hl7 v3 clinical genomics – overview the hl7 clinical genomics work group prepared by amnon shabo...

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HL7 v3 Clinical Genomics Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling Facilitator HL7 Structured Documents WG CDA Co-editor CCD Implementation Guide Co-editor

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Page 1: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

HL7 v3 Clinical Genomics –

Overview

The HL7 Clinical Genomics Work Group

Prepared by Amnon Shabo (Shvo), PhD

HL7 Clinical Genomics WGCo-chair and Modeling Facilitator

HL7 Structured Documents WGCDA Co-editorCCD Implementation Guide Co-editor

Page 2: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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Haifa Research Lab

The HL7 Clinical Genomics Work Group

Mission To enable the standard use of patient-related genetic data such as DNA sequence variations and gene expression levels, for healthcare purposes (‘personalized medicine’) as well as for clinical trials & research

Work Products and Contributions to HL7 ProcessesThe Work Group will collect, review, develop and document clinical genomics use cases in order to determine what data needs to be exchanged. The WG will review existing genomics standards formats such as BSML (Bioinformatics Sequence Markup Language), MAGE-ML (Microarray and GeneExpression Markup Language), LSID (Life Science Identifier) and other. This group will recommend enhancements to and/or extensions of HL7's normative standards for exchange of information about clinical genomic orders and observations.

In addition, Clinical Genomics will seek to assure that related or supportive standards produced by other HL7 groups are robust enough to accommodate their use in both research and clinical care use. The group will also monitor information interchange standards developed outside HL7, and attempt harmonization of information content and representation of such standards with the HL7 content and representation.

Page 3: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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Overview of Activities

v3:

Family History (Pedigree) Topic

Genetic Variations Topic

Gene Expression Topic

CMETs defined by the Domain

v2:

v2 Implementation Guides

* The IG “Genetic Test Result Reporting to EHR” is modeled after the HL7 Version 2.5.1 Implementation Guide: Orders And Observations; Interoperable Laboratory Result Reporting To EHR (US Realm), Release 1

CDA:

A CDA Implementation Guide for Genetic Testing Reports

Common:

Domain Analysis Models for the various topics

A Domain Information Model (v3) describing the common semantics

Semantic alignment among the various specs

Three Tracks:

      Normative

      DSTU

      Informative

Page 4: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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Haifa Research Lab

HL7 Clinical Genomics: The v3 Track

Family

History

Domain Information Model: Genome

Gene Expression

Phenotype(utilizing the HL7

Clinical Statement)

Utilize

Co

ns

train

Genetic VariationC

on

stra

in

utilize

Page 5: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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Haifa Research Lab

To achieve semantic interoperability…

ClinicalTrials

Imaging

EHR

Orders& Observations

Pharmacy

ClinicalGuidelines

Health RIM

ClinicalDocuments

ClinicalGenomics

Central Health RIM (e.g., an extended HL7 V3 Reference Information Model):Bio & medical-informatics standard specs are derived from the same RIM

…we need standard specs derived from a Central Health RIM:

Bioinformatics

Data Models

?

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Utilizations / Implementation

Utilization by other HL7 Domains HL7 RCRIM Work Group (clinical trials specs) utilized the CG models in

their Pharmacogenomics message, which was an extension of the CTLab message (an approved but expired DSTU)

The Lab Work Group might utilize a constrained version of the Genetic Variation model in their Result message

Selected Implementations The Family History spec is used in Mass General Hospital

Expanding to other family history applications including the US Surgeon General Family History tool

The Genetic Variation model is used in Hypergenes (a European project on essential hypertension, http://www.hypergenes.eu/)

The Pedigree and Genetic Variation models are used in Italy, the Rizzoli institute in Bologna

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0..* associatedObservation

typeCode*: <= COMP

component

0..* associatedProperty

typeCode*: <= DRIV

derivedFrom2

0..* polypeptide

typeCode*: <= DRIV

derivedFrom5

SEQUENCES & PROTEOMICS

0..* expression

typeCode*: <= COMPcomponent1

0..* sequenceVariation

typeCode*: <= COMP

component3

IndividualAlleleclassCode*: <= OBSmoodCode*: <= EVNid: II [0..1]negationInd: BL [0..1]text: ED [0..1]effectiveTime: GTS [0..1]value: CD [0..1] (allele code, drawn from HUGO-HGVS or OMIM)methodCode: SET<CE> CWE [0..*]

