tutorial what is_an_ontology_ncbo_march_2012

1

What is an Ontology and What is it Useful For?

Barry Smith

http://ontology.buffalo.edu/smith

• html demonstrated the power of the Web to allow sharing of information

• can we use semantic technology to create a Web 2.0 which would allow algorithmic reasoning with online information based on XLM, RDF and above all OWL (Web Ontology Language)?

• can we use RDF and OWL to break down silos, and create useful integration of on-line data and information

2

A brief history of the Semantic Web

people tried, but the more they were successful, they more they failed

OWL breaks down data silos via controlled vocabularies for the description of data dictionaries

Unfortunately the very success of this approach led to the creation of multiple, new, semantic silos – because multiple ontologies are being created in ad hoc ways

3

reasons for this effect• Tim Berners Lee mentality

– let a million ‘lite ontologies bloom’, and somehow intelligence will be created

– ‘links’ can mean anything (à la html)

• shrink-wrapped software mentality – you will not get paid for reusing old and good ontologies

• requirements-driven software development• reducing potential secondary uses

4/24

Ontology success stories, and some reasons for failure

•

A fragment of the “Linked Open Data” in the biomedical domain

5

What you get with ‘mappings’

HPO: all phenotypes (excess hair loss, duck feet)

6


HPO: all phenotypes (excess hair loss, duck feet ...)

NCIT: all organisms

7


all phenotypes (excess hair loss, duck feet)

all organisms

allose (a form of sugar)

8


all phenotypes (excess hair loss, duck feet)

all organisms

allose (a form of sugar)

Acute Lymphoblastic Leukemia (A.L.L.)

9

Mappings are hard

They are fragile, and expensive to maintainNeed a new authority to maintain, yielding new

risk of forkingThe goal should be to minimize the need for

mappingsInvest resources in disjoint ontology modules

which work well together – reduce need for mappings to minimum possible

11

Why should you care?

• you need to create systems for data mining and text processing which will yield useful digitally coded output

• if the codes you use are constantly in need of ad hoc repair huge resources will be wasted

• relevant data will not be found• serious reasoning will be defeated from the

start

12/24

15

…

How to do it right?

• how create an incremental, evolutionary process, where what is good survives, and what is bad fails

• where the number of ontologies needing to be linked is small

• where links are stable• create a scenario in which people will find it

profitable to reuse ontologies, terminologies and coding systems which have been tried and tested

16/24

Uses of ‘ontology’ in PubMed abstracts

17

By far the most successful: GO (Gene Ontology)

18

GO provides a controlled system of terms for use in annotating (describing, tagging) data

• multi-species, multi-disciplinary, open source

• contributing to the cumulativity of scientific results obtained by distinct research communities

• compare use of kilograms, meters, seconds in formulating experimental results

19

Hierarchical view representing relations between represented types 20

Pleural Cavity

Pleural Cavity

Interlobar recess

Interlobar recess

Mesothelium of Pleura

Mesothelium of Pleura

Pleura(Wall of Sac)

Pleura(Wall of Sac)

VisceralPleura

VisceralPleura

Pleural SacPleural Sac

Parietal Pleura

Parietal Pleura

Anatomical SpaceAnatomical Space

OrganCavityOrganCavity

Serous SacCavity

Serous SacCavity

AnatomicalStructure

AnatomicalStructure

OrganOrgan

Serous SacSerous Sac

MediastinalPleura

MediastinalPleura

TissueTissue

Organ PartOrgan Part

Organ Subdivision

Organ Subdivision

Organ Component

Organ Component

Organ CavitySubdivision

Organ CavitySubdivision

Serous SacCavity

Subdivision

Serous SacCavity

Subdivision

part

_of

is_a

Foundational Model of Anatomy (FMA)

21

US $100 mill. invested in literature and data curation using GO

over 11 million annotations relating gene products described in the UniProt, Ensembl and other databases to terms in the GOexperimental results reported in 52,000 scientific journal articles manually annoted by expert biologists using GO

22

23

Reasons why GO has been successful

It is a system for prospective standardization built with coherent top level but with content contributed and monitored by domain specialists

Based on community consensusUpdated every nightClear versioning principles ensure backwards

compatibility; prior annotations do not lose their value

Initially low-tech to encourage users, with movement to more powerful formal approaches (including OWL-DL – though GO community still recommending caution)

24

GO has learned the lessons of successful cooperation

• Clear documentation• The terms chosen are already familiar• Fully open source (allows thorough testing in

manifold combinations with other ontologies)• Subjected to considerable third-party critique• Rapid turnaround tracker and help desk• Usable also for education• Focus on reality

Why is the focus on reality important

Each community, each local data structure, has its own conceptualization

What shall serve as benchmark for the integration of the data generated by data communities?

Answer: Reality, as understood by bench scientists

Conclusion: Bench scientists have to be involved in the construction and coordination of ontologies

25

26

Data structures and ontologies have different purposes

Information models and ontologies are at different levels• The purpose of an information model is:to

specify valid data structures to carry information

• To constrain the data structures to just those which a given software system can process

The purpose of an ontology is to represent the world

27

Data structures and ontologies have different characteristics

All persons have a sex

However not all data structures about people have a field for sex

Information structures are intrinsically closed

We can describe them completely

Ontologies are intrinsically open

We can never describe the real world completely

Benefits of GO

Establishing a bridge between the molecular/gene level and higher order biology – you get nothing by just looking at genes.

Building up a larger picture of biological systems as a mosaic of areas studied in depth by one or other of the model organism databases (but never all, and not all in any one)

Creating a view to link studies on different organisms.

28

Sample Gene Array Data

29

30

where in the body ?

what kind of disease process ?

need for semantic annotation of data

31

natural language labels

to make the data cognitively accessible to human beings

32

compare: legends for mapscompare: legends for maps

33

ontologies are legends for data

34

annotation with Gene Ontology

supports reusability of data

supports search of data by humans

supports reasoning with data by humans and machines

GO has been amazingly successful in overcoming the data balkanization

problembut it covers only generic biological entities of three sorts:

– cellular components– molecular functions– biological processes

and it does not provide representations of diseases, symptoms, …

35

RELATION TO TIME

GRANULARITY

CONTINUANT OCCURRENT

INDEPENDENT DEPENDENT

ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity(FMA, CARO)

OrganFunction

(FMP, CPRO) Phenotypic

Quality(PaTO)

Biological Process

(GO)CELL AND CELLULAR

COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule

(ChEBI, SO,RnaO, PrO)

Molecular Function(GO)

Molecular Process

(GO)

Original OBO Foundry ontologies (Gene Ontology in yellow) 36

37

RELATION TO TIME

GRANULARITY



ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)


OrganFunction


Quality(PaTO)

Biological Process


COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule



Molecular Process

(GO)

Environment Ontology

envi

ron

men

ts

are

her

e

38

RELATION TO TIME

GRANULARITY



COMPLEX OFORGANISMS

Family, Community, Deme, Population

OrganFunction

(FMP, CPRO)

Population Phenotype

PopulationProcess

ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity(FMA, CARO) Phenotypic

Quality(PaTO)

Biological Process


COMPONENT

Cell(CL)

Cellular Componen

t(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule



Molecular Process

(GO)

http://obofoundry.org

Ontology success stories, and some reasons for failure

•

39

40

RELATION TO TIME

GRANULARITY



COMPLEX OFORGANISMS

Family, Community, Deme, Population

OrganFunction

(FMP, CPRO)

Population Phenotype

PopulationProcess

ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity(FMA, CARO) Phenotypic

Quality(PaTO)

Biological Process


COMPONENT

Cell(CL)

Cellular Componen

t(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule



Molecular Process

(GO)


Developers commit to working to ensure that, for each domain, there is community convergence on a single ontology

and agree in advance to collaborate with developers of ontologies in adjacent domains.


The OBO Foundry: a step-by-step, evidence-based approach to expand

the GO

41

OBO Foundry Principles

Common governance (coordinating editors)

Common training

Common architecture to overcome Tim Berners Lee-ism:

• simple shared top level ontology

• shared Relation Ontology: www.obofoundry.org/ro

42

Open Biomedical Ontologies Foundry

Seeks to create high quality, validated terminology modules across all of the life sciences which will be

• one ontology for each domain, so no need for mappings

• close to language use of experts

• evidence-based

• incorporate a strategy for motivating potential developers and users

• revisable as science advances

43

44

A prospective standard

designed to guarantee interoperability of ontologies from the very start (and to keep out weeds)

initial set of 10 criteria tested in the annotation of

scientific literature

model organism databases

life science experimental results

45

ORTHOGONALITY

modularity ensures • annotations can be additive• division of labor amongst domain experts• high value of training in any given module• lessons learned in one module can benefit

work on other modules• incentivization of those responsible for

individual modules

Benefits of coordination

Can profit from lessons learned through mistakes made by others

Can more easily reuse what is made by others

Can more easily inspect and criticize results of others’ work

Leads to innovations (e.g. Mireot in strategies for combining ontologies and for importing terms from other ontologies)

