NINDS-Genome-Wide Genotyping in Parkinson's Disease: First Stage Analysis and Public Release of Data
Ontology highlight
ABSTRACT: Epidemiological studies have estimated a cumulative prevalence of PD of greater than 1 per thousand. When prevalence is
limited to senior populations, this proportion increases nearly 10-fold. The estimated genetic risk ratio for PD is
approximately 1.7 (70% increased risk for PD if a sibling has PD) for all ages, and increases over 7-fold for those under
age 66 years. The role for genes contributing to the risk of PD is therefore significant. This study utilized the well characterized collection of North American Caucasians
with Parkinson's disease, and neurologically normal controls from the sample
population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection
for a first stage whole genome analysis. Genome-wide, single nucleotide polymorphism (SNP) genotyping of these publicly
available samples was originally done in 267 Parkinson's disease patients and 270 controls, and this has been extended
to include genome wide genotyping in 939 Parkinson's disease cases and 802 controls. The NINDS repository was established in 10-2001 towards the goal of developing standardized, broadly useful diagnostic
and other clinical data and a collection of DNA and cell line samples to further advances in gene discovery of neurological
disorders. All samples, phenotypic, and genotypic data are available to the research community including to academics and
industry scientists. In addition, well characterized neurologically normal control subjects are a part of the collection.
This collection formed the basis of this first stage study by Fung et al., and the expanded study by Simon-Sanchez et al.
The genotyping data was generated and provided by the laboratory of Dr. Andrew Singleton NIA, and Dr. John Hardy
NIA (NIH Intramural, funding from NIA and NINDS). Important links to apply for individual-level data
PROVIDER: phs000089.v3.p2 | EGA |
REPOSITORIES: EGA
Publications
Genome-wide association study reveals genetic risk underlying Parkinson's disease.
Simón-Sánchez Javier J Schulte Claudia C Bras Jose M JM Sharma Manu M Gibbs J Raphael JR Berg Daniela D Paisan-Ruiz Coro C Lichtner Peter P Scholz Sonja W SW Hernandez Dena G DG Krüger Rejko R Federoff Monica M Klein Christine C Goate Alison A Perlmutter Joel J Bonin Michael M Nalls Michael A MA Illig Thomas T Gieger Christian C Houlden Henry H Steffens Michael M Okun Michael S MS Racette Brad A BA Cookson Mark R MR Foote Kelly D KD Fernandez Hubert H HH Traynor Bryan J BJ Schreiber Stefan S Arepalli Sampath S Zonozi Ryan R Gwinn Katrina K van der Brug Marcel M Lopez Grisel G Chanock Stephen J SJ Schatzkin Arthur A Park Yikyung Y Hollenbeck Albert A Gao Jianjun J Huang Xuemei X Wood Nick W NW Lorenz Delia D Deuschl Günther G Chen Honglei H Riess Olaf O Hardy John A JA Singleton Andrew B AB Gasser Thomas T
Nature genetics 20091115 12
We performed a genome-wide association study (GWAS) in 1,713 individuals of European ancestry with Parkinson's disease (PD) and 3,978 controls. After replication in 3,361 cases and 4,573 controls, we observed two strong association signals, one in the gene encoding alpha-synuclein (SNCA; rs2736990, OR = 1.23, P = 2.24 x 10(-16)) and another at the MAPT locus (rs393152, OR = 0.77, P = 1.95 x 10(-16)). We exchanged data with colleagues performing a GWAS in Japanese PD cases. Association to PD at S ...[more]
Similar Datasets
Project description:<p>This study utilized the well characterized collection of North American Caucasians with Parkinson's disease, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection. Two sub-studies are included, in sub-study NINDS-Genome-Wide Genotyping in Parkinson's Disease, genome-wide, single nucleotide polymorphism (SNP) genotyping of these publicly available samples was originally done in 267 Parkinson's disease patients and 270 controls, and this has been extended to include genome wide genotyping in 939 Parkinson's disease cases and 802 controls; in sub-study NINDS-Exome Sequencing in Parkinson's Disease, genome wide exome DNA sequencing was done in 618 Parkinson's disease samples deposited in Coriell NINDS repository. The DNA comes from a mixture of blood, and from cell lines (lymphoblast cell lines) derived from blood. The GWAS data and exome sequencing data was generated and provided by the laboratory of Neurogenetics lead by Dr. Andrew Singleton, NIA, and Dr. John Hardy, a former chief at NIA, NIH.</p> <p><b>The NINDS Parkinson's Disease Cohort study is utilized in the following dbGaP individual studies.</b> To view genotypes, whole exome sequencing, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page <a href="study.cgi?study_id=phs001172">phs001172</a> NINDS Parkinson's Disease Cohort study. <ul> <li><a href="study.cgi?study_id=phs000089">phs000089</a> PD GWAS</li> <li><a href="study.cgi?study_id=phs001103">phs001103</a> PD Exome</li> </ul> </p>
| phs001172 | dbGaP
Project description:<p>The NINDS repository <a href="http://ccr.coriell.org/ninds">(http://ccr.coriell.org/ninds/)</a> was established in October 2001 with the goal of developing standardized, broadly useful diagnostic and other clinical data, as well as a collection of DNA and cell line samples to further advance gene discovery of neurological disorders. All samples and both phenotypic and genotypic data are available to the research community including academic and industry scientists. A set of samples from individuals who do not have neurological disease was felt to be essential to allow gene discovery in neurological disorders to proceed. Towards this goal, the NINDS has and is collecting samples and phenotypic data on neurologically normal individuals. The data being collected includes demographic, ethnic, and exclusion of neurological disease information. Variables were measured using the <a href="javascript:getPage('document.cgi', 43);">Control Clinical Data Elements form</a>. As of June 2007, there are a total of 2157 publicly available and an additional >2000 which will be added to the publicly available biomaterials collection shortly.</p> <p>Blood samples were drawn from neurologically normal, unrelated, individuals at many different sites. Spouses, convenience controls, and population controls were all included in this collection. Each participant underwent a detailed medical history interview and had no family history on specific query of Alzheimer's disease, amyotrophic lateral sclerosis, ataxia, autism, bipolar disorder, brain aneurysm, dementia, dystonia, or Parkinson's disease. Folstein Mini-mental state examination scores ranged from 26-30 and are available on a subset of individuals. All participants were interviewed for family history in detail and specifically had no first degree relative with any of the following: amyotrophic lateral sclerosis, ataxia, autism, brain aneurysm, dystonia, Parkinson's disease, and schizophrenia. </p> <p>A subset of neurologically normal control subjects was utilized in <a href="./study.cgi?id=phs000089">NINDS Parkinson's Disease</a>, <a href="./study.cgi?id=phs000101">NINDS Amyotrophic Lateral Sclerosis and Controls</a> and <a href="./study.cgi?id=phs000102">NINDS Ischemic Stroke Genetics Study (ISGS)</a>.</p>
| phs000004.v1.p1 | EGA
Project description:<p>The NINDS repository was established in October 2001 with the goal of developing standardized, broadly useful diagnostic and other
clinical data, as well as a collection of DNA and cell line samples to further advance gene discovery of neurological disorders.
All samples and both phenotypic and genotypic data are available to the research community including academic and industry scientists.
This collection includes thousands of samples and associated phenotypic data sets from individuals with Parkinsonism, including Parkinson's
disease (PD).</p>
<p>Epidemiological studies have shown an estimated cumulative prevalence of PD of greater than 1 per thousand. When prevalence
is limited to senior populations, this proportion increases nearly 10-fold. The estimated genetic risk ratio for PD is approximately
1.7 (70% increased risk for PD if a sibling has PD) for all ages, and increases over 7-fold for those under age 66 years. The role
for genes contributing to the risk of PD is therefore significant.</p>
<p>A subset of subjects from the collection of North American Caucasians with Parkinson's disease was utilized in the
<a href="./study.cgi?id=phs000089">NINDS Parkinson's Disease </a> study.</p>
| phs000003.v1.p1 | EGA
Project description:<p>The third leading cause of death in the United States, stroke is an acute neurological event leading to death of neural tissues.
Although the majority of strokes are ischemic strokes, meaning there is oxygen deprivation to the brain, almost 20% of strokes are
hemorrhagic, resulting from bleeding into the brain. Stroke is a complex disorder and likely multigenic in nature, resulting from
a combination of genetic and environmental factors. These well characterized risk factors that contribute to the incidence of stroke
include hypertension, cardiac disease, sickle cell disease, hyperhomocysteinemia, family history of stroke and smoking.
</p>
<p>ISGS aim is to perform a prospective genetic association study of ischemic stroke focusing on the hemostatic system. ISGS
is a 5-center case-control study of first-ever ischemic stroke cases and concurrent controls individually matched for age,
sex and recruitment site.
</p>
<p>This data includes that from subjects both banked in the <a href="http://ccr.coriell.org/Sections/Collections/NINDS/?SsId=10">
NINDS repository</a> with biologicals publicly available, and those whose samples are not banked/not available.
</p>
<!-- <p><b>Important links to apply for individual-level data</b>
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<li><a href="http://dbgap.ncbi.nlm.nih.gov/aa/wga.cgi?view_pdf&stacc=phs000102.v1.p1" target="_blank">Data Use Certification Requirements (DUC)</a></li>
<li><a href="http://view.ncbi.nlm.nih.gov/dbgap-controlled" target="_blank">Apply here for controlled access to individual level data</a></li>
<li><a href="GetPdf.cgi?id=phd000582" target="_blank">Participant Protection Policy FAQ</a></li>
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<p>This study utilized the <a href="./study.cgi?id=phs000005">NINDS Repository Cerebrovascular/Stroke Study</a>,
and <a href="./study.cgi?id=phs000004">neurologically normal controls</a> from the sample population which are banked in the National
Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis.</p>
| phs000102.v1.p1 | EGA
Project description:<p>The third leading cause of death in the United States, stroke is an acute neurological event leading to death of neural tissues.
Although the majority of strokes are ischemic strokes, meaning there is oxygen deprivation to the brain, almost 20% of strokes are
hemorrhagic, resulting from bleeding into the brain. Stroke is a complex disorder and likely multigenic in nature, resulting from
a combination of genetic and environmental factors. These well characterized risk factors that contribute to the incidence of stroke
include hypertension, cardiac disease, sickle cell disease, hyperhomocysteinemia, family history of stroke and smoking.
</p>
<p>ISGS aim is to perform a prospective genetic association study of ischemic stroke focusing on the hemostatic system. ISGS
is a 5-center case-control study of first-ever ischemic stroke cases and concurrent controls individually matched for age,
sex and recruitment site.
</p>
<p>This data includes that from subjects both banked in the <a href="http://ccr.coriell.org/Sections/Collections/NINDS/?SsId=10">
NINDS repository</a> with biologicals publicly available, and those whose samples are not banked/not available.
</p>
<!-- <p><b>Important links to apply for individual-level data</b>
<ol>
<li><a href="http://dbgap.ncbi.nlm.nih.gov/aa/wga.cgi?view_pdf&stacc=phs000102.v1.p1" target="_blank">Data Use Certification Requirements (DUC)</a></li>
<li><a href="http://view.ncbi.nlm.nih.gov/dbgap-controlled" target="_blank">Apply here for controlled access to individual level data</a></li>
<li><a href="GetPdf.cgi?id=phd000582" target="_blank">Participant Protection Policy FAQ</a></li>
</ol>
</p> -->
<p>This study utilized the <a href="./study.cgi?id=phs000005">NINDS Repository Cerebrovascular/Stroke Study</a>,
and <a href="./study.cgi?id=phs000004">neurologically normal controls</a> from the sample population which are banked in the National
Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis.</p>
| phs000102 | dbGaP
Project description:Whole genome expression in Parkinson disease and neurologically healthy control prefrontal cortex Brodmann area 9 samples
2012-09-19 | E-MTAB-812 | biostudies-arrayexpress
Project description:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.
2016-01-15 | E-GEOD-68719 | biostudies-arrayexpress
Project description:<a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome" target="_blank">Explore This Study at the NCI Proteomic Data Commons</a><p>The goal of the CPTAC, TCGA Cancer Proteome Study of Colorectal Tissue is to analyze the proteomes of TCGA tumor samples that have been comprehensively characterized by molecular methods (<a href="http://www.ncbi.nlm.nih.gov/pubmed/22810696" target="_blank">Cancer Genome Atlas Network, Nature 2012</a>).</p><p>Ninety-five TCGA tumor samples were used in this study from 90 patients, with 5 samples representing different portions from the same tumor. The samples originated from two TCGA cohorts: 64 are from <a href="https://portal.gdc.cancer.gov/projects/TCGA-COAD" target="_blank">Colon Adenocarcinoma (COAD)</a> samples and 31 are from the <a href="https://portal.gdc.cancer.gov/projects/TCGA-READ" target="_blank">Rectum Adenocarcinoma (READ)</a> collection. The primary data from the liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic profiling of each tumor sample is associated with a data set in the table below. This work was accomplished by the Proteome Characterization Center (PCC) at Vanderbilt University led by Dr. Daniel C. Liebler. Clinical data files contain both the human readable TCGA bar codes and the UUIDs for each sample.</p><p>Complete Data Analysis from Vanderbilt University as published in Nature (Zhang, B., et al., Nature (2014) doi:10.1038/nature13438 Published online) is available <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S022">here</a>.</p><p>Data available on this study page (peptide spectrum matches and protein reports) are from the CPTAC Common Data Analysis Pipeline.</p><p>COAD tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-COAD%22%5D%7D%7D%5D%7D" target="_blank">here</a>.<br/>READ tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-READ%22%5D%7D%7D%5D%7D" target="_blank">here</a>.<br/><br/>Colon tissue samples (ascending and descending) were obtained from 30 patients. Each sample was analyzed with label free global proteomic profiling. These colon samples, while derived from colon cancer subjects, did not contain tumor. Samples were obtained from the <a href="http://www.vicc.org/jimayersinstitute" target="_blank">Jim Ayers Institute for Precancer Detection and Diagnosis.</a> Data sets below are labeled with the patient identification number and contain data for both ascending and descending tissue samples. Data from colon tumor samples are available in the <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016" target="_blank">TCGA Colorectal Cancer study</a>.</p><ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016">https://cptac-data-portal.georgetown.edu/cptac/s/S016</a> and <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S019">https://cptac-data-portal.georgetown.edu/cptac/s/S019</a> on 06/23/16</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome">https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome</a></li></ul>
2016-06-23 | MSV000079852 | MassIVE
Project description:<a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome" target="_blank">Explore This Study at the NCI Proteomic Data Commons</a><p><a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13438.html" target="_blank">Zhang, B., et al., Nature (2014) doi:10.1038/nature13438 Published online</a></p><p>Proteomes of colon and rectal tumors previously characterized by the Cancer Genome Atlas (TCGA) were analyzed along with integrated proteogenomic analyses. Ninety-five TCGA tumor samples were used in this study from 90 patients, with 5 samples representing different portions from the same tumor. The samples originated from two TCGA cohorts: 64 are from <a href="https://portal.gdc.cancer.gov/projects/TCGA-COAD" target="_blank">Colon Adenocarcinoma (COAD)</a> samples and 31 are from the <a href="https://portal.gdc.cancer.gov/projects/TCGA-READ" target="_blank">Rectum Adenocarcinoma (READ)</a> collection. The primary data from the liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic profiling of each tumor sample is associated with a data set in the table below. Three protein assemblies are provided from different protein database searches.</p><p>TCGA_VU_N95<br/>This assembly reflects the 95 TCGA samples for 90 tumors, spanning three search engines (MS-GF+, MyriMatch, and Pepitome), employing a standard RefSeq database and NIST spectral library.</p><p>TCGA_VU_N95_Custom<br/>The Custom assembly represents the same samples, the sequence database has been augmented with nonsynonymous sequence variants detected by TCGA.<br/></p><p>TCGA_VU_N95-Normal_VU_N60<br/>The third assembly contains the searches of the 95 TCGA samples employed in the first assembly alongside the 60 normal colons analyzed by Vanderbilt University as a control, employing the same three search engines, a standard RefSeq database, and a NIST spectral library.</p><p>TCGA_Colorectal_Cancer_proBAM_PSM_genome_mapping_files<br/>Peptide spectrum matches from the TCGA_VU_N95_Custom IDPicker3 protein assembly were converted to protein BAM (proBAM) format for visualization, available in the metadata folder below.</p><p>COAD tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-COAD%22%5D%7D%7D%5D%7D" target="_blank">here</a>.<br/>READ tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-READ%22%5D%7D%7D%5D%7D" target="_blank">here</a>.<br/></p><p>Normal colon epithelium sample mass spectrometry data can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S019" target="_blank">here</a>.<br/>Mass spectrometry data for comparison and reference (CompRef) sample standards run with this study can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S017" target="_blank">here</a>.<br/>Peptide-Spectrum-Matches and Protein Reports from the CPTAC Common Data Analysis Pipeline (CDAP) can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016" target="_blank">here</a>.<br/>Network analysis of this study can be viewed at the NetGestalt CRC Portal <a href="http://www.netgestalt.org/index.html" target="_blank">here</a>.<br/><br/>This work was accomplished by the Proteome Characterization Center (PCC) at Vanderbilt University led by Dr. Daniel C. Liebler.</p><ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S022">https://cptac-data-portal.georgetown.edu/cptac/s/S022</a> on 08/26/19</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome" target="_blank">https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome</a></li></ul>
2019-08-26 | MSV000084238 | MassIVE
Project description:<p>The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (<a href="http://ccr.coriell.org/Sections/Collections/NINDS/?SsId=10">the NINDS Repository</a>), banks phenotypic data and biological samples, including from individuals with motor neuron disease, in order to facilitate gene discovery in neurological disorders. Those samples are used in a number of studies, and genotyping data from studies using this resource are encouraged to be shared via dbGaP. Many studies have already shared data in this fashion, which in turn, can be linked back to the biologicals banked at the NINDS Repository. </p> <p>Motor Neuron Disease is characterized by selective degeneration of the motor neurons of the spinal cord, brainstem, or motor cortex. Clinical subtypes are distinguished by the major site of degeneration. In Amyotrophic Lateral Sclerosis (ALS), there is involvement of upper, lower, and brainstem motor neurons. In progressive muscular atrophy and related syndromes, the motor neurons in the spinal cord are primarily affected. With progressive bulbar palsy, the initial degeneration occurs in the brainstem. In primary lateral sclerosis, the cortical neurons are affected in isolation (Adams et al, Principles of Neurology, 6th ed, p 1089). The Motor Neuron Disease Collection of DNA and cell lines in the NINDS Repository is largely Amyotrophic Lateral Sclerosis cases (others include progressive muscular atrophy, primary lateral sclerosis, progressive bulbar palsy, Kennedy's disease). Amyotrophic lateral sclerosis (ALS) is the most common form of motor neuron disease (MND). Although ALS is the most common MND, it is still a relatively rare disease with an incidence of around 1.6 per 100,000 in the United States. It is currently incurable and treatment is largely limited to supportive care. Family history is associated with an increased risk of ALS, and many Mendelian causes have been discovered (including SOD1). However, most forms of the disease are not obviously familial. It is suspected that the sporadic forms of neurodegenerative disorders are caused by multiple genetic variants that individually make relatively weak contributions to risk. </p> <p>There is also an associated Control collection (see <a href="./study.cgi?study_id=phs000004.v1.p1">dbGaP</a> and <a href="http://ccr.coriell.org/Sections/Collections/NINDS/Population.aspx?PgId=194&coll=ND"> Coriell</a>). Studies in motor Neuron Disease may use cases from the NINDS repository, controls from the NINDS repository, as well as cases, and controls, from other sources. A subset of subjects from The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (the NINDS Repository): Motor Neuron/Amyotrophic Lateral Sclerosis (ALS) Study was utilized in the <a href="./study.cgi?id=phs000101">Genome-wide genotyping in amyotrophic lateral sclerosis and neurologically normal controls: first stage analysis and public release of data</a> study. </p> <p><b>Note: The publication <a href="http://www.ncbi.nlm.nih.gov/pubmed/19193627" target="_blank">Chio et al., 2009</a> states that "Raw sample-level genotype data from the initial GWAS study ... are available for download through the dbGAP portal (<a href="./study.cgi?id=phs000006" target="_blank">phs000006.v1.p1</a>)". Instead, please follow this link: <a href="./study.cgi?study_id=phs000101.v1.p1">phs000101.v1.p1</a>.</b></p>
| phs000006.v1.p1 | EGA