Ontology and Referent Tracking for Neurodegenerative Disorders

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Ontology and Referent TrackingforNeurodegenerati
ve Disorders

• Dr. Werner Ceusters
• European Centre for Ontological Research
• Saarland University, Saarbrücken, Germany

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Part I.Neurodegenerative disordersmodern
history
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Examples ofneurodegenerative diseases

• Involving the central nervous system
• Alzheimer's Disease
• Parkinson Disease
• ALS (Lou Gehrig's Disease)
• Frontal Temporal Dementia
• Huntington's Disease
• Cerebellar Ataxias
• Hereditary Spastic Paraplegias
• Involving the peripheral nervous system
• Charcot-Marie Tooth Hereditary Neuropathies
• Muscular Dystrophy.

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Some disease characteristics

• Neurodegeneration is a major element.
• But some disorders with ND are not usually
  classified as degenerative e.g. multiple
  sclerosis, epilepsy, some inborn errors of
  metabolism, schizophrenia, and even tumours.
• selective, at least initially, for a particular
  neuronal pool
• both genetic and environmental risk factors play
  a part in the etiology
• a long run-in period until sufficient protein
  accumulates, followed by a cascade of symptoms
  over 2-20 years, with increasing disability
  leading to death

A. Williams. Defining neurodegenerative diseases.
BMJ 20023241465-1466 ( 22 June )
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Wide range of phenotypes in same category, e.g.
cerebellar ataxias (SCA)

• SCA 1 hypermetric saccades and hyperreflexia.
• SCA 2 reduced velocity of saccadic eye
  movements, areflexia and changes similar to those
  seen in olivopontocerebellar atrophy on brain
  imaging.
• SCA 3 protruded eyes, muscle fasciculations,
  spasticity, chorea, gaze-evoked nystagmus,
  parkinsonism and peripheral neuropathy.
• SCAs 5, 6, 10 and 11 pure cerebellar signs.
• SCA 7 macular degeneration.
• SCA 8 mild sensory neuropathy, late-onset
  spasticity.
• SCA 10 seizures with ataxia.
• SCA 12 head and hand tremors.
• SCA 17 Intellectual deterioration and dysphagia.

T.E. King. Molecular diagnosis of adult
neurodegenerative diseases and movement
disorders. April 2005. http//www.bioethics-singap
ore.org/resources/pdf/GeneticTestingMovementDisord
ers_tanek.pdf
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Histopathological phenomenain some central NDs
L. Bertram and R.E. Tanzi. The genetic
epidemiology of neurodegenerative disease. J.
Clin. Invest. 1151449-1457 (2005).
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Multi-factorial with cross-relations, e.g.
genetic epidemiology of Alzheimer
L. Bertram and R.E. Tanzi. The genetic
epidemiology of neurodegenerative disease. J.
Clin. Invest. 1151449-1457 (2005).
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Main research epochs

• Early 1900
• Microscopic study of stained tissues
• Alzheimer, Lewy, Pick, ...
• NDs classified as clinicopathological entities
• Last decade
• Molecular genetics and molecular biology
• Advanced functional and sequential imaging
• NDs classified by means of pathological
  biochemical pathways

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Research purposes for ND

• characterize the clinical, laboratory, and
  pathological phenotypes of the various disorders
  included in this category
• identify and clone genes directly causing or
  functioning as risk factors for these disorders
• understand basic mechanisms underlying the
  biochemical and molecular pathogenesis of these
  disorders
• Find application to treatment and prevention

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Research purposes froman omics perspective

• understand the normal functions of genes and
  proteins involved in neurodegenerative diseases,
• characterize their role in pathogenic disease
  mechanisms,
• model their functions in animals,
• explore their roles in the diagnosis, treatment
  and prevention

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Technical strategy foranalysing ND pathogenesis

• identify pathogenic genes
• by positional cloning,
• by cloning genes that encode proteins involved in
  the disease,
• or by combining the two approaches
• find pathogenic mutations
• model and study the disease
• in cells by transfection and
• in mice by transgenesis

D. L. Price, S. S. Sisodia, D. R. Borchelt,
Science 282, 1078 (1998)
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E.g. positional cloning

• identify large multigenerational families with a
  long history of carrying the disorder
• determine linkage with polymorphic genetic
  markers
• look for cytogenetic rearrangements associated
  with the disease
• isolate overlapping DNA clones from the region
• identifying the gene that is responsible

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Another strategy for ND gene detection
L. Bertram and R.E. Tanzi. The genetic
epidemiology of neurodegenerative disease. J.
Clin. Invest. 1151449-1457 (2005).
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New NDs are discovered

• a previously unrecognized adult-onset dominantly
  inherited ND that affects the basal ganglia
  associated with iron accumulation.
• Phenotype
• extrapyramidal symptoms and low ferritin serum
  levels.
• lesions in the globus pallidus with abundant
  spherical inclusions containing aggregates of
  ferritin and iron.
• axonal swellings throughout the brain
• organs such as the pancreas, liver, and heart
  that are typically affected in iron accumulation
  disease, appear to function normally

Curtis ARJ, Fey C, Morris CM, et al. Mutation in
the gene encoding ferritin light polypeptide
causes dominant adult-onset basal ganglia
disease. Nature Genetics 2001 28 350-354.
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Intermediate conclusions

• NDs are challenging with respect to reality
  representation
• Involve entities of diverse nature
• true nature of some entities not yet understood
• Type of relationships unclear

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Part II.Role of ontology
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Ontology

• Ontology the study of being as a science
• An ontology a representation of some
  pre-existing domain of reality which
• (1) reflects the properties of the objects within
  its domain in such a way that there obtains
  a systematic correlation between reality and the
  representation itself,
• (2) is intelligible to a domain expert
• (3) is formalized in a way that allows it to
  support automatic information processing
• ontological (as adjective)
• Within an ontology.
• Derived by applying the methodology of ontology
• ...

