Patchy fibrosis promotes trigger–substrate interactions that both generate and maintain atrial fibrillation

Fibrosis has been mechanistically linked to arrhythmogenesis in multiple cardiovascular conditions, including atrial fibrillation (AF). Previous studies have demonstrated that fibrosis can create functional barriers to conduction which may promote excitation wavebreak and the generation of re-entry, while also acting to pin re-entrant excitation in stable rotors during AF. However, few studies have investigated the role of fibrosis in the generation of AF triggers in detail. We apply our in-house computational framework to study the impact of fibrosis on the generation of AF triggers and trigger–substrate interactions in two- and three-dimensional atrial tissue models. Our models include a reduced and efficient description of stochastic, spontaneous cellular triggers as well as a simple model of heterogeneous intercellular coupling. Our results demonstrate that fibrosis promotes the emergence of focal excitations, primarily through reducing the electrotonic load on individual fibre strands. This enables excitation to robustly initiate within these single strands before spreading to neighbouring strands and inducing a full tissue focal excitation. Enhanced conduction block can allow trigger–substrate interactions that result in the emergence of complex, re-entrant excitation patterns. This study provides new insight into the mechanisms by which fibrosis promotes the triggers and substrate necessary to induce and sustain arrhythmia

Multi-scale approaches for the simulation of cardiac electrophysiology: I – sub-cellular and stochastic calcium dynamics from cell to organ

Computational models of the heart at multiple spatial scales, from sub-cellular nanodomains to the whole-organ, are a powerful tool for the simulation of cardiac electrophysiology. Application of these models has provided remarkable insight into the normal and pathological functioning of the heart. In these two articles, we present methods for modelling cardiac electrophysiology at all of these spatial scales. In part one, presented here, we discuss methods and approaches for modelling sub-cellular calcium dynamics at the whole-cell and organ scales, valuable for modelling excitation–contraction coupling and mechanisms of arrhythmia triggers

Ionic current changes underlying action potential repolarization responses to physiological pacing and adrenergic stimulation in adult rat ventricular myocytes

This study aimed to simulate ventricular responses to elevations in myocyte pacing and adrenergic stimulation using a novel electrophysiological rat model and investigate ion channel responses underlying action potential (AP) modulations. Peak ion currents and AP repolarization to 50% and 90% of full repolarization (APD50-90) were recorded during simulations at 1–10 Hz pacing under control and adrenergic stimulation conditions. Further simulations were performed with incremental ion current block (L-type calcium current, ICa; transient outward current, Ito; slow delayed rectifier potassium current, IKs; rapid delayed rectifier potassium current, IKr; inward rectifier potassium current, IK1) to identify current influence on AP response to exercise. Simulated APD50-90 closely resembled experimental findings. Rate-dependent increases in IKs (6%–101%), IKr (141%–1339%), and ICa (0%–15%) and reductions in Ito (11%–57%) and IK1 (1%–9%) were observed. Meanwhile, adrenergic stimulation triggered moderate increases in all currents (23%–67%) except IK1. Further analyses suggest AP plateau is most sensitive to modulations in Ito and ICa while late repolarization is most sensitive to IK1, ICa, and IKs, with alterations in IKs predominantly stimulating the greatest magnitude of influence on late repolarization (35%–846% APD90 prolongation). The modified Leeds rat model (mLR) is capable of accurately modeling APs during physiological stress. This study highlights the importance of ICa, Ito, IK1, and IKs in controlling electrophysiological responses to exercise. This work will benefit the study of cardiac dysfunction, arrythmia, and disease, though future physiologically relevant experimental studies and model development are required

Nasal Nitric Oxide in Primary Immunodeficiency and Primary Ciliary Dyskinesia: Helping to Distinguish Between Clinically Similar Diseases

Purpose: Primary ciliary dyskinesia (PCD) is a rare disorder of the mucociliary clearance leading to recurrent upper and lower respiratory tract infections. PCD is difficult to clinically distinguish from other entities leading to recurrent oto-sino-pulmonary infections, including primary immunodeficiency (PID). Nasal nitric oxide (nNO) is a sensitive and specific diagnostic test for PCD, but it has not been thoroughly examined in PID. Past publications have suggested an overlap in nNO levels among subjects with PCD and PID. We sought to determine if nNO measurements among patients diagnosed with PID would fall significantly above the established PCD diagnostic cutoff value of 77 nL/min. Methods: Children > 5 years old and adults with definitive PID or PCD diagnoses were recruited from outpatient subspecialty clinics. Participants underwent nNO testing by standardized protocol using a chemiluminescence analyzer and completed a questionnaire concerning their chronic oto-sino-pulmonary symptoms, including key clinical criteria specific to diagnosed PCD (neonatal respiratory distress at term birth, year-round cough or nasal congestion starting before 6 months of age, any organ laterality defect). Results: Participants included 32 patients with PID, 27 patients with PCD, and 19 healthy controls. Median nNO was 228.9.1 nL/min in the PID group, 19.7 nL/min in the PCD group, and 269.4 in the healthy controls (p < 0.0001). Subjects with PCD were significantly more likely to report key clinical criteria specific to PCD, but approximately 25% of PID subjects also reported at least 1 of these key clinical criteria (mainly year-round cough or nasal congestion). Conclusions: While key clinical criteria associated with PCD often overlap with the symptoms reported in PID, nNO measurement by chemiluminescence technology allows for effective discrimination between PID and PCD

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy