320 research outputs found
Opportunistic hip fracture risk prediction in Men from X-ray: Findings from the Osteoporosis in Men (MrOS) Study
Osteoporosis is a common disease that increases fracture risk. Hip fractures,
especially in elderly people, lead to increased morbidity, decreased quality of
life and increased mortality. Being a silent disease before fracture,
osteoporosis often remains undiagnosed and untreated. Areal bone mineral
density (aBMD) assessed by dual-energy X-ray absorptiometry (DXA) is the
gold-standard method for osteoporosis diagnosis and hence also for future
fracture prediction (prognostic). However, the required special equipment is
not broadly available everywhere, in particular not to patients in developing
countries. We propose a deep learning classification model (FORM) that can
directly predict hip fracture risk from either plain radiographs (X-ray) or 2D
projection images of computed tomography (CT) data. Our method is fully
automated and therefore well suited for opportunistic screening settings,
identifying high risk patients in a broader population without additional
screening. FORM was trained and evaluated on X-rays and CT projections from the
Osteoporosis in Men (MrOS) study. 3108 X-rays (89 incident hip fractures) or
2150 CTs (80 incident hip fractures) with a 80/20 split were used. We show that
FORM can correctly predict the 10-year hip fracture risk with a validation AUC
of 81.44 +- 3.11% / 81.04 +- 5.54% (mean +- STD) including additional
information like age, BMI, fall history and health background across a 5-fold
cross validation on the X-ray and CT cohort, respectively. Our approach
significantly (p < 0.01) outperforms previous methods like Cox
Proportional-Hazards Model and \frax with 70.19 +- 6.58 and 74.72 +- 7.21
respectively on the X-ray cohort. Our model outperform on both cohorts hip aBMD
based predictions. We are confident that FORM can contribute on improving
osteoporosis diagnosis at an early stage.Comment: Accepted at MICCAI 2022 Workshop (PRIME
Epidemiology of rib fractures in older men: Osteoporotic Fractures in Men (MrOS) prospective cohort study
Objective To study the causes and consequences of radiologically confirmed rib fractures (seldom considered in the context of osteoporosis) in community dwelling older men
Fibroblast growth factor 23, mineral metabolism and mortality among elderly men (Swedish MrOs)
Background: Fibroblast growth factor 23 (FGF23) is the earliest marker of disturbed mineral metabolism as renal function decreases. Its serum levels are associated with mortality in dialysis patients, persons with chronic kidney disease (CKD) and prevalent cardiovascular disease (CVD), and it is associated with atherosclerosis, endothelial dysfunction and left ventricular hypertrophy in the general population. The primary aim of this study is to examine the association between FGF23 and mortality, in relation to renal function in the community. A secondary aim is to examine the association between FGF23 and CVD related death. Methods: The population-based cohort of MrOS Sweden included 3014 men (age 69-81 years). At inclusion intact FGF23, intact parathyroid hormone (PTH), 25 hydroxyl vitamin D (25D), calcium and phosphate were measured. Mortality data were collected after an average of 4.5 years follow-up. 352 deaths occurred, 132 of CVD. Association between FGF23 and mortality was analyzed in quartiles of FGF23. Kaplan-Meier curves and Log-rank test were used to examine time to events. Cox proportional hazards regression was used to examine the association between FGF23, in quartiles and as a continuous variable, with mortality. The associations were also analyzed in the sub-cohort with estimated glomerular filtration rate (eGFR) above 60 ml/min/1.73 m(2). Results: There was no association between FGF23 and all-cause mortality, Hazard ratio (HR) 95% confidence interval (CI): 1.02 (0.89-1.17). For CVD death the HR (95% CI) was 1.26 (0.99 - 1.59)/(1-SD) increase in log(10) FGF23 after adjustment for eGFR, and other confounders. In the sub-cohort with eGFR > 60 ml/min/1.73 m(2) the HR (95% CI) for CVD death was 55% (13-111)/(1-SD) increase in log(10) FGF23. Conclusions: FGF23 is not associated with mortality of all-cause in elderly community living men, but there is a weak association with CVD death, even after adjustment for eGFR and the other confounders. The association with CVD death is noticeable only in the sub-cohort with preserved renal function
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Individual and joint trajectories of change in bone, lean mass and physical performance in older men.
BackgroundDeclines in bone, muscle and physical performance are associated with adverse health outcomes in older adults. However, few studies have described concurrent age-related patterns of change in these factors. The purpose of this study was to characterize change in four properties of muscle, physical performance, and bone in a prospective cohort study of older men.MethodsUsing repeated longitudinal data from up to four visits across 6.9 years from up to 4681 men (mean age at baseline 72.7 yrs. ±5.3) participating in the Osteoporotic Fractures in Men (MrOS) Study, we used group-based trajectory models (PROC TRAJ in SAS) to identify age-related patterns of change in four properties of muscle, physical performance, and bone: total hip bone mineral (BMD) density (g/m2) and appendicular lean mass/ht2 (kg/m2), by DXA; grip strength (kg), by hand dynamometry; and walking speed (m/s), by usual walking pace over 6 m. We also described joint trajectories in all pair-wise combinations of these measures. Mean posterior probabilities of placement in each trajectory (or joint membership in latent groups) were used to assess internal reliability of the model. The number of trajectories for each individual factor was limited to three, to ensure that the pair-wise determination of joint trajectories would yield a tractable number of groups as well as model fit considerations.ResultsThe patterns of change identified were generally similar for all measures, with three district groups declining over time at roughly similar rates; joint trajectories revealed similar patterns with no cross-over or convergence between groups. Mean posterior probabilities for all trajectories were similar and consistently above 0.8 indicating reasonable model fit to the data.ConclusionsOur description of trajectories of change with age in bone mineral density, grip strength, walking speed and appendicular lean mass found that groups identified by these methods appeared to have little crossover or convergence of change with age, even when considering joint trajectories of change in these factors
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Candidate gene analysis of femoral neck trabecular and cortical volumetric bone mineral density in older men.
