This article is a US government work, and, as such, is in the public domain in the United States of America.
On combining family and case-control studies†
Article first published online: 2 MAY 2008
Published 2008 Wiley-Liss, Inc.
Volume 32, Issue 7, pages 638–646, November 2008
How to Cite
Pfeiffer, R. M., Pee, D. and Landi, M. T. (2008), On combining family and case-control studies. Genet. Epidemiol., 32: 638–646. doi: 10.1002/gepi.20338
- Issue published online: 27 OCT 2008
- Article first published online: 2 MAY 2008
- Manuscript Accepted: 10 MAR 2008
- Manuscript Revised: 7 FEB 2008
- Manuscript Received: 14 NOV 2007
- nested random effects model;
- marginal model;
- family history;
- stratified sampling
Studies to detect genetic association with disease can be family-based, often using families with multiple affected members, or population based, as in population-based case-control studies. If data on both study types are available from the same population, it is useful to combine them to improve power to detect genetic associations. Two aspects of the data need to be accommodated, the sampling scheme and potential residual correlations among family members. We propose two approaches for combining data from a case-control study and a family study that collected families with multiple cases. In the first approach, we view a family as the sampling unit and specify the joint likelihood for the family members using a two-level mixed effects model to account for random familial effects and for residual genetic correlations among family members. The ascertainment of the families is accommodated by conditioning on the ascertainment event. The individuals in the case-control study are treated as families of size one, and their unconditional likelihood is combined with the conditional likelihood for the families. This approach yields subject specific maximum likelihood estimates of covariate effects. In the second approach, we view an individual as the sampling unit. The sampling scheme is accommodated using two-phase sampling techniques, marginal covariate effects are estimated, and correlations among family members are accounted for in the variance calculations. The models are compared in simulations. Data from a case-control and a family study from north-eastern Italy on melanoma and a low-risk melanoma-susceptibility gene, MC1R, are used to illustrate the approaches. Genet. Epidemiol. 2008. Published 2008 Wiley-Liss, Inc.