April 26, 2022
The Burden of Alzheimer’s Disease
Alzheimer’s disease (AD) is a progressive neurodegenerative disease whose underlying mechanisms have proven difficult to uncover. Attempts to target the misfolded amyloid protein plaques characteristically found in AD patients’ brains have largely failed.
However, it is likely that protein misfolding is only one contributing element in this multifactorial disease and may even be driven by other mutations or pathogenic processes.
Single Cell Analysis of Alzheimer’s Neurons
Thus, in the age of genomics and bioinformatics, a new approach to this devastating disease was long overdue. In a study published in Nature last week by Miller et. al, the authors utilized single cell whole genome sequencing on healthy neurons and AD neurons.
It turns out that over time, neurons progressively accumulate mutations in their DNA in spite of being a non-dividing cell type, and they accumulate these mutations at similar rates to those of other, dividing cell types. So how do those mutations differ in AD neurons?
Somatic Mutation Signatures of AD
The authors found that neurons affected by AD have higher rates of DNA mutations than typical neurons, and that those mutations follow distinct patterns, patterns which seemingly could be caused by oxidative stress. One is an unusually high rate of C to A (cytosine to adenine) changes, while other mutations cause errors in transcriptional repair machinery, causing further mutations and increased cellular stress.
These results suggest that the known pathogenic mechanisms of AD like oxidative stress may do their damage via previously unidentified DNA mutations and genomic damage, accumulating over time to progressively impair neuronal function. This adds another piece to the puzzle of the many contributing factors to AD pathogenesis and could provide further molecular targets for therapeutic research.
Outsourcing Bioinformatics Analysis
Building pipelines for scRNA-seq data analysis is a complex computational task. Outsourcing your bioinformatics analyses can expedite the process, eliminate common challenges and improve reproducibility. Book a free discovery call with us at Bridge Informatics to discuss your project needs.
Jane Cook, Journalist & Content Writer, Bridge Informatics
Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email daniel.dacey@old.bridgeinformatics.com or dan.ryder@old.bridgeinformatics.com.
Sources:
https://www.nature.com/articles/s41586-022-04640-1