In contrast to conventional dual-energy X-ray absorptiometry, quantitative computed tomography separately measures trabecular and cortical volumetric bone mineral density (vBMD). Little is known about the genetic variants associated with trabecular and cortical vBMD in humans, although both may be important for determining bone strength and osteoporotic risk. In the current analysis, we tested the hypothesis that there are genetic variants associated with trabecular and cortical vBMD at the femoral neck by genotyping 4608 tagging and potentially functional single-nucleotide polymorphisms (SNPs) in 383 bone metabolism candidate genes in 822 Caucasian men aged 65 years or older from the Osteoporotic Fractures in Men Study (MrOS). Promising SNP associations then were tested for replication in an additional 1155 men from the same study. We identified SNPs in five genes (IFNAR2, NFATC1, SMAD1, HOXA, and KLF10) that were robustly associated with cortical vBMD and SNPs in nine genes (APC, ATF2, BMP3, BMP7, FGF18, FLT1, TGFB3, THRB, and RUNX1) that were robustly associated with trabecular vBMD. There was no overlap between genes associated with cortical vBMD and trabecular vBMD. These findings identify novel genetic variants for cortical and trabecular vBMD and raise the possibility that some genetic loci may be unique for each bone compartment
Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information
Janssen S, McDonald D, Gonzalez A, et al. Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information. mSystems. 2018;3(3):e00021-18
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Association of dietary patterns with the gut microbiota in older, community-dwelling men.
BackgroundWhile the gut microbiota is relatively stable through adulthood, its composition is influenced by various host and environmental factors, including changes in health, gastrointestinal processes (e.g., transit time, gastric acidity), medication use, and diet. The association of habitual diet, in the form of a posteriori-derived dietary patterns, and microbiota composition has not been adequately studied, particularly in older men.ObjectiveThe objective was to investigate the association of dietary patterns with the composition and diversity of the gut bacterial microbiota in community-dwelling, older men.MethodsThis cross-sectional study included 517 men who were participants in the Osteoporotic Fractures in Men (MrOS) Study (≥65 y of age at baseline in 2000-2002) and who provided a stool sample and completed an FFQ at MrOS Visit 4 in 2014-2016. Dietary patterns were derived by factor analysis. 16S ribosomal RNA target gene sequencing was performed and taxonomy assignments were derived using the Greengenes database. Linear regression and permutational multivariate analysis of variance (PERMANOVA) considered variations in alpha and beta diversity by dietary pattern, and a model that implements a 0-inflated Gaussian distribution of mean group abundance for each taxa (metagenomeSeq) assessed taxonomic variations by dietary pattern.ResultsIn multivariable-adjusted models, greater adherence to the Western pattern was positively associated with families Mogibacteriaceae and Veillonellaceae and genera Alistipes, Anaerotruncus, CC-115, Collinsella, Coprobacillus, Desulfovibrio, Dorea, Eubacterium, and Ruminococcus, while greater adherence to the prudent pattern was positively associated with order Streptophyta, family Victivallaceae, and genera Cetobacterium, Clostridium, Faecalibacterium, Lachnospira, Paraprevotella, and Veillonella. The relative abundance of the dominant gut bacterial phyla, Bacteroidetes and Firmicutes, did not differ between participants with greater adherence to the Western pattern, compared with those with greater adherence to the prudent pattern. Dietary patterns were not associated with measures of alpha diversity, but beta diversity measures were significantly associated with both Western and prudent patterns.ConclusionsWe observed significant associations between dietary patterns and measures of gut microbial composition in this sample of community-dwelling, older men
Protein co-expression network analysis (ProCoNA)
Abstract Background Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. Results We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show that approximately scale-free peptide networks, composed of statistically significant modules, are feasible and biologically meaningful using two mouse lung experiments and one human plasma experiment. Within each network, peptides derived from the same protein are shown to have a statistically higher topological overlap and concordance in abundance, which is potentially important for inferring protein abundance. The module representatives, called eigenpeptides, correlate significantly with biological phenotypes. Furthermore, within modules, we find significant enrichment for biological function and known interactions (gene ontology and protein-protein interactions). Conclusions Biological networks are important tools in the analysis of complex systems. In this paper we evaluate the application of weighted co-expression network analysis to quantitative proteomics data. Protein co-expression networks allow novel approaches for biological interpretation, quality control, inference of protein abundance, a framework for potentially resolving degenerate peptide-protein mappings, and a biomarker signature discovery
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