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[Preprint]. 2024 Apr 3:rs.3.rs-4160354.
doi: 10.21203/rs.3.rs-4160354/v1.

Respiratory Infection- and Asthma-prone, Low Vaccine Responder Children Demonstrate Distinct Mononuclear Cell DNA Methylation Pathways

Affiliations

Respiratory Infection- and Asthma-prone, Low Vaccine Responder Children Demonstrate Distinct Mononuclear Cell DNA Methylation Pathways

David Martino et al. Res Sq. .

Update in

Abstract

Background: Infants with frequent viral and bacterial respiratory infections exhibit compromised immunity to routine immunisations. They are also more likely to develop chronic respiratory diseases in later childhood. This study investigated the feasibility of epigenetic profiling to reveal endotype-specific molecular pathways with potential for early identification and immuno-modulation. Peripharal immune cells from respiratory infection allergy/asthma prone (IAP) infants were retrospectively selected for genome-wide DNA methylation and single nucleotide polymorphism analysis. The IAP infants were enriched for the low vaccine responsiveness (LVR) phenotype (Fishers Exact p-value = 0.01).

Results: An endotype signature of 813 differentially methylated regions (DMRs) comprising 238 lead CpG associations (FDR < 0.05) emerged, implicating pathways related to asthma, mucin production, antigen presentation and inflammasome activation. Allelic variation explained only a minor portion of this signature. Stimulation of mononuclear cells with monophosphoryl lipid A (MPLA), a TLR agonist, partially reversing this signature at a subset of CpGs, suggesting the potential for epigenetic remodelling.

Conclusions: This proof-of-concept study establishes a foundation for precision endotyping of IAP children and highlights the potential for immune modulation strategies using adjuvants for furture investigation.

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Conflict of interest statement

Competing interests JL-S is a scientific advisor to Precion Inc. and TruDiagnostic Inc. OL and SvH are named inventors on patents related to vaccine adjuvants and human in vitro systems that model immune responses. Their laboratories have received a sponsored research agreement from GlaxoSmithKline (GSK). OL is a co-founder of Ovax LLC.

Figures

Figure 1
Figure 1. Epigenome-wide association study of IAP and NIAP infants demonstrates differentially methylated regions enriched with immune response genes.
(A) Volcano plot of differentially methylated regions significantly associated with IAP status. X-axis represents the average methylation change from NIAP group (delta methylation ratio) and the y-axis shows the log region size in base pairs. Points are coloured according to maximum observed methylation difference in region. (B) Circular visualization of significant SNP-CpG association pairs showing chromosomal location of associated markers. (C) Boxplot of representative methylation quantitative trait loci (mQTLs). Y-axis shows mean methylation ratio with standard deviation stratified by SNP genotype. (D) Dotchart of summary statistics from gene ontology enrichment analysis of the infection prone associated methylation signature highlighting significantly enriched pathways. The y-axis shows gene set nomenclature, point size reflects total count of differentially methylated genes, points are ranked by the percentage of genes in the set covered, and coloured according to false discovery rate adjusted P-value. Diff = Differentially, DMRs = differentially methylated regions, IAP = Infection allergy/asthma prone, NIAP = non-infection allergy/asthma prone, PBS = phosphate buffered saline, max = maximum, bp = base pairs, P.DE = p-value for over-representation of the GO or KEGG term, Coverage = percentage of genes identified within specified pathway.
Figure 2
Figure 2. Stimulation with MPL adjuvant modifies a subset of endotype-associated CpGs.
(A) Dotchart of summary statistics from gene ontology enrichment analysis for the MPL-associated differentially methylated regions highlighting significantly enriched pathways. The y-axis shows gene set nomenclature, point size reflects total count of differentially methylated genes, points are ranked by the percentage of genes in the set covered, and coloured according to false discovery rate adjusted P-value. (B) Venn diagram of overlapping regions showing counts of unique and overlapping regions. (C) Bland-Altman visualization of methylation difference after MPL stimulation for 183 MPL-sensitive CpGs. Y-values represent the difference in log2 fold-change (NIAP – IAP) between PBS and MPL condition. X-axis shows mean methylation value for each CpG. Upper and lower 95% confidence intervals are shown as red lines. (D) Boxplot of median and quartile range for the four most significantly ranked endotype-associated CpGs modified by MPL treatment. DMRs = differentially methylated regions, MPL = monophosphoryl lipid A, P.DE = p-value for over-representation of the GO or KEGG term, Coverage = percentage of genes identified within specified pathway. Hypermeth = hypermethylated regions. Hypometh = hypomethylated regions.*** = P<0.001, **=P<0.05 – 0.05, ns= P > 0.05, two sided t-test.

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