Sleep and Circadian Health of Critical Survivors: A 12-Month Follow-Up Study.

OBJECTIVES: To investigate the sleep and circadian health of critical survivors 12 months after hospital discharge and to evaluate a possible effect of the severity of the disease within this context. DESIGN: Observational, prospective study. SETTING: Single-center study. PATIENTS: Two hundred sixty patients admitted to the ICU due to severe acute respiratory syndrome coronavirus 2 infection. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The cohort was composed of 260 patients (69.2% males), with a median (quartile 1-quartile 3) age of 61.5 years (52.0-67.0 yr). The median length of ICU stay was 11.0 days (6.00-21.8 d), where 56.2% of the patients required invasive mechanical ventilation (IMV). The Pittsburgh Sleep Quality Index (PSQI) revealed that 43.1% of the cohort presented poor sleep quality 12 months after hospital discharge. Actigraphy data indicated an influence of the disease severity on the fragmentation of the circadian rest-activity rhythm at the 3- and 6-month follow-ups, which was no longer significant in the long term. Still, the length of the ICU stay and the duration of IMV predicted a higher fragmentation of the rhythm at the 12-month follow-up with effect sizes (95% CI) of 0.248 (0.078-0.418) and 0.182 (0.005-0.359), respectively. Relevant associations between the PSQI and the Hospital Anxiety and Depression Scale (rho = 0.55, anxiety; rho = 0.5, depression) as well as between the fragmentation of the rhythm and the diffusing lung capacity for carbon monoxide (rho = -0.35) were observed at this time point. CONCLUSIONS: Our findings reveal a great prevalence of critical survivors presenting poor sleep quality 12 months after hospital discharge. Actigraphy data indicated the persistence of circadian alterations and a possible impact of the disease severity on the fragmentation of the circadian rest-activity rhythm, which was attenuated at the 12-month follow-up. This altogether highlights the relevance of considering the sleep and circadian health of critical survivors in the long term.

Navigating the path of reproducibility in microRNA-based biomarker research with ring trials.

The development of microRNA (miRNA)-based biomarkers has gained significant attention due to their potential diagnostic, prognostic and therapeutic applications. However, the reproducibility of miRNA biomarker research faces unique challenges, primarily due to the influence of pre-analytical and analytical factors. The absence of standardized procedures contributes to inconsistencies across studies, alongside challenges in reference gene selection, data analysis methods and miRNA profiling platforms. Inter-laboratory comparison trials, or ring trials, offer a strategic approach to address technical and biological variability in miRNA biomarker studies. These trials promote standardization, identify sources of variability and strengthen the correlation between miRNAs and clinical outcomes. Despite their underutilization in miRNA biomarker research, ring trials represent a valuable tool for enhancing reproducibility and expediting the translation of miRNA-based biomarkers into clinical applications.

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort.

BACKGROUND: Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster. METHODS: Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3. RESULTS: Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3. CONCLUSIONS: During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

Development of circulating microRNA-based biomarkers for medical decision-making: a friendly reminder of what should NOT be done.

Circulating cell-free microRNAs (miRNAs) represent a major reservoir for biomarker discovery. Unfortunately, their implementation in clinical practice is limited due to a profound lack of reproducibility. The great technical variability linked to major pre-analytical and analytical caveats makes the interpretation of circulating cell-free miRNA data challenging and leads to inconsistent findings. Additional efforts directed to standardization are fundamental. Several well-established protocols are currently used by independent groups worldwide. Nonetheless, there are some specific aspects in specimen collection and processing, sample handling, miRNA quantification, and data analysis that should be considered to ensure reproducibility of results. Here, we have addressed this challenge using an alternative approach. We have highlighted and discussed common pitfalls that negatively impact the robustness of circulating miRNA quantification and their application for clinical decision-making. Furthermore, we provide a checklist usable by investigators to facilitate and ensure the control of the whole miRNA quantification and analytical process. We expect that these recommendations improve the reproducibility of findings, and ultimately, facilitate the incorporation of circulating miRNA profiles into clinical practice as the next generation of disease biomarkers.

Circulating miR-133a-3p defines a low-risk subphenotype in patients with heart failure and central sleep apnea: a decision tree machine learning approach.

