Relative risks for general phenotypes and genetic models
Azra Kurbasic and Ola Hössjer
Centre for Mathematical Sciences
Lund Institute of Technology,
Many common diseases are known to have genetic components but since they
are non-Mendelian, i.e. a large number of genetic factors effect the phenotype,
these components are difficult to localize. These traits are often called
complex and analysis of siblings is a valuable tool for mapping. It has been
shown that the power of affected relative pairs method to detect linkage
of a disease susceptibility locus depends on the locus contribution to increased
risk of relatives compared with population prevalence [Risch, 1990a and 1990b].
In this paper we generalize calculation of relative risk to arbitrary phenotypes
and genetic models but also show that the relative risk can be split into
the relative risk at the main locus and the relative risk due to interaction
between the main locus and loci at other chromosomes. In order to achieve
power to detect linkage a certain number of relative pairs has to be collected.
To be able to quantify the amount of information of the relative pair we
use the effective number of meioses introduced in Hössjer , which
is closely related to power to detect linkage. Relative risks and effective
number of meioses are computed for several genetic models with binary or
quantitative phenotypes, with or without polygenic effects.
Complex diseases, relative risk, linkage analysis, effective number of meioses.