Linkage analysis of diabetes status among hypertensive families: The hypertension genetc epidemiology network study

Christy L. Avery, Barry I. Freedman, Gerardo Heiss, Aldi Kraja, Treva Rice, Donna Arnett, Michael B. Miller, James S. Pankow, Cora E. Lewis, Richard H. Myers, Steven C. Hunt, Laura Almasy, Kari E. North

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Type 2 diabetes susceptibility is determined by multiple genetic and environmental factors. Genome-wide linkage scans have localized common regions, possibly harboring susceptibility genes on chromosomes 1, 2, 12, and 20. Variability in linkage findings underscores the probable genetic heterogeneity of type 2 diabetes. Thus, we conducted a genome scan of diabetes status using maximum likelihood methods that model affection status by a liability threshold model. Hypertensive sibships and their offspring and/or parents in the Hypertension Genetic Epidemiology Network study were recruited from five field centers. The diabetes phenotype was derived using the World Health Organization criteria and adjusted for race/study center, age, age2, sex, and with and without percent body fat. In total, 567 diabetic participants were identified in 437 families. Variance component linkage analysis was performed among 1,545 Caucasians and 1,608 African Americans using race-specific marker allele frequencies. We detected a quantitative trait loci (QTLs) influencing diabetes variance (logarithm of odds = 3.4) on chromosome 22, which overlaps a positive type 2 diabetes finding among Canadian Oji-Cree Indians. We also observed suggestive evidence for linkage on chromosomes 1, 2,5,8,14,17, and 19. The identification and replication of type 2 diabetes QTLs will bring us closer to the detection of functional genes that influence diabetes susceptibility.

Original languageEnglish (US)
Pages (from-to)3307-3312
Number of pages6
JournalDiabetes
Volume53
Issue number12
DOIs
StatePublished - Dec 2004
Externally publishedYes

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism

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