Newly identified proteins are predictors for dementia

Milena Flankova writes about new insights in dementia research: changes in the proteome as a potential indicator for an increased risk of disease, up to 10 years prior 

Image by Gerd Altmann from Pixabay

Dementia is a syndrome whereby brain function continuously reduces. Alzheimer’s is the most common type of dementia. The most significantly affected age group affected by Alzheimer’s is 65+. Statistically, according to the UK National Healthcare Service (NHS), 1 in 14 people over the age of 65 and 1 in 6 people over the age of 80 are affected by this condition. However, note that 1 in 20 patients with Alzheimer’s are between 40 and 65 years old.

Alzheimer’s disease is a progressive condition that causes a decline in physical and cognitive function, starting with slight memory problems and gradually developing into confusion, disorientation, speech and language problems, personality changes, motility problems, hallucinations and delusions. It is challenging to diagnose Alzheimer’s early in its development due to a slow progression of symptoms and a frequent association of some symptoms, like memory problems, purely with old age. Moreover, as a consequence of the disease, people might not be able to detect changes in their memory. A timely diagnosis of Alzheimer’s disease would allow to start controlling some behavioural symptoms early.

This disease has been studied for decades, yet no efficient treatment that can terminate or slow it down has been discovered. For that reason, scientists have been focusing on diagnosing and treating Alzheimer’s before dementia symptoms appear. When it comes to Alzheimer’s brain pathology, there are generally two diagnostic characteristics; amyloid beta protein forming amyloid plaques, which are large structures of aggregating peptides in the brain. Another feature is the presence of neurofibrillary tangles which occur when tau protein excessively accumulates in neurons. Under normal circumstances, tau protein is important for stabilising the microtubules in cells and allows cellular flexibility, but when hyperactivated, it can aggregate to form these tangles. The diagnosis of Alzheimer’s typically involves analysing brain images and measuring blood or cerebrospinal fluid to check for levels of these characteristic proteins (amyloid beta and tau). These biologically relevant molecules have been broadly associated with the risk for Alzheimer’s, yet little is known about how changes to the blood plasma proteome in the years before developing dementia occur.

“The disease has been studied for decades, yet no efficient treatment that can terminate or slow it down has been discovered. For that reason, scientists have been focusing on diagnosing and treating Alzheimer’s before dementia symptoms appear.”

Recently, researchers from Johns Hopkins University Bloomberg School of Public Health have identified a number of plasma proteins that can accumulate to abnormal levels in the blood up to five years before the first Alzheimer’s disease-related symptoms occur. 

This comprehensive analysis first involved blood samples obtained in 2011 to 2013 from more than 4,800 late-middle-aged participants in a large epidemiological study of heart disease-related risk factors and outcomes referred to as the Atherosclerosis Risk in Communities (ARIC) study. SomaScan, an aptamer-based proteomics assay recently developed, was used to relate abnormal plasma levels of 4,877 proteins with the risk for incident dementia in, at that time, non-demented older individuals. Aptamers are single-stranded DNA, RNA, or synthetic XNA molecules of high affinity for specific targets, more specifically, proteins of interest. This research showed that aberrant levels of 38 proteins are correlated with higher risks of developing Alzheimer’s disease within the following five years. 

Next, the researchers utilised SomaScan to analyse more than 11,000 samples taken from younger ARIC participants, using data collected from 1993 to 1995. This examination revealed that 16 of the total 38 proteins act as indicators of Alzheimer’s, 20 years preceding its onset, as supported by a follow-up clinical evaluation from 2011 to 2013.

Then, the results of SomaScan blood samples received from 2002 to 2006 during an Icelandic study were used to back up the aforementioned SomaScan findings in a different patient scenario. This analysis involved assays of 13 of the 16 proteins from the ARIC molecular study. 6 out of those 13 proteins were determined to appear within 10 years before experiencing the very first Alzheimer’s symptoms. 

“A timely diagnosis of Alzheimer’s disease would allow to start controlling some behavioural symptoms early.”

Most of the 16 proteins are likely to be byproducts of the slowly progressing disease or the preliminary process leading to the disease. However, out of these risk markers, a particular protein called SVEP1 was identified as a likely causal agent of Alzheimer’s. This conclusion was based on two-sample Mendelian randomisation, an analytical technique revealing causal effects of modifiable gene expression on disease outcome by relying on statistical data from genome-wide association studies. SVEP1 is a cellular adhesion protein with an immunological function. High plasma levels of SVEP1 were correlated with atrophy in regions of the brain associated with  Alzheimer’s pathology. Some other proteins from the list include key immune proteins that are associated with extreme immune activity in the brain, in patients with Alzheimer’s disease. SomaScan proved to be well-suited for analysing proteins in blood bank specimens that are suspected to be a part of Alzheimer’s-triggering pathways. 

Overall, the current analysis confirmed that there are specific widespread proteomic changes that can be identified many years prior to the onset of Alzheimer’s disease. This has provided a new platform for research, aiming to understand and develop potential targeted therapies for dementia. 

Written by Milena Flankova and edited by Diana Jorge.

Milena Flankova is a 3rd year BSc Biological sciences student, you can find her on LinkedIn @Milena Flankova

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