title: Implementation of the CDC translational informatics platform--from genetic variants to the national Swedish Rheumatology Quality Register.
abstract: BACKGROUND
  Sequencing of the human genome and the subsequent analyses have produced immense volumes of data. The technological advances have opened new windows into genomics beyond the DNA sequence. In parallel, clinical practice generate large amounts of data. This represents an underused data source that has much greater potential in translational research than is currently realized. This research aims at implementing a translational medicine informatics platform to integrate clinical data (disease diagnosis, diseases activity and treatment) of Rheumatoid Arthritis (RA) patients from Karolinska University Hospital and their research database (biobanks, genotype variants and serology) at the Center for Molecular Medicine, Karolinska Institutet.
  
  
  METHODS
  Requirements engineering methods were utilized to identify user requirements. Unified Modeling Language and data modeling methods were used to model the universe of discourse and data sources. Oracle11g were used as the database management system, and the clinical development center (CDC) was used as the application interface. Patient data were anonymized, and we employed authorization and security methods to protect the system.
  
  
  RESULTS
  We developed a user requirement matrix, which provided a framework for evaluating three translation informatics systems. The implementation of the CDC successfully integrated biological research database (15172 DNA, serum and synovial samples, 1436 cell samples and 65 SNPs per patient) and clinical database (5652 clinical visit) for the cohort of 379 patients presents three profiles. Basic functionalities provided by the translational medicine platform are research data management, development of bioinformatics workflow and analysis, sub-cohort selection, and re-use of clinical data in research settings. Finally, the system allowed researchers to extract subsets of attributes from cohorts according to specific biological, clinical, or statistical features.
  
  
  CONCLUSIONS
  Research and clinical database integration is a real challenge and a road-block in translational research. Through this research we addressed the challenges and demonstrated the usefulness of CDC. We adhered to ethical regulations pertaining to patient data, and we determined that the existing software solutions cannot meet the translational research needs at hand. We used RA as a test case since we have ample data on active and longitudinal cohort.
authors.affiliation: Department of Medicine, The Unit of Computational Medicine, Center for Molecular Medicine, Karolinska Institutet, Solna, Sweden.
authors.forename: Imad
authors.initials: I
authors.lastname: Abugessaisa
authors.forename: David
authors.initials: D
authors.lastname: Gomez-Cabrero
authors.forename: Omri
authors.initials: O
authors.lastname: Snir
authors.forename: Staffan
authors.initials: S
authors.lastname: Lindblad
authors.forename: Lars
authors.initials: L
authors.lastname: Klareskog
authors.forename: Vivianne
authors.initials: V
authors.lastname: Malmström
authors.forename: Jesper
authors.initials: J
authors.lastname: Tegnér
mesh_terms: D001172:Arthritis, Rheumatoid / Q000175:diagnosis* / Q000235:genetics*; D002487:Centers for Disease Control and Prevention, U.S.; D015331:Cohort Studies; D003196:Computer Graphics; D014644:Genetic Variation; D023281:Genomics; D005838:Genotype; D006801:Humans; D008490:Medical Informatics / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D012042:Registries; D012219:Rheumatology / Q000379:methods*; D017422:Sequence Analysis, DNA; D012984:Software; D013548:Sweden; D057170:Translational Research, Biomedical / Q000379:methods*; D014481:United States; D014584:User-Computer Interface
references.citation: Arthritis Rheum. 2010 Jan;62(1):44-52
references.pmid: 20039432
references.citation: Int J Med Inform. 2003 Apr;70(1):59-77
references.pmid: 12706183
references.citation: Med Law. 2007 Dec;26(4):677-97
references.pmid: 18284110
references.citation: Nature. 2012 Sep 13;489(7415):208
references.pmid: 22972285
references.citation: PLoS Genet. 2008 Aug 29;4(8):e1000167
references.pmid: 18769715
references.citation: J Am Med Inform Assoc. 2010 Mar-Apr;17(2):124-30
references.pmid: 20190053
references.citation: Ann Rheum Dis. 2011 Aug;70(8):1407-14
references.pmid: 21518724
references.citation: Lancet. 2009 Feb 21;373(9664):659-72
references.pmid: 19157532
references.citation: J Med Ethics. 2007 Jul;33(7):390-3
references.pmid: 17601865
references.citation: Nat Genet. 2007 Apr;39(4):425
references.pmid: 17392794
references.citation: Healthc Inform. 1997 Mar;14(3):74
references.pmid: 10166952
references.citation: Nat Genet. 2010 Jun;42(6):508-14
references.pmid: 20453842
references.citation: Ann Rheum Dis. 2011 Apr;70(4):624-9
references.pmid: 21149495
references.citation: Nat Rev Genet. 2003 May;4(5):337-45
references.pmid: 12728276
references.citation: J Crit Care. 2010 Jun;25(2):364.e1-9
references.pmid: 19836194
references.citation: JAMA. 2008 Jul 16;300(3):326-7
references.pmid: 18632546
references.citation: JAMA. 2008 Dec 17;300(23):2715
references.pmid: 19088343
references.citation: AMIA Annu Symp Proc. 2009 Nov 14;2009:391-5
references.pmid: 20351886
references.citation: Mol Biol Rep. 2012 May;39(5):5961-6
references.pmid: 22228086
references.citation: Am J Med Genet A. 2007 Mar 15;143A(6):564-9
references.pmid: 17318844
references.citation: Eur J Hum Genet. 2006 Nov;14(11):1170-8
references.pmid: 16868560
references.citation: Ann Intern Med. 1978 Mar;88(3):424-6
references.pmid: 629506
references.citation: Ann Rheum Dis. 2006 Jun;65(6):707-12
references.pmid: 16414975
references.citation: J Transl Med. 2010 Jul 19;8:68
references.pmid: 20642836
references.citation: Nat Med. 2007 Nov;13(11):1276-7; author reply 1277-8
references.pmid: 17987014