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  • Ovid Technologies (Wolters Kluwer Health)  (6)
  • Adams, Hieab H.H.  (6)
  • 1
    Online Resource
    Online Resource
    Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting
    Ovid Technologies (Wolters Kluwer Health) ; 2019
    In:  Neurology Vol. 92, No. 5 ( 2019-01-29)
    Details
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 92, No. 5 ( 2019-01-29)
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    URL: Article
    DOI: 10.1212/WNL.0000000000006851
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2019
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  • 2
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    Online Resource
    Association of common genetic variants with brain microbleeds : A genome-wide association study
    Ovid Technologies (Wolters Kluwer Health) ; 2020
    In:  Neurology Vol. 95, No. 24 ( 2020-12-15), p. e3331-e3343
    Details
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 95, No. 24 ( 2020-12-15), p. e3331-e3343
    Abstract: To identify common genetic variants associated with the presence of brain microbleeds (BMBs). Methods We performed genome-wide association studies in 11 population-based cohort studies and 3 case–control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs. Results BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR] any BMB [95% confidence interval (CI)] 1.33 [1.21–1.45] ; p = 2.5 × 10 −10 ). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19–1.50] ; p = 1.0 × 10 −6 ) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86–1.25] ; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB. Conclusions Genetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    URL: Article
    DOI: 10.1212/WNL.0000000000010852
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2020
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  • 3
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    Online Resource
    Enlarged perivascular spaces and cognition : A meta-analysis of 5 population-based studies
    Ovid Technologies (Wolters Kluwer Health) ; 2018
    In:  Neurology Vol. 91, No. 9 ( 2018-08-28), p. e832-e842
    Details
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 91, No. 9 ( 2018-08-28), p. e832-e842
    Abstract: To investigate the association of enlarged perivascular spaces (ePVS) with cognition in elderly without dementia. Methods We included 5 studies from the Uniform Neuro-Imaging of Virchow-Robin Space Enlargement (UNIVRSE) consortium, namely the Austrian Stroke Prevention Family Study, Study of Health in Pomerania, Rotterdam Study, Epidemiology of Dementia in Singapore study, and Risk Index for Subclinical Brain Lesions in Hong Kong study. ePVS were counted in 4 regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) with harmonized rating across studies. Mini-Mental State Examination (MMSE) and general fluid cognitive ability factor (G-factor) were used to assess cognitive function. For each study, a linear regression model was performed to estimate the effect of ePVS on MMSE and G-factor. Estimates were pooled across studies with the use of inverse variance meta-analysis with fixed- or random-effect models when appropriate. Results The final sample size consisted of 3,575 persons (age range 63.4–73.2 years, 50.6% women). Total ePVS counts were not significantly associated with MMSE score (mean difference per ePVS score increase 0.001, 95% confidence interval [CI] −0.007 to 0.008, p = 0.885) or G-factor (mean difference per ePVS score increase 0.002, 95% CI −0.001 to 0.006, p = 0.148) in age-, sex-, and education-adjusted models. Adjustments for cardiovascular risk factors and MRI markers did not change the results. Repeating the analyses with region-specific ePVS rendered similar results. Conclusions In this study, we found that ePVS counts were not associated with cognitive dysfunction in the general population. Future studies with longitudinal designs are warranted to examine whether ePVS contribute to cognitive decline.
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    URL: Article
    DOI: 10.1212/WNL.0000000000006079
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2018
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  • 4
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    Online Resource
    White Matter Lesion Progression : Genome-Wide Search for Genetic Influences
    Ovid Technologies (Wolters Kluwer Health) ; 2015
    In:  Stroke Vol. 46, No. 11 ( 2015-11), p. 3048-3057
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 46, No. 11 ( 2015-11), p. 3048-3057
    Abstract: White matter lesion (WML) progression on magnetic resonance imaging is related to cognitive decline and stroke, but its determinants besides baseline WML burden are largely unknown. Here, we estimated heritability of WML progression, and sought common genetic variants associated with WML progression in elderly participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Methods— Heritability of WML progression was calculated in the Framingham Heart Study. The genome-wide association study included 7773 elderly participants from 10 cohorts. To assess the relative contribution of genetic factors to progression of WML, we compared in 7 cohorts risk models including demographics, vascular risk factors plus single-nucleotide polymorphisms that have been shown to be associated cross-sectionally with WML in the current and previous association studies. Results— A total of 1085 subjects showed WML progression. The heritability estimate for WML progression was low at 6.5%, and no single-nucleotide polymorphisms achieved genome-wide significance ( P 〈 5×10 −8 ). Four loci were suggestive ( P 〈 1×10 −5 ) of an association with WML progression: 10q24.32 (rs10883817, P =1.46×10 −6 ); 12q13.13 (rs4761974, P =8.71×10 −7 ); 20p12.1 (rs6135309, P =3.69×10 −6 ); and 4p15.31 (rs7664442, P =2.26×10 −6 ). Variants that have been previously related to WML explained only 0.8% to 11.7% more of the variance in WML progression than age, vascular risk factors, and baseline WML burden. Conclusions— Common genetic factors contribute little to the progression of age-related WML in middle-aged and older adults. Future research on determinants of WML progression should focus more on environmental, lifestyle, or host-related biological factors.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/STROKEAHA.115.009252
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2015
    detail.hit.zdb_id: 1467823-8
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  • 5
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    Online Resource
    Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities
    Ovid Technologies (Wolters Kluwer Health) ; 2020
    In:  Stroke Vol. 51, No. 7 ( 2020-07), p. 2111-2121
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 51, No. 7 ( 2020-07), p. 2111-2121
    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. Methods: 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. Results: 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. Conclusions: 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.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/STROKEAHA.119.027544
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2020
    detail.hit.zdb_id: 1467823-8
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  • 6
    Online Resource
    Online Resource
    Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging
    Ovid Technologies (Wolters Kluwer Health) ; 2018
    In:  Stroke Vol. 49, No. 8 ( 2018-08), p. 1812-1819
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 49, No. 8 ( 2018-08), p. 1812-1819
    Abstract: White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods— In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results— At 17q25, we confirmed the association of multiple common variants in TRIM65 , FBF1 , and ACOX1 ( P 〈 6×10 −7 ). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; P EA =4.5×10 −8 ) partially independent of known common signal ( P EA(conditional) =1.4×10 −3 ). We further identified a locus at 2q33 containing common variants in NBEAL1 , CARF , and WDR12 (lead, rs2351524; P all =1.9×10 −10 ). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( P rs34136221 =2.8×10 −8 ). Conclusions— Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/STROKEAHA.118.020689
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2018
    detail.hit.zdb_id: 1467823-8
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