Showing papers by "University of Southern California published in 2019"
TL;DR: Protein Analysis Through Evolutionary Relationships is a resource for the evolutionary and functional classification of genes from organisms across the tree of life, and an entirely new PANTHER GO-slim is developed, containing over four times as many Gene Ontology terms as the previous GO- slim.
Abstract: PANTHER (Protein Analysis Through Evolutionary Relationships, http://pantherdb.org) is a resource for the evolutionary and functional classification of genes from organisms across the tree of life. We report the improvements we have made to the resource during the past two years. For evolutionary classifications, we have added more prokaryotic and plant genomes to the phylogenetic gene trees, expanding the representation of gene evolution in these lineages. We have refined many protein family boundaries, and have aligned PANTHER with the MEROPS resource for protease and protease inhibitor families. For functional classifications, we have developed an entirely new PANTHER GO-slim, containing over four times as many Gene Ontology terms as our previous GO-slim, as well as curated associations of genes to these terms. Lastly, we have made substantial improvements to the enrichment analysis tools available on the PANTHER website: users can now analyze over 900 different genomes, using updated statistical tests with false discovery rate corrections for multiple testing. The overrepresentation test is also available as a web service, for easy addition to third-party sites.
2,162 citations
TL;DR: GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models.
Abstract: The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page.
2,138 citations
European Bioinformatics Institute1, University of Manchester2, University of California, San Francisco3, Swiss Institute of Bioinformatics4, Laboratory of Molecular Biology5, J. Craig Venter Institute6, University of Delaware7, National Institutes of Health8, University of Southern California9, Georgetown University Medical Center10, University of Udine11, University of Padua12, University College London13
TL;DR: Recent developments with InterPro (version 70.0) and its associated software are reported, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website.
Abstract: The InterPro database (http://www.ebi.ac.uk/interpro/) classifies protein sequences into families and predicts the presence of functionally important domains and sites. Here, we report recent developments with InterPro (version 70.0) and its associated software, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website. These developments extend and enrich the information provided by InterPro, and provide greater flexibility in terms of data access. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB, and discuss how our evaluation of residue coverage may help guide future curation activities.
1,167 citations
TL;DR: Genome-wide analysis identifies 30 loci associated with bipolar disorder, allowing for comparisons of shared genes and pathways with other psychiatric disorders, including schizophrenia and depression.
Abstract: Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
1,090 citations
TL;DR: This review examines molecular and cellular mechanisms underlying the establishment of the blood-brain barrier, and examines how BBB dysfunction relates to neurological deficits and other pathologies in the majority of sporadic AD, PD, and ALS cases, multiple sclerosis, other neurodegenerative disorders, and acute CNS disorders.
Abstract: The blood-brain barrier (BBB) prevents neurotoxic plasma components, blood cells, and pathogens from entering the brain. At the same time, the BBB regulates transport of molecules into and out of t...
1,033 citations
TL;DR: The Simons Observatory (SO) is a new cosmic microwave background experiment being built on Cerro Toco in Chile, due to begin observations in the early 2020s as mentioned in this paper.
Abstract: The Simons Observatory (SO) is a new cosmic microwave background experiment being built on Cerro Toco in Chile, due to begin observations in the early 2020s. We describe the scientific goals of the experiment, motivate the design, and forecast its performance. SO will measure the temperature and polarization anisotropy of the cosmic microwave background in six frequency bands centered at: 27, 39, 93, 145, 225 and 280 GHz. The initial configuration of SO will have three small-aperture 0.5-m telescopes and one large-aperture 6-m telescope, with a total of 60,000 cryogenic bolometers. Our key science goals are to characterize the primordial perturbations, measure the number of relativistic species and the mass of neutrinos, test for deviations from a cosmological constant, improve our understanding of galaxy evolution, and constrain the duration of reionization. The small aperture telescopes will target the largest angular scales observable from Chile, mapping ≈ 10% of the sky to a white noise level of 2 μK-arcmin in combined 93 and 145 GHz bands, to measure the primordial tensor-to-scalar ratio, r, at a target level of σ(r)=0.003. The large aperture telescope will map ≈ 40% of the sky at arcminute angular resolution to an expected white noise level of 6 μK-arcmin in combined 93 and 145 GHz bands, overlapping with the majority of the Large Synoptic Survey Telescope sky region and partially with the Dark Energy Spectroscopic Instrument. With up to an order of magnitude lower polarization noise than maps from the Planck satellite, the high-resolution sky maps will constrain cosmological parameters derived from the damping tail, gravitational lensing of the microwave background, the primordial bispectrum, and the thermal and kinematic Sunyaev-Zel'dovich effects, and will aid in delensing the large-angle polarization signal to measure the tensor-to-scalar ratio. The survey will also provide a legacy catalog of 16,000 galaxy clusters and more than 20,000 extragalactic sources.
1,027 citations
University of California, San Francisco1, University of Birmingham2, University of Liège3, Advocate Lutheran General Hospital4, Kantonsspital St. Gallen5, University of Adelaide6, Baylor College of Medicine7, Mayo Clinic8, University of Southern California9, Asahikawa Medical University10, University of Dundee11, Pontifical Catholic University of Chile12, Uppsala University13, University of Hong Kong14, Royal Adelaide Hospital15, University of Hamburg16, Sunnybrook Health Sciences Centre17, University of Minnesota18, Technische Universität München19, University of Cambridge20, University of Bologna21, Washington University in St. Louis22, Greenville Health System23, University of Bristol24, University of Ottawa25, Nagoya University26, University of Texas Southwestern Medical Center27, Shanghai Jiao Tong University28, Icahn School of Medicine at Mount Sinai29, Brigham and Women's Hospital30, Oregon Health & Science University31, University of Buenos Aires32, Duke University33, St. Elizabeth's Medical Center34, Dartmouth College35, University of Massachusetts Amherst36, University of the Witwatersrand37, Ghent University Hospital38, Sun Yat-sen University39
TL;DR: The GVG proposes a new Global Anatomic Staging System (GLASS), which involves defining a preferred target artery path (TAP) and then estimating limb-based patency (LBP) resulting in three stages of complexity for intervention.
993 citations
University of New South Wales1, Oregon State University2, Braunschweig University of Technology3, University of California, San Diego4, Norwegian University of Life Sciences5, University of Liverpool6, Max Planck Society7, University of Tasmania8, University of Vermont9, ETH Zurich10, Stazione Zoologica Anton Dohrn11, Montana State University12, University of Amsterdam13, University of Southern California14, Pacific Northwest National Laboratory15, University of Hawaii at Manoa16, University of California, Berkeley17, Marine Biological Laboratory18, University of California, Irvine19, University of Georgia20, California Institute of Technology21, University of Edinburgh22, Ohio State University23, University of Sydney24, University of Alberta25, Georgia Institute of Technology26, Australian Institute of Marine Science27, University of Melbourne28, University of Texas Medical Branch29, University of Queensland30
TL;DR: This Consensus Statement documents the central role and global importance of microorganisms in climate change biology and puts humanity on notice that the impact of climate change will depend heavily on responses of micro organisms, which are essential for achieving an environmentally sustainable future.
Abstract: In the Anthropocene, in which we now live, climate change is impacting most life on Earth. Microorganisms support the existence of all higher trophic life forms. To understand how humans and other life forms on Earth (including those we are yet to discover) can withstand anthropogenic climate change, it is vital to incorporate knowledge of the microbial 'unseen majority'. We must learn not just how microorganisms affect climate change (including production and consumption of greenhouse gases) but also how they will be affected by climate change and other human activities. This Consensus Statement documents the central role and global importance of microorganisms in climate change biology. It also puts humanity on notice that the impact of climate change will depend heavily on responses of microorganisms, which are essential for achieving an environmentally sustainable future.
963 citations
13 May 2019
TL;DR: Pixel-aligned Implicit Function (PIFu) as mentioned in this paper aligns pixels of 2D images with the global context of their corresponding 3D object to produce highresolution surfaces including largely unseen regions such as the back of a person.
Abstract: We introduce Pixel-aligned Implicit Function (PIFu), an implicit representation that locally aligns pixels of 2D images with the global context of their corresponding 3D object. Using PIFu, we propose an end-to-end deep learning method for digitizing highly detailed clothed humans that can infer both 3D surface and texture from a single image, and optionally, multiple input images. Highly intricate shapes, such as hairstyles, clothing, as well as their variations and deformations can be digitized in a unified way. Compared to existing representations used for 3D deep learning, PIFu produces high-resolution surfaces including largely unseen regions such as the back of a person. In particular, it is memory efficient unlike the voxel representation, can handle arbitrary topology, and the resulting surface is spatially aligned with the input image. Furthermore, while previous techniques are designed to process either a single image or multiple views, PIFu extends naturally to arbitrary number of views. We demonstrate high-resolution and robust reconstructions on real world images from the DeepFashion dataset, which contains a variety of challenging clothing types. Our method achieves state-of-the-art performance on a public benchmark and outperforms the prior work for clothed human digitization from a single image.
907 citations
TL;DR: The authors provide an update to their 2013 protocol for using the PANTHER classification system, detailing how to analyze genome-wide experimental data with the newest version of PANTHER (v.14.0), with improvements in the areas of data quality, data coverage, statistical algorithms and user experience.
Abstract: The PANTHER classification system ( http://www.pantherdb.org ) is a comprehensive system that combines genomes, gene function classifications, pathways and statistical analysis tools to enable biologists to analyze large-scale genome-wide experimental data. The current system (PANTHER v.14.0) covers 131 complete genomes organized into gene families and subfamilies; evolutionary relationships between genes are represented in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models (HMMs)). The families and subfamilies are annotated with Gene Ontology (GO) terms, and sequences are assigned to PANTHER pathways. A suite of tools has been built to allow users to browse and query gene functions and analyze large-scale experimental data with a number of statistical tests. PANTHER is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. Since the protocol for using this tool (v.8.0) was originally published in 2013, there have been substantial improvements and updates in the areas of data quality, data coverage, statistical algorithms and user experience. This Protocol Update provides detailed instructions on how to analyze genome-wide experimental data in the PANTHER classification system.
900 citations
Carlos III Health Institute1, University of Cologne2, University of Sydney3, Paris Descartes University4, Universidade Federal de Ciências da Saúde de Porto Alegre5, Pontifícia Universidade Católica do Rio Grande do Sul6, Medical University of Graz7, University of California, San Diego8, University of Copenhagen9, Katholieke Universiteit Leuven10, University of Bologna11, University of the Witwatersrand12, RMIT University13, McGill University14, Hacettepe University15, University of Paris16, Utrecht University17, Mazandaran University of Medical Sciences18, Tel Aviv University19, Hospital General de México20, Istituto Giannina Gaslini21, Mahidol University22, Federal University of São Paulo23, King's College, Aberdeen24, Comenius University in Bratislava25, Boston Children's Hospital26, Hospital General Universitario Gregorio Marañón27, Complutense University of Madrid28, University Hospital Heidelberg29, University of California, Los Angeles30, American University of Beirut31, Innsbruck Medical University32, University of Lausanne33, Catholic University of Korea34, Goethe University Frankfurt35, Erasmus University Rotterdam36, National and Kapodistrian University of Athens37, Monash University38, Federal University of Rio de Janeiro39, Catholic University of the Sacred Heart40, University of Health Sciences Antigua41, National Institutes of Health42, Amrita Institute of Medical Sciences and Research Centre43, University of Pittsburgh44, Peter MacCallum Cancer Centre45, University of Melbourne46, P. D. Hinduja Hospital and Medical Research Centre47, University of Southern California48, Duke University49, Singapore General Hospital50, NewYork–Presbyterian Hospital51, Cardiff University52, University of Texas Health Science Center at San Antonio53, Children's Hospital of Philadelphia54, Post Graduate Institute of Medical Education and Research55
TL;DR: Management of mucormycosis depends on recognising disease patterns and on early diagnosis, and limited availability of contemporary treatments burdens patients in low and middle income settings.
