Wanting what we don’t want to want: Representing addiction in interoperable bio-ontologies Janna Hastings 1,2∗, Nicolas le Novère 3 , Werner Ceusters 4 , Kevin Mulligan 5 and Barry Smith 6 1 Cheminformatics and Metabolism, European Bioinformatics Institute, Cambridge, UK 2 Swiss Center for Affective Sciences, University of Geneva, Switzerland 3 Computational Systems Neurobiology, European Bioinformatics Institute, Cambridge, UK 4 Department of Psychiatry and National Center for Ontological Research, University at Buffalo, USA 5 Department of Philosophy and Swiss Center for Affective Sciences, University of Geneva, Switzerland 6 Department of Philosophy and National Center for Ontological Research, University at Buffalo, USA ABSTRACT different specialist disciplines. In the various fields investigating Ontologies are being developed throughout the biomedical scie- mental health and related issues, the problem of terminology and nces to address standardization, integration, classification and rea- integration is particularly severe, as much of the terminology emplo- soning needs against the background of an increasingly data-driven yed refers to subjective experiences on the side of the patient and research paradigm. In particular, ontologies facilitate the translation subjective judgements on the side of the caregiver, for which it is of basic research into benefits for the patient by making resea- difficult to design standardised measurements across different disci- rch results more discoverable and by facilitating knowledge transfer plines and to integrate results arising from different methodological across disciplinary boundaries. and technological approaches. Research into mental illness needs to Addressing and adequately treating mental illness is one of our be correlated with research on the associated canonical mental pro- most pressing public health challenges. Primary research across mul- cesses and with underlying biological and neurochemical pathways tiple disciplines such as psychology, psychiatry, biology, neuroscience in order to better understand conditions and mechanisms of action, and pharmacology needs to be integrated in order to promote a more and ultimately to lead thereby to the discovery and design of novel comprehensive understanding of underlying processes and mechani- therapeutics for challenging conditions (Ceusters and Smith, 2010; sms, and this need for integration only becomes more pressing with National Advisory Mental Health Council Workgroup, 2010). our increase in understanding of differences among individuals and Addiction is a primary mental health problem affecting an incre- populations at the molecular level concerning susceptibility to specific asing percentage of the population in the developed world (National illnesses. Substance addiction is a particularly relevant public health Institute on Drug Abuse, 2007). In the year 2000, the estima- challenge in the developed world, affecting a substantial percentage ted death toll due solely to use of tobacco was around 5 million of the population, often co-morbid with other illnesses such as mood worldwide (Ezzati and Lopez, 2009). Furthermore, addiction is disorders. Currently, however, there is no straightforward automa- often co-morbid with other mental health conditions such as bipo- ted method to combine data of relevance to the study of substance lar disorder and depression. We will limit the ensuing discussion to addiction across multiple disciplines and populations. substance addiction, leaving process addictions (such as addiction In this contribution, we describe a framework of interlinked, inte- to gambling) to one side. The DSM-IV description for patients with roperable bio-ontologies for the annotation of primary research data alleged substance addiction (or dependence) reads: ‘When an indi- relating to substance addiction, and discuss how this framework ena- vidual persists in use of alcohol or other drugs despite problems bles easy integration of results across disciplinary boundaries. We related to use of the substance, substance dependence may be dia- describe entities and relationships relevant for the description of addi- gnosed. Compulsive and repetitive use may result in tolerance to the ction within the Mental Functioning Ontology, Chemical Entities of effect of the drug and withdrawal symptoms when use is reduced or Biological Interest Ontology, Protein Ontology, Gene Ontology and stopped.’ (APA, 2000). the Neuroscience Information Framework ontologies. While the DSM, controlled vocabularies such as SNOMED CT and patient classification systems such as ICD include references 1 INTRODUCTION to various sorts of mental illness, as yet none of these provides the facility to smoothly interlink the results of relevant related resea- Ontologies are increasingly designed to support scientific research rch from different domains such as psychology, psychiatry, biology, through annotation and integration of research results, with the goals chemistry and neuroscience. The OBO Foundry (Smith et al., 2007) of enabling sophisticated querying and disambiguation of the termi- promotes the development of interoperable domain-specific public nology employed in scientific literature. Furthermore, ontologies, domain ontologies that – in contrast to the above-mentioned resou- when designed with not only logical consistency but also faithful- rces – can be interlinked with bridging relationships that have been ness to reality in mind (Smith and Ceusters, 2010; Brochhausen termed cross-products (Mungall et al., 2010). Within each domain, et al., 2011), help facilitate the translation of primary research into the domain-specific ontology is applied to annotation of research therapeutic endpoints by easing the transfer of knowledge between results. For example, the Gene Ontology (The Gene Ontology Con- ∗ To whom correspondence should be addressed: hastings@ebi.ac.uk sortium, 2000) is used to annotate gene products, the Chemical 1 Hastings, le Novère et al Entities of Biological Interest ontology (de Matos et al., 2010) In what follows, we will work within the Mental Functioning is used to annotate chemicals. Bridging relationships (for exam- Ontology (MF) as the context for our representation. MF is an ple, chemical participation in a biological process) then are able ontology for all aspects of mental functioning, including mental to span different resources based on the relationships between the processes such as cognition and traits such as intelligence (Hastings ontology entities. This strategy allows automated reasoning to retri- et al., 2012). Disorders and diseases of mental functioning are inclu- eve relevant results across disciplines with different primary entities ded in a separate module, the Mental Disease Ontology (MD). They and annotation standards – without necessitating that each resource are being developed beneath the upper-level ontology Basic Formal provide additional primary annotation to the ontologies which are Ontology (BFO) (Grenon and Smith, 2004). Figure 1 illustrates the outside of its core domain. upper levels of the ontologies. The purpose of this paper is to illustrate such a framework for the overlapping disciplines of mental health, mental illness and che- 2.1 Types of Addiction mical biology, focusing on data pertaining to addiction. In the next The type substance addiction can be further refined by reference section, we discuss the definition and symptoms of addiction, and to the substance that determines its subtypes. Such substances are how these can be described in ontologies of mental functioning and described in databases such as DrugBank (Wishart et al., 2006) disease. Thereafter, we describe how underlying mechanisms of and included in ChEBI (de Matos et al., 2010). Although these action for addiction and the substances which are the objects of addi- resources may not be fully comprehensive, many common addictive ction are described in other bio-ontologies. Finally, we discuss the substances are already included, and the bulk of addictive substance framework in comparison to related work and prevailing methods. chemistry is represented in ChEBI in the form of parent compounds from which many new illicit drugs are likely to be derived. Addiction is a disposition to, inter alia, use of the substance in question. Substance use is characterised by intake of some sort 2 REPRESENTING ADDICTION (eating tablets or injecting fluids, for example). We can describe Addiction is an example of a mental disease. Following (Ceusters substance use as a bodily process that has as participant some and Smith, 2010), we regard mental disease as a disposition to path- portion of the substance in question (OWL Manchester syntax (Hor- ological processes rather than as itself an example of a pathological ridge and Patel-Schneider, 2009)): process. This can be seen as corresponding to the sense in which MF:Nicotine Use subClassOf ( MF:Bodily Process and a patient with nicotine addiction is still addicted even if he has not hasParticipant1 some CHEBI:Portion of Nicotine ) smoked in the last week, and for some severe addictions such as CHEBI:Portion of Nicotine subClassOf ( heroin, relatively few substance use events can be enough to confer CHEBI:Chemical Substance and hasGranularPart2 some the addiction for the remainder of the patient’s life. The process of CHEBI:Nicotine Molecule ) ongoing substance use by an organism eventually results in changes MD:Nicotine Addiction subClassOf ( MD:Addiction and to the organism such that the disposition – the addiction – is created. isRealizedIn3 some MF:Nicotine Use ) In the remainder of this paper, we will use the term ‘mental disease’ This description is necessary, but certainly not sufficient to define exclusively as a technical term in this sense, and use ‘mental disor- substance use, as there are many bodily processes in which sub- der’ to denotes the physical basis that brings a mental disease into stances participate that would not qualify as substance use (for existence and ‘mental disease course’ for the totality of processes example, accidental inhalation of secondary smoke). However, that realizes a mental disease (Scheuermann et al., 2009). We will the axiom nevertheless serves as a link between ‘addiction’ and reserve the term ‘addiction’ to refer to the mental disease so defi- ‘nicotine’ that can be reasoned over. ned, although in common language ‘addiction’ is ambiguous: it can be used to mean either the disease or the disease course (the latter 2.2 Symptoms of Addiction being something which varies in type from patient to patient, for Addiction – or rather, in our terminology, the disease course of example according to presence or absence of treatment). addiction – is described in the DSM-IV as having the following sym- ptoms, three or more of which in a 12 month period are required for a positive diagnosis (APA, 2000): 1.Preoccupation with use of the chemical between periods of use. 2.Using more of the chemical than had been anticipated. 3.The development of tolerance to the chemical in question. 4.A characteristic withdrawal syndrome from the chemical. 5.Use of the chemical to avoid or control withdrawal symptoms. 6.Repeated efforts to cut back or stop the drug use. 1 hasParticipant is defined in (Smith, 2012), section entitled ‘Relation of participation’. 2 As described in (Batchelor et al., 2010), we follow (Bittner and Don- nelly, 2006) in using hasGranularPart, a sub-property of hasPart, to link bulk portions of chemical substances to the molecules from which they are composed. 3 isRealizedIn is defined in (Smith, 2012), section entitled ‘Relation of Fig. 1. Upper levels of the Mental Functioning Ontology realization’. 2 Representing addiction in interoperable bio-ontologies 7.Intoxication at inappropriate times (such as at work), or when 2.4 Planning withdrawal interferes with daily functioning (such as when han- Planning is a cognitive process that has as output a realizable plan gover makes person too sick to go to work). that the organism develops about its own future behaviour. The plan 8.A reduction in social, occupational or recreational activities in is realized if the corresponding behaviour is executed. favor of further substance use. MF:Planning subClassOf MF:Cognitive Process 9.Continued substance use in spite of the individual having suffered MF:Planning Substance Use subClassOf ( MF:Planning social, emotional, or physical problems related to drug use. and hasParticipant some ( MF:Cognitive Representation and Cognitive processes are mental processes that manipulate cogni- isAbout some MF:Plan for Quantity of Substance to Use ) ) tive representations, such as thinking and planning. Many of the Here, the Plan for Quantity of Substance to Use would be, for the symptoms listed above can be characterised in part as mental proces- individual, further specified in terms of the quantity of the substa- ses, and in part as behaviour. Preoccupation with use of the chemical nce and a time-frame over which the quantity is to be distributed. is an uncontrolled form of thinking about the chemical – a cognitive For example, a plan could involve a specification such as ‘I want to process. Using more of the chemical than had been anticipated is smoke no more than five cigarettes per day’. Planning is also impli- behaviour (using the chemical) as well as an implicit description cated in the symptom where the use of the chemical is taken to avoid of a historical anticipation or plan for how much of the substance or control withdrawal symptoms. Here, though, the plan, to control to use (even if the plan involved is very vague, e.g. ‘use less’ or withdrawal symptoms, is in fact realized. ‘try to quit’). While tolerance and withdrawal are best characteri- sed in physiological terms, deliberate use of the chemical to avoid 2.5 Behaviour or control withdrawal symptoms is again behaviour, as are repeated Most of the processes described in the list of symptoms are beh- efforts to cut back or stop the drug use. Similarly, interference of aviour, and most of these have to do with taking the substance in intoxication or withdrawal in daily functioning, reduction in social question. This is in itself unsurprising, since the DSM-IV is desi- or other activities in favour of further substance use, and continued gned as a tool to aid diagnosis, and behavioural symptoms are those substance use in spite of related problems suffered, can all be cha- which are easiest to observe. A further elucidation of the use of the racterised as contrasts between behaviour affected by substance use substance in question could include the following: and what would have been the canonical or normal behaviour of the MF:Substance Use subClassOf ( MF:Behaviour organism. In particular, substance addiction is often characterised and hasParticipant some CHEBI:Addictive Substance ) by repeated failed efforts to control or give up the use of the substa- CHEBI:Addictive Substance subClassOf ( nce – in which case, we might say, the organism wants not to want CHEBI:Portion of Chemical Substance and to use the substance. hasDisposition some In what follows we sketch how some of the symptoms can be CHEBI:Disposition to Alter Reward System Functioning )) represented with explicit relationships to mental functioning terms, Here, Disposition to Alter Reward System Functioning needs to be which will allow bridging from disease annotations to annotations further annotated in the ontology by reference to the various known of research into normal mental processes. mechanisms by which addictive substances alter the functioning of the brain reward system (Berridge and Robinson, 2003). We discuss 2.3 Thinking some of these mechanisms in Section 3. The primary altered form of thinking that is characteristic of addi- 2.6 Linking the symptoms to the disease ction is the preoccupation, in which the content of the thinking It is important to note that the existence of any of the above sym- process is use of the substance in question: ptoms in isolation does not imply the presence of an addiction, in MF:Thinking subClassOf MF:Cognitive Process particular as some of them may also be symptoms of different dis- MF:Preoccupation With Substance Use subClassOf ( eases. Neither does addiction imply the existence of any one of the MF:Thinking and hasParticipant some ( symptoms, as only a subset of symptoms need be present. Therefore MF:Cognitive Representation and we cannot assert an existential restriction on a relationship between isAbout4 some MF:Plan to Use Substance ) ) the symptoms and the disease without creating incorrect implica- Missing from the above description is a characterization of the tions (Boeker et al., 2011). Rather, the inference from symptoms thinking process that merits the description ‘preoccupation’. In to disease is made on the judgement of a clinician in the case of order for a thinking process to be described as a preoccupation, it a particular patient (Ceusters and Smith, 2006). Nevertheless, we needs to be regularly recurring and be uncontrolled. It is implied can assume – if the DSM-IV criteria are taken to be correct – that that the patient cannot help undergoing this thought process, despite there are at least some cases of addiction in which some of these the existence of efforts to think about other things instead. These symptoms are displayed as manifestations of the disease. To link attributes of the thinking process are process profiles. Process pro- the symptoms and the disease for purposes of automated reasoning, files are structural dimensions of processes, such as rates and other we could create a subtype of the disease which displays the relevant attributes, recently introduced in BFO 2 (Smith, 2012). symptom, for example: MD:Addiction with Preoccupation subClassOf ( MD:Addiction and realizedIn some MF:Preoccupation With Substance Use ) This strategy will allow the symptoms of mental diseases to be 4 isAbout is defined in the Information Artifact Ontology (IAO, Ruttenburg linked to the corresponding ‘normal’ mental functionings such as et al. (2012)) as that relation which holds between a representation and the ordinary thinking and planning, thus enabling automated retrieval entity that it is a representation of. of relevant results across the boundary of research into normal and 3 Hastings, le Novère et al abnormal functioning. However, DSM-IV does not refer explicitly (REACT 15295), and some models of the relevant signaling path- to any information at the biochemical or neurobiological levels of ways are present in the BioModels (Li et al., 2010) database (e.g. description. The next section addresses this shortcoming. BIOMD0000000153, MODEL9079740062). In both resources, the processes are annotated by GO terms and the physical entities. These inter-ontology interlinkages to describe the biochemistry 3 BIOCHEMISTRY AND NEUROBIOLOGY and neurobiology of addiction facilitate enhanced querying across Substance addictions are caused by the highjacking of the reward all resources in which any of the ontologies are applied as annotati- system of the brain (Koob and Volkow, 2010). This system, part ons. For example, rather than querying pathway databases for heroin of the basal ganglia, is a crucial relay of the cortico-striato-thalamic alone, a query can retrieve results for all molecules that act with the loop, involved in learning, motivation and control of voluntary loco- same mechanism of action. 22 molecules have hasRole ‘µ-opioid motion. Most psychostimulant drugs of abuse – the mechanism of receptor agonist’ (CHEBI:55322) in the January 2012 release. action for depressants such as alcohol is slightly different – stimu- The key missing ingredient in this picture is the link from these late the global activity of the mesocorticolimbic dopamine system, annotations involving mechanism of action to the disease itself. Lin- causing an increase of extracellular dopamine in the striatum. The king entities in ontologies describing mental disease to the entities exact mechanism to achieve this differs from substance to substance: described in ontologies for the underlying mechanism of action, nicotine mimics acetylcholine and stimulates the release of dopa- which are in turn linked to ontologies for biological entities such mine; cocaine and amphetamine inhibit the re-uptake of dopamine; as chemicals and proteins, will allow automated retrieval of biologi- dopamine agonists – such as those used to treat Parkinson’s dise- cal knowledge in relevant databases and automated linking of these ase – mimic dopamine; while opioids, cannabinoids and caffeine data to the corresponding medical and psychiatric data for addiction, amplify the effect of dopamine receptors by mimicking respectively facilitating the translation of basic research into clinical applicati- the effect of enkephalines, anandamine and adenosine. ons. Such links will take the form of ontology cross-products linking As a consequence of these effects of substance use, the meso- specific types of addiction to specific known pathways (biological corticolimbic system adapts to the drug intake, through molecular, processes), representing the best of current scientific knowledge. cellular and tissular mechanisms, causing withdrawal symptoms when the drug consumption is interrupted. Onset and maintenance of addiction involves the response of neurotransmitter receptors to 4 DISCUSSION the drug, recruitment of signalling pathways and disregulation of Interlinking of entities across different domains has been populari- transcription factor cascades, but also chromatine remodeling via zed in Semantic Web approaches. For example, Sahoo et al. (2008) histone modification (Robison and Nestler, 2011). This leads to provide an ontology-based semantic ‘mash-up’ of nicotine depende- a complete cell reprogramming of the dopaminergic neurons and nce related pathways and genes. While our approach is compatible their targets, including protein production and targeting, synapse with use within the Semantic Web, it is not restricted to such usage, generation and dendritic remodeling. and the ontologies we mention are in most cases already being This mechanism of action can be amply described using exi- applied to many different application scenarios including primary sting ontologies such as the Chemical Entities of Biological Interest data-driven research. Ontology annotations are becoming an essen- Ontology (CHEBI, de Matos et al. (2010)), Protein Ontology (PR, tial tool in life sciences data management and comparison, and Natale et al. (2011)), Gene Ontology (GO, The Gene Ontology Con- have been used to compare systems biology models as a clustering sortium (2000)), NeuroLex and BIRNlex (Bug et al., 2008). For method for retrieval (Schulz et al., 2011). instance, when a portion of heroin is consumed, the molecule heroin Existing lexicons in the domain of mental functioning and disease (CHEBI:27808), participates in a binding process (GO:0031628), have by and large been designed with one application or commu- to µ-opioid receptors (PR:000001612). Similarly, when a por- nity in mind, and the result has been the proliferation of distinct tion of tobacco is smoked, the molecule nicotine (CHEBI:27808), and overlapping ontologies, none of which is appropriately interlin- participates in a binding process (GO:0033130), to nicotinic acet- ked in the way we have described for addiction, and in which the ycholine receptors (GO:0005892). Those receptors are present on classification of entities has been ad-hoc and application-specific. A the dopaminergic neurons (NeuroLex – nlx:144018), of the nucleus search for ‘addiction’ in BioPortal returns 12 exact matches from accumbens, described in BIRNlex (birnlex:727). different vocabularies and 462 partial matches and synonyms. Yet, Heroin is assigned to the ‘biological role’ class ‘µ-opioid receptor none of these occur in contexts where the disease is explicitly rela- agonist’ (CHEBI:55322). As described in (Batchelor et al., 2010), ted to its mechanisms of action or symptoms in the fashion we have ChEBI biological roles are functions that are realized in biologi- described. Mental processes such as thinking and planning are also cal processes, in this case ‘regulation of opioid receptor signaling described in multiple resources, for example the Cognitive Atlas pathway’ (GO:2000474), in which process both the chemical and (Poldrack et al., 2011), but this resource does not include a term for the µ-opioid receptor participates. Those receptors are present on addiction (although it does in fact include a task for the measure- the striatal medium-sized spiny neurons (NeuroLex – nifext:141), ment of nicotine dependence, not related to any cognitive terms). of the nucleus accumbens, described in BIRNlex (birnlex:727). The NIF vocabularies include terms for mental disorders such as This binding potentiates the dopamine (CHEBI:18243) receptor heroin dependence (nlx:89410) and opioid-related disorder (birn- (PR:000001107) signaling pathways (GO:0007212). In particular, lex:12713), but do not link these to the chemicals in question nor the protein kinase A signaling cascade (GO:0010737) activates the to any of the other related vocabularies. In short, the proliferation transcription factor CREB (PR:000005854; GO:0032793). of standard vocabularies within specific domains and application Furthmore, the entire opioid signaling pathway is descri- scenarios has hindered rather than facilitated data integration and bed in the pathway database Reactome (Matthews et al., 2009) enhanced querying thus far. 4 Representing addiction in interoperable bio-ontologies Following the OBO Foundry approach and creating an interlinked Ceusters, W. and Smith, B. (2010). 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