46

Problems with the OBO Foundry

1. the results are over-complex for almost all users

2. high quality ontology development is slow, slow, slow

For 1., views (Brinkley, Uvic, ontodog, …)

For 2., the hub and spokes model

47

The Hub and Spokes Model

“Constructing a lattice of Infectious Disease Ontologies from a Staphylococcus aureus Isolate Repository”

Albert Goldfain, Lindsay Cowell and Barry Smith, Proceeedings of the Third International Conference on Biomedical Ontology, Graz, July 22-25, 2012, forthcoming.

48

Infectious Disease Ontology (IDO)

– IDO Core: • General terms in the ID domain. • A hub for all IDO extensions.

– IDO Extensions: • Disease specific. • Developed by subject matter experts.

• Provides:– Clear, precise, and consistent natural language

definitions– Computable logical representations (OWL, OBO)

How IDO evolvesIDOCore

IDOSa

IDOHumanSa

IDORatSa

IDOStrep

IDORatStrep

IDOHumanStrep

IDOMRSa

IDOHumanBacterial

IDOAntibioticResistant

IDOMAL IDOHIVCORE and SPOKES:Domain ontologies

SEMI-LATTICE:By subject matter experts in different communities of interest.

IDOFLU

IDO Core

• Contains general terms in the ID domain:– E.g., ‘colonization’, ‘pathogen’, ‘infection’

• A contract between IDO extension ontologies and the datasets that use them.

• 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)

Sample IDO Definitions

• Host of Infectious Agent (BFO Role): A role borne by an organism in virtue of the fact that its extended organism contains an infectious agent.

• Extended Organism (OGMS): An object aggregate consisting of an organism and all material entities located within the organism, overlapping the organism, or occupying sites formed in part by the organism.

• Infectious Agent: A pathogen whose pathogenic disposition is an infectious disposition.

IDO and IDOSa

• Scale of the infection (disorder)

from Shetty, Tang, and Andrews, 200912/10/2010 53

Staphylococcus aureus (Sa)

MSSa MRSa

HA-MRSa CA-MRSa

UK CA-MRSa Australian CA-MRSa

Specific Strains

{Antibiotic Resistance

{Pathogenesis Location Type

{Geographic Region

{Various Differentia

Differentiated by:

Sample Application: A lattice of infectious disease application ontologies from NARSA isolate data

Network on Antimicrobial Resistance in Staphylococcus aureus–http://www.narsa.net/content/staphLinks.jsp

True personalized medicine – YourDiseaseOntology

http://www.narsa.net/content/staphLinks.jsp

http://www.narsa.net/content/staphLinks.jsp

Ways of differentiating Staphylococcus aureus infectious diseases

• Infectious Disease– By host type– By (sub-)species of pathogen– By antibiotic resistance– By anatomical site of infection

• Bacterial Infectious Disease– By PFGE (Strain)– By MLST (Sequence Type)– By BURST (Clonal Complex)

• Sa Infectious Disease– By SCCmec type

• By ccr type• By mec class

– spa type

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

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

ido.owl

narsa.owl

narsa-isolates.owl

ndf-rt

NRS701’s resistance to clindamycin

New York State Center of Excellence in Bioinformatics & Life Sciences

R T U New York State Center of Excellence in Bioinformatics & Life Sciences

R T U

Ontologies make data collections comparable

...

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CharacteristicsCases

...

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case5

case4

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Linking the variables of distinct data collections to a realism-based ontology.

New York State Center of Excellence in Bioinformatics & Life Sciences

R T U New York State Center of Excellence in Bioinformatics & Life Sciences

R T U

Werner Ceusters

1R01DE021917-01A1

National Institute of Dental and Craniofacial Research (NIDCR).

OPMQoL: an Ontology for pain-related disablement, mental

health and quality of life

IASP definition for ‘pain’:– ‘an unpleasant sensory and emotional experience

associated with actual or potential tissue damage, or described in terms of such damage’;

which asserts:– a common phenomenology (‘unpleasant sensory

and emotional experience’) to all instances of pain,

– the recognition of three distinct subtypes of pain involving, respectively:

1. actual tissue damage, 2. what is called ‘potential tissue damage’, and 3. a description involving reference to tissue damage

whether or not there is such damage.

data collection

data item

1

1..*

A data collection consists of at least 1 data item, each data item belonging to exactly 1 collection

data collection

data dictionaryuses

1..*

1

used-for

data item

1

1..*

1

explained-in

1..*

exp

lain

s

Data dictionaries provide information about data items and data collections

data collection

assessmentinstrument

data dictionary

uses

used-in

1..*

uses

1..*

1

used-for

data item

0..*

terminology

1

1..*

uses 1..* usedfor

0..*1

explained-in

1..*

exp

lain

s

uses1..*

usedfor

0..*

Data dictionaries provide also information about terminologies and assessment instruments used for data

generation, in addition to information about the collection’s structure

data collection


data dictionary

uses

used-in

1..*

uses

1..*

1

used-for

data item

0..*

terminology

1

1..*

uses 1..* usedfor

0..*1

explained-in

1..*

exp

lain

s

uses1..*

usedfor

0..*

Relation of Terminology component to Data component

Terminology component

Data component

term

concept

1broader

narrower1..*

1..*

used in

uses0..*

0..*

1..*

means

expressed-by

data collection


data dictionary

uses

used-in

1..*

uses

1..*

1

1..*

used-for


Data component

data item

0..*

terminology1

1

1..*

uses 1..* usedfor

0..*1

explained-in

1..*

exp

lain

s

uses1..*

usedfor

0..*

Terminology links terms to ‘concepts’

term

concept

1broader

narrower1..*

1..*

used in

uses0..*

0..*

1..*

means

expressed-by

data collection


data dictionary

uses

used-in

1..*

uses

1..*

1

1..*

used-for


Data component

data item

0..*

terminology1

1

1..*

uses 1..* usedfor

0..*1

explained-in

1..*

exp

lain

s

uses1..*

usedfor

0..*

Not ‘concepts’ are of interest, but entities in reality

Ontologycomponent

entity

term

concept

1broader

narrower1..*

1..*

used in

uses0..*

0..*

1..*

means

expressed-by

data collection


data dictionary

uses

used-in

1..*

uses

1..*

1

1..*

used-for


Data component

data item

0..*

terminology1

1

1..*

uses 1..* usedfor

0..*1

explained-in

1..*

exp

lain

s

uses1..*

usedfor

0..*

It is real entities that should be denoted in ontologies

Ontologycomponent

entity

ontology

reference ontology1..*

1

denotes0..*

denoted by

1

denotator

term

concept

1broader

narrower1..*

1..*

used in

uses0..*

0..*

1..*

means

expressed-by

data collection


data dictionary

uses

used-in

1..*

uses

1..*

1

1..*

used-for


Data component

data item

0..*

terminology1

1

1..*

uses 1..* usedfor

0..*1

explained-in

1..*

exp

lain

s

uses1..*

usedfor

0..*

Application ontologies cover the domains of the sources

Ontologycomponent

entity

ontology

reference ontology1..*

1

denotes0..*

denoted by

1

denotator

1

used-for1..*

usedfor

1

uses

applicationontology

data collectionontology

assessment instrument ontology

1uses

term

concept

1broader

narrower1..*

1..*

used in

uses0..*

0..*

1..*

means

expressed-by

data collection


0..1expresses

0..*

ontology

data dictionary

uses

used-in

1

1..*

uses

1..*

1

reference ontology

1..*

used-for1..*

usedfor

1

uses

bridging axiom

used-for

usedfor

0..*

uses1..*

applicationontology


Data component

Ontologycomponent

data item

representationalartifact

1..*

data collectionontology

assessment instrument ontology

1uses

0..*

terminology

1..*

uses1

used-for

entity 1

denotes0..*

denoted by

1

1

1..*

uses 1..* usedfor

0..*

1

corresponds-to

1

explained-in

1..*

exp

lain

s

uses1..*

usedfor

0..*

denotator

Bridging axioms link data to ontologies and terminologies

Anatomy Ontology(FMA*, CARO)

Environment

Ontology(EnvO)

Infectious Disease

Ontology(IDO*)

Biological Process

Ontology (GO*)

Cell Ontology

(CL)

CellularComponentOntology

(FMA*, GO*) Phenotypic Quality

Ontology(PaTO)

Subcellular Anatomy Ontology (SAO)Sequence Ontology

(SO*) Molecular Function

(GO*)Protein Ontology(PRO*) OBO Foundry Modular Organization 71

top level

mid-level

domain level

Information Artifact Ontology

(IAO)

Ontology for Biomedical

Investigations(OBI)

Spatial Ontology(BSPO)

Basic Formal Ontology (BFO)

BFO: the very top

Continuant Occurrent(Process, Event)

IndependentContinuant

DependentContinuant

73

RELATION TO TIME

GRANULARITY



ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)


OrganFunction


Quality(PaTO)

Biological Process


COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule



Molecular Process

(GO)



ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity

(FMA, CARO)

OrganFunction


Quality(PaTO)

Organism-Level Process

(GO)

CELL AND CELLULAR

COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

Cellular Process

(GO)

MOLECULEMolecule



Molecular Process

(GO)

obofoundry.org

GRANULARITY

RELATION TO TIME

Basic Formal Ontology

continuant occurrent

biological processes

independentcontinuant

cellular component

dependentcontinuant

molecular function

BFO: The Very Top

continuant


dependentcontinuant

qualityfunctionroledisposition

occurrent


Continuant Occurrent

process, eventIndependentContinuant

thing

DependentContinuant

quality

.... ..... .......

types

instances

Basic of BFO in GO

Continuant Occurrent

biological processIndependent

Continuant

cellular component

DependentContinuant

molecular function

..... ..... ........

Experience with BFO in building ontologies provides

• a community of skilled ontology developers and users (google user group has 118 members)

• associated logical tools • documentation for different types of users• a methodology for building conformant ontologies

by starting with BFO and populating downwards

Example: The Cell Ontology

:.

Users of BFOPharmaOntology (W3C HCLS SIG)

MediCognos / Microsoft Healthvault

Cleveland Clinic Semantic Database in Cardiothoracic Surgery

Major Histocompatibility Complex (MHC) Ontology (NIAID)

Neuroscience Information Framework Standard (NIFSTD) and Constituent Ontologies

Interdisciplinary Prostate Ontology (IPO)

Nanoparticle Ontology (NPO): Ontology for Cancer Nanotechnology Research

Neural Electromagnetic Ontologies (NEMO)

ChemAxiom – Ontology for Chemistry

81

:.

Users of BFOGO Gene Ontology

CL Cell Ontology

SO Sequence Ontology

ChEBI Chemical Ontology

PATO Phenotype (Quality) Ontology

FMA Foundational Model of Anatomy Ontology

ChEBI Chemical Entities of Biological Interest

PRO Protein Ontology

Plant Ontology

Environment Ontology

Ontology for Biomedical Investigations

RNA Ontology

82

:.

Users of BFOOntology for Risks Against Patient Safety (RAPS/REMINE)

eagle-i an VIVO (NCRR)

IDO Infectious Disease Ontology (NIAID)

National Cancer Institute Biomedical Grid Terminology (BiomedGT)

US Army Biometrics Ontology

US Army Command and Control Ontology

Sleep Domain Ontology

Subcellular Anatomy Ontology (SAO)

Translaftional Medicine On (VO)

Yeast Ontology (yOWL)

Zebrafish Anatomical Ontology (ZAO)

83




dependentcontinuant

organism

84

Continuants

• continue to exist through time, preserving their identity while undergoing different sorts of changes

• independent continuants – objects, things, ...

• dependent continuants – qualities, attributes, shapes, potentialities ...

85

Occurrents

• processes, events, happenings– your life– this process of accelerated cell

division

86

Qualitiestemperatureblood pressuremass...

are continuantsthey exist through time while undergoing changes

87

Qualitiestemperature / blood pressure /

mass ...are dimensions of variation within the structure of the entitya quality is something which can change while its bearer remains one and the same

88

A Chart representing how John’s temperature

changes

89

A Chart representing how John’s temperature

changes

90

John’s temperature,the temperature he has throughout his entire life, cycles through different determinate temperatures from one time to the next

John’s temperature is a physiology variable which, in thus changing, exerts an influence on other physiology variables through time

91

BFO: The Very Top

continuant


dependentcontinuant

quality

occurrent

temperature 92

Blinding Flash of the Obvious


dependentcontinuant

quality

temperature types

instances

organism

John John’s

temperature 93



dependentcontinuant

quality

temperature types

instances

organism

John John’s

temperature 94


temperature types

instances

organism

John John’s

temperature .