GeneticLocusclassCode*: <= OBSmoodCode*: <= EVNid: II [0..1]code: CE CWE [0..1] (e.g., ALLELIC, NON_ALLELIC)text: ED [0..1]effectiveTime: IVL<TS> [0..1]confidentialityCode: SET<CE> CWE [0..*] <= ConfidentialityuncertaintyCode: CE CNE [0..1] <= Uncertaintyvalue: CD [0..1] (identifying a gene through GenBank GeneID with an optional translation to HUGO name.)methodCode: SET<CE> CWE [0..*]

0..* individualAllele

typeCode*: <= COMP

component1

SequenceclassCode*: <= OBSmoodCode*: <= EVNid: II [0..1]code: CD CWE [1..1] (the sequence standard code, e.g. BSML)text: ED [0..1] (sequence's annotations)effectiveTime: GTS [0..1]uncertaintyCode: CE CNE [0..1] <= Uncertaintyvalue: ED [1..1] (the actual sequence)interpretationCode: SET<CE> CWE [0..*] <= ObservationInterpretationmethodCode: SET<CE> CWE [0..*] (the sequencing method)

ExpressionclassCode*: <= OBSmoodCode*: <= EVNid: II [0..1]code: CE CWE [1..1] (the standard's code (e.g., MAGE-ML identifier)negationInd: BL [0..1]text: ED [0..1]effectiveTime: GTS [0..1]uncertaintyCode: CE CNE [0..1] <= Uncertaintyvalue: ED [1..1] (the actual gene or protein expression levels)interpretationCode: SET<CE> CWE [0..*] <= ObservationInterpretationmethodCode: SET<CE> CWE [0..*]

PolypeptideclassCode*: <= OBSmoodCode*: <= EVNid: II [0..1]text: ED [0..1]effectiveTime: GTS [0..1]value: CD [0..1] (protein code, drawn from SwissProt, PDB, PIR,HUPO, etc.)methodCode: SET<CE> CWE [0..*]

DeterminantPeptidesclassCode*: <= OBSmoodCode*: <= EVNid: II [0..1]text: ED [0..1]effectiveTime: GTS [0..1]value: CD [0..1] (peptide code, drawn from referencedatabases like those used in the Polypeptide class)methodCode: SET<CE> CWE [0..*]

Constrained to a restrictedMAGE-ML constrained schema,specified separately.

Constraint: GeneExpression.value

Note:A related allele that is ona different locus, and hasinterrelation with thesource allele, e.g.,translocated duplicatesof the gene.

0..* clinicalPhenotype

typeCode*: <= PERTpertinentInformation

ExternalObservedClinicalPhenotypeclassCode*: <= OBSmoodCode*: <= EVNid*: II [1..1] (The unique id of an external observation residing outside of the instance)code: CD CWE [0..1]text: ED [0..1]effectiveTime: GTS [0..1]

Note:An external observation is preferably a valid observationinstance existing in any other HL7-compliant instance,e.g., a document or a message.Use the id attribute of this class to point to the uniqueinstance identifier of that observation.

Note:A phenotype which has been actuallyobserved in the patient representedinternally in this model.

Note:This is a computed outcome, i.e.,the lab does not test for the actualprotein, but secondary processespopulate this class with thetranslational protein.

SequenceVariationclassCode*: <= OBSmoodCode*: <= EVNid: II [0..1]code: CD CWE [0..1]negationInd: BL [0..1]text: ED [0..1]effectiveTime: GTS [0..1]value: ANY [0..1] (The variation itself expressed with recognized notation like 269T>C or markup like BSML or drawn from an external reference like OMIM or dbSNP.)interpretationCode: SET<CE> CWE [0..*] <= ObservationInterpretationmethodCode: SET<CE> CWE [0..*]

KnownClinicalPhenotypeclassCode*: <= OBSmoodCode*: <= DEFcode: CD CWE [0..1]text: ED [0..1]effectiveTime: GTS [0..1]uncertaintyCode: CE CNE [0..1] <= ActUncertaintyvalue: ANY [0..1]

Note:These phenotypes are not the actual (observed)phenotypes for the patient, rather they are thescientifically known phenotypes of the sourcegenomic observation (e.g., known risks of amutation or know responsiveness to a medication).