Abstract: Mucormycosis is a difficult to diagnose rare disease with high morbidity and mortality. Diagnosis is often delayed, and disease tends to progress rapidly. Urgent surgical and medical intervention is lifesaving. Guidance on the complex multidisciplinary management has potential to improve prognosis, but approaches differ between health-care settings. From January, 2018, authors from 33 countries in all United Nations regions analysed the published evidence on mucormycosis management and provided consensus recommendations addressing differences between the regions of the world as part of the "One World One Guideline" initiative of the European Confederation of Medical Mycology (ECMM). Diagnostic management does not differ greatly between world regions. Upon suspicion of mucormycosis appropriate imaging is strongly recommended to document extent of disease and is followed by strongly recommended surgical intervention. First-line treatment with high-dose liposomal amphotericin B is strongly recommended, while intravenous isavuconazole and intravenous or delayed release tablet posaconazole are recommended with moderate strength. Both triazoles are strongly recommended salvage treatments. Amphotericin B deoxycholate is recommended against, because of substantial toxicity, but may be the only option in resource limited settings. Management of mucormycosis depends on recognising disease patterns and on early diagnosis. Limited availability of contemporary treatments burdens patients in low and middle income settings. Areas of uncertainty were identified and future research directions specified.
TL;DR: Neuroimaging and cerebrospinal fluid analyses in humans reveal that loss of blood–brain barrier integrity and brain capillary pericyte damage are early biomarkers of cognitive impairment that occur independently of changes in amyloid-β and tau.
Abstract: Vascular contributions to cognitive impairment are increasingly recognized1-5 as shown by neuropathological6,7, neuroimaging4,8-11, and cerebrospinal fluid biomarker4,12 studies. Moreover, small vessel disease of the brain has been estimated to contribute to approximately 50% of all dementias worldwide, including those caused by Alzheimer's disease (AD)3,4,13. Vascular changes in AD have been typically attributed to the vasoactive and/or vasculotoxic effects of amyloid-β (Aβ)3,11,14, and more recently tau15. Animal studies suggest that Aβ and tau lead to blood vessel abnormalities and blood-brain barrier (BBB) breakdown14-16. Although neurovascular dysfunction3,11 and BBB breakdown develop early in AD1,4,5,8-10,12,13, how they relate to changes in the AD classical biomarkers Aβ and tau, which also develop before dementia17, remains unknown. To address this question, we studied brain capillary damage using a novel cerebrospinal fluid biomarker of BBB-associated capillary mural cell pericyte, soluble platelet-derived growth factor receptor-β8,18, and regional BBB permeability using dynamic contrast-enhanced magnetic resonance imaging8-10. Our data show that individuals with early cognitive dysfunction develop brain capillary damage and BBB breakdown in the hippocampus irrespective of Alzheimer's Aβ and/or tau biomarker changes, suggesting that BBB breakdown is an early biomarker of human cognitive dysfunction independent of Aβ and tau.
University of Kentucky1, Mayo Clinic2, University of Pennsylvania3, Rush University Medical Center4, Illinois Institute of Technology5, Uppsala University6, Newcastle University7, University of Cambridge8, University of Southern California9, University of Minnesota10, University of Sydney11, University of California, Irvine12, University of Washington13, Medical University of Vienna14, Emory University15, Stanford University16, University of California, San Diego17, University of California, San Francisco18, Harvard University19, University of Texas Southwestern Medical Center20
TL;DR: A recently recognized brain disorder that mimics the clinical features of Alzheimer’s disease: Limbic-predominant Age-related TDP-43 Encephalopathy (LATE).
