Showing papers by "University of Michigan published in 2011"
TL;DR: VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API.
Abstract: Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API.
Availability: http://vcftools.sourceforge.net
Contact: [email protected]
10,164 citations
TL;DR: It is reported that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1,BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes.
Abstract: A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients' lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.
5,878 citations
TL;DR: Plasmon-enhanced water splitting on composite photocatalysts containing semiconductor and plasmonic-metal building blocks is focused on, and recently reported plasMon-mediated photocatallytic reactions on plAsmonic nanostructures of noble metals are discussed.
Abstract: Recent years have seen a renewed interest in the harvesting and conversion of solar energy. Among various technologies, the direct conversion of solar to chemical energy using photocatalysts has received significant attention. Although heterogeneous photocatalysts are almost exclusively semiconductors, it has been demonstrated recently that plasmonic nanostructures of noble metals (mainly silver and gold) also show significant promise. Here we review recent progress in using plasmonic metallic nanostructures in the field of photocatalysis. We focus on plasmon-enhanced water splitting on composite photocatalysts containing semiconductor and plasmonic-metal building blocks, and recently reported plasmon-mediated photocatalytic reactions on plasmonic nanostructures of noble metals. We also discuss the areas where major advancements are needed to move the field of plasmon-mediated photocatalysis forward.
4,074 citations
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TL;DR: The high level of collaboration on the gem5 project, combined with the previous success of the component parts and a liberal BSD-like license, make gem5 a valuable full-system simulation tool.
Abstract: The gem5 simulation infrastructure is the merger of the best aspects of the M5 [4] and GEMS [9] simulators. M5 provides a highly configurable simulation framework, multiple ISAs, and diverse CPU models. GEMS complements these features with a detailed and exible memory system, including support for multiple cache coherence protocols and interconnect models. Currently, gem5 supports most commercial ISAs (ARM, ALPHA, MIPS, Power, SPARC, and x86), including booting Linux on three of them (ARM, ALPHA, and x86).The project is the result of the combined efforts of many academic and industrial institutions, including AMD, ARM, HP, MIPS, Princeton, MIT, and the Universities of Michigan, Texas, and Wisconsin. Over the past ten years, M5 and GEMS have been used in hundreds of publications and have been downloaded tens of thousands of times. The high level of collaboration on the gem5 project, combined with the previous success of the component parts and a liberal BSD-like license, make gem5 a valuable full-system simulation tool.
4,039 citations
TL;DR: This new adenocarcinoma classification is needed to provide uniform terminology and diagnostic criteria, especially for bronchioloalveolar carcinoma (BAC), the overall approach to small nonresection cancer specimens, and for multidisciplinary strategic management of tissue for molecular and immunohistochemical studies.
3,850 citations
TL;DR: Alice K. Jacobs, MD, FACC, FAHA, Chair Jeffrey L. Anderson, PhD, CCNS, CCRN, FAH, Chair-Elect - The first female FACC-FAHA board member to be elected in the history of the sport.
Abstract: Alice K. Jacobs, MD, FACC, FAHA, Chair
Jeffrey L. Anderson, MD, FACC, FAHA, Chair-Elect
Nancy Albert, PhD, CCNS, CCRN, FAHA
Mark A. Creager, MD, FACC, FAHA
Steven M. Ettinger, MD, FACC
Robert A. Guyton, MD, FACC
Jonathan L. Halperin, MD, FACC, FAHA
Judith S. Hochman, MD, FACC, FAHA
3,040 citations
Proceedings Article•
28 Jun 2011TL;DR: This work presents a series of tasks for multimodal learning and shows how to train deep networks that learn features to address these tasks, and demonstrates cross modality feature learning, where better features for one modality can be learned if multiple modalities are present at feature learning time.
Abstract: Deep networks have been successfully applied to unsupervised feature learning for single modalities (e.g., text, images or audio). In this work, we propose a novel application of deep networks to learn features over multiple modalities. We present a series of tasks for multimodal learning and show how to train deep networks that learn features to address these tasks. In particular, we demonstrate cross modality feature learning, where better features for one modality (e.g., video) can be learned if multiple modalities (e.g., audio and video) are present at feature learning time. Furthermore, we show how to learn a shared representation between modalities and evaluate it on a unique task, where the classifier is trained with audio-only data but tested with video-only data and vice-versa. Our models are validated on the CUAVE and AVLetters datasets on audio-visual speech classification, demonstrating best published visual speech classification on AVLetters and effective shared representation learning.
