Biology subjects

De Witte, W.

Publications and source records attributed to De Witte, W..

2 recordsLinked to original sources

bioRxiv2019

Genetic overlap between obsessive-compulsive disorder, related symptoms in the population and insulin signaling: etiological implications

ObjectiveObsessive-compulsive symptoms (OCS) in the population have been linked to obsessive-compulsive disorder (OCD) in genetic and epidemiological studies. Insulin signaling has been implicated in OCD. We extend previous work by assessing genetic overlap between OCD, population-based OCS, and central nervous system (CNS) and peripheral insulin signaling.\n\nMethodsWe conducted genome-wide association studies (GWASs) in the population-based Philadelphia Neurodevelopmental Cohort (PNC, 650 children and adolescents) of the total OCS score and six OCS factors from an exploratory factor analysis of 22 questions. Subsequently, we performed polygenic risk score (PRS) analysis to assess shared genetic etiologies between clinical OCD (using GWAS data from the Psychiatric Genomics Consortium), the total OCS score and OCS factors. We then performed gene-set analyses with a set of OCD-linked genes centered around CNS insulin-regulated synaptic function and PRS analyses for five peripheral insulin signaling-related traits. For validation purposes, we explored data from the independent Spit for Science population cohort (5047 children and adolescents).\n\nResultsIn the PNC, we found a shared genetic etiology between OCD and impairment, contamination/cleaning and guilty taboo thoughts. In the Spit for Science cohort, we were able to validate the finding for contamination/cleaning, and additionally observed genetic sharing between OCD and symmetry/counting/ordering. The CNS insulin-linked gene-set associated with symmetry/counting/ordering. We also identified genetic sharing between peripheral insulin signaling-related traits (type 2 diabetes and the blood levels of HbA1C, fasting insulin and 2 hour glucose) and OCD as well as certain OCS.\n\nConclusionsOCD, OCS in the population and insulin-related traits share genetic risk factors, indicating a common etiological mechanism underlying somatic and psychiatric disorders.

genetics↗

bioRxiv2019

RICOPILI: Rapid Imputation for COnsortias PIpeLIne

MotivationGenome-wide association study (GWAS) analyses, at sufficient sample sizes and power, have successfully revealed biological insights for several complex traits. RICOPILI, an open sourced Perl-based pipeline was developed to address the challenges of rapidly processing large scale multi-cohort GWAS studies including quality control, imputation and downstream analyses. The pipeline is computationally efficient with portability to a wide range of high-performance computing (HPC) environments.\n\nSummaryRICOPILI was created as the Psychiatric Genomics Consortium (PGC) pipeline for GWAS and has been adopted by other users. The pipeline features i) technical and genomic quality control in case-control and trio cohorts ii) genome-wide phasing and imputation iv) association analysis v) meta-analysis vi) polygenic risk scoring and vii) replication analysis. Notably, a major differentiator from other GWAS pipelines, RICOPILI leverages on automated parallelization and cluster job management approaches for rapid production of imputed genome-wide data. A comprehensive meta-analysis of simulated GWAS data has been incorporated demonstrating each step of the pipeline. This includes all of the associated visualization plots, to allow ease of data interpretation and manuscript preparation. Simulated GWAS datasets are also packaged with the pipeline for user training tutorials and developer work.\n\nAvailability and ImplementationRICOPILI has a flexible architecture to allow for ongoing development and incorporation of newer available algorithms and is adaptable to various HPC environments (QSUB, BSUB, SLURM and others). Specific links for genomic resources are either directly provided in this paper or via tutorials and external links. The central location hosting scripts and tutorials is found at this URL: https://sites.google.com/a/broadinstitute.org/RICOPILI/home\n\nContactsripke@broadinstitute.org\n\nSupplementary informationSupplementary data are available.

genetics↗