3 April 2011. Casting a larger net boosts the chance of landing fish. The same goes for genes. Over the last few years, researchers have been pushing genomewide association studies (GWAS) as a means to find genetic variants that put people at risk for Alzheimer’s disease. The strategy tallies hundreds of thousands of genetic variants in the genomes of thousands of people to identify those that more likely occur in AD patients than normal controls. Most of the catch is under legal size quotas—statistically speaking—and has to be tossed back into the gene pool. Those are the variants that fall short of genomewide significance. But enlarge the net and the chance of finding genuine risk genes grows. Indeed, this approach just paid off. In today’s Nature Genetics, two back-to-back papers report strong evidence for four new AD risk genes, and one that was previously linked to the disease in families. “It’s an exciting time for genetics,” said Christine Van Broeckhoven, University of Antwerp, Belgium, one of the many coauthors. “I’m really interested to see how this plays out for patients,” she told ARF.
In addition to new genes, the studies also confirmed ApoE4, the strongest risk gene for late-onset AD to date, and PICALM, CR1, CLU, and BIN1, genes previously identified in smaller genomewide analyses (see ARF related news story and ARF news story). This brings the total GWAS gene haul for case-control studies to 10, according to the authors. Genes previously claimed to be associated with AD in family and case-control GWAS include ATXN1 (Bertram et al., 2008 and Bettens et al., 2009), PCDH11X (Carrasquillo et al., 2009; Beecham et al., 2010), and MTHFD1L (Naj et al., 2010).
The new genes were not detected before simply because the samples were too few, said Gerard Schellenberg, University of Pennsylvania, senior author on one of the papers. Schellenberg and well over 100 colleagues at the Alzheimer’s Disease Genetics Consortium (ADGC), carried out a meta-analysis of datasets from previous cohorts to look at genomewide variation among 8,309 AD patients and 7,366 normal controls. Joint first authors Adam Naj, University of Miami, Florida, and Gyungah Jun, Boston University, Massachusetts, and colleagues then carried out two more replications of the analysis using yet different datasets, one comprising about 3,500 cases and roughly the same number of controls, while the third had almost 7,000 cases and roughly 24,600 controls. The latter were provided by the authors of the second study.
Those researchers, primarily in Europe and led by Julie Williams at Cardiff University in Wales, also carried out a three-stage meta-analysis. Step 1 comprised primarily European samples with some input from American datasets (total of almost 7,000 cases and just over 13,600 controls), while stage 2 added further samples from Iceland and Germany (almost 5,000 each of controls and AD samples). In stage 3 (8,200 cases and 21,200 controls), joint first authors Paul Hollingworth, Denise Harold, Rebecca Sima, and Amy Gerrish at Cardiff University, and Jean-Charles Lambert, University of North Lille, France, and Minerva Carrasquillo at the Mayo Clinic, Jacksonville, Florida, added a mix of samples from Europe and the U.S.
The two consortia came up with almost identical results. Both found that genetic variants in four genes—CD2AP, MS4A4/MS4A6E, EPHA1, and CD33—associated with AD. The data passed strict statistical standards for genomewide significance. CD33 was previously identified as a potential AD risk gene by researchers led by Rudy Tanzi at Massachusetts General Hospital, Charlestown (see ARF related news story on Bertram et al., 2008), though the variants identified by these latest GWAS and Tanzi’s group are different. Naj and colleagues were unable to find a link between the previously identified CD33 variant and AD, but noted that the two are in weak linkage disequilibrium, or in other words, not necessarily inherited together. The fifth gene identified, ABCA7, came only from the European study.
What does this news mean for the general public? The minor allele frequencies for the genes ranged from about 19 to 39 percent. The genetic variations are not uncommon, said Schellenberg, and may be in 20-30 percent of the population. Each susceptibility variant was associated with a small increase in risk for the disease of about 10-12 percent. ApoE4, by comparison, is believed to increase risk by two- to fourfold if one copy is inherited, and by up to 15-fold when two copies are present. Naj and colleagues calculated the population attributable fraction (PAF), or the percentage of Alzheimer’s cases that could be eliminated if the genetic risk factors were taken out of the picture, at between 3 and 6 percent for each of the nine non-ApoE genes and perhaps 30 percent for the nine combined. But Schellenberg cautioned that their study was not set up to address this question, and that the real PAF might be different. Williams reckons with all the genetic analysis done to date, scientists can now account for about 32 percent of the genetic risk for AD and about 20 percent of the total risk.
“Although the significance of any particular gene is relatively small, the biological significance is much bigger because we are finding definite pathways pointing in directions of disease mechanisms,” said Williams. There are now several genes that seem to play a role in lipid processing (ApoE4, ABCA7, CLU), in the immune system (CD33, CLU, CR1, ABCA7, and EPHA1), and in endocytosis or membrane trafficking (CD2AP, PICALM, BIN1, and CD33).
Tanzi agreed. “We are beginning to see binning or boxing of genes. For me, the most interesting is the innate immunity box,” he told ARF. In addition to the immune-related genes that have emerged from GWAS, there are also a number of other genes linked to AD in the AlzGene database that are intimately involved in immunity, including IL1A, IL1B, IL8, which is number 10 in the AlzGene hit parade, and TNFα.
Van Broeckhoven is optimistic that, going forward, even more genes will be found. Both consortia are now joining forces in a mega-meta-analysis. The International Genomics of Alzheimer’s Project, or IGAP (see ARF related news story) is already underway, and researchers expect to see the first analysis of that published within the year. Williams predicts that new genes will emerge that are in the same mechanistic pathways as those already discovered. “History shows that when you have done enough GWAS to get to the stage where we are now, that further, more powerful studies will confirm the pathway already identified,” she said. Genetic analysis of multiple sclerosis and Crohn’s disease bear this out.
With a huge dataset like the one IGAP is analyzing (roughly 20,000 cases and controls), van Broeckhoven predicts that researchers can begin to ask more detailed questions. For example, which genetic variants are linked to earlier age at onset, to fluid biomarkers, epigenetics? Which genes interact with each other? “There is so much work to be done,” said van Broeckhoven. “We don’t know if we will need a mouse model for every variant, or if a cell model will suffice.” When and how the GWAS information is translated into the clinic remains to be seen.—Tom Fagan.
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