Relevance of the genes for bone mass variation to susceptibility to osteoporotic fractures and its implications to gene search for complex human diseases

Deng, Hong Wen; Mahaney, Michael C.; Williams, Jeff T.; Li, Jing; Conway, Theresa; Davies, K. Michael; Li, Jin Long; Deng, Hong‐Wen; Recker, Robert R.

doi:10.1002/gepi.1040

Cited by 121 publications

(114 citation statements)

References 55 publications

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“…17,18 In brief, univariate and bivariate variance decomposition analyses were performed by Sequential Oligogenic Linkage Analysis Routines (SOLAR, available on http://www.sfbr.org/solar/). 19 The univariate variance analyses were performed to estimate the h 2 of the obesity phenotypes and AAM and to screen the effects of covariates on obesity phenotypes in polygenic models.…”

Section: Statistical Analysesmentioning

confidence: 99%

Genetic and environmental correlations between obesity phenotypes and age at menarche

Wang

Zhao

et al. 2006

Int J Obes

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Objective: To assess the extent that the genetic and environmental factors contribute to the phenotypic correlations between obesity traits and age at menarche (AAM), and also to examine the influence of AAM on obesity in both pre-and postmenopausal women. Methods: Five hundred and twelve pedigrees with 2667 Caucasian female subjects from two to four generations were recruited. Fat mass and lean mass (both in kg) were measured by dual-energy X-ray absorptiometry scanner. Body mass index (BMI) (kg/m 2 ) was calculated. We performed bivariate quantitative genetic analyses in the total sample containing 2667 Caucasian women. We also selected 206 unrelated premenopausal women and 140 unrelated postmenopausal women from the total sample, and computed the respective phenotypic correlation between obesity and AAM in these two subgroups. Results: For fat mass, lean mass and BMI, we detected their significant negative genetic correlations with AAM after adjustment for significant covariates, which were À0.3170 (Po0.001), À0.1721 (Po0.05) and À0.3665 (Po0.001), respectively. However, their environmental correlations with AAM were all nonsignificant (P40.05), ranging from À0.0016 to 0.0192. In the premenopausal subgroup, significant associations were observed between fat mass and AAM (r ¼ À0.231, Po0.01) as well as between BMI and AAM (r ¼ À0.257, Po0.01). In the postmenopausal subgroup, no such associations were observed. Conclusion: Our results for the first time suggested that significant phenotypic association between obesity phenotypes and AAM is mainly attributable to shared genetic rather than environmental factors, and AAM may have stronger effects on obesity phenotypes in pre-than in postmenopausal women.

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Section: Statistical Analysesmentioning

confidence: 99%

Genetic and environmental correlations between obesity phenotypes and age at menarche

Wang

Zhao

et al. 2006

Int J Obes

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“…All subjects signed informed consent documents before entering the project. Exclusion criteria were chosen to minimize any known potential confounding factors on BMD, as detailed by Deng et al (2002), and subjects were assessed by gaining information from nurseadministered questionnaires and/or medical records.…”

Section: Subjectsmentioning

confidence: 99%

Estrogen receptor α gene relationship with peak bone mass and body mass index in Chinese nuclear families

et al. 2005

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Estrogen receptor alpha (ER-a) plays an important role in mediating estrogen signaling. Studies in Caucasian populations have shown that it is involved in endocrine-related diseases such as osteoporosis and obesity. In the present study, we first used a quantitative transmission disequilibrium test (QTDT) to examine the relationship between this gene and both the osteoporosis-related phenotype bone mineral density (BMD), and the obesity-related phenotype body mass index (BMI), in 384 Chinese nuclear families. We genotyped a dinucleotide repeat marker (TA) n , and a long-range haplotype was reconstructed using this marker and two other restriction fragment length polymorphism (RFLP) markers at PvuII and XbaI loci. Although we found significant total association [allele (TA) 21 with hip BMD (P=0.001), and haplotype Px(TA) 21 with spine (P=0.0007) and hip (P=0.0006) BMD], the more reliable within-family associations were not significant between these phenotype pairs. No linkage signal was obtained for either spine BMD or hip BMD. We found no association or linkage between any of the three studied polymorphisms and the long-range haplotypes of the ER-a gene and BMI. Our study does not support an association of the ER-a gene with BMD and BMI in the Chinese population.

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“…(23,24) Note that the candidate gene variants for osteoporotic fracture are not simply the same as those for low BMD. (8,25) In addition to BMD, the bone matrix, bone strength, falling risk, and environmental factors take responsibility for osteoporotic fracture. So far, the 1p36, 8q24, and 6p21 loci have been identified as associated with osteoporotic fracture by Styrkarsdottir and colleagues.…”

Section: Introductionmentioning

confidence: 99%

Susceptibility genes for osteoporotic fracture in postmenopausal chinese women

Wang

Zeng

Zhang

et al. 2012

Journal of Bone and Mineral Research

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To identify the susceptibility genes for osteoporotic fracture in postmenopausal Chinese women, a two-stage case-control association study using joint analysis was conducted in 1046 patients with nontraumatic vertebra, hip, or distal radius fractures and 2303 healthy controls. First, 113 single-nucleotide polymorphisms (SNPs) in 16 potential osteoporosis candidate genes reported in recent genomewide association studies, meta-analyses studies, large-scale association studies, and functional studies were genotyped in a smallsample-size subgroup consisting of 541 patients with osteoporotic fractures and 554 healthy controls. Variants and haplotypes in SPTBN1, TNFRSF11B, CNR2, LRP4, and ESR1 that have been identified as being associated with osteoporotic fractures were further reanalyzed in the entire case-control group. We identified one SNP in TNFRSF11B (rs3102734), three SNPs in ESR1 (rs9397448, rs2234693, and rs1643821), two SNPs in LRP4 (rs17790156 and rs898604), and four SNPs in SPTBN1 (rs2971886, rs2941583, rs2941584, and rs12475342) were associated with all of the broadly defined osteoporotic fractures. The most significant polymorphism was rs3102734, with increased risk of osteoporotic fractures (odds ratio, 1.35; 95% confidence interval [CI], 1.17-1.55, Bonferroni p ¼ 2.6 Â 10 À4 ). Furthermore, rs3102734, rs2941584, rs12475342, rs9397448, rs2234693, and rs898604 exhibited significant allelic, genotypic, and/or haplotypic associations with vertebral fractures. SNPs rs12475342, rs9397448, and rs2234693 showed significant genotypic associations with hip fractures, whereas rs3102734, rs2073617, rs1643821, rs12475342, and rs2971886 exhibited significant genotypic and/or haplotypic associations with distal radius fractures. Accordingly, we suggest that in addition to the clinical risk factors, the variants in TNFRSF11B, SPTBN1, ESR1, and LRP4 are susceptibility genetic loci for osteoporotic fracture in postmenopausal Chinese women. ß

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Relevance of the genes for bone mass variation to susceptibility to osteoporotic fractures and its implications to gene search for complex human diseases

Cited by 121 publications

References 55 publications

Genetic and environmental correlations between obesity phenotypes and age at menarche

Genetic and environmental correlations between obesity phenotypes and age at menarche

Estrogen receptor α gene relationship with peak bone mass and body mass index in Chinese nuclear families

Susceptibility genes for osteoporotic fracture in postmenopausal chinese women

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