BACKGROUND: Patients with heart failure with reduced ejection fraction (HFrEF) and central sleep apnea (CSA) are at a very high risk of fatal outcomes. OBJECTIVE: To test whether the circulating miRNome provides additional information for risk stratification on top of clinical predictors in patients with HFrEF and CSA. METHODS: The study included patients with HFrEF and CSA from the SERVE-HF trial. A three-step protocol was applied: microRNA (miRNA) screening (n = 20), technical validation (n = 60), and biological validation (n = 587). The primary outcome was either death from any cause, lifesaving cardiovascular intervention, or unplanned hospitalization for worsening of heart failure, whatever occurred first. MiRNA quantification was performed in plasma samples using miRNA sequencing and RT-qPCR. RESULTS: Circulating miR-133a-3p levels were inversely associated with the primary study outcome. Nonetheless, miR-133a-3p did not improve a previously established clinical prognostic model in terms of discrimination or reclassification. A customized regression tree model constructed using the Classification and Regression Tree (CART) algorithm identified eight patient subphenotypes with specific risk patterns based on clinical and molecular characteristics. MiR-133a-3p entered the regression tree defining the group at the lowest risk; patients with log(NT-proBNP) ≤ 6 pg/mL (miR-133a-3p levels above 1.5 arbitrary units). The overall predictive capacity of suffering the event was highly stable over the follow-up (from 0.735 to 0.767). CONCLUSIONS: The combination of clinical information, circulating miRNAs, and decision tree learning allows the identification of specific risk subphenotypes in patients with HFrEF and CSA.

Cardiovascular complications of diabetes: role of non-coding RNAs in the crosstalk between immune and cardiovascular systems.

Diabetes mellitus, a group of metabolic disorders characterized by high levels of blood glucose caused by insulin defect or impairment, is a major risk factor for cardiovascular diseases and related mortality. Patients with diabetes experience a state of chronic or intermittent hyperglycemia resulting in damage to the vasculature, leading to micro- and macro-vascular diseases. These conditions are associated with low-grade chronic inflammation and accelerated atherosclerosis. Several classes of leukocytes have been implicated in diabetic cardiovascular impairment. Although the molecular pathways through which diabetes elicits an inflammatory response have attracted significant attention, how they contribute to altering cardiovascular homeostasis is still incompletely understood. In this respect, non-coding RNAs (ncRNAs) are a still largely under-investigated class of transcripts that may play a fundamental role. This review article gathers the current knowledge on the function of ncRNAs in the crosstalk between immune and cardiovascular cells in the context of diabetic complications, highlighting the influence of biological sex in such mechanisms and exploring the potential role of ncRNAs as biomarkers and targets for treatments. The discussion closes by offering an overview of the ncRNAs involved in the increased cardiovascular risk suffered by patients with diabetes facing Sars-CoV-2 infection.

A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study.

BACKGROUND: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. METHODS: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. RESULTS: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. CONCLUSIONS: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.

Dietary microRNAs and cancer: A new therapeutic approach?

Cancer is one of the leading causes of premature death and constitutes a challenge for both low- and high-income societies. Previous evidence supports a close association between modifiable risk factors, including dietary habits, and cancer risk. Investigation of molecular mechanisms that mediate the pro-oncogenic and anti-oncogenic effects of diet is therefore fundamental. MicroRNAs (miRNAs) have received much attention in the past few decades as crucial molecular elements of human physiology and disease. Aberrant expression patterns of these small noncoding transcripts have been observed in a wide array of cancers. Interestingly, human miRNAs not only can be modulated by bioactive dietary components, but it has also been proposed that diet-derived miRNAs may contribute to the pool of human miRNAs. Results from independent groups have suggested that these exogenous miRNAs may be functional in organisms. These findings open the door to novel and innovative approaches to cancer therapy. Here, we provide an overview of the biology of miRNAs, with a special focus on plant-derived dietary miRNAs, summarize recent findings in the field of cancer, address the possible applications to clinical practice and discuss obstacles and challenges in the field.

Sleep and Circadian Health of Critical COVID-19 Survivors 3 Months After Hospital Discharge.

