Serum 25-Hydroxyvitamin D Levels Among Boston Trainee Doctors in Winter

As indoor workers, trainee doctors may be at risk for inadequate vitamin D. All trainee doctors (residents) in a Boston pediatric training program (residency) were invited to complete a survey, and undergo testing for serum 25-hydroxyvitamin D [25(OH)D], PTH, and calcium during a 3-week period in March 2010. We examined the association between resident characteristics and serum 25(OH)D using Chi2 and Kruskal-Wallis test and multivariable linear and logistic regression. Of the 119 residents, 102 (86%) participated. Although the mean serum 25(OH)D level was 67 nmol/L (±26), 25 (25%) had a level <50 nmol/L and 3 (3%) residents had levels <25 nmol/L. In the multivariable model, factors associated with 25(OH)D levels were: female sex (β 12.7, 95% CI 3.6, 21.7), white race (β 21.7, 95% CI 11.7, 31.7), travel to more equatorial latitudes during the past 3 months (β 6.3, 95% CI 2.0, 10.5) and higher daily intake of vitamin D (β 1.1, 95% CI 0.04, 2.1). Although one in four residents in our study had a serum 25(OH)D <50 nmol/L, all of them would have been missed using current Centers for Medicare and Medicaid Services (CMS) screening guidelines. The use of traditional risk factors appears insufficient to identify low vitamin D in indoor workers at northern latitudes

Bacterial Signatures of Paediatric Respiratory Disease : An Individual Participant Data Meta-Analysis

Introduction: The airway microbiota has been linked to specific paediatric respiratory diseases, but studies are often small. It remains unclear whether particular bacteria are associated with a given disease, or if a more general, non-specific microbiota association with disease exists, as suggested for the gut. We investigated overarching patterns of bacterial association with acute and chronic paediatric respiratory disease in an individual participant data (IPD) meta-analysis of 16S rRNA gene sequences from published respiratory microbiota studies.Methods: We obtained raw microbiota data from public repositories or via communication with corresponding authors. Cross-sectional analyses of the paediatric (10 case subjects were included. Sequence data were processed using a uniform bioinformatics pipeline, removing a potentially substantial source of variation. Microbiota differences across diagnoses were assessed using alpha- and beta-diversity approaches, machine learning, and biomarker analyses.Results: We ultimately included 20 studies containing individual data from 2624 children. Disease was associated with lower bacterial diversity in nasal and lower airway samples and higher relative abundances of specific nasal taxa including Streptococcus and Haemophilus. Machine learning success in assigning samples to diagnostic groupings varied with anatomical site, with positive predictive value and sensitivity ranging from 43 to 100 and 8 to 99%, respectively.Conclusion: IPD meta-analysis of the respiratory microbiota across multiple diseases allowed identification of a non-specific disease association which cannot be recognised by studying a single disease. Whilst imperfect, machine learning offers promise as a potential additional tool to aid clinical diagnosis.Peer reviewe

A joint modeling approach for longitudinal microbiome data improves ability to detect microbiome associations with disease.

Changes in the composition of the microbiome over time are associated with myriad human illnesses. Unfortunately, the lack of analytic techniques has hindered researchers' ability to quantify the association between longitudinal microbial composition and time-to-event outcomes. Prior methodological work developed the joint model for longitudinal and time-to-event data to incorporate time-dependent biomarker covariates into the hazard regression approach to disease outcomes. The original implementation of this joint modeling approach employed a linear mixed effects model to represent the time-dependent covariates. However, when the distribution of the time-dependent covariate is non-Gaussian, as is the case with microbial abundances, researchers require different statistical methodology. We present a joint modeling framework that uses a negative binomial mixed effects model to determine longitudinal taxon abundances. We incorporate these modeled microbial abundances into a hazard function with a parameterization that not only accounts for the proportional nature of microbiome data, but also generates biologically interpretable results. Herein we demonstrate the performance improvements of our approach over existing alternatives via simulation as well as a previously published longitudinal dataset studying the microbiome during pregnancy. The results demonstrate that our joint modeling framework for longitudinal microbiome count data provides a powerful methodology to uncover associations between changes in microbial abundances over time and the onset of disease. This method offers the potential to equip researchers with a deeper understanding of the associations between longitudinal microbial composition changes and disease outcomes. This new approach could potentially lead to new diagnostic biomarkers or inform clinical interventions to help prevent or treat disease

Serum 25-Hydroxyvitamin D Levels Among Boston Trainee Doctors in Winter

As indoor workers, trainee doctors may be at risk for inadequate vitamin D. All trainee doctors (residents) in a Boston pediatric training program (residency) were invited to complete a survey, and undergo testing for serum 25-hydroxyvitamin D [25(OH)D], PTH, and calcium during a 3-week period in March 2010. We examined the association between resident characteristics and serum 25(OH)D using Chi2 and Kruskal-Wallis test and multivariable linear and logistic regression. Of the 119 residents, 102 (86%) participated. Although the mean serum 25(OH)D level was 67 nmol/L (±26), 25 (25%) had a level &lt; 50 nmol/L and 3 (3%) residents had levels &lt; 25 nmol/L. In the multivariable model, factors associated with 25(OH)D levels were: female sex (β 12.7, 95% CI 3.6, 21.7), white race (β 21.7, 95% CI 11.7, 31.7), travel to more equatorial latitudes during the past 3 months (β 6.3, 95% CI 2.0, 10.5) and higher daily intake of vitamin D (β 1.1, 95% CI 0.04, 2.1). Although one in four residents in our study had a serum 25(OH)D &lt; 50 nmol/L, all of them would have been missed using current Centers for Medicare and Medicaid Services (CMS) screening guidelines. The use of traditional risk factors appears insufficient to identify low vitamin D in indoor workers at northern latitudes