Initial acquisition and succession of the cystic fibrosis lung microbiome is associated with disease progression in infants and preschool children

The cystic fibrosis (CF) lung microbiome has been studied in children and adults; however, little is known about its relationship to early disease progression. To better understand the relationship between the lung microbiome and early respiratory disease, we characterized the lower airways microbiome using bronchoalveolar lavage (BAL) samples obtained from clinically stable CF infants and preschoolers who underwent bronchoscopy and chest computed tomography (CT). Cross-sectional samples suggested a progression of the lower airways microbiome with age, beginning with relatively sterile airways in infancy. By age two, bacterial sequences typically associated with the oral cavity dominated lower airways samples in many CF subjects. The presence of an oral-like lower airways microbiome correlated with a significant increase in bacterial density and inflammation. These early changes occurred in many patients, despite the use of antibiotic prophylaxis in our cohort during the first two years of life. The majority of CF subjects older than four harbored a pathogen dominated airway microbiome, which was associated with a further increase in inflammation and the onset of structural lung disease, despite a negligible increase in bacterial density compared to younger patients with an oral-like airway microbiome. Our findings suggest that changes within the CF lower airways microbiome occur during the first years of life and that distinct microbial signatures are associated with the progression of early CF lung disease

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990�2015: a systematic analysis for the Global Burden of Disease Study 2015

Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors�the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25 over the same period. All risks jointly evaluated in 2015 accounted for 57·8 (95 CI 56·6�58·8) of global deaths and 41·2 (39·8�42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million 192·7 million to 231·1 million global DALYs), smoking (148·6 million 134·2 million to 163·1 million), high fasting plasma glucose (143·1 million 125·1 million to 163·5 million), high BMI (120·1 million 83·8 million to 158·4 million), childhood undernutrition (113·3 million 103·9 million to 123·4 million), ambient particulate matter (103·1 million 90·8 million to 115·1 million), high total cholesterol (88·7 million 74·6 million to 105·7 million), household air pollution (85·6 million 66·7 million to 106·1 million), alcohol use (85·0 million 77·2 million to 93·0 million), and diets high in sodium (83·0 million 49·3 million to 127·5 million). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

A screening tool to identify risk for bronchiectasis progression in children with cystic fibrosis

Background The marked heterogeneity in cystic fibrosis (CF) disease complicates the selection of those most likely to benefit from existing or emergent treatments. Objective We aimed to predict the progression of bronchiectasis in preschool children with CF. Methods Using data collected up to 3 years of age, in the Australian Respiratory Early Surveillance Team for CF cohort study, clinical information, chest computed tomography (CT) scores, and biomarkers from bronchoalveolar lavage were assessed in a multivariable linear regression model as predictors for CT bronchiectasis at age 5-6. Results Follow-up at 5-6 years was available in 171 children. Bronchiectasis prevalence at 5-6 was 134/171 (78%) and median bronchiectasis score was 3 (range 0-12). The internally validated multivariate model retained eight independent predictors accounting for 37% (adjusted R-2) of the variance in bronchiectasis score. The strongest predictors of future bronchiectasis were: pancreatic insufficiency, repeated intravenous treatment courses, recurrent lower respiratory infections in the first 3 years of life, and lower airway inflammation. Dichotomizing the resulting prediction score at a bronchiectasis score of above the median resulted in a diagnostic odds ratio of 13 (95% confidence interval [CI], 6.3-27) with positive and negative predictive values of 80% (95% CI, 72%-86%) and 77% (95% CI, 69%-83%), respectively. Conclusion Early assessment of bronchiectasis risk in children with CF is feasible with reasonable precision at a group level, which can assist in high-risk patient selection for interventional trials. The unexplained variability in disease progression at individual patient levels remains high, limiting the use of this model as a clinical prediction tool.Development and application of statistical models for medical scientific researc