Discovery of a potent thiazolidine free fatty acid receptor 2 agonist with favorable pharmacokinetic properties

Free fatty acid receptor 2 (FFA2/GPR43) is a receptor for short-chain fatty acids reported to be involved in regulation of metabolism, appetite, fat accumulation and inflammatory responses, and is a potential target for treatment of various inflammatory and metabolic diseases. By bioisosteric replacement of the central pyrrolidine core of a previously disclosed FFA2 agonist with a synthetically more tractable thiazolidine, we were able to rapidly synthesize and screen analogues modified at both the 2- and 3-positions on the thiazolidine core. Herein, we report SAR exploration of thiazolidine FFA2 agonists and the identification of 31 (TUG-1375), a compound with significantly increased potency (7-fold in a cAMP assay) and reduced lipophilicity (50-fold reduced clogP) relative to the pyrrolidine lead structure. The compound has high solubility, high chemical, microsomal and hepatocyte stability, favorable pharmacokinetic properties, and was confirmed to induce human neutrophil mobilization and to inhibit lipolysis in murine adipocytes

Dabigatran use in Danish atrial fibrillation patients in 2011: a nationwide study

OBJECTIVE: Dabigatran was recently approved for anticoagulation in patients with atrial fibrillation (AF); data regarding real-world use, comparative effectiveness and safety are sparse. DESIGN: Pharmacoepidemiological cohort study. METHODS/SETTINGS: From nationwide registers, we identified patients with an in-hospital or outpatient-clinic AF diagnosis who claimed a prescription of dabigatran 110 or 150 mg, or vitamin K antagonist (VKA), between 22 August and 31 December 2011. HRs of thromboembolic events (ischaemic stroke, transitory ischaemic attack and peripheral artery embolism) and bleedings were estimated using Cox regression analyses in all patients and stratified by previous VKA use. RESULTS: Overall, 1612 (3.1%) and 1114 (2.1%) patients claimed a prescription of dabigatran 110 and 150 mg, and 49640 (94.8%) of VKA. Patients treated with dabigatran 150 mg were younger with less comorbidity than those treated with dabigatran 110 mg and VKA, as were VKA naïve patients compared with previous VKA users. Recommendations set by the European Medicine Agency (EMA) for dabigatran were met in 90.3% and 55.5% of patients treated with 110 and 150 mg. Patients treated with 150 mg dabigatran, who did not fulfil the recommendations by EMA, were >80 years, patients with liver or kidney disease, patients with previous bleeding. Compared with VKA, the thromboembolic risk associated with dabigatran 110 and 150 mg was HR 3.52 (1.40 to 8.84) and 5.79 (1.81 to 18.56) in previous VKA users, and HR 0.95(0.47 to 1.91) and 1.14(0.60 to 2.16) in VKA naïve patients. Bleeding risk was increased in previous VKA users receiving dabigatran 110 mg, but not in patients with 150 mg dabigatran, nor in the VKA naïve users. CONCLUSIONS: Deviations from the recommended use of dabigatran were frequent among patients treated with 150 mg. With cautious interpretation, dabigatran use in VKA naïve patients seems safe. Increased risk of thromboembolism and bleeding with dabigatran among previous VKA users was unexpected and may reflect patient selection and ‘drug switching’ practices

Intracranial tumors of the central nervous system and air pollution - A nationwide case-control study from Denmark

Background: Inconclusive evidence has suggested a possible link between air pollution and central nervous system (CNS) tumors. We investigated a range of air pollutants in relation to types of CNS tumors. Methods: We identified all (n = 21,057) intracranial tumors in brain, meninges and cranial nerves diagnosed in Denmark between 1989 and 2014 and matched controls on age, sex and year of birth. We established personal 10- year mean residential outdoor exposure to particulate matter < 2.5 μm (PM2.5), nitrous oxides (NOX), primary emitted black carbon (BC) and ozone. We used conditional logistic regression to calculate odds ratios (OR) linearly (per interquartile range (IQR)) and categorically. We accounted for personal income, employment, marital status, use of medication as well as socio-demographic conditions at area level. Results: Malignant tumors of the intracranial CNS was associated with BC (OR: 1.034, 95%CI: 1.005–1.065 per IQR. For NOx the OR per IQR was 1.026 (95%CI: 0.998–1.056). For malignant non-glioma tumors of the brain we found associations with PM2.5 (OR: 1.267, 95%CI: 1.053–1.524 per IQR), BC (OR: 1.049, 95%CI: 0.996–1.106) and NOx (OR: 1.051, 95% CI: 0.996–1.110). Conclusion: Our results suggest that air pollution is associated with malignant intracranial CNS tumors and malignant non-glioma of the brain. However, additional studies are needed

Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study

BACKGROUND: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited. OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts. METHODS: Within the project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (O3), as well as 8 PM2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders. RESULTS: Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM2.5 (hazard ratio per 5 µg/m3: 1.25; 95% confidence interval: 1.01-1.55), NO2 (1.13; 0.95-1.34 per 10 µg/m3), and BC (1.12; 0.94-1.34 per 0.5 × 10-5m-1), and a negative association with O3 (0.74; 0.58-0.94 per 10 µg/m3). Associations of PM2.5, NO2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM2.5 remained robust when adjusted for NO2 (1.24; 0.95-1.62) or BC (1.28; 0.96-1.71), whereas associations with NO2 or BC attenuated to null. O3 associations remained negative, but no longer statistically significant in models with PM2.5. We detected suggestive positive associations with the potassium component of PM2.5. CONCLUSION: Long-term exposure to PM2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality

Development of Europe-Wide Models for Particle Elemental Composition Using Supervised Linear Regression and Random Forest.

We developed Europe-wide models of long-term exposure to eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in particulate matter with diameter <2.5 μm (PM2.5) using standardized measurements for one-year periods between October 2008 and April 2011 in 19 study areas across Europe, with supervised linear regression (SLR) and random forest (RF) algorithms. Potential predictor variables were obtained from satellites, chemical transport models, land-use, traffic, and industrial point source databases to represent different sources. Overall model performance across Europe was moderate to good for all elements with hold-out-validation R-squared ranging from 0.41 to 0.90. RF consistently outperformed SLR. Models explained within-area variation much less than the overall variation, with similar performance for RF and SLR. Maps proved a useful additional model evaluation tool. Models differed substantially between elements regarding major predictor variables, broadly reflecting known sources. Agreement between the two algorithm predictions was generally high at the overall European level and varied substantially at the national level. Applying the two models in epidemiological studies could lead to different associations with health. If both between- and within-area exposure variability are exploited, RF may be preferred. If only within-area variability is used, both methods should be interpreted equally

European Code against Cancer 4th Edition: Alcohol drinking and cancer.

Alcohol consumption is the third leading risk factor for disease and mortality in Europe. As evaluated by the International Agency for Research on Cancer (IARC) Monographs, a causal relationship is established for consumption of alcoholic beverages and cancers of the oral cavity, pharynx, larynx, oesophagus, liver, colorectum and female breast, even at low and moderate alcohol intakes. The higher the amount of alcohol consumed, the higher the risk of developing cancer. In Europe, an estimated 10% (95% CI: 7%-13%) of all cancer cases in men and 3% (95% CI: 1%-5%) of all cancer cases in women are attributable to alcohol consumption. Several biological mechanisms explain the carcinogenicity of alcohol; among them, ethanol and its genotoxic metabolite, acetaldehyde, play a major role. Taking all this evidence into account, a recommendation of the 4th edition of European Code against Cancer is: "If you drink alcohol of any type, limit your intake. Not drinking alcohol is better for cancer prevention.

Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project.

BACKGROUND: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence). METHODS: We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects. RESULTS: Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates' standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter. CONCLUSIONS: Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data

Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort

Background The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. Methods Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants’ baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. Results The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. Conclusions We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise