QTL analysis of longitudinal quantitative trait data in complex pedigrees

¹ Cardiff University
² University of Edinburgh
³ Queensland Institute of Medical Research

^* To whom correspondence should be addressed. E-mail: macgregors{at}cf.ac.uk.

Submitted on March 30, 2005
Revised on June 21, 2005
Accepted on 7 July 2005

	Abstract

There is currently considerable interest in genetic analysis of quantitative traits such as blood pressure and Body Mass Index. Despite the fact that these traits change throughout life they are commonly only analyzed at a single time point. The genetic basis of such traits can be better understood by collecting and effectively analyzing longitudinal data. Analyses of these data are complicated by the need to incorporate information from complex pedigree structures and genetic markers. We propose conducting longitudinal quantitative trait locus (QTL) analyses on such data sets by using a flexible random regression estimation technique. The relationship between genetic effects at different ages is efficiently modelled using covariance functions (CFs). Using simulated data we show that the change in genetic effects over time can be well characterized using CFs and that including parameters to model the change in effect with age can provide substantial increases in power to detect QTL compared with repeated measure or univariate techniques. The asymptotic distributions of the methods used are investigated and methods for overcoming the practical difficulties in fitting CFs are discussed. The CF based techniques should allow efficient multivariate analyses of many data sets in human and natural population genetics.

Key Words: Complex pedigrees, Covariance function, Multivariate, QTL, Random regression

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