Bivariate whole genome linkage analyses for total body lean mass and BMD

System-wide coordinates of higher order functions in host-pathogen environment upon Mycobacterium tuberculosis infection

Molecular signatures and their interactions behind the successful establishment of infection of Mycobacterium tuberculosis (Mtb) inside macrophage are largely unknown. In this work, we present an inter-system scale atlas of the gene expression signatures, their interactions and higher order gene functions of macrophage-Mtb environment at the time of infection. We have carried out large-scale meta-analysis of previously published gene expression microarray studies andhave identified a ranked list of differentially expressed genes and their higher order functions in intracellular Mtb as well as the infected macrophage. Comparative analysis of gene expression signatures of intracellular Mtb with the in vitro dormant Mtb at different hypoxic and oxidative stress conditions led to the identification of the large number of Mtb functional groups, namely operons, regulons and pathways that were common and unique to the intracellular environment and dormancy state. Some of the functions that are specific to intracellular Mtb are cholesterol degradation and biosynthesis of immunomodulatory phenolic compounds. The molecular signatures we have identified to be involved in adaptation to different stress conditions in macrophage environment may be critical for designing therapeutic interventions against tuberculosis. And, our approach may be broadly applicable for investigating other host-pathogen interactions.

Relative Contributions of Lean and Fat Mass to Bone Mineral Density: Insight From Prader-Willi Syndrome

Context: Low bone mineral density (BMD) is the most important risk factor for fragility fracture. Body weight is a simple screening predictor of difference in BMD between individuals. However, it is not clear which component of body weight, lean (LM), or fat mass (FM), is associated with BMD. People with the genetic disorder of Prader-Willi syndrome (PWS) uniquely have a reduced LM despite increased FM. Objective: We sought to define the individual impact of LM and FM on BMD by investigating subjects with and without PWS. Design, Setting and Participants: This cross-sectional study was conducted at the Clinical Research Facility of the Garvan Institute of Medical Research, with PWS and control participants recruited from a specialized PWS clinic and from the general public by advertisement, respectively. The study involved 11 adults with PWS, who were age- and sex-matched with 12 obese individuals (Obese group) and 10 lean individuals (Lean group). Main Outcome Measures: Whole body BMD was measured by dual-energy X-ray absorptiometry. Total body FM and LM were derived from the whole body scan. Differences in BMD between groups were assessed by the analysis of covariance model, taking into account the effects of LM and FM. Results: The PWS group had significantly shorter height than the lean and obese groups. As expected, there was no significant difference in FM between the Obese and PWS group, and no significant difference in LM between the Lean and PWS group. However, obese individuals had greater LM than lean individuals. BMD in lean individuals was significantly lower than in PWS individuals (1.13 g/cm² vs. 1.21 g/cm², p < 0.05) and obese individuals (1.13 g/cm² vs. 1.25 g/cm², p < 0.05). After adjusting for both LM and FM, there was no significant difference in BMD between groups, and the only significant predictor of BMD was LM. Conclusions: These data from the human genetic model Prader-Willi syndrome suggest that LM is a stronger determinant of BMD than fat mass.

A review of sarcopenia: Enhancing awareness of an increasingly prevalent disease

Sarcopenia is defined as an age associated decline in skeletal muscle mass. The pathophysiology of sarcopenia is multifactorial, with decreased caloric intake, muscle fiber denervation, intracellular oxidative stress, hormonal decline, and enhanced myostatin signaling all thought to contribute. Prevalence rates are as high as 29% and 33% in elderly community dwelling and long-term care populations, respectively, with advanced age, low body mass index, and low physical activity as significant risk factors. Sarcopenia shares many characteristics with other disease states typically associated with risk of fall and fracture, including osteoporosis, frailty, and obesity. There is no current universally accepted definition of sarcopenia. Diagnosing sarcopenia with contemporary operational definitions requires assessments of muscle mass, muscle strength, and physical performance. Screening is recommended for both elderly patients and those with conditions that noticeably reduce physical function. Sarcopenia is highly prevalent in orthopedic patient populations and correlates with higher hospital costs and rates of falling, fracture, and mortality. As no muscle building agents are currently approved in the United States, resistance training and nutritional supplementation are the primary methods for treating sarcopenia. Trials with various agents, including selective androgen receptor modulators and myostatin inhibitors, show promise as future treatment options. Increased awareness of sarcopenia is of great importance to begin reaching consensus on diagnosis and to contribute to finding a cure for this condition.

