Osteoprotegerin and coronary artery disease in type 2 diabetic patients with microalbuminuria

<p>Abstract</p> <p>Objective</p> <p>Plasma osteoprotegerin (P-OPG) is an independent predictor of cardiovascular disease in diabetic and other populations. OPG is a bone-related glycopeptide produced by vascular smooth muscle cells and increased P-OPG may reflect arterial damage. We investigated the correlation between P-OPG and coronary artery disease (CAD) in asymptomatic type 2 diabetic patients with microalbuminuria.</p> <p>Methods</p> <p>P-OPG was measured in 200 asymptomatic diabetic patients without known cardiac disease. Patients with P-NT-proBNP >45.2 ng/l and/or coronary calcium score (CCS) ≥400 were stratified as high risk of CAD (n = 133), and all other patients as low risk patients (n = 67). High risk patients were examined by myocardial perfusion imaging (MPI; n = 109), and/or CT-angiography (n = 20), and/or coronary angiography (CAG; n = 86). Significant CAD was defined by presence of significant myocardial perfusion defects at MPI and/or >70% coronary artery stenosis at CAG.</p> <p>Results</p> <p>Significant CAD was demonstrated in 70 of the high risk patients and of these 23 patients had >70% coronary artery stenosis at CAG. Among high risk patients, increased P-OPG was an independent predictor of significant CAD (adjusted odds ratio [CI] 3.11 [1.01-19.54] and 3.03 [1.00-9.18] for second and third tertile vs.first tertile P-OPG, respectively) and remained so after adjustments for NT-proBNP and CCS. High P-OPG was also associated with presence of >70% coronary artery stenosis(adjusted odds ratio 14.20 [1.35-148.92] for third vs. first tertile P-OPG), and 91% of patients with low (first tertile) P-OPG did not have >70% coronary artery stenosis.</p> <p>Conclusions</p> <p>Elevated P-OPG is an independent predictor of the presence of CAD in asymptomatic type 2 diabetic patients with microalbuminuria.</p

Exercise training does not improve myocardial diastolic tissue velocities in Type 2 diabetes

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Plasma neutrophil gelatinase associated lipocalin (NGAL) is associated with kidney function in uraemic patients before and after kidney transplantation

<p>Abstract</p> <p>Background</p> <p>Neutrophil gelatinase associated lipocalin (NGAL) is a biomarker of kidney injury. We examined plasma levels of NGAL in a cohort of 57 kidney allograft recipients (Tx group, 39 ± 13 years), a uraemic group of 40 patients remaining on the waiting list (47 ± 11 years) and a control group of 14 healthy subjects matched for age, sex and body mass index (BMI). The kidney graft recipients were studied at baseline before transplantation and 3 and 12 months after transplantation and the uraemic group at baseline and after 12 months.</p> <p>Methods</p> <p>NGAL was measured using a validated in-house Time-Resolved Immuno-flourometric assay (TRIFMA). Repeated measurements differed by < 10% and mean values were used for statistical analyses. Spearman rank order correlation analysis and the Kruskal-Wallis non-parametric test were used to evaluate the association of NGAL concentrations with clinical parameters.</p> <p>Results</p> <p>Plasma NGAL levels before transplantation in the Tx and uraemic groups were significantly higher than in the healthy controls (1,251 μg/L, 1,478 μg/L vs. 163 μg/L, p < 0.0001). In the Tx group NGAL concentrations were associated with serum creatinine (R = 0.51, p < 0.0001), duration of end-stage renal failure (R = 0.41, p = 0.002) and leukocyte count (R = 0.29, p < 0.026). At 3 and 12 months plasma NGAL concentrations declined to 223 μg/L and 243 μg/L, respectively and were associated with homocysteine (R = 0.39, p = 0.0051 and R = 0.47, p = 0.0007).</p> <p>Conclusions</p> <p>Plasma NGAL is a novel marker of kidney function, which correlates to duration of end-stage renal failure (ESRD) and serum creatinine in uraemic patients awaiting kidney transplantation. Plasma NGAL is associated with homocysteine in transplanted patients. The prognostic value of these findings requires further studies.</p

Modeled deposition of nitrogen and sulfur in Europe estimated by 14 air quality model systems: evaluation, effects of changes in emissions and implications for habitat protection

The evaluation and intercomparison of air quality models is key to reducing model errors and uncertainty. The projects AQMEII3 and EURODELTA-Trends, in the framework of the Task Force on Hemispheric Transport of Air Pollutants and the Task Force on Measurements and Modelling, respectively (both task forces under the UNECE Convention on the Long Range Transport of Air Pollution, LTRAP), have brought together various regional air quality models to analyze their performance in terms of air concentrations and wet deposition, as well as to address other specific objectives. This paper jointly examines the results from both project communities by intercomparing and evaluating the deposition estimates of reduced and oxidized nitrogen (N) and sulfur (S) in Europe simulated by 14 air quality model systems for the year 2010. An accurate estimate of deposition is key to an accurate simulation of atmospheric concentrations. In addition, deposition fluxes are increasingly being used to estimate ecological impacts. It is therefore important to know by how much model results differ and how well they agree with observed values, at least when comparison with observations is possible, such as in the case of wet deposition. This study reveals a large variability between the wet deposition estimates of the models, with some performing acceptably (according to previously defined criteria) and others underestimating wet deposition rates. For dry deposition, there are also considerable differences between the model estimates. An ensemble of the models with the best performance for N wet deposition was made and used to explore the implications of N deposition in the conservation of protected European habitats. Exceedances of empirical critical loads were calculated for the most common habitats at a resolution of 100  ×  100 m2 within the Natura 2000 network, and the habitats with the largest areas showing exceedances are determined. Moreover, simulations with reduced emissions in selected source areas indicated a fairly linear relationship between reductions in emissions and changes in the deposition rates of N and S. An approximate 20 % reduction in N and S deposition in Europe is found when emissions at a global scale are reduced by the same amount. European emissions are by far the main contributor to deposition in Europe, whereas the reduction in deposition due to a decrease in emissions in North America is very small and confined to the western part of the domain. Reductions in European emissions led to substantial decreases in the protected habitat areas with critical load exceedances (halving the exceeded area for certain habitats), whereas no change was found, on average, when reducing North American emissions in terms of average values per habitat

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

Funder: Funder: Fundación bancaria ‘La Caixa’ Number: LCF/PR/PR16/51110003 Funder: Grifols SA Number: LCF/PR/PR16/51110003 Funder: European Union/EFPIA Innovative Medicines Initiative Joint Number: 115975 Funder: JPco-fuND FP-829-029 Number: 733051061Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease

Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues

The Influence of Climate Change on Atmospheric Deposition of Mercury in the Arctic—A Model Sensitivity Study

Mercury (Hg) is a global pollutant with adverse health effects on humans and wildlife. It is of special concern in the Arctic due to accumulation in the food web and exposure of the Arctic population through a rich marine diet. Climate change may alter the exposure of the Arctic population to Hg. We have investigated the effect of climate change on the atmospheric Hg transport to and deposition within the Arctic by making a sensitivity study of how the atmospheric chemistry-transport model Danish Eulerian Hemispheric Model (DEHM) reacts to climate change forcing. The total deposition of Hg to the Arctic is 18% lower in the 2090s compared to the 1990s under the applied Special Report on Emissions Scenarios (SRES-A1B) climate scenario. Asia is the major anthropogenic source area (25% of the deposition to the Arctic) followed by Europe (6%) and North America (5%), with the rest arising from the background concentration, and this is independent of the climate. DEHM predicts between a 6% increase (Status Quo scenario) and a 37% decrease (zero anthropogenic emissions scenario) in Hg deposition to the Arctic depending on the applied emission scenario, while the combined effect of future climate and emission changes results in up to 47% lower Hg deposition

Occurrence and Seasonality of Cyclic Volatile Methyl Siloxanes in Arctic Air

Cyclic volatile methyl siloxanes (cVMS) are present in technical applications and personal care products. They are predicted to undergo long-range atmospheric transport, but measurements of cVMS in remote areas remain scarce. An active air sampling method for decamethylcyclopentasiloxane (D5) was further evaluated to include hexamethylcyclotrisiloxane (D3), octamethylcyclotetrasiloxane (D4), and dodecamethylcyclohexasiloxane (D6). Air samples were collected at the Zeppelin observatory in the remote Arctic (79° N, 12° E) with an average sampling time of 81 ± 23 h in late summer (August−October) and 25 ± 10 h in early winter (November−December) 2011. The average concentrations of D5 and D6 in late summer were 0.73 ± 0.31 and 0.23 ± 0.17 ng/m3, respectively, and 2.94 ± 0.46 and 0.45 ± 0.18 ng/m3 in early winter, respectively. Detection of D5 and D6 in the Arctic atmosphere confirms their long-range atmospheric transport. The D5 measurements agreed well with predictions from a Eulerian atmospheric chemistry−transport model, and seasonal variability was explained by the seasonality in the OH radical concentrations. These results extend our understanding of the atmospheric fate of D5 to high latitudes, but question the levels of D3 and D4 that have previously been measured at Zeppelin with passive air samplers.acceptedVersio

A dynamic model to study the exchange of gas-phase POPs between air and a seasonal snowpack.

An arctic snow model was developed to predict the exchange of vapor-phase persistent organic pollutants between the atmosphere and the snowpack over a winter season. Using modeled meteorological data simulating conditions in the Canadian High Arctic, a single-layer snowpack was created on the basis of the precipitation rate, with the snow depth, snow specific surface area, density, and total surface area (TSA) evolving throughout the annual time series. TSA, an important parameter affecting the vapor-sorbed quantity of chemicals in snow, was within a factor of 5 of measured values. Net fluxes for fluorene, phenanthrene, PCB-28 and -52, and α- and γ-HCH (hexachlorocyclohexane) were predicted on the basis of their wet deposition (snowfall) and vapor exchange between the snow and atmosphere. Chemical fluxes were found to be highly dynamic, whereby deposition was rapidly offset by evaporative loss due to snow settling (i.e., changes in TSA). Differences in chemical behavior over the course of the season (i.e., fluxes, snow concentra tions) were largely dependent on the snow/air partition coefficients (Ksa). Chemicals with relatively higher Ksa values such as α- and γ-HCH were efficiently retained within the snowpack until later in the season compared to fluorene, phenathrene, and PCB-28 and -52. Average snow and air concentrations predicted by the model were within a factor of 5−10 of values measured from arctic field studies, but tended to be overpredicted for those chemicals with higher Ksa values (i.e., HCHs). Sensitivity analysis revealed that snow concentrations were more strongly influenced by Ksa than either inclusion of wind ventilation of the snowpack or other changes in physical parameters. Importantly, the model highlighted the relevance of the arctic snowpack in influencing atmospheric concentrations. For the HCHs, evaporative fluxes from snow were more pronounced in April and May, toward the end of the winter, providing evidence that the snowpack plays an important role in influencing the seasonal increase in air concentrations for these compounds at this time of year