Alzheimer’s disease (AD) is a highly prevalent form of dementia – the genetic variations underlying the disease are poorly understood and the number and effectiveness of drug therapies is very limited. This study underlines the potential of health data science to make progress in tackling major healthcare issues. It demonstrates that the analysis of larger samples, from electronic health records (EHRs), than have previously been used can result in a better understanding of AD, and potentially contribute to the search for better treatments.
Late onset Alzheimer’s disease (LOAD) is a polygenic illness affecting those over 65. Predictions suggest that it is likely to largely be caused by around 300 genetic variants. Until recently just 31 genetic risk loci had been identified. With around 50%-70% of UK dementia patients having AD, it is a major healthcare and societal problem and advances in understanding and treatment are essential.
This research recognised that analysing data from larger numbers of patients than had been used in previous research would increase the statistical power to identify other causal variants and might also highlight additional disease mechanisms.
A team including Douglas P. Wightman, a PhD student at Vrije Universiteit, Amsterdam, carried out a meta-analysis on a sample of 1,126,563 people (combining 13 cohorts) from the UK, Europe and the USA. This included AD patients supplemented by proxy cases – people with a high hereditary predisposition to the disease.
Their results were recently published in Nature Genetics.
Impact and outcomes
The study identified 38 genetic risk loci for LOAD, confirming the known 31 and adding seven that were new. Five had not previously been associated with any form of dementia. The seven previously unidentified loci were functionally annotated and fine-mapped to help narrow down candidate causal genes.
A highly promising aspect of the research is the insights it offers into the role of genes that are important in the immune system.
The research points to potentially fruitful new approaches to AD research and paves the way for pharmaceutical companies to consider whether they already have drugs available that could be useful.
Mr Wightman said:
“If you know which genes are important, and you know an existing drug targets one of those genes, you can try that drug and see if it’s beneficial.”
The project was carried out on an open science basis and the data is available to be shared with other researchers.
Future work is planned that will focus on fine-mapping and generating larger databases in more specific cells types. Much of the work to date has looked at AD in people of European ancestry and it is hoped that this will be broadened in future.
The HDR UK Impact Committee chose this paper for its excellence, significance, originality and rigour. And for its potential to contribute to the identification of further genetic variants that contribute to Alzheimer’s pathology.
Professor Danielle Posthuma firstname.lastname@example.org
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