Note:Code: COPY_NUMBER, ZYGOSITY, DOMINANCY, GENE_FAMILY,etc. For example, if code = COPY_NUMBER, then the value is oftype INT and is holding the no. of copies of this gene or allele.

0..* clinicalPhenotype

typeCode*: <= PERT

pertinentInformation

EXPRESSION DATA

SEQUENCE VARIATIONS

Polypeptide

Note:The Expression class refers to both gene and proteinexpression levels. It is an encapsulating class that allowsthe encapsulation of raw expression data in its value attribute.

0..* sequence

typeCode*: <= COMPcomponent2

0..* clinicalPhenotypetypeCode*: <= PERT

pertinentInformation

0..* clinicalPhenotype

typeCode*: <= PERT

pertinentInformation

Note:The code attribute indicates inwhat molecule the variation occurs,i.e., DNA, RNA or Protein.

0..* expression

typeCode*: <= COMP

component5

Note:Use the associations to the shadowclasses when the data set type (e.g.,expression) is not at deeper levels(e.g., allelic level) and needs to beassociated directly with the locus(e.g., the expression level is thetranslational result of both alleles).

0..* associatedObservationtypeCode*: <= COMP

component2

0..1 associatedObservation

typeCode*: <= COMP

component4 Note:This recursive associationenables the association of anRNA sequence derived froma DNA sequence and apolypeptide sequence derivedfrom the RNA sequence.

0..* clinicalPhenotype

typeCode*: <= PERT

pertinentInformation

Note:

This class is a placeholder for a specific locus on the genome - that is - a position of a particulargiven sequence in the subject’s genome or linkage map.Note that the semantics of the locus (e.g., gene, marker, variation, etc.) is defined by data assignedin the code & value attributes of this class, and also by placing additional data relating to thislocus into the classes associated with this class like Sequence, Expression, etc..

Note:The term 'Individual Allele' doesn't refer necessarily to aknown variant of the gene/locus, rather it refers to theindividual patient data regarding the gene/locus and mightwell contain personal variations w/unknown significance.

AssociatedObservationclassCode*: <= OBSmoodCode*: <= EVNid: SET<II> [0..*]code: CD CWE [0..1]text: ED [0..1]effectiveTime: GTS [0..1]value: ANY [0..1]methodCode: SET<CE> CWE [0..*]

Note:The code attribute could hold codes likeNORMALIZED_INTENSITY, P_VALUE, etc.The value attribute is populated based on theselected code and its data type is then setupaccordingly during instance creation.

Note:The code attribute could hold codes like TYPE,POSITION.GENOME, LENGTH, REFERENCE, REGION, etc..The value attribute is populated based on the selected codeand its data type is then setup accordingly during instancecreation. Here are a few examples:If code = TYPE, then the value is of type CV and holds one of thefollowing: SNP (tagSNP), INSERTION, DELETION,TRANSLOCATION, etc.

if code = POSITION, then value is of type INT and holdsthe actual numeric value representing the variation positionalong the gene.

if code = LENGTH, then value is of type INT and holdsthe actual numeric value representing the variation length.

If code = POSITION.GENE, then value is of type CV and is oneof the following codes:INTRON, EXON, UTR, PROMOTER, etc.

If code = POSITION.GENOME, then value is of type CV and is oneof the following codes:NORMAL_LOCUS, ECTOPIC, TRANSLOCATION, etc.

If the code = REFERENCE, then value istype CD and holds the reference gene identifier drawn from areference database like GenBank.

The full description of the allowed vocabularies for codes and itsrespective values could be found in the specification.

AssociatedObservation

Note:Code: CLASSIFICATION, etc.For example, if code =CLASSIFICATION, then the valueis of type CV and is holding eitherKNOWN or NOVEL.

reference

0..* geneticLocus

typeCode*: <= REFR

Note:A related gene that is on adifferent locus, and stillhas significant interrelationwith the source gene (similarto the recursive associationof an IndividualAllele).

ClinicalPhenotypeclassCode*: <= ORGANIZERmoodCode*: <= EVN

0..* observedClinicalPhenotype

typeCode*: <= COMP

component1

0..* knownClinicalPhenotype

typeCode*: <= COMP

component2

0..* externalObservedClinicalPhenotype

typeCode*: <= COMP

component3

At least one of the target acts ofthe three component act relationshipsshould be populated, since this isjust a wrapper class.

