Validation of the Chronic Pain Acceptance Questionnaire-8 in an Australian pain clinic sample

Background: Recently, an 8-item short-form version of the Chronic Pain Acceptance Questionnaire (CPAQ-8) was developed predominantly in an internet sample. Further investigation of the factor structure in a multidisciplinary pain clinic sample is required. Investigation of the concurrent validity of the CPAQ-8 after accounting for the effects of variables commonly measured in the pain clinic setting is also necessary. Purpose: This study examines the factor structure and concurrent validity of the CPAQ-8 in a sample of treatmentseeking patients who attended a multidisciplinary pain clinic. Methods: Participants were 334 patients who attended an Australian multidisciplinary pain service. Participants completed the CPAQ, a demographic questionnaire, and measures of patient adjustment and functioning. Results: Confirmatory factor analysis identified a two-factor 8-item model consisting of Activity Engagement and Pain Willingness factors (SRMR=0.039, RMSEA=0.063, CFI=0.973, TLI=0.960) was superior to both the CPAQ and CPAQ with an item removed. The CPAQ and CPAQ-8 total scores were highly correlated (r=0.93). After accounting for pain intensity, the CPAQ-8 was a significant predictor of depression, anxiety, stress, and disability. The subscales of the CPAQ-8 were both unique contributors to depression and disability in regression analyses, after accounting for pain intensity and kinesiophobia, and after accounting for pain intensity and catastrophizing. Conclusions: The CPAQ-8 has a sound factor structure and similar psychometric properties to the CPAQ; it may have clinical utility as a measure of pain acceptance in treatmentseeking, chronic pain patients

The influence of 'significant others' on persistent back pain and work participation: a qualitative exploration of illness perceptions

Background Individual illness perceptions have been highlighted as important influences on clinical outcomes for back pain. However, the illness perceptions of 'significant others' (spouse/partner/close family member) are rarely explored, particularly in relation to persistent back pain and work participation. The aim of this study was to initiate qualitative research in this area in order to further understand these wider influences on outcome. Methods Semi-structured interviews based on the chronic pain version of the Illness Perceptions Questionnaire-Revised were conducted with a convenience sample of UK disability benefit claimants, along with their significant others (n=5 dyads). Data were analysed using template analysis. Results Significant others shared, and perhaps further reinforced, claimants' unhelpful illness beliefs including fear of pain/re-injury associated with certain types of work and activity, and pessimism about the likelihood of return to work. In some cases, significant others appeared more resigned to the permanence and negative inevitable consequences of the claimant's back pain condition on work participation, and were more sceptical about the availability of suitable work and sympathy from employers. In their pursuit of authenticity, claimants were keen to stress their desire to work whilst emphasising how the severity and physical limitations of their condition prevented them from doing so. In this vein, and seemingly based on their perceptions of what makes a 'good' significant other, significant others acted as a 'witness to pain', supporting claimants' self-limiting behaviour and statements of incapacity, often responding with empathy and assistance. The beliefs and responses of significant others may also have been influenced by their own experience of chronic illness, thus participants lives were often intertwined and defined by illness. Conclusions The findings from this exploratory study reveal how others and wider social circumstances might contribute both to the propensity of persistent back pain and to its consequences. This is an area that has received little attention to date, and wider support of these findings may usefully inform the design of future intervention programmes aimed at restoring work participation

A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

© 2014 Haider et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options

The impact of different DNA extraction kits and laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing

Peer reviewedPublisher PD

Natural polymorphisms in C. elegans HECW-1 E3 ligase affect pathogen avoidance behaviour

available in PMC 2012 June 22.Heritable variation in behavioural traits generally has a complex genetic basis1, and thus naturally occurring polymorphisms that influence behaviour have been defined in only rare instances2,3. The isolation of wild strains of Caenorhabditis elegans has facilitated the study of natural genetic variation in this species4 and provided insights into its diverse microbial ecology5. C. elegans responds to bacterial infection with conserved innate immune responses6-8 and, while lacking the immunological memory of vertebrate adaptive immunity, exhibits an aversive learning response to pathogenic bacteria9. Here, we report the molecular characterization of naturally occurring coding polymorphisms in a C. elegans gene encoding a conserved HECT domain-containing E3 ubiquitin ligase, HECW-1. We show that two distinct polymorphisms in neighbouring residues of HECW-1 each affect C. elegans behavioural avoidance of a lawn of Pseudomonas aeruginosa. Neuronspecific rescue and ablation experiments, and genetic interaction analysis suggest that HECW-1 functions in a pair of sensory neurons to inhibit P. aeruginosa lawn avoidance behaviour through inhibition of the neuropeptide receptor NPR-110, which we have previously shown promotes P. aeruginosa lawn avoidance behaviour11. Our data establish a molecular basis for natural variation in a C. elegans behaviour that may undergo adaptive changes in response to microbial pathogens.National Institutes of Health (U.S.) (NIH Grant GM084477

Mammalian microRNAs predominantly act to decrease target mRNA levels

MicroRNAs (miRNAs) are endogenous ~22-nucleotide RNAs that mediate important gene-regulatory events by pairing to the mRNAs of protein-coding genes to direct their repression. Repression of these regulatory targets leads to decreased translational efficiency and/or decreased mRNA levels, but the relative contributions of these two outcomes have been largely unknown, particularly for endogenous targets expressed at low-to-moderate levels. Here, we use ribosome profiling to measure the overall effects on protein production and compare these to simultaneously measured effects on mRNA levels. For both ectopic and endogenous miRNA regulatory interactions, lowered mRNA levels account for most (≥84%) of the decreased protein production. These results show that changes in mRNA levels closely reflect the impact of miRNAs on gene expression and indicate that destabilization of target mRNAs is the predominant reason for reduced protein output.National Institutes of Health (U.S.

Detection of Fused Genes in Eukaryotic Genomes using Gene deFuser: Analysis of the Tetrahymena thermophila genome

<p>Abstract</p> <p>Background</p> <p>Fused genes are important sources of data for studies of evolution and protein function. To date no service has been made available online to aid in the large-scale identification of fused genes in sequenced genomes. We have developed a program, Gene deFuser, that analyzes uploaded protein sequence files for characteristics of gene fusion events and presents the results in a convenient web interface.</p> <p>Results</p> <p>To test the ability of this software to detect fusions on a genome-wide scale, we analyzed the 24,725 gene models predicted for the ciliated protozoan <it>Tetrahymena thermophila</it>. Gene deFuser detected members of eight of the nine families of gene fusions known or predicted in this species and identified nineteen new families of fused genes, each containing between one and twelve members. In addition to these genuine fusions, Gene deFuser also detected a particular type of gene misannotation, in which two independent genes were predicted as a single transcript by gene annotation tools. Twenty-nine of the artifacts detected by Gene deFuser in the initial annotation have been corrected in subsequent versions, with a total of 25 annotation artifacts (about 1/3 of the total fusions identified) remaining in the most recent annotation.</p> <p>Conclusions</p> <p>The newly identified <it>Tetrahymena </it>fusions belong to classes of genes involved in processes such as phospholipid synthesis, nuclear export, and surface antigen generation. These results highlight the potential of Gene deFuser to reveal a large number of novel fused genes in evolutionarily isolated organisms. Gene deFuser may also prove useful as an ancillary tool for detecting fusion artifacts during gene model annotation.</p

Interplay between genetic predisposition, macronutrient intake and type 2 diabetes incidence: analysis within EPIC-InterAct across eight European countries.

AIMS/HYPOTHESIS: Gene-macronutrient interactions may contribute to the development of type 2 diabetes but research evidence to date is inconclusive. We aimed to increase our understanding of the aetiology of type 2 diabetes by investigating potential interactions between genes and macronutrient intake and their association with the incidence of type 2 diabetes. METHODS: We investigated the influence of interactions between genetic risk scores (GRSs) for type 2 diabetes, insulin resistance and BMI and macronutrient intake on the development of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a prospective case-cohort study across eight European countries (N = 21,900 with 9742 incident type 2 diabetes cases). Macronutrient intake was estimated from diets reported in questionnaires, including proportion of energy derived from total carbohydrate, protein, fat, plant and animal protein, saturated, monounsaturated and polyunsaturated fat and dietary fibre. Using multivariable-adjusted Cox regression, we estimated country-specific interaction results on the multiplicative scale, using random-effects meta-analysis. Secondary analysis used isocaloric macronutrient substitution. RESULTS: No interactions were identified between any of the three GRSs and any macronutrient intake, with low-to-moderate heterogeneity between countries (I2 range 0-51.6%). Results were similar using isocaloric macronutrient substitution analyses and when weighted and unweighted GRSs and individual SNPs were examined. CONCLUSIONS/INTERPRETATION: Genetic susceptibility to type 2 diabetes, insulin resistance and BMI did not modify the association between macronutrient intake and incident type 2 diabetes. This suggests that macronutrient intake recommendations to prevent type 2 diabetes do not need to account for differences in genetic predisposition to these three metabolic conditions

Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity.

We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterize their association with intermediate phenotypes, and to investigate their role in type 2 diabetes (T2D) risk among normal-weight, overweight, and obese individuals. We investigated the association of genetic scores with euglycemic-hyperinsulinemic clamp- and oral glucose tolerance test-based measures of insulin resistance and secretion and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight, and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (β in SDs per allele [95% CI], -0.03 [-0.04, -0.01]; P = 0.004). This score was associated with lower BMI (-0.01 [-0.01, -0.0]; P = 0.02) and gluteofemoral fat mass (-0.03 [-0.05, -0.02; P = 1.4 × 10(-6)) and with higher alanine transaminase (0.02 [0.01, 0.03]; P = 0.002) and γ-glutamyl transferase (0.02 [0.01, 0.03]; P = 0.001). While the secretion score had a stronger association with T2D in leaner individuals (Pinteraction = 0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI or waist strata (Pinteraction > 0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size.The MRC-Ely Study was funded by the Medical Research Council (MC_U106179471) and Diabetes UK. We are grateful to all the volunteers, and to the staff of St. Mary’s Street Surgery, Ely and the study team. The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team and the Epidemiology Field, Data and Laboratory teams. DBS and RKS are funded by the Wellcome Trust, the U.K. NIHR Cambridge Biomedical Research Centre and the MRC Centre for Obesity and Related Metabolic Disease. Genotyping in ULSAM was performed by the SNP&SEQ Technology Platform in Uppsala (www.genotyping.se), which is supported by Uppsala University, Uppsala University Hospital, Science for Life Laboratory - Uppsala and the Swedish Research Council (Contracts 80576801 and 70374401). The RISC Study was supported by European Union grant QLG1-CT-2001-01252 and AstraZeneca. The RISC Study Project Management Board: B Balkau, F Bonnet, SW Coppack, JM Dekker, E Ferrannini, A Golay, A Mari, A Natali, J Petrie, M Walker. We thank all EPIC participants and staff for their contribution to the study. We thank the lab team at the MRC Epidemiology Unit for sample management and Nicola Kerrison of the MRC Epidemiology Unit for data management. Funding for the EPIC-InterAct project was provided by the EU FP6 programme (grant number LSHM_CT_2006_037197).In addition, EPIC-InterAct investigators acknowledge funding from the following agencies: PWF: Swedish Research Council, Novo Nordisk, Swedish Diabetes Association, Swedish Heart-Lung Foundation; LCG: Swedish Research Council; NS: Health Research Fund (FIS) of the Spanish Ministry of Health; Murcia Regional Government (Nº 6236); LA: We thank the participants of the Spanish EPIC cohort for their contribution to the study as well as to the team of trained nurses who participated in the recruitment; RK: German Cancer Aid, German Ministry of Research (BMBF); TJK: Cancer Research UK; PMN: Swedish Research Council; KO: Danish Cancer Society; SP: Compagnia di San Paolo; JRQ: Asturias Regional Government; OR: The Västerboten County Council; AMWS and DLvdA: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands; RT: AIRE-ONLUS Ragusa, AVIS-Ragusa, Sicilian Regional Government; IS: Verification of diabetes cases was additionally funded by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht; IB: Wellcome Trust grant 098051 and United Kingdom NIHR Cambridge Biomedical Research Centre; MIM: InterAct, Wellcome Trust (083270/Z/07/Z), MRC (G0601261); ER: Imperial College Biomedical Research.This is the author accepted manuscript. The final version is available from the American Diabetes Association via http://dx.doi.org/10.2337/db14-031