Increased Muc5AC and Decreased Ciliated Cells in Severe Asthma Partially Restored by Inhibition of IL-4Rα Receptor.

BACKGROUND: The role of IL-13 on the airway epithelium in severe asthma leading to airway remodeling remains poorly understood. OBJECTIVE: To study IL-13 induced airway remodeling on goblet cells and cilia in the airway epithelium in severe asthma and the impact of an anti-IL4Rα antibody, dupilumab, in vitro. METHODS: Quantitative CT (qCT) lungs and endobronchial biopsies and brushings were obtained in 51 participants (22 severe, 11 non-severe asthma and 18 healthy participants) in the Severe Asthma Research Program (SARPIII) and measured for mucin and cilia related proteins. Epithelial cells were differentiated in air-liquid interphase (ALI) with IL-13 +/-dupilumab and assessed for mucin, cilia, cilia beat frequency (CBF) and epithelial integrity (transepithelial electrical resistance, TEER). RESULTS: Increased Muc5AC (Δ+263.2±92.7 lums/EpiArea) and decreased ciliated cells (Δ-0.07±0.03 Foxj1+cells/EpiArea) were observed in biopsies from severe asthma when compared to healthy (p<0.01 and p=0.047 respectively). RNAseq of epithelial cell brushes confirmed a Muc5AC increase with a decrease in a 5-gene cilia-related mean in severe asthma compared to healthy (all p<0.05). IL-13 (5 ng/mL) differentiated ALI cultures of healthy and asthmatic (severe and non-severe participants) increased Muc5AC, decreased cilia (α-acytl-tubulin) in healthy (Δ+6.5±1.5%, Δ-14.1±2.7%; all p<0.001 respectively) and asthma (Δ+4.4±2.5%, Δ-13.1±2.7%; p=0.084, p<0.001 respectively); decreased epithelial integrity (TEER) in healthy (-140.9±21.3 [ohms], p<0.001) while decreasing CBF in asthma (Δ-4.4±1.7 [Hz], p<0.01). When dupilumab was added to ALI with IL-13, there was no significant decrease in Mu5AC but there was restoration of cilia in healthy and asthma participants (absolute increase of 67.5% and 32.5% cilia, all p<0.05 respectively) while CBF increased (Δ+3.6±1.1 [Hz], p<0.001) and TEER decreased (only in asthma Δ-37.8±16.2 [ohms] p<0.05). CONCLUSIONS: IL-13 drives features of airway remodeling in severe asthma which are partially reversed by inhibiting IL-4Rα receptor in vitro.

An R Shiny Application (SDOH) for Predictive Modeling Using Regional Social Determinants of Health Survey Responses.

Social determinants of health (SDoH) surveys are data sets that provide useful health-related information about individuals and communities. This study aims to develop a user-friendly web application that allows clinicians to get a predictive insight into the social needs of their patients before their in-patient visits using SDoH survey data to provide an improved and personalized service. The study used a longitudinal survey that consisted of 108,563 patient responses to 12 questions. Questions were designed to have a binary outcome as the response and the patient's most recent responses for each of these questions were modeled independently by incorporating explanatory variables. Multiple classification and regression techniques were used, including logistic regression, Bayesian generalized linear model, extreme gradient boosting, gradient boosting, neural networks, and random forests. Based on the area under the curve values, gradient boosting models provided the highest precision values. Finally, the models were incorporated into an R Shiny application, enabling users to predict and compare the impact of SDoH on patients' lives. The tool is freely hosted online by the University of Kansas Medical Center's Department of Biostatistics and Data Science. The supporting materials for the application are publicly accessible on GitHub.

Comparing outcomes of right verse left hepatic approach percutaneous biliary drainage catheters.

Purpose: Determine if there is a difference in adverse events (AE) between right or left hepatic percutaneous biliary drain placement (PTBD) in patients with biliary strictures. Materials & methods: This retrospective study included patients with benign or malignant biliary stricture treated with PTBD at a single institution from 7/28/2004-3/30/2021. 357 patients met inclusion criteria, 77 (21.6 %) had PTBD on the left and 280 (78.4 %) on the right. AEs associated with the initial drain placement or during subsequent intervention were collected and categorized. AEs that were grouped as periprocedural included: surgery, infection, hemorrhage, and drain failure. AEs in the postprocedural group included: chills, catheter displacement, cholangitis, biliary stones, drain malfunction, fever resolving without treatment, and pericatheter leakage. Surgery was considered a major AE and the remaining AEs were categorized as minor. Statistical analyses were performed using Logistic Regression Analysis and p-values less than 0.05 were considered statistically significant. Results: Overall, there was no statistically significant difference in AEs between right and left drains in the periprocedural and postprocedural period (p = 0.832, OR = 0.95 and p = 0.808, OR = 0.93 respectively). When analyzing minor AEs individually, only cholangitis occurred at a higher rate on the right side (p = 0.033, OR = 0.43). There was no statistical difference in the rate of major AEs in the periprocedural period between left and right drains (p = 0.311, OR = 1.37). Conclusion: Current literature is equivocal when comparing right versus left percutaneous biliary drains. This analysis describes no statistically significant difference in AEs between right and left hepatobiliary drains aside from slightly higher incidence of cholangitis for right sided drains.

A Regional Study to Evaluate the Impact of Coal-fired Power Plants on Lung Cancer Incident Rates.

Background: Lung cancer is the leading cause of cancer related deaths. In Kansas, where coal-fired power plants account for 34% of power, we investigated whether hosting counties had higher age-adjusted lung cancer incidence rates. We also examined demographics, poverty levels, percentage of smokers, and environmental conditions using spatial analysis. Methods: Data from the Kansas Health Matters, and the Behavioral Risk Factor Surveillance System (2010-2014) for 105 counties in Kansas were analyzed. Multiple Linear Regression (MLR) assessed associations between potential risk factors and age-adjusted lung cancer incidence rates while Geographically Weighted Regression (GWR) examined regional risk factors. Results: Moran's I test confirmed spatial autocorrelation in age-adjusted lung cancer incidence rates (p<0.0003). MLR identified percentage of smokers, population size, and proportion of elderly population as significant predictors of age-adjusted lung cancer incidence rates (p<0.05). GWR showed positive associations between percentage of smokers and age-adjusted lung cancer incidence rates in over 50% of counties. Conclusion: Contrary to our hypothesis, proximity to a coal-fired power plant was not a significant predictor of age-adjusted lung cancer incidence rates. Instead, percentage of smokers emerged as a consistent global and regional risk factor. Regional lung cancer outcomes in Kansas are influenced by wind patterns and elderly population.

An assessment of compositional methods for the analysis of DNA methylation-based deconvolution estimates.

DNA methylation (DNAm)-based deconvolution estimates contain relative data, forming a composition, that standard methods (testing directly on cell proportions) are ill-suited to handle. In this study we examined the performance of an alternative method, analysis of compositions of microbiomes (ANCOM), for the analysis of DNAm-based deconvolution estimates. We performed two different simulation studies comparing ANCOM to a standard approach (two sample t-test performed directly on cell proportions) and analyzed a real-world data from the Women's Health Initiative to evaluate the applicability of ANCOM to DNAm-based deconvolution estimates. Our findings indicate that ANCOM can effectively account for the compositional nature of DNAm-based deconvolution estimates. ANCOM adequately controls the false discovery rate while maintaining statistical power comparable to that of standard methods.

DNA methylation (DNAm)-based deconvolution provides highly accurate estimates of the proportion of each cell type in a mixed-cell type biological sample (e.g., whole-blood). These estimates can be used for examining the association between cell type proportions and biological or clinical end points; for example, comparing the estimated neutrophil proportion in whole blood between smokers and non-smokers. Cell proportion data has unique features which present challenges for traditional and widely used statistical methods. In response to this issue, our work presents two simulation studies and a real-world analysis that benchmark the performance of current standard statistical methods against an alternative method called analysis composition of microbes (ANCOM), which was originally developed for the analysis of microbiome data. In our real-world analysis we used DNAm data collected from Women's Health Initiative Long Life Study I and compared the results of each method against a gold-standard that is typically not available for these analyses. In each of our simulation studies, ANCOM was able to detect true differences in cell proportions between the groups being compared but had a much lower rate of false discovery compared with the standard statistical methods. Our real-world analysis demonstrated similar findings. Overall, our study highlights the potential of ANCOM as a powerful and robust method for analyzing DNAm-derived deconvolution estimates when the interest is comparisons of cell type proportions and biological or clinical end points. ANCOM's ability to minimize false discovery while maintaining robust statistical power positions it as a valuable addition to the epigenomic analysis toolkit.

