A perplexing range of neurodegenerative diseases are known to attack distinct regions of the brain, causing severe cognitive and motor deficit. The combined impact of those (generally fatal) diseases has inflicted a devastating toll on society. Latest insights suggest lots of these afflictions have their origin in a constellation of common processes, which play out in alternative ways as each disease develops.

In a study appearing in the present issue of Alzheimer’s & Dementia: The Journal of the Alzheimer’ Association, corresponding creator Carol Huseby of Arizona State University and her colleagues take a look at cellular alterations in six distinct neurodegenerative diseases: amyotrophic lateral sclerosis or Lou Gehrig’s disease, Alzheimer’s disease, Friedreich’s ataxia, frontotemporal dementia, Huntington’s disease and Parkinson’s disease.Carol Huseby is a researcher with the ASU-Banner Neurodegenerative Disease Research Center.

The study uses an modern approach, which incorporates the machine learning evaluation of RNA present in whole blood. By comparing multiple diseases, researchers can discover which RNA markers occur across several neurodegenerative diseases and that are unique to every disease.

It seems that multiple neurodegenerative diseases harbor similar fundamental dysfunctional cellular processes. Differences between diseases could also be key to discovering regional cell-type vulnerabilities and therapeutic targets for every disease.”

Carol Huseby, Researcher, ASU-Banner Neurodegenerative Disease Research Center

The blood samples used for the study were derived from a publicly available data set referred to as the Gene Expression Omnibus. Each of the six neurodegenerative diseases were probed. Because the machine learning algorithm combed through hundreds of genes, it assembled sets of RNA transcripts that optimally classified each disease, comparing the info with RNA samples from healthy patient blood.

The chosen RNA transcripts reveal eight common themes across the six neurodegenerative diseases: transcription regulation, degranulation (a process involved in inflammation), immune response, protein synthesis, cell death or apoptosis, cytoskeletal components, ubiquitylation/proteasome (involved in protein degradation) and mitochondrial complexes (which oversee energy usage in cells). The eight cellular dysfunctions uncovered are related to identifiable pathologies within the brain characteristic of every disease.

The study also identified unusual transcripts for every disease, which can represent unexplored disease pathways. Such disease-specific outliers could also be explored as a possible source of diagnostic biomarkers.

For instance, while synaptic loss was a typical feature in all six of the diseases analyzed, transcripts related to a phenomenon referred to as spliceosome regulation were only detected within the case of Alzheimer’s disease. (The spliceosome is a protein complex present in the cell nucleus, essential for correct cell function. Defective splicing of RNA is related to disease.)

The investigation of blood biomarkers for neurodegenerative diseases, coupled with powerful statistical methods using artificial intelligence, has opened a recent window on these serious afflictions. Blood will be easily sampled in living patients in any respect stages of health and disease, providing a robust recent tool for early diagnosis.

In line with the United Nations, when all neurodegenerative diseases are considered, the worldwide death toll may top a staggering 1 billion people. The course of many such diseases is protracted and pitiless, causing not only grave suffering to patients but a large economic burden on health care systems. Latest methods of early diagnosis, improved treatments and possible methods of prevention are vitally needed.

Most neurodegenerative diseases, nevertheless, have been tricky to accurately diagnose and stubbornly proof against treatment, including Alzheimer’s disease (AD), the leading explanation for dementia. While genetic aspects do play a task in the event of AD, most cases are thought to be sporadic, meaning the underlying causes are unclear. This can be the case with three other diseases highlighted within the study: frontotemporal dementia, ALS and Parkinson’s disease. Huntington’s disease and Friedreich’s ataxia look like genetically determined and are said to be familial.

Signposts of neurodegeneration are detectable in each the central nervous and peripheral vascular systems. The diseases might also migrate from their point of origin to distant brain regions, where they inflict most of their damage.

The study describes RNA clusters or trees chosen by the machine learning process, which uncovers patterns of gene expression common to the six neurodegenerative diseases explored within the study in addition to expression profiles which are distinct and disease dependent. 1000’s of such trees are created and statistically compared by the machine learning algorithm, to pick groupings of 20 transcripts that almost all closely align with known disease pathways within the diseases under study.

The findings offer clues about common cellular features which will play a task in jump-starting processes of neurodegeneration. The study also raises puzzling questions on how distinct disease forms ultimately develop from these common elements.

From the RNA transcripts extracted from blood, some 10,000 genes are expressed. The machine learning algorithm, referred to as Random Forest, categorizes the info and compares results with gene expression profiles known to be related to disease-linked biological pathways.

Screening of whole blood and examination of the whole RNA profile can overcome the constraints of many other types of testing, which are sometimes less comprehensive in addition to expensive, highly invasive and labor intensive. Diagnosis through whole blood, in contrast, will be carried out at low price virtually anywhere on this planet. Blood results will be tracked over time, providing a worthwhile window on disease progression. Research of this sort might also encourage recent modes of treatment.

The outcomes suggest a tantalizing possibility: Transcriptional changes shared by multiple disease types may provide the initial seeds that later grow to be each of the distinct brain afflictions. The mechanisms accountable for these common aspects germinating to supply diverse diseases and symptomologies, attacking different regions of the brain, remain a central puzzle to be solved.

Future research will explore transcriptional impacts on neurons along with blood cells in addition to the underlying mechanisms that set the stage for neurodegenerative diseases to develop and evolve their distinct pathologies.

Source:

Journal reference:

Huseby, C.J., et al. (2022) Blood RNA transcripts reveal similar and differential alterations in fundamental cellular processes in Alzheimer’s disease and other neurodegenerative diseases. Alzheimer s & Dementia. doi.org/10.1002/alz.12880.