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. 2025 Apr 28;18(1):25.
doi: 10.1186/s13072-025-00587-5.

DNA methylation signatures of severe RSV infection in infants: evidence from non-invasive saliva samples

Sara Pischedda  1   2   3 , Alberto Gómez-Carballa  1   2   3 , Jacobo Pardo-Seco  1   2   3 , Sandra Viz-Lasheras  1   3 , Alba Camino-Mera  1   2   3 , Xabier Bello  1   2   3 , María José Curras-Tuala  1   2   3 , Irene Rivero-Calle  1   3   4 , Ana I Dacosta-Urbieta  1   3   4 , Federico Martinón-Torres #  1   3   4 , Antonio Salas #  5   6   7 ; GENDRES Consortium
Collaborators, Affiliations

DNA methylation signatures of severe RSV infection in infants: evidence from non-invasive saliva samples

Sara Pischedda et al. Epigenetics Chromatin. .

Abstract

Background: Respiratory syncytial virus (RSV) poses significant morbidity and mortality risks in childhood, particularly for previously healthy infants admitted to hospitals lacking predisposing risk factors for severe disease. This study aimed to investigate the role of the host epigenome in RSV infection severity using non-invasive buccal swabs from sixteen hospitalized infants admitted to the hospital for RSV infection. Eight patients had severe symptoms, and eight had mild to moderate symptoms. For DNA methylation analyses, the Illumina EPIC BeadChip was used with DNA isolated from saliva samples. To evaluate the basal DNA methylation level of the identified biomarkers a cohort of healthy control children was used. Furthermore, DNA methylation levels of candidate genes were confirmed by pyrosequencing in both the discovery and validation cohorts of patients with mild to moderate symptoms.

Results: A panel of differentially methylated positions (DMPs) distinguishing severe from mild to moderate symptoms in infants was identified. DMPs were determined using a threshold of an adjusted P-value (false discovery rate, FDR) < 0.01 and an absolute difference in DNA methylation (delta beta) > 0.10. Differentially methylated regions (DMRs) were identified in the ZBTB38 (implicated in asthma and pulmonary disease) and the TRIM6-TRM34 gene region (associated with viral infections). The differential DNA methylation of these genes was validated in an independent replication cohort. A weighted correlation network analysis emphasized the pivotal role of a module with RAB11FIP5 as the hub gene, known for its critical function in regulating viral infections.

Conclusions: Oral mucosa methylation may play a role in determining the severity of RSV disease in infants.

Keywords: Buccal swab; DNA methylation; Epigenetic biomarkers; Respiratory syncytial virus; Severity.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study involving human participants was reviewed and approved by the Ethics Committee of Clinical Investigation of Galicia (CEIC 2016/484). Written informed consent to participate in this study was provided by the participant’s legal guardian/next of kin. This project is conducted following the ICH Harmonized Tripartite Guidelines for Good Clinical Practice, with the current national regulations (Law 14/2007 on Biomedical Research), and with the ethical principles established in the Declaration of Helsinki. The confidentiality of the data of the study participants will be guaranteed, ensuring compliance with Organic Law 3/2018, of December 5, on the Protection of Personal Data and guarantee of digital rights. Consent for publication: Not Applicable. Competing interests: Ana Isabel Dacosta Urbieta has participated in clinical trials for RSV vaccines and monoclonals with all honoraria paid to the institution. Irene Rivero Calle has received honoraria from GSK, Pfizer, Sanofi, and MSD for taking part in advisory boards and expert meetings and acting as a speaker in congresses outside the scope of the submitted work. IRC has also acted as sub-investigator in randomized controlled trials of Abbot, Astrazeneca, Enanta, Gilead, GlaxoSmithKline, Janssen, Medimmune, Merck, Moderna, MSD, Novavax, Pfizer, Reviral, Roche, Sanofi Pasteur, and Seqirus.