Abstract: We describe a recently recognized disease entity, limbic-predominant age-related TDP-43 encephalopathy (LATE). LATE neuropathological change (LATE-NC) is defined by a stereotypical TDP-43 proteinopathy in older adults, with or without coexisting hippocampal sclerosis pathology. LATE-NC is a common TDP-43 proteinopathy, associated with an amnestic dementia syndrome that mimicked Alzheimer's-type dementia in retrospective autopsy studies. LATE is distinguished from frontotemporal lobar degeneration with TDP-43 pathology based on its epidemiology (LATE generally affects older subjects), and relatively restricted neuroanatomical distribution of TDP-43 proteinopathy. In community-based autopsy cohorts, ∼25% of brains had sufficient burden of LATE-NC to be associated with discernible cognitive impairment. Many subjects with LATE-NC have comorbid brain pathologies, often including amyloid-β plaques and tauopathy. Given that the 'oldest-old' are at greatest risk for LATE-NC, and subjects of advanced age constitute a rapidly growing demographic group in many countries, LATE has an expanding but under-recognized impact on public health. For these reasons, a working group was convened to develop diagnostic criteria for LATE, aiming both to stimulate research and to promote awareness of this pathway to dementia. We report consensus-based recommendations including guidelines for diagnosis and staging of LATE-NC. For routine autopsy workup of LATE-NC, an anatomically-based preliminary staging scheme is proposed with TDP-43 immunohistochemistry on tissue from three brain areas, reflecting a hierarchical pattern of brain involvement: amygdala, hippocampus, and middle frontal gyrus. LATE-NC appears to affect the medial temporal lobe structures preferentially, but other areas also are impacted. Neuroimaging studies demonstrated that subjects with LATE-NC also had atrophy in the medial temporal lobes, frontal cortex, and other brain regions. Genetic studies have thus far indicated five genes with risk alleles for LATE-NC: GRN, TMEM106B, ABCC9, KCNMB2, and APOE. The discovery of these genetic risk variants indicate that LATE shares pathogenetic mechanisms with both frontotemporal lobar degeneration and Alzheimer's disease, but also suggests disease-specific underlying mechanisms. Large gaps remain in our understanding of LATE. For advances in prevention, diagnosis, and treatment, there is an urgent need for research focused on LATE, including in vitro and animal models. An obstacle to clinical progress is lack of diagnostic tools, such as biofluid or neuroimaging biomarkers, for ante-mortem detection of LATE. Development of a disease biomarker would augment observational studies seeking to further define the risk factors, natural history, and clinical features of LATE, as well as eventual subject recruitment for targeted therapies in clinical trials.
Daniel Taliun1, Daniel N. Harris2, Michael D. Kessler2, Jedidiah Carlson3 +191 more•Institutions (61)
TL;DR: The nearly complete catalog of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and non-coding sequence variants to phenotypic variation as well as resources and early insights from the sequence data.
Abstract: Summary paragraph The Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency
Nasim Mavaddat1, Kyriaki Michailidou1, Kyriaki Michailidou2, Joe Dennis1 +307 more•Institutions (105)
TL;DR: This PRS, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset is developed and empirically validated and is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
TL;DR: This paper presents a new method for product design based on the digital twin approach, which places emphasis on the analysis of physical data rather than the virtual models and illustrates the application of the proposed DTPD method.
Abstract: With the advent of new generation information technologies in industry and product design, the big data-driven product design era has arrived. However, the big data-driven product design mainly pla...
Proceedings Article•
24 May 2019
TL;DR: This paper showed that gradient descent achieves zero training loss in polynomial time for a deep over-parameterized neural network with residual connections (ResNet) and further extended their analysis to deep residual convolutional neural networks and obtained a similar convergence result.
Abstract: Gradient descent finds a global minimum in training deep neural networks despite the objective function being non-convex. The current paper proves gradient descent achieves zero training loss in polynomial time for a deep over-parameterized neural network with residual connections (ResNet). Our analysis relies on the particular structure of the Gram matrix induced by the neural network architecture. This structure allows us to show the Gram matrix is stable throughout the training process and this stability implies the global optimality of the gradient descent algorithm. We further extend our analysis to deep residual convolutional neural networks and obtain a similar convergence result.
University of Southern California1, University of Washington2, Harvard University3, University of Michigan4, Max Planck Society5, University of Groningen6, University of Maryland, Baltimore7, Icahn School of Medicine at Mount Sinai8, Xi'an Jiaotong University9, University of Texas MD Anderson Cancer Center10, University of North Carolina at Charlotte11, Broad Institute12, European Bioinformatics Institute13, Yale University14, University of California, Davis15, University of Utah16, Pacific Biosciences17, University of California, San Diego18, Illumina19, Ludwig Institute for Cancer Research20, Ewha Womans University21, Drexel University22, University of Texas Health Science Center at Houston23, Washington University in St. Louis24, University of Malaya25, University of California, San Francisco26, BC Cancer Agency27, University of British Columbia28
TL;DR: A suite of long-read, short- read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms are applied to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner.
Abstract: The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.
TL;DR: It is proposed that the gut microbiota regulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.
Stanford University1, University of North Carolina at Chapel Hill2, Fred Hutchinson Cancer Research Center3, Vanderbilt University4, Anschutz Medical Campus5, University of Southern California6, Icahn School of Medicine at Mount Sinai7, University of California, San Francisco8, University of Hawaii9, University of Washington10, University of Texas Health Science Center at Houston11, University of Potsdam12, Johns Hopkins University13, Pennsylvania State University14, National Institutes of Health15, University of California, Davis16, Ohio State University17, Cancer Prevention Institute of California18, University of Vermont19, Rutgers University20
TL;DR: The value of diverse, multi-ethnic participants in large-scale genomic studies is demonstrated and evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications are shown.
Abstract: Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.
17 Jul 2019
TL;DR: The spatiotemporal multi-graph convolution network (ST-MGCN), a novel deep learning model for ride-hailing demand forecasting, is proposed which first encode the non-Euclidean pair-wise correlations among regions into multiple graphs and then explicitly model these correlations using multi- graph convolution.
Abstract: Region-level demand forecasting is an essential task in ridehailing services. Accurate ride-hailing demand forecasting can guide vehicle dispatching, improve vehicle utilization, reduce the wait-time, and mitigate traffic congestion. This task is challenging due to the complicated spatiotemporal dependencies among regions. Existing approaches mainly focus on modeling the Euclidean correlations among spatially adjacent regions while we observe that non-Euclidean pair-wise correlations among possibly distant regions are also critical for accurate forecasting. In this paper, we propose the spatiotemporal multi-graph convolution network (ST-MGCN), a novel deep learning model for ride-hailing demand forecasting. We first encode the non-Euclidean pair-wise correlations among regions into multiple graphs and then explicitly model these correlations using multi-graph convolution. To utilize the global contextual information in modeling the temporal correlation, we further propose contextual gated recurrent neural network which augments recurrent neural network with a contextual-aware gating mechanism to re-weights different historical observations. We evaluate the proposed model on two real-world large scale ride-hailing demand datasets and observe consistent improvement of more than 10% over stateof-the-art baselines.
03 Apr 2019
TL;DR: This work proposes a truly differentiable rendering framework that is able to directly render colorized mesh using differentiable functions and back-propagate efficient supervision signals to mesh vertices and their attributes from various forms of image representations, including silhouette, shading and color images.
Abstract: Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical process of image formation. By inverting such renderer, one can think of a learning approach to infer 3D information from 2D images. However, standard graphics renderers involve a fundamental discretization step called rasterization, which prevents the rendering process to be differentiable, hence able to be learned. Unlike the state-of-the-art differentiable renderers, which only approximate the rendering gradient in the back propagation, we propose a truly differentiable rendering framework that is able to (1) directly render colorized mesh using differentiable functions and (2) back-propagate efficient supervision signals to mesh vertices and their attributes from various forms of image representations, including silhouette, shading and color images. The key to our framework is a novel formulation that views rendering as an aggregation function that fuses the probabilistic contributions of all mesh triangles with respect to the rendered pixels. Such formulation enables our framework to flow gradients to the occluded and far-range vertices, which cannot be achieved by the previous state-of-the-arts. We show that by using the proposed renderer, one can achieve significant improvement in 3D unsupervised single-view reconstruction both qualitatively and quantitatively. Experiments also demonstrate that our approach is able to handle the challenging tasks in image-based shape fitting, which remain nontrivial to existing differentiable renderers. Code is available at https://github.com/ShichenLiu/SoftRas.
04 Jan 2019
TL;DR: This survey study provides nationally representative estimates of the distribution, severity, and factors associated with adult food allergy in the United States.
Abstract: Importance Food allergy is a costly, potentially life-threatening condition. Although studies have examined the prevalence of childhood food allergy, little is known about prevalence, severity, or health care utilization related to food allergies among US adults. Objective To provide nationally representative estimates of the distribution, severity, and factors associated with adult food allergies. Design, Setting, and Participants In this cross-sectional survey study of US adults, surveys were administered via the internet and telephone from October 9, 2015, to September 18, 2016. Participants were first recruited from NORC at the University of Chicago’s probability-based AmeriSpeak panel, and additional participants were recruited from the non–probability-based Survey Sampling International (SSI) panel. Exposures Demographic and allergic participant characteristics. Main Outcomes and Measures Self-reported food allergies were the main outcome and were considered convincing if reported symptoms to specific allergens were consistent with IgE-mediated reactions. Diagnosis history to specific allergens and food allergy–related health care use were also primary outcomes. Estimates were based on this nationally representative sample using small-area estimation and iterative proportional fitting methods. To increase precision, AmeriSpeak data were augmented by calibration-weighted, non–probability-based responses from SSI. Results Surveys were completed by 40 443 adults (mean [SD] age, 46.6 [20.2] years), with a survey completion rate of 51.2% observed among AmeriSpeak panelists (n = 7210) and 5.5% among SSI panelists (n = 33 233). Estimated convincing food allergy prevalence among US adults was 10.8% (95% CI, 10.4%-11.1%), although 19.0% (95% CI, 18.5%-19.5%) of adults self-reported a food allergy. The most common allergies were shellfish (2.9%; 95% CI, 2.7%-3.1%), milk (1.9%; 95% CI, 1.8%-2.1%), peanut (1.8%; 95% CI, 1.7%-1.9%), tree nut (1.2%; 95% CI, 1.1%-1.3%), and fin fish (0.9%; 95% CI, 0.8%-1.0%). Among food-allergic adults, 51.1% (95% CI, 49.3%-52.9%) experienced a severe food allergy reaction, 45.3% (95% CI, 43.6%-47.1%) were allergic to multiple foods, and 48.0% (95% CI, 46.2%-49.7%) developed food allergies as an adult. Regarding health care utilization, 24.0% (95% CI, 22.6%-25.4%) reported a current epinephrine prescription, and 38.3% (95% CI, 36.7%-40.0%) reported at least 1 food allergy–related lifetime emergency department visit. Conclusions and Relevance These data suggest that at least 10.8% (>26 million) of US adults are food allergic, whereas nearly 19% of adults believe that they have a food allergy. Consequently, these findings suggest that it is crucial that adults with suspected food allergy receive appropriate confirmatory testing and counseling to ensure food is not unnecessarily avoided and quality of life is not unduly impaired.
University of Tübingen1, German Center for Neurodegenerative Diseases2, Washington University in St. Louis3, University Hospital of Basel4, Ludwig Maximilian University of Munich5, Florey Institute of Neuroscience and Mental Health6, Edith Cowan University7, Neuroscience Research Australia8, University of New South Wales9, University College London10, Mayo Clinic11, Brown University12, Indiana University13, University of Southern California14, Columbia University Medical Center15, Harvard University16, Icahn School of Medicine at Mount Sinai17
TL;DR: Serum NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer’s disease, which supports its potential utility as a clinically useful biomarker.
Abstract: Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer’s disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini–Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer’s disease, which supports its potential utility as a clinically useful biomarker.
Scott & White Hospital1, University of Connecticut2, University of Pittsburgh3, University of Oklahoma Health Sciences Center4, Emory University5, University of Southern California6, University of Alabama at Birmingham7, University of California, San Francisco8, Mayo Clinic9, University of Pennsylvania10, Medical College of Wisconsin11, Icahn School of Medicine at Mount Sinai12, University of California, San Diego13, University Hospitals of Cleveland14, Harvard University15, Henry Ford Hospital16, National Institutes of Health17, Northwestern University18, American Academy of Dermatology19
TL;DR: The treatment of psoriasis with biologic agents will be reviewed, emphasizing treatment recommendations and the role of the dermatologist in monitoring and educating patients regarding benefits as well as associated risks.
Abstract: Psoriasis is a chronic, inflammatory multisystem disease that affects up to 3.2% of the US population. This guideline addresses important clinical questions that arise in psoriasis management and care, providing recommendations based on the available evidence. The treatment of psoriasis with biologic agents will be reviewed, emphasizing treatment recommendations and the role of the dermatologist in monitoring and educating patients regarding benefits as well as associated risks.
Günter Blöschl1, Marc F. P. Bierkens2, António Chambel3, Christophe Cudennec4 +209 more•Institutions (124)
TL;DR: In this article, a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts is described. But despite the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work.
Abstract: This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.
TL;DR: Clinical trials should be designed to test drug efficacy and safety according to sex, age, reproductive stage (i.e., menopause), and synthetic hormone use, to fill current gaps and implement precision medicine for patients with NAFLD.
University of California, San Diego1, McGill University2, Oregon Health & Science University3, Florida International University4, Yale University5, Washington University in St. Louis6, Virginia Commonwealth University7, University of Vermont8, University of Michigan9, Medical University of South Carolina10, National Institutes of Health11, SRI International12, University of Southern California13, McGovern Institute for Brain Research14, Harvard University15, Medical College of Wisconsin16, University of California, Irvine17, University of California, Los Angeles18, University of California, San Francisco19, University of Colorado Boulder20, University of Florida21, University of Maryland, Baltimore22, University of Massachusetts Boston23, University of Minnesota24, University of Pittsburgh25, University of Rochester26, University of Tennessee27, University of Utah28, University of Wisconsin–Milwaukee29, United States Department of Veterans Affairs30, Boston University31
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the Adolescent Brain Cognitive Development Study are described to be a resource of unprecedented scale and depth for studying typical and atypical development.
VU University Amsterdam1, Leibniz Institute for Neurobiology2, Broad Institute3, Tufts University4, University of Southern California5, Cornell University6, Johns Hopkins University School of Medicine7, Johns Hopkins University8, Max Planck Society9, Harvard University10, KAIST11, Utrecht University12, University of Lausanne13, University of Rome Tor Vergata14, European Bioinformatics Institute15, University of Milan16, Autonomous University of Barcelona17, Yale University18, Swiss Institute of Bioinformatics19, Stanford University20, University of California, San Francisco21, Genentech22, Howard Hughes Medical Institute23, National University of Singapore24, Montreal Neurological Institute and Hospital25, University of Southampton26
TL;DR: It is shown that synaptic genes are exceptionally well conserved and less tolerant to mutations than other genes, and among de novo variants associated with neurodevelopmental disorders, including schizophrenia.
TL;DR: In this paper, the problem of learning a shallow neural network that best fits a training data set was studied in the over-parameterized regime, where the numbers of observations are fewer than the number of parameters in the model.
Abstract: In this paper, we study the problem of learning a shallow artificial neural network that best fits a training data set. We study this problem in the over-parameterized regime where the numbers of observations are fewer than the number of parameters in the model. We show that with the quadratic activations, the optimization landscape of training, such shallow neural networks, has certain favorable characteristics that allow globally optimal models to be found efficiently using a variety of local search heuristics. This result holds for an arbitrary training data of input/output pairs. For differentiable activation functions, we also show that gradient descent, when suitably initialized, converges at a linear rate to a globally optimal model. This result focuses on a realizable model where the inputs are chosen i.i.d. from a Gaussian distribution and the labels are generated according to planted weight coefficients.