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Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r g ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r gs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors., (© 2020 Society for the Study of Addiction.)

Cigarette smoking is a severe health burden being related to a number of chronic diseases. Frequently, smokers report about sleep problems. Sleep disturbance, in turn, has been demonstrated to be involved in the pathophysiology of several disorders related to smoking and may be relevant for the pathophysiology of nicotine dependence. Therefore, determining the frequency of sleep disturbance in otherwise healthy smokers and its association with degree of nicotine dependence is highly relevant. In a population-based case-control study, 1071 smokers and 1243 non-smokers without lifetime Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Axis I disorder were investigated. Sleep quality (SQ) of participants was determined by the Pittsburgh Sleep Quality Index. As possible confounders, age, sex and level of education and income, as well as depressiveness, anxiety, attention deficit hyperactivity, alcohol drinking behaviour and perceived stress, were included into multiple regression analyses. Significantly more smokers than non-smokers (28.1% versus 19.1%; P < 0.0001) demonstrated a disturbed global SQ. After controlling for the confounders, impaired scores in the component scores of sleep latency, sleep duration and global SQ were found significantly more often in smokers than non-smokers. Consistently, higher degrees of nicotine dependence and intensity of smoking were associated with shorter sleep duration. This study demonstrates for the first time an elevated prevalence of sleep disturbance in smokers compared with non-smokers in a population without lifetime history of psychiatric disorders even after controlling for potentially relevant risk factors. It appears likely that smoking is a behaviourally modifiable risk factor for the occurrence of impaired SQ and short sleep duration., (© 2012 The Authors, Addiction Biology © 2012 Society for the Study of Addiction.)

The aim of the present study was to examine neurocognitive function associated with chronic nicotine use. A total of 2163 healthy participants (1002 smokers, 1161 never-smoking controls) participated in a population-based case-control design. The main outcome measures were six cognitive domain factors derived from a neuropsychological test battery. In smokers, the battery was administered after controlled smoking of one cigarette. Analyses included age, sex and education as covariates. Results demonstrated small, but significant deficits in smokers for visual attention (P<0.001) and cognitive impulsivity (P<0.006), while verbal episodic memory, verbal fluency, verbal working memory, and Stroop-interference did not differ between groups. These attention/impulsivity deficits were also present in smokers with only a low amount of cigarette consumption. Lifetime nicotine use (pack-years) was not correlated with cognition in smokers. In conclusion, this study confirmed subtle and specific cognitive deficits in non-deprived smokers. The independence of these deficits from consumption intensity may argue for an a priori deficit of some cognitive abilities in smokers. These specific deficits may constitute intermediate phenotypes for genetic research on nicotine use., (© 2012 The Authors, Addiction Biology © 2012 Society for the Study of Addiction.)

Alcohol dependence (AD) is an important contributory factor to the global burden of disease. The etiology of AD involves both environmental and genetic factors, and the disorder has a heritability of around 50%. The aim of the present study was to identify susceptibility genes for AD by performing a genome-wide association study (GWAS). The sample comprised 1333 male in-patients with severe AD according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, and 2168 controls. These included 487 patients and 1358 controls from a previous GWAS study by our group. All individuals were of German descent. Single-marker tests and a polygenic score-based analysis to assess the combined contribution of multiple markers with small effects were performed. The single nucleotide polymorphism (SNP) rs1789891, which is located between the ADH1B and ADH1C genes, achieved genome-wide significance [P = 1.27E-8, odds ratio (OR) = 1.46]. Other markers from this region were also associated with AD, and conditional analyses indicated that these made a partially independent contribution. The SNP rs1789891 is in complete linkage disequilibrium with the functional Arg272Gln variant (P = 1.24E-7, OR = 1.31) of the ADH1C gene, which has been reported to modify the rate of ethanol oxidation to acetaldehyde in vitro. A polygenic score-based approach produced a significant result (P = 9.66E-9). This is the first GWAS of AD to provide genome-wide significant support for the role of the ADH gene cluster and to suggest a polygenic component to the etiology of AD. The latter result may indicate that many more AD susceptibility genes still await identification., (© 2011 The Authors, Addiction Biology © 2011 Society for the Study of Addiction.)

Tobacco smoking is a major risk factor for most of the diseases leading in mortality. Nicotine dependence (ND), which sustains regular smoking, is now acknowledged to be under substantial genetic control with some environmental contribution. At present, however, genetic studies on ND are mostly conducted in populations that have been poorly characterized with regard to ND-related phenotypes for the simple reason that the respective populations were not primarily collected to study ND. The German multi-centre study 'Genetics of Nicotine Dependence and Neurobiological Phenotypes', which is funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) as part of the Priority Program (Schwerpunktprogramm) SPP1226: 'Nicotine-Molecular and Physiological Effects in CNS', was intended to overcome some of these inherent problems of current genetic studies of ND. The multi-centre study is a population-based case-control study of smokers and never-smokers (n = 2396). The study was unique worldwide because it was the first large-scale genetic study specifically addressing ND with the collection of a wide range of environmental, psychosocial and neurobiological phenotypes. Study design and major population characteristics with emphasis on risk prediction of smoking status were presented in this paper., (© 2011 The Authors, Addiction Biology © 2011 Society for the Study of Addiction.)

P50 gating is a major functional biomarker in research on schizophrenia and other psychiatric conditions with high smoking prevalence. It is used as endophenotype for studying nicotinic systems genetics and as surrogate endpoint measure for drug development of nicotinic agonists. Surprisingly, little is known about P50 gating in the general population and the relationship to smoking-related characteristics. In this multicenter study at six academic institutions throughout Germany, n=907 never-smokers (NS<20 cigarettes/lifetime), n=463 light smokers (LS) with Fagerström Test for Nicotine Dependence (FTND)≥4 and n=353 heavy smokers (HS, FTND<4) were randomly selected from the general population. As part of a standardized protocol for investigating the genetics of nicotine dependence (ND), an auditory P50 paradigm was applied. The main outcome measure was P50-amplitude difference followed by time-frequency analyses and functional imaging (sLORETA). Reduced P50 gating was found in HS compared to NS with LS taking an intermediate position-correlating with the degree of ND. sLORETA and time-frequency analyses indicate that high-frequency oscillations in frontal brain regions are particularly affected. With growing age, P50 gating increased in (heavy) smokers. This is the first large-scale study (normative sample data) on P50 sensory gating and smoking in the general population. Diminished gating of P50 and associated high-frequency oscillations in the frontal brain region are indications of a deficient inhibitory cortical function in nicotine-dependent smokers. The suitability and application of sensory P50 gating as functional biomarker with regard to genetic and pharmacological studies is discussed., (© 2011 The Authors, Addiction Biology © 2011 Society for the Study of Addiction.)