367 research outputs found
A discrete cluster of urinary biomarkers discriminates between active systemic lupus erythematosus patients with and without glomerulonephritis.
BackgroundManagement of lupus nephritis (LN) would be greatly aided by the discovery of biomarkers that accurately reflect changes in disease activity. Here, we used a proteomics approach to identify potential urinary biomarkers associated with LN.MethodsUrine was obtained from 60 LN patients with paired renal biopsies, 25 active non-LN SLE patients, and 24 healthy controls. Using Luminex, 128 analytes were quantified and normalized to urinary creatinine levels. Data were analyzed by linear modeling and non-parametric statistics, with corrections for multiple comparisons. A second cohort of 33 active LN, 16 active non-LN, and 30 remission LN SLE patients was used to validate the results.ResultsForty-four analytes were identified that were significantly increased in active LN as compared to active non-LN. This included a number of unique proteins (e.g., TIMP-1, PAI-1, PF4, vWF, and IL-15) as well as known candidate LN biomarkers (e.g., adiponectin, sVCAM-1, and IL-6), that differed markedly (>4-fold) between active LN and non-LN, all of which were confirmed in the validation cohort and normalized in remission LN patients. These proteins demonstrated an enhanced ability to discriminate between active LN and non-LN patients over several previously reported biomarkers. Ten proteins were found to significantly correlate with the activity score on renal biopsy, eight of which strongly discriminated between active proliferative and non-proliferative/chronic renal lesions.ConclusionsA number of promising urinary biomarkers that correlate with the presence of active renal disease and/or renal biopsy changes were identified and appear to outperform many of the existing proposed biomarkers
Autoantibodies in Systemic Lupus Erythematosus Target Mitochondrial RNA
The mitochondrion supplies energy to the cell and regulates apoptosis. Unlike other mammalian organelles, mitochondria are formed by binary fission and cannot be directly produced by the cell. They contain numerous copies of a compact circular genome that encodes RNA molecules and proteins involved in mitochondrial oxidative phosphorylation. Whereas, mitochondrial DNA (mtDNA) activates the innate immune system if present in the cytosol or the extracellular milieu, it is also the target of circulating autoantibodies in systemic lupus erythematosus (SLE). However, it is not known whether mitochondrial RNA is also recognized by autoantibodies in SLE. In the present study, we evaluated the presence of autoantibodies targeting mitochondrial RNA (AmtRNA) in SLE. We quantified AmtRNA in an inducible model of murine SLE. The AmtRNA were also determined in SLE patients and healthy volunteers. AmtRNA titers were measured in both our induced model of murine SLE and in human SLE, and biostatistical analyses were performed to determine whether the presence and/or levels of AmtRNA were associated with clinical features expressed by SLE patients. Both IgG and IgM classes of AmtRNA were increased in SLE patients (n = 86) compared to healthy controls (n = 30) (p < 0.0001 and p = 0.0493, respectively). AmtRNA IgG levels correlated with anti-mtDNA-IgG titers (rs = 0.54, p < 0.0001) as well as with both IgG and IgM against β-2-glycoprotein I (anti-β2GPI; rs = 0.22, p = 0.05), and AmtRNA-IgG antibodies were present at higher levels when patients were positive for autoantibodies to double-stranded-genomic DNA (p < 0.0001). AmtRNA-IgG were able to specifically discriminate SLE patients from healthy controls, and were negatively associated with plaque formation (p = 0.04) and lupus nephritis (p = 0.03). Conversely, AmtRNA-IgM titers correlated with those of anti-β2GPI-IgM (rs = 0.48, p < 0.0001). AmtRNA-IgM were higher when patients were positive for anticardiolipin antibodies (aCL-IgG: p = 0.01; aCL-IgM: p = 0.002), but AmtRNA-IgM were not associated with any of the clinical manifestations assessed. These findings identify mtRNA as a novel mitochondrial antigen target in SLE, and support the concept that mitochondria may provide an important source of circulating autoantigens in SLE
Alpha2beta1 Integrin (VLA-2) Protects Activated Human Effector T Cells From Methotrexate-Induced Apoptosis
β1 integrins are critical for T cell migration, survival and costimulation. The integrin α2β1, which is a receptor for collagen, also named VLA-2, is a major costimulatory pathway of effector T cells and has been implicated in arthritis pathogenesis. Herein, we have examined its ability to promote methotrexate (MTX) resistance by enhancing effector T cells survival. Our results show that attachment of anti-CD3-activated human polarized Th17 cells to collagen but not to fibronectin or laminin led to a significant reduction of MTX-induced apoptosis. The anti-CD3+collagen-rescued cells still produce significant amounts of IL-17 and IFNγ upon their reactivation indicating that their inflammatory nature is preserved. Mechanistically, we found that the prosurvival role of anti-CD3+collagen involves activation of the MTX transporter ABCC1 (ATP Binding Cassette subfamily C Member 1). Finally, the protective effect of collagen/α2β1 integrin on MTX-induced apoptosis also occurs in memory CD4+ T cells isolated from rheumatoid arthritis (RA) patients suggesting its clinical relevance. Together these results show that α2β1 integrin promotes MTX resistance of effector T cells, and suggest that it could contribute to the development of MTX resistance that is seen in RA
Prospectives
Tiré de: Prospectives, vol. 11, no 5, déc. 1975Titre de l'écran-titre (visionné le 24 janv. 2013
Local and systemic in vivo responses to osseointegrative titanium nanotube surfaces
Orthopedic implants requiring osseointegration are often surface modified; however, implants may shed these coatings and generate wear debris leading to complications. Titanium nanotubes (TiNT), a new surface treatment, may promote osseointegration. In this study, in vitro (rat marrow-derived bone marrow cell attachment and morphology) and in vivo (rat model of intramedullary fixation) experiments characterized local and systemic responses of two TiNT surface morphologies, aligned and trabecular, via animal and remote organ weight, metal ion, hematologic, and nondecalcified histologic analyses. In vitro experiments showed total adherent cells on trabecular and aligned TiNT surfaces were greater than control at 30 min and 4 h, and cells were smaller in diameter and more eccentric. Control animals gained more weight, on average; however, no animals met the institutional trigger for weight loss. No hematologic parameters (complete blood count with differential) were significantly different for TiNT groups vs. control. Inductively coupled plasma mass spectrometry (ICP-MS) showed greater aluminum levels in the lungs of the trabecular TiNT group than in those of the controls. Histologic analysis demonstrated no inflammatory infiltrate, cytotoxic, or necrotic conditions in proximity of K-wires. There were significantly fewer eosinophils/basophils and neutrophils in the distal region of trabecular TiNT-implanted femora; and, in the midshaft of aligned TiNT-implanted femora, there were significantly fewer foreign body giant/multinucleated cells and neutrophils, indicating a decreased immune response in aligned TiNT-implanted femora compared to controls
Patterns of multimorbidity in working Australians
Background: Multimorbidity is becoming more prevalent. Previously-used methods of assessing multimorbidity relied on counting the number of health conditions, often in relation to an index condition (comorbidity), or grouping conditions based on body or organ systems. Recent refinements in statistical approaches have resulted in improved methods to capture patterns of multimorbidity, allowing for the identification of nonrandomly occurring clusters of multimorbid health conditions. This paper aims to identify nonrandom clusters of multimorbidity.Methods: The Australian Work Outcomes Research Cost-benefit (WORC) study cross-sectional screening dataset (approximately 78,000 working Australians) was used to explore patterns of multimorbidity. Exploratory factor analysis was used to identify nonrandomly occurring clusters of multimorbid health conditions.Results: Six clinically-meaningful groups of multimorbid health conditions were identified. These were: factor 1: arthritis, osteoporosis, other chronic pain, bladder problems, and irritable bowel; factor 2: asthma, chronic obstructive pulmonary disease, and allergies; factor 3: back/neck pain, migraine, other chronic pain, and arthritis; factor 4: high blood pressure, high cholesterol, obesity, diabetes, and fatigue; factor 5: cardiovascular disease, diabetes, fatigue, high blood pressure, high cholesterol, and arthritis; and factor 6: irritable bowel, ulcer, heartburn, and other chronic pain. These clusters do not fall neatly into organ or body systems, and some conditions appear in more than one cluster.Conclusions: Considerably more research is needed with large population-based datasets and a comprehensive set of reliable health diagnoses to better understand the complex nature and composition of multimorbid health conditions
Estimating Grizzly Bear Use of Large Ungulate Carcasses With GPS Telemetry Data
Ungulate meat is among the most calorie-rich food sources available to grizzly bears (Ursus arctos) in the greater Yellowstone ecosystem (GYE). However, the ephemeral and unpredictable nature of carcasses makes them difficult to study and their influence on grizzly bear foraging and spatial ecology is poorly understood. We developed a spatial-clustering technique specifically for detecting grizzly bear use of large ungulate carcasses using Global Positioning System (GPS) telemetry locations (n = 54 bear years). We used the DBScan algorithm to identify GPS clusters of individual bears (n = 2,038) and intersected these clusters with an independent dataset of site visits to recent bear movement paths based from randomly selected days (n = 732 site visits; 2004–2011) resulting in 174 clusters associated with field measured bear behavior. Using a suite of predictor variables derived from GPS telemetry locations, e.g., duration of cluster, area used, activity sensor values, re-visitation rate, we used multinomial logistic regression to predict the probability of belonging to each of the five response classes (resting, multiple-use, low-biomass carcass, high-biomass carcass, old carcass). Focusing on the high-biomass carcass category, for which our top model correctly classified 88 percent of the carcasses correctly, we applied our approach to a larger dataset of GPS data to examine trends in large-ungulate carcass using of grizzly bears in the GYE from 2002-2011. We found quantitative support for a positive effect of year and mortality adjusted white bark pine cone counts on the carcass-use index during the fall months (Sep and Oct) from 2002-2011
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ABSTRACT. Objective. We describe the pattern of incidence of thrombovascular events after diagnosis of systemic lupus erythematosus (SLE) in a cohort of lupus patients. Methods. Descriptive study of prospectively collected data using incidence rates of thrombovascular events and 95% confidence intervals (CI) calculated for predetermined periods of observation. KaplanMeier survival curves were plotted to estimate thrombovascular event-free survival. Results. Among 426 individuals, person-years contributed were as follows: 399 persons and 4356.0 person-years for all events; 417 persons and 4691.9 person-years for arterial events; and 408 persons and 4846.6 person-years for venous events. The incidence of thrombovascular events was highest during the first year after SLE diagnosis (4.00, 95% CI 2.24-6.59) and after 20 years (ranging from 3.32, 95% CI 1.52-6.30, to 4.99, 95% CI 0.60-18.01), and was lowest between 1 and 5 years after SLE diagnosis (1.00, 95% CI 0.53-1.72). A similar pattern was observed for arterial events, while venous events showed a higher incidence rate only in the first 30 days after SLE diagnosis (12.06, 95% CI 3.29-30.87) and remained low afterwards. The probabilities of remaining event-free at 5, 10, and 15 years were as follows: 0.92, 0.85, and 0.78, respectively, for all thrombovascular events; 0.95, 0.88, and 0.82, respectively, for arterial events; and 0.98, 0.95, and 0.94, respectively, for venous events. Conclusion. Thrombovascular events occur throughout the course of lupus, with the highest risk of arterial or venous events in the first year after diagnosis, and the pattern of occurrence varying there
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