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Summary Background Parkinson's disease is heterogeneous in symptom presentation and progression. Increased understanding of both aspects can enable better patient management and improve clinical trial design. Previous approaches to modelling Parkinson's disease progression assumed static progression trajectories within subgroups and have not adequately accounted for complex medication effects. Our objective was to develop a statistical progression model of Parkinson's disease that accounts for intra-individual and inter-individual variability and medication effects. Methods In this longitudinal data study, data were collected for up to 7-years on 423 patients with early Parkinson's disease and 196 healthy controls from the Parkinson's Progression Markers Initiative (PPMI) longitudinal observational study. A contrastive latent variable model was applied followed by a novel personalised input-output hidden Markov model to define disease states. Clinical significance of the states was assessed using statistical tests on seven key motor or cognitive outcomes (mild cognitive impairment, dementia, dyskinesia, presence of motor fluctuations, functional impairment from motor fluctuations, Hoehn and Yahr score, and death) not used in the learning phase. The results were validated in an independent sample of 610 patients with Parkinson's disease from the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP). Findings PPMI data were download July 25, 2018, medication information was downloaded on Sept 24, 2018, and PDBP data were downloaded between June 15 and June 24, 2020. The model discovered eight disease states, which are primarily differentiated by functional impairment, tremor, bradykinesia, and neuropsychiatric measures. State 8, the terminal state, had the highest prevalence of key clinical outcomes including 18 (95%) of 19 recorded instances of dementia. At study outset 4 (1%) of 333 patients were in state 8 and 138 (41%) of 333 patients reached stage 8 by year 5. However, the ranking of the starting state did not match the ranking of reaching state 8 within 5 years. Overall, patients starting in state 5 had the shortest time to terminal state (median 2·75 [95% CI 1·75–4·25] years). Interpretation We developed a statistical progression model of early Parkinson's disease that accounts for intra-individual and inter-individual variability and medication effects. Our predictive model discovered non-sequential, overlapping disease progression trajectories, supporting the use of non-deterministic disease progression models, and suggesting static subtype assignment might be ineffective at capturing the full spectrum of Parkinson's disease progression. Funding Michael J Fox Foundation.

Changes in the blood-based RNA transcriptome have the potential to inform biomarkers of Parkinson’s disease (PD) progression. Here we sequenced a discovery set of whole-blood RNA species in 4,871 longitudinally collected samples from 1,570 clinically phenotyped individuals from the Parkinson’s Progression Marker Initiative (PPMI) cohort. Samples were sequenced to an average of 100 million read pairs to create a high-quality transcriptome. Participants with PD in the PPMI had significantly altered RNA expression (>2,000 differentially expressed genes), including an early and persistent increase in neutrophil gene expression, with a concomitant decrease in lymphocyte cell counts. This was validated in a cohort from the Parkinson’s Disease Biomarkers Program (PDBP) consisting of 1,599 participants and by alterations in immune cell subtypes. This publicly available transcriptomic dataset, coupled with available detailed clinical data, provides new insights into PD biological processes impacting whole blood and new paths for developing diagnostic and prognostic PD biomarkers. The authors report whole-blood RNA-seq for 4,871 samples from 1,570 participants in the Parkinson Progression Marker Initiative. This Resource documents blood-based transcriptomic changes associated with PD, including early increases in neutrophil gene expression with a decrease in lymphocytes.

