Author Correction: Activated ß-catenin in Foxp3+ regulatory T cells links inflammatory environments to autoimmunity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Activated ß-catenin in Foxp3+ regulatory T cells links inflammatory environments to autoimmunity.

Foxp3+ regulatory T cells (Treg cells) are the central component of peripheral immune tolerance. Whereas a dysregulated Treg cytokine signature has been observed in autoimmune diseases, the regulatory mechanisms underlying pro- and anti-inflammatory cytokine production are elusive. Here, we identify an imbalance between the cytokines IFN-γ and IL-10 as a shared Treg signature present in patients with multiple sclerosis and under high-salt conditions. RNA-sequencing analysis on human Treg subpopulations revealed ß-catenin as a key regulator of IFN-γ and IL-10 expression. The activated ß-catenin signature was enriched in human IFN-γ+ Treg cells, as confirmed in vivo with Treg-specific ß-catenin-stabilized mice exhibiting lethal autoimmunity with a dysfunctional Treg phenotype. Moreover, we identified prostaglandin E receptor 2 (PTGER2) as a regulator of IFN-γ and IL-10 production under a high-salt environment, with skewed activation of the ß-catenin-SGK1-Foxo axis. Our findings reveal a novel PTGER2-ß-catenin loop in Treg cells linking environmental high-salt conditions to autoimmunity.

Complement C1q activates canonical Wnt signaling and promotes aging-related phenotypes.

Wnt signaling plays critical roles in development of various organs and pathogenesis of many diseases, and augmented Wnt signaling has recently been implicated in mammalian aging and aging-related phenotypes. We here report that complement C1q activates canonical Wnt signaling and promotes aging-associated decline in tissue regeneration. Serum C1q concentration is increased with aging, and Wnt signaling activity is augmented during aging in the serum and in multiple tissues of wild-type mice, but not in those of C1qa-deficient mice. C1q activates canonical Wnt signaling by binding to Frizzled receptors and subsequently inducing C1s-dependent cleavage of the ectodomain of Wnt coreceptor low-density lipoprotein receptor-related protein 6. Skeletal muscle regeneration in young mice is inhibited by exogenous C1q treatment, whereas aging-associated impairment of muscle regeneration is restored by C1s inhibition or C1qa gene disruption. Our findings therefore suggest the unexpected role of complement C1q in Wnt signal transduction and modulation of mammalian aging.

Shared and Reciprocal Mechanisms Between Heart Failure and Cancer　- An Emerging Concept of Heart-Cancer Axis.

Epidemiological evidence of increased risks of cancer in heart failure (HF) patients and HF in cancer patients has suggested close relationships between the pathogenesis of both diseases. Indeed, HF and cancer share common risk factors, including aging and unhealthy lifestyles, and underlying mechanisms, including activation of the sympathetic nervous system and renin-angiotensin-aldosterone system, chronic inflammation, and clonal hematopoiesis of indeterminate potential. Mechanistically, HF accelerates cancer development and progression via secreted factors, so-called cardiokines, and epigenetic remodeling of bone marrow cells into an immunosuppressive phenotype. Reciprocally, cancer promotes HF via cachexia-related wasting and metabolic remodeling in the heart, and possibly via cancer-derived extracellular vesicles influencing myocardial structure and function. The novel concept of the "heart-cancer axis" will help in our understanding of the shared and reciprocal relationships between HF and cancer, and provide innovative diagnostic and therapeutic approaches for both diseases.

Deep Learning Models for Predicting Left Heart Abnormalities From Single-Lead Electrocardiogram for the Development of Wearable Devices.

BACKGROUND: Left heart abnormalities are risk factors for heart failure. However, echocardiography is not always available. Electrocardiograms (ECGs), which are now available from wearable devices, have the potential to detect these abnormalities. Nevertheless, whether a model can detect left heart abnormalities from single Lead I ECG data remains unclear.Methods and Results: We developed Lead I ECG models to detect low ejection fraction (EF), wall motion abnormality, left ventricular hypertrophy (LVH), left ventricular dilatation, and left atrial dilatation. We used a dataset comprising 229,439 paired sets of ECG and echocardiography data from 8 facilities, and validated the model using external verification with data from 2 facilities. The area under the receiver operating characteristic curves of our model was 0.913 for low EF, 0.832 for wall motion abnormality, 0.797 for LVH, 0.838 for left ventricular dilatation, and 0.802 for left atrial dilatation. In interpretation tests with 12 cardiologists, the accuracy of the model was 78.3% for low EF and 68.3% for LVH. Compared with cardiologists who read the 12-lead ECGs, the model's performance was superior for LVH and similar for low EF. CONCLUSIONS: From a multicenter study dataset, we developed models to predict left heart abnormalities using Lead I on the ECG. The Lead I ECG models show superior or equivalent performance to cardiologists using 12-lead ECGs.

Oxidized LDL but not angiotensin II induces cardiomyocyte hypertrophic responses through the interaction between LOX-1 and AT1 receptors.

It is well known that lectin-like oxidized low-density lipoprotein (ox-LDL) and its receptor LOX-1, angiotensin II (AngII) and its type 1 receptor (AT1-R) play an important role in the development of cardiac hypertrophy. However, the molecular mechanism is not clear. In this study, we found that ox-LDL-induced cardiac hypertrophy was suppressed by inhibition of LOX-1 or AT1-R but not by AngII inhibition. These results suggest that the receptors LOX-1 and AT1-R, rather than AngII, play a key role in the role of ox-LDL. The same results were obtained in mice lacking endogenous AngII and their isolated cardiomyocytes. Ox-LDL but not AngII could induce the binding of LOX-1 and AT1-R; inhibition of LOX-1 or AT1-R but not AngII could abolish the binding of these two receptors. Overexpression of wild type LOX-1 with AT1-R enhanced ox-LDL-induced binding of two receptors and phosphorylation of ERKs, however, transfection of LOX-1 dominant negative mutant (lys266ala / lys267ala) or an AT1-R mutant (glu257ala) not only reduced the binding of two receptors but also inhibited the ERKs phosphorylation. Phosphorylation of ERKs induced by ox-LDL in LOX-1 and AT1-R-overexpression cells was abrogated by an inhibitor of Gq protein rather than Jak2, Rac1 or RhoA. Genetically, an AT1-R mutant lacking Gq protein coupling ability inhibited ox-LDL induced ERKs phosphorylation. Furthermore, through bimolecular fluorescence complementation analysis, we confirmed that ox-LDL rather than AngII stimulation induced the direct binding of LOX-1 and AT1-R. We conclude that direct binding of LOX-1 and AT1-R and the activation of downstream Gq protein are important mechanisms of ox-LDL-induced cardiomyocyte hypertrophy.

Nonsyndromic arteriopathy and aortopathy and vascular Ehlers-Danlos syndrome causing COL3A1 variants.

Vascular Ehlers-Danlos syndrome (vEDS) is an autosomal dominant genetic disorder characterized by soft connective tissue vulnerability due to dysfunction of Type III collagen and caused by the pathogenic variants in COL3A1 gene. In the era of next-generation sequencing, multiple genes including COL3A1 can be simultaneously analyzed, and among patients suffering from aortopathy even without any other clinical features suggestive of vEDS, pathogenic COL3A1 variants have been increasingly identified. Here, we briefly summarize the characteristics of 12 Japanese patients from 11 families with arteriopathy and pathogenic or likely pathogenic COL3A1 variants in our hospital. Five patients did not have any extra-arterial clinical features, however, the multigene panel testing for hereditary thoracic aortic aneurysm and dissection unexpectedly revealed that two had glycine substitutions in the triple-helical region and three had haploinsufficient type variants in the COL3A1 gene, whose pathogenicities were all classified as pathogenic or likely pathogenic. Further genetic screening and identification of pathogenic variants in patients with nonsyndromic arteriopathy and aortopathy will enable us to develop risk-stratification and management based on the genetic diagnosis.

