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System-Wide Associations between DNA-Methylation, Gene Expression, and Humoral Immune Response to Influenza Vaccination.

Zimmermann MT, Oberg AL, Grill DE, Ovsyannikova IG, Haralambieva IH, Kennedy RB, Poland GA - PLoS ONE (2016)

Bottom Line: The genes and molecular functions implicated by each analysis were compared, highlighting different aspects of the biologic mechanisms of immune response affected by differential methylation.Both cis-acting (within the gene or promoter) and trans-acting (enhancers and transcription factor binding sites) sites show significant associations with measures of humoral immunity.Specifically, we identified a group of CpGs that, when coordinately hypo-methylated, are associated with lower humoral immune response, and methylated with higher response.

View Article: PubMed Central - PubMed

Affiliation: Department of Health Science Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, United States of America.

ABSTRACT
Failure to achieve a protected state after influenza vaccination is poorly understood but occurs commonly among aged populations experiencing greater immunosenescence. In order to better understand immune response in the elderly, we studied epigenetic and transcriptomic profiles and humoral immune response outcomes in 50-74 year old healthy participants. Associations between DNA methylation and gene expression reveal a system-wide regulation of immune-relevant functions, likely playing a role in regulating a participant's propensity to respond to vaccination. Our findings show that sites of methylation regulation associated with humoral response to vaccination impact known cellular differentiation signaling and antigen presentation pathways. We performed our analysis using per-site and regionally average methylation levels, in addition to continuous or dichotomized outcome measures. The genes and molecular functions implicated by each analysis were compared, highlighting different aspects of the biologic mechanisms of immune response affected by differential methylation. Both cis-acting (within the gene or promoter) and trans-acting (enhancers and transcription factor binding sites) sites show significant associations with measures of humoral immunity. Specifically, we identified a group of CpGs that, when coordinately hypo-methylated, are associated with lower humoral immune response, and methylated with higher response. Additionally, CpGs that individually predict humoral immune responses are enriched for polycomb-group and FOXP2 transcription factor binding sites. The most robust associations implicate differential methylation affecting gene expression levels of genes with known roles in immunity (e.g. HLA-B and HLA-DQB2) and immunosenescence. We believe our data and analysis strategy highlight new and interesting epigenetic trends affecting humoral response to vaccination against influenza; one of the most common and impactful viral pathogens.

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Related in: MedlinePlus

Genes whose expression is highly correlated with cis-acting CpGs show functional enrichment.A) Genes with significant association (p < 1E-4) indicate 32 GO terms enriched at the p < 0.01 level and annotating at least 3 genes, across time points. Color intensity is used to signify statistical significance. Genes are mapped to network biology resources (see Methods) and the associations at B) baseline, C) during early and D) late time periods shown, represented in the same location in all panels; (for brevity, only genes within the largest connected components are shown). We color genes in the network that have a significant association at each time period (baseline teal, early green, late orange). The network layout is manually adjusted and edges bundled to improve legibility. See the online version for sufficient resolution to view gene names.
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pone.0152034.g001: Genes whose expression is highly correlated with cis-acting CpGs show functional enrichment.A) Genes with significant association (p < 1E-4) indicate 32 GO terms enriched at the p < 0.01 level and annotating at least 3 genes, across time points. Color intensity is used to signify statistical significance. Genes are mapped to network biology resources (see Methods) and the associations at B) baseline, C) during early and D) late time periods shown, represented in the same location in all panels; (for brevity, only genes within the largest connected components are shown). We color genes in the network that have a significant association at each time period (baseline teal, early green, late orange). The network layout is manually adjusted and edges bundled to improve legibility. See the online version for sufficient resolution to view gene names.

Mentions: We considered the correlation between methylation loci and cis-gene expression independent of immune outcome. Table 1 lists the top 20 cis-associations between Day 0 methylation levels and Day 0 gene expression measured by RNA-Seq, for the average methylation level across each genomic region (gene promoter or body). See S6 Table for the full list, and for correlations with gene expression at later time points. The system-wide summary of differential (through time) cis-acting methylation is shown in Fig 1, using the genes whose expression is correlated with a cis-acting CpG with p < 1E-4; 716 CpG sites in total, with the 161 genes sharing network connections displayed in Fig 1. We show the same network configuration with color indicating three different temporal states: Baseline (Day 0, pre-vaccination); Early (Day 3); and Late (Day 28) immune response after vaccination. While Day 28 is approximately a peak of adaptive response [68,69], we refer to it as “late” in this study for simplicity. The genes meeting the aforementioned significance threshold were carried on to GO term [70] enrichment, which identifies participation in similar biologic functions. Further, this group of genes with significant methylation-expression associations are depleted (compared to randomly selecting 716 genes) for network interactions (p = 0.028), potentially indicating their diverse functional roles. Interestingly, there are many genes in common between the three time states; 28.8% are significant in all three, and 61.7% in at least two (S1 Fig).


System-Wide Associations between DNA-Methylation, Gene Expression, and Humoral Immune Response to Influenza Vaccination.

Zimmermann MT, Oberg AL, Grill DE, Ovsyannikova IG, Haralambieva IH, Kennedy RB, Poland GA - PLoS ONE (2016)

Genes whose expression is highly correlated with cis-acting CpGs show functional enrichment.A) Genes with significant association (p < 1E-4) indicate 32 GO terms enriched at the p < 0.01 level and annotating at least 3 genes, across time points. Color intensity is used to signify statistical significance. Genes are mapped to network biology resources (see Methods) and the associations at B) baseline, C) during early and D) late time periods shown, represented in the same location in all panels; (for brevity, only genes within the largest connected components are shown). We color genes in the network that have a significant association at each time period (baseline teal, early green, late orange). The network layout is manually adjusted and edges bundled to improve legibility. See the online version for sufficient resolution to view gene names.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4816338&req=5

pone.0152034.g001: Genes whose expression is highly correlated with cis-acting CpGs show functional enrichment.A) Genes with significant association (p < 1E-4) indicate 32 GO terms enriched at the p < 0.01 level and annotating at least 3 genes, across time points. Color intensity is used to signify statistical significance. Genes are mapped to network biology resources (see Methods) and the associations at B) baseline, C) during early and D) late time periods shown, represented in the same location in all panels; (for brevity, only genes within the largest connected components are shown). We color genes in the network that have a significant association at each time period (baseline teal, early green, late orange). The network layout is manually adjusted and edges bundled to improve legibility. See the online version for sufficient resolution to view gene names.
Mentions: We considered the correlation between methylation loci and cis-gene expression independent of immune outcome. Table 1 lists the top 20 cis-associations between Day 0 methylation levels and Day 0 gene expression measured by RNA-Seq, for the average methylation level across each genomic region (gene promoter or body). See S6 Table for the full list, and for correlations with gene expression at later time points. The system-wide summary of differential (through time) cis-acting methylation is shown in Fig 1, using the genes whose expression is correlated with a cis-acting CpG with p < 1E-4; 716 CpG sites in total, with the 161 genes sharing network connections displayed in Fig 1. We show the same network configuration with color indicating three different temporal states: Baseline (Day 0, pre-vaccination); Early (Day 3); and Late (Day 28) immune response after vaccination. While Day 28 is approximately a peak of adaptive response [68,69], we refer to it as “late” in this study for simplicity. The genes meeting the aforementioned significance threshold were carried on to GO term [70] enrichment, which identifies participation in similar biologic functions. Further, this group of genes with significant methylation-expression associations are depleted (compared to randomly selecting 716 genes) for network interactions (p = 0.028), potentially indicating their diverse functional roles. Interestingly, there are many genes in common between the three time states; 28.8% are significant in all three, and 61.7% in at least two (S1 Fig).

Bottom Line: The genes and molecular functions implicated by each analysis were compared, highlighting different aspects of the biologic mechanisms of immune response affected by differential methylation.Both cis-acting (within the gene or promoter) and trans-acting (enhancers and transcription factor binding sites) sites show significant associations with measures of humoral immunity.Specifically, we identified a group of CpGs that, when coordinately hypo-methylated, are associated with lower humoral immune response, and methylated with higher response.

View Article: PubMed Central - PubMed

Affiliation: Department of Health Science Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, United States of America.

ABSTRACT
Failure to achieve a protected state after influenza vaccination is poorly understood but occurs commonly among aged populations experiencing greater immunosenescence. In order to better understand immune response in the elderly, we studied epigenetic and transcriptomic profiles and humoral immune response outcomes in 50-74 year old healthy participants. Associations between DNA methylation and gene expression reveal a system-wide regulation of immune-relevant functions, likely playing a role in regulating a participant's propensity to respond to vaccination. Our findings show that sites of methylation regulation associated with humoral response to vaccination impact known cellular differentiation signaling and antigen presentation pathways. We performed our analysis using per-site and regionally average methylation levels, in addition to continuous or dichotomized outcome measures. The genes and molecular functions implicated by each analysis were compared, highlighting different aspects of the biologic mechanisms of immune response affected by differential methylation. Both cis-acting (within the gene or promoter) and trans-acting (enhancers and transcription factor binding sites) sites show significant associations with measures of humoral immunity. Specifically, we identified a group of CpGs that, when coordinately hypo-methylated, are associated with lower humoral immune response, and methylated with higher response. Additionally, CpGs that individually predict humoral immune responses are enriched for polycomb-group and FOXP2 transcription factor binding sites. The most robust associations implicate differential methylation affecting gene expression levels of genes with known roles in immunity (e.g. HLA-B and HLA-DQB2) and immunosenescence. We believe our data and analysis strategy highlight new and interesting epigenetic trends affecting humoral response to vaccination against influenza; one of the most common and impactful viral pathogens.

Show MeSH
Related in: MedlinePlus