Citations

Objective We aimed to use machine learning (ML) models to investigate the impact of clinical, social and behavioural factors on 1-year progression from pre-diabetes to type 2 diabetes mellitus (DM). Design A retrospective cohort study. Setting A large health system including eight sites in southeast Michigan. Participants Adults with haemoglobin A1c (HbA1c) between 5.7% and 6.4% for two consecutive years between 1 January 2008 and 31 December 2023, and no prior history of type 2 DM or metformin use. Primary outcome measure New-onset type 2 DM (HbA1c ≥6.5%) in 1 year. Results Among 11 809 individuals, 815 (6.9%) progressed to type 2 DM within 1 year. CatBoost demonstrated the best performance (average area under the curve 0.78). Prior-year HbA1c was the most influential covariate (SHapley Additive exPlanations 1.02). Traditional metabolic factors (high-density lipoprotein, body mass index (BMI), white blood cell, age, gender, triglycerides) also contributed. Lastly, while inclusion of social and behavioural determinants of health (SBDH) did not significantly improve the overall model performance, depression emerged as the prominent SBDH covariate. Depression was a stronger predictor of diabetes progression in individuals with higher baseline BMI and lower baseline HbA1c. Conclusions Inclusion of social and behavioural covariates provided no incremental value for prediction of diabetes progression from pre-diabetes. However, machine learning revealed that depression may play a role in progression to type 2 DM.

Abstract Background Prostaglandin E2 (PGE2) exerts paradoxical effects in asthma, acting as both a protective mediator and a contributor to pathology depending on context. Its role is shaped by type 2 (T2)-status, eosinophilia, and exacerbation frequency. In epithelial cell cultures from asthmatic and healthy individuals, interleukin (IL)-13 suppresses PGE2 synthesis genes (PTGS2 and PGES) while upregulating HPGD, which encodes for the PGE2 catabolic enzyme 15-prostaglandin dehydrogenase (15-PGDH) (PMID:16751012), suggesting diminished PGE2 availability during T2 inflammation. Similarly, in aspirin-exacerbated respiratory disease (AERD), impaired cyclooxygenase disrupts PGE2 biosynthesis, fueling unchecked leukotriene production and eosinophilic inflammation (PMID: 30516547), underscoring PGE2’s protective role in limiting disease progression. Conversely, in nasal polyps, tuft cells are activated by IL-13 to produce PGE2 (PMID: 35608904), highlighting PGE2’s potential pathogenicity. Objective To assess associations between PGE2-pathway gene expression in bronchial brushings and asthma severity, and to determine how nasal polyp history modifies these relationships. Methods We analyzed bronchial epithelial brushings from 109 adults with asthma (mean age 42.4±12.1, 64% female, 52% severe asthma, 18% nasal polyps) using normalized and batch-corrected RNA-seq data from the baseline visit in the Severe Asthma Research Program (SARP)3 (PMID: 36796454). Age-adjusted and nasal polyp-adjusted relationships were calculated between ratios of PGE2 synthesis and metabolism genes and clinical outcomes (ASSESS score, FEV1 %predicted). The composite PGE2 score (PMID: 35608904), derived from nasal polyp analysis, was calculated from the average scaled log-normalized expression of six PGE2-responsive genes. All data were analyzed using a linear regression mixed model with a random effect for site. Results Ratios of PGE2 synthesis genes (PTGS1/2, PTGES2) to HPGD were significantly associated with greater disease severity (change in ASSESS Score) (Fig.1A, solid lines) and lower lung function (change in FEV1 %predicted) (Fig.1B, solid lines). These relationships persisted after adjusting for nasal polyps (Fig.1, dashed lines). The composite PGE2 score was also related to disease severity (Fig.1A, black solid line) but attenuated when nasal polyps were accounted for (Fig.1A, black dashed lines). Interestingly, lower lung function remained associated with the PGE2 score even after nasal polyp adjustment (Fig.1B, dashed black lines). Conclusions Our analysis demonstrates that the balance between PGE2 synthesis and degradation in the bronchial epithelium is closely linked to asthma severity and lung function, independent of nasal polyp status. Future work will integrate transcriptomic and clinical data longitudinally to establish whether PGE2 could serve as a biomarker for asthma trajectory. This abstract is funded by: HL115118 (LCD), U10HL109152 (S.E.W.), U10HL109172 (to E.I. and B.D.L), U10HL109168 (N.N.J.), U10HL109250 (S.C.E), U10HL109164 (W.C.M), U10HL109257 (M.C), and U10HL109146 (to P.G.W. and S.A.C.)

Abstract Motivation Intratumor heterogeneity arises from ongoing somatic evolution and complicates cancer diagnosis, prognosis, and treatment. Reconstructing evolutionary dynamics typically requires spatiotemporal samples, which are often unavailable in clinical settings. Computational approaches that can infer tumor evolutionary history from single-timepoint bulk sequencing data remain limited. Results We present estimating evolutionary events through single-timepoint sequencing (TEATIME), a novel computational framework that models tumors as mixtures of two competing cell populations: an ancestral clone with baseline fitness and a derived subclone with elevated fitness. Using cross-sectional bulk sequencing data, TEATIME estimates mutation rates, timing of subclone emergence, relative fitness, and number of generations of growth. To quantify intratumor fitness asymmetries, we introduce a novel metric—fitness diversity—which captures the imbalance between competing cell populations and serves as a measure of functional intratumor heterogeneity. Applying TEATIME to 33 tumor types from The Cancer Genome Atlas, we revealed divergent as well as convergent evolutionary patterns. Notably, we found that immune-hot microenvironments constraint subclonal expansion and limit fitness diversity. Moreover, we detected temporal dependencies in mutation acquisition, where early driver mutations in ancestral clones epistatically shape the fitness landscape, predisposing specific subclones to selective advantages. These findings underscore the importance of intratumor competition and tumor-microenvironment interactions in shaping evolutionary trajectories, driving intratumor heterogeneity. Lastly, we demonstrate that TEATIME-derived evolutionary parameters and fitness diversity offer novel prognostic insights across multiple cancer types. Availability and implementation R implementation of TEATIME is available on GitHub (https://github.com/liliulab/TEATIME) and Zenodo (https://zenodo.org/records/17422174).

Abstract Background: Black women continue to face disproportionate mortality and long-term challenges after breast cancer treatment, including gaps in follow-up care, culturally relevant support, and access to survivorship resources. Digital tools designed with Black survivors in mind remain limited, despite their potential to reduce disparities in post-treatment engagement. Objective: To address these gaps, we developed HERCaRE (Health Equity Resources for Breast Cancer Responsive Education), a progressive web application (PWA) designed to deliver culturally responsive survivorship education and engagement tools to Black breast cancer survivors. HERCaRE was designed to meet the need for a culturally responsive, easily accessible resource that empowers survivors to engage more confidently in their post-treatment care. Methods: The concept for HERCaRE was informed by a previous pilot study on virtual breast health education, in which participants expressed the need for more sustained and accessible support for survivors. Building on that insight, the platform was developed with advisory input from Black breast cancer survivors and community advocates through informal, discussion-based feedback. While not a formal co-design process, this input helped ensure cultural relevance in tone, structure, and visual language. HERCaRE includes three core features: educational modules on key survivorship topics, interactive behavior-prompting activities, and a notes section for self-reflection and goal tracking. The platform is grounded in the Health Promotion Model and RE-AIM framework, providing a foundation for future implementation and evaluation. The platform is currently being prepared for pilot testing, which will assess usability, perceived relevance, and engagement frequency among Black breast cancer survivors. Mixed-method surveys and platform analytics will guide refinement ahead of broader implementation. Preliminary Insights: Early input emphasized the importance of affirming, plain-language content and simple navigation. Activities were designed to promote exploration of the educational material and personal health behaviors through simple, self-guided prompts. Current efforts are focused on content finalization, participant recruitment, and platform readiness for testing. Conclusion: HERCaRE offers a responsive, theory-informed approach to digital survivorship support for Black women. While still in the pre-implementation phase, its development reflects a commitment to accessible design, cultural alignment, and future scalability. The platform lays important groundwork for reducing disparities in survivorship care and expanding digital health tools that center the needs of historically underserved populations. HERCaRE’s modular design and emphasis on user experience position it for adaptation across diverse clinical and community settings, including integration into survivorship programs serving other medically underserved populations. Citation Format: Manisha Salinas, Timethia Bonner, Laura Pacheco-Spann, Oluwadamilola Oladeru, Dianne Townsend, Che Ngufor. A culturally tailored digital health platform to improve breast cancer survivorship for Black women: HERCaRE [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr B048.

Abstract Outcomes in classic Hodgkin lymphoma (cHL) have steadily improved; however, additional therapies are needed for patients who relapse or do not respond to novel agents. Here, we report the efficacy and safety of camidanlumab tesirine (Cami), an anti-CD25 antibody-drug conjugate, in patients with relapsed/refractory cHL after brentuximab vedotin/programmed cell death protein 1 inhibitor therapies from the phase 2 ADCT-301-201 study. Eligible patients were adults with cHL who had received ≥3 previous lines of systemic therapy (or ≥2 if ineligible for hematopoietic stem cell transplant). Patients received 45 μg/kg Cami (IV, once every 3 weeks) in cycles 1 to 2, followed by 30 μg/kg IV once every 3 weeks for ≤1 year. The primary end point was overall response rate (ORR) per 2014 Lugano classification. Secondary end points included complete response rate (CRR), progression-free survival (PFS), and overall survival (OS). In total, 117 patients were enrolled with a median age of 37.0 years (range, 19-87). The ORR was 70.1% (95% confidence interval [CI], 60.9-78.2), with a CRR of 33.3% (95% CI, 24.9-42.6). The median PFS was 9.13 months (95% CI, 5.3-15.0); median OS was not reached. Thirty-three (28.2%) patients discontinued treatment because of treatment-emergent adverse events; the most common reasons were skin and subcutaneous tissue disorders (n = 10 [8.5%] patients), infections and infestations (n = 5 [4.3%]), and nervous systems disorders (n = 5 [4.3%]). Guillain-Barré–type or polyradiculopathy-type events occurred in 8 (6.8%) patients. Cami was efficacious in this heavily pretreated population; however, the efficacy was overshadowed by substantial issues with the safety profile. This trial was registered at www.clinicaltrials.gov as #NCT04052997.

Abstract RATIONALE: The American Thoracic Society (ATS) recently recommended using “race-neutral” GLI-Global prediction equations to interpret spirometry results. However, the unintended consequences for workers have not been fully evaluated. METHODS: We analyzed the impact of adopting GLI-Global on 24 hypothetical subjects, using on-line calculators to examine the effects on 1) larger vs. smaller predicted values; 2) Black, Southeast Asian, Northeast Asian, and White races; and 3) 80%, 100%, and 120% of race-specific predicted forced vital capacity (FVC). RESULTS: Race-specific predicted FVCs decline by group: White > NE Asian > SE Asian > Black, with a difference of 0.84 L between Blacks and Whites. GLI-Global Predicteds are midway between Blacks’ and Whites’. Workers at 80% of race-specific Predicted change the most when GLI-Global is employed: Blacks and SE Asians show declining %Predicted values and Z-scores and an increase in FVCs<LLN, while Whites and NE Asians show increasing %Predicted and Z-scores and a decrease in FVCs<LLN. CONCLUSIONS: Choice of prediction equation for use in occupational health practice differentially affects individuals in several groups: a) When fixed criteria are used for job placement and retention decisions, Black and SE Asian persons may be particularly adversely affected, while Whites and NE Asians will more likely exceed the fixed criteria; b) When fixed criteria are used for disability decisions, Black and SE Asian persons may look increasingly disabled, while White and NE Asian persons may now fail to qualify for disability; and c) Disparate effects are most prominent for persons with lung function measures in the lower portion of the normal range. Since occupational criteria are unlikely to change quickly, clinicians and policymakers should consider the real-world implications of mandating or recommending specific equations.

The effectiveness of in-person psychological interventions for chronic pain populations has been widely studied. The current retrospective pilot study evaluates the effectiveness of a 10-week integrative telehealth pain group intervention consisting of cognitive, behavioral, mindfulness, and lifestyle strategies on anxiety, depression, pain catastrophizing, pain interference, and pain intensity. Participants at a large multidisciplinary hospital are referred internally from various medical departments within the hospital. The present study consists of data from 9 group cohorts from October 2020 to June 2022. The study included 86 patients, with 52 completing all 10 weeks of the intervention with post-questionnaire data available. Measures assessing anxiety, depression, pain catastrophizing, pain interference, and pain intensity at baseline and at the completion of the intervention. A series of paired samples t-tests were used to assess change in each outcome measure from baseline to after completion of the program. All the outcome variables including anxiety, depression, pain interference, pain intensity, and pain catastrophizing showed statistically significant reductions after the intervention compared to baseline assessments. There were no significant differences in any of the demographic variables (age, gender, ethnicity, education level) or chronic pain condition between participants who did and did not complete the program. Preliminary data suggest that this 10-week integrative telehealth pain group intervention significantly lowered anxiety, depression, pain catastrophizing, pain interference, and pain intensity from pre- to post-intervention. Larger, randomized controlled studies are needed to validate these results.

Abstract The Midwest Aging Consortium (MAC) has emerged as a critical collaborative initiative aimed at advancing our understanding of aging and developing strategies to combat the rising prevalence of age-related diseases. Founded in 2019, MAC brings together researchers from various disciplines and institutions across the Midwestern United States to foster interdisciplinary geroscience research. This report summarizes the highlights of the Fourth Annual Symposium of MAC, which was held at Iowa State University in May 2023. The symposium featured presentations on a wide array of topics, including studies on slow-aging animals, cellular senescence and senotherapeutics, the role of the immune system in aging, metabolic changes in aging, neuronal health in aging, and biomarkers for measuring the aging process. Speakers shared findings from studies involving a variety of animals, ranging from commonly used species such as mice, rats, worms, yeast, and fruit flies, to less-common ones like naked mole-rats, painted turtles, and rotifers. MAC continues to emphasize the importance of supporting emerging researchers and fostering a collaborative environment, positioning itself as a leader in aging research. This symposium not only showcased the current state of aging biology research but also highlighted the consortium’s role in training the next generation of scientists dedicated to improving the healthspan and well-being of the aging population.