Unique cellular hallmarks found in 6 neurodegenerative diseases - Video

In a study appearing in the current issue ofAlzheimer's & Dementia: The Journal of the Alzheimer' Association,corresponding author Carol Huseby of Arizona State University and her colleagueslook 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 andParkinson's disease.Carol Huseby is a researcher with the ASU-BannerNeurodegenerative Disease Research Center.

The study uses an innovative approach, whichincludes the machine learning analysis of RNA found in whole blood. Bycomparing multiple diseases, researchers can identify which RNA markers occuracross several neurodegenerative diseases and which are unique to each disease.

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

"It appears that multiple neurodegenerativediseases harbor similar fundamental dysfunctional cellular processes," saysHuseby, a researcher with the ASU-Banner Neurodegenerative Disease ResearchCenter. "Differences between diseases may be key to discovering regionalcell-type vulnerabilities and therapeutic targets for each disease."

The blood samples used for the study werederived from a publicly available data set known as the Gene ExpressionOmnibus. Each of the six neurodegenerative diseases were probed. As the machinelearning algorithm combed through thousands of genes, it assembled sets of RNAtranscripts that optimally classified each disease, comparing the data with RNAsamples from healthy patient blood.

The selected RNA transcripts reveal eightcommon themes across the six neurodegenerative diseases: transcriptionregulation, degranulation (a process involved in inflammation), immuneresponse, protein synthesis, cell death or apoptosis, cytoskeletal components,ubiquitylation/proteasome (involved in protein degradation) and mitochondrialcomplexes (which oversee energy usage in cells). The eight cellulardysfunctions uncovered are associated with identifiable pathologies in thebrain characteristic of each disease.

The study also identified uncommon transcriptsfor each disease, which may represent unexplored disease pathways. Suchdisease-specific outliers may be explored as a potential source of diagnosticbiomarkers.

For example, while synaptic loss was a common featurein all six of the diseases analyzed, transcripts related to a phenomenon knownas spliceosome regulation were only detected in the case of Alzheimer'sdisease. (The spliceosome is a protein complex found in the cell nucleus,essential for proper cell function. Defective splicing of RNA is associatedwith disease.)

The investigation of blood biomarkers forneurodegenerative diseases, coupled with powerful statistical methods usingartificial intelligence, has opened a new window on these serious afflictions.Blood can be easily sampled in living patients at all stages of health anddisease, providing a powerful new tool for early diagnosis.

According to the United Nations, when allneurodegenerative diseases are considered, the global death toll may top astaggering 1 billion people. The course of many such diseases is protracted andpitiless, causing not only grave suffering to patients but a massive economicburden on health care systems. New methods of early diagnosis, improvedtreatments and possible methods of prevention are vitally needed.

Most neurodegenerative diseases, however, havebeen tricky to accurately diagnose and stubbornly resistant to treatment,including Alzheimer's disease (AD), the leading cause of dementia. Whilegenetic factors do play a role in the development of AD, most cases areregarded as sporadic, meaning the underlying causes are unclear. This is alsothe case with three other diseases highlighted in the study: frontotemporaldementia, ALS and Parkinson's disease. Huntington's disease and Friedreich'sataxia appear to be genetically determined and are said to be familial.

Signposts of neurodegeneration are detectablein both the central nervous and peripheral vascular systems. The diseases mayalso migrate from their point of origin to distant brain regions, where theyinflict most of their damage.

The study describes RNA clusters or treesselected by the machine learning process, which uncovers patterns of geneexpression common to the six neurodegenerative diseases explored in the studyas well as expression profiles that are distinct and disease dependent.Thousands of such trees are created and statistically compared by the machinelearning algorithm, to pick out groupings of 20 transcripts that most closelyalign with known disease pathways in the diseases under study.

The findings offer clues about common cellularfeatures that may play a role in jump-starting processes of neurodegeneration.The study also raises puzzling questions about how distinct disease forms ultimatelydevelop from these common elements.

From the RNA transcripts extracted from blood,some 10,000 genes are expressed. The machine learning algorithm, known asRandom Forest, categorizes the data and compares results with gene expressionprofiles known to be associated with disease-linked biological pathways.

Screening of whole blood and examination ofthe complete RNA profile can overcome the limitations of many other forms oftesting, which are often less comprehensive as well as expensive, highlyinvasive and labor intensive. Diagnosis through whole blood, in contrast, canbe carried out at low cost virtually anywhere in the world. Blood results canbe tracked over time, providing a valuable window on disease progression.Research of this kind may also encourage new modes of treatment.

The results suggest a tantalizing possibility:Transcriptional changes shared by multiple disease types may provide theinitial seeds that later develop into each of the distinct brain afflictions.The mechanisms responsible for these common factors germinating to producediverse diseases and symptomologies, attacking different regions of the brain,remain a central puzzle to be solved.

Future research will explore transcriptionalimpacts on neurons in addition to blood cells as well as the underlyingmechanisms that set the stage for neurodegenerative diseases to develop andevolve their distinct pathologies.

Reference:

CarolHuseby et al,Blood RNA transcripts reveal similar and differential alterationsin fundamental cellular processes in Alzheimer's disease and otherneurodegenerative diseases,Alzheimer s & Dementia,DOI:10.1002/alz.12880