Logistic regression analysis of populations of electrophysiological models to assess proarrythmic risk.

Population-based computational approaches have been developed in recent years and helped to gain insight into arrhythmia mechanisms, and intra- and inter-patient variability (e.g., in drug responses). Here, we illustrate the use of multivariable logistic regression to analyze the factors that enhance or reduce the susceptibility to cellular arrhythmogenic events. As an example, we generate 1000 model variants by randomly modifying ionic conductances and maximal rates of ion transports in our atrial myocyte model and simulate an arrhythmia-provoking protocol that enhances early afterdepolarization (EAD) proclivity. We then treat EAD occurrence as a categorical, yes or no variable, and perform logistic regression to relate perturbations in model parameters to the presence/absence of EADs. We find that EAD formation is sensitive to the conductance of the voltage-gated Na+, the acetylcholine-sensitive and ultra-rapid K+ channels, and the Na+/Ca2+ exchange current, which matches our mechanistic understanding of the process and preliminary sensitivity analysis. The described technique: •allows investigating the factors underlying dichotomous outcomes, and is therefore a useful tool improve our understanding of arrhythmic risk;•is valid for analyzing both deterministic and stochastic models, and various phenomena (e.g., delayed afterdepolarizations and Ca2+ sparks);•is computationally more efficient than one-at-a-time parameter sensitivity analysis

A Heart for Diversity: Simulating Variability in Cardiac Arrhythmia Research

In cardiac electrophysiology, there exist many sources of inter- and intra-personal variability. These include variability in conditions and environment, and genotypic and molecular diversity, including differences in expression and behavior of ion channels and transporters, which lead to phenotypic diversity (e.g., variable integrated responses at the cell, tissue, and organ levels). These variabilities play an important role in progression of heart disease and arrhythmia syndromes and outcomes of therapeutic interventions. Yet, the traditional in silico framework for investigating cardiac arrhythmias is built upon a parameter/property-averaging approach that typically overlooks the physiological diversity. Inspired by work done in genetics and neuroscience, new modeling frameworks of cardiac electrophysiology have been recently developed that take advantage of modern computational capabilities and approaches, and account for the variance in the biological data they are intended to illuminate. In this review, we outline the recent advances in statistical and computational techniques that take into account physiological variability, and move beyond the traditional cardiac model-building scheme that involves averaging over samples from many individuals in the construction of a highly tuned composite model. We discuss how these advanced methods have harnessed the power of big (simulated) data to study the mechanisms of cardiac arrhythmias, with a special emphasis on atrial fibrillation, and improve the assessment of proarrhythmic risk and drug response. The challenges of using in silico approaches with variability are also addressed and future directions are proposed

A neuronal network of mitochondrial dynamics regulates metastasis.

The role of mitochondria in cancer is controversial. Using a genome-wide shRNA screen, we now show that tumours reprogram a network of mitochondrial dynamics operative in neurons, including syntaphilin (SNPH), kinesin KIF5B and GTPase Miro1/2 to localize mitochondria to the cortical cytoskeleton and power the membrane machinery of cell movements. When expressed in tumours, SNPH inhibits the speed and distance travelled by individual mitochondria, suppresses organelle dynamics, and blocks chemotaxis and metastasis, in vivo. Tumour progression in humans is associated with downregulation or loss of SNPH, which correlates with shortened patient survival, increased mitochondrial trafficking to the cortical cytoskeleton, greater membrane dynamics and heightened cell invasion. Therefore, a SNPH network regulates metastatic competence and may provide a therapeutic target in cancer

A computational model of induced pluripotent stem-cell derived cardiomyocytes incorporating experimental variability from multiple data sources