Constraint: ClinicalPhenotype

Note:- code should indicate the type of source, e.g., OMIM- text could contain pieces from research papers- value could contain a phenotype code if known (e.g., if it’s a disease, then the disease code)

ClinicalPhenotype

ClinicalPhenotype

ClinicalPhenotype

ClinicalPhenotype

ClinicalPhenotype

ClinicalPhenotype

0..1 identifiedEntity

typeCode*: <= SBJcontextControlCode: CS CNE [0..1] <= ContextControl "OP"

subject

reference

0..* individualAllele

typeCode*: <= REFR

ObservedClinicalPhenotype

Note:This CMET might be replacedwith the Clinical Statement SharedModel for richer expressivity, whenthe that mode is approved(currently in ballot).

Constrained to a restricted BSMLcontent model, specified in aseparate schema.

Constraint: Sequence.value

0..* sequence

typeCode*: <= COMP

component4

0..* sequenceVariation

typeCode*: <= COMP

component3

AssociatedPropertyclassCode*: <= OBSmoodCode*: <= EVNcode: CD CWE [0..1]text: ED [0..1]value: ANY [0..1]

0..* associatedProperty

typeCode*: <= DRIVderivedFrom1

AssociatedObservation

0..* associatedObservation

typeCode*: <= COMP

component

AssociatedPropertyAssociatedObservation

0..* associatedProperty

typeCode*: <= DRIV

derivedFrom

AssociatedProperty0..* associatedProperty

typeCode*: <= DRIVderivedFrom1

AssociatedObservation0..* associatedObservation

typeCode*: <= COMPcomponent

0..* sequenceVariationtypeCode*: <= DRIV

derivedFrom3derivedFrom2

0..* sequence

typeCode*: <= DRIV

0..* determinantPeptides

typeCode*: <= DRIV

derivedFrom4

0..* determinantPeptides

typeCode*: <= DRIVderivedFrom

0..* clinicalPhenotype

typeCode*: <= PERT

pertinentInformation 0..* clinicalPhenotype

typeCode*: <= PERT

pertinentInformation

AssociatedProperty

0..* associatedProperty

typeCode*: <= DRIV

derivedFrom

AssociatedProperty

GeneticLociclassCode*: <= OBSmoodCode*: <= EVNid: SET<II> [0..*]code: CD CWE [0..1]effectiveTime: GTS [0..1]value: ANY [0..1]

0..* geneticLocitypeCode*: <= COMPcomponentOf

0..* clinicalPhenotype

typeCode*: <= PERTpertinentInformation

GeneticLoci

0..* geneticLoci

typeCode*: <= COMP

componentOf

GeneticLoci

0..* geneticLoci

typeCode*: <= COMP

componentOf

0..* polypeptide

typeCode*: <= DRIVderivedFrom1

Polypeptide

0..* polypeptide

typeCode*: <= DRIV

derivedFrom2

Note:Use this class to indicate a set of genetic locito which this locus belongs. The loci set couldbe a haplotype, a genetic profile and so forth.Use the id attribute to point to the GeneticLociinstance if available. The other attributesserve as a minimal data set about the loci group.

PHENOTYPES

Note:Any observation related to the variation and is notan inherent part of the variation observation (the lattershould be represented in the AssociatedProperty class).For example, the zygosity of the variation.

Note:Use this class to point to a variationgroup to which this variation belongs.For example, a SNP haplotype.

Note:Any observation related to the sequence and is notan inherent part of the sequence observation (the lattershould be represented in the AssociatedProperty class).For example, splicing alternatives.

Note:Key peptides in the proteinthat determine its function.

Note:There could be zero to manyIndividualAllele objects in aspecific instance. A typicalcase would be an allele pair,one on the paternalchromosome and one on thematernal chromosome.

Note:Use this class toshow an allelehaplotype like in HLA.

Note:Any observationrelated to theexpression assayand is not aninherent part ofthe expressionobservation.

Note:Use this class forinherent dataabout the locus, e.g.chromosome no.

IdentifiedEntityclassCode*: <= IDENTid: SET<II> [0..*]code: CE CWE [0..1] <= RoleCode

Note:Use this role to identify a different subject(e.g., healthy tissue, virus, etc.) than theone propagated from the wrappingmessage or payload (e.g., GeneticLoci).

ScopingEntityclassCode*: <= LIVdeterminerCode*: <= INSTANCEid: SET<II> [0..*]code: CE CWE [0..1] <= EntityCode

0..* assignedEntity

typeCode*: <= PRFcontextControlCode: CS CNE [0..1] <= ContextControl "OP"

performer

0..*

performer

0..*

performer1

0..*

performer2

0..*

performer1

0..*

performer2

Genetic Locus(POCG_RM000010)

The entry point tothe GeneticLocus modelis any locus on the genome.

Constrained to a restricted MAGE-MLcontent model, specified in aseparate schema.

Constraint: Expression.value

Expression

Sequence

SequenceVariation

SequenceVariation

0..* clinicalPhenotypetypeCode*: <= PERT

pertinentInformation

ClinicalPhenotype

CMET: (ASSIGNED) R_AssignedEntity

[universal](COCT_MT090000)

0..1 scopedRoleName

CMET: (ACT) A_SupportingClinicalInformation

[universal](COCT_MT200000)

The Locus and its Alleles

SequenceVariations

ExpressionData

Sequenceand

Proteomics

ClinicalPhenotypes

The DSTU GeneticLocus Model Focal Areas (DIM forerunner):

Page 8: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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The Underlying Paradigm: Encapsulate & Bubble-up

Clinical PracticesGenomic Data Sources

EHR System

HL7 CG Messages with m

ainly

Encapsulating HL7 Objects HL7 C

G M

essa

ges

with

enca

psul

ated

dat

a as

soci

ated

with

HL7 c

linic

al o

bjec

ts (p

heno

type

s)

Bubble up the most clinically-significant raw

genomic data into specialized HL7 objects and

link them with clinical data from the patient EHR

Decision Support Applications

Knowledge(KBs, Ontologies, registries,

reference DBs, Papers, etc.)

Bridging is the challenge…

Encapsulation by predefined & constrained

bioinformatics schemas

Bubbling-up is done continuously by specialized DS

applications

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Decision Support Applications

Encapsulate & Bubble-up Example

Genetic CounselingDNA Lab

HL7 CG Messages with a Sequence

HL7 Object encapsulating the raw

sequencing results

HL7 C

G M

essa

ges

with

enca

psul

ated

seq

uenc

ing

data

asso

ciat

ed w

ith c

linic

al p

heno

type

s

Bubble up the most clinically-significant SNP data into

HL7 SNP and Mutation objects and

link them with clinical data from the patient EHR

Sequencing Example…

Encapsulation by a constrained BSML schema

Bubbling-up is done dynamically

by specialized applications, e.g.,

sequence analyzing programs

EHR System

Knowledge Sources

on genetic variants

(e.g., OMIM)

Page 10: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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Example: Family History XML Encoding

Point

back…

Bubble

up… To

phenotype

and beyond….

Taken from a patient pedigree, the

portion related to patient’s daughter

(in collaboration with Partners HealthCare

& other HL7 CG SIG members)

Point back to the raw data of this relative providing “personal evidence”

Page 11: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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XML Fusion: Encapsulation of Raw Genomic DataR

aw g

eno

mic

dat

a re

pre

sen

ted

in

Bio

info

rmat

ics

mar

kup

HL

7 v3

XM

L

Page 12: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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Haifa Research Lab

The Phenotype Model

Observed Phenotype

Interpretive

Phenotype

Page 13: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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The Genetic Variation CMET (passed normative in Jan. 2010)

Genetic Loci

Genetic

Locus

Individual Allele

Sequence

Variation

Sequence

(observed or reference)

Participants

(including specimen)

Associated data (vocab. Controlled)

Observed or Interpretive phenotypes

Genetic Report (CDA)

Genetic Testing Order

Page 14: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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The HL7 RCRIM CT Laboratory Model- The Pharmacogenomics Extension

Utilizes the Clinical Genomics

CMET

Genetic Lab

Clinical

Trial

Enrolled Subject

Specimen

Consent to Genotype

Pharmacogenomics Test

Page 15: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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Gene Expression Topic

Domain Analysis Model (DAM) Passed informative

ballot Based on several

models for geneexpression dataalong with extensions

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New v3 Models for Future Ballot

Gene Expression CMET Model An Implementation Guide constraining the Genotype models for

gene expression data

Domain Information Model (Genome ) Allows non-locus specific data (e.g., large deletions, cytogenetics,

etc.) to be represented Link to the locus-specific models, i.e., GeneticLoci & GeneticLocus

Query Model Based on the HL7 V3 Query by Parameter Infrastructure Adds selected attributes from the Clinical Genomics models as

parameters of the query message

Page 17: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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The Gene Expression CMET Draft

Genetic Loci

Genetic Locus

Gene Expression

Associated observations

GTR Report

Participants

Page 18: HL7 v3 Clinical Genomics – Overview The HL7 Clinical Genomics Work Group Prepared by Amnon Shabo (Shvo), PhD HL7 Clinical Genomics WG Co-chair and Modeling

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The Domain Information Model - Genome

Individual Allele

Bio Sequenc

e

Sequence Variation

(SNP, Mutation,

Polymorphism, etc.)