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34–52%) for TBLH-BMD, and 39% (95% CI: 30–48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29–56%). We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.

Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total body lean mass and bone mass density in children, and show genetic loci with pleiotropic effects on both traits.

Genome-wide approaches for identifying genetic risk factors for osteoporosis

Osteoporosis, the most common type of bone disease worldwide, is clinically characterized by low bone mineral density (BMD) and increased susceptibility to fracture. Multiple genetic and environmental factors and gene-environment interactions have been implicated in its pathogenesis. Osteoporosis has strong genetic determination, with the heritability of BMD estimated to be as high as 60%. More than 80 genes or genetic variants have been implicated in risk of osteoporosis by hypothesis-free genome-wide studies. However, these genes or genetic variants can only explain a small portion of BMD variation, suggesting that many other genes or genetic variants underlying osteoporosis risk await discovery. Here, we review recent progress in genome-wide studies of osteoporosis and discuss their implications for medicine and the major challenges in the field.

The association between fat and lean mass and bone mineral density: the Healthy Twin Study

The potential beneficial effects of increased body weight on bone mineral density (BMD) conflict with the adverse effects of obesity on various health outcomes, necessitating more specific evaluations of the association between each body component and BMD. In the present study, we evaluated associations of lean mass (LM) and fat mass (FM) with BMD in a Korean sample consisting of a total of 1782 men and women whose mean (standard deviation) age was 43.2 (12.6) years. They were selected from the Healthy Twin Study, a nationwide Korean twin and family study. BMD, FM and LM were measured using dual-energy X-ray absorptiometry. Quantitative genetic analysis and linear mixed analysis were performed with respect to familial relationships and a wide range of probable covariates. Linear mixed analysis revealed that BMD was positively associated with both FM and LM at each region of BMD measurement (whole body, spine, arms, and legs) in men, premenopausal women, and postmenopausal women. However, the association with BMD was stronger for LM than FM. Both LM and FM had positive genetic correlations with BMD at each region, although the correlation with BMD tended to be stronger for LM than FM. Together, these findings suggest that increased LM, rather than FM, is more beneficial for BMD in the Korean population and warrants further study of the common genetic determinants of BMD and body composition.

Molecular genetic studies of gene identification for sarcopenia

Sarcopenia, which is characterized by a progressive decrease of skeletal muscle mass and function with aging, is closely related to several common diseases (such as cardiovascular and airway diseases) and functional impairment/disability. Strong genetic determination has been reported for muscle mass and muscle strength, two most commonly recognized and studied risk phenotypes for sarcopenia, with heritability ranging from 30 to 85% for muscle strength and 45-90% for muscle mass. Sarcopenia has been the subject of increasing genetic research over the past decade. This review is designed to comprehensively summarize the most important and representative molecular genetic studies designed to identify genetic factors associated with sarcopenia. We have methodically reviewed whole-genome linkage studies in humans, quantitative trait loci mapping in animal models, candidate gene association studies, newly reported genome-wide association studies, DNA microarrays and microRNA studies of sarcopenia or related skeletal muscle phenotypes. The major results of each study are tabulated for easy comparison and reference. The findings of representative studies are discussed with respect to their influence on our present understanding of the genetics of sarcopenia. This is a comprehensive review of molecular genetic studies of gene identification for sarcopenia, and an overarching theme for this review is that the currently accumulating results are tentative and occasionally inconsistent and should be interpreted with caution pending further investigation. Consequently, this overview should enhance recognition of the need to validate/replicate the genetic variants underlying sarcopenia in large human cohorts and animal. We believe that further progress in understanding the genetic etiology of sarcopenia will provide valuable insights into important fundamental biological mechanisms underlying muscle physiology that will ultimately lead to improved ability to recognize individuals at risk for developing sarcopenia and our ability to treat this debilitating condition.

