Conditional Two-Locus NPL-Analysis: Theory and Applications
Centre for Mathematical Sciences
Lund Institute of Technology,
Type-2 diabetes is a serious, genetically influenced disease for which no
fully effective treatments are available (Gelder Ehm et al., 2000). The molecular
basis of type 2 diabetes is unknown, to a great extent because of the substantial
locus heterogeneity that is associated with diabetes risk (Gelder Ehm et
al., 2000) and Parker et al., 2001). However, studies indicate that a genetic
component exists. Type 2 diabetes is a complex disorder and therefore it
is assumed to depend on the actions and interactions of multiple genetic
and environmental factors (see for example Cox et al.,1999). Simultaneous
consideration of susceptibility from multiple regions may improve the possibility
to find genes that are involved in the mechanism behind a complex disorder.
In this work conditional two-locus NPL-analyses will be performed. That means
that one uses one-locus family scores from interesting regions (markers)
to weight the results from other regions and finally, as a result, get the
conditional two-locus NPL-score. This aims to find two correlated regions
in linkage with the disease. Theory that describes how to calculate p-values
under the null hypothesis of no linkage, which will make it possible to draw
conclusions about any possible significance of the results, will be described
and applied to the present data set. Aspects of robustness will be discussed.
The data set consists of 2606 individuals belonging to 337 families originating
from Sweden and Finland.