The pathogenesis of Alzheimer's disease (AD) is identified to be significantly regulated by long non-coding RNA (lncRNA) based on in vivo and clinical experiments. Single nucleotide polymorphisms (SNPs) can strongly impact expression and function of lncRNA in AD, and previous genome-wide associations studies (GWAS) have discovered substantial amount of risk SNPs associated with AD. However, current studies omit the important information about SNPs when identifying potential AD-related lncRNAs. In addition to single discovery approach and small-scale samples in these studies, the number of lncRNAs discovered as keys in AD is limited. Here, multiple computational methods were integrated to discover novel and key lncRNA of the pathology of AD. First, large-scale GWAS data involved in three ethnicities were collected from two authoritative sources, and meta-analyses were conducted to find SNPs significantly associated with AD (tag SNPs). Second, these tag SNPs together with their linkage disequilibrium information were used to discover potential lncRNAs related to AD. Third, after validation by microarray probe re-annotation of 1,282 samples and RNA-seq data analysis of 117 samples, respectively, a total of five key lncRNAs of AD were identified. Finally, possible function of these lncRNAs was predicted by genome mapping, expression quantitative trait loci, differential co-expression, and gene set enrichment analysis. Based on function prediction, four of the five key lncRNAs were identified to affect the risk of AD by regulating corresponding pathogenic genes and pathways, which are involved in regulation of amyloid-β peptide and the immune system. In summary, these findings can facilitate the discovery of potential disease-related lncRNAs and enhance understanding of the pathogenesis of AD.
Keywords: Alzheimer’s disease; differential co-expression; genome-wide association study; long non-coding RNA; microarray probe re-annotation.