Abstract
Background: Neonatal sepsis is a heterogeneous condition affecting preterm infants whose underlying mechanisms remain unknown. The analysis of changes in the DNA methylation pattern can contribute to improving the understanding of molecular pathways underlying disease pathophysiology. Methylation EPIC 850K BeadChip technology is an excellent tool for genome-wide methylation analyses and the detection of differentially methylated regions (DMRs). Objective: The aim is to identify DNA methylation traits in complex diseases, such as neonatal sepsis, using data from Methylation EPIC 850K BeadChip arrays. Methods: Two different bioinformatic methods, DMRcate (a supervised approach) and mCSEA (an unsupervised approach), were used to identify DMRs using EPIC data from leukocytes of neonatal septic patients. Here, we describe with detail the implementation of both methods as well as their applicability, briefly discussing the results obtained for neonatal sepsis. Results: Differences in methylation levels were observed in neonatal sepsis patients. Moreover, differences were identified between the two subsets of the disease: Early-Onset neonatal Sepsis (EOS) and Late-Onset Neonatal Sepsis (LOS). Conclusion: This approach by using DMRcate and mCSA helped us to gain insight into the intricate mechanisms that may drive EOS and LOS development and progression in newborns.
Highlights
Epigenetics encompasses all mechanisms that control the gene expression pattern without altering the DNA sequence itself, which participate in cell development and differentiation, lineage identity and transcriptional regulation
Differences were identified between the two subsets of the disease: Early-Onset neonatal Sepsis (EOS) and Late-Onset Neonatal Sepsis (LOS)
The exploration of data before and after the processing was performed by a PCA analysis (Fig. 3A), which shows that samples tend to separate between sepsis and control samples with some overlap
Summary
Epigenetics encompasses all mechanisms that control the gene expression pattern without altering the DNA sequence itself, which participate in cell development and differentiation, lineage identity and transcriptional regulation. The present study aims to propose an analysis strategy to identify DNAm traits in neonatal sepsis using Illumina Infinium Methylation EPIC 850k BeadChip array data for identifying differentially methylated CpGs (DMCs) and differentially methylated regions (DMRs). The identification of DMCs is performed by means of the standard differential analysis, while the discovery of DMRs entails a greater complexity because they integrate the methylation data of consecutive CpGs, and in some cases, an accurate FDR control is non-trivial. Methylation EPIC 850K BeadChip technology is an excellent tool for genome-wide methylation analyses and the detection of differentially methylated regions (DMRs)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
