An ADAM33 Polymorphism Associates with Progression of Preschool Wheeze into Childhood Asthma:A Prospective Case-Control Study with Replication in a Birth Cohort Study

The influence of asthma candidate genes on the development from wheeze to asthma in young children still needs to be defined.To link genetic variants in asthma candidate genes to progression of wheeze to persistent wheeze into childhood asthma.In a prospective study, children with recurrent wheeze from the ADEM (Asthma DEtection and Monitoring) study were followed until the age of six. At that age a classification (transient wheeze or asthma) was based on symptoms, lung function and medication use. In 198 children the relationship between this classification and 30 polymorphisms in 16 asthma candidate genes was assessed by logistic regression. In case of an association based on a p<0.10, replication analysis was performed in an independent birth cohort study (KOALA study, n = 248 included for the present analysis).In the ADEM study, the minor alleles of ADAM33 rs511898 and rs528557 and the ORMDL3/GSDMB rs7216389 polymorphisms were negatively associated, whereas the minor alleles of IL4 rs2243250 and rs2070874 polymorphisms were positively associated with childhood asthma. When replicated in the KOALA study, ADAM33 rs528557 showed a negative association of the CG/GG-genotype with progression of recurrent wheeze into childhood asthma (0.50 (0.26-0.97) p = 0.04) and no association with preschool wheeze.Polymorphisms in ADAM33, ORMDL3/GSDMB and IL4 were associated with childhood asthma in a group of children with recurrent wheeze. The replication of the negative association of the CG/GG-genotype of rs528557 ADAM33 with childhood asthma in an independent birth cohort study confirms that a compromised ADAM33 gene may be implicated in the progression of wheeze into childhood asthma

Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging

Although optical absorption is strongly associated with the physiological status of biological tissue, existing high-resolution optical imaging modalities, including confocal microscopy, two-photon microscopy and optical coherence tomography, do not sense optical absorption directly. Furthermore, optical scattering prevents these methods from imaging deeper than ~1 mm below the tissue surface. Here we report functional photoacoustic microscopy (fPAM), which provides multiwavelength imaging of optical absorption and permits high spatial resolution beyond this depth limit with a ratio of maximum imaging depth to depth resolution greater than 100. Reflection mode, rather than orthogonal or transmission mode, is adopted because it is applicable to more anatomical sites than the others. fPAM is demonstrated with in vivo imaging of angiogenesis, melanoma, hemoglobin oxygen saturation (sO_2) of single vessels in animals and total hemoglobin concentration in humans

Congruence of tissue expression profiles from Gene Expression Atlas, SAGEmap and TissueInfo databases

BACKGROUND: Extracting biological knowledge from large amounts of gene expression information deposited in public databases is a major challenge of the postgenomic era. Additional insights may be derived by data integration and cross-platform comparisons of expression profiles. However, database meta-analysis is complicated by differences in experimental technologies, data post-processing, database formats, and inconsistent gene and sample annotation. RESULTS: We have analysed expression profiles from three public databases: Gene Expression Atlas, SAGEmap and TissueInfo. These are repositories of oligonucleotide microarray, Serial Analysis of Gene Expression and Expressed Sequence Tag human gene expression data respectively. We devised a method, Preferential Expression Measure, to identify genes that are significantly over- or under-expressed in any given tissue. We examined intra- and inter-database consistency of Preferential Expression Measures. There was good correlation between replicate experiments of oligonucleotide microarray data, but there was less coherence in expression profiles as measured by Serial Analysis of Gene Expression and Expressed Sequence Tag counts. We investigated inter-database correlations for six tissue categories, for which data were present in the three databases. Significant positive correlations were found for brain, prostate and vascular endothelium but not for ovary, kidney, and pancreas. CONCLUSION: We show that data from Gene Expression Atlas, SAGEmap and TissueInfo can be integrated using the UniGene gene index, and that expression profiles correlate relatively well when large numbers of tags are available or when tissue cellular composition is simple. Finally, in the case of brain, we demonstrate that when PEM values show good correlation, predictions of tissue-specific expression based on integrated data are very accurate

Prediction of asthma exacerbations in children by innovative exhaled inflammatory markers: results of a longitudinal study

BACKGROUND: In asthma management guidelines the primary goal of treatment is asthma control. To date, asthma control, guided by symptoms and lung function, is not optimal in many children and adults. Direct monitoring of airway inflammation in exhaled breath may improve asthma control and reduce the number of exacerbations. AIM: 1) To study the use of fractional exhaled nitric oxide (FeNO) and inflammatory markers in exhaled breath condensate (EBC), in the prediction of asthma exacerbations in a pediatric population. 2) To study the predictive power of these exhaled inflammatory markers combined with clinical parameters. METHODS: 96 asthmatic children were included in this one-year prospective observational study, with clinical visits every 2 months. Between visits, daily symptom scores and lung function were recorded using a home monitor. During clinical visits, asthma control and FeNO were assessed. Furthermore, lung function measurements were performed and EBC was collected. Statistical analysis was performed using a test dataset and validation dataset for 1) conditionally specified models, receiver operating characteristic-curves (ROC-curves); 2) k-nearest neighbors algorithm. RESULTS: Three conditionally specified predictive models were constructed. Model 1 included inflammatory markers in EBC alone, model 2 included FeNO plus clinical characteristics and the ACQ score, and model 3 included all the predictors used in model 1 and 2. The area under the ROC-curves was estimated as 47%, 54% and 59% for models 1, 2 and 3 respectively. The k-nearest neighbors predictive algorithm, using the information of all the variables in model 3, produced correct predictions for 52% of the exacerbations in the validation dataset. CONCLUSION: The predictive power of FeNO and inflammatory markers in EBC for prediction of an asthma exacerbation was low, even when combined with clinical characteristics and symptoms. Qualitative improvement of the chemical analysis of EBC may lead to a better non-invasive prediction of asthma exacerbations.status: publishe