SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Extended search

Träfflista för sökning "WFRF:(Van Steen Kristel) "

Search: WFRF:(Van Steen Kristel)

  • Result 1-10 of 10
Sort/group result
   
EnumerationReferenceCoverFind
1.
  • Hibar, Derrek P., et al. (author)
  • Novel genetic loci associated with hippocampal volume
  • 2017
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
  • Journal article (peer-reviewed)abstract
    • The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r(g) = -0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
  •  
2.
  • Satizabal, Claudia L., et al. (author)
  • Genetic architecture of subcortical brain structures in 38,851 individuals
  • 2019
  • In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:11, s. 1624-
  • Journal article (peer-reviewed)abstract
    • Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
  •  
3.
  • Thompson, Paul M., et al. (author)
  • The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
  • 2014
  • In: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
  • Journal article (peer-reviewed)abstract
    • The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
  •  
4.
  • Moens, Lotte N, et al. (author)
  • Sequencing of DISC1 Pathway Genes Reveals Increased Burden of Rare Missense Variants in Schizophrenia Patients from a Northern Swedish Population
  • 2011
  • In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:8, s. e23450-
  • Journal article (peer-reviewed)abstract
    • In recent years, DISC1 has emerged as one of the most credible and best supported candidate genes for schizophrenia and related neuropsychiatric disorders. Furthermore, increasing evidence - both genetic and functional - indicates that many of its protein interaction partners are also involved in the development of these diseases. In this study, we applied a pooled sample 454 sequencing strategy, to explore the contribution of genetic variation in DISC1 and 10 of its interaction partners (ATF5, Grb2, FEZ1, LIS-1, PDE4B, NDE1, NDEL1, TRAF3IP1, YWHAE, and ZNF365) to schizophrenia susceptibility in an isolated northern Swedish population. Mutation burden analysis of the identified variants in a population of 486 SZ patients and 514 control individuals, revealed that non-synonymous rare variants with a MAF<0.01 were significantly more present in patients compared to controls (8.64% versus 4.7%, P = 0.018), providing further evidence for the involvement of DISC1 and some of its interaction partners in psychiatric disorders. This increased burden of rare missense variants was even more striking in a subgroup of early onset patients (12.9% versus 4.7%, P = 0.0004), highlighting the importance of studying subgroups of patients and identifying endophenotypes. Upon investigation of the potential functional effects associated with the identified missense variants, we found that similar to 90% of these variants reside in intrinsically disordered protein regions. The observed increase in mutation burden in patients provides further support for the role of the DISC1 pathway in schizophrenia. Furthermore, this study presents the first evidence supporting the involvement of mutations within intrinsically disordered protein regions in the pathogenesis of psychiatric disorders. As many important biological functions depend directly on the disordered state, alteration of this disorder in key pathways may represent an intriguing new disease mechanism for schizophrenia and related neuropsychiatric diseases. Further research into this unexplored domain will be required to elucidate the role of the identified variants in schizophrenia etiology.
  •  
5.
  • Ripatti, Samuli, et al. (author)
  • GENESTAT : an information portal for design and analysis of genetic association studies
  • 2009
  • In: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 17:4, s. 533-536
  • Journal article (peer-reviewed)abstract
    • We present the rationale, the background and the structure for version 2.0 of the GENESTAT information portal (www.genestat.org) for statistical genetics. The fast methodological advances, coupled with a range of standalone software, makes it difficult for expert as well as non-expert users to orientate when designing and analysing their genetic studies. The ultimate ambition of GENESTAT is to guide on statistical methodology related to the broad spectrum of research in genetic epidemiology. GENESTAT 2.0 focuses on genetic association studies. Each entry provides a summary of a topic and gives links to key papers, websites and software. The flexibility of the internet is utilised for cross-referencing and for open editing. This paper gives an overview of GENESTAT and gives short introductions to the current main topics in GENESTAT, with additional entries on the website. Methods and software developers are invited to contribute to the portal, which is powered by a Wikipedia-type engine and allows easy additions and editing.
  •  
6.
  •  
7.
  • Goyette, Philippe, et al. (author)
  • High-density mapping of the MHC identifies a shared role for HLA-DRB1*01 : 03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis
  • 2015
  • In: Nature Genetics. - New York, USA : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 47:2, s. 172-179
  • Journal article (peer-reviewed)abstract
