Estimating and testing haplotype-trait associations in non-diploid populations

Malaria is an infectious disease that is caused by a group of parasites of the genus Plasmodium. Characterizing the association between polymorphisms in the parasite genome and measured traits in an infected human host may provide insight into disease aetiology and ultimately inform new strategies for improved treatment and prevention. This, however, presents an analytic challenge since individuals are often multiply infected with a variable and unknown number of genetically diverse parasitic strains. In addition, data on the alignment of nucleotides on a single chromosome, which is commonly referred to as haplotypic phase, is not generally observed. An expectation-maximization algorithm for estimating and testing associations between haplotypes and quantitative traits has been described for diploid (human) populations. We extend this method to account for both the uncertainty in haplotypic phase and the variable and unknown number of infections in the malaria setting. Further extensions are described for the human immunodeficiency virus quasi-species setting. A simulation study is presented to characterize performance of the method. Application of this approach to data arising from a cross-sectional study of n=126 multiply infected children in Uganda reveals some interesting associations requiring further investigation.