NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases

Additional rare variant analysis in Parkinson's disease cases with and without known pathogenic mutations: evidence for oligogenic inheritance

Oligogenic inheritance implies a role for several genetic factors in disease etiology. We studied oligogenic inheritance in Parkinson’s (PD) by assessing the potential burden of additional rare variants in established Mendelian genes and/or GBA, in individuals with and without a primary pathogenic genetic cause in two large independent cohorts totaling 7,900 PD cases and 6,166 controls. An excess (≥30%) of cases with a recognised primary genetic cause had ≥1 additional rare variants in Mendelian PD genes, as compared with no known mutation PD cases (17%) and unaffected controls (16%), supporting our hypothesis. Carriers of additional Mendelian gene variants have younger ages at onset (AAO). The effect of additional Mendelian variants in LRRK2 G2019S mutation carriers, of which ATP13A2 variation is particularly common, may account for some of the variation in penetrance. About 10% of No Known Mutation-PD cases harbour a rare GBA variant compared to known pathogenic mutation PD cases (8%) and controls (5%), with carriers having earlier AAOs. Together, the data suggest that the oligogenic inheritance of rare Mendelian variants may be important in patient with a primary pathogenic cause, whereas GBA increases risk across all forms of PD. This study highlights the potential genetic complexity of Mendelian PD. The identification of potential modifying variants provides new insights into disease mechanisms by potentially separating relevant from benign variants and by the interaction between genes in specific pathways. In the future this may be relevant to genetic testing and counselling of patients with PD and their families.

NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases

Genetics has proven to be a powerful approach in neurodegenerative diseases research, resulting in the identification of numerous causal and risk variants. Previously, we introduced the NeuroX Illumina genotyping array, a fast and efficient genotyping platform designed for the investigation of genetic variation in neurodegenerative diseases. Here, we present its updated version, named NeuroChip. The NeuroChip is a low-cost, custom-designed array containing a tagging variant backbone of about 306,670 variants complemented with a manually curated custom content comprised of 179,467 variants implicated in diverse neurological diseases, including Alzheimer's disease, Parkinson's disease, Lewy body dementia, amyotrophic lateral sclerosis, frontotemporal dementia, progressive supranuclear palsy, corticobasal degeneration, and multiple system atrophy. The tagging backbone was chosen because of the low cost and good genome-wide resolution; the custom content can be combined with other backbones, like population or drug development arrays. Using the NeuroChip, we can accurately identify rare variants and impute over 5.3 million common SNPs from the latest release of the Haplotype Reference Consortium. In summary, we describe the design and usage of the NeuroChip array and show its capability for detecting rare pathogenic variants in numerous neurodegenerative diseases. The NeuroChip has a more comprehensive and improved content, which makes it a reliable, high-throughput, cost-effective screening tool for genetic research and molecular diagnostics in neurodegenerative diseases.

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.

Large-scale exploratory genetic analysis of cognitive impairment in Parkinson's disease

Cognitive impairment is a common and disabling problem in Parkinson's disease (PD). Identification of genetic variants that influence the presence or severity of cognitive deficits in PD might provide a clearer understanding of the pathophysiology underlying this important nonmotor feature. We genotyped 1105 PD patients from the PD Cognitive Genetics Consortium for 249,336 variants using the NeuroX array. Participants underwent assessments of learning and memory (Hopkins Verbal Learning Test-Revised [HVLT-R]), working memory/executive function (Letter-Number Sequencing and Trail Making Test [TMT] A and B), language processing (semantic and phonemic verbal fluency), visuospatial abilities (Benton Judgment of Line Orientation [JoLO]), and global cognitive function (Montreal Cognitive Assessment). For common variants, we used linear regression to test for association between genotype and cognitive performance with adjustment for important covariates. Rare variants were analyzed using the optimal unified sequence kernel association test. The significance threshold was defined as a false discovery rate-corrected p-value (P_FDR) of 0.05. Eighteen common variants in 13 genomic regions exceeded the significance threshold for one of the cognitive tests. These included GBA rs2230288 (E326K; P_FDR = 2.7 × 10^-4) for JoLO, PARP4 rs9318600 (P_FDR = 0.006), and rs9581094 (P_FDR = 0.006) for HVLT-R total recall, and MTCL1 rs34877994 (P_FDR = 0.01) for TMT B-A. Analysis of rare variants did not yield any significant gene regions. We have conducted the first large-scale PD cognitive genetics analysis and nominated several new putative susceptibility genes for cognitive impairment in PD. These results will require replication in independent PD cohorts.

