Frailty in Chronic Obstructive Pulmonary Disease and Risk of Exacerbations and Hospitalizations

Background: Frailty is a complex clinical syndrome associated with vulnerability to adverse health outcomes. While frailty is thought to be common in chronic obstructive pulmonary disease (COPD), the relationship between frailty and COPD-related outcomes such as risk of acute exacerbations of COPD (AE-COPD) and hospitalizations is unclear.Purpose: To examine the association between physical frailty and risk of acute exacerbations, hospitalizations, and mortality in patients with COPD.Methods: A longitudinal analysis of data from a cohort of 280 participants was performed. Baseline frailty measures included exhaustion, weakness, low activity, slowness, and undernutrition. Outcome measures included AE-COPD, hospitalizations, and mortality over 2 years. Negative binomial regression and Cox proportional hazard modeling were used.Results: Sixty-two percent of the study population met criteria for pre-frail and 23% were frail. In adjusted analyses, the frailty syndrome was not associated with COPD exacerbations. However, among the individual components of the frailty syndrome, weakness measured by handgrip strength was associated with increased risk of COPD exacerbations (IRR 1.46, 95% CI 1.09– 1.97). The frailty phenotype was not associated with all-cause hospitalizations but was associated with increased risk of non-COPD-related hospitalizations.Conclusion: This longitudinal cohort study shows that a high proportion of patients with COPD are pre-frail or frail. The frailty phenotype was associated with an increased risk of non-COPD hospitalizations but not with all-cause hospitalizations or COPD exacerbations. Among the individual frailty components, low handgrip strength was associated with increased risk of COPD exacerbations over a 2-year period. Measuring handgrip strength may identify COPD patients who could benefit from programs to reduce COPD exacerbations

High Throughput Functional Assays of the Variant Antigen PfEMP1 Reveal a Single Domain in the 3D7 Plasmodium falciparum Genome that Binds ICAM1 with High Affinity and Is Targeted by Naturally Acquired Neutralizing Antibodies

Plasmodium falciparum–infected erythrocytes bind endothelial receptors to sequester in vascular beds, and binding to ICAM1 has been implicated in cerebral malaria. Binding to ICAM1 may be mediated by the variant surface antigen family PfEMP1: for example, 6 of 21 DBLβC2 domains from the IT4 strain PfEMP1 repertoire were shown to bind ICAM1, and the PfEMP1 containing these 6 domains are all classified as Group B or C type. In this study, we surveyed binding of ICAM1 to 16 DBLβC2 domains of the 3D7 strain PfEMP1 repertoire, using a high throughput Bioplex assay format. Only one DBL2βC2 domain from the Group A PfEMP1 PF11_0521 showed strong specific binding. Among these 16 domains, DBL2βC2PF11_0521 best preserved the residues previously identified as conserved in ICAM1-binding versus non-binding domains. Our analyses further highlighted the potential role of conserved residues within predominantly non-conserved flexible loops in adhesion, and, therefore, as targets for intervention. Our studies also suggest that the structural/functional DBLβC2 domain involved in ICAM1 binding includes about 80 amino acid residues upstream of the previously suggested DBLβC2 domain. DBL2βC2PF11_0521 binding to ICAM1 was inhibited by immune sera from east Africa but not by control US sera. Neutralizing antibodies were uncommon in children but common in immune adults from east Africa. Inhibition of binding was much more efficient than reversal of binding, indicating a strong interaction between DBL2βC2PF11_0521 and ICAM1. Our high throughput approach will significantly accelerate studies of PfEMP1 binding domains and protective antibody responses

Smoking cessation in severe mental ill health : what works? an updated systematic review and meta-analysis

BACKGROUND: People with severe mental ill health are more likely to smoke than those in the general population. It is therefore important that effective smoking cessation strategies are used to help people with severe mental ill health to stop smoking. This study aims to assess the effectiveness and cost -effectiveness of smoking cessation and reduction strategies in adults with severe mental ill health in both inpatient and outpatient settings. METHODS: This is an update of a previous systematic review. Electronic databases were searched during September 2016 for randomised controlled trials comparing smoking cessation interventions to each other, usual care, or placebo. Data was extracted on biochemically-verified, self-reported smoking cessation (primary outcome), as well as on smoking reduction, body weight, psychiatric symptom, and adverse events (secondary outcomes). RESULTS: We included 26 trials of pharmacological and/or behavioural interventions. Eight trials comparing bupropion to placebo were pooled showing that bupropion improved quit rates significantly in the medium and long term but not the short term (short term RR = 6.42 95% CI 0.82-50.07; medium term RR = 2.93 95% CI 1.61-5.34; long term RR = 3.04 95% CI 1.10-8.42). Five trials comparing varenicline to placebo showed that that the addition of varenicline improved quit rates significantly in the medium term (RR = 4.13 95% CI 1.36-12.53). The results from five trials of specialised smoking cessation programmes were pooled and showed no evidence of benefit in the medium (RR = 1.32 95% CI 0.85-2.06) or long term (RR = 1.33 95% CI 0.85-2.08). There was insufficient data to allowing pooling for all time points for varenicline and trials of specialist smoking cessation programmes. Trials suggest few adverse events although safety data were not always reported. Only one pilot study reported cost effectiveness data. CONCLUSIONS: Bupropion and varenicline, which have been shown to be effective in the general population, also work for people with severe mental ill health and their use in patients with stable psychiatric conditions. Despite good evidence for the effectiveness of smoking cessation interventions for people with severe mental ill health, the percentage of people with severe mental ill health who smoke remains higher than that for the general population

Genome-Wide Interaction-Based Association Analysis Identified Multiple New Susceptibility Loci for Common Diseases

Genome-wide interaction-based association (GWIBA) analysis has the potential to identify novel susceptibility loci. These interaction effects could be missed with the prevailing approaches in genome-wide association studies (GWAS). However, no convincing loci have been discovered exclusively from GWIBA methods, and the intensive computation involved is a major barrier for application. Here, we developed a fast, multi-thread/parallel program named “pair-wise interaction-based association mapping” (PIAM) for exhaustive two-locus searches. With this program, we performed a complete GWIBA analysis on seven diseases with stringent control for false positives, and we validated the results for three of these diseases. We identified one pair-wise interaction between a previously identified locus, C1orf106, and one new locus, TEC, that was specific for Crohn's disease, with a Bonferroni corrected P<0.05 (P = 0.039). This interaction was replicated with a pair of proxy linked loci (P = 0.013) on an independent dataset. Five other interactions had corrected P<0.5. We identified the allelic effect of a locus close to SLC7A13 for coronary artery disease. This was replicated with a linked locus on an independent dataset (P = 1.09×10−7). Through a local validation analysis that evaluated association signals, rather than locus-based associations, we found that several other regions showed association/interaction signals with nominal P<0.05. In conclusion, this study demonstrated that the GWIBA approach was successful for identifying novel loci, and the results provide new insights into the genetic architecture of common diseases. In addition, our PIAM program was capable of handling very large GWAS datasets that are likely to be produced in the future

Identification of microRNA-mRNA modules using microarray data

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs.</p> <p>Results</p> <p>We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest.</p> <p>Conclusions</p> <p>Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation.</p

Disordered Microbial Communities in the Upper Respiratory Tract of Cigarette Smokers

Cigarette smokers have an increased risk of infectious diseases involving the respiratory tract. Some effects of smoking on specific respiratory tract bacteria have been described, but the consequences for global airway microbial community composition have not been determined. Here, we used culture-independent high-density sequencing to analyze the microbiota from the right and left nasopharynx and oropharynx of 29 smoking and 33 nonsmoking healthy asymptomatic adults to assess microbial composition and effects of cigarette smoking. Bacterial communities were profiled using 454 pyrosequencing of 16S sequence tags (803,391 total reads), aligned to 16S rRNA databases, and communities compared using the UniFrac distance metric. A Random Forest machine-learning algorithm was used to predict smoking status and identify taxa that best distinguished between smokers and nonsmokers. Community composition was primarily determined by airway site, with individuals exhibiting minimal side-of-body or temporal variation. Within airway habitats, microbiota from smokers were significantly more diverse than nonsmokers and clustered separately. The distributions of several genera were systematically altered by smoking in both the oro- and nasopharynx, and there was an enrichment of anaerobic lineages associated with periodontal disease in the oropharynx. These results indicate that distinct regions of the human upper respiratory tract contain characteristic microbial communities that exhibit disordered patterns in cigarette smokers, both in individual components and global structure, which may contribute to the prevalence of respiratory tract complications in this population