Bivariate association analysis in selected samples: application to a GWAS of two bone mineral density phenotypes in males with high or low BMD

Our specific aims were to evaluate the power of bivariate analysis and to compare its performance with traditional univariate analysis in samples of unrelated subjects under varying sampling selection designs. Bivariate association analysis was based on the seemingly unrelated regression (SUR) model that allows different genetic models for different traits. We conducted extensive simulations for the case of two correlated quantitative phenotypes, with the quantitative trait locus making equal or unequal contributions to each phenotype. Our simulation results confirmed that the power of bivariate analysis is affected by the size, direction and source of the phenotypic correlations between traits. They also showed that the optimal sampling scheme depends on the size and direction of the induced genetic correlation. In addition, we demonstrated the efficacy of SUR-based bivariate test by applying it to a real Genome-Wide Association Study (GWAS) of Bone Mineral Density (BMD) values measured at the lumbar spine (LS) and at the femoral neck (FN) in a sample of unrelated males with low BMD (LS Z-scores ≤ -2) and with high BMD (LS and FN Z-scores >0.5). A substantial amount of top hits in bivariate analysis did not reach nominal significance in any of the two single-trait analyses. Altogether, our studies suggest that bivariate analysis is of practical significance for GWAS of correlated phenotypes.

An investigation into the relationship between soft tissue body composition and bone mineral density in a young adult twin sample

The purpose of this study was to investigate the relationship of fat mass (FM) and lean mass (LM) with bone mineral density (BMD) independent of genetic effects. We also assessed the extent to which genetic and environmental influences explain the associations between these phenotypes. Body composition and BMD were measured using dual-energy X-ray absorptiometry in 57 monozygotic and 92 same-sex dizygotic twin pairs, aged 23 to 31 years, chosen to represent a wide range of intrapair differences in body mass index (BMI; 0 to 15.2 kg/m(2)). Heritability estimates were adjusted for height and gender. In multiple linear regression analysis, intrapair differences in both FM and LM were independently associated with intrapair differences in BMD at most skeletal sites after adjustment for gender and differences in height. Within monozygotic and dizygotic pairs, LM was a significantly stronger predictor of whole-body BMD than FM (p < .01). Additive genetic factors explained 87% [95% confidence interval (CI) 80%-91%), 81% (95% CI 70%-88%), and 61% (95% CI 41%-75%) of the variation in whole-body BMD, LM, and FM, respectively. Additive genetic factors also accounted for 69% to 88% of the covariance between LM and BMD and for 42% to 72% of the covariance between FM and BMD depending on the skeletal site. The genetic correlation between LM and whole-body BMD (r(g) = 0.46, 95% CI 0.32-0.58) was greater than that of FM and whole-body BMD (r(g) = 0.25, 95% CI 0.05-0.42). In conclusion, our data indicate that peak BMD is influenced by acquired body weight as well as genetic factors. In young adulthood, LM and BMD may have more genes in common than do FM and BMD.

Molecular genetic studies of gene identification for osteoporosis: the 2009 update

Osteoporosis is a complex human disease that results in increased susceptibility to fragility fractures. It can be phenotypically characterized using several traits, including bone mineral density, bone size, bone strength, and bone turnover markers. The identification of gene variants that contribute to osteoporosis phenotypes, or responses to therapy, can eventually help individualize the prognosis, treatment, and prevention of fractures and their adverse outcomes. Our previously published reviews have comprehensively summarized the progress of molecular genetic studies of gene identification for osteoporosis and have covered the data available to the end of September 2007. This review represents our continuing efforts to summarize the important and representative findings published between October 2007 and November 2009. The topics covered include genetic association and linkage studies in humans, transgenic and knockout mouse models, as well as gene-expression microarray and proteomics studies. Major results are tabulated for comparison and ease of reference. Comments are made on the notable findings and representative studies for their potential influence and implications on our present understanding of the genetics of osteoporosis.

Mapping quantitative traits in unselected families: algorithms and examples

Linkage analysis has been widely used to identify from family data genetic variants influencing quantitative traits. Common approaches have both strengths and limitations. Likelihood ratio tests typically computed in variance component analysis can accommodate large families but are highly sensitive to departure from normality assumptions. Regression-based approaches are more robust but their use has primarily been restricted to nuclear families. In this paper, we develop methods for mapping quantitative traits in moderately large pedigrees. Our methods are based on the score statistic, which in contrast to the likelihood ratio statistic can use nonparametric estimators of variability to achieve robustness of the false-positive rate against departures from the hypothesized phenotypic model. Because the score statistic is easier to calculate than the likelihood ratio statistic, our basic mapping methods utilize relatively simple computer code that performs statistical analysis on output from any program that computes estimates of identity by descent. This simplicity also permits development and evaluation of methods to deal with multivariate and ordinal phenotypes, and with gene-gene and gene-environment interaction. We demonstrate our methods on simulated data and on fasting insulin, a quantitative trait measured in the Framingham Heart Study.