A Genome-Wide Study of Single-Nucleotide Polymorphisms in MicroRNAs and Further In Silico Analysis Reveals Their Putative Role in Susceptibility to Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease (LOAD) is a neurodegenerative disorder of growing relevance in an aging society for which predictive biomarkers are needed. Many genes involved in LOAD are tightly controlled by microRNAs (miRNAs), which can be modulated by single-nucleotide polymorphisms (SNPs). Our aim was to determine the association between SNPs in miRNAs and LOAD. We selected all SNPs in pre-miRNAs with a minor allele frequency (MAF) > 1% and genotyped them in a cohort of 229 individuals diagnosed with LOAD and 237 unrelated healthy controls. In silico analyses were performed to predict the effect of SNPs on miRNA stability and detect downstream pathways. Four SNPs were associated with LOAD risk with apvalue < 0.01 (rs74704964 in hsa-miR-518d, rs71363366 in hsa-miR-1283-2, rs11983381 in hsa-miR-4653, and rs10934682 in hsa-miR-544b). In silico analyses support a possible functional effect of those SNPs in miRNA levels and in the regulation of pathways of relevance for the development of LOAD. Although the results are promising, additional studies are needed to validate the association between SNPs in miRNAs and the risk of developing LOAD.

Automated summary

This study identified four SNPs in miRNAs associated with LOAD risk, with in silico analyses supporting a potential functional effect of these SNPs on miRNA levels and regulation of pathways relevant to LOAD development. Additional studies are needed to validate these findings.