Phenome-wide association studies: a new method for functional genomics in humans

被引:27
作者
Roden, Dan M. [1 ,2 ,3 ]
机构
[1] Vanderbilt Univ, Med Ctr, Dept Med, 221 Kirkland Hall, Nashville, TN 37235 USA
[2] Vanderbilt Univ, Med Ctr, Dept Pharmacol, 221 Kirkland Hall, Nashville, TN 37235 USA
[3] Vanderbilt Univ, Med Ctr, Dept Biomed Informat, 221 Kirkland Hall, Nashville, TN 37235 USA
来源
JOURNAL OF PHYSIOLOGY-LONDON | 2017年 / 595卷 / 12期
基金
美国国家卫生研究院;
关键词
ELECTRONIC MEDICAL-RECORDS; HEALTH RECORDS; BIOBANK; VARIANTS; RISK;
D O I
10.1113/JP273122
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
In experimental physiological research, a common study design for examining the functional role of a gene or a genetic variant is to introduce that genetic variant into a model organism (such as yeast or mouse) and then to search for phenotypic consequences. The development of DNA biobanks linked to dense phenotypic information enables such an experiment to be applied to human subjects in the form of a phenome-wide association study (PheWAS). The PheWAS paradigm takes advantage of a curated medical phenome, often derived from electronic health records, to search for associations between 'input functions' and phenotypes in an unbiased fashion. The most commonly studied input function to date has been single nucleotide polymorphisms (SNPs), but other inputs, such as sets of SNPs or a disease or drug exposure, are now being explored to probe the genetic and phenotypic architecture of human traits. Potential outcomes of these approaches include defining subsets of complex diseases (that can then be targeted by specific therapies) and drug repurposing.
引用
收藏
页码:4109 / 4115
页数:7
相关论文
共 33 条
  • [1] UK Biobank Data: Come and Get It
    Allen, Naomi E.
    Sudlow, Cathie
    Peakman, Tim
    Collins, Rory
    [J]. SCIENCE TRANSLATIONAL MEDICINE, 2014, 6 (224)
  • [2] Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort
    Banda, Yambazi
    Kvale, Mark N.
    Hoffmann, Thomas J.
    Hesselson, Stephanie E.
    Ranatunga, Dilrini
    Tang, Hua
    Sabatti, Chiara
    Croen, Lisa A.
    Dispensa, Brad P.
    Henderson, Mary
    Iribarren, Carlos
    Jorgenson, Eric
    Kushi, Lawrence H.
    Ludwig, Dana
    Olberg, Diane
    Quesenberry, Charles P., Jr.
    Rowell, Sarah
    Sadler, Marianne
    Sakoda, Lori C.
    Sciortino, Stanley
    Shen, Ling
    Smethurst, David
    Somkin, Carol P.
    Van Den Eeden, Stephen K.
    Walter, Lawrence
    Whitmer, Rachel A.
    Kwok, Pui-Yan
    Schaefer, Catherine
    Risch, Neil
    [J]. GENETICS, 2015, 200 (04) : 1285 - +
  • [3] Unravelling the human genome-phenome relationship using phenome-wide association studies
    Bush, William S.
    Oetjens, Matthew T.
    Crawford, Dana C.
    [J]. NATURE REVIEWS GENETICS, 2016, 17 (03) : 129 - 145
  • [4] China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up
    Chen, Zhengming
    Chen, Junshi
    Collins, Rory
    Guo, Yu
    Peto, Richard
    Wu, Fan
    Li, Liming
    [J]. INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2011, 40 (06) : 1652 - 1666
  • [5] A New Initiative on Precision Medicine
    Collins, Francis S.
    Varmus, Harold
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2015, 372 (09) : 793 - 795
  • [6] eMERGEing progress in genomics-the first seven years
    Crawford, Dana C.
    Crosslin, David R.
    Tromp, Gerard
    Kullo, Iftikhar J.
    Kuivaniemi, Helena
    Hayes, M. Geoffrey
    Denny, Joshua C.
    Bush, William S.
    Haines, Jonathan L.
    Roden, Dan M.
    McCarty, Catherine A.
    Jarvik, Gail P.
    Ritchie, Marylyn D.
    [J]. FRONTIERS IN GENETICS, 2014, 5
  • [7] Phenome-Wide Association Studies as a Tool to Advance Precision Medicine
    Denny, Joshua C.
    Bastarache, Lisa
    Roden, Dan M.
    [J]. ANNUAL REVIEW OF GENOMICS AND HUMAN GENETICS, VOL 17, 2016, 17 : 353 - 373
  • [8] Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data
    Denny, Joshua C.
    Bastarache, Lisa
    Ritchie, Marylyn D.
    Carroll, Robert J.
    Zink, Raquel
    Mosley, Jonathan D.
    Field, Julie R.
    Pulley, Jill M.
    Ramirez, Andrea H.
    Bowton, Erica
    Basford, Melissa A.
    Carrell, David S.
    Peissig, Peggy L.
    Kho, Abel N.
    Pacheco, Jennifer A.
    Rasmussen, Luke V.
    Crosslin, David R.
    Crane, Paul K.
    Pathak, Jyotishman
    Bielinski, Suzette J.
    Pendergrass, Sarah A.
    Xu, Hua
    Hindorff, Lucia A.
    Li, Rongling
    Manolio, Teri A.
    Chute, Christopher G.
    Chisholm, Rex L.
    Larson, Eric B.
    Jarvik, Gail P.
    Brilliant, Murray H.
    McCarty, Catherine A.
    Kullo, Iftikhar J.
    Haines, Jonathan L.
    Crawford, Dana C.
    Masys, Daniel R.
    Roden, Dan M.
    [J]. NATURE BIOTECHNOLOGY, 2013, 31 (12) : 1102 - +
  • [9] Variants Near FOXE1 Are Associated with Hypothyroidism and Other Thyroid Conditions: Using Electronic Medical Records for Genome- and Phenome-wide Studies
    Denny, Joshua C.
    Crawford, Dana C.
    Ritchie, Marylyn D.
    Bielinski, Suzette J.
    Basford, Melissa A.
    Bradford, Yuki
    Chai, High Seng
    Bastarache, Lisa
    Zuvich, Rebecca
    Peissig, Peggy
    Carrell, David
    Ramirez, Andrea H.
    Pathak, Jyotishman
    Wilke, Russell A.
    Rasmussen, Luke
    Wang, Xiaoming
    Pacheco, Jennifer A.
    Kho, Abel N.
    Hayes, M. Geoffrey
    Weston, Noah
    Matsumoto, Martha
    Kopp, Peter A.
    Newton, Katherine M.
    Jarvik, Gail P.
    Li, Rongling
    Manolio, Teri A.
    Kullo, Iftikhar J.
    Chute, Christopher G.
    Chisholm, Rex L.
    Larson, Eric B.
    McCarty, Catherine A.
    Masys, Daniel R.
    Roden, Dan M.
    de Andrade, Mariza
    [J]. AMERICAN JOURNAL OF HUMAN GENETICS, 2011, 89 (04) : 529 - 542
  • [10] PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations
    Denny, Joshua C.
    Ritchie, Marylyn D.
    Basford, Melissa A.
    Pulley, Jill M.
    Bastarache, Lisa
    Brown-Gentry, Kristin
    Wang, Deede
    Masys, Dan R.
    Roden, Dan M.
    Crawford, Dana C.
    [J]. BIOINFORMATICS, 2010, 26 (09) : 1205 - 1210