30 research outputs found
Gene expression imputation across multiple brain regions provides insights into schizophrenia risk
Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression
Evidence for Increased Genetic Risk Load for Major Depression in Patients Assigned to Electroconvulsive Therapy
Electroconvulsive therapy (ECT) is the treatment of choice for severe and treatment-resistant
depression; disorder severity and unfavorable treatment outcomes are shown to be influenced
by an increased genetic burden for major depression (MD). Here, we tested whether ECT assignment
and response/nonresponse are associated with an increased genetic burden for major
depression (MD) using polygenic risk score (PRS), which summarize the contribution of diseaserelated
common risk variants. Fifty-one psychiatric inpatients suffering from a major depressive
episode underwent ECT. MD-PRS were calculated for these inpatients and a separate
population-based sample (n = 3,547 healthy; n = 426 self-reported depression) based on summary
statistics from the Psychiatric Genomics Consortium MDD-working group (Cases:
n = 59,851; Controls: n = 113,154). MD-PRS explained a significant proportion of disease status
between ECT patients and healthy controls (p = .022, R2 = 1.173%); patients showed higher
MD-PRS. MD-PRS in population-based depression self-reporters were intermediate between
ECT patients and controls (n.s.). Significant associations between MD-PRS and ECT response
(50% reduction in Hamilton depression rating scale scores) were not observed. Our findings indicate
that ECT cohorts show an increased genetic burden for MD and are consistent with the
hypothesis that treatment-resistant MD patients represent a subgroup with an increased genetic
risk for MD. Larger samples are needed to better substantiate these findings
Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes
publisher: Elsevier articletitle: Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes journaltitle: Cell articlelink: https://doi.org/10.1016/j.cell.2018.05.046 content_type: article copyright: © 2018 Elsevier Inc
P2744Low survival after out-of-hospital cardiac arrest in nursing homes despite early initiation of bystander cardiopulmonary resuscitation - a nationwide study
Low survival after out-of-hospital cardiac arrest in nursing homes despite early initiation of bystander cardiopulmonary resuscitation:a nationwide study
Effect of a first responder on survival outcomes after out-of-hospital cardiac arrest occurs during a period of exercise in a public place
Factors determining level of hospital care and its association with outcome after resuscitation from pre-hospital pulseless electrical activity
Ginkgo biloba does not benefit patients with tinnitus: a randomized placebo-controlled double-blind trial and meta-analysis of randomized trials
Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns
Abstract
Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk