Ontologies for Immunology

Barry Smith

1991198283914738

https://immport.niaid.nih.gov/

NIAID Division of Allergy, Immunology and Transpantation (DAIT)

Areas of Research• Allergic Diseases• Asthma• Autoimmune Diseases• Food Allergy• Immune Tolerance• Medical Countermeasures Against Radiological and

Nuclear Threats• Transplantation

DAIT-Funded Projects Depositing Data into ImmPort

• Immune Tolerance Network (ITN)• Atopic Dermatitis and Vaccinia Network (ADVN)• Population Genetics Analysis Program• Immune Function and Biodefense in Children,

Elderly, and Immunocompromised Populations• HLA Region Genetics in Immune-Mediated

Diseases• Modeling Immunity for Biodefense

Goals of ImmPort• Accelerate a more collaborative and coordinated research

environment

• Create an integrated database that broadens the usefulness of scientific data

• Advance the pace and quality of scientific discovery while extending the value of scientific data in all areas of immunological research

• Integrate relevant data sets from participating laboratories, public and government databases, and private data sources

• Promote rapid availability of important findings

• Provide analysis tools to advance immunological research

Standards and ontologies needed to advance especially this

• Integrate relevant data sets from participating laboratories, public and government databases, and private data sources

SDY 165: Characterization of in vitro Stimulated B Cells from Human Subjects shared to Semi-

Public Workspace (SPW) Proje

SDY 165: Characterization of in vitro Stimulated B Cells from Human Subjects shared to Semi-

Public Workspace (SPW) Project

During the human B cell (Bc) recall response, rapid cell division results in multiple Bc subpopulations. RNA microarray and functional analyses showed that proliferating CD27lo cells are a transient pre-plasmablast population, expressing genes associated with Bc receptor editing. Undivided cells had an active transcriptional program of non-ASC B cell functions, including cytokine secretion and costimulation, suggesting a link between innate and adaptive Bc responses. Transcriptome analysis suggested a gene regulatory network for CD27lo and CD27hi Bc differentiation.

Functionally Distinct Subpopulations of CpG-Activated Memory B Cells, Alicia D. Henn … & Martin S. Zand, Pubmed 2246822

Figure 5: The Fate of CD27lo cells

ImmPort Antibody Registry

ImmPort Antibody Registry BD Lyoplate Screening Panels Human Surface Markers

http://pir.georgetown.edu/cgi-bin/pro/entry_pro?id=PR:000001963

Discoverability

• Find all ImmPort studies involving genes associated with B cell receptor editing

• Find all data in public and government databases relating to B cell receptor editing

GOPubMed: 179 documents

(B cell receptor editing Zand) AND ("Zand"[au])

SDY 165 Discoverability

During the human B cell (Bc) recall response, rapid cell division results in multiple Bc subpopulations. RNA microarray and functional analyses showed that proliferating CD27lo cells are a transient pre-plasmablast population, expressing genes associated with Bc receptor editing. Undivided cells had an active transcriptional program of non-ASC B cell functions, including cytokine secretion and costimulation, suggesting a link between innate and adaptive Bc responses. Transcriptome analysis suggested a gene regulatory network for CD27lo and CD27hi Bc differentiation.

NIAID Sample Data Sharing Plan (Last Reviewed February 12, 2013)

• Sharing of data generated by this project is an essential part of our proposed activities and will be carried out in several different ways.

• Presentations at national scientific meetings. … it is expected that approximately four presentations at national meetings would be appropriate. …

• Annual lectureship. A lectureship has brought to the University distinguished scientists and clinicians …

• Newsletter. The [disease interest group] publishes a newsletter …• Web site of the Interest Group. The [interest group] currently maintains a Web

site where information [about the disease] is posted. Summaries of the scientific presentation from the [quarterly project] meetings will be posted on this Web site, written primarily for a general audience. [Link to Web site]

• Annual [Disease] Awareness wee k….• SAGE Library Data. It is our explicit intention that these [Serial analysis of gene

expression] data will be placed in a readily accessible public database. …

Plan addressing Key Elements for a Data Sharing Plan under NIH Extramural Support

(Last Reviewed August 09, 2012)

What data that will be shared [sic]: I will share phenotypic data associated with the collected samples by depositing these data at _______which is an NIH-funded repository. ... Additional data documentation and de-identified data will be deposited for sharing along with phenotypic data, which includes demographics, family history of XXXXXX disease, and diagnosis, consistent with applicable laws and regulations. … Meta-analysis data and associated phenotypic data, along with data content, format, and organization, will be available at ___. Submitted data will confirm [sic] with relevant data and terminology standards.Who will have access to the data: … Where will the data be available: … When will the data be shared: …How will researchers locate and access the data: I agree that I will identify where the data will be available and how to access the data in any publications and presentations that I author or co-author about these data … repository has policies and procedures in place that will provide data access to qualified researchers, fully consistent with NIH data sharing policies and applicable laws and regulations.

What should be required / recommended

• LOINC• CDISC• BRIDG• SNOMED• Minimal Information Checklists• OBI• Immunology Ontologies

Lab resources do not recommend use of LOINC

http://www.niaid.nih.gov/LabsAndResources/resources/DAIDSClinRsrch/Documents/gclp.pdf

Can some these be built into

• LDMS• LIS• CTMS• EHRs

need to explore relation of SDY data in ImmPort to CDISC

From the Summary specification

CDISC definitions

• A study arm represents one planned path through the study. The path is composed of a study cell for each epoch in the study.

• A study cell is the part of study design that describes what happens in a particular epoch for a particular arm. The cell describes how the purpose of its epoch is fulfilled for each arm.

CDISC Structural Elements

Building blocks of a study design: Epochs, Cells, Arms, Segments, Activities• A study arm represents a path • A path is composed of a cell• A cell is a part of a study design• A cell describes what happens in an epoch • An Activity represents a point in a study at

which a specific action is to be taken.

BRIDG

• http://bridgmodel.nci.nih.gov/files/BRIDG_Model_3.2_html/index.htm

BRIDG Adverse Event

BRIDG Adverse Event

Product Brief - Biomedical Research Integrated Domain Group (BRIDG)

Implementations/ Case Studies (Actual Users)• The BRIDG Project is a collaborative effort

engaging stakeholders from four organizations:– Clinical Data Interchange Standards Consortium

(CDISC)– HL7 Regulated Clinical Research Information

Management Working Group (HL7 RCRIM WG)– National Cancer Institute (NCI), including the Cancer

Biomedical Informatics Grid (caBIG™) project– Food and Drug Administration (FDA)

Does BRIDG have any users?

Ballot Cycle Info

2010 May Ballot Cycle Info: INFORMATIVEBallot results: Met basic vote requirements for approval. 24 Negative votes to reconcileDocument Name: HL7 Version 3 Domain Analysis Model: Biomedical Research Integrated Domain (BRIDG), Release 1Ballot Code: V3DAM_BRIDG_R1_TBDNIB Submitted By: Edward Tripp

Misc Notes

May 2013: Published NE 2013; PMO archiving.March 2013: Received ANSI approval for Technical Report of HL7 Version 3 Domain Analysis Model: Biomedical Research Integrated Domain (BRIDG), Release 1. PMO set status as Ready for Normative Edition Publication. Project Team does not need to do any further work.Nov 2012: TSC approved a publication request for HL7 Version 3 Domain Analysis Model: Biomedical Research Integrated Domain (BRIDG), Release 1 as an informative document and registration with ANSI as a Technical Report, from TSC tracker # 2406.As of 2012-09-01: Project restarted. BRIDG project team re-writing new NWIP for submission September 2012.2011Dec: Per L. Laakso The Bridg project at PI 538 is an ISO/JIC project (ISO/CD 14199). PMO changed it to be an ISO/JIC project type.2010Nov(LL): updated dates per RCRIM three-year plan. cyclical development indicative of informative ballot developemnt Jan cycles, ballot May cycles, publication and renewed development in September cycles.2010July: added repository URLSept 2009: PMO changed from 3-Year Plan item to Active Project

Product Type Domain Analysis Model (DAM)Project Document Repository

http://wiki.hl7.org/index.php?title=BRIDG_as_DAM

What should be required / recommended

• LOINC• CDISC• BRIDG• SNOMED• Minimal Information Checklists• OBI• Immunology Ontologies

MIFLOWCYT: Minimal Information for a Flow Cytometry Experiment

Minimal Information about a Cellular Assay

Project HeaderSource: Contact details of researcher/person in charge of the project (name, affiliation/institution, department, address, Email, etc.). Project: Description (text) of the project within a larger context (biological process that is addressed; description of measured effect, controls, etc.). Application: Description (text) of the specific application of this project (abstract; reference to publication). Array(s): culturing and reaction container(s) that are used during the project (name; • identifier; type (e.g. 384, 96, 24 well, flask, glass slide for cell arrays); vendor or • manufacturer; order-number; surface area/feature size. CellLine(s): Description of cell lines employed (name; identifier; ATCC number (if applicable) or details: Species, tissue, organ, contact-details (when from different lab); • reference to publication; passage number; mycoplasma test (Y/N) and other validation; • modifications (optional, if any made, e.g. stably transfected, induced resistance, etc.). Reagents: Media, supplements, kits, buffers, and solutions (name, identifier, vendor or manufacturer, order number, lot number). Perturbator(s): Description of materials/conditions that are used in the project to perturb the cells (type - e.g. siRNA, cDNA, small chemical compound, name, external references - • gene/protein identifiers/order numbers, sequences if applicable). Instrument(s): Description of the data acquisition station and other instruments utilized in the project, e.g. for transfection (name, type, model, manufacturer).