Study protocol: Insight 46 - a neuroscience sub-study of the MRC National Survey of Health and Development

BACKGROUND

Increasing age is the biggest risk factor for dementia, of which Alzheimer's disease is the commonest cause. The pathological changes underpinning Alzheimer's disease are thought to develop at least a decade prior to the onset of symptoms. Molecular positron emission tomography and multi-modal magnetic resonance imaging allow key pathological processes underpinning cognitive impairment - including β-amyloid depostion, vascular disease, network breakdown and atrophy - to be assessed repeatedly and non-invasively. This enables potential determinants of dementia to be delineated earlier, and therefore opens a pre-symptomatic window where intervention may prevent the onset of cognitive symptoms.

METHODS/DESIGN

This paper outlines the clinical, cognitive and imaging protocol of "Insight 46", a neuroscience sub-study of the MRC National Survey of Health and Development. This is one of the oldest British birth cohort studies and has followed 5362 individuals since their birth in England, Scotland and Wales during one week in March 1946. These individuals have been tracked in 24 waves of data collection incorporating a wide range of health and functional measures, including repeat measures of cognitive function. Now aged 71 years, a small fraction have overt dementia, but estimates suggest that ~1/3 of individuals in this age group may be in the preclinical stages of Alzheimer's disease. Insight 46 is recruiting 500 study members selected at random from those who attended a clinical visit at 60-64 years and on whom relevant lifecourse data are available. We describe the sub-study design and protocol which involves a prospective two time-point (0, 24 month) data collection covering clinical, neuropsychological, β-amyloid positron emission tomography and magnetic resonance imaging, biomarker and genetic information. Data collection started in 2015 (age 69) and aims to be completed in 2019 (age 73).

DISCUSSION

Through the integration of data on the socioeconomic environment and on physical, psychological and cognitive function from 0 to 69 years, coupled with genetics, structural and molecular imaging, and intensive cognitive and neurological phenotyping, Insight 46 aims to identify lifetime factors which influence brain health and cognitive ageing, with particular focus on Alzheimer's disease and cerebrovascular disease. This will provide an evidence base for the rational design of disease-modifying trials.

A data-driven approach links microglia to pathology and prognosis in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease that lacks a predictive and broadly applicable biomarker. Continued focus on mutation-specific upstream mechanisms has yet to predict disease progression in the clinic. Utilising cellular pathology common to the majority of ALS patients, we implemented an objective transcriptome-driven approach to develop noninvasive prognostic biomarkers for disease progression. Genes expressed in laser captured motor neurons in direct correlation (Spearman rank correlation, p < 0.01) with counts of neuropathology were developed into co-expression network modules. Screening modules using three gene sets representing rate of disease progression and upstream genetic association with ALS led to the prioritisation of a single module enriched for immune response to motor neuron degeneration. Genes in the network module are important for microglial activation and predict disease progression in genetically heterogeneous ALS cohorts: Expression of three genes in peripheral lymphocytes - LILRA2, ITGB2 and CEBPD – differentiate patients with rapid and slowly progressive disease, suggesting promise as a blood-derived biomarker. TREM2 is a member of the network module and the level of soluble TREM2 protein in cerebrospinal fluid is shown to predict survival when measured in late stage disease (Spearman rank correlation, p = 0.01). Our data-driven systems approach has, for the first time, directly linked microglia to the development of motor neuron pathology. LILRA2, ITGB2 and CEBPD represent peripherally accessible candidate biomarkers and TREM2 provides a broadly applicable therapeutic target for ALS.

C9ORF72 hexanucleotide repeat exerts toxicity in a stable, inducible motor neuronal cell model, which is rescued by partial depletion of Pten

Amyotrophic lateral sclerosis (ALS) is a devastating and incurable neurodegenerative disease, characterised by progressive failure of the neuromuscular system. A (G4C2)n repeat expansion in C9ORF72 is the most common genetic cause of ALS and frontotemporal dementia (FTD). To date, the balance of evidence indicates that the (G4C2)n repeat causes toxicity and neurodegeneration via a gain-of-toxic function mechanism; either through direct RNA toxicity or through the production of toxic aggregating dipeptide repeat proteins. Here, we have generated a stable and isogenic motor neuronal NSC34 cell model with inducible expression of a (G4C2)102 repeat, to investigate the gain-of-toxic function mechanisms. The expression of the (G4C2)102 repeat produces RNA foci and also undergoes RAN translation. In addition, the expression of the (G4C2)102 repeat shows cellular toxicity. Through comparison of transcriptomic data from the cellular model with laser-captured spinal motor neurons from C9ORF72-ALS cases, we also demonstrate that the PI3K/Akt cell survival signalling pathway is dysregulated in both systems. Furthermore, partial knockdown of Pten rescues the toxicity observed in the NSC34 (G4C2)102 cellular gain-of-toxic function model of C9ORF72-ALS. Our data indicate that PTEN may provide a potential therapeutic target to ameliorate toxic effects of the (G4C2)n repeat.

Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing

BACKGROUND

Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models.

RESULTS

Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication.

CONCLUSIONS

By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies.

Rare variants analysis of cutaneous malignant melanoma genes in Parkinson's disease

A shared genetic susceptibility between cutaneous malignant melanoma (CMM) and Parkinson's disease (PD) has been suggested. We investigated this by assessing the contribution of rare variants in genes involved in CMM to PD risk. We studied rare variation across 29 CMM risk genes using high-quality genotype data in 6875 PD cases and 6065 controls and sought to replicate findings using whole-exome sequencing data from a second independent cohort totaling 1255 PD cases and 473 controls. No statistically significant enrichment of rare variants across all genes, per gene, or for any individual variant was detected in either cohort. There were nonsignificant trends toward different carrier frequencies between PD cases and controls, under different inheritance models, in the following CMM risk genes: BAP1, DCC, ERBB4, KIT, MAPK2, MITF, PTEN, and TP53. The very rare TYR p.V275F variant, which is a pathogenic allele for recessive albinism, was more common in PD cases than controls in 3 independent cohorts. Tyrosinase, encoded by TYR, is the rate-limiting enzyme for the production of neuromelanin, and has a role in the production of dopamine. These results suggest a possible role for another gene in the dopamine-biosynthetic pathway in susceptibility to neurodegenerative Parkinsonism, but further studies in larger PD cohorts are needed to accurately determine the role of these genes/variants in disease pathogenesis.

Common variant rs356182 near SNCA defines a Parkinson's disease endophenotype

Objective

Parkinson's disease (PD) presents clinically with several motor subtypes that exhibit variable treatment response and prognosis. Here, we investigated genetic variants for their potential association with PD motor phenotype and progression.

Methods

We screened 10 SNPs, previously associated with PD risk, for association with tremor‐dominant (TD) versus postural‐instability gait disorder (PIGD) motor subtypes. SNPs that correlated with the TD/PIGD ratio in a discovery cohort of 251 PD patients were then evaluated in a multi‐site replication cohort of 559 PD patients. SNPs associated with motor phenotype in both cross‐sectional cohorts were next evaluated for association with (1) rates of motor progression in a longitudinal subgroup of 230 PD patients and (2) brain alpha‐synuclein (SNCA) expression in the GTEx (Genotype‐Tissue Expression project) consortium database.

Results

Genotype at rs356182, near SNCA, correlated with the TD/PIGD ratio in both the discovery (Bonferroni‐corrected P = 0.04) and replication cohorts (P = 0.02). The rs356182 GG genotype was associated with a more tremor‐predominant phenotype and predicted a slower rate of motor progression (1‐point difference in annual rate of UPDRS‐III motor score change, P = 0.01). The rs356182 genotype was associated with SNCA expression in the cerebellum (P = 0.005).

Interpretation

Our study demonstrates that the GG genotype at rs356182 provides molecular definition for a clinically important endophenotype associated with (1) more tremor‐predominant motor phenomenology, (2) slower rates of motor progression, and (3) decreased brain expression of SNCA. Such molecularly defined endophenotyping in PD may benefit both clinical trial design and tailoring of clinical care as we enter the era of precision medicine.

Clinical-genetic model predicts incident impulse control disorders in Parkinson's disease

OBJECTIVES

Impulse control disorders (ICD) are commonly associated with dopamine replacement therapy (DRT) in patients with Parkinson's disease (PD). Our aims were to estimate ICD heritability and to predict ICD by a candidate genetic multivariable panel in patients with PD.

METHODS

Data from de novo patients with PD, drug-naïve and free of ICD behaviour at baseline, were obtained from the Parkinson's Progression Markers Initiative cohort. Incident ICD behaviour was defined as positive score on the Questionnaire for Impulsive-Compulsive Disorders in PD. ICD heritability was estimated by restricted maximum likelihood analysis on whole exome sequencing data. 13 candidate variants were selected from the DRD2, DRD3, DAT1, COMT, DDC, GRIN2B, ADRA2C, SERT, TPH2, HTR2A, OPRK1 and OPRM1 genes. ICD prediction was evaluated by the area under the curve (AUC) of receiver operating characteristic (ROC) curves.

RESULTS

Among 276 patients with PD included in the analysis, 86% started DRT, 40% were on dopamine agonists (DA), 19% reported incident ICD behaviour during follow-up. We found heritability of this symptom to be 57%. Adding genotypes from the 13 candidate variants significantly increased ICD predictability (AUC=76%, 95% CI (70% to 83%)) compared to prediction based on clinical variables only (AUC=65%, 95% CI (58% to 73%), p=0.002). The clinical-genetic prediction model reached highest accuracy in patients initiating DA therapy (AUC=87%, 95% CI (80% to 93%)). OPRK1, HTR2A and DDC genotypes were the strongest genetic predictive factors.

CONCLUSIONS

Our results show that adding a candidate genetic panel increases ICD predictability, suggesting potential for developing clinical-genetic models to identify patients with PD at increased risk of ICD development and guide DRT management.

Ser(P)-1292 LRRK2 in urinary exosomes is elevated in idiopathic Parkinson's disease

BACKGROUND

Mutations in Leucine-rich repeat kinase 2 (LRRK2) enhance levels of the autophosphorylated LRRK2 protein and are the most common known cause of inherited Parkinson's disease (PD). LRRK2 has been further implicated in susceptibility to idiopathic PD in genetic association studies.

OBJECTIVE

The objective of this study was to compare autophosphorylated Ser(P)-1292 LRRK2 levels from biobanked urine samples with clinical data in PD patients and controls.

METHODS

Ser(P)-1292 LRRK2 levels were measured from urine exosome fractions from 79 PD patients and 79 neurologically healthy controls enrolled in the Parkinson Disease Biomarker Program at the University of Alabama at Birmingham.

RESULTS

Ser(P)-1292 LRRK2 levels were higher in men than women (P < .0001) and elevated in PD patients when compared with controls (P = .0014). Ser(P)-1292 LRRK2 levels were higher in PD cases with worse cognition and correlated with poor performance in MoCA (r = -0.2679 [-0.4628 to -0.0482]), MDS-UPDRS subscales 1 and 2 (r = 0.2239 [0.0014-0.4252], 0.3404 [0.1276-0.5233], respectively), Epworth Sleepiness Scale (r = 0.3215 [0.1066-0.5077]), and Modified Schwab and England Activities of Daily Living Scales (r = -0.4455 [-0.6078 to -0.2475]). Ser(P)-1292 LRRK2 levels predicted those with worse cognitive impairment in PD patients with some success (c = 0.73).

CONCLUSIONS

Urinary exosome Ser(P)-1292 LRRK2 levels are elevated in idiopathic PD and correlated with the severity of cognitive impairment and difficultly in accomplishing activities of daily living. These results implicate biochemical changes in LRRK2 in idiopathic PD. © 2016 International Parkinson and Movement Disorder Society.

Mutation analysis of sporadic early-onset Alzheimer's disease using the NeuroX array

We have screened sporadic early-onset Alzheimer's disease (sEOAD, n = 408) samples using the NeuroX array for known causative and predicted pathogenic variants in 16 genes linked to familial forms of neurodegeneration. We found 2 sEOAD individuals harboring a known causative variant in PARK2 known to cause early-onset Parkinson's disease; p.T240M (n = 1) and p.Q34fs delAG (n = 1). In addition, we identified 3 sEOAD individuals harboring a predicted pathogenic variant in MAPT (p.A469T), which has previously been associated with AD. It is currently unknown if these variants affect susceptibility to sEOAD, further studies would be needed to establish this. This work highlights the need to screen sEOAD individuals for variants that are more classically attributed to other forms of neurodegeneration.

Genome-wide assessment of Parkinson's disease in a Southern Spanish population

Here, we set out to study the genetic architecture of Parkinson's disease (PD) through a Genome-Wide Association Study in a Southern Spanish population. About 240 PD cases and 192 controls were genotyped on the NeuroX array. We estimated genetic variation associated with PD risk and age at onset (AAO). Risk profile analyses for PD and AAO were performed using a weighted genetic risk score. Total heritability was estimated by genome-wide complex trait analysis. Rare variants were screened with single-variant and burden tests. We also screened for variation in known PD genes. Finally, we explored runs of homozygosity and structural genomic variations. We replicate PD association (uncorrected p-value < 0.05) at the following loci: ACMSD/TMEM163, MAPT, STK39, MIR4697, and SREBF/RAI1. Subjects in the highest genetic risk score quintile showed significantly increased risk of PD versus the lowest quintile (odds ratio = 3.6, p-value < 4e(-7)), but no significant difference in AAO. We found evidence of runs of homozygosity in 2 PD-associated regions: one intersecting the HLA-DQB1 gene in 6 patients and 1 control; and another intersecting the GBA-SYT11 gene in PD case. The GBA N370S and the LRRK2 G2019S variants were found in 8 and 7 cases, respectively, replicating previous work. A structural variant was found in 1 case in the PARK2 gene locus. This current work represents a comprehensive assessment at a genome-wide level characterizing a novel population in PD genetics.