Figures

Fig. 1
Fig. 1
Differentially methylated positions distinguish infants with severe infection from those with mild to moderate symptoms. A PCA and B Heatmap of the significant DMPs (nominal P-value < 0.01 and delta beta > 0.10) between the severe and mild/moderate groups
Fig. 2
Fig. 2
Hypomethylation of the ZBTB38 and TRIM genes in the severe group. Boxplot and ROC curve of the cluster of CpGs observed within A ZBTB38 and B TRIM6-TRIM34 genes
Fig. 3
Fig. 3
Differentially methylated regions distinguish infants with severe infection from those with mild to moderate symptoms. Top panel: DMR plot for the two most significant DMRs within the A ZBTB38 and B TRIM6-TRIM34 genes. DNA methylation patterns in severe and mild/moderate samples differed for most of the CpGs in the DMRs. In the figure, some beta value dots of the CpGs that constitute the DMRs overlap in the two groups with similar values. Bottom panel: pairwise correlation between CpG sites in DMRs in A ZBTB38 and B TRIM6-TRIM34 genes
Fig. 4
Fig. 4
DNA methylation levels of DMPs within ZBTB38 in RSV and HC cohorts. Boxplots showing DNA methylation levels at five DMPs within ZBTB38 for the RSV cohort compared to the HC cohort from GEO. The HC cohort includes samples collected from children at three-time points: birth, 12 months, and 60 months. The RSV cohort is represented by children with mild to moderate symptoms. Methylation levels at birth are similar to the methylation levels of RSV children with mild to moderate symptoms. For all the CpGs, the HC cohort shows an increase of methylation with age, in contrast to the RSV cohort, where hypomethylation is observed for children severely ill
Fig. 5
Fig. 5
Pathway analysis revealed enrichment of pathways associated with olfactory signaling and activation. Bar plot representing the results of the enrichment pathway analysis conducted on all CpGs and specifically on CpGs located within the promoter regions using the methylglm approach. The results were obtained using the KEGG, Reactome and GO databases. The size of each bar along the x-axis indicates the number of genes associated with each pathway. Furthermore, false discovery rate (FDR) P-values are indicated
Fig. 6
Fig. 6
High reproducibility of pyrosequencing technical replicates in discovery and validation cohorts. Correlation plots showing the Pearson correlation between technical replicates for each cohort analyzed using pyrosequencing. Both the Discovery and Validation cohorts demonstrate near-perfect correlation, with Pearson correlation coefficients close to 1 and a highly significant P-value (< 2.2 × 10−16), confirming the high reproducibility of the analysis
Fig. 7
Fig. 7
Methylation levels of DMPs in discovery and validation cohorts. Boxplots showing the distribution of DNAm levels for the 10 DMPs analyzed using pyrosequencing in the Discovery and Validation cohorts and in each replicate. The analysis includes seven CpG sites in the ZBTB38 gene and three CpG sites in the TRIM6-TRIM34 gene, confirming the reproducibility of methylation patterns across independent cohorts
Fig. 8
Fig. 8
Co-methylated modules associated with RSV severity. A Selection of the soft-thresholding power involved analyzing plots that depict the correlation between the soft-thresholding powers and two metrics: the scale-free fit index (left) and the mean connectivity (right). B Clustering dendrogram of probes, with dissimilarity based on topological overlap, together with assigned module colors. C Bar plot displaying the P-values from correlation tests between the module eigengenes and the RSV severity phenotype. The color of each module is defined by its hub gene. D Heatmap of Pearson correlation analysis of modules and the clinical traits associated with RSV severity. The rows represent the 21 module eigengenes, and the columns represent the phenotypes
Fig. 9
Fig. 9
Strong negative correlation between the RAB11FIP5 module and RSV severity. A Plot of correlations between gene significance and module membership for the RAB11FIP5 module. Color coding is equivalent to module names. B Heatmap displaying the beta-values of the CpGs belonging to the RAB11FIP5 module. Additionally, the eigengene values of the samples are also shown. C Boxplot showing the variations in eigengene values of the samples from the RAB11FIP5 module between the severe and mild/moderate groups. D Dot plot showing the top KEGG pathways with an FDR < 0.01 associated with the genes in the RAB11FIP5 module. The size of each dot on the x-axis represents the number of genes associated with each pathway. Additionally, the color of each dot corresponds to the respective FDR P-values linked to the pathways
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