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AimsPost-infarct myocardium contains viable corridors traversing scar or lipomatous metaplasia (LM). Ventricular tachycardia (VT) circuitry has been separately reported to associate with corridors that traverse LM and with repolarization heterogeneity. We examined the association of corridor activation recovery interval (ARI) and ARI dispersion with surrounding tissue type.Methods and resultsThe cohort included 33 post-infarct patients from the prospective Intra-Myocardial Fat Deposition and Ventricular Tachycardia in Cardiomyopathy (INFINITY) study. We co-registered scar and corridors from late gadolinium enhanced magnetic resonance, and LM from computed tomography with intracardiac electrogram locations. Activation recovery interval was calculated during sinus or ventricular pacing, as the time interval from the minimum derivative within the QRS to the maximum derivative within the T-wave on unipolar electrograms. Regional ARI dispersion was defined as the standard deviation (SD) of ARI per AHA segment (ARISD). Lipomatous metaplasia exhibited higher ARI than scar [325 (interquartile range 270–392) vs. 313 (255–374), P < 0.001]. Corridors critical to VT re-entry were more likely to traverse through or near LM and displayed prolonged ARI compared with non-critical corridors [355 (319–397) vs. 302 (279–333) ms, P < 0.001]. ARISD was more closely associated with LM than with scar (likelihood ratio χ2 50 vs. 12, and 4.2-unit vs. 0.9-unit increase in 0.01*Log(ARISD) per 1 cm2 increase per AHA segment). Additionally, LM and scar exhibited interaction (P < 0.001) in their association with ARISD.ConclusionLipomatous metaplasia is closely associated with prolonged local action potential duration of corridors and ARI dispersion, which may facilitate the propensity of VT circuit re-entry.

Cardiometabolic diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1–3. Polygenic scores (PGS) aggregate these into a metric representing an individual’s genetic predisposition to disease. PGS have shown promise for early risk prediction4–7 and there is an open question as to whether PGS can also be used to understand disease biology8. Here, we demonstrate that cardiometabolic disease PGS can be used to elucidate the proteins underlying disease pathogenesis. In 3,087 healthy individuals, we found that PGS for coronary artery disease, type 2 diabetes, chronic kidney disease and ischaemic stroke are associated with the levels of 49 plasma proteins. Associations were polygenic in architecture, largely independent of cis and trans protein quantitative trait loci and present for proteins without quantitative trait loci. Over a follow-up of 7.7 years, 28 of these proteins associated with future myocardial infarction or type 2 diabetes events, 16 of which were mediators between polygenic risk and incident disease. Twelve of these were druggable targets with therapeutic potential. Our results demonstrate the potential for PGS to uncover causal disease biology and targets with therapeutic potential, including those that may be missed by approaches utilizing information at a single locus., Ritchie et al. use polygenic scores to identify plasma proteins with causal roles in cardiometabolic disease.

For Alzheimer’s disease–a leading cause of dementia and global morbidity–improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer’s disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer’s disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer’s disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer’s disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer’s disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution.

Lyme disease is a zoonotic illness caused by Borrelia burgdorferi, which present with skin, joint, heart, and central nervous system complications. Central nervous system manifestations of this disease are common, and typically include meningitis, facial nerve palsies, and radiculoneuritis. In this case report, we present a patient who presented with acute right sided hemiplegia and ataxia with negative neuroimaging findings of stroke, inflammation, or mass. Further investigation with cerebrospinal fluid studies and infectious panels revealed the patient had active Lyme disease. The patient improved his motor function, coordination and sensation with ceftriaxone treatment over a few weeks. Acute hemiplegia and ataxia are rare manifestations of Lyme Disease.

Aims Inadequate modification of the atrial fibrotic substrate necessary to sustain re-entrant drivers (RDs) may explain atrial fibrillation (AF) recurrence following failed pulmonary vein isolation (PVI). Personalized computational models of the fibrotic atrial substrate derived from late gadolinium enhanced (LGE)-magnetic resonance imaging (MRI) can be used to non-invasively determine the presence of RDs. The objective of this study is to assess the changes of the arrhythmogenic propensity of the fibrotic substrate after PVI. Methods and results Pre- and post-ablation individualized left atrial models were constructed from 12 AF patients who underwent pre- and post-PVI LGE-MRI, in six of whom PVI failed. Pre-ablation AF sustained by RDs was induced in 10 models. RDs in the post-ablation models were classified as either preserved or emergent. Pre-ablation models derived from patients for whom the procedure failed exhibited a higher number of RDs and larger areas defined as promoting RD formation when compared with atrial models from patients who had successful ablation, 2.6 ± 0.9 vs. 1.8 ± 0.2 and 18.9 ± 1.6% vs. 13.8 ± 1.5%, respectively. In cases of successful ablation, PVI eliminated completely the RDs sustaining AF. Preserved RDs unaffected by ablation were documented only in post-ablation models of patients who experienced recurrent AF (2/5 models); all of these models had also one or more emergent RDs at locations distinct from those of pre-ablation RDs. Emergent RDs occurred in regions that had the same characteristics of the fibrosis spatial distribution (entropy and density) as regions that harboured RDs in pre-ablation models. Conclusion Recurrent AF after PVI in the fibrotic atria may be attributable to both preserved RDs that sustain AF pre- and post-ablation, and the emergence of new RDs following ablation. The same levels of fibrosis entropy and density underlie the pro-RD propensity in both pre- and post-ablation substrates.

Objective: To inspect relationship among parental usage of specific serotonin reuptake inhibitors (SSRIs) during pregnancy and language ability at age three years, taking into account motherly indications of nervousness and sadness. Plan: Populace-founded study of partners in impending pregnancy. Setting: The Pakistani cohort study of mothers and children; pregnant women enrolled from 1999 to 2008; 45,268 women with 53,755 singleton pregnancies. Our current research was led at Sir Ganga Ram Hospital, Lahore from March 2018 to February 2019. Strategies: The relationship among short- or long-term usage of SSRIs through pregnancy and language ability in youth remained examined using a multinomial relapse computed through 3 result classifications: for some time, convoluted sentences, truly comprehensive sentences, also language delay. Result principle quantifies: The children's language ability at age three as estimated by the mother's report on an approved language punctuation gauge. Results: Females reported the usage of SSRIs in 388 (0.8%) pregnancies. Of those, 165 (43%) detailed longstanding usage. The balanced comparative danger ratio proportions of having truly comprehensive sentences were 1.22 (96% CI: 0.86-1.73) and 2.29 (1.57-3.39) for short- and long-term use of SSRIs, separately. The balanced RRRs for language interruption were 0.87 (0.43-0.78) and 2.31 (1.22-4.38). The side effects of tension and discouragement during pregnancy were independently identified with language delay, with balanced RRRs of 1.26 (1.04-1.51) and 1.83 (1.41-2.41) for short- and long-term manifestations, individually. Conclusion: Protracted usage of SSRIs throughout pregnancy has been related through lower language ability in 3-year-olds without melancholia. Having signs of melancholia finished pregnancy had an autonomous impact. Keywords: Children, melancholia, language ability, MoBa, pregnancy, introduction of SSRIs.

Objective: Attractive reverberation imaging allows non-invasive perception of PO2 changes between air and oxygen respiration by measuring the attractive longitudinal run time T1. The variations in PO2 correspond to changes in longitudinal flow rate DR1 (where DR1 = 1/T1Oxygen _ 1/T1air). Information on this response may suggest medical mediations by means of parental oxygen organization during the prenatal period to cure fetal developmental confinement. Researchers present in vivo estimates of fetal-placental unit reply to maternal hyperoxia. Test: Ten women with a generally safe pregnancy (22-34 weeks incubation) and six non-pregnant adults. Methods: Our current research was conducted at Mayo Hospital, Lahore from October 2017 to September 2018. Throughout imaging, mothers' air supply was different from restorative air (21% oxygen) to therapeutic oxygen (100% oxygen), and T1 was observed after some time in placenta and fetal brain using an imaging group with intermittently rephased attractive reverberation. To show that the strategy could identify a mental reply, the brain responses of five typical adult volunteers were estimated using the comparative imaging convention. The basic results amount changes in T1 subsequent an oxygenation test. Results: Not any critical DR1 (P = 0.43, paired t-trial) was detected in fetal minds. The critical placental DR1 (P = 0.0003, paired t-test) of 0.03 _ 0.02/s (average _ SD) was observed at all times in similar limbs. In the minds of non-pregnant adults, a huge DR1 (P = 0.02, combined t-test) of 0.006 _ 0.003/s was detected. Conclusion: The organization of short-term parental oxygen does not improve oxygenation of the fetal mind, unlike the reaction seen in adult brain. Keywords: Brain, fetus, longitudinal relaxation rate, magnetic character imaging, oxygen, placenta, pregnancy.

