Polygenic risk score analysis of pathologically confirmed Alzheimer disease

Previous estimates of the utility of polygenic risk score analysis for the prediction of Alzheimer disease have given area under the curve (AUC) estimates of <80%. However, these have been based on the genetic analysis of clinical case–control series. Here, we apply the same analytic approaches t...

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Bibliographic Details
Published inAnnals of neurology Vol. 82; no. 2; pp. 311 - 314
Main Authors Escott‐Price, Valentina, Myers, Amanda J., Huentelman, Matt, Hardy, John
Format Journal Article
LanguageEnglish
Published United States Wiley Subscription Services, Inc 01.08.2017
Subjects
Alzheimer Disease - diagnosis
Alzheimer Disease - genetics
Alzheimer Disease - pathology
Alzheimer's disease
Area Under Curve
Genetic analysis
Genetic Predisposition to Disease - genetics
Genome-Wide Association Study
Humans
Models, Genetic
Multifactorial Inheritance
Neurodegenerative diseases
Polymorphism, Single Nucleotide - genetics
Predictive control
Risk analysis
Risk Assessment - methods
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Summary:Previous estimates of the utility of polygenic risk score analysis for the prediction of Alzheimer disease have given area under the curve (AUC) estimates of <80%. However, these have been based on the genetic analysis of clinical case–control series. Here, we apply the same analytic approaches to a pathological case–control series and show a predictive AUC of 84%. We suggest that this analysis has clinical utility and that there is limited room for further improvement using genetic data. Ann Neurol 2017;82:311–314.
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ISSN:0364-5134
1531-8249
1531-8249
DOI:10.1002/ana.24999