Citations

Abstract Objectives Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications. Materials and Methods A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions. Results Leveraging EHR data from 11 627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032). Discussion These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions. Conclusions Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques.

AbstractDNA damage plays a significant role in the tumorigenesis and progression of the disease. Abnormal DNA repair affects the therapy and prognosis of cancer. In this study, it is demonstrated that the deubiquitinase USP25 promotes non‐homologous end joining (NHEJ), which in turn contributes to chemoresistance in cancer. It is shown that USP25 deubiquitinates SHLD2 at the K64 site, which enhances its binding with REV7 and promotes NHEJ. Furthermore, USP25 deficiency impairs NHEJ‐mediated DNA repair and reduces class switch recombination (CSR) in USP25‐deficient mice. USP25 is overexpressed in a subset of colon cancers. Depletion of USP25 sensitizes colon cancer cells to IR, 5‐Fu, and cisplatin. TRIM25 is also identified, an E3 ligase, as the enzyme responsible for degrading USP25. Downregulation of TRIM25 leads to an increase in USP25 levels, which in turn induces chemoresistance in colon cancer cells. Finally, a peptide that disrupts the USP25‐SHLD2 interaction is successfully identified, impairing NHEJ and increasing sensitivity to chemotherapy in PDX model. Overall, these findings reveal USP25 as a critical effector of SHLD2 in regulating the NHEJ repair pathway and suggest its potential as a therapeutic target for cancer therapy.

Background: Despite the growing interest in the role of isolated left ventricular (LV) diastolic dysfunction in cardiac remodeling, little is known about its association with cognitive performance in midlife, prior to the onset of dementia. Hypothesis: We hypothesized that LV diastolic dysfunction and cardiac remodeling will be associated with cognitive performance in middle-aged adults. These associations might differ by sex and race. Aim: To investigate the impact of left atrial (LA) size, LV mass, volume, systolic and diastolic function on cognition in middle-aged Black and White, men and women from a rural, community-based cohort, the Bogalusa Heart Study (BHS), in Louisiana. Methods: A total of 1,107 participants from the BHS (48.1±5.4 years, 56.7% female, 34.3% black) with echocardiography and cognitive testing were included. Cognitive performance was quantified in a global cognitive score (GCS) comprised of the z standardized sum of 7 neuropsychiatric tests. Multivariate linear regression analysis was used for the association of E/e’, LA volume index (LAVi), LV end-diastolic volume (LVEDV), mass index (LVMi) as well as ejection fraction (LVEF) with GCS adjusted for age, sex, race, systolic and diastolic blood pressure, total and HDL cholesterol, history of smoking, diabetes, and hypertension as well as education. Interactions by sex and race were tested. Results: Even after adjusting for age, sex and race, larger LAVi, LVEDV, LVMi, higher E/e’ and lower e’ were associated with poorer cognitive function (all p <0.05), but not LVEF. These associations remained significant for E/e’, e’, and LVMi after adjusting for systolic and diastolic blood pressure, total and HDL cholesterol, history of smoking, diabetes, hypertension, as well as education. There was no significant race interaction. In contrast, the association of E/e’ with GCS was significantly stronger (standardized β coefficient =-0.20; p <0.01) in middle-aged women, but not in middle-aged men (standardized β coefficient =-0.04; p <0.36; p interaction=0.02). Conclusion: LV diastolic function is more closely associated with mid-life cognition than systolic function, and the association is present among middle aged women but not men.

Purpose: Population-based evidence in the interrelationships among hearing, brain structure, and cognition is limited. This study aims to investigate the cross-sectional associations of peripheral hearing, brain imaging measures, and cognitive function with speech-in-noise performance among older adults. Method: We studied 602 participants in the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) brain magnetic resonance imaging (MRI) ancillary study, including 427 ACHIEVE baseline (2018–2020) participants with hearing loss and 175 Atherosclerosis Risk in Communities Neurocognitive Study Visit 6/7 (2016–2017/2018–2019) participants with normal hearing. Speech-in-noise performance, as outcome of interest, was assessed by the Quick Speech-in-Noise (QuickSIN) test (range: 0–30; higher = better). Predictors of interest included (a) peripheral hearing assessed by pure-tone audiometry; (b) brain imaging measures: structural MRI measures, white matter hyperintensities, and diffusion tensor imaging measures; and (c) cognitive performance assessed by a battery of 10 cognitive tests. All predictors were standardized to z scores. We estimated the differences in QuickSIN associated with every standard deviation ( SD ) worse in each predictor (peripheral hearing, brain imaging, and cognition) using multivariable-adjusted linear regression, adjusting for demographic variables, lifestyle, and disease factors (Model 1), and, additionally, for other predictors to assess independent associations (Model 2). Results: Participants were aged 70–84 years, 56% female, and 17% Black. Every SD worse in better-ear 4-frequency pure-tone average was associated with worse QuickSIN (−4.89, 95% confidence interval, CI [−5.57, −4.21]) when participants had peripheral hearing loss, independent of other predictors. Smaller temporal lobe volume was associated with worse QuickSIN, but the association was not independent of other predictors (−0.30, 95% CI [−0.86, 0.26]). Every SD worse in global cognitive performance was independently associated with worse QuickSIN (−0.90, 95% CI [−1.30, −0.50]). Conclusions: Peripheral hearing and cognitive performance are independently associated with speech-in-noise performance among dementia-free older adults. The ongoing ACHIEVE trial will elucidate the effect of a hearing intervention that includes amplification and auditory rehabilitation on speech-in-noise understanding in older adults. Supplemental Material: https://doi.org/10.23641/asha.25733679

Abstract Background: In breast cancer, the spatial relationship between immune and tumor cells is increasingly recognized as critical in determining the efficacy of neoadjuvant therapy (NAT). This study investigated how the distribution of immune cells, particularly CD8+ T cells, relative to tumor cells affects treatment outcomes. Methods: Biopsies from 104 breast cancer patients were examined, both pre- and post-NAT, using multiplex immunohistochemistry (mIHC). This study focused on the density and distribution of CD8+ T cells, CD68+ macrophages, FoxP3+ regulatory T cells, and other immune markers. Results: The spatial proximity of CD8+ T cells within 20 µm of cancer cells (N20-CD8+T) was strongly correlated with improved clinical outcomes across diverse tumor subtypes and NAT regimens. A significant post-NAT decrease in CD4+, CD68+, and FoxP3+ cells highlights notable shifts in the tumor immune landscape. A noteworthy finding was the positive correlation between CXCL9 expression and N20-CD8+T cells, suggesting a mechanism for immune cell recruitment and interaction within the tumor microenvironment. These results highlight the complex interplay among NAT, immune cell modifications, and patient outcomes. Conclusions: This study revealed that the proximity of N20-CD8+ T cells to tumor cells is consistently associated with favorable NAT outcomes, transcending tumor subtypes, and treatment differences. This highlights the potential of immune cell dynamics, especially CD8+ T cells, as predictive biomarkers for therapeutic responses in breast cancer, underscoring their vital role in tumor immunity.