Polypeptide

Expression Data

Phenotype

Entry Point: Geneome

Expression

Attributes

Variation

Attributes

Encapsulating Obj.

Bubbled-up Obj.

genotypephenotype

Genetic Loci

Genetic Locus

Non-locus specific

data

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The CG V3 Query Model: Query by Parameter

QueryByParameterPayload(QueryByParameter)queryId: II [0..1]statusCode: CS CNE [0..1] <= QueryStatusCoderesponseElementGroupId: SET<II> [0..*]responseModalityCode: CS CNE [0..1] <= ResponseModalityresponsePriorityCode: CS CNE [0..1] <= QueryPriorityinitialQuantity: INT [0..1]initialQuantityCode: CE CWE [0..1] <= QueryRequestLimit

ControlActProcessclassCode*: <= CACTmoodCode*: <= ActMoodCompletionTrack

0..1queryByParameterPayload

GeneticLocus.value(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (GeneticLocus.value)

0..*geneticLocus.value

Query(POCG_RM000090)

Entry point for Clinical Genomics query message

GeneticLocus.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (GeneticLocus.ID)

0..*geneticLocus.id

IndividualAllele.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (IndividualAllele.id)

IndividualAllele.value(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (IndividualAllele.value)

0..1individualAllele.value

0..*individualAllele.id

SequenceVariation.value(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (SequenceVariation.value)

SequenceVariation.id(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (SequenceVariation.id)

0..1sequenceVariation.value

0..1sequenceVariation.id

Expression.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Expression.id)

Sequence.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Sequence.id)

0..*sequence.id

0..*expression.id

Polypeptide.value(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Polypeptide.value)

Polypeptide.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Polypeptide.id)

0..*polypeptide.value

0..*polypeptide.id

DeterminantPeptide.value(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (DeterminantPeptide.value)

DeterminantPeptide.id(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (DeterminantPeptide.value)

0..*determinantPeptide.value

0..*determinantPeptide.id

GeneticLoci.id(ParameterItem)value: II CWE [0..1]semanticsText: ST [0..1] (GeneticLoci.id)

GeneticLoci.value(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (GeneticLoci.value)

0..*geneticLoci.value

0..*geneticLoci.id

GeneticLoci.code(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (GeneticLoci.code)

0..*geneticLoci.code

ClinicalPhenotype.id(ParameterItem)value: II CWE [0..1]semanticsText: ST [0..1] (ClinicalPhenotype.id)

ClinicalPhenotype.code(ParameterItem)value: CD CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (ClinicalPhenotype.code)

ClinicalPhenotype.value(ParameterItem)value: ANY CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (ClinicalPhenotype.value)

0..*clinicalPhenotype.id

0..*clinicalPhenotype.code

0..*clinicalPhenotype.value

RecordTarget.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (RecordTarget.id)

0..*recordTarget.id

Subject.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Subject.id)

0..*subject.id

Performer.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Performer.id)

0..*performer.id

Author.id(ParameterItem)value: II CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Author.id)

0..*author.id

Method.code(ParameterItem)value: CE CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Method.code)

Interpretation.code(ParameterItem)value: CE CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (Interpretation.code)

effectiveTime(ParameterItem)value: GTS CWE [0..1] <= QueryParameterValuesemanticsText: ST [0..1] (effectiveTime)

0..*method.code

0..*interpretation.code

0..*effectiveTime

GeneticLocus parameters

Starting point with query

identifiers and attributes

Miscellaneous parameters

GeneticLoci parameters

participants parameters

Phenotype parameters

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V2 Implementation Guides

The IG “Genetic Test Result Reporting to EHR” passed informative ballot

It is modeled after the HL7 Version 2.5.1 Implementation Guide: Orders And Observations; Interoperable Laboratory Result Reporting To EHR (US Realm), Release 1