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Need for widely acceptedTop Level Ontology (TLO)

• TLO an ontology that describes by means of
  theories or specifications the most general,
  domain-independent categories of reality such as
  time, space, inherence, instantiation, identity,
  processes, events, attributes, relations, ...
• Ongoing efforts
• BFO
• DOLCE
• SUMO

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Need for widely acceptedBiomedical Domain
Ontology (BMO)

• domain ontology
• an ontology that describes the most general
  categories within a specific domain, using the
  framework of the top level ontology. In our case
  the domain is biomedicine.
• Where a top level ontology describes entities
  such as objects and processes, a biomedical
  domain ontology
• describes entities such as genes and insulin, and
  transcription and hormon secretion.
• further classifies these entities within the
  framework of the top level ontology, thereby
  adding new descriptive elements that are relevant
  at that level of reality.

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Essential (and missing) components for a
biomedical domain ontology

• Ontology for functions and processes
• levels of granularity for functions
• localizing functions and processes to understand
  their mutual relationships
• functional states of molecules
• Ontology for anatomical levels of granularities
• levels of granularity based on grains and
  structure
• determination of parthood relations across
  entities in different levels of granularity
• Pathophysiology ontology
• Dependence relations between physiological
  entities and pathology
• Determination of parthood relations for
  pathological entities
• An upper ontology for health information stored
  in public health information databases

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Links to ongoing efforts

• Use BMO
• To make more DB semantics explicit and formal
• to make the various databases semantically
  interoperable at both structure and content level.

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ExampleKEGG Pathway Database onNeurodegenerativ
e Disorders

• Alzheimer's disease
• Parkinson's disease
• Amyotrophic lateral sclerosis (ALS)
• Huntington's disease
• Dentatorubropallidoluysian atrophy (DRPLA)
• Prion disease

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KEGG Pathway ND
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KEGG Pathway Alzheimer
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KEGG Pathway notation
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Part III.Referent Tracking
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The missing link

• From genotype to phenotype
• Most DBs contain data without reference to
  particular patients
• Some DBs (usually not publicly accessible) just
  have snapshots of correlations
• No DBs provide a dynamically growing pool of data
  about interrelated patient phenomena
• Note
• NOT interrelated data
• Relationships between data are distinct from
  relationships amongst the entities the data are
  about
• The right approach Referent Tracking

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Referent Tracking ...

• Corrects the overemphasis on data and information
  and too little attention to reality
• data modelling
• information modelling
• Does right what the Object Oriented model
  claims to do right.
• objects are said to be those things that exist in
  reality
• But The object-oriented model is based on a
  collection of objects
• An object contains values stored in instance
  variables within the object.
• Unlike the record-oriented models, these values
  are themselves objects.

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A look at the database Use of SNOMED codes for
unambiguous understanding
How many numerically different disorders are
listed here ?

How many different types of disorders are listed
here ?

How many disorders have patients 5572, 2309 and
298 each had thus far in their lifetime ?

cause, not disorder
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Would it be easier if youcould see the code
labels ?
5572
04/07/1990
79001
Essential hypertension
0939
24/12/1991
255174002
benign polyp of biliary tract
2309
21/03/1992
26442006
closed fracture of shaft of femur
0939
20/12/1998
255087006
malignant polyp of biliary tract
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Proposed solutionReferent Tracking

• Purpose
• explicit reference to the concrete individual
  entities relevant to the accurate description of
  each patients condition, therapies, outcomes,
  ...
• Method
• Introduce an Instance Unique Identifier (IUI) for
  each relevant individual ( particular,
  instance).
• Distinguish between
• IUI assignment for instances that do exist
• IUI reservation for entities expected to come
  into existence in the future

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No confusion withexplicit references
IUI-003
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Essentials of Referent Tracking

• Generation of universally unique identifiers
• deciding what particulars should receive a IUI
• finding out whether or not a particular has
  already been assigned a IUI (each particular
  should receive maximally one IUI)
• using IUIs in the EHR, i.e. issues concerning the
  syntax and semantics of statements containing
  IUIs
• determining the truth values of statements in
  which IUIs are used
• correcting errors in the assignment of IUIs.

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Architecture of aReferent Tracking System (RTS)

• RTS system in which all statements referring to
  particulars contain the IUIs for those
  particulars judged to be relevant.
• Ideally set up as broad as possible
• some metrics
• of particulars referred to by means of IUI
• of HCs active in a region
• Geographic region
• functional region defined by contacts amongst
  patients
• of patients referred to within a region
• Services
• IUI generator
• IUI repository statements about assignments and
  reservations
• Referent Tracking Database (RTDB) index (LSID)
  to statements relating instances to instances and
  classes

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Ultimate goal
Ontology
continuant
disorder
person
CAG repeat
EHR
Juvenile HD
IUI-1 affects IUI-2 IUI-3 affects
IUI-2 IUI-1 causes IUI-3 ...
Referent Tracking Database