A Combined Analysis of Genomewide Linkage Scans for Body Mass Index, from the National Heart, Lung, and Blood Institute Family Blood Pressure Program

Abstract

A combined analysis of genome scans for obesity was undertaken using the interim results from the National Heart, Lung, and Blood Institute Family Blood Pressure Program. In this research project, four multicenter networks of investigators conducted eight individual studies. Data were available on 6,849 individuals from four ethnic groups (white, black, Mexican American, and Asian). The sample represents the largest single collection of genomewide scan data that has been analyzed for obesity and provides a test of the reproducibility of linkage analysis for a complex phenotype. Body mass index (BMI) was used as the measure of adiposity. Genomewide linkage analyses were first performed separately in each of the eight ethnic groups in the four networks, through use of the variance-component method. Only one region in the analyses of the individual studies showed significant linkage with BMI: 3q22.1 (LOD 3.45, for the GENOA network black sample). Six additional regions were found with an associated LOD >2, including 3p24.1, 7p15.2, 7q22.3, 14q24.3, 16q12.2, and 17p11.2. Among these findings, the linkage at 7p15.2, 7q22.3, and 17p11.2 has been reported elsewhere. A modified Fisher's omnibus procedure was then used to combine the P values from each of the eight genome scans. A complimentary approach to the meta-analysis was undertaken, combining the average allele-sharing identity by descent (pi) for whites, blacks, and Mexican Americans. Using this approach, we found strong linkage evidence for a quantitative-trait locus at 3q27 (marker D3S2427; LOD 3.40, P=.03). The same location has been shown to be linked with obesity-related traits and diabetes in at least two other studies. These results (1) confirm the previously reported obesity-susceptibility locus on chromosomes 3, 7, and 17 and (2) demonstrate that combining samples from different studies can increase the power to detect common genes with a small-to-moderate effect, so long as the same gene has an effect in all samples considered.

Sex-specific findings from a genome-wide linkage analysis of human fatness in non-Hispanic whites and African Americans: The HyperGEN Study

“…The support for linkage on chromosome 3 between 191 and 200 cM is a notable replication of a region of the genome that has been localized in several studies of adiposity-related phenotypes, 3q27. 22,26,29,64 Of particular interest is the genome scan reported by Wu et al, 29 a meta-analysis of the Family Blood Pressure Program (FBPP), which included HyperGEN participants. However, this study that included only the hypertensive sibpairs was analyzed by ethnicity, combining sexes, and only for BMI.…”

Genome-wide scan revealed genetic loci for energy metabolism in Hispanic children and adolescents

“…The linkage signal near marker D17S799 on chromosome 17 was replicated by a combined analysis of genome scans for BMI using the interim results from the National Heart, Lung and Blood Institute Family Blood Pressure Program with 6849 individuals from four ethnic groups (white, black, Mexican American and Asian). 41 Suggestive linkage signals in this region were also found for BMI in childhood, 42 acylation-stimulating protein in Mexican American adults, 43 adiponectin in Northern Europeans and leptin. 44 Possible candidate genes on chromosome 17 near marker D17S799 are peptide YY-2 (PYY2), pancreatic polypeptide-2 (PPY2) and aldolase C (ALDC, fructosebisphosphate).…”

Meta‐Analysis of Linkage Studies for Complex Diseases: An Overview of Methods and a Simulation Study

“…Other examples of meta-analysis are multiple sclerosis, where three groups combined their samples (The Transatlantic Multiple Sclerosis Genetics Cooperative, 2001), a metaanalysis with published genome scan data for autism (Badner & Gershon, 2002b), a combined analysis of data from eight linkage genome scans for body mass index (Wu et al 2002), and a pooled analysis of three studies for type I diabetes . For some diseases, consortia were formed to facilitate and prospectively plan the pooling of data.…”

“…Zaykin et al (2002) presented an extension of Fisher's method to combine only p-values below a certain threshold, which is presented in detail in the methods section (a similar method was proposed by Olkin & Saner (2001) in a general meta-analysis context). Finally, Wu et al (2002) analyzed eight samples from four ethnic groups in a study on obesity, and used a modification of Fisher's method as proposed by Province (2001), who suggested interpreting a nonparametric LOD of 0 as a pvalue of 0.72 to avoid bias when including results from nonparametric methods that truncate the LOD score space at 0. Badner & Goldin (1999) proposed another method to combine p-values across studies by calculating the probability for a set of attained p-values in a genetic region.…”

“…Wu et al 2002). Gu et al (1998) presented a method for combining IBD estimates, even from different sib pair designs (e.g.…”