More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinson's disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of ∼27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P<5×10−8) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P = 1.3×10−8). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.

This study provides compelling independent evidence that genetic variants in CLU, CR1, and PICALM are genetically associated with risk for AD. Furthermore, the CSF biomarker analyses provide a first insight into the potentially predominant pathogenetic mechanism(s) underlying the association between AD risk and PICALM.

Spatial navigation relies on multiple mnemonic mechanisms and previous work in younger adults has described two separate types of spatial memory. One type uses directional as well as boundary-related information for spatial memory and mainly implicates the hippocampal formation. The other type has been linked to directional and landmark-related information and primarily involves the striatum. Using a virtual reality navigation paradigm, we studied the impacts of aging and a single nucleotide polymorphism (SNP rs17070145) of the KIBRA gene (official name: WWC1) on these memory forms. Our data showed that older adult's spatial learning was preferentially related to processing of landmark information, whereas processing of boundary information played a more prominent role in younger adults. Moreover, among older adults T-allele carriers of the examined KIBRA polymorphism showed better spatial learning compared to C homozygotes. Together these findings provide the first evidence for an effect of the KIBRA rs17070145 polymorphism on spatial memory in humans and age differences in the reliance on landmark and boundary-related spatial information.

The genetics of Alzheimer’s disease (AD) is heterogeneous and remains only ill-defined. We have recently created a freely available and continuously updated online database (AlzGene; http://www.alzgene.org) for which we collect all published genetic association studies in AD and perform systematic meta-analyses on all polymorphisms with sufficient genotype data. In this study, we tested 27 genes (ACE, BDNF, CH25H, CHRNB2, CST3, CTSD, DAPK1, GALP, hCG2039140, IL1B, LMNA, LOC439999, LOC651924, MAPT, MTHFR, MYH13, PCK1, PGBD1, PRNP, PSEN1, SORCS1, SORL1, TF, TFAM, TNK1, GWA_14q32.13, and GWA_7p15.2), all showing significant association with AD risk in the AlzGene meta-analyses, in a large collection of family-based samples comprised of 4,180 subjects from over 1,300 pedigrees. Overall, we observe significant association with risk for AD and polymorphisms in ACE, CHRNB2, TF, and an as yet uncharacterized locus on chromosome 7p15.2 [rs1859849]. For all four loci, the association was observed with the same alleles as in the AlzGene meta-analyses. The convergence of case–control and family-based findings suggests that these loci currently represent the most promising AD gene candidates. Further fine-mapping and functional analyses are warranted to elucidate the potential biochemical mechanisms and epidemiological relevance of these genes.