Biology Faculty Articles
Title
Integrated whole transcriptome and DNA methylation analysis identifies gene networks specific to late-onset Alzheimer’s disease
Document Type
Article
Publication Date
1-1-2015
Publication Title
Journal of Alzheimers Disease
ISSN
1387-2877
Volume
44
Issue/No.
3
First Page
977
Last Page
987
Abstract
Previous transcriptome studies observed disrupted cellular processes in late-onset Alzheimer's disease (LOAD), yet it is unclear whether these changes are specific to LOAD, or are common to general neurodegeneration. In this study, we address this question by examining transcription in LOAD and comparing it to cognitively normal controls and a cohort of "disease controls." Differential transcription was examined using RNA-seq, which allows for the examination of protein coding genes, non-coding RNAs, and splicing. Significant transcription differences specific to LOAD were observed in five genes: C10orf105, DIO2, a lincRNA, RARRES3, and WIF1. These findings were replicated in two independent publicly available microarray data sets. Network analyses, performed on 2,504 genes with moderate transcription differences in LOAD, reveal that these genes aggregate into seven networks. Two networks involved in myelination and innate immune response specifically correlated to LOAD. FRMD4B and ST18, hub genes within the myelination network, were previously implicated in LOAD. Of the five significant genes, WIF1 and RARRES3 are directly implicated in the myelination process; the other three genes are located within the network. LOAD specific changes in DNA methylation were located throughout the genome and substantial changes in methylation were identified within the myelination network. Splicing differences specific to LOAD were observed across the genome and were decreased in all seven networks. DNA methylation had reduced influence on transcription within LOAD in the myelination network when compared to both controls. These results hint at the molecular underpinnings of LOAD and indicate several key processes, genes, and networks specific to the disease.
NSUWorks Citation
Humphries, C. E.; M. A. Kohli; Lubov Nathanson; P. Whitehead; G. Beecham; E. Martin; D. C. Mash; M. A. Pericak-Vance; and J. Gilbert. 2015. "Integrated whole transcriptome and DNA methylation analysis identifies gene networks specific to late-onset Alzheimer’s disease." Journal of Alzheimers Disease 44, (3): 977-987. https://nsuworks.nova.edu/cnso_bio_facarticles/122
