CN112877419A - DNA methylation marker for predicting schizophrenia occurrence risk, screening method and application - Google Patents
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- C12Q2600/00—Oligonucleotides characterized by their use
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Abstract
The invention provides a DNA methylation marker for predicting schizophrenia occurrence risk, which is characterized in that the DNA methylation marker is selected from at least one methylated CpG locus on human chromosomes 1-22. The invention also provides the application of the methylation marker in preparing a diagnostic reagent and/or an auxiliary diagnostic reagent and/or a diagnostic kit for predicting the occurrence risk of schizophrenia. The present invention further provides a method for screening the methylation marker. The DNA methylation marker for predicting the occurrence risk of schizophrenia predicts the occurrence risk of schizophrenia, can improve the prediction accuracy of the occurrence risk of schizophrenia, saves cost, is suitable for popularization and application, and has good application prospect; the method for screening the methylation marker is simple, scientific and reliable.
Description
Technical Field
The invention relates to the field of biotechnology, in particular to a DNA methylation marker for predicting schizophrenia occurrence risk and a screening method and application thereof.
Background
Schizophrenia is a heterogeneous disease, the etiology and the onset of the disease are complex, and the etiology, the pathogenesis and the diagnosis of the disease are important research subjects in the field of neuroscience. Schizophrenia is currently considered to be a genetically predisposed disease. Classical genetic studies, i.e., genome-wide association analysis studies, screened more than 100 candidate genes with less reproducibility, suggesting that in addition to classical genetic alterations (genetic polymorphisms), epigenetic alterations may be involved in the pathogenesis of schizophrenia. Epigenetic refers to the genetic change of gene expression without change of DNA sequence and protein coding, thereby affecting gene function and finally causing phenotypic change, including DNA methylation, histone acetylation, RNA interference and other mechanisms. DNA methylation is the most deeply studied mechanism in epigenetics and is one of the important epigenetic ways to regulate gene expression. DNA methylation modification plays a crucial role in normal cell development, gene expression patterns, and neural plasticity. More importantly, DNA methylation records the interaction information of the organism and the environment, reflects the pathological trace generated by the interaction of the organism and the environment on the individual, and is a very powerful tool for researching complex diseases caused by the co-action of the gene and the environment, such as schizophrenia and the like.
In 2001, after summarizing the research situation of complex diseases such as schizophrenia, Petronis suggested that epigenetic modification may be involved in the pathological process of complex diseases such as schizophrenia, and many contents which cannot be explained by classical genetics, such as the conditions of different monozygotic twin diseases, can be better explained by the concept of epigenetic modification. The genetic codes of monozygotic twins are completely identical, but the concordance rate of schizophrenia monozygotic twins is only about 50%, which is not well explained by classical genetics, but if the two siblings of monozygotic twins have different epigenetic modifications (such as different methylation patterns), it can be well understood why the phenotype of monozygotic twins has such a large difference. There are several studies to date which have found abnormalities in DNA methylation in schizophrenic patients. Costa E et al found that the expression of reelin is reduced by about 50% in schizophrenia and affective diseases, and that reelin protein is an essential substance in nerve migration and axon formation. Chen Y and other researches find that the expression reduction of the Reelin gene in the brain tissue of a schizophrenia patient is related to the hypermethylation state of a CpG island in a promoter region of the schizophrenia patient. The systematic analysis of more than 8000 methylation probes by Mill et al using a chip method revealed that methylation probes of some genes of glutamatergic, GABAergic and neurodevelopmental systems are associated with schizophrenia and bipolar disorder, including some currently highly valued schizophrenia candidate genes, such as Dysbindin gene. Analysis of still other small samples revealed that methylation of CpG islands in promoter regions of genes such as sox10, COMT, Synaptatagenes, DRD2 and reelin was associated with schizophrenia. Currently, researchers mostly study schizophrenia pathogenesis from the level of single gene methylation, the number of whole genome methylation studies is small at present, and most of the methylation studies are not independently verified, the detected methylation markers are not enough to detect schizophrenia early, but the markers or marker combinations may be useful for schizophrenia risk stratification. A high-throughput methylation quantitative method, namely a whole genome methylation method, is utilized, and a detailed analysis algorithm is combined to deeply mine data information, so that a focus is on further mining an information methylation marker, and a characteristic biomarker for the onset risk of schizophrenia is expected to be searched.
In conclusion, finding an accurate biomarker is a crucial step in the prediction of schizophrenia risk.
Disclosure of Invention
The present invention is directed to solving at least some of the problems of the prior art by providing a DNA methylation marker for predicting the risk of developing schizophrenia, and the use of the methylation marker in the preparation of a diagnostic reagent and/or an auxiliary diagnostic reagent and/or a diagnostic kit for predicting the risk of developing schizophrenia. The present invention further provides a method for screening the methylation marker. The DNA methylation marker for predicting the occurrence risk of schizophrenia predicts the occurrence risk of schizophrenia, can improve the prediction accuracy of the occurrence risk of schizophrenia, saves cost, is suitable for popularization and application, and has good application prospect; the method for screening the methylation marker is simple, scientific and reliable. By analyzing DNA methylation data, novel biomarkers related to the prediction of the occurrence risk of schizophrenia are discovered.
In a first aspect of the present invention, the present invention provides a DNA methylation marker for predicting schizophrenia occurrence risk, wherein the DNA methylation marker for predicting schizophrenia occurrence risk is selected from at least one methylated CpG site on human chromosome 1-22.
Preferably, the DNA methylation marker for predicting the occurrence risk of schizophrenia is selected from the group consisting of a methylation CpG site cg02497700 of human chromosome 1, a methylation CpG site cg04437762 of chromosome 1, a methylation CpG site cg05697909 of chromosome 1, a methylation CpG site cg09277376 of chromosome 1, a methylation CpG site cg10540110 of chromosome 1, a methylation CpG site cg16399365 of chromosome 1, a methylation CpG site cg17176894 of chromosome 1, a methylation CpG site cg17985912 of chromosome 1, a methylation CpG site cg18881723 of chromosome 1, a methylation CpG site cg19698993 of chromosome 1, a methylation CpG site cg21686694 of chromosome 1, a methylation site cg24155129 of chromosome 1, a methylation site cg 34340526 of chromosome 1, a methylation site cg 0582176 of chromosome 1, a methylation site cg 920326 of chromosome 1, a methylation site cg 92260326 of chromosome 1, a methylation site cg 9226 of chromosome 1, a methylation site cg 03922626 of chromosome 1, a methylation site cg 920326 of chromosome 1, a methylation site cg 9226 of chromosome 1, a methylation site cg0326 of chromosome 1, a methylation site cg 9226, a methylation site cg 03764 of chromosome 1, a methylation site cg 9226, a methylation site of chromosome 1, a methylation site cg 038, Methylation CpG site cg06117093 of chromosome 2, methylation CpG site cg07065759 of chromosome 2, methylation CpG site cg12287813 of chromosome 2, methylation CpG site cg13424923 of chromosome 2, methylation CpG site cg13651986 of chromosome 2, methylation CpG site cg15890754 of chromosome 2, methylation CpG site cg21319458 of chromosome 2, methylation CpG site cg 249947 of chromosome 2, methylation CpG site cg26823762 of chromosome 2, methylation CpG site cg05551922 of chromosome 3, methylation CpG site cg12198140 of chromosome 3, methylation CpG site cg14011327 of chromosome 4, methylation CpG site cg 54939 of chromosome 4, methylation site cg27305383 of chromosome 4, methylation site cg 019533 of chromosome 2, methylation site cg 35045571 of chromosome 4, methylation site cg 7431559 of chromosome 4, methylation site cg019 315571 of chromosome 2, methylation site cg019 31556 of chromosome 2, methylation site cg 315571 of chromosome 2, methylation site cg019, The methylation CpG site cg05217983 of chromosome 6, the methylation CpG site cg13265740 of chromosome 6, the methylation CpG site cg16254746 of chromosome 6, the methylation CpG site cg00653387 of chromosome 7, the methylation CpG site cg02627991 of chromosome 7, the methylation CpG site cg03993154 of chromosome 7, the methylation CpG site cg08313420 of chromosome 7, the methylation CpG site cg08634133 of chromosome 7, the methylation CpG site cg16555537 of chromosome 7, the methylation CpG site cg27496339 of chromosome 7, the methylation CpG site cg 24688396 of chromosome 8, the methylation site cg08872550 of chromosome 8, the methylation site cg24023258 of chromosome 8, the methylation site cg 4704104171 of chromosome 9, the methylation site cg 245161396 of chromosome 8, the methylation site cg 0487740 of chromosome 10, the methylation site cg 251043976 of chromosome 6, the methylation site cg 2512512515639 of chromosome 6, the methylation site cg 517994 of chromosome 7, the methylation site cg 25125194 of chromosome 7, the methylation site cg 25155537 of chromosome 7, the methylation site cg 64047994 of chromosome 7, the methylation site cg 2512, the methylation site cg 64047994 of chromosome 10, the methylation site cg 2512, the methylation site of chromosome 10, the methylation site cg 2513976 of chromosome 7, the methylation site cg 2512, Methylated CpG site cg03365311 of chromosome 11, methylated CpG site cg13912027 of chromosome 11, methylated CpG site cg15374924 of chromosome 11, methylated CpG site cg20411756 of chromosome 11, methylated CpG site cg27470087 of chromosome 11, methylated CpG site cg09045655 of chromosome 12, methylated CpG site cg09183316 of chromosome 12, methylated CpG site cg 159802 of chromosome 12, methylated CpG site cg22277972 of chromosome 12, methylated CpG site CpG 0918313 of chromosome 13, methylated CpG site cg 14068893 of chromosome 13, methylated CpG site cg14012112 of chromosome 14, methylated CpG site cg01557 of chromosome 14, methylated CpG site cg 9123 of chromosome 14, methylated site cg 9114 of chromosome 11, methylated site cg 95118 of chromosome 11, methylated site cg 27214, methylated site cg 95114 of chromosome 11, methylated site cg 95114, methylated site cg 27214 of chromosome 11, methylated site cg 95114, methylated site cg 27214, methylated site cg 15618 of chromosome 11, methylated site cg 2724718, methylated site cg 951 of chromosome 11, methylated site cg 914718, methylated site cg 951 of chromosome 11, methylated site cg 951, methylated site cgi, methylated site, Methylation CpG site cg03790899 of chromosome 15, methylation CpG site cg13163919 of chromosome 15, methylation CpG site cg17716765 of chromosome 15, methylation CpG site cg26971042 of chromosome 15, methylation CpG site cg00762678 of chromosome 16, methylation CpG site cg02187822 of chromosome 16, methylation CpG site cg03989617 of chromosome 16, methylation CpG site cg 04538 of chromosome 16, methylation CpG site cg04699663 of chromosome 16, methylation CpG site cg06907405 of chromosome 16, methylation CpG site cg07013955 of chromosome 16, methylation site cg 08187 of chromosome 16, methylation site CpG 6803 of chromosome 16, methylation site cg 2591720 of chromosome 17, methylation site cg 2591259233 of chromosome 17, methylation site cg 09640933 of chromosome 15, methylation site cg 096409640933 of chromosome 15, methylation site cg 09640964099 of chromosome 15, Methylation CpG site cg11393185 of chromosome 17, methylation CpG site cg16807061 of chromosome 17, methylation CpG site cg21603891 of chromosome 17, methylation CpG site cg22635673 of chromosome 17, methylation CpG site cg26604214 of chromosome 17, methylation CpG site cg 20731 of chromosome 18, methylation CpG site cg07381806 of chromosome 19, methylation CpG site cg11811510 of chromosome 19, methylation CpG site cg 168868 of chromosome 19, methylation CpG site cg26796095 of chromosome 19, methylation CpG site cg 82367 of chromosome 20, methylation site cg01329151 of chromosome 20, methylation site cg 94258982 of chromosome 20, methylation site cg 717 of chromosome 21, methylation site cg 07070522 of chromosome 17, methylation site cg 1128722 of chromosome 17, methylation site cg 112602642 of chromosome 17, methylation site cg 112642 of chromosome 17, methylation site cg 640480 of chromosome 20, methylation site cg 0787642 of chromosome 17, methylation site cg 07879 of chromosome 17, methylation site cg 0522 of chromosome 17, and methylation site cg 112879 of chromosome 17, A methylated CpG site cg21431832 of chromosome 22 and a methylated CpG site cg27087377 of chromosome 22.
Preferably, the DNA methylation marker for predicting the occurrence risk of schizophrenia is selected from the group consisting of a methylation CpG site cg02497700 of human chromosome 1, a methylation CpG site cg04437762 of chromosome 1, a methylation CpG site cg05697909 of chromosome 1, a methylation CpG site cg09277376 of chromosome 1, a methylation CpG site cg10540110 of chromosome 1, a methylation CpG site cg16399365 of chromosome 1, a methylation CpG site cg17176894 of chromosome 1, a methylation CpG site cg17985912 of chromosome 1, a methylation CpG site cg18881723 of chromosome 1, a methylation CpG site cg19698993 of chromosome 1, a methylation CpG site cg21686694 of chromosome 1, a methylation site cg26348226 of chromosome 1, a methylation site cg 5898993 of chromosome 2, a methylation site cg 0592176 of chromosome 1, a methylation site cg 920393 of chromosome 1, a methylation site cg 059293 of chromosome 1, a methylation site cg 039293 of chromosome 1, a methylation site cg 056993 of chromosome 1, a methylation site cg 039293 of chromosome 1, a methylation site cg032, a methylation site cg 9293 of chromosome 1, a methylation site cg 039293, a methylation site of chromosome 1, methylation CpG site cg07065759 of chromosome 2, methylation CpG site cg12287813 of chromosome 2, methylation CpG site cg13651986 of chromosome 2, methylation CpG site cg15890754 of chromosome 2, methylation CpG site cg21319458 of chromosome 2, methylation CpG site cg24749947 of chromosome 2, methylation CpG site cg05551922 of chromosome 3, methylation CpG site cg 54939 of chromosome 4, methylation CpG site cg27305383 of chromosome 4, methylation CpG site cg11958644 of chromosome 5, methylation CpG site cg01955533 of chromosome 6, methylation site cg 043171 of chromosome 6, methylation CpG site cg 17983 of chromosome 6, methylation site cg 65cg 65740 of chromosome 6, methylation site cg 132740 of chromosome 1323531740, methylation site cg 3146 of chromosome 2, methylation site cg 16238754 of chromosome 2, methylation site cg 31387 of chromosome 4, methylation site cg 16238746 of chromosome 2, methylation site cg 162387 of chromosome 2, methylation site cg 31387 of chromosome 2, methylation site cg 162387 of chromosome 4, methylation site CpG, Methylation CpG site cg08313420 of chromosome 7, methylation CpG site cg08634133 of chromosome 7, methylation CpG site cg16555537 of chromosome 7, methylation CpG site cg27496339 of chromosome 7, methylation CpG site cg06688396 of chromosome 8, methylation CpG site cg08872550 of chromosome 8, methylation CpG site cg24023258 of chromosome 8, methylation CpG site cg24475171 of chromosome 9, methylation CpG site cg04179740 of chromosome 10, methylation CpG site cg 076194 of chromosome 10, methylation CpG site cg25104397 of chromosome 10, methylation site cg 65311 CpG of chromosome 11, methylation CpG site cg 13927 of chromosome 11, methylation site cg 20456 of chromosome 11, methylation site cg 27655 of chromosome 11, methylation site cg 274712 of chromosome 11, methylation site cg 09083091316 of chromosome 8, methylation site cg 13927 of chromosome 11, methylation site cg 450045316 of chromosome 11, methylation site cg20411, methylation site cg 274712 of chromosome 7, methylation site cg 274747 of chromosome 8, methylation site cg 0904747 of chromosome 8, methylation site cg 004747 of chromosome 8, methylation site cg 0904747 of chromosome 8, methylation site cg20411, and methylation site cgi of chromosome 0047316, Methylation CpG site cg15975802 of chromosome 12, methylation CpG site cg22277972 of chromosome 12, methylation CpG site cg14012112 of chromosome 13, methylation CpG site cg01557792 of chromosome 14, methylation CpG site cg11121623 of chromosome 14, methylation CpG site cg15691199 of chromosome 14, methylation CpG site cg13163919 of chromosome 15, methylation CpG site cg 716765 of chromosome 15, methylation CpG site cg26971042 of chromosome 15, methylation CpG site cg00762678 of chromosome 16, methylation CpG site cg02187822 of chromosome 16, methylation site cg03989617 of chromosome 16, methylation CpG site cg 28038 of chromosome 16, methylation site cg00762678 of chromosome 16, methylation site cg 0463 of chromosome 066955, methylation site cg 0709605 of chromosome 16, methylation site cg 7416, methylation site cg 7405 of chromosome 16, methylation site cg 7416, methylation site cg 08155 of chromosome 16, methylation site cg 7416 of chromosome 16, and methylation site cg 7435 of chromosome 16, Methylation CpG site cg02225720 of chromosome 17, methylation CpG site cg07850987 of chromosome 17, methylation CpG site cg09648933 of chromosome 17, methylation CpG site cg09915396 of chromosome 17, methylation CpG site cg11393185 of chromosome 17, methylation CpG site cg16807061 of chromosome 17, methylation CpG site cg21603891 of chromosome 17, methylation CpG site cg 26604203314 of chromosome 17, methylation CpG site cg20786131 of chromosome 18, methylation CpG site cg07381806 of chromosome 19, methylation CpG site cg11811510 of chromosome 19, methylation site cg 93868 of chromosome 19, methylation site cg 267995 of chromosome 19, methylation site cg 91717 of chromosome 20, methylation site cg 1688982 of chromosome 17, methylation site cg 948982 of chromosome 17, methylation site cg 267982 of chromosome 17, methylation site cg 948982 of chromosome 17, methylation site cg 94602642 of chromosome 18, methylation site cg 646082 of chromosome 20, methylation site cg 91717 of chromosome 20, methylation site cg 1688982 of chromosome 17, methylation site cg 946028982 of chromosome 17, and methylation site cg 948986822 of chromosome 17, The methylation CpG site cg05877528 of the 22 nd chromosome, the methylation CpG site cg11205006 of the 22 nd chromosome, the methylation CpG site cg21431832 of the 22 nd chromosome, and the methylation CpG site cg27087377 of the 22 nd chromosome.
More preferably, the methylated CpG site cg02497700 is located on ZNF238 gene; the methylated CpG site cg04437762 is located on IL6R gene; the methylated CpG site cg05697909 is located on HES5 gene; the methylated CpG site cg09277376 is located on MGC12982 gene; the methylated CpG site cg10540110 is located on KDM5B gene; the methylated CpG locus cg16399365 is positioned on ZNF238 gene; the methylated CpG site cg17176894 is located on LRRC8C gene; the methylated CpG site cg17985912 is located on LIN9 gene; the methylation CpG site cg18881723 is located on the SLAMF1 gene; the methylated CpG locus cg19698993 is positioned on ZNF238 gene; the methylated CpG locus cg21686694 is located on RNF220 gene; the methylated CpG site cg26348226 is located on ECE1 gene; the methylated CpG site cg03589296 is located on the MEIS1 gene; the methylated CpG site cg05874176 is located on the TLK1 gene; the methylation CpG locus cg06117093 is located on HDAC4 gene; the methylated CpG site cg07065759 is located on ANKRD44 gene; the methylated CpG site cg12287813 is located on the GCC2 gene; the methylated CpG site cg13651986 is located on the WIPF1 gene; the methylation CpG site cg15890754 is positioned on the ITGA6 gene; the methylated CpG site cg21319458 is located on BAZ2B gene; the methylation CpG site cg24749947 is positioned on ACVR1 gene; the methylated CpG site cg05551922 is located on GPX1 gene; the methylated CpG locus cg21254939 is located on the SORCS2 gene; the methylated CpG site cg27305383 is positioned on the HOPX gene; the methylated CpG site cg11958644 is located on RAPGEF6 gene; the methylation CpG locus cg01955533 is positioned on the CDKN1A gene; the methylation CpG site cg04353171 is positioned on FLOT1 gene; the methylated CpG site cg05217983 is located on RUNX2 gene; the methylated CpG site cg13265740 is located on C6orf115 gene; the methylation CpG site cg16254746 is positioned on FLOT1 gene; the methylated CpG site cg00653387 is positioned on PTN gene; the methylation CpG site cg03993154 is positioned on SLC13A1 gene; the methylated CpG site cg08313420 is located on the DAGLB gene; the methylation CpG site cg08634133 is located on ATP6V0E2 gene; the methylated CpG site cg16555537 is located on TRIP6 gene; the methylation CpG locus cg27496339 is positioned on BLVRA gene; the methylated CpG site cg06688396 is located on TMEM55A gene; the methylated CpG site cg08872550 is located on CA2 gene; the methylated CpG site cg24023258 is located on LY6K gene; the methylated CpG site cg24475171 is located on the C9orf78 gene; the methylated CpG site cg04179740 is located on the CDH23 gene; the methylated CpG site cg07616394 is located on HHEX gene; the methylated CpG site cg25104397 is located on the C10orf26 gene; the methylated CpG locus cg03365311 is located on the MIR129-2 gene; the methylated CpG site cg13912027 is located on FCHSD2 gene; the methylated CpG site cg20411756 is located on DRD4 gene; the methylated CpG locus cg27470087 is located on the RPS6KA4 gene; the methylated CpG site cg09045655 is located on HOXC9 gene; the methylated CpG site cg09183316 is located on the CTDSP2 gene; the methylated CpG site cg15975802 is located on PTPN6 gene; the methylated CpG site cg22277972 is located on the ISCU gene; the methylated CpG site cg14012112 is located on the PCDH9 gene; the methylated CpG site cg01557792 is positioned on KIAA0247 gene; the methylated CpG site cg11121623 is located on the PELI2 gene; the methylated CpG site cg15691199 is located on CEBPE gene; the methylation CpG site cg13163919 is positioned on the TLE3 gene; the methylated CpG site cg17716765 is located on APBA2 gene; the methylation CpG locus cg26971042 is positioned on the TLE3 gene; the methylation CpG locus cg00762678 is positioned on CBFA2T3 gene; the methylated CpG site cg02187822 is positioned on CBFA2T3 gene; the methylated CpG site cg03989617 is located on GPR56 gene; the methylated CpG site cg04528038 is located on TMEM159 gene; the methylation CpG locus cg04699663 is positioned on CBFA2T3 gene; the methylated CpG site cg06907405 is located on SIAH1 gene; the methylated CpG position cg07013955 is positioned on the IFT140 gene; the methylated CpG site cg08113187 is located on ZCCHC14 gene; the methylated CpG site cg02225720 is located on ITGAE gene; the methylated CpG site cg07850987 is located on HOXB3 gene; the methylated CpG site cg09648933 is located on CD79B gene; the methylated CpG site cg09915396 is located on the RAP1GAP2 gene; the methylated CpG site cg11393185 is located on TUSC5 gene; the methylated CpG site cg16807061 is located on the RAP1GAP2 gene; the methylated CpG locus cg21603891 is located on KCNJ2 gene; the methylated CpG site cg26604214 is located on RAP1GAP2 gene; the methylated CpG site cg20786131 is located on CABLES1 gene; the methylated CpG locus cg07381806 is positioned on the MOBKL2A gene; the methylated CpG site cg11811510 is located on CEACAM1 gene; the methylation CpG site cg16893868 is positioned on the LILRA2 gene; the methylation CpG site cg26796095 is positioned on the SAFB gene; the methylated CpG site cg01329151 is located on DIDO1 gene; the methylated CpG site cg25948982 is located on the C20orf123 gene; the methylated CpG site cg03307717 is located on the U2AF1 gene; the methylation CpG site cg05602642 is positioned on CERK gene; the methylated CpG site cg05877528 is located on HPS4 gene; the methylated CpG site cg11205006 is located on the HPS4 gene; the methylated CpG site cg21431832 is located on HPS4 gene; the methylated CpG site cg27087377 is located on HPS4 gene.