Author(s): Mollenhauer, Brit; Dakna, Mohammed; Kruse, Niels; Galasko, Douglas; Foroud, Tatiana; Zetterberg, Henrik; Schade, Sebastian; Gera, Roland G; Wang, Wenting; Gao, Feng; Frasier, Mark; Chahine, Lana M; Coffey, Christopher S; Singleton, Andrew B; Simuni, Tanya; Weintraub, Daniel; Seibyl, John; Toga, Arthur W; Tanner, Caroline M; Kieburtz, Karl; Marek, Kenneth; Siderowf, Andrew; Cedarbaum, Jesse M; Hutten, Samantha J; Trenkwalder, Claudia; Graham, Danielle | Abstract: BackgroundThe objective of this study was to assess neurofilament light chain as a Parkinson's disease biomarker.MethodsWe quantified neurofilament light chain in 2 independent cohorts: (1) longitudinal cerebrospinal fluid samples from the longitudinal de novo Parkinson's disease cohort and (2) a large longitudinal cohort with serum samples from Parkinson's disease, other cognate/neurodegenerative disorders, healthy controls, prodromal conditions, and mutation carriers.ResultsIn the Parkinson's Progression Marker Initiative cohort, mean baseline serum neurofilament light chain was higher in Parkinson's disease patients (13 ± 7.2 pg/mL) than in controls (12 ± 6.7 pg/mL), P = 0.0336. Serum neurofilament light chain increased longitudinally in Parkinson's disease patients versus controls (P l 0.01). Motor scores were positively associated with neurofilament light chain, whereas some cognitive scores showed a negative association.ConclusionsNeurofilament light chain in serum samples is increased in Parkinson's disease patients versus healthy controls, increases over time and with age, and correlates with clinical measures of Parkinson's disease severity. Although the specificity of neurofilament light chain for Parkinson's disease is low, it is the first blood-based biomarker candidate that could support disease stratification of Parkinson's disease versus other cognate/neurodegenerative disorders, track clinical progression, and possibly assess responsiveness to neuroprotective treatments. However, use of neurofilament light chain as a biomarker of response to neuroprotective interventions remains to be assessed. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Author(s): Simuni, Tanya; Siderowf, Andrew; Lasch, Shirley; Coffey, Chris S; Caspell-Garcia, Chelsea; Jennings, Danna; Tanner, Caroline M; Trojanowski, John Q; Shaw, Leslie M; Seibyl, John; Schuff, Norbert; Singleton, Andrew; Kieburtz, Karl; Toga, Arthur W; Mollenhauer, Brit; Galasko, Doug; Chahine, Lana M; Weintraub, Daniel; Foroud, Tatiana; Tosun, Duygu; Poston, Kathleen; Arnedo, Vanessa; Frasier, Mark; Sherer, Todd; Chowdhury, Sohini; Marek, Kenneth; Parkinson's Progression Marker Initiative* | Abstract: OBJECTIVE:The objective of this study was to assess longitudinal change in clinical and dopamine transporter imaging outcomes in early, untreated PD. METHODS:We describe 5-year longitudinal change of the MDS-UPDRS and other clinical measures using results from the Parkinson's Progression Markers Initiative, a longitudinal cohort study of early Parkinson's disease (PD) participants untreated at baseline. We also provide data on the longitudinal change in dopamine transporter 123-I Ioflupane striatal binding and correlation between the 2 measures. RESULTS:A total of 423 PD participants were recruited, and 358 remain in the study at year 5. Baseline MDS-UPDRS total score was 32.4 (standard deviation 13.1), and the average annual change (assessed medications OFF for the treated participants) was 7.45 (11.6), 3.11 (11.7), 4(11.9), 4.7 (11.1), and 1.74(11.9) for years 1, 2, 3, 4, and 5, respectively (P l .0001 for the change over time), with a steeper change in year 1. Dopaminergic therapy had a significant effect on the change of MDS-UPDRS. There was a significant longitudinal change in dopamine transporter binding in all striatal regions (P l .001). There was a significant but weak correlation between MDS-UPDRS and dopamine transporter binding at baseline and years 1, 2, and 4, but no correlation between the rate of change of the 2 variables. CONCLUSIONS:We present 5-year longitudinal data on the change of the MDS-UPDRS and other clinical and dopamine transporter imaging outcome measures in early PD. These data can be used for sample size estimates for interventional studies in the de novo PD population. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Parkinson's disease biomarkers are needed to increase diagnostic accuracy, to objectively monitor disease progression and to assess therapeutic efficacy as well as target engagement when evaluating novel drug and therapeutic strategies. This article summarizes perianalytical considerations for biomarker studies (based on immunoassays) in Parkinson's disease, with emphasis on quantifying total α-synuclein protein in biological fluids. Current knowledge and pitfalls are discussed, and selected perianalytical variables are presented systematically, including different temperature of sample collection and types of collection tubes, gradient sampling, the addition of detergent, aliquot volume, the freezing time, and the different thawing methods. We also discuss analytical confounders. We identify gaps in the knowledge and delineate specific areas that require further investigation, such as the need to identify posttranslational modifications of α-synuclein and antibody-independent reference methods for quantification, as well as the analysis of potential confounders, such as comorbidities, medication, and phenotypes of Parkinson's disease in larger cohorts. This review could be used as a guideline for future Parkinson's disease biomarker studies and will require regular updating as more information arises in this growing field, including new technical developments as they become available. In addition to reviewing best practices, we also identify the current technical limitations and gaps in the knowledge that should be addressed to enable accurate and quantitative assessment of α-synuclein levels in the clinical setting. © 2017 International Parkinson and Movement Disorder Society.