Objectives This study sought to assess the relationship between fibrosis and re-entrant activity in persistent atrial fibrillation (AF). Background The mechanisms involved in sustaining re-entrant activity during AF are poorly understood. Methods Forty-one patients with persistent AF (age 56 ± 12 years; 6 women) were evaluated. High-resolution electrocardiographic imaging (ECGI) was performed during AF by using a 252-chest electrode array, and phase mapping was applied to locate re-entrant activity. Sites of high re-entrant activity were defined as re-entrant regions. Late gadolinium-enhanced (LGE) cardiac magnetic resonance (CMR) was performed at 1.25 × 1.25 × 2.5 mm resolution to characterize atrial fibrosis and measure atrial volumes. The relationship between LGE burden and the number of re-entrant regions was analyzed. Local LGE density was computed and characterized at re-entrant sites. All patients underwent catheter ablation targeting re-entrant regions, the procedural endpoint being AF termination. Clinical, CMR, and ECGI predictors of acute procedural success were then analyzed. Results Left atrial (LA) LGE burden was 22.1 ± 5.9% of the wall, and LA volume was 74 ± 21 ml/m 2 . The number of re-entrant regions was 4.3 ± 1.7 per patient. LA LGE imaging was significantly associated with the number of re-entrant regions (R = 0.52, p = 0.001), LA volume (R = 0.62, p Conclusions The number of re-entrant regions during AF relates to the extent of LGE on CMR, with the location of these regions clustering to LGE areas. These characteristics affect procedural outcomes of ablation.

KEY POINTS Optogenetics has emerged as a potential alternative to electrotherapy for treating heart rhythm disorders, but its applicability for terminating atrial arrhythmias remains largely unexplored. We used computational models reconstructed from clinical MRI scans of fibrotic patient atria to explore the feasibility of optogenetic termination of atrial tachycardia (AT), comparing two different illumination strategies: distributed vs. targeted. We show that targeted optogenetic stimulation based on automated, non-invasive flow-network analysis of patient-specific re-entry morphology may be a reliable approach for identifying the optimal illumination target in each individual (i.e. the critical AT isthmus). The above-described approach yields very high success rates (up to 100%) and requires dramatically less input power than distributed illumination We conclude that simulations in patient-specific models show that targeted light pulses lasting longer than the AT cycle length can efficiently and reliably terminate AT if the human atria can be successfully light-sensitized via gene delivery of ChR2. ABSTRACT Optogenetics has emerged as a potential alternative to electrotherapy for treating arrhythmia, but feasibility studies have been limited to ventricular defibrillation via epicardial light application. Here, we assess the efficacy of optogenetic atrial tachycardia (AT) termination in human hearts using a strategy that targets for illumination specific regions identified in an automated manner. In three patient-specific models reconstructed from late gadolinium-enhanced MRI scans, we simulated channelrhodopsin-2 (ChR2) expression via gene delivery. In all three models, we attempted to terminate re-entrant AT (induced via rapid pacing) via optogenetic stimulation. We compared two strategies: (1) distributed illumination of the endocardium by multi-optrode grids (number of optrodes, Nopt = 64, 128, 256) and (2) targeted illumination of the critical isthmus, which was identified via analysis of simulated activation patterns using an algorithm based on flow networks. The illuminated area and input power were smaller for the targeted approach (19-57.8 mm2 ; 0.6-1.8 W) compared to the sparsest distributed arrays (Nopt = 64; 124.9 ± 6.3 mm2 ; 3.9 ± 0.2 W). AT termination rates for distributed illumination were low, ranging from

Polygenic risk scores (PRSs) capture the polygenic architecture of common diseases by aggregating genome-wide genetic variation into a single score that reflects individual9s disease risk, affording a new opportunity to identify downstream molecular pathways involved in disease pathogenesis. We performed an integrative analysis to characterise associations of PRSs of five cardiometabolic diseases with 3,442 plasma proteins in 3,175 healthy individuals. Through polygenic association scans we identified 48 plasma proteins whose levels were associated with PRSs for coronary artery disease (CAD), chronic kidney disease (CKD), or type 2 diabetes (T2D). This approach identified both well-known disease-associated proteins as well as those with previously no known link to these diseases. We found that PRSs to protein associations were largely truly polygenic; independent of single loci and genomic regions expected to have strong effects on protein levels. Our integrative analysis and laboratory experiments revealed a role for polygenic effects on several well-known disease proteins and identified several promising novel targets for follow-up studies, including genes which through Mendelian randomization analysis displayed causal evidence for effects on disease risk. Mouse studies highlighted specific tissues and phenotypes for PRS-associated human proteins. We found that implicated genes were responsive to dietary intervention in mice and showed strong evidence of druggability in humans, consistent with PRS-associated proteins having therapeutic potential. Overall, our study provides a framework for polygenic association studies, and demonstrates the power of polygenic scores to unravel novel disease biology.

Severe obesity is a rapidly growing global health threat. Although often attributed to unhealthy lifestyle choices or environmental factors, obesity is known to be heritable and highly polygenic; the majority of inherited susceptibility is related to the cumulative effect of many common DNA variants. Here we derive and validate a new polygenic predictor comprised of 2.1 million common variants to quantify this susceptibility and test this predictor in more than 300,000 individuals ranging from middle age to birth. Among middle-aged adults, we observe a 13-kg gradient in weight and a 25-fold gradient in risk of severe obesity across polygenic score deciles. In a longitudinal birth cohort, we note minimal differences in birthweight across score deciles, but a significant gradient emerged in early childhood and reached 12 kg by 18 years of age. This new approach to quantify inherited susceptibility to obesity affords new opportunities for clinical prevention and mechanistic assessment. © 2019 Author(s), National Human Genome Research Institute (1K08HG0101), Wellcome Trust (202802/Z/16/Z), University of Bristol NIHR Biomedical Research Centre (S- BRC-1215-20011), National Human Genome Research Institute (HG008895), National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300025C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300026C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300027C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300028C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300029C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268200900041C, National Institute on Aging (AG0005), NHLBI (AG0005), National Human Genome Research Institute (U01-HG004729), National Human Genome Research Institute (U01-HG04424), National Human Genome Research Institute (U01-HG004446), Wellcome (102215/2/13/2)

This study sought to evaluate the association between contrast-enhanced multidetector computed tomography (CE-MDCT) attenuation and local epicardial conduction speed (ECS) and electrographic abnormalities in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) and ventricular tachycardia (VT).CE-MDCT is a widely available and fast imaging technology with high spatial resolution that is less prone to defibrillator generator-related safety issues and image artifacts. However, the association between hypoattenuation on MDCT and VT substrates in ARVC remains unknown.Patients with ARVC who underwent CE-MDCT followed by endocardial (n = 30) and epicardial (n = 21) electroanatomical mapping (EAM) and VT ablation were prospectively enrolled. Right ventricular (RV) mid-myocardial attenuation was calculated from 3-dimensional MDCT images and registered to EAM. Local ECS was calculated by averaging the ECS between each point and 5 adjacent points with concordant wave front direction.A total of 17,311 epicardial and 5,204 endocardial points were included. In multivariable regression analysis clustered by patient, RV myocardial attenuation was associated with epicardial bipolar voltage amplitude (2.5% decrease in amplitude per 10 HU decrease in attenuation; p 0.001), with endocardial unipolar voltage amplitude (0.9% decrease in amplitude per 10 HU decrease in attenuation; p 0.001), and with ECS (0.4% decrease in ECS per 10 HU decrease in attenuation; p = 0.001).CE-MDCT attenuation distribution is associated with regional ECS and electrographic amplitude in ARVC. Regions with low attenuation likely reflect fibro-fatty involvement in the RV and may serve as important VT substrates in patients with ARVC who are undergoing VT ablation.

Aims The mechanisms underlying persistent atrial fibrillation (AF) in patients with atrial fibrosis are poorly understood. The goal of this study was to use patient-derived atrial models to test the hypothesis that AF re-entrant drivers (RDs) persist only in regions with specific fibrosis patterns. Methods and results Twenty patients with persistent AF (PsAF) underwent late gadolinium-enhanced MRI to detect the presence of atrial fibrosis. Segmented images were used to construct personalized 3D models of the fibrotic atria with biophysically realistic atrial electrophysiology. In each model, rapid pacing was applied to induce AF. AF dynamics were analysed and RDs were identified using phase mapping. Fibrosis patterns in RD regions were characterized by computing maps of fibrosis density (FD) and entropy (FE). AF was inducible in 13/20 models and perpetuated by few RDs (2.7 ± 1.5) that were spatially confined (trajectory of phase singularities: 7.6 ± 2.3 mm). Compared with the remaining atrial tissue, regions where RDs persisted had higher FE (IQR: 0.42–0.60 vs. 0.00–0.40, P < 0.05) and FD (IQR: 0.59–0.77 vs. 0.00–0.33, P < 0.05). Machine learning classified RD and non-RD regions based on FD and FE and identified a subset of fibrotic boundary zones present in 13.8 ± 4.9% of atrial tissue where 83.5 ± 2.4% of all RD phase singularities were located. Conclusion Patient-derived models demonstrate that AF in fibrotic substrates is perpetuated by RDs persisting in fibrosis boundary zones characterized by specific regional fibrosis metrics (high FE and FD). These results provide new insights into the mechanisms that sustain PsAF and could pave the way for personalized, MRI-based management of PsAF.

Atrial fibrillation (AF)-the most common arrhythmia-significantly increases the risk of stroke and heart failure. Although catheter ablation can restore normal heart rhythms, patients with persistent AF who develop atrial fibrosis often undergo multiple failed ablations, and thus increased procedural risks. Here, we present personalized computational modelling for the reliable predetermination of ablation targets, which are then used to guide the ablation procedure in patients with persistent AF and atrial fibrosis. First, we show that a computational model of the atria of patients identifies fibrotic tissue that, if ablated, will not sustain AF. Then, we report the results of integrating the target ablation sites in a clinical mapping system and testing its feasibility in ten patients with persistent AF. The computational prediction of ablation targets avoids lengthy electrical mapping and could improve the accuracy and efficacy of targeted AF ablation in patients while eliminating the need for repeat procedures.

Cardiac magnetic resonance imaging has been shown to be beneficial for identification of the ventricular tachycardia (VT) substrate before catheter ablation. Contrast-enhanced perfusion multidetector computed tomography (CEP-MDCT) is more generalizable to clinical practice, and wall thickness and regional hypoenhancement on CEP-MDCT can identify potential substrate sites, albeit with decreased specificity.The purpose of this study was to evaluate the association between wall thickness and attenuation on CEP-MDCT with local conduction velocity (CV) and electrogram abnormalities in patients with postinfarct VT.Fourteen patients with postinfarct VT underwent preprocedural CEP-MDCT followed by endocardial electroanatomic mapping (EAM) and ablation. Myocardial attenuation and wall thickness were calculated from 3-dimensional MDCT images using ADAS-VT software (Galgo Medical). EAM was registered with 3-dimensional MDCT images using the CartoMERGE module of CARTO3 software (Biosense Webster). Local CV was calculated by averaging the velocity between each point and 5 adjacent points with concordant wavefront direction.A total of 3689 points were included. In multivariable regression analysis clustered by patient, local CV was positively associated with myocardial attenuation, bipolar voltage, unipolar voltage, and wall thickness. Each 10-HU drop in full-thickness attenuation correlated to 2.6% decrease in CV (P.001) and 5.5% decrease in bipolar voltage amplitude (P.001), after adjusting for wall thickness.Myocardial attenuation distribution on CEP-MDCT is associated with regional CV and electrogram amplitude. Regions with low CV identified with low attenuation on CEP-MDCT may serve as important VT substrates in postinfarct patients.

