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MiRNAs have been shown to play a powerful regulatory role in the progression of serious diseases, including cancer, Alzheimer's, and others, raising the possibility of new miRNA-based therapies for these conditions. Current experimental methods, such as differential expression analysis, can discover disease-associated miRNAs, yet many of these miRNAs play no functional role in disease progression. Interventional experiments used to discover disease causal miRNAs can be time consuming and costly. We present DisiMiR: a novel computational method that predicts pathogenic miRNAs by inferring biological characteristics of pathogenicity, including network influence and evolutionary conservation. DisiMiR separates disease causal miRNAs from merely disease-associated miRNAs, and was accurate in four diseases: breast cancer (0.826 AUC), Alzheimer's (0.794 AUC), gastric cancer (0.853 AUC), and hepatocellular cancer (0.957 AUC). Additionally, DisiMiR can generate hypotheses effectively: 78.4% of its false positives that are mentioned in the literature have been confirmed to be causal through recently published research. In this work, we show that DisiMiR is a powerful tool that can be used to efficiently and flexibly to predict pathogenic miRNAs in an expression dataset, for the further elucidation of disease mechanisms, and the potential identification of novel drug targets.

MicroRNAs have been independently associated with asthma and COPD; however, it is unclear if microRNA associations will overlap when evaluating retrospective acute exacerbations. Objective: We hypothesized that peripheral blood microRNAs would be associated with retrospective acute asthma exacerbations in a pediatric asthma cohort and that such associations may also be relevant to acute COPD exacerbations. Methods: We conducted small-RNA sequencing on 374 whole-blood samples from children with asthma ages 6-14 years who participated in the Genetics of Asthma in Costa Rica Study (GACRS) and 450 current and former adult smokers with and without COPD who participated in the COPDGene study. Measurements and Main Results: After QC, we had 351 samples and 649 microRNAs for Differential Expression (DE) analysis between the frequent ( n = 183) and no or infrequent exacerbation ( n = 168) groups in GACRS. Fifteen upregulated miRs had odds ratios (OR) between 1.22 and 1.59 for a doubling of miR counts, while five downregulated miRs had ORs between 0.57 and 0.8. These were assessed for generalization in COPDGene, where three of the upregulated miRs (miR-532-3p, miR-296-5p, and miR-766-3p) and two of the downregulated miRs (miR-7-5p and miR-451b) replicated. Pathway enrichment analysis showed MAPK and PI3K-Akt signaling pathways were strongly enriched for target genes of DE miRNAs and miRNAs generalizing to COPD exacerbations, as well as infection response pathways to various pathogens. Conclusion: miRs (451b; 7-5p; 532-3p; 296-5p and 766-3p) associated with both childhood asthma and adult COPD exacerbations may play a vital role in airflow obstruction and exacerbations and point to shared genomic regulatory machinery underlying exacerbations in both diseases.

Metabolomic indicators of asthma treatment responses have yet to be identified. In this study, we aimed to uncover plasma metabolomic profiles associated with asthma exacerbations while on inhaled corticosteroid (ICS) treatment. We determined whether these profiles change with age from adolescence to adulthood. We utilized data from 170 individuals with asthma on ICS from the Mass General Brigham Biobank to identify plasma metabolites associated with asthma exacerbations while on ICS and examined potential effect modification of metabolite-exacerbation associations by age. We used liquid chromatography-high-resolution mass spectrometry-based metabolomic profiling. Sex-stratified analyses were also performed for the significant associations. The age range of the participating individuals was 13-43 years with a mean age of 33.5 years. Of the 783 endogenous metabolites tested, eight demonstrated significant associations with exacerbation after correction for multiple comparisons and adjusting for potential confounders (Bonferroni p value < 6.2 × 10 -4 ). Potential effect modification by sex was detected for fatty acid metabolites, with males showing a greater reduction in their metabolite levels with ICS exacerbation. Thirty-eight metabolites showed suggestive interactions with age on exacerbation (nominal p -value < 0.05). Our findings demonstrate that plasma metabolomic profiles differ for individuals who experience asthma exacerbations while on ICS. The differentiating metabolites may serve as biomarkers of ICS response and may highlight metabolic pathways underlying ICS response variability.

