ORCID Profile
0000-0003-2001-1375
Current Organisation
VU University Amsterdam
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Publisher: Elsevier BV
Date: 04-2007
Publisher: Springer Science and Business Media LLC
Date: 31-01-2019
Publisher: Springer Science and Business Media LLC
Date: 02-2016
DOI: 10.1038/NN.4228
Publisher: Cold Spring Harbor Laboratory
Date: 22-03-2022
DOI: 10.1101/2022.03.21.484899
Abstract: Mechanisms underpinning age-related variations in cortical thickness in the human brain remain poorly understood. We investigated whether inter-regional age-related variations in cortical thinning (in a multicohort neuroimaging dataset from the ENIGMA Lifespan Working Group totalling 14,248 in iduals, aged 4-89 years) depended on cell-specific marker gene expression levels. We found differences amidst early-life ( years), mid-life (20-60 years), and late-life ( years) in the patterns of association between inter-regional profiles of cortical thickness and expression profiles of marker genes for CA1 and S1 pyramidal cells, astrocytes, and microglia. Gene ontology and enrichment analyses indicated that each of the three life-stages was associated with different biological processes and cellular components: synaptic modeling in early life, neurotransmission in mid-life, and neurodegeneration in late-life. These findings provide mechanistic insights into age-related cortical thinning during typical development and aging.
Publisher: Elsevier BV
Date: 07-2014
Publisher: Research Square Platform LLC
Date: 27-05-2022
DOI: 10.21203/RS.3.RS-1686228/V1
Abstract: Mechanisms underpinning neurotypical age-related variations in cortical thickness in the human brain remain insufficiently specified. Here we used cell-specific marker genes, followed by gene ontology and enrichment analyses, to quantify the association between gene-expression levels and inter-regional age-related variations in neurotypical cortical thinning using multicohort neuroimaging data from 14,248 in iduals ages 4-89 years. We found that early-life ( years), mid-life (20-60 years), and late-life ( years) were associated with distinct patterns of association between inter-regional profiles of cortical thickness and expression profiles of markers genes for CA1 and S1 pyramidal cells, astrocytes, and microglia. Gene ontology and enrichment analyses indicated each of the three life-stages was associated with different biological processes and cellular components these related to synaptic modeling in early life, neurotransmission in mid-life, and neurodegeneration in late-life. These findings provide mechanistic insights on age-related cortical thinning during typical development and ageing.
Publisher: Springer Science and Business Media LLC
Date: 03-10-2016
DOI: 10.1038/NN.4398
Publisher: Cambridge University Press (CUP)
Date: 06-2012
DOI: 10.1017/THG.2012.20
Abstract: This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are le evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are ex les of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI) white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.
Publisher: American Medical Association (AMA)
Date: 04-2020
Publisher: Springer Science and Business Media LLC
Date: 08-01-2014
Publisher: Elsevier BV
Date: 12-2014
Publisher: Elsevier BV
Date: 05-2015
Publisher: Springer Science and Business Media LLC
Date: 18-01-2017
DOI: 10.1038/NCOMMS13624
Abstract: The hippoc al formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippoc al volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippoc al structure here we perform a genome-wide association study (GWAS) of 33,536 in iduals and discover six independent loci significantly associated with hippoc al 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 hippoc al 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 hippoc al 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 hippoc al volume and risk for neuropsychiatric illness.
Publisher: Springer Science and Business Media LLC
Date: 04-2022
DOI: 10.1038/S41593-022-01042-4
Abstract: Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 in iduals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
Publisher: Springer Science and Business Media LLC
Date: 21-10-2019
Publisher: Springer Science and Business Media LLC
Date: 21-01-2015
DOI: 10.1038/NATURE14101
Publisher: Elsevier BV
Date: 11-2009
No related grants have been discovered for Dennis van 't Ent.