ADDI's Editorial Take

What is it and what does it include? 

In this study, investigators collected human brain samples from control and advanced AD patients from the Mount Sinai Brain Bank. These samples were subjected to RNAseq analysis to monitor RNA level changes during AD progression. RNA was Trizol extracted, Ribominus selected and submitted for high-throughput sequencing. 

Investigators’ rationale was that Neuronal ELAV-like (nELAVL) RNA binding proteins have been linked to numerous neurological disorders. They identified nELAVL binding sites which correlated with differential splicing of a number of transcripts of RNA regulation in AD brain. 

How can I use this dataset to advance my research? 

This dataset is ideal if: 

  • you’re studying the existence and relationship between miRNAs regulation of multiple AD-related cellular and molecular pathways. 

Has this dataset helped researchers understand Alzheimer’s and other dementias better? 

Of course!  

  • AD & Gene Expression: 

In 2018, researchers aimed to study miRNAs involved in AD and their target genes, the determination of the most important miRNAs, genes and their pathways in AD, and their research demonstrated the most important genes, miRNAs, miRNA-mRNA interactions and their related pathways in AD using Bioinformatics methods. Accordingly, their defined genes and miRNAs could be used for future molecular studies in the context of AD. Their findings suggests that the different expressions of genes and miRNAs are one of the most important variables in AD; these should be probed in further studies for better understanding of the gene regulatory network, molecular mechanisms of AD, developing new therapeutic approaches, future studying of miRNA function and regulation and their potential as diagnostic biomarkers for AD. March 2018 – DOI:  https://www.nature.com/articles/s41598-018-20959-0#Sec10 

  • AD & RNAseq: 

In 2016, investigators found that intronic nELAVL binding regulates alternative splicing of numerous transcripts in human brain, including transcripts associated with central nervous system disorders. They proposed that the increased nELAVL/Y RNA association during stress may lead to nELAVL sequestration, redistribution of nELAVL target binding, and altered neuronal RNA splicing. They also investigated RNA regulation in AD brains, and found that numerous transcripts were differentially spliced in AD, which correlated with differential nELAVL binding in some cases. Further work is needed to explain some of these mechanistic connections between the Y RNAs and AD. Feb 2016 – DOI: 10.7554/eLife.10421