Citations

Background Irritable bowel syndrome (IBS) is a complex disorder of gut-brain interaction, with heterogeneous symptoms, no available biomarkers and limited pathogenetic insight. Objective To identify genetic risk factors and actionable mechanisms for future clinical translation in IBS. Design We conducted a genome-wide association study (GWAS) meta-analysis of IBS in 2 775 539 individuals from 22 biobanks. IBS genetics was studied across multiple ancestries, different case definitions and symptom-related subtypes. Heritability and genetic correlations with other traits were estimated, and Mendelian randomisation was used to test causal relationships. GWAS data were functionally annotated and fine-mapped to prioritise tissues, cell types, pathways, candidate genes, specific mechanisms and druggable targets. Results Significant heritability was only detected in individuals of European ancestry, with near-identical genetic architecture across case definitions. Genetic correlations with GI, psychiatric and cardiometabolic traits were observed, including causal relationships with triglyceride (TG) levels. Functional annotation of IBS risk loci highlighted cell types and pathways relevant to brain, enteric neuro-glial and cardiometabolic domains, as well as actionable targets like GCKR, a regulator of TG metabolism. Druggability analyses converged on cardiometabolic mechanisms, including TG modulation. IBS polygenic risk scores were derived and showed a significant association with case status in an independent case-control dataset, supporting further evaluation in external population-based and clinically ascertained cohorts. Conclusions This study provides the most comprehensive assessment of IBS genetics to date, demonstrating reproducible polygenic inheritance. We link IBS risk to convergent neurogastrointestinal and novel cardiometabolic mechanisms, highlight specific biological pathways and actionable mechanisms and outline translational opportunities emerging from integrated computational analyses.

Abstract The brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), relinquish physiological integrity and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to drive aggressive growth remains elusive. Here, we infused 13C-labeled glucose into patients and mice with brain cancer, coupled with quantitative metabolic flux analysis, to map the fates of glucose-derived carbon in tumor vs. cortex. Through the first direct and comprehensive measurements of carbon and nitrogen labeling in both cortex and glioma tissues, we uncover profound metabolic transformations. In human cortex, glucose carbons fuel essential physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. Conversely, gliomas downregulate these processes and scavenge alternative carbon sources such as amino acids from the environment, repurposing glucose-derived carbons to generate molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary amino acid modulation selectively alters GBM metabolism, slows tumor growth, and augments the efficacy of standard-of-care treatments. These findings illuminate how aggressive brain tumors exploit glucose to suppress normal physiological activity in favor of malignant expansion and offer potential therapeutic strategies to enhance treatment outcomes.

Abstract Chronic widespread pain (CWP) remains challenging due to its heterogeneous causes and complex mechanisms. A total of 2920 plasma proteins are analyzed from 29,254 UK Biobank participants. A total of 256 proteins are identified as cross‐sectionally correlated with CWP. A simple (top 10 proteins) and comprehensive (all significant proteins) proteomic‐based score (ProtS) is created for CWP diagnosis, both outperforming and improving the existing clinical score (area under the curve, AUC: 0.801, 0.723, and 0.791 alone, and 0.856 and 0.880 in combination). In addition, the protein score predicted 13‐years risk of pain‐related traits over the body, including pain onset, progression, and intensity; Moreover, it has stronger associations with nociplastic pain and fibromyalgia compared to nociceptive and neuropathic pain, implying a unique protein signature of different pain mechanisms. Finally, among 434 candidate proteins prioritized in the observational analysis, 18 are corroborated with causal relevance by Mendelian randomization, and importantly, four (CA14, DPEP1, LGALS3, and TNF) showed potential as novel drug targets repurposed for treating CWP.

Objective To describe the potential applications of awake cochlear implantation (CI). Patients Adult patients with sensorineural hearing loss who qualify for CI. Interventions CI under local anesthesia, without any form of systemic analgesia or anesthesia. Main Outcome Measures Acoustic hearing preservation, subjective patient report of cochlear implant pitch matching, and subjective patient report of cochlear implant sound quality. Results Four illustrative cases are presented, highlighting the potential uses of CI performed under local anesthesia for optimizing outcomes in hearing preservation, implant pitch matching, and implant sound quality. Conclusions CI under local anesthesia allows surgeons to use real-time patient feedback during electrode array insertion to minimize intracochlear trauma, particularly in cases where hearing preservation is a goal of CI, and to potentially improve implant performance by optimizing pitch matching and sound quality.

