Publications by authors named "Ward De Witte"

8 Publications

  • Page 1 of 1

Potential role for immune-related genes in autism spectrum disorders: Evidence from genome-wide association meta-analysis of autistic traits.

Autism 2021 Aug 4:13623613211019547. Epub 2021 Aug 4.

Radboud University Medical Center, The Netherlands.

Lay Abstract: Autism spectrum disorders are complex, with a strong genetic basis. Genetic research in autism spectrum disorders is limited by the fact that these disorders are largely heterogeneous so that patients are variable in their clinical presentations. To address this limitation, we investigated the genetics of individual dimensions of the autism spectrum disorder phenotypes, or autistic-like traits. These autistic-like traits are continuous variations in autistic behaviours that occur in the general population. Therefore, we meta-analysed data from four different population cohorts in which autistic-like traits were measured. We performed a set of genetic analyses to identify common variants for autistic-like traits, understand how these variants related to autism spectrum disorders, and how they contribute to neurobiological processes. Our results showed genetic associations with specific autistic-like traits and a link to the immune system. We offer an example of the potential to use a dimensional approach when dealing with heterogeneous, complex disorder like autism spectrum disorder. Decomposing the complex autism spectrum disorder phenotype in its core features can inform on the specific biology of these features which is likely to account to clinical variability in patients.
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http://dx.doi.org/10.1177/13623613211019547DOI Listing
August 2021

Genetic overlap between Alzheimer's disease and blood lipid levels.

Neurobiol Aging 2021 Jul 3. Epub 2021 Jul 3.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands. Electronic address:

Late-onset Alzheimer's disease (AD) has a significant genetic component, but the molecular mechanisms through which genetic risk factors contribute to AD pathogenesis are unclear. We screened for genetic sharing between AD and the blood levels of 615 metabolites to elucidate how the polygenic architecture of AD affects metabolomic profiles. We retrieved summary statistics from genome-wide association studies of AD and the metabolite blood levels and assessed for shared genetic etiology, using a polygenic risk score-based approach. For the blood levels of 31 metabolites, all of which were lipids, we identified and replicated genetic sharing with AD. We also found a positive genetic concordance - implying that genetic risk factors for AD are associated with higher blood levels - for 16 of the 31 replicated metabolites. In the brain, lipids and their intermediate metabolites have essential structural and functional roles, such as forming and dynamically regulating synaptic membranes. Our results imply that genetic risk factors for AD affect lipid levels, which may be leveraged to develop novel treatment strategies for AD.
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http://dx.doi.org/10.1016/j.neurobiolaging.2021.06.019DOI Listing
July 2021

Shared Genetic Etiology between Alzheimer's Disease and Blood Levels of Specific Cytokines and Growth Factors.

Genes (Basel) 2021 06 5;12(6). Epub 2021 Jun 5.

Department of Human Genetics, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.

Late-onset Alzheimer's disease (AD) has a significant genetic and immunological component, but the molecular mechanisms through which genetic and immunity-related risk factors and their interplay contribute to AD pathogenesis are unclear. Therefore, we screened for genetic sharing between AD and the blood levels of a set of cytokines and growth factors to elucidate how the polygenic architecture of AD affects immune marker profiles. For this, we retrieved summary statistics from Finnish genome-wide association studies of AD and 41 immune marker blood levels and assessed for shared genetic etiology, using a polygenic risk score-based approach. For the blood levels of 15 cytokines and growth factors, we identified genetic sharing with AD. We also found positive and negative genetic concordances-implying that genetic risk factors for AD are associated with higher and lower blood levels-for several immune markers and were able to relate some of these results to the literature. Our results imply that genetic risk factors for AD also affect specific immune marker levels, which may be leveraged to develop novel treatment strategies for AD.
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http://dx.doi.org/10.3390/genes12060865DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226721PMC
June 2021

Genetic underpinnings of sociability in the general population.

Neuropsychopharmacology 2021 08 30;46(9):1627-1634. Epub 2021 May 30.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.

Levels of sociability are continuously distributed in the general population, and decreased sociability represents an early manifestation of several brain disorders. Here, we investigated the genetic underpinnings of sociability in the population. We performed a genome-wide association study (GWAS) of a sociability score based on four social functioning-related self-report questions from 342,461 adults in the UK Biobank. Subsequently we performed gene-wide and functional follow-up analyses. Robustness analyses were performed in the form of GWAS split-half validation analyses, as well as analyses excluding neuropsychiatric cases. Using genetic correlation analyses as well as polygenic risk score analyses we investigated genetic links of our sociability score to brain disorders and social behavior outcomes. Individuals with autism spectrum disorders, bipolar disorder, depression, and schizophrenia had a lower sociability score. The score was significantly heritable (SNP h of 6%). We identified 18 independent loci and 56 gene-wide significant genes, including genes like ARNTL, DRD2, and ELAVL2. Many associated variants are thought to have deleterious effects on gene products and our results were robust. The sociability score showed negative genetic correlations with autism spectrum, disorders, depression, schizophrenia, and two sociability-related traits-loneliness and social anxiety-but not with bipolar disorder or Alzheimer's disease. Polygenic risk scores of our sociability GWAS were associated with social behavior outcomes within individuals with bipolar disorder and with major depressive disorder. Variation in population sociability scores has a genetic component, which is relevant to several psychiatric disorders. Our findings provide clues towards biological pathways underlying sociability.
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http://dx.doi.org/10.1038/s41386-021-01044-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280100PMC
August 2021

Shared genetic etiology between Parkinson's disease and blood levels of specific lipids.

NPJ Parkinsons Dis 2021 Mar 5;7(1):23. Epub 2021 Mar 5.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.

Parkinson's disease (PD) is characterized by the degeneration of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies. The mechanisms underlying these molecular and cellular effects are largely unknown. Previously, based on genetic and other data, we built a molecular landscape of PD that highlighted a central role for lipids. To explore which lipid species may be involved in PD pathology, we used published genome-wide association study (GWAS) data to conduct polygenic risk score-based analyses to examine putative genetic sharing between PD and blood levels of 370 lipid species and lipid-related molecules. We found a shared genetic etiology between PD and blood levels of 25 lipids. We then used data from a much-extended GWAS of PD to try and corroborate our findings. Across both analyses, we found genetic overlap between PD and blood levels of eight lipid species, namely two polyunsaturated fatty acids (PUFA 20:3n3-n6 and 20:4n6), four triacylglycerols (TAG 44:1, 46:1, 46:2, and 48:0), phosphatidylcholine aa 32:3 (PC aa 32:3) and sphingomyelin 26:0 (SM 26:0). Analysis of the concordance-the agreement in genetic variant effect directions across two traits-revealed a significant negative concordance between PD and blood levels of the four triacylglycerols and PC aa 32:3 and a positive concordance between PD and blood levels of both PUFA and SM 26:0. Taken together, our analyses imply that genetic variants associated with PD modulate blood levels of a specific set of lipid species supporting a key role of these lipids in PD etiology.
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http://dx.doi.org/10.1038/s41531-021-00168-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935855PMC
March 2021

Shared genetic etiology between obsessive-compulsive disorder, obsessive-compulsive symptoms in the population, and insulin signaling.

Transl Psychiatry 2020 04 27;10(1):121. Epub 2020 Apr 27.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.

Obsessive-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. We 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)-based 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-based analyses for five peripheral insulin signaling-related traits. For validation purposes, we explored data from the independent Spit for Science population cohort (5,047 children and adolescents). In the PNC, we found a significant shared genetic etiology between OCD and 'guilty taboo thoughts'. In the Spit for Science cohort, we additionally observed genetic sharing between 'symmetry/counting/ordering' and 'contamination/cleaning'. The CNS insulin-linked gene-set also associated with 'symmetry/counting/ordering' in the PNC. Further, we identified genetic sharing between peripheral insulin signaling-related traits: type 2 diabetes with 'aggressive taboo thoughts', and levels of fasting insulin and 2 h glucose with OCD. In conclusion, OCD, OCS in the population and insulin-related traits share genetic risk factors, indicating a common etiological mechanism underlying somatic and psychiatric disorders.
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http://dx.doi.org/10.1038/s41398-020-0793-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186226PMC
April 2020

Social and non-social autism symptoms and trait domains are genetically dissociable.

Commun Biol 2019 3;2:328. Epub 2019 Sep 3.

1Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK.

The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, though this hypothesis has not yet been tested using molecular genetics. We test this using a genome-wide association study ( = 51,564) of a non-social trait related to autism, systemising, defined as the drive to analyse and build systems. We demonstrate that systemising is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemising. Supporting this, polygenic scores for systemising are significantly and positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.
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http://dx.doi.org/10.1038/s42003-019-0558-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6722082PMC
April 2020

RICOPILI: Rapid Imputation for COnsortias PIpeLIne.

Bioinformatics 2020 02;36(3):930-933

Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.

Summary: Genome-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 (QC), imputation and downstream analyses. The pipeline is computationally efficient with portability to a wide range of high-performance computing environments. RICOPILI was created as the Psychiatric Genomics Consortium pipeline for GWAS and adopted by other users. The pipeline features (i) technical and genomic QC 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 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.

Availability And Implementation: RICOPILI 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.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz633DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7868045PMC
February 2020
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