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dc.contributor.authorDaunt, P
dc.contributor.authorBallard, CG
dc.contributor.authorCreese, B
dc.contributor.authorDavidson, G
dc.contributor.authorHardy, J
dc.contributor.authorOshota, O
dc.contributor.authorPither, RJ
dc.contributor.authorGibson, AM
dc.date.accessioned2020-09-30T14:20:43Z
dc.date.issued2020-11-11
dc.description.abstractBACKGROUND: 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 yearsen_GB
dc.description.sponsorshipNational Institutes of Health (NIH)en_GB
dc.description.sponsorshipDepartment of Defenseen_GB
dc.description.sponsorshipInnovate UKen_GB
dc.identifier.citationPublished online 11 November 2020en_GB
dc.identifier.doi10.14283/jpad.2020.64
dc.identifier.grantnumberU01 AG024904en_GB
dc.identifier.grantnumberW81XWH-12-2-0012en_GB
dc.identifier.grantnumber5195en_GB
dc.identifier.urihttp://hdl.handle.net/10871/123040
dc.language.isoenen_GB
dc.publisherSpringer Natureen_GB
dc.rights© The Author(s) 2020. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
dc.subjectPolygenic risken_GB
dc.subjectcognitive declineen_GB
dc.subjectAlzheimer’s diseaseen_GB
dc.titlePolygenic Risk Scoring is an Effective Approach to Predict Those Individuals Most Likely to Decline Cognitively Due to Alzheimer’s Diseaseen_GB
dc.typeArticleen_GB
dc.date.available2020-09-30T14:20:43Z
dc.identifier.issn2274-5807
dc.descriptionThis is the final version. Available on open access from Springer Nature via the DOI in this recorden_GB
dc.identifier.journalThe Journal of Prevention of Alzheimer's Diseaseen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-09-30
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-09-30
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-09-30T14:00:45Z
refterms.versionFCDAM
refterms.dateFOA2020-11-25T15:22:59Z
refterms.panelAen_GB


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© The Author(s) 2020. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Except where otherwise noted, this item's licence is described as © The Author(s) 2020. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.