In a second aspect of the invention, the invention provides the use of the above-mentioned DNA methylation marker in the preparation of a diagnostic agent and/or an auxiliary diagnostic agent and/or a diagnostic kit for predicting the risk of schizophrenia occurrence.
In a third aspect of the present invention, the present invention provides a kit comprising the above-mentioned DNA methylation marker as a marker for predicting the risk of schizophrenia occurrence.
In a fourth aspect of the present invention, the present invention provides a method for screening the DNA methylation marker for predicting the risk of schizophrenia, comprising the steps of:
step 1), screening based on the methylation Beta value: detecting the methylation level of the whole genome of a first untreated schizophrenia patient and a normal contrast by adopting an Illumina 450K methylation chip, removing polymorphic CpG sites in the detected methylated CpG sites, and obtaining residual methylated CpG sites and the methylation level, namely Beta values;
step 2), threshold screening based on Fold-change (FC): further calculating the FC value of the Beta value of each methylated CpG locus according to the methylated Beta value of the residual methylated CpG loci calculated in the step 1), and further screening out the methylated CpG loci with the FC value larger than 1.15;
step 3), screening based on statistical test: selecting different detection methods according to the methylation Beta values of the methylation CpG sites screened out in the step 2) to carry out difference detection of two populations, and screening out the differential methylation CpG sites;
step 4), constructing a schizophrenia prediction model: constructing a schizophrenia prediction model for the methylation Beta value of the differential methylation CpG sites screened out in the step 3), verifying the methylation CpG sites by adopting a machine learning support vector machine model and ten-fold cross validation, calculating the prediction accuracy of the sample, and verifying the feasibility of the methylation CpG sites of the schizophrenia prediction model for predicting schizophrenia;
step 5), obtaining DNA methylation markers for predicting schizophrenia occurrence risk: one or more of the methylated CpG sites in the schizophrenia prediction model of the step 4) are DNA methylation markers which can predict the occurrence risk of schizophrenia.
In the technical scheme of the invention, in the step 3), if the methylation Beta value data of the methylation CpG loci screened out in the step 2) obeys normal distribution and meets the condition of homogeneity of variance, a t test is adopted; if the methylation Beta value data of the methylation CpG sites screened out in the step 2) obey normal distribution but do not meet the condition of homogeneity of variance, adopting an approximate t test; if the methylated Beta value data of the methylated CpG sites screened in the step 2) do not conform to normal distribution, Wilcoxon rank sum test is adopted, and the CpG sites with P value less than 0.05 after FDR correction are considered to have significant difference.
In the technical solution of the present invention, in the step 4), the machine learns the support vector machine model, performs data analysis using the R language platform (v3.6.3), uses the tool kit e1071(v 1.7.4), and combines with the ten-fold cross validation, constructs a prediction model using the methylation Beta values of the different CpG sites in the step 3) to perform mutual validation.
In the technical scheme of the present invention, in the step 4), a calculation formula of the prediction accuracy is as follows:
wherein a is the number of samples predicted as schizophrenia patients and actually also schizophrenia patients, b is the number of samples predicted as schizophrenia patients and actually normal persons, c is the number of samples predicted as normal persons and actually schizophrenia patients, and d is the number of samples predicted as normal persons and actually normal persons.
The invention has the beneficial effects that:
1. the invention provides a DNA methylation marker for predicting schizophrenia occurrence risk; the DNA methylation marker for predicting the occurrence risk of schizophrenia comprises at least one of the 100 methylation CpG sites, and the 100 methylation CpG sites can be combined to predict the occurrence risk of schizophrenia, so that the accuracy rate of predicting the occurrence risk of schizophrenia can be improved, the cost is saved, and the DNA methylation marker is suitable for popularization and application and has a better application prospect;
2. the invention provides an application of the methylation marker in preparing a diagnostic reagent and/or an auxiliary diagnostic reagent and/or a diagnostic kit for predicting schizophrenia occurrence risk; the occurrence risk of schizophrenia can be predicted by the methylation level of the DNA methylation marker;
3. the invention provides a method for screening the methylation marker, which can screen the DNA methylation marker for predicting the occurrence risk of mental cracking diseases, and is simple, scientific and reliable.
Drawings
FIG. 1 is a flow chart of a method for screening methylated CpG sites which can predict the risk of schizophrenia;
FIG. 2 is a graph of the average accuracy results of ten-fold cross-validation on the test set.
Detailed Description
The scheme of the invention will be explained with reference to the examples. It will be appreciated by those skilled in the art that the following examples are illustrative of the invention only and should not be taken as limiting the scope of the invention. The specific techniques or conditions are not specified in the examples, and are performed according to the techniques or conditions described in the literature in the field or according to the product specification.
Example 1: screening of DNA methylation markers for predicting risk of schizophrenia occurrence
A flow chart of a method for screening methylated CpG sites which can predict the risk of schizophrenia is shown in FIG. 1. A method for screening a DNA methylation marker for predicting the risk of schizophrenia occurrence, comprising the steps of,
step 1), screening based on the methylation Beta value: detecting the methylation level of the whole genome of a first untreated schizophrenia patient and a normal contrast by adopting an Illumina 450K methylation chip, removing polymorphic CpG sites in the detected methylated CpG sites, and obtaining the methylation level of the remaining 27 ten thousand methylated CpG sites, namely a Beta value;
in this example, 38 first untreated schizophrenia patients and 38 normal controls were recruited, whole blood DNA of all patients and controls was collected at a fixed time such as 6:30 a.m. at the time of group entry, 45 ten thousand methylated CpG sites in total were detected in the whole genome of all subjects based on the Illumina 450K whole genome methylation chip, and about 27 ten thousand methylated CpG sites remained after removal of CpG sites having polymorphism were obtained as a methylated Beta value for the methylated CpG sites.
Step 2): threshold screening based on Fold-change (FC): further calculating the FC value of the Beta value of each methylated CpG position according to the methylated Beta value of the residual methylated CpG position calculated in the step 1), wherein the calculation of the FC value is as follows:
in step 2), for two groups of sample data from schizophrenic patients (A in the following formula) and normal control group (B in the following formula), the FC value is defined as follows:
the next differential analysis, i.e., statistical test screening, was performed for methylated CpG sites with FC values greater than 1.15 (a total of 3494 CpG sites).
Step 3): screening based on statistical test: selecting different detection methods according to the methylation Beta values of 3494 methylation CpG sites screened in the step 2) to carry out differential detection on two populations (a schizophrenia patient group and a normal control group) and screening out differential methylation CpG sites;
in the step 3), if the methylation Beta value data of the methylation CpG sites screened out in the step 2) obey normal distribution and meet the condition of homogeneity of variance, adopting t test; if the methylation Beta value data of the methylation CpG sites screened out in the step 2) are normally distributed but do not meet the condition of homogeneity of variance, adopting an approximate t test; if the methylated Beta value data of the methylated CpG sites screened in the step 2) do not conform to normal distribution, Wilcoxon rank sum test is adopted, and the CpG sites with P value less than 0.05 corrected by FDR are considered to have significant difference.
In the step, 100 methylated CpG sites with difference among groups are screened out through statistical test.
Step 4), constructing a schizophrenia prediction model: constructing a schizophrenia prediction model for methylation Beta values of the 100 differential methylation CpG sites screened out in the step 3), verifying the methylation CpG sites by adopting a machine learning support vector machine model and ten-fold cross validation, calculating the prediction accuracy of the sample, and verifying the feasibility of the methylation CpG sites of the schizophrenia prediction model for predicting schizophrenia;
cross-fold cross validation, 10-fold cross-validation, is a commonly used test method to test the accuracy of algorithm predictions. The data set is divided into ten parts, and 9 parts of the data set are taken as training data and 1 part of the data set is taken as test data for prediction in turn. Each test will yield a corresponding accuracy. The average of the accuracy of the 10 results was used as an estimate of the accuracy of the algorithm. In the step 4), the machine learning support vector machine model uses an R language platform (v3.6.3) to perform data analysis, uses a tool kit e1071(v 1.7.4), and combines with ten-fold cross validation, and constructs a prediction model by using the methylation Beta values of 100 differentially methylated CpG sites in the step 3) to perform mutual validation.
In the step 4), a calculation formula of the prediction accuracy is as follows:
wherein a is the number of samples predicted as schizophrenia patients and actually also schizophrenia patients, b is the number of samples predicted as schizophrenia patients and actually normal persons, c is the number of samples predicted as normal persons and actually schizophrenia patients, and d is the number of samples predicted as normal persons and actually normal persons.
The step (4) is detailed as follows: this example uses a support vector machine method, uses the R language platform (v3.6.3) for data analysis, uses the tool kit e1071(v 1.7.4), and combines with cross validation to construct a schizophrenia occurrence risk prediction model by using the methylation Beta values of 100 differentially methylated CpG sites in the above step (3) for mutual validation.
In this example, the R language platform (v3.6.3) was used for data analysis, and the tool kit used was e1071(v 1.7.4); methylation analysis of sample data yielded 100 significant (corrected P-value <0.05), methylated CpG sites likely to be associated with risk of schizophrenia development (see table 1), and the methylation Beta value of the methylated CpG sites, i.e. intensity value from methylated bead type/(intensity value from methylated + intensity value from unmethylated bead type +100), was calculated to determine the DNA methylation level. The methylated CpG sites are DNA methylation markers for predicting the occurrence risk of schizophrenia. Table 1 shows 100 methylated CpG sites which are predictive of the risk of schizophrenia.
TABLE 1 DNA methylation markers for predicting risk of schizophrenia occurrence
Establishing a schizophrenia occurrence risk prediction model by using the methylation Beta value of the methylation CpG locus, and verifying the feasibility of the model by calculating the sample prediction accuracy, wherein the sample prediction accuracy calculation formula is as follows:
wherein a is the number of samples predicted as schizophrenia patients and actually also schizophrenia patients, b is the number of samples predicted as schizophrenia patients and actually normal persons, c is the number of samples predicted as normal persons and actually schizophrenia patients, and d is the number of samples predicted as normal persons and actually normal persons.
The prediction models were mutually verified using machine learning methods (support vector machine, cross-validation):
among machine learning methods, a Support Vector Machine (SVM) is a supervised machine learning method, which is generally used for binary classification of data. Given input data and a learning objective X ═ X in a classification problem1,...,XN},y＝{y1,...,yN-each sample of input data contains a plurality of features, thereby forming a feature space: xi＝[X1,...,Xn]Is epsilon.X. The learning objective y ∈ { -1,1} is a binary variable representing a negative case and a positive case.
If the feature space where the input data is located has a hyperplane serving as a decision boundary, the learning target is separated according to a positive class and a negative class, and the distance between the point of any sample and the plane is more than or equal to 1:
decision boundary: w is aTX+b＝0
Point-to-plane distance: y isi(wTXi+b)≥1
The classification problem is said to have linear separability. The parameters w and b are the normal vector and the intercept, respectively, of the hyperplane.
Decision boundaries that satisfy this condition actually construct two parallel hyperplanes as interval boundaries to differentiate the classification of samples.
Samples above the interval boundary are judged to be positive example samples, and samples below the interval boundary are judged to be negative example samples. Defining the distance between two spaced boundaries as
The positive and negative examples located on the interval boundary are used as support vectors.
The applicant predicts the occurrence risk of the patient by using the methylation level, namely Beta value, of the 100 methylation CpG sites with the difference between groups through a machine learning Support Vector Machine (SVM) method, wherein the average accuracy of ten-fold cross validation on a test set is 85.05%, and the average accuracy of each ten-fold cross validation on the test set is shown in FIG. 2. In the figure, the abscissa represents the number of times, and the ordinate represents the accuracy.
The DNA methylation marker for predicting the occurrence risk of schizophrenia disclosed by the invention comprises at least one of the 100 methylation CpG sites, one or more of the 100 methylation CpG sites or the combination of the 100 methylation CpG sites can be used for predicting the occurrence risk of schizophrenia, the prediction accuracy of the occurrence risk of schizophrenia can be obviously improved, the cost is saved, and the DNA methylation marker is suitable for popularization and application and has a better application prospect.
Step 5), obtaining DNA methylation markers for predicting schizophrenia occurrence risk: one or more of the methylated CpG sites in the schizophrenia prediction model in the step (4) are DNA methylation markers which can predict the occurrence risk of schizophrenia.
The differential methylation CpG sites between the two groups obtained by the screening method of the DNA methylation marker for predicting the occurrence risk of schizophrenia are 100. The CpG sites that can predict the efficacy of a patient are as follows (see table 1): the methylation CpG site cg02497700 of the human chromosome 1, the methylation CpG site cg04437762 of the chromosome 1, the methylation CpG site cg05697909 of the chromosome 1, the methylation CpG site cg09277376 of the chromosome 1, the methylation CpG site cg10540110 of the chromosome 1, the methylation CpG site cg16399365 of the chromosome 1, the methylation CpG site cg17176894 of the chromosome 1, the methylation CpG site cg17985912 of the chromosome 1, the methylation CpG site cg 81723 of the chromosome 1, the methylation CpG site cg19698993 of the chromosome 1, the methylation CpG site cg 21694 of the chromosome 1, the methylation CpG site cg24155129 of the chromosome 1, the methylation CpG site cg 268226 of the chromosome 1, the methylation site cg 1965896 of the chromosome 2, the methylation site cg 055896 of the chromosome 1, the methylation site cg 07075032 of the chromosome 1, the methylation site cg 7503759 of the chromosome 1, the methylation site cg 070989 of the chromosome 1, the methylation site cg 07098039286696 of the chromosome 1, the methylation site cg 65036593 of the chromosome 1, the methylation site cg 65039286696 of the chromosome 1, the methylation site cg 659 of the methylation site cg 1709, The methylation CpG site cg12287813 of chromosome 2, the methylation CpG site cg13424923 of chromosome 2, the methylation CpG site cg13651986 of chromosome 2, the methylation CpG site cg15890754 of chromosome 2, the methylation CpG site cg21319458 of chromosome 2, the methylation CpG site cg24749947 of chromosome 2, the methylation CpG site cg26823762 of chromosome 2, the methylation CpG site cg05551922 of chromosome 3, the methylation CpG site cg12198140 of chromosome 3, the methylation CpG site cg14011327 of chromosome 4, the methylation CpG site cg21254939 of chromosome 4, the methylation site cg27305383 of chromosome 4, the methylation CpG site cg11958644 of chromosome 5, the methylation site cg01955533 of chromosome 6, the methylation site cg01955533 of chromosome 2, the methylation site cg 3531740, the methylation site cg 1323 of chromosome 2, the methylation site cg 179871 of chromosome 3, the methylation site cg 019989871 of chromosome 2, the methylation site cg01955533 of chromosome 2, the methylation site cg 313531740, the methylation site cg 31740 of chromosome 3, the methylation site cg 1323, the methylation site cg 98989871 of chromosome 3, The methylation CpG site cg16254746 of chromosome 6, the methylation CpG site cg00653387 of chromosome 7, the methylation CpG site cg02627991 of chromosome 7, the methylation CpG site cg03993154 of chromosome 7, the methylation CpG site cg08313420 of chromosome 7, the methylation CpG site cg08634133 of chromosome 7, the methylation CpG site cg 55537 of chromosome 7, the methylation CpG site cg27496339 of chromosome 7, the methylation CpG site cg06688396 of chromosome 8, the methylation CpG site cg08872550 of chromosome 8, the methylation CpG site cg24023258 of chromosome 8, the methylation site cg24475171 of chromosome 9, the methylation site CpG 79740 of chromosome 10, the methylation site cg 637994 of chromosome 10, the methylation site cg 076194 of chromosome 10, the methylation site cg 613975 of chromosome 7, the methylation site cg 12011 of chromosome 7, the methylation site cg 251311 of chromosome 10, the methylation site cg 25111 of chromosome 7, the methylation site cg 25127 of chromosome 7, the methylation site cg 251563229 of chromosome 7, the methylation site cg 6480 of chromosome 7, the methylation site cg 64045632563229 of chromosome 7, the methylation site of chromosome 10, the methylation site cg 25127 of chromosome 10, the methylation site cg 63797927 of chromosome 10, the methylation site cg 2512, the methylation site cga methylation, Methylated CpG site cg15374924 of chromosome 11, methylated CpG site cg20411756 of chromosome 11, methylated CpG site cg27470087 of chromosome 11, methylated CpG site cg09045655 of chromosome 12, methylated CpG site cg09183316 of chromosome 12, methylated CpG site cg15975802 of chromosome 12, methylated CpG site cg22277972 of chromosome 12, methylated CpG site of chromosome 13, methylated CpG site cg 68893 of chromosome 13, methylated CpG site cg14012 of chromosome 13, methylated CpG site cg01557792 of chromosome 14, methylated site cg11121623 of chromosome 14, methylated site cg15691199 of chromosome 14, methylated site cg 95118 of chromosome 14, methylated site cg 951 of chromosome 11, methylated site cg 951 of chromosome 15, methylated site cg 03919 of chromosome 12, methylated site cg 919 of chromosome 12, methylated site cg 11121699 of chromosome 12, methylated site cg 13429 of chromosome 14, methylated site cg 951 of chromosome 11, methylated site cg 951, and methylated site cg 03919 of chromosome 15, Methylation CpG site cg17716765 of chromosome 15, methylation CpG site cg26971042 of chromosome 15, methylation CpG site cg00762678 of chromosome 16, methylation CpG site cg02187822 of chromosome 16, methylation CpG site cg03989617 of chromosome 16, methylation CpG site cg04528038 of chromosome 16, methylation CpG site cg04699663 of chromosome 16, methylation CpG site cg06907405 of chromosome 16, methylation CpG site cg07013955 of chromosome 16, methylation CpG site cg 08187 of chromosome 16, methylation CpG site cg26706803 of chromosome 16, methylation site cg02225720 of chromosome 17, methylation CpG site cg 078587 of chromosome 17, methylation site cg 07099133 of chromosome 17, methylation site cg 09640933 of chromosome 17, methylation site cg 1680964185 of chromosome 17, methylation site cg 096409185 of chromosome 17, methylation site cg 09640961 of chromosome 17, methylation site cg 09640917 of chromosome 16, methylation site cg 096409640917, and methylation site cg 09640964096409185 of chromosome 16, Methylated CpG site cg21603891 of chromosome 17, methylated CpG site cg22635673 of chromosome 17, methylated CpG site cg26604214 of chromosome 17, methylated CpG site cg20786131 of chromosome 18, methylated CpG site cg07381806 of chromosome 19, methylated CpG site cg11811510 of chromosome 19, methylated CpG site cg 168868 of chromosome 19, methylated CpG site cg26796095 of chromosome 19, methylated CpG site cg00682367 of chromosome 20, methylated CpG site cg01329151 of chromosome 20, methylated CpG site cg25948982 of chromosome 20, methylated CpG site cg03307717 of chromosome 21, methylated CpG site cg05602642 of chromosome 22, methylated CpG site cg05877528 of chromosome 22, methylated CpG site cg11205006 of chromosome 22, methylated CpG site cg21431832 of chromosome 22, and methylated CpG site cg27087377 of chromosome 22.
The risk of schizophrenia occurrence is predicted by combining the methylated Beta values of one or more than one of the 100 methylated CpG sites, and the method is suitable for large-scale popularization and application.
Example 2
This example provides a diagnostic kit for predicting the risk of schizophrenia, which uses the methylation marker as a marker of the efficacy of antipsychotic drugs.
Further, the present embodiment provides a method for predicting the risk of schizophrenia occurrence, comprising:
1. extracting the genome DNA of a sample to be detected;
2. performing PCR amplification by using the kit by using the genomic DNA in the step 1 as a template;
3. sequencing with bisulfite;
4. obtaining a DNA methylation detection result;
5. according to the methylation levels of 100 methylated CpG sites in the table 1, the prediction of the schizophrenia occurrence risk of the sample to be tested is realized.
Although embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that changes, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (9)
1. A DNA methylation marker for predicting schizophrenia occurrence risk, wherein the DNA methylation marker for predicting schizophrenia occurrence risk is selected from at least one methylated CpG site on human chromosome 1-22.
2. The DNA methylation marker according to claim 1, wherein the DNA methylation marker for predicting the risk of schizophrenia is selected from the group consisting of a methylation CpG site cg02497700 of chromosome 1, a methylation CpG site cg04437762 of chromosome 1, a methylation CpG site cg05697909 of chromosome 1, a methylation CpG site cg09277376 of chromosome 1, a methylation CpG site cg10540110 of chromosome 1, a methylation CpG site cg16399365 of chromosome 1, a methylation CpG site cg17176894 of chromosome 1, a methylation CpG site cg17985912 of chromosome 1, a methylation CpG site cg18881723 of chromosome 1, a methylation CpG 19698993 of chromosome 1, a methylation site cg21686694 of chromosome 1, a methylation site cg 55129 of chromosome 1, a methylation site cg 925826 of chromosome 1, a methylation site cg 2682268226 of chromosome 1, a methylation site cg 9282034 of chromosome 1, a methylation site cg 9286694 of chromosome 1, a methylation site cg 55129 of chromosome 1, a methylation site cg 340326 of chromosome 1, and a methylation site cg 92827626 of chromosome 1, Methylation CpG site cg05874176 of chromosome 2, methylation CpG site cg06117093 of chromosome 2, methylation CpG site cg07065759 of chromosome 2, methylation CpG site cg12287813 of chromosome 2, methylation CpG site cg13424923 of chromosome 2, methylation CpG site cg 136986 of chromosome 2, methylation CpG site cg15890754 of chromosome 2, methylation CpG site cg21319458 of chromosome 2, methylation CpG site cg 247447 of chromosome 2, methylation CpG site cg26823762 of chromosome 2, methylation CpG site cg05551922 of chromosome 3, methylation CpG site cg12198140 of chromosome 3, methylation CpG site cg14011327 of chromosome 4, methylation site cg 019559 of chromosome 4, methylation site cg 54533 of chromosome 4, methylation site cg 273158383 of chromosome 2, methylation site cg 121383 of chromosome 2, methylation site cg 019383 of chromosome 4, methylation site cg 019383 of chromosome 2, methylation site cg019 31383 of chromosome 4, methylation site cg 01946 g of chromosome 2, methylation site cg019 31383 of chromosome 2, methylation site cg019 31559 of chromosome 4, methylation site cg 01927533 of chromosome 2, methylation site cg 31383 of chromosome 2, methylation site cg 3158383 of chromosome 2, methylation site cg 31383 of chromosome 2, methylation site cg 3158383 of chromosome 2, methylation site cg of, The methylation CpG site cg05217983 of chromosome 6, the methylation CpG site cg13265740 of chromosome 6, the methylation CpG site cg16254746 of chromosome 6, the methylation CpG site cg00653387 of chromosome 7, the methylation CpG site cg02627991 of chromosome 7, the methylation CpG site cg03993154 of chromosome 7, the methylation CpG site cg08313420 of chromosome 7, the methylation CpG site cg08634133 of chromosome 7, the methylation CpG site cg16555537 of chromosome 7, the methylation CpG site cg27496339 of chromosome 7, the methylation CpG site cg 24688396 of chromosome 8, the methylation site cg08872550 of chromosome 8, the methylation site cg24023258 of chromosome 8, the methylation site cg 470414704171 of chromosome 9, the methylation site cg 2461396 of chromosome 6110, the methylation site cg 043976 of chromosome 8, the methylation site cg 251045631 of chromosome 6, the methylation site cg 2512515631 of chromosome 11, the methylation site cg 25155537 of chromosome 7, the methylation site cg 6356357980 of chromosome 7, the methylation site cg 6404475635 of chromosome 8, the methylation site cg 6404477994 of chromosome 11, the methylation site cg 2515635 of chromosome 11, the methylation site cg 2512, the methylation site of chromosome 7, the methylation site cg 64043976 of chromosome 7, the methylation site cg, Methylated CpG site cg13912027 of chromosome 11, methylated CpG site cg15374924 of chromosome 11, methylated CpG site cg20411756 of chromosome 11, methylated CpG site cg27470087 of chromosome 11, methylated CpG site cg09045655 of chromosome 12, methylated CpG site cg09183316 of chromosome 12, methylated CpG site cg15975802 of chromosome 12, methylated CpG site cg22277972 of chromosome 12, methylated CpG site cg03268893 of chromosome 13, methylated CpG site cg14012112 of chromosome 13, methylated CpG site cg01557792 of chromosome 14, methylated site cg11121623 of chromosome 14, methylated CpG site cg 91199 of chromosome 14, methylated site cg 95118 of chromosome 15, methylated site cg 037165 of chromosome 11, methylated site cg 679715, methylated site cg 9775 of chromosome 12, methylated site cg 97919 of chromosome 14, methylated site cg 799799 of chromosome 15, methylated site cg 7165, methylated site cg 9775 of chromosome 12, methylated site cg 9799 of chromosome 12, methylated site cg 7165, methylated site cg 7197919 of chromosome 15, methylated site cg 7165, methylated site cg 9799 of chromosome 12, methylated site cg 7165, methylated site cg 7197919 of chromosome 12, methylated site cg 7165, methylated site cg 719775, methylated site cg 7165, Methylation CpG site cg00762678 of chromosome 16, methylation CpG site cg 28038 of chromosome 16, methylation CpG site cg02187822 of chromosome 16, methylation CpG site cg03989617 of chromosome 16, methylation CpG site cg 04538 of chromosome 16, methylation CpG site cg04699663 of chromosome 16, methylation CpG site cg 067405 of chromosome 16, methylation CpG site cg07013955 of chromosome 16, methylation CpG site cg08113187 of chromosome 16, methylation CpG site cg26706803 of chromosome 16, methylation CpG site cg 25720 of chromosome 17, methylation CpG site cg07850987 of chromosome 17, methylation site cg09648933 of chromosome 17, methylation site CpG 09915396 of chromosome 17, methylation site cg 113185 of chromosome 17, methylation site cg 9317, methylation site cg09648933 of chromosome 17, methylation site cg 094261 of chromosome 17, methylation site cg 674217, methylation site cg 034226 of chromosome 17, methylation site cg 677217, methylation site cg 07060893 of chromosome 16, methylation site cg 677217, methylation site cg 67893 of chromosome 16, methylation site cg 7260606072607217, chromosome 16, methylation site cg 728961, methylation site cg 72893 of chromosome 16, methylation site cg 7260608961, methylation site cg 726060606060893, and methylation site cb, Methylated CpG site cg20786131 of chromosome 18, methylated CpG site cg07381806 of chromosome 19, methylated CpG site cg11811510 of chromosome 19, methylated CpG site cg16893868 of chromosome 19, methylated CpG site cg26796095 of chromosome 19, methylated CpG site cg00682367 of chromosome 20, methylated CpG site cg01329151 of chromosome 20, methylated CpG site cg25948982 of chromosome 20, methylated CpG site cg03307717 of chromosome 21, methylated CpG site cg 642 of chromosome 22, methylated CpG site cg05877528 of chromosome 22, methylated CpG site cg11205006 of chromosome 22, methylated CpG site cg21431832 of chromosome 22, and methylated site cg 270377 of chromosome 22.
3. The DNA methylation marker according to claim 2, wherein the methylation CpG site cg02497700 is located on ZNF238 gene; the methylated CpG site cg04437762 is located on IL6R gene; the methylated CpG site cg05697909 is located on HES5 gene; the methylated CpG site cg09277376 is located on MGC12982 gene; the methylated CpG site cg10540110 is located on KDM5B gene; the methylated CpG locus cg16399365 is positioned on ZNF238 gene; the methylated CpG site cg17176894 is located on LRRC8C gene; the methylated CpG site cg17985912 is located on LIN9 gene; the methylation CpG site cg18881723 is located on the SLAMF1 gene; the methylated CpG locus cg19698993 is positioned on ZNF238 gene; the methylated CpG locus cg21686694 is located on RNF220 gene; the methylated CpG site cg26348226 is located on ECE1 gene; the methylated CpG site cg03589296 is located on the MEIS1 gene; the methylated CpG site cg05874176 is located on the TLK1 gene; the methylation CpG locus cg06117093 is located on HDAC4 gene; the methylated CpG site cg07065759 is located on ANKRD44 gene; the methylated CpG site cg12287813 is located on the GCC2 gene; the methylated CpG site cg13651986 is located on the WIPF1 gene; the methylation CpG site cg15890754 is positioned on the ITGA6 gene; the methylated CpG site cg21319458 is located on BAZ2B gene; the methylation CpG site cg24749947 is positioned on ACVR1 gene; the methylated CpG site cg05551922 is located on GPX1 gene; the methylated CpG locus cg21254939 is located on the SORCS2 gene; the methylated CpG site cg27305383 is positioned on the HOPX gene; the methylated CpG site cg11958644 is located on RAPGEF6 gene; the methylation CpG locus cg01955533 is positioned on the CDKN1A gene; the methylation CpG site cg04353171 is positioned on FLOT1 gene; the methylated CpG site cg05217983 is located on RUNX2 gene; the methylated CpG site cg13265740 is located on C6orf115 gene; the methylation CpG site cg16254746 is positioned on FLOT1 gene; the methylated CpG site cg00653387 is positioned on PTN gene; the methylation CpG site cg03993154 is positioned on SLC13A1 gene; the methylated CpG site cg08313420 is located on the DAGLB gene; the methylation CpG site cg08634133 is located on ATP6V0E2 gene; the methylated CpG site cg16555537 is located on TRIP6 gene; the methylation CpG locus cg27496339 is positioned on BLVRA gene; the methylated CpG site cg06688396 is located on TMEM55A gene; the methylated CpG site cg08872550 is located on CA2 gene; the methylated CpG site cg24023258 is located on LY6K gene; the methylated CpG site cg24475171 is located on the C9orf78 gene; the methylated CpG site cg04179740 is located on the CDH23 gene; the methylated CpG site cg07616394 is located on HHEX gene; the methylated CpG site cg25104397 is located on the C10orf26 gene; the methylated CpG locus cg03365311 is located on the MIR129-2 gene; the methylated CpG site cg13912027 is located on FCHSD2 gene; the methylated CpG site cg20411756 is located on DRD4 gene; the methylated CpG locus cg27470087 is located on the RPS6KA4 gene; the methylated CpG site cg09045655 is located on HOXC9 gene; the methylated CpG site cg09183316 is located on the CTDSP2 gene; the methylated CpG site cg15975802 is located on PTPN6 gene; the methylated CpG site cg22277972 is located on the ISCU gene; the methylated CpG site cg14012112 is located on the PCDH9 gene; the methylated CpG site cg01557792 is positioned on KIAA0247 gene; the methylated CpG site cg11121623 is located on the PELI2 gene; the methylated CpG site cg15691199 is located on CEBPE gene; the methylation CpG site cg13163919 is positioned on the TLE3 gene; the methylated CpG site cg17716765 is located on APBA2 gene; the methylation CpG locus cg26971042 is positioned on the TLE3 gene; the methylation CpG locus cg00762678 is positioned on CBFA2T3 gene; the methylated CpG site cg02187822 is positioned on CBFA2T3 gene; the methylated CpG site cg03989617 is located on GPR56 gene; the methylated CpG site cg04528038 is located on TMEM159 gene; the methylation CpG locus cg04699663 is positioned on CBFA2T3 gene; the methylated CpG site cg06907405 is located on SIAH1 gene; the methylated CpG position cg07013955 is positioned on the IFT140 gene; the methylated CpG site cg08113187 is located on ZCCHC14 gene; the methylated CpG site cg02225720 is located on ITGAE gene; the methylated CpG site cg07850987 is located on the HOXB3 gene; the methylated CpG site cg09648933 is located on CD79B gene; the methylated CpG site cg09915396 is located on the RAP1GAP2 gene; the methylated CpG site cg11393185 is located on TUSC5 gene; the methylated CpG site cg16807061 is located on the RAP1GAP2 gene; the methylated CpG locus cg21603891 is located on KCNJ2 gene; the methylated CpG site cg26604214 is located on RAP1GAP2 gene; the methylated CpG site cg20786131 is located on CABLES1 gene; the methylated CpG locus cg07381806 is positioned on the MOBKL2A gene; the methylated CpG site cg11811510 is located on CEACAM1 gene; the methylation CpG site cg16893868 is positioned on the LILRA2 gene; the methylation CpG site cg26796095 is positioned on the SAFB gene; the methylated CpG site cg01329151 is located on DIDO1 gene; the methylated CpG site cg25948982 is located on the C20orf123 gene; the methylated CpG site cg03307717 is located on the U2AF1 gene; the methylation CpG site cg05602642 is positioned on CERK gene; the methylated CpG site cg05877528 is located on HPS4 gene; the methylated CpG site cg11205006 is located on the HPS4 gene; the methylated CpG site cg21431832 is located on HPS4 gene; the methylated CpG site cg27087377 is located on the HPS4 gene.
4. Use of a DNA methylation marker according to claim 1 or 2 or 3 for the preparation of a diagnostic agent and/or an auxiliary diagnostic agent and/or a diagnostic kit for predicting the risk of schizophrenia occurrence.
5. A kit comprising one or more of the methylation markers of claim 1, 2 or 3 as a marker for predicting the risk of schizophrenia.
6. A method for screening a DNA methylation marker for predicting the risk of schizophrenia occurrence, comprising the steps of:
step 1), screening based on the methylation Beta value: detecting the methylation level of the whole genome of a first untreated schizophrenia patient and a normal contrast by adopting an Illumina 450K methylation chip, removing polymorphic CpG sites in the detected methylated CpG sites, and obtaining residual methylated CpG sites and the methylation level, namely Beta values;
step 2), threshold screening based on Fold-change (FC): further calculating the FC value of the Beta value of each methylated CpG locus according to the methylated Beta value of the residual methylated CpG loci calculated in the step 1), and further screening out the methylated CpG loci with the FC value larger than 1.15;
step 3), screening based on statistical test: selecting different detection methods according to the methylation Beta values of the methylation CpG sites screened out in the step 2) to carry out difference detection of two populations, and screening out the differential methylation CpG sites;
step 4), constructing a schizophrenia prediction model: constructing a schizophrenia prediction model for the methylation Beta value of the differential methylation CpG sites screened out in the step 3), calculating the prediction accuracy of the sample by adopting a machine learning support vector machine model and cross verifying the methylation CpG sites by ten folds, and verifying the feasibility of the methylation CpG sites of the schizophrenia prediction model for predicting schizophrenia;
step 5), obtaining DNA methylation markers for predicting schizophrenia occurrence risk: one or more of the methylated CpG sites in the schizophrenia prediction model of the step 4) are DNA methylation markers which can predict the occurrence risk of schizophrenia.
7. The screening method according to claim 6, wherein in the step 3), if the methylated Beta value data of the methylated CpG sites screened in the step 2) obeys normal distribution and satisfies the condition of homogeneity of variance, a t test is adopted; if the methylation Beta value data of the methylation CpG sites screened out in the step 2) obey normal distribution but do not meet the condition of homogeneity of variance, adopting an approximate t test; if the methylated Beta value data of the methylated CpG sites screened in the step 2) do not conform to normal distribution, Wilcoxon rank sum test is adopted, and the CpG sites with P value less than 0.05 corrected by FDR are considered to have significant difference.
8. The screening method according to claim 6, wherein in the step 4), the machine learning support vector machine model is used for data analysis by using an R language platform (v3.6.3), the used tool kit is e1071(v 1.7.4), and combined with ten-fold cross validation, a prediction model is constructed by using the methylation Beta value of the differential methylation CpG sites in the step 3) for mutual validation.
9. The screening method according to claim 6, wherein in the step 4), the calculation formula of the prediction accuracy is as follows:
wherein a is the number of samples predicted as being a schizophrenia patient and actually also a schizophrenia patient, b is the number of samples predicted as being a schizophrenia patient and actually being a normal person, c is the number of samples predicted as being a normal person and actually being a schizophrenia patient, and d is the number of samples predicted as being a normal person and actually also being a normal person.
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