2,830 citations
TL;DR: This crystal structure represents the first high-resolution view of transmembrane signalling by a GPCR and the most surprising observation is a major displacement of the α-helical domain of Gαs relative to the Ras-like GTPase domain.
Abstract: G protein-coupled receptors (GPCRs) are responsible for the majority of cellular responses to hormones and neurotransmitters as well as the senses of sight, olfaction and taste. The paradigm of GPCR signalling is the activation of a heterotrimeric GTP binding protein (G protein) by an agonist-occupied receptor. The b2 adrenergic receptor (b2AR) activation of Gs, the stimulatory G protein for adenylyl cyclase, has long been a model system for GPCR signalling. Here we present the crystal structure of the active state ternary complex composed of agonist-occupied monomericb2AR and nucleotide-free Gs heterotrimer. The principal interactions between the b2AR and Gs involve the amino- and carboxy-terminal a-helices of Gs, with conformational changes propagating to the nucleotide-binding pocket. The
2,676 citations
TL;DR: The medical profession should play a central role in evaluating the evidence related to drugs, devices, and procedures for the detection, management, and prevention of disease as mentioned in this paper, and when properly applied, expert analysis of available data on the benefits and risks of these therapies and procedures can
2,495 citations
TL;DR: Eplerenone, as compared with placebo, reduced both the risk of death and therisk of hospitalization among patients with systolic heart failure and mild symptoms.
Abstract: A B S T R AC T BACKGROUND Mineralocorticoid antagonists improve survival among patients with chronic, se- vere systolic heart failure and heart failure after myocardial infarction. We evalu- ated the effects of eplerenone in patients with chronic systolic heart failure and mild symptoms. METHODS In this randomized, double-blind trial, we randomly assigned 2737 patients with New York Heart Association class II heart failure and an ejection fraction of no more than 35% to receive eplerenone (up to 50 mg daily) or placebo, in addition to recommended therapy. The primary outcome was a composite of death from car- diovascular causes or hospitalization for heart failure. RESULTS The trial was stopped prematurely, according to prespecified rules, after a median follow-up period of 21 months. The primary outcome occurred in 18.3% of patients in the eplerenone group as compared with 25.9% in the placebo group (hazard ra- tio, 0.63; 95% confidence interval (CI), 0.54 to 0.74; P<0.001). A total of 12.5% of patients receiving eplerenone and 15.5% of those receiving placebo died (hazard ratio, 0.76; 95% CI, 0.62 to 0.93; P = 0.008); 10.8% and 13.5%, respectively, died of cardiovascular causes (hazard ratio, 0.76; 95% CI, 0.61 to 0.94; P = 0.01). Hospital- izations for heart failure and for any cause were also reduced with eplerenone. A serum potassium level exceeding 5.5 mmol per liter occurred in 11.8% of patients in the eplerenone group and 7.2% of those in the placebo group (P<0.001). CONCLUSIONS Eplerenone, as compared with placebo, reduced both the risk of death and the risk of hospitalization among patients with systolic heart failure and mild symptoms. (Funded by Pfizer; ClinicalTrials.gov number, NCT00232180.)
2,398 citations
TL;DR: The sequence kernel association test (SKAT) is proposed, a supervised, flexible, computationally efficient regression method to test for association between genetic variants (common and rare) in a region and a continuous or dichotomous trait while easily adjusting for covariates.