    • Genome-wide association studies of the related chronic inflammatory bowel diseases (IBD) known as Crohn's disease and ulcerative colitis have shown strong evidence of association to the major histocompatibility complex (MHC). This region encodes a large number of immunological candidates, including the antigen-presenting classical human leukocyte antigen (HLA) molecules. Studies in IBD have indicated that multiple independent associations exist at HLA and non-HLA genes, but they have lacked the statistical power to define the architecture of association and causal alleles. To address this, we performed high-density SNP typing of the MHC in >32,000 individuals with IBD, implicating multiple HLA alleles, with a primary role for HLA-DRB1*01:03 in both Crohn's disease and ulcerative colitis. Noteworthy differences were observed between these diseases, including a predominant role for class II HLA variants and heterozygous advantage observed in ulcerative colitis, suggesting an important role of the adaptive immune response in the colonic environment in the pathogenesis of IBD.
  •  
8.
  • Li, Jiarui, et al. (author)
  • Robust genome-wide ancestry inference for heterogeneous datasets : illustrated using the 1,000 genome project with 3D facial images
  • 2020
  • In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
  • Journal article (peer-reviewed)abstract
    • Estimates of individual-level genomic ancestry are routinely used in human genetics, and related fields. The analysis of population structure and genomic ancestry can yield insights in terms of modern and ancient populations, allowing us to address questions regarding admixture, and the numbers and identities of the parental source populations. Unrecognized population structure is also an important confounder to correct for in genome-wide association studies. However, it remains challenging to work with heterogeneous datasets from multiple studies collected by different laboratories with diverse genotyping and imputation protocols. This work presents a new approach and an accompanying open-source toolbox that facilitates a robust integrative analysis for population structure and genomic ancestry estimates for heterogeneous datasets. We show robustness against individual outliers and different protocols for the projection of new samples into a reference ancestry space, and the ability to reveal and adjust for population structure in a simulated case-control admixed population. Given that visually evident and easily recognizable patterns of human facial characteristics co-vary with genomic ancestry, and based on the integration of three different sources of genome data, we generate average 3D faces to illustrate genomic ancestry variations within the 1,000 Genome project and for eight ancient-DNA profiles, respectively.
  •  
9.
  • Martins Dos Santos, Vitor, et al. (author)
  • Systems Biology in ELIXIR: modelling in the spotlight
  • 2022
  • In: F1000Research. - : F1000 Research Ltd. - 1759-796X .- 2046-1402. ; 11
  • Journal article (peer-reviewed)abstract
    • In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR's future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.
  •  
10.
  • Wei, Zhi, et al. (author)
  • Large sample size, wide variant spectrum, and advanced machine-learning technique boost risk prediction for inflammatory bowel disease
  • 2013
  • In: American Journal of Human Genetics. - : University of Chicago Press. - 0002-9297 .- 1537-6605. ; 92:6, s. 1008-12
  • Journal article (peer-reviewed)abstract
    • We performed risk assessment for Crohn's disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), by using data from the International IBD Genetics Consortium's Immunochip project. This data set contains ~17,000 CD cases, ~13,000 UC cases, and ~22,000 controls from 15 European countries typed on the Immunochip. This custom chip provides a more comprehensive catalog of the most promising candidate variants by picking up the remaining common variants and certain rare variants that were missed in the first generation of GWAS. Given this unprecedented large sample size and wide variant spectrum, we employed the most recent machine-learning techniques to build optimal predictive models. Our final predictive models achieved areas under the curve (AUCs) of 0.86 and 0.83 for CD and UC, respectively, in an independent evaluation. To our knowledge, this is the best prediction performance ever reported for CD and UC to date.
  •  
Skapa referenser, mejla, bekava och länka
  • Result 1-10 of 10
Type of publication
journal article (10)
Type of content
peer-reviewed (10)
Author/Editor
Franke, Barbara (3)
Ching, Christopher R ... (3)
Agartz, Ingrid (3)
Brouwer, Rachel M (3)
Melle, Ingrid (3)
Westlye, Lars T (3)
show more...
Thompson, Paul M (3)
Andreassen, Ole A (3)
de Geus, Eco J. C. (3)
Martin, Nicholas G. (3)
Boomsma, Dorret I. (3)
Djurovic, Srdjan (3)
Meyer-Lindenberg, An ... (3)
Thalamuthu, Anbupala ... (3)
Cichon, Sven (3)
Rietschel, Marcella (3)
Schofield, Peter R (3)
Deary, Ian J (3)
Mattheisen, Manuel (3)
Montgomery, Grant W. (3)
Heinz, Andreas (3)
Le Hellard, Stephani ... (3)
Homuth, Georg (3)
Francks, Clyde (3)
Hartman, Catharina A ... (3)
Hottenga, Jouke-Jan (3)
Wardlaw, Joanna M. (3)
Jahanshad, Neda (3)
Crespo-Facorro, Bene ... (3)
Tordesillas-Gutierre ... (3)
Veltman, Dick J (3)
van Tol, Marie-José (3)
Sachdev, Perminder S ... (3)
Medland, Sarah E (3)
Mueller-Myhsok, Bert ... (3)
Grabe, Hans J. (3)
Saemann, Philipp G. (3)
Voelzke, Henry (3)
Wittfeld, Katharina (3)
Wright, Margaret J. (3)
Schmaal, Lianne (3)
Schork, Andrew J (3)
Teumer, Alexander (3)
Schumann, Gunter (3)
Milaneschi, Yuri (3)
Ophoff, Roel A (3)
Armstrong, Nicola J. (3)
Buckner, Randy L. (3)
de Zubicaray, Greig ... (3)
Ehrlich, Stefan (3)
show less...
University
Karolinska Institutet (5)
Umeå University (4)
Uppsala University (4)
Stockholm University (4)
Örebro University (2)
University of Gothenburg (1)
show more...
Chalmers University of Technology (1)
show less...
Language
English (10)
Research subject (UKÄ/SCB)
Natural sciences (5)
Medical and Health Sciences (5)
Social Sciences (2)
Engineering and Technology (1)

Year

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view