Citations

Abstract Inflammation is a key driver of coronary syndromes across the continuum from chronic coronary syndromes to acute coronary syndromes. It contributes to atherogenesis, plaque destabilization, and ischaemic events and influences myocardial injury, repair, and remodelling. Inflammatory activity is further amplified by metabolic and autoimmune comorbidities such as diabetes, obesity, and connective tissue diseases, with obesity representing a major driver of chronic low-grade inflammation through adipose tissue dysfunction and cytokine activation, while psychosocial stress and environmental exposures including air pollution serve as additional triggers. Genetic variations, including human leucocyte antigen genotypes, modulate individual susceptibility to vascular inflammation and myocardial injury. This expert consensus from the European Society of Cardiology’s Association for Acute CardioVascular Care summarizes the current understanding of inflammation across the full spectrum of coronary syndromes, including underlying mechanisms, relevant biomarkers, and imaging approaches that characterize vascular inflammation, and integrates insights from experimental and clinical studies. Importantly, this document provides explicit consensus-based guidance on when, how, and in whom inflammation should be assessed and treated in routine clinical practice. While the causal association between inflammation and atherosclerotic cardiovascular disease is well established, pharmacological modification of inflammation has produced conflicting evidence. Some agents, such as low-dose colchicine, have demonstrated modest reductions in cardiovascular events, although results across trials have been inconsistent. Other anti-inflammatory therapies have not shown clinical benefit, whereas selective cytokine inhibition with canakinumab has reduced cardiovascular risk at the cost of increased infection rates. The present manuscript also focuses on the evaluation of inflammatory activity in cardiovascular patients in routine clinical practice. It further discusses criteria for patient selection and clinical decision-making regarding the introduction of anti-inflammatory therapy in individuals with established atherosclerotic cardiovascular disease.

Abstract Metabolic disorders such as obesity, type 2 diabetes, and dyslipidaemia are major drivers of cardiovascular risk and have reached epidemic levels in Western populations. Recent advances in clinical research have uncovered unexpected and often beneficial effects of pharmacological classes of metabolic drugs on cardiovascular outcomes, revealing complex interactions between metabolism and cardiac pathology. Despite their clinical efficacy, the molecular and cellular mechanisms through which many of these agents act remain only partially understood. This gap in knowledge underscores the urgent need for fundamental research that not only dissects the biology of metabolic disorders and cardiovascular disease but also reveals the mechanistic basis of existing and emerging therapies, thereby enabling rational therapeutic development. This scientific statement, developed by researchers from the European Society of Cardiology (ESC) Council on Basic Cardiovascular Science and several ESC Working Groups, provides a state-of-the-art overview of the emerging molecular and cellular pathways linking metabolic abnormalities with vascular and cardiac disease. By illuminating these critical connections and unresolved questions, this article aims to catalyse innovation in the prevention and management of cardiovascular disease in the context of metabolic dysfunction and to suggest new directions for future research.

AbstractBackgroundGiven the rarity of genetic frontotemporal dementia (FTD), researchers across the world have come together to form the FTD Prevention Initiative (FPI) in an effort to improve prevention trials design. As this initiative begins to bring together large‐scale data from worldwide cohort series, including ALLFTD in North America and GENFI in Europe and Canada, it is critical for FPI to quantify the level of relatedness between all participants. Here we provide the most recent update to these ongoing analyses.MethodsGenome‐wide SNP genotyping data from 1,684 ALLFTD and 568 GENFI participants was used to perform lineage analyses using PLINK. Briefly, QC was performed similarly in all datasets to remove individuals with low call rate and filter autosomal SNPs for missingness, frequency, and deviation from Hardy‐Weinberg equilibrium. Genetic ancestry was inferred by projecting genotyped samples into the principal components of the 1000 Genomes reference panel, using R package bigsnpr. Overlapping ALLFTD and GENFI genotyping data was then used, in a two‐stage approach, to calculate pairwise identity‐by‐descent (IBD) estimates and KING coefficients, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsFirst, we calculated IBD estimates among all participants by restricting pairs to those with estimates>0.1875 (up to second‐degree relatives). Overall, we identified a total of 292 second‐degree family networks, including 168 ALLFTD and 120 GENFI families, mostly associated with pathogenic variants in the 3 major FTD‐causing genes. We also identified 4 family networks with participants enrolled in both the ALLFTD and GENFI series, as well as several multi‐site families within the ALLFTD consortium. This first, overall approach allowed us to predict close relationships even between individuals with different ancestral backgrounds, including at least 4 confirmed admixed families. More distant relationships were also detected within ALLFTD and GENFI by performing ancestry‐based analysis among participants with estimated European ancestry, using the KING‐robust algorithm.ConclusionsThese lineage analyses allowed us to identify, otherwise unknown, close (and distant) relatives from different study sites, as well as within the ALLFTD and GENFI series. This dataset will be a crucial resource to increase statistical accuracy and power in upcoming collaborative FPI studies.

AbstractBackgroundThe ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) research consortium is actively enrolling participants across 23 North American centers to characterize sporadic and familial frontotemporal dementia (FTD) and prepare for disease‐modifying clinical trials. The ability to identify, otherwise unknown, relatives among these participants is critical to rigorously build family structures for downstream clinical and genetic research studies.MethodsGenome‐wide SNP genotyping data from ALLFTD participants was used to perform lineage analyses using PLINK. Briefly, QC was performed to remove individuals with low call rate and filter autosomal SNPs for missingness, allele frequency, and deviation from Hardy‐Weinberg equilibrium, before pruning SNPs for linkage disequilibrium. Identity‐by‐descent (IBD) estimates were then calculated for determining relatedness, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsAbout 46% of ALLFTD participants that were genotyped and passed QC (n = 1,453) had reported a family history, while 50% (n = 721) did not and were considered sporadic. We identified a total of 460 participants that had at least one relative who was second degree or closer (PI_HAT>0.1875) based on IBD sharing, resulting in 150 family networks. This included 9 participants who self‐identified as sporadic, demonstrating the utility of direct genetic characterization to determine familiality in FTD. Most of the predicted families were associated with disease causing variants in the 3 major FTD‐causing genes: 66 families with known C9orf72 repeat expansion carriers, 35 with MAPT (including 11 families with the variant historically known as p.P301L) and 30 with GRN pathogenic variant carriers, as well as 2 families with carriers of both a C9orf72 expansion and a GRN pathogenic variant. We also identified 5 families with carriers of pathogenic variants in other familial dementia genes (2 TARDBP, 2 VCP and 1 PSEN1), as well as 12 families with yet unknown genetic etiology.ConclusionsThis dataset sets up a crucial resource to increase statistical accuracy and power in downstream association studies using the clinical, neuropsychological, neuroimaging and biomarker data currently being generated by the ALLFTD consortium. It will also facilitate genetic studies aimed at novel gene discovery, and identification of haplotypes and genetic modifiers associated with the 3 major FTD causal genes.

Abstract The formation of a thrombus in an epicardial artery may result in an acute myocardial infarction (AMI). Despite major advances in acute treatment using network approaches to allocate patients to timely reperfusion and optimal antithrombotic treatment, patients remain at high risk for thrombotic complications. Ongoing activation of the coagulation system as well as thrombin-mediated platelet activation may both play a crucial role in this context. Whether measurement of circulating biomarkers of coagulation and fibrinolysis could be useful for risk stratification in secondary prevention is currently not fully understood. In addition, measurement of such biomarkers could be helpful to identify thrombus formation as the leading mechanism for AMI. The introduction of biomarkers of myocardial injury such as high-sensitivity cardiac troponins made rule-out of AMI even more precise. However, elevated markers of myocardial injury cannot provide proof of a type 1 AMI, let alone thrombus formation. The combined measurement of markers of myocardial injury with biomarkers reflecting ongoing thrombus formation might be helpful for the fast and correct diagnosis of an atherothrombotic type 1 AMI. This position paper gives an overview of the current knowledge and possible role of biomarkers of coagulation and fibrinolysis for the diagnosis of AMI, risk stratification, and individualized treatment strategies in patients with AMI.

AbstractIntroductionThe Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) consortia are two closely connected studies, involving multiple North American centers that evaluate both sporadic and familial frontotemporal dementia (FTD) participants and study longitudinal changes.MethodsWe screened the major dementia‐associated genes in 302 sporadic and 390 familial (symptomatic or at‐risk) participants enrolled in these studies.ResultsAmong the sporadic patients, 16 (5.3%) carried chromosome 9 open reading frame 72 (C9orf72), microtubule‐associated protein tau (MAPT), and progranulin (GRN) pathogenic variants, whereas in the familial series we identified 207 carriers from 146 families. Of interest, one patient was found to carry a homozygous C9orf72 expansion, while another carried both a C9orf72 expansion and a GRN pathogenic variant. We also identified likely pathogenic variants in the TAR DNA binding protein (TARDBP), presenilin 1 (PSEN1), and valosin containing protein (VCP) genes, and a subset of variants of unknown significance in other rare FTD genes.DiscussionOur study reports the genetic characterization of a large FTD series and supports an unbiased sequencing screen, irrespective of clinical presentation or family history.

Background: The efficacy of remote ischaemic conditioning in clinical trials of ST-segment elevation myocardial infarction (STEMI) or elective percutaneous coronary intervention is controversial. We aimed to systematically review and meta-analyse whether remote ischaemic conditioning reduces myocardial damage in those patients. Methods: We searched PubMed, Embase and Web of Science from inception until December 2017 for randomised clinical trials evaluating remote ischaemic conditioning versus a control group. Two independent reviewers extracted data of 23 trials (2118 patients with STEMI; 2048 patients undergoing elective percutaneous coronary intervention) which were meta-analysed using random-effects models. Results: Remote ischaemic conditioning reduced infarct size in STEMI patients when assessed by imaging (mean difference of infarct size as percentage of left ventricle −2.43, 95% confidence interval (CI) –4.37 to −0.48; P=0.01; I2=44%; n=925) or biomarkers related to myocardial injury (peak values of cardiac biomarker release reported as standardised mean difference −0.19, 95% CI −0.37 to −0.02; P=0.03; I2=58%; n=1483) and increased myocardial salvage index (mean difference 0.07, 95% CI 0.01 to 0.13; P=0.02; I2=49%; n= 636). Left ventricular ejection fraction was increased when assessed during the first days after STEMI (mean difference 1.53, 95% CI 0.23 to 2.83; P=0.02; I2=28%; n=1192). Remote ischaemic conditioning had no influence on biomarker values after elective percutaneous coronary intervention (standardised mean difference 0.06, 95% CI −0.17 to 0.30; P=0.59). Conclusions: Despite a statistically significant reduction of myocardial damage in STEMI patients, the magnitude of the reduction was small and a significant impact on clinical events is unlikely. With respect to elective percutaneous coronary intervention, remote ischaemic conditioning had no influence on myocardial injury and its use is not supported by our analysis.