BACKGROUND: There is a clear need for simple and effective tests to identify individuals
who are most likely to develop Alzheimer’s Disease (AD) both for the purposes of clinical
trial recruitment but also for improved management of patients who may be experiencing
early pre-clinical symptoms or who have clinical concerns.
OBJECTIVES: ...
BACKGROUND: There is a clear need for simple and effective tests to identify individuals
who are most likely to develop Alzheimer’s Disease (AD) both for the purposes of clinical
trial recruitment but also for improved management of patients who may be experiencing
early pre-clinical symptoms or who have clinical concerns.
OBJECTIVES: To predict individuals at greatest risk of progression of cognitive
impairment due to Alzheimer’s Disease in individuals from the Alzheimer’s Disease
Neuroimaging Initiative (ADNI) using a polygenic risk scoring algorithm. To compare the
performance of a PRS algorithm in predicting cognitive decline against that of using the
pTau/Aẞ1-42 ratio CSF biomarker profile.
DESIGN: A longitudinal analysis of data from the Alzheimer’s Disease Neuroimaging
Initiative study conducted across over 50 sites in the US and Canada
SETTING: Multi-center genetics study
PARTICPANTS: 515 subjects who upon entry to the study were diagnosed as cognitively
normal or with mild cognitive impairment
MEASUREMENTS: Use of genotyping and/or whole genome sequencing data to calculate
polygenic risk scores and assess ability to predict subsequent cognitive decline as measured
by CDR-SB and ADAS-Cog13 over 4 years
RESULTS: The overall performance for predicting those individuals who would decline by
at least 15 ADAS-Cog13 points from a baseline mild cognitive impairment in 4 years was
72.8% (CI:67.9-77.7) AUC increasing to 79.1% (CI: 75.6-82.6) when also including
cognitively normal participants. Assessing mild cognitive impaired subjects only and using a
threshold of greater than 0.6, the high genetic risk participant group declined, on average, by
1.4 points (CDR-SB) more than the low risk group over 4 years. The performance of the
PRS algorithm tested was similar to that of the pTau/Aẞ1-42 ratio CSF biomarker profile in
predicting cognitive decline.
CONCLUSION: Calculating polygenic risk scores offers a simple and effective way, using
DNA extracted from a simple mouth swab, to select mild cognitively impaired patients who
are most likely to decline cognitively over the next four years