KEY POINTS: Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) capture patient-specific genotype-phenotype relationships, as well as cell-to-cell variability of cardiac electrical activity Computational modelling and simulation provide a high throughput approach to reconcile multiple datasets describing physiological variability, and also identify vulnerable parameter regimes We have developed a whole-cell model of iPSC-CMs, composed of single exponential voltage-dependent gating variable rate constants, parameterized to fit experimental iPSC-CM outputs We have utilized experimental data across multiple laboratories to model experimental variability and investigate subcellular phenotypic mechanisms in iPSC-CMs This framework links molecular mechanisms to cellular-level outputs by revealing unique subsets of model parameters linked to known iPSC-CM phenotypes ABSTRACT: There is a profound need to develop a strategy for predicting patient-to-patient vulnerability in the emergence of cardiac arrhythmia. A promising in vitro method to address patient-specific proclivity to cardiac disease utilizes induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). A major strength of this approach is that iPSC-CMs contain donor genetic information and therefore capture patient-specific genotype-phenotype relationships. A cited detriment of iPSC-CMs is the cell-to-cell variability observed in electrical activity. We postulated, however, that cell-to-cell variability may constitute a strength when appropriately utilized in a computational framework to build cell populations that can be employed to identify phenotypic mechanisms and pinpoint key sensitive parameters. Thus, we have exploited variation in experimental data across multiple laboratories to develop a computational framework for investigating subcellular phenotypic mechanisms. We have developed a whole-cell model of iPSC-CMs composed of simple model components comprising ion channel models with single exponential voltage-dependent gating variable rate constants, parameterized to fit experimental iPSC-CM data for all major ionic currents. By optimizing ionic current model parameters to multiple experimental datasets, we incorporate experimentally-observed variability in the ionic currents. The resulting population of cellular models predicts robust inter-subject variability in iPSC-CMs. This approach links molecular mechanisms to known cellular-level iPSC-CM phenotypes, as shown by comparing immature and mature subpopulations of models to analyse the contributing factors underlying each phenotype. In the future, the presented models can be readily expanded to include genetic mutations and pharmacological interventions for studying the mechanisms of rare events, such as arrhythmia triggers.S

CaMKII delta C Drives Early Adaptive Ca(2+)Change and Late Eccentric Cardiac Hypertrophy

Rationale: CaMKII (Ca2+-Calmodulin dependent protein kinase) delta C activation is implicated in pathological progression of heart failure (HF) and CaMKII delta C transgenic mice rapidly develop HF and arrhythmias. However, little is known about early spatio-temporal Ca(2+)handling and CaMKII activation in hypertrophy and HF. Objective: To measure time- and location-dependent activation of CaMKII delta C signaling in adult ventricular cardiomyocytes, during transaortic constriction (TAC) and in CaMKII delta C transgenic mice. Methods and Results: We used human tissue from nonfailing and HF hearts, 4 mouse lines: wild-type, KO (CaMKII delta-knockout), CaMKII delta C transgenic in wild-type (TG), or KO background, and wild-type mice exposed to TAC. Confocal imaging and biochemistry revealed disproportional CaMKII delta C activation and accumulation in nuclear and perinuclear versus cytosolic regions at 5 days post-TAC. This CaMKII delta activation caused a compensatory increase in sarcoplasmic reticulum Ca(2+)content, Ca(2+)transient amplitude, and [Ca2+] decline rates, with reduced phospholamban expression, all of which were most prominent near and in the nucleus. These early adaptive effects in TAC were entirely mimicked in young CaMKII delta TG mice (6-8 weeks) where no overt cardiac dysfunction was present. The (peri)nuclear CaMKII accumulation also correlated with enhanced HDAC4 (histone deacetylase) nuclear export, creating a microdomain for transcriptional regulation. At longer times both TAC and TG mice progressed to overt HF (at 45 days and 11-13 weeks, respectively), during which time the compensatory Ca(2+)transient effects reversed, but further increases in nuclear and time-averaged [Ca2+] and CaMKII activation occurred. CaMKII delta TG mice lacking delta B exhibited more severe HF, eccentric myocyte growth, and nuclear changes. Patient HF samples also showed greatly increased CaMKII delta expression, especially for CaMKII delta C in nuclear fractions. Conclusions: We conclude that in early TAC perinuclear CaMKII delta C activation promotes adaptive increases in myocyte Ca(2+)transients and nuclear transcriptional responses but that chronic progression of this nuclear Ca2+-CaMKII delta C axis contributes to eccentric hypertrophy and HF

