Mutations on NUS1 Gene Can Significantly Raise Person’s Risk of Parkinson’s, Study Reports

NUS1 mutations

Mutations affecting the NUS1 gene are linked to a significantly increased risk — 11 times higher — of developing Parkinson’s disease, study shows.

The study, “Coding mutations in NUS1 contribute to Parkinson’s disease,” was published in Proceedings of the National Academy of Sciences.

Although exact triggers of Parkinson’s disease remain unclear, aging, and environmental and genetic factors are believed to be major culprits.

SNCA was the first gene to be linked to the development of Parkinson’s. Since its discovery in 1997, scientists have attempted to find other genes that may also play a role.

Chinese researchers conducted a detailed genetic analysis of samples collected from 39 patients with early-onset Parkinson’s disease, their parents, and 20 unaffected siblings, aiming to detect de novo mutations associated with the disease.

A de novo mutation is a genetic alteration evident for the first time in one family member as a result of a mutation in the egg or sperm of a parent, or a mutation that arises in the fertilized egg itself during early development. A child with a de novo (new) mutation will develop the associated disease, while his parents or siblings will not.

Researchers identified 12 genes carrying de novo mutations — MAD1L1, NUP98, PPP2CB, PKMYT1, TRIM24, CEP131, CTTNBP2, NUS1, SMPD3, MGRN1, IFI35, and RUSC2. These genes are known to be expressed in two brain regions affected in Parkinson’s disease, called the stratum and substantia nigra, and could be functionally relevant to early-onset Parkinson’s.

Biologic network analysis showed that all the identified genes may share similar biological functions, and act together to increase the risk of developing Parkinson’s.

Patients did not have any other genetic variants previously associated with the disease.

Next, researchers explored the presence of rare mutations in these 12 genes in samples collected from 1,852 patients with sporadic (non-familial) Parkinson’s disease and 1,565 healthy volunteers. In this secondary screening, no significant alterations were found with exception of the NUS1 gene.

To confirm this finding, the team performed a detailed analysis of the NUS1 gene in a larger number of samples (3,237 patients and 2,858 controls). Similar to the previous analysis, Parkinson’s patients carried NUS1 mutations that were not present in the (healthy) control samples.

The presence of NUS1 variants, and consequent lower levels of the gene, were associated with a 11.3 times higher risk of having Parkinson’s disease.

Researchers also examined the role of the NUS1 gene in vivo, by deleting the equivalent gene — which shares 44% similarly with the human NUS1 — in a fly model (Drosophila). They observed that this deletion induced the loss of dopamine-producing nerve cells and, consequently, lower brain dopamine levels — two main hallmarks of Parkinson’s disease.

“These data … suggest that NUS1 plays important roles in dopamine neurons and that the loss of NUS1 could lead to neuronal dysfunction that is related to Parkinson’s disease,” the researchers wrote.

“[D]e novo mutations could contribute to early onset PD [Parkinson’s disease] pathogenesis and identify NUS1 as a candidate gene for PD,” they concluded.

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New Software May Help Detect Early Parkinson’s Motor Signs At Home

Parkinson's software

Researchers have validated a software that evaluates typing patterns with keyboards to detect Parkinson’s disease-specific motor impairment. This approach, done in an at-home setting, may allow early detection of the disease, as well as monitor disease progression.

The study, “Detecting Motor Impairment in Early Parkinson’s Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting,” was published in the Journal of Medical Internet Research.

Early detection of Parkinson’s disease can be crucial to prevent disease progression. The current standard to evaluate motor signs is the Unified Parkinson’s Disease Rating Scale part III (UPDRS-III), which requires a trained specialist and attendance at the clinic. This limits the frequency at which disease state and progression can be assessed.

Recently, efforts have been made to develop more accessible methods to detect motor signs of Parkinson’s, including the use of digital technologies. Analysis of the time a person takes between pressing and releasing a key while typing (key hold time) was found to be a reliable method to detect impaired psycho-motor function.

A recent study showed that analysis of key hold times could detect motor signs in the early stages of Parkinson’s in a controlled typing task in the clinic. The work involved a new computational algorithm able to generate a Parkinson’s disease motor index based on key hold times, called “neuroQWERTY index” (nQi).

This approach measures the key hold times during the normal use of a computer without any change in hardware and converts it to a neuroQWERTY index. This has the potential to detect motor problems remotely, in a natural environment (like home),  which would allow data to be collected much more often than current standard of care.

Researchers evaluated the use of the neuroQWERTY approach in an uncontrolled at-home setting. This study analyzed the baseline data collected from participants who had less than five years of disease and were about to initiate dopaminergic therapy, in a six-month Parkinson’s clinical trial (NCT02522065).

At the beginning of the trial, 60 participants (30 early-diagnosed Parkison’s patients and 30 healthy controls) underwent clinical evaluation, that included the UPDRS-III method and the neuroQWERTY typing test in clinic (which takes approximately 15 minutes).

Participants who reported using the computer for at least 30 minutes a day had the platform and software installed in their personal laptops. Data was collected for seven days after the first log-in to the neuroQWERTY platform, and participants were encouraged to type an email or a document for at least 15 minutes per day.

At the end, only 52 participants had enough data for the final analysis — 25 Parkinson’s patients and 27 healthy individuals. Researchers compared that data with the one collected during the typing task in the clinic.

The neuroQWERTY approach at home was able to distinguish Parkinson’s patients from healthy individuals through the analysis of at-home typing patterns, and had a comparable performance to that performed in the clinic.

“These results prove that the data collected from subjects’ routine use of the computer also are valid to detect PD-related motor signs, getting us closer to our ultimate goal of providing an objective ambulatory tool to monitor PD progression,” researchers wrote.

The team now wants to develop a tool that can track Parkinson’s progression and therapeutic effectiveness. However, additional studies must be performed to validate the neuroQWERTY approach to monitor Parkinson’s disease progression over time.

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Source: Parkinson's News Today

Measuring Caffeine Levels in Blood Might Help Diagnose Early Parkinson’s, Study Suggests

blood caffeine levels

Low levels of blood caffeine and its metabolites may help identify patients with early Parkinson’s disease, according to new research. The findings are consistent with caffeine’s neuroprotective effects, previously observed in neurodegenerative diseases.

The study, “Serum caffeine and metabolites are reliable biomarkers of early Parkinson disease,” was published in the journal Neurology. The work was conducted by researchers at the Juntendo University School of Medicine in Tokyo, Japan.

A large number of epidemiological studies report a dose-responsive, inverse relationship between coffee/caffeine consumption and the risk of developing Parkinson’s. However, little is known about caffeine metabolism in Parkinson’s patients.

With that in mind, the team recruited 108 Parkinson’s patients without memory problems plus 31 age-matched healthy people as controls, and investigated their blood caffeine (and 11 of its metabolites) levels and whether there were mutations in their caffeine-related genes.

Both groups consumed the same amount of caffeine (about two cups of coffee a day).

Results showed that even early-onset Parkinson’s patients had significantly lower levels of caffeine and nine of its metabolites in their blood, compared to the control group. This was found to be unrelated to total caffeine intake or the severity of the disease.

“If these results can be confirmed, they would point to an easy test for early diagnosis of Parkinson’s, possibly even before symptoms are appearing. This is important because Parkinson’s disease is difficult to diagnose, especially at the early stages,” David G. Munoz, MD, of the University of Toronto in Canada, who wrote an editorial accompanying the study, said in a news release.

A statistical analysis revealed that this simple blood test was able to reliably identify Parkinson’s patients.

“Likewise, caffeine concentrations in patients with [Parkinson’s disease] with motor complications were significantly decreased compared with those without motor complications,” the team wrote.

When looking at the caffeine-associated genes, researchers reported no differences between Parkinson’s patients and healthy subjects.

Despite the promising results, this is a relative small study which needs to be replicated at a larger scale.

As part of the study’s limitations, people with severe Parkinson’s were not included, making it difficult to detect a relationship between disease severity and blood caffeine levels. Also, all Parkinson’s patients were medicated for the disease, which could influence caffeine metabolism, and thus the study results.

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Source: Parkinson's News Today