ObjectiveTo assess neurofilament light chain (NfL), as a biomarker for Parkinson’s disease (PD).MethodsWe quantified NfL in (1) longitudinal CSF samples from PD, other cognate/neurodegenerative disorders (OND), and healthy controls (HC); (2) a cross-sectional cohort with paired CSF and serum samples from participants with PD, OND, and HC, and (3) a large longitudinal validation cohort with serum samples from PD, OND, HC, prodromal conditions, and mutation carriers.ResultsIn the longitudinal discovery cohort (1) NfL in CSF was highest in OND and higher in PD vs. HC across all visits (p; pConclusionsNfL levels in serum samples are increased in PD vs. HC, increase significantly over time, and correlate with clinical measures of PD severity. Although the specificity of NfL in PD is low and more specific biomarkers are needed, serum NfL is the first blood-based biomarker candidate that could support disease stratification (PD vs. OND), track clinical progression, and possibly assess responsiveness to neuroprotective treatments. NfL as a biomarker of response to neuroprotective interventions remains to be determined.Funding sources for studyPPMI is sponsored by the Michael J. Fox Foundation for Parkinson’s Research (MJFF) and is co-funded by MJFF, Abbvie, Avid Radiopharmaceuticals, Biogen Idec, Bristol-Myers Squibb, Covance, Eli Lilly & Co., F. Hoffman-La Roche, Ltd., GE Healthcare, Genentech, GlaxoSmithKline, Lundbeck, Merck, MesoScale, Piramal, Pfizer and UCB. The funders had no role in the design and conduct of the study, in the collection, management, analysis, and interpretation of the data, in the preparation, review, or approval of the manuscript or in the decision to submit the manuscript for publication.Financial Disclosure/Conflict of Interest concerning the research related to the manuscriptBrit Mollenhauer, Douglas Galasko, Tatiana Foroud, Lana M. Chahine, Christopher S. Coffey, Andrew B. Singleton, Tanya Simuni, Daniel Weintraub, John Seibyl, Arthur W. Toga, and Caroline M. Tanner received funding from The Michael J. Fox Foundation for Parkinson’s Research.Mohammed Dakna, Tzu-Ying Liu, Henrik Zetterberg, Sebastian Schade, Roland G. Gera, Wenting Wang, Feng Gao, Niels Kruse, Mark Frasier, Jesse M. Cedarbaum, Samantha J. Hutten, Claudia Trenkwalder, and Danielle Graham report no disclosures.

Objective:To analyze longitudinal levels of CSF biomarkers in drug-naive patients with Parkinson disease (PD) and healthy controls (HC), examine the extent to which these biomarker changes relate to clinical measures of PD, and identify what may influence them.Methods:CSF α-synuclein (α-syn), total and phosphorylated tau (t- and p-tau), and β-amyloid 1–42 (Aβ42) were measured at baseline and 6 and 12 months in 173 patients with PD and 112 matched HC in the international multicenter Parkinson's Progression Marker Initiative. Baseline clinical and demographic variables, PD medications, neuroimaging, and genetic variables were evaluated as potential predictors of CSF biomarker changes.Results:CSF biomarkers were stable over 6 and 12 months, and there was a small but significant increase in CSF Aβ42 in both patients with patients with PD and HC from baseline to 12 months. The t-tau remained stable. The p-tau increased marginally more in patients with PD than in HC. α-syn remained relatively stable in patients with PD and HC. Ratios of p-tau/t-tau increased, while t-tau/Aβ42 decreased over 12 months in patients with PD. CSF biomarker changes did not correlate with changes in Movement Disorder Society–sponsored revision of the Unified Parkinson’s Disease Rating Scale motor scores or dopamine imaging. CSF α-syn levels at 12 months were lower in patients with PD treated with dopamine replacement therapy, especially dopamine agonists.Conclusions:These core CSF biomarkers remained stable over 6 and 12 months in patients with early PD and HC. PD medication use may influence CSF α-syn. Novel biomarkers are needed to better profile progressive neurodegeneration in PD.

