BFO-aligned Ontologies for Clinical and Translational Research:

OGMS, IDO, and VO

(Orlando Presentation, 2/8/2013)http://ncorwiki.buffalo.edu/index.php/CTSA_Ontology_Workshop

Yongqun “Oliver” He

University of Michigan Medical SchoolAnn Arbor, MI 48109

BFO and OBO Foundry Principles

• BFO: Basic Formal Ontology

• BFO has been used a top level ontology for many ontologies associated with clinical and translational research

• Examples: OGMS, IDO, VO, OBI, OAE

• All OBO foundry library ontologies follow OBO Foundry principles, e.g., openness, collaboration, and use of a common shared syntax

OGMS: Ontology of General

Medical Science • An ontology of the major

types of entities involved in a clinical encounter.– An upper ontology for

clinical medicine– A mid-level ontology with

respect to BFO

• Includes ~100 general terms

• By: – Albert Goldfain – Richard Scheuermann– Barry Smith, …

https://code.google.com/p/ogms/

Wide OGMS Applications

Ontologies using OGMS:

• IDO• DO• SDO• AERO • OAE• VSO• OMRSE• VO• ...

Courtesy: figure kindly provided by Albert Goldfain

OGMS application example:Development of OAE

• OAE: Ontology of Adverse Events• OAE ‘adverse event’:

– = def. a OGMS: ‘pathological bodily process’ that occurs after a medical intervention.

– Does not assume causality – ‘causal adverse event’ assumes causality

• >1,000 specific AE terms in OAE now, mapped to MedDRA terms

OAE for AE data analysisRef: Sarntivijai et al., 2012PLoS ONE

IDO: Infectious Disease Ontology

• IDO: represent the entire infectious disease domain

• Interoperability with other disease and health domains

• IDO-core: by Lindsay Cowell, Barry Smith, and others

Courtesy: figure kindly provided by Lindsay Cowell

IDO-core Central Terms:

IDO Core-Extension Development Strategy

• IDO extensions are developed by extending IDO-core

OGMS

OBIGO BP

CL

I IDO-Core

IDO-Bac

IDO-Virus

IDO-Sa

IDO-Flu IDO-Mal

IDO-Par

IDO-Fun

IDO-Flav

IDO-TB

IDO-Sch

IDO-Asp

IDO-Cry

Courtesy: figure kindly provided by Lindsay Cowell

• We developed an IDO extension: Brucellosis Ontology

IDOBRU: Brucellosis Ontology as an IDO Extension

• Focuses on the domain of zoonotic brucellosis, caused by Gram-negative bacterium Brucella. 

• Incorporates all IDO-core terms, has over 880 Brucella-specific terms, and imports terms from other ontologies.

Citation: “Asiyah” Yu Lin, Zuoshuang Xiang, Yongqun He. Brucellosis Ontology (IDOBRU) as an extension of the Infectious Disease Ontology. Journal of Biomedical Semantics. 2011 Oct 31;2(1):9. PMID: 22041276.

IDO-core is the top ontology of IDOBRU

Vaccine Ontology (VO)

• VO: A biomedical ontology in the domain of vaccine and vaccination

• Support data integration, literature mining, and reasoning

• Integrated with VIOLIN• VIOLIN: a vaccine database and analysis

system, including many programs, e.g.:o ~3000 vaccineso Protegen: protective antigens. ~600o Vaxjo: vaccine adjuvants: > 100o Vaxign: vaccine designo Widely used by vaccine community

• Funded by a NIAID R01 grant

http://www.violinet.org/vaccineontology

http://www.violinet.org

Many Ontology Tools developed during VO development

is_aontology

development tool

Hegroup RDF triple

store

Ontorat: generate new ontology

terms

OntoFox: reuse existing ontology

terms

is_a

Ontodog: generate ontology community

view

Ontobee: linked ontology

data server

uses

is_a

ontology application

tool

uses

uses

uses is_a

is_a

uses is_a

OntoCOG: COG enrichment

analysis tool

Ontobat: biodata analysis tool

(In development)

Ontology fetching tool Linked ontology data server

Mass generation of new terms

Ontology community view generator

Ontology data analysis

VO Statistics and Development

# Class ObjectProperty Subtotal

VO 4800 7 4807BFO 2 22 38 60

RO 0 4 4CARO 9 0 9CHEBI 20 0 20DOID 57 0 57

GO 19 0 19OBI 36 11 47

OGMS 1 0 1PATO 17 0 17FMA 2 0 2IAO 18 2 20IDO 2 0 2

NCBITaxon 397 0 397PRO 2 0 2

UBERON 8 0 8UO 1 0 1

Subtotal 5411 62 5473

• OntoFox to import external terms and axioms from other 16 ontologies

• Ontorat to generate a large number of terms and axioms automatically

• VO includes >1000 vaccines for >20 host spp. against various diseases

VO imports OBI terms for vaccine investigation

OBI/VO modeling of “vaccine protection

assay”

Reference: Brinkman et al. (2007). Modeling biomedical experimental processes with OBI. Journal of Biomedical Semantics. 2010, 1(Suppl 1):S7. PMID: 20626927.

OBI: Ontology for Biomedical Investigations

~20 communities involved

Example: Afluria Influenza Vaccine

Afluria-1Flu vaccine

is_a

CSL Limited

intramuscular vaccination

adaptive immune response

is_manufactured

_byinactivated

chicken egg protein allergen

has_quality has_part

bearer_of

vaccine allergen

disposition

bearer_of

dose specification

viral vaccine-induced

immunization

has_specified_output_ofis_specified_

input_of

has_part bearer_of some ‘acquired immunity to Influenza virus’

age

viral pathogen target role

Influenza virus

has_participant

is_about

Bob (a human)

realizes

vaccine host role

has_quality

age measurement datum (value: 6

unit: month)

quality_is_measured_as

has_participant

realizes

bearer_of

measurementdata

is_a has_participant

plan specification

is_realized

-byhas_part

U of Michigan Ontology Research

• UM Ontology Working Group:o Members: Marcy Harris, Alla Karnovsky, Frank Manion,

Oliver He, Asiyah Yu Lin, Jeff Cowall, … o Activities: Biweekly meetings, …o Developing a Clinical and Translational Research Ontology.

• UM MCubed pilot award:o Title: Ontology Development and Applications for Clinical

and Translational Scienceo To: Alla, Marcy, and Oliver; Period: 1.5 years

• UM CTSA: Michigan Institute for Clinical & Health Research (MICHR)o Ontology research needed to integrate huge datasets o Committed to collaborative community efforto One project: Informed Consent Ontology (ICO) (next slide)

• Case study: Head and neck cancer biorepository

Informed Consent Ontology (ICO)• ICO: A prototype, aligned with BFO.• Currently focused on research permissions• UM CTSA Project Team:

Alla Karnovsky, Frank Manion, Marcy Harris, Oliver He, Nick Steneck, Blake Roessler

Reference: Development of an Informed Consent Ontology to Support Biobanking. Alla Karnovsky, Frank J. Manion, Oliver He, Terry Weymouth, V. Glenn Tarcea; Lisa Powell, Blake J. Roessler, Nicholas H. Steneck. AMIA 2012 Annual Symposium.

Protocol

Patient Record

Institutional Records

IRB/eResearch

Informed Consent Form

Subject matter expert view

Courtesy: figures kindly provided by Alla Karnovsky and Nickolas Steneck

Clinical Data Integration Required• Records of millions of patients in UM Health System (UMHS)• Ontology is needed for true clinical data integration

Courtesy: figure kindly provided by Jeff Cowall

Acknowledgements

Funding: NIH grants R01AI081062 & U54-DA-021519UM MCubed pilot project, MICHR (UM CTSA)

Oliver He Group:

• Zuoshuang “Allen” Xiang• “Asiyah” Yu Lin• Sirarat Sarntivijai

UM Literature Mining Collaborators:

• Arzucan Özgür • Junguk Hur

VO Collaborators:

Barry, Lindsay, Alan, Bjoern, ….

Barry Smith (BFO, OGMS, IDO, VO, ...)

OBI Consortium:

• Bjoern Peters• Jie Zheng• Chris Stoeckert• Alan Rutternberg• Melanie Courtot, …

UM Ontology Working Group Listed in a previous slide

Lindsay Cowell (IDO)

OGMS Development Team

• Albert Goldfain • Richard Scheuermann, …