Asthma is a complex heritable disease that is increasing in prevalence and severity, particularly in developed countries such as the United States, where 11% of the population is affected. The contribution of environmental and genetic factors to this growing epidemic is currently not well understood. We developed the hypothesis, based on previous literature, that changes in DNA methylation resulting in aberrant gene transcription may enhance the risk of developing allergic airway disease. Our findings indicate that in mice, a maternal diet supplemented with methyl donors enhanced the severity of allergic airway disease that was inherited transgenerationally. Using a genomic approach, we discovered 82 gene-associated loci that were differentially methylated after in utero supplementation with a methyl-rich diet. These methylation changes were associated with decreased transcriptional activity and increased disease severity. Runt-related transcription factor 3 (Runx3), a gene known to negatively regulate allergic airway disease, was found to be excessively methylated, and Runx3 mRNA and protein levels were suppressed in progeny exposed in utero to a high-methylation diet. Moreover, treatment with a demethylating agent increased Runx3 gene transcription, further supporting our claim that a methyl-rich diet can affect methylation status and consequent transcriptional regulation. Our findings indicate that dietary factors can modify the heritable risk of allergic airway disease through epigenetic mechanisms during a vulnerable period of fetal development in mice.
John W. Hollingsworth, Shuichiro Maruoka, Kathy Boon, Stavros Garantziotis, Zhuowei Li, John Tomfohr, Nathaniel Bailey, Erin N. Potts, Gregory Whitehead, David M. Brass, David A. Schwartz
Usage data is cumulative from January 2019 through January 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.