Acute HDM exposure shows time-of-day and sex-based differences in the severity of lung inflammation and circadian clock disruption.

Background: Asthma is a chronic inflammatory disease that shows a time-of-day response to variations in symptoms/severity. However, how the lung circadian clock influences time-of-day response and sex-based differences in house dust mite (HDM)-induced airway inflammation and remodeling has not been thoroughly investigated. Objective: We sought to determine whether acute HDM exposure in wild-type mice shows time-of-day response and sex-based differences in allergic airway inflammation and circadian clock disruption in the lungs. Methods: Wild-type (C57BL/6J) and Rev-erbα knockout (KO) mice were exposed to either PBS or HDM (for 10 days) intranasally at Zeitgeber time (ZT0: 6 am; ZT12: 6 pm) and euthanized 48 hours after the last exposure. Acute HDM-induced time-of-day response and sex-based differences in lung inflammation, gated cytokines/chemokines, humoral and hormonal responses, and circadian clock gene expression were analyzed. Results: Acute HDM-exposed mice showed a time-of-day response and sex-based differences in exaggerated lung inflammation (inflammatory eosinophils and interstitial macrophages) at ZT12 when compared with ZT0. HDM-exposed female mice showed increased inflammatory response at ZT12, but HDM-exposed male mice showed comparatively lower inflammation with no time-of-day response. HDM-exposed female and male mice showed augmented IgE levels at ZT12 when compared with ZT0. Myeloid innate immunity panel, cytokines/chemokines, and mucin genes showed a time-of-day gating response at ZT0 and ZT12 in the HDM group. In addition, HDM exposure altered the expression of circadian clock genes in the lung, which was evident in female mice at ZT12. Overall, female mice showed significant time-of-day responses to all these parameters compared with male mice. Rev-erbα KO mice exposed to acute HDM showed exaggerated lung inflammation associated with increased IgE and proinflammatory cytokines in bronchoalveolar lavage fluid. Interestingly, HDM exposure causes reduced expression of clock genes in flow-sorted resident eosinophils but not alveolar macrophages. Acute HDM exposure reduced the nocturnal locomotor activity in mice 5 days post-HDM exposure until day 10. Conclusions: This study shows a time-of-day response to acute HDM exposure and sex-based differences in the severity of lung inflammation and humoral immune response associated with circadian clock disruption. Our findings support the use of separate female and male mice cohorts for preclinical studies to understand the molecular heterogeneity in asthma pathophysiology.

Chronic HDM exposure shows time-of-day and sex-based differences in inflammatory response associated with lung circadian clock disruption.

Circadian rhythms and sex differences are involved in the pathophysiology of asthma. Yet, there are no reports that simultaneously address the role of the circadian clock and sex-based differences in chronic house dust mite (HDM)-induced asthma. Here, we sought to determine if chronic HDM exposure during the resting phase (zeitgeber time: ZT0/6:00 a.m.) versus the active phase (ZT12/6:00 p.m.) differentially affects the circadian clock and alters asthma pathobiology in female and male mice. HDM exposure at ZT12 exaggerated infiltration of eosinophil subtypes and associated chemokines in females compared to males. Furthermore, HDM exposure augmented eosinophil chemokines, Th2 gene expression and cytokine release, and humoral immune response in females compared to males at ZT12. Concurrently, histopathological evaluation confirmed increased airway inflammation at ZT12 in both females and males. Overall, we showed a time-of-day response and sex-based differences in HDM-induced exaggerated asthmatic phenotypes (inflammation/remodeling) and circadian clock disruption in females compared to males.

