Two-Stage Extreme Phenotype Sequencing Design for Discovering and Testing Common and Rare Genetic Variants: Efficiency and Power

Abstract

Next-generation sequencing technology provides an unprecedented opportunity to identify rare susceptibility variants. It is not yet financially feasible to perform whole-genome sequencing on a large number of subjects, and a two-stage design has been advocated to be a practical option. In stage I, variants are discovered by sequencing the whole genomes of a small number of carefully selected individuals. In stage II, the discovered variants of a large number of individuals are genotyped to assess associations. Individuals with extreme phenotypes are typically selected in stage I. Using simulated data for unrelated individuals, we explore two important aspects of this two-stage design: the efficiency of discovering common and rare single-nucleotide polymorphisms (SNPs) in stage I and the impact of incomplete SNP discovery in stage I on the power of testing associations in stage II. We applied a sum test and a sum of squared score test for gene-based association analyses evaluating the power of the two-stage design. We obtained the following results from extensive simulation studies and analysis of the GAW17 dataset. When individuals with trait values more extreme than the 99.7–99th quantile were included in stage I, the two-stage design could achieve the same power as or even higher than the one-stage design if the rare causal variants had large effect sizes. In such design, fewer than half of the total SNPs including more than half of the causal SNPs were discovered, which included nearly all SNPs with minor allele frequencies (MAFs) ≥5%, more than half of the SNPs with MAFs between 1% and 5%, and fewer than half of the SNPs with MAFs <1%. Although a one-stage design may be preferable to identify multiple rare variants having small to moderate effect sizes, our observations support using the two-stage design as a cost-effective option for next-generation sequencing studies.

Cancer pharmacogenomics: strategies and challenges

“…Under the extreme phenotype hypothesis, one approach to reduce the amount of sequencing required is to sequence only individuals in the upper and lower tails of a phenotypic distribution 84–86 . For example, the therapeutic dose of a particular drug may vary tenfold between the 5% of patients that are most sensitive and the 5% of patients that are most resistant: both of these sets of patients may be enriched for the genetic variants that contribute to differences in drug sensitivity 87 .…”

Focused Analysis of Exome Sequencing Data for Rare Germline Mutations in Familial and Sporadic Lung Cancer

“…Rare variants, with minor allele frequencies (MAFs) of less than 0.01, and with modest to high effect sizes [5–7], might play a crucial role in the etiology of complex traits and could account for missing heritability unexplained by common variants.…”

Phenotypic extremes in rare variant study designs

“…Studies have shown that extreme sampling can enrich for the presence of causal variants 16,17 and, furthermore, that extreme phenotypic sampling and/or a twostage analysis can lead to gains in power. [17][18][19] Lee et al 20 compare available gene-based tests and discuss design strategies for RVASs. Meta-analysis frameworks have been proposed to combine individual variant score statistics across studies and reconstruct gene-based tests, 21 but this may lead to biases when selection, sequencing, and quality control differ between studies.…”