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Gottesman, R. F.

Publications and source records attributed to Gottesman, R. F..

3 recordsLinked to original sources

Spatial Patterns of White Matter Hyperintensities and Cognitive Function in Older Adults: A Community-Based Study

Abstract Objectives White matter hyperintensities (WMH) are associated with cognitive decline in older adults. We examined whether anatomically defined spatial WMH patterns are associated with cognitive performance and subsequent decline in a large community-based cohort with approximately six years of follow-up. Methods We analyzed 1,667 participants (mean age 76 years) from the Atherosclerosis Risk in Communities Neurocognitive Study. WMH were segmented from FLAIR images and mapped to 112 white matter regions using deep-learning-based parcellation. Principal component analysis identified dominant WMH distribution patterns; candidate components were selected by Horn's parallel analysis and retained if stable across resampled split samples. Linear mixed-effects models examined associations between WMH patterns and cognitive performance at baseline and follow-up, adjusting for demographic, genomic, and vascular risk factors. Robustness was assessed using analyses accounting for total WMH burden, study center, and selective attrition. Results Of 14 candidate principal components (PCs) identified by parallel analysis, eight met the resampling stability criterion and were retained, together explaining 42% of the variance. Three components were associated with cross-sectional or future cognition. PC3, characterized by deep white matter burden in the corpus callosum and anterior corona radiata with relative preservation of superficial white matter, showed no cross-sectional association at baseline but was associated with accelerated decline across multiple domains. Interpretation A deep spatial pattern of WMH loading on the corpus callosum and anterior corona radiata was associated with subsequent cognitive decline in the absence of a cross-sectional association at baseline, independent of total lesion burden.

neuroscience↗

Common genetic variation indicates separate etiologies for periventricular and deep white matter hyperintensities

We conducted a genome-wide association meta-analysis of two ischemic white matter disease subtypes in the brain, periventricular and deep white matter hyperintensities (PVWMH and DWMH). In 26,654 participants, we found 10 independent genome-wide significant loci only associated with PVWMH, four of which have not been described previously for total WMH burden (16q24.2, 17q21.31, 10q23.1, 7q36.1). Additionally, in both PVWMH and DWMH we observed the previous association of the 17q25.1 locus with total WMH. We found that both phenotypes have shared but also distinct genetic architectures, consistent with both different underlying and related pathophysiology. PVWMH had more extensive genetic overlap with small vessel ischemic stroke, and unique associations with several loci implicated in ischemic stroke. DWMH were characterized by associations with loci previously implicated in vascular as well as astrocytic and neuronal function. Our study confirms the utility of these phenotypes and identifies new candidate genes associated only with PVWMH.

neuroscience↗

Genome-wide Association Study Links APOEϵ4 and BACE1 Variants with Plasma Amyloid β Levels

INTRODUCTIONThere is increasing interest in plasma A{beta} as an endophenotype and biomarker of Alzheimers disease (AD). Identifying the genetic determinants of plasma A{beta} levels may elucidate important processes that determine plasma A{beta} measures. METHODSWe included 12,369 non-demented participants derived from eight population-based studies. Imputed genetic data and plasma A{beta}1-40, A{beta}1-42 levels and A{beta}1-42/A{beta}1-40 ratio were used to perform genome-wide association studies, gene-based and pathway analyses. Significant variants and genes were followed-up for the association with PET A{beta} deposition and AD risk. RESULTSSingle-variant analysis identified associations across APOE for A{beta}1-42 and A{beta}1-42/A{beta}1-40 ratio, and BACE1 for A{beta}1-40. Gene-based analysis of A{beta}1-40 additionally identified associations for APP, PSEN2, CCK and ZNF397. There was suggestive interaction between a BACE1 variant and APOE{varepsilon}4 on brain A{beta} deposition. DISCUSSIONIdentification of variants near/in known major A{beta}-processing genes strengthens the relevance of plasma-A{beta} levels both as an endophenotype and a biomarker of AD.

genetics↗