Differential DNA methylation regions in cytokine and transcription factor genomic loci associate with childhood physical aggression.
- Authors
- ProvenΓ§al, Nadine; Suderman, Matthew J; Caramaschi, Doretta; Wang, Dongsha; Hallett, Michael; Vitaro, Frank; Tremblay, Richard E; Szyf, Moshe
- Year
- 2013
- Journal
- PloS one
- PMID
- 23977113
- DOI
- 10.1371/journal.pone.0071691
- PMCID
- PMC3747262
BACKGROUND: Animal and human studies suggest that inflammation is associated with behavioral disorders including aggression. We have recently shown that physical aggression of boys during childhood is strongly associated with reduced plasma levels of cytokines IL-1Ξ±, IL-4, IL-6, IL-8 and IL-10, later in early adulthood. This study tests the hypothesis that there is an association between differential DNA methylation regions in cytokine genes in T cells and monocytes DNA in adult subjects and a trajectory of physical aggression from childhood to adolescence. METHODOLOGY/PRINCIPAL FINDINGS: We compared the methylation profiles of the entire genomic loci encompassing the IL-1Ξ±, IL-6, IL-4, IL-10 and IL-8 and three of their regulatory transcription factors (TF) NFkB1, NFAT5 and STAT6 genes in adult males on a chronic physical aggression trajectory (CPA) and males with the same background who followed a normal physical aggression trajectory (control group) from childhood to adolescence. We used the method of methylated DNA immunoprecipitation with comprehensive cytokine gene loci and TF loci microarray hybridization, statistical analysis and false discovery rate correction. We found differentially methylated regions to associate with CPA in both the cytokine loci as well as in their transcription factors loci analyzed. Some of these differentially methylated regions were located in known regulatory regions whereas others, to our knowledge, were previously unknown as regulatory areas. However, using the ENCODE database, we were able to identify key regulatory elements in many of these regions that indicate that they might be involved in the regulation of cytokine expression. CONCLUSIONS: We provide here the first evidence for an association between differential DNA methylation in cytokines and their regulators in T cells and monocytes and male physical aggression.
DNA methylation differences between CPA (n = 8) and control (n = 12) groups in pro-inflammatory cytokines IL-6 and IL-1Ξ± loci in T cells.Expanded views from the UCSC genome browser of IL-6 (A) and IL-1Ξ± (B) loci located on chromosomes 7 and 2 are depicted (top panel). In both panels, the first track shows the average MeDIP probe log2-fold differences (scale top panel: β0.4 to 0.4, botom panel: β1.0 to 1.0) between chronic physical aggressive (CPA) and control groups for T cells. In black are probes that are more methylated and in gray are those that are less methylated in the CPA group. Highlighted in blue are regions significantly differentially methylated between the groups. The second track shows Pearsonβs correlation coefficient values (scale top panel: β0.4 to 0.4, botom panel: β0.7 to 0.7) calculated between the MeDIP microarray probe intensities and the plasma IL-6 (A) and IL-1Ξ± (B) levels obtained from the same subjects (n = 20). In red are probes whose methylation levels correlate positively with the cytokine level in plasma and in green are those that correlated negatively. In the top panel, the lowest track shows the average methylation level for all the subjects in T cells estimated from the microarray data. The bottom panel zooms on the closest region upstream of the TSS where the CPA group is found significantly less methylated than the control group in the IL-6 (A) and IL-1Ξ± (B) loci. In both regions, an overall positive correlation between methylation and cytokine level in plasma is observed but only reached significance after correcting for multiple testing in IL-1Ξ± (B) differentially methylated region. The regulatory elements from ENCODE identified in these regions (see methods) are shown in the additional tracks. First, shown with black lines, is the location of individual CpG sites. Second, is the location of DNase hypersensitive clusters where black indicate strong signal and grey a weaker signal from ChIP-seq data in 24 cell lines. Third is the location of transcription factors (TF) identified from ChIP-seq data in 24 cell lines where black indicate a strong and grey weaker signal occupancy. The letter next to the TF boxes identified the cell line where it was found enriched (see Table S1 for the full legend). The last tracks, identified the level of enrichment of three histone marks determined from ChIP-seq assay, histone 3 lysine 4 tri- and mono-methylation as well as histone 3 lysine 27 acetylation in two cell lines, GM12878 (pink) and K562 [106].
