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Start Over Search Limiters Full Text Topic heart failure Publication Year Range Last 3 years
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1. Metabolomics and a Breath Sensor Identify Acetone as a Biomarker for Heart Failure.

Author

Gladding PA, Cooper M, Young R, Loader S, Smith K, Zarate E, Green S, Villas Boas SG, Shepherd P, Kakadiya P, Thorstensen E, Keven C, Coe M, Jüllig M, Zhang E, and Schlegel TT

Subjects
Humans, Acetone, Stroke Volume, Biomarkers metabolism, Metabolomics, Heart Failure
Abstract

Background: Multi-omics delivers more biological insight than targeted investigations. We applied multi-omics to patients with heart failure with reduced ejection fraction (HFrEF)., Methods: 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography mass spectrometry (LC-MS/GC-MS) and solid-phase microextraction (SPME) volatilomics in plasma and urine. HFrEF was defined using left ventricular global longitudinal strain, ejection fraction and NTproBNP. A consumer breath acetone (BrACE) sensor validated results in n = 73., Results: 28 metabolites were identified by GCMS, 35 by LCMS and 4 volatiles by SPME in plasma and urine. Alanine, aspartate and glutamate, citric acid cycle, arginine biosynthesis, glyoxylate and dicarboxylate metabolism were altered in HFrEF. Plasma acetone correlated with NT-proBNP (r = 0.59, 95% CI 0.4 to 0.7), 2-oxovaleric and cis-aconitic acid, involved with ketone metabolism and mitochondrial energetics. BrACE > 1.5 ppm discriminated HF from other cardiac pathology (AUC 0.8, 95% CI 0.61 to 0.92, p < 0.0001)., Conclusion: Breath acetone discriminated HFrEF from other cardiac pathology using a consumer sensor, but was not cardiac specific.

Published
2022
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2. Multiomics, virtual reality and artificial intelligence in heart failure.

Author

Gladding PA, Loader S, Smith K, Zarate E, Green S, Villas-Boas S, Shepherd P, Kakadiya P, Hewitt W, Thorstensen E, Keven C, Coe M, Nakisa B, Vuong T, Rastgoo MN, Jüllig M, Starc V, and Schlegel TT

Subjects
Artificial Intelligence, Humans, Prognosis, Stroke Volume, Ventricular Function, Left, Heart Failure diagnostic imaging, Ventricular Dysfunction, Left diagnostic imaging, Virtual Reality
Abstract

Aim: Multiomics delivers more biological insight than targeted investigations. We applied multiomics to patients with heart failure (HF) and reduced ejection fraction (HFrEF), with machine learning applied to advanced ECG (AECG) and echocardiography artificial intelligence (Echo AI). Patients & methods: In total, 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography-mass spectrometry and solid-phase microextraction volatilomics in plasma and urine. HFrEF was defined using left ventricular (LV) global longitudinal strain, EF and N-terminal pro hormone BNP. AECG and Echo AI were performed over 5 min, with a subset of patients undergoing a virtual reality mental stress test. Results: A-ECG had similar diagnostic accuracy as N-terminal pro hormone BNP for HFrEF (area under the curve = 0.95, 95% CI: 0.85-0.99), and correlated with global longitudinal strain (r = -0.77, p < 0.0001), while Echo AI-generated measurements correlated well with manually measured LV end diastolic volume r = 0.77, LV end systolic volume r = 0.8, LVEF r = 0.71, indexed left atrium volume r = 0.71 and indexed LV mass r = 0.6, p < 0.005. AI-LVEF and other HFrEF biomarkers had a similar discrimination for HFrEF (area under the curve AI-LVEF = 0.88; 95% CI: -0.03 to 0.15; p = 0.19). Virtual reality mental stress test elicited arrhythmic biomarkers on AECG and indicated blunted autonomic responsiveness (alpha 2 of RR interval variability, p = 1 × 10 -4 ) in HFrEF. Conclusion: Multiomics-related machine learning shows promise for the assessment of HF.

Published
2021
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3. Cardiac Outcomes in Adults With Mitochondrial Diseases

Author

Konstantinos Savvatis, Christoffer Rasmus Vissing, Lori Klouvi, Anca Florian, Mehjabin Rahman, Anthony Béhin, Abdallah Fayssoil, Marion Masingue, Tanya Stojkovic, Henri Marc Bécane, Nawal Berber, Fanny Mochel, Denis Duboc, Bertrand Fontaine, Bjørg Krett, Caroline Stalens, Julie Lejeune, Robert D.S. Pitceathly, Luis Lopes, Malika Saadi, Thomas Gossios, Vincent Procaccio, Marco Spinazzi, Céline Tard, Pascal De Groote, Claire-Marie Dhaenens, Claire Douillard, Andoni Echaniz-Laguna, Ros Quinlivan, Michael G. Hanna, Ali Yilmaz, John Vissing, Pascal Laforêt, Perry Elliott, Karim Wahbi, Queen Mary University of London (QMUL), IT University of Copenhagen (ITU), Association française contre les myopathies (AFM-Téléthon), University Hospital Münster - Universitaetsklinikum Muenster [Germany] (UKM), University College of London [London] (UCL), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Hôpital Raymond Poincaré [Garches], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université de Versailles Saint-Quentin-en-Yvelines - UFR Sciences de la santé Simone Veil (UVSQ Santé), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université Paris Cité (UPCité), Sorbonne Université (SU), Hôpital Cochin [AP-HP], Aristotle University of Thessaloniki, MitoVasc - Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC), Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Département de Biochimie et Génétique [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), Lille Neurosciences & Cognition - U 1172 (LilNCog), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP), Hôpital Claude Huriez [Lille], CHU Lille, AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Handicap neuromusculaire : Physiopathologie, Biothérapie et Pharmacologies appliquées (END-ICAP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM), MR/S005021/1, Association Française contre les Myopathies, AFM, Medical Research Council, MRC: MR/S002065/1, Department of Health and Social Care, DH, University College London Hospitals NHS Foundation Trust, UCLH, NIHR Cambridge Biomedical Research Centre, This study was funded by grants from the Association Française contre les Myopathies (French Alliance against Myopathies), which was not involved in the design and conduct of the study, the collection, management, analysis, and interpretation of the data, the preparation, review or approval of the manuscript, and nor in the decision to submit the manuscript for publication. Dr Pitceathly is supported by a Medical Research Council (United Kingdom) Clinician Scientist Fellowship (MR/S002065/1). Drs Pitceathly and Hanna receive funding from a Medical Research Council (United Kingdom) strategic award to establish an International Centre for Genomic Medicine in Neuromuscular Diseases (ICGNMD) (MR/S005021/1). Dr Lopes is supported by a Medical Research Council (United Kingdom) clinical academic partnership (CARP) award. Dr Quinlivan was funded by National Institute for Health and Care Research Biomedical Research Centre, University College Hospitals Foundation Trust. The University College London Hospitals/University College London Queen Square Institute of Neurology sequencing facility receives a proportion of funding from the Department of Health's National Institute for Health and Care Research Biomedical Research Centre’s funding scheme. The clinical and diagnostic 'Rare Mitochondrial Disorders' Service in London is funded by the U.K. NHS Highly Specialised Commissioners. Dr Elliott has received consultancy fees from Pfizer, Sanofi, Sarepta, DinaQor, Freeline, Novo Nordisk, and Bristol Myers Squibb. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Subjects
Adult, conduction disease, mitochondrial diseases, [SDV]Life Sciences [q-bio], heart failure, sudden death, Heart, Stroke Volume, Prognosis, DNA, Mitochondrial, Ventricular Function, Left, single large-scale deletions, Risk Factors, Humans, Hypertrophy, Left Ventricular, Cardiology and Cardiovascular Medicine, G%22">m3243A>G
Abstract

International audience; Background: Patients with mitochondrial diseases are at risk of heart failure (HF) and arrhythmic major adverse cardiac events (MACE). Objectives: We developed prediction models to estimate the risk of HF and arrhythmic MACE in this population. Methods: We determined the incidence and searched for predictors of HF and arrhythmic MACE using Cox regression in 600 adult patients from a multicenter registry with genetically confirmed mitochondrial diseases. Results: Over a median follow-up time of 6.67 years, 29 patients (4.9%) reached the HF endpoint, including 19 hospitalizations for nonterminal HF, 2 cardiac transplantations, and 8 deaths from HF. Thirty others (5.1%) reached the arrhythmic MACE, including 21 with third-degree or type II second-degree atrioventricular blocks, 4 with sinus node dysfunction, and 5 sudden cardiac deaths. Predictors of HF were the m.3243A>G variant (HR: 4.3; 95% CI: 1.8-10.1), conduction defects (HR: 3.0; 95% CI: 1.3-6.9), left ventricular (LV) hypertrophy (HR: 2.6; 95% CI: 1.1-5.8), LV ejection fraction

Published
2022