95

inheres_in

temperature types

instances

John’s temperature

96

37ºC37.1º

C37.5º

C37.2º

C37.3º

C37.4º

C

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

human types

instances

John

97

embryo

fetus adultneonat

einfant child

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

Temperature subtypesDevelopment-stage

subtypes

are threshold divisions (hence we do not have sharp boundaries, and we have a certain degree of choice, e.g. in how many subtypes to distinguish, though not in their ordering)

98


dependentcontinuant

quality

temperature types

instances

organism

John John’s

temperature

99


dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

course of temperature

changes

John’s temperature history

100


dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

temperature process profile

John’s temperature history


dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

life of an organism

John’s life

102

BFO: The Very Top



dependentcontinuant

quality disposition

103

Disposition- of a glass vase, to shatter if dropped- of a human, to eat - of a banana, to ripen- of John, to lose hair

104

Dispositionif it ceases to exist, then its bearer and/or its immediate surrounding environment is physically changedits realization occurs when its bearer is in some special physical circumstancesits realization is what it is in virtue of the bearer’s physical make-up

105

:.

Function - of liver: to store glycogen- of birth canal: to enable transport- of eye: to see- of mitochondrion: to produce ATP

functions are dispositions which are designed or selected for

106


dependentcontinuant

function

to seeeye

John’s eye function of John’s eye: to see

occurrent

process

process of seeing

John seeing

107

OGMSOntology for General Medical

Science

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

108

109

Physical Disorder

:.

Physical Disorder

– independent continuantfiat object part

A causally linked combination of physical components of the extended organism that is clinically abnormal.

110

Clinically abnormal

– (1) not part of the life plan for an organism of the relevant type (unlike aging or pregnancy),

– (2) causally linked to an elevated risk either of pain or other feelings of illness, or of death or dysfunction, and

– (3) such that the elevated risk exceeds a certain threshold level.*

*Compare: baldness111

Big Picture

112

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

Disease =def. – A disposition to undergo pathological processes that exists in an organism because of one or more disorders in that organism.

Disease course =def. – The aggregate of processes in which a disease disposition is realized.

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Pathological Process=def. A bodily process that is a manifestation of a disorder and is clinically abnormal.

Disease =def. – A disposition to undergo pathological processes that exists in an organism because of one or more disorders in that organism.

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Cirrhosis - environmental exposure

• Etiological process - phenobarbitol-induced hepatic cell death– produces

• Disorder - necrotic liver– bears

• Disposition (disease) - cirrhosis– realized_in

• Pathological process - abnormal tissue repair with cell proliferation and fibrosis that exceed a certain threshold; hypoxia-induced cell death– produces

• Abnormal bodily features– recognized_as

• Symptoms - fatigue, anorexia• Signs - jaundice, enlarged spleen

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Influenza - infectious

• Etiological process - infection of airway epithelial cells with influenza virus

– produces

• Disorder - viable cells with influenza virus

– bears

• Disposition (disease) - flu

– realized_in

• Pathological process - acute inflammation

– produces

• Abnormal bodily features

– recognized_as

• Symptoms - weakness, dizziness

• Signs - fever 116

Dispositions and Predispositions

All diseases are dispositions; not all dispositions are diseases.

Predisposition to Disease

=def. – A disposition in an organism that constitutes an increased risk of the organism’s subsequently developing some disease.

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Huntington’s Disease - genetic

• Etiological process - inheritance of >39 CAG repeats in the HTT gene– produces

• Disorder - chromosome 4 with abnormal mHTT– bears

• Disposition (disease) - Huntington’s disease– realized_in

• Pathological process - accumulation of mHTT protein fragments, abnormal transcription regulation, neuronal cell death in striatum– produces

• Abnormal bodily features– recognized_as

• Symptoms - anxiety, depression• Signs - difficulties in speaking and

swallowing

Symptoms & Signs used_in

Interpretive process produces

Hypothesis - rule out Huntington’s suggests

Laboratory tests produces

Test results - molecular detection of the HTT gene with >39CAG repeats used_in


Result - diagnosis that patient X has a disorder that bears the disease Huntington’s disease

HNPCC - genetic pre-disposition

• Etiological process - inheritance of a mutant mismatch repair gene– produces

• Disorder - chromosome 3 with abnormal hMLH1– bears

• Disposition (disease) - Lynch syndrome– realized_in

• Pathological process - abnormal repair of DNA mismatches– produces

• Disorder - mutations in proto-oncogenes and tumor suppressor genes with microsatellite repeats (e.g. TGF-beta R2)– bears

• Disposition (disease) - non-polyposis colon cancer

Systemic arterial hypertension

• Etiological process – abnormal reabsorption of NaCl by the kidney

– produces

• Disorder – abnormally large scattered molecular aggregate of salt in the blood

– bears

• Disposition (disease) - hypertension

– realized_in

• Pathological process – exertion of abnormal pressure against arterial wall

– produces

• Abnormal bodily features

– recognized_as

• Symptoms -

• Signs – elevated blood pressure



Hypothesis - rule out hypertension suggests

Laboratory tests produces

Test results - used_in


Result - diagnosis that patient X has a disorder that bears the disease hypertension

Type 2 Diabetes Mellitus

• Etiological process – – produces

• Disorder – abnormal pancreatic beta cells and abnormal muscle/fat cells

– bears• Disposition (disease) – diabetes mellitus

– realized_in• Pathological processes – diminished

insulin production , diminished muscle/fat uptake of glucose

– produces• Abnormal bodily features

– recognized_as• Symptoms – polydipsia, polyuria,

polyphagia, blurred vision• Signs – elevated blood glucose and

hemoglobin A1c



Hypothesis - rule out diabetes mellitus suggests

Laboratory tests – fasting serum blood glucose, oral glucose challenge test, and/or blood hemoglobin A1c produces

Test results - used_in


Result - diagnosis that patient X has a disorder that bears the disease type 2 diabetes mellitus

Type 1 hypersensitivity to penicillin

• Etiological process – sensitizing of mast cells and basophils during exposure to penicillin-class substance

– produces• Disorder – mast cells and basophils with

epitope-specific IgE bound to Fc epsilon receptor I

– bears• Disposition (disease) – type I

hypersensitivity– realized_in

• Pathological process – type I hypersensitivity reaction

– produces• Abnormal bodily features

– recognized_as• Symptoms – pruritis, shortness of breath• Signs – rash, urticaria, anaphylaxis



Hypothesis - suggests

Laboratory tests – produces

Test results – occasionally, skin testing used_in


Result - diagnosis that patient X has a disorder that bears the disease type 1 hypersensitivity to penicillin

Early Onset Alzheimer’s Disease

Disorder – mutations in APP, PSEN1 and PSEN2bears

Disposition – impaired APP processingrealized in

Pathological process – accumulation of intra- and extracellular protein in the brainproduces

Disorder – amyloid plaque and neurofibrillary tanglesbearsDisposition – of neurons to dierealized in Pathological process – neuronal loss

producesDisorder – cognitive brain regions damaged and reduced in size

bearsDisposition (disease) – Alzheimer’s dementia

realized inSymptoms – episodic memory loss and other cognitive domain impairment

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Arterial Aneurysm• Disposition – atherosclerosis

– realized in• Pathological process – fatty material collects within the walls of arteries

– produces• Disorder – artery with weakened wall

– bears• Disposition – of artery to become distended

– realized_in• Pathological process – process of distending

– produces• Disorder – arterial aneurysm

– bears• Disposition – of artery to rupture

– realized in• Pathological process – (catastrophic event) of rupturing

– produces• Disorder – ruptured artery, arterial system with dangerously low blood pressure

– bears• Disposition – circulatory failure

– realized in• Pathological process – exsanguination, failure of homeostasis

– produces• Death

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Hemorrhagic stroke

• Disorder – cerebral arterial aneurysm– bears

• Disposition – of weakened artery to rupture– realized in

• Pathological process – rupturing of weakened blood vessel– produces

• Disorder – Intraparenchymal cerebral hemorrhage– bears

• Disposition (disease) – to increased intra-cranial pressure– realized in

• Pathological process – increasing intra-cranial pressure, compression of brain structures– produces

• Disorder – Cerebral ischemia, Cerebral neuronal death– bears

• Disposition (disease) – stroke– realized in

• Symptoms – weakness/paralysis, loss of sensation, etc

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coronary heart disease

John’s coronary heart disease

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asymptomatic (‘silent’) infarction

early lesions and small

fibrous plaques

stable angina

surface disruption of plaque

unstable angina

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

time


dependentcontinuant

disposition

diseasedisorder

John’s disordered

heart

John’s coronary heart

disease

occurrent

process

course of disease

course of John’s disease

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