Abstract: Sequencing studies are increasingly being conducted to identify rare variants associated with complex traits. The limited power of classical single-marker association analysis for rare variants poses a central challenge in such studies. We propose the sequence kernel association test (SKAT), a supervised, flexible, computationally efficient regression method to test for association between genetic variants (common and rare) in a region and a continuous or dichotomous trait while easily adjusting for covariates. As a score-based variance-component test, SKAT can quickly calculate p values analytically by fitting the null model containing only the covariates, and so can easily be applied to genome-wide data. Using SKAT to analyze a genome-wide sequencing study of 1000 individuals, by segmenting the whole genome into 30 kb regions, requires only 7 hr on a laptop. Through analysis of simulated data across a wide range of practical scenarios and triglyceride data from the Dallas Heart Study, we show that SKAT can substantially outperform several alternative rare-variant association tests. We also provide analytic power and sample-size calculations to help design candidate-gene, whole-exome, and whole-genome sequence association studies.
Proceedings Article•
14 Jun 2011TL;DR: In this paper, the authors show that the number of hidden nodes in the model may be more important to achieving high performance than the learning algorithm or the depth of the model, and they apply several othe-shelf feature learning algorithms (sparse auto-encoders, sparse RBMs, K-means clustering, and Gaussian mixtures) to CIFAR, NORB, and STL datasets using only single-layer networks.
Abstract: A great deal of research has focused on algorithms for learning features from unlabeled data. Indeed, much progress has been made on benchmark datasets like NORB and CIFAR by employing increasingly complex unsupervised learning algorithms and deep models. In this paper, however, we show that several simple factors, such as the number of hidden nodes in the model, may be more important to achieving high performance than the learning algorithm or the depth of the model. Specifically, we will apply several othe-shelf feature learning algorithms (sparse auto-encoders, sparse RBMs, K-means clustering, and Gaussian mixtures) to CIFAR, NORB, and STL datasets using only singlelayer networks. We then present a detailed analysis of the eect of changes in the model setup: the receptive field size, number of hidden nodes (features), the step-size (“stride”) between extracted features, and the eect of whitening. Our results show that large numbers of hidden nodes and dense feature extraction are critical to achieving high performance—so critical, in fact, that when these parameters are pushed to their limits, we achieve state-of-the-art performance on both CIFAR-10 and NORB using only a single layer of features. More surprisingly, our best performance is based on K-means clustering, which is extremely fast, has no hyperparameters to tune beyond the model structure itself, and is very easy to implement. Despite the simplicity of our system, we achieve accuracy beyond all previously published results on the CIFAR-10 and NORB datasets (79.6% and 97.2% respectively).
Space Telescope Science Institute1, University of California, Santa Cruz2, Johns Hopkins University3, Rutgers University4, Durham University5, University of Nottingham6, Harvard University7, University of Innsbruck8, University of Michigan9, DSM10, University of Edinburgh11, University of Massachusetts Amherst12, California Institute of Technology13, UK Astronomy Technology Centre14, University of California, Irvine15, Swinburne University of Technology16, University of Arizona17, Goddard Space Flight Center18, The Catholic University of America19, Hebrew University of Jerusalem20, University of Victoria21, University of California, Berkeley22, Texas A&M University23, University of Notre Dame24, Carnegie Institution for Science25, Smithsonian Institution26, Yale University27, University of Missouri–Kansas City28, University of California, Riverside29, Max Planck Society30, University of Pittsburgh31, Inter-University Centre for Astronomy and Astrophysics32, University of Barcelona33, European Southern Observatory34, University of Minnesota35, National Research Council36, Western Kentucky University37, Stanford University38, Atacama Large Millimeter Submillimeter Array39, University of Missouri40
TL;DR: The Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) as discussed by the authors was designed to document the first third of galactic evolution, from z approx. 8 - 1.5 to test their accuracy as standard candles for cosmology.
