P3‐108: The application of snp profiling to the risk stratification for future cognitive decline in mild cognitive impairment (MCI)

Clinically, mild cognitive impairment (MCI) is a condition of subtle cognitive change which often, but by no means always, represents the first manifestation of Alzheimer's Disease (AD). Since we believe that we need to treat AD very early and we need to assess whether such early treatments work in slowing progression, we need to get better both at diagnosing those within the MCI cohort who have early AD and also identifying the variables which determine their rate of conversion to full blown disease. In both cases, genetic analysis is a promising route to this important clinical dissection. Our aim in this work is to identify genetic risk variants, or single nucleotide polymorphisms (SNPs), which can be used ultimately, in the definition of an algorithm to predict AD progression. In turn, this would be expected to facilitate AD clinical trials by reducing both misdiagnosis rates and enabling better prediction of expected disease progression rates. We are carrying out whole genome association analysis (testing genetic variants across the genome) using standard technologies developed over the last five years, in highly selected and characterised clinical samples. The output of our preliminary statistical analysis and modelling of data from cross-sectional AD and control subjects, suggests that the definition of a SNP panel and associated algorithm to distinguish these two groups may be possible. Further work is ongoing to assess whether sufficient sensitivity and specificity performance consistent with potential clinical utility, could be achieved.