This article is a US Government work and, as such, is in the public domain in the United States of America.
Analysis of metabolic syndrome phenotypes in Framingham Heart Study families from Genetic Analysis Workshop 13†
Article first published online: 14 NOV 2003
Published 2003 Wiley-Liss, Inc.
Supplement: Genetic Analysis Workshop 13
Volume 25, Issue Supplement 1, pages S78–S89, 2003
How to Cite
Goldin, L. R., Camp, N. J., Keen, K. J., Martin, L. J., Moslehi, R., Ghosh, S., North, K. E., Wyszynski, D. F. and Blacker, D. (2003), Analysis of metabolic syndrome phenotypes in Framingham Heart Study families from Genetic Analysis Workshop 13. Genet. Epidemiol., 25: S78–S89. doi: 10.1002/gepi.10288
- Issue published online: 14 NOV 2003
- Article first published online: 14 NOV 2003
- metabolic syndrome;
- longitudinal measures;
- linkage methods;
- susceptibility genes
Twelve teams of investigators constituted a group which analyzed phenotypes related to metabolic syndrome, making use of the available longitudinal measurements from the family component of the Framingham Heart Study or the simulated data, as distributed by Genetic Analysis Workshop 13 (GAW13). Body mass index, obesity, lipid abnormalities, glucose, or combinations of these traits were analyzed by this group. A wide variety of approaches were taken to construct phenotypes from the longitudinal measurements, including considering single or multiple cross-sectional time points, single ages, minimum values, maximum values, means, other lifetime values, ever/never dichotomy, or age at onset of some threshold value. Approaches also differed in the family structures utilized (sib pairs to full extended pedigrees), the genetic data considered (two-point or multipoint), and the statistics calculated (model-free and parametric), and led to a diverse set of analyses being performed. Inferences were made about heritability, and attempts were made to map underlying genes. Over 40 genome-wide linkage analyses were conducted. Despite the broad range of approaches, several regions of the genome were repeatedly identified across multiple analyses. Genet Epidemiol 25 (Suppl. 1):S78–S89, 2003. Published 2003 Wiley-Liss, Inc.