of DNA under the action of methylase and the modification of DNA by methylation.The most common area of DNA methylation is the cytosine phosphate-guanine(Cp G)island.In human cells,about 70-80% of DNA methylation occurs at the Cp G locus in the whole genome and is affected by DNA base sequence and environmental factors.However,with the deepening of research,many non-Cp G islands of cytosine can also undergo methylation modification under specific conditions.Especially in the promoter region,once cytosine methylation occurs,the conformation of the specific structure of the gene changes,which can persistently prevent the binding of transcription factors,or hinder gene expression by recombinant chromatin.Through the combined analysis of DNA methylation and expression profiles,we can not only discover the intrinsic pathogenic mechanism of pathogenic genes,but also provide sufficient reference for the treatment of CAD.Methods: The occurrence and development of disease is a dynamic process.Current microarray analysis technology is more mature than before.However,single microarray analysis can only explain one level of disease occurrence and development.Therefore,multi-group,multi-sample and multi-microarray joint analysis has gradually become the mainstream.In this study,the microarray data of GSE23561 and GSE107143 were downloaded from the GEO database.GSE23561 is an expression profile microarray,which contains 35 human gene expression analysis data,including 6 patients with CAD and 9 healthy controls.GSE107143 is a genome-wide DNA methylation analysis microarray.It contains 8 patients with atherosclerosis and 8 healthy controls.The two microarrays were all from peripheral blood,and the purpose of the study was similar.The number of samples and age matched,which met the requirements of joint analysis.We carried out:(1)genome-wide DNA methylation and gene expression profiling analysis,screening the differentially expressed genes of the two microarrays,and then comparing them,taking the intersection and entering the next stage;(2)Gene Ontology annotation(GO)and Kyoto Enopedia of Genes were completed by using cluster Profiler and DOSE package in R language.D Genomes(KEGG)pathway enrichment was analyzed.Protein-protein interaction(PPI)network was established by Cytoscape software,and important modules were detected and analyzed by MCODE plugin.Key genes were selected;(3)Eleven different methylation sites and their corresponding gene expression were validated by pyrophosphatic acid sequencing and RT-PCR in CAD patients;(4)correlation analysis between DNA methylation and gene expression data.Results: A tot al of 669 differentially expressed were matched with differentially methylated genes.After disease ontology,Kyoto Encyclopedia of Gene and Genome Pathways,Gene Ontology,Protein-Protein Interaction and Network Construction and Modular Analysis,11 differentially methylated sites(DMPs)corresponding to 11 unique genes were observed.They included BDNF-cg26949694,BTRC-cg24381155,CDH5-cg022351,CXCL12-cg11267527,EGFR-cg277738,IL-6-cg13104385,ITGB1-cg205410,PDGFRB-cg25613180,PIK3R1-cg00559992,PLCB1-cg27178677 and PTPRC-cg09247619.After validating the expression of 11 interesting DMPs and related genes,we found that the hypomethylation of CXCL12 was lower in CAD group,and the relative expression of ITGB1,PDGFRB and PIK3R1 was lower in CAD patients,but only two loci of CXCL12 and ITGB1 methylation were negatively correlated with their expression levels.Conclusions: This study identified the correlation between DNA methylation and gene expression and highlighted the importance of CXCL12 in CAD pathogenesis. |
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