Opinion

VIEWPOINT

Manu Sharma, PhD Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany, and Institute for Clinical Epidemiology and Applied Biometry, University of Tübingen, Tübingen, Germany. Rejko Krüger, MD Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany. Thomas Gasser, MD Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany.

Corresponding Author: Manu Sharma, PhD, Hertie Institute of Clinical Brain Research, Department of Neurology, University of Tübingen, Hoppe-Seyler-Strasse 3, 72076 Tübingen, Germany (manu.sharma @uni-tuebingen.de).

From Genome-Wide Association Studies to Next-Generation Sequencing Lessons From the Past and Planning for the Future The question whether common or rare variants will eventually help us understand the genetic architecture of complex diseases, including neurodegenerative disorders, is currently being debated. Recently published studies of Alzheimer disease (AD) and Parkinson disease (PD) are suggesting the role of common and rare variants in both disorders.

GWAS and Missing Heritability “Are we ready for genome-wide association studies?” This question was asked in 2006 to raise issues about genome-wide association studies (GWAS).1 Since then, more than 9000 studies have been published, which led to the discovery and replication of many novel loci for diverse phenotypes, highlighting the success of GWAS, and lending support to the “common disease–common variant” (CDCV) hypothesis. The CDCV hypothesis postulates that a significant proportion of phenotypic variance in a population is due to common variants, suggesting that susceptibility for a given trait is largely due to common variants. Typically, the variants included in standard arrays for GWAS are single-nucleotide polymorphisms (SNPs), selected for having minor allele frequencies greater than 5%. They are thought to detect most of the genetic risk for a given disease contributed by common variants. However, despite the success of GWAS in defining robust risk factors for complex diseases, this approach explains still only a fraction of the heritability of these common diseases, even when very large sample sizes are analyzed.2 Currently, 2 possible explanations are being discussed for this missing or yet-to-be identified heritability. First, most of the GWAS performed so far have not been able to sufficiently capture SNPs, which are on the lower end of the frequency spectrum. Commonly used array chips poorly tag low-frequency variants through linkage disequilibrium, and hence GWAS are unable to detect rare susceptibility variants. Second, the overwhelming number of published GWAS have mainly involved white populations, precluding a large proportion of genetic variability contributing to specific diseases in different populations worldwide. Differences in the allelic architecture and historical recombination events are important factors that influence the ease at which putative risk factors can be mapped in different populations. These factors may influence the ability to detect disease-related variants in one population as compared with another. Such differences among different ethnic populations have been illustrated by the recent discovery of an association with PD at a new putative locus at chromosome 1 (PARK16) in the Japanese popula-

tion. The associated SNP, rs823128, has a minor allele frequency of approximately 20% in the Japanese population as compared with only 3% in the white population. With this minor allele frequency, individual GWAS in white populations have very little power to detect an association, even though the SNP is well tagged with the arrays.3 Using 1000 Genomes and HapMap data as a reference sample to impute genotypes of untyped markers (ie, to increase genomic coverage) and to perform GWASbased meta-analysis for diverse phenotypes is now routine. This approach already allowed for the discovery of new putative loci for different complex disorders that have been missed in initial GWAS. The cataloguing of common and uncommon variants in conjunction with efforts to diversify genomic research in ethnically diverse populations that are so far underrepresented, such as south Asian and African populations, will eventually increase the heritability estimates in complex diseases.

Exome and Whole-Genome Sequencing In contrast to the CDCV hypothesis, the alternative view, “common disease–rare variants” (CDRV), has been postulated to explain the missing heritability. The CDRV hypothesis states that multiple rare variants (with minor allele frequencies

From genome-wide association studies to next-generation sequencing: lessons from the past and planning for the future.

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