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Ulrike Peters

Bio: Ulrike Peters is an academic researcher from Fred Hutchinson Cancer Research Center. The author has contributed to research in topics: Colorectal cancer & Genome-wide association study. The author has an hindex of 78, co-authored 371 publications receiving 27276 citations. Previous affiliations of Ulrike Peters include University of Washington & University of North Carolina at Chapel Hill.


Papers
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01 Jan 2015
TL;DR: This paper conducted a genome-wide association study and meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals.
Abstract: Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

2,721 citations

Journal ArticleDOI
Shane A. McCarthy1, Sayantan Das2, Warren W. Kretzschmar3, Olivier Delaneau4, Andrew R. Wood5, Alexander Teumer6, Hyun Min Kang2, Christian Fuchsberger2, Petr Danecek1, Kevin Sharp3, Yang Luo1, C Sidore7, Alan Kwong2, Nicholas J. Timpson8, Seppo Koskinen, Scott I. Vrieze9, Laura J. Scott2, He Zhang2, Anubha Mahajan3, Jan H. Veldink, Ulrike Peters10, Ulrike Peters11, Carlos N. Pato12, Cornelia M. van Duijn13, Christopher E. Gillies2, Ilaria Gandin14, Massimo Mezzavilla, Arthur Gilly1, Massimiliano Cocca14, Michela Traglia, Andrea Angius7, Jeffrey C. Barrett1, D.I. Boomsma15, Kari Branham2, Gerome Breen16, Gerome Breen17, Chad M. Brummett2, Fabio Busonero7, Harry Campbell18, Andrew T. Chan19, Sai Chen2, Emily Y. Chew20, Francis S. Collins20, Laura J Corbin8, George Davey Smith8, George Dedoussis21, Marcus Dörr6, Aliki-Eleni Farmaki21, Luigi Ferrucci20, Lukas Forer22, Ross M. Fraser2, Stacey Gabriel23, Shawn Levy, Leif Groop24, Leif Groop25, Tabitha A. Harrison10, Andrew T. Hattersley5, Oddgeir L. Holmen26, Kristian Hveem26, Matthias Kretzler2, James Lee27, Matt McGue28, Thomas Meitinger29, David Melzer5, Josine L. Min8, Karen L. Mohlke30, John B. Vincent31, Matthias Nauck6, Deborah A. Nickerson11, Aarno Palotie19, Aarno Palotie23, Michele T. Pato12, Nicola Pirastu14, Melvin G. McInnis2, J. Brent Richards32, J. Brent Richards16, Cinzia Sala, Veikko Salomaa, David Schlessinger20, Sebastian Schoenherr22, P. Eline Slagboom33, Kerrin S. Small16, Tim D. Spector16, Dwight Stambolian34, Marcus A. Tuke5, Jaakko Tuomilehto, Leonard H. van den Berg, Wouter van Rheenen, Uwe Völker6, Cisca Wijmenga35, Daniela Toniolo, Eleftheria Zeggini1, Paolo Gasparini14, Matthew G. Sampson2, James F. Wilson18, Timothy M. Frayling5, Paul I.W. de Bakker36, Morris A. Swertz35, Steven A. McCarroll19, Charles Kooperberg10, Annelot M. Dekker, David Altshuler, Cristen J. Willer2, William G. Iacono28, Samuli Ripatti24, Nicole Soranzo27, Nicole Soranzo1, Klaudia Walter1, Anand Swaroop20, Francesco Cucca7, Carl A. Anderson1, Richard M. Myers, Michael Boehnke2, Mark I. McCarthy37, Mark I. McCarthy3, Richard Durbin1, Gonçalo R. Abecasis2, Jonathan Marchini3 
TL;DR: A reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies.
Abstract: We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.

2,149 citations

Journal ArticleDOI
Andrew R. Wood1, Tõnu Esko2, Jian Yang3, Sailaja Vedantam4  +441 moreInstitutions (132)
TL;DR: This article identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height, and all common variants together captured 60% of heritability.
Abstract: Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

1,872 citations

Shane A. McCarthy, Sayantan Das, Warren W. Kretzschmar, Olivier Delaneau, Andrew R. Wood, Alexander Teumer, Hyun Min Kang, Christian Fuchsberger, Petr Danecek, Kevin Sharp, Yang Luo, Carlo Sidorel, Alan Kwong, Nicholas J. Timpson, Seppo Koskinen, Scott I. Vrieze, Laura J. Scott, He Zhang, Anubha Mahajan, Jan H. Veldink, Ulrike Peters, Carlos N. Pato, Cornelia M. van Duijn, Christopher E. Gillies, Ilaria Gandin, Massimo Mezzavilla, Arthur Gilly, Massimiliano Cocca, Michela Traglia, Andrea Angius, Jeffrey C. Barrett, D.I. Boomsma, Kari Branham, Gerome Breen, Chad M. Brummett, Fabio Busonero, Harry Campbell, Andrew T. Chan, Sai Che, Emily Y. Chew, Francis S. Collins, Laura J Corbin, George Davey Smith, George Dedoussis, Marcus Dörr, Aliki-Eleni Farmaki, Luigi Ferrucci, Lukas Forer, Ross M. Fraser, Stacey Gabriel, Shawn Levy, Leif Groop, Tabitha A. Harrison, Andrew T. Hattersley, Oddgeir L. Holmen, Kristian Hveem, Matthias Kretzler, James Lee, Matt McGue, Thomas Meitinger, David Melzer, Josine L. Min, Karen L. Mohlke, John B. Vincent, Matthias Nauck, Deborah A. Nickerson, Aarno Palotie, Michele T. Pato, Nicola Pirastu, Melvin G. McInnis, J. Brent Richards, Cinzia Sala, Veikko Salomaa, David Schlessinger, Sebastian Schoenherr, P. Eline Slagboom, Kerrin S. Small, Tim D. Spector, Dwight Stambolian, Marcus A. Tuke, Jaakko Tuomilehto, Leonard H. van den Berg, Wouter van Rheenen, Uwe Völker, Cisca Wijmenga, Daniela Toniolo, Eleftheria Zeggini, Paolo Gasparini, Matthew G. Sampson, James F. Wilson, Timothy M. Frayling, Paul I.W. de Bakker, Morris A. Swertz, Steven A. McCarroll, Charles Kooperberg, Annelot M. Dekker, David Altshuler, Cristen J. Willer, William G. Iacono, Samuli Ripatti, Nicole Soranzo, Klaudia Walter, Anand Swaroop, Francesco Cucca, Carl A. Anderson, Richard M. Myers, Michael Boehnke, Mark I. McCarthy, Richard Durbin, Gonçalo R. Abecasis, Jonathan Marchini 
01 Jan 2016
TL;DR: In this article, a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry is presented.
Abstract: We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.

1,261 citations

Journal ArticleDOI
TL;DR: Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal cancers, it is determined that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants.
Abstract: We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15-20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries.

666 citations


Cited by
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Journal ArticleDOI
06 Jun 2013-Cell
TL;DR: Nine tentative hallmarks that represent common denominators of aging in different organisms are enumerated, with special emphasis on mammalian aging, to identify pharmaceutical targets to improve human health during aging, with minimal side effects.

9,980 citations

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
11 Oct 2018-Nature
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