Comprehensive linkage and linkage heterogeneity analysis of 4344 sibling pairs affected with hypertension from the Family Blood Pressure Program

Tiffany A. Greenwood, Ondrej Libiger, Sharon Kardia, Craig Hanis, Alanna C. Morrison, C. Charles Gu, Treva Rice, Michael Miller, Stephen T. Turner, Richard H. Myers, John Grove, Chin Fu Hsiao, Alan B. Weder, Nicholas J. Schork

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Linkage analyses of complex, multifactorial traits and diseases, such as essential hypertension, have been difficult to interpret and reconcile. Many published studies provide evidence suggesting that different genes and genomic regions influence hypertension, but knowing which of these studies reflect true positive results is challenging. The reasons for this include the diversity of analytical methods used across these studies, the different samples and sample sizes in each study, and the complicated biological underpinnings of hypertension. We have undertaken a comprehensive linkage analysis of 371 autosomal microsatellite markers genotyped on 4,334 sibling pairs affected with hypertension from five ethnic groups sampled from 13 different field centers associated with the Family Blood Pressure Program (FBPP). We used a single analytical technique known to be robust to interpretive problems associated with a lack of completely informative markers to assess evidence for linkage to hypertension both within and across the ethnic groups and field centers. We find evidence for linkage to a number of genomic regions, with the most compelling evidence from analyses that combine data across field center and ethnic groups (e.g., chromosomes 2 and 9). We also pursued linkage analyses that accommodate locus heterogeneity, which is known to plague the identification of disease susceptibility loci in linkage studies of complex diseases. We find evidence for linkage heterogeneity on chromosomes 2 and 17. Ultimately our results suggest that evidence for linkage heterogeneity can only be detected with large sample sizes, such as the FBPP, which is consistent with theoretical sample size calculations.

Original languageEnglish
Pages (from-to)195-210
Number of pages16
JournalGenetic Epidemiology
Volume31
Issue number3
DOIs
StatePublished - Apr 2007

Keywords

  • Blood pressure
  • Genetic heterogeneity
  • Genome scan
  • Hypertension
  • LOD score

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