Genome-wide association study confirms SNPs in SNCA and the MAPT region as common risk factors for Parkinson disease.

Parkinson disease (PD) is a chronic neurodegenerative disorder with a cumulative prevalence of greater than one per thousand. To date three independent genome-wide association studies (GWAS) have investigated the genetic susceptibility to PD. These studies implicated several genes as PD risk loci with strong, but not genome-wide significant, associations. In this study, we combined data from two previously published GWAS of Caucasian subjects with our GWAS of 604 cases and 619 controls for a joint analysis with a combined sample size of 1752 cases and 1745 controls. SNPs in SNCA (rs2736990, p-value = 6.7 x 10(-8); genome-wide adjusted p = 0.0109, odds ratio (OR) = 1.29 [95% CI: 1.17-1.42] G vs. A allele, population attributable risk percent (PAR%) = 12%) and the MAPT region (rs11012, p-value = 5.6 x 10(-8); genome-wide adjusted p = 0.0079, OR = 0.70 [95% CI: 0.62-0.79] T vs. C allele, PAR%= 8%) were genome-wide significant. No other SNPs were genome-wide significant in this analysis. This study confirms that SNCA and the MAPT region are major genes whose common variants are influencing risk of PD.

Exome sequencing of a multigenerational human pedigree.

Over the next few years, the efficient use of next-generation sequencing (NGS) in human genetics research will depend heavily upon the effective mechanisms for the selective enrichment of genomic regions of interest. Recently, comprehensive exome capture arrays have become available for targeting approximately 33 Mb or approximately 180,000 coding exons across the human genome. Selective genomic enrichment of the human exome offers an attractive option for new experimental designs aiming to quickly identify potential disease-associated genetic variants, especially in family-based studies. We have evaluated a 2.1 M feature human exome capture array on eight individuals from a three-generation family pedigree. We were able to cover up to 98% of the targeted bases at a long-read sequence read depth of > or = 3, 86% at a read depth of > or = 10, and over 50% of all targets were covered with > or = 20 reads. We identified up to 14,284 SNPs and small indels per individual exome, with up to 1,679 of these representing putative novel polymorphisms. Applying the conservative genotype calling approach HCDiff, the average rate of detection of a variant allele based on Illumina 1 M BeadChips genotypes was 95.2% at > or = 10x sequence. Further, we propose an advantageous genotype calling strategy for low covered targets that empirically determines cut-off thresholds at a given coverage depth based on existing genotype data. Application of this method was able to detect >99% of SNPs covered > or = 8x. Our results offer guidance for "real-world" applications in human genetics and provide further evidence that microarray-based exome capture is an efficient and reliable method to enrich for chromosomal regions of interest in next-generation sequencing experiments.