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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
TL;DR: A statistical tool that uses principal-component analysis (PCA) to normalize exome read depth and a hidden Markov model (HMM) to discover exon-resolution CNV and genotype variation across samples and shows that XHMM breakpoint quality scores enable researchers to explicitly search for novel classes of structural variation.
Abstract: Sequencing of gene-coding regions (the exome) is increasingly used for studying human disease, for which copy-number variants (CNVs) are a critical genetic component. However, detecting copynumber from exomesequencing is challenging because of the noncontiguous nature of the captured exons. This is compounded by the complex relationship between read depth and copynumber; this results from biases in targeted genomic hybridization, sequence factors such as GC content, and batching of samples during collection and sequencing. We present a statistical tool (exome hidden Markov model [XHMM]) that uses principal-component analysis (PCA) to normalize exome read depth and a hidden Markov model (HMM) to discover exon-resolution CNV and genotype variation across samples. We evaluate performance on 90 schizophrenia trios and 1,017 case-control samples. XHMM detects a median of two rare (<1%) CNVs per individual (one deletion and one duplication) and has 79% sensitivity to similarly rare CNVs overlapping three or more exons discovered with microarrays. With sensitivity similar to state-of-the-art methods, XHMM achieves higher specificity by assigning quality metrics to the CNV calls to filter out bad ones, as well as to statistically genotype the discovered CNV in all individuals, yielding a trio call set with Mendelian-inheritance properties highly consistent with expectation. We also show that XHMM breakpoint quality scores enable researchers to explicitly search for novel classes of structural variation. For example, we apply XHMM to extract those CNVs that are highly likely to disrupt (delete or duplicate) only a portion of a gene.

523 citations

Journal ArticleDOI
Patrick T. Ellinor, Kathryn L. Lunetta1, Christine M. Albert2, Christine M. Albert3, Nicole L. Glazer4, Marylyn D. Ritchie5, Albert V. Smith6, Dan E. Arking7, Martina Müller-Nurasyid8, Bouwe P. Krijthe9, Steven A. Lubitz3, Steven A. Lubitz2, Joshua C. Bis4, Mina K. Chung10, Mina K. Chung11, Marcus Dörr, Kouichi Ozaki, Jason D. Roberts12, J. Gustav Smith13, J. Gustav Smith14, Arne Pfeufer15, Moritz F. Sinner3, Moritz F. Sinner8, Moritz F. Sinner1, Kurt Lohman16, Jingzhong Ding16, Nicholas L. Smith, Jonathan D. Smith11, Jonathan D. Smith10, Michiel Rienstra, Kenneth Rice4, David R. Van Wagoner10, David R. Van Wagoner11, Jared W. Magnani1, Reza Wakili8, Sebastian Clauss8, Jerome I. Rotter17, Gerhard Steinbeck8, Lenore J. Launer18, Robert W. Davies12, Matthew Borkovich12, Tamara B. Harris18, Honghuang Lin1, Uwe Völker, Henry Völzke, David J. Milan3, Albert Hofman9, Eric Boerwinkle19, Lin Y. Chen20, Elsayed Z. Soliman16, Benjamin F. Voight14, Guo Li4, Aravinda Chakravarti7, Michiaki Kubo, Usha B. Tedrow3, Usha B. Tedrow2, Lynda M. Rose2, Paul M. Ridker3, Paul M. Ridker2, David Conen21, Tatsuhiko Tsunoda, Tetsushi Furukawa22, Nona Sotoodehnia4, Siyan Xu1, Naoyuki Kamatani, Daniel Levy1, Yusuke Nakamura23, Babar Parvez24, Saagar Mahida3, Karen L. Furie3, Jonathan Rosand3, Raafia Muhammad24, Bruce M. Psaty, Thomas Meitinger15, Siegfried Perz, H-Erich Wichmann8, Jacqueline C.M. Witteman9, W. H. Linda Kao25, Sekar Kathiresan14, Sekar Kathiresan3, Dan M. Roden24, André G. Uitterlinden9, Fernando Rivadeneira9, Barbara McKnight4, Marketa Sjögren13, Anne B. Newman26, Yongmei Liu16, Michael H. Gollob12, Olle Melander13, Toshihiro Tanaka, Bruno H. Stricker, Stephan B. Felix, Alvaro Alonso20, Dawood Darbar24, John Barnard11, Daniel I. Chasman3, Daniel I. Chasman2, Susan R. Heckbert27, Susan R. Heckbert4, Emelia J. Benjamin, Vilmundur Gudnason6, Stefan Kääb8 
TL;DR: Six new atrial fibrillation susceptibility loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules that are associated with stroke, heart failure and death.
Abstract: Atrial fibrillation is a highly prevalent arrhythmia and a major risk factor for stroke, heart failure and death. We conducted a genome-wide association study (GWAS) in individuals of European ancestry, including 6,707 with and 52,426 without atrial fibrillation. Six new atrial fibrillation susceptibility loci were identified and replicated in an additional sample of individuals of European ancestry, including 5,381 subjects with and 10,030 subjects without atrial fibrillation (P < 5 × 10(-8)). Four of the loci identified in Europeans were further replicated in silico in a GWAS of Japanese individuals, including 843 individuals with and 3,350 individuals without atrial fibrillation. The identified loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules.

523 citations

Journal ArticleDOI
TL;DR: In an effort to ensure that high-quality, significant data are entering the proteomics literature, Molecular & Cellular Proteomics (MCP) is introducing guidelines for authors planning to submit manuscripts containing large numbers of proteins identified primarily by LC-MS/MS.

522 citations

Journal ArticleDOI
Ron Do1, Ron Do2, Nathan O. Stitziel3, Hong-Hee Won2, Hong-Hee Won1, Anders Berg Jørgensen4, Stefano Duga5, Pier Angelica Merlini, Adam Kiezun2, Martin Farrall6, Anuj Goel6, Or Zuk2, Illaria Guella5, Rosanna Asselta5, Leslie A. Lange7, Gina M. Peloso1, Gina M. Peloso2, Paul L. Auer8, Domenico Girelli9, Nicola Martinelli9, Deborah N. Farlow2, Mark A. DePristo2, Robert Roberts10, Alex Stewart10, Danish Saleheen11, John Danesh11, Stephen E. Epstein12, Suthesh Sivapalaratnam13, G. Kees Hovingh13, John J.P. Kastelein13, Nilesh J. Samani14, Heribert Schunkert15, Jeanette Erdmann16, Svati H. Shah17, William E. Kraus17, Robert W. Davies10, Majid Nikpay10, Christopher T. Johansen18, Jian Wang18, Robert A. Hegele18, Eliana Hechter2, Winfried März19, Winfried März20, Winfried März21, Marcus E. Kleber21, Jie Huang, Andrew D. Johnson22, Mingyao Li23, Greg L. Burke24, Myron D. Gross25, Yongmei Liu26, Themistocles L. Assimes27, Gerardo Heiss7, Ethan M. Lange7, Aaron R. Folsom25, Herman A. Taylor28, Oliviero Olivieri9, Anders Hamsten29, Robert Clarke6, Dermot F. Reilly30, Wu Yin30, Manuel A. Rivas6, Peter Donnelly6, Jacques E. Rossouw22, Bruce M. Psaty31, Bruce M. Psaty32, David M. Herrington26, James G. Wilson28, Stephen S. Rich33, Michael J. Bamshad31, Russell P. Tracy34, L. Adrienne Cupples35, Daniel J. Rader23, Muredach P. Reilly23, John A. Spertus36, Sharon Cresci3, Jaana Hartiala37, W.H. Wilson Tang38, Stanley L. Hazen38, Hooman Allayee37, Alexander P. Reiner8, Alexander P. Reiner31, Christopher S. Carlson8, Charles Kooperberg8, Rebecca D. Jackson39, Eric Boerwinkle40, Eric S. Lander2, Stephen M. Schwartz8, Stephen M. Schwartz31, David S. Siscovick31, Ruth McPherson10, Anne Tybjærg-Hansen4, Gonçalo R. Abecasis41, Hugh Watkins6, Deborah A. Nickerson31, Diego Ardissino, Shamil R. Sunyaev1, Shamil R. Sunyaev2, Christopher J. O'Donnell, David Altshuler2, David Altshuler1, Stacey Gabriel2, Sekar Kathiresan2, Sekar Kathiresan1 
05 Feb 2015-Nature
TL;DR: Kathiresan et al. as mentioned in this paper used exome sequencing of nearly 10,000 people to identify alleles associated with early-onset myocardial infarction; mutations in low-density lipoprotein receptor (LDLR) or apolipoprotein A-V (APOA5) were associated with disease risk.
Abstract: Exome sequence analysis of nearly 10,000 people was carried out to identify alleles associated with early-onset myocardial infarction; mutations in low-density lipoprotein receptor (LDLR) or apolipoprotein A-V (APOA5) were associated with disease risk, identifying the key roles of low-density lipoprotein cholesterol and metabolism of triglyceride-rich lipoproteins. Sekar Kathiresan and colleagues use exome sequencing of nearly 10,000 people to probe the contribution of multiple rare mutations within a gene to risk for myocardial infarction at a population level. They find that mutations in low-density lipoprotein receptor (LDLR) or apolipoprotein A-V (APOA5) are associated with disease risk. When compared with non-carriers, LDLR mutation carriers had higher plasma levels of LDL cholesterol, whereas APOA5 mutation carriers had higher plasma levels of triglycerides. As well as confirming that APOA5 is a myocardial infarction gene, this work informs the design and conduct of rare-variant association studies for complex diseases. Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance1,2. When MI occurs early in life, genetic inheritance is a major component to risk1. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families3,4,5,6,7,8, whereas common variants at more than 45 loci have been associated with MI risk in the population9,10,11,12,13,14,15. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol16. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl−1. At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase15,17 and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.

521 citations

Journal ArticleDOI
03 Mar 2016-Nature
TL;DR: It is shown that high-fat diet (HFD)-induced obesity augments the numbers and function of Lgr5+ intestinal stem cells of the mammalian intestine and highlights how diet-modulated PPAR-δ activation alters not only the function of intestinal stem and progenitor cells, but also their capacity to initiate tumours.
Abstract: Little is known about how pro-obesity diets regulate tissue stem and progenitor cell function. Here we show that high-fat diet (HFD)-induced obesity augments the numbers and function of Lgr5(+) intestinal stem cells of the mammalian intestine. Mechanistically, a HFD induces a robust peroxisome proliferator-activated receptor delta (PPAR-δ) signature in intestinal stem cells and progenitor cells (non-intestinal stem cells), and pharmacological activation of PPAR-δ recapitulates the effects of a HFD on these cells. Like a HFD, ex vivo treatment of intestinal organoid cultures with fatty acid constituents of the HFD enhances the self-renewal potential of these organoid bodies in a PPAR-δ-dependent manner. Notably, HFD- and agonist-activated PPAR-δ signalling endow organoid-initiating capacity to progenitors, and enforced PPAR-δ signalling permits these progenitors to form in vivo tumours after loss of the tumour suppressor Apc. These findings highlight how diet-modulated PPAR-δ activation alters not only the function of intestinal stem and progenitor cells, but also their capacity to initiate tumours.

521 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