Literature DB >> 30342790

Genomic and Phenomic Research in the 21st Century.

Scott Hebbring1.   

Abstract

The field of human genomics has changed dramatically over time. Initial genomic studies were predominantly restricted to rare disorders in small families. Over the past decade, researchers changed course from family-based studies and instead focused on common diseases and traits in populations of unrelated individuals. With further advancements in biobanking, computer science, electronic health record (EHR) data, and more affordable high-throughput genomics, we are experiencing a new paradigm in human genomic research. Rapidly changing technologies and resources now make it possible to study thousands of diseases simultaneously at the genomic level. This review will focus on these advancements as scientists begin to incorporate phenome-wide strategies in human genomic research to understand the etiology of human diseases and develop new drugs to treat them.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  GWAS; PheWAS; big data; biobank; drug development; genome-wide association study; phenome-wide association study; pleiotropy

Mesh:

Year:  2018        PMID: 30342790      PMCID: PMC6309501          DOI: 10.1016/j.tig.2018.09.007

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  103 in total

1.  Dissection of genomewide-scan data in extended families reveals a major locus and oligogenic susceptibility for age-related macular degeneration.

Authors:  Sudha K Iyengar; Danhong Song; Barbara E K Klein; Ronald Klein; James H Schick; Jennifer Humphrey; Christopher Millard; Rachel Liptak; Karlie Russo; Gyungah Jun; Kristine E Lee; Bonnie Fijal; Robert C Elston
Journal:  Am J Hum Genet       Date:  2003-12-19       Impact factor: 11.025

2.  Common genetic variants account for differences in gene expression among ethnic groups.

Authors:  Richard S Spielman; Laurel A Bastone; Joshua T Burdick; Michael Morley; Warren J Ewens; Vivian G Cheung
Journal:  Nat Genet       Date:  2007-01-07       Impact factor: 38.330

3.  Estimation of complex effect-size distributions using summary-level statistics from genome-wide association studies across 32 complex traits.

Authors:  Yan Zhang; Guanghao Qi; Ju-Hyun Park; Nilanjan Chatterjee
Journal:  Nat Genet       Date:  2018-08-13       Impact factor: 38.330

4.  Metformin pharmacogenomics: a genome-wide association study to identify genetic and epigenetic biomarkers involved in metformin anticancer response using human lymphoblastoid cell lines.

Authors:  Nifang Niu; Tongzheng Liu; Junmei Cairns; Reynold C Ly; Xianglin Tan; Min Deng; Brooke L Fridley; Krishna R Kalari; Ryan P Abo; Gregory Jenkins; Anthony Batzler; Erin E Carlson; Poulami Barman; Sebastian Moran; Holger Heyn; Manel Esteller; Liewei Wang
Journal:  Hum Mol Genet       Date:  2016-11-01       Impact factor: 6.150

5.  Profiling and Leveraging Relatedness in a Precision Medicine Cohort of 92,455 Exomes.

Authors:  Jeffrey Staples; Evan K Maxwell; Nehal Gosalia; Claudia Gonzaga-Jauregui; Christopher Snyder; Alicia Hawes; John Penn; Ricardo Ulloa; Xiaodong Bai; Alexander E Lopez; Cristopher V Van Hout; Colm O'Dushlaine; Tanya M Teslovich; Shane E McCarthy; Suganthi Balasubramanian; H Lester Kirchner; Joseph B Leader; Michael F Murray; David H Ledbetter; Alan R Shuldiner; George D Yancoupolos; Frederick E Dewey; David J Carey; John D Overton; Aris Baras; Lukas Habegger; Jeffrey G Reid
Journal:  Am J Hum Genet       Date:  2018-05-03       Impact factor: 11.025

6.  PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

Authors:  Joshua C Denny; Marylyn D Ritchie; Melissa A Basford; Jill M Pulley; Lisa Bastarache; Kristin Brown-Gentry; Deede Wang; Dan R Masys; Dan M Roden; Dana C Crawford
Journal:  Bioinformatics       Date:  2010-03-24       Impact factor: 6.937

7.  A PheWAS approach in studying HLA-DRB1*1501.

Authors:  S J Hebbring; S J Schrodi; Z Ye; Z Zhou; D Page; M H Brilliant
Journal:  Genes Immun       Date:  2013-02-07       Impact factor: 2.676

8.  Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.

Authors:  Joshua C Denny; Lisa Bastarache; Marylyn D Ritchie; Robert J Carroll; Raquel Zink; Jonathan D Mosley; Julie R Field; Jill M Pulley; Andrea H Ramirez; Erica Bowton; Melissa A Basford; David S Carrell; Peggy L Peissig; Abel N Kho; Jennifer A Pacheco; Luke V Rasmussen; David R Crosslin; Paul K Crane; Jyotishman Pathak; Suzette J Bielinski; Sarah A Pendergrass; Hua Xu; Lucia A Hindorff; Rongling Li; Teri A Manolio; Christopher G Chute; Rex L Chisholm; Eric B Larson; Gail P Jarvik; Murray H Brilliant; Catherine A McCarty; Iftikhar J Kullo; Jonathan L Haines; Dana C Crawford; Daniel R Masys; Dan M Roden
Journal:  Nat Biotechnol       Date:  2013-12       Impact factor: 54.908

9.  Next-generation phenotyping of electronic health records.

Authors:  George Hripcsak; David J Albers
Journal:  J Am Med Inform Assoc       Date:  2012-09-06       Impact factor: 4.497

10.  Phenome-wide association study for CYP2A6 alleles: rs113288603 is associated with hearing loss symptoms in elderly smokers.

Authors:  Renato Polimanti; Kevin P Jensen; Joel Gelernter
Journal:  Sci Rep       Date:  2017-04-21       Impact factor: 4.379

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  6 in total

Review 1.  Using Human Genetics to Understand Mechanisms in Ischemic Stroke Outcome: From Early Brain Injury to Long-Term Recovery.

Authors:  Jin-Moo Lee; Israel Fernandez-Cadenas; Arne G Lindgren
Journal:  Stroke       Date:  2021-08-17       Impact factor: 10.170

2.  E-Pedigrees: a large-scale automatic family pedigree prediction application.

Authors:  Xiayuan Huang; Nicholas Tatonetti; Katie LaRow; Brooke Delgoffee; John Mayer; David Page; Scott J Hebbring
Journal:  Bioinformatics       Date:  2021-06-04       Impact factor: 6.931

3.  A web-based survey on various symptoms of computer vision syndrome and the genetic understanding based on a multi-trait genome-wide association study.

Authors:  Keito Yoshimura; Yuji Morita; Kenji Konomi; Sachiko Ishida; Daisuke Fujiwara; Keisuke Kobayashi; Masami Tanaka
Journal:  Sci Rep       Date:  2021-05-03       Impact factor: 4.379

Review 4.  Great future or greedy venture: Precision medicine needs philosophy.

Authors:  Fei Jiao; Ruoyu Guo; Jacques S Beckmann; Zhonghai Yan; Yun Yang; Jinxia Hu; Xin Wang; Shuyang Xie
Journal:  Health Sci Rep       Date:  2021-09-14

Review 5.  The Genetics of Polycystic Ovary Syndrome: An Overview of Candidate Gene Systematic Reviews and Genome-Wide Association Studies.

Authors:  Danielle Hiam; Alba Moreno-Asso; Helena J Teede; Joop S E Laven; Nigel K Stepto; Lisa J Moran; Melanie Gibson-Helm
Journal:  J Clin Med       Date:  2019-10-03       Impact factor: 4.241

6.  Genomics of Gulf War Illness in U.S. Veterans Who Served during the 1990-1991 Persian Gulf War: Methods and Rationale for Veterans Affairs Cooperative Study #2006.

Authors:  Krishnan Radhakrishnan; Elizabeth R Hauser; Renato Polimanti; Drew A Helmer; Dawn Provenzale; Rebecca B McNeil; Alysia Maffucci; Rachel Quaden; Hongyu Zhao; Stacey B Whitbourne; Kelly M Harrington; Jacqueline Vahey; Joel Gelernter; Daniel F Levey; Grant D Huang; John Michael Gaziano; John Concato; Mihaela Aslan
Journal:  Brain Sci       Date:  2021-06-25
  6 in total

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