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Microbiome functional gene pathways predict cognitive performance in older adults with Alzheimer's disease [preprint]
Get PDFThis article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.Disturbances in the gut microbiome is increasing correlated with neurodegenerative disorders, including Alzheimer's Disease. The microbiome may in fact influence disease pathology in AD by triggering or potentiating systemic and neuroinflammation, thereby driving disease pathology along the "microbiota-gut-brain-axis". Currently, drivers of cognitive decline and symptomatic progression in AD remain unknown and understudied. Changes in gut microbiome composition may offer clues to potential systemic physiologic and neuropathologic changes that contribute to cognitive decline. Here, we recruited a cohort of 260 older adults (age 60+) living in the community and followed them over time, tracking objective measures of cognition, clinical information, and gut microbiomes. Subjects were classified as healthy controls or as having mild cognitive impairment based on cognitive performance. Those with a diagnosis of Alzheimer's Diseases with confirmed using serum biomarkers. Using metagenomic sequencing, we found that relative species abundances correlated well with cognition status (MCI or AD). Furthermore, gene pathways analyses suggest certain microbial metabolic pathways to either be correlated with cognitive decline or maintaining cognitive function. Specifically, genes involved in the urea cycle or production of methionine and cysteine predicted worse cognitive performance. Our study suggests that gut microbiome composition may predict AD cognitive performance.No embarg
Multi-level socioeconomic modifiers of the comorbidity of post-traumatic stress and tobacco, alcohol, and cannabis use: the importance of income
No full textPurpose: Post-traumatic stress (PTS) symptoms are highly comorbid with substance use (i.e., alcohol, tobacco, and cannabis). Few studies have investigated potential individual-, household-, and neighborhood-level socioeconomic effect modifiers of this comorbidity in longitudinal analyses. We aim to examine interactions between this multi-level environment and PTS symptoms on future substance use behaviors.
Methods: Data were drawn from the Advancing Understanding of RecOvery afteR traumA (AURORA) study, including 2943 individuals who presented to the emergency department (ED) within 72 h of a traumatic event. Frequency of tobacco, alcohol, cannabis use, and PTS symptoms were reported at 6 timepoints. Mixed effect Poisson models, clustered by state, were used to generate incidence rate ratios (IRRs) substance use, both cross-sectionally and prospectively. Moderation analysis of PTS and substance use, stratified by household income and area deprivation index (ADI), was conducted using mixed effect models and parallel process growth curves.
Results: Significant associations were observed between PTS with tobacco, alcohol, and cannabis use frequency cross-sectionally, and for tobacco and alcohol and PTS exposure prospectively. Lower income (P < 0.001) and higher deprivation (P < 0.001) were associated with tobacco use, while higher income (P < 0.001) and less deprivation (P = 0.01) were associated with increased alcohol use. We found modest modification by household income for alcohol and tobacco, and little evidence of modification by neighborhood ADI.
Conclusions: Household income had greater evidence of effect modification for substance use, compared to neighborhood-level ADI. Our findings demonstrate that household indicators of socioeconomic status likely modify the relationship between PTS and substance use.No embarg
Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy
Get PDFBackground: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significant reproducibility issues. We compare the prediction of overall survival (OS) in recurrent high-grade glioma(HGG) patients undergoing immunotherapy, using deep learning (DL) classification networks along with radiomic signatures derived from manual and convolutional neural networks (CNN) automated segmentation.
Materials and methods: We retrospectively retrieved 154 cases of recurrent HGG from multiple centers. Tumor segmentation was performed by expert radiologists and a convolutional neural network (CNN). From the segmented tumors, 2553 radiomic features were extracted for each case. A robust feature subset was selected using intraclass correlation coefficient analysis between manual and automated segmentations. The data was divided into a 9:1 ratio and validated through ten-fold cross-validation and tested on a rotating test set. Features selection was done by the Kruskal-Wallis test. The Radiomics-based OS predictions, generated using Support Vector Machine (SVM), were compared between the two segmentation approaches and against OS prediction by the CNN model adapted for classification. Model efficacy was evaluated using the area under the receiver operating characteristic curve (AUC).
