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Title: Genome-wide linkage analysis of longitudinal phenotypes using sigma(2)(A) random effects (SSARs) fitted by Gibbs sampling
Authors: Palmer, L. J.
Scurrah, Katrina J.
Tobin, Martin
Patel, S. R.
Celedon, J. C.
Burton, Paul R.
Weiss, S. T.
First Published: 31-Dec-2003
Presented at: Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors New Orleans Marriott Hotel, New Orleans, LA, USA, November 11–14, 2002
Publisher: BioMed Central
Citation: BMC Genetics, 2003, 4
Abstract: The study of change in intermediate phenotypes over time is important in genetics. In this paper we explore a new approach to phenotype definition in the genetic analysis of longitudinal phenotypes. We utilized data from the longitudinal Framingham Heart Study Family Cohort to investigate the familial aggregation and evidence for linkage to change in systolic blood pressure (SBP) over time. We used Gibbs sampling to derive sigma-squared-A-random-effects (SSARs) for the longitudinal phenotype, and then used these as a new phenotype in subsequent genome-wide linkage analyses. Additive genetic effects (σ2A.time) were estimated to account for ~9.2% of the variance in the rate of change of SBP with age, while additive genetic effects (σ2A) were estimated to account for ~43.9% of the variance in SBP at the mean age. The linkage results suggested that one or more major loci regulating change in SBP over time may localize to chromosomes 2, 3, 4, 6, 10, 11, 17, and 19. The results also suggested that one or more major loci regulating level of SBP may localize to chromosomes 3, 8, and 14. Our results support a genetic component to both SBP and change in SBP with age, and are consistent with a complex, multifactorial susceptibility to the development of hypertension. The use of SSARs derived from quantitative traits as input to a conventional linkage analysis appears to be valuable in the linkage analysis of genetically complex traits. We have now demonstrated in this paper the use of SSARs in the context of longitudinal family data.
DOI Link: 10.1186/1471-2156-4-S1-S12
ISSN: 1471-2156
eISSN: 1471-2156
Type: Journal Article
Rights: © 2003 Palmer et al; licensee BioMed Central Ltd This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Version of record:
Appears in Collections:Published Articles, Dept. of Health Sciences

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