Metabolism

Sporadic or idiopathic Parkinson's disease (PD) is an age-related neurodegenerative disorder of unknown origin that ranks only second behind Alzheimer's disease (AD) in prevalence and its consequent social and economic burden. PD neuropathology is characterized by a selective loss of dopaminergic neurons in the substantia nigra pars compacta; however, more widespread involvement of other CNS structures and peripheral tissues now is widely documented. The onset of molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD. The hallmark symptoms of PD, resting tremors, rigidity and postural disabilities, are related to dopamine (DA) deficiency. Current therapies treat these symptoms by replacing or boosting existing DA. All current interventions have limited therapeutic benefit for disease progression because damage likely has progressed over an estimated period of ~5 to 15years to a loss of 60%-80% of the nigral DA neurons, before symptoms emerge. There is no accepted definitive biomarker of PD. An urgent need exists to develop early diagnostic biomarkers for two reasons: (1) to intervene at the onset of disease and (2) to monitor the progress of therapeutic interventions that may slow or stop the course of the disease. In the context of disease development, one of the promises of personalized medicine is the ability to predict, on an individual basis, factors contributing to the susceptibility for the development of a given disease. Recent advances in our understanding of genetic factors underlying or contributing to PD offer the potential for monitoring susceptibility biomarkers that can be used to identify at-risk individuals and possibly prevent the onset of disease through treatment. Finally, the exposome concept is new in the biomarker discovery arena and it is suggested as a way to move forward in identifying biomarkers of neurological diseases. It is a two-stage scheme involving a first stage of exposome-wide association studies (EWAS) to profile omic features in serum to discover molecular biomarkers. The second stage involves application of this knowledge base in follow-up studies. This strategy is unique in that it promotes the use of data-driven (omic) strategies in interrogating diseased and healthy populations and encourages a movement away from using only reductionist strategies to discover biomarkers of exposure and disease. In this short review we will examine 1) advances in our understanding of the molecular mechanisms underlying PD that have led to candidate biomarkers for diagnosis and treatment efficacy and 2) new technologies on the horizon that will lead to novel approaches in biomarker development.CC999999/Intramural CDC HHS/United States2016-01-21T00:00:00Z25510818PMC47212537487vault:1461

2008 Progress Report on Brain Research

Highlights new research on various disorders, nervous system injuries, neuroethics, neuroimmunology, pain, sense and body function, stem cells and neurogenesis, and thought and memory. Includes essays on arts and cognition and on deep brain stimulation

How should we be using biomarkers in trials of disease modification in Parkinson’s disease?

The recent validation of the alpha synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson’s disease has formed the backbone for a proposed staging system for incorporation in Parkinson’s disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson’s disease patients into trials (as distinct from patients with non- Parkinson’s disease parkinsonism or non- Parkinson’s disease tremors). There remain however further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson’s disease, namely: optimising the distinction between different alpha synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; as sensitive means of confirming target engagement; and in the early prediction of longer-term clinical benefit. For example; levels of cerebrospinal fluid proteins such as the lysosomal enzyme ß-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer disease like pathology (detectable through cerebrospinal fluid levels of Amyloid Beta-42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline of Parkinson’s disease even in its later stages. The exploitation of additional biomarkers to the alpha synuclein seed amplification assay will therefore greatly add to our ability to plan trials and assess disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson’s disease. However, correlation with clinical progression does not necessarily equate to causation and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson’s disease

Multiple system atrophy - a clinicopathological update

Multiple system atrophy (MSA) is a fatal, adult-onset neurodegenerative disorder of uncertain etiology, clinically characterized by various combinations of Levo-dopa-unresponsive parkinsonism, and cerebellar, motor, and autonomic dysfunctions. MSA is an α-synucleinopathy with specific glioneuronal degeneration involving striatonigral, olivopontocerebellar, autonomic and peripheral nervous systems. The pathologic hallmark of this unique proteinopathy is the deposition of aberrant α-synuclein (αSyn) in both glia (mainly oligodendroglia) and neurons forming pathological inclusions that cause cell dysfunction and demise. The major variants are striatonigral degeneration (MSA with predominant parkinsonism / MSA-P) and olivopontocerebellar atrophy (MSA with prominent cerebellar ataxia / MSA-C). However, the clinical and pathological features of MSA are broader than previously considered. Studies in various mouse models and human patients have helped to better understand the molecular mechanisms that underlie the progression of the disease. The pathogenesis of MSA is characterized by propagation of disease-specific strains of αSyn from neurons to oligodendroglia and cell-to-cell spreading in a "prion-like" manner, oxidative stress, proteasomal and mitochondrial dysfunctions, myelin dysregulation, neuroinflammation, decreased neurotrophic factors, and energy failure. The combination of these mechanisms results in neurodegeneration with widespread demyelination and a multisystem involvement that is specific for MSA. Clinical diagnostic accuracy and differential diagnosis of MSA have improved by using combined biomarkers. Cognitive impairment, which has been a non-supporting feature of MSA, is not uncommon, while severe dementia is rare. Despite several pharmacological approaches in MSA models, no effective disease-modifying therapeutic strategies are currently available, although many clinical trials targeting disease modification, including immunotherapy and combined approaches, are under way. Multidisciplinary research to elucidate the genetic and molecular background of the noxious processes as the basis for development of an effective treatment of the hitherto incurable disorder are urgently needed

Biomarker and pathology studies in neurodegenerative cognitive impairment

Background: Dementia is a major cause of functional impairment and early death in older age groups. Neurodegenerative disorders are the most common cause of dementia. The most frequent neuropathological lesions include neurofibrillary tangles and senile plaques, hallmark lesions for Alzheimer´s disease (AD), and Lewy body pathology, which characterize Lewy body disease (LBD). Clinically, the neuropathological entity LBD can present as either Parkinson´s disease (PD) or dementia with Lewy bodies (DLB), differentiated on the basis of the presenting symptoms being either motor or cognitive. While the majority of LBD patients develop both motor symptoms and cognitive impairment, some patients with clinical PD will never experience cognitive impairment and likewise some patients with DLB will never develop motor symptoms. Similarly the clinical presentation of AD is also heterogeneous, for instance, the highly variable occurrence of neuropsychiatric symptoms and rate of progression. These differences have a major impact on quality of life for patients and carers, as well as health care costs, but their mechanisms and neuropathological underpinnings are poorly understood. Furthermore the correlation between clinical diagnosis and neuropathological findings is relatively low, and LBD patients presenting with cognitive impairment particularly risk being misclassified as AD. This highlight the need for more precise biomarkers for these clinical syndromes that can be implemented at the start of and during the course of the disease. Biomarkers may inform about disease pathology, thus paving the way for new treatment, they increase diagnostic accuracy and aid in setting a prognosis. Biomarkers are needed in the selection of patients for treatment studies and to identify which patients should benefit from new treatment when available. The cerebrospinal fluid (CSF) biomarkers beta-amyloid 42 (abeta42), total tau (t-tau) and tau protein phosphorylated at amino acid 181 (p-tau181) reflect key AD pathologies. The Lewy bodies found in LBD are composed mainly of the protein !-synuclein. !-synuclein is reduced in CSF in LBD, but with considerable overlap between LBD, controls and other disease groups. Aim: The main aim of this thesis was to increase understanding of pathological mechanisms underlying important clinical features in neurodegenerative cognitive impairment, by exploring the associations between clinical presentation and biomarkers and pathology. The first objective was to explore the association between AD pathology CSF markers and neuropsychiatric symptoms in newly diagnosed AD patients; secondly to assess the association between CSF markers of AD and LBD pathology and early cognitive impairment in PD; thirdly to examine the correlation between clinical diagnosis of DLB and Lewy body pathology at autopsy. Methods: This is a clinical translational neuroscience project based on two clinical cohort studies. The dementia Study of Western Norway (Demvest) included newly diagnosed dementia patients from specialist clinics in geriatric medicine and old age psychiatry in Western Norway. The Parkinson´s Progression Markers Initiative (PPMI) is an international multicentre study, including newly diagnosed PD patients and healthy controls. A comprehensive battery of neuropsychological tests, a structured neuropsychiatric evaluation, clinical examination, and imaging were part of both studies. CSF sampling was done according to standardized protocols and CSF was analysed using commercially available immunoassays. In the Demvest study, participants were recruited for brain donation, and autopsy results were obtained applying commonly used neuropathological protocols and diagnostic criteria. Results: We undertook three specific studies to investigate objective I, II and III. In study I, apathy in patients with early Alzheimer´s disease correlated with t-tau and ptau181 concentrations in CSF, higher values being associated with more severe apathy. There were no associations between depression or psychosis and agitation and CSF markers. In study II, decreased CSF !-synuclein in newly diagnosed PD-patients without dementia correlated with impaired global cognition and impairment of executive functions and attention. CSF abeta42 was decreased in PD with mild cognitive impairment compared with controls after adjusting for covariates. No correlations were found between memory or visuospatial functions and CSF markers. Study III examined autopsy results of 56 patients followed from dementia diagnosis to death. 20 patients received a pathological diagnosis of LBD; the corresponding clinical diagnosis were probable DLB (n=11), Parkinson´s disease with dementia (PDD) (n=5) and probable or possible AD (n=4). Of the 56, 14 patients received a clinical diagnosis of probable DLB, 11 of these had pathological LBD and three AD. Sensitivity, specificity, positive and negative predictive values of a clinical DLB diagnosis were 73%, 93%, 70%, and 90% respectively. Conclusions and implications: We have reported a novel association between neuropsychiatric symptoms and CSF biomarkers reflecting core AD pathology. The relationship between t-tau and p-tau181 and apathy may reflect an association between neurofibrillary tangle pathology and apathy in early AD. Cognitive impairment in early PD was associated with biomarkers of both Lewy body and AD pathology. 18 of 20 LBD patients in the Demvest study had Braak neurofibrillary tangle stage IV or higher, representing severe AD pathology at autopsy. Thus our findings suggest a role for AD pathology in both early and established LBD. Accurate diagnosis is crucial for clinical practice and research. With a sensitivity of 73%, the clinical 2005 DLB criteria are not sensitive enough. More than one in four DLB patients were not identified even when structured rating scales for core DLB symptoms were applied. We regard a specificity of 93% as satisfactory. Our results illustrate that not all DLB patients fulfil the 2005 DLB criteria at disease presentation, highlighting the need for re-evaluation of the diagnosis if new symptoms appear. Studies applying the most recent 2017 DLB criteria will show if this revision has increased sensitivity without decreasing specificity

The relationship of microRNAs to clinical features of Huntington's and Parkinson's disease

MicroRNAs (miRNAs) represent a major system of post-transcriptional regulation, by either preventing translational initiation or by targeting messenger RNA transcripts for storage or degradation. miRNA deregulation has been reported in neurodegenerative disorders, such as Huntington’s disease (HD) and Parkinson’s disease (PD), which may impact gene expression and modify disease progression and/or severity. To assess the relationship of miRNA levels to HD, small RNA sequence analysis was performed for 26 HD and 36 non-disease control samples derived from human prefrontal cortex. 75 miRNAs were differentially expressed in HD brain as compared to controls at genome-wide significance (FDR q<0.05). Among HD brains, nine miRNAs were significantly associated with the extent of neuropathological involvement in the striatum and three of these significantly related to a continuous measure of striatal involvement, after statistical adjustment for the contribution of HD gene length. Five miRNAs were identified as having a significant, inverse relationship to age of motor onset, in particular, miR-10b-5p, the mostly strongly over-expressed miRNA in HD cases. Although prefrontal cortex was the source of tissue profiled in these studies, the relationship of miR-10b-5p levels to striatal involvement in the disease was independent of cortical involvement. In blood plasma from 26 HD, 4 asymptomatic HD gene carriers and 8 controls, miR-10b-5p levels were significantly elevated in HD as compared to non-diseased and preclinical HD subjects, demonstrating that miRNA alterations associated with diseased brain may be detected peripherally. Using small RNA sequence analysis for 29 PD brains, 125 miRNAs were identified as differentially expressed at genome-wide significance (FDR q<0.05) in PD versus controls. A set of 29 miRNAs accurately classified PD from non-diseased brain (93.9% specificity, 96.6% sensitivity, 4.8% absolute error). In contrast to HD, among PD cases, miR-10b-5p was significantly decreased and had a significant, positive association to onset age independent of age at death. These studies provide a detailed miRNA profile for HD and PD brain, identify miRNAs associated with disease pathology and suggest miRNA changes observed in brain can be detected in blood. Together, these findings support the potential of miRNA biomarkers for the diagnosis and assessment of progression for neurodegenerative diseases

Nonlinear Weighting Ensemble Learning Model to Diagnose Parkinson's Disease Using Multimodal Data

