Lower serum level of miRNA-21 may be considered as a comorbidity-independent characteristic of frailty in cardiovascular patients

Lower serum level of miRNA-21 may be considered as a comorbidity-independent characteristic of frailty in cardiovascular patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Lower serum level of miRNA-21 may be considered as a comorbidity-independent characteristic of frailty in cardiovascular patients Julia Cieśla, Stanisław Wawrzyniak, Michał Krawiec, Michał Janik, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7133943/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 8 You are reading this latest preprint version Abstract We examined the serum level of miRNA-21 in a cohort of frail cardiovascular patients. We have enrolled 261 patients into this ancillary analysis of the FRAPICA trial (ClinicalTrials.org NCT03209414, registered 06/07/20217). The phenotype Fried frailty scale identified 93 robust, 131 pre-frail, and 37 frail patients. The groups differed in terms of demographics, morphology, and clinical characteristics. Frail patients had significantly lower miRNA-21 serum levels (median, 0.022; IQR, 0.0188–0.0351) compared to pre-frail (0.0477; 0.0467–0.0511) and robust patients (0.0477; 0.0428–0.0526), with P < 0.001. In the case of each frailty trait, patients with the presence of this trait had lower miRNA-21 levels than patients without the trait. The comorbidities had no impact on the miRNA-21 level. The miRNA-21 level correlated positively with weight, lean body mass, instrumental activities of daily living score, renal excretory function, expiratory pulmonary function, and hemoglobin concentration. This finding proposes miR-21 as a potential blood circulating biomarker of frailty, indicating that low levels of this miRNA represent a comorbid-independent characteristic of frailty in cardiovascular patients. Future studies are warranted to investigate the prognostic impact of baseline miRNA-21 levels on cardiovascular outcomes, as well as the longitudinal fluctuations of miRNA-21 serum levels and their clinical implications. Health sciences/Biomarkers Health sciences/Cardiology Health sciences/Diseases Biological sciences/Genetics Health sciences/Medical research Health sciences/Risk factors Frailty syndrome epigenetics cardiovascular diseases comorbidity microRNA Figures Figure 1 Introduction Frailty syndrome is a clinical condition characterized by a decline in physiological reserves, increased vulnerability to stressors, and an increased risk of adverse health outcomes. Fried et al. have described frailty as the presence of at least three out of five key criteria: exhaustion, weakness, slowness, unintentional weight loss, and low physical activity ( 1 ). These features reflect a progressive deterioration in physical and functional capacities, often leading to disability, hospitalization, and mortality ( 1 , 2 ). The incidence of cardiovascular diseases (CVD) increases with the progression from robust to frail status, characterized by the development of frailty ( 1 ). Frail CVD patients have a significantly higher comorbid burden, angiographic disease severity, and more frequently observed highly vulnerable thin cap fibroatheroma in intravascular ultrasound examination ( 3 ). These features translate into increased risk and worse procedural outcomes. Frail patients treated with percutaneous coronary intervention, irrespective of primary diagnosis, e.g., acute or chronic coronary syndrome, have an increased periprocedural bleeding risk ( 4 , 5 ), vascular injury risk ( 5 ), increased risk of stroke or transient ischemic attack ( 5 ), and increased short-, medium-, and long-term mortality risk ( 5 – 9 ). Just over half of frail patients with acute myocardial infarction are scheduled for angiography and percutaneous coronary intervention ( 7 , 9 ). Following Afilalo et al. ( 10 ), we lack optimized resource allocation, which would enable frail patients to avoid costly but futile interventions. Eventually, frailty should not be viewed as a reason to withhold care, but rather to deliver it in a more patient-oriented manner ( 11 ). To overcome the challenge of frailty, an individualized patient approach involves implementing precision medicine by utilizing biological biomarkers to enhance diagnostic accuracy and optimize management. Identifying biomarkers would allow cardiologists to predict the functional trajectories of older adults at preclinical stages ( 12 ). Precision medicine was defined by the National Research Council’s Toward Precision Medicine in 2008 as: “The tailoring of medical treatment to the individual characteristics of each patient … to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment. Preventive and therapeutic interventions can then be concentrated on those patients who will benefit, sparing expense and side effects for those who will not”. Our recent literature search identified the GrimAge epigenetic clock, miRNA-146a, and miRNA-21 as potential biomarkers of frailty ( 13 ). miRNA-21 regulates pathways involved in inflammation and fibrosis, which are exacerbated in conditions such as coronary artery disease and myocardial infarction ( 14 , 15 ). Given the overlap between inflammatory pathways in frailty and cardiovascular disease, miRNA21 may serve as a valuable marker for assessing the severity of frailty and predicting patient outcomes, particularly in invasive cardiovascular treatments. The elevated levels of miRNA21 seen after acute MI, combined with its role in inflammation and fibrosis, suggest that it could be a valuable marker for both frailty and cardiovascular disease severity ( 15 ). This could help guide treatment decisions and improve patient outcomes, particularly in cases requiring more aggressive interventions. The study aimed to assess serum levels of miRNA-21 in frail patients, compare them to those in pre-frail and robust counterparts, and evaluate miRNA-21 levels in relation to comorbidities and phenotypic frailty features. Materials and methods a. Study population This is the ancillary sub-study of the FRAPICA trial (ClinicalTrials.gov NCT04035486, registered 06/07/20217 ). The design and rationale of the FRAPICA study have been described previously (16). In brief, the study's inclusion criteria were age 65 years or older and informed consent to participate in the project. We enrolled 261 consecutive eligible patients in this analysis, who were admitted to the 2nd Department of Cardiology in Zabrze between February 2023 and December 2023. Patients were assessed for the severity of frailty syndrome according to the Fried phenotype criteria (1). Respiratory parameters like peak expiratory flow (PEF) and forced expiratory volume in 1 second (FEV1) were measured using an Asmaplan 1 peak flow meter (Vitalograph, Ireland). Patients’ height and weight were measured with a Seca 287 measuring station (Seca, Hamburg, Germany). Fat-free body mass (FFBM) was measured using Harpenden’s skinfold caliper and Baty’s body assessment software v. 17 (Baty International Ltd., Burgess Hill, UK) with a three-site Jackson/Pollock algorithm (17). For practical purposes, we have cross-checked the aforementioned method with Seca mBCA 528 bioimpedance analysis in 20 subjects (10 volunteers and 10 FRAPICA patients) aged 22–82 years. The Bland-Altman analysis revealed a mean difference of -0.062 kg; all results fell within the 95% confidence intervals (data not shown). Patients were drawn for fasting blood, and serum was prepared. Serum samples were stored at -81℃ until analysis. Clinical and laboratory data were retrieved from patients’ electronic medical records. The study was conducted under the Declaration of Helsinki and approved by the Ethics Committee of the Medical University of Silesia (3 Oct 2017 (KNW/0022/KB1/39/I/17)); (8 Feb 2022 (PCN/CBN/0022/KB1/39/II/17/22)). Informed consent was obtained from all the participants. b. Frailty syndrome evaluation To diagnose the degree of frailty, each patient was assessed using the Frailty Phenotype Score using the following criteria: · Slowness—reduced gait speed at a distance of 5m at the usual pace. The patient must repeat the test three times, and the results are averaged. If a patient walks for more than 6 seconds, the criterion is positive. · Weakness is assessed with a maximal handgrip strength test. It is carried out in the dominant arm. We use an electronic hand dynamometer EH101 (VETEK AB, Sweden). A patient must repeat the measurement three times, and the maximal value is recorded. The test is positive for frailty when strength is lower than 20 kg for women and 30 kg for men. · The Minnesota Leisure Time Activity questionnaire assesses