Comparison of prospective and retrospective methods for haplotype inference in case‐control studies

Abstract

We compare bias and power of three methods for haplotype inference on disease risk using unphased genotype data from a case-control study. We examine the prospective score test of Schaid et al., a novel modification of the prospective estimating equations of Zhao et al. and the retrospective likelihood of Epstein and Satten. We find that all three approaches are roughly comparable when the haplotype effect on disease odds follows a multiplicative model. However, for dominant and recessive models of haplotype effect, the retrospective-likelihood method has increased efficiency with respect to the prospective methods. As all three methods assume haplotype frequencies are in Hardy-Weinberg Equilibrium (HWE), we compare the robustness of each procedure to departures from HWE. We find the prospective methods are robust to departure from HWE, while the retrospective-likelihood method is biased for dominant and recessive models of haplotype effect. To remedy this limitation of the retrospective-likelihood method, we propose a modification that allows for a non-negative fixation index (common to all haplotype pairs) and show it dramatically reduces the bias of the retrospective likelihood when HWE is violated.

Simple methods for assessing haplotype‐environment interactions in case‐only and case‐control studies

“…While the HWE assumption often holds, situations may arise where we would expect departure from HWE, such as when inbreeding occurs or when population stratification exists and is unaccounted for in analysis. In such situations, Satten and Epstein (2004) showed that departure from HWE in the target population can lead to incorrect inference on haplotype effects in retrospective approaches. To resolve this problem, we could model the departure from HWE by estimating a fixation index among the control participants, as described in Satten and Epstein [2004] and Lin and Zeng [2006].…”

“…In such situations, Satten and Epstein (2004) showed that departure from HWE in the target population can lead to incorrect inference on haplotype effects in retrospective approaches. To resolve this problem, we could model the departure from HWE by estimating a fixation index among the control participants, as described in Satten and Epstein [2004] and Lin and Zeng [2006]. Satten and Epstein [2004] showed that including a single fixation index in the haplotype distribution greatly diminished the bias even in simulated data where individual haplotype pairs had a different fixation index.…”

“…Lake et al [2003] developed a logistic-regression approach based on a prospective likelihood that modeled the probability of disease conditional on haplotype and environment. While the approach is easy to implement, its power may suffer with respect to an approach based on a retrospective likelihood that models the probability of haplotype and environment conditional on disease [Satten and Epstein, 2004]. This claim is in contrast to the well-known result of Prentice and Pyke [1979], who showed that the analysis of retrospective case-control data using a prospective likelihood should yield no loss of efficiency relative to the (more appropriate) retrospective likelihood.…”

Germline BCL-2 sequence variants and inherited predisposition to prostate cancer

“…Hardy-Weinberg equilibrium was evaluated in each group using a w 2 test for heterogeneity. BCL-2 haplotypes were estimated from the marker genotypes by a maximum likelihood ratio (LR) method using the CHAPLIN software, 25 which provides a LR statistic for testing the null hypothesis that there is no difference in the distribution of BCL-2 haplotypes between cases and controls. Logistic regression models were used to estimate the odds ratio (OR) and 95% confidence interval (CI) for the association between prostate cancer risk and BCL-2 genotypes and haplotypes, adjusting for potential confounders (i.e., age at the time of diagnosis for case subjects and at the time of ascertainment for controls), using the homozygous wild-type genotype as the reference group.…”

Haplotype Thinking in Lung Disease

“…A variety of haplotype-based association methods have been developed in both unrelated subjects (case-control or population-based) or in families; some of the more commonly used methods are listed in Table 1 (19,22,25,27,37,38). For example, Schaid and colleagues developed a regression-based score test for haplotype association in unrelated subjects that allows for testing of both global haplotype association and individual haplotype association as implemented in the Haplo.Stats program (19).…”