Estimating Disease Risk Associated with Mutated Genes in Family-Based Designs

Abstract

Objective: Many clinical decisions require accurate estimates of disease risk associated with inherited gene mutations. While several family-based designs have been proposed, their relative advantages remain unclear. Methods: We considered four commonly-used family-based designs and evaluated their performance in terms of accuracy and efficiency under several genetic models via simulation studies. We also derived and assessed several ascertainment-corrected likelihood methods for analyzing the simulated data and real data from 12 HNPCC pedigrees from Newfoundland. Results: We found that the design efficiency depends on the question of interest: the clinic-based family design with random probands yields the most efficient estimate of genetic relative risks, whereas the population-based family design with mutation carrier probands provides the most efficient penetrance estimates. For a particular question, an ascertainment correction seems possible using regular likelihood methods but the presence of genetic heterogeneity due to a strong second gene effect can lead to some bias in the risk estimation. Conclusions: This work gives a general methodological framework for analyzing family-based designs in gene characterization studies and provides more rationale for the choice of an efficient design and an appropriate likelihood method to estimate the risk associated with an inherited gene mutation.

The Dutch founder mutation SDHD.D92Y shows a reduced penetrance for the development of paragangliomas in a large multigenerational family

“…25,26 This could lead to overestimation of penetrance in SDHD-linked disease, especially when high-risk families are used for penetrance calculations. 25,27 In this respect, it is interesting to note that age-related penetrance estimates of SDHD-linked disease found in this study are lower compared with those reported by Benn et al and Neumann et al 15,16 This may reflect an upward bias in the latter two studies because of the inclusion of large numbers of index cases and relatively low numbers of asymptomatic mutation carriers. Further positive bias may have arisen in these studies because all risk factors tend to be overrepresented in case patients.…”

Estimating penetrance from multiple case families with predisposing mutations: extension of the ‘genotype-restricted likelihood’ (GRL) method

“…Regarding precision of the estimates, we showed that the standard errors in current situations were rather small, although retrospective likelihood methods are known to be poorly efficient. 21,22 We studied the robustness of the GRL to departures from underlying hypotheses. We found that the method was very robust to a misspecification of disease incidence in the general population, even for important errors.…”

“…25,26 Such an effect could affect major gene penetrance estimate. 22,27,28 The GRL will have to be extended to take into account such effects when better identified.…”

On Combining Family Data from Different Study Designs for Estimating Disease Risk Associated with Mutated Genes

“…In particular, ascertainment-corrected likelihood approaches have been developed by several authors (for example, Choi et al, 2008;Carayol & Bonaïti-Pellié, 2004;Kraft & Thomas, 2000;Le Bihan et al, 1995). Based on the survival approach, Le Bihan et al (1995) formulated a prospective likelihood for modeling phenotypes as the age of onset and disease status given genotypes, and corrected the likelihood by the probability of families being ascertained for study.…”

“…Although this approach provides the most robust way to obtain consistent estimates of relative risk even with the ascertainment schemes that are imprecisely defined or complex, it encounters the computational burden of summing over possible genotypes of all family members and a decreased efficiency resulting from conditioning. Choi et al (2008) adapted the retrospective likelihood conditioning only on phenotypes of individuals who were involved in the ascertainment criteria; for families sampled from the population-based designs, only probands were used to correct for the ascertainment, whereas for families from the clinic-based designs, the probands and their parents and sibs were used for ascertainment correction. Moreover, Schaid et al (2010) accommodated the composite likelihood approach to obtaining the retrospective likelihood based on all possible pairs of individuals in families to reduce the computational burden.…”