The RNA Polymerase Dictates ORF1 Requirement and Timing of LINE and SINE Retrotransposition

Mobile elements comprise close to one half of the mass of the human genome. Only LINE-1 (L1), an autonomous non-Long Terminal Repeat (LTR) retrotransposon, and its non-autonomous partners—such as the retropseudogenes, SVA, and the SINE, Alu—are currently active human retroelements. Experimental evidence shows that Alu retrotransposition depends on L1 ORF2 protein, which has led to the presumption that LINEs and SINEs share the same basic insertional mechanism. Our data demonstrate clear differences in the time required to generate insertions between marked Alu and L1 elements. In our tissue culture system, the process of L1 insertion requires close to 48 hours. In contrast to the RNA pol II-driven L1, we find that pol III transcribed elements (Alu, the rodent SINE B2, and the 7SL, U6 and hY sequences) can generate inserts within 24 hours or less. Our analyses demonstrate that the observed retrotransposition timing does not dictate insertion rate and is independent of the type of reporter cassette utilized. The additional time requirement by L1 cannot be directly attributed to differences in transcription, transcript length, splicing processes, ORF2 protein production, or the ability of functional ORF2p to reach the nucleus. However, the insertion rate of a marked Alu transcript drastically drops when driven by an RNA pol II promoter (CMV) and the retrotransposition timing parallels that of L1. Furthermore, the “pol II Alu transcript” behaves like the processed pseudogenes in our retrotransposition assay, requiring supplementation with L1 ORF1p in addition to ORF2p. We postulate that the observed differences in retrotransposition kinetics of these elements are dictated by the type of RNA polymerase generating the transcript. We present a model that highlights the critical differences of LINE and SINE transcripts that likely define their retrotransposition timing

The TOP-SCOPE Survey of Planck Galactic Cold Clumps : Survey Overview and Results of an Exemplar Source, PGCC G26.53+0.17

The low dust temperatures (<14 K) of Planck Galactic cold clumps (PGCCs) make them ideal targets to probe the initial conditions and very early phase of star formation. "TOP-SCOPE" is a joint survey program targeting similar to 2000 PGCCs in J = 1-0 transitions of CO isotopologues and similar to 1000 PGCCs in 850 mu m continuum emission. The objective of the "TOP-SCOPE" survey and the joint surveys (SMT 10 m, KVN 21 m, and NRO 45 m) is to statistically study the initial conditions occurring during star formation and the evolution of molecular clouds, across a wide range of environments. The observations, data analysis, and example science cases for these surveys are introduced with an exemplar source, PGCC G26.53+0.17 (G26), which is a filamentary infrared dark cloud (IRDC). The total mass, length, and mean line mass (M/L) of the G26 filament are similar to 6200 M-circle dot, similar to 12 pc, and similar to 500 M-circle dot pc(-1), respectively. Ten massive clumps, including eight starless ones, are found along the filament. The most massive clump as a whole may still be in global collapse, while its denser part seems to be undergoing expansion owing to outflow feedback. The fragmentation in the G26 filament from cloud scale to clump scale is in agreement with gravitational fragmentation of an isothermal, nonmagnetized, and turbulent supported cylinder. A bimodal behavior in dust emissivity spectral index (beta) distribution is found in G26, suggesting grain growth along the filament. The G26 filament may be formed owing to large-scale compression flows evidenced by the temperature and velocity gradients across its natal cloud.Peer reviewe