Abstract
α-Synuclein is a naturally unfolded protein which easily aggregates and forms toxic inclusions and deposits. It is associated with several neurodegenerative diseases, including Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). These diseases, called synucleinopathies, have overlapping symptoms but require different methods of treatment. There are no reliable approaches for early diagnoses of these diseases, and as a result, the treatment begins late, and the disorders are often misdiagnosed. Recent studies revealed that α-synuclein forms distinctive spatial structures or strains at the early steps of these diseases, which may be used for early diagnosis. One of these early diagnostic methods called PMCA (protein misfolding cyclic amplification) allows identification of the distinct α-synuclein strains specific for different human diseases. The method is successfully used for differential diagnosis of patients with PD and MSA.
Highlights
The number of diseases due to the amplification of misfolded protein aggregates is quickly growing
We briefly describe here ultrasensitive methods assessing the amplification of misfolded protein aggregates
Synucleinopathies are conformational diseases characterized by the excessive accumulation of fibrillary α-synuclein in neurons, nerve fibers or glial cells [7]. α-Synuclein possesses prion-like properties and can spread between cells [8]
Summary
The number of diseases due to the amplification of misfolded protein aggregates is quickly growing. Traditional methods used to assay protein amplification, such as immunohistochemistry, enzyme-linked immunosorbent assay, and western blotting, do not have high sensitivity. They require significant amounts of biological samples for reliable analysis. To overcome these drawbacks, more sensitive and robust amplification assays were developed. We briefly describe here ultrasensitive methods assessing the amplification of misfolded protein aggregates. We outline how efficiently they are for diagnosis of human neurodegenerative diseases
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