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Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing
Mark Daly, Richard Gibbs, Joseph Buxbaum, Gerard Schellenberg and James Sutcliffe 
ARRA Autism Sequencing Collaboration
NDAR
Closed
Shared
$14,982,039.00
2,103
0
0
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NIH - Extramural None

https://software.broadinstitute.org/gatk/ Software Genome Analysis Toolkit Qualified Researchers
http://picard.sourceforge.net/ Software Picard Qualified Researchers
http://samtools.sourceforge.net/ Software SAM Tools Qualified Researchers

R01MH089208-01 2/5-Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing 09/30/2009 08/31/2011 Not Reported Not Reported BROAD INSTITUTE, INC. $4,165,764.00
R01MH089175-01 1/5: Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing 09/30/2009 08/31/2011 Not Reported Not Reported BAYLOR COLLEGE OF MEDICINE $2,998,515.00
R01MH089482-01 5/5 - Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing 09/30/2009 08/31/2011 Not Reported Not Reported VANDERBILT UNIVERSITY $5,196,989.00
R01MH089004-01 4/5-Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing 09/30/2009 08/31/2011 Not Reported Not Reported UNIVERSITY OF PENNSYLVANIA $1,208,739.00
R01MH089025-01 3/5-Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing 09/30/2009 08/31/2011 Not Reported Not Reported ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI $1,412,032.00

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Shared Data

Data structures with the number of subjects submitted and shared are provided.

Autism Diagnostic Interview - Cumulative Clinical Assessments 435
Autism Diagnostic Observation Schedule (ADOS) - Module 4 Clinical Assessments 9
Autism Diagnostic Observation Schedule (ADOS)- Module 1 Clinical Assessments 154
Autism Diagnostic Observation Schedule (ADOS)- Module 2 Clinical Assessments 68
Autism Diagnostic Observation Schedule (ADOS)- Module 3 Clinical Assessments 110
CPEA STAART PPVT SUMMARY 2004 Clinical Assessments 322
Genomics Sample Genomics 2094
Genomics Subject Genomics 2097
Ravens Coloured Progressive Matrices (CPM) Clinical Assessments 322
Stanford-Binet Intelligence Scales, Fifth Edition (SB5) Clinical Assessments 18

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Publications

Publications relevant to NDAR data are listed below. Most displayed publications have been associated with the grant within Pubmed. Use the "+ New Publication" button to add new publications. Publications relevant/not relevant to data expected are categorized. Relevant publications are then linked to the underlying data by selecting the Create Study link. Study provides the ability to define cohorts, assign subjects, define outcome measures and lists the study type, data analysis and results. Analyzed data and results are expected in this way.

PubMed IDStudyTitleJournalAuthorsDateStatus
26439716Create StudyInterpreting de novo Variation in Human Disease Using denovolyzeR.Current protocols in human genetics / editorial board, Jonathan L. Haines ... [et al.]Ware JS, Samocha KE, Homsy J, Daly MJ2015Not Determined
25363760Create StudySynaptic, transcriptional and chromatin genes disrupted in autism.NatureDe Rubeis S, He X, Goldberg AP, Poultney CS, Samocha K, Cicek AE, Kou Y, Liu L, Fromer M, Walker S, Singh T, Klei L, Kosmicki J, Shih-Chen F, Aleksic B, Biscaldi M, Bolton PF, Brownfeld JM, Cai J, Campbell NG, Carracedo A, Chahrour MH, Chiocchetti AG, Coon H, Crawford EL, et al.November 13, 2014Not Relevant
25270638Create StudyConsensus Genotyper for Exome Sequencing (CGES): improving the quality of exome variant genotypes.Bioinformatics (Oxford, England)Trubetskoy V, Rodriguez A, Dave U, Campbell N, Crawford EL, Cook EH, Sutcliffe JS, Foster I, Madduri R, Cox NJ, Davis LKJanuary 15, 2015Not Relevant
25086666Create StudyA framework for the interpretation of de novo mutation in human disease.Nature geneticsSamocha KE, Robinson EB, Sanders SJ, Stevens C, Sabo A, McGrath LM, Kosmicki JA, Rehnström K, Mallick S, Kirby A, Wall DP, MacArthur DG, Gabriel SB, DePristo M, Purcell SM, Palotie A, Boerwinkle E, Buxbaum JD, Cook EH, Gibbs RA, Schellenberg GD, Sutcliffe JS, Devlin B, Roeder K, Neale BM, et al.September 2014Not Determined
24094742Create StudyIdentification of small exonic CNV from whole-exome sequence data and application to autism spectrum disorder.American journal of human geneticsPoultney CS, Goldberg AP, Drapeau E, Kou Y, Harony-Nicolas H, Kajiwara Y, De Rubeis S, Durand S, Stevens C, Rehnström K, Palotie A, Daly MJ, Ma'ayan A, Fromer M, Buxbaum JDOctober 3, 2013Not Relevant
23979605Create StudyDe novo mutation in the dopamine transporter gene associates dopamine dysfunction with autism spectrum disorder.Molecular psychiatryHamilton PJ, Campbell NG, Sharma S, Erreger K, Herborg Hansen F, Saunders C, Belovich AN, , Sahai MA, Cook EH, Gether U, McHaourab HS, Matthies HJ, Sutcliffe JS, Galli ADaly MJGibbs RABoerwinkle EBuxbaum JDCook EHDevlin BLim ETNeale BMRoeder KSabo ASchellenberg GDStevens CSutcliffe JSDecember 2013Not Determined
23966865Create StudyIntegrated model of de novo and inherited genetic variants yields greater power to identify risk genes.PLoS geneticsHe X, Sanders SJ, Liu L, De Rubeis S, Lim ET, Sutcliffe JS, Schellenberg GD, Gibbs RA, Daly MJ, Buxbaum JD, State MW, Devlin B, Roeder K2013Not Determined
23943636Create StudyDRAW+SneakPeek: analysis workflow and quality metric management for DNA-seq experiments.Bioinformatics (Oxford, England)Lin CF, Valladares O, Childress DM, Klevak E, Geller ET, Hwang YC, Tsai EA, Schellenberg GD, Wang LSOctober 1, 2013Not Determined
23743231Create StudyWhole exome sequencing reveals minimal differences between cell line and whole blood derived DNA.GenomicsSchafer CM, Campbell NG, Cai G, Yu F, Makarov V, Yoon S, Daly MJ, Gibbs RA, Schellenberg GD, Devlin B, Sutcliffe JS, Buxbaum JD, Roeder KOctober 2013Not Determined
23684009Create StudySequence kernel association tests for the combined effect of rare and common variants.American journal of human geneticsIonita-Laza I, Lee S, Makarov V, Buxbaum JD, Lin XJune 6, 2013Not Determined
23593035Create StudyAnalysis of rare, exonic variation amongst subjects with autism spectrum disorders and population controls.PLoS geneticsLiu L, Sabo A, Neale BM, Nagaswamy U, Stevens C, Lim E, Bodea CA, Muzny D, Reid JG, Banks E, Coon H, Depristo M, Dinh H, Fennel T, Flannick J, Gabriel S, Garimella K, Gross S, Hawes A, Lewis L, Makarov V, Maguire J, Newsham I, Poplin R, Ripke S, et al.April 2013Not Relevant
23386037Create StudyFamily-based association tests for sequence data, and comparisons with population-based association tests.European journal of human genetics : EJHGIonita-Laza I, Lee S, Makarov V, Buxbaum JD, Lin XOctober 2013Not Relevant
23352160Create StudyRare complete knockouts in humans: population distribution and significant role in autism spectrum disorders.NeuronLim ET, Raychaudhuri S, Sanders SJ, Stevens C, Sabo A, MacArthur DG, Neale BM, Kirby A, Ruderfer DM, Fromer M, Lek M, Liu L, Flannick J, Ripke S, Nagaswamy U, Muzny D, Reid JG, Hawes A, Newsham I, Wu Y, Lewis L, Dinh H, Gross S, Wang LS, Lin CF, et al.January 23, 2013Not Relevant
23216583Create StudyCharacterizing polymorphisms and allelic diversity of von Willebrand factor gene in the 1000 Genomes.Journal of thrombosis and haemostasis : JTHWang QY, Song J, Gibbs RA, Boerwinkle E, Dong JF, Yu FLFebruary 2013Not Relevant
22843986Create StudyzCall: a rare variant caller for array-based genotyping: genetics and population analysis.Bioinformatics (Oxford, England)Goldstein JI, Crenshaw A, Carey J, Grant GB, Maguire J, Fromer M, O'Dushlaine C, Moran JL, Chambert K, Stevens C, , , Sklar P, Hultman CM, Purcell S, McCarroll SA, Sullivan PF, Daly MJ, Neale BMOctober 1, 2012Not Relevant
22641211Create StudyExome sequencing and the genetic basis of complex traits.Nature geneticsKiezun A, Garimella K, Do R, Stitziel NO, Neale BM, McLaren PJ, Gupta N, Sklar P, Sullivan PF, Moran JL, Hultman CM, Lichtenstein P, Magnusson P, Lehner T, Shugart YY, Price AL, de Bakker PI, Purcell SM, Sunyaev SRJune 2012Not Relevant
22610117Create StudyExtremely low-coverage sequencing and imputation increases power for genome-wide association studies.Nature geneticsPasaniuc B, Rohland N, McLaren PJ, Garimella K, Zaitlen N, Li H, Gupta N, Neale BM, Daly MJ, Sklar P, Sullivan PF, Bergen S, Moran JL, Hultman CM, Lichtenstein P, Magnusson P, Purcell SM, Haas DW, Liang L, Sunyaev S, Patterson N, de Bakker PI, Reich D, Price ALJune 2012Not Relevant
22578327Create StudyScan-statistic approach identifies clusters of rare disease variants in LRP2, a gene linked and associated with autism spectrum disorders, in three datasets.American journal of human geneticsIonita-Laza I, Makarov V, , Buxbaum JDBoerwinkle EBuxbaum JDCook EHDaly MJDevlin BGibbs RRoeder KSabo ASchellenberg GDSutcliffe JSJune 8, 2012Not Relevant
22511880Study (293)Whole-exome sequencing and homozygosity analysis implicate depolarization-regulated neuronal genes in autism.PLoS geneticsChahrour MH, Yu TW, Lim ET, Ataman B, Coulter ME, Hill RS, Stevens CR, Schubert CR, , Greenberg ME, Gabriel SB, Walsh CA2012Relevant
22499558Create StudyNetwork- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability.American journal of medical genetics. Part C, Seminars in medical geneticsKou Y, Betancur C, Xu H, Buxbaum JD, Ma'ayan AMay 15, 2012Not Relevant
22495311Study (317)Patterns and rates of exonic de novo mutations in autism spectrum disorders.NatureNeale BM, Kou Y, Liu L, Ma'ayan A, Samocha KE, Sabo A, Lin CF, Stevens C, Wang LS, Makarov V, Polak P, Yoon S, Maguire J, Crawford EL, Campbell NG, Geller ET, Valladares O, Schafer C, Liu H, Zhao T, Cai G, Lihm J, Dannenfelser R, Jabado O, Peralta Z, et al.May 10, 2012Relevant
22257670Create StudyAnnTools: a comprehensive and versatile annotation toolkit for genomic variants.Bioinformatics (Oxford, England)Makarov V, O'Grady T, Cai G, Lihm J, Buxbaum JD, Yoon SMarch 1, 2012Not Relevant
22137099Create StudyFinding disease variants in Mendelian disorders by using sequence data: methods and applications.American journal of human geneticsIonita-Laza I, Makarov V, Yoon S, Raby B, Buxbaum J, Nicolae DL, Lin XDecember 9, 2011Not Relevant
21408211Create StudyTesting for an unusual distribution of rare variants.PLoS geneticsNeale BM, Rivas MA, Voight BF, Altshuler D, Devlin B, Orho-Melander M, Kathiresan S, Purcell SM, Roeder K, Daly MJMarch 2011Not Relevant
20876472Create StudyA comprehensive analysis of deletions, multiplications, and copy number variations in PARK2.NeurologyKay DM, Stevens CF, Hamza TH, Montimurro JS, Zabetian CP, Factor SA, Samii A, Griffith A, Roberts JW, Molho ES, Higgins DS, Gancher S, Moses L, Zareparsi S, Poorkaj P, Bird T, Nutt J, Schellenberg GD, Payami HSeptember 28, 2010Not Relevant
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Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
No records found.
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Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
genomics/omics info iconApproved
Structure not yet defined

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Associated Studies

Studies that have been defined using data from a Collection are important criteria to determine the value of data shared. The number of subjects column displays the counts from this Collection that are included in a Study, out of the total number of subjects in that study. The Data Use column represents whether or not the study is a primary analysis of the data or a secondary analysis. State indicates whether the study is private or shared with the research community.

Study Name Description Number of Subjects
Collection / Total
Data Use State
Elucidating the Genetic Architecture of Autism by Deep Genomic Sequencing ARRA Autism Sequencing Collaboration The VCF files provided as Study Results for this study are what was provided at the time the study was created and consist of the Autism Only consent group. There is an additional General Research Use cohort, but those data are not provided here in this study. To obtain data from the General Research Use cohort please visit the dbGaP Study phs000298. It should be noted that the dbGaP study has been updated since the time this study was created, and the update includes genomics data on additional subjects. http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000298.v2.p2 2095 / 2095 Primary Analysis Shared
Rare Inherited and De Novo CNVs Reveal Complex Contributions to ASD Risk in Multiplex families NOTE: NOT ALL DATA HAS BEEN UPLOADED FOR THIS STUDY. Rare mutations, including copy-number variants (CNVs), contribute significantly to autism spectrum disorder (ASD) risk. Although their importance has been established in families with only one affected child (simplex families), the contribution of both de novo and inherited CNVs to ASD in families with multiple affected individuals (multiplex families) is less well understood. We analyzed 1,532 families from the Autism Genetic Resource Exchange (AGRE) to assess the impact of de novo and rare CNVs on ASD risk in multiplex families. We observed a higher burden of large, rare CNVs, including inherited events, in individuals with ASD than in their unaffected siblings (odds ratio [OR] = 1.7), but the rate of de novo events was significantly lower than in simplex families. In previously characterized ASD risk loci, we identified 49 CNVs, comprising 24 inherited events, 19 de novo events, and 6 events of unknown inheritance, a significant enrichment in affected versus control individuals (OR = 3.3). In 21 of the 30 families (71%) in whom at least one affected sibling harbored an established ASD major risk CNV, including five families harboring inherited CNVs, the CNV was not shared by all affected siblings, indicating that other risk factors are contributing. We also identified a rare risk locus for ASD and language delay at chromosomal region 2q24 (implicating NR4A2) and another lower-penetrance locus involving inherited deletions and duplications of WWOX. The genetic architecture in multiplex families differs from that in simplex families and is complex, warranting more complete genetic characterization of larger multiplex ASD cohorts. 296 / 5288 Primary Analysis Shared
Patterns and rates of exonic de novo mutations in autism spectrum disorders. Notes: Data submitted to NDAR did not include interview age. Publication Abstract: Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors. 104 / 104 Primary Analysis Shared
Germline Mutations in Predisposition Genes in Pediatric Cancer Background The prevalence and spectrum of predisposing mutations among children and adolescents with cancer are largely unknown. Knowledge of such mutations may improve the understanding of tumorigenesis, direct patient care, and enable genetic counseling of patients and families. Methods In 1120 patients younger than 20 years of age, we sequenced the whole genomes (in 595 patients), whole exomes (in 456), or both (in 69). We analyzed the DNA sequences of 565 genes, including 60 that have been associated with autosomal dominant cancer-predisposition syndromes, for the presence of germline mutations. The pathogenicity of the mutations was determined by a panel of medical experts with the use of cancer-specific and locus-specific genetic databases, the medical literature, computational predictions, and second hits identified in the tumor genome. The same approach was used to analyze data from 966 persons who did not have known cancer in the 1000 Genomes Project, and a similar approach was used to analyze data from an autism study (from 515 persons with autism and 208 persons without autism). Results Mutations that were deemed to be pathogenic or probably pathogenic were identified in 95 patients with cancer (8.5%), as compared with 1.1% of the persons in the 1000 Genomes Project and 0.6% of the participants in the autism study. The most commonly mutated genes in the affected patients were TP53 (in 50 patients), APC (in 6), BRCA2 (in 6), NF1 (in 4), PMS2 (in 4), RB1 (in 3), and RUNX1 (in 3). A total of 18 additional patients had protein-truncating mutations in tumor-suppressor genes. Of the 58 patients with a predisposing mutation and available information on family history, 23 (40%) had a family history of cancer. Conclusions Germline mutations in cancer-predisposing genes were identified in 8.5% of the children and adolescents with cancer. Family history did not predict the presence of an underlying predisposition syndrome in most patients. 723 / 723 Secondary Analysis Shared
No Evidence for Association of Autism with Rare Heterozygous Point Mutations in Contactin-Associated Protein-Like 2 (CNTNAP2), or in Other Contactin-Associated Proteins or Contactins Contactins and Contactin-Associated Proteins, and Contactin-Associated Protein-Like 2 (CNTNAP2) in particular, have been widely cited as autism risk genes based on findings from homozygosity mapping, molecular cytogenetics, copy number variation analyses, and both common and rare single nucleotide association studies. However, data specifically with regard to the contribution of heterozygous single nucleotide variants (SNVs) have been inconsistent. In an effort to clarify the role of rare point mutations in CNTNAP2 and related gene families, we have conducted targeted next-generation sequencing and evaluated existing sequence data in cohorts totaling 2704 cases and 2747 controls. We find no evidence for statistically significant association of rare heterozygous mutations in any of the CNTN or CNTNAP genes, including CNTNAP2, placing marked limits on the scale of their plausible contribution to risk. 2094 / 4118 Primary Analysis Shared
* Data not on individual level
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