Journal
ANNALS OF HUMAN GENETICS
Volume 72, Issue -, Pages 319-326Publisher
BLACKWELL PUBLISHING
DOI: 10.1111/j.1469-1809.2007.00423.x
Keywords
obesity phenotypes; principal component analysis; linkage; QTL
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Funding
- NHLBI NIH HHS [HV48141] Funding Source: Medline
- NIAMS NIH HHS [P50 AR055081, R01 AR050496-01] Funding Source: Medline
- NIA NIH HHS [R01 AG026564, R21 AG027110] Funding Source: Medline
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Traditional whole genome linkage scans for obesity were usually performed for a number of correlated obesity related phenotypes separately without considering their correlations. The purpose of this study was to identify quantitative trait loci (QTLs) underlying variations in multiple correlated obesity phenotypes. We performed principal component analysis (PCA) for four highly correlated obesity phenotypes (body mass index [BMI], fat mass, percentage of fat mass [PFM], and lean mass) in a sample of 427 pedigrees (comprising 3,273 individuals) and generated two independent principal components (PC1 and PC2). A whole genome linkage scan (WGS) was then conducted for PC1 and PC2. For PC1, the strongest linkage signal was identified on chromosome 20p12 (LOD = 2.67). For PC2, two suggestive linkages were found on 5q35 (LOD = 2.03) and 7p22 (LOD = 2.18). This study provided evidence supporting several previously identified linkage regions for obesity (e.g., 1p36, 6p23 and 7q34). In addition, our approach by linear combination of highly correlated obesity phenotypes identified several novel QTLs which were not found in genome linkage scans for individual phenotypes.
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