AUTHOR=Li Keyi , Chi Runqiu , Liu Liangjie , Feng Mofan , Su Kai , Li Xia , He Guang , Shi Yi 

TITLE=3D genome-selected microRNAs to improve Alzheimer's disease prediction

JOURNAL=Frontiers in Neurology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2023.1059492

DOI=10.3389/fneur.2023.1059492

ISSN=1664-2295

ABSTRACT=Alzheimer's disease (AD) is a type of neurodegenerative disease that has no effective treatment in its late stage, making the early prediction of AD critical. microRNAs (miRNAs) are a class of non-coding RNAs widely present in eukaryotic transcriptomes. There have been accumulating studies indicating that miRNAs play an important role in neurodegenerative diseases including Alzheimer's disease via epigenetic modifications including DNA methylation. Therefore, miRNAs may serve as excellent biomarkers in early AD prediction. Considering that the non-coding RNAs’ activity may be linked to their corresponding DNA loci in the 3D genome, we collected the existing AD-related miRNAs combined with 3D genomic data in this study. We proposed a novel approach for predicting AD-related classification, which can potentially be applied in AD early diagnosis and intervention.