Protective role of 11β-HSD1 inhibition in the metabolic syndrome and atherosclerosis

Obesity is associated with an increased risk of diabetes type 2, dyslipidaemia and atherosclerosis. These cardiovascular and metabolic abnormalities are exacerbated by dietary fats such as cholesterol and its metabolites. High adipose tissue glucocorticoid levels, generated by the intracellular enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) are also implicated in the pathogenesis of obesity, metabolic syndrome and atherosclerosis. Transgenic mice over-expressing 11β-HSD1 selectively in adipose tissue develop the metabolic syndrome whereas 11β-HSD1-/- mice have a ‘cardioprotective’ phenotype, deriving in part from improved adipose tissue function. Consistent with this, prototypical therapeutic 11β-HSD1 inhibitors ameliorate metabolic disturbances associated with obesity. 11β-HSD1 also inter-converts the atherogenic oxysterols 7-ketocholesterol (7KC) and 7β-hydroxycholesterol (7β-HC). Work presented in the first part of the thesis defines the impact of these alternative substrates on the metabolism of glucocorticoids in adipocyte cell lines (3T3-L1 and 3T3-F442A). 11β-HSD1 catalyses the reduction of 7KC in mature adipocytes leading to accumulation of 7β-HC. Oxysterol and glucocorticoid conversion by 11β-HSD1 was competitive and occurred within a physiologically-relevant IC50 range of 450nM for 7KC inhibition of glucocorticoid metabolism. Working as an inhibitor of 11β-HSD1 activity, 7KC decreased the regeneration of active glucocorticoid and limited the process of preadipocyte differentiation. 7-oxysterols did not display intrinsic activation of the glucocorticoid receptor (GR). However, when co-incubated with glucocorticoid, 7KC repressed, and 7β-HC enhanced GR transcriptional activity. The effect of 7-oxysterols resulted from the modulation of 11β-HSD1 reaction direction, at least in transfected HEK293 cells, and could be abrogated by over-expression of hexose 6-phosphate dehydrogenase, which supplies NADPH to drive the reductase activity of 11β-HSD1. 11β-HSD1 inhibition protects from atherosclerosis, yet it is unknown whether it is an effect of alterations in the metabolism of 7-oxysterols. 7KC and 7β-HC did not activate the potential cognate receptor LXRα and FXR/RXR in transactivation assays. No differential regulation of key gene targets of LXRα, FXR and RORα in the liver and fat depots of high fat fed 11β-HSD1-/- and wild type mice was observed. To further determine the molecular basis for the metabolically beneficial phenotype of 11β-HSD1-/- mice I analysed global gene expression in subcutaneous and mesenteric adipose tissues of high fat-fed (4 weeks) 11β-HSD1-/- and congenic C57BL/6J mice by microarrays, followed by pathway analysis, gene clustering and realtime-PCR validation of transcripts with >1.5-fold difference between genotypes. 11β-HSD1-/- mice gained less weight and distributed adipose tissue to subcutaneous rather than visceral depots. Broadly, high fat-fed 11β-HSD1-/- mice showed up-regulation of transcripts in subcutaneous fat (70% of 1622 differentially-expressed transcripts), but down-regulation in mesenteric adipose tissue (73% of 849 transcripts). Genes up-regulated in 11β-HSD1-/- subcutaneous adipose were associated with β-adrenergic signaling, glucose metabolism, lipid oxidation, oxidative phosphorylation, MAPK, Wnt/β-catenin, EGF, and PI3K/AKT insulin signaling pathways. Increased subcutaneous fat insulin signaling was confirmed by increased IRS-1 and Akt phosphorylation in vivo. Down-regulated genes in 11β-HSD1-/- mesenteric fat were associated with immune cells, NK-kappaB, Jak/Stat, SAPK/JNK, chemokine, toll-like-receptor and Wnt signaling pathways suggesting reduced immune cell infiltration in mesenteric adipose in high fat-fed 11β-HSD1-/- mice. 11β-HSD1 deficiency protects against metabolic disease by increasing peripheral fat insulin sensitivity and through a novel mechanism involving reduction in visceral fat immune/inflammatory cell function. Data presented in this thesis contribute to the understanding of the role of 11β-HSD1 in adipose tissues in obesity and, potentially, atherosclerosis

