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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Using case-parent triads to estimate relative risks associated with a candidate haplotype.

Min Shi¹, David M Umbach, Clarice R Weinberg

¹Biostatistics Branch, NIEHS, NIH, DHHS, Research Triangle Park, NC 27709, USA.

Annals of Human Genetics

|April 7, 2009

Summary

Estimating genetic risks from family studies is complex. This study introduces a log-linear model to assess candidate haplotype risks, offering flexibility with different population assumptions for improved accuracy.

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Area of Science:

Genetics
Statistical Genetics
Population Genetics

Background:

Estimating haplotype relative risks in family studies is challenging due to phase ambiguity and numerous parameters.
Previous research highlights the manageability of this problem when a specific haplotype is already linked to risk.

Purpose of the Study:

To develop and assess a log-linear modeling approach for estimating risks associated with a candidate haplotype relative to other haplotypes.
To evaluate the performance of the method under varying assumptions about haplotype distribution in the source population.

Main Methods:

Utilized existing haplotype-reconstruction algorithms within a log-linear model framework.
Assessed three levels of assumptions regarding haplotype distribution: Hardy-Weinberg Equilibrium (HWE), random mating, and no assumptions.
Performed simulations to evaluate performance across different risk haplotype frequencies, missing data patterns, and genetic effects (offspring or maternal).

Main Results:

The unconstrained model offers robustness to population structure but demands large sample sizes, especially with numerous haplotypes.
Assuming Hardy-Weinberg Equilibrium (HWE) allows for more haplotypes but reduces robustness.
The random mating model presents an intermediate balance between haplotype capacity and robustness.

Conclusions:

The developed log-linear model provides a flexible framework for estimating candidate haplotype risks in family-based studies.
The choice of population distribution assumptions (HWE, random mating, or unconstrained) impacts the trade-off between sample size requirements and robustness to population structure.
The method was illustrated using a 9-SNP haplotype analysis of the IRF6 gene in orofacial clefts data.