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HL7 Clinical-Genomics SIG: Tissue-Typing Models and a Reusable Genotype Module HL7 V3 Compliant IBM Research Lab in Haifa together with Hadassah University.

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Presentation on theme: "HL7 Clinical-Genomics SIG: Tissue-Typing Models and a Reusable Genotype Module HL7 V3 Compliant IBM Research Lab in Haifa together with Hadassah University."— Presentation transcript:

1 HL7 Clinical-Genomics SIG: Tissue-Typing Models and a Reusable Genotype Module HL7 V3 Compliant IBM Research Lab in Haifa together with Hadassah University Hospital Amnon Shabo January 2004 (C) Copyright IBM Corp. 2003

2 Haifa Research Lab The Genotype CMET  Represents genomic data in HL7 RIM Classes  Not meant to be a biological model  Concise and targeted at healthcare use for personalized medicine  Consists of:  A Genotype (entry point)  1.. 3 alleles  Mutations  SNPs  Haplotypes  DNA Sequencing  Gene expression  Proteomics  Phenotypes (clinical data such as diseases, allergies, etc.)

3 Haifa Research Lab The Genotype CMET(cont.)  Design Principles:  Reusable component  Basic encapsulation of genomic data that might be used in healthcare regardless of the use case  Stemmed from looking for commonalities in specific use cases  Presented as the CG SIG DIM (Domain Information Model) in ballot#6  Most of the clones are optional, thus allowing the representation of merely a genotype with a minimum of one allele (a typical use by early adopters)  At the same time, allows the use of finer-grain genomic data, thus accommodating the more complex use cases such as tissue typing or clinical trials  Its use is currently illustrated in three R-MIMs:  Tissue Typing  Cystic Fibrosis  Viral genotyping

4 Haifa Research Lab The Genotype Model Individual Allele SNP Allele Sequence Mutation Proteomic s Gene Expression Shadow Allele (second ) Clinical Phenotype Haplotype Entry Point: Genotype Shadow Allele (Third)

5 Haifa Research Lab The Genotype Model in Tissue Typing BMT Tissue Typing Tissue Typing Observation Genotype Allele SNP Haplotype Individual1 HLA Matching Individual2 HLA Donor Banks BMT Ward Tissue- Typing Lab

6 Haifa Research Lab Tissue Typing Observation How the Genotype fits to Tissue-Typing

7 Haifa Research Lab How the Genotype fits to Tissue-Typing Tissue Typing Observation Class I Antigens Class II Antigens The Genotype model is used for each HLA Antigen

8 Haifa Research Lab The Genotype Model in Cystic Fibrosis Entry Point: Blood Sample Patien t Provider EMR System MGS Report DNA Genotype CMET MLG Counselor ML Consultant Molecular Genetic lab

9 Haifa Research Lab The Genotype Model in Viral Genotyping Entry Point: Blood Sample Pathoge n Patient Viral DNA Sequencing Viral DNA Regions Genotype CMET DNA Lab Test Panel Sponso r Repor t Resistance Profile

10 Haifa Research Lab Constrained-BSML Schema  BSML – Bioinformatics Sequence Markup Language  Aimed at any biological sequence, for example:  DNA  RNA  Protein  Constraining the BSML DTD to fit the healthcare needs  Leave out research and display markup  Ensure the patient identification  Creating an XML Schema, set up as the content model of an HL7 attribute of type ED

11 Haifa Research Lab Constrained-MAGE-ML Schema  Convert MAGE-ML DTD to XML Schema and eliminate research elements  Shared issues:  not only eliminate research & display related data but requires the presence of certain elements, for example - patient identifiers  Require that one and only one patient will be the subject of the data, to avoid bringing data of another patient into the HL7 message

12 Haifa Research Lab OBS Specialization Examples  PublicHealthCase  detectionMethodCode :: CE  transmissionModeCode :: CE  diseaseImportedCode :: CE  Diagnostic Image  subjectOrientationCode:: CE  The above examples are relatively ‘simple’ considering the uniqueness of the genomic observation attributes

13 Haifa Research Lab GenomicObservation  Specialization to the RIM Observation Class  Rationale: has additional attributes that are unique to genomics (LSID, Bioinformatics Markup, etc.)  Proposal: add the following attributes- (initial set, could be expanded later through harmonization processes)  II :: LSID Life Science Identifier from I3C  ED :: MoleculeSequence constrained to BSML-like schema  ED :: GeneExpression constrained to MAGE-like schema  BL :: TagSNP Boolean  CD :: ProteinFunction proteomic ontology’s  CS :: PaternalMaternalAff HL7 Vocabulary

14 Haifa Research Lab Proposed HL7 Vocabularies  Tissue Typing related Vocabularies:  TissueTypingLocusMatchingClass  TissueTypingMatchingClass  TissueTypingTestingClass  TissueTypingTestingMethod  TissueTypingDocumentType  TissueTypingOrderClass  DonorType (allogeneic, autologous, etc.)  Genomics related Vocabularies:  AllelesRelation (recessive, heterozygote, etc.)  SequencingMethodCode  Genotype-to-phenotype types of effects

15 Haifa Research Lab XML Examples  Genotype Examples: o GenotypeSample1.xml A genotype of two HLA alleles in the B locus o GenotypeSample2.xml A genotype of two HLA alleles in the B locus, along with a SNP designation in the first allele  Tissue Typing Observation Examples: o TissueTypingObservationSample1.xml Consists of a single tissue typing observation of a patient or a donor o TissueTypingObservationSample2.xml Consists of two tissue typing observations of a patient & donor, leading to a tissue typing matching observation  Donor Search Examples: o TissueTypingDonorBankSample1.xml This example is aimed at illustrating an unsolicited message from a BMT Center to a donor bank, sending a patient's tissue typing observation for the purpose of searching an appropriate donor

16 Haifa Research Lab Next Steps  HL7  Derive message models (R-MIMs) from each use case ‘DIM’  Schemas ( a draft is already available for the Genotype model)Genotype  Instances (for review and experimental use)  Vocabularies  HL7- develop  External- get HL7 to recognize them  Constraining Bioinformatics Markup (continue the effort and include markup in the next ballot)  MAGE-ML or MIAME  BSML  Hapmap (?)

17 Haifa Research Lab The End… Thank you…


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