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Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Epilepsy-related mortality, including Sudden Unexpected Death in Epilepsy and suicide, is a crucial topic within the interdisciplinary scope of caring for people with epilepsy (PWE). This review highlights best practices that emphasize proactive education for patients, caregivers, and communities, as well as evidence-based strategies and interventions for seizure management aimed at reducing mortality risk. It further underscores the essential contribution of the multidisciplinary care team in managing epilepsy-related mortality, highlighting considerations such as comorbid behavioral health conditions, challenges with treatment adherence, the use of the ketogenic diet, and the impact of social determinants of health and health disparities on historically marginalized populations. The authors provide actionable insights to address these challenges and barriers and enhance the outcomes and quality of life for PWE and their loved ones.

Abstract Background Ventricular systolic dysfunction (LVSD) is the main predictor of mortality in Chagas disease (ChD). Although LVSD can be treated with affordable medications that enhance both symptoms and survival, its diagnosis necessitates advanced imaging tests, which are often unavailable in resource-limited settings. Recently, artificial intelligence (AI) models applied to an electrocardiogram (ECG) have shown promise in detecting LVSD and assessing disease progression, acting as digital biomarkers and offering the potential for screening tools. Purpose This study aims to evaluate the performance of an AI-ECG model in detecting LVSD and predicting mortality in patients with ChD. Specifically, we will fine-tune the AI-ECG model to improve LVSD identification and update the previously published mortality score (JAHA) by replacing NT-proBNP with AI-ECG to assess mortality risk. Methods This study was conducted with patients from the SaMi-Trop project, a prospective cohort of individuals seropositive for ChD from 21 municipalities in Minas Gerais, an endemic region of Brazil. The baseline assessment occurred in 2013–2014, with follow-ups in 2015–2016 (FU1) and 2022–2023 (FU2). The AI-ECG model was fine-tuned using a dataset with an 8% low ejection fraction prevalence. The model was trained with a binary cross-entropy loss function, a batch size of 128, and an Adam optimizer with a learning rate of 0.001. The area under the curve (AUC) was calculated for validation. The fine-tuned model, parsed into 2-second ECG windows, was applied to two waves of the SaMi-Trop cohort: Baseline (4,701 ECGs from 1,906 patients) and FU1 (2,324 ECGs from 1,059 patients). The association between AI-detected LVSD (AI-LVSD) and mortality was assessed using Cox proportional hazard models. Results The fine-tuned AI-LVSD model achieved an AUC of 0.88 (95% CI: 0.78–0.97) in detecting LVSD. When updating the JAHA mortality score, AI-LVSD replaced NT-proBNP with a stronger association with mortality risk, yielding hazard ratios (HR) of 4.5 (95% CI: 3,0–6.8) for two-year mortality and 4.3 (95% CI: 3.4–5.5) for overall mortality. Additionally, when incorporated into a simplified hazard model alongside age and NYHA class, AI-LVSD emerged as a strong biomarker for mortality risk, with hazard ratios of 5.4 (95% CI: 3.7–7.8) for two-year mortality and 4.9 (95% CI: 4.0–6.1) for overall mortality (Figure 1). Conclusion The AI-ECG model accurately identified LVSD for screening purposes and effectively replaced NT-proBNP in a simplified mortality risk model for Chagas disease. This tool can potentially enhance early detection and risk stratification, particularly in remote areas with limited access to advanced diagnostic resources.Figure 01.Cox proportional hazard model

BACKGROUND: Thresholds to define prognosis with hs-cTnI (high-sensitivity cardiac troponin I) have not been systematically addressed in wild-type transthyretin amyloid cardiomyopathy, in part because of the multiplicity of hs-cTnI assays. The aims of this study were: first, to assess the prognostic performance of hs-cTnI measured with different assays in patients with wild-type transthyretin amyloid cardiomyopathy and, second, to identify assay-specific hs-cTnI thresholds for prognosis that could be integrated into staging systems for risk stratification. METHODS: Observational multicenter study of stable wild-type transthyretin amyloid cardiomyopathy patients from different cohorts using the Abbott Architect Stat hs-cTnI assay and the Beckman Coulter Access hs-cTnI assay (testing cohorts) and the Siemens Centaur XPT hs-cTnI assay (validation cohort). Outcome was all-cause mortality. RESULTS: In the Abbott cohort (n=136; median follow-up 22 [13–41] months; 31 [23%] deaths) and Beckman cohort (n=98; median follow-up 19 [12–28] months; 16 [16%] deaths), natural log-transformed hs-cTnI was an independent predictor of mortality (age- and sex-adjusted hazard ratio, 1.62 [95% CI, 1.11–2.35]; P =0.012 and 2.47 [95% CI, 1.48–4.14]; P <0.001, respectively). The best hs-cTnI threshold for 18-month mortality of the combined Abbott/Beckman cohorts (n=234) was 81 ng/L, rounded to 80 ng/L for simplicity of clinical use. A 2-variable staging system (based on the Mayo Clinic system) using hs-cTnI (>80 ng/L) and NPs (natriuretic peptides; NT-proBNP [N-terminal pro-B-type natriuretic peptide] >3000 ng/L or BNP [B-type natriuretic peptide] >250 ng/L) identified 3 groups with progressively worse prognosis. The staging system (using hs-cTnI >80 ng/L and NT-proBNP>3000 ng/L) was then applied to an independent cohort evaluated with the hs-cTnI Siemens assay (n=345, median follow-up 32 [24-42] months, 119 [34%] deaths). The significant differences between the groups were maintained. CONCLUSIONS: In patients with wild-type transthyretin amyloid cardiomyopathy, hs-cTnI is a strong and independent predictor of mortality. A threshold of hs-cTnI of 80 ng/L for these 3 assays provides effective risk stratification alone and in a staging system with NP.

AbstractThe European Society of Gastrointestinal Endoscopy (ESGE) presents a short list of performance measures for colonoscopy in inflammatory bowel disease (IBD) patients. Current performance measures for colonoscopy mainly focus on detecting (pre)malignant lesions. However, these performance measures are not relevant for all colonoscopy indications in IBD patients. Therefore, our aim was to provide endoscopy services across Europe and other interested countries with a tool for quality monitoring and improvement in IBD colonoscopy. Eight key performance measures and one minor performance measure were recommended for measurement and evaluation in daily endoscopy practice.