Summary: Multiple neurodegenerative disorders harbor similar fundamental dysfunctional cellular processes.
Source: University of Arizona
A bewildering array of neurodegenerative diseases are known to attack distinct regions of the brain, causing severe cognitive and motor deficits. The combined impact of these (usually fatal) diseases has taken a heavy toll on society.
New knowledge suggests that many of these conditions have their origins in a constellation of common processes, which play out in different ways as each disease develops.
In a study published in the current issue of Alzheimer’s and dementia: the journal of the Alzheimer’s associationcorresponding author Carol Huseby of Arizona State University and colleagues study 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 Center for Neurodegenerative Disease Research.
The study uses an innovative approach, which includes machine learning analysis of RNA present in whole blood. By comparing multiple diseases, researchers can identify which RNA markers are present in multiple neurodegenerative diseases and which are unique to each disease.
“It appears that several neurodegenerative diseases harbor similar fundamental dysfunctional cellular processes,” says Huseby, a researcher at the ASU-Banner Center for Neurodegenerative Disease Research.
“Differences between diseases may be key to uncovering regional cell type vulnerabilities and therapeutic targets for each disease.”
The blood samples used for the study came from a publicly available dataset known as the Gene Expression Omnibus. Each of the six neurodegenerative diseases was probed. As the machine learning algorithm iterated through thousands of genes, it gathered sets of RNA transcripts that optimally classified each disease, comparing the data with RNA samples from blood from healthy patients.
Selected RNA transcripts reveal eight themes common to the six neurodegenerative diseases: transcriptional regulation, degranulation (a process involved in inflammation), immune response, protein synthesis, cell death or apoptosis, cytoskeletal components, ubiquitylation/proteasome ( involved in protein breakdown) and mitochondrial complexes (which oversee energy use in cells). The eight cellular dysfunctions brought to light are associated with identifiable cerebral pathologies characteristic of each disease.
The study also identified uncommon transcripts for each disease, which may represent unexplored disease pathways. These disease-specific outliers can be explored as a potential source of diagnostic biomarkers.
For example, while synaptic loss was a common feature across the six diseases analyzed, transcripts related to a phenomenon known as spliceosome regulation were detected only in Alzheimer’s disease. (The spliceosome is a protein complex found in the cell nucleus that is essential for proper cell function. Faulty RNA splicing is associated with disease.)
The investigation of blood biomarkers of neurodegenerative diseases, coupled with powerful statistical methods using artificial intelligence, has opened a new window on these serious conditions. Blood can be easily collected from living patients in all stages of health and disease, providing a powerful new tool for early diagnosis.
According to the United Nations, when all neurodegenerative diseases are taken into account, the global death toll could exceed a staggering one billion people. The course of many of these diseases is long and unforgiving, causing not only severe suffering for patients, but also a massive economic burden on health care systems.
New methods of early diagnosis, improved treatments and possible methods of prevention are essential.
However, most neurodegenerative diseases are difficult to accurately diagnose and stubbornly resist treatment, including Alzheimer’s disease (AD), the leading cause of dementia.
Although genetic factors play a role in the development of AD, most cases are considered sporadic, meaning the underlying causes are unclear.
This is also the case for three other diseases highlighted in the study: frontotemporal dementia, ALS and Parkinson’s disease. Huntington’s disease and Friedreich’s ataxia seem to be of genetic origin and are said to be familial.
Signs of neurodegeneration are detectable in the central nervous and peripheral vascular systems. Diseases can 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 selected by the machine learning process, which reveals gene expression patterns common to the six neurodegenerative diseases explored in the study as well as distinct and disease-dependent expression profiles. disease.
Thousands of these trees are created and statistically compared by the machine learning algorithm, to select clusters of 20 transcripts that best match known disease pathways in the diseases under study.
The results offer clues to common cellular characteristics that may play a role in initiating neurodegenerative processes. The study also raises baffling questions about how distinct forms of disease ultimately develop from these common elements.
From RNA transcripts extracted from blood, some 10,000 genes are expressed. The machine learning algorithm, known as Random Forest, categorizes the data and compares the results with gene expression profiles known to be associated with disease-related biological pathways.
Whole blood screening and full RNA profile examination can overcome the limitations of many other forms of testing, which are often less comprehensive, expensive, highly invasive, and labor intensive.
See also
Whole blood diagnostics, on the other hand, can be performed at low cost virtually anywhere in the world. Blood results can be tracked over time, providing a valuable window into disease progression. Research of this type can also encourage new modes of treatment.
The results suggest a tantalizing possibility: Transcriptional changes shared by multiple disease types may provide the initial seeds that later develop into each of the distinct brain conditions. The mechanisms responsible for the germination of these common factors to produce various diseases and symptoms, attacking different regions of the brain, remain a central enigma to be solved.
Future research will explore the transcriptional impacts on neurons in addition to blood cells as well as the underlying mechanisms that set the stage for neurodegenerative diseases to develop and evolve their distinct pathologies.
About this Neurology and Genetics Research News
Author: Press office
Source: University of Arizona
Contact: Press Office – University of Arizona
Image: Image is credited to Shireen Dooling
Original research: Access closed.
“Blood RNA Transcripts Reveal Similar and Differential Alterations in Fundamental Cellular Processes in Alzheimer’s Disease and Other Neurodegenerative Diseases” by Carol J. Huseby et al. Alzheimer’s and dementia
Abstract
Blood RNA transcripts reveal similar and differential alterations in fundamental cellular processes in Alzheimer’s disease and other neurodegenerative diseases
Background
The dysfunctional processes of Alzheimer’s disease and other neurodegenerative diseases lead to neural degeneration of the central and peripheral nervous system. Research demonstrates that neurodegeneration of any kind is a systemic disease that can even begin outside of the region vulnerable to disease. Neurodegenerative diseases are defined by the vulnerabilities and pathology occurring in affected regions.
Method
Random forest machine learning analysis of whole blood transcriptomes of six neurodegenerative diseases generated unbiased RNA transcripts classifying the diseases, which were then subjected to pathway analysis.
Results
We report that selected blood transcriptome transcripts for each of the neurodegenerative diseases represent fundamental biological cellular processes, including transcriptional regulation, degranulation, immune response, protein synthesis, apoptosis, cytoskeletal components, l Ubiquitylation/proteasome and mitochondrial complexes 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.
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