Dataset Information

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

ABSTRACT:

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 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.

SUBMITTER: Hong X

PROVIDER: S-EPMC2582574 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature

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Publications

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

Hong Xiumei X Tsai Hui-Ju HJ Liu Xin X Li Zhiping Z Liu Xue X Tang Genfu G Xing Houxun H Yang Jianhua J Wang Binyan B Feng Yan Y Xu Xin X Xu Xiping X Wang Xiaobin X

The Journal of clinical endocrinology and metabolism 20080826 11

<h4>Context</h4>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.<h4>Objective</h4>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.<h4>Methods</h4>We conducted a large-scale, ge ...[more]

PMID: 18728177

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Project description:BackgroundLung function is a heritable complex phenotype with obesity being one of its important risk factors. However, knowledge of their shared genetic basis is limited. Most genome-wide association studies (GWASs) for lung function have been based on European populations, limiting the generalisability across populations. Large-scale lung function GWASs in other populations are lacking.MethodsWe included 100 285 subjects from the China Kadoorie Biobank (CKB). To identify novel loci for lung function, single-trait GWAS analyses were performed on forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC in the CKB. We then performed genome-wide cross-trait analysis between lung function and obesity traits (body mass index (BMI), BMI-adjusted waist-to-hip ratio and BMI-adjusted waist circumference) to investigate the shared genetic effects in the CKB. Finally, polygenic risk scores (PRSs) of lung function were developed in the CKB and their interaction with BMI's association on lung function were examined. We also conducted cross-trait analysis in parallel with the CKB using up to 457 756 subjects from the UK Biobank (UKB) for replication and investigation of ancestry-specific effects.ResultsWe identified nine genome-wide significant novel loci for FEV1, six for FVC and three for FEV1/FVC in the CKB. FEV1 and FVC showed significant negative genetic correlation with obesity traits in both the CKB and UKB. Genetic loci shared between lung function and obesity traits highlighted important biological pathways, including cell proliferation, embryo, skeletal and tissue development, and regulation of gene expression. Mendelian randomisation analysis suggested significant negative causal effects of BMI on FEV1 and on FVC in both the CKB and UKB. Lung function PRSs significantly modified the effect of change in BMI on change in lung function during an average follow-up of 8 years.ConclusionThis large-scale GWAS of lung function identified novel loci and shared genetic aetiology between lung function and obesity. Change in BMI might affect change in lung function differently according to a subject's polygenic background. These findings may open new avenues for the development of molecular-targeted therapies for obesity and lung function improvement.

Dataset Information

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

Context

Objective

Methods

Results

Conclusion

Publications

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

Similar Datasets

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