Genes play a strong role in Alzheimer’s disease (AD), with late-onset AD showing heritability of 58–79% and early-onset AD showing over 90%. Genetic association provides a robust platform to build our understanding of the etiology of this complex disease. Over 50 loci are now implicated for AD, suggesting that AD is a disease of multiple components, as supported by pathway analyses (immunity, endocytosis, cholesterol transport, ubiquitination, amyloid-β and tau processing). Over 50% of late-onset AD heritability has been captured, allowing researchers to calculate the accumulation of AD genetic risk through polygenic risk scores. A polygenic risk score predicts disease with up to 90% accuracy and is an exciting tool in our research armory that could allow selection of those with high polygenic risk scores for clinical trials and precision medicine. It could also allow cellular modelling of the combined risk. Here we propose the multiplex model as a new perspective from which to understand AD. The multiplex model reflects the combination of some, or all, of these model components (genetic and environmental), in a tissue-specific manner, to trigger or sustain a disease cascade, which ultimately results in the cell and synaptic loss observed in AD.
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Cardiff University was supported by the UK Dementia Research Institute at Cardiff (MC_PC_17112), Medical Research Council MR/K013041/1), the Alzheimer’s Society, Alzheimer’s Research UK (ARUK-NC2018-WAL), Dementia Platform UK (HQR00720), the European Joint Programme for Neurodegenerative Disease (MR/N029402/1), the Welsh Assembly Government, Centre for Ageing & Dementia Research (SGR544:CADR) and a donation from the Moondance Charitable Foundation. We thank T. D. Cushion, G. Leonenko, J. Harwood and B. Lan-Leung for their support preparing this manuscript. Finally, we thank all patients and affected families for their continued generosity and willingness to participate in medical research; without their involvement, there would be no advancement in our knowledge of disease genetics.
The authors declare no competing interests.
Peer review information Nature Neuroscience thanks Mina Ryten and Bryan Traynor for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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