Background
Zika virus is a mosquito-borne disease and its infection has no or mild symptoms in the majority of cases. However, Zika virus infection during pregnancy is associated with severe birth defects in newborns with microcephaly being the most concerning complication. The precise mechanisms of how the infection affects the fetus remain elusive even though the importance of epigenetic changes during Zika virus infection is known to be highly relevant. Inference of differentially methylated regions (DMRs) can provide useful insights in understanding the mechanisms of which genetic regions and how Zika virus infection affects in the fetus, yet the reliable and sensitive tools are lacking.
Solutions
- We developed a new data-driven algorithm called Persimmon for the identification of differentially methylated regions (DMRs). We applied it to publicly available EPIC microarray data of newborns from control and Zika virus-infected people during pregnancy. Our analysis revealed previously unknown DMRs in the blood of babies born with congenital microcephaly caused by maternal Zika virus infection.
- Persimmon takes a data-driven approach to detect regions of similar methylation patterns and leverages the power of mixed effect linear regression models to test their association with the condition of interest.
- Our approach unveiled 12 previously undetected DMRs situated in regulatory regions of both known (N=9) and novel (N=3) Zika infection-associated genes.
- Functional analysis highlighted enrichment in pathways related to development, neuron death, brain pathogenesis, and olfactory signaling, shedding light on potential mechanisms underlying the outcomes of Zika virus infection.
- These findings offer novel insights into the role of methylation changes during fetal development and Zika virus pathogenesis, ultimately enabling the development of therapeutic interventions.
This analysis emphasizes a need for continuous development of computational algorithms and tools to empower understanding of diseases and novel therapeutic development.
Cover image credits: airborne77 / Adobe Stock