ORCID Profile
0000-0002-6527-6361
Current Organisation
University of California San Diego Health Sciences
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Publisher: Elsevier BV
Date: 07-2018
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 07-2020
DOI: 10.1161/STROKEAHA.119.027544
Abstract: Periventricular white matter hyperintensities (WMH PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 ( NBEAL ), 10q23.1 ( TSPAN14/FAM231A ), and 10q24.33 ( SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 ( NOS3 ) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.
Publisher: Wiley
Date: 31-05-2018
DOI: 10.1111/ADD.14252
Publisher: American Psychological Association (APA)
Date: 03-2021
DOI: 10.1037/NEU0000718
Publisher: Elsevier BV
Date: 2022
Publisher: Springer Science and Business Media LLC
Date: 04-03-2019
Publisher: Radiological Society of North America (RSNA)
Date: 06-2011
Publisher: Elsevier BV
Date: 07-2001
DOI: 10.1016/S0197-4580(01)00217-2
Abstract: Normal volunteers, aged 30 to 99 years, were studied with MRI. Age was related to estimated volumes of: gray matter, white matter, and CSF of the cerebrum and cerebellum gray matter, white matter, white matter abnormality, and CSF within each cerebral lobe and gray matter of eight subcortical structures. The results were: 1) Age-related losses in the hippoc us were significantly accelerated relative to gray matter losses elsewhere in the brain. 2) Among the cerebral lobes, the frontal lobes were disproportionately affected by cortical volume loss and increased white matter abnormality. 3) Loss of cerebral and cerebellar white matter occurred later than, but was ultimately greater than, loss of gray matter. It is estimated that between the ages of 30 and 90 volume loss averages 14% in the cerebral cortex, 35% in the hippoc us, and 26% in the cerebral white matter. Separate analyses were conducted in which genetic risk associated with the Apolipoprotein E epsilon4 allele was either overrepresented or underrepresented among elderly participants. Accelerated loss of hippoc al volume was observed with both analyses and thus does not appear to be due to the presence of at-risk subjects. MR signal alterations in the tissues of older in iduals pose challenges to the validity of current methods of tissue segmentation, and should be considered in the interpretation of the results.
Publisher: Wiley
Date: 29-12-2016
DOI: 10.1002/HBM.23502
Publisher: Elsevier BV
Date: 12-2021
Publisher: Cold Spring Harbor Laboratory
Date: 06-08-2021
DOI: 10.1101/2021.08.04.455143
Abstract: Despite their increasing application, the genetic and environmental etiology of global predicted brain ageing (PBA) indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 52 to 72 years. Biometrical genetic analyses revealed significant and highly correlated estimates of additive genetic heritability ranging from 59% to 75%. Multivariate longitudinal modelling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences.
Publisher: Elsevier BV
Date: 07-2019
Publisher: Informa UK Limited
Date: 02-2011
Publisher: Wiley
Date: 09-02-2018
DOI: 10.1002/HBM.24002
Location: United States of America
Location: United States of America
Location: United States of America
No related grants have been discovered for Christine Fennema-Notestine.