Nature Communications (Sep 2020)
Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture
- Qian Zhang,
- Julia Sidorenko,
- Baptiste Couvy-Duchesne,
- Riccardo E. Marioni,
- Margaret J. Wright,
- Alison M. Goate,
- Edoardo Marcora,
- Kuan-lin Huang,
- Tenielle Porter,
- Simon M. Laws,
- Australian Imaging Biomarkers and Lifestyle (AIBL) Study,
- 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
Affiliations
- Qian Zhang
- Institute for Molecular Bioscience, The University of Queensland
- Julia Sidorenko
- Institute for Molecular Bioscience, The University of Queensland
- Baptiste Couvy-Duchesne
- Institute for Molecular Bioscience, The University of Queensland
- Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh
- Margaret J. Wright
- Queensland Brain Institute, The University of Queensland
- Alison M. Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai
- Edoardo Marcora
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai
- Kuan-lin Huang
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai
- Tenielle Porter
- Collaborative Genomics Group, Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University
- Simon M. Laws
- Collaborative Genomics Group, Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University
- Australian Imaging Biomarkers and Lifestyle (AIBL) Study
- Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales
- Karen A. Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales
- Nicola J. Armstrong
- Department of Mathematics and Statistics, Murdoch University
- Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales
- Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales
- Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland
- Jian Yang
- Institute for Molecular Bioscience, The University of Queensland
- Naomi R. Wray
- Institute for Molecular Bioscience, The University of Queensland
- Allan F. McRae
- Institute for Molecular Bioscience, The University of Queensland
- Peter M. Visscher
- Institute for Molecular Bioscience, The University of Queensland
- DOI
- https://doi.org/10.1038/s41467-020-18534-1
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 11
Abstract
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.
