Anti-citrullinated peptide autoantibodies, human leukocyte antigen shared epitope and risk of future rheumatoid arthritis: a nested case–control study

Introduction: The aim of this study was to characterize anti-citrullinated peptide antibody (ACPA) serostatus in pre-clinical rheumatoid arthritis (RA) with and without Human Leukocyte Antigen-Shared Epitope (HLA-SE) alleles. Methods: We identified 192 women in the Nurses’ Health Study cohorts with blood samples obtained 4 months to 17 years prior to medical record-confirmed RA diagnosis. Three controls were selected matched on age, cohort, menopausal status and post-menopausal hormone use. Reactivities to 18 ACPAs were measured using a custom BioPlex platform. We used conditional logistic regression to calculate the relative risk (RR) of RA for any ACPA-positive and peptide-specific ACPA-positive and examined RRs by time between blood draw and RA onset. Measures of multiplicative and additive interaction between any ACPA-positive and HLA-SE were calculated. Results: All ACPAs by peptide groups were significantly associated with RA risk, RRs ranged from 4.7 to 11.7. The association between ACPA and RA varied over time with the strongest association in those with blood draw less than 5 years before onset (RR 17.0 [95% CI 5.8 to 53.7]) and no association 10 or more years prior to onset (RR 1.4 [95% CI 0.5 to 4.3]). Individuals with both HLA-SE and any ACPA-positive had the highest risk of RA. HLA-SE-positive RA cases showed reactivity to more ACPA types than HLA-SE negative (χ2 test for trend, P = 0.01). Conclusions: There is increasing ACPA reactivity up to 10 years before RA onset with the strongest association within 5 years of RA onset. The magnitude of the response to ACPAs, in combination with the presence of HLA-SE, is most important for identifying those individuals with the highest risk of RA

All different or all the same? Exploring the diversity of professional practices in Portuguese school psychology

"Published online: 29 March 2016"Studies have generally characterized school psychologists as a relative homogenous population. Understanding the differences in professional practices and related variables is important for the development of the profession. Using a sample of 446 Portuguese school psychologists, this study used cluster analysis to identify distinct profiles of professional activity, based on practitioners’ time distribution among different target audiences (i.e.,students, parents, teachers, school board members, school non-professional staff, and other professionals within the school community). Three distinct profiles emerged from the data: a group highly oriented to work with students, a group that distributes time almost equitably between adults and students, and a group that concentrates attention and professional expertise on adults. Practice setting variables, such as school-psychologists-to-student ratio, schoolpsychologists-to-school ratio, number of referrals per year, and school community level of demand for different activities, were found to be significantly related to cluster membership. No personal- or professional-background-related variables differentiated the three groups. The main implications of these findings are discussed in light of recent literature regarding the models of service delivery for school psychologists

Robust Biomarkers: Methodologically Tracking Causal Processes in Alzheimer’s Measurement

In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological use of clinical biomarkers in pharmacological measurement: Some biomarkers, called ‘surrogate markers’, are used to substitute for a clinically meaningful endpoint corresponding to events and their penultimate risk factors. We confront the reliability of clinical biomarkers that are used to gather information about clinically meaningful endpoints. Our aim is to present a systematic methodology for assessing the reliability of multiple surrogate markers (and biomarkers in general). To do this we draw upon the robustness analysis literature in the philosophy of science and the empirical use of clinical biomarkers. After introducing robustness analysis we present two problems with biomarkers in relation to reliability. Next, we propose an intervention-based robustness methodology for organizing the reliability of biomarkers in general. We propose three relevant conditions for a robust methodology for biomarkers: (R1) Intervention-based demonstration of partial independence of modes: In biomarkers partial independence can be demonstrated through exogenous interventions that modify a process some number of “steps” removed from each of the markers. (R2) Comparison of diverging and converging results across biomarkers: By systematically comparing partially-independent biomarkers we can track under what conditions markers fail to converge in results, and under which conditions they successfully converge. (R3) Information within the context of theory: Through a systematic cross-comparison of the markers we can make causal conclusions as well as eliminate competing theories. We apply our robust methodology to currently developing Alzheimer’s research to show its usefulness for making causal conclusions

The Future of Rheumatoid Arthritis and Hand Surgery - Combining Evolutionary Pharmacology and Surgical Technique

Rheumatoid arthritis is a systemic autoimmune disease of uncertain aetiology, which is characterized primarily by synovial inflammation with secondary skeletal destructions

The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

<p>Abstract</p> <p>Background</p> <p>Social networks are theorized as significant influences in the innovation adoption and behavior change processes. Our understanding of how social networks operate within healthcare settings is limited. As a result, our ability to design optimal interventions that employ social networks as a method of fostering planned behavior change is also limited. Through this proposed project, we expect to contribute new knowledge about factors influencing uptake of knowledge translation interventions.</p> <p>Objectives</p> <p>Our specific aims include: To collect social network data among staff in two long-term care (LTC) facilities; to characterize social networks in these units; and to describe how social networks influence uptake and use of feedback reports.</p> <p>Methods and design</p> <p>In this prospective study, we will collect data on social networks in nursing units in two LTC facilities, and use social network analysis techniques to characterize and describe the networks. These data will be combined with data from a funded project to explore the impact of social networks on uptake and use of feedback reports. In this parent study, feedback reports using standardized resident assessment data are distributed on a monthly basis. Surveys are administered to assess report uptake. In the proposed project, we will collect data on social networks, analyzing the data using graphical and quantitative techniques. We will combine the social network data with survey data to assess the influence of social networks on uptake of feedback reports.</p> <p>Discussion</p> <p>This study will contribute to understanding mechanisms for knowledge sharing among staff on units to permit more efficient and effective intervention design. A growing number of studies in the social network literature suggest that social networks can be studied not only as influences on knowledge translation, but also as possible mechanisms for fostering knowledge translation. This study will contribute to building theory to design such interventions.</p

Current quality of life and its determinants among opiate-dependent individuals five years after starting methadone treatment

This study explores the current QoL of opiate-dependent individuals who started outpatient methadone treatment at least 5 years ago and assesses the influence of demographic, psychosocial, drug and health-related variables on individuals' QoL. Participants (n = 159) were interviewed about their current QoL, psychological distress and severity of drug-related problems, using the Lancashire Quality of Life Profile, the Brief Symptom Inventory and the Addiction Severity Index. Potential determinants of QoL were assessed in a multiple linear regression analysis. Five years after the start of methadone treatment, opiate-dependent individuals report low QoL scores on various domains. No association was found between drug-related variables and QoL, but a significant negative impact of psychological distress was identified. Severity of psychological distress, taking medication for psychological problems and the inability to change one's living situation were associated with lower QoL. Having at least one good friend and a structured daily activity had a significant, positive impact on QoL. Opiate-dependent individuals' QoL is mainly determined by their psychological well-being and a number of psychosocial variables. These findings highlight the importance of a holistic approach to treatment and support in methadone maintenance treatment, which goes beyond fixing the negative physical consequences of opiate dependence

Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes

Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs