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DOI: 10.15265/IY-2014-0015
Surveying Recent Themes in Translational Bioinformatics: Big Data in EHRs, Omics for Drugs, and Personal Genomics
Correspondence to:
Publication History
15 August 2014
Publication Date:
05 March 2018 (online)
Summary
Objective: To provide a survey of recent progress in the use of large-scale biologic data to impact clinical care, and the impact the reuse of electronic health record data has made in genomic discovery.
Method: Survey of key themes in translational bioinformatics, primarily from 2012 and 2013.
Result: This survey focuses on four major themes: the growing use of Electronic Health Records (EHRs) as a source for genomic discovery, adoption of genomics and pharmacogenomics in clinical practice, the possible use of genomic technologies for drug repurposing, and the use of personal genomics to guide care.
Conclusion: Reuse of abundant clinical data for research is speeding discovery, and implementation of genomic data into clinical medicine is impacting care with new classes of data rarely used previously in medicine.
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Keywords
Translational bioinformatics - personalized medicine - electronic health records - genomics - big data
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References
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Correspondence to:
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References
- 1 Green ED, Guyer MS. Charting a course for genomic medicine from base pairs to bedside.. Nature 2011; Feb 10 470 7333 204-13.
- 2 International Human Genome Sequencing Consortium.. Finishing the euchromatic sequence of the human genome.. Nature 2004; Oct 21 431 7011 931-45.
- 3 Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits.. Proc Natl Acad Sci USA 2009; Jun 9 106 (23) 9362-7.
- 4 OMIM - Online Mendelian Inheritance in Man [Internet].. [cited 2014 May 20].. Available from: http://omim.org
- 5 Altman RB, Miller KS. 2010 Translational bioinformatics year in review.. J Am Med Inform Assoc 2011; Jul 1 18 (04) 358-66.
- 6 McCarty CA, Chisholm RL, Chute CG, Kullo IJ, Jarvik GP, Larson EB. et al. The eMERGE Network: A consortium of biorepositories linked to electronic medical records data for conducting genomic studies.. BMC Med Genomics 2011; 4 (01) 13.
- 7 Gottesman O, Kuivaniemi H, Tromp G, Faucett WA, Li R, Manolio TA. et al. The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future.. Genet Med 2013; 15 (10) 761-71.
- 8 Denny JC, Ritchie MD, Crawford DC, Schildcrout JS, Ramirez AH, Pulley JM. et al. Identification of genomic predictors of atrioventricular conduction: using electronic medical records as a tool for genome science.. Circulation 2010; Nov 16 122 (20) 2016-21.
- 9 Kullo IJ, Ding K, Jouni H, Smith CY, Chute CG. A genome-wide association study of red blood cell traits using the electronic medical record.. PloS One [Internet].; 2010. [cited 2010 Oct 29];5(9). Available from: http://www.ncbi.nlm.nih.gov/pubmed/20927387
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- 11 Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K. et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.. Bioinformatics 2010; May 1 26 (09) 1205-10.
- 12 Newton KM, Peissig PL, Kho AN, Bielinski SJ, Berg RL, Choudhary V. et al. Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network.. J Am Med Inform Assoc 2013 Mar 26;
- 13 Denny JC, Crawford DC, Ritchie MD, Bielinski SJ, Basford MA, Bradford Y. et al. Variants Near FOXE1 Are Associated with Hypothyroidism and Other Thyroid Conditions: Using Electronic Medical Records for Genome- and Phenome-wide Studies.. Am J Hum Genet 2011; Oct 7 89 (04) 529-42.
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- 16 Delaney JT, Ramirez AH, Bowton E, Pulley JM, Basford MA, Schildcrout JS. et al. Predicting clopidogrel response using DNA samples linked to an electronic health record.. Clin Pharmacol Ther 2012; Feb 91 (02) 257-63.
- 17 Xu H, Jiang M, Oetjens M, Bowton EA, Ramirez AH, Jeff JM. et al. Facilitating pharmacogenetic studies using electronic health records and natural-language processing: a case study of warfarin.. J Am Med Inform Assoc 2011; Aug 18 (04) 387-91.
- 18 Wei W-Q, Feng Q, Jiang L, Waitara MS, Iwuchukwu OF, Roden DM. et al. Characterization of Statin Dose Response in Electronic Medical Records.. Clin Pharmacol Ther [Internet]; 2013. Nov 13 [cited 2013 Dec 31]; Available from: http://www.nature.com/clpt/journal/vaop/ncurrent/full/clpt2013202a.html
- 19 Wilke RA, Xu H, Denny JC, Roden DM, Krauss RM, McCarty CA. et al. The emerging role of electronic medical records in pharmacogenomics.. Clin Pharmacol Ther 2011; Mar 89 (03) 379-86.