Report of a workshop on research gaps in the treatment of cerebral palsy

Cerebral palsy (CP) is heterogeneous in etiology and manifestations, making research into relevant therapies difficult and limiting the generalizability of the results. We report here on the NIH CP symposium, where stakeholders from academic, clinical, regulatory, and advocacy backgrounds discussed the major challenges and needs for moving forward with clinical research in CP, and outlined priorities and action items. New information is constantly generated through research into pathogenesis and etiology. Clinical research and new therapeutic approaches need to keep pace, through large data registry integration and new research designs. Development of standardized data collection, increasing academic focus on CP research, and iterative approaches to treatment throughout the patients' lives, have all been identified as areas of focus. The workshop identified critical gaps and areas of focus to increase the evidence base for therapeutic approaches to determine which treatments work best for which patients in the near future. These include consolidation and optimization of databases and registries, updates to the research methodology, and better integration of resources and stakeholders.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

BACKGROUND

A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data.

METHODS AND FINDINGS

Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson's disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting.

CONCLUSIONS

Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson's disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer's, Huntington's, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.

The NINDS Parkinson's disease biomarkers program

BACKGROUND

Neuroprotection for Parkinson's disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke has therefore established the Parkinson's Disease Biomarkers Program to promote discovery of PD biomarkers for use in phase II and III clinical trials.

METHODS

Using a novel consortium design, the Parkinson's Disease Biomarker Program is focused on the development of clinical and laboratory-based biomarkers for PD diagnosis, progression, and prognosis. Standardized operating procedures and pooled reference samples were created to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the research community for additional biomarker projects.

RESULTS

Eleven consortium projects are ongoing, seven of which recruit participants and obtain biosamples. As of October 2014, 1,082 participants have enrolled (620 PD, 101 with other causes of parkinsonism, 23 essential tremor, and 338 controls), 1,040 of whom have at least one biosample. Six thousand eight hundred ninety-eight total biosamples are available from baseline, 6-, 12-, and 18-month visits: 1,006 DNA, 1,661 RNA, 1,419 whole blood, 1,382 plasma, 1,200 serum, and 230 cerebrospinal fluid (CSF). Quality control analysis of plasma, serum, and CSF samples indicates that almost all samples are high quality (24 of 2,812 samples exceed acceptable hemoglobin levels).

CONCLUSIONS

By making samples and data widely available, using stringent operating procedures based on existing standards, hypothesis testing for biomarker discovery, and providing a resource that complements existing programs, the Parkinson's Disease Biomarker Program will accelerate the pace of PD biomarker research. © 2015 International Parkinson and Movement Disorder Society.

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

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.

Resequencing analysis of five Mendelian genes and the top genes from genome-wide association studies in Parkinson's Disease

Background

Most sequencing studies in Parkinson’s disease (PD) have focused on either a particular gene, primarily in familial and early onset PD samples, or on screening single variants in sporadic PD cases. To date, there is no systematic study that sequences the most common PD causing genes with Mendelian inheritance [α-synuclein (SNCA), leucine-rich repeat kinase 2 (LRRK2), PARKIN, PTEN-induced putative kinase 1 (PINK1) and DJ-1 (Daisuke-Junko-1)] and susceptibility genes [glucocerebrosidase beta acid (GBA) and microtubule-associated protein tau (MAPT)] identified through genome-wide association studies (GWAS) in a European-American case-control sample (n=815).

Results

Disease-causing variants in the SNCA,LRRK2 and PARK2 genes were found in 2 % of PD patients. The LRRK2, p.G2019S mutation was found in 0.6 % of sporadic PD and 4.8 % of familial PD cases. Gene-based analysis suggests that additional variants in the LRRK2 gene also contribute to PD risk. The SNCA duplication was found in 0.8 % of familial PD patients. Novel variants were found in 0.8 % of PD cases and 0.6 % of controls. Heterozygous Gaucher disease-causing mutations in the GBA gene were found in 7.1 % of PD patients. Here, we established that the GBA variant (p.T408M) is associated with PD risk and age at onset. Additionally, gene-based and single-variant analyses demostrated that GBA gene variants (p.L483P, p.R83C, p.N409S, p.H294Q and p.E365K) increase PD risk.