Is used in a pilot of information exchange between Partners Healthcare and Intermountain Health Care

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The v2 Message Structure

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V2 Sample Message OBR|1||PM-08-J00094^HPCGG-LMM^2.16.840.1.113883.3.167.1^ISO|

lm_DCM-pnlB_L^Dilated Cardiomyopathy Panel B (5 genes)^99LMM-ORDER-TEST-ID||20080702000000|20080702100909|||||||||234567891^Pump^Patrick^^^^^^NPI^L||||||20080703000000|||F||||||00000009^Cardiovascular^99HPCGG-GVIE-INDICATION^^^^^^Clinical Diagnosis and Family History of DCM|&Geneticist&Gene&&&&&NPI^^^^^^^HPCGG-LMM&2.16.840.1.113883.3.167.1&ISO|||||||||||||||55233-1^Genetic analysis master panel ^LN

SPM|1|||119273009&Peripheral blood&SNM3&&&&0707Intl&&Blood, Peripheral|||||||||||||20080702000000

OBR|2||PM-08-J00094-1^HPCGG-LMM^2.16.840.1.113883.3.167.1^ISO|55232-3^Genetic analysis summary panel^LN|||20080702000000|||||||||||||||20080703000000|||F||||^PM-08-J00094&HPCGG-LMM&2.16.840.1.113883.3.167.1&ISO

OBX|1|CWE|51967-8^Genetic disease assessed^LN||399020009^DCM-Dilated Cardiomyopathy^SNM3^^^0707Intl||||||F|20080702100909|||||||||||Laboratory for Molecular Medicine^L^22D1005307^^^CLIA&2.16.840.1.113883.4.7&ISO|1000 Laboratory Lane^Ste. 123^Cambridge^MA^99999^USA^B

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CDA IG for Genetic Testing Reports

Scope The Clinical Genomics Work Group develops a CDA Implementation

Guide (IG) for genetic testing report co-sponsored by the Structured Documents Work Group

Design principles Follow existing report formats commonly used in healthcare &

research Emphasize interpretations & recommendations Provide general background information on tests performed Represent interpretation by utilizing patterns of ‘genotype-

phenotype’ associations in the HL7 v3 Clinical Genomics and implement them as harmonized clinical statement entry-level templates in this IG

Reference HL7 Clinical Genomics instances as the place holders of raw data (personal evidences), similarly to referencing images (technically-wise)

Developed using the MDHT open source tool (OHT)

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CDA GTR Ballot Status

Balloted as DSTU and passed in October 2010

Major negative comments: Vocabulary binding (need to align to the new principles) Layout issues (needs to get the help of the MDHT developers) Sample XML snippets cannot have sample data OIDs for LOINC panels Sub-template ids registration Document type refinement Alignment with sub-templates in other CDA IGs

(e.g., Findings, Care Plan, etc.) Add drug safety Clarify definitions of LOINC codes

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CDA GTR Issues

Ballot a Universal IG along with specific types of GTR: Healthcare - US Realm; Research; etc.

Get family history data by linking to an HL7 Pedigree instance

Similarly, link to HL7 Clinical Genomics instances to get the richest expression of genotype-phenotype associations along with encapsulated raw data (e.g., sequences)

Get volenteers to contribute to the editorial group

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CDA GTR Section Outline

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GTR Genetic Variation Section

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Clinical Genomic Statement

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Interpretive Phenotype Observation

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Summary Section

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Alignment Among the Various Specs

v3 specs and CDA are all based the RIM CDA GTR-IG will be based on CDA R3 Depending on the “right side” of R3, if it allows RIM-based domain

models, then alignment is trivial

v3-v2 alignment: Proposal: represent semantics with v3 and implement it in various

ways, one of which is v2; develop an “v2 ITS” for the v3 models See proposal made by Amnon in a separate presentation

(click here to see that presentation)

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Summary

Small group coping with v3, v2 and CDA Clinical & Research environments

Genetic Variation - Normative CMET Vocabulary harmonization's (facilitator is back to activity) Timing confusing:

collecting specimen, extracting genetic material, identifying genomic observations, interpretation

Entry point into a choice box

CDA GTR through OHT CDA Editor

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The End

• Thank you for your attention…

• Questions? Contact Amnon at [email protected]

• Comments of general interest should be posted to the CG mailing list at [email protected]