Alzheimer's disease (AD) is a neurodegenerative disorder that is the most common cause of dementia in the elderly, and intracellular neurofibrillary tangles (NFTs) are one of the pathological features of AD. Recent studies have suggested long noncoding RNAs (lncRNAs) play important roles in AD. Competing endogenous RNAs (ceRNAs) is a mechanism that has recently been proposed, in which lncRNAs compete for common miRNA-binding sites with mRNAs. However, the roles of lncRNAs and ceRNA in AD NFTs is limited. In this study, we constructed a global triple network based on ceRNA theory, then an AD NFT lncRNA-mRNA network (NFTLMN) was generated. By analyzing the NFTLMN, three lncRNAs (AP000265.1, KB-1460A1.5 and RP11-145M9.4), which are highly related with AD NFTs were identified. To further explore the cross-talk between mRNAs and lncRNAs, a clustering module analysis was performed on the NFTLMN and two AD NFT related modules were identified. Our study provides a better understanding of the molecular basis of AD NFTs and may offer novel treatment strategies for AD.
Keywords: Alzheimer's disease; Competing endogenous RNAs (ceRNAs); Intracellular neurofibrillary tangles (NFT); Long noncoding RNAs (lncRNAs); Network.
Copyright © 2016. Published by Elsevier Inc.