Literature DB >> 26875678

Unravelling the human genome-phenome relationship using phenome-wide association studies.

William S Bush1, Matthew T Oetjens2, Dana C Crawford1.   

Abstract

Advances in genotyping technology have, over the past decade, enabled the focused search for common genetic variation associated with human diseases and traits. With the recently increased availability of detailed phenotypic data from electronic health records and epidemiological studies, the impact of one or more genetic variants on the phenome is starting to be characterized both in clinical and population-based settings using phenome-wide association studies (PheWAS). These studies reveal a number of challenges that will need to be overcome to unlock the full potential of PheWAS for the characterization of the complex human genome-phenome relationship.

Entities:  

Mesh：

Year:  2016        PMID： 26875678     DOI： 10.1038/nrg.2015.36

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN： 1471-0056            Impact factor:   53.242


  172 in total

1.  Using PhenX measures to identify opportunities for cross-study analysis.

Authors:  Huaqin Pan; Kimberly A Tryka; Daniel J Vreeman; Wayne Huggins; Michael J Phillips; Jayashri P Mehta; Jacqueline H Phillips; Clement J McDonald; Heather A Junkins; Erin M Ramos; Carol M Hamilton
Journal:  Hum Mutat       Date:  2012-04-03       Impact factor: 4.878

Review 2.  Phenome-Wide Association Studies: Embracing Complexity for Discovery.

Authors:  Sarah A Pendergrass; Anurag Verma; Anna Okula; Molly A Hall; Dana C Crawford; Marylyn D Ritchie
Journal:  Hum Hered       Date:  2015-07-28       Impact factor: 0.444

3.  R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment.

Authors:  Robert J Carroll; Lisa Bastarache; Joshua C Denny
Journal:  Bioinformatics       Date:  2014-04-14       Impact factor: 6.937

4.  Body mass index and the built and social environments in children and adolescents using electronic health records.

Authors:  Brian S Schwartz; Walter F Stewart; Sarah Godby; Jonathan Pollak; Joseph Dewalle; Sharon Larson; Dione G Mercer; Thomas A Glass
Journal:  Am J Prev Med       Date:  2011-10       Impact factor: 5.043

5.  Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels.

Authors:  Richa Saxena; Benjamin F Voight; Valeriya Lyssenko; Noël P Burtt; Paul I W de Bakker; Hong Chen; Jeffrey J Roix; Sekar Kathiresan; Joel N Hirschhorn; Mark J Daly; Thomas E Hughes; Leif Groop; David Altshuler; Peter Almgren; Jose C Florez; Joanne Meyer; Kristin Ardlie; Kristina Bengtsson Boström; Bo Isomaa; Guillaume Lettre; Ulf Lindblad; Helen N Lyon; Olle Melander; Christopher Newton-Cheh; Peter Nilsson; Marju Orho-Melander; Lennart Råstam; Elizabeth K Speliotes; Marja-Riitta Taskinen; Tiinamaija Tuomi; Candace Guiducci; Anna Berglund; Joyce Carlson; Lauren Gianniny; Rachel Hackett; Liselotte Hall; Johan Holmkvist; Esa Laurila; Marketa Sjögren; Maria Sterner; Aarti Surti; Margareta Svensson; Malin Svensson; Ryan Tewhey; Brendan Blumenstiel; Melissa Parkin; Matthew Defelice; Rachel Barry; Wendy Brodeur; Jody Camarata; Nancy Chia; Mary Fava; John Gibbons; Bob Handsaker; Claire Healy; Kieu Nguyen; Casey Gates; Carrie Sougnez; Diane Gage; Marcia Nizzari; Stacey B Gabriel; Gung-Wei Chirn; Qicheng Ma; Hemang Parikh; Delwood Richardson; Darrell Ricke; Shaun Purcell
Journal:  Science       Date:  2007-04-26       Impact factor: 47.728

6.  The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.

Authors:  Tara C Matise; Jose Luis Ambite; Steven Buyske; Christopher S Carlson; Shelley A Cole; Dana C Crawford; Christopher A Haiman; Gerardo Heiss; Charles Kooperberg; Loic Le Marchand; Teri A Manolio; Kari E North; Ulrike Peters; Marylyn D Ritchie; Lucia A Hindorff; Jonathan L Haines
Journal:  Am J Epidemiol       Date:  2011-08-11       Impact factor: 4.897

7.  Patterns of cis regulatory variation in diverse human populations.

Authors:  Barbara E Stranger; Stephen B Montgomery; Antigone S Dimas; Leopold Parts; Oliver Stegle; Catherine E Ingle; Magda Sekowska; George Davey Smith; David Evans; Maria Gutierrez-Arcelus; Alkes Price; Towfique Raj; James Nisbett; Alexandra C Nica; Claude Beazley; Richard Durbin; Panos Deloukas; Emmanouil T Dermitzakis
Journal:  PLoS Genet       Date:  2012-04-19       Impact factor: 5.917

8.  Pleiotropic genes for metabolic syndrome and inflammation.

Authors:  Aldi T Kraja; Daniel I Chasman; Kari E North; Alexander P Reiner; Lisa R Yanek; Tuomas O Kilpeläinen; Jennifer A Smith; Abbas Dehghan; Josée Dupuis; Andrew D Johnson; Mary F Feitosa; Fasil Tekola-Ayele; Audrey Y Chu; Ilja M Nolte; Zari Dastani; Andrew Morris; Sarah A Pendergrass; Yan V Sun; Marylyn D Ritchie; Ahmad Vaez; Honghuang Lin; Symen Ligthart; Letizia Marullo; Rebecca Rohde; Yaming Shao; Mark A Ziegler; Hae Kyung Im; Renate B Schnabel; Torben Jørgensen; Marit E Jørgensen; Torben Hansen; Oluf Pedersen; Ronald P Stolk; Harold Snieder; Albert Hofman; Andre G Uitterlinden; Oscar H Franco; M Arfan Ikram; J Brent Richards; Charles Rotimi; James G Wilson; Leslie Lange; Santhi K Ganesh; Mike Nalls; Laura J Rasmussen-Torvik; James S Pankow; Josef Coresh; Weihong Tang; W H Linda Kao; Eric Boerwinkle; Alanna C Morrison; Paul M Ridker; Diane M Becker; Jerome I Rotter; Sharon L R Kardia; Ruth J F Loos; Martin G Larson; Yi-Hsiang Hsu; Michael A Province; Russell Tracy; Benjamin F Voight; Dhananjay Vaidya; Christopher J O'Donnell; Emelia J Benjamin; Behrooz Z Alizadeh; Inga Prokopenko; James B Meigs; Ingrid B Borecki
Journal:  Mol Genet Metab       Date:  2014-05-09       Impact factor: 4.797

9.  A genome-wide association study identifies novel alleles associated with hair color and skin pigmentation.

Authors:  Jiali Han; Peter Kraft; Hongmei Nan; Qun Guo; Constance Chen; Abrar Qureshi; Susan E Hankinson; Frank B Hu; David L Duffy; Zhen Zhen Zhao; Nicholas G Martin; Grant W Montgomery; Nicholas K Hayward; Gilles Thomas; Robert N Hoover; Stephen Chanock; David J Hunter
Journal:  PLoS Genet       Date:  2008-05-16       Impact factor: 5.917

10.  Automated extraction of clinical traits of multiple sclerosis in electronic medical records.

Authors:  Mary F Davis; Subramaniam Sriram; William S Bush; Joshua C Denny; Jonathan L Haines
Journal:  J Am Med Inform Assoc       Date:  2013-10-22       Impact factor: 4.497
View more
  105 in total

1.  Using Electronic Health Records To Generate Phenotypes For Research.

Authors:  Sarah A Pendergrass; Dana C Crawford
Journal:  Curr Protoc Hum Genet       Date:  2018-12-05

Review 2.  High-throughput mouse phenomics for characterizing mammalian gene function.

Authors:  Steve D M Brown; Chris C Holmes; Ann-Marie Mallon; Terrence F Meehan; Damian Smedley; Sara Wells
Journal:  Nat Rev Genet       Date:  2018-06       Impact factor: 53.242

Review 3.  The UMOD Locus: Insights into the Pathogenesis and Prognosis of Kidney Disease.

Authors:  Olivier Devuyst; Cristian Pattaro
Journal:  J Am Soc Nephrol       Date:  2017-11-27       Impact factor: 10.121

4.  Statistical Impact of Sample Size and Imbalance on Multivariate Analysis in silico and A Case Study in the UK Biobank.

Authors:  Xinyuan Zhang; Ruowang Li; Marylyn D Ritchie
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

5.  Genetic Epidemiology of Complex Phenotypes.

Authors:  Darren D O'Rielly; Proton Rahman
Journal:  Methods Mol Biol       Date:  2021

6.  Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms.

Authors:  Michael H Guo; Satish K Nandakumar; Jacob C Ulirsch; Seyedeh M Zekavat; Jason D Buenrostro; Pradeep Natarajan; Rany M Salem; Roberto Chiarle; Mario Mitt; Mart Kals; Kalle Pärn; Krista Fischer; Lili Milani; Reedik Mägi; Priit Palta; Stacey B Gabriel; Andres Metspalu; Eric S Lander; Sekar Kathiresan; Joel N Hirschhorn; Tõnu Esko; Vijay G Sankaran
Journal:  Proc Natl Acad Sci U S A       Date:  2016-12-28       Impact factor: 11.205

7.  A Phenome-Wide Association Study Uncovers a Role for Autoimmunity in the Development of Chronic Obstructive Pulmonary Disease.

Authors:  Xiangming Ji; Xinnan Niu; Jun Qian; Victoria Martucci; Sarah A Pendergrass; Ivan P Gorlov; Christopher I Amos; Joshua C Denny; Pierre P Massion; Melinda C Aldrich
Journal:  Am J Respir Cell Mol Biol       Date:  2018-06       Impact factor: 6.914

8.  Association of Interleukin 6 Receptor Variant With Cardiovascular Disease Effects of Interleukin 6 Receptor Blocking Therapy: A Phenome-Wide Association Study.

Authors:  Tianxi Cai; Yichi Zhang; Yuk-Lam Ho; Nicholas Link; Jiehuan Sun; Jie Huang; Tianrun A Cai; Scott Damrauer; Yuri Ahuja; Jacqueline Honerlaw; Jie Huang; Lauren Costa; Petra Schubert; Chuan Hong; David Gagnon; Yan V Sun; J Michael Gaziano; Peter Wilson; Kelly Cho; Philip Tsao; Christopher J O'Donnell; Katherine P Liao
Journal:  JAMA Cardiol       Date:  2018-09-01       Impact factor: 14.676

9.  A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies.

Authors:  Zhonghua Liu; Xihong Lin
Journal:  J Am Stat Assoc       Date:  2019-02-26       Impact factor: 5.033

10.  Leveraging Genome and Phenome-Wide Association Studies to Investigate Genetic Risk of Acute Lymphoblastic Leukemia.

Authors:  Eleanor C Semmes; Jayaram Vijayakrishnan; Chenan Zhang; Jillian H Hurst; Richard S Houlston; Kyle M Walsh
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-05-28       Impact factor: 4.254
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.