Conclusions

Our data suggest that the impact of additional untested coding variants in the GBA and LRRK2 genes is higher than previously estimated. Our data also provide compelling evidence of the existence of additional untested variants in the primary Mendelian and PD GWAS genes that contribute to the genetic etiology of sporadic PD.

Screening exons 16 and 17 of the amyloid precursor protein gene in sporadic early-onset Alzheimer's disease

Early-onset Alzheimer's disease (EOAD) can be familial (FAD) or sporadic EOAD (sEOAD); both have a disease onset ≤65 years of age. A total of 451 sEOAD samples were screened for known causative mutations in exons 16 and 17 of the amyloid precursor protein (APP) gene. Four samples were shown to be heterozygous for 1 of 3 known causative mutations: p.A713T, p.V717I, and p.V717G; this highlights the importance of screening EOAD patients for causative mutations. Additionally, we document an intronic 6 base pair (bp) deletion located 83 bp downstream of exon 17 (rs367709245, IVS17 83-88delAAGTAT), which has a nonsignificantly increased minor allele frequency in our sEOAD cohort (0.006) compared to LOAD (0.002) and controls (0.002). To assess the effect of the 6-bp deletion on splicing, COS-7 and BE(2)-C cells were transfected with a minigene vector encompassing exon 17. There was no change in splicing of exon 17 from constructs containing either wild type or deletion inserts. Sequencing of cDNA generated from cerebellum and temporal cortex of a patient harboring the deletion found no evidence of transcripts with exon 17 removed.

Exercise and Nutritional Benefits in PD: Rodent Models and Clinical Settings

Physical exercise offers a highly effective health-endowering activity as has been evidence using rodent models of Parkinson's disease (PD). It is a particularly useful intervention in individuals employed in sedentary occupations or afflicted by a neurodegenerative disorder, such as PD. The several links between exercise and quality-of-life, disorder progression and staging, risk factors and symptoms-biomarkers in PD all endower a promise for improved prognosis. Nutrition provides a strong determinant for disorder vulnerability and prognosis with fish oils and vegetables with a mediterranean diet offering both protection and resistance. Three factors determining the effects of exercise on disorder severity of patients may be presented: (i) Exercise effects upon motor impairment, gait, posture and balance, (ii) Exercise reduction of oxidative stress, stimulation of mitochondrial biogenesis and up-regulation of autophagy, and (iii) Exercise stimulation of dopamine (DA) neurochemistry and trophic factors. Running-wheel performance, as measured by distance run by individual mice from different treatment groups, was related to DA-integrity, indexed by striatal DA levels. Finally, both nutrition and exercise may facilitate positive epigenetic outcomes, such as lowering the dosage of L-Dopa required for a therapeutic effect.

Genome-wide analysis of genetic correlation in dementia with Lewy bodies, Parkinson's and Alzheimer's diseases

The similarities between dementia with Lewy bodies (DLB) and both Parkinson's disease (PD) and Alzheimer's disease (AD) are many and range from clinical presentation, to neuropathological characteristics, to more recently identified, genetic determinants of risk. Because of these overlapping features, diagnosing DLB is challenging and has clinical implications since some therapeutic agents that are applicable in other diseases have adverse effects in DLB. Having shown that DLB shares some genetic risk with PD and AD, we have now quantified the amount of sharing through the application of genetic correlation estimates, and show that, from a purely genetic perspective, and excluding the strong association at the APOE locus, DLB is equally correlated to AD and PD.

Evaluating pathogenic dementia variants in posterior cortical atrophy

Posterior cortical atrophy (PCA) is an understudied visual impairment syndrome most often due to "posterior Alzheimer's disease (AD)" pathology. Case studies detected mutations in PSEN1, PSEN2, GRN, MAPT, and PRNP in subjects with clinical PCA. To detect the frequency and spectrum of mutations in known dementia genes in PCA, we screened 124 European-American subjects with clinical PCA (n = 67) or posterior AD neuropathology (n = 57) for variants in genes implicated in AD, frontotemporal dementia, and prion disease using NeuroX, a customized exome array. Frequencies in PCA of the variants annotated as pathogenic or potentially pathogenic were compared against ∼ 4300 European-American population controls from the NHLBI Exome Sequencing Project. We identified 2 rare variants not previously reported in PCA, TREM2 Arg47His, and PSEN2 Ser130Leu. No other pathogenic or potentially pathogenic variants were detected in the screened dementia genes. In this first systematic variant screen of a PCA cohort, we report 2 rare mutations in TREM2 and PSEN2, validate our previously reported APOE ε4 association, and demonstrate the utility of NeuroX.

Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI)

BACKGROUND

The Parkinson's Progression Marker Initiative is an international multicenter study whose main goal is investigating markers for Parkinson's disease (PD) progression as part of a path to a treatment for the disease. This manuscript describes the baseline genetic architecture of this study, providing not only a catalog of disease-linked variants and mutations, but also quantitative measures with which to adjust for population structure.

METHODS

Three hundred eighty-three newly diagnosed typical PD cases, 65 atypical PD and 178 healthy controls, from the Parkinson's Progression Marker Initiative study have been genotyped on the NeuroX or Immunochip arrays. These data are freely available to all researchers interested in pursuing PD research within the Parkinson's Progression Marker Initiative.

RESULTS

The Parkinson's Progression Marker Initiative represents a study population with low genetic heterogeneity. We recapitulate known PD associations from large-scale genome-wide association studies and refine genetic risk score models for PD predictability (area under the curve, ∼0.74). We show the presence of six LRRK2 p.G2019S and nine GBA p.N370S mutation carriers.

CONCLUSIONS

The Parkinson's Progression Marker Initiative study and its genetic data are useful in studies of PD biomarkers. The genetic architecture described here will be useful in the analysis of myriad biological and clinical traits within this study.

Variation in PARK10 is not associated with risk and age at onset of Parkinson's disease in large clinical cohorts

A recent study in autopsy-confirmed Parkinson's disease (PD) patients and controls revived the debate about the role of PARK10 in this disorder. In an attempt to replicate these results and further understand the role of this locus in the risk and age at onset of PD, we decided to explore NeuroX genotyping and whole exome sequencing data from 2 large independent cohorts of clinical patients and controls from the International Parkinson's Disease Genomic Consortium. A series of single-variant and gene-based aggregation (sequence kernel association test and combined multivariate and collapsing test) statistical tests suggested that common and rare genetic variation in this locus do not influence the risk or age at onset of clinical PD.

HFE p.H63D polymorphism does not influence ALS phenotype and survival

It has been recently reported that the p.His63Asp polymorphism of the HFE gene accelerates disease progression both in the SOD1 transgenic mouse and in amyotrophic lateral sclerosis (ALS) patients. We have evaluated the effect of HFE p.His63Asp polymorphism on the phenotype in 1351 Italian ALS patients (232 of Sardinian ancestry). Patients were genotyped for the HFE p.His63Asp polymorphism (CC, GC, and GG). All patients were also assessed for C9ORF72, TARDBP, SOD1, and FUS mutations. Of the 1351 ALS patients, 363 (29.2%) were heterozygous (GC) for the p.His63Asp polymorphism and 30 (2.2%) were homozygous for the minor allele (GG). Patients with CC, GC, and GG polymorphisms did not significantly differ by age at onset, site of onset of symptoms, and survival; however, in SOD1 patients with CG or GG polymorphism had a significantly longer survival than those with a CC polymorphism. Differently from what observed in the mouse model of ALS, the HFE p.His63Asp polymorphism has no effect on ALS phenotype in this large series of Italian ALS patients.

Parkinson's disease biomarkers program brain imaging repository

The Parkinson's Disease Biomarkers Program (PDBP) is a multi-site study designed to identify Parkinson's disease (PD) biomarkers that can be used to improve the understanding of PD pathophysiology and to develop tools that provide novel measures to evaluate PD clinical trials. The PDBP consortium comprises numerous individual projects of which two are specifically geared to the development of brain imaging markers for diagnosis, progression, and prognosis of PD or related disorders. All study data from PD patients, atypical Parkinsonian patients, patients with essential tremor, and healthy controls collected from the sites are integrated in the PDBP database and will be publically available. All subjects are asked to submit blood samples, and undergo a battery of clinical evaluations that cover motor, cognitive, and other background information. In addition, a subset of subjects contributed cerebrospinal fluid samples. A restricted access, web-based Data Management Resource facilitates rapid sharing of data and biosamples across the entire PD research community. The PDBP consortium is a useful resource for research and collaboration aimed at the discovery of biomarkers and their use in understanding the pathophysiology of PD.

