Prediction of Persistent Organic Pollutants Biodegradation in Contaminated Marine Sediments Using Passive Sampling Probes

The aim of this study is to evaluate a new configuration (new materials) of the commercial passive sampler Chemcatcher as probe for predicting the bioavailability of persistent organic pollutants in marine sediments. To predict the availability of pollutants to biota, it is important to understand both solution- and solid-phase processes in the sediment, including the kinetics of pollutants release from its binding agent (ligand and/or particle). The present study examined the kinetic of desorption and biodegradation of Polycyclic Aromatic Hydrocarbons (PAHs) in two different marine sediments sampled in the Adriatic Sea. The sediments were spiked with a standard mix of 16 PAHs in the range of 11-12 mg/Kg (dry sediment). Formaldehyde was added into the sediments to prevent biodegradation. After equilibration, the passive probes were placed in the specimens with prevented biodegradation, recovered and analyzed at prefixed time slots (in the range of 50 days) for the assessment of the accumulated PAHs; in parallel a little amount of sediments was collected and the residual concentration of PAHs was measured. Free PAHs in the sediment pore waters were also determined. The results suggest that the kinetically labile solid-phase pool of PAHs, which is included in the DGT measurement, played an important role in biodegradation processes along with the free PAHs in sediment pore water

Prognostic value of molecules of average mass in patients with chronic obstructive pulmonary disease

Background. Chronic obstructive pulmonary disease is a socially significant disease affecting patient’s quality of life. Assessment of endogenous intoxication in patients with chronic obstructive pulmonary disease will allow to understand pathogenetic features of different phenotypes of this disease, which can be taken into account when predicting its course.The aim of the study. To determine the prognostic value of levels of mediumand low-molecular-weight substances and oligopeptides in patients with chronic obstructive pulmonary disease.Materials and methods. One hundred and four patients with chronic obstructive pulmonary disease (COPD) and 110 somatically healthy individuals were examined. Molecular weight medium and low molecular weight substances (LMWSM) and oligopeptides (OP) were determined in blood plasma, erythrocytes and urine. Based on these indicators mathematically calculated indices of endogenous intoxication and coefficient of elimination were defined. Statistical processing of the data was performed using the SPSS 26.0 software package (IBM Corp., USA).Results. In all biological fluids, the levels of average molecules and calculated indices in the COPD patients’ group were statistically significantly different from those in the control group. The indices characterizing endotoxin accumulation were statistically significantly higher, while those characterizing toxin elimination were lower. The level of endotoxemia was correlated with the frequency of exacerbations, clinical manifestations severity, quality of life, COPD group and phenotype.Conclusions. Frequent exacerbations, groups C and D, bronchitic and mixed COPD phenotypes are characterized by more severe endotoxicosis manifested by high levels of LMWSM, OP and calculated indices

Prevalence of PALB2 Mutations in Breast Cancer Patients in Multi-Ethnic Asian Population in Malaysia and Singapore

10.1371/journal.pone.0073638PLoS ONE88-POLN

Prevalence of Age-Related Macular Degeneration in Europe: The Past and the Future.

PURPOSE: Age-related macular degeneration (AMD) is a frequent, complex disorder in elderly of European ancestry. Risk profiles and treatment options have changed considerably over the years, which may have affected disease prevalence and outcome. We determined the prevalence of early and late AMD in Europe from 1990 to 2013 using the European Eye Epidemiology (E3) consortium, and made projections for the future. DESIGN: Meta-analysis of prevalence data. PARTICIPANTS: A total of 42 080 individuals 40 years of age and older participating in 14 population-based cohorts from 10 countries in Europe. METHODS: AMD was diagnosed based on fundus photographs using the Rotterdam Classification. Prevalence of early and late AMD was calculated using random-effects meta-analysis stratified for age, birth cohort, gender, geographic region, and time period of the study. Best-corrected visual acuity (BCVA) was compared between late AMD subtypes; geographic atrophy (GA) and choroidal neovascularization (CNV). MAIN OUTCOME MEASURES: Prevalence of early and late AMD, BCVA, and number of AMD cases. RESULTS: Prevalence of early AMD increased from 3.5% (95% confidence interval [CI] 2.1%-5.0%) in those aged 55-59 years to 17.6% (95% CI 13.6%-21.5%) in those aged ≥85 years; for late AMD these figures were 0.1% (95% CI 0.04%-0.3%) and 9.8% (95% CI 6.3%-13.3%), respectively. We observed a decreasing prevalence of late AMD after 2006, which became most prominent after age 70. Prevalences were similar for gender across all age groups except for late AMD in the oldest age category, and a trend was found showing a higher prevalence of CNV in Northern Europe. After 2006, fewer eyes and fewer ≥80-year-old subjects with CNV were visually impaired (P = 0.016). Projections of AMD showed an almost doubling of affected persons despite a decreasing prevalence. By 2040, the number of individuals in Europe with early AMD will range between 14.9 and 21.5 million, and for late AMD between 3.9 and 4.8 million. CONCLUSION: We observed a decreasing prevalence of AMD and an improvement in visual acuity in CNV occuring over the past 2 decades in Europe. Healthier lifestyles and implementation of anti-vascular endothelial growth factor treatment are the most likely explanations. Nevertheless, the numbers of affected subjects will increase considerably in the next 2 decades. AMD continues to remain a significant public health problem among Europeans

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores