You are viewing a javascript disabled version of the site. Please enable Javascript for this site to function properly.
Go to headerGo to navigationGo to searchGo to contentsGo to footer
In content section. Select this link to jump to navigation

Integrated Whole Transcriptome and DNA Methylation Analysis Identifies Gene Networks Specific to Late-Onset Alzheimer's Disease

Article type: Research Article

Authors: Humphries, Crystal E.a | Kohli, Martin A.b | Nathanson, Lubovc; e | Whitehead, Patriceb | Beecham, Garya; b | Martin, Edena; b | Mash, Deborah C.d | Pericak-Vance, Margaret A.a; b | Gilbert, Johna; b; *

Affiliations: [a] University of Miami, Miller School of Medicine, Dr. John T. Macdonald Foundation Department of Human Genetics, Miami, FL, USA | [b] University of Miami, Miller School of Medicine, John P. Hussman Institute for Human Genomics, Miami, FL, USA | [c] University of Miami, Miller School of Medicine, Department of Medicine, Miami, FL, USA | [d] University of Miami, Miller School of Medicine, Miami Brain Bank Endowment, FL, USA | [e] Nova Southeastern University, Ft. Lauderdale, FL, USA

Correspondence: [*] Correspondence to: John Gilbert, PhD, University of Miami Miller School of Medicine, 1501 NW 10th Avenue, Biomedical Research Building, Suite 616, Miami, FL 33136, USA. Tel.: +1 305 243 2282; Fax: +1 305 243 2703; E-mail: jgilbert@med.miami.edu.

Keywords: Alzheimer's disease, dementia with Lewy bodies, DNA methylation, expression, human brain, Illumina Human Methylation 450K, late-onset transcriptome, myelination, networks, RNA-seq, splicing

DOI: 10.3233/JAD-141989

Journal: Journal of Alzheimer's Disease, vol. 44, no. 3, pp. 977-987, 2015

Accepted 3 October 2014
|
Published: 6 February 2015
Get PDF
Supplementary Materials:

Supplementary Figure 1.

Supplementary Figure 2.

Supplementary Figure 3.

Supplementary Tables.

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.

Show more