Inflammation in Parkinson's disease: role of glucocorticoids

Chronic inflammation is a major characteristic feature of Parkinson's disease (PD). Studies in PD patients show evidence of augmented levels of potent pro-inflammatory molecules e.g., TNF-α, iNOS, IL-1β whereas in experimental Parkinsonism it has been consistently demonstrated that dopaminergic neurons are particularly vulnerable to activated glia releasing these toxic factors. Recent genetic studies point to the role of immune system in the etiology of PD, thus in combination with environmental factors, both peripheral and CNS-mediated immune responses could play important roles in onset and progression of PD. Whereas microglia, astrocytes and infiltrating T cells are known to mediate chronic inflammation, the roles of other immune-competent cells are less well understood. Inflammation is a tightly controlled process. One major effector system of regulation is HPA axis. Glucocorticoids (GCs) released from adrenal glands upon stimulation of HPA axis, in response to either cell injury or presence of pathogen, activate their receptor, GR. GR regulates inflammation both through direct transcriptional action on target genes and by indirectly inhibiting transcriptional activities of transcriptional factors such as NF-κB, AP-1 or interferon regulatory factors. In PD patients, the HPA axis is unbalanced and the cortisol levels are significantly increased, implying a deregulation of GR function in immune cells. In experimental Parkinsonism, the activation of microglial GR has a crucial effect in diminishing microglial cell activation and reducing dopaminergic degeneration. Moreover, GCs are also known to regulate human brain vasculature as well as blood brain barrier (BBB) permeability, any dysfunction in their actions may influence infiltration of cytotoxic molecules resulting in increased vulnerability of dopamine neurons in PD. Overall, deregulation of glucocorticoid receptor actions is likely important in dopamine neuron degeneration through establishment of chronic inflammation.

Epigenetic mechanisms in neurological and neurodegenerative diseases

The role of epigenetic mechanisms in the function and homeostasis of the central nervous system (CNS) and its regulation in diseases is one of the most interesting processes of contemporary neuroscience. In the last decade, a growing body of literature suggests that long-term changes in gene transcription associated with CNS's regulation and neurological disorders are mediated via modulation of chromatin structure. "Epigenetics", introduced for the first time by Waddington in the early 1940s, has been traditionally referred to a variety of mechanisms that allow heritable changes in gene expression even in the absence of DNA mutation. However, new definitions acknowledge that many of these mechanisms used to perpetuate epigenetic traits in dividing cells are used by neurons to control a variety of functions dependent on gene expression. Indeed, in the recent years these mechanisms have shown their importance in the maintenance of a healthy CNS. Moreover, environmental inputs that have shown effects in CNS diseases, such as nutrition, that can modulate the concentration of a variety of metabolites such as acetyl-coenzyme A (acetyl-coA), nicotinamide adenine dinucleotide (NAD(+)) and beta hydroxybutyrate (β-HB), regulates some of these epigenetic modifications, linking in a precise way environment with gene expression. This manuscript will portray what is currently understood about the role of epigenetic mechanisms in the function and homeostasis of the CNS and their participation in a variety of neurological disorders. We will discuss how the machinery that controls these modifications plays an important role in processes involved in neurological disorders such as neurogenesis and cell growth. Moreover, we will discuss how environmental inputs modulate these modifications producing metabolic and physiological alterations that could exert beneficial effects on neurological diseases. Finally, we will highlight possible future directions in the field of epigenetics and neurological disorders.

Mutation analysis of patients with neurodegenerative disorders using NeuroX array

Genetic analyses of patients with neurodegenerative disorders have identified multiple genes that need to be investigated for the presence of damaging variants. However, mutation analysis by Sanger sequencing is costly and time consuming. We tested the utility of a recently designed semi-custom genome-wide array (NeuroX; Illumina, Inc) tailored to study neurodegenerative diseases (e.g., mutation screening). We investigated 192 patients with 4 different neurodegenerative disorders for the presence of rare damaging variations in 77 genes implicated in these diseases. Several causative mutations were identified and confirmed by Sanger sequencing, including PSEN1 p.M233T responsible for Alzheimer's disease in a large Italian family, as well as SOD1 p.A4V and p.I113T in patients with amyotrophic lateral sclerosis. In total, we identified 78 potentially damaging rare variants (frequency <1%), including ABCA7 p.L400V in a family with Alzheimer's disease and LRRK2 p.R1514Q in 6 of 98 patients with Parkinson's disease (6.1%). In conclusion, NeuroX appears to be helpful for rapid and accurate mutation screening, although further development may be still required to improve some current caveats.