Use of Bayesian decision analysis to maximize value in patient-centered randomized clinical trials in Parkinson's disease.

A fixed one-sided significance level of 5% is commonly used to interpret the statistical significance of randomized clinical trial (RCT) outcomes. While it is necessary to reduce the false positive rate, the threshold used could be chosen quantitatively and transparently to specifically reflect patient preferences regarding benefit-risk tradeoffs as well as other considerations. How can patient preferences be explicitly incorporated into RCTs in Parkinson's disease (PD), and what is the impact on statistical thresholds for device approval? In this analysis, we apply Bayesian decision analysis (BDA) to PD patient preference scores elicited from survey data. BDA allows us to choose a sample size (n) and significance level (α) that maximizes the overall expected value to patients of a balanced two-arm fixed-sample RCT, where the expected value is computed under both null and alternative hypotheses. For PD patients who had previously received deep brain stimulation (DBS) treatment, the BDA-optimal significance levels fell between 4.0% and 10.0%, similar to or greater than the traditional value of 5%. Conversely, for patients who had never received DBS, the optimal significance level ranged from 0.2% to 4.4%. In both of these populations, the optimal significance level increased with the severity of the patients' cognitive and motor function symptoms. By explicitly incorporating patient preferences into clinical trial designs and the regulatory decision-making process, BDA provides a quantitative and transparent approach to combine clinical and statistical significance. For PD patients who have never received DBS treatment, a 5% significance threshold may not be conservative enough to reflect their risk-aversion level. However, this study shows that patients who previously received DBS treatment present a higher tolerance to accept therapeutic risks in exchange for improved efficacy which is reflected in a higher statistical threshold.

Patient-Centered Identification of Meaningful Regulatory Endpoints for Medical Devices to Treat Parkinson's Disease.

Introduction. A growing literature has developed on identifying outcomes that matter to patients. This study demonstrates an approach involving patient and regulatory perspectives to identify outcomes that are meaningful in the context of medical devices for Parkinson's disease (PD). Methods. A systematic process was used for specifying relevant regulatory endpoints by synthesizing inputs of various sources and stakeholders. First, a literature review was conducted to identify important benefits, risks, and other considerations for medical devices to treat PD; patient discussion groups (n = 6) were conducted to refine the list of considerations, followed by a survey (n = 29) to prioritize them; and patient and Food and Drug Administration (FDA) reviewers informed specification of the final endpoints. Two FDA clinicians gave clinical and regulatory perspectives at each step. Results. Movement symptoms were ranked as most important (ranked 1 or 2 by 72% of participants) and psychological and cognitive symptoms as the next most important (ranked 1 or 2 by 52% of participants). Within movement symptoms, falls, impaired movement, bradykinesia, resting tremor, stiffness, and rigidity were ranked highly. Overall, nine attributes were identified and prioritized as patient-centric for use in clinical trial design and quantitative patient preference studies. These attributes were benefits and risks related to therapeutics for PD as well as other considerations, including time until a medical device is available for patient use. Discussion. This prospective approach identified meaningful and relevant benefits, risks, and other considerations that may be used for clinical trial design and quantitative patient preference studies. Although PD was the focus of this study, the approach can be used to study patient perspectives about other disease or treatment areas.

Parkinson's Patients' Tolerance for Risk and Willingness to Wait for Potential Benefits of Novel Neurostimulation Devices: A Patient-Centered Threshold Technique Study.

Background. Parkinson's disease (PD) is neurodegenerative, causing motor, cognitive, psychological, somatic, and autonomic symptoms. Understanding PD patients' preferences for novel neurostimulation devices may help ensure that devices are delivered in a timely manner with the appropriate level of evidence. Our objective was to elicit preferences and willingness-to-wait for novel neurostimulation devices among PD patients to inform a model of optimal trial design. Methods. We developed and administered a survey to PD patients to quantify the maximum levels of risks that patients would accept to achieve potential benefits of a neurostimulation device. Threshold technique was used to quantify patients' risk thresholds for new or worsening depression or anxiety, brain bleed, or death in exchange for improvements in "on-time," motor symptoms, pain, cognition, and pill burden. The survey elicited patients' willingness to wait to receive treatment benefit. Patients were recruited through Fox Insight, an online PD observational study. Results. A total of 2740 patients were included and a majority were White (94.6%) and had a 4-year college degree (69.8%). Risk thresholds increased as benefits increased. Threshold for depression or anxiety was substantially higher than threshold for brain bleed or death. Patient age, ambulation, and prior neurostimulation experience influenced risk tolerance. Patients were willing to wait an average of 4 to 13 years for devices that provide different levels of benefit. Conclusions. PD patients are willing to accept substantial risks to improve symptoms. Preferences are heterogeneous and depend on treatment benefit and patient characteristics. The results of this study may be useful in informing review of device applications and other regulatory decisions and will be input into a model of optimal trial design for neurostimulation devices.

FDA Perspectives on the Regulation of Neuromodulation Devices.

The United States Food and Drug Administration (FDA) ensures that patients in the United States have access to safe and effective medical devices. The division of neurological and physical medicine devices reviews medical technologies that interface with the nervous system, including many neuromodulation devices. This article focuses on neuromodulation devices and addresses how to navigate the FDA's regulatory landscape to successfully bring devices to patients.

Finding useful biomarkers for Parkinson's disease.

The recent advent of an "ecosystem" of shared biofluid sample biorepositories and data sets will focus biomarker efforts in Parkinson's disease, boosting the therapeutic development pipeline and enabling translation with real-world impact.

Cerebrospinal fluid, plasma, and saliva in the BioFIND study: Relationships among biomarkers and Parkinson's disease Features.

OBJECTIVE: Examine relationships among neurodegenerative biomarkers and PD motor and nonmotor symptoms. BACKGROUND: CSF alpha-synuclein is decreased in PD versus healthy controls, but whether plasma and saliva alpha-synuclein differentiate these groups is controversial. Correlations of alpha-synuclein among biofluids (CSF, plasma, saliva) or biomarkers (eg, beta-amyloid, tau [total, phosphorylated]) are not fully understood. The relationships of these biomarkers with PD clinical features remain unclear. METHODS: BioFIND, a cross-sectional, observational study, examines clinical and biomarker characteristics in moderate-advanced PD and matched healthy controls. We compared alpha-synuclein concentrations across diagnosis, biofluids, and CSF biomarkers. Correlations of CSF biomarkers and MDS-UPDRS, motor phenotype, MoCA, and rapid eye movement sleep behavior disorder questionnaire scores in PD were examined. RESULTS: CSF alpha-synuclein was lower in PD versus controls (P = .01), controlling for age, gender, and education. Plasma and saliva alpha-synuclein did not differ between PD and controls, and alpha-synuclein did not significantly correlate among biofluids. CSF beta-amyloid1-42 was lower in PD versus controls (P < .01), and correlated weakly with MoCA recall scores (r = 0.23, P = .02). CSF alpha-synuclein was lower in the postural instability/gait difficulty phenotype than other motor phenotypes (P < .01). No CSF biomarkers predicted or correlated with total motor or rapid eye movement sleep behavior disorder scores. CSF alpha-synuclein correlated with beta-amyloid1-42 , total-tau, and phosphorylated-tau (r = 0.41, 0.81, 0.43, respectively; Ps < .001). CONCLUSION: Lower CSF alpha-synuclein is associated with diagnosis and motor phenotype in moderate-advanced PD. Plasma and saliva alpha-synuclein neither correlate with CSF alpha-synuclein, nor distinguish PD from controls. CSF beta-amyloid1-42 remains a potential biomarker for cognitive impairment in PD. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Excess α-synuclein compromises phagocytosis in iPSC-derived macrophages.

To examine the pathogenic role of α-synuclein (αS) in Parkinson's Disease, we have generated induced Pluripotent Stem Cell lines from early onset Parkinson's Disease patients with SNCA A53T and SNCA Triplication mutations, and in this study have differentiated them to PSC-macrophages (pMac), which recapitulate many features of their brain-resident cousins, microglia. We show that SNCA Triplication pMac, but not A53T pMac, have significantly increased intracellular αS versus controls and release significantly more αS to the medium. SNCA Triplication pMac, but not A53T pMac, show significantly reduced phagocytosis capability and this can be phenocopied by adding monomeric αS to the cell culture medium of control pMac. Fibrillar αS is taken up by pMac by actin-rearrangement-dependent pathways, and monomeric αS by actin-independent pathways. Finally, pMac degrade αS and this can be arrested by blocking lysosomal and proteasomal pathways. Together, these results show that macrophages are capable of clearing αS, but that high levels of exogenous or endogenous αS compromise this ability, likely a vicious cycle scenario faced by microglia in Parkinson's disease.

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.

Knowledge gaps and research recommendations for essential tremor.

Essential tremor (ET) is a common cause of significant disability, but its etiologies and pathogenesis are poorly understood. Research has been hampered by the variable definition of ET and by non-standardized research approaches. The National Institute of Neurological Disorders and Stroke (USA) invited experts in ET and related fields to discuss current knowledge, controversies, and gaps in our understanding of ET and to develop recommendations for future research. Discussion focused on phenomenology and phenotypes, therapies and clinical trials, pathophysiology, pathology, and genetics. Across all areas, the need for collaborative and coordinated research on a multinational level was expressed. Standardized data collection using common data elements for genetic, clinical, neurophysiological, and pathological studies was recommended. Large cohorts of patients should be studied prospectively to collect bio-samples, characterize the natural history of the clinical syndrome including patient-oriented outcomes, investigate potential etiologies of various phenotypes, and identify pathophysiological mechanisms. In particular, cellular and system-level mechanisms of tremor oscillations should be elucidated because they may yield effective therapeutic targets and biomarkers. A neuropathology consortium was recommended to standardize postmortem analysis and further characterize neuropathological observations in the cerebellum and elsewhere. Furthermore, genome-wide association studies on large patient cohorts (>10,000 patients) may allow the identification of common genes contributing to risk, and whole exome or genome sequencing may enable the identification of genetic risk and causal mutations in cohorts and well-characterized families.

Nutritional interventions in primary mitochondrial disorders: Developing an evidence base.

In December 2014, a workshop entitled "Nutritional Interventions in Primary Mitochondrial Disorders: Developing an Evidence Base" was convened at the NIH with the goals of exploring the use of nutritional interventions in primary mitochondrial disorders (PMD) and identifying knowledge gaps regarding their safety and efficacy; identifying research opportunities; and forging collaborations among researchers, clinicians, patient advocacy groups, and federal partners. Sponsors included the NIH, the Wellcome Trust, and the United Mitochondrial Diseases Foundation. Dietary supplements have historically been used in the management of PMD due to their potential benefits and perceived low risk, even though little evidence exists regarding their effectiveness. PMD are rare and clinically, phenotypically, and genetically heterogeneous. Thus patient recruitment for randomized controlled trials (RCTs) has proven to be challenging. Only a few RCTs examining dietary supplements, singly or in combination with other vitamins and cofactors, are reported in the literature. Regulatory issues pertaining to the use of dietary supplements as treatment modalities further complicate the research and patient access landscape. As a preface to exploring a research agenda, the workshop included presentations and discussions on what PMD are; how nutritional interventions are used in PMD; challenges and barriers to their use; new technologies and approaches to diagnosis and treatment; research opportunities and resources; and perspectives from patient advocacy, industry, and professional organizations. Seven key areas were identified during the workshop. These areas were: 1) defining the disease, 2) clinical trial design, 3) biomarker selection, 4) mechanistic approaches, 5) challenges in using dietary supplements, 6) standards of clinical care, and 7) collaboration issues. Short- and long-term goals within each of these areas were identified. An example of an overarching goal is the enrollment of all individuals with PMD in a natural history study and a patient registry to enhance research capability. The workshop demonstrates an effective model for fostering and enhancing collaborations among NIH and basic research, clinical, patient, pharmaceutical industry, and regulatory stakeholders in the mitochondrial disease community to address research challenges on the use of dietary supplements in PMD.

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.

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.

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

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

Defining neurodegeneration on Guam by targeted genomic sequencing.

OBJECTIVE: Amyotrophic lateral sclerosis/parkinsonism-dementia complex has been described in Guam, Western Papua, and the Kii Peninsula of Japan. The etiology and pathogenesis of this complex neurodegenerative disease remains enigmatic. METHODS: In this study, we have used targeted genomic sequencing to evaluate the contribution of genetic variability in the pathogenesis of amyotrophic lateral sclerosis, parkinsonism, and dementia in Guamanian Chamorros. RESULTS: Genes previously linked to or associated with amyotrophic lateral sclerosis, parkinsonism, dementia, and related neurodegenerative syndromes were sequenced in Chamorro subjects living in the Mariana Islands. Homozygous PINK1 p.L347P, heterozygous DCTN1 p.T54I, FUS p.P431L, and HTT (42 CAG repeats) were identified as pathogenic mutations. INTERPRETATION: The findings explain the clinical, pathologic, and genetic heterogeneity observed in some multi-incident families and contribute to the excess incidence of neurodegeneration previously reported on Guam.

Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network.

BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.

Agreement between TOAST and CCS ischemic stroke classification: the NINDS SiGN study.

