Associations between ambient wood smoke and other particulate pollutants and biomarkers of systemic inflammation, coagulation and thrombosis in cardiac patients.

BACKGROUND: Increased particulate air pollution has been associated with both an increased risk of myocardial infarction (MI) and adverse changes in cardiac biomarkers. Up to 30% of ambient wintertime fine particles (PM2.5) in Rochester, NY are from wood burning. Our study examined associations between ambient levels of a marker of wood smoke (Delta-C) and other particulate air pollutants and biomarkers of inflammation, coagulation and thrombosis. METHODS: We measured blood concentrations of C-reactive protein (CRP), D-dimer, fibrinogen, P-selectin, platelet factor 4 (PF-4), von Willebrand factor (vWF), and myeloperoxidase (MPO) of 135 patients undergoing cardiac catheterization during the winters of 2011-2013. We coupled these data with hourly ambient concentrations of Delta-C, black carbon (BC; marker of traffic pollution), and ultrafine (10-100nm; UFP), accumulation mode (100-500nm; AMP), and fine particles (<2.5µm; PM2.5). Using linear regression models, we estimated the change in each biomarker associated with increased pollutant concentrations at intervals between 1 and 96h preceding blood collection. RESULTS: Each 0.13µg/m3 increase in Delta-C concentration in the prior 12h was associated with a 0.91% increase in fibrinogen levels (95% CI=0.23%, 1.59%), but unexpectedly in the prior 48h, each 0.17µg/m3 increase in Delta-C concentration was associated with a 2.75% decrease in MPO levels (95% CI=-5.13%,-0.37%). We did not see associations between Delta-C concentrations and any other biomarkers. Interquartile range (IQR) increases in PM2.5, BC, UFP, and AMP concentrations were generally associated with increased CRP and fibrinogen, but not PF4, D-dimer, vWF, or P-selectin. CONCLUSIONS: In a population of cardiac patients, we noted adverse changes in fibrinogen associated with increased concentrations of a marker of wood smoke. Increases in PM2.5, BC, AMP, and UFP concentrations in the previous 96h were also associated with adverse changes in markers of systemic inflammation and coagulation, but not with markers of endothelial cell dysfunction or platelet activation.

Potentially Beneficial Effect of Hydroxychloroquine in a Patient with a Novel Mutation in Protein Kinase Cδ Deficiency.

Protein kinase C delta (PRKCD) has essential functions in controlling B-cell proliferation and apoptosis, development of B-cell tolerance and NK-cell cytolitic activity. Human PRKCD deficiency was recently identified to be causative for an autoimmune lymphoproliferative syndrome like disorder with significant B-cell proliferation particularly of immature B cells. Here we report a child with a novel mutation in PRKCD gene who presented with CMV infection and an early onset SLE-like disorder which was successfully treated with hydroxychloroquine.

Spatial regression modelling of particulate pollution in Calgary, Canada.

The study presents a spatial analysis of particulate pollution, which includes not only particulate matter, but also black carbon, a pollutant of growing concern for human health. We developed land use regression (LUR) models for two particulate matter size fractions, PM2.5 and PM10, and for δC, an index calculated from black carbon (BC)-a component of PM2.5-which indicates the portion of organic versus elemental BC. LUR models were estimated over Calgary (Canada) for summer 2015 and winter 2016. As all samples exhibited significant spatial autocorrelation, spatial autoregressive lag (SARlag) and error (SARerr) models were computed. SARlag models were preferred for all pollutants in both seasons, and yielded goodness of fit aligned with or higher than values reported in the literature. LUR models yielded consistent sets of predictors, representing industrial activities, traffic, and elevation. The obtained model coefficients were then combined with local land use variables to compute fine-scale concentration predictions over the entire city. The predicted concentrations were slightly lower and less dispersed than the observed ones. Consistent with observed pollution records, prediction maps exhibited higher concentration over the road network, industrial areas, and the eastern quadrants of the city. Lastly, results of a corresponding study of PM in summer 2010 and winter 2011 were considered. While the small size of the 2010-2011 sample hampered a multi-temporal analysis, we cautiously note comparable seasonal patterns and consistent association with land use variables for both PM fine fractions over the 5-year interval.

Daily land use regression estimated woodsmoke and traffic pollution concentrations and the triggering of ST-elevation myocardial infarction: a case-crossover study.

Prior work has reported acute associations between ST-elevation myocardial infarction (STEMI) and short-term increases in airborne particulate matter. Subsequently, the association between STEMI and hourly measures of Delta-C (marker of woodsmoke) and black carbon (marker of traffic pollution) measured at a central site in Rochester, NY, were examined, but no association was found. Therefore, land use regression estimates of Delta-C and black carbon concentrations at each patient's residence were developed for 246 STEMI patients treated at the University of Rochester Medical Center during the winters of 2008-2012. Using case-crossover methods, the rate of STEMI associated with increased Delta-C and BC concentration on the same and previous 3 days was estimated after adjusting for 3-day mean temperature and relative humidity. Non-statistically significant increased rates of STEMI associated with interquartile range increases in concentrations of BC in the previous 2 days (1.10 µg/m3; OR = 1.12; 95% CI 0.93, 1.35) and Delta-C in the previous 3 days (0.43 µg/m3; OR = 1.16; 95% CI 0.96, 1.40) were found. Significantly increased rates of STEMI associated with interquartile range increases in concentrations of BC (1.23 µg/m3; OR = 1.04; 95% CI = 0.87, 1.24) or Delta-C (0.40 µg/m3; OR = 0.94; 95% CI = 0.85, 1.09) on the same day were not observed likely due, in part, to temporal misalignment. Therefore, sophisticated spatial-temporal models will be needed to minimize exposure error and bias by better predicting concentrations at individual locations for individual hours, especially for outcomes with short-term responses to air pollution (< 24 h).

miRNA Quantification Method Using Quantitative Polymerase Chain Reaction in Conjunction with C q Method.

MicroRNAs are small noncoding RNAs that function to regulate gene expression. In general, miRNAs are posttranscriptional regulators that imperfectly bind to the 3'untranslated region (3'UTR) of target mRNAs bearing complementary sequences, and target more than half of all protein-coding genes in the human genome. The dysregulation of miRNA expression and activity has been linked with numerous diseases, including cancer, cardiovascular diseases, neurodegenerative disorders, and diabetes. To better understand the relationship between miRNAs and human disease, a variety of techniques have been used to measure and validate miRNA expression in many cells, tissues, body fluids, and organs. For many years, quantitative polymerase chain reaction (qPCR) has been the gold standard for measuring relative gene expression, and is now also widely used to assess miRNA abundance. In this chapter, we describe a quick protocol for miRNA extraction, reverse transcription, qPCR, and data analysis.