A large-scale genome-wide linkage analysis to map loci linked to stature in Chinese population

Xiumei Hong, Hui Ju Tsai, Xin Liu, Zhiping Li, Xue Liu, Genfu Tang, Houxun Xing, Jianhua Yang, Binyan Wang, Yan Feng, Xin Xu, Xiping Xu, Xiaobin Wang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Context: A number of genome-wide scans of stature have been reported previously, but with inconsistent results. The inconsistency may be partly due to differential population characteristics and gender- and/or age-specific effects on this trait. Objective: This study aimed to identify the quantitative trait loci (QTLs) underlying the variation of stature in Chinese population, and to evaluate age- and gender-specific linkage for stature. Methods: We conducted a large-scale, genome-wide linkage scan using the data from three independent samples (a total of 7112 subjects from 1811 pedigrees) enrolled from the same geographical region in China. Linkage analyses were performed in the pooled samples and in subgroups defined by age (≤25 vs. >25 yr), gender, or both, using the model-free regression method implemented in MERLIN-REGRESS. Results: The strongest linkage signal was obtained on 17q24 (LOD = 3.82) in the pooled samples. Age-specific analysis revealed two additional significant QTLs on 13q34 and 18p11.3 among subjects 25 yr or younger. In gender-specific analyses, males showed suggestive QTLs on 12q21 (LOD = 2.31) and 17q22 (LOD = 2.60), and females showed a suggestive QTL on 13q31.1 (LOD = 2.68). Age-and gender-specific linkage analyses suggested that males older than 25 yr contributed more signals to QTLs on 12q21 and 17q22, with a LOD score of 3.00 and 2.26, respectively, whereas females older than 25 yr presented a suggestive QTL on 8q24.3 (LOD = 2.57). Conclusion: Our study identified a strong linkage of chromosome 17q24 to stature in this Chinese population, and indicated that it may be informative to consider differential age and gender effects in the genetic dissection of stature.

Original languageEnglish (US)
Pages (from-to)4511-4518
Number of pages8
JournalJournal of Clinical Endocrinology and Metabolism
Issue number11
StatePublished - Nov 2008

ASJC Scopus subject areas

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


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