OBJECTIVE: The objective of this study was to assess the level of agreement between stroke subtype classifications made using the Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS) systems. METHODS: Study subjects included 13,596 adult men and women accrued from 20 US and European genetic research centers participating in the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN). All cases had independently classified TOAST and CCS stroke subtypes. Kappa statistics were calculated for the 5 major ischemic stroke subtypes common to both systems. RESULTS: The overall agreement between TOAST and CCS was moderate (agreement rate, 70%; κ = 0.59, 95% confidence interval [CI] 0.58-0.60). Agreement varied widely across study sites, ranging from 28% to 90%. Agreement on specific subtypes was highest for large-artery atherosclerosis (κ = 0.71, 95% CI 0.69-0.73) and lowest for small-artery occlusion (κ = 0.56, 95% CI 0.54-0.58). CONCLUSION: Agreement between TOAST and CCS diagnoses was moderate. Caution is warranted when comparing or combining results based on the 2 systems. Replication of study results, for example, genome-wide association studies, should utilize phenotypes determined by the same classification system, ideally applied in the same manner.

Using previously genotyped controls in genome-wide association studies (GWAS): application to the Stroke Genetics Network (SiGN).

Genome-wide association studies (GWAS) are widely applied to identify susceptibility loci for a variety of diseases using genotyping arrays that interrogate known polymorphisms throughout the genome. A particular strength of GWAS is that it is unbiased with respect to specific genomic elements (e.g., coding or regulatory regions of genes), and it has revealed important associations that would have never been suspected based on prior knowledge or assumptions. To date, the discovered SNPs associated with complex human traits tend to have small effect sizes, requiring very large sample sizes to achieve robust statistical power. To address these issues, a number of efficient strategies have emerged for conducting GWAS, including combining study results across multiple studies using meta-analysis, collecting cases through electronic health records, and using samples collected from other studies as controls that have already been genotyped and made publicly available (e.g., through deposition of de-identified data into dbGaP or EGA). In certain scenarios, it may be attractive to use already genotyped controls and divert resources to standardized collection, phenotyping, and genotyping of cases only. This strategy, however, requires that careful attention be paid to the choice of "public controls" and to the comparability of genetic data between cases and the public controls to ensure that any allele frequency differences observed between groups is attributable to locus-specific effects rather than to a systematic bias due to poor matching (population stratification) or differential genotype calling (batch effects). The goal of this paper is to describe some of the potential pitfalls in using previously genotyped control data. We focus on considerations related to the choice of control groups, the use of different genotyping platforms, and approaches to deal with population stratification when cases and controls are genotyped across different platforms.

Stroke Genetics Network (SiGN) study: design and rationale for a genome-wide association study of ischemic stroke subtypes.

BACKGROUND AND PURPOSE: Meta-analyses of extant genome-wide data illustrate the need to focus on subtypes of ischemic stroke for gene discovery. The National Institute of Neurological Disorders and Stroke SiGN (Stroke Genetics Network) contributes substantially to meta-analyses that focus on specific subtypes of stroke. METHODS: The National Institute of Neurological Disorders and Stroke SiGN includes ischemic stroke cases from 24 genetic research centers: 13 from the United States and 11 from Europe. Investigators harmonize ischemic stroke phenotyping using the Web-based causative classification of stroke system, with data entered by trained and certified adjudicators at participating genetic research centers. Through the Center for Inherited Diseases Research, the Network plans to genotype 10,296 carefully phenotyped stroke cases using genome-wide single nucleotide polymorphism arrays and adds to these another 4253 previously genotyped cases, for a total of 14,549 cases. To maximize power for subtype analyses, the study allocates genotyping resources almost exclusively to cases. Publicly available studies provide most of the control genotypes. Center for Inherited Diseases Research-generated genotypes and corresponding phenotypes will be shared with the scientific community through the US National Center for Biotechnology Information database of Genotypes and Phenotypes, and brain MRI studies will be centrally archived. CONCLUSIONS: The Stroke Genetics Network, with its emphasis on careful and standardized phenotyping of ischemic stroke and stroke subtypes, provides an unprecedented opportunity to uncover genetic determinants of ischemic stroke.

Creation of an open-access, mutation-defined fibroblast resource for neurological disease research.

Our understanding of the molecular mechanisms of many neurological disorders has been greatly enhanced by the discovery of mutations in genes linked to familial forms of these diseases. These have facilitated the generation of cell and animal models that can be used to understand the underlying molecular pathology. Recently, there has been a surge of interest in the use of patient-derived cells, due to the development of induced pluripotent stem cells and their subsequent differentiation into neurons and glia. Access to patient cell lines carrying the relevant mutations is a limiting factor for many centres wishing to pursue this research. We have therefore generated an open-access collection of fibroblast lines from patients carrying mutations linked to neurological disease. These cell lines have been deposited in the National Institute for Neurological Disorders and Stroke (NINDS) Repository at the Coriell Institute for Medical Research and can be requested by any research group for use in in vitro disease modelling. There are currently 71 mutation-defined cell lines available for request from a wide range of neurological disorders and this collection will be continually expanded. This represents a significant resource that will advance the use of patient cells as disease models by the scientific community.