Results: The clinical model AUC for OS prediction was 0.640 ± 0.013 (mean ± 95% confidence interval) in the training set and 0.610 ± 0.131 in the test set. The radiomics prediction of OS based on manual segmentation outperformed automatic segmentation (AUC of 0.662 ± 0.122 vs. 0.471 ± 0.086, respectively) in the test set. Robust features improved the performance of manual segmentation to AUC of 0.700 ± 0.102, of automated segmentation to 0.554 ± 0.085. The CNN prognosis model demonstrated promising results, with an average AUC of 0.755 ± 0.071 for training sets and 0.700 ± 0.101 for the test set.
Conclusion: Manual segmentation-derived radiomic features outperformed automated segmentation-derived features for predicting OS in recurrent high-grade glioma patients undergoing immunotherapy. The end-to-end CNN prognosis model performed similarly to radiomics modeling using manual-segmentation-derived features without the need for segmentation. The potential time-saving must be weighed against the lower interpretability of end-to-end black box modeling.No embarg
Exploring Respect, Healthcare Utilization, and Affordability Among Transgender and Gender-Diverse Individuals: An All of Us Analysis
No full textNo embarg
Characterization of Blood Vascular Endothelial Cell Heterogeneity and Mechanisms Regulating Pericyte Cell Identity
No full textVascular system pathology is a precipitating factor in numerous diseases lacking effective treatment. Advancing our understanding of the cell types that comprise the vascular system opens new therapeutic avenues for these diseases. Two key vascular cell types are endothelial cells (ECs) and pericytes. ECs form a monolayer lining the lumen of all vessels and are essential to vascular function. Pericytes lie atop the EC monolayer, sharing a basement membrane. Together, ECs and pericytes preserve vascular integrity, regulate blood flow, mediate immune cell trafficking, and control the exchange of molecules between the bloodstream and surrounding tissues.
Recent advances in integrative single-cell transcriptomics and epigenomic profiling have facilitated tackling critical questions about ECs and pericytes. In this work, we examined EC transcriptional heterogeneity and interrogated the transcriptional and regulatory mechanism that control pericyte identity. Utilizing zebrafish (Danio rerio) as the model animal, single-cell RNA sequencing (scRNA-seq) of ECs followed by transgenic-reporter validation, revealed anatomical and function specific transcriptional signatures of ECs across the vascular tree. Parallel scRNA seq and single nucleus ATAC seq of pericytes identified notch3 as the central transcriptional hub in pericytes. Enhancers containing RBPJ DNA-binding motifs were sufficient to drive reporter expression in pericytes, while CRISPR-mediated disruption of these motifs abolished activity, demonstrating their necessity in vivo. Genetic analyses confirmed notch3’s essential role in pericyte development and uncovered an additional, non-redundant role for jag2b. These findings expand the molecular atlas of vascular cell types and uncover mechanisms by which notch3 maintains pericyte identity, offering new entry points for therapeutic modulation of vascular disease.Interdisciplinary Graduate Program2 years2027-12-0
UMCCTS Newsletter, February 2025
No full textThis is the February 2025 issue of the UMass Center for Clinical and Translational Science Newsletter containing news and events of interest.Supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grants UL1 TR001453, TL1 TR001454 and KL2 TR001455.No embarg
Uncovering the Mechanisms that Drive Resistance to Radiation Therapy in Triple-Negative Breast Cancer
Get PDFThe current therapeutic approaches for triple-negative breast cancer (TNBC) have not yielded the same clinical outcomes as the ones utilized in other breast cancer subtypes. A major reason for this is the lack of targeted treatment options that synergize with current treatment modalities, and limited exploration into the biological associations of therapy resistance and tumor progression. Radiation therapy significantly reduces locoregional recurrence rates for breast cancer patients, and the recent developments in image-based guidance improve efficacy and mitigate toxicity. However, the biological underpinnings of radiation resistance in TNBC are rarely studied. My work explored factors responsible for resistance to radiotherapy and it also uncovered the radiation-induced signaling cascades that impact metastasis of TNBC.
The first project of my thesis explores the role of inhibiting the binding of vascular endothelial growth factor (VEGF) to neuropilin-2 (NRP2) signaling to enhance the radiosensitivity of TNBC. Given the role of NRP2 in activating cancer stem cell (CSC) properties such as self-renewal and chemoresistance, I was intrigued by my data demonstrating that combining a function blocking antibody of VEGF/NRP2 with radiotherapy significantly decreases the survival of TNBC cell lines, organoids, and patient-derived xenografts (PDXs) compared to radiotherapy alone. I later determined that this sensitivity is a product of decreased nitric oxide synthase 2 (NOS2) expression in NRP2-expressing cells. The nitric oxide hub mediated by NRP2 expressing cells is a critical component of nuclear factor erythroid 2-related factor (Nrf2) activation and the expression of its antioxidant response elements. Therefore, the VEGF/NRP2 axis can mitigate the radiation-induced oxidative stress on tumor cells.
The second aspect of my thesis uncovers the role of RNA metabolism in radioresistant TNBC that mediates enhanced metastasis compared to radiosensitive TNBC. Specifically, I identified the role of the RNA binding protein heterogenous nuclear ribonucleoprotein L (HNRNPL) in mediating the formation of circular RNAs (circRNAs) that sponge the let-7 family of microRNAs (miRNAs). Overall, I implicated HNRNPL-derived circRNAs as important mediators of the stability of integrin b3 (ITGb3) mRNA, which promotes metastasis. Interestingly, this pathway is a byproduct of enhanced Nrf2 activation that can induce HNRNPL expression in TNBC.
Interestingly, the subpopulation of cells within TNBC that have the capacity to initiate antioxidant pathways are the ones capable of surviving radiation therapy, as well as execute cellular programs that mediate metastasis. In summary, my thesis provides a targeted therapy that can be utilized in TNBC to enhance its radiosensitivity, and I identify a novel mechanism within radioresistant TNBC that promotes its metastatic capacity.MD/PhDCancer BiologyNo embarg
Mobile applications for atrial fibrillation self-management: a systematic search and evaluation [preprint]
Get PDFThis article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.Atrial fibrillation (AF) is the most common cardiac arrhythmia, increasing the risk of stroke, heart failure, and healthcare costs. Although patient self-management can improve outcomes, sustaining long-term engagement is often difficult. Mobile health applications may help address this gap, but their quality and clinical alignment have not been systematically assessed using a validated framework. A structured search of the Apple App Store and Google Play Store identified free, English-language apps supporting AF self-management. Eligible apps included features such as symptom tracking, medication reminders, or educational content. App quality was assessed using the Mobile Application Rating Scale (MARS), which evaluates engagement, functionality, aesthetics, and information quality. Of 455 apps identified, five met all inclusion criteria. Common features included symptom tracking and medication logging, but coverage of evidence-based care domains varied. Mean MARS scores ranged from 4.07 to 4.53 out of 5. Higher-performing apps excelled in functionality and information quality but often lacked comprehensive integration of guideline-recommended care, such as stroke risk assessment or personalized feedback. These findings highlight a gap in high-quality, clinically grounded digital tools for AF self-care. Improved co-design processes and clearer frameworks for app evaluation may help guide the development and selection of effective tools to support AF self-management.