Automatic Detection of Left Ventricular Dilatation and Hypertrophy from Electrocardiograms Using Deep Learning.

Left ventricular dilatation (LVD) and left ventricular hypertrophy (LVH) are risk factors for heart failure, and their detection improves heart failure screening. This study aimed to investigate the ability of deep learning to detect LVD and LVH from a 12-lead electrocardiogram (ECG). Using ECG and echocardiographic data, we developed deep learning and machine learning models to detect LVD and LVH. We also examined conventional ECG criteria for the diagnosis of LVH. We calculated the area under the receiver operating characteristic (AUROC) curve, sensitivity, specificity, and accuracy of each model and compared the performance of the models. We analyzed data for 18,954 patients (mean age (standard deviation): 64.2 (16.5) years, men: 56.7%). For the detection of LVD, the value (95% confidence interval) of the AUROC was 0.810 (0.801-0.819) for the deep learning model, and this was significantly higher than that of the logistic regression and random forest methods (P < 0.001). The AUROCs for the logistic regression and random forest methods (machine learning models) were 0.770 (0.761-0.779) and 0.757 (0.747-0.767), respectively. For the detection of LVH, the AUROC was 0.784 (0.777-0.791) for the deep learning model, and this was significantly higher than that of the logistic regression and random forest methods and conventional ECG criteria (P < 0.001). The AUROCs for the logistic regression and random forest methods were 0.758 (0.751-0.765) and 0.716 (0.708-0.724), respectively. This study suggests that deep learning is a useful method to detect LVD and LVH from 12-lead ECGs.

Deep Learning Algorithm to Detect Cardiac Sarcoidosis From Echocardiographic Movies.

BACKGROUND: Because the early diagnosis of subclinical cardiac sarcoidosis (CS) remains difficult, we developed a deep learning algorithm to distinguish CS patients from healthy subjects using echocardiographic movies.Methods and Results:Among the patients who underwent echocardiography from January 2015 to December 2019, we chose 151 echocardiographic movies from 50 CS patients and 151 from 149 healthy subjects. We trained two 3D convolutional neural networks (3D-CNN) to identify CS patients using a dataset of 212 echocardiographic movies with and without a transfer learning method (Pretrained algorithm and Non-pretrained algorithm). On an independent set of 41 echocardiographic movies, the area under the receiver-operating characteristic curve (AUC) of the Pretrained algorithm was greater than that of Non-pretrained algorithm (0.842, 95% confidence interval (CI): 0.722-0.962 vs. 0.724, 95% CI: 0.566-0.882, P=0.253). The AUC from the interpretation of the same set of 41 echocardiographic movies by 5 cardiologists was not significantly different from that of the Pretrained algorithm (0.855, 95% CI: 0.735-0.975 vs. 0.842, 95% CI: 0.722-0.962, P=0.885). A sensitivity map demonstrated that the Pretrained algorithm focused on the area of the mitral valve. CONCLUSIONS: A 3D-CNN with a transfer learning method may be a promising tool for detecting CS using an echocardiographic movie.

Detection of Profound Myocardial Damage by Cardiac MRI in a Patient with Severe Cardiotoxicity Induced by Anti-HER2 Therapy.

Anti-HER2 therapy has greatly improved the long-term prognosis of patients with HER2-positive breast cancer. Meanwhile, by interfering with the protective effects of neuregulin-1/HER2 signaling on stressed cardiomyocytes, anti-HER2 therapy occasionally induces reversible cancer therapeutics-related cardiac dysfunction (CTRCD). Cardiac magnetic resonance (CMR) parametric mapping or myocardial feature-tracking, in combination with late gadolinium enhancement (LGE) imaging, has the potential to detect changes in the myocardium in anti-HER2 therapy-related cardiac dysfunction. Here we report a breast cancer patient who experienced life-threatening CTRCD after treatment with trastuzumab plus pertuzumab. This case showed multiple transmural LGE-positive myocardial lesions in CMR imaging and high native T1 and T2 values in CMR parametric mapping, which was apparently more extensive than those observed in most patients with anti-HER2 therapy-related cardiac dysfunction. Consistent with profound myocardial damage indicated by CMR, her cardiac function was not fully restored despite intensive care and cardioprotective drug therapy. These findings suggest the potential usefulness of LGE imaging and parametric mapping by CMR for the assessment of myocardial injury to determine the clinical severity of anti-HER2 therapy-related cardiac dysfunction.

The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms.

Deep learning models can be applied to electrocardiograms (ECGs) to detect left ventricular (LV) dysfunction. We hypothesized that applying a deep learning model may improve the diagnostic accuracy of cardiologists in predicting LV dysfunction from ECGs. We acquired 37,103 paired ECG and echocardiography data records of patients who underwent echocardiography between January 2015 and December 2019. We trained a convolutional neural network to identify the data records of patients with LV dysfunction (ejection fraction < 40%) using a dataset of 23,801 ECGs. When tested on an independent set of 7,196 ECGs, we found the area under the receiver operating characteristic curve was 0.945 (95% confidence interval: 0.936-0.954). When 7 cardiologists interpreted 50 randomly selected ECGs from the test dataset of 7,196 ECGs, their accuracy for predicting LV dysfunction was 78.0% ± 6.0%. By referring to the model's output, the cardiologist accuracy improved to 88.0% ± 3.7%, which indicates that model support significantly improved the cardiologist diagnostic accuracy (P = 0.02). A sensitivity map demonstrated that the model focused on the QRS complex when detecting LV dysfunction on ECGs. We developed a deep learning model that can detect LV dysfunction on ECGs with high accuracy. Furthermore, we demonstrated that support from a deep learning model can help cardiologists to identify LV dysfunction on ECGs.

[Dawning of Onco-Cardiology].

Recent progress in cancer therapy has decreased all-cancer mortality, but cardiovascular adverse events owing to chemotherapy and radiotherapy have greater impact on clinical outcome and quality of life in cancer patients and survivors. There are a wide variety of cardiovascular adverse events related to cancer therapy, and the opportunities requiring specialized care by cardiovascular experts are increasing in clinical practice. Under such circumstances, onco-cardiology is becoming very important as a new discipline and attracting much attention in Japan. The Japanese Onco-Cardiology Society was established in 2017, and continues integration of academic activities to solve challenging problems in this field. Interdisciplinary collaborations between cardiologists and oncologists will be further progressed in medical care, clinical and basic research, and education.

Cancer Therapeutics-Related Cardiac Dysfunction　- Insights From Bench and Bedside of Onco-Cardiology.

Improvements in the long-term survival of cancer patients have led to growing awareness of the clinical importance of cancer therapeutics-related cardiac dysfunction (CTRCD), which can have a considerable effect on the prognosis and quality of life of cancer patients and survivors. Under such circumstances, onco-cardiology/cardio-oncology has emerged as a new discipline, with the aim of best managing cardiovascular complications, including CTRCD. Despite the recent accumulation of epidemiological and clinical information regarding CTRCD, the molecular mechanisms underlying the pathogenesis of CTRCD by individual drugs remain to be determined. To achieve the goal of preventing cardiovascular complications in cancer patients and survivors, it is important to elucidate the pathogenic mechanisms and to establish diagnostic strategies with risk prediction and mechanism- and evidence-based therapies against CTRCD.

Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning.

The development of deep learning technology has enabled machines to achieve high-level accuracy in interpreting medical images. While many previous studies have examined the detection of pulmonary nodules in chest X-rays using deep learning, the application of this technology to heart failure remains rare. In this paper, we investigated the performance of a deep learning algorithm in terms of diagnosing heart failure using images obtained from chest X-rays. We used 952 chest X-ray images from a labeled database published by the National Institutes of Health. Two cardiologists verified and relabeled a total of 260 "normal" and 378 "heart failure" images, with the remainder being discarded because they had been incorrectly labeled. Data augmentation and transfer learning were used to obtain an accuracy of 82% in diagnosing heart failure using the chest X-ray images. Furthermore, heatmap imaging allowed us to visualize decisions made by the machine. Deep learning can thus help support the diagnosis of heart failure using chest X-ray images.

Erratum: Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning.

An error appeared in the article entitled "Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning" by Takuya Matsumoto, Satoshi Kodera, Hiroki Shinohara, Hirotaka Ieki, Toshihiro Yamaguchi, Yasutomi Higashikuni, Arihiro Kiyosue, Kaoru Ito, Jiro Ando, Eiki Takimoto, Hiroshi Akazawa, Hiroyuki Morita, Issei Komuro (Vol. 61, No. 4, 781-786, 2020). The Figure 5on page 784 should be replaced by the following figure.

A Fatal Case of Myocarditis Following Myositis Induced by Pembrolizumab Treatment for Metastatic Upper Urinary Tract Urothelial Carcinoma.

We report a case of lethal myocarditis and myositis after pembrolizumab treatment for advanced upper urinary tract urothelial carcinoma. A 69-year-old man underwent pembrolizumab therapy as a second-line treatment. He had myalgia and a slightly elevated creatinine kinase (CK) on the day of the second administration of pembrolizumab. Five days later, the patient was admitted with severe fatigue and an abnormal gait. Physical examination revealed reduced muscle reflexes and proximal muscle weakness. An electrocardiogram (ECG) demonstrated a wide QRS complex ventricular rhythm. A marked elevation of cardiac enzymes, including CK, myoglobin, and cardiac troponin I, was detected. Myocardial biopsy revealed inflammatory cell infiltration and the partial impairment of myocardial tissue. The electromyogram was normal, but inflammation in myofibers was noted in a muscle biopsy. Myocarditis and myositis as immune-related adverse events (irAEs) were suspected, and the patient began intravenous steroid therapy and plasma exchange. However, the patient underwent cardiac arrest three days after admission and began extracorporeal membrane oxygenation and intra-aortic balloon pumping therapy. Despite steroid pulse therapy, the patient demonstrated no sign of improvement and subsequently died 17 days after admission. Immune-mediated myocarditis is a rare but fatal irAE of an immune checkpoint inhibitor (ICI). The present case suggests that myositis precedes myocarditis. Therefore, if myositis is suspected, subsequent myocarditis may need attention. In conclusion, we found that myositis and myocarditis developed in a patient with advanced urothelial carcinoma after pembrolizumab treatment. A routine follow-up of CK and cardiac troponin I, as well as an ECG, should be performed to identify any possible ICI-induced myocarditis and myositis quickly.

High-throughput single-molecule RNA imaging analysis reveals heterogeneous responses of cardiomyocytes to hemodynamic overload.

BACKGROUND: The heart responds to hemodynamic overload through cardiac hypertrophy and activation of the fetal gene program. However, these changes have not been thoroughly examined in individual cardiomyocytes, and the relation between cardiomyocyte size and fetal gene expression remains elusive. We established a method of high-throughput single-molecule RNA imaging analysis of in vivo cardiomyocytes and determined spatial and temporal changes during the development of heart failure. METHODS AND RESULTS: We applied three novel single-cell analysis methods, namely, single-cell quantitative PCR (sc-qPCR), single-cell RNA sequencing (scRNA-seq), and single-molecule fluorescence in situ hybridization (smFISH). Isolated cardiomyocytes and cross sections from pressure overloaded murine hearts after transverse aortic constriction (TAC) were analyzed at an early hypertrophy stage (2 weeks, TAC2W) and at a late heart failure stage (8 weeks, TAC8W). Expression of myosin heavy chain ß (Myh7), a representative fetal gene, was induced in some cardiomyocytes in TAC2W hearts and in more cardiomyocytes in TAC8W hearts. Expression levels of Myh7 varied considerably among cardiomyocytes. Myh7-expressing cardiomyocytes were significantly more abundant in the middle layer, compared with the inner or outer layers of TAC2W hearts, while such spatial differences were not observed in TAC8W hearts. Expression levels of Myh7 were inversely correlated with cardiomyocyte size and expression levels of mitochondria-related genes. CONCLUSIONS: We developed a new image-analysis pipeline to allow automated and unbiased quantification of gene expression at the single-cell level and determined the spatial and temporal regulation of heterogenous Myh7 expression in cardiomyocytes after pressure overload.

