Australian data on the utilisation and duration on treatment of ibrutinib with a proton pump inhibitor in patients with relapsed or refractory chronic lymphocytic leukaemia

In Australia, over half of patients with relapsed/refractory chronic lymphocytic leukaemia treated with ibrutinib use concomitant proton pump inhibitors (PPIs). High gastric pH reduces the bioavailability of some Bruton tyrosine kinase inhibitors. There was no difference in duration on ibrutinib with or without concomitant PPI (unadjusted P = 0.61; adjusted hazard ratio: 1.23, 95% confidence interval: 0.75–2.02, P = 0.411). PPI use does not affect ibrutinib treatment persistence

Expression of SMARCD1 interacts with age in association with asthma control on inhaled corticosteroid therapy.

BackgroundGlobal gene expression levels are known to be highly dependent upon gross demographic features including age, yet identification of age-related genomic indicators has yet to be comprehensively undertaken in a disease and treatment-specific context.MethodsWe used gene expression data from CD4+ lymphocytes in the Asthma BioRepository for Integrative Genomic Exploration (Asthma BRIDGE), an open-access collection of subjects participating in genetic studies of asthma with available gene expression data. Replication population participants were Puerto Rico islanders recruited as part of the ongoing Genes environments & Admixture in Latino Americans (GALA II), who provided nasal brushings for transcript sequencing. The main outcome measure was chronic asthma control as derived by questionnaires. Genomic associations were performed using regression of chronic asthma control score on gene expression with age in years as a covariate, including a multiplicative interaction term for gene expression times age.ResultsThe SMARCD1 gene (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily D member 1) interacted with age to influence chronic asthma control on inhaled corticosteroids, with a doubling of expression leading to an increase of 1.3 units of chronic asthma control per year (95% CI [0.86, 1.74], p = 6 × 10- 9), suggesting worsening asthma control with increasing age. This result replicated in GALA II (p = 3.8 × 10- 8). Cellular assays confirmed the role of SMARCD1 in glucocorticoid response in airway epithelial cells.ConclusionFocusing on age-dependent factors may help identify novel indicators of asthma medication response. Age appears to modulate the effect of SMARCD1 on asthma control with inhaled corticosteroids

Superpulsed low-level laser therapy protects skeletal muscle of mdx mice against damage, inflammation and morphological changes delaying dystrophy progression.

Aim: To evaluate the effects of preventive treatment with low-level laser therapy (LLLT) on progression of dystrophy in mdx mice. Methods: Ten animals were randomly divided into 2 experimental groups treated with superpulsed LLLT (904 nm, 15 mW, 700 Hz, 1 J) or placebo-LLLT at one point overlying the tibialis anterior muscle (bilaterally) 5 times per week for 14 weeks (from 6th to 20th week of age). Morphological changes, creatine kinase (CK) activity and mRNA gene expression were assessed in animals at 20th week of age. Results: Animals treated with LLLT showed very few morphological changes in skeletal muscle, with less atrophy and fibrosis than animals treated with placebo-LLLT. CK was significantly lower (p = 0.0203) in animals treated with LLLT (864.70 U.l−1, SEM 226.10) than placebo (1708.00 U.l−1, SEM 184.60). mRNA gene expression of inflammatory markers was significantly decreased by treatment with LLLT (p<0.05): TNF-α (placebo-control = 0.51 µg/µl [SEM 0.12], - LLLT = 0.048 µg/µl [SEM 0.01]), IL-1β (placebo-control = 2.292 µg/µl [SEM 0.74], - LLLT = 0.12 µg/µl [SEM 0.03]), IL-6 (placebo-control = 3.946 µg/µl [SEM 0.98], - LLLT = 0.854 µg/µl [SEM 0.33]), IL-10 (placebo-control = 1.116 µg/µl [SEM 0.22], - LLLT = 0.352 µg/µl [SEM 0.15]), and COX-2 (placebo-control = 4.984 µg/µl [SEM 1.18], LLLT = 1.470 µg/µl [SEM 0.73]). Conclusion: Irradiation of superpulsed LLLT on successive days five times per week for 14 weeks decreased morphological changes, skeletal muscle damage and inflammation in mdx mice. This indicates that LLLT has potential to decrease progression of Duchenne muscular dystrophy

Mapping transcription mechanisms from multimodal genomic data

Background Identification of expression quantitative trait loci (eQTLs) is an emerging area in genomic study. The task requires an integrated analysis of genome-wide single nucleotide polymorphism (SNP) data and gene expression data, raising a new computational challenge due to the tremendous size of data. Results We develop a method to identify eQTLs. The method represents eQTLs as information flux between genetic variants and transcripts. We use information theory to simultaneously interrogate SNP and gene expression data, resulting in a Transcriptional Information Map (TIM) which captures the network of transcriptional information that links genetic variations, gene expression and regulatory mechanisms. These maps are able to identify both cis- and trans- regulating eQTLs. The application on a dataset of leukemia patients identifies eQTLs in the regions of the GART, PCP4, DSCAM, and RIPK4 genes that regulate ADAMTS1, a known leukemia correlate. Conclusions The information theory approach presented in this paper is able to infer the dependence networks between SNPs and transcripts, which in turn can identify cis- and trans-eQTLs. The application of our method to the leukemia study explains how genetic variants and gene expression are linked to leukemia.National Human Genome Research Institute (U.S.) (R01HG003354)National Institute of Allergy and Infectious Diseases (U.S.) (U19 AI067854-05)National Heart, Lung, and Blood Institute (grant T32 HL007427-28)National Institutes of Health (U.S.) (grant K99 LM009826

Metabolite signatures associated with microRNA miR-143-3p serve as drivers of poor lung function trajectories in childhood asthma

Background: Lung function trajectories (LFTs) have been shown to be an important measure of long-term health in asthma. While there is a growing body of metabolomic studies on asthma status and other phenotypes, there are no prospective studies of the relationship between metabolomics and LFTs or their genomic determinants. Methods: We utilized ordinal logistic regression to identify plasma metabolite principal components associated with four previously-published LFTs in children from the Childhood Asthma Management Program (CAMP) (n = 660). The top significant metabolite principal component (PCLF) was evaluated in an independent cross-sectional child cohort, the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) (n = 1151) and evaluated for association with spirometric measures. Using meta-analysis of CAMP and GACRS, we identified associations between PCLF and microRNA, and SNPs in their target genes. Statistical significance was determined using an false discovery rate-adjusted Q-value. Findings: The top metabolite principal component, PCLF, was significantly associated with better LFTs after multiple-testing correction (Q-value = 0.03). PCLF is composed of the urea cycle, caffeine, corticosteroid, carnitine, and potential microbial (secondary bile acid, tryptophan, linoleate, histidine metabolism) metabolites. Higher levels of PCLF were also associated with increases in lung function measures and decreased circulating neutrophil percentage in both CAMP and GACRS. PCLF was also significantly associated with microRNA miR-143-3p, and SNPs in three miR-143-3p target genes; CCZ1 (P-value = 2.6 × 10−5), SLC8A1 (P-value = 3.9 × 10−5); and TENM4 (P-value = 4.9 × 10−5). Interpretation: This study reveals associations between metabolites, miR-143-3p and LFTs in children with asthma, offering insights into asthma physiology and possible interventions to enhance lung function and long-term health. Funding: Molecular data for CAMP and GACRS via the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung, and Blood Institute (NHLBI)

Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts

Background Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes. Methods We constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC <0·7 and FEV1 <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth. Findings The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74–1·88] and non-European (1·42 [1·34–1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56–9·72) in European ancestry and 4·83 (3·45–6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79–0·81] vs 0·76 [0·75–0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern. Interpretation A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtyp

Dystropathology increases energy expenditure and protein turnover in the mdx mouse model of Duchenne muscular dystrophy

The skeletal muscles in Duchenne muscular dystrophy and the mdx mouse model lack functional dystrophin and undergo repeated bouts of necrosis, regeneration, and growth. These processes have a high metabolic cost. However, the consequences for whole body energy and protein metabolism, and on the dietary requirements for these macronutrients at different stages of the disease, are not well-understood. This study used juvenile (4- to 5- wk-old) and adult (12- to 14-wk-old) male dystrophic C57BL/10ScSn-mdx/J and age-matched C57BL/10ScSn/J control male mice to measure total and resting energy expenditure, food intake, spontaneous activity, body composition, whole body protein turnover, and muscle protein synthesis rates. In juvenile mdx mice that have extensive muscle damage, energy expenditure, muscle protein synthesis, and whole body protein turnover rates were higher than in age-matched controls. Adaptations in food intake and decreased activity were insufficient to meet the increased energy and protein needs of juvenile mdx mice and resulted in stunted growth. In (non-growing) adult mdx mice with less severe dystropathology, energy expenditure, muscle protein synthesis, and whole body protein turnover rates were also higher than in age-matched controls. Food intake was sufficient to meet their protein and energy needs, but insufficient to result in fat deposition. These data show that dystropathology impacts the protein and energy needs of mdx mice and that tailored dietary interventions are necessary to redress this imbalance. If not met, the resultant imbalance blunts growth, and may limit the benefits of therapies designed to protect and repair dystrophic muscles

The metabolomics of asthma control: a promising link between genetics and disease

Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative “omics” approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), ­ using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites—monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control

Disease Gene Interaction Pathways: A Potential Framework for How Disease Genes Associate by Disease-Risk Modules

BACKGROUND: Disease genes that interact cooperatively play crucial roles in the process of complex diseases, yet how to analyze and represent their associations is still an open problem. Traditional methods have failed to represent direct biological evidences that disease genes associate with each other in the pathogenesis of complex diseases. Molecular networks, assumed as 'a form of biological systems', consist of a set of interacting biological modules (functional modules or pathways) and this notion could provide a promising insight into deciphering this topic. METHODOLOGY/PRINCIPAL FINDINGS: In this paper, we hypothesized that disease genes might associate by virtue of the associations between biological modules in molecular networks. Then we introduced a novel disease gene interaction pathway representation and analysis paradigm, and managed to identify the disease gene interaction pathway for 61 known disease genes of coronary artery disease (CAD), which contained 46 disease-risk modules and 182 interaction relationships. As demonstrated, disease genes associate through prescribed communication protocols of common biological functions and pathways. CONCLUSIONS/SIGNIFICANCE: Our analysis was proved to be coincident with our primary hypothesis that disease genes of complex diseases interact with their neighbors in a cooperative manner, associate with each other through shared biological functions and pathways of disease-risk modules, and finally cause dysfunctions of a series of biological processes in molecular networks. We hope our paradigm could be a promising method to identify disease gene interaction pathways for other types of complex diseases, affording additional clues in the pathogenesis of complex diseases