A Follow-Up Linkage Study for Quantitative Trait Loci Contributing to Obesity-Related Phenotypes

Yong Jun Liu, Fu Hua Xu, Hui Shen, Yao Zhong Liu, Hong Yi Deng, Lan Juan Zhao, Qing Yang Huang, Volodymyr Dvornyk, Theresa Conway, K. Michael Davies, Jin Long Li, Robert R. Recker, Hong Wen Deng

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30 Scopus citations


We have recently reported a whole-genome scan in a sample of 630 subjects from 53 extended pedigrees, in which several genomic regions that may contain quantitative trait loci (QTLs) for obesity were suggested. In the present study, with an attempt to confirm our previous findings, we performed a follow-up linkage study in an expanded sample of 79 pedigrees with 1816 subjects (including expanded previous 53 pedigrees and 26 newly recruited pedigrees containing 1058 subjects). A new set of microsatellite markers spanning previously identified regions were selected, with the average genomic distance narrowed from approximately 10 cM to approximately 5 cM in this study. Using a variance component method, we performed two- and multipoint linkage analyses in the following three sample sets: expanded previous 53 pedigrees (758 subjects), 26 new pedigrees, and 79 total pedigrees. For body mass index, analyses of the expanded 53 pedigrees attained a LOD score of 2.32 near marker D1S468 in two-point analysis and a maximum LOD score (MLS) of 2.21 in multipoint analysis; 2q14 near marker D2S347 attained a LOD score of 3.42 in two-point analysis and a MLS of 3.93 in multipoint analysis. The linkage peaks at 1p36 and 2q14 were further supported in the analyses of all 79 pedigrees, with multipoint MLS being 1.38 and 0.90, respectively. For fat mass, genomic region 6q27 achieved a LOD score of 1.24 in two-point analysis and an MLS of 0.92 in multipoint analysis in all 79 pedigrees. Our data support that 1p36, 2q14, and 6q27 are promising regions that may harbor QTLs for obesity phenotypes.

Original languageEnglish (US)
Pages (from-to)875-882
Number of pages8
JournalJournal of Clinical Endocrinology and Metabolism
Issue number2
StatePublished - Feb 2004

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Endocrinology
  • Clinical Biochemistry
  • Biochemistry, medical


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