A risk profile for identifying community-dwelling elderly with a highrisk of recurrent falling: results of a 3-year prospective study

Introduction: The aim of the prospective study reported here was to develop a risk profile that can be used to identify community-dwelling elderly at a high risk of recurrent falling. Materials and methods: The study was designed as a 3-year prospective cohort study. A total of 1365 community-dwelling persons, aged 65 years and older, of the population-based Longitudinal Aging Study Amsterdam participated in the study. During an interview in 1995/1996, physical, cognitive, emotional and social aspects of functioning were assessed. A follow-up on the number of falls and fractures was conducted during a 3-year period using fall calendars that participants filled out weekly. Recurrent fallers were identified as those who fell at least twice within a 6-month period during the 3-year follow-up. Results: The incidence of recurrent falls at the 3-year follow-up point was 24.9% in women and 24.4% in men. Of the respondents, 5.5% reported a total of 87 fractures that resulted from a fall, including 20 hip fractures, 21 wrist fractures and seven humerus fractures. Recurrent fallers were more prone to have a fall-related fracture than those who were not defined as recurrent fallers (11.9% vs. 3.4%; OR: 3.8; 95% CI: 2.3-6.1). Backward logistic regression analysis identified the following predictors in the risk profile for recurrent falling: two or more previous falls, dizziness, functional limitations, weak grip strength, low body weight, fear of falling, the presence of dogs/cats in the household, a high educational level, drinking 18 or more alcoholic consumptions per week and two interaction terms (high educationx18 or more alcohol consumptions per week and two or more previous falls x fear of falling) (AUC=0.71). Discussion: At a cut-off point of 5 on the total risk score (range 0-30), the model predicted recurrent falling with a sensitivity of 59% and a specificity of 71%. At a cut-off point of 10, the sensitivity and specificity were 31% and 92%, respectively. A risk profile including nine predictors that can easily be assessed seems to be a useful tool for the identification of community-dwelling elderly with a high risk of recurrent falling. © International Osteoporosis Foundation and National Osteoporosis Foundation 2006

Echium oil is not protective against weight loss in head and neck cancer patients undergoing curative radio(chemo)therapy: a randomised-controlled trial

Background: Therapy-induced mucositis and dysphagia puts head and neck (H&N) cancer patients at increased risk for developing cachexia. Omega-3 fatty acids (n-3 FA) have been suggested to protect against cachexia. We aimed to examine if echium oil, a plant source of n-3 FA, could reduce weight loss in H&N cancer patients undergoing radio(chemo)therapy with curative intent. Methods: In a double-blind trial, patients were randomly assigned to echium oil (intervention (I) group; 7.5 ml bis in die (b.i.d.), 235 mg/ml α-linolenic acid (ALA) + 95 mg/ml stearidonic acid (SDA) + 79 mg/ml γ-linolenic acid (GLA)) or n-3 FA deficient sunflower oil high oleic (control (C) group; 7.5 ml b.i.d.) additional to standard nutritional support during treatment. Differences in percentage weight loss between both groups were analysed according to the intention-to-treat principle. Erythrocyte FA profile, body composition, nutritional status and quality of life were collected. Results: Ninety-one eligible patients were randomised, of whom 83 were evaluable. Dietary supplement adherence was comparable in both groups (median, I: 87%, C: 81%). At week 4, the I group showed significantly increased values of erythrocyte n-3 eicosapentanoic acid (EPA, 14% vs −5%) and n-6 GLA (42% vs −20%) compared to the C group, without a significant change in n-6 arachidonic acid (AA, 2% vs −1%). Intention-to-treat analysis could not reveal a significant reduction in weight loss related to echium oil consumption (median weight loss, I: 8.9%, C: 7.6%). Also, no significant improvement was observed in the other evaluated anthropometric parameters. Conclusions: Echium oil effectively increased erythrocyte EPA and GLA FAs in H&N cancer patients. It failed however to protect against weight loss, or improve nutritional parameters. Trial registration: ClinicalTrials.gov Identifier NCT01596933

Epigenome-wide methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2+): a prospective cohort study in the United States.

BACKGROUND: Methylation levels may be associated with and serve as markers to predict risk of progression of precancerous cervical lesions. We conducted an epigenome-wide association study (EWAS) of CpG methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2 +) following an abnormal screening test. METHODS: A prospective US cohort of 289 colposcopy patients with normal or CIN1 enrollment histology was assessed. Baseline cervical sample DNA was analyzed using Illumina HumanMethylation 450K (n = 76) or EPIC 850K (n = 213) arrays. Participants returned at provider-recommended intervals and were followed up to 5 years via medical records. We assessed continuous CpG M values for 9 cervical cancer-associated genes and time-to-progression to CIN2+. We estimated CpG-specific time-to-event ratios (TTER) and hazard ratios using adjusted, interval-censored Weibull accelerated failure time models. We also conducted an exploratory EWAS to identify novel CpGs with false discovery rate (FDR) < 0.05. RESULTS: At enrollment, median age was 29.2 years; 64.0% were high-risk HPV-positive, and 54.3% were non-white. During follow-up (median 24.4 months), 15 participants progressed to CIN2+. Greater methylation levels were associated with a shorter time-to-CIN2+ for CADM1 cg03505501 (TTER = 0.28; 95%CI 0.12, 0.63; FDR = 0.03) and RARB Cluster 1 (TTER = 0.46; 95% CI 0.29, 0.71; FDR = 0.01). There was evidence of similar trends for DAPK1 cg14286732, PAX1 cg07213060, and PAX1 Cluster 1. The EWAS detected 336 novel progression-associated CpGs, including those located in CpG islands associated with genes FGF22, TOX, COL18A1, GPM6A, XAB2, TIMP2, GSPT1, NR4A2, and APBB1IP. CONCLUSIONS: Using prospective time-to-event data, we detected associations between CADM1-, DAPK1-, PAX1-, and RARB-related CpGs and cervical disease progression, and we identified novel progression-associated CpGs. IMPACT: Methylation levels at novel CpG sites may help identify individuals with ≤CIN1 histology at higher risk of progression to CIN2+ and inform risk-based cervical cancer screening guidelines

Detection of gene pathways with predictive power for breast cancer prognosis

<p>Abstract</p> <p>Background</p> <p>Prognosis is of critical interest in breast cancer research. Biomedical studies suggest that genomic measurements may have independent predictive power for prognosis. Gene profiling studies have been conducted to search for predictive genomic measurements. Genes have the inherent pathway structure, where pathways are composed of multiple genes with coordinated functions. The goal of this study is to identify gene pathways with predictive power for breast cancer prognosis. Since our goal is fundamentally different from that of existing studies, a new pathway analysis method is proposed.</p> <p>Results</p> <p>The new method advances beyond existing alternatives along the following aspects. First, it can assess the predictive power of gene pathways, whereas existing methods tend to focus on model fitting accuracy only. Second, it can account for the joint effects of multiple genes in a pathway, whereas existing methods tend to focus on the marginal effects of genes. Third, it can accommodate multiple heterogeneous datasets, whereas existing methods analyze a single dataset only. We analyze four breast cancer prognosis studies and identify 97 pathways with significant predictive power for prognosis. Important pathways missed by alternative methods are identified.</p> <p>Conclusions</p> <p>The proposed method provides a useful alternative to existing pathway analysis methods. Identified pathways can provide further insights into breast cancer prognosis.</p

Topological Machine Learning with Persistence Indicator Functions

Techniques from computational topology, in particular persistent homology, are becoming increasingly relevant for data analysis. Their stable metrics permit the use of many distance-based data analysis methods, such as multidimensional scaling, while providing a firm theoretical ground. Many modern machine learning algorithms, however, are based on kernels. This paper presents persistence indicator functions (PIFs), which summarize persistence diagrams, i.e., feature descriptors in topological data analysis. PIFs can be calculated and compared in linear time and have many beneficial properties, such as the availability of a kernel-based similarity measure. We demonstrate their usage in common data analysis scenarios, such as confidence set estimation and classification of complex structured data.Comment: Topology-based Methods in Visualization 201

Mutations that permit residual CFTR function delay acquisition of multiple respiratory pathogens in CF patients

<p>Abstract</p> <p>Background</p> <p>Lung infection by various organisms is a characteristic feature of cystic fibrosis (CF). <it>CFTR </it>genotype effects acquisition of <it>Pseudomonas aeruginosa (Pa)</it>, however the effect on acquisition of other infectious organisms that frequently precede <it>Pa </it>is relatively unknown. Understanding the role of CFTR in the acquisition of organisms first detected in patients may help guide symptomatic and molecular-based treatment for CF.</p> <p>Methods</p> <p>Lung infection, defined as a single positive respiratory tract culture, was assessed for 13 organisms in 1,381 individuals with CF. Subjects were divided by predicted CFTR function: 'Residual': carrying at least one partial function <it>CFTR </it>mutation (class IV or V) and 'Minimal' those who do not carry a partial function mutation. Kaplan-Meier estimates were created to assess <it>CFTR </it>effect on age of acquisition for each organism. Cox proportional hazard models were performed to control for possible cofactors. A separate Cox regression was used to determine whether defining infection with <it>Pa</it>, mucoid <it>Pa </it>or <it>Aspergillus (Asp) </it>using alternative criteria affected the results. The influence of severity of lung disease at the time of acquisition was evaluated using stratified Cox regression methods by lung disease categories.</p> <p>Results</p> <p>Subjects with 'Minimal' CFTR function had a higher hazard than patients with 'Residual' function for acquisition of 9 of 13 organisms studied (HR ranging from 1.7 to 3.78 based on the organism studied). Subjects with minimal CFTR function acquired infection at a younger age than those with residual function for 12 of 13 organisms (p-values ranging: < 0.001 to 0.017). Minimal CFTR function also associated with younger age of infection when 3 alternative definitions of infection with <it>Pa</it>, mucoid <it>Pa </it>or <it>Asp </it>were employed. Risk of infection is correlated with CFTR function for 8 of 9 organisms in patients with good lung function (>90%ile) but only 1 of 9 organisms in those with poorer lung function (<50%ile).</p> <p>Conclusions</p> <p>Residual CFTR function correlates with later onset of respiratory tract infection by a wide spectrum of organisms frequently cultured from CF patients. The protective effect conferred by residual CFTR function is diminished in CF patients with more advanced lung disease.</p

Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation

<p>Abstract</p> <p>Background</p> <p>External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analyses based on clustering or gene set enrichment only partly reveal this information, matrix factorization techniques are well suited for a detailed temporal analysis. In signal processing, factorization techniques incorporating data properties like spatial and temporal correlation structure have shown to be robust and computationally efficient. However, such correlation-based methods have so far not be applied in bioinformatics, because large scale biological data rarely imply a natural order that allows the definition of a delayed correlation function.</p> <p>Results</p> <p>We therefore develop the concept of graph-decorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways in a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the features (e.g. genes) and are thus able to define a graph-delayed correlation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph-decorrelation algorithm (GraDe). To analyze alterations in the gene response in <it>IL-6 </it>stimulated primary mouse hepatocytes, we performed a time-course microarray experiment and applied GraDe. In contrast to standard techniques, the extracted time-resolved gene expression profiles showed that <it>IL-6 </it>activates genes involved in cell cycle progression and cell division. Genes linked to metabolic and apoptotic processes are down-regulated indicating that <it>IL-6 </it>mediated priming renders hepatocytes more responsive towards cell proliferation and reduces expenditures for the energy metabolism.</p> <p>Conclusions</p> <p>GraDe provides a novel framework for the decomposition of large-scale 'omics' data. We were able to show that including prior knowledge into the separation task leads to a much more structured and detailed separation of the time-dependent responses upon <it>IL-6 </it>stimulation compared to standard methods. A Matlab implementation of the GraDe algorithm is freely available at <url>http://cmb.helmholtz-muenchen.de/grade</url>.</p

Uniform Selection as a Primary Force Reducing Population Genetic Differentiation of Cavitation Resistance across a Species Range

Background: Cavitation resistance to water stress-induced embolism determines plant survival during drought. This adaptive trait has been described as highly variable in a wide range of tree species, but little is known about the extent of genetic and phenotypic variability within species. This information is essential to our understanding of the evolutionary forces that have shaped this trait, and for evaluation of its inclusion in breeding programs. Methodology: We assessed cavitation resistance (P 50), growth and carbon isotope composition in six Pinus pinaster populations in a provenance and progeny trial. We estimated the heritability of cavitation resistance and compared the distribution of neutral markers (FST) and quantitative genetic differentiation (QST), for retrospective identification of the evolutionary forces acting on these traits. Results/Discussion: In contrast to growth and carbon isotope composition, no population differentiation was found for cavitation resistance. Heritability was higher than for the other traits, with a low additive genetic variance (h 2 ns = 0.4360.18, CVA = 4.4%). QST was significantly lower than FST, indicating uniform selection for P50, rather than genetic drift. Putativ