Experimental modulesTreatment(s): Description of the conditions that are applied to the cells during culturing (name, identifier, time-stamp, materials used, volume, actual passage number of cells, seeding density, temperature, CO2-content, humidity). Perturbation(s): Description of the perturbation, (special case of a treatment), which describes the application of ‘perturbator(s)’, e.g. transfection (siRNA, expression clone), treatment with small compound, temperature shift, etc. PostTreatment(s): Description of the conditions that are applied after culturing and prior to data acquisition, i.e. lysis, fixation, staining, antibody incubation, etc. DataAcquisition(s): Detection of the effect(s) induced by the perturbation (identifier, time stamp, reference to instrument above, instrument-settings, e.g. excitation and emission wavelengths with filter sets, lamp/Laser energy). DataProcessingDescription of the processes applied to analyze the raw-data in order to generate a hit list. Reference to publication(s) describing the procedures and/or to software utilized (incl. version and settings). Links to the raw, the processed, and to the interpreted data.

Minimal Information about a Cellular Assay

Minimal Information about a T-Cell Assay

• Janetzki S, Britten CM, Kalos M, Levitsky HI, Maecker HT, Melief CJ, Old LJ, Romero P, Hoos A, Davis MM. 2009. "MIATA"-Minimal Information about T Cell Assays. Immunity. 31: 527-8

http://www.miataproject.org/

http://mibbi.sourceforge.net/portal.shtml

MIBBI= Minimal Information about a Biological or Biomedical Investigation

• How to make MIBBI checklists non-redundant, factorable, such as to support interoperability / sharing of data?

• Need to use the same words for the same things and events in each checklist

• OBI = Ontology for Biomedical Investigations

OBI representation of a neuroscience study

OBI: Vaccine Protection Investigation

OBI ontology terms (examples)

OBI Relations

Advantages of OBI

• Federal reporting (drug trials)• Enhancement of plans for data sharing• Supports retrieval and meta-analysis by allowing

searches over protocols, metadata about experiments, imaging processes, statistical processes, sources of analytes, equipment vendors, …

• Supports comparison of runs performed by different labs on the same machines, using the same sorts of settings, stainings, samples …

ImmPort (recommended) Ontologies Chemical Entities of Biological Interest (CHEBI)The Protein Ontology (PRO)The Gene Ontology (GO)GO Annotation for the Immune SystemThe Cell Ontology (CL)Beta Cell Genomics Ontology (BCGO) The Immune Epitope Ontology (ONTIE)The Infectious Disease Ontology (IDO)Ontology for General Medical Science (OGMS))DesiderataAllergy OntologyImmunology OntologyAutoimmune Disease Ontology

How to advance interoperability of immunology (clinical trial) data

How connect• experimental data• ontology resources?• 1. identify ways that submitters of data can benefit

early on through use of ontologies• 2. identify ways to make it easier for submitters of

data to use ontologies• 3. identify ways to annotate data using ontologies

post-submission

1. identify ways that submitters of data can benefit early on through use of ontologies

a. help to satisfy NIH mandates– can we influence NIH mandates?

b. help to satisfy regulatory reporting requirements (FDA)

c. help to analyze their data (and to incorporate other sorts of data)

d. help them to do better science by imitating successes of others who have exploited ontologies

2. identify ways to make it easier for submitters of data to use ontologiesa. build them into EHRs

– can we influence EHR vendors?b. build them into Lab Information Systemsc. build them into Clinical Trial Management

Systems

3. identify ways to annotate data using ontologies post-submission

a. NLP - New tools for classification and monitoring of autoimmune diseases.Maecker HT, Lindstrom TM, Robinson WH, Utz PJ, Hale M, Boyd SD, Shen-Orr SS, Fathman CG.Nat Rev Rheumatol. 2012 May 31;8(6):317-28- Towards a Cytokine-Cell Interaction Knowledgebase of the Adaptive Immune System. Shen-Orr SS, Goldberger O,Garten Y,Rosenberg-Hasson Y,Lovelace PA,Hirschberg DL, Altman RB, Davis MM, Butte AJ.Pacific Symposium on Biocomputing 2009:439-450

b. manual annotation of ImmPort summariesc. ?

The Infectious Disease Ontology

with thanks to Albert Goldfain and Lindsay G. Cowell

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IDO-Core• OBO Foundry ontology based on BFO and OGMS• Contains general terms in the ID domain:

• E.g., ‘colonization’, ‘pathogen’, ‘infection’• Intended to represent information along several

dimensions:• biological scale (gene, cell, organ, organism,

population)• discipline (clinical, immunological, microbiological) • organisms involved (host, pathogen, and vector types)

• A hub for further extension ontologies• A contract between IDO extension ontologies and the datasets that

use them.

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“Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease”

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ICD 9: Catch-all Codes and Scattered Exclusions• 041 Bacterial infection in conditions classified elsewhere and of unspecified site

• Note: This category is provided to be used as an additional code to identify the bacterial agent in diseases classified elsewhere. This category will also be used to classify bacterial infections of unspecified nature or site.

• Excludes: septicemia (038.0-038.9)• 041.1 Staphylococcus

• 041.10 Staphylococcus, unspecified• 041.11 Methicillin susceptible Staphylococcus aureus

• MSSA• Staphylococcus aureus NOS

• 041.12 Methicillin resistant Staphylococcus aureus• Methicillin-resistant staphylococcus aureus (MRSA)

• 041.19 Other Staphylococcus

• 038 Septicemia• 038.1 Staphylococcal septicemia

• 038.10 Staphylococcal septicemia, unspecified• 038.11 Methicillin susceptible Staphylococcus aureus septicemia

• MSSA septicemia• Staphylococcus aureus septicemia NOS

• 038.12 Methicillin resistant Staphylococcus aureus septicemia• 038.19 Other staphylococcal septicemia

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ICD 9: Catch-all Codes and Scattered Exclusions• 041 Bacterial infection in conditions classified elsewhere and of unspecified site

• Note: This category is provided to be used as an additional code to identify the bacterial agent in diseases classified elsewhere. This category will also be used to classify bacterial infections of unspecified nature or site.

• Excludes: septicemia (038.0-038.9)• 041.1 Staphylococcus

• 041.10 Staphylococcus, unspecified• 041.11 Methicillin susceptible Staphylococcus aureus

• MSSA• Staphylococcus aureus NOS

• 041.12 Methicillin resistant Staphylococcus aureus• Methicillin-resistant staphylococcus aureus (MRSA)

• 041.19 Other Staphylococcus

• 038 Septicemia• 038.1 Staphylococcal septicemia

• 038.10 Staphylococcal septicemia, unspecified• 038.11 Methicillin susceptible Staphylococcus aureus septicemia

• MSSA septicemia• Staphylococcus aureus septicemia NOS

• 038.12 Methicillin resistant Staphylococcus aureus septicemia• 038.19 Other staphylococcal septicemia

[041.19] Other Staphylococcus[041] Bacterial infection in conditions classified elsewhere and of

unspecified site.

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IDO: Core and Extensions Framework

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A Lattice of Lightweight Application-Specific Ontologies

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IDO-Staph: Introduction• Initial Release Candidate: http://

purl.obolibrary.org/obo/ido/sa.owl• Google Code Page: http://code.google.com/p/ido-staph/ • Scope

• Entities specific to Staphylococcus aureus (Sa) infectious diseases at multiple granularities

• Biological and clinical terms describing host-Sa interactions• An IDO extension ontology

• Extends IDO-Core, OGMS• BFO as an upper ontology • Built on OBO Foundry principles

• Applications • Duke Staph aureus Bacteremia Group data annotation• Lattice of infectious diseases

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Sa Organism: Parts and Products• Molecular Entities: Toxins, Invasins, Adhesins

from Shetty, Tang, and Andrews, 2009

80Source: http://textbookofbacteriology.net/themicrobialworld/staph.html

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Toxic Shock Syndrome• Staphylococcal TSS is a ido:‘infectious disease’

• has_material_basis SOME (Sa infectious disorder AND (has_part SOME TSST)

• TSST is a pr:protein• has_disposition SOME ‘exotoxin disposition’ [INF: is a exotoxin]

• tstH is a so:gene• has_gene_product SOME TSST• part_of SOME (SaPI2 OR SaPI3)

• SaPI2 is a so:‘pathogenic island’• SaPI3 is a so:‘pathogenic island’

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Sa Diseases: Asserted Hierarchy

• Primary classification of staphylococcal diseases• These are first and foremost infectious diseases

• Use DOIDs for disease terms• Assert ido:‘infectious disease’ as a parent term for these

diseases

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Sa Diseases: Inferred Hierarchy

• Secondary classification as Sa Infectious Diseases

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Ways of differentiating infectious diseases

• High-level types• By host type (species)• By anatomical site of infection• By signs and symptoms• By mode of transmission• By (sub-)species of pathogen

• Differentiation based on host features• Clinical phenotype• Strain (e.g. A/J)• Gene types (e.g. C5-deficient)• SNP alleles

• Differentiation based on pathogen features• By phenotype (e.g. drug resistance)• By genotype

• By banding patterns (e.g. PFGE)• By typing of house-keeping genes (e.g. MLST)• By virulence factor typing (e.g. spa, SCCmec)• By whole genome?

“Methicillin-Susceptible Staphylococcus aureus Endocarditis Isolates Are Associated with Clonal Complex 30 Genotype and a Distinct Repertoire of Enterotoxins and Adhesins”Nienaber et al. 2011 J Infect Dis. 204(5):704-13.

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Ways of differentiating Staph aureus infectious diseases• Sa Infectious Disease

• By SCCmec type• By ccr type• By mec class

• By spa type• IWG-SCC

• Maintains up-to-date SCCMec types

• General guidelines for reporting novel SCCmec elements

http://www.sccmec.org/Pages/SCC_ClassificationEN.html

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SCCMec (Staphylococcal Chromosome Cassette)• A mobile genetic element in Staphylococcus aureus that

carries the central determinant for broad-spectrum beta-lactam resistance encoded by the mecA gene and has the following features:• (1) carriage of mecA in a mec gene complex, • (2) carriage of ccr gene(s) (ccrAB or ccrC) in a ccr gene complex, • (3) integration at a specific site in the staphylococcal chromosome,

referred to as the integration site sequence for SCC (ISS), which serves as a target for ccr-mediated recombination, and

• (4) the presence of flanking direct repeat sequences containing the ISS.

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Representing SCCMec: IDO-Staph + SO

mec complex

gene group pathogenic island

SCCmec

SCCmec Type IVmec complex class B

mecAIS1272

geneinsertion sequence

ccr complex

ccr complex Type 2

ccrA2 ccrB2

has_part has_part

has_part has_parthas_parthas_part has_part has_part

is a is a is a

is a

is a is a

is a is a is a

is a

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NARSA Isolate Data• Isolate data from the Network for Antimicrobial Resistance

to Staph. Aureus• CDC Active Bacterial Core surveillance (ABCs) Isolates

Subset• Known Clinically Associated Strains• 101 Sa isolates

• Isolate data• Culture source (e.g. bone/joint)• Antimicrobial profile (e.g. erythromycin resistant)• Virulence factors expressed (e.g. TSST-1+)• PFGE type (e.g. USA300)• Genomic typing (e.g. MLST type 8, SCCmec type IV))

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Building the Lattice• For each NARSA Isolate we extract

• SCCMec Type (IDO-STAPH)• TSST +/- (IDO-STAPH)• PVL +/- (IDO-STAPH)• Culture Source (FMA)• Antimicrobial Profile

• Drug (CHEBI)• Minimum Inhibitory Concentration (OBI)• CLSI Interpretation of Resistance (IDO)

• Each particular isolate can be part of a particular Staph aureus infectious disorder.

• Each particular Staph aureus isolate can be the material basis for a particular Staph aureus infectious disease.

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Resistance of NRS701 to clindamycin• resistance_of_Iso_to_D instanceOf resistance_to_D• Iso has_disposition ‘resistance_of_Iso_to_D’• Iso_D_MIC instanceOf ‘MIC data item’• Iso_D_MIC has_measurement_value M

+

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Faceted Browser• http://awqbi.com/LATTICE/narsa-complete.html • http://purl.obolibrary.org/obo/ido/sa/narsa-isolates.owl

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Conclusion• Good web resources on Staph aureus exist…

• IWG-SCC• NARSA• Comprehensive Antibiotic Resistance Database (CARD)

• …but currently in information siloes and flat HTML• Disease specific application ontologies can be induced

from isolate data• Each such application ontology

• Has a well-defined place in the lattice beneath IDO-Core• Can be used to make Sa specific genetic-phenotypic assertions.

• We believe an IDO-based lattice of application ontologies can contribute to a new taxonomy of (infectious) disease.

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Acknowledgements• This work was funded by the National Institutes of Health

through Grant R01 AI 77706-01. Smith’s contributions were funded through the NIH Roadmap for Medical Research, Grant U54 HG004028 (National Center for Biomedical Ontology).

• Duke SABG• IDO Consortium• OBO Foundry