Enabling querying and browsing of biomedical and neuroscientific research on addiction using interoperable ontologies and cross-products. Presented at ICBO 2012.
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Representing addiction in Mental Functioning and Disease ontologies
1. ICBO @ Graz, July 2012
Wanting what we don’t want to want
Representing addiction
in interoperable bio-ontologies
Janna Hastings1,2
Nicolas le Novère1
Werner Ceusters3
Kevin Mulligan2
Barry Smith3
1 European Bioinformatics Institute, UK
2 University of Geneva, Switzerland
3 University at Buffalo, USA
4. Substance addiction in DSM-IV
When an individual persists in use
of alcohol or other drugs
despite problems related to use of the substance,
substance dependence may be diagnosed.
Compulsive and repetitive use may result in tolerance
to the effect of the drug
and withdrawal symptoms
when use is reduced or stopped.
Friday, July 27, 2012 4
6. What do we know about addiction?
Behaviour Neural
Psychiatric
of addicted pathways
treatment
persons
Brain
activation Metabolism
and
excretion of
Biochemical
pathways Properties of substances
the addictive Toxicity
substances
Genetic
susceptibility … actually, rather a lot
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7. How do we find data about addiction?
PSYCHOLOGY, OBSERVATION
, NEUROBIOLOGY
MEDICAL RECORDS
CLINICAL QUESTIONNAIRES MODELS
Behaviour Neural
Psychiatric
of addicted pathways
treatment
persons
Brain
activation Metabolism
FUNCTIONAL BIOACTIVITY
IMAGING and
excretion of
Biochemical
pathways Properties of substances
the addictive Toxicity
MODELS substances
CHEMISTRY
Genetic
GENES susceptibility … many, many databases
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10. The same applies to many types of data
METABOLIC
DATA (e.g. NMR)
GENE
EXPRESSION
PATHWAYS, biological DATA
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processes
11. Describing mechanism of action
When a portion of heroin is consumed, the
molecule heroin (CHEBI:27808) participates in a
binding process (GO:0031628) to mu-opioid
receptors (PR:000001612).
Similarly, when a portion of tobacco is smoked, the
molecule nicotine (CHEBI:27808) participates in a
binding process (GO:0033130) to nicotinic
acetycholine receptors (GO:0005892).
Those receptors are present on the dopaminergic
neurons (NeuroLex – nlx:144018), of the nucleus
accumbens, described in BIRNlex (birnlex:727).
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12. What is missing?
GLUE
DOMAIN-SPECIFIC ONTOLOGIES
Neuroscientific
Psychological Biological
knowledge & data:
research into knowledge & data:
Medical neurons, neurochemistr
canonical human mechanisms, genetic
y, brain structure &
functioning variants etc.
function
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13. Mental Functioning Ontology and
Mental Disease Ontology
Domain-neutral
BFO ontological upper level
Mental Functioning
OGMS MF
Ontology
Ontology for General
Medical Science
MFO-EM Emotion Ontology
MD Mental Disease Ontology
(Current focus on affective disorders
and addiction)
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14. Substance addictions can be
characterised by the substances that
they are addictions to
MF:0000071
realized in MF:0010071
cocaine addiction
cocaine addiction
disease course
has part
S:00100100 has input MF:0020071
portion of cocaine use of cocaine
has granular part
CHEBI:27958
Chemical and
cocaine
metabolic data
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15. Addiction in the Mental Disease Ontology
MF:0000046
addiction
MF:0000053 MF:0000053
process addiction substance addiction
MF:0000054 MF:0000066 MF:0000065
gambling addiction benzodiazepine addiction opiate addiction
MF:0000055 MF:0000067 MF:0000059
sex addiction diazepam addiction heroin addiction
MF:0000064 MF:0000068
internet addiction morphine addiction
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16. Canonical research can be related to
non-canonical symptoms in the
disease course
MF:0001002 MF:0001001
non-canonical (impaired) non-canonical (impaired)
thinking process planning process
MF:0001012 MF:0001011
preoccupation with failed attempts to
substance use stop substance use
has part
MF:0001053
MF:0000053 realized in
substance addiction
substance addiction
disease course
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17. Bridging to underlying mechanisms
Addictions hijack neurotransmitter receptors and
pathways
molecular entity biological role Molecular function
(CHEBI:25375) (CHEBI:24432) (GO:0003674)
subtype
neurotransmitter
dopamine neurotransmitter receptor activity
(CHEBI:25375) (CHEBI:25512) (GO:0030594)
has role realized in
Friday, July 27, 2012 17
19. Acknowledgements
Colin Batchelor
Jane Lomax, David Osumi-Sutherland
Occasional and regular members of the
Cambridge ontology discussion group
Christoph Steinbeck
Friday, July 27, 2012 19
Notas del editor
Why am I interested in substance addiction? Co-morbidity with mood disorders. Serious condition in and of itself. Strikes vulnerable teenagers. Takes away something of the intrinsic self-directedness of humans. We will draw here on concrete examples from the domain of substance addiction. The choice of topic is arbitrary in the sense that another aspect of mental functioning would have worked just as well. Addiction is a primary mental health problem affecting an increasing percentage of the population in the developed world (NationalInstitute on Drug Abuse, 2007). The estimated death toll for 2000 due solely to use of tobacco was around 5 million worldwide (Ezzatiand Lopez, 2009). Furthermore, addiction is often co-morbid with other mental health conditions such as bipolar disorder and depression.
La Morfina, Santiago Rusinol y Prats
Pathway illustration sourced from KEGG: http://www.kegg.jp/kegg-bin/highlight_pathway?scale=1.0&map=map05030&keyword=addictionNMR spectrum illustration (of a derivative of cocaine) comes from http://www.justice.gov/dea/programs/forensicsci/microgram/journal_v4_num14/pg5.html
Computable representation of the symptoms of mental diseases, linked up to the questionnaires and other instruments that are used in diagnosisWhat sorts of things are the symptoms? What is known about normal functionings of the relevant sorts (so that we can compare data?)How do we use general search terms to also retrieve data at much lower levels of granularity, without doing massive annotation of irrelevant information (from the perspective of the lower-level researchers)?