Browsing by Author "Wilhalme, Holly"

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    Associations of the Top 20 Alzheimer Disease Risk Variants With Brain Amyloidosis
    (American Medical Association, 2018-03-01) Apostolova, Liana G.; Risacher, Shannon L.; Duran, Tugce; Stage, Eddie C.; Goukasian, Naira; West, John D.; Do, Triet M.; Grotts, Jonathan; Wilhalme, Holly; Nho, Kwangsik; Phillips, Meredith; Elashoff, David; Saykin, Andrew J.; Neurology, School of Medicine
    Importance: Late-onset Alzheimer disease (AD) is highly heritable. Genome-wide association studies have identified more than 20 AD risk genes. The precise mechanism through which many of these genes are associated with AD remains unknown. Objective: To investigate the association of the top 20 AD risk variants with brain amyloidosis. Design, Setting, and Participants: This study analyzed the genetic and florbetapir F 18 data from 322 cognitively normal control individuals, 496 individuals with mild cognitive impairment, and 159 individuals with AD dementia who had genome-wide association studies and 18F-florbetapir positron emission tomographic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a prospective, observational, multisite tertiary center clinical and biomarker study. This ongoing study began in 2005. Main Outcomes and Measures: The study tested the association of AD risk allele carrier status (exposure) with florbetapir mean standard uptake value ratio (outcome) using stepwise multivariable linear regression while controlling for age, sex, and apolipoprotein E ε4 genotype. The study also reports on an exploratory 3-dimensional stepwise regression model using an unbiased voxelwise approach in Statistical Parametric Mapping 8 with cluster and significance thresholds at 50 voxels and uncorrected P < .01. Results: This study included 977 participants (mean [SD] age, 74 [7.5] years; 535 [54.8%] male and 442 [45.2%] female) from the ADNI-1, ADNI-2, and ADNI-Grand Opportunity. The adenosine triphosphate-binding cassette subfamily A member 7 (ABCA7) gene had the strongest association with amyloid deposition (χ2 = 8.38, false discovery rate-corrected P < .001), after apolioprotein E ε4. Significant associations were found between ABCA7 in the asymptomatic and early symptomatic disease stages, suggesting an association with rapid amyloid accumulation. The fermitin family homolog 2 (FERMT2) gene had a stage-dependent association with brain amyloidosis (FERMT2 × diagnosis χ2 = 3.53, false discovery rate-corrected P = .05), which was most pronounced in the mild cognitive impairment stage. Conclusions and Relevance: This study found an association of several AD risk variants with brain amyloidosis. The data also suggest that AD genes might differentially regulate AD pathologic findings across the disease stages.
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    The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism
    (Elsevier, 2016-12-19) Stage, Eddie; Duran, Tugce; Risacher, Shannon L.; Goukasian, Naira; Do, Triet M.; West, John D.; Wilhalme, Holly; Nho, Kwangsik; Phillips, Meredith; Elashoff, David; Saykin, Andrew J.; Apostolova, Liana G.; Department of Neurology, IU School of Medicine
    INTRODUCTION: We analyzed the effects of the top 20 Alzheimer disease (AD) risk genes on gray-matter density (GMD) and metabolism. METHODS: We ran stepwise linear regression analysis using posterior cingulate hypometabolism and medial temporal GMD as outcomes and all risk variants as predictors while controlling for age, gender, and APOE ε4 genotype. We explored the results in 3D using Statistical Parametric Mapping 8. RESULTS: Significant predictors of brain GMD were SLC24A4/RIN3 in the pooled and mild cognitive impairment (MCI); ZCWPW1 in the MCI; and ABCA7, EPHA1, and INPP5D in the AD groups. Significant predictors of hypometabolism were EPHA1 in the pooled, and SLC24A4/RIN3, NME8, and CD2AP in the normal control group. DISCUSSION: Multiple variants showed associations with GMD and brain metabolism. For most genes, the effects were limited to specific stages of the cognitive continuum, indicating that the genetic influences on brain metabolism and GMD in AD are complex and stage dependent.