The Relative Power of Family-Based and Case-Control Designs for Linkage Disequilibrium Studies of Complex Human Diseases I. DNA Pooling (original) (raw)

  1. Neil Risch1,2,3,4 and
  2. Jun Teng3
  3. Departments of 1Genetics and 2Health Research and Policy, Stanford University School of Medicine and3Department of Statistics, Stanford University, Stanford, California 94305 USA

Abstract

We consider statistics for analyzing a variety of family-based and nonfamily-based designs for detecting linkage disequilibrium of a marker with a disease susceptibility locus. These designs include sibships with parents, sibships without parents, and use of unrelated controls. We also provide formulas for and evaluate the relative power of different study designs using these statistics. In this first paper in the series, we derive statistical tests based on data derived from DNA pooling experiments and describe their characteristics. Although designs based on affected and unaffected sibs without parents are usually robust to population stratification, they suffer a loss of power compared with designs using parents or unrelateds as controls. Although increasing the number of unaffected sibs improves power, the increase is generally not substantial. Designs including sibships with multiple affected sibs are typically the most powerful, with any of these control groups, when the disease allele frequency is low. When the allele frequency is high, however, designs with unaffected sibs as controls do not retain this advantage. In designs with parents, having an affected parent has little impact on the power, except for rare dominant alleles, where the power is increased compared with families with no affected parents. Finally, we also demonstrate that for sibships with parents, only the parents require individual genotyping to derive the TDT statistic, whereas all the offspring can be pooled. This can potentially lead to considerable savings in genotyping, especially for multiplex sibships. The formulas and tables we derive should provide some guidance to investigators designing nuclear family-based linkage disequilibrium studies for complex diseases.

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