Heritability and genetic association analysis of neuroimaging measures in the Diabetes Heart Study

NEUROBIOLOGY OF AGING

卷:36

Article

Raffield, Laura M.^1,2,3  Cox, Amanda J.^2,3,4  Hugenschmidt, Christina E.⁵  Freedman, Barry I.⁶  Langefeld, Carl D.⁷  Williamson, Jeff D.⁵  Hsu, Fang-Chi⁷  Maldjian, Joseph A.⁸  Bowden, Donald W.^2,3,4 

[1] Wake Forest Sch Med, Mol Genet & Genom Program, Winston Salem, NC 27157 USA

[2] Wake Forest Sch Med, Ctr Genom & Personalized Med Res, Winston Salem, NC 27157 USA

[3] Wake Forest Sch Med, Ctr Diabet Res, Winston Salem, NC 27157 USA

[4] Wake Forest Sch Med, Dept Biochem, Winston Salem, NC 27157 USA

[5] Wake Forest Sch Med, Dept Gerontol & Geriatr, Winston Salem, NC 27157 USA

[6] Wake Forest Sch Med, Dept Internal Med Nephrol, Winston Salem, NC 27157 USA

[7] Wake Forest Sch Med, Dept Biostat Sci, Winston Salem, NC 27157 USA

[8] Wake Forest Sch Med, Dept Radiol, Winston Salem, NC 27157 USA

关键词: Magnetic resonance imaging;    Type 2 diabetes;    Genetics;    Heritability;   

DOI  :  10.1016/j.neurobiolaging.2014.11.008

来源: Elsevier

【 摘 要 】

Patients with type 2 diabetes are at increased risk of age-related cognitive decline and dementia. Neuroimaging measures such as white matter lesion volume, brain volume, and fractional anisotropy may reflect the pathogenesis of these cognitive declines, and genetic factors may contribute to variability in these measures. This study examined multiple neuroimaging measures in 465 participants from 238 families with extensive genotype data in the type 2 diabetes enriched Diabetes Heart Study-Mind cohort. Heritability of these phenotypes and their association with candidate single-nucleotide polymorphisms (SNPs), and SNP data from genome-and exome-wide arrays were explored. All neuroimaging measures analyzed were significantly heritable ((h) over cap (2) = 0.55-0.99 in unadjusted models). Seventeen candidate SNPs (from 16 genes/regions) associated with neuroimaging phenotypes in prior studies showed no significant evidence of association. A missense variant (rs150706952, A432V) in PLEKHG4B from the exome-wide array was significantly associated with white matter mean diffusivity (p = 3.66 x 10(-7)) and gray matter mean diffusivity (p = 2.14 x 10(-7)). This analysis suggests genetic factors contribute to variation in neuroimaging measures in a population enriched for metabolic disease and other associated comorbidities. (C) 2015 Elsevier Inc. All rights reserved.

【 授权许可】

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