Mark Frasier

The Parkinson Progression Marker Initiative (PPMI)

The Parkinson Progression Marker Initiative (PPMI) is a comprehensive observational, international, multi-center study designed to identify PD progression biomarkers both to improve understanding of disease etiology and course and to provide crucial tools to enhance the likelihood of success of PD modifying therapeutic trials. The PPMI cohort will comprise 400 recently diagnosed PD and 200 healthy subjects followed longitudinally for clinical, imaging and biospecimen biomarker assessment using standardized data acquisition protocols at twenty-one clinical sites. All study data will be integrated in the PPMI study database and will be rapidly and publically available through the PPMI web site- www.ppmi-info.org. Biological samples including longitudinal collection of blood, cerebrospinal fluid (CSF) and urine will be available to scientists by application to an independent PPMI biospecimen review committee also through the PPMI web site. PPMI will rely on a partnership of government, PD foundations, industry and academics working cooperatively. This approach is crucial to enhance the potential for success of this ambitious strategy to develop PD progression biomarkers that will accelerate research in disease modifying therapeutics.

Priorities in Parkinson's disease research

The loss of dopaminergic neurons in the substantia nigra pars compacta leads to the characteristic motor symptoms of Parkinsons disease: bradykinesia, rigidity and resting tremors. Although these symptoms can be improved using currently available dopamine replacement strategies, there is still a need to improve current strategies of treating these symptoms, together with a need to alleviate non-motor symptoms of the disease. Moreover, treatments that provide neuroprotection and/or disease-modifying effects remain an urgent unmet clinical need. This Review describes the most promising biological targets and therapeutic agents that are currently being assessed to address these treatment goals. Progress will rely on understanding genetic mutations or susceptibility factors that lead to Parkinsons disease, better translation between preclinical animal models and clinical research, and improving the design of future clinical trials.>

Loss of Leucine-rich Repeat Kinase 2 (LRRK2) in Rats Leads to Progressive Abnormal Phenotypes in Peripheral Organs

The objective of this study was to evaluate the pathology time course of the LRRK2 knockout rat model of Parkinson’s disease at 1-, 2-, 4-, 8-, 12-, and 16-months of age. The evaluation consisted of histopathology and ultrastructure examination of selected organs, including the kidneys, lungs, spleen, heart, and liver, as well as hematology, serum, and urine analysis. The LRRK2 knockout rat, starting at 2-months of age, displayed abnormal kidney staining patterns and/or morphologic changes that were associated with higher serum phosphorous, creatinine, cholesterol, and sorbitol dehydrogenase, and lower serum sodium and chloride compared to the LRRK2 wild-type rat. Urinalysis indicated pronounced changes in LRRK2 knockout rats in urine specific gravity, total volume, urine potassium, creatinine, sodium, and chloride that started as early as 1- to 2-months of age. Electron microscopy of 16-month old LRRK2 knockout rats displayed an abnormal kidney, lung, and liver phenotype. In contrast, there were equivocal or no differences in the heart and spleen of LRRK2 wild-type and knockout rats. These findings partially replicate data from a recent study in 4-month old LRRK2 knockout rats [1] and expand the analysis to demonstrate that the renal and possibly lung and liver abnormalities progress with age. The characterization of LRRK2 knockout rats may prove to be extremely valuable in understanding potential safety liabilities of LRRK2 kinase inhibitor therapeutics for treating Parkinson’s disease.

Diagnosis of Parkinson's disease on the basis of clinical and genetic classification: a population-based modelling study

