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Eero Lindholm

Associate professor

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Power in the Phenotypic Extremes: A Simulation Study of Power in Discovery and Replication of Rare Variants

Author

  • Lin T. Guey
  • Jasmina Kravic
  • Olle Melander
  • Noel P. Burtt
  • Jason M. Laramie
  • Valeriya Lyssenko
  • Anna Jonsson
  • Eero Lindholm
  • Tiinamaija Tuomi
  • Bo Isomaa
  • Peter Nilsson
  • Peter Almgren
  • Sekar Kathiresan
  • Leif Groop
  • Albert B. Seymour
  • David Altshuler
  • Benjamin F. Voight

Summary, in English

Next-generation sequencing technologies are making it possible to study the role of rare variants in human disease. Many studies balance statistical power with cost-effectiveness by (a) sampling from phenotypic extremes and (b) utilizing a two-stage design. Two-stage designs include a broad-based discovery phase and selection of a subset of potential causal genes/variants to be further examined in independent samples. We evaluate three parameters: first, the gain in statistical power due to extreme sampling to discover causal variants; second, the informativeness of initial (Phase I) association statistics to select genes/variants for follow-up; third, the impact of extreme and random sampling in (Phase 2) replication. We present a quantitative method to select individuals from the phenotypic extremes of a binary trait, and simulate disease association studies under a variety of sample sizes and sampling schemes. First, we find that while studies sampling from extremes have excellent power to discover rare variants, they have limited power to associate them to phenotype-suggesting high false-negative rates for upcoming studies. Second, consistent with previous studies, we find that the effect sizes estimated in these studies are expected to be systematically larger compared with the overall population effect size; in a well-cited lipids study, we estimate the reported effect to be twofold larger. Third, replication studies require large samples from the general population to have sufficient power; extreme sampling could reduce the required sample size as much as fourfold. Our observations offer practical guidance for the design and interpretation of studies that utilize extreme sampling. Genet. Epidemiol. 35: 236-246, 2011. (c) 2011 Wiley-Liss, Inc.

Department/s

  • Genomics, Diabetes and Endocrinology
  • Cardiovascular Research - Hypertension
  • Internal Medicine - Epidemiology
  • EXODIAB: Excellence in Diabetes Research in Sweden
  • EpiHealth: Epidemiology for Health

Publishing year

2011

Language

English

Pages

236-246

Publication/Series

Genetic Epidemiology

Volume

35

Issue

4

Document type

Journal article

Publisher

John Wiley and Sons

Topic

  • Other Clinical Medicine
  • Cardiac and Cardiovascular Systems
  • Endocrinology and Diabetes

Keywords

  • * next-generation sequencing* liability ascertainment* variant discovery* replication of association* phenotype extremes

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology
  • Cardiovascular Research - Hypertension
  • Internal Medicine - Epidemiology

ISBN/ISSN/Other

  • ISSN: 0741-0395