Dataset Information

White Matter Lesion Progression: Genome-Wide Search for Genetic Influences.

ABSTRACT: BACKGROUND AND PURPOSE: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.

SUBMITTER: Hofer E

PROVIDER: S-EPMC4749149 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

White Matter Lesion Progression: Genome-Wide Search for Genetic Influences.

Hofer Edith E Cavalieri Margherita M Bis Joshua C JC DeCarli Charles C Fornage Myriam M Sigurdsson Sigurdur S Srikanth Velandai V Trompet Stella S Verhaaren Benjamin F J BF Wolf Christiane C Yang Qiong Q Adams Hieab H H HH Amouyel Philippe P Beiser Alexa A Buckley Brendan M BM Callisaya Michele M Chauhan Ganesh G de Craen Anton J M AJ Dufouil Carole C van Duijn Cornelia M CM Ford Ian I Freudenberger Paul P Gottesman Rebecca F RF Gudnason Vilmundur V Heiss Gerardo G Hofman Albert A Lumley Thomas T Martinez Oliver O Mazoyer Bernard B Moran Chris C Niessen Wiro J WJ Phan Thanh T Psaty Bruce M BM Satizabal Claudia L CL Sattar Naveed N Schilling Sabrina S Shibata Dean K DK Slagboom P Eline PE Smith Albert A Stott David J DJ Taylor Kent D KD Thomson Russell R Töglhofer Anna M AM Tzourio Christophe C van Buchem Mark M Wang Jing J Westendorp Rudi G J RG Windham B Gwen BG Vernooij Meike W MW Zijdenbos Alex A Beare Richard R Debette Stéphanie S Ikram M Arfan MA Jukema J Wouter JW Launer Lenore J LJ Longstreth W T WT Mosley Thomas H TH Seshadri Sudha S Schmidt Helena H Schmidt Reinhold R

Stroke 20151008 11

<h4>Background and purpose</h4>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.<h4>Methods</h4>Heritability of WML progression was ca ...[more]

PMID: 26451028

Similar Datasets

Project description:Chronic active and slowly expanding lesions with smouldering inflammation are neuropathological correlates of progressive multiple sclerosis pathology. T1 hypointense volume and signal intensity on T1-weighted MRI reflect brain tissue damage that may develop within newly formed acute focal inflammatory lesions or in chronic pre-existing lesions without signs of acute inflammation. Using a recently developed method to identify slowly expanding/evolving lesions in vivo from longitudinal conventional T2- and T1-weighted brain MRI scans, we measured the relative amount of chronic lesion activity as measured by change in T1 volume and intensity within slowly expanding/evolving lesions and non-slowly expanding/evolving lesion areas of baseline pre-existing T2 lesions, and assessed the effect of ocrelizumab on this outcome in patients with primary progressive multiple sclerosis participating in the phase III, randomized, placebo-controlled, double-blind ORATORIO study (n = 732, NCT01194570). We also assessed the predictive value of T1-weighted measures of chronic lesion activity for clinical multiple sclerosis progression as reflected by a composite disability measure including the Expanded Disability Status Scale, Timed 25-Foot Walk and 9-Hole Peg Test. We observed in this clinical trial population that most of total brain non-enhancing T1 hypointense lesion volume accumulation was derived from chronic lesion activity within pre-existing T2 lesions rather than new T2 lesion formation. There was a larger decrease in mean normalized T1 signal intensity and greater relative accumulation of T1 hypointense volume in slowly expanding/evolving lesions compared with non-slowly expanding/evolving lesions. Chronic white matter lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in slowly expanding/evolving lesions and in non-slowly expanding/evolving lesion areas of pre-existing lesions predicted subsequent composite disability progression with consistent trends on all components of the composite. In contrast, whole brain volume loss and acute lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in new focal T2 lesions did not predict subsequent composite disability progression in this trial at the population level. Ocrelizumab reduced longitudinal measures of chronic lesion activity such as T1 hypointense lesion volume accumulation and mean normalized T1 signal intensity decrease both within regions of pre-existing T2 lesions identified as slowly expanding/evolving and in non-slowly expanding/evolving lesions. Using conventional brain MRI, T1-weighted intensity-based measures of chronic white matter lesion activity predict clinical progression in primary progressive multiple sclerosis and may qualify as a longitudinal in vivo neuroimaging correlate of smouldering demyelination and axonal loss in chronic active lesions due to CNS-resident inflammation and/or secondary neurodegeneration across the multiple sclerosis disease continuum.

Project description:Background and purposeWM lesion segmentation is often performed with the use of subjective rating scales because manual methods are laborious and tedious; however, automated methods are now available. We compared the performance of total lesion volume grading computed by use of an automated WM lesion segmentation algorithm with that of subjective rating scales and expert manual segmentation in a cohort of subjects with type 2 diabetes.Materials and methodsStructural T1 and FLAIR MR imaging data from 50 subjects with diabetes (age, 67.7 ± 7.2 years) and 50 nondiabetic sibling pairs (age, 67.5 ± 9.4 years) were evaluated in an institutional review board-approved study. WM lesion segmentation maps and total lesion volume were generated for each subject by means of the Statistical Parametric Mapping (SPM8) Lesion Segmentation Toolbox. Subjective WM lesion grade was determined by means of a 0-9 rating scale by 2 readers. Ground-truth total lesion volume was determined by means of manual segmentation by experienced readers. Correlation analyses compared manual segmentation total lesion volume with automated and subjective evaluation methods.ResultsCorrelation between average lesion segmentation and ground-truth total lesion volume was 0.84. Maximum correlation between the Lesion Segmentation Toolbox and ground-truth total lesion volume (ρ = 0.87) occurred at the segmentation threshold of k = 0.25, whereas maximum correlation between subjective lesion segmentation and the Lesion Segmentation Toolbox (ρ = 0.73) occurred at k = 0.15. The difference between the 2 correlation estimates with ground-truth was not statistically significant. The lower segmentation threshold (0.15 versus 0.25) suggests that subjective raters overestimate WM lesion burden.ConclusionsWe validate the Lesion Segmentation Toolbox for determining total lesion volume in diabetes-enriched populations and compare it with a common subjective WM lesion rating scale. The Lesion Segmentation Toolbox is a readily available substitute for subjective WM lesion scoring in studies of diabetes and other populations with changes of leukoaraiosis.

Dataset Information

White Matter Lesion Progression: Genome-Wide Search for Genetic Influences.

Publications

White Matter Lesion Progression: Genome-Wide Search for Genetic Influences.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets