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Studies on impulse control disorders in subpopulations
Impulse control disorders have been studied in subpopulations, defined by an age range or another disorder. Besides Parkinson’s disease, which we will detail in the next section, the most studied disorders are obsessive-compulsive disorders (Fontenelle et al., 2005; Grant et al., 2006). ICDs and obsessive-compulsive disorders overlap in their phenomenology, co-morbidity, pathophysiology and family history (Fontenelle et al., 2011). Compulsive and impulsive disorders have been viewed at the opposite ends of a single dimension: the former motivated by a desire to avoid harm and the latter by reward-seeking behavior (Fineberg et al., 2010). The prevalence of ICDs in patients with obsessive-compulsive disorders is estimated to be around 11–35%, skin picking being the most common comorbid ICD (Fontenelle et al., 2005; Grant et al., 2006, 2010).
A review on ICDs and bipolar disorder highlighted the high number of common features for both disorders: phenomenological similarities, including pleasurable, dan-gerous, or harmful behaviors, impulsivity, and similar affective symptoms and dysregu-lation; onset in late childhood or early adulthood with episodic and/or chronic course; high comorbidity with one another and comparable comorbidity with other psychiatric disorders; high familial rates of mood disorder; and response to mood stabilizers and antidepressants (McElroy et al., 1996).
Impulse control disorders have been reported in Tourette syndrome (Jankovic and Kurlan, 2011), restless leg syndrome (Cornelius et al., 2010) and Perry syndrome (Mishima et al., 2015). Impulse control disorders have also been studied in university students. In this subpopulation, the prevalence is estimated to be around 10% (Odlaug and Grant, 2010) and are associated with stress (Leppink et al., 2016b) and depression (Leppink et al., 2016a). Among elderly people, the prevalence is estimated to be around 17% and ICDs are associated with childhood conduct disorder and alcohol/substance abuse (Odlaug and Grant, 2010).
Impulse control disorders in Parkinson’s disease
Since the first reports of impulse control disorders in Parkinson’s disease in the early 2000s, impulse control disorders have been increasingly recognized. Given their potential impact on life functioning, including activities of daily living, interpersonal relationships, and social-occupational functioning, clinicians growingly pay specific attention to these impulsive behaviors (Weintraub and Claassen, 2017). ICDs are actually not symptoms of Parkinson’s disease itself, but adverse effects of dopamine replacement therapy (de la Riva et al., 2014). ICDs have been broadly studied in PD, from prevalence to assessment to comorbidities.
Epidemiology
One of the earliest case reports dates back to 2003, which identified nine patients (0.5% of the sample) with pathological gambling (Driver-Dunckley et al., 2003). In 2010, the DOMINION study aimed at evaluating the point prevalence estimates of the four main ICDs among 3090 medicated PD patients in the United States and Canada (Weintraub et al., 2010a). One or more ICDs were identified in 13.6% of patients (compulsive buying in 5.7%, gambling in 5.0%, binge-eating disorder in 4.3%, and compulsive sex-ual behavior in 3.5%), with 3.9% of participants having two or more ICDs. A more recent longitudinal analysis of ICDs in a French research cohort estimated the 5-year cumulative incidence to be about 46% (Corvol et al., 2018).
As for any psychiatric disorder, environmental factors may influence the presence of ICDs in PD. In particular, cultural factors seem to impact the prevalence of specific ICDs. Studies in Turkey and India reported very low prevalences for pathological gam-bling (Kenangil et al., 2010; Sarathchandran et al., 2013), while this ICD has one of the highest prevalence in most Western studies (Baig et al., 2019; Garcia-Ruiz et al., 2014; Hurt et al., 2014; Weintraub et al., 2010a). Gambling is illegal in Turkey and heavily restricted in India, whereas it is legal in Western countries, and an important part of the American culture. Various studies lack uniformity to assess ICDs, and the definition itself of ICDs is subject to cultural differences (Weintraub and Claassen, 2017).
Assessment and diagnosis
As impulse control disorders have been increasingly recognized in Parkinson’s disease, several screening tools and rating scales have been developed and used to assess and diagnose them. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Dis-ease Rating Scale (MDS-UPDRS) has an item entitled Features of dopamine dysregu-lation syndrome in the part assessing non-motor aspects of experiences of daily living (Goetz et al., 2008). This single item encompasses impulse control disorders, dopamine dysregulation syndrome, punding, and hobbyism.
The Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease (QUIP) was developed as a screening instrument for ICDs and related behaviors and is struc-tured to be consistent with diagnostic criteria or defining clinical characteristics as de-scribed in the Diagnostic and Statistical Manual of Mental Disorders (Weintraub et al., 2009). Its three sections focus on (i) the four most common ICDs, (ii) punding and hobbyism, and (iii) compulsive medication use. The Rating Scale version of the QUIP (QUIP-RS) was derived from the QUIP to measure the severity of ICDs (Weintraub et al., 2012). Each item is rated on a 5-point Likert scale and assesses the frequency of the symptoms with a range of scores from 0 (never) to 4 (very often). The sections are similar than the ones in the QUIP, although a slight difference is that punding and hobbyism have been grouped together (Evans et al., 2019). This scale has been validated in several countries (Choi et al., 2020; Marques et al., 2019; Probst et al., 2014).
The Ardouin Scale of Behavior in Parkinson’s Disease consists of eighteen items addressing non-motor symptoms, grouped in four parts: general psychological evalua-tion, apathy, non-motor fluctuations and hyperdopaminergic behaviors (Ardouin et al., 2009).
The Scale for Outcomes in Parkinson’s Disease – Psychiatric Complications is a screening and severity scale that consists of a 7-item questionnaire (Visser et al., 2007). Two items are related to impulsive control disorders: one item for compulsive shopping and pathological gambling, and another one for hypersexuality. Each item score range from 0 (no symptoms) to 3 (severe symptoms) (Evans et al., 2019).
The Minnesota Impulsive Disorders Interview was originally developed in 2008 for the diagnosis of compulsive buying, trichotillomania, kleptomania, pyromania, intermit-tent explosive disorder, pathological gambling, and compulsive sexual behavior (Cham-berlain and Grant, 2018; Grant, 2008). The original version was revised to match the changes made in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (Chamberlain and Grant, 2018).
Parkinson’s Progressive Markers Initiative
In the field of Parkinson’s disease therapeutics, the ultimate goal is to develop disease-modifying treatments that slow, prevent or even reverse the underlying disease process. Validated biomarkers of disease progression would dramatically accelerate PD thera-peutics research. However, current progression biomarkers are not optimal and are not fully validated.
The Parkinson’s Progression Markers Initiative (www.ppmi-info.org) is a landmark observational clinical study to comprehensively evaluate cohorts of significant interest using advanced imaging, biologic sampling and clinical and behavioral assessments to identify biomarkers of Parkinson’s disease progression. PPMI is taking place at clinical sites in the United States, Europe, Israel, and Australia (see Table 1.2 for the full list of clinical sites).
Data and samples acquired from study participants enable the development of a comprehensive Parkinson’s database and biorepository, which is currently available to the scientific community to conduct field-changing research. PPMI follows standardized data acquisition protocols to ensure that tests and assessments conducted at multiple sites and across multiple cohorts can be pooled in centralized databases and repositories. The clinical, imaging and biologic data is easily accessible to researchers in real time through their website.
Drug Interaction With Genes in Parkinson’s Disease
The Drug Interaction With Genes in Parkinson’s Disease study is a longitudinal cohort study of patients with PD consecutively recruited from May 2009 to July 2013 in 4 French university hospitals and 4 general hospitals (Corvol et al., 2018). Eligible pa-tients were patients with PD (UK Parkinson’s Disease Society Brain Bank criteria) with disease duration shorter than 5 years at recruitment. After the baseline visit, annual clinical evaluations were performed over 5 years by movement disorders specialists who checked whether patients still fulfilled UK Parkinson’s Disease Society Brain Bank cri-teria at each visit and filled out standardized questionnaires. All patients had a blood sampling for DNA extraction and genome-wide genotyping. The study was conducted according to Good Clinical Practice Guidelines, and sponsored by Assistance Publique Hôpitaux de Paris. All patients provided informed consent, and the study was approved by local ethical committee and regulation authorities.
Table of contents :
Abstract
Résumé
Remerciements
Scientific production
List of Figures
List of Tables
List of Abbreviations
Introduction
1 Background
1.1 Parkinson’s disease
1.1.1 History
1.1.2 Classification
1.1.3 Pathophysiology
1.1.4 Diagnosis
1.1.5 Symptoms
1.1.6 Medications and their limitations
1.1.7 Motor complications
1.2 Impulse control disorders
1.2.1 Definition of specific impulse control disorders
1.2.2 Studies on impulse control disorders in subpopulations
1.3 Impulse control disorders in Parkinson’s disease
1.3.1 Epidemiology
1.3.2 Assessment and diagnosis
1.3.3 Associations
1.3.4 Prediction
1.3.5 Other behavioral addictions
1.4 Machine learning
1.4.1 Notations
1.4.2 Algorithms
1.4.3 Regularization
1.4.4 Metrics
1.5 Putting it all together
1.6 Materials
1.6.1 Data sets
1.6.2 Software
2 Prediction of impulse control disorders in Parkinson’s disease
2.1 Introduction
2.2 Materials and methods
2.2.1 Populations
2.2.2 Participants and clinical measurements
2.2.3 Genetic variants
2.2.4 Data processing
2.2.5 Machine learning algorithms
2.2.6 Cross-validation
2.2.7 Statistical analysis
2.3 Results
2.3.1 Population characteristics
2.3.2 Predictive performance
2.3.3 Contribution of the different features
2.4 Discussion
3 Exploratory analysis of the genetics of impulse control disorders in Parkinson’s disease using genetic risk scores
3.1 Introduction
3.2 Materials and methods
3.2.1 Populations
3.2.2 Participants
3.2.3 Genetic ancestry
3.2.4 Genotyping and quality control
3.2.5 Phenotypes and genome-wide association studies
3.2.6 Computation of genetic risk scores
3.2.7 Statistical analyses
3.3 Results
3.3.1 Participants and genetic variants
3.3.2 Genome-wide association studies
3.3.3 Association analyses
3.4 Discussion
4 Combining static and dynamic data in recurrent neural networks
4.1 Introduction
4.2 Related work
4.3 Proposed approach
4.4 Experiments
4.5 Conclusion
Conclusion
A Supplementary materials for the prediction of impulse control disorders from clinical and genetic data with replication in an independent cohort
A.1 Reduction approaches
A.2 Supplementary Tables