OBJECTIVES: To evaluate the sleep and circadian rest-activity pattern of critical COVID-19 survivors 3 months after hospital discharge. DESIGN: Observational, prospective study. SETTING: Single-center study. PATIENTS: One hundred seventy-two consecutive COVID-19 survivors admitted to the ICU with acute respiratory distress syndrome. INTERVENTIONS: Seven days of actigraphy for sleep and circadian rest-activity pattern assessment; validated questionnaires; respiratory tests at the 3-month follow-up. MEASUREMENTS AND MAIN RESULTS: The cohort included 172 patients, mostly males (67.4%) with a median (25th-75th percentile) age of 61.0 years (52.8-67.0 yr). The median number of days at the ICU was 11.0 (6.00-24.0), and 51.7% of the patients received invasive mechanical ventilation (IMV). According to the Pittsburgh Sleep Quality Index (PSQI), 60.5% presented poor sleep quality 3 months after hospital discharge, which was further confirmed by actigraphy. Female sex was associated with an increased score in the PSQI (p < 0.05) and IMV during ICU stay was able to predict a higher fragmentation of the rest-activity rhythm at the 3-month follow-up (p < 0.001). Furthermore, compromised mental health measured by the Hospital Anxiety and Depression Scale was associated with poor sleep quality (p < 0.001). CONCLUSIONS: Our findings highlight the importance of considering sleep and circadian health after hospital discharge. Within this context, IMV during the ICU stay could aid in predicting an increased fragmentation of the rest-activity rhythm at the 3-month follow-up. Furthermore, compromised mental health could be a marker for sleep disruption at the post-COVID period.

Impact of time to intubation on mortality and pulmonary sequelae in critically ill patients with COVID-19: a prospective cohort study.

QUESTION: We evaluated whether the time between first respiratory support and intubation of patients receiving invasive mechanical ventilation (IMV) due to COVID-19 was associated with mortality or pulmonary sequelae. MATERIALS AND METHODS: Prospective cohort of critical COVID-19 patients on IMV. Patients were classified as early intubation if they were intubated within the first 48 h from the first respiratory support or delayed intubation if they were intubated later. Surviving patients were evaluated after hospital discharge. RESULTS: We included 205 patients (140 with early IMV and 65 with delayed IMV). The median [p25;p75] age was 63 [56.0; 70.0] years, and 74.1% were male. The survival analysis showed a significant increase in the risk of mortality in the delayed group with an adjusted hazard ratio (HR) of 2.45 (95% CI 1.29-4.65). The continuous predictor time to IMV showed a nonlinear association with the risk of in-hospital mortality. A multivariate mortality model showed that delay of IMV was a factor associated with mortality (HR of 2.40; 95% CI 1.42-4.1). During follow-up, patients in the delayed group showed a worse DLCO (mean difference of - 10.77 (95% CI - 18.40 to - 3.15), with a greater number of affected lobes (+ 1.51 [95% CI 0.89-2.13]) and a greater TSS (+ 4.35 [95% CI 2.41-6.27]) in the chest CT scan. CONCLUSIONS: Among critically ill patients with COVID-19 who required IMV, the delay in intubation from the first respiratory support was associated with an increase in hospital mortality and worse pulmonary sequelae during follow-up.

Plasma circular RNA hsa_circ_0001445 and coronary artery disease: Performance as a biomarker.

