Inducible expression quantitative trait locus analysis of the MUC5AC gene in asthma in urban populations of children

BACKGROUND: Mucus plugging can worsen asthma control, lead to reduced lung function and fatal exacerbations. MUC5AC is the secretory mucin implicated in mucus plugging, and MUC5AC gene expression has been associated with development of airway obstruction and asthma exacerbations in urban children with asthma. However, the genetic determinants of MUC5AC expression are not established. OBJECTIVE: To assess single-nucleotide polymorphisms (SNPs) that influence MUC5AC expression and relate to pulmonary functions in childhood asthma. METHODS: We used RNA-sequencing data from upper airway samples and performed cis-expression quantitative trait loci (eQTL) and allele specific expression (ASE) analyses in two cohorts of predominantly Black and Hispanic urban children, a high asthma-risk birth cohort and an exacerbation-prone asthma cohort. We further investigated inducible MUC5AC eQTLs during incipient asthma exacerbations. We tested significant eQTLs SNPs for associations with lung function measurements and investigated their functional consequences in DNA regulatory databases. RESULTS: We identified two independent groups of SNPs in the MUC5AC gene that were significantly associated with MUC5AC expression. Moreover, these SNPs showed stronger eQTL associations with MUC5AC expression during asthma exacerbations, consistent with inducible expression. SNPs in one group also showed significant association with decreased pulmonary functions. These SNPs included multiple EGR1 transcription factor binding sites suggesting a mechanism of effect. CONCLUSIONS: These findings demonstrate the applicability of organ specific RNA-sequencing data to determine genetic factors contributing to a key disease pathway. Specifically, they suggest important genetic variations that may underlie propensity to mucus plugging in asthma and could be important in targeted asthma phenotyping and disease management strategies

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; \u3c37 \u3eweeks) or (2) early preterm birth (ePTB; \u3c32 \u3eweeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

On the intrinsic sterility of 3D printing.

3D printers that build objects using extruded thermoplastic are quickly becoming commonplace tools in laboratories. We demonstrate that with appropriate handling, these devices are capable of producing sterile components from a non-sterile feedstock of thermoplastic without any treatment after fabrication. The fabrication process itself results in sterilization of the material. The resulting 3D printed components are suitable for a wide variety of applications, including experiments with bacteria and cell culture

On the intrinsic sterility of 3D printing.

3D printers that build objects using extruded thermoplastic are quickly becoming commonplace tools in laboratories. We demonstrate that with appropriate handling, these devices are capable of producing sterile components from a non-sterile feedstock of thermoplastic without any treatment after fabrication. The fabrication process itself results in sterilization of the material. The resulting 3D printed components are suitable for a wide variety of applications, including experiments with bacteria and cell culture

Using emotion to guide decisions: the accuracy and perceived value of emotional intensity forecasts

Forecasts about future emotion are often inaccurate, so why do people rely on them to make decisions? People may forecast some features of their emotional experience better than others, and they may report relying on forecasts that are more accurate to make decisions. To test this, four studies assessed the features of emotion people reported forecasting to make decisions about their careers, education, politics, and health. In Study 1, graduating medical students reported relying more on forecast emotional intensity than frequency or duration to decide how to rank residency programs as part of the process of being matched with a program. Similarly, participants reported relying more on forecast emotional intensity than frequency or duration to decide which universities to apply to (Study 2), which presidential candidate to vote for (Study 3), and whether to travel as Covid-19 rates declined (Study 4). Studies 1 and 3 also assessed forecasting accuracy. Participants forecast emotional intensity more accurately than frequency or duration. People make better decisions when they can anticipate the future. Thus, people's reports of relying on forecast emotional intensity to guide life-changing decisions, and the greater accuracy of these forecasts, provide important new evidence of the adaptive value of affective forecasts

Seasonal Airway Microbiome and Transcriptome Interactions Promote Childhood Asthma Exacerbations

BACKGROUND: Seasonal variation in respiratory illnesses and exacerbations in pediatric populations with asthma is well described, though whether upper airway microbes play season-specific roles in these events is unknown. OBJECTIVE: We hypothesized that nasal microbiota composition is seasonally dynamic and that discrete microbial-host interactions modify risk of asthma exacerbation in a season-specific manner. METHODS: Repeated nasal samples from children with exacerbation-prone asthma collected during periods of respiratory health (Baseline; n=181 samples) or first captured respiratory illness (n=97) across all seasons, underwent bacterial (16S rRNA gene) and fungal (ITS2) biomarker sequencing. Virus detection was performed by multiplex PCR. Paired nasal transcriptome data was examined for seasonal dynamics and integrative analyses. RESULTS: Upper airway bacterial and fungal microbiota and rhinovirus detection exhibited significant seasonal dynamics. In seasonally-adjusted analysis, variation in both baseline and respiratory illness microbiota related to subsequent exacerbation. Specifically in the fall, when respiratory illness and exacerbation events were most frequent, several Moraxella and Haemophilus members were enriched both in viral positive respiratory illnesses and those that progressed to exacerbations. The abundance of two discrete bacterial networks, characteristically comprising either Streptococcus or Staphylococcus exhibited opposing interactions with an exacerbation-associated SMAD3 nasal epithelial transcriptional module to significantly increase odds of subsequent exacerbation [OR=14.7, 95% CI: 1.50-144, P=0.02; OR=39.17, 95% CI: 2.44-626, P=0.008, respectively]. CONCLUSIONS: Upper airway microbiomes co-vary with season and with seasonal trends in respiratory illnesses and asthma exacerbations. Seasonally-adjusted analyses reveal specific bacterial-host interactions that significantly increase risk of asthma exacerbation in these children