Background 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. Methods BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross‐sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. Results We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. Conclusion Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society

Background Efforts to identify fluid biomarkers of Parkinson’s disease (PD) have intensified in the last decade. As the role of inflammation in PD pathophysiology becomes increasingly recognized, investigators aim to define inflammatory signatures to help elucidate underlying mechanisms of disease pathogenesis and aid in identification of patients with inflammatory endophenotypes that could benefit from immunomodulatory interventions. However, discordant results in the literature and a lack of information regarding the stability of inflammatory factors over a 24-h period have hampered progress. Methods Here, we measured inflammatory proteins in serum and CSF of a small cohort of PD (n = 12) and age-matched healthy control (HC) subjects (n = 6) at 11 time points across 24 h to (1) identify potential diurnal variation, (2) reveal differences in PD vs HC, and (3) to correlate with CSF levels of amyloid β (Aβ) and α-synuclein in an effort to generate data-driven hypotheses regarding candidate biomarkers of PD. Results Despite significant variability in other factors, a repeated measures two-way analysis of variance by time and disease state for each analyte revealed that serum IFNγ, TNF, and neutrophil gelatinase-associated lipocalin (NGAL) were stable across 24 h and different between HC and PD. Regression analysis revealed that C-reactive protein (CRP) was the only factor with a strong linear relationship between CSF and serum. PD and HC subjects showed significantly different relationships between CSF Aβ proteins and α-synuclein and specific inflammatory factors, and CSF IFNγ and serum IL-8 positively correlated with clinical measures of PD. Finally, linear discriminant analysis revealed that serum TNF and CSF α-synuclein discriminated between PD and HC with a minimum of 82% sensitivity and 83% specificity. Conclusions Our findings identify a panel of inflammatory factors in serum and CSF that can be reliably measured, distinguish between PD and HC, and monitor inflammation as disease progresses or in response to interventional therapies. This panel may aid in generating hypotheses and feasible experimental designs towards identifying biomarkers of neurodegenerative disease by focusing on analytes that remain stable regardless of time of sample collection.

Therapeutic development in Parkinson’s 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 Parkinson’s 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 Foundation’s 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 Parkinson’s disease biomarkers.

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-naive 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 e4 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.

Parkinson's disease (PD) is the most common neurodegenerative movement disorder and is characterized by the loss of dopaminergic neurons in the substantia nigra compacta. alpha-Synuclein is strongly implicated in the pathophysiology of PD because aggregated alpha-synuclein accumulates in the brains of subjects with PD, mutations in alpha-synuclein cause familial PD, and overexpressing mutant human alpha-synuclein (A30P or A53T) causes degenerative disease in mice or drosophila. The pathophysiology of PD is poorly understood, but increasing evidence implicates mitochondrial dysfunction and oxidative stress. To understand how mutations in alpha-synuclein contribute to the pathophysiology of PD, we undertook a proteomic analysis of transgenic mice overexpressing A30P alpha-synuclein to investigate which proteins are oxidized. We observed more than twofold selective increases in specific carbonyl levels of three metabolic proteins in brains of symptomatic A30P alpha-synuclein mice: carbonic anhydrase 2 (Car2), alpha-enolase (Eno1), and lactate dehydrogenase 2 (Ldh2). Analysis of the activities of these proteins demonstrates decreased functions of these oxidatively modified proteins in brains from the A30P compared to control mice. Our findings suggest that proteins associated with impaired energy metabolism and mitochondria are particularly prone to oxidative stress associated with A30P-mutant alpha-synuclein.