The role of circular RNAs (circRNAs) as biomarkers remains poorly characterized. Here, we investigated the performance of the circRNA hsa_circ_0001445 as a biomarker of coronary artery disease (CAD) in a real-world clinical practice setting. Plasma hsa_circ_0001445 was measured in a study population of 200 consecutive patients with suspected stable CAD who had undergone coronary computed tomographic angiography (CTA). Multivariable logistic models were constructed combining conventional risk factors with established biomarkers and hsa_circ_0001445. Model robustness was internally validated by the bootstrap technique. Biomarker accuracy was evaluated using the C-index. The integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were also calculated. Risk groups were developed via classification tree models. The stability of plasma hsa_circ_0001445 was evaluated under different clinical conditions. hsa_circ_0001445 levels were associated with higher coronary atherosclerosis extent and severity with a 2-fold increase across tertiles (28.4%-50.0%). Levels of hsa_circ_0001445 were proportional to coronary atherosclerotic burden, even after comprehensive adjustment for cardiovascular risk factors, medications, and established biomarkers (fully adjusted OR = 0.432 for hsa_circ_0001445 as a continuous variable and fully adjusted OR = 0.277 for hsa_circ_0001445 as a binary variable). The classification of patients was improved with the incorporation of hsa_circ_0001445 into a base clinical model (CM) composed of conventional cardiovascular risk factors, showing an IDI of 0.047 and NRI of 0.482 for hsa_circ_0001445 as a continuous variable and an IDI of 0.056 and NRI of 0.373 for hsa_circ_0001445 as a binary variable. A trend toward higher discrimination capacity was also observed (C-indexCM  = 0.833, C-indexCM+continuous hsa_circ_0001445  = 0.856 and C-indexCM+binary hsa_circ_0001445  = 0.855). Detailed analysis of stability showed that hsa_circ_0001445 was present in plasma in a remarkably stable form. In vitro, hsa_circ_0001445 was downregulated in extracellular vesicles secreted by human coronary smooth muscle cells upon exposure to atherogenic conditions. In patients with suspected stable CAD referred for coronary CTA, plasma hsa_circ_0001445 improves the identification of coronary artery atherosclerosis.

Peripheral blood microRNAs and the COVID-19 patient: methodological considerations, technical challenges and practice points.

The COVID-19 emergency pandemic resulting from infection with SARS-CoV-2 represents a major threat to public health worldwide. There is an urgent clinical demand for easily accessible tools to address weaknesses and gaps in the management of COVID-19 patients. In this context, transcriptomic profiling of liquid biopsies, especially microRNAs (miRNAs), has recently emerged as a robust source of potential clinical indicators for medical decision-making. Nevertheless, the analysis of the circulating miRNA signature and its translation to clinical practice requires strict control of a wide array of methodological details. In this review, we indicate the main methodological aspects that should be addressed when evaluating the circulating miRNA profiles in COVID-19 patients, from preanalytical and analytical variables to the experimental design, impact of confounding, analysis of the data and interpretation of the findings, among others. Additionally, we provide practice points to ensure the rigour and reproducibility of miRNA-based biomarker investigations of this condition.Abbreviations: ACE: angiotensin-converting enzyme; ARDS: acute respiratory distress syndrome; COVID-19: coronavirus disease 2019; ERDN: early Detection Research Network; LMWH: low molecular weight heparin; miRNA: microRNA; ncRNA: noncoding RNA; SARS-CoV-2: severe acute respiratory syndrome coronavirus-2; SOP: standard operating procedure.

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients.

BACKGROUND: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. METHODS: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. RESULTS: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). CONCLUSIONS: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation.

Circulating MicroRNA Profiling Reveals Specific Subsignatures in Response to a Maximal Incremental Exercise Test.

ABSTRACT: Fernández-Sanjurjo, M, Díaz-Martínez, ÁE, Díez-Robles, S, González-González, F, de Gonzalo-Calvo, D, Rabadán, M, Dávalos, A, Fernández-García, B, and Iglesias-Gutiérrez, E. Circulating microRNA profiling reveals specific subsignatures in response to a maximal incremental exercise test. J Strength Cond Res 35(2): 287-291, 2021-Circulating microRNAs (c-miRNAs) have been described as emergent regulators and biomarkers of exercise. The aim of this study was to analyze the c-miRNA response to a maximal incremental exercise test (MIET) and its relationship with markers of exercise response and adaptation. Two blood samples were collected from 9 male amateur runners (31-50 years), before (Pre) and after (Post) a MIET. The maximal oxygen uptake (V̇o2max), maximum heart rate (HRmax), and maximal aerobic speed (MAS) were recorded. Lactate and creatine kinase (CK) plasma concentrations were measured. A panel of 752 miRNAs was analyzed using standardized protocols and relative quantification to Pre. A total of 13 miRNAs were found significantly upregulated at Post. By focusing on the exercise markers that correlate with the expression of these miRNAs, they were clustered into different functional groups or subsignatures. Thus, miR-21-5p, miR-29b-3p, and miR-183-5p showed a strong correlation with HRmax and a validated target signature related to fatty acid metabolism. Furthermore, let-7c-5p, miR-340-5p, miR-425-3p, and miR-629-5p were significantly correlated with CK, and the most significantly enriched pathways for these subsignatures were the Hippo signaling pathway and signaling pathways regulating pluripotency of stem cells. Finally, Pre miR-106b-5p expression showed an inverse association with MAS and Post lactate concentration, which highlights its relevance as biomarker of training status and its predictive value for performance. No significant correlations were observed with V̇o2max. Our results define for the first time specific functional c-miRNA subsignatures, adding novel evidence about their potential regulatory role in exercise response.

Exercise dose affects the circulating microRNA profile in response to acute endurance exercise in male amateur runners.

The systemic response to exercise is dose-dependent and involves a complex gene expression regulation and cross-talk between tissues. This context ARISES the need for analyzing the influence of exercise dose on the profile of circulating microRNAs (c-miRNAs), as emerging posttranscriptional regulators and intercellular communicators. Thus, we hypothesized that different exercise doses will determine specific c-miRNA signatures that will highlight its potential as exercise dose biomarker. Nine active middle-aged males completed a 10-km race (10K), a half-marathon (HM), and a marathon (M). Blood samples were collected immediately before and after races. Plasma RNA was extracted, and a global screening of 752 microRNAs was analyzed using RT-qPCR. Three different c-miRNA profiles were defined according to the three doses. In 10K, 14 c-miRNAs were found to be differentially expressed between pre- and post-exercise, 13 upregulated and 1 downregulated. Regarding HM, 13 c-miRNAs were found to be differentially modulated, in all the cases upregulated. A total of 28 c-miRNAs were found to be differentially expressed in M, 21 overexpressed and 7 repressed after this race. We had also found 3 common c-miRNAs between 10K and M and 2 common c-miRNAs between 10K and HM. In silico analysis supported a close association between exercise dose c-miRNA profiles and cellular pathways linked to energy metabolism and cell cycle. In conclusion, we have observed that different exercise doses induced specific c-miRNA profiles. So, our results point to c-miRNAs as emerging exercise dose biomarkers and as one of regulatory mechanisms modulating the response to endurance exercise.

Circulating non-coding RNAs in biomarker-guided cardiovascular therapy: a novel tool for personalized medicine?

Current clinical guidelines emphasize the unmet need for technological innovations to guide physician decision-making and to transit from conventional care to personalized cardiovascular medicine. Biomarker-guided cardiovascular therapy represents an interesting approach to inform tailored treatment selection and monitor ongoing efficacy. However, results from previous publications cast some doubts about the clinical applicability of biomarkers to direct individualized treatment. In recent years, the non-coding human transcriptome has emerged as a new opportunity for the development of novel therapeutic strategies and biomarker discovery. Non-coding RNA (ncRNA) signatures may provide an accurate molecular fingerprint of patient phenotypes and capture levels of information that could complement traditional markers and established clinical variables. Importantly, ncRNAs have been identified in body fluids and their concentrations change with physiology and pathology, thus representing promising non-invasive biomarkers. Previous publications highlight the translational applicability of circulating ncRNAs for diagnosis and prognostic stratification within cardiology. Numerous independent studies have also evaluated the potential of the circulating non-coding transcriptome to predict and monitor response to cardiovascular treatment. However, this field has not been reviewed in detail. Here, we discuss the state-of-the-art research into circulating ncRNAs, specifically microRNAs and long non-coding RNAs, to support clinical decision-making in cardiovascular therapy. Furthermore, we summarize current methodological and conceptual limitations and propose future steps for their incorporation into personalized cardiology. Despite the lack of robust population-based studies and technical barriers, circulating ncRNAs emerge as a promising tool for biomarker-guided therapy.

Circulating microRNAs in suspected stable coronary artery disease: A coronary computed tomography angiography study.

