Background: Dysfunctional processes in Alzheimer's disease and other neurodegenerative diseases lead to neural degeneration in the central and peripheral nervous system. Research demonstrates that neurodegeneration of any kind is a systemic disease that may even begin outside of the region vulnerable to the disease. Neurodegenerative diseases are defined by the vulnerabilities and pathology occurring in the regions affected.
Method: A random forest machine learning analysis on whole blood transcriptomes from six neurodegenerative diseases generated unbiased disease-classifying RNA transcripts subsequently subjected to pathway analysis.
Results: We report that transcripts of the blood transcriptome selected for each of the neurodegenerative diseases represent fundamental biological cell processes including transcription regulation, degranulation, immune response, protein synthesis, apoptosis, cytoskeletal components, ubiquitylation/proteasome, and mitochondrial complexes that are also affected in the brain and reveal common themes across six neurodegenerative diseases.
Conclusion: Neurodegenerative diseases share common dysfunctions in fundamental cellular processes. Identifying regional vulnerabilities will reveal unique disease mechanisms.
Highlights: Transcriptomics offer information about dysfunctional processes. Comparing multiple diseases will expose unique malfunctions within diseases. Blood RNA can be used ante mortem to track expression changes in neurodegenerative diseases. Protocol standardization will make public datasets compatible.
Keywords: Alzheimer's disease; Friedreich's ataxia; Huntington's disease; Lou Gehrig's disease; Parkinson's disease; amyotrophic lateral sclerosis; frontotemporal dementia; machine learning; pathway analysis; random forest classification; whole blood RNA.
© 2022 the Alzheimer's Association.