- 20 Bowton E, Field JR, Wang S, Schildcrout JS, Van Driest SL, Delaney JT. et al. Biobanks and electronic medical records: enabling cost-effective research.. Sci Transl Med 2014; Apr 30 6 (234) 234cm3.
- 21 Hebbring SJ. The Challenges, Advantages, and Future of Phenome-Wide Association Studies.. Immunology; 2013. Oct 22;
- 22 Hebbring SJ, Schrodi SJ, Ye Z, Zhou Z, Page D, Brilliant MH. A PheWAS approach in studying HLA-DRB1*1501.. Genes Immun 2013; Apr 14 (03) 187-91.
- 23 Ritchie MD, Denny JC, Zuvich RL, Crawford DC, Schildcrout JS, Bastarache L. et al. Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.. Circulation 2013; Apr 2 127 (13) 1377-85.
- 24 Shameer K, Denny JC, Ding K, Jouni H, Crosslin DR, de Andrade M. et al. A genome- and phenome-wide association study to identify genetic variants influencing platelet count and volume and their pleiotropic effects.. Hum Genet; 2013. Sep 12;
- 25 Denny JC, Bastarache L, Ritchie MD, Carroll RJ, Zink R, Mosley JD. et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.. Nat Biotechnol 2013; Nov 24 31 (12) 1102-11.
- 26 Pendergrass SA, Brown-Gentry K, Dudek S, Frase A, Torstenson ES, Goodloe R. et al. Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network.. PLoS Genet 2013; 9 (01) e 1003087.
- 27 Pendergrass SA, Dudek SM, Crawford DC, Ritchie MD. Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View.. BioData Min 2012; 5 (01) 5.
- 28 Million Veteran Program (MVP) [Internet].. [cited 2012 Jun 20].. Available from: http://www.research.va.gov/mvp/
- 29 The Research Program on Genes, Environment, and Health [Internet].. [cited 2014 Jan 2].. Available from: http://www.dor.kaiser.org/external/DORExternal/rpgeh/index.aspx?ekmensel=194f64c3_47_48_btnlink
- 30 Collins R. What makes UK Biobank special?. Lancet 2012; Mar 31 379 9822 1173-4.
- 31 Chen Z, Chen J, Collins R, Guo Y, Peto R, Wu F. et al. China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up.. Int J Epidemiol 2011; Dec 40 (06) 1652-66.
- 32 LePendu P, Iyer SV, Bauer-Mehren A, Harpaz R, Mortensen JM, Podchiyska T. et al. Pharmacovigilance Using Clinical Notes.. Clin Pharmacol Ther [Internet]; 2013. Apr 10 [cited 2013 Apr 12]; Available from: http://www.nature.com/clpt/journal/vaop/ncurrent/full/clpt201347a.html
- 33 Leeper NJ, Bauer-Mehren A, Iyer SV, LePendu P, Olson C, Shah NH. Practice-Based Evidence: Profiling the Safety of Cilostazol by Text-Mining of Clinical Notes.. PLoS ONE 2013; May 23 8 (05) e 63499.
- 34 Ryan PB, Madigan D, Stang PE, Schuemie MJ, Hripcsak G. Medication-Wide Association Studies.. CPT Pharmacomet Syst Pharmacol 2013; Sep 18 2 (09) e76.
- 35 Frankovich J, Longhurst CA, Sutherland SM. Evidence-Based Medicine in the EMR Era.. N Engl J Med 2011; 365 (19) 1758-9.
- 36 Liao KP, Kurreeman F, Li G, Duclos G, Murphy S. P RG, et al. Autoantibodies, autoimmune risk alleles and clinical associations in rheumatoid arthritis cases and non-RA controls in the electronic medical records.. Arthritis Rheum; 2012. Dec 10;
- 37 Neuraz A, Chouchana L, Malamut G, Le Beller C, Roche D, Beaune P. et al. Phenome-Wide Association Studies on a Quantitative Trait: Application to TPMT Enzyme Activity and Thiopurine Therapy in Pharmacogenomics.. PLoS Comput Biol 2013; Dec 26 9 (12) e 1003405.
- 38 Boland MR, Hripcsak G, Albers DJ, Wei Y, Wilcox AB, Wei J. et al. Discovering medical conditions associated with periodontitis using linked electronic health records.. J Clin Periodontol 2013; May 40 (05) 474-82.
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