11beta-hydroxysteroid dehydrogenase type 1 inhibitor: a novel therapeutic target in the metabolic syndrome

Coraz częściej spotykany zespół metaboliczny, choć fenotypowo przypomina rzadkie schorzenie, zespół Cushinga, jednak występuje w nim prawidłowe stężenie kortyzolu we krwi. Dehydrogenaza 11betahydrosteroidowa (11beta-HSD1) miejscowo kontroluje dostępność aktywnej formy glukokortykoidu (kortyzol, kortykosteron) dla receptora glukokortykoidowego. W ostatnich badaniach wykazano, że otyłość u ludzi i gryzoni koreluje ze zwiększoną aktywnością 11beta-HSD1 selektywnie w tkance tłuszczowej. Amplifikacja glukokortykoidów zależna od 11beta-HSD1 w tkance tłuszczowej może tłumaczyć paradoks podobieństw między zespołem metabolicznym i zespołem Cushinga. Dowody na zmieniony wewnątrzkomórkowy metabolizm glukokortykoid ów w patogenezie otyłości podkreślają rolę selektywnej inhibicji 11beta-HSD1 jako nowego celu w badaniach nad lekami. Wiele firm farmaceutycznych koncentruje swoje badania nad poszukiwaniem inhibitora 11beta-HSD1. Trwają prace nad opracowaniem leku, który miałby zastosowanie w terapii takich schorzeń, jak: cukrzyca typu 2, dyslipidemia, otyłość trzewna, miażdżyca. W niniejszej pracy omówiono rolę, jaką odgrywa 11beta-HSD1 w zespole metabolicznym i przedstawiono znaczenie selektywnej inhibicji 11beta-HSD1.The common metabolic syndrome phenotypically resembles the rare disorder Cushing’s syndrome. However, plasma cortisol level is within normal range. 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) locally controls the availability of an active form of glucocorticoid (cortisol and corticosterone) for glucocorticoid receptor. Recent studies reported that obesity in humans and rodents correlates with enhanced activity of 11beta-HSD1 selectively in adipose tissue. 11beta-HSD1 - dependent glucocorticoid amplification in the fat tissue may explain the Cushing’s syndrome/metabolic syndrome paradox. The evidence of an altered intracellular glucocorticoid metabolism in the pathogenesis of the murine obesity with associated metabolic syndrome underpins the importance of selective 11beta-HSD1 inhibition as a novel target for drug development. Multiple pharmaceutical companies are searching intensively for the 11beta-HSD1 inhibitor with the intention to create drugs that treat disorders such as diabetes type 2, dyslipidemia, visceral obesity, atherosclerosis. Here we review the role of 11beta-HSD1 in the metabolic syndrome and discuss the impact of selective 11beta-HSD1 inhibition

11beta-hydroxysteroid dehydrogenase type 1 inhibitor : a novel therapeutic target in the metabolic syndrome

Coraz częściej spotykany zespół metaboliczny, choć fenotypowo przypomina rzadkie schorzenie, zespół Cushinga, jednak występuje w nim prawidłowe stężenie kortyzolu we krwi. Dehydrogenaza 11betahydrosteroidowa (11beta-HSD1) miejscowo kontroluje dostępność aktywnej formy glukokortykoidu (kortyzol, kortykosteron) dla receptora glukokortykoidowego. W ostatnich badaniach wykazano, że otyłość u ludzi i gryzoni koreluje ze zwiększoną aktywnością 11beta-HSD1 selektywnie w tkance tłuszczowej. Amplifikacja glukokortykoidów zależna od 11beta-HSD1 w tkance tłuszczowej może tłumaczyć paradoks podobieństw między zespołem metabolicznym i zespołem Cushinga. Dowody na zmieniony wewnątrzkomórkowy metabolizm glukokortykoidów w patogenezie otyłości podkreślają rolę selektywnej inhibicji 11beta-HSD1 jako nowego celu w badaniach nad lekami. Wiele firm farmaceutycznych koncentruje swoje badania nad poszukiwaniem inhibitora 11beta-HSD1. Trwają prace nad opracowaniem leku, który miałby zastosowanie w terapii takich schorzeń, jak: cukrzyca typu 2, dyslipidemia, otyłość trzewna, miażdżyca. W niniejszej pracy omówiono rolę, jaką odgrywa 11beta-HSD1 w zespole metabolicznym i przedstawiono znaczenie selektywnej inhibicji 11beta-HSD1.The common metabolic syndrome phenotypically resembles the rare disorder Cushing’s syndrome. However, plasma cortisol level is within normal range. 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) locally controls the availability of an active form of glucocorticoid (cortisol and corticosterone) for glucocorticoid receptor. Recent studies reported that obesity in humans and rodents correlates with enhanced activity of 11beta-HSD1 selectively in adipose tissue. 11beta-HSD1 - dependent glucocorticoid amplification in the fat tissue may explain the Cushing’s syndrome/metabolic syndrome paradox. The evidence of an altered intracellular glucocorticoid metabolism in the pathogenesis of the murine obesity with associated metabolic syndrome underpins the importance of selective 11beta- -HSD1 inhibition as a novel target for drug development. Multiple pharmaceutical companies are searching intensively for the 11beta-HSD1 inhibitor with the intention to create drugs that treat disorders such as diabetes type 2, dyslipidemia, visceral obesity, atherosclerosis. Here we review the role of 11beta-HSD1 in the metabolic syndrome and discuss the impact of selective 11beta-HSD1 inhibition

KUASA ALGORITMIK DALAM MASYARAKAT DIGITAL (INTERPRETASI PANDANGAN FOUCAULT ATAS TEKNOLOGI)

Nowadays, study about digital society had been excessively done. This study could not be released by quickly developing innovation of technology in many flanks human life. Innovations of technology showed optimism and pessimism in various realm. The development of speed spaces expressed phenomenon moreover argumentation which sanctioning human ability to manage the technology that they were created. Therefore, this study tries to become disentangled technology development by using Michael Foucault’s conceptual framework for explaining algorithmic power subjects and algorithmic governmentality in digital society. This study used qualitative descriptive approach with document research method along with content analysis method from primary resource and secondary resource till this study can be able to answer questions which was the basis why this study shall be doing. The results of this research shows there are power relations among actors like country and global capitalism within constructing freedom fantasies and democracy on digital society. For creating submissive society, every power actors used development of technology to predict and control critical awareness of society pass through algorithmic subjects and governmentality. As expressed by Michael Foucault, technology had been created for power to dominate digital society and created normality in human life. This study was offering practical steps to critical people to formulate algorithmic governmentality in a way to build their own technology to transform specific goals achievement like happiness, purity and wisdom as well as perfection and eternity

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis

Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to validate a novel machine learning method for the phenotyping of diabetes in the context of comorbidities. Data from 9967 multimorbid patients with a new diagnosis of diabetes were extracted from Clinical Practice Research Datalink. First, using BEHRT (a transformer-based deep learning architecture), the embeddings corresponding to diabetes were learned. Next, topological data analysis (TDA) was carried out to test how different areas in high-dimensional manifold correspond to different risk profiles. The following endpoints were considered when profiling risk trajectories: major adverse cardiovascular events (MACE), coronary artery disease (CAD), stroke (CVA), heart failure (HF), renal failure (RF), diabetic neuropathy, peripheral arterial disease, reduced visual acuity and all-cause mortality. Kaplan Meier curves were plotted for each derived phenotype. Finally, we tested the performance of an established risk prediction model (QRISK) by adding TDA-derived features. We identified four subgroups of patients with diabetes and divergent comorbidity patterns differing in their risk of future cardiovascular, renal, and other microvascular outcomes. Phenotype 1 (young with chronic inflammatory conditions) and phenotype 2 (young with CAD) included relatively younger patients with diabetes compared to phenotypes 3 (older with hypertension and renal disease) and 4 (older with previous CVA), and those subgroups had a higher frequency of pre-existing cardio-renal diseases. Within ten years of follow-up, 2592 patients (26%) experienced MACE, 2515 patients (25%) died, and 2020 patients (20%) suffered RF. QRISK3 model’s AUC was augmented from 67.26% (CI 67.25–67.28%) to 67.67% (CI 67.66–67.69%) by adding specific TDA-derived phenotype and the distances to both extremities of the TDA graph improving its performance in the prediction of CV outcomes. We confirmed the importance of accounting for multimorbidity when risk stratifying heterogenous cohort of patients with new diagnosis of diabetes. Our unsupervised machine learning method improved the prediction of clinical outcomes

