Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture

• DOI: 10.1038/s41467-020-18534-1
• Publication Date: 2020-09-23T10:03:33Z
• Authors: Qian Zhang; Julia Sidorenko; Baptiste Couvy-Du...; Riccardo E. Marioni; Margaret J. Wright; Alison M. Goate; Edoardo Marcora; Kuan-lin Huang; Tenielle Porter; Simon M. Laws; ; Colin L. Masters; Ashley I. Bush; Christopher Fowler; David Darby; Kelly Pertile; Carolina Restrepo; Blaine Roberts; Jo Robertson; Rebecca Rumble; Tim Ryan; Steven Collins; Christine Thai; Brett Trounson; Kate Lennon; Qiao-Xin Li; Fernanda Yevenes ...; Irene Volitakis; Michael Vovos; Rob Williams; Jenalle Baker; Alyce Russell; Madeline Peretti; Lidija Milicic; Lucy Lim; Mark Rodrigues; Kevin Taddei; Tania Taddei; Eugene Hone; Florence Lim; Shane Fernandez; Stephanie Rainey-...; Steve Pedrini; Ralph Martins; James Doecke; Pierrick Bourgeat; Jurgen Fripp; Simon Gibson; Hugo Leroux; David Hanson; Vincent Dore; Ping Zhang; Samantha Burnham; Christopher C. Rowe; Victor L. Villemagne; Paul Yates; Sveltana Bozin Pe...; Gareth Jones; David Ames; Elizabeth Cyarto; Nicola Lautenschl...; Kevin Barnham; Lesley Cheng; Andy Hill; Neil Killeen; Paul Maruff; Brendan Silbert; Belinda Brown; Harmid Sohrabi; Greg Savage; Michael Vacher; Perminder S. Sachdev; Karen A. Mather; Nicola J. Armstrong; Anbupalam Thalamuthu; Henry Brodaty; Loic Yengo; Jian Yang; Naomi R. Wray; Allan F. McRae; Peter M. Visscher
• Keywords: Male; Aging; 4202 Epidemiology; anzsrc-for: 4202 Epidemiology; Neurodegenerative; Alzheimer's Disease; Genome-Wide Association; Australian Imaging Biomarkers and Lifestyle (AIBL) Study; Risk Factors; Medicine and Health Sciences; 2.1 Biological and endogenous factors; genetics; 3100 Physics and Astronomy; anzsrc-for: 31 Biological Sciences; Age of Onset; 0303 health sciences; anzsrc-for: 42 Health Sciences; Loci; Q; Epha1; Single Nucleotide; Alzheimer's disease; Metaanalysis; Middle Aged; 1600 Chemistry; genome informatics; Female; Cd2Ap; Adult; 1300 Biochemistry; Science; 610; Genetics and Molecular Biology; Insights; Polymorphism, Single Nucleotide; 3105 Genetics; Article; 03 medical and health sciences; Alzheimer Disease; Genetics; Acquired Cognitive Impairment; Humans; Genetic Predisposition to Disease; Polymorphism; Genetic Association Studies; Aged; Common Variants; Prevention; Parkinsons-Disease; Human Genome; Methodology; Immunity; Neurosciences; 42 Health Sciences; Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD); Brain Disorders; anzsrc-for: 3105 Genetics; genome-wide association studies; Dementia; 31 Biological Sciences

AbstractGenetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimalP-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.