Polygenic score prediction captures nearly all common genetic risk for Alzheimer's disease.
We estimate the maximum prediction accuracy for the risk of Alzheimer's disease based on disease prevalence and heritability of liability. We demonstrate that the recently reported AUC values for predicting of Alzheimer's disease using polygenic scores reach about 90% of the estimated maximum accuracy that can be achieved by predictors of genetic risk based on genomic profiles.
Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK. Electronic address: EscottPriceV@cardiff.ac.uk.
Valentina
V
Escott-Price
Institute of Neurology, University College London, London, UK.
Maryam
M
Shoai
Cytox Ltd, UK, Oxford, UK.
Richard
R
Pither
Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK.
Julie
J
Williams
Institute of Neurology, University College London, London, UK. Electronic address: j.hardy@ucl.ac.uk.
John
J
Hardy
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000453:epidemiology / Q000235:genetics*; D019540:Area Under Curve; D005260:Female; D005544:Forecasting; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D006801:Humans; D008297:Male; D020412:Multifactorial Inheritance / Q000235:genetics*; D015995:Prevalence; D012372:ROC Curve; D012306:Risk
AUC; Heritability; Polygenic score