Abstract The complementarity and clinical utility of combining liquid biopsies and radiomic image analysis has not been demonstrated. ctDNA minimal residual disease after chemoradiotherapy (CRT) for non–small cell lung cancer (NSCLC) is highly prognostic, but on-treatment biomarkers are needed to enable response-adapted therapies. In this study, we analyzed 418 patients with NSCLC undergoing CRT to develop and validate a novel dynamic risk model that accurately predicts ultimate progression-free survival during treatment. We optimize tissue-free variant calling from plasma samples to facilitate ctDNA monitoring and demonstrate the importance of accounting for persistent clonal hematopoiesis variants. We show that mid-CRT ctDNA concentration is prognostic for disease progression and integrate additional pre-CRT risk factors, including radiomics, into a combined model that improves outcome prediction. Our results suggest that tumor features, radiomics, and mid-CRT ctDNA analysis are complementary and can identify patients at high and low risk of progression to potentially enable response-adapted therapies. Significance: This study demonstrates that combining tumor features, radiomics, and ctDNA analysis improves outcome prediction in NSCLC treated with CRT therapy. Our integrated model could enable personalized and response-adapted therapies to reduce toxicity and improve outcomes in patients. See related commentary by Anagnostou and Aggarwal, p. 1534

Abstract Objectives To explore patients’ use of patient portals to access lab test results, their comprehension of lab test data, and factors associated with these. Materials and Methods An online survey was administered to 276 adults 18+ years. Multivariate logistic regression was used to determine factors associated with patient portal use to view lab test results and lab test comprehension. Results The sample was predominantly White (72.5%), female (55.4%), with mean age 50.7 ± 15.5 years. Overall, participants had low numeracy (10.79 ± 2.71) and eHealth literacy skills (23.91 ± 5.29), and moderate lab test comprehension scores (18 ± 2.3). White participants with greater eHealth literacy were more likely to access lab test results via patient portals, whereas those with a college education were less likely to do so (χ2 [3]=31.23, P < .001). The regression showed that older age, fewer chronic conditions, and use of patient portals were significantly related to higher lab test comprehension scores (F [22, 250]=8.73, P <.001). Older adults performed better on comprehension tests but reported having difficulty understanding lab tests, expressing a preference for their doctors to explain them. Discussion The findings shed light on the experiences and needs of different user groups that must be addressed to enhance their ability to effectively use patient portals for obtaining lab test results. Conclusion More research is needed to determine patient barriers to comprehending lab test results online and to develop tailored strategies to improve patients’ self-efficacy to meaningfully use medical information in patient portals.

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.

Abstract Purpose To assess intra‐ (repeatability) and inter‐observer (reproducibility) variability of laser speckle flowgraphy (LSFG) for retinal blood flow (RBF) measurement in 20 eyes of wild type (C57BL/6J) mice and effect of intravitreal Aflibercept on RBF in optic nerve head (ONH) region of 10 eyes of Ins2 (Akita) diabetic mice. Methods ‘Mean blur rate (MBR)’ was measured for all quadrants of tissue area (MT), vessel (MV) and total area (MA) of ONH region. Changes in MT were analysed at each timepoint. Repeatability was evaluated by measuring MBR variability without changing mouse head position, and reproducibility after resetting mouse head position by another operator. Coefficient of repeatability (CR) through Bland–Altman plot method coefficient of variation (COV) and Intraclass correlation coefficient (ICC) was calculated. Intravitreal Aflibercept (1 μg) was administered to Akita eyes and intraocular pressure (IOP) was measured using a tonometer at baseline, day 7, 14, 21 and 28 post‐injection. Hurvich and Tsai's criterion was used. Results Coefficient of repeatability values of repeatability and reproducibility for all quadrants were within limits of agreement. Reliability was excellent (ICC 0.98–0.99) and reproducibility was moderate to excellent (ICC 0.64–0.96). There was a non‐significant IOP increase in all Akita eyes at Day 28 ( p > 0.05), and significant increase in MT in all quadrants at Day 21 and superior, inferior and temporal quadrants at Day 28 ( p < 0.05). Conclusion Laser speckle flowgraphy demonstrates excellent repeatability and moderate to excellent reproducibility in measuring RBF. Intravitreal Aflibercept injection results in a significant increase in MT up to 28 days post‐injection without significant increase in IOP.