Overview of the 83rd Annual Scientific Meeting of the Japanese Circulation Society　- Renaissance of Cardiology for the Creation of Future Medicine.

The 83rdAnnual Scientific Meeting of the Japanese Circulation Society was held in Yokohama, Japan, on March 29-31, 2019, just as the cherry blossoms came into full bloom. Because the environment around cardiovascular healthcare is rapidly changing, it becomes highly important to make a breakthrough at the dawn of a new era. The main theme of this meeting was "Renaissance of Cardiology for the Creation of Future Medicine". The meeting benefited from the participation of 18,825 people, and there were in-depth and extensive discussions at every session, focusing on topics covering clinical and basic research, medical care provision system, human resource development, and public awareness in cardiovascular medicine. The meeting was completed with great success, and we greatly appreciate the tremendous cooperation and support from all affiliates.

Pressure Overload Impairs Cardiac Function in Long-Chain Fatty Acid Transporter CD36-Knockout Mice.

CD36 is one of the important transporters of long-chain fatty acids (LCFAs) in the myocardium. We previously reported that CD36-deficient patients demonstrate a marked reduction of myocardial uptake of LCFA, while myocardial glucose uptake shows a compensatory increase, and are often accompanied by cardiomyopathy. However, the molecular mechanisms and functional role of CD36 in the myocardium remain unknown.The current study aimed to explore the pathophysiological role of CD36 in the heart. Methods: Using wild type (WT) and knockout (KO) mice, we generated pressure overload by transverse aortic constriction (TAC) and analyzed cardiac functions by echocardiography. To assess cardiac hypertrophy and fibrosis, histological and molecular analyses and measurement of ATP concentration in mouse hearts were performed.By applying TAC, the survival rate was significantly lower in KO than that in WT mice. After TAC, KO mice showed significantly higher heart weight-to-tibial length ratio and larger cross-sectional area of cardiomyocytes than those of WT. Although left ventricular (LV) wall thickness in the KO mice was similar to that in the WT mice, the KO mice showed a significant enlargement of LV cavity and reduced LV fractional shortening compared to the WT mice with TAC. A tendency for decreased myocardial ATP concentration was observed in the KO mice compared to the WT mice after TAC operation.These data suggest that the LCFA transporter CD36 is required for the maintenance of energy provision, systolic function, and myocardial structure.

[Onco-cardiology in the field of hematology].

Recent progress in cancer therapy has improved the long-term outcomes of cancer patients, and it has increased the importance of managing cardiovascular complications associated with cancer and cancer therapies. In the field of hematology, there is a serious concern about cardiovascular complications associated with a variety of chemotherapeutic drugs, such as anthracyclines, BCR-ABL tyrosine kinase inhibitors, and proteasome inhibitors. Despite the recent accumulation of epidemiological and clinical data and the fact that these are molecularly targeted drugs, molecular mechanisms underlying the pathogenesis of cardiovascular toxicities associated with individual drugs remain to be precisely defined. Recently emerging "onco-cardiology" will extend the interdisciplinary collaboration between oncology, hematology, and cardiology specialists in clinical practice, research, and education in order to protect cancer patients and survivors from cardiovascular complications.