Abstract: The Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) is designed to document the first third of galactic evolution, from z approx. 8 - 1.5. It will image > 250,000 distant galaxies using three separate cameras on the Hubble Space Tele8cope, from the mid-UV to near-IR, and will find and measure Type Ia supernovae beyond z > 1.5 to test their accuracy as standard candles for cosmology. Five premier multi-wavelength sky regions are selected, each with extensive ancillary data. The use of five widely separated fields mitigates cosmic variance and yields statistically robust and complete samples of galaxies down to a stellar mass of 10(exp 9) solar mass to z approx. 2, reaching the knee of the UV luminosity function of galaxies to z approx. 8. The survey covers approximately 800 square arc minutes and is divided into two parts. The CANDELS/Deep survey (5(sigma) point-source limit H =27.7mag) covers approx. 125 square arcminutes within GOODS-N and GOODS-S. The CANDELS/Wide survey includes GOODS and three additional fields (EGS, COSMOS, and UDS) and covers the full area to a 50(sigma) point-source limit of H ? or approx. = 27.0 mag. Together with the Hubble Ultradeep Fields, the strategy creates a three-tiered "wedding cake" approach that has proven efficient for extragalactic surveys. Data from the survey are non-proprietary and are useful for a wide variety of science investigations. In this paper, we describe the basic motivations for the survey, the CANDELS team science goals and the resulting observational requirements, the field selection and geometry, and the observing design.
TL;DR: This work demonstrates how the generalization of blockmodels to incorporate this missing element leads to an improved objective function for community detection in complex networks and proposes a heuristic algorithm forcommunity detection using this objective function or its non-degree-corrected counterpart.
Abstract: Stochastic blockmodels have been proposed as a tool for detecting community structure in networks as well as for generating synthetic networks for use as benchmarks. Most blockmodels, however, ignore variation in vertex degree, making them unsuitable for applications to real-world networks, which typically display broad degree distributions that can significantly affect the results. Here we demonstrate how the generalization of blockmodels to incorporate this missing element leads to an improved objective function for community detection in complex networks. We also propose a heuristic algorithm for community detection using this objective function or its non-degree-corrected counterpart and show that the degree-corrected version dramatically outperforms the uncorrected one in both real-world and synthetic networks.
Space Telescope Science Institute1, University of California, Santa Cruz2, Johns Hopkins University3, Western Kentucky University4, University of Massachusetts Amherst5, Carnegie Institution for Science6, European Southern Observatory7, Ohio State University8, Rutgers University9, Durham University10, University of Nottingham11, Max Planck Society12, University of Innsbruck13, University of Michigan14, French Alternative Energies and Atomic Energy Commission15, University of Edinburgh16, Harvard University17, California Institute of Technology18, University of California, Irvine19, Swinburne University of Technology20, University of Arizona21, Goddard Space Flight Center22, Hebrew University of Jerusalem23, Victoria University, Australia24, DSM25, University of California, Berkeley26, Texas A&M University27, University of Notre Dame28, Smithsonian Institution29, Yale University30, University of Missouri–Kansas City31, University of California, Riverside32, Imperial College London33, University of Pittsburgh34, Inter-University Centre for Astronomy and Astrophysics35, National Research Council36, Stanford University37
TL;DR: In this paper, the authors describe the Hubble Space Telescope imaging data products and data reduction procedures for the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS).
Abstract: This paper describes the Hubble Space Telescope imaging data products and data reduction procedures for the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS). This survey is designed to document the evolution of galaxies and black holes at z 1.5-8, and to study Type Ia supernovae at z > 1.5. Five premier multi-wavelength sky regions are selected, each with extensive multi-wavelength observations. The primary CANDELS data consist of imaging obtained in the Wide Field Camera 3 infrared channel (WFC3/IR) and the WFC3 ultraviolet/optical channel, along with the Advanced Camera for Surveys (ACS). The CANDELS/Deep survey covers ~125 arcmin2 within GOODS-N and GOODS-S, while the remainder consists of the CANDELS/Wide survey, achieving a total of ~800 arcmin2 across GOODS and three additional fields (Extended Groth Strip, COSMOS, and Ultra-Deep Survey). We summarize the observational aspects of the survey as motivated by the scientific goals and present a detailed description of the data reduction procedures and products from the survey. Our data reduction methods utilize the most up-to-date calibration files and image combination procedures. We have paid special attention to correcting a range of instrumental effects, including charge transfer efficiency degradation for ACS, removal of electronic bias-striping present in ACS data after Servicing Mission 4, and persistence effects and other artifacts in WFC3/IR. For each field, we release mosaics for individual epochs and eventual mosaics containing data from all epochs combined, to facilitate photometric variability studies and the deepest possible photometry. A more detailed overview of the science goals and observational design of the survey are presented in a companion paper.
