Comorbidity, family history and personality traits in pathological gamblers compared with healthy controls.

BACKGROUND: While DSM-5 classified pathological gambling as an addictive disorder, there is debate as to whether ICD-11 should follow suit. The debate hinges on scientific evidence such as neurobiological findings, family history of psychiatric disorders, psychiatric comorbidity, and personality variables. METHODS: In the "Baden-Württemberg Study of Pathological Gambling", we compared a group of 515 male pathological gamblers receiving treatment with 269 matched healthy controls. We studied differences in sociodemographic characteristics, gambling-related variables, psychiatric comorbidity (lifetime), family history of psychiatric conditions, as well as personality traits such as impulsivity (Barratt Impulsiveness Scale), sensation seeking (Zuckerman's Sensation Seeking Scale) and the NEO-FFI big five. Personality traits were validated in an age- and ethnicity-matched subsample of "pure" gamblers without any psychiatric comorbidity (including nicotine dependence). Data were analyzed using two-sample t-tests, Chi2 analyses, Fisher's exact test and Pearson correlation analysis, as appropriate. Bonferroni correction was applied to correct for multiple comparisons. RESULTS: Only 1% of the gamblers had been diagnosed with an impulse control disorder other than gambling (ICD-10). Notably, 88% of the gamblers in our sample had a comorbid diagnosis of substance dependence. The highest axis I comorbidity rate was for nicotine dependence (80%), followed by alcohol dependence (28%). Early age of first gambling experience was correlated with gambling severity. Compared to first-degree relatives of controls, first-degree relatives of pathological gamblers were more likely to suffer from alcohol dependence (27.0% vs. 7.4%), pathological gambling (8.3% vs. 0.7%) and suicide attempts (2.7% vs. 0.4%). Significant group differences were observed for the NEO-FFI factors neuroticism, agreeableness and conscientiousness. Gamblers were also more impulsive than controls, but did not differ from controls in terms of sensation seeking. CONCLUSIONS: Our findings support classifying pathological gambling as a behavioural addiction in the ICD-11. This decision will have a significant impact on the approaches available for prevention (e.g. age limits) and treatment.

Neurobiological correlates of internet gaming disorder: Similarities to pathological gambling.

The number of massively multiplayer online games (MMOs) is on the rise worldwide along with the fascination that they inspire. Problems occur when the use of MMOs becomes excessive at the expense of other life domains. Although not yet formally included as disorder in common diagnostic systems, internet gaming disorder (IGD) is considered a "condition for further study" in section III of the DSM-5. The current review aims to provide an overview of cognitive and neurobiological data currently available on IGD, with a particular focus on impulsivity, compulsivity, and sensitivity to reward and punishment. Additionally, we also compare these findings on IGD with data from studies on pathological gambling (PG)-so far the only condition officially classified as a behavioral addiction in the DSM-5. Multiple similarities have been observed in the neurobiology of IGD and PG, as measured by alterations in brain function and behavior. Both patients with IGD and those with PG exhibited decreased loss sensitivity; enhanced reactivity to gaming and gambling cues, respectively; enhanced impulsive choice behavior; aberrant reward-based learning; and no changes in cognitive flexibility. In conclusion, the evidence base on the neurobiology of gaming and gambling disorders is beginning to illuminate the similarities between the two. However, as only a few studies have addressed the neurobiological basis of IGD, and some of these studies suffer from significant limitations, more research is required before IGD's inclusion as a second behavioral addiction in the next versions of the ICD and DSM can be justified.

Genome-wide association study of pathological gambling.

BACKGROUND: Pathological gambling is a behavioural addiction with negative economic, social, and psychological consequences. Identification of contributing genes and pathways may improve understanding of aetiology and facilitate therapy and prevention. Here, we report the first genome-wide association study of pathological gambling. Our aims were to identify pathways involved in pathological gambling, and examine whether there is a genetic overlap between pathological gambling and alcohol dependence. METHODS: Four hundred and forty-five individuals with a diagnosis of pathological gambling according to the Diagnostic and Statistical Manual of Mental Disorders were recruited in Germany, and 986 controls were drawn from a German general population sample. A genome-wide association study of pathological gambling comprising single marker, gene-based, and pathway analyses, was performed. Polygenic risk scores were generated using data from a German genome-wide association study of alcohol dependence. RESULTS: No genome-wide significant association with pathological gambling was found for single markers or genes. Pathways for Huntington's disease (P-value=6.63×10(-3)); 5'-adenosine monophosphate-activated protein kinase signalling (P-value=9.57×10(-3)); and apoptosis (P-value=1.75×10(-2)) were significant. Polygenic risk score analysis of the alcohol dependence dataset yielded a one-sided nominal significant P-value in subjects with pathological gambling, irrespective of comorbid alcohol dependence status. CONCLUSIONS: The present results accord with previous quantitative formal genetic studies which showed genetic overlap between non-substance- and substance-related addictions. Furthermore, pathway analysis suggests shared pathology between Huntington's disease and pathological gambling. This finding is consistent with previous imaging studies.

A comparison of region-of-interest measures for extracting whole brain data using survival analysis in alcoholism as an example.

BACKGROUND: Aggregation of functional magnetic resonance imaging (fMRI) data in regions-of-interest (ROIs) is required for complex statistical analyses not implemented in standard fMRI software. Different data-aggregation measures assess various aspects of neural activation, including spatial extent and intensity. NEW METHOD: In this study, conducted within the framework of the PREDICT study, we compared different aggregation measures for voxel-wise fMRI activations to be used as prognostic factors for relapse in 49 abstinent alcohol-dependent individuals in an outpatient setting using a cue-reactivity task. We compared the importance of the data-aggregation measures as prognostic factors for treatment outcomes by calculating the proportion of explained variation. RESULTS AND COMPARISON WITH EXISTING METHOD(S): Relapse risk was associated with cue-induced brain activation during abstinence in the ventral striatum (VS) and in the orbitofrontal cortex (OFC). While various ROI measures proved appropriate for using fMRI cue-reactivity to predict relapse, on the descriptive level the most "important" prognostic factor was a measure defined as the sum of t-values exceeding an individually defined threshold. Data collected in the VS was superior to that from other regions. CONCLUSIONS: In conclusion, it seems that fMRI cue-reactivity, especially in the VS, can be used as prognostic factor for relapse in abstinent alcohol-dependent patients. Our findings suggest that data-aggregation measures that take both spatial extent and intensity of cue-induced brain activation into account make better biomarkers for predicting relapse than measures that consider an activation's spatial extent or intensity alone.

Single nucleotide polymorphism in the neuroplastin locus associates with cortical thickness and intellectual ability in adolescents.

Despite the recognition that cortical thickness is heritable and correlates with intellectual ability in children and adolescents, the genes contributing to individual differences in these traits remain unknown. We conducted a large-scale association study in 1583 adolescents to identify genes affecting cortical thickness. Single-nucleotide polymorphisms (SNPs; n=54,837) within genes whose expression changed between stages of growth and differentiation of a human neural stem cell line were selected for association analyses with average cortical thickness. We identified a variant, rs7171755, associating with thinner cortex in the left hemisphere (P=1.12 × 10(-)(7)), particularly in the frontal and temporal lobes. Localized effects of this SNP on cortical thickness differently affected verbal and nonverbal intellectual abilities. The rs7171755 polymorphism acted in cis to affect expression in the human brain of the synaptic cell adhesion glycoprotein-encoding gene NPTN. We also found that cortical thickness and NPTN expression were on average higher in the right hemisphere, suggesting that asymmetric NPTN expression may render the left hemisphere more sensitive to the effects of NPTN mutations, accounting for the lateralized effect of rs7171755 found in our study. Altogether, our findings support a potential role for regional synaptic dysfunctions in forms of intellectual deficits.

Genomic architecture of human neuroanatomical diversity.

Human brain anatomy is strikingly diverse and highly inheritable: genetic factors may explain up to 80% of its variability. Prior studies have tried to detect genetic variants with a large effect on neuroanatomical diversity, but those currently identified account for <5% of the variance. Here, based on our analyses of neuroimaging and whole-genome genotyping data from 1765 subjects, we show that up to 54% of this heritability is captured by large numbers of single-nucleotide polymorphisms of small-effect spread throughout the genome, especially within genes and close regulatory regions. The genetic bases of neuroanatomical diversity appear to be relatively independent of those of body size (height), but shared with those of verbal intelligence scores. The study of this genomic architecture should help us better understand brain evolution and disease.

[Neurobiology of behavioral addictions]. / Neurobiologische Grundlagen der Verhaltenssüchte.

Reward learning represents a crucial mechanism in the acquisition and maintenance of addictive behavior. The underlying neurobiological foundations and associated neurobiological pathways are identified in this review and similarities between substance abuse and behavioral addictions will be discussed. In the second section current neuroimaging findings on neurobiological mechanisms of pathological gambling and computer and internet addiction are discussed. The main focuses are on changes in neurocognitive processes, such as cue reactivity, reward and punishment processing and behavioral control.

[The concept of behavioral addiction and limits of the term addiction]. / Konzept der Verhaltenssüchte und Grenzen des Suchtbegriffs.

The numbers of persons with a prevalence for behavioral addiction are rising especially among the young. Psychiatrists and psychotherapists are still awaiting indications for diagnostic classification and treatment approaches. We discuss the nosological aspects and suggest categorizing gambling and excessive computer and internet use as behavioral addictions. In specific cases the addiction model can also be applied for excessive sexual behavior, compulsive buying and obesity.