Genome-wide Linkage Scans for Fasting Glucose, Insulin, and Insulin Resistance in the National Heart, Lung, and Blood Institute Family Blood Pressure Program

Abstract

Genome-wide linkage analyses were performed using a multipoint variance components method in eight study groups from four multicenter networks (whites and blacks in GenNet; whites, blacks, and Mexican Americans in GENOA; whites and blacks in HyperGEN; and Asians in SAPPHIRe) that comprise the National Heart, Lung, and Blood Institute Family Blood Pressure Program (FBPP), in order to identify quantitative trait loci (QTLs) influencing fasting glucose, insulin, and homeostasis model assessment of insulin resistance (HOMA-IR). These study populations were enriched with subjects who had elevated blood pressure. Participants fasting <8 h, those with a history of type 2 diabetes, or those on antidiabetic medications were excluded from the current investigation. These three phenotypes were suitably transformed to approximate normal distributions. Each phenotype was adjusted for the effects of age, BMI, and field center separately by sex within each of the eight network ethnicity groups before genetic analysis. A total of 8,664 subjects comprising 5,923 sibpairs from 4,043 families with 365 markers were available for conducting a meta-analysis using a modified Fisher’s method of combining the P values from each of the eight scans. Evidence of linkages was found on chromosome 7q36 at 163 cM, with a logarithm of odds (LOD) score of 3.21 for HOMA-IR, and on chromosome 19q13 at 88 cM, with a LOD score of 3.33 for fasting glucose. We also found suggestive linkages (LOD score ≥2.2) on chromosome 7q36 at 163 cM, with LOD scores of 2.31 for fasting glucose and 2.26 for fasting insulin (versus the LOD score of 3.21 for HOMA-IR at this locus). In conclusion, QTLs were identified on chromosomes 7q36 and 19q13 for fasting glucose, insulin, and insulin resistance in large and multiple-ethnicity populations in the FBPP with good replications across several other independent studies for relevant traits. Follow-up dense mapping and association studies are warranted.