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Substance use disorders (SUDs) are seen as a continuum ranging from goal-directed and hedonic drug use to loss of control over drug intake with aversive consequences for mental and physical health and social functioning. The main goals of our interdisciplinary German collaborative research centre on Losing and Regaining Control over Drug Intake (ReCoDe) are (i) to study triggers (drug cues, stressors, drug priming) and modifying factors (age, gender, physical activity, cognitive functions, childhood adversity, social factors, such as loneliness and social contact/interaction) that longitudinally modulate the trajectories of losing and regaining control over drug consumption under real-life conditions. (ii) To study underlying behavioural, cognitive and neurobiological mechanisms of disease trajectories and drug-related behaviours and (iii) to provide non-invasive mechanism-based interventions. These goals are achieved by: (A) using innovative mHealth (mobile health) tools to longitudinally monitor the effects of triggers and modifying factors on drug consumption patterns in real life in a cohort of 900 patients with alcohol use disorder. This approach will be complemented by animal models of addiction with 24/7 automated behavioural monitoring across an entire disease trajectory; i.e. from a naïve state to a drug-taking state to an addiction or resilience-like state. (B) The identification and, if applicable, computational modelling of key molecular, neurobiological and psychological mechanisms (e.g., reduced cognitive flexibility) mediating the effects of such triggers and modifying factors on disease trajectories. (C) Developing and testing non-invasive interventions (e.g., Just-In-Time-Adaptive-Interventions (JITAIs), various non-invasive brain stimulations (NIBS), individualized physical activity) that specifically target the underlying mechanisms for regaining control over drug intake. Here, we will report on the most important results of the first funding period and outline our future research strategy., (© 2024 The Author(s). Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Panic disorder (PD) has a lifetime prevalence of 2-4% and heritability estimates of 40%. The contributory genetic variants remain largely unknown, with few and inconsistent loci having been reported. The present report describes the largest genome-wide association study (GWAS) of PD to date comprising genome-wide genotype data of 2248 clinically well-characterized PD patients and 7992 ethnically matched controls. The samples originated from four European countries (Denmark, Estonia, Germany, and Sweden). Standard GWAS quality control procedures were conducted on each individual dataset, and imputation was performed using the 1000 Genomes Project reference panel. A meta-analysis was then performed using the Ricopili pipeline. No genome-wide significant locus was identified. Leave-one-out analyses generated highly significant polygenic risk scores (PRS) (explained variance of up to 2.6%). Linkage disequilibrium (LD) score regression analysis of the GWAS data showed that the estimated heritability for PD was 28.0-34.2%. After correction for multiple testing, a significant genetic correlation was found between PD and major depressive disorder, depressive symptoms, and neuroticism. A total of 255 single-nucleotide polymorphisms (SNPs) with p < 1 × 10 -4 were followed up in an independent sample of 2408 PD patients and 228,470 controls from Denmark, Iceland and the Netherlands. In the combined analysis, SNP rs144783209 showed the strongest association with PD (pcomb = 3.10  × 10 -7 ). Sign tests revealed a significant enrichment of SNPs with a discovery p-value of <0.0001 in the combined follow up cohort (p = 0.048). The present integrative analysis represents a major step towards the elucidation of the genetic susceptibility to PD., (© 2019. The Author(s), under exclusive licence to Springer Nature Limited.)

Context: The efficacy of antidepressant drug treatment in depression is unsatisfactory; 1 in 3 patients does not fully recover even after several treatment trials. Genetic factors and clinical characteristics contribute to the failure of a favorable treatment outcome., Objective: To identify genetic and clinical determinants of antidepressant drug treatment outcome in depression., Design: Genomewide pharmacogenetic association study with 2 independent replication samples., Setting: We performed a genomewide association study in patients from the Munich Antidepressant Response Signature (MARS) project and in pooled DNA from an independent German replication sample. A set of 328 single-nucleotide polymorphisms highly related to outcome in both genomewide association studies was genotyped in a sample of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study., Participants: A total of 339 inpatients with a depressive episode (MARS sample), a further 361 inpatients with depression (German replication sample), and 832 outpatients with major depression (STAR*D sample)., Main Outcome Measures: We generated a multilocus genetic variable that described the individual number of alleles of the selected single nucleotide polymorphisms associated with beneficial treatment outcome in the MARS sample ("response" alleles) to evaluate additive genetic effects on antidepressant drug treatment outcome., Results: Multilocus analysis revealed a significant contribution of a binary variable that categorized patients as carriers of a high vs low number of response alleles in the prediction of antidepressant drug treatment outcome in both samples (MARS and STAR*D). In addition, we observed that patients with a comorbid anxiety disorder combined with a low number of response alleles showed the least favorable outcome., Conclusion: These results demonstrate the importance of multiple genetic factors combined with clinical features in the prediction of antidepressant drug treatment outcome, which underscores the multifactorial nature of this trait.

We identified association of restless legs syndrome (RLS) with PTPRD at 9p23-24 in 2,458 affected individuals and 4,749 controls from Germany, Austria, Czechia and Canada. Two independent SNPs in the 5' UTR of splice variants expressed predominantly in the central nervous system showed highly significant P values (rs4626664, P(nominal/lambda corrected) = 5.91 x 10(-10), odds ratio (OR) = 1.44; rs1975197, P(nominal/lambda corrected) = 5.81 x 10(-9), OR = 1.31). This work identifies PTPRD as the fourth genome-wide significant locus for RLS.