Genetic Variation Underlying Traumatic Brain Injury and Late-Onset Alzheimer's
disease
 
   Lead Investigator:    Sandra Barral
   Institution      :    Columbia U
   E-Mail           :    smb2174@cumc.columbia.edu
   Proposal ID      :    738



   Proposal Description:
   Our proposal has two main goals, first, to provide a better understanding of      the genetic architecture and the underlying association between Traumatic Brain   Injury (TBI) and Late-Onset Alzheimer???s Disease (LOAD) and second, to aid in    the need of diagnostic test to detect the progression to AD and subsequent TBI.   There is a significant deficit in the literature investigating the possible       association between Traumatic Brain Injury (TBI) and increased susceptibility     to develop Late-Onset Alzheimer???s Disease (LOAD) later in life.                 Genetic variation has been investigated as a potential modulator of association   between (TBI) and increased susceptibility to develop LOAD later in life,         however, no specific genes have been discovered. Identifying individuals at       higher risk of developing AD after TBI (carriers of the identified high risk      genetic variants), will aid the prognosis and early detection of disease and      subsequent therapeutic decisions.                                                 We hypothesize that genetic risk factors interact with exposure to TBI to         modify risk of LOAD.                                                              Our specific aims for this proposal are:                                          ??? To characterize trajectories of memory change in subjects stratified by       LOAD and TBI status using the longitudinal data in 4,878 samples from the         National Alzheimer Coordinating Center (NACC).                                    ??? To identify genes that interact with TBI and modify risk associated with      LOAD using a genome-wide gene-based interaction approach.                         o To identify genome-wide TBI-interacting genes that predict risk of LOAD using   the non-stratified sample from the National Alzheimer Coordinating Center         (NACC).                                                                           o To assess nominally significan