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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.


Papers
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Journal ArticleDOI
Cristen J. Willer1, Ellen M. Schmidt1, Sebanti Sengupta1, Gina M. Peloso2  +316 moreInstitutions (87)
TL;DR: It is found that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index.
Abstract: Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

2,585 citations

Journal ArticleDOI
23 Jul 2004-Science
TL;DR: It is shown that large-scale copy number polymorphisms (CNPs) (about 100 kilobases and greater) contribute substantially to genomic variation between normal humans.
Abstract: The extent to which large duplications and deletions contribute to human genetic variation and diversity is unknown. Here, we show that large-scale copy number polymorphisms (CNPs) (about 100 kilobases and greater) contribute substantially to genomic variation between normal humans. Representational oligonucleotide microarray analysis of 20 individuals revealed a total of 221 copy number differences representing 76 unique CNPs. On average, individuals differed by 11 CNPs, and the average length of a CNP interval was 465 kilobases. We observed copy number variation of 70 different genes within CNP intervals, including genes involved in neurological function, regulation of cell growth, regulation of metabolism, and several genes known to be associated with disease.

2,572 citations

Journal ArticleDOI
23 Jan 2014-Nature
TL;DR: It is found that large-scale genomic analysis can identify nearly all known cancer genes in these cancer types and 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis.
Abstract: Although a few cancer genes are mutated in a high proportion of tumours of a given type (.20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600– 5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics. Comprehensive knowledge of the genes underlying human cancers is a critical foundation for cancer diagnostics, therapeutics, clinical-trial design and selection of rational combination therapies. It is now possible to use genomic analysis to identify cancer genes in an unbiased fashion, based on the presence of somatic mutations at a rate significantly higher than the expected background level. Systematic studies have revealed many new cancer genes, as well as new classes of cancer genes 1,2 . They have also made clear that, although some cancer genes are mutated at high frequencies, most cancer genes in most patients occur at intermediate frequencies (2–20%) or lower. Accordingly, a complete catalogue of mutations in this frequency class will be essential for recognizing dysregulated pathways and optimal targets for therapeutic intervention. However, recent work suggests major gaps in our knowledge of cancer genes of intermediate frequency. For example, a study of 183 lung adenocarcinomas 3 found that 15% of patients lacked even a single mutation affecting any of the 10 known hallmarks of cancer, and 38% had 3 or fewer such mutations. In this paper, we analysed somatic point mutations (substitutions and small insertion and deletions) in nearly 5,000 human cancers and their matched normal-tissue samples (‘tumour–normal pairs’) across 21 tumour types. The questions that we examine here are: first, whether large-scale genomic analysis across tumour types can reliably identify all known cancer genes; second, whether it will reveal many new candidate cancer genes; and third, how far we are from having a complete catalogue of cancer genes (at least those of intermediate frequency). We used rigorous statistical methods to enumerate candidate cancer genes and then carefully inspected each gene to identify those with strong biological connections to cancer and mutational patterns consistent with the expected function. The analysis reveals nearly all known cancer genes and revealed 33 novel candidates, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Importantly, the data show that the

2,565 citations

Journal ArticleDOI
TL;DR: Key concepts in the function of DNA methylation in mammals are discussed, stemming from more than two decades of research, including many recent studies that have elucidated when and whereDNA methylation has a regulatory role in the genome.
Abstract: DNA methylation is among the best studied epigenetic modifications and is essential to mammalian development. Although the methylation status of most CpG dinucleotides in the genome is stably propagated through mitosis, improvements to methods for measuring methylation have identified numerous regions in which it is dynamically regulated. In this Review, we discuss key concepts in the function of DNA methylation in mammals, stemming from more than two decades of research, including many recent studies that have elucidated when and where DNA methylation has a regulatory role in the genome. We include insights from early development, embryonic stem cells and adult lineages, particularly haematopoiesis, to highlight the general features of this modification as it participates in both global and localized epigenetic regulation.

2,550 citations

Journal ArticleDOI
13 Mar 2008-Nature
TL;DR: It is demonstrated that M2 expression is necessary for aerobic glycolysis and that this metabolic phenotype provides a selective growth advantage for tumour cells in vivo.
Abstract: Many tumour cells express the M2 form of pyruvate kinase rather than the usual M1 form. PKM2 is now shown to promote tumorigenesis and switch the cellular metabolism to increased lactate production and reduced oxygen consumption, recapitulating key aspects of the Warburg effect.

2,532 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
2022628
20211,727
20201,534
20191,364
20181,107