COPENHAGEN — A new clinical model, based on distinct features of patients with GBA-related Parkinson's disease in two different patient cohorts, could be used to predict GBA mutation carrier status and guide genetic testing in patients with the disease, results of a new study suggest.
This is a "simple and clinically useful model for prediction of GBA carrier status that helps to quantify those features that are most highly associated" with the gene, said study presenter Julia Greenberg, MD, a neurologist with NYU Langone Health, New York, New York.
"We hope that this model will help to guide genetic testing and patient counseling in the clinical setting, by selecting for patients with those features that are most highly associated with pathogenic variants," Greenberg said at the International Congress of Parkinson's Disease and Movement Disorders (MDS) 2023.
The GBA gene encodes for the lysosomal enzyme glucocerebrosidase (GCase), which maintains glycosphingolipid homeostasis, and it is estimated that approximately 5%-15% of patients with Parkinson's disease carry mutations.
Targeting a Specific Population for Genetic Testing
Greenberg told Medscape Medical News that GBA mutations are associated with a number of demographic and clinical features in Parkinson's disease, including younger age at onset, Ashkenazi Jewish ancestry, and more severe clinical features, such as autonomic dysfunction and cognitive decline.
Together, these features create a "unique phenotype" that could be a future target for novel treatments, she explained.
It is therefore important these patients are identified early, she said, but it can be challenging to distinguish GBA-related disease from idiopathic disease solely from a clinical perspective.
That said, "from a research standpoint, and also in nontertiary centers, genetic testing remains expensive and has limited availability," she added.
"From a healthcare resource standpoint, just like we shouldn't be performing an MRI on everybody to rule out cancer, I don't think we should be getting genetic testing for every single patient who has Parkinson's disease," she explained. "So, I think it's important to figure out how to target a specific population."
The team conducted an in-depth clinical assessment of 100 patients with Parkinson's disease from their center who had already undergone genetic testing, using a number of standardized rating scales for motor and nonmotor symptoms, and self-reported information for the same traits.
The clinical and self-reported ratings were then compared, and the clinical features that the researchers identified were used to generate a predictive model for the presence of GBA mutations that had been detected.
The model was initially tested in the original study cohort of 100 patients with Parkinson's disease, and then in a larger cohort of 420 participants from the Parkinson's Progression Markers Initiative (PPMI) whose GBA mutation carrier status was also already known.
The two cohorts were broadly comparable in terms of baseline characteristics, although the initial study cohort had a larger proportion of patients who were positive for GBA mutations, at 21% vs 13% for the PPMI dataset, and a greater proportion with Ashkenazi ancestry, at 36% vs 7%.
When the researchers tested the model on the initial study cohort, only Ashkenazi ancestry emerged as significantly associated with GBA status (P < .001), at an area under the receiver-operating characteristic curve (AUC) of 0.8969.
However, when the model was applied to the PPMI cohort, age of symptom onset (P < .01), cognitive impairment (P < .05), urinary symptoms (P < .05), and Ashkenazi ancestry (P < .05) were all significantly associated with GBA status, at an AUC of 0.7378.
Further analysis revealed that PPMI-derived model matched well to the original study cohort, at an AUC of 0.740.
This is important, Greenberg told attendees, "because PPMI represents one of the largest Parkinson's disease registries available, and so it makes the model a powerful tool for prediction of GBA carrier status in smaller and less well characterized cohorts."
On the other hand, the model derived from the study cohort did not apply to the PPMI data, at an AUC of 0.5671. This, Greenberg explained, "is likely due to the small sample size and intrinsic bias in that cohort."
A Step Toward a 'More Sensitive and Specific Tool'
Approached for comment, Michael S. Okun, MD, said there is "no question that a powerful tool which could predict GBA carrier status for Parkinson's disease could be useful to identify folks early and to open the door for an option to enroll in clinical trials."
However, an algorithm or tool like this will face steep challenges, "given the current increasing availability of genetic testing," Okun, director of the Norman Fixel Institute for Neurological Diseases at the University of Florida Health, Gainesville, Florida, told Medscape Medical News.
"One feature that was clearly learned from this study was that the idea that when a clinician encounters someone with Parkinson's disease and also Ashkenazi Jewish heritage, these folks would be more likely to test positive for a GBA mutation."
"Using information on Jewish heritage to inform the consideration for ordering genetic testing in Parkinson's disease is an important take-home from their data," he added.
"Though this prediction model will not likely have a huge immediate impact, it is likely that studies such as these will add to future attempts to hone a more sensitive and specific tool," Okun concluded. This "may one day impact Parkinson's clinical practice, as well as screening for clinical trials."
No funding was declared. No relevant financial relationships were declared.
International Congress of Parkinson's Disease and Movement Disorders (MDS) 2023. Abstract 1082. Presented August 30, 2023.
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Cite this: Clinical Model Could Guide GBA Gene Testing in Parkinson's - Medscape - Sep 05, 2023.