Does Parkinson’s disease have different subtypes?
- A
machine-learning study at Weill Cornell Medicine was able to classify
Parkinson’s disease into three subgroups, a development with the potential
to effectively target patients with treatments specific to their disease’s
progression.
- By
analyzing data from an existing study, researchers split the cohort into
Rapid Pace, Inching Pace, and Moderate Pace — an approach that
acknowledges the heterogeneous nature of the disease.
- Experts say the findings are logical and hold great promise, but caution that larger populations need to be explored to create more accurate models.
On the heels of new research from Boston University showing
that an artificial intelligence model was able to predict a person’s chances of
developing Alzheimer’s disease, Weill Cornell Medicine
researchers have been able to classify Parkinson’s
disease into three subtypes using machine learning.
The findings — which appear
in
What are the
3 subtypes of Parkinson’s?
Researchers at Cornell analyzed data from 406 people
who participated in the Parkinson’s Progression Markers
Initiative (PPMI), which is an international observational study
that “systematically collected clinical, biospecimen, multi-omics, and brain
imaging data of participants.”
They developed a
deep-learning model called deep phenotypic progression embedding (DPPE), which
was able to “holistically” model “multidimensional, longitudinal progression
data of the participants,” as the authors explain in the study paper.
The authors further note
that in recent years there has been a move toward observing Parkinson’s as a
condition with heterogeneous symptoms and progression.
Not all individuals with Parkinson’s will have the
same experience, in other words, and therefore treatment could be much more
tailored to suit different patients’ needs.
The three subgroups of
Parkinson’s identified by the machine learning are based on the pace of the
disease’s progression:
- Rapid Pace
(PD-R), which is marked by rapid progression of symptoms. Of the cohort
observed, 54 people (13.3%) had this subtype.
- Inching
Pace (PD-I), which has mild baseline symptoms and relatively mild
progression. Of the cohort observed, 145 people (35.7%) had this variety.
- Moderate Pace (PD-M), which is characterized by mild baseline symptoms and moderate progression. This was the largest portion of the cohort observed, with 207 people (50.9%) living with this form of Parkinson’s.
The study authors note that their classifications
“highlighted the necessity of treating [Parkinson’s disease] subtypes as unique
sub-disorders within clinical practice, where our pace subtypes could inform
patient stratification and management.”
By identifying specific
varieties of the disease, clinical approaches could be much more targeted and
effective.
Findings on
Parkinson’s subtypes need confirming
Clemens
Scherzer, MD, a physician-scientist and the Stephen & Denise
Adams Professor of Neurology at Yale School of Medicine, who was not involved
in the study, told Medical News Today that the study’s
computational findings were very interesting, but cautioned that they are
extremely preliminary and need larger populations to develop and validate such
classifiers.
“The goal of precision
medicine is to predict the disease course in a patient and to therapeutically
intervene ahead of time to prevent complications from developing. To achieve
this we need to identify the disease driver in each patient and develop targeted
therapeutics,” Scherzer pointed out.
“For example, we have found
that 10% of Parkinson’s patients in the [United States] have
Nevertheless, Daniel Truong, MD, a neurologist and medical
director of the Truong Neuroscience Institute at MemorialCare Orange Coast
Medical Center in Fountain Valley, CA, and editor in chief of the Journal of
Clinical Parkinsonism and Related Disorders, who also was not involved in the
study, told MNT that
the subgroupings are a logical, systematic approach to treating Parkinson’s.
“For instance, patients with the Rapid Pace subtype
(PD-R) might benefit from more aggressive therapeutic strategies and closer
monitoring compared to those with the Inching Pace subtype (PD-I), who may need
less intensive management. Knowledge of a patient’s subtype can guide the
selection of medications, including the potential repurposing of existing drugs
like metformin, which the study suggests might be
particularly beneficial for the PD-R subtype.”– Daniel Truong, MD
“It allows predictive and preventive healthcare to be
designed for each subtype,” Truong explained.
“Early intervention may be
required for rapid progressive patients. This is crucial for managing symptoms
before they become severe and debilitating. Subtyping helps in stratifying
patients based on their risk, enabling more focused and effective clinical
trials for new treatments, as well as better allocation of healthcare
resources,” he added.
Steven Allder, BMedSci, BMBS, FRCP,
DM, a consultant neurologist at Re:Cognition Health, not involved in
the study, agreed that advance identification of different subgroups would
allow medical professionals to work on specific treatment plans for each one.
He listed the possible
treatments for each, noting:
- Inching
Pace (PD-I): “Treatments could focus on maintaining quality of life and
preventing symptom progression through lifestyle modifications, physical
therapy, and possibly neuroprotective drugs.”
- Moderate
Pace (PD-M): “These patients exhibit moderate disease advancement. They
might benefit from a combination of pharmacological treatments to manage
symptoms and slow progression, such as dopamine agonists, MAO-B inhibitors
or other disease-modifying therapies.”
- Rapid Pace (PD-R): “This subtype progresses quickly and often involves cognitive deficits. Metformin has shown promise in improving symptoms in this group, especially related to cognition and falls. Early intervention with Metformin and other neuroprotective agents could be crucial for managing this subtype.”
Is it problematic to use AI to predict Parkinson’s?
Allder’s main concern about using machine-learning
technology to predict diseases such as Parkinson’s revolved around the
accessibility of such a tool for people who need it.
“I don’t foresee problems
with the AI model, but I do foresee problems with patients accessing it,“ he
told us.
“While AI models are powerful tools for identifying
disease subtypes and predicting progression, there are potential issues related
to patient access. Not all patients may have access to advanced diagnostic
tools or treatments derived from AI research, especially in under-resourced
settings,“ Allder pointed out.
However, according to him,
another issue might be “[t]he use of extensive patient data for AI model training,“
which “raises concerns about data privacy and security.“
“AI models need to be
validated across diverse populations to ensure they are not biased towards
specific cohorts,” said Allder.
Scherzer, echoing his
earlier statement, said that the significant power of artificial intelligence
toward precise medical treatments will ultimately depend on more research and
trials.
“The success of AI to
predict outcomes depends on the size and quality of the input data,” he noted.
“A key gap in the field is that we need much larger, high quality, longitudinal
data sets of Parkinson’s patients — data on large populations spanning
prodromal stages and the entire disease course. These will be essential for
training and validating AI models useful for augmented medicine.”
https://www.medicalnewstoday.com/articles/parkinsons-disease-could-have-3-subtypes-researchers-find
No comments:
Post a Comment