4.5 Article

Transcriptomics Profiling of Alzheimer's Disease Reveal Neurovascular Defects, Altered Amyloid-beta Homeostasis, and Deregulated Expression of Long Noncoding RNAs

Journal

JOURNAL OF ALZHEIMERS DISEASE
Volume 48, Issue 3, Pages 647-665

Publisher

IOS PRESS
DOI: 10.3233/JAD-150398

Keywords

Alzheimer's disease; amyloid homeostasis; cerebral vasculature; long noncoding RNAs; natural antisense transcripts; RNA sequencing

Categories

Funding

  1. US NIH NINDS [R01NS081208-01A1]
  2. Swiss National Science Foundation
  3. NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R01NS081208] Funding Source: NIH RePORTER

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The underlying genetic variations of late-onset Alzheimer's disease (LOAD) cases remain largely unknown. A combination of genetic variations with variable penetrance and lifetime epigenetic factors may converge on transcriptomic alterations that drive LOAD pathological process. Transcriptome profiling using deep sequencing technology offers insight into common altered pathways regardless of underpinning genetic or epigenetic factors and thus represents an ideal tool to investigate molecular mechanisms related to the pathophysiology of LOAD. We performed directional RNA sequencing on high quality RNA samples extracted from hippocampi of LOAD and age-matched controls. We further validated our data using qRT-PCR on a larger set of postmortem brain tissues, confirming downregulation of the gene encoding substance P (TAC1) and upregulation of the gene encoding the plasminogen activator inhibitor-1 (SERPINE1). Pathway analysis indicates dysregulation in neural communication, cerebral vasculature, and amyloid-beta clearance. Beside protein coding genes, we identified several annotated and non-annotated long noncoding RNAs that are differentially expressed in LOAD brain tissues, three of them are activity-dependent regulated and one is induced by A beta(1-42) exposure of human neural cells. Our data provide a comprehensive list of transcriptomics alterations in LOAD hippocampi and warrant holistic approach including both coding and non-coding RNAs in functional studies aimed to understand the pathophysiology of LOAD.

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