title: Alzheimer's disease genetics current status and future perspectives.
abstract: Alzheimer's disease (AD) is a genetically complex disease whose pathogenesis is largely influenced by genetic factors. Three decades of intensive research have yielded four established AD genes (APP, PSEN1, PSEN2, APOE), and hundreds of potential susceptibility loci, none of which has been unequivocally shown to modify disease risk using conventional methodologies. The results of genome-wide association studies (GWAS) are now adding to an already vast and complicated body of data. To facilitate the evaluation and interpretation of these findings, we have recently created a database for genetic association studies in AD ("AlzGene"; available at http://www.alzgene.org). In addition to systematically screening and summarizing the scientific literature for eligible studies, AlzGene provides the results of allele-based meta-analyses for all polymorphisms with sufficient genotype data. Currently, these meta-analyses highlight over 20 different potential AD genes, several of which were originally implicated by a GWAS. First follow-up analyses in a large collection of over 1300 AD families reveal that-in addition to APOE-genetic variants in ACE, CHRNB2, GAB2, and TF show the most consistent risk effects across a wide range of independent samples and study designs. The chapter highlights these and other promising findings from the recent AD genetics literature and provides an overview of the powerful new tools aiding researchers today to unravel the genetic underpinnings of this devastating disease.
authors.affiliation: Neuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max-Planck Institute for Molecular Genetics, Berlin 14195, Germany.
authors.forename: Lars
authors.initials: L
authors.lastname: Bertram
mesh_terms: D000544:Alzheimer Disease / Q000209:etiology / Q000235:genetics*; D000818:Animals; D016206:Databases, Bibliographic / Q000706:statistics & numerical data / Q000639:trends; D055106:Genome-Wide Association Study / Q000379:methods* / Q000639:trends*; D006801:Humans; D015201:Meta-Analysis as Topic; D008954:Models, Biological