Estimating heritability using family and unrelated individuals data

Case Western Reserve University School of Medicine, 2103 Cornell Road, Cleveland, OH 44106, USA. .
BMC proceedings 11/2011; 5 Suppl 9(Suppl 9):S34. DOI: 10.1186/1753-6561-5-S9-S34
Source: PubMed


For the family data from Genetic Analysis Workshop 17, we obtained heritability estimates of quantitative traits Q1 and Q4 using the ASSOC program in the S.A.G.E. software package. ASSOC is a family-based method that estimates heritability through the estimation of variance components. The covariate-adjusted mean heritability was 0.650 for Q1 and 0.745 for Q4. For the unrelated individuals data, we estimated the heritability of Q1 as the proportion of total variance that can be accounted for by all single-nucleotide polymorphisms under an additive model. We examined a novel ordinary least-squares method, a naïve restricted maximum-likelihood method, and a calibrated restricted maximum-likelihood method. We applied the different methods to all 200 replicates for Q1. We observed that the ordinary least-squares method yielded many estimates outside the interval [0, 1]. The restricted maximum-likelihood estimates were more stable than the ordinary least-squares estimates. The naïve restricted maximum-likelihood method yielded an average estimate of 0.462 ± 0.1, and the calibrated restricted maximum-likelihood method yielded an average of 0.535 ± 0.121. Our results demonstrate discrepancies in heritability estimates using the family data and the unrelated individuals data.

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    • "Heritability was estimated for Q1 using the population-based (200 replicates) and the family-based (4 random replicates) designs, adjusting for age, sex, and the smoking status [Shetty et al., 2011] (Table I–C). In the family-based design, heritability was estimated using a polygenic mixed effect model applying the George-Elston transformation to normalize the distribution of residuals obtained after adjustment for age, sex, and smoking status [George and Elston, 1988]. "
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