Insights from our three guest speakers:
Robert Martone, Associate Director, Neurology Biomarkers, Labcorp Biomarker Solution Center, Labcorp Drug Development
Hiba Kazmi, PhD, Biomarker Scientist, IXICO
Antoniya Todorova, MD, PhD, Medical Director, Labcorp Drug Development
On September 12, three leading biomarker specialists shared their insights on ongoing research in Parkinson’s disease (PD) biomarkers to enable earlier detection of neurodegeneration, monitor disease progression, elucidate disease mechanisms and identify potential therapeutic targets.
How can drug development sponsors best identify and incorporate the right Parkinson’s biomarkers into their clinical trials while recognizing the benefits and limitations of current and emerging biomarkers for Parkinson’s disease? Here are a few of the key takeaways gleaned from the specialists during the webinar.
1. Use the appropriate Parkinson’s disease biomarkers at the right time
“Selecting the right biomarker as an endpoint is critical,” said Antoniya Todorova, MD, PhD, Medical Director at Labcorp Drug Development. “Researchers must find a balance between preserving the scientific integrity of a study and the feasibility of achieving the study goals as they identify the most appropriate measures and biomarkers, combining focus on the disease and the product-targeted place of effect.”
Researchers should also “use different measures, including proven, well-known assessments, and exploratory biomarkers that are innovative and measure for the targeted symptoms,” Dr. Todorova continued.
“It’s critical to evaluate the risk/benefit ratio for adding in any extra measures, including frequency and time points. For example, dopamine-transporter single photon emission computed tomography (DaT-SPECT) screening can be used for confirmation that the right patient has been enrolled in the study, but not as an efficacy endpoint if it is not relevant to the therapeutic effect.”
She noted that it is also critical that researchers maximize the use of exploratory endpoints in the early phases of the clinical trial by identifying those that are most relevant to the product’s therapeutic effect and then using them in the next phases of the trial on a subset of patients only.
2. Is there more than one route of PD progression?
Researchers have made great strides in identifying early signs of the disease; in many cases, it’s evidenced by REM sleep behavior disorder, hyposmia or constipation. However, by the time a patient experiences motor symptoms, they have already undergone a substantial amount of nerve degeneration and the disease is at mid-stage.
Robert Martone, Associate Director, Neurology Biomarkers at Labcorp Biomarker Solution Center discussed the brain-first versus body-first progression models of PD, noting they are “essentially opposite patterns.” In the body-first model of Parkinson’s disease, the disease begins in the enteric nervous system and is propagated through the brain stem, basal ganglia, before progressing to the rest of the brain. Patients with body-first disease have more autonomic symptoms and the disease is more symmetrical. In contrast, in the brain-first model, which originates in the brain before progressing elsewhere, fewer autonomic symptoms are observed as the disease is often asymmetric and progresses more slowly along with slower cognitive decline.
Hiba Kazmi, PhD, Biomarker Scientist, IXICO, expanded on the topic, stating that “a combination of fluid and imaging biomarkers helped identify different subtypes of body-first and brain-first Parkinson’s.”
3. Several Parkinson’s biomarkers help with identification and progression of the disease
Martone discussed the current use of fluid biomarkers for identification and diagnosis of PD, such as the quantification of α-synuclein (αSyn) in cerebrospinal fluid (CSF) and plasma.
“There are different ways of approaching a diagnosis of Parkinson’s disease that include measurements of oligomeric forms of synuclein using methods such as real-time quaking-induced conversion (RTQuIC) or composite assays from CSF analytes,” said Martone.
In terms of PD genetics, several genes are associated with Mendelian inheritance of disease and these genetic associations suggest that these proteins are involved in the pathogenesis of the disease, which may be useful for future biomarkers.
Martone believes neurofilament light (NfL) is an exciting biomarker of neural injury. While it is not specific to PD but many other trauma and neurological diseases, NfL tertiles correlate with the risk of progression to MCI and dementia, both in plasma and in CSF.
Finally, changes in the microbiome of the gastrointestinal tract and related metabolites represent another emerging biomarker as a recent study showed that the gut organisms of PD patients presented quite differently from those in normal subjects.
4. Utilizing neuroimaging for patient selection and stratification
Imaging can be helpful throughout a Parkinson’s disease clinical trial. According to Hiba Kazmi, PhD, Biomarker Scientist at IXICO, imaging is helpful for diagnostic purposes at the start of the trial “for patient selection and stratification.” Imaging can also help distinguish between healthy control patients and those with PD, as well as to root out any abnormalities and can also support disease monitoring.
Various types of neuroimaging are now available, such as single photon emission computed tomography (SPECT), positron emission tomography (PET) and magnetic resonance imaging (MRI).
Dr. Kazmi explained the differences between PET versus SPECT imaging, noting, “SPECT is obviously more readily available, it’s less expensive than PET and there’s less of an issue with half-life. However, PET can provide better spatial resolution, shorter scan times and better quantitative capacity.”
Dr. Kazmi also noted that dopamine transporter (DAT) imaging using a highly DAT-selective radiopharmaceutical (called PE2I) can be more convenient for patients as this method offers “a shorter time between injection to scan and acquisition.”
5. Advanced MRI-detected Parkinson’s disease biomarkers can support research
In Parkinson’s disease patients, the interrelated mechanisms involving the accumulation and altered distribution of iron, dopamine and neuromelanin can trigger neurodegenerative processes.1
Dr. Kazmi pointed out that use of advanced MRI techniques support imaging the nigrosome 1 (N1) sign, providing a visual means to see changes in local iron content in the substantia nigra, as excessive iron content is thought to contribute to neuronal death.
Advanced MRI can also generate neuromelanin-sensitive images. Per Dr. Kazmi, “quite a few studies have shown high accuracy with reduced neuromelanin signals in the substantia nigra in those with Parkinson’s disease versus healthy controls.” Potentially, neuromelanin can be used as a diagnostic marker as well as a progressive marker to illustrate the progressive loss of these cells.
In yet another advanced MRI technique, free-water analysis can be applied to diffusion MRI data and can demonstrate neurodegeneration by assessing tissue structure as the increase in free water is observed in Parkinson’s disease subjects over time.
Multimodal imaging and non-imaging markers are also key to improving our understanding of Parkinson’s disease. They have the potential to play a huge role in clinical trials to measure progression, drug efficacy and could help identify the pathology of subtypes of PD.
Dr. Kazmi also noted the growing importance of the use of both dopaminergic and non-dopaminergic measures. By combining these modalities together, as well as using a multi-centered approach and collaborative research initiatives, researchers can improve their understanding and set the standardization for imaging in Parkinson’s disease.
Interested in learning more about biomarkers in Parkinson’s disease?
Watch the full presentation in the Labcorp Knowledge Library.
References
[i] Zucca FA, Segura-Aguilar J, Ferrari E, Muñoz P, Paris I, Sulzer D, Sarna T, Casella L, Zecca L. Interactions of iron, dopamine and neuromelanin pathways in brain aging and Parkinson’s disease. Prog Neurobiol. 2017 Aug;155:96-119.