Parkinson's disease (PD) is currently diagnosed using clinical features. While experienced neurologists can typically diagnose PD with 70–90% accuracy, there are many situations early in the course of the disease when clinical diagnosis is less precise. There is a paucity of objective measures that could be employed to improve the diagnosis, stratify patients by subtypes, and track underlying disease progression. Development of innovative new therapies that slow or stop the progression of the disease would be accelerated by such objective biomarkers. Various imaging modalities including specific dopaminergic markers and morphometric measures are available, but have not been firmly established as markers for these purposes. Markers that can be detected in easily obtainable biofluids would be ideal for these purposes and would increase the power to detect the effect of therapeutic agents in a shorter time with reduced cost. Unbiased exploratory examination of panels of RNAs, both mRNA and noncoding RNAs, exosomes, proteins, antibodies, and metabolites in small individual cohorts have yielded promising candidate markers that yearn for replication in independent cohorts (Kroksveen et al., 2011). More targeted approaches to identify biomarkers based on PD pathophysiology have shown disease-related proteins as strong candidates. Alpha-synuclein is decreased in the cerebrospinal fluid of PD patients (Hong et al., 2010), although significant overlap with controls makes it less useful in assisting individual diagnosis. Other potential protein candidates include DJ-1 and inflammatory cytokines. Post-translationally modified forms of these proteins may improve the biomarker specificity. Most of these studies have utilized CSF (Parnetti et al., 2013), although increased oxidized DJ-1 in PD patients was detected in blood (Saito et al., 2009) and epidermal growth factor levels in plasma has been shown to predict cognitive decline in PD (Chen-Plotkin et al., 2011). Ultimately one could predict that a panel of multiple biochemical markers could be combined to increase the accuracy of diagnosis and disease progression. Heterogeneity of patient populations and lack of standardization of collection methods may contribute to the inconsistent and variable observations in the literature. A major need in the field is the availability of biospecimens from well-characterized cohorts for discovery of new biomarkers and validation. In response to these needs, three major programs have been launched. The Parkinson's Progression Marker Initiative (PPMI) is a prospective study of 400 newly diagnosed PD patients and 200 controls that will be followed over 5 years and collect extensive clinical (motor and non-motor information), imaging, and biosample (blood, cerebrospinal fluid, DNA/RNA from blood, urine) information from all 600 subjects at sites around the world (Marek, 2011). PPMI expanded to include a prodromal cohort of 100 individuals at risk for developing PD to develop biomarkers that are present prior to the onset of clinical motor symptoms. The Fox Investigation for New Discovery of Biomarkers (BioFIND) is a study supported in collaboration with National Institute of Neurological Diseases and Stroke (NINDS) focused on novel biomarker discovery by enrolling 120 rigorously defined clinically typical PD in mid-stage and 120 age- and gender-matched controls at one timepoint in US sites. BioFIND was launched to serve as a platform to test new biomarkers in somewhat narrow spectrum of clinically typical PD in moderate stages to maximize the chance of discovering differences in a less heterogeneous population. The Parkinson's Disease Biomarker Program (PDBP) is a program designed to support new and existing biomarker cohorts that collect biospecimens using standardized protocols. Biospecimens and data from all above studies are available to the research community. Through standardization and coordination of data and sample collection, we are optimistic that new markers will emerge which will assist in clinical trials and ultimately result in improved management of the disease.

The development of an α-synuclein imaging agent could be transformative for Parkinson's 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.

International audience; The loss of dopaminergic neurons in the substantia nigra pars compacta leads to the characteristic motor symptoms of Parkinson's 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 Parkinson's disease, better translation between preclinical animal models and clinical research, and improving the design of future clinical trials.

Recessively inherited loss-of-function mutations in the DJ-1 or PINK1 gene are linked to familial cases of early-onset Parkinson’s disease (PD). Single-knockout mice (lacking either DJ-1 or PINK1) exhibit disruptions of dopamine homeostasis but no nigral dopaminergic degeneration. As part of the strategy to provide more tools for the research community, the MJ. Fox Foundation for Parkinson’s Research (MJFF) has funded the generation of novel rat models lacking either DJ-1 or PINK1 genes and sponsored a standardized characterization including behavioral, neurochemical and pathological measures to determine if these rats exhibit progressive PD-like phenotype. In the presentation, we will discuss PINK1 KO rats motor dysfunction and gait impairment compared to wild-type rats (WT) up to 8-months of age. The DJ-1 KO rats expressed similar motor and gait abnormalities, however these deficits were less pronounced and appeared mostly between 6 and 8 months of age. Characterizations of alpha-synuclein immunoreactivity and other biomarkers levels in these rat models are currently ongoing. These preliminary data demonstrate that loss of either the PINK1 or the DJ-1 gene in rats produces a progressive loss of dopaminergic neurons, and that this neurodegeneration may be correlated to progressive motor and gait deficits. Thus, these MJFF-generated Pink1 and DJ-1 knockout rats will help elucidate the mechanisms by which these recessive genes produce PD pathology and aid in therapeutic development.