Polygenic Risk Scoring is an Effective Approach to Predict Those Individuals Most Likely to Decline Cognitively Due to Alzheimer’s Disease

Abstract

Copyright © The Author(s) 2020. 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/Aßl-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.