Polygenic Risk Scoring is an Effective Approach to Predict Those Individuals Most Likely to Decline Cognitively Due to Alzheimer’s Disease - 21/11/24

Doi : 10.14283/jpad.2020.64 
P. Daunt 1, C.G. Ballard 2, B. Creese 2, G. Davidson 3, J. Hardy 4, O. Oshota 1, R.J. Pither 1, Alex M. Gibson 1,

for the Alzheimer’s Disease Neuroimaging Initiative

1 John Eccles House, Cytox Ltd., Robert Robinson Avenue, Oxford Science Park, OX4 4GP, Oxford, UK 
2 University of Exeter Medical School, Exeter, UK 
3 Ledcourt Associates Limited, Cambridge, UK 
4 UK Dementia Research Institute, University College London, London, UK 

h alex.gibson@cytoxgroup.com

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Abstract

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.

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Key words : Polygenic risk, cognitive decline, Alzheimer’s disease


Mappa


 Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: ADNI_Acknowledgement_List.pdf
 Conflict of Interest: P. Daunt, A.Gibson, O.Oshota and R. Pither are all employees of Cytox Ltd. G. Davidson received payment from Cytox Ltd. for work done both within and outside the scope of this article.


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P. 78-83 - Gennaio 2021 Ritorno al numero
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