KR102113549B1 - Gene methylation markers for exposure to air pollutants and methods for providing information using the same - Google Patents

Abstract

The present invention relates to a gene methylation marker for exposure to air pollution and a method for providing information using the same to determine whether a gene is methylated or not by performing an epigenome-wide association study (EWAS) on a sample with regard to exposure to air pollutants, so as to evaluate an effect of air pollutants on the body. With regard to long-term exposure to air pollution, it is possible to identify a differentiated DNA methylation signal from blood and determine correlation between differentiated methylation and differentiated gene expression. Differentiated methylated CpG and region may be used as a potential bio marker for exposure to air pollution, so this result can be used in analysis of a mechanism which associates the exposure to air pollution with harmful health results.

Description

Gene methylation markers for exposure to air pollutants and methods for providing information using the same}

The present invention relates to a gene methylation marker for exposure to air pollution and a method for providing information using the same, and more specifically, it is determined whether the gene is methylated by an epigenetic-wide range association analysis (EWAS) for air pollutant exposure from a sample. And it relates to a gene methylation marker for air pollution exposure and a method for providing information using the same to enable the evaluation of the effect of the body on air pollutants.

In general, exposure to air pollution has been well documented for adverse effects on health, including cardiovascular disease and lung function. Oxidative stress and inflammation are the underlying mechanisms, but the specific data supporting these connections are lacking. Although evidence suggests that exposure to air pollution has a negative impact on health, the underlying mechanisms are not well understood.

DNA methylation, a epigenetic modification that can affect gene expression, is known to be associated with smoking (Joehanes et al. 2016). There is little data, but there is also evidence that air pollution affects methylation (Chi et al., Hou et al., Lichtenfels et al., 2018, Plusquin et al., 2017).

Most studies of long-term exposure and methylation of air pollution have been conducted in white adults, and evidence for differentially methylated probes (DMPs) in cross-study studies is rare.

Ana Juliade F.C.Lichtenfels, Diana A.vanderPlaat et al. Long-term Air Pollution Exposure, Genome-wide DNA Methylation and Lung Function in the LifeLines Cohort Study (2018) Plusquin, M., Guida, F., Polidoro, S. et al. DNA methylation and exposure to ambient air pollution in two prospective cohorts. (2017)

Therefore, the present inventors evaluated the relationship between long-term exposure to nitrogen dioxide (NO ₂ ) and particulate matter (PM ₁₀ ) having a diameter of 10 μm or less with DNA methylation in blood isolated from adult participants. Different C-phosphate-G (CpG) probe levels and different methylated signals with respect to air pollution exposure were identified at both regional levels associated with multiple CpG probes (CpGs).

In addition, the present invention was completed by evaluating whether the methylation level of DMPs is related to the expression level of the associated transcript in a large independent data sheet with gene expression and DNA methylation.

Accordingly, it is an object of the present invention to provide a DNA methylation marker for exposure to air pollutants.

In addition, another object of the present invention is to provide a method for providing gene methylation information for exposure to air pollutants.

According to an embodiment of the present invention for achieving the above object, to separate the DNA from the sample collected from the subject object; It provides a method for providing gene methylation information for air pollution exposure, comprising detecting methylation of one or more genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57, and C20orf123 from the DNA.

In addition, according to another embodiment of the present invention, gene methylation analysis for exposure to air pollution, comprising a substance capable of detecting methylation of one or more genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57 and C20orf123 Provided is a composition.

In addition, according to another embodiment of the present invention, there is provided a kit for analyzing gene methylation for exposure to air pollution, comprising a composition for analyzing gene methylation for exposure to air pollution.

According to the present invention as described above, it is possible to identify different DNA methylation signals in the blood in relation to long-term exposure to air pollution, and to determine the relationship between different methylation and different gene expression. CpG and regions showing different methylation can serve as potential biomarkers for air pollution exposure. These results can be used to analyze mechanisms linking exposure to air pollution with harmful health outcomes.

The effects according to the present invention in the above are not limited to the above, and other effects of the present invention are clearly understood by those skilled in the art to which the present invention pertains through the examples and claims described below. Will be understandable.

Figure 1 shows the workflow of the epigenetic-wide range association analysis for long-term exposure to air pollution of the present invention.
Figure 2 shows the Manhattan plot and quantile-quantile plot of epigenetic-wide range association analysis for long-term exposure to air pollution in the present invention.
(A) Manhattan plot showing EWAS for PM ₁₀ long-term exposure
(B) Quantile-quantile plot showing EWAS for PM ₁₀ long-term exposure
(C) Manhattan plot showing EWAS for NO ₂ long-term exposure
(D) Quantile-quantile plot showing EWAS for NO ₂ long-term exposure
Figure 3 is a visualization of the area for the association of long-term exposure to air pollution (PM10 and NO ₂ ) of the present invention and blood DNA methylation.
(A) Different methylation in TRIM39 with respect to PM ₁₀ exposure
(B) Different methylation in LTA with respect to PM ₁₀ exposure
(C) Different methylation in LTA with respect to NO ₂ exposure
(D) Different methylation in TRIM39 with respect to NO ₂ exposure
Figure 4 is a visualization of the route analysis results of the present invention.
(A) Heat map showing reinforcement of gene (row) and pathway (column)
(B) Categories related to immunology of genes in 6 pathways in relation to PM ₁₀ and NO ₂
Figure 5 shows a significant correlation (FDR <0.05) with PM ₁₀ exposure of tissue and cell type specific enrichment patterns in CpGs.
Figure 6 shows a significant correlation (FDR <0.05) with NO ₂ exposure of tissue and cell type specific enrichment patterns in CpGs.

Hereinafter, the present invention will be described in more detail.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art to which the present invention pertains may easily practice. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. In addition, in order to clearly describe the present invention, parts not related to the description are omitted.

In the present invention, when a part is said to "include" a certain component, it means that the component may be further included other than excluding other components, unless otherwise stated.

The terms "about", "substantially", and the like used throughout the specification of the present invention are used in terms of or close to those values when manufacturing and material tolerances unique to the stated meanings are presented, and To aid understanding, accurate or absolute figures are used to prevent unconscionable abusers from unduly using the disclosed disclosure.

The term "~ (step)" or "step of" as used in the present specification does not mean "step for".

Throughout the specification of the present invention, the term “combination of these” included in the expression of the marki form means one or more mixtures or combinations selected from the group consisting of the components described in the expression of the marki form, wherein the composition It means to include one or more selected from the group of elements.

Throughout the present specification, “sample” or “sample” includes a wide range of biological samples obtained from individuals, body fluids, cell lines, tissue cultures, etc., depending on the type of analysis being performed, eg, blood, serum , Plasma, urine, cells, tissues, biopsies, paraffin tissues, and microneedle aspiration samples, but are not limited thereto. Methods for obtaining bodily fluids and / or tissue biopsies from a mammary fluid containing humans are commonly known.

In the present specification, "methylation" refers to a methyl group attached to a base constituting DNA. Preferably, in the present invention, methylation means whether methylation occurs in a cytosine of a specific CpG region of a specific gene. In the DNA of mammalian cells, in addition to adenine, cytosine, guanine and thymine, there is a base called 5-methylcytosine (5-mC) with a methyl group attached to the fifth carbon of the cytosine ring, 5-methyl The methylation of cytosine occurs only in C of CG dinucleotide (5'-mCG-3 ') called CpG, and the methylation of CpG inhibits the expression of alu or transposon and repeat sequences of the genome. In addition, since 5-mC of the CpG is naturally deaminated, it is easy to become thymine (T), so CpG is a site where most epigenetic changes occur frequently in mammalian cells. In addition, when methylation occurs, the binding of transcription factors is interrupted thereby, and expression of a specific gene is suppressed. Conversely, when non-methylation or hypomethylation occurs, expression of a specific gene increases.

The present invention relates to a gene methylation marker for exposure to air pollution and a method for providing information using the same. Specifically, the gene methylation of air pollutant exposure to determine whether the gene is methylated by the epigenetic gene-wide association analysis (EWAS) for air pollutant exposure from the sample and to evaluate the effect of the body on the air pollutant It relates to a marker and information providing method using the same.

Hereinafter, a gene methylation marker for air pollution exposure of the present invention and an information providing method using the same will be described in detail with reference to embodiments and examples and drawings. However, the present invention is not limited to these embodiments and examples and drawings.

