334 research outputs found
The risk of subsequent osteoporotic fractures is decreased in subjects experiencing fracture while on denosumab: results from the FREEDOM and FREEDOM Extension studies
Bone and mineral researc
A pooled analysis of fall incidence from placebo‐controlled trials of denosumab
Recent studies suggest that the RANK/RANKL system impacts muscle function and/or mass. In the pivotal placebo‐controlled fracture trial of the RANKL inhibitor denosumab in women with postmenopausal osteoporosis, treatment was associated with a lower incidence of non‐fracture‐related falls (p = 0.02). This ad hoc exploratory analysis pooled data from five placebo‐controlled trials of denosumab to determine consistency across trials, if any, of the reduction of fall incidence. The analysis included trials in women with postmenopausal osteoporosis and low bone mass, men with osteoporosis, women receiving adjuvant aromatase inhibitors for breast cancer, and men receiving androgen deprivation therapy for prostate cancer. The analysis was stratified by trial, and only included data from the placebo‐controlled period of each trial. A time‐to‐event analysis of first fall and exposure‐adjusted subject incidence rates of falls were analyzed. Falls were reported and captured as adverse events. The analysis comprised 10,036 individuals; 5030 received denosumab 60 mg subcutaneously once every 6 months for 12 to 36 months and 5006 received placebo. Kaplan–Meier estimates showed an occurrence of falls in 6.5% of subjects in the placebo group compared with 5.2% of subjects in the denosumab group (hazard ratio = 0.79; 95% confidence interval 0.66–0.93; p = 0.0061). Heterogeneity in study designs did not permit overall assessment of association with fracture outcomes. In conclusion, denosumab may reduce the risk of falls in addition to its established fracture risk reduction by reducing bone resorption and increasing bone mass. These observations require further exploration and confirmation in studies with muscle function or falls as the primary outcome
Summary of the performances of the superconducting electron cyclotron resonance ion source at 14 GHz
This article deals with the most recent performance of the superconducting electron cyclotron resonance ion source (SERSE) working at 14 GHz with high magnetic fields after the required conditioning and optimization of several operating parameters. SERSE has now achieved an outstanding level of performance in delivering highly charged ion beams in argon and oxygen gases: the results obtained while operating in a stainless steel chamber and with an aluminum liner are shown and discussed
Production of intense highly charged ion beams with SERSE
The source SERSE is operational at LNS since June 1998 and many improvements have been carried out in this period. The frequency has been increased from 14.5 GHz to 18 GHz and the use of two frequency heating has given positive results. Metallic ion production has been tested by means of a high temperature oven and the preliminary results are described. Tests of magnetic field scaling and frequency scaling have confirmed the results of previous tests with SC-ECRIS at lower frequency and seems to suggest that the upgrading of the source to higher frequency may be considered
Treatment‐related changes in bone turnover and fracture risk reduction in clinical trials of antiresorptive drugs: proportion of treatment effect explained
Few analyses of antiresorptive (AR) treatment trials relate short‐term changes in bone turnover markers (BTMs) to subsequent fracture reduction seeking to estimate the proportion of treatment effect explained (PTE) by BTMs. Pooling such information would be useful to assess new ARs or novel dosing regimens. In the Foundation for the National Institutes of Health (FNIH) Bone Quality project, we analyzed individual‐level data from up to 62,000 participants enrolled in 12 bisphosphonate (BP) and four selective estrogen receptor modulator (SERM) placebo‐controlled fracture endpoint trials. Using BTM results for two bone formation markers (bone‐specific alkaline phosphatase [bone ALP] and pro‐collagen I N‐propeptide [PINP]) and one bone resorption marker (C‐terminal telopeptide of type I collagen [CTX]) and incident fracture outcome data, we estimated the PTE using two different models. Separate analyses were performed for incident morphometric vertebral, nonvertebral, and hip fractures over 1 to 5 years of follow‐up. For vertebral fracture, the results showed that changes in all three BTMs at 6 months explained a large proportion of the treatment effect of ARs (57 to >100%), but not for and non‐vertebral or hip fracture. We conclude that short‐term AR treatment‐related changes in bone ALP, PINP, and CTX account for a large proportion of the treatment effect for vertebral fracture. Change in BTMs is a useful surrogate marker to study the anti‐fracture efficacy of new AR compounds or novel dosing regiments with approved AR drugs. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research
Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.
To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity
Identification of tag single-nucleotide polymorphisms in regions with varying linkage disequilibrium
We compared seven different tagging single-nucleotide polymorphism (SNP) programs in 10 regions with varied amounts of linkage disequilibrium (LD) and physical distance. We used the Collaborative Studies on the Genetics of Alcoholism dataset, part of the Genetic Analysis Workshop 14. We show that in regions with moderate to strong LD these programs are relatively consistent, despite different parameters and methods. In addition, we compared the selected SNPs in a multipoint linkage analysis for one region with strong LD. As the number of selected SNPs increased, the LOD score, mean information content, and type I error also increased
Investigation of altering single-nucleotide polymorphism density on the power to detect trait loci and frequency of false positive in nonparametric linkage analyses of qualitative traits
Genome-wide linkage analysis using microsatellite markers has been successful in the identification of numerous Mendelian and complex disease loci. The recent availability of high-density single-nucleotide polymorphism (SNP) maps provides a potentially more powerful option. Using the simulated and Collaborative Study on the Genetics of Alcoholism (COGA) datasets from the Genetics Analysis Workshop 14 (GAW14), we examined how altering the density of SNP marker sets impacted the overall information content, the power to detect trait loci, and the number of false positive results. For the simulated data we used SNP maps with density of 0.3 cM, 1 cM, 2 cM, and 3 cM. For the COGA data we combined the marker sets from Illumina and Affymetrix to create a map with average density of 0.25 cM and then, using a sub-sample of these markers, created maps with density of 0.3 cM, 0.6 cM, 1 cM, 2 cM, and 3 cM. For each marker set, multipoint linkage analysis using MERLIN was performed for both dominant and recessive traits derived from marker loci. Our results showed that information content increased with increased map density. For the homogeneous, completely penetrant traits we created, there was only a modest difference in ability to detect trait loci. Additionally, as map density increased there was only a slight increase in the number of false positive results when there was linkage disequilibrium (LD) between markers. The presence of LD between markers may have led to an increased number of false positive regions but no clear relationship between regions of high LD and locations of false positive linkage signals was observed
Interactions between genetic variation and cellular environment in skeletal muscle gene expression
From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.Peer reviewe
Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle
We integrate comeasured gene expression and DNA methylation (DNAme) in 265 human skeletal muscle biopsies from the FUSION study with >7 million genetic variants and eight physiological traits: height, waist, weight, waist-hip ratio, body mass index, fasting serum insulin, fasting plasma glucose, and type 2 diabetes. We find hundreds of genes and DNAme sites associated with fasting insulin, waist, and body mass index, as well as thousands of DNAme sites associated with gene expression (eQTM). We find that controlling for heterogeneity in tissue/muscle fiber type reduces the number of physiological trait associations, and that long-range eQTMs (>1 Mb) are reduced when controlling for tissue/muscle fiber type or latent factors. We map genetic regulators (quantitative trait loci; QTLs) of expression (eQTLs) and DNAme (mQTLs). Using Mendelian randomization (MR) and mediation techniques, we leverage these genetic maps to predict 213 causal relationships between expression and DNAme, approximately two-thirds of which predict methylation to causally influence expression. We use MR to integrate FUSION mQTLs, FUSION eQTLs, and GTEx eQTLs for 48 tissues with genetic associations for 534 diseases and quantitative traits. We identify hundreds of genes and thousands of DNAme sites that may drive the reported disease/quantitative trait genetic associations. We identify 300 gene expression MR associations that are present in both FUSION and GTEx skeletal muscle and that show stronger evidence of MR association in skeletal muscle than other tissues, which may partially reflect differences in power across tissues. As one example, we find that increased RXRA muscle expression may decrease lean tissue mass.Peer reviewe
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