Use of parents, sibs, and unrelated controls for detection of associations between genetic markers and disease

Am J Hum Genet. 1998 Nov;63(5):1492-506. doi: 10.1086/302094.


Detecting the association between genetic markers and complex diseases can be a critical first step toward identification of the genetic basis of disease. Misleading associations can be avoided by choosing as controls the parents of diseased cases, but the availability of parents often limits this design to early-onset disease. Alternatively, sib controls offer a valid design. A general multivariate score statistic is presented, to detect the association between a multiallelic genetic marker locus and affection status; this general approach is applicable to designs that use parents as controls, sibs as controls, or even unrelated controls whose genotypes do not fit Hardy-Weinberg proportions or that pool any combination of these different designs. The benefit of this multivariate score statistic is that it will tend to be the most powerful method when multiple marker alleles are associated with affection status. To plan these types of studies, we present methods to compute sample size and power, allowing for varying sibship sizes, ascertainment criteria, and genetic models of risk. The results indicate that sib controls have less power than parental controls and that the power of sib controls can be increased by increasing either the number of affected sibs per sibship or the number of unaffected control sibs. The sample-size results indicate that the use of sib controls to test for associations, by use of either a single-marker locus or a genomewide screen, will be feasible for markers that have a dominant effect and for common alleles having a recessive effect. The results presented will be useful for investigators planning studies using sibs as controls.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Female
  • Gene Frequency
  • Genetic Diseases, Inborn / genetics*
  • Genetic Markers*
  • Genotype
  • Humans
  • Male
  • Models, Genetic*
  • Models, Statistical*
  • Nuclear Family*
  • Parents*


  • Genetic Markers