DNA methylation differences between CPA (n = 8) and control (n = 12) groups in anti-inflammatory cytokines IL-4 and IL-10 loci in T cells.Expanded views from the UCSC genome browser of IL-4 (A) and IL-10 (B) loci located on chromosomes 5 and 1 are depicted (top panel). In both panels, the first track shows the average MeDIP probe log2-fold differences (scale top panel: β0.4 to 0.4, botom panel: β1.0 to 1.0) between chronic physical aggressive (CPA) and control groups are shown for T cells. In black are probes that are more methylated and in gray are those that are less methylated in the CPA group. Highlighted in blue are regions significantly differentially methylated between the groups in T cells for IL-4 (A) and IL-10 (B). The second track shows Pearsonβs correlation coefficient (scale top panel: β0.4 to 0.4, botom panel: β0.7 to 0.7) calculated between the MeDIP microarray probe intensities and the plasma IL-4 (A) and IL-10 (B) levels obtained from the same subject (n = 20). In red are probes whose methylation levels correlate positively with the cytokine level in plasma and in green are those that correlated negatively. In the top panel, the last track shows the average methylation level for all the subjects in T cells for IL-4 (A) and IL-10 (B) estimated from the microarray data. The bottom panel shows differentially methylated regions located within known Th2 LCRs where the CPA group is found significantly less methylated than the control group in the IL-4 locus (A) and significantly more methylated in the IL-10 locus (B). For the first differentially methylated region in IL-4, an overall positive correlation between methylation and IL-4 level in plasma is observed but did not reach significance after correcting for multiple testing (A, bottom panel). In the region more methylated in the CPA group of the IL-10 locus (B, bottom panel), the overall correlation with IL-10 level in plasma is negative although not significant after corrections for multiple testing. The regulatory elements from ENCODE identified in these regions (see methods) are shown in the additional tracks. First, shown with black lines, is the location of individual CpG sites. Second, is the location of DNase hypersensitive clusters where black indicate strong signal and grey a weaker signal from ChIP-seq data in 24 cell lines. Third is the location of transcription factors (TF) identified from ChIP-seq data in 24 cell lines where black indicate a strong and grey weaker signal occupancy. The letter next to the TF boxes identified the cell line where it was found enriched (see Table S1 for the full legend). The last tracks, identified the level of enrichment of three histone marks determined from ChIP-seq assay, histone 3 lysine 4 tri- and mono-methylation as well as histone 3 lysine 27 acetylation in two cell lines, GM12878 (pink) and K562 [106].