This work was supported by the FEDER/Junta deAndalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades/Proyecto (B-TIC-586-UGR20); the MCIN/AEI/10.13039/501100011033/ and FEDER \Una manerade hacer Europa" under the RTI2018-098913-B100 project, by the Consejeria de Economia, Innovacion,Ciencia y Empleo (Junta de Andalucia) and FEDER under CV20-45250, A-TIC-080-UGR18 and P20-00525 projects. Grant by F.J.M.M. RYC2021-030875-I funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR. Work by D.C.B. is supported by the MCIN/AEI/FJC2021-048082-I Juan de la Cierva Formacion'. Work by J.E.A. is supported by Next Generation EU Fund through a Margarita Salas Grant, and work by C.J.M. is supported by Ministerio de Universidades under the FPU18/04902 grant.Parkinson's Disease (PD) is the second most prevalent neurodegenerative disorder among adults. Although its triggers are still not clear, they may be due to a combination of different types of biomarkers measured through medical imaging, metabolomics, proteomics or genetics, among others. In this context, we have proposed a Computer-Aided Diagnosis (CAD) system that combines structural and functional imaging data from subjects in Parkinson's Progression Markers Initiative dataset by means of an Ensemble Learning methodology trained to identify and penalize input sources with low classification rates and/or high-variability. This proposal improves results published in recent years and provides an accurate solution not only from the point of view of image preprocessing (including a comparison between different intensity preservation techniques), but also in terms of dimensionality reduction methods (Isomap). In addition, we have also introduced a bagging classification schema for scenarios with unbalanced data.As shown by our results, the CAD proposal is able to detect PD with 96.48% of balanced accuracy, and opens up the possibility of combining any number of input data sources relevant for PD.FEDER/Junta deAndalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades/Proyecto B-TIC-586-UGR20MCIN/AEI P20-00525FEDER \Una manerade hacer Europa RYC2021-030875-IJunta de AndaluciaEuropean Union (EU) Spanish Government RTI2018-098913-B100, CV20-45250, A-TIC-080-UGR18European Union (EU)Juan de la Cierva FormacionNext Generation EU Fund through a Margarita Salas GrantMinisterio de Universidades FPU18/0490

Big Data and Parkinson’s Disease: Exploration, Analyses, and Data Challenges.

In healthcare, a tremendous amount of clinical and laboratory tests, imaging, prescription and medication data are being collected. Big data analytics on these data aim at early detection of disease which will help in developing preventive measures and in improving patient care. Parkinson disease is the second-most common neurodegenerative disorder in the United States. To find a cure for Parkinson\u27s disease biological, clinical and behavioral data of different cohorts are collected, managed and propagated through Parkinson’s Progression Markers Initiative (PPMI). Applying big data technology to this data will lead to the identification of the potential biomarkers of Parkinson’s disease. Data collected in human clinical studies is imbalanced, heterogeneous, incongruent and sparse. This study focuses on the ways to overcome the challenges offered by PPMI data which is wide and gappy. This work leverages the initial discoveries made through descriptive studies of various attributes. The exploration of data led to identifying the significant attributes. We are further working to build a software suite that enables end to end analysis of Parkinson’s data (from cleaning and curating data, to imputation, to dimensionality reduction, to multivariate correlation and finally to identify potential biomarkers)

Genome-Wide Association Studies of Cognitive and Motor Progression in Parkinson's Disease.

BACKGROUND: There are currently no treatments that stop or slow the progression of Parkinson's disease (PD). Case-control genome-wide association studies have identified variants associated with disease risk, but not progression. The objective of the current study was to identify genetic variants associated with PD progression. METHODS: We analyzed 3 large longitudinal cohorts: Tracking Parkinson's, Oxford Discovery, and the Parkinson's Progression Markers Initiative. We included clinical data for 3364 patients with 12,144 observations (mean follow-up 4.2 years). We used a new method in PD, following a similar approach in Huntington's disease, in which we combined multiple assessments using a principal components analysis to derive scores for composite, motor, and cognitive progression. These scores were analyzed in linear regression in genome-wide association studies. We also performed a targeted analysis of the 90 PD risk loci from the latest case-control meta-analysis. RESULTS: There was no overlap between variants associated with PD risk, from case-control studies, and PD age at onset versus PD progression. The APOE ε4 tagging variant, rs429358, was significantly associated with composite and cognitive progression in PD. Conditional analysis revealed several independent signals in the APOE locus for cognitive progression. No single variants were associated with motor progression. However, in gene-based analysis, ATP8B2, a phospholipid transporter related to vesicle formation, was nominally associated with motor progression (P = 5.3 × 10-6 ). CONCLUSIONS: We provide early evidence that this new method in PD improves measurement of symptom progression. We show that the APOE ε4 allele drives progressive cognitive impairment in PD. Replication of this method and results in independent cohorts are needed. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.Funding sources: Parkinson’s U