We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.

/pdf/heritability-enrichment-of-specifically-expressed-genes-322z5ealai.pdf

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types.

For over a century, psychiatric disorders have been defined by expert opinion and clinical observation. The modern DSM has relied on a consensus of experts to define categorical syndromes based on clusters of symptoms and signs, and, to some extent, external validators, such as longitudinal course and response to treatment. In the absence of an established etiology, psychiatry has struggled to validate these descriptive syndromes, and to define the boundaries between disorders and between normal and pathologic variation. Recent advances in genomic research, coupled with large-scale collaborative efforts like the Psychiatric Genomics Consortium, have identified hundreds of common and rare genetic variations that contribute to a range of neuropsychiatric disorders. At the same time, they have begun to address deeper questions about the structure and classification of mental disorders: To what extent do genetic findings support or challenge our clinical nosology? Are there genetic boundaries between psychiatric and neurologic illness? Do the data support a boundary between disorder and normal variation? Is it possible to envision a nosology based on genetically informed disease mechanisms? This review provides an overview of conceptual issues and genetic findings that bear on the relationships among and boundaries between psychiatric disorders and other conditions. We highlight implications for the evolving classification of psychopathology and the challenges for clinical translation.

/pdf/psychiatric-genetics-and-the-structure-of-psychopathology-2luxsxrmpt.pdf

Psychiatric genetics and the structure of psychopathology.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of school-age children and 25% of adults Common genetic variants contribute substantially to ADHD susceptibility, but no individual variants have been robustly associated with ADHD We report a genome-wide association meta-analysis of 20,183 ADHD cases and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, revealing new and important information on the underlying biology of ADHD Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes, as well as around brain-expressed regulatory marks These findings, based on clinical interviews and/or medical records are supported by additional analyses of a self-reported ADHD sample and a study of quantitative measures of ADHD symptoms in the population Meta-analyzing these data with our primary scan yielded a total of 16 genome-wide significant loci The results support the hypothesis that clinical diagnosis of ADHD is an extreme expression of one or more continuous heritable traits

https://www.biorxiv.org/content/biorxiv/early/2017/06/03/145581.full.pdf

Discovery Of The First Genome-Wide Significant Risk Loci For ADHD

Gilles de la Tourette syndrome (GTS) is a childhood-onset neurodevelopmental disorder that is characterized by several motor and phonic tics. Tics usually develop before 10 years of age, exhibit a waxing and waning course and typically improve with increasing age. A prevalence of approximately 1% is estimated in children and adolescents. The condition can result in considerable social stigma and poor quality of life, especially when tics are severe (for example, with coprolalia (swearing tics) and self-injurious behaviours) or when GTS is accompanied by attention-deficit/hyperactivity disorder, obsessive-compulsive disorder or another neuropsychiatric disorder. The aetiology is complex and multifactorial. GTS is considered to be polygenic, involving multiple common risk variants combined with rare, inherited or de novo mutations. These as well as non-genetic factors (such as perinatal events and immunological factors) are likely to contribute to the heterogeneity of the clinical phenotype, the structural and functional brain anomalies and the neural circuitry involvement. Management usually includes psychoeducation and reassurance, behavioural methods, pharmacotherapy and, rarely, functional neurosurgery. Future research that integrates clinical and neurobiological data, including neuroimaging and genetics, is expected to reveal the pathogenesis of GTS at the neural circuit level, which may lead to targeted interventions.

Gilles de la Tourette syndrome

https://orbilu.uni.lu/bitstream/10993/36985/1/Fineberg_EN_2018.pdf

Manifesto for a European research network into Problematic Usage of the Internet.

Disorders of the brain exhibit considerable epidemiological comorbidity and frequently share symptoms, provoking debate about the extent of their etiologic overlap. Here we apply linkage disequilibrium score regression (LDSC) to quantify the extent of shared genetic contributions across 23 brain disorders (n=842,820), 11 quantitative and four dichotomous traits of interest (n=722,125) based on genome-wide association meta-analyses. Psychiatric disorders show substantial sharing of common variant risk, while many neurological disorders appear more distinct from one another, suggesting substantive differences in the specificity of the genetic etiology of these disorders. Further, we observe little evidence of widespread sharing of the common genetic risk between neurological and psychiatric disorders studied. In addition, we identify significant sharing of genetic influences between the certain quantitative measures and brain disorders, including major depressive disorder and neuroticism personality score. These results highlight the importance of common genetic variation as a source of risk for brain disorders and the potential of using heritability methods to obtain a more comprehensive view of the genetic architecture of brain phenotypes.

/pdf/analysis-of-shared-heritability-in-common-disorders-of-the-52z9pd001r.pdf

Ocd

Papers

Analysis of shared heritability in common disorders of the brain