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      Circulating Th17 and Th22 Cells Are Associated With CMR Imaging Biosignatures of Diffuse Myocardial Interstitial Remodeling in Chronic Coronary Artery Disease


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          Meet the First Author, see p 592 Myocardial fibrosis is the common pathophysiologic denominator between myocardial remodeling and the failing heart. Experimental evidence points toward a prominent role of CD4+ T helper (Th) lymphocytes, particularly Th17 and Th22 cells, as key players in myocardial remodeling, hence their involvement in humans remains unclear. Quantitative tissue characterization by cardiac magnetic resonance imaging supports noninvasive detection of diffuse myocardial interstitial remodeling by measurement of rates of T1 relaxation. 1 We have previously shown that characterization of noninfarcted myocardium by T1 mapping is predictive of outcome in patients with coronary artery disease (CAD), over and above traditional imaging measures. 2 We hypothesized that expansion of specific T-cell subsets would be associated with myocardial T1 mapping measurements. Therefore, circulating T cells were measured in forty-six patients with chronic CAD, who were enrolled in the prospective T1 mapping outcome study (NCT03749343). Exclusion criteria were neoplastic/autoimmune/infectious disease, specific nonischemic cardiomyopathies, myocarditis, and immunosuppressive medication. Patients were categorized into 2 groups, based on sequence-specific ranges for native T1 of noninfarcted myocardium 2 : normal native T1, indicating no remodeling (n=24; median age: 64 [IQR, 52–68] years; LVEF (left ventricular function): 58 [54–62]%) and abnormal native T1 (n=22; 61 [52–69] years; LVEF: 55 [41–64]%) as indicative for diffuse interstitial remodeling and fibrosis. Twelve subjects of similar age (57 [52–66] years) and sex mix with no known cardiac disease and with normal cardiac magnetic resonance findings served as controls. Blood samples were analyzed for standard cardiac and inflammatory biomarkers. Th-cell subsets were analyzed using multiparameter flow cytometry, and the raw data were subjected to hierarchical cluster analysis as described previously. 3 Hierarchical cluster analysis detected a marked expansion of 2 specific Th-cell clusters, phenotypically corresponding to Th22 and Th17 (Figure 1B) in patients with diffuse remodeling. We further confirmed a significant increase in Th17 and Th22 cell counts in patients with abnormal T1 signatures (Figure 1C). Among patients with CAD, there were no significant relationships between Th-cell subsets and age, sex, CV risk factors, cardiac magnetic resonance cardiac structure or function or the presence of postinfarction scar by late gadolinium enhancement. The latter indicates that expansions of proinflammatory T lymphocytes were indicative for diffuse fibrosis but not for replacement fibrosis. Figure. Inflammatory T-cell signatures of cardiac fibrosis. A, Scatter plots of Th-cell clusters (as identified by hierarchical cluster analysis) and (B) Uniform Manifold Approximation and Projection dimensionality reduction plots showing expansion of Th17 (CD194+CD196+CCR10−CD183−, red cluster) and Th22 (CD194+CD196+CCR10+CD183−, green cluster) cells from representative patients with normal (Case 1) and raised (Case 2) native T1. C, Absolute Th-cell counts (Kruskal-Wallis H-test followed by Dunn test). CAD indicates coronary artery disease. High-sensitive troponin T (Controls versus CAD normal versus CAD abnormal T1: 4.5 [3–5.9] versus 5.9 [4.5–11] vs 12 [6.8–20] pg/mL; P=0.002) and high-sensitivity C-reactive protein (0.09 [0.05–0.21] versus 0.08 [0.05–0.18] versus 0.22 [0.09–0.50] mg/dL; P=0.018) were significantly higher in the group with diffuse remodeling, whereas N-terminal pro-brain natriuretic peptide (94 [39–122] versus 64 [32–179] versus 201 [79–566] pg/mL; P=0.052) was not significantly different. The groups were similar for total blood leukocyte (P=0.18), granulocyte (P=0.25), or monocyte (P=0.09) counts. In summary, our results indicate that Th17 and Th22 cells may relate to diffuse interstitial remodeling of noninfarcted myocardium in the context of CAD. Despite its novelty, this study is limited by the small sample size and therefore potentially biased by reverse causation and confounding. Future studies are needed to prove the prognostic value of Th17/Th22 polarization, as well as the therapeutic potential of anti-inflammatory treatments to prevent progression of diffuse myocardial remodeling. Sources of Funding This work was supported by the Adolf-Messer-Stiftung. K. Fišer is supported by Czech Health Research Council (NV18-08-00385). Disclosures None.

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          Native T1 and ECV of Noninfarcted Myocardium and Outcome in Patients With Coronary Artery Disease

          Coronary artery disease (CAD) remains the major cause of cardiac morbidity and mortality worldwide, despite the advances in treatment with coronary revascularization and modern antiremodeling therapy. Risk stratification in CAD patients is primarily based on left ventricular volumes, ejection fraction (LVEF), risk scores, and the presence and extent of late gadolinium enhancement (LGE). The prognostic role of T1 mapping in noninfarcted myocardium in CAD patients has not yet been determined.
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            Comparison of MOLLI, shMOLLLI, and SASHA in discrimination between health and disease and relationship with histologically derived collagen volume fraction

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              Detection and monitoring of normal and leukemic cell populations with hierarchical clustering of flow cytometry data.

              Flow cytometry is a valuable tool in research and diagnostics including minimal residual disease (MRD) monitoring of hematologic malignancies. However, its gradual advancement toward increasing numbers of fluorescent parameters leads to information rich datasets, which are challenging to analyze by standard gating and do not reflect the multidimensionality of the data. We have developed a novel method to analyze complex flow cytometry data, based on hierarchical clustering analysis (HCA) but with a new underlying algorithm, using Mahalanobis distance measure. HCA is scalable to analyze complex multiparameter datasets (here demonstrated on up to 12 color flow cytometry and on a 20-parameter synthetic dataset). We have validated this method by comparison with standard gating approaches when performed independently by expert cytometrists. Acute lymphoblastic leukemia blast populations were analyzed in diagnostic and follow-up datasets (n = 123) from three centers. HCA results correlated very well (Passing-Bablok correlation coefficient = 0.992, slope = 1, intercept = -0.01) with standard gating data obtained by the I-BFM FLOW-MRD study group. To further improve the performance in follow-up samples with low MRD levels and to automate MRD detection, we combined HCA with support vector machine (SVM) learning. HCA in combination with SVM provides a novel diagnostic tool that not only allows analysis of increasingly complex flow cytometry data but also is less observer-dependent compared with classical gating and has potential for automation. Copyright © 2011 International Society for Advancement of Cytometry.

                Author and article information

                Circ Res
                Circ. Res
                Circulation Research
                Lippincott Williams & Wilkins (Hagerstown, MD )
                24 June 2020
                14 August 2020
                : 127
                : 5
                : 699-701
                [1 ]From the Departments of Medicine and Cardiology (J.H., V.O.P., A.B., E.N., A.M.Z.), Goethe University, Frankfurt, Germany
                [2 ]Institute for Experimental and Translational Cardiovascular Imaging (J.H., V.O.P., M.L.C., E.N., S.D.), Goethe University, Frankfurt, Germany
                [3 ]Institute of Cardiovascular Regeneration, Center of Molecular Medicine (T.R., S.D.), Goethe University, Frankfurt, Germany
                [4 ]German Center for Cardiovascular Research DZHK, Berlin, Germany, partner site Rhine-Main (J.H., V.O.P., E.N., S.D., A.M.Z.)
                [5 ]Department of Pediatric Haematology and Oncology, CLIP—Childhood Leukemia Investigation Prague, Charles University, Czech Republic (K.F.).
                Author notes
                Correspondence to: Jedrzej Hoffmann, Department of Cardiology, Center of Internal Medicine, University Hospital Frankfurt, Germany. Email jedrzej.hoffmann@ 123456kgu.de
                © 2020 The Authors.

                Circulation Research is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial-NoDerivs License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited, the use is noncommercial, and no modifications or adaptations are made.

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