Kynurenine metabolism is altered in mdx mice: a potential muscle to brain connection

Regular exercise can direct muscle kynurenine (KYN) metabolism toward the neuroprotective branch of the kynurenine pathway thereby limiting the accumulation of neurotoxic metabolites in the brain and contributing to mental resilience. While the effect of regular exercise has been studied, the effect of muscle disease on KYN metabolism has not yet been investigated. Previous work has highlighted anxiety-like behaviors in approximately 25% of patients with DMD, possibly due to altered KYN metabolism. Here, we characterized KYN metabolism in mdx mouse models of Duchenne muscular dystrophy (DMD). Young (8-10 week old) DBA/2J (D2) mdx mice, but not age-matched C57BL/10 (C57) mdx mice, had lower levels of circulating KYNA and KYNA:KYN ratio compared with their respective wild-type (WT) controls. Moreover, only D2 mdx mice displayed signs of anxiety-like behaviour, spending more time in the corners of their cages during a novel object recognition test when compared with WT. Along with this, we found that muscles from D2 mdx mice had less peroxisome proliferator-activated receptor-gamma coactivator 1-alpha and kynurenine amino transferase-1 enzyme content as well as elevated expression of inflammatory cytokines compared with WT muscles. Thus, our pilot work shows that KYN metabolism is altered in D2 mdx mice, with a potential contribution from altered muscle health.

Comprehensive Multi-cohort Transcriptional Meta-analysis of Muscle Diseases Identifies a Signature of Disease Severity

Muscle diseases share common pathological features suggesting common underlying mechanisms. We hypothesized there is a common set of genes dysregulated across muscle diseases compared to healthy muscle and that these genes correlate with severity of muscle disease. We performed meta-analysis of transcriptional profiles of muscle biopsies from human muscle diseases and healthy controls. Studies obtained from public microarray repositories fulfilling quality criteria were divided into six categories: i) Immobility, ii) inflammatory myopathies, iii) ICU acquired weakness (ICUAW), iv) congenital muscle diseases, v) chronic systemic diseases, vi) motor neuron disease. Patient cohorts were separated in discovery and validation cohorts retaining roughly equal proportions of samples for the disease categories. To remove bias towards a specific muscle disease category we repeated the meta-analysis five times by removing data sets corresponding to one muscle disease class at a time in a “leave-one-disease-out” analysis. We used 636 muscle tissue samples from 30 independent cohorts to identify a 52 gene signature (36 up-regulated and 16 down-regulated genes). We validated the discriminatory power of this signature in 657 muscle biopsies from 12 additional patient cohorts encompassing five categories of muscle diseases with an area under the receiver operating characteristic curve of 0.91, 83% sensitivity, and 85.3% specificity. The expression score of the gene signature inversely correlated with quadriceps muscle mass (r =-0.50, p-value = 0.011) in ICUAW and shoulder abduction strength (r=-0.77, p-value = 0.014) in amyotrophic lateral sclerosis (ALS). The signature also positively correlated with histologic assessment of muscle atrophy in ALS (r=0.88, p-value=1.62x10−3) and fibrosis in muscular dystrophy (Jonckheere trend test p-value = 4.45 x 10−9). Our results identify a conserved transcriptional signature associated with clinical and histologic muscle disease severity. Several genes in this conserved signature have not been previously associated with muscle disease severity.

A szívtroponinok laboratóriumi mérési módszereinek fő analitikai jellemzői: történeti és modern nézőpont

Összefoglaló. A cardialis troponinok biomarkerként való alkalmazása az akut myocardialis infarctus diagnosztikájában nagy múltra tekint vissza, és ez idő alatt jelentősen megváltoztak a cardialis troponinok diagnosztikai jelentőségével kapcsolatos elképzelések. Ez pedig a szívtroponinok és mindenekelőtt az érzékenység mérésére szolgáló laboratóriumi módszerek fejlődésének köszönhető. A legelső laboratóriumi módszerek, amelyeket több mint 30 évvel ezelőtt fejlesztettek ki a cardialis troponinok vérszérumban való kimutatására, még rendkívül alacsony érzékenységűek voltak, ezért csak 12–24 órával az akut myocardialis infarctus jelentkezése után tudták kimutatni a diagnózis felállításában jelentőséggel bíró troponinszintet. Ezenkívül a szívtroponin molekuláinak diagnosztikai reagensei nem specifikus módon kölcsönhatásba léphetnek a vázizombeli troponin molekuláival, ami a vázizmok betegségei és sérülései esetén a cardialis troponin koncentrációjának gyakori hamis pozitív növekedéséhez vezetett. Ahogy a cardialis troponinok mérési módszerei javultak, érzékenységük növekedésével (nagy érzékenységű cardialis troponinok) új lehetőségek nyíltak meg az akut myocardialis infarctus korai diagnózisának felállítására, és többek között modern diagnosztikai algoritmusokat is kifejlesztettek: 0–1 órás, 0–2 órás, 0–3 órás. Ez a korai diagnózis felállítását engedte meg azoknál a betegeknél, akiknek mellkasi fájdalmaik voltak, s ezzel korábban dönthettek a páciens gyógyításának optimális taktikájáról. Miután bevezetésre kerültek a cardialis troponin szintjének nagy érzékenységű mérési módszerei, a cardialis troponin molekuláinak biológiájával kapcsolatos elképzeléseink némileg megváltoztak, különösképpen, hogy innentől kezdve már nem tekinthetők szigorúan intracelluláris molekuláknak, mivel minden egészséges emberben kimutathatók, valamint nemi, életkori és cirkadián tulajdonságokat is felfedeztek a cardialis troponin koncentrációiban, amelyek ugyancsak szerepet játszhatnak az akut myocardialis infarctus diagnózisának felállításában. Arról nem is beszélve, hogy a nagy érzékenységű cardialis troponinok alkalmazási lehetőségei messze túlmutatnak az akut myocardialis infarctus diagnózisán. A jelen cikk egy történeti és egy modern perspektívát kíván bemutatni a cardialis troponinok legfontosabb analitikai jellemzőiről, érintve az azok biológiájára vonatkozó új adatokat és felhasználásuk új diagnosztikai lehetőségeit is. Orv Hetil. 2022; 163(1): 12–20. Summary. Throughout a very long history of using cardiac troponins in clinical practice as biomarkers of acute myocardial infarction, there have been significant changes in ideas about their diagnostic value. Such a circumstance is caused by the improvement of laboratory methods of cardiac troponin determination and, first of all, sensitivity. Thus, the very first laboratory methods designed to detect cardiac troponins in serum, developed over 30 years ago, had extremely low sensitivity, due to which they could detect diagnostically significant levels of troponins only 12–24 hours after the development of acute myocardial infarction. In addition, diagnostic antibodies directed against cardiac troponin molecules could interact nonspecifically with skeletal troponin molecules, leading to frequent false-positive increases in cardiac troponin concentrations in skeletal muscle disease and injury. As the methods of determining cardiac troponins improved, increasing their sensitivity (high-sensitivity cardiac troponins), the prospects for early diagnosis of acute myocardial infarction opened up, in particular, modern diagnostic algorithms: 0–1 hour, 0–2 hours, 0–3 hours. This allowed earlier diagnosis of patients who came with chest pain, and earlier decision-making on the choice of optimal tactics for the treatment of patients. With the introduction of high-sensitivity cardiac troponin assays, our understanding of the biology of cardiac troponin molecules has changed somewhat, in particular, they are no longer considered strictly intracellular molecules, as they are now detectable in all healthy individuals, and gender, age and circadian patterns in cardiac troponin concentrations have been discovered, which may have an impact on the diagnosis of acute myocardial infarction. Moreover, the possibilities of using highly sensitive cardiac troponins go far beyond the diagnosis of acute myocardial infarction. This article presents a view of the main analytical characteristics from a historical and contemporary perspective, covering some new data on the biology of cardiac troponins and new diagnostic possibilities for their use. Orv Hetil. 2022; 163(1): 12–20.

The Role of AI in Characterizing the DCM Phenotype

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.

