Annals of Human Genetics

Table of Contents - 1998 - Volume 62, Issue 06  


Genetic linkage analysis using lognormal variance components

Y. WAN a1c1, M. DE ANDRADE a2, L. YU a2, J. COHEN a3 and C. I. AMOS a2
a1 Department of Internal Medicine, The University of Texas Houston Medical School, 6411 Fannin, RPV 673, Houston, Texas 77030, USA
a2 Department of Epidemiology, The University of Texas, M.D. Anderson Cancer Center, Houston, Texas 77030, USA
a3 Center for Human Nutrition, The University of Texas, Southwestern Medical Center, Dallas, Texas 75235, USA

Abstract

Typically genetic studies of continuous traits such as cholesterol levels or blood pressure assume that interindividual variability follows a normal distribution. Here we develop methods to analyze positively skewed data by assuming a lognormal distribution. We develop a variance components approach for identifying such effects from a major gene, residual polygenic factors and nongenetic factors. We compare by a simulation study results from fitting this lognormal model with either applying the log transformation or not transforming the data. We found that the lognormal model provided more precise estimates and more powerful tests than a simple log transformation when analyzing lognormally distributed data. Power varied with sibship size. For the same total number of nonindependent sibpairs, larger sibships were less powerful. However, larger sibships are more economical because they require a smaller sample size to obtain a specified power. To illustrate the application of this lognormal model to real data, we studied evidence for linkage between triglycerides and the lipoprotein lipase gene.

(Received July 13 1998)
(Accepted November 29 1998)


Correspondence:
c1 Corresponding Author: Ying Wan, Ph.D. at Department of Internal Medicine, The University of Texas Houston Medical School, University Clinical Research Center, 6411 Fannin, RPV 673, Houston, Texas 77030, USA. Tel: 713-704-0378. Fax: 713-704-6417. E-mail: ywan@heart.med.uth.tmc.edu

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