DNA methylation differences between CPA (n = 8) and control (n = 12) groups in pro-inflammatory chemokine IL-8 locus in monocytes.Expanded views from the UCSC genome browser of IL-8 (A) locus located on chromosomes 4 is depicted (top panel). In both panels, the first track shows the average MeDIP probe log2-fold differences (scale top panel: β0.4 to 0.4, botom panel: β1.0 to 1.0) between chronic physical aggressive (CPA) and control groups are shown for monocytes. In black are probes that are more methylated and in gray are those that are less methylated in the CPA group. Highlighted in red are regions significantly differentially methylated between the groups. The second track shows Pearsonβs correlation coefficient (scale top panel: β0.4 to 0.4, botom panel: β0.5 to 0.5) calculated between MeDIP microarray probe intensities (DNA methylation levels) and the plasma IL-8 levels obtained from the same subject (n = 20). In red are probes whose methylation levels correlate positively with the cytokine levels in plasma and in green are those that correlated negatively. In the top panel, the last track shows the average methylation level for all the subjects in monocytes estimated from the microarray data. The bottom panel shows the closest region upstream of the TSS where the CPA group is found significantly less methylated than the control group in the IL-8 locus. In both regions, an overall negative correlation between methylation and cytokine level in plasma is observed but did not reach significance after correcting for multiple testing. The regulatory elements from ENCODE identified in these regions (see methods) are shown in the additional tracks. First, shown with black lines, is the location of individual CpG sites. Second, is the location of DNase hypersensitive clusters where black indicate strong signal and grey a weaker signal from ChIP-seq data in 24 cell lines. Third is the location of transcription factors (TF) identified from ChIP-seq data in 24 cell lines where black indicate a strong and grey weaker signal occupancy. The letter next to the TF boxes identified the cell line where it was found enriched (see Table S1 for the full legend). The last tracks, identified the level of enrichment of three histone marks determined from ChIP-seq assay, histone 3 lysine 4 tri- and mono-methylation as well as histone 3 lysine 27 acetylation in two cell lines, GM12878 (pink) and K562 [106].
DNA methylation differences between CPA (n = 8) and control (n = 12) groups in cytokineβs transcription factor STAT6 in T cells.Expanded views from the UCSC genome browser of STAT6 (A) locus located on chromosomes 12 is depicted (top panel). In both panels, the first track shows the average MeDIP probe log2-fold differences (scale top panel: β0.4 to 0.4, botom panel: β1.0 to 1.0) between chronic physical aggressive (CPA) and control groups for T cells. In black are probes that are more methylated and in gray are those that are less methylated in the CPA group. Highlighted in blue are regions significantly differentially methylated between the groups. The second track shows Pearsonβs correlation coefficient (scale top panel: β0.4 to 0.4, botom panel: β0.6 to 0.6) calculated between MeDIP microarray probe intensities and the plasma IL-4 (first) and IL-10 (second) levels obtained from the same subject. These correlations did not reach significance after correcting for multiple testing in T cells. In red are probes whose methylation levels correlate positively with the cytokine level in plasma and in green are those that correlated negatively. In the top panel, the last track shows the average methylation level for all the subjects in T cells estimated from the microarray data (n = 20). The bottom panel shows the two regions close to the TSS of each STAT6 isoform where the CPA group is found significantly more methylated than the control group. The regulatory elements from ENCODE identified in these regions (see methods) are shown in the additional tracks. First, shown with black lines, is the location of individual CpG sites. Second, is the location of DNase hypersensitive clusters where black indicate strong signal and grey a weaker signal from ChIP-seq data in 24 cell lines. Third is the location of transcription factors (TF) identified from ChIP-seq data in 24 cell lines where black indicate a strong presence and grey weaker signal occupancy. The letter next to the TF boxes identified the cell line where it was found enriched (see Table S1 for the full legend). The last tracks, identified the level of enrichment of three histone marks determined from ChIP-seq assay, histone 3 lysine 4 tri- and mono-methylation as well as histone 3 lysine 27 acetylation in two cell lines, GM12878 (pink) and K562 [106].
Pyrosequencing analyses of differentially methylated sequences in T cells and monocytes between CPA (n = 8) and control (n = 12) groups.DNA methylation differences (%) between the aggressive groups in the IL-6 (A), IL-8 (B) and STAT6 (C) genes as determined by pyrosequencing. CpG sites near the significant probes were analyzed in triplicate. For each gene, the mean methylation per group per CpG with the standard error of the mean (SEM) are shown in the bar graph (top panel). The rightmost bar indicates the mean methylation levels of all CpG sites analyzed in the region. A map of the sites relative to the transcription start site is shown above the bar graph. Each line with a circle represents a CpG site. The location of probes which fold difference is significantly different between the groups is identified by a grey square where dark and light grey indicated more or less methylated in the CPA group respectively. Red arrows delimit the region analyzed by pyrosequencing. Correlations between mean methylation levels obtained by pyrosequencing for each gene and expression levels in plasma obtained by ELISA for each cytokine [32] is shown in the bottom panel. Correlation statistics were performed using Pearson correlation. All error bars represent standard error of the mean (SEM). The symbol β#β denotes a p-value β€0.1 and the symbol β*β denotes a p-value β€0.05 as determined by a Student t-test.
