GWAS-driven targeted resequencing of candidate genes to assess the impact of rare and low-frequency coding variation in restless legs syndrome

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Restless legs syndrome (RLS) is a common sleep-related movement disorder that affects up to 10% of the population in western societies. Despite its profound impact on health and quality of life, the underlying pathophysiology is still poorly understood. So far, genome-wide association studies (GWAS) of the disease have been the most promising approach because they provided the first molecular starting points to study the mechanisms at work.However, these GWAS assessed common, mostly non-coding variants, which have only modest effects on the phenotype, and, inherent to their design, only delineated genomic regions of interest (risk loci) instead of directly identifying causal genes and variants. Here, we aim to identify causal low-frequency and rare variants of potentially high impact on the phenotype. We will sequence coding regions of candidate genes selected from risk loci identified in our meta-analysis of the two largest GWAS in samples of European ancestry (unpublished data). Coding regions will be sequenced in 4,500 cases and 4,500 controls using molecular inversion probes (MIPs) to enrich the targeted sequences, followed by next-generation sequencing (NGS). Association analysis will be performed for individual low-frequency variants as well as by aggregating all variants across a gene in gene-based association tests. Studying low-frequency and rare coding variation in RLS has the potential to identify specific high-impact causal variants and genes. The molecular consequences of such variants will be straightforward to analyze in in-vivo and in-vitro functional assays such iPS cells or animal model to elucidate the pathophysiology of RLS. Finally, this facilitates the molecular analysis of a complex disease such as RLS and will deliver new targets for improved therapeutics or even preventive measures.