News Release, National Institutes of Health ,
by Dr. Francis Collins
Predicting whether someone will get Alzheimer’s disease (AD) late in life, and how to use that information for prevention, has been an intense focus of biomedical research. The goal of this work is to learn not only about the genes involved in AD, but how they work together and with other complex biological, environmental, and lifestyle factors to drive thisdevastating neurological disease.
It’s good news to be able to report that an international team of researchers, partly funded by NIH, has made more progress in explaining the genetic component of AD. Their analysis, involving data from more than 35,000 individuals with late-onset AD, has identified variants in five new genes that put people at greater risk of AD . It also points to molecular pathways involved in AD as possible avenues for prevention, and offers further confirmation of 20 other genes that had been implicated previously in AD.
The results of this largest-ever genomic study of AD suggests key roles for genes involved in the processing of beta-amyloid peptides, which form plaques in the brain recognized as an important early indicator of AD. They also offer the first evidence for a genetic link to proteins that bind tau, the protein responsible for telltale tangles in the AD brain thattrack closelywith a person’s cognitive decline.
The new findings are the latest from the International Genomics of Alzheimer’s Project (IGAP) consortium, led by a large, collaborative team including Brian Kunkle and Margaret Pericak-Vance, University of Miami Miller School of Medicine, Miami, FL. The effort, spanning four consortia focused on AD in the United States and Europe, was launched in 2011 with the aim of discovering and mapping all the genes that contribute to AD.
An earlier IGAP study including about 25,500 people with late-onset AD identified 20 common gene variants that influence a person’s risk for developing AD late in life . While that was terrific progress to be sure, the analysis also showed that those gene variants could explain only a third of the genetic component of AD. It was clear more genes with ties to AD were yet to be found.
So, in the study reported inNature Genetics, the researchers expanded the search. While so-calledgenome-wide association studies(GWAS) are generally useful in identifying gene variants that turn up often in association with particular diseases or other traits, the ones that arise more rarely require much larger sample sizes to find.
To increase their odds of finding additional variants, the researchers analyzed genomic data for more than 94,000 individuals, including more than 35,000 with a diagnosis of late-onset AD and another 60,000 older people without AD. Their search led them to variants in five additional genes, namedIQCK, ACE, ADAM10, ADAMTS1,andWWOX,associated with late-onset AD that hadn’t turned up in the previous study.
Further analysis of those genes supports a view of AD in which groups of genes work together to influence risk and disease progression. In addition to some genes influencing the processing of beta-amyloid peptides and accumulation of tau proteins, others appear to contribute to AD via certain aspects of the immune system and lipid metabolism.
Each of these newly discovered variants contributes only a small amount of increased risk, and therefore probably have limited value in predicting an average person’s risk of developing AD later in life. But they are invaluable when it comes to advancing our understanding of AD’s biological underpinnings and pointing the way to potentially new treatment approaches. For instance, these new data highlight intriguing similarities betweenearly-onsetand late-onset AD, suggesting that treatments developed for people with the early-onset form also might prove beneficial for people with the more common late-onset disease.
It’s worth noting that the new findings continue to suggest that the search is not yet over—many more as-yet undiscovered rare variants likely play a role in AD. The search for answers to AD and so many other complex health conditions—assisted through collaborative data sharing efforts such as this one—continues at an accelerating pace.