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Institution

Broad Institute

NonprofitCambridge, Massachusetts, United States
About: Broad Institute is a nonprofit organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 6584 authors who have published 11618 publications receiving 1522743 citations. The organization is also known as: Eli and Edythe L. Broad Institute of MIT and Harvard.


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Journal ArticleDOI
Ditte Demontis1, Ditte Demontis2, Raymond K. Walters3, Raymond K. Walters4, Joanna Martin5, Joanna Martin6, Joanna Martin3, Manuel Mattheisen, Thomas Damm Als1, Thomas Damm Als2, Esben Agerbo1, Esben Agerbo2, Gisli Baldursson, Rich Belliveau3, Jonas Bybjerg-Grauholm7, Jonas Bybjerg-Grauholm1, Marie Bækvad-Hansen7, Marie Bækvad-Hansen1, Felecia Cerrato3, Kimberly Chambert3, Claire Churchhouse4, Claire Churchhouse3, Ashley Dumont3, Nicholas Eriksson, Michael J. Gandal, Jacqueline I. Goldstein3, Jacqueline I. Goldstein4, Katrina L. Grasby8, Jakob Grove, Olafur O Gudmundsson9, Olafur O Gudmundsson10, Christine Søholm Hansen11, Christine Søholm Hansen1, Christine Søholm Hansen7, Mads E. Hauberg2, Mads E. Hauberg1, Mads V. Hollegaard1, Mads V. Hollegaard7, Daniel P. Howrigan3, Daniel P. Howrigan4, Hailiang Huang4, Hailiang Huang3, Julian Maller3, Alicia R. Martin4, Alicia R. Martin3, Nicholas G. Martin8, Jennifer L. Moran3, Jonatan Pallesen1, Jonatan Pallesen2, Duncan S. Palmer4, Duncan S. Palmer3, Carsten Bøcker Pedersen1, Carsten Bøcker Pedersen2, Marianne Giørtz Pedersen2, Marianne Giørtz Pedersen1, Timothy Poterba3, Timothy Poterba4, Jesper Buchhave Poulsen7, Jesper Buchhave Poulsen1, Stephan Ripke3, Stephan Ripke12, Stephan Ripke4, Elise B. Robinson4, F. Kyle Satterstrom3, F. Kyle Satterstrom4, Hreinn Stefansson9, Christine Stevens3, Patrick Turley3, Patrick Turley4, G. Bragi Walters10, G. Bragi Walters9, Hyejung Won13, Hyejung Won14, Margaret J. Wright15, Ole A. Andreassen16, Philip Asherson17, Christie L. Burton18, Dorret I. Boomsma19, Bru Cormand, Søren Dalsgaard2, Barbara Franke20, Joel Gelernter21, Joel Gelernter22, Daniel H. Geschwind14, Daniel H. Geschwind13, Hakon Hakonarson23, Jan Haavik24, Jan Haavik25, Henry R. Kranzler26, Henry R. Kranzler21, Jonna Kuntsi17, Kate Langley5, Klaus-Peter Lesch27, Klaus-Peter Lesch28, Klaus-Peter Lesch29, Christel M. Middeldorp19, Christel M. Middeldorp15, Andreas Reif30, Luis Augusto Rohde31, Panos Roussos, Russell Schachar18, Pamela Sklar32, Edmund J.S. Sonuga-Barke17, Patrick F. Sullivan6, Patrick F. Sullivan33, Anita Thapar5, Joyce Y. Tung, Irwin D. Waldman34, Sarah E. Medland8, Kari Stefansson10, Kari Stefansson9, Merete Nordentoft1, Merete Nordentoft35, David M. Hougaard1, David M. Hougaard7, Thomas Werge35, Thomas Werge11, Thomas Werge1, Ole Mors36, Ole Mors1, Preben Bo Mortensen, Mark J. Daly, Stephen V. Faraone37, Anders D. Børglum2, Anders D. Børglum1, Benjamin M. Neale4, Benjamin M. Neale3 
TL;DR: A genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls identifies variants surpassing genome- wide significance in 12 independent loci and implicates neurodevelopmental pathways and conserved regions of the genome as being involved in underlying ADHD biology.
Abstract: Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

1,436 citations

Journal ArticleDOI
TL;DR: Coexpression of EGFRvIII and PTEN by glioblastoma cells is associated with responsiveness to EGFR kinase inhibitors, and effects of the molecular abnormalities in vitro are identified.
Abstract: Background The epidermal growth factor receptor (EGFR) is frequently amplified, overexpressed, or mutated in glioblastomas, but only 10 to 20 percent of patients have a response to EGFR kinase inhibitors. The mechanism of responsiveness of glioblastomas to these inhibitors is unknown. Methods We sequenced kinase domains in the EGFR and human EGFR type 2 (Her2/neu) genes and analyzed the expression of EGFR, EGFR deletion mutant variant III (EGFRvIII), and the tumor-suppressor protein PTEN in recurrent malignant gliomas from patients who had received EGFR kinase inhibitors. We determined the molecular correlates of clinical response, validated them in an independent data set, and identified effects of the molecular abnormalities in vitro. Results Of 49 patients with recurrent malignant glioma who were treated with EGFR kinase inhibitors, 9 had tumor shrinkage of at least 25 percent. Pretreatment tissue was available for molecular analysis from 26 patients, 7 of whom had had a response and 19 of whom had rap...

1,433 citations

Journal ArticleDOI
TL;DR: In this paper, the authors performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data.
Abstract: Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ~1,700 transcriptional interactions at a precision of ~50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.

1,424 citations

Journal ArticleDOI
07 Nov 2008-Science
TL;DR: The intellectual foundations of genetic mapping of Mendelian and complex traits in humans are discussed, lessons emerging from linkage analysis of MendELian diseases and genome-wide association studies of common diseases are examined, and questions and challenges that lie ahead are discussed.
Abstract: Genetic mapping provides a powerful approach to identify genes and biological processes underlying any trait influenced by inheritance, including human diseases We discuss the intellectual foundations of genetic mapping of Mendelian and complex traits in humans, examine lessons emerging from linkage analysis of Mendelian diseases and genome-wide association studies of common diseases, and discuss questions and challenges that lie ahead

1,421 citations


Authors

Showing all 7146 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Albert Hofman2672530321405
Frank B. Hu2501675253464
David J. Hunter2131836207050
Kari Stefansson206794174819
Mark J. Daly204763304452
Lewis C. Cantley196748169037
Matthew Meyerson194553243726
Gad Getz189520247560
Stacey Gabriel187383294284
Stuart H. Orkin186715112182
Ralph Weissleder1841160142508
Chris Sander178713233287
Michael I. Jordan1761016216204
Richard A. Young173520126642
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202337
2022627
20211,727
20201,534
20191,364
20181,107