The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism

Eddie Stage; Tugce Duran; Shannon L Risacher; Naira Goukasian; Triet M Do; John D West; Holly Wilhalme; Kwangsik Nho; Meredith Phillips; David Elashoff; Andrew J Saykin; Liana G Apostolova

doi:10.1016/j.dadm.2016.12.003

The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism

Alzheimers Dement (Amst). 2016 Dec 19:5:53-66. doi: 10.1016/j.dadm.2016.12.003. eCollection 2016.

Authors

Affiliations

¹ Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.
² Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.
³ Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
⁴ Department of Medicine Statistics Core, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
⁵ Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medicine Statistics Core, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Indiana University Network Science Institute, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
⁶ Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.

Abstract

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.

Keywords: AD; ADNI; Alzheimer disease; Atrophy; Brain mapping; Brain metabolism; Fluorodeoxyglucose positron emission tomography (FDG PET); Genetic variation; Genome-wide association studies (GWAS); Imaging genetics; Magnetic resonance imaging (MRI); Positron emission tomography (PET); Risk genes; Statistical parametric mapping (SPM).

Abstract

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