Ribosomal protein S6 kinase beta-1 gene variants cause hypertrophic cardiomyopathy

BackgroundHypertrophic cardiomyopathy (HCM) is a genetic heart muscle disease with preserved or increased ejection fraction in the absence of secondary causes. Mutations in the sarcomeric protein-encoding genes predominantly cause HCM. However, relatively little is known about the genetic impact of signalling proteins on HCM.Methods and resultsHere, using exome and targeted sequencing methods, we analysed two independent cohorts comprising 401 Indian patients with HCM and 3521 Indian controls. We identified novel variants in ribosomal protein S6 kinase beta-1 (RPS6KB1 or S6K1) gene in two unrelated Indian families as a potential candidate gene for HCM. The two unrelated HCM families had the same heterozygous missense S6K1 variant (p.G47W). In a replication association study, we identified two S6K1 heterozygotes variants (p.Q49K and p.Y62H) in the UK Biobank cardiomyopathy cohort (n=190) compared with matched controls (n=16 479). These variants are neither detected in region-specific controls nor in the human population genome data. Additionally, we observed an S6K1 variant (p.P445S) in an Arab patient with HCM. Functional consequences were evaluated using representative S6K1 mutated proteins compared with wild type in cellular models. The mutated proteins activated the S6K1 and hyperphosphorylated the rpS6 and ERK1/2 signalling cascades, suggesting a gain-of-function effect.ConclusionsOur study demonstrates for the first time that the variants in the S6K1 gene are associated with HCM, and early detection of the S6K1 variant carriers can help to identify family members at risk and subsequent preventive measures. Further screening in patients with HCM with different ethnic populations will establish the specificity and frequency of S6K1 gene variants.

Histopathological Features and Protein Markers of Arrhythmogenic Cardiomyopathy

Arrhythmogenic cardiomyopathy (ACM) is a heritable heart muscle disease characterized by syncope, palpitations, ventricular arrhythmias and sudden cardiac death (SCD) especially in young individuals. It is estimated to affect 1:5,000 individuals in the general population, with >60% of patients bearing one or more mutations in genes coding for desmosomal proteins. Desmosomes are intercellular adhesion junctions, which in cardiac myocytes reside within the intercalated disks (IDs), the areas of mechanical and electrical cell-cell coupling. Histologically, ACM is characterized by fibrofatty replacement of cardiac myocytes predominantly in the right ventricular free wall though left ventricular and biventricular forms have also been described. The disease is characterized by age-related progression, vast phenotypic manifestation and incomplete penetrance, making proband diagnosis and risk stratification of family members particularly challenging. Key protein redistribution at the IDs may represent a specific diagnostic marker but its applicability is still limited by the need for a myocardial sample. Specific markers of ACM in surrogate tissues, such as the blood and the buccal epithelium, may represent a non-invasive, safe and inexpensive alternative for diagnosis and cascade screening. In this review, we shall cover the most relevant biomarkers so far reported and discuss their potential impact on the diagnosis, prognosis and management of ACM.

359 Transient vs. persistent improved ejection fraction in non-ischaemic dilated cardiomyopathy

Aims The recent definition of heart failure with improved ejection fraction (HFimpEF) outlined the importance of the longitudinal assessment of left ventricular ejection fraction (LVEF). However, long-term progression and outcomes of this subgroup are poorly explored. We sought to assess the LVEF trajectories and the correlations with outcome in non-ischaemic dilated cardiomyopathy (NICM) with improved ejection fraction (impEF). Methods and results Consecutive NICM patients with baseline LVEF ≤40% enrolled in the Trieste Heart Muscle Disease Registry with ≥1 LVEF assessment after baseline were included. ImpEF was defined as a baseline LVEF ≤40%, a ≥ 10 point increase from baseline LVEF, and a second measurement of LVEF >40%. Transient impEF was defined by the documentation of recurrent LVEF ≤40% during follow-up. The primary endpoint was a composite of all-cause death, heart transplantation and left ventricular assist device (D/HT/LVAD). Among 800 patients, 460 (57%) had impEF (median time to improvement 13 months). Higher heart rate, smaller left atrium, absence of severe mitral regurgitation and shorter duration of disease were associated with impEF. ImpEF was independently associated with lower risk of D/HT/LVAD (HR: 0.36; 95% CI: 0.27–0.48; P < 0.001). Transient impEF was observed in 189 patients (41% of the overall impEF group) and was associated with higher risk of D/HT/LVAD compared with persistent impEF at multivariable analysis (HR: 2.54; 95% CI: 1.60–4.04). Conclusions In NICM, we observed a 57% rate of impEF. However, recurrent decline in LVEF was observed in ≈40% of impEF patients and it was associated with an increased risk of D/HT/LVAD.