Alzheimer’s Disease Genetics Consortium

Alzheimer’s Disease Genetics Consortium

Since 2010, Dr. Pericak-Vance has co-led the analysis teams for the Alzheimer’s Disease Genetics Consortium (ADGC), which includes nearly all of the nation’s researchers who are working on the genetics of Alzheimer’s Disease (AD), as well as many investigators and resources of the 29 federally funded Alzheimer’s Disease Centers. Funded by the National Institute on Aging, the ADGC has grown to include 44 universities and research institutions in the United States, reaching many research milestones during the last 6 years.

Milestones

2014: We confirmed an association of APOE variants with age at onset among affected participants with late-onset AD (LOAD) and observed novel associations of CR1 (OMIM 120620), BIN1, and PICALM (OMIM 603025) with age at onset. In contrast to earlier hypothetical modeling, we showed that the combined effects of AD risk variants on age at onset are on the scale of, but do not exceed, the APOE effect. (Naj et al., 2014)

2013: Eleven susceptibility loci for LOAD were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome wide association study (GWAS) in individuals of European ancestry. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with AD. (Lambert et al., 2013)

Because apolipoprotein-E gene (APOE) locus variants contribute to risk of LOAD and to differences in age at onset, it is important to know whether other established LOAD risk loci also affect age at onset in affected participants.

2011: The ADGC performed a GWAS of LOAD using a 3 stage design. This data was coordinated by the National Alzheimer’s Coordinating Center (NACC) with samples coordinated by the National Cell Repository for Alzheimer’s Disease (NCRAD). Genome-wide significant results were obtained, revealing four common variants associated with LOAD. (Naj et al., 2011)