Abstract
This Genetic Analysis Workshop 13 contribution presents a linkage analysis of hypertension in the Framingham data based on the posterior probability of linkage, or PPL. We dichotomized the phenotype, coding individuals who had been treated for hypertension at any time, as well as those with repeated high blood pressure measurements, as affected. Here we use a new variation on the multipoint PPL that incorporates integration over the genetic model. PPLs were computed for chromosomes 1 through 5, 11, 14, and 17 and remained below the 2% assumed prior probability of linkage for 73% of the locations examined. The maximum PPL of 4.5% was obtained on chromosome 1 at 178 cM. Although this is more than twice the assumed prior probability of linkage, it is well below a level at which we would recommend committing substantial additional resources to molecular follow-up. While the PPL analysis of this data remains inconclusive, Bayesian methodology gives us a clear mechanism for using the information gained here in further studies.
Highlights
The posterior probability of linkage, or PPL, has several advantages over other parametric methods [1]
As a Bayesian statistic, can incorporate any prior information that the researcher might have before the outset of a study
Multipoint LOD scores are computed by a series of programs that make repeated calls to GENEHUNTER [12], varying the values of the genetic model in each run
Summary
The posterior probability of linkage, or PPL, has several advantages over other parametric methods [1]. It is directly interpretable as the probability of linkage to a specific marker or location along the genome. Using integration in this way allows us to avoid the inflationary effects on the likelihood of maximizing over multiple parameters. This makes the model-integrated PPL an ideal tool for the analysis of complex diseases such as hypertension. This represents the first analysis using a model-integrated version of the PPL based on multipoint likelihoods. The multipoint PPL gives us an indication of whether or not there is a disease gene close to each position on the chromosome [2], in contrast to the two-point version [1,3,4,5], which estimates the probability of linkage to each marker individually
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