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Na Yu,
Yong-Jun Liu,
Yufang Pei,
Lei Zhang,
Shufeng Lei,
Niraj R Kothari,
Ding-You Li,
Christopher J Papasian, James Hamilton,
Ji-Qun Cai,
Hong-Wen Deng
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ABSTRACT: Compressive strength index (CSI) of the femoral neck is a parameter that integrates the information of bone mineral density (BMD), femoral neck width (FNW), and body weight. CSI is considered to have the potential to improve the performance of assessment for hip fracture risk. However, studies on CSI have been rare. In particular, few studies have evaluated the performance of CSI, in comparison with BMD, FNW, and bending geometry, for assessment of hip fracture risk. We studied two large populations, including 1683 unrelated U.S. Caucasians and 2758 unrelated Chinese adults. For all the study subjects, CSI, femoral neck BMD (FN_BMD), FNW, and bending geometry (section modulus [Z]) of the samples were obtained from dual-energy X-ray absorptiometry scans. We investigated the age-related trends of these bone phenotypes and potential sex and ethnic differences. We further evaluated the performance of these four phenotypes for assessment of hip fracture risk by logistic regression models. Chinese had significantly lower FN_BMD, FNW, and Z, but higher CSI than sex-matched Caucasians. Logistic regression analysis showed that higher CSI was significantly associated with lower risk of hip fracture, and the significance remained after adjusting for covariates of age, sex, and height. Each standard deviation (SD) increment in CSI was associated with odds ratios of 0.765 (95% confidence interval, 0.634, 0.992) and 0.724 (95% confidence interval, 0.569, 0.921) for hip fracture risk in Caucasians and Chinese, respectively. The higher CSI in Chinese may partially help explain the lower incidence of hip fractures in this population compared to Caucasians. Further studies in larger cohorts and/or longitudinal observations are necessary to confirm our findings.
Calcified Tissue International 10/2010; 87(4):324-32. · 2.38 Impact Factor
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Yan Guo,
Li-Jun Tan,
Shu-Feng Lei,
Tie-Lin Yang,
Xiang-Ding Chen,
Feng Zhang,
Yuan Chen,
Feng Pan,
Han Yan,
Xiaogang Liu, [......],
Meng Li,
Jin-Tang Wang,
Ting Wen,
Betty Drees, James Hamilton,
Christopher J Papasian,
Robert R Recker,
Xiao-Ping Song,
Jing Cheng,
Hong-Wen Deng
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ABSTRACT: Osteoporosis is a major public health problem. It is mainly characterized by low bone mineral density (BMD) and/or low-trauma osteoporotic fractures (OF), both of which have strong genetic determination. The specific genes influencing these phenotypic traits, however, are largely unknown. Using the Affymetrix 500K array set, we performed a case-control genome-wide association study (GWAS) in 700 elderly Chinese Han subjects (350 with hip OF and 350 healthy matched controls). A follow-up replication study was conducted to validate our major GWAS findings in an independent Chinese sample containing 390 cases with hip OF and 516 controls. We found that a SNP, rs13182402 within the ALDH7A1 gene on chromosome 5q31, was strongly associated with OF with evidence combined GWAS and replication studies (P = 2.08x10(-9), odds ratio = 2.25). In order to explore the target risk factors and potential mechanism underlying hip OF risk, we further examined this candidate SNP's relevance to hip BMD both in Chinese and Caucasian populations involving 9,962 additional subjects. This SNP was confirmed as consistently associated with hip BMD even across ethnic boundaries, in both Chinese and Caucasians (combined P = 6.39x10(-6)), further attesting to its potential effect on osteoporosis. ALDH7A1 degrades and detoxifies acetaldehyde, which inhibits osteoblast proliferation and results in decreased bone formation. Our findings may provide new insights into the pathogenesis of osteoporosis.
PLoS Genetics 01/2010; 6(1):e1000806. · 8.69 Impact Factor
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Marleen H M De Moor,
Yong-Jun Liu,
Dorret I Boomsma,
Jian Li, James J Hamilton,
Jouke-Jan Hottenga,
Shawn Levy,
Xiao-Gang Liu,
Yu-Fang Pei,
Danielle Posthuma,
Robert R Recker,
Patrick F Sullivan,
Liang Wang,
Gonneke Willemsen,
Han Yan,
Eco J C De Geus,
Hong-Wen Deng
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ABSTRACT: The objective of this study was to identify genetic variants that are associated with adult leisure time exercise behavior using genome-wide association (GWA) in two independent samples.
Exercise behavior was measured in 1644 unrelated Dutch and 978 unrelated American adults of European ancestry with detailed questions about type, frequency, and duration of exercise. Individuals were classified into regular exercisers or nonexercisers using a threshold of 4 MET·h (metabolic equivalents-hours per week). GWA analyses of ∼1.6 million observed and imputed Single Nucleotide Polymorphism (SNP) were conducted in both samples independently using logistic regression in SNPTEST, including sex, age, and body mass index as covariates. A meta-analysis of the results was performed using the weighted inverse variance method in METAL.
Thirty-seven novel SNPs in the PAPSS2 gene and in two intergenic regions on chromosomes 2q33.1 and 18p11.32 were associated with exercise participation (pooled P values <1.0 × 10(-5)). Previously reported associations (ACE, CASR, CYP19A1, DRD2, LEPR, and MC4R genes) or linkage findings (2p22.3, 4q28, 4q31.21 7p13, 9q31, 11p15, 13q22, 15q13, 18q12.2, 18q21.1, 19p13.3, and 20q12) were not replicated, although suggestive evidence was found for association to rs12405556 in the LEPR gene (pooled P value 9.7 × 10(-4); American sample, P value 9.8 × 10(-5)) and for association to rs8036270 in the GABRG3 gene (pooled P value 4.6 × 10(-5)) in the linkage region 15q12-13.
The heritability of leisure time exercise behavior is likely to be accounted for by many genetic variants with small effect size. These can be detected by GWA as was shown here for the PAPSS2 gene, but larger samples with genome-wide genotypes and high-quality exercise data are needed for further progress.
Medicine and science in sports and exercise 09/2009; 41(10):1887-95. · 3.71 Impact Factor
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ABSTRACT: With the advent of genome-wide association (GWA) studies, researchers are hoping that reliable genetic association of common human complex diseases/traits can be detected. Currently, there is an increasing enthusiasm about GWA and a number of GWA studies have been published. In the field a common practice is that replication should be used as the gold standard to validate an association finding. In this article, based on empirical and theoretical data, we emphasize that replication of GWA findings can be quite difficult, and should not always be expected, even when true variants are identified. The probability of replication becomes smaller with the increasing number of independent GWA studies if the power of individual replication studies is less than 100% (which is usually the case), and even a finding that is replicated may not necessarily be true. We argue that the field may have unreasonably high expectations on success of replication. We also wish to raise the question whether it is sufficient or necessary to treat replication as the ultimate and gold standard for defining true variants. We finally discuss the usefulness of integrating evidence from multiple levels/sources such as genetic epidemiological studies (at the DNA level), gene expression studies (at the RNA level), proteomics (at the protein level), and follow-up molecular and cellular studies for eventual validation and illumination of the functional relevance of the genes uncovered.
PLoS ONE 02/2008; 3(12):e4037. · 4.09 Impact Factor
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ABSTRACT: It was previously believed that obesity and osteoporosis were two unrelated diseases, but recent studies have shown that both diseases share several common genetic and environmental factors. Body fat mass, a component of body weight, is one of the most important indices of obesity, and a substantial body of evidence indicates that fat mass may have beneficial effects on bone. Contrasting studies, however, suggest that excessive fat mass may not protect against osteoporosis or osteoporotic fracture. Differences in experimental design, sample structure, and even the selection of covariates may account for some of these inconsistent or contradictory results. Despite the lack of a clear consensus regarding the impact of effects of fat on bone, a number of mechanistic explanations have been proposed to support the observed epidemiologic and physiologic associations between fat and bone. The common precursor stem cell that leads to the differentiation of both adipocytes and osteoblasts, as well the secretion of adipocyte-derived hormones that affect bone development, may partially explain these associations. Based on our current state of knowledge, it is unclear whether fat has beneficial effects on bone. We anticipate that this will be an active and fruitful focus of research in the coming years.
Journal of Bone and Mineral Research 02/2008; 23(1):17-29. · 6.37 Impact Factor
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ABSTRACT: The relationship between obesity and osteoporosis has been widely studied, and epidemiological evidence shows that obesity is correlated with increased bone mass. Previous analyses, however, did not control for the mechanical loading effects of total body weight on bone mass and may have generated a confounded or even biased relationship between obesity and osteoporosis.
The objective of this study was to reevaluate the relationship between obesity and osteoporosis by accounting for the mechanical loading effects of total body weight on bone mass.
We measured whole body fat mass, lean mass, percentage fat mass, body mass index, and bone mass in two large samples of different ethnicity: 1988 unrelated Chinese subjects and 4489 Caucasian subjects from 512 pedigrees. We first evaluated the Pearson correlations among different phenotypes. We then dissected the phenotypic correlations into genetic and environmental components with bone mass unadjusted or adjusted for body weight. This allowed us to compare the results with and without controlling for mechanical loading effects of body weight on bone mass.
In both Chinese and Caucasian subjects, when the mechanical loading effect of body weight on bone mass was adjusted for, the phenotypic correlation (including its genetic and environmental components) between fat mass (or percentage fat mass) and bone mass was negative. Further multivariate analyses in subjects stratified by body weight confirmed the inverse relationship between bone mass and fat mass, after mechanical loading effects due to total body weight were controlled.
Increasing fat mass may not have a beneficial effect on bone mass.
Journal of Clinical Endocrinology & Metabolism 06/2007; 92(5):1640-6. · 6.50 Impact Factor
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ABSTRACT: The purpose of this study was to determine the genetic and environmental correlations between weight, lean mass and bone geometric parameters (sub-periosteal diameter, W; cross-sectional area, CSA; cortical thickness, CT; section modulus, Z; and buckling ratio, BR) of femoral neck. The sample was composed of 512 Caucasian pedigrees, including 2667 females and 1822 males. Bivariate quantitative genetic analyses were performed to evaluate the genetic (rho(G)), environmental (rho(E)) and phenotypic (rho(P)) correlations between the study traits. Univariate genetic analyses showed that the heritabilities (h(2)) for bone geometric parameters were significant (P < 0.001) ranging from 0.50 to 0.60. The significant common household effects indicated the common environment shared by household members for W, CSA, CT, Z and BR (P < 0.05), but the magnitude was small compared with heritabilities. rho(E), rho(G) and rho(P) between bone geometric parameters and weight, lean mass were generally significant. Interestingly, lean mass showed both stronger genetic and environmental correlations with the bone geometric parameters than weight. In addition, according to the magnitude of correlation coefficients, the rho(G) between body compositions and bone geometric parameters were generally stronger than rho(E) (except for that between BR and body compositions). These data suggested that the geometric parameters of femoral neck are under strong genetic control. Furthermore, some common genetic and environmental factors are shared by bone geometric parameters and weight, lean mass. The results may help understand the intertwined relationships between bone metabolisms, mechanical loading and body compositions.
Calcified Tissue International 07/2006; 79(1):43-9. · 2.38 Impact Factor
