Genotype-by-sex interaction on fasting insulin concentration: The HyperGEN study

Kari E. North, Nora Franceschini, Ingrid B. Borecki, C. Charles Gu, Gerardo Heiss, Michael A. Province, Donna K. Arnett, Cora E. Lewis, Michael B. Miller, Richard H. Myers, Steven C. Hunt, Barry I. Freedman

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Recent studies have demonstrated the importance of sex effects on the underlying genetic architecture of insulin-related traits. To explore sex-specific genetic effects on fasting insulin, we tested for genotype-by-sex interaction and conducted linkage analysis of fasting insulin in Hypertension Genetic Epidemiology Network families. Hypertensive siblings and their first-degree relatives were recruited from five field centers. We performed a genome scan for quantitative trait loci influencing fasting insulin among 1,505 European Americans and 1,616 African Americans without diabetes. Sex-stratified linear regression models, adjusted for race, center, and age, were explored. The Mammalian Genotyping Service typed 391 microsatellite markers, spaced roughly 9 cM. Variance component linkage analysis was performed in SOLAR using ethnic-specific marker allele frequencies and multipoint IBDs calculated in MERLIN. We detected a quantitative trait locus influencing fasting insulin in female subjects (logarithm of odds [LOD] = 3.4) on chromosome 2 at 95 cM (between GATA69E12 and GATA71G04) but not in male subjects (LOD = 0.0, P for interaction = 0.007). This sex-specific signal at 2p13.2 was detected in both European-American (LOD = 2.1) and African-American (LOD = 1.2) female subjects. Our findings overlap with several other linkage reports of insulin-related traits and demonstrate the importance of considering complex context-dependent interactions in the search for insulin-related genes.

Original languageEnglish
Pages (from-to)137-142
Number of pages6
JournalDiabetes
Volume56
Issue number1
DOIs
StatePublished - Jan 2007

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism

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