Imaging features and ultraearly hematoma growth in intracerebral hemorrhage associated with COVID-19

Purpose: Intracerebral hemorrhage (ICH) is an uncommon but deadly event in patients with COVID-19 and its imaging features remain poorly characterized. We aimed to describe the clinical and imaging features of COVID-19-associated ICH. Methods: Multicenter, retrospective, case-control analysis comparing ICH in COVID-19 patients (COV19\u2009+) versus controls without COVID-19 (COV19\u2009-). Clinical presentation, laboratory markers, and severity of COVID-19 disease were recorded. Non-contrast computed tomography (NCCT) markers (intrahematoma hypodensity, heterogeneous density, blend sign, irregular shape fluid level), ICH location, and hematoma volume (ABC/2 method) were analyzed. The outcome of interest was ultraearly hematoma growth (uHG) (defined as NCCT baseline ICH volume/onset-to-imaging time), whose predictors were explored with multivariable linear regression. Results: A total of 33 COV19\u2009+\u2009patients and 321 COV19\u2009-\u2009controls with ICH were included. Demographic characteristics and vascular risk factors were similar in the two groups. Multifocal ICH and NCCT markers were significantly more common in the COV19\u2009+\u2009population. uHG was significantly higher among COV19\u2009+\u2009patients (median 6.2 mL/h vs 3.1 mL/h, p\u2009=\u20090.027), and this finding remained significant after adjustment for confounding factors (systolic blood pressure, antiplatelet and anticoagulant therapy), in linear regression (B(SE)\u2009=\u20090.31 (0.11), p\u2009=\u20090.005). This association remained consistent also after the exclusion of patients under anticoagulant treatment (B(SE)\u2009=\u20090.29 (0.13), p\u2009=\u20090.026). Conclusions: ICH in COV19\u2009+\u2009patients has distinct NCCT imaging features and a higher speed of bleeding. This association is not mediated by antithrombotic therapy and deserves further research to characterize the underlying biological mechanisms

Different paths, same destination: divergent action potential responses produce conserved cardiac fight-or-flight response in mouse and rabbit hearts

Sympathetic activation of the heart results in positive chronotropy and inotropy, which together rapidly increase cardiac output. The precise mechanisms that produce the electrophysiological and Ca2+ handling changes underlying chronotropic and inotropic responses have been studied in detail in isolated cardiac myocytes. However, few studies have examined the dynamic effects of physiological sympathetic nerve activation on cardiac action potentials (APs) and intracellular Ca2+ transients (CaTs) in the intact heart. Here, we performed bilateral sympathetic nerve stimulation (SNS) in fully innervated, Langendorff‐perfused rabbit and mouse hearts. Dual optical mapping with voltage‐ and Ca2+‐sensitive dyes allowed for analysis of spatio‐temporal AP and CaT dynamics. The rabbit heart responded to SNS with a monotonic increase in heart rate (HR), monotonic decreases in AP and CaT duration (APD, CaTD), and a monotonic increase in CaT amplitude. The mouse heart had similar HR and CaT responses; however, a pronounced biphasic APD response occurred, with initial prolongation (50.9 ± 5.1 ms at t = 0 s vs. 60.6 ± 4.1 ms at t = 15 s, P < 0.05) followed by shortening (46.5 ± 9.1 ms at t = 60 s, P = NS vs. t = 0). We determined the biphasic APD response in mouse was partly due to dynamic changes in HR during SNS and was exacerbated by β‐adrenergic activation. Simulations with species‐specific cardiac models revealed that transient APD prolongation in mouse allowed for greater and more rapid CaT responses, suggesting more rapid increases in contractility; conversely, the rabbit heart requires APD shortening to produce optimal inotropic responses. Thus, while the cardiac fight‐or‐flight response is highly conserved between species, the underlying mechanisms orchestrating these effects differ significantly