1. Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture
- Author
-
Henry Brodaty, Riccardo E. Marioni, Julia Sidorenko, Tenielle Porter, Peter M. Visscher, Edoardo Marcora, Naomi R. Wray, Allan F. McRae, Qian Zhang, Alison Goate, Kuan-lin Huang, Nicola J. Armstrong, Baptiste Couvy-Duchesne, Loic Yengo, Karen A. Mather, Simon M. Laws, Jian Yang, Margaret J. Wright, Australian Imaging Biomarkers, Anbupalam Thalamuthu, Perminder S. Sachdev, and Lifestyle (Aibl) Study
- Subjects
0301 basic medicine ,Adult ,Male ,Science ,General Physics and Astronomy ,Genome-wide association study ,Single-nucleotide polymorphism ,Disease ,Biology ,Genome informatics ,Genome-wide association studies ,Polymorphism, Single Nucleotide ,General Biochemistry, Genetics and Molecular Biology ,Article ,Odds ,Decile ,03 medical and health sciences ,0302 clinical medicine ,Alzheimer Disease ,Risk Factors ,Statistics ,Genetics ,Humans ,Genetic Predisposition to Disease ,Age of Onset ,lcsh:Science ,Genetic Association Studies ,Genetic association ,Aged ,Multidisciplinary ,fungi ,General Chemistry ,Alzheimer's disease ,Middle Aged ,Genetic architecture ,030104 developmental biology ,lcsh:Q ,Female ,Age of onset ,030217 neurology & neurosurgery - Abstract
Genetic 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 optimal P-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., Despite the identification of genetic risk loci for late-onset Alzheimer’s disease (LOAD), the genetic architecture and prediction remains unclear. Here, the authors use genetic risk scores for prediction of LOAD across three datasets and show evidence suggesting oligogenic variant architecture for this disease.
- Published
- 2020