Author
Paola G. Ferrario
Other affiliations: University of Stuttgart
Bio: Paola G. Ferrario is an academic researcher from University of Lübeck. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 10, co-authored 21 publications receiving 1125 citations. Previous affiliations of Paola G. Ferrario include University of Stuttgart.
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Washington University in St. Louis1, Broad Institute2, University of Texas Health Science Center at Houston3, University of North Carolina at Chapel Hill4, University of Oxford5, University of Lübeck6, University of Washington7, University of Wisconsin–Milwaukee8, Stanford University9, University of Pennsylvania10, University of Amsterdam11, Technische Universität München12, University of California, Los Angeles13, Cleveland Clinic14, University of Vermont15, University of Missouri–Kansas City16, Ohio State University17, Baylor College of Medicine18, University of Virginia19, Boston University20, University of Michigan21, Harvard University22, Mayo Clinic23, University of Copenhagen24, Vanderbilt University25, University of Dundee26, King Abdulaziz University27, University of Cambridge28, Pompeu Fabra University29, University of Ottawa30, University of Mississippi31
TL;DR: In this paper, the exons of the Niemann-Pick C1-like 1 (NPC1L1) protein were sequenced in 7364 patients with coronary heart disease and in 14,728 controls without such disease who were of European, African or South Asian ancestry.
Abstract: Ezetimibe lowers plasma levels of low-density lipoprotein (LDL) cholesterol by inhibiting the activity of the Niemann-Pick C1-like 1 (NPC1L1) protein. However, whether such inhibition reduces the risk of coronary heart disease is not known. Human mutations that inactivate a gene encoding a drug target can mimic the action of an inhibitory drug and thus can be used to infer potential effects of that drug.We sequenced the exons of NPC1L1 in 7364 patients with coronary heart disease and in 14,728 controls without such disease who were of European, African, or South Asian ancestry. We identified carriers of inactivating mutations (nonsense, splice-site, or frameshift mutations). In addition, we genotyped a specific inactivating mutation (p.Arg406X) in 22,590 patients with coronary heart disease and in 68,412 controls. We tested the association between the presence of an inactivating mutation and both plasma lipid levels and the risk of coronary heart disease.With sequencing, we identified 15 distinct NPC1L1 inactivating mutations; approximately 1 in every 650 persons was a heterozygous carrier for 1 of these mutations. Heterozygous carriers of NPC1L1 inactivating mutations had a mean LDL cholesterol level that was 12 mg per deciliter (0.31 mmol per liter) lower than that in noncarriers (P=0.04). Carrier status was associated with a relative reduction of 53% in the risk of coronary heart disease (odds ratio for carriers, 0.47; 95% confidence interval, 0.25 to 0.87; P=0.008). In total, only 11 of 29,954 patients with coronary heart disease had an inactivating mutation (carrier frequency, 0.04%) in contrast to 71 of 83,140 controls (carrier frequency, 0.09%).Naturally occurring mutations that disrupt NPC1L1 function were found to be associated with reduced plasma LDL cholesterol levels and a reduced risk of coronary heart disease. (Funded by the National Institutes of Health and others.).
374 citations
University of Washington1, University of Cambridge2, University of Leicester3, University of Lübeck4, University of Copenhagen5, University of Wisconsin–Milwaukee6, University of Michigan7, Montreal Heart Institute8, University of Oxford9, Broad Institute10, Samsung Medical Center11, University of Amsterdam12, Queen Mary University of London13, University of Göttingen14, University of Dundee15, University of Verona16, Vanderbilt University17, University of Kiel18, University of Bonn19, University of Basel20, Norwegian University of Science and Technology21, Umeå University22, University of Duisburg-Essen23, Technische Universität München24, University of Tartu25, Lund University26, University of Ottawa27, King Abdulaziz University28, Merck & Co.29, Ohio State University30, National Institutes of Health31, Johns Hopkins University32, Harvard University33, University of Insubria34, University of Glasgow35, Leiden University36, Queen's University Belfast37, Pierre-and-Marie-Curie University38, Wellcome Trust Sanger Institute39, University of Leeds40, Duke University41, University of Pennsylvania42
TL;DR: It was found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease.
Abstract: BACKGROUND The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS Through DNA genotyping, we ...
339 citations
University of Leicester1, University of Lübeck2, Queen Mary University of London3, Washington University in St. Louis4, Technische Universität München5, Uppsala University6, University of Tartu7, Icahn School of Medicine at Mount Sinai8, Vanderbilt University Medical Center9, University of Wisconsin–Milwaukee10, Fred Hutchinson Cancer Research Center11, University of Michigan12, Université de Montréal13, University of Oxford14, Harvard University15, University of Veterinary Medicine Vienna16, Wellcome Trust Centre for Human Genetics17, University of Dundee18, Humanitas University19, University of Kiel20, University of Bonn21, Norwegian University of Science and Technology22, Umeå University23, University of Verona24, Broad Institute25, Lund University26, University of Edinburgh27, National Institutes of Health28, University of Ottawa29, Montreal Heart Institute30, King Abdulaziz University31, Merck & Co.32, Utrecht University33, University College London34, Ohio State University35, Ludwig Maximilian University of Munich36, University of Cambridge37, Robertson Centre for Biostatistics38, Leiden University Medical Center39, Lille University of Science and Technology40, Copenhagen University Hospital41, University of Toulouse42, University of Pennsylvania43, British Heart Foundation44, University of Strasbourg45, University of Leeds46, Duke University47, Columbia University48, University of Washington49, Glenfield Hospital50
TL;DR: Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk, and identify 6 new loci associated with CAD at genome-wide significance.
222 citations
University of Bologna1, Carlos III Health Institute2, University College Dublin3, Chalmers University of Technology4, University of Turin5, Technische Universität München6, University of Auvergne7, Wageningen University and Research Centre8, University of Eastern Finland9, Ghent University10, Max Planck Society11, University of Trento12, University of Alberta13
TL;DR: A methodological description of nutritional metabolomics is provided that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance as well as points of reflections to harmonize this field.
Abstract: The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.
161 citations
TL;DR: Meat and fish consumption differentially affects TMAO concentrations in body fluids, and only a small fraction of variance is explained by current diet.
Abstract: cope
: Knowledge on the influence of current diet on TMAO levels in humans is still inconsistent. Thus, we aimed to investigate associations of current diet with urine and plasma TMAO levels and to determine the effect of different foods on TMAO variation.
Methods and results
: TMAO concentrations of 297 healthy individuals were assessed using 1H-NMR spectroscopy for 24h urine collection and spot urine, and LC-MS for plasma. Of 35 assessed food groups, those with a correlation of ρ >|0.15| with plasma or urine TMAO levels were further investigated in multivariate linear regression models showing current fish and (red) meat consumption as plausible dietary sources of TMAO. Overall, explained variance of TMAO levels by current diet and co-variates (age, sex, lean body mass, glomerular filtration rate) was small. Associations with urine and plasma concentrations differed depending on the TMAO source. Fish consumption was associated with urine and plasma TMAO concentrations, whereas meat consumption was only associated with TMAO concentrations in plasma. Furthermore, associations of plasma TMAO concentration with fish consumption were two times stronger than with meat consumption.
Conclusions
: Meat and fish consumption differentially affects TMAO concentrations in body fluids. Only a small fraction of variance is explained by current diet.
This article is protected by copyright. All rights reserved
83 citations
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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: The Statistical Update represents the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA's My Life Check - Life’s Simple 7, which include core health behaviors and health factors that contribute to cardiovascular health.
Abstract: Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter.
Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter.
Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …
5,102 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
4,069 citations