Genome-wide scans meta-analysis for pulse pressure.
Genome scans for identifying susceptibility loci for pulse pressure have produced inconclusive results. A heterogeneity-based genome search meta-analysis was applied to available genome-scan data on pulse pressure. A genome search meta-analysis divides the whole genome into 120 bins and identifies bins that rank high on average in terms of linkage statistics across genome scans unweighted or weighted by study size. The significance of each bin's average rank (right-sided test) and heterogeneity among studies (left-sided test) was calculated using a Monte Carlo test. The meta-analysis involved 7 genome scans, 3 consisting of subjects of European descent. Of the 120 bins, 5 bins had significant average rank (P(rank)<or=0.05) by either unweighted or weighted analyses, 4 of which (bins 21.2: 21q22.11 to 21q22.3, 18.3: 18q12.2 to 18q21.33, 18.4: 18q21.33 to 18q23, and 6.2: 6p22.3 to 6p21.1) were significant by both. In subjects of European descent, 3 bins (22.1: 22q11.1 to 22q12.3, 22.2: 22q12.3 to 22q13.3, 10.4: 10q22.1 to 10q23.32) had P(rank)<or=0.05 with both unweighted and weighted analyses. Bin 10.4 showed low heterogeneity (P(Q)=0.04). None of the bins showed low heterogeneity (P(Q)>0.05), indicating variation in the strength of association. Further investigation of these regions may help to direct the identification of candidate genes for pulse pressure variation.
Zintzaras
Elias
E
Center for Clinical Evidence Synthesis, Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, MA 02111, USA. ezintzaras@nemc-tufts.org
Kitsios
Georgios
G
Kent
David
D
Camp
Nicola J
NJ
Atwood
Larry
L
Hopkins
Paul N
PN
Hunt
Steven C
SC
D001794:Blood Pressure / Q000235:genetics*; D002874:Chromosome Mapping; D018740:Genetic Heterogeneity; D008040:Genetic Linkage; D020022:Genetic Predisposition to Disease / Q000235:genetics; D015894:Genome, Human; D006801:Humans; D009010:Monte Carlo Method