TL;DR: Improved quality-filtering pipeline was applied to several benchmarking studies and observed that even with the stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.
Abstract: The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×106 reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.
TL;DR: This Review highlights the cellular and molecular mechanisms at play in the generation of obesity-induced inflammation and underscores how defining the immune regulation in metabolic tissues has broadened the understanding of the diversity of inflammatory responses.
Abstract: The obesity epidemic has forced us to evaluate the role of inflammation in the health complications of obesity. This has led to a convergence of the fields of immunology and nutrient physiology and the understanding that they are inextricably linked. The reframing of obesity as an inflammatory condition has had a wide impact on our conceptualization of obesity-associated diseases. In this Review, we highlight the cellular and molecular mechanisms at play in the generation of obesity-induced inflammation. We also emphasize how defining the immune regulation in metabolic tissues has broadened the understanding of the diversity of inflammatory responses.
University of Chicago1, Roy J. and Lucille A. Carver College of Medicine2, University of Texas MD Anderson Cancer Center3, University of California, Los Angeles4, University of Michigan5, Cornell University6, Memorial Sloan Kettering Cancer Center7, Icahn School of Medicine at Mount Sinai8, National Institute of Standards and Technology9, University of Pittsburgh10, Food and Drug Administration11, Science Applications International Corporation12, Agfa-Gevaert13, iCAD Inc.14, Carestream Health15, Philips16, Siemens17, GE Healthcare18
TL;DR: The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus and is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.
Abstract: Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (" nodule�3 mm," " nodule<3 mm," and "non- nodule�3 mm "). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked " nodul�3 mm " by at least one radiologist, of which 928 (34.7) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. © 2011 U.S. Government.
09 Feb 2011
TL;DR: It is concluded that word-of-mouth diffusion can only be harnessed reliably by targeting large numbers of potential influencers, thereby capturing average effects and that predictions of which particular user or URL will generate large cascades are relatively unreliable.
Abstract: In this paper we investigate the attributes and relative influence of 1.6M Twitter users by tracking 74 million diffusion events that took place on the Twitter follower graph over a two month interval in 2009. Unsurprisingly, we find that the largest cascades tend to be generated by users who have been influential in the past and who have a large number of followers. We also find that URLs that were rated more interesting and/or elicited more positive feelings by workers on Mechanical Turk were more likely to spread. In spite of these intuitive results, however, we find that predictions of which particular user or URL will generate large cascades are relatively unreliable. We conclude, therefore, that word-of-mouth diffusion can only be harnessed reliably by targeting large numbers of potential influencers, thereby capturing average effects. Finally, we consider a family of hypothetical marketing strategies, defined by the relative cost of identifying versus compensating potential "influencers." We find that although under some circumstances, the most influential users are also the most cost-effective, under a wide range of plausible assumptions the most cost-effective performance can be realized using "ordinary influencers"---individuals who exert average or even less-than-average influence.
TL;DR: A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function, and these findings suggest potential novel therapeutic pathways for cardiovascular disease prevention.
Abstract: Blood pressure is a heritable trait(1) influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (>= 140 mm Hg systolic blood pressure or >= 90 mm Hg diastolic blood pressure)(2). Even small increments in blood pressure are associated with an increased risk of cardiovascular events(3). This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.
TL;DR: OTTIP RNA binds the adaptor protein WDR5 directly and targets WDR 5/MLL complexes across HOXA, driving histone H3 lysine 4 trimethylation and gene transcription.
Abstract: A major question in developmental biology is how functionally related groups of genes are switched on at the right time and in the right place. Long intergenic non-coding RNAs (lincRNAs) have been implicated in both gene silencing and activation, and could be a means of long-range control of gene expression. A lincRNA termed HOTTIP that coordinates the activation of multiple 5' HOXA regulatory genes has now been identified at the 5' tip of the HOXA locus. Chromosomal looping brings HOTTIP close its target genes, where it facilitates histone H3 lysine 4 trimethylation and gene transcription. Long intergenic non-coding RNAs (lincRNAs) have been implicated in both gene silencing and activation, and could be a means for long-range control of gene expression. Here a lincRNA termed HOTTIP is identified at the 5′ tip of the HOXA locus that coordinates the activation of multiple 5′ HOXA genes. Chromosomal looping brings HOTTIP into the proximity of its target genes, where it seems to be required to facilitate histone H3 lysine 4 trimethylation and gene transcription. The genome is extensively transcribed into long intergenic noncoding RNAs (lincRNAs), many of which are implicated in gene silencing1,2. Potential roles of lincRNAs in gene activation are much less understood3,4,5. Development and homeostasis require coordinate regulation of neighbouring genes through a process termed locus control6. Some locus control elements and enhancers transcribe lincRNAs7,8,9,10, hinting at possible roles in long-range control. In vertebrates, 39 Hox genes, encoding homeodomain transcription factors critical for positional identity, are clustered in four chromosomal loci; the Hox genes are expressed in nested anterior-posterior and proximal-distal patterns colinear with their genomic position from 3′ to 5′of the cluster11. Here we identify HOTTIP, a lincRNA transcribed from the 5′ tip of the HOXA locus that coordinates the activation of several 5′ HOXA genes in vivo. Chromosomal looping brings HOTTIP into close proximity to its target genes. HOTTIP RNA binds the adaptor protein WDR5 directly and targets WDR5/MLL complexes across HOXA, driving histone H3 lysine 4 trimethylation and gene transcription. Induced proximity is necessary and sufficient for HOTTIP RNA activation of its target genes. Thus, by serving as key intermediates that transmit information from higher order chromosomal looping into chromatin modifications, lincRNAs may organize chromatin domains to coordinate long-range gene activation.
TL;DR: The Alzheimer Disease Genetics Consortium performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1), two replication stages (stages 2 and 3), and both joint analysis and meta-analysis approaches were used.
Abstract: The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1) and two replication stages (stages 2 and 3). Both joint analysis and meta-analysis approaches were used. We obtained genome-wide significant results at MS4A4A (rs4938933; stages 1 and 2, meta-analysis P (P(M)) = 1.7 × 10(-9), joint analysis P (P(J)) = 1.7 × 10(-9); stages 1, 2 and 3, P(M) = 8.2 × 10(-12)), CD2AP (rs9349407; stages 1, 2 and 3, P(M) = 8.6 × 10(-9)), EPHA1 (rs11767557; stages 1, 2 and 3, P(M) = 6.0 × 10(-10)) and CD33 (rs3865444; stages 1, 2 and 3, P(M) = 1.6 × 10(-9)). We also replicated previous associations at CR1 (rs6701713; P(M) = 4.6 × 10(-10), P(J) = 5.2 × 10(-11)), CLU (rs1532278; P(M) = 8.3 × 10(-8), P(J) = 1.9 × 10(-8)), BIN1 (rs7561528; P(M) = 4.0 × 10(-14), P(J) = 5.2 × 10(-14)) and PICALM (rs561655; P(M) = 7.0 × 10(-11), P(J) = 1.0 × 10(-10)), but not at EXOC3L2, to late-onset Alzheimer's disease susceptibility.
University of Miami1, University of Texas Southwestern Medical Center2, University of Alabama at Birmingham3, Harvard University4, University of Illinois at Chicago5, Veterans Health Administration6, Wake Forest University7, Tulane University8, University of California, San Francisco9, University of Pennsylvania10, University of Michigan11, Temple University12, University of Münster13, National Institutes of Health14
TL;DR: It is reported that elevated FGF23 levels are independently associated with LVH in a large, racially diverse CKD cohort and suggested that chronically elevated F GF23 levels contribute directly to high rates of LVH and mortality in individuals with CKD.
