A pathway-based analysis provides additional support for an immune-related genetic susceptibility to Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease affecting 1-2% in people >60 and 3-4% in people >80. Genome-wide association (GWA) studies have now implicated significant evidence for association in at least 18 genomic regions. We have studied a large PD-meta analysis and identified a significant excess of SNPs (P < 1 × 10(-16)) that are associated with PD but fall short of the genome-wide significance threshold. This result was independent of variants at the 18 previously implicated regions and implies the presence of additional polygenic risk alleles. To understand how these loci increase risk of PD, we applied a pathway-based analysis, testing for biological functions that were significantly enriched for genes containing variants associated with PD. Analysing two independent GWA studies, we identified that both had a significant excess in the number of functional categories enriched for PD-associated genes (minimum P = 0.014 and P = 0.006, respectively). Moreover, 58 categories were significantly enriched for associated genes in both GWA studies (P < 0.001), implicating genes involved in the 'regulation of leucocyte/lymphocyte activity' and also 'cytokine-mediated signalling' as conferring an increased susceptibility to PD. These results were unaltered by the exclusion of all 178 genes that were present at the 18 genomic regions previously reported to be strongly associated with PD (including the HLA locus). Our findings, therefore, provide independent support to the strong association signal at the HLA locus and imply that the immune-related genetic susceptibility to PD is likely to be more widespread in the genome than previously appreciated.

Gene-wide analysis detects two new susceptibility genes for Alzheimer's disease.

BACKGROUND: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. PRINCIPAL FINDINGS: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. SIGNIFICANCE: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

Analysis of genome-wide association studies of Alzheimer disease and of Parkinson disease to determine if these 2 diseases share a common genetic risk.

IMPORTANCE: Despite Alzheimer disease (AD) and Parkinson disease (PD) being clinically distinct entities, there is a possibility of a pathological overlap, with some genome-wide association (GWA) studies suggesting that the 2 diseases represent a biological continuum. The application of GWA studies to idiopathic forms of AD and PD have identified a number of loci that contain genetic variants that increase the risk of these disorders. OBJECTIVE: To assess the genetic overlap between PD and AD by testing for the presence of potentially pleiotropic loci in 2 recent GWA studies of PD and AD. DESIGN: Combined GWA analysis. SETTING: Data sets from the United Kingdom, Germany, France, and the United States. PARTICIPANTS: Thousands of patients with AD or PD and their controls. MAIN OUTCOMES AND MEASURES: Meta-analysis of GWA studies of AD and PD. METHODS: To identify evidence for potentially pleiotropic alleles that increased the risk for both PD and AD, we performed a combined PD-AD meta-analysis and compared the results with those obtained in the primary GWA studies.We also tested for a net effect of potentially polygenic alleles that were shared by both disorders by performing a polygenic score analysis. Finally, we also performed a gene-based association analysis that was aimed at detecting genes that harbor multiple disease-causing single-nucleotide polymorphisms, some of which confer a risk of PD and some a risk of AD. RESULTS: Detailed interrogation of the single-nucleotide polymorphism, polygenic, and gene-based analyses resulted in no significant evidence that supported the presence of loci that increase the risk of both PD and AD. CONCLUSIONS AND RELEVANCE: Our findings therefore imply that loci that increase the risk of both PD and AD are not widespread and that the pathological overlap could instead be "downstream" of the primary susceptibility genes that increase the risk of each disease.

Permutation-based approaches do not adequately allow for linkage disequilibrium in gene-wide multi-locus association analysis.

Additional information about risk genes or risk pathways for diseases can be extracted from genome-wide association studies through analyses of groups of markers. The most commonly employed approaches involve combining individual marker data by adding the test statistics, or summing the logarithms of their P-values, and then using permutation testing to derive empirical P-values that allow for the statistical dependence of single-marker tests arising from linkage disequilibrium (LD). In the present study, we use simulated data to show that these approaches fail to reflect the structure of the sampling error, and the effect of this is to give undue weight to correlated markers. We show that the results obtained are internally inconsistent in the presence of strong LD, and are externally inconsistent with the results derived from multi-locus analysis. We also show that the results obtained from regression and multivariate Hotelling T(2) (H-T2) testing, but not those obtained from permutations, are consistent with the theoretically expected distributions, and that the H-T2 test has greater power to detect gene-wide associations in real datasets. Finally, we show that while the results from permutation testing can be made to approximate those from regression and multivariate Hotelling T(2) testing through aggressive LD pruning of markers, this comes at the cost of loss of information. We conclude that when conducting multi-locus analyses of sets of single-nucleotide polymorphisms, regression or multivariate Hotelling T(2) testing, which give equivalent results, are preferable to the other more commonly applied approaches.