This article is part of the supplement: Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors
Comparison of the linkage results of two phenotypic constructs from longitudinal data in the Framingham Heart Study: analyses on data measured at three time points and on the average of three measurements
1 Columbia Genome Center, Columbia University, 1150 St. Nicholas Avenue, New York, New York, USA
2 New York State Psychiatric Institute, Columbia University, 1051 Riverside Drive, New York, New York, USA
3 Department of Epidemiology, Columbia University, New York, New York, USA
BMC Genetics 2003, 4(Suppl 1):S20 doi:10.1186/1471-2156-4-S1-S20Published: 31 December 2003
Family studies are often conducted in a cross-sectional manner without long-term follow-up data. The relative contribution of a gene to a specific trait could change over the lifetime. The Framingham Heart Study offers a unique opportunity to investigate potential gene × time interaction. We performed linkage analysis on the body mass index (BMI) measured in 1970, 1978, and 1986 for this project.
We analyzed the data in two different ways: three genome-wide linkage analyses on each exam, and one genome-wide linkage analysis on the mean of the three measurements. Variance-component linkage analyses were performed by the SOLAR program. Genome-wide scans show consistent evidence of linkage of quantitative trait loci (QTLs) on chromosomes 3, 6, 9, and 16 in three measurements with a maximum multipoint LOD score > 2.2. However, only chromosome 9 has a LOD score = 2.14 when the mean values were analyzed. More interestingly, we found potential gene × environment interactions: increasing LOD scores with age on chromosomes 3, 9, and 16 and decreasing LOD scores on chromosome 6 in the three exams.
The results indicate two points: 1) it is possible that a gene (or genes) influencing BMI is (are) up- or down-regulated as people aged due to aging process or changes in lifestyle, environments, or genetic epistasis; 2) using mean values from longitudinal data may reduce the power to detect linkage and may have no power to detect gene × time, and/or gene × gene interactions.