Author
Dirk S. Paul
Other affiliations: National Institute for Health Research, AstraZeneca, British Heart Foundation ...read more
Bio: Dirk S. Paul is an academic researcher from University of Cambridge. The author has contributed to research in topics: DNA methylation & Genome-wide association study. The author has an hindex of 31, co-authored 61 publications receiving 5506 citations. Previous affiliations of Dirk S. Paul include National Institute for Health Research & AstraZeneca.
Papers
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Wellcome Trust Sanger Institute1, National Institute for Health Research2, University of Cambridge3, NHS Blood and Transplant4, European Bioinformatics Institute5, Barts Health NHS Trust6, Radboud University Nijmegen7, University of Geneva8, Katholieke Universiteit Leuven9, Wellcome Trust Centre for Human Genetics10, University of Oxford11, British Heart Foundation12, University of Amsterdam13, Newcastle University14, McGill University15, Pompeu Fabra University16, University College London17, John Radcliffe Hospital18, Churchill Hospital19
TL;DR: A genome-wide association analysis in the UK Biobank and INTERVAL studies is performed, providing evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations betweenBlood cell indices and cardiovascular disease may be non-causal.
982 citations
TL;DR: The genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study is characterized, and it is shown that protein quantitative trait loci overlap with gene expression quantitative traits, as well as with disease-associated loci, and evidence that protein biomarkers have causal roles in disease is found.
Abstract: Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.
961 citations
TL;DR: PhenoScanner is a curated database of publicly available results from large-scale genetic association studies that aims to facilitate ‘phenome scans’, the cross-referencing of genetic variants with many phenotypes, to help aid understanding of disease pathways and biology.
Abstract: This work was supported by the UK Medical Research Council [G66840, G0800270], Pfizer [G73632], British Heart Foundation [SP/09/002], UK National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council [268834], and European Commission Framework Programme 7 [HEALTH-F2-2012-279233].
766 citations
University of Cambridge1, Australian National University2, Norwegian Institute of Public Health3, Utrecht University4, University of Tromsø5, The George Institute for Global Health6, Johns Hopkins University7, University of Oxford8, National Institutes of Health9, Copenhagen University Hospital10, University of Copenhagen11, Harry Perkins Institute of Medical Research12, Fiona Stanley Hospital13, University of Western Australia14, University of London15, Lund University16, University of Pittsburgh17, French Institute of Health and Medical Research18, University College London19, Technische Universität München20, University of Ulm21, University of Padua22, University of Southampton23, German Cancer Research Center24, Erasmus University Medical Center25, Umeå University26, Cardiff University27, Greifswald University Hospital28, Aarhus University29, Portland State University30, University of New South Wales31, National and Kapodistrian University of Athens32, Harvard University33, University of Hawaii34, Columbia University35, University of Iowa36, Duke University37, Yamagata University38, Tuskegee University39, University of Oulu40, University of Helsinki41, Medical University of South Carolina42, Kaiser Permanente43, University of Washington44, University of Groningen45, University of Granada46, Yale University47, Prevention Institute48, University of Edinburgh49, Uppsala University50, Basque Government51, Royal Prince Alfred Hospital52, Kyushu University53, Harokopio University54, University of California, San Diego55, VU University Medical Center56, Aalborg University57, University of Eastern Finland58, Laval University59, University of Vermont60, Wake Forest Baptist Medical Center61, Wake Forest University62, Kanazawa Medical University63, Baker IDI Heart and Diabetes Institute64, Heidelberg University65, Istituto Superiore di Sanità66, Pasteur Institute67, City College of New York68, Howard University69, University of Glasgow70, International Agency for Research on Cancer71, University of Bristol72, University of Auckland73
TL;DR: Current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week, and data support limits for alcohol consumption that are lower than those recommended in most current guidelines.
711 citations
University of Cambridge1, Wellcome Trust Sanger Institute2, McGill University3, European Bioinformatics Institute4, Pompeu Fabra University5, University College London6, NHS Blood and Transplant7, Radboud University Nijmegen8, Max Planck Society9, University of Geneva10, New York University11, British Heart Foundation12, Newcastle University13, University of Amsterdam14
TL;DR: High-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types from up to 197 individuals yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.
504 citations
Cited by
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TL;DR: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee.
Abstract: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee
5,739 citations
TL;DR: This year's edition of the Statistical Update includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association’s 2020 Impact Goals.
Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovas...
5,078 citations
TL;DR: Deep phenotype and genome-wide genetic data from 500,000 individuals from the UK Biobank is described, describing population structure and relatedness in the cohort, and imputation to increase the number of testable variants to 96 million.
Abstract: The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.
4,489 citations
01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
4,409 citations
4,069 citations