Metabolomic biomarkers predictive of early structural lung disease in cystic fibrosis

Neutrophilic airway inflammation plays a role in early structural lung disease in cystic fibrosis (CF), but the mechanisms underlying this pathway are incompletely understood

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

Comparing the frequency of common genetic variants and haplotypes between carriers and non-carriers of BRCA1 and BRCA2 deleterious mutations in Australian women diagnosed with breast cancer before 40 years of age

BACKGROUND: BRCA1 and BRCA2 mutations are found in a proportion of families with multiple early-onset breast cancers. There are a large number of different deleterious mutations in both genes, none of which would be detectable using standard genetic association studies. Single common variants and haplotypes of common variants may capture groups of deleterious mutations since some low prevalence haplotypes of common variants occur more frequently among chromosomes that carry rare, deleterious mutations than chromosomes that do not. METHODS: DNA sequence data for BRCA1 and BRCA2 was obtained from 571 participants from the Australian Breast Cancer Family Study. Genetic variants were classified as either deleterious mutations or common genetic variants. Variants tagging common polymorphisms were selected and haplotypes resolved using Haploview. Their frequency was compared to those with and without deleterious mutations using a permutation test. RESULTS: A common genetic variant in BRCA1 (3232A > G) was found to be over-represented in deleterious mutation carriers (p = 0.05), whereas a common genetic variant in BRCA2 (1342A > C) occurred less frequently in deleterious mutation carriers (p = 0.04). All four of the common BRCA1 variants used to form haplotypes occurred more frequently in the deleterious mutation carriers when compared to the non-carriers, but there was no evidence of a difference in the distributions between the two groups (p = 0.34). In BRCA2, all four common variants were found to occur less frequently in the deleterious mutation carriers when compared to non-carriers, but the evidence for difference in the distribution between the two groups was weak (p = 0.16). Several less common haplotypes of common BRCA1 variants were found to be over-represented among deleterious mutation carriers but there was no evidence for this at the population level. In BRCA2, only the most common haplotype was found to occur more frequently in deleterious mutation carriers, with again no evidence at the population level. CONCLUSIONS: We observed differences in the frequency of common genetic variants of the BRCA1 and BRCA2 and their haplotypes between early-onset breast cancer cases who did and did not carry deleterious mutations in these genes. Although our data provide only weak evidence for a difference in frequencies at the population level, the number of deleterious mutation carriers was low and the results may yet be substantiated in a larger study using pooled data

Imputation of missing genotypes in genetic association studies of genes of iron metabolism and disease features in hereditary haemochromatosis

© 2014 Dr. Lidija TurkovicOne of the aims of my doctoral work is to investigate different methods of multiple imputation in genetic association studies of unrelated individuals using simulation and data from HealthIron study. HealthIron project has generated two types of genetic data. Firstly re-sequenced exonic regions of twelve candidate genes of iron metabolism in a random sample of 94 C282Y homozygotes and 94 randomly chosen individuals unselected for HFE genotype. Secondly, SNP genotyping in all HealthIron participants who provided a blood sample (n=865) providing a broad coverage of 35 genes. Different techniques of multiple imputation will be used to impute SNP genotypes in individuals without re-sequencing data.The goal of these analyses is to determine if the accuracy of the calculated measures of association can be improved by filling in missing genotype while appropriately accounting for the uncertainty in imputation. Imputed data will then be incorporated in association analyses of SNP genotypes and binary disease outcomes

Chest imaging in cystic fibrosis studies: What counts, and can be counted?

Background: The dawn of precision medicine and CFTR modulators require more detailed assessment of lung structure in cystic fibrosis (CF) clinical studies. Various imaging markers have emerged and are measurable, but clarity is needed to identify what markers should count for clinical studies. High-resolution chest computed tomography (CT) scoring has yielded sensitive markers for the study of CF disease progression. Once completed, CT scores from ongoing randomized controlled trials can be used to examine relationships between imaging endpoints and therapeutic effectiveness. Similarly, Magnetic Resonance Imaging (MRI) is in development to generate structural as well as functional markers. Results: The aim of this review is to characterize the role of currently available CT and MRI markers in clinical studies, and to discuss study design, data processing and statistical challenges unique to these endpoints in CF studies. Suggestions to overcome these challenges in CF studies are included. Conclusions: To maximize the potential of CT and MRI markers in clinical studies and advance treatment of CF disease progression, efforts should be made to conduct longitudinal randomized controlled trials including these modalities, develop data repositories, promote standardization and conduct reproducible research

The cumulative effect of inflammation and infection on structural lung disease in early cystic fibrosis

Introduction: Pulmonary inflammation and infection are important clinical and prognostic markers of lung disease in cystic fibrosis (CF). However, whether in young children they are transient findings or have cumulative, long-term impacts on respiratory health is largely unknown. We aimed to determine whether their repeated detection has a deleterious effect on structural lung disease. Methods: All patients aged <6 years with annual computed tomography (CT) and bronchoalveolar lavage (BAL) were included. Structural lung disease on CT (%Disease) was determined using the PRAGMA-CF (Perth–Rotterdam Annotated Grid Morphometric Analysis for CF) method. The number of times free neutrophil elastase (NE) and infection were detected in BAL were counted, to determine cumulative BAL history. Linear mixed model analysis, accounting for repeat visits and adjusted for age, was used to determine associations. Results: 265 children (683 scans) were included for analysis, with BAL history comprising 1161 visits. %Disease was significantly associated with the number of prior NE (0.31, 95% CI 0.09–0.54; p=0.007) but not infection (0.23, 95% CI −0.01–0.47; p=0.060) detections. Reference equations were determined. Conclusions: Pulmonary inflammation in surveillance BAL has a cumulative effect on structural lung disease extent, more so than infection. This provides a strong rationale for therapies aimed at reducing inflammation in young children