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P1‐059: MAPT haplotypes modify the association between head injury and risk of Alzheimer's disease
Author(s) -
Tsuang Debby,
Vardarajan Badri N.,
Bird Thomas D.,
Boeve Bradley,
Schaid Daniel,
Taner Nilufer,
Allen Mariet,
Barral Sandra,
Bennett David A.,
Cruchaga Carlos,
Goate Alison,
Graff-Radford Neil,
Faber Kelly,
Farlow Martin R.,
Foroud Tatiana M.,
Ottman Ruth,
Rosenberg Roger N.,
Rumbaugh Malia,
Sano Mary,
Schellenberg Gerard D.,
Silverman Jeremy M.,
Sweet Robert,
Mayeux Richard
Publication year - 2015
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2015.06.256
Subject(s) - haplotype , disease , apolipoprotein e , head injury , alzheimer's disease , allele , tau protein , medicine , genetics , biology , psychiatry , gene
Background:Alzheimer’s disease (AD) is a complex disease in which the quest for causative genes has been challenging. In this search, genome-wide studies (GWAS) have been a valuable tool, being able to investigate, through thousands of markers, associations with the disease or with its endophenotypes. However, GWAS analyses almost always use cross-sectional data. Despite the adversities of obtaining and analyzing longitudinal data, the information about the disease progress can be of great importance. For this reason, we have searched for genetic markers associated with changes in brain amyloid (Ab) load and glucose uptake. Methods: [F]Florbetapir positron emission tomography (PET) imaging was employed to assess brain Ab levels in 412 participants from the Alzheimer’s Disease Neuroimaging Initiative, whilst glucose uptake was measured using [F]fludeoxyglucose PET (FDG) in 419 subjects from the same cohort. The genotypes were obtained with IlluminaHumanOmni2.5 beadchip. After quality control in both imaging and genetic data, a GWAS was performed. The phenotypes used were the differences between global SUVR in the baseline and 24 months follow-up of [F]florbetapir and FDG. Covariates as diagnostic status and baseline SUVR were added in the genetic analysis. The Bonferroni threshold of genome-wide significance is 3.9x10. Values higher then 3.9x10 but less then 10were considered trends of association. Results: None of the SNPs reached genome-wide significance, however trends of association are reported here (Figure 1). Ab accumulation shows a trend with 24 markers from 15 genes, in which probably the most relevant, and significant, is PLCH1. Brain hipometabolism indicate trend associations with 21 markers from 8 genes. The genes TTC39B and NRP1were the most significant. Conclusions: The major genes reported to be associated with AD were not found in the present study. Interestingly, Ab accumulation seems to be related to the PLCH1 gene, which encodes for a phospholipase-C family-member. Phospholipases are important enzymes with key roles in cell signaling. Another relevant result may be the association of hypometabolism with the TTC39B gene. Its function is not clear, however this gene has been related to lipid metabolism. Further studies with bigger sample size would be necessary to confirm present results.