OBJECTIVES: To explore the diagnostic performance of circulating microRNAs (miRNAs) as biomarkers in patients with suspected stable coronary artery disease (CAD). METHODS: Plasma samples were collected from 237 consecutive patients referred for coronary computed tomography angiography (CCTA). Presence, extension and severity of coronary stenosis were evaluated using the indexes: presence of diameter stenosis ≥ 50%, segment involvement score (SIS), segment stenosis score (SSS) and 3-vessel plaque score. A panel of 10 miRNAs previously associated with CAD was analysed using RT-qPCR. Multivariate analyses were used to analyse the associations between biomarkers and indexes. Discrimination was evaluated using the area under the ROC curve (AUC). Decision trees were generated using chi-squared Automatic Interaction Detector (CHAID) prediction models. RESULTS: After comprehensive adjustment including cardiovascular risk factors, medication use, confounding factors and protein-based biomarkers (hs-TnT and hs-CRP), several circulating miRNAs were inversely associated with coronary atherosclerosis extension (SIS and 3-vessel plaque score) and severity (SSS). In the whole population, circulating miRNAs showed a poor discrimination value for all indexes (AUC = 0.539-0.644) and did not increase the discrimination capacity of a clinical model of coronary stenosis presence, extension and severity based on conventional cardiovascular risk factors. Conversely, the inclusion of circulating miRNAs in decision trees produces models that improve the classification of cases and controls in specific patient subgroups. CONCLUSIONS: This study identifies a group of circulating miRNAs that failed to improve the discrimination capacity of cardiovascular risk factors but that has the potential to define specific subpopulations of patients with suspected stable CAD.

Identification of new biophysical markers for pathological ventricular remodelling in tachycardia-induced dilated cardiomyopathy.

Our aim was to identify biophysical biomarkers of ventricular remodelling in tachycardia-induced dilated cardiomyopathy (DCM). Our study includes healthy controls (N = 7) and DCM pigs (N = 10). Molecular analysis showed global myocardial metabolic abnormalities, some of them related to myocardial hibernation in failing hearts, supporting the translationality of our model to study cardiac remodelling in dilated cardiomyopathy. Histological analysis showed unorganized and agglomerated collagen accumulation in the dilated ventricles and a higher percentage of fibrosis in the right (RV) than in the left (LV) ventricle (P = .016). The Fourier Transform Infrared Spectroscopy (FTIR) 1st and 2nd indicators, which are markers of the myofiber/collagen ratio, were reduced in dilated hearts, with the 1st indicator reduced by 45% and 53% in the RV and LV, respectively, and the 2nd indicator reduced by 25% in the RV. The 3rd FTIR indicator, a marker of the carbohydrate/lipid ratio, was up-regulated in the right and left dilated ventricles but to a greater extent in the RV (2.60-fold vs 1.61-fold, P = .049). Differential scanning calorimetry (DSC) showed a depression of the freezable water melting point in DCM ventricles - indicating structural changes in the tissue architecture - and lower protein stability. Our results suggest that the 1st, 2nd and 3rd FTIR indicators are useful markers of cardiac remodelling. Moreover, the 2nd and 3rd FITR indicators, which are altered to a greater extent in the right ventricle, are associated with greater fibrosis.

Non-coding RNAs and exercise: pathophysiological role and clinical application in the cardiovascular system.

There is overwhelming evidence that regular exercise training is protective against cardiovascular disease (CVD), the main cause of death worldwide. Despite the benefits of exercise, the intricacies of their underlying molecular mechanisms remain largely unknown. Non-coding RNAs (ncRNAs) have been recognized as a major regulatory network governing gene expression in several physiological processes and appeared as pivotal modulators in a myriad of cardiovascular processes under physiological and pathological conditions. However, little is known about ncRNA expression and role in response to exercise. Revealing the molecular components and mechanisms of the link between exercise and health outcomes will catalyse discoveries of new biomarkers and therapeutic targets. Here we review the current understanding of the ncRNA role in exercise-induced adaptations focused on the cardiovascular system and address their potential role in clinical applications for CVD. Finally, considerations and perspectives for future studies will be proposed.

Circulating microRNA as Emerging Biomarkers of Exercise.

An interest has recently emerged in the role of circulating microRNAs (c-miRNAs) as posttranscriptional regulators, intercellular communicators and, especially, as potential biomarkers of the systemic response to acute exercise and training. We propose that, with the limited, heterogeneous, and mainly descriptive information currently available, c-miRNAs do not provide a reliable biomarker of exercise in healthy or diseased individuals.