Abstract: Chronic kidney disease (CKD) is a public health epidemic that increases risk of death due to cardiovascular disease. Left ventricular hypertrophy (LVH) is an important mechanism of cardiovascular disease in individuals with CKD. Elevated levels of FGF23 have been linked to greater risks of LVH and mortality in patients with CKD, but whether these risks represent causal effects of FGF23 is unknown. Here, we report that elevated FGF23 levels are independently associated with LVH in a large, racially diverse CKD cohort. FGF23 caused pathological hypertrophy of isolated rat cardiomyocytes via FGF receptor–dependent activation of the calcineurin-NFAT signaling pathway, but this effect was independent of klotho, the coreceptor for FGF23 in the kidney and parathyroid glands. Intramyocardial or intravenous injection of FGF23 in wild-type mice resulted in LVH, and klotho-deficient mice demonstrated elevated FGF23 levels and LVH. In an established animal model of CKD, treatment with an FGF–receptor blocker attenuated LVH, although no change in blood pressure was observed. These results unveil a klotho-independent, causal role for FGF23 in the pathogenesis of LVH and suggest that chronically elevated FGF23 levels contribute directly to high rates of LVH and mortality in individuals with CKD.
TL;DR: Experimental and analytical approaches relating to exome sequencing have established a rich framework for discovering the genes underlying unsolved Mendelian disorders and set the stage for applying exome and whole-genome sequencing to facilitate clinical diagnosis and personalized disease-risk profiling.
Abstract: Exome sequencing — the targeted sequencing of the subset of the human genome that is protein coding — is a powerful and cost-effective new tool for dissecting the genetic basis of diseases and traits that have proved to be intractable to conventional gene-discovery strategies. Over the past 2 years, experimental and analytical approaches relating to exome sequencing have established a rich framework for discovering the genes underlying unsolved Mendelian disorders. Additionally, exome sequencing is being adapted to explore the extent to which rare alleles explain the heritability of complex diseases and health- related traits. These advances also set the stage for applying exome and whole-genome sequencing to facilitate clinical diagnosis and personalized disease-risk profiling.
TL;DR: It is shown that plasmonic nanostructures of silver can concurrently use low-intensity visible light and thermal energy to drive catalytic oxidation reactions--such as ethylene epoxidation, CO oxidation, and NH₃ oxidation--at lower temperatures than their conventional counterparts that use only thermal stimulus.
Abstract: Catalysis plays a critical role in chemical conversion, energy production and pollution mitigation. High activation barriers associated with rate-limiting elementary steps require most commercial heterogeneous catalytic reactions to be run at relatively high temperatures, which compromises energy efficiency and the long-term stability of the catalyst. Here we show that plasmonic nanostructures of silver can concurrently use low-intensity visible light (on the order of solar intensity) and thermal energy to drive catalytic oxidation reactions--such as ethylene epoxidation, CO oxidation, and NH₃ oxidation--at lower temperatures than their conventional counterparts that use only thermal stimulus. Based on kinetic isotope experiments and density functional calculations, we postulate that excited plasmons on the silver surface act to populate O₂ antibonding orbitals and so form a transient negative-ion state, which thereby facilitates the rate-limiting O₂-dissociation reaction. The results could assist the design of catalytic processes that are more energy efficient and robust than current processes.
TL;DR: A camelid antibody fragment to the human β2 adrenergic receptor is generated, and an agonist-bound, active-state crystal structure of the receptor-nanobody complex is obtained, providing insights into the process of agonist binding and activation.
Abstract: G protein coupled receptors (GPCRs) exhibit a spectrum of functional behaviours in response to natural and synthetic ligands. Recent crystal structures provide insights into inactive states of several GPCRs. Efforts to obtain an agonist-bound active-state GPCR structure have proven difficult due to the inherent instability of this state in the absence of a G protein. We generated a camelid antibody fragment (nanobody) to the human b2 adrenergic receptor (b2AR) that exhibits G protein-like behaviour, and obtained an agonist-bound, active-state crystal structure of the receptor-nanobody complex. Comparison with the inactive b2AR structure reveals subtle changes in the binding
TL;DR: This review highlights the emerging impact of ncRNAs in cancer research, with a particular focus on the mechanisms and functions of lncRNAs.
Abstract: The discovery of numerous non-coding RNA (ncRNA) transcripts in species from yeast to mammals has dramatically altered our understanding of cell biology, especially disease biology such as cancer. In humans, the identification of abundant long ncRNA (lncRNAs) >200 bp in length has catalyzed their characterization as critical components of cancer biology. Recently, roles for lncRNAs as drivers of tumor suppressive and oncogenic functions have appeared in prevalent cancer types, such as breast and prostate cancer. In this review, we will highlight the emerging impact of ncRNAs in cancer research, with a particular focus on the mechanisms and functions of lncRNAs.
TL;DR: In this article, a review of gene mutations in colorectal cancer is presented, focusing on the nature and significance of individual and collective genetic and epigenetic defects in CRC.
Abstract: Over the past three decades, molecular genetic studies have revealed some critical mutations underlying the pathogenesis of the sporadic and inherited forms of colorectal cancer (CRC). A relatively limited number of oncogenes and tumor-suppressor genes—most prominently the APC, KRAS, and p53 genes—are mutated in a sizeable fraction of CRCs, and a larger collection of genes that are mutated in subsets of CRC have begun to be defined. Together with DNA-methylation and chromatin-structure changes, the mutations act to dysregulate conserved signaling networks that exert context-dependent effects on critical cell phenotypes, including the regulation of cellular metabolism, proliferation, differentiation, and survival. Much work remains to be done to fully understand the nature and significance of the individual and collective genetic and epigenetic defects in CRC. Some key concepts for the field have emerged, two of which are emphasized in this review. Specifically, the gene defects in CRC often target protein...
Cleveland Clinic1, University of Texas Health Science Center at San Antonio2, Fred Hutchinson Cancer Research Center3, University of Colorado Denver4, National Institutes of Health5, Harvard University6, University of Texas MD Anderson Cancer Center7, Mayo Clinic8, Duke University9, University of Toronto10, University of California, San Diego11, University of Western Ontario12, University of California, Irvine13, University of Michigan14
TL;DR: Dietary supplementation with vitamin E significantly increased the risk of prostate cancer among healthy men in relatively healthy men.
Abstract: Context The initial report of the Selenium and Vitamin E Cancer Prevention Trial (SELECT) found no reduction in risk of prostate cancer with either selenium or vitamin E supplements but a statistically nonsignificant increase in prostate cancer risk with vitamin E. Longer follow-up and more prostate cancer events provide further insight into the relationship of vitamin E and prostate cancer. Objective To determine the long-term effect of vitamin E and selenium on risk of prostate cancer in relatively healthy men. Design, Setting, and Participants A total of 35 533 men from 427 study sites in the United States, Canada, and Puerto Rico were randomized between August 22, 2001, and June 24, 2004. Eligibility criteria included a prostate-specific antigen (PSA) of 4.0 ng/mL or less, a digital rectal examination not suspicious for prostate cancer, and age 50 years or older for black men and 55 years or older for all others. The primary analysis included 34 887 men who were randomly assigned to 1 of 4 treatment groups: 8752 to receive selenium; 8737, vitamin E; 8702, both agents, and 8696, placebo. Analysis reflect the final data collected by the study sites on their participants through July 5, 2011. Interventions Oral selenium (200 μg/d from L-selenomethionine) with matched vitamin E placebo, vitamin E (400 IU/d of all rac-α-tocopheryl acetate) with matched selenium placebo, both agents, or both matched placebos for a planned follow-up of a minimum of 7 and maximum of 12 years. Main Outcome Measures Prostate cancer incidence. Results This report includes 54 464 additional person-years of follow-up and 521 additional cases of prostate cancer since the primary report. Compared with the placebo (referent group) in which 529 men developed prostate cancer, 620 men in the vitamin E group developed prostate cancer (hazard ratio [HR], 1.17; 99% CI, 1.004-1.36, P = .008); as did 575 in the selenium group (HR, 1.09; 99% CI, 0.93-1.27; P = .18), and 555 in the selenium plus vitamin E group (HR, 1.05; 99% CI, 0.89-1.22, P = .46). Compared with placebo, the absolute increase in risk of prostate cancer per 1000 person-years was 1.6 for vitamin E, 0.8 for selenium, and 0.4 for the combination. Conclusion Dietary supplementation with vitamin E significantly increased the risk of prostate cancer among healthy men. Trial Registration Clinicaltrials.gov Identifier: NCT00006392
TL;DR: Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies.