The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

/pdf/integrative-analysis-of-111-reference-human-epigenomes-4bavnjaon6.pdf

Integrative analysis of 111 reference human epigenomes

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

/pdf/ld-score-regression-distinguishes-confounding-from-58i9nc2cv7.pdf

LD score regression distinguishes confounding from polygenicity in genome-wide association studies :

Genetics and analysis of quantitative traits

http://news.medlive.cn/uploadfile/20130709/13733376781389.pdf

Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis

Die Aufmerksamkeitsdefizit-/Hyperaktivitatsstorung (ADHS) ist ein Storungsbild mit Beginn im fruhen Kindesalter, welches seit dem 19. Jahrhundert in der Psychiatrie beschrieben wurde. Etwa 5% aller Kinder und Jugendlichen sind weltweit betroffen.

Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung und Sozialverhaltensstörungen

[Reports. The psychopharmacological off-label prescribing in the treatment of children and adolescents with psychiatric disorders].

Running title: Adversity, morphology and anxiety

Tics treten uber alle Altersgruppen hinweg mit einer Pravalenz von ca. 1% auf. Tics sind unwillkurliche rasche, einschiesende motorische Bewegungen oder vokale Lautauserungen. Es werden hierbei einfache Formen von komplexen Tics unterschieden. Bei gleichzeitigem Auftreten motorischer und vokaler Tics spricht man vom Tourette-Syndrom. Ausgepragte Tics konnen die subjektive Befindlichkeit und soziale Integrationsfahigkeit nachhaltig einschranken, obgleich in vielen Fallen keine Behandlungsbedurftigkeit besteht. Sie beginnen definitionsgemas vor dem 18. Lebensjahr und haben eine hohe Tendenz zur Remission. Neben verhaltenstherapeutischen Masnahmen ist die Pharmakotherapie bei hohem Schweregrad, starker psychosozialer Belastung und unzureichender Krankheitsbewaltigung indiziert. Komplexe Tics sind bisweilen schwer von Zwangssymptomen abzugrenzen, zumal in etwa 30% der Falle beide Storungsbilder komorbid auftreten. Tics treten weiterhin haufig komorbid mit hyperkinetische Storungen sowie emotionalen Storungen auf.

Ticstörungen und Zwangsstörungen

Reward-based learning and decision-making are prime candidates to understand symptoms of attention deficit hyperactivity disorder (ADHD). However, only limited evidence is available regarding the neurocomputational underpinnings of the alterations seen in ADHD. This particularly concerns the flexible behavioral adaption in dynamically changing environments, which is challenging for individuals with ADHD. One previous study points to elevated choice switching in adolescent ADHD, which was accompanied by disrupted learning signals in medial prefrontal cortex. In the present study, we investigated young adults with ADHD (n=17, 18-32 years) and age and sex matched controls (n=17, 18-30 years) using a probabilistic reversal learning experiment during functional magnetic resonance imaging (fMRI). The task requires continuous learning to guide flexible behavioral adaptation to changing reward contingencies. To disentangle the neurocomputational underpinnings of the behavioral data, we used detailed reinforcement learning (RL) models, which informed the analysis of fMRI data. ADHD patients performed worse than controls particularly in trials before reversals, i.e., when reward contingencies were stable. This pattern resulted from "noisy" choice switching regardless of previous feedback. RL modelling showed decreased reinforcement sensitivity and enhanced learning rates for negative feedback in ADHD patients. At the neural level, this was reflected in diminished representation of choice probability in the left posterior parietal cortex in ADHD. Moreover, modelling showed a marginal reduction of learning about the unchosen option, which was paralleled by an equally marginal reduction in learning signals incorporating the unchosen option in the left ventral striatum. Taken together, we show that flexible behavioral adaptation in the context of dynamically changing reward contingencies is impaired in ADHD. This is due to excessive choice switching ("hyper-flexibility"), which can be detrimental or beneficial depending on the learning environment. Computationally, this results from blunted sensitivity to reinforcement. We detected neural correlates of this blunted sensitivity to reinforcement in the attention-control network, specifically in the parietal cortex. These neurocomputational findings are promising but remain preliminary due to the relatively small sample size.

/pdf/impaired-flexible-reward-learning-is-associated-with-blunted-3orq29d2.pdf

Impaired flexible reward learning is associated with blunted reinforcement sensitivity and attenuated learning and choice signals in ventral striatum and parietal cortex of ADHD patients

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