BACKGROUND Accurate diagnosis and early detection of complex diseases, such as Parkinsons disease, has the potential to be of great benefit for researchers and clinical practice. We aimed to create a non-invasive, accurate classification model for the diagnosis of Parkinsons disease, which could serve as a basis for future disease prediction studies in longitudinal cohorts. METHODS We developed a model for disease classification using data from the Parkinsons Progression Marker Initiative (PPMI) study for 367 patients with Parkinsons disease and phenotypically typical imaging data and 165 controls without neurological disease. Olfactory function, genetic risk, family history of Parkinsons disease, age, and gender were algorithmically selected by stepwise logistic regression as significant contributors to our classifying model. We then tested the model with data from 825 patients with Parkinsons disease and 261 controls from five independent cohorts with varying recruitment strategies and designs: the Parkinsons Disease Biomarkers Program (PDBP), the Parkinsons Associated Risk Study (PARS), 23andMe, the Longitudinal and Biomarker Study in PD (LABS-PD), and the Morris K Udall Parkinsons Disease Research Center of Excellence cohort (Penn-Udall). Additionally, we used our model to investigate patients who had imaging scans without evidence of dopaminergic deficit (SWEDD). FINDINGS In the population from PPMI, our initial model correctly distinguished patients with Parkinsons disease from controls at an area under the curve (AUC) of 0·923 (95% CI 0·900-0·946) with high sensitivity (0·834, 95% CI 0·711-0·883) and specificity (0·903, 95% CI 0·824-0·946) at its optimum AUC threshold (0·655). All Hosmer-Lemeshow simulations suggested that when parsed into random subgroups, the subgroup data matched that of the overall cohort. External validation showed good classification of Parkinsons disease, with AUCs of 0·894 (95% CI 0·867-0·921) in the PDBP cohort, 0·998 (0·992-1·000) in PARS, 0·955 (no 95% CI available) in 23andMe, 0·929 (0·896-0·962) in LABS-PD, and 0·939 (0·891-0·986) in the Penn-Udall cohort. Four of 17 SWEDD participants who our model classified as having Parkinsons disease converted to Parkinsons disease within 1 year, whereas only one of 38 SWEDD participants who were not classified as having Parkinsons disease underwent conversion (test of proportions, p=0·003). INTERPRETATION Our model provides a potential new approach to distinguish participants with Parkinsons disease from controls. If the model can also identify individuals with prodromal or preclinical Parkinsons disease in prospective cohorts, it could facilitate identification of biomarkers and interventions. FUNDING National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J Fox Foundation.

Phenotypic characterization of recessive gene knockout rat models of Parkinson's disease

Recessively inherited loss-of-function mutations in the PTEN-induced putative kinase 1(Pink1), DJ-1 (Park7) and Parkin (Park2) genes are linked to familial cases of early-onset Parkinsons disease (PD). As part of its strategy to provide more tools for the research community, The Michael J. Fox Foundation for Parkinsons Research (MJFF) funded the generation of novel rat models with targeted disruption ofPink1, DJ-1 or Parkin genes and determined if the loss of these proteins would result in a progressive PD-like phenotype. Pathological, neurochemical and behavioral outcome measures were collected at 4, 6 and 8months of age in homozygous KO rats and compared to wild-type (WT) rats. Both Pink1 and DJ-1 KO rats showed progressive nigral neurodegeneration with about 50% dopaminergic cell loss observed at 8 months of age. ThePink1 KO and DJ-1 KO rats also showed a two to three fold increase in striatal dopamine and serotonin content at 8 months of age. Both Pink1 KO and DJ-1 KO rats exhibited significant motor deficits starting at 4months of age. However, Parkin KO rats displayed normal behaviors with no neurochemical or pathological changes. These results demonstrate that inactivation of the Pink1 or DJ-1 genes in the rat produces progressive neurodegeneration and early behavioral deficits, suggesting that these recessive genes may be essential for the survival of dopaminergic neurons in the substantia nigra (SN). These MJFF-generated novel rat models will assist the research community to elucidate the mechanisms by which these recessive genes produce PD pathology and potentially aid in therapeutic development.