Author summary: We wanted to understand whether smartphone apps can help people manage atrial fibrillation (AF), a common heart rhythm condition that raises the risk of stroke and heart failure. While actively managing AF through lifestyle changes and regular monitoring can reduce health risks, many people find it hard to stay engaged over time. Mobile apps could make self-care more convenient, but their quality and usefulness vary greatly. We searched the two largest app stores for free apps in English that offer tools to help people track symptoms, manage medications, and learn about their condition. Out of more than 450 apps, only five met our criteria. We found that while these apps include helpful features, they often do not cover all aspects of AF care or follow current medical guidelines closely. Our findings show that people with AF have limited trustworthy options to support self-care. We hope our study encourages app developers, healthcare professionals, and patients to work together to create better digital tools that can safely and effectively support people living with AF.No embarg
Contralateral knee osteoarthritis severity relates to magnetic resonance imaging findings in knees with and without osteoarthritis: Data from the osteoarthritis initiative
Get PDFObjective: We explored whether a magnetic resonance imaging (MRI)-based composite score of bone marrow lesion and effusion-synovitis volumes related to contralateral knee osteoarthritis disease severity.
Design: Using data from the Osteoarthritis Initiative, we conducted cross-sectional knee-based analyses among participants with bilateral knee MRIs and at least one knee with Kellgren-Lawrence (KL) grade ≥1 and a WOMAC pain score ≥10/100 (n = 693). Bone marrow lesion and effusion-synovitis volumes on MRIs were used to calculate a composite score ("disease activity"). We divided the disease activity score into tertiles. We used multinomial logistic models to explore the association between disease activity in knees with and without radiographic osteoarthritis (outcome) and the contralateral disease severity (KL grade or disease activity; exposure).
Results: We included 1386 knees from participants with an average age of 62 (standard deviation = 9) years. Most participants were overweight and had mild-to-moderate radiographic osteoarthritis. Disease activity among knees without radiographic osteoarthritis had statistically significant relationships with contralateral disease activity (range of odds ratios: 4.86-23.22) but not contralateral KL grade (range of odds ratios: 0.86-1.01). Disease activity among knees with radiographic osteoarthritis had statistically significant relationships with contralateral disease activity and KL grade; however, the association was stronger for contralateral disease activity than KL grade (range of odds ratios: 3.67-21.29 versus 1.96-2.20).
Conclusion: Structural findings in one knee may relate to structural findings in the other knee. This highlights the need for future studies to explore how the contralateral knee could impact clinical trial screening, monitoring, and intervention strategies, especially when testing localized therapies.No embarg
Understanding Comorbidities in Hypermobile Ehlers-Danlos Syndrome: Could a Viral Infection Lead to a Diagnosis? [preprint]
Get PDFThis article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.Hypermobile Ehlers-Danlos Syndrome (hEDS) is a complex, underdiagnosed connective tissue disorder characterized by widespread symptoms affecting multiple organ systems. Recent clinical observations suggest that individuals with hEDS may be at increased risk for persistent symptoms following COVID-19, commonly referred to as Long COVID. Using data from over 23 million patients across the United States, we examined associations between hEDS, COVID-19 infection, Long COVID, and related chronic conditions. We identified nearly 30,000 individuals with hEDS and found that the estimated prevalence was approximately 1 in 800, higher than previously recognized. While rates of COVID-19 infection were similar between patients with hEDS and matched controls, those with hEDS were significantly more likely to develop Long COVID. This risk was especially elevated among patients with hEDS with overlapping conditions commonly seen in post-viral syndromes, including autonomic dysfunction, immune dysregulation, and chronic fatigue. Specifically, individuals with postural orthostatic tachycardia, mast cell-related symptoms, or chronic fatigue syndrome had the highest rates of Long COVID. Cumulative incidence analysis revealed that many patients received an hEDS diagnosis only after a COVID-19 infection, suggesting that viral illness may exacerbate or reveal previously unrecognized symptoms. Patients with hEDS also exhibited higher odds of having additional risk factors for severe or prolonged illness, including chronic lung and autoimmune conditions, depression, and cerebrovascular disease. These findings highlight a previously unrecognized vulnerability in patients with hEDS and underscore the need for greater clinical awareness of their heightened risk for persistent post-COVID illness. Improved screening, earlier diagnosis, and integrated care pathways are urgently needed to support this complex and underserved patient population.The UMass Center for Clinical and Translational Science (UMCCTS), UL1TR001453, helped fund this study.No embarg