Abstract
Pedigrees collected for linkage studies are a valuable resource that could be used to estimate genetic relative risks (RRs) for genetic variants recently discovered in case-control genome wide association studies. To estimate RRs from highly ascertained pedigrees, a pedigree "retrospective likelihood" can be used, which adjusts for ascertainment by conditioning on the phenotypes of pedigree members. We explore a variety of approaches to compute the retrospective likelihood, and illustrate a Newton-Raphson method that is computationally efficient particularly for single nucleotide polymorphisms (SNPs) modeled as log-additive effect of alleles on the RR. We also illustrate, by simulations, that a naïve "composite likelihood" method that can lead to biased RR estimates, mainly by not conditioning on the ascertainment process - or as we propose - the disease status of all pedigree members. Applications of the retrospective likelihood to pedigrees collected for a prostate cancer linkage study and recently reported risk-SNPs illustrate the utility of our methods, with results showing that the RRs estimated from the highly ascertained pedigrees are consistent with odds ratios estimated in case-control studies. We also evaluate the potential impact of residual correlations of disease risk among family members due to shared unmeasured risk factors (genetic or environmental) by allowing for a random baseline risk parameter. When modeling only the affected family members in our data, there was little evidence for heterogeneity in baseline risks across families.
Original language | English (US) |
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Pages (from-to) | 287-298 |
Number of pages | 12 |
Journal | Genetic epidemiology |
Volume | 34 |
Issue number | 4 |
DOIs | |
State | Published - May 2010 |
Keywords
- Ascertainment
- Bias
- Composite likelihood
- Gene-dropping
- Linkage
- Prostate cancer
- Relative risk
ASJC Scopus subject areas
- Epidemiology
- Genetics(clinical)