Genome-wide association studies (GWAS) of response to asthma medications have primarily focused on Caucasian populations, with findings that may not be generalizable to minority populations. We derived a polygenic risk score (PRS) for response to albuterol as measured by bronchodilator response (BDR), and examined the PRS in a cohort of Hispanic school-aged children with asthma. We leveraged a published GWAS of BDR to identify relevant genetic variants, and ranked the top variants according to their Combined Annotation Dependent Depletion (CADD) scores. Variants with CADD scores greater than 10 were used to compute the PRS. Once we derived the PRS, we determined the association of the PRS with BDR in a cohort of Hispanic children with asthma (the Genetics of Asthma in Costa Rica Study (GACRS)) in adjusted linear regression models. Mean BDR in GACRS participants was5.6% with a standard deviation of 10.2%. We observed a 0.63% decrease in BDR in response to albuterol for a standard deviation increase in the PRS ( p = 0.05). We also observed decreased odds of a BDR response at or above the 12% threshold for a one standard deviation increase in the PRS (OR = 0.80 (95% CI 0.67 to 0.95)). Our findings show that combining variants from a pharmacogenetic GWAS into a PRS may be useful for predicting medication response in asthma.

Of children with recurrent wheezing in early childhood, approximately half go on to develop asthma. MicroRNAs have been described as excellent non-invasive biomarkers due to their prognostic utility. We hypothesized that circulating microRNAs can predict incident asthma and that that prediction might be modified by vitamin D. We selected 75 participants with recurrent wheezing at 3 years old from the Vitamin D Antenatal Asthma Reduction Trial (VDAART). Plasma samples were collected at age 3 and sequenced for small RNA-Seq. The read counts were normalized and filtered by depth and coverage. Logistic regression was employed to associate miRNAs at age 3 with asthma status at age 5. While the overall effect of miRNA on asthma occurrence was weak, we identified 38 miRNAs with a significant interaction effect with vitamin D and 32 miRNAs with a significant main effect in the high vitamin D treatment group in VDAART. We validated the VDAART results in Project Viva for both the main effect and interaction effect. Meta-analysis was performed on both cohorts to obtain the combined effect and a logistic regression model was used to predict incident asthma at age 7 in Project Viva. Of the 23 overlapped miRNAs in the stratified and interaction analysis above, 9 miRNAs were replicated in Project Viva with strong effect size and remained in the meta-analysis of the two populations. The target genes of the 9 miRNAs were enriched for asthma-related Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. Using logistic regression, microRNA hsa-miR-574-5p had a good prognostic ability for incident asthma prognosis with an area under the receiver operating characteristic (AUROC) of 0.83. In conclusion, miRNAs appear to be good biomarkers of incident asthma, but only when vitamin D level is considered.

Asthma patient response to inhaled corticosteroids (ICS) is variable and difficult to quantify. We aimed to define a measure of steroid response suitable for pharmacogenetic research in longitudinal and cross-sectional cohorts. Using longitudinal data from the Childhood Asthma Management Program (CAMP) asthma cohort, we defined the Cross-sectional Asthma STEroid Response (CASTER) measure in cross-sectional data. We then applied this to cross-sectional slices of four independent asthma cohorts: The Improving Asthma Control Trial (IMPACT), the Salmeterol or Corticosteroids Study (SOCS), the Pediatric Asthma Controller Trial (PACT), and the Genetics of Asthma in Costa Rica Study (GACRS). CASTER achieved high accuracy on the childhood asthma cohorts: GACRS, PACT, and also on cross-sectional data from CAMP (AUCs 82%, 71%, 63%, respectively). This demonstrates that select cross-sectional clinical information is sufficient to identify good and poor responders to ICS treatment in childhood asthma. Thus, CASTER represents a major improvement in the usability and applicability of steroid response measures in asthma research.

Asthma affects more than 300 million people in the world, costs over $80 billion annually in the United States, and is efficaciously treated with inhaled corticosteroids (ICS). To our knowledge, no studies have examined the real-world effectiveness of ICS, including the combination therapy consisting of ICS and long-acting beta agonists (LABAs), and patterns of use over a 15-year time period. We used data from the Kaiser Permanente Northern California multi-ethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort which comprises longitudinal electronic health record data of over 100,000 people. Data included longitudinal asthma-related events, such as ambulatory office visits, hospitalizations, emergency department (ED) visits, and fills of ICS and ICS-LABA combination. Asthma exacerbations were defined as an asthma-related ED visit, hospitalization, or oral corticosteroid (OCS) burst. We used an expected-value approach to determine ICS and ICS-LABA coverage over exacerbation events. We compared rates of exacerbation of subjects on ICS or ICS-LABAs to their own rates of exacerbation when off controller medications. We found ICS-LABA therapy had significant effects, reducing all types of exacerbations per day by a factor of 1.76 (95% CI (1.06, 2.93), p = 0.03) and, specifically, bursts per day by a factor of 1.91 (95% CI (1.04, 3.53), p = 0.037). In conclusion, ICS-LABA therapy was significantly associated with fewer asthma-related exacerbations in a large population of individuals with asthma who were followed for 15 years.