| # | Section | Preview |
|---|---|---|
| 40 | Materials and Methods β Participants | The subjects for the plasma cytokine level analysis (sample 1) [32] were recruited from maleβ¦ |
| 41 | Materials and Methods β Participants | The two groups of Caucasian males we recruited from these longitudinal studies were all born inβ¦ |
| 42 | Materials and Methods β Participants | lower anti-inflammatory interleukin IL-4 (T(27.1) = 4.91, P = 0.00004) and IL-10 (T(29.8) = 2.84, Pβ¦ |
| 43 | Materials and Methods β Ethics Statement | After complete description of the study to the subject, all participants provided written informedβ¦ |
| 44 | Materials and Methods β Assessment of Subjectsβ Familial Adversity, Behavior Problems, Psychiatric Diagnoses and Criminal Records β Familial adversity | The index of family adversity is a composite score of the degree of adversity in families rangingβ¦ |
| 45 | Materials and Methods β Assessment of Subjectsβ Familial Adversity, Behavior Problems, Psychiatric Diagnoses and Criminal Records β Physical aggression and other behavior problems | In the course of the longitudinal studies, teachers annually rated the frequency of boysβ physicalβ¦ |
| 46 | Materials and Methods β Assessment of Subjectsβ Familial Adversity, Behavior Problems, Psychiatric Diagnoses and Criminal Records β Self reported violence | During the data collection at 21 years, subjects were asked how often in the past year they had beenβ¦ |
| 47 | Materials and Methods β Assessment of Subjectsβ Familial Adversity, Behavior Problems, Psychiatric Diagnoses and Criminal Records β Criminal record | Canadian youth between 13 and 17 years who commit delinquent acts are referred to the juvenileβ¦ |
| 48 | Materials and Methods β Assessment of Subjectsβ Familial Adversity, Behavior Problems, Psychiatric Diagnoses and Criminal Records β Mental disorders | When the subjects were 15 years, structured psychiatric interviews using a French translation of theβ¦ |
| 49 | Materials and Methods β CD3+ T cells and Monocytes DNA Preparation | For the study, 20 ml of blood were drawn in EDTA coated-tubes for each subjects. PBMC (wholeβ¦ |
| 50 | Materials and Methods β Methylated DNA Immunoprecipitation (MeDIP), Amplification and Labeling | The MeDIP analysis was adapted from [98]. Briefly, 2 Β΅g of each of the T cells and monocytes DNAβ¦ |
| 51 | Materials and Methods β Microarray Design, Hybridization, Scanning and Analysis | A detailed description of the methods and analyses concerning microarrays used in this study wereβ¦ |
| 52 | Materials and Methods β Microarray Design, Hybridization, Scanning and Analysis | Differential methylation between groups of samples was determined at both the probe and regionβ¦ |
| 53 | Materials and Methods β Microarray Design, Hybridization, Scanning and Analysis | Figures 1, 2, 3, 4, S1, S2, S3, S4, S5 and S6 were obtained using the UCSC genome browserβ¦ |
| 54 | Materials and Methods β Microarray Design, Hybridization, Scanning and Analysis | The identification of regulatory elements contained in the cytokine and TF loci shown in the figuresβ¦ |
| 55 | Materials and Methods β Microarray Design, Hybridization, Scanning and Analysis | The microarray data are available at http://www.ncbi.nlm.nih.gov/geo under the accession numberβ¦ |
| 56 | Materials and Methods β Microarray Validation β Bisulfite treatment and pyrosequencing | 1 Β΅g of EcoRI digested DNA was subjected to bisulfite treatment as previously described [105]. Lociβ¦ |
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