The Effects of COVID-19 Pandemic Policy on Social Needs Across the State of Kansas and Western Missouri: Paired Survey Response Testing.

BACKGROUND: Studying patients' social needs is critical to the understanding of health conditions and disparities, and to inform strategies for improving health outcomes. Studies have shown that people of color, low-income families, and those with lower educational attainment experience greater hardships related to social needs. The COVID-19 pandemic represents an event that severely impacted people's social needs. This pandemic was declared by the World Health Organization on March 11, 2020, and contributed to food and housing insecurity, while highlighting weaknesses in the health care system surrounding access to care. To combat these issues, legislators implemented unique policies and procedures to help alleviate worsening social needs throughout the pandemic, which had not previously been exerted to this degree. We believe that improvements related to COVID-19 legislature and policy have positively impacted people's social needs in Kansas and Missouri, United States. In particular, Wyandotte County is of interest as it suffers greatly from issues related to social needs that many of these COVID-19-related policies aimed to improve. OBJECTIVE: The research objective of this study was to evaluate the change in social needs before and after the COVID-19 pandemic declaration based on responses to a survey from The University of Kansas Health System (TUKHS). We further aimed to compare the social needs of respondents from Wyandotte County from those of respondents in other counties in the Kansas City metropolitan area. METHODS: Social needs survey data from 2016 to 2022 were collected from a 12-question patient-administered survey distributed by TUKHS during a patient visit. This provided a longitudinal data set with 248,582 observations, which was narrowed down into a paired-response data set for 50,441 individuals who had provided at least one response before and after March 11, 2020. These data were then bucketed by county into Cass (Missouri), Clay (Missouri), Jackson (Missouri), Johnson (Kansas), Leavenworth (Kansas), Platte (Missouri), Wyandotte (Kansas), and Other counties, creating groupings with at least 1000 responses in each category. A pre-post composite score was calculated for each individual by adding their coded responses (yes=1, no=0) across the 12 questions. The Stuart-Maxwell marginal homogeneity test was used to compare the pre and post composite scores across all counties. Additionally, McNemar tests were performed to compare responses before and after March 11, 2020, for each of the 12 questions across all counties. Finally, McNemar tests were performed for questions 1, 7, 8, 9, and 10 for each of the bucketed counties. Significance was assessed at P<.05 for all tests. RESULTS: The Stuart-Maxwell test for marginal homogeneity was significant (P<.001), indicating that respondents were overall less likely to identify an unmet social need after the COVID-19 pandemic. McNemar tests for individual questions indicated that after the COVID-19 pandemic, respondents across all counties were less likely to identify unmet social needs related to food availability (odds ratio [OR]=0.4073, P<.001), home utilities (OR=0.4538, P<.001), housing (OR=0.7143, P<.001), safety among cohabitants (OR=0.6148, P<.001), safety in their residential location (OR=0.6172, P<.001), child care (OR=0.7410, P<0.01), health care access (OR=0.3895, P<.001), medication adherence (OR=0.5449, P<.001), health care adherence (OR=0.6378, P<.001), and health care literacy (0.8729, P=.02), and were also less likely to request help with these unmet needs (OR=0.7368, P<.001) compared with prepandemic responses. Responses from individual counties were consistent with the overall results for the most part. Notably, no individual county demonstrated a significant reduction in social needs relating to a lack of companionship. CONCLUSIONS: Post-COVID-19 responses showed improvement across almost all social needs-related questions, indicating that the federal policy response possibly had a positive impact on social needs across the populations of Kansas and western Missouri. Some counties were impacted more than others and positive outcomes were not limited to urban counties. The availability of resources, safety net services, access to health care, and educational opportunities could play a role in this change. Future research should focus on improving survey response rates from rural counties to increase their sample size, and to evaluate other explanatory variables such as food pantry access, educational status, employment opportunities, and access to community resources. Government policies should be an area of focused research as they may affect the social needs and health of the individuals considered in this analysis.

Bolstering the complex study start-up process at NCI cancer centers using technology.

Background: The study startup process for interventional clinical trials is a complex process that involves the efforts of many different teams. Each team is responsible for their startup checklist in which they verify that the necessary tasks are done before a study can move on to the next team. This regulatory process provides quality assurance and is vital for ensuring patient safety [10]. However, without having this startup process centralized and optimized, study approval can take longer than necessary as time is lost when it passes through many different hands. Objective: This manuscript highlights the process and the systems that were developed at The University of Kansas Comprehensive Cancer Center regarding the study startup process. To facilitate this process the regulatory management, site development, cancer center administration, and the Biostatistics & Informatics Shared Resources (BISR) teams came together to build a platform aimed at streamlining the startup process and providing a transparent view of where a study is in the startup process. Process: Ensuring the guidelines are clearly articulated for the review criteria of each of the three review boards, i.e., Disease Working Group (DWG), Executive Resourcing Committee (ERC), and Protocol Review and Monitoring Committee (PRMC) along with a system that can track every step and its history throughout the review process. Results: Well-defined processes and tracking methodologies have allowed the operations teams to track each study closely and ensure the 90-day and 120-day deadlines are met, this allows the operational team to dynamically prioritize their work daily. It also provides Principal investigators a transparent view of where their study stands within the study startup process and allows them to prepare for the next steps accordingly. Conclusion/future work: The current process and technology deployment has been a significant improvement to expedite the review process and minimize study startup delays. There are still a few opportunities to fine-tune the study startup process; an example of which includes automatically informing the operational managers or the study teams to act upon deadlines regarding study review rather than the current manual communication process which involves them looking it up in the system which can add delays.

Accelerating Cancer Patient Recruitment Through a Mobile Application (Clinical Trial Finder).

OBJECTIVE: Participant recruitment is a challenge for any clinical trial but is especially complex in cancer specifically due to the need to initiate treatment urgently. Most participants enrolled in oncology clinical trials are identified as potential participants by the oncologist or other referring provider. Optimal clinical care for patients with cancer includes consideration of participation in a clinical trial. However, the process of finding a clinical trial that is appropriate the patient can be cumbersome and time consuming. MATERIAL AND METHODS: The University of Kansas Cancer Center has developed a mobile application (app) which streamlines the clinical trial search process for physicians, patients, and caregivers by cohesively integrating all clinical trials currently recruiting in the center and making them easy to browse. RESULTS: Key aspects of the app include simple filtering options, the ability to search for trials by name, easily accessible assistance, and in-app referral by phone or email. Initial feedback on the app has been very positive, with several suggestions already being implemented in future development. The app was designed to be used both by physicians to find trials, as well as patients in collaboration with their physicians. CONCLUSION: While long-term results will be crucial to understanding how the app can best serve our patient population, our initial results suggest that health system specific clinical trial apps can address a currently unmet need in the clinical trial recruitment process.

A framework for personalized mammogram screening.

Breast cancer screening guidelines serve as crucial evidence-based recommendations in deciding when to begin regular screenings. However, due to developments in breast cancer research and differences in research interpretation, screening guidelines can vary between organizations and within organizations over time. This leads to significant lapses in adopting updated guidelines, variable decision making between physicians, and unnecessary screening for low to moderate risk patients (Jacobson and Kadiyala, 2017; Corbelli et al., 2014). For analysis, risk factors were assessed for patient screening behaviors and results. The outcome variable for the first analysis was whether the patient had undergone screening. The risk factors considered were age, marital status, education level, rural versus urban residence, and family history of breast cancer. The outcome variable for the second analysis was whether patients who had undergone breast cancer screening presented abnormal results. The risk factors considered were age, Body Mass Index, family history, smoking and alcohol status, hormonal contraceptive use, Hormone Replacement Therapy use, age of first pregnancy, number of pregnancies (parity), age of first menses, rural versus urban residence, and whether or not patients had at least one child. Logistic regression analysis displayed strong associations for both outcome variables. Risk of screening nonattendance was negatively associated with age as a continuous variable, age as a dichotomous variable, being married, any college education, and family history. Risk of one or more abnormal mammogram findings was positively associated with family history, and hormonal contraceptive use. This procedure will be further developed to incorporate additional risk factors and refine the analysis of currently implemented risk factors.