CSF biomarkers associated with disease heterogeneity in early Parkinson’s disease: the Parkinson’s Progression Markers Initiative study

The development of biomarkers to predict the progression of Parkinson’s disease (PD) from its earliest stage through its heterogeneous course is critical for research and therapeutic development. The Parkinson’s Progression Markers Initiative (PPMI) study is an ongoing international multicenter, prospective study to validate biomarkers in drug-naïve PD patients and matched healthy controls (HC). We quantified cerebrospinal fluid (CSF) alpha-synuclein (α-syn), amyloid-beta1-42 (Aβ1-42), total tau (t-tau), and tau phosphorylated at Thr181 (p-tau) in 660 PPMI subjects at baseline, and correlated these data with measures of the clinical features of these subjects. We found that CSF α-syn, t-tau and p-tau levels, but not Aβ1-42, were significantly lower in PD compared with HC, while the diagnostic value of the individual CSF biomarkers for PD diagnosis was limited due to large overlap. The level of α-syn, but not other biomarkers, was significantly lower in PD patients with non-tremor-dominant phenotype compared with tremor-dominant phenotype. In addition, in PD patients the lowest Aβ1-42, or highest t-tau/Aβ1-42 and t-tau/α-syn quintile in PD patients were associated with more severe non-motor dysfunction compared with the highest or lowest quintiles, respectively. In a multivariate regression model, lower α-syn was significantly associated with worse cognitive test performance. APOE ε4 genotype was associated with lower levels of Aβ1-42, but neither with PD diagnosis nor cognition. Our data suggest that the measurement of CSF biomarkers in early-stage PD patients may relate to disease heterogeneity seen in PD. Longitudinal observations in PPMI subjects are needed to define their prognostic performance.

α-synuclein imaging: a critical need for Parkinson's disease research.

The development of an α-synuclein imaging agent could be transformative for Parkinsons disease research and drug development. The ability to image α-synuclein in the brain would enable tracking of the degree and location of pathology over time and monitoring of therapies aimed at reducing α-synuclein levels. The Michael J. Fox Foundation has assembled a consortium of researchers to develop an α-synuclein radiotracer for use in positron emission tomography (PET) imaging studies. While this poses a number of challenges they should not be insurmountable and lessons learned from the development of tau radiotracers should provide valuable insights.

A strategy for the generation, characterization and distribution of animal models by The Michael J. Fox Foundation for Parkinson's Research

Progress in Parkinson’s disease (PD) research and therapeutic development is hindered by many challenges, including a need for robust preclinical animal models. Limited availability of these tools is due to technical hurdles, patent issues, licensing restrictions and the high costs associated with generating and distributing these animal models. Furthermore, the lack of standardization of phenotypic characterization and use of varying methodologies has made it difficult to compare outcome measures across laboratories. In response, The Michael J. Fox Foundation for Parkinson’s Research (MJFF) is directly sponsoring the generation, characterization and distribution of preclinical rodent models, enabling increased access to these crucial tools in order to accelerate PD research. To date, MJFF has initiated and funded the generation of 30 different models, which include transgenic or knockout models of PD-relevant genes such as Park1 (also known as Park4 and SNCA), Park8 (LRRK2), Park7 (DJ-1), Park6 (PINK1), Park2 (Parkin), VPS35, EiF4G1 and GBA. The phenotypic characterization of these animals is performed in a uniform and streamlined manner at independent contract research organizations. Finally, MJFF created a central repository at The Jackson Laboratory (JAX) that houses both non-MJFF and MJFF-generated preclinical animal models. Funding from MJFF, which subsidizes the costs involved in transfer, rederivation and colony expansion, has directly resulted in over 2500 rodents being distributed to the PD community for research use.

Biomarkers in Parkinson's disease: a funder's perspective.

Therapeutic development in Parkinsons disease is hampered by the paucity of well-validated biomarkers that can assist with diagnosis and/or tracking the progression of the disease. Since its inception, the Michael J Fox Foundation for Parkinsons Research has invested heavily in biomarker research and continues to prioritize discovery and development efforts. This article summarizes the history and evolution of the Michael J Fox Foundations role in supporting biomarker research and lays out the current challenges in successfully developing markers that can be used to test therapies, while also providing a vision of future funding efforts in Parkinsons disease biomarkers.

The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort

Identifying PD‐specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well‐characterized, clinically typical, moderate to advanced PD cohorts is critically needed.