Focal impulse and rotor mapping (FIRM) involves intracardiac detection and catheter ablation of re-entrant drivers (RDs), some of which may contribute to arrhythmia perpetuation in persistent atrial fibrillation (PsAF). Patient-specific computational models derived from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) has the potential to non-invasively identify all areas of the fibrotic substrate where RDs could potentially be sustained, including locations where RDs may not manifest during mapped AF episodes. The objective of this study was to carry out multi-modal assessment of the arrhythmogenic propensity of the fibrotic substrate in PsAF patients by comparing locations of RD-harboring regions found in simulations and detected by FIRM (RDsim and RDFIRM) and analyze implications for ablation strategies predicated on targeting RDs. For 11 PsAF patients who underwent pre-procedure LGE-MRI and FIRM-guided ablation, we retrospectively simulated AF in individualized atrial models, with geometry and fibrosis distribution reconstructed from pre-ablation LGE-MRI scans, and identified RDsim sites. Regions harboring RDsim and RDFIRM were compared. RDsim were found in 38 atrial regions (median [inter-quartile range (IQR)] = 4 [3; 4] per model). RDFIRM were identified and subsequently ablated in 24 atrial regions (2 [1; 3] per patient), which was significantly fewer than the number of RDsim-harboring regions in corresponding models (p < 0.05). Computational modeling predicted RDsim in 20 of 24 (83%) atrial regions identified as RDFIRM-harboring during clinical mapping. In a large number of cases, we uncovered RDsim-harboring regions in which RDFIRM were never observed (18/22 regions that differed between the two modalities; 82%); we termed such cases “latent” RDsim sites. During follow-up (230 [180; 326] days), AF recurrence occurred in 7/11 (64%) individuals. Interestingly, latent RDsim sites were observed in all seven computational models corresponding to patients who experienced recurrent AF (2 [2; 2] per patient); in contrast, latent RDsim sites were only discovered in two of four patients who were free from AF during follow-up (0.5 [0; 1.5] per patient; p < 0.05 vs. patients with AF recurrence). We conclude that substrate-based ablation based on computational modeling could improve outcomes.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e., spiral waves), which promote fibrillatory activity. Targeted catheter ablation of RD-harboring tissues has shown promise as a clinical treatment for PsAF, but the outcomes remain sub-par. Personalized computational modeling has been proposed as a means of non-invasively predicting optimal ablation targets in individual PsAF patients, but it remains unclear how RD localization dynamics are influenced by inter-patient variability in the spatial distribution of atrial fibrosis, action potential duration (APD), and conduction velocity (CV). Here, we conduct simulations in computational models of fibrotic atria derived from the clinical imaging of PsAF patients to characterize the sensitivity of RD locations to these three factors. We show that RDs consistently anchor to boundaries between fibrotic and non-fibrotic tissues, as delineated by late gadolinium-enhanced magnetic resonance imaging, but those changes in APD/CV can enhance or attenuate the likelihood that an RD will anchor to a specific site. These findings show that the level of uncertainty present in patient-specific atrial models reconstructed without any invasive measurements (i.e., incorporating each individual's unique distribution of fibrotic tissue from medical imaging alongside an average representation of AF-remodeled electrophysiology) is sufficiently high that a personalized ablation strategy based on targeting simulation-predicted RD trajectories alone may not produce the desired result.

Multiple types of natural collagens specifically assemble and co-exist in the extracellular matrix. Although noncollagenous trimerization domains facilitate the folding of triple-helical regions, it is intriguing to ask whether collagen sequences are also capable of controlling heterospecific association. In this study, we designed a model system mimicking simultaneous specific assembly of two collagen heterotrimers using a genetically inspired operation, circular permutation. Previously, surface charge-pair interactions were optimized on three collagen peptides to promote the formation of an abc-type heterotrimer. Circular permutation of these sequences retained networks of stabilizing interactions, preserving both triple-helical structure and heterospecificity of assembly. Combining original peptides A, B, and C and permuted peptides D, E, and F resulted primarily in formation of A:B:C and D:E:F, a heterospecificity of 2 of 56 possible stoichiometries. This degree of specificity in collagen molecular recognition is unprecedented in natural or synthetic collagens. Analysis of natural collagen sequences indicates low similarity between the neighboring exons. Combining the synthetic collagen model and bioinformatic analysis provides insight on how fibrillar collagens might have arisen from the duplication of smaller domains. Background: Multiple types of collagens specifically assemble and co-exist as a major component in extracellular matrix. Results: Orthogonal assembly of two collagen heterotrimers was induced by circularly permuting the sequences of a previously designed heterotrimer. Conclusion: High collagen assembly specificity can be achieved with a simple sequence rearrangement. Significance: This study provides insights on how fibrillar collagens might have arisen from gene duplication and domain shuffling.

Epicardial adipose tissue (EAdT) is metabolically active and likely contributes to atrial fibrillation (AF) through the release of inflammatory cytokines into the myocardium or through its rich innervation with ganglionated plexi at the pulmonary vein ostia. The electrophysiologic mechanisms underlying the association between EAdT and AF remain unclear.The purpose of this study was to investigate the association of EAdT with adjacent myocardial substrate.Thirty consecutive patients who underwent cardiac computed tomography as well as electroanatomic mapping in sinus rhythm before an initial AF ablation procedure were studied. Semiautomatic segmentation of atrial EAdT was performed and registered anatomically to the voltage map.In multivariable regression analysis clustered by patient, age (-0.01 per year) and EAdT (-0.29) were associated with log bipolar voltage as well as low-voltage zones (0.5 mV). Age (odds ratio [OR]: 1.02 per year), male gender (OR: 3.50), diabetes (OR: 2.91), hypertension (OR: 2.55), and EAdT (OR: 8.56) were associated with fractionated electrograms, and age (OR: 2.80), male gender (OR: 3.00), and EAdT (OR: 7.03) were associated with widened signals. Age (OR: 1.03 per year) and body mass index (OR: 1.06 per kg/mThe presence of overlaying EAdT was associated with lower bipolar voltage and electrogram fractionation as electrophysiologic substrates for AF. EAdT was not a statistical mediator of the association between clinical variables and AF substrate. Body mass index was directly associated with the presence of EAdT in patients with AF.

Atrial arrhythmias involving a fibrotic substrate are an important cause of morbidity and mortality. In many cases, effective treatment of such rhythm disorders is severely hindered by a lack of mechanistic understanding relating features of fibrotic remodelling to dynamics of re-entrant arrhythmia. With the advent of clinical imaging modalities capable of resolving the unique fibrosis spatial pattern present in the atria of each individual patient, a promising new research trajectory has emerged in which personalized computational models are used to analyse mechanistic underpinnings of arrhythmia dynamics based on the distribution of fibrotic tissue. In this review, we first present findings that have yielded a robust and detailed biophysical representation of fibrotic substrate electrophysiological properties. Then, we summarize the results of several recent investigations seeking to use organ-scale models of the fibrotic human atria to derive new insights on mechanisms of arrhythmia perpetuation and to develop novel strategies for model-assisted individualized planning of catheter ablation procedures for atrial arrhythmias.

Background— Prior studies have demonstrated regional left atrial late gadolinium enhancement (LGE) heterogeneity on magnetic resonance imaging. Heterogeneity in regional conduction velocities is a critical substrate for functional reentry. We sought to examine the association between left atrial conduction velocity and LGE in patients with atrial fibrillation. Methods and Results— LGE imaging and left atrial activation mapping were performed during sinus rhythm in 22 patients before pulmonary vein isolation. The locations of 1468 electroanatomic map points were registered to the corresponding anatomic sites on 469 axial LGE image planes. The local conduction velocity at each point was calculated using previously established methods. The myocardial wall thickness and image intensity ratio defined as left atrial myocardial LGE signal intensity divided by the mean left atrial blood pool intensity was calculated for each mapping site. The local conduction velocity and image intensity ratio in the left atrium (mean±SD) were 0.98±0.46 and 0.95±0.26 m/s, respectively. In multivariable regression analysis, clustered by patient, and adjusting for left atrial wall thickness, conduction velocity was associated with the local image intensity ratio (0.20 m/s decrease in conduction velocity per increase in unit image intensity ratio, P Conclusions— In this clinical in vivo study, we demonstrate that left atrial myocardium with increased gadolinium uptake has lower local conduction velocity. Identification of such regions may facilitate the targeting of the substrate for reentrant arrhythmias.

Cardiac optogenetics has been envisioned as a pain-free approach for terminating arrhythmia, but questions of clinical feasibility remain unexplored. It remains unknown how advantages of light-based stimulation, such as the ability to induce sustained depolarization in precisely defined tissue regions, might be beneficial in the context of anti-arrhythmic therapy. We used computer simulations to assess the feasibility of terminating reentrant atrial arrhythmias with localized optogenetic stimuli.We conducted simulations in atrial models constructed from MRI scans of three atrial arrhythmia patients. Light sensitization via viral gene delivery of the light-sensitive protein ChR2 was modeled by incorporating a realistic photocurrent model in 40% of atrial tissue (diffuse spatial pattern). In each model, arrhythmia was induced by rapid pacing and the reentrant circuit (RC) was identified using a previously validated approach; then, we simulated placement of blue LED strips along the endocardial surface spanning the narrowest part of each RC (average illuminated area: 38.03mm²). Light-based termination was attempted with four light pulse durations (1-1000ms); to characterize therapeutic reliability, pulse timing was varied in 20ms intervals that spanned the arrhythmia reentrant cycle.Targeted optogenetic stimulation terminated arrhythmia in all three models. The primary mechanism was induction of sustained transmural depolarization in the narrowest part of the RC, which led to conduction block and abrogation of reentry. For each pulse duration tested, at least one timing was successful; however, configurations with longer pulses were more resilient to differences in timing (1000ms pulse: 97.92% success rate; 100ms: 74.68%, 10ms: 55.81%, 1ms: 22.29%). Input energy for optogenetic stimuli was extremely low (average: 7.92mJ/ms) compared to typical defibrillation shocks (∼15J).Long-lasting (≥100ms) optogenetic stimulation via endocardial LED strips is a feasible approach to terminating atrial arrhythmia if the narrowest part of the RC can be targeted.

Background Left atrial flutter (LAFL) occurs in patients after atrial fibrillation ablation. Identification of optimal ablation targets to terminate LAFL remains challenging. Objective The purpose of this study was to use patient-specific models to simulate LAFL and predict optimal ablation targets using a novel approach based on flow network theory. Methods Late gadolinium-enhanced cardiac magnetic resonance scans from 10 patients with LAFL were used to construct atrial models incorporating fibrosis by investigators blinded to procedural findings. Rapid pacing was applied in silico to induce LAFL. In each LAFL, we represented reentrant wave propagation as an electric flow network and identified the "minimum cut" (MC), which was the smallest amount of tissue that separated the flow into 2 discontinuous components. In silico ablation was applied at MCs, and targets were compared to those that terminated LAFL during catheter ablation. Results Patient-specific atrial models were successfully generated from patient scans. LAFL was induced in 7 of 10 models. Ablation of MCs terminated LAFL in 4 models and produced new, slower LAFL morphologies in the other 3. For the latter cases, flow analysis was repeated to identify MCs of emergent LAFLs. Ablation of these MCs terminated emergent LAFLs. The MC-based ablation lesions in simulations were similar in length and location to ablation targets that terminated LAFL during catheter ablation for these 7 patients. Conclusion Personalized atrial simulations can predict ablation targets for LAFL. These simulations provide a powerful tool for planning ablation procedures and may reduce procedural times and complications.

Under diseased conditions, remodeling of the cardiac tissue properties (“passive properties”) takes place; these are aspects of electrophysiological behavior that are not associated with active ion transport across cell membranes. Remodeling of the passive electrophysiological properties most often results from structural remodeling, such as gap junction down-regulation and lateralization, fibrotic growth infiltrating the myocardium, or the development of an infarct scar. Such structural remodeling renders atrial or ventricular tissue as a major substrate for arrhythmias. The current review focuses on these aspects of cardiac arrhythmogenesis. Due to the inherent complexity of cardiac arrhythmias, computer simulations have provided means to elucidate interactions pertinent to this spatial scale. Here we review the current state-of-the-art in modeling atrial and ventricular arrhythmogenesis as arising from the disease-induced changes in the passive tissue properties, as well as the contributions these modeling studies have made to our understanding of the mechanisms of arrhythmias in the heart. Because of the rapid advance of structural imaging methodologies in cardiac electrophysiology, we chose to present studies that have used such imaging methodologies to construct geometrically realistic models of cardiac tissue, or the organ itself, where the regional remodeling properties of the myocardium can be represented in a realistic way. We emphasize how the acquired knowledge can be used to pave the way for clinical applications of cardiac organ modeling under the conditions of structural remodeling.

Net-negatively-charged heterospecific A:B:C collagen peptide heterotrimers were designed using an automated computational approach. The design algorithm considers both target stability and the energy gap between the target states and misfolded competing states. Structural characterization indicates the net-negative charge balance on the new designs enhances the specificity of the target state at the expense of its stability.

The caption descriptions for Figs ​Figs44 and ​and55 are switched. The authors have provided a corrected version here. Fig 4 Maps of APD distribution for atrial models Utah III (left) and Utah IV (right). Fig 5 Transmembrane potential maps at four time instants in substrates Utah III (top row) and Utah IV (bottom row) following pacing from a “prime” region outside the PVs (pacing sites marked by red arrows).

We have successfully designed an A:B:C collagen peptide heterotrimer using an automated computational approach. The algorithm maximizes the energy gap between the target and competing misfolded states while enforcing a minimum target stability. Circular dichroism (CD) measurements confirm that all three peptides are required to form a stable, structured triple helix. This study highlights the power of automated computational design, providing model systems to probe the biophysics of collagen assembly and developing general methods for the design of fibrous proteins.