The present invention provides evidence that long-term exposure to air pollution affects DNA methylation. Different methylation signals can serve as potential air pollution biomarkers. These results can help to better understand the impact of air pollution on human health.

In one embodiment of the present invention, DNA is separated from a sample collected from a subject; It provides a method for providing gene methylation information for exposure to air pollution, comprising detecting methylation of one or more genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57, and C20orf123 from the DNA.

In the present invention, the method comprises detecting the methylation of 1, 2, 3, 4, 5 or 6 genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57 and C20orf123. It can provide the information needed to assess the physical impact of exposure.

According to an embodiment of the present invention, the gene is 94491958 th base of chromosome 14 for the OTUB2 gene, 30297174 to 30297627 th base region of the chromosome 6 for the TRIM39 gene, and 31539539 to 31540750 th chromosome 6 for the LTA gene Base region, methylation of 19459672 to 19460243 base region of chromosome 8 for CSGALNACT1 gene, 80084554 to 80085082 base region of chromosome 17 for CCDC57 gene, and 45179157 to 45179413 base region of chromosome 20 for C20orf123 gene It may be to detect, but may not be limited to this.

In addition, according to an embodiment of the present invention, the sample may be selected from tissue, cells, blood, plasma and urine separated from human subjects, and preferably may be blood, but may not be limited thereto. The samples can be obtained by methods commonly used in the art.

In one embodiment of the present invention, the detection of methylation is PCR, methylation specific PCR, real time methylation specific PCR, PCR using methylated DNA specific binding antibody or aptamer, quantitative PCR, DNA chips, pyrosequencing and bisulfite sequencing may be performed by a method selected from, but may not be limited to. This can be accomplished by a methylation detection method commonly used in the art.

According to one embodiment of the present invention, it may include comparing the level or the level of gene expression related to the disease with methylation or level of the detected gene. It can compare gene methylation associated with disease to determine different methylation for normal and natural methylation in EWAS. At this time, the comparison of the methylation level may be to compare the methylation ratio of CpG in a specific region.

For example, if OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57, and C20orf123 detected from DNA in a sample to be tested are methylated or the methylation level of the gene is different from the methylation level or methylation level detected from the DNA of the normal control or positive control. , It is possible to judge the risk of exposure to the air pollutants of the target and the human influence on the air pollutants.

Alternatively, the methylation level or methylation level of a gene selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57 and C20orf123 detected from DNA in a sample of a subject individual may be compared with a standardized standard.

In another embodiment of the present invention provides a composition for gene methylation analysis for exposure to air pollution comprising a substance capable of detecting methylation of one or more genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57 and C20orf123 .

For example, the composition can detect methylation of one, two, three, four, five, or six genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57, and C20orf123, but is not limited thereto. It may not.

For example, the composition includes a substance capable of detecting methylation of the gene from DNA in a sample taken from a test subject, wherein the sample is selected from tissue, cells, blood, plasma and urine of a human subject. It may be, but may not be limited to this.

In one embodiment of the present invention, the substance capable of detecting methylation is capable of hybridizing with a methylated base or a primer pair capable of amplifying a fragment comprising a methylated base region, a methylated base or a methylated base region. Methylation specific binding protein, methylation specific binding antibody or aptamer capable of binding to a probe, methylated base or methylated base region, methylation sensitivity limiting endonuclease, sequencing primer, sequencing by synthesis primer and sequencing by ligation It may be selected from the group consisting of primers, but may not be limited thereto.

According to an embodiment of the present invention, the methylated base or methylated base region is the 94491958 th base of chromosome 14 for the OTUB2 gene, the 6th base region of 30297174 to 30297627 of the chromosome 6 for the TRIM39 gene, and the 6th for the LTA gene Chromosome 31539539 to 31540750 base region, CSGALNACT1 gene 8 chromosome 19459672 to 19460243 base region, CCDC57 gene 17 chromosome 80084554 to 80085082 base region, and C20orf123 gene 20 chromosome 45179157 to 45179413, but may not be limited thereto.

Meanwhile, in another embodiment of the present invention, a kit for gene methylation analysis for air pollution exposure may be provided, which includes a composition for gene methylation analysis for air pollutant exposure. For example, the kit may include a sample or a compartmentalized carrier means for containing a sample, and a substance capable of detecting methylation of a gene in the sample.

For example, the kit includes a compartmentalized carrier means for containing a sample isolated from a test subject, a first container containing an agent that sensitively cleaves unmethylated cytosine, a second container containing a primer for amplifying CpG-containing nucleic acids, and And a third container containing means for detecting the presence of a truncated or uncleaved nucleic acid.

In addition, according to another embodiment of the present invention, a nucleic acid chip comprising a probe capable of hybridizing to a fragment comprising a methylation site of one or more genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57 and C20orf123 For example, DNA separated from the sample may be applied to the nucleic acid chip. As long as the methylation of a specific gene fragment can be detected, the present invention can be applied to any nucleic acid chip known in the art to which the present invention pertains.

Hereinafter, the present invention will be further described through examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

<Example 1> Experiment Preparation and Method

1-1 Research Population

For DNA methylation profiling, 100 participants were selected from the Korean COPD population. Data and biological samples collected at the visit were used in this experiment.

Blood, urine specimens and questionnaires were collected from all study participants who had undergone a physical examination. The trained nurse measured height and weight using a body composition analyzer IOI 353 (Aarna Systems., Udaipur, India).

Body mass index (BMI) was calculated as weight (kg) divided by height squared (m ² ).

Information on cigarette smoking status and annual smoking amount was collected through questionnaires. The number of cigarettes smoked per day was multiplied by the number of years smoked to calculate the annual smoking amount of current and past smokers. Current non-smoking status confirmed urine cotinine levels (nmol / L) measured by immunoassay (Immulite 2000 Xpi, Siemens Healthcare Diagnostics, Tarrytown, NY, USA). The flow chart of this experiment is shown in FIG. 1.

This experiment was approved by the Jury of Kangwon National University and consent was obtained from all participants.

1-2 Air pollution exposure at residential address

National average exposure prediction models (Kim and Song 2017) were used to measure the average annual concentrations of PM ₁₀ (μg / m3) and NO ₂ (ppb) in each residence obtained in the baseline survey. This predictive model used the 2010 air pollution regulatory monitoring data to measure the annual average concentration of pollutants in a universal kriging flamework based on geographic predictors and spatial correlations. Geographic predictors are estimated by hundreds of geographic variables representing pollutants, including transportation, demographic characteristics, land use, physical topography, transportation facilities, emissions, vegetation and altitude. In this experiment, the residential address was coded based on the participants of the visit using GeoCoder-Xr software (Geoservice, Seoul, South Korea).

1-3 DNA methylation profiling

DNA was extracted from blood samples of participants collected at the visit. The methylation profile of the whole gene was obtained using Infinium HumanMethylation450K BeadChip (Illumina, Inc., San Diego, CA, USA). For signal extraction and initial low-quality probe filtering, a Chip Analysis Methylation Pipeline (ChAMP) R package (Morris et al. 2014) was used, with p-values> 0.01 and bead-count <3 in 5% in samples or beads. Excluded. Correction for probe design bias was performed using Beta Mixture Quantile dilation standardization (Teschendorff et al., 2013). Batch effect correction was corrected using Combat (Johnson et al. 2007) in the sva R package (Leek et al. 2012). In addition, non-CpG probes likely to be affected by nearby genetic variations, such as non-specific or nearby single base polymorphism (SNP), were additionally removed to minimize false positive results.

Excluding probes for X and Y chromosomes, the remaining 402,508 CpGs were used for linkage analysis. More than three times the quartile range of the 25th and 75th percentiles of each probe's methylation value with more extreme methylation values than Tukey's outer fences (Tukey 1977) to reduce the potential impact of extreme methylation outliers on the association results. Defined as 75,549 values (0.19%) of all participants were removed.

Reinius reference panel and Huseman algorithm applied to evaluate cell type proportions including CD8 + T-lymphocytes, CD4 + T-lymphocytes, natural killer cells, B cells, monocytes and granulocytes Did.

1-4 Identification of different methylated probes (DMPs)

To evaluate the relationship between air pollution exposure and DNA methylation, robust linear regression models were used to reduce the effect of methylation values and heterogeneity on the results. The average annual concentration of contaminants (PM ₁₀ or NO ₂ ) was using a predictor, and the methylation beta value was a response variable. The methylated beta value is the ratio of methylated CpG probe strength to total probe strength and ranges between 0 (unmethylated) and 1 (methylated). Covariates include age, gender, cigarette smoking, annual cigarette smoking, body mass index (BMI, kg / m2) COPD status (cases, noncases) and estimated cell-type ratio. For statistical significance throughout the genome, the threshold of the p value corrected for false discovery rate (FDR) was set to less than 0.05 unless otherwise noted. In addition, p-value <1.2E-07 (= 0.05 / 402,508) was used as cutoff for statistically significant association after Bonferroni correction. R version 3.0.2 and R version 3.4.0 for association analysis and visualization of different methylation regions were used to pre-process methylation data from initial data (.idat files) to methylation beta values.

1-5 Identification of different methylated regions (DMRs)

In addition to the associated analysis of each CpG, two methods were used to identify different DNA methylation at the region level in relation to air pollution: DMRcate (Peters et al. 2015) and comb-p (Pedersen et al. 2012). .

Since both methods implement different algorithms to identify DMR, both methods with important DMR are used while reducing false positives. DMRcate uses a tunable kernel smoothing process with different methylation related signals, while comb-p checks for local clustering of low p-values at irregularly spaced p-values. The 'dmrcate' function (regression coefficient, standard deviation, and uncorrected p-value) of DMRcate, an input file of epigenetic-wide range association study results, was used. The standalone software Comb-p was used with an input file containing uncorrected p-values and chromosomal location information (chromosome and physical location). The following three criteria were applied to define significant DMR in this experiment.

First, at least one CpG must be in the DMR.

Second, different methylation signals for each zone can be calculated using adjacent CpGs within 1,000 base pairs (bp).

Third, the zone must have a multi-calibrated P value <0.05 in both methods.

Since both the FDR of DMRcate and the Sidak of comb-p, the minimum number of CpGs in the region (N = 2) and the minimum length of distance (N = 1000 nucleotides) were the defaults for DMRcate, comb-p to harmonize the results of the two methods. The same values were used for.

Since both methods call DMR based on the results of the association of adjacent probes, important DMR does not necessarily overlap with important DMP in the region. And coMET was used to visualize different methylation regions.

1-6 Biological Effects of Related Results

Gene annotation for each CpG was performed using Illumina's annotation file, and the UCSC RefGene name was obtained. For the biological effects of different methylation signals in relation to each contaminant (PM ₁₀ or NO ₂ ), we have determined the uncorrected p-value <1E-04 (any cutoff for implicit binding) or DMP with significant DMR. Functional pathway analysis of the annotated gene was performed.

The mapped gene list was entered for 'Core Analysis' of Ingenuity Pathway Analysis (IPA, Ingenuity Systems, QIAGEN, CA, USA). To evaluate the frequency of gene expression of tissue or cell type specific signals, we used experimentally derived functional elements to overlap DDNs with a minimum p value in each DMR (FDR <0.05, when overlapping with a DNase 1 hypersensitivity site (DHS). ) And probes were analyzed (EWAS ReGions).

1-7 Replication look-up

To reproduce DMP as a result of previous EWAS, the evidence of DMP (FDR <0.05) was confirmed in two epigene-wide association studies of PM ₁₀ or NO ₂ exposure in adults (Lichtenfels et al. 2018; Plusquin et al. 2017 ). We also investigated whether the DMPs reported in both studies were repeated in this study. In both studies, 5,001 DMPs were reported (FDR <0.05), PM10 was 9, and NO ₂ was 4,992. Of these, 4,671 were used for search analysis in the data after probe filtering, and PM10 was 9 and NO ₂ was 4,662. The cutoff of the uncorrected p-value was set to less than 0.05 for statistical significance for lookup.

Correlation between methylation levels of 1-8 DMPs and gene expression levels of nearby transcripts: expression quantitative trait methylation (eQTM) of BIOS data

To evaluate the association between the methylation level of DMPs and the expression level of nearby transcripts (cis-eQTMs), the methylated M value, log2 ratio of methylation to unmethylated probe strength, gene expression, age, gender, lymphocyte percentage, monocyte percentage and RNA flow cell numbers were regressed. The expansion of the model was corrected using the "Bacon" method. The eQTM was mapped to a portion of a 250 kilobase pair (kb) centered on an important DMP (FDR <0.05). For this analysis, a total of 3,075 samples with methylation and gene expression data available in all four populations (Leiden Longevity Study, LifeLines Study, Rotterdam Study and Netherland Twin Study) were used. Each group was analyzed separately, and then the results were meta-analyzed using an inverse distributed weighted fixed-effects model using METAL software.

<Example 2> Results

The mean age of the participants was 73 years (standard deviation, SD = 6), and 66% were male (Table 1). And 39 non-smokers, 30 past smokers and 31 current smokers. The average air pollution concentration was 45.1 μg / m ³ for PM10 and 13.1 ppb for NO ₂ . The two air pollutants were highly correlated (Spearman correlation coefficient = 0.74, p value <2.2E-16).

A number of DMPs were found with two contaminants (FDR <0.05). 11, if only PM10, 44 gae when only NO _2, PM10 and NO ₂ are both gaeyeotda 1.

Table 2 shows the different methylated CpGs (FDR <0.05) in blood DNA in relation to PM ₁₀ exposure by chromosomal location, and Table 3 shows the different methylated CpGs (FDR <in blood DNA in relation to NO ₂ exposure). 0.05).

Some of the 56 DMPs showed the same significance for cg05454562 (WDR46), cg13999433 (AKNA) and cg11691844 (SYTL2) associated with PM ₁₀ exposure after Bonferroni multiplex assay (Table 2).

cg05171937 (STK38L), cg26583725 (8,541 bp away from IRS2) and cg06226567 (C20orf56) were associated with NO ₂ exposure (Table 3).

DMP cg06992688 (OTUB2) was completely correlated with PM10 and NO ₂ (FDR <0.05).

Exposure to both air pollutants was mostly entirely correlated with DNA methylation, 92% for PM10 and 71% for NO ₂ .

As shown in FIG. 2, Manhattan and quantile-quantile plots are used for visual representation of epigenetic-wide range association analysis (EWAS) in the present invention. Systematic inflation was not observed because the genomic inflation factor lambda value in this example was 0.83 for PM ₁₀ exposure and 1.07 for NO ₂ exposure.

In addition, a number of DMRs have been discovered in relation to air pollution. There are 22 in the PM ₁₀ , 52 in the NO ₂ , and 5 in both the PM10 and NO ₂ .

Different methylated regions (DMRs) in blood DNA with respect to PM ₁₀ exposure are shown in Table 4 (adjusted to P <0.05 in DMRcate and comb-p).

Different methylated regions (DMRs) in blood DNA with respect to NO ₂ exposure are shown in Table 5 (adjusted to P <0.05 in DMRcate and comb-p).

The five DMRs associated with the two contaminants are chr6: 30297174-30297627 (TRIM39), chr6: 31539539-31540750 (LTA), chr8: 19459672-19460243 (CSGALNACT1), chr17: 80084554-80085082 (CCDC57) and chr20: 45179157-45179413 (C20orf123).

DMR does not necessarily include DMP, but DMRs associated with PM ₁₀ exposure chr8: 28961315-28961356 (KIF13B) include DMP-cg07023317. The four DMRs associated with NO ₂ exposure are chr1: 153347819-153348305 (S100A12) cg02901136, chr6: 31539539-31540750 (LTA) cg11586857, chr14: 105390602-105391263 (PLD4) cg15352829 and chr15: 45670068-45671708 cg040256 (GATM; LOC145663).

In each DMR method, the top two DMRs based on the multi-calibrated p-value (FDR in DMRcate) are shown in FIG. 3 for the results of the association of the regions including the annotation of the regulatory genomic region and the bidirectional correlation of neighboring probes. Visualized.

Annotated DMPs with minimal p value in DMR (FDR <0.05) or FDR <0.05 in DMRcate (enhanced biological network in relevant results based on genes with Sidak corrected p value <comb-p <0.05)) , PM10 is 138, NO ₂ is 288. The enhanced network included inflammatory and immune responses and cardiovascular, respiratory and metabolic diseases. Cancer, hematologic development, immunological and inflammatory disease pathways overlap between different methylation signals associated with PM10 and NO ₂ (FIG. 4A). Among the genes involved in exposure to PM10 and NO ₂ were genes contributing to hematologic, immunological and inflammatory networks such as NLRC4, RPTOR, CUX1, S100A12, LTA and HLA-DMB (Figure 4b) (Figure 4b).

Specific histone marks (H3K27me3, H3K36me3, H3K4me3, H3K4me3 and H3K4me1) of tissue or cell type among 132 probes associated with air pollution (PM10 or NO ₂ ) exposure were found using eFORGE (Breeze et al. 2016). In DMP analysis FDR <0.05 or minimum p value of the DMR: PM ₁₀ for 11 DMPs, NO ₂ alone exposure when a single exposure to 44 for DMPs, PM ₁₀ and NO ₂ both exposure of 1 DMP, 19 represents the minimum P value Probes are PM ₁₀ exposure related DMR, 49 probes showing the minimum p value are NO ₂ exposure related DMR, and 8 probes showing the minimum p value are PM10 and NO ₂ exposure related DMR. Enhancement of H3K4me1 in blood observed different methylation associated with PM ₁₀ exposure (FIG. 5). With respect to different methylation associated with NO ₂ exposure, several histone marks have been enhanced; H3K4me1 (FIG. 6A), H3K27me3 (FIG. 6B), H3K4me3 (FIG. 6C) and H3K9me3 (FIG. 6D). H3K4me1 and H3K27me3 in embryonic stem (ES) cells; Lung H3K4me1 was identified (FIG. 6).

Several DMPs (FDR <0.05) in the present invention have been reported to be due to exposure to air pollution in genetic wide DNA methylation studies prior to the present invention. In the present invention, 11 of 27 DMPs associated with NO ₂ (FDR <0.05) were reported to be related to NO ₂ exposure in the direction of the same effect in the LifeLines group (Lichtenfels et al. 2018) (Table 6).

The 12 DMPs associated with PM10 in this example (FDR <0.05) are new and have not been reported to be associated with this contaminant in two previous studies (Lichtenfels et al., 2018; Plusquin et al., 2017). In particular, 26% (N = 1,231) of the 4,662 probes that were associated with NO ₂ exposure in 2 studies and reported to be available in this data were of minimal nominal importance (uncorrected p-value <0.05 in this example). ).

As a result of analyzing the DNA methylation and gene expression in the BIOS data, it was confirmed that the correlation between the methylation level of DMPs and the nearby transcript (over 250 bp region) gene expression level (uncorrected p value <0.05). In particular, 70% of 56 DMPs (FDR <0.05) (N = 39) were significantly associated with gene expression in nearby transcripts.

Results analysis

In this example, many different methylated signals (individual probes and regions) were identified in relation to long-term exposure to air pollutants PM10 and NO ₂ in the blood. In particular, the level of methylation of many DMPs is related to the level of gene expression in the vicinity of the transcript, and the association between gene expression and different methylation associated with air pollution has been confirmed.

Some DMPs annotated with loci reported in a gene-wide study on various health outcomes related to air pollution were identified. There is a different methylation of cg11586857 associated with the exposure of two pollutants treated in tin to LTA, which in previous studies confirmed that rs1799964 (p value = 3.3E-07) is related to blood lipid concentration. Cg06992688, which is associated with exposure to two air pollutants, is in OTUB2, the closest gene of three genetic variations with respect to pulmonary function with p values around 1.0E-04. In addition, cg05284742 associated with NO ₂ exposure is located in ITPK1. This gene contains rs2295394 (p value = 2.3E-16) associated with myocardial infarction in the Asian population.

The results of strengthening networks such as inflammatory and immune responses and cardiovascular, pulmonary and metabolic diseases through this example support prior air pollution exposure and confirmed disease associations. Several enhanced histone macros of different tissues and cell types (embryonic stem cells, blood and lungs) indicate the biological relevance of different methylation signals.

Different methylation signals in this example indicate a similar relationship between air pollution in Asia and DNA methylation. To investigate whether the common and unique biological markers and mechanisms associated with two pollutants in this example included all of the PM10 and NO ₂ exposure. In addition, by examining the relationship with gene expression and tracking DMP, the majority of them were found to be related to gene expression, suggesting a related functional significance. In addition, route analysis and enrichment analysis was performed for specific histone marks of tissues and cell types to better understand the biological significance of the different methylation signals observed. Finally, in addition to identifying DMPs, two methods were used to identify DMRs by combining link signals from adjacent CpGs.

Through the present invention, different DNA methylation signals have been identified in the blood in relation to long-term air pollution exposure, and different methylation and different gene expression are involved. CpG and regions showing different methylation can serve as potential biomarkers for air pollution exposure. These results can be used to analyze mechanisms linking exposure to air pollution with harmful health outcomes.

As described above, specific embodiments of the present invention have been described in detail, but those skilled in the art to understand the spirit of the present invention may add other components within the scope of the same spirit, change, delete, etc., and degenerate other inventions However, other embodiments included within the scope of the inventive concept may be easily proposed. Therefore, it should be understood that the above-described embodiments are illustrative in all respects and not restrictive. The scope of the present invention is indicated by the scope of claims to be described later rather than the detailed description described above, and all the changed or modified forms derived from the meaning and scope of the claims and their equivalent concepts are included in the scope of the present invention. It should be interpreted as.

Claims (9)

DNA is isolated from samples collected from Korean subjects,
Detecting the methylation of one or more genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57 and C20orf123 from the DNA,
For the OTUB2 gene, the 94491958 th base of chromosome 14, for the TRIM39 gene, the 30297174 to 30297627 th base region of the chromosome 6, for the LTA gene, the 31539539 to 31540750 th base region of chromosome 6, for the CSGALNACT1 gene chromosome 8 Characterized by detecting methylation of 19459672 to 19460243 nucleotide region, 80084554 to 80085082 nucleotide region of chromosome 17 for CCDC57 gene, and 45179157 to 45179413 nucleotide region of chromosome 20 for C20orf123 gene,
How to provide gene methylation information for Korean air pollution exposure.
delete According to claim 1,
The sample is selected from tissues, cells, blood, plasma and urine of human subjects, a method for providing gene methylation information for exposure to air pollution in Koreans.
According to claim 1,
Detection of methylation is PCR, methylation specific PCR, real time methylation specific PCR, PCR using methylated DNA specific binding antibody or aptamer, quantitative PCR, DNA chip, pyrosequencing and A method for providing gene methylation information for exposure to air pollution in Koreans, characterized by being performed by a method selected from the group consisting of bisulfite sequencing.
According to claim 1,
A method for providing gene methylation information for exposure to air pollution in Koreans, comprising comparing the methylation level of the detected gene or the methylation level with a gene expression level associated with the disease.
Contains substances capable of detecting methylation of one or more genes selected from OTUB2, TRIM39, LTA, CSGALNACT1, CCDC57 and C20orf123,
For the OTUB2 gene, the 94491958 th base of chromosome 14, for the TRIM39 gene, the 30297174 to 30297627 th base region of the chromosome 6, for the LTA gene, the 31539539 to 31540750 th base region of chromosome 6, for the CSGALNACT1 gene chromosome 8 Characterized by detecting methylation of 19459672 to 19460243 nucleotide region, 80084554 to 80085082 nucleotide region of chromosome 17 for CCDC57 gene, and 45179157 to 45179413 nucleotide region of chromosome 20 for C20orf123 gene,
Composition for gene methylation analysis of exposure to air pollution in Koreans.
The method of claim 6,
The substance capable of detecting methylation is a primer pair capable of amplifying a fragment containing a methylated base or a methylated base region, a probe capable of hybridizing with a methylated base or a methylated base region, a methylated base or methylation Selected from the group consisting of methylation specific binding protein, methylation specific binding antibody or aptamer, methylation sensitivity limiting endonuclease, sequencing primer, sequencing by synthesis primer, and sequencing by ligation primer capable of binding to the base region The composition for analysis of gene methylation for exposure to air pollution in Koreans.
delete A kit for analysis of gene methylation for exposure to air pollution in Koreans, comprising the composition of claim 6.

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