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis

\ua9 2023, The Author(s). Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to validate a novel machine learning method for the phenotyping of diabetes in the context of comorbidities. Data from 9967 multimorbid patients with a new diagnosis of diabetes were extracted from Clinical Practice Research Datalink. First, using BEHRT (a transformer-based deep learning architecture), the embeddings corresponding to diabetes were learned. Next, topological data analysis (TDA) was carried out to test how different areas in high-dimensional manifold correspond to different risk profiles. The following endpoints were considered when profiling risk trajectories: major adverse cardiovascular events (MACE), coronary artery disease (CAD), stroke (CVA), heart failure (HF), renal failure (RF), diabetic neuropathy, peripheral arterial disease, reduced visual acuity and all-cause mortality. Kaplan Meier curves were plotted for each derived phenotype. Finally, we tested the performance of an established risk prediction model (QRISK) by adding TDA-derived features. We identified four subgroups of patients with diabetes and divergent comorbidity patterns differing in their risk of future cardiovascular, renal, and other microvascular outcomes. Phenotype 1 (young with chronic inflammatory conditions) and phenotype 2 (young with CAD) included relatively younger patients with diabetes compared to phenotypes 3 (older with hypertension and renal disease) and 4 (older with previous CVA), and those subgroups had a higher frequency of pre-existing cardio-renal diseases. Within ten years of follow-up, 2592 patients (26%) experienced MACE, 2515 patients (25%) died, and 2020 patients (20%) suffered RF. QRISK3 model’s AUC was augmented from 67.26% (CI 67.25–67.28%) to 67.67% (CI 67.66–67.69%) by adding specific TDA-derived phenotype and the distances to both extremities of the TDA graph improving its performance in the prediction of CV outcomes. We confirmed the importance of accounting for multimorbidity when risk stratifying heterogenous cohort of patients with new diagnosis of diabetes. Our unsupervised machine learning method improved the prediction of clinical outcomes

Multiorgan impairment in low-risk individuals with post-COVID-19 syndrome: a prospective, community-based study

OBJECTIVE: To assess medium-term organ impairment in symptomatic individuals following recovery from acute SARS-CoV-2 infection. DESIGN: Baseline findings from a prospective, observational cohort study. SETTING: Community-based individuals from two UK centres between 1 April and 14 September 2020. PARTICIPANTS: Individuals ≥18 years with persistent symptoms following recovery from acute SARS-CoV-2 infection and age-matched healthy controls. INTERVENTION: Assessment of symptoms by standardised questionnaires (EQ-5D-5L, Dyspnoea-12) and organ-specific metrics by biochemical assessment and quantitative MRI. MAIN OUTCOME MEASURES: Severe post-COVID-19 syndrome defined as ongoing respiratory symptoms and/or moderate functional impairment in activities of daily living; single-organ and multiorgan impairment (heart, lungs, kidneys, liver, pancreas, spleen) by consensus definitions at baseline investigation. RESULTS: 201 individuals (mean age 45, range 21-71 years, 71% female, 88% white, 32% healthcare workers) completed the baseline assessment (median of 141 days following SARS-CoV-2 infection, IQR 110-162). The study population was at low risk of COVID-19 mortality (obesity 20%, hypertension 7%, type 2 diabetes 2%, heart disease 5%), with only 19% hospitalised with COVID-19. 42% of individuals had 10 or more symptoms and 60% had severe post-COVID-19 syndrome. Fatigue (98%), muscle aches (87%), breathlessness (88%) and headaches (83%) were most frequently reported. Mild organ impairment was present in the heart (26%), lungs (11%), kidneys (4%), liver (28%), pancreas (40%) and spleen (4%), with single-organ and multiorgan impairment in 70% and 29%, respectively. Hospitalisation was associated with older age (p=0.001), non-white ethnicity (p=0.016), increased liver volume (p<0.0001), pancreatic inflammation (p<0.01), and fat accumulation in the liver (p<0.05) and pancreas (p<0.01). Severe post-COVID-19 syndrome was associated with radiological evidence of cardiac damage (myocarditis) (p<0.05). CONCLUSIONS: In individuals at low risk of COVID-19 mortality with ongoing symptoms, 70% have impairment in one or more organs 4 months after initial COVID-19 symptoms, with implications for healthcare and public health, which have assumed low risk in young people with no comorbidities. TRIAL REGISTRATION NUMBER: NCT04369807; Pre-results

