Two-Locus Nonparametric Linkage Analysis for Complex Diseases

Markus Kämpe

Handledare: Ola Hössjer

Centre for Mathematical Sciences
Mathematical Statistics
Lund Institute of Technology,
Lund University,

Disorders such as diabetes, cardiovascular disease, asthma, psoriasis, cancer, and schizophrenia all appear to have inheritable components (Cox et al. 1999 and Risch 1990).
In Many genetic diseases have complex modes of inheritance (Ploughmann 1989). This thesis the utility of a two-locus nonparametric linkage (NPL) approach is compared to the one-locus NPL analysis. Recent studies show that by taking correlation between one-locus NPL-scores at two loci into account in the analysis of diabetes more information can be extracted when two-locus score functions upweighting positive correlation are used (Cox et al. 1999). In particular focus in this thesis is on finding a disease model giving positive correlation between the one-locus NPL-scores at the two disease loci considered.
The pedigree structure used consists of two parents with unknown affection status and two affected offspring, i.e. an affected sib-pair. In the NPL analysis allele sharing identical by decent is considered and to simulate genotypes for the pedigree members additive, multiplicative, and heterogenic disease models among others are used.