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Brain Commun
Published

Genome-wide association studies for Alzheimer's disease: bigger is not always better.

Authors

Valentina Escott-Price, John Hardy

Abstract

As the size of genome-wide association studies increase, the number of associated trait loci identified inevitably increase. One welcomes this if it allows the better delineation of the pathways to disease and increases the accuracy of genetic prediction of disease risk through polygenic risk score analysis. However, there are several problems in the continuing increase in the genome-wide analysis of 'Alzheimer's disease'. In this review, we have systematically assessed the history of Alzheimer's disease genome-wide association studies, including their sample sizes, age and selection/assessment criteria of cases and controls and heritability explained by these disease genome-wide association studies. We observe that nearly all earlier disease genome-wide association studies are now part of all current disease genome-wide association studies. In addition, the latest disease genome-wide association studies include (i) only a small fraction (∼10%) of clinically screened controls, substituting for them population-based samples which are systematically younger than cases, and (ii) around 50% of Alzheimer's disease cases are in fact 'proxy dementia cases'. As a consequence, the more genes the field finds, the less the heritability they explain. We highlight potential caveats this situation creates and discuss some of the consequences occurring when translating the newest Alzheimer's disease genome-wide association study results into basic research and/or clinical practice.

PMID:35663382 | DOI:10.1093/braincomms/fcac125

UK DRI Authors

Valentina Escott-Price

Prof Valentina Escott-Price

Group Leader

Using Big Data, machine learning and AI to accelerate discoveries into dementia

Prof Valentina Escott-Price
John Hardy

Prof Sir John Hardy

Group Leader

Harnessing genetics to build a better understanding of dementia

Prof Sir John Hardy