Blood pressure lowering and risk of new-onset type 2 diabetes: an individual participant data meta-analysis

Background: Blood pressure lowering is an established strategy for preventing microvascular and macrovascular complications of diabetes, but its role in the prevention of diabetes itself is unclear. We aimed to examine this question using individual participant data from major randomised controlled trials. Methods: We performed a one-stage individual participant data meta-analysis, in which data were pooled to investigate the effect of blood pressure lowering per se on the risk of new-onset type 2 diabetes. An individual participant data network meta-analysis was used to investigate the differential effects of five major classes of antihypertensive drugs on the risk of new-onset type 2 diabetes. Overall, data from 22 studies conducted between 1973 and 2008, were obtained by the Blood Pressure Lowering Treatment Trialists’ Collaboration (Oxford University, Oxford, UK). We included all primary and secondary prevention trials that used a specific class or classes of antihypertensive drugs versus placebo or other classes of blood pressure lowering medications that had at least 1000 persons-years of follow-up in each randomly allocated arm. Participants with a known diagnosis of diabetes at baseline and trials conducted in patients with prevalent diabetes were excluded. For the one-stage individual participant data meta-analysis we used stratified Cox proportional hazards model and for the individual participant data network meta-analysis we used logistic regression models to calculate the relative risk (RR) for drug class comparisons. Findings: 145 939 participants (88 500 [60·6%] men and 57 429 [39·4%] women) from 19 randomised controlled trials were included in the one-stage individual participant data meta-analysis. 22 trials were included in the individual participant data network meta-analysis. After a median follow-up of 4·5 years (IQR 2·0), 9883 participants were diagnosed with new-onset type 2 diabetes. Systolic blood pressure reduction by 5 mm Hg reduced the risk of type 2 diabetes across all trials by 11% (hazard ratio 0·89 [95% CI 0·84–0·95]). Investigation of the effects of five major classes of antihypertensive drugs showed that in comparison to placebo, angiotensin-converting enzyme inhibitors (RR 0·84 [95% 0·76–0·93]) and angiotensin II receptor blockers (RR 0·84 [0·76–0·92]) reduced the risk of new-onset type 2 diabetes; however, the use of β blockers (RR 1·48 [1·27–1·72]) and thiazide diuretics (RR 1·20 [1·07–1·35]) increased this risk, and no material effect was found for calcium channel blockers (RR 1·02 [0·92–1·13]). Interpretation: Blood pressure lowering is an effective strategy for the prevention of new-onset type 2 diabetes. Established pharmacological interventions, however, have qualitatively and quantitively different effects on diabetes, likely due to their differing off-target effects, with angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers having the most favourable outcomes. This evidence supports the indication for selected classes of antihypertensive drugs for the prevention of diabetes, which could further refine the selection of drug choice according to an individual's clinical risk of diabetes. Funding: British Heart Foundation, National Institute for Health Research, and Oxford Martin School

Blood pressure lowering and risk of new-onset type 2 diabetes:an individual participant data meta-analysis

Background Blood pressure lowering is an established strategy for preventing microvascular and macrovascular complications of diabetes, but its role in the prevention of diabetes itself is unclear. We aimed to examine this question using individual participant data from major randomised controlled trials. Methods We performed a one-stage individual participant data meta-analysis, in which data were pooled to investigate the effect of blood pressure lowering per se on the risk of new-onset type 2 diabetes. An individual participant data network meta-analysis was used to investigate the differential effects of five major classes of antihypertensive drugs on the risk of new-onset type 2 diabetes. Overall, data from 22 studies conducted between 1973 and 2008, were obtained by the Blood Pressure Lowering Treatment Trialists' Collaboration (Oxford University, Oxford, UK). We included all primary and secondary prevention trials that used a specific class or classes of antihypertensive drugs versus placebo or other classes of blood pressure lowering medications that had at least 1000 persons-years of followup in each randomly allocated arm. Participants with a known diagnosis of diabetes at baseline and trials conducted in patients with prevalent diabetes were excluded. For the one-stage individual participant data meta-analysis we used stratified Cox proportional hazards model and for the individual participant data network meta-analysis we used logistic regression models to calculate the relative risk (RR) for drug class comparisons. Findings 145 939 participants (88 500 [60.6%] men and 57 429 [39.4%] women) from 19 randomised controlled trials were included in the one-stage individual participant data meta-analysis. 22 trials were included in the individual participant data network meta-analysis. After a median follow-up of 4.5 years (IQR 2.0), 9883 participants were diagnosed with new-onset type 2 diabetes. Systolic blood pressure reduction by 5 mm Hg reduced the risk of type 2 diabetes across all trials by 11% (hazard ratio 0.89 [95% CI 0.84-0.95]). Investigation of the effects of five major classes of antihypertensive drugs showed that in comparison to placebo, angiotensin-converting enzyme inhibitors (RR 0.84 [95% 0.76-0.93]) and angiotensin II receptor blockers (RR 0.84 [0.76-0.92]) reduced the risk of new-onset type 2 diabetes; however, the use of beta blockers (RR 1.48 [1.27-1.72]) and thiazide diuretics (RR 1.20 [1.07-1.35]) increased this risk, and no material effect was found for calcium channel blockers (RR 1.02 [0.92-1.13]). Interpretation Blood pressure lowering is an effective strategy for the prevention of new-onset type 2 diabetes. Established pharmacological interventions, however, have qualitatively and quantitively different effects on diabetes, likely due to their differing off-target effects, with angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers having the most favourable outcomes. This evidence supports the indication for selected classes of antihypertensive drugs for the prevention of diabetes, which could further refine the selection of drug choice according to an individual's clinical risk of diabetes

Cardiac abnormalities in Long COVID 1-year post-SARS-CoV-2 infection

BACKGROUND: Long COVID is associated with multiple symptoms and impairment in multiple organs. Cross-sectional studies have reported cardiac impairment to varying degrees by varying methodologies. Using cardiac MR (CMR), we investigated a 12-month trajectory of abnormalities in Long COVID. OBJECTIVES: To investigate cardiac abnormalities 1-year post-SARS-CoV-2 infection. METHODS: 534 individuals with Long COVID underwent CMR (T1/T2 mapping, cardiac mass, volumes, function and strain) and multiorgan MRI at 6 months (IQR 4.3-7.3) since first post-COVID-19 symptoms. 330 were rescanned at 12.6 (IQR 11.4-14.2) months if abnormal baseline findings were reported. Symptoms, questionnaires and blood samples were collected at both time points. CMR abnormalities were defined as ≥1 of low left or right ventricular ejection fraction (LVEF), high left or right ventricular end diastolic volume, low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in ≥3 cardiac segments. Significant change over time was reported by comparison with 92 healthy controls. RESULTS: Technical success of multiorgan and CMR assessment in non-acute settings was 99.1% and 99.6% at baseline, and 98.3% and 98.8% at follow-up. Of individuals with Long COVID, 102/534 (19%) had CMR abnormalities at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing CMR abnormalities at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms or clinical outcomes. At baseline, low LVEF was associated with persistent CMR abnormality, abnormal GLS associated with low quality of life and abnormal T1 in at least three segments was associated with better clinical outcomes at 12 months. CONCLUSION: CMR abnormalities (left entricular or right ventricular dysfunction/dilatation and/or abnormal T1mapping), occurred in one in five individuals with Long COVID at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers could not identify CMR abnormalities in Long COVID. TRIAL REGISTRATION NUMBER: NCT04369807