More Reliable Alpha-synuclein Test Speeds Diagnosis

Marta Figueiredo, PhD avatar

by Marta Figueiredo, PhD |

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Researchers have developed a faster method of measuring the rate at which alpha-synuclein protein forms toxic clumps that reliably distinguishes people with Parkinson’s disease from those without the condition.

The findings support the use of this test — which cuts by more than half the time required to obtain final results — in Parkinson’s diagnosis.

The study, “A rapid α‐synuclein seed assay of Parkinson’s disease CSF panel shows high diagnostic accuracy,” was published in the journal Annals of Clinical and Translational Neurology.

Parkinson’s disease is characterized by the buildup of toxic alpha-synuclein protein aggregates (Lewy bodies) within brain cells, particularly dopamine-producing neurons, contributing to their degeneration and death. Dopamine is a chemical messenger (neurotransmitter) that allows for communication between nerve cells (neurons).

Given its role in the development and progression of Parkinson’s, alpha-synuclein is seen as a potential lead biomarker.

While quantifying all forms of alpha-synuclein in fluids and tissues cannot accurately distinguish between Parkinson’s patients and healthy people, measuring its seeding activity, or the rate at which the protein clumps together to form toxic aggregates, has shown high diagnostic utility.

Currently used alpha-synuclein seeding activity tests of cerebrospinal fluid (CSF, the fluid that bathes the brain and spinal cord) samples can discriminate Parkinson’s patients from healthy individuals with greater than 80% specificity (percentage of unaffected cases being correctly ruled out) and 85% sensitivity (percentage of Parkinson’s cases being correctly identified).

However, these methods typically require five to 13 days to provide final results. In a previous study, a team of researchers in the U.S. reported the development of an improved method whose reactions took only one to two days.

Now, the same team has tested its method against a panel of CSF samples from 108 people with moderate‐to‐advanced Parkinson’s and 85 age- and sex-matched healthy individuals (used as controls).

Patients had no significant history of dementia and controls had no history of neurological disorders and no first‐degree family members with Parkinson’s. Samples and clinical data were obtained from The Michael J. Fox Foundation’s BioFIND database.

Results showed that the test identified 97% of Parkinson’s patients as having the disease (sensitivity), and deemed 87% of controls as negative for the condition (specificity). Notably, the test’s performance was comparable to that previously reported for current methods when analyzing BioFIND samples (95.2–96.2% sensitivity and 82.3–89.9% specificity).

Interestingly, five of the 11 apparent false positives and two of the three false negatives also were previously indicated as such by current methods, suggesting either that “these cases were initially misdiagnosed or that the samples contained an unidentified component that influenced the outcome of all three tests,” the researchers wrote.

Future studies with a larger number of samples will help clarify this issue, they noted.

In addition, Parkinson’s patients who reported more symptoms of REM sleep behavior disorder — a condition in which people act out their dreams and often experienced by Parkinson’s patients — showed a faster rate of alpha-synuclein aggregation than those less likely to have the condition.

“Our study using the BioFIND CSF sample set reaffirms the already strong evidence of the high diagnostic sensitivity and accuracy of [alpha-synuclein] seeding assays for the diagnosis of Parkinson’s disease,” the researchers wrote.

Moreover, the test “significantly improved the time needed to complete the assay without sacrificing assay performance,” supporting its use over previous methods, they added.

The team also noted that further research focused on how the molecular processes that cause Parkinson’s disease relate to the test parameters are needed to determine whether it could be used to monitor Parkinson’s status and progression.