0000000000222676
AUTHOR
Elisabeth B. Binder
Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation
Genome-wide study in Germans identifies four novel multiple sclerosis risk genes and confirms already known gene loci.
Formin 2 links neuropsychiatric phenotypes at young age to an increased risk for dementia
Age-associated memory decline is due to variable combinations of genetic and environmental risk factors. How these risk factors interact to drive disease onset is currently unknown. Here we begin to elucidate the mechanisms by which post-traumatic stress disorder (PTSD) at a young age contributes to an increased risk to develop dementia at old age. We show that the actin nucleator Formin 2 (Fmn2) is deregulated in PTSD and in Alzheimer's disease (AD) patients. Young mice lacking the Fmn2 gene exhibit PTSD-like phenotypes and corresponding impairments of synaptic plasticity, while the consolidation of new memories is unaffected. However, Fmn2 mutant mice develop accelerated age-associated me…
MicroRNA hsa-miR-4717-5p regulates RGS2 and may be a risk factor for anxiety-related traits
Regulator of G-protein Signaling 2 (RGS2) is a key regulator of G-protein-coupled signaling pathways involved in fear and anxiety. Data from rodent models and genetic analysis of anxiety-related traits and disorders in humans suggest down-regulation of RGS2 expression to be a risk factor for anxiety. Here we investigated, whether genetic variation in microRNAs mediating posttranscriptional down-regulation of RGS2 may be a risk factor for anxiety as well. 75 microRNAs predicted to regulate RGS2 were identified by four bioinformatic algorithms and validated experimentally by luciferase reporter gene assays. Specificity was confirmed for six microRNAs (hsa-miR-1271-5p, hsa-miR-22-3p, hsa-miR-3…
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs
AM Vicente - Cross-Disorder Group of the Psychiatric Genomics Consortium Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in …
Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysis
Funder: Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada); doi: https://doi.org/10.13039/501100000024
A Polymorphism in the Crhr1 Gene Determines Stress Vulnerability in Male Mice
Chronic stress is a risk factor for psychiatric disorders but does not necessarily lead to uniform long-term effects on mental health, suggesting modulating factors such as genetic predispositions. Here we address the question whether natural genetic variations in the mouse CRH receptor 1 (Crhr1) locus modulate the effects of adolescent chronic social stress (ACSS) on long-term stress hormone dysregulation in outbred CD1 mice, which allows a better understanding of the currently reported genes × environment interactions of early trauma and CRHR1 in humans. We identified 2 main haplotype variants in the mouse Crhr1 locus that modulate the long-term effects of ACSS on basal hypothalamic-pitui…
DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning
Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe “DeepWAS”, a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to…
Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
G.B. and S.N. acknowledge funding support for this work from the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. P.H.L. is supported by US National Institute of Mental Health (NIMH) grant K99MH101367. Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an an…
Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder
Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generat…
Common genes associated with antidepressant response in mouse and man identify key role of glucocorticoid receptor sensitivity.
Response to antidepressant treatment in major depressive disorder (MDD) cannot be predicted currently, leading to uncertainty in medication selection, increasing costs, and prolonged suffering for many patients. Despite tremendous efforts in identifying response-associated genes in large genome-wide association studies, the results have been fairly modest, underlining the need to establish conceptually novel strategies. For the identification of transcriptome signatures that can distinguish between treatment responders and nonresponders, we herein submit a novel animal experimental approach focusing on extreme phenotypes. We utilized the large variance in response to antidepressant treatmen…