Background Genome-wide association studies (GWASs) in Parkinson's disease (PD) have increased the scope of biological knowledge about the disease over the past decade. We sought to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into disease etiology. Methods We performed the largest meta-GWAS of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases (having a first degree relative with PD), and 1.4M controls. We carried out a meta-analysis of this GWAS data to nominate novel loci. We then evaluated heritable risk estimates and predictive models using this data. We also utilized large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type and biological pathway enrichments for the identified risk factors. Additionally we examined shared genetic risk between PD and other phenotypes of interest via genetic correlations followed by Mendelian randomization. Findings We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of PD depending on prevalence. Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. Mendelian randomization between cognitive performance and PD risk showed a robust association. Interpretation These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified. Funding See supplemental materials (Text S2). lead to earlier detection and refined diagnostics, which may help improve clinical trials (4). The generation of copious amounts of public summary statistics created by this effort relating to both the GWAS and subsequent analyses of gene expression and methylation patterns may be of use to investigators planning follow-up functional studies in stem cells or other cellular screens, allowing them to prioritize targets more efficiently using our data as additional evidence. We hope our findings may have some downstream clinical impact in the future such as improved patient stratification for clinical trials and genetically informed drug targets.

Genome-wide association (GWA) studies have identified a large number of single-nucleotide polymorphisms (SNPs) associated with disease phenotypes. As most GWA studies have been performed primarily in populations of European descent, this review examines the issues involved in extending consideration of GWA studies to diverse worldwide populations. Although challenges exist with such issues as imputation, admixture, and replication, investigation of diverse populations in GWA studies has significant potential to advance the project of mapping the genetic determinants of complex diseases for the human population as a whole.In the last few years, genome-wide association (GWA) studies have produced numerous successes in identifying genetic variants that contribute to complex human traits1 , 2. Several factors are recognized3 , 4 as having dramatically enlarged the number of genotypephenotype associations documented for a wide range of phenotypes5 , 6. These include: increasingly dense sets of genetic markers, increasingly large sample sizes, improved resources on genomic variation, and new statistical techniques for genotype imputation 7 , 8 and meta-analysis9 , 10 that leverage these resources.With few exceptions, however, GWA studies have been centered in populations of European descent (Box 1), and the degree to which knowledge gained from these studies is transferrable to other populations has not been extensively investigated. Recent reports such populations as Chinese11 , 12, Japanese13 , 14, Koreans15 , 16, and Pacific islanders from Kosrae17 , 18 represent some of the first in a new wave of GWA studies in non-European populations, as researchers seek to search additional groups for new findings on widely distributed phenotypes, to consider new phenotypes that are more prevalent in non-European populations, and to establish the generality of findings obtained initially in Europeans and European Americans. NIH Public Access Author ManuscriptNat Rev Genet. Author manuscript; available in PMC 2011 May 1. Populations in past GWA studiesTo assess the extent to which non-European populations have been incorporated into GWA studies, we examined the distribution of study populations across 492 GWA articles in the National Human Genome Research Institute catalog of GWA results6 , 130. This database provides a manually curated list of SNP-phenotype associations (P < 10 −5 ) identified in studies with at least 100,000 SNPs. Article classifications were assessed independently by two raters, with discrepancies resolved by consensus in discussions with a third rater. The figure on the right tabulates classifications based on whether articles used individuals of European descent, individuals of non-European descent, or a combination of individuals of European and non-European descent. Eight articles that provided insufficient information about study subjects are omitted, so that each bar represents 80 or 81 articles, grouped by date. The later date ranges are narrower, indicating that in more recent time periods, ...

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Despite the wide range of skin pigmentation in humans, little is known about its genetic basis in global populations. Examining ethnically diverse African genomes, we identify variants in or near SLC24A5, MFSD12, DDB1, TMEM138, OCA2 and HERC2 that are significantly associated with skin pigmentation. Genetic evidence indicates that the light pigmentation variant at SLC24A5 was introduced into East Africa by gene flow from non-Africans. At all other loci, variants associated with dark pigmentation in Africans are identical by descent in southern Asian and Australo-Melanesian populations. Functional analyses indicate that MFSD12 encodes a lysosomal protein that affects melanogenesis in zebrafish and mice, and that mutations in melanocyte-specific regulatory regions near DDB1/TMEM138 correlate with expression of UV response genes under selection in Eurasians.

According to historical records of transatlantic slavery, traders forcibly deported an estimated 12.5 million people from ports along the Atlantic coastline of Africa between the 16th and 19th centuries, with global impacts reaching to the present day, more than a century and a half after slavery’s abolition. Such records have fueled a broad understanding of the forced migration from Africa to the Americas yet remain underexplored in concert with genetic data. Here, we analyzed genotype array data from 50,281 research participants, which—combined with historical shipping documents—illustrate that the current genetic landscape of the Americas is largely concordant with expectations derived from documentation of slave voyages. For instance, genetic connections between people in slave trading regions of Africa and disembarkation regions of the Americas generally mirror the proportion of individuals forcibly moved between those regions. While some discordances can be explained by additional records of deportations within the Americas, other discordances yield insights into variable survival rates and timing of arrival of enslaved people from specific regions of Africa. Furthermore, the greater contribution of African women to the gene pool compared to African men varies across the Americas, consistent with literature documenting regional differences in slavery practices. This investigation of the transatlantic slave trade, which is broad in scope in terms of both datasets and analyses, establishes genetic links between individuals in the Americas and populations across Atlantic Africa, yielding a more comprehensive understanding of the African roots of peoples of the Americas.