Novel Technology Found to Distinguish Between Parkinson Disease, Multiple System Atrophy
A novel protein misfolding cyclic amplification technology was able to distinguish between 2 progressive neurodegenerative diseases, Parkinson disease (PD) and multiple system atrophy, signaling potential improvements in diagnosis of PD.
A novel protein misfolding cyclic amplification (PMCA) technology was able to distinguish between 2 progressive neurodegenerative diseases,
The study was published in Nature. In a news release, developer of the PMCA technology and senior study author Claudio Soto, PhD, professor in the Department of Neurology at McGovern Medical School at The University of Texas Health Science Center at Houston,
This process can occur for years and even decades before signs of motor improvement can occur, complicating diagnosis distinction that is currently determined by waiting and seeing how the disease progresses.
“By the time people show progressed symptoms of MSA, a substantial amount of brain cells are already damaged or dead, and they can’t be brought back. It has been difficult to develop treatment for both diseases because of the high rates of misdiagnosis, so we needed to find a way to distinguish between the two at the onset of early symptoms,” said Soto.
Providing accurate medication in a timely manner is of utmost importance for both patients with MSA and PD, as complications can prove detrimental to a patient’s health. More than
Previously, Soto’s PMCA technology was shown to be reliable in detecting aSyn aggregates of patients with PD and healthy subjects with high sensitivity and specificity through cerebrospinal fluid (CSF) samples. He and fellow researchers took a small amount of the aSyn proteins from the CSF of patients with PD (n = 105) and combined it with normal proteins from healthy subjects (n = 79) to see if and how they converted the normal proteins.
This finding could prove vital for future generations at risk for
Soto sought to expand this model to develop a sensitive biochemical diagnosis for PD, utilizing CSF samples from patients with MSA (n = 43) and PD (n = 43). The research was funded in part by grants from
After characterizing the product of the aSyn-PMCA through various biochemical, biophysical, and biological methods, researchers found that the technology can discriminate CSF samples coming from patients diagnosed with PD or MSA with an overall sensitivity of 95.4%. “Our latest research shows that the aSyn aggregates of PD and MSA have different properties, so by amplifying the abnormal aggregates we can detect with high efficiency which disease the patient has,” said Soto.
Researchers found that the properties of aggregates amplified from CSF of each disease were similar to those obtained by amplification of aggregates from the brain, resulting in a potentially profound impact on understanding the mechanism of αSyn misfolding. “This has huge implications both for accurate diagnosis and clinical care of the patient, and the development of new specific treatments for both diseases,” said Soto.
As CSF extraction during spinal taps is known to be invasive and painful, researchers hope that in future research the PMCA technology can detect aSyn in blood or urine, as
Luis Oliveira, PhD, associate director of research programs at MJFF, lauded the findings, which can potentially establish a preventive mechanism for progression of PD. “Objective diagnosis of Parkinson’s and MSA—and differential diagnosis between the two—would be game-changing for the many patients and families searching for answers when issues arise and, potentially, would help develop, test, and prescribe early interventions to stop disease before symptoms begin,” said Oliveira.
Reference
Shahnawaz M, Mukherjee A, Pritzkow S, et al. Discriminating α-synuclein strains in Parkinson’s disease and multiple system atrophy [published online February 5, 2020]. Nature. doi: 10.1038/s41586-020-1984-7.
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