low physical activity. The result is positive when calorie expenditure per week is lower than 270 kcal/week in women and <383 kcal/week in men. We have prepared a Microsoft Excel-based template for rapid questioning and easy calculation of all activities and respective calorie expenditures. We are assessing physical activity from the past 12 months. · Exhaustion—self-reported by a patient. It is evaluated by the answer to 2 questions from the Center for Epidemiologic Studies Depression Scale Revised (CESD-R) scale. The patient has to answer the following questions: “How often in the past week did you feel like everything you did was an effort? How often did you feel like you could not get going in the past week?” The possible answers are “often” (≥3 days) or “not often” when the feeling is present in 0 to 2 days. A positive answer is when the patient says “often.” · Weight loss exceeding 10 pounds (approximately 4.5 kg) unintentionally in the past year. We recognize frailty if three or more out of five features are met. Patients with 1 or 2 traits present are classified as pre-frail. Patients who did not meet any of the requirements are marked as robust. c. MiRNA-21 assays The study used hsa-miR-21-5p miREIA (BioVendor, Czech Republic) - an enzyme immunoassay for the quantitative measurement of human microRNA-21-5p. The samples were analyzed in parallel using a cel-miR-39-3p miREIA assay kit (BioVendor, Czech Republic), and then miRNA-21 expression was normalized with the extraction coefficient. Cell-free miRNA from serum was isolated with RNA Isolation Kit Plasma/Serum (BioVendor, Czech Republic). After lysis, the spike-in from the cel-miR-39-3p miREIA assay kit was added to each sample, with a final concentration of spike-in of 1000 amol/μl. All samples were kept at -81℃ until further analysis. For cel-miR39-3p measurements, 20 μl of 50x diluted RNA sample was used and for hsa-miR-21-5p 20 μl of undiluted RNA sample was used. The miRNA-21 levels analyzed and presented are the normalized values. d. Statistical analysis After analyzing the data for normality of distribution and equality of variances (Shapiro-Wilk test), we employed both parametric and non-parametric statistical methods for comparing the robust, prefrail, and frail groups. We have used ANOVA for multiple group comparisons of normally distributed quantitative data. Any significances disclosed in the analysis of variance were checked with Student’s t-test. We have used the Kruskal-Wallis ANOVA to compare the levels of miRNA-21 across multiple groups, and the Mann-Whitney U test to compare two groups. The Chi-squared test with Yates' correction for comparing frequency data. We have presented data as means and standard deviations, as medians and interquartile ranges, or as frequency data. Quantitative variables were correlated using the Spearman test. Statistical significance was considered at p-values < 0.05. Results e. Demographic and medical data Among the 261 patients recruited to the study, the majority were pre-frail patients (50%), followed by the robust patients (36%), while 14% of patients were frail. The percentage of women increased from 23.6% (robust) to 48.6% (frail, P<0.01). The groups differed in terms of age, height, and lean body mass. Frail patients had the lowest height and FFBM values, as well as the highest mean age. There were no differences between the groups in terms of total body mass. Considering eGFR, statistically significant differences were observed between the groups before coronary angiography, with the lowest values in patients with frailty. Considering the values of red blood cell count, hematocrit, and hemoglobin, statistically significant differences (p < 0.001) were noted, with the lowest values observed in patients with frailty. Strong statistical significance (p < 0.01) was also noted for respiratory parameters, including FEV1 and PEF. Clinical characteristics are presented in Table 1. Table 1. Patient demographics and clinical presentation. Robust (n=93) Pre-frail (n=131) Frail (n=37) Significance Age, years, X±SD 71.24 ± 5.14 73.52 ± 5.29 75.00 ± 6.70 <0.05 Men/women, n/n 71/22 78/53 19/18 <0.01 Weight, kg, X±SD 84.33 ± 14.54 81.50 ± 17.13 82.35 ± 22.36 NS Height, cm, X±SD 170.25 ± 7.16 167.25 ± 9.51 162.19 ± 16.78 <0.05 BMI, kg/m2, X±SD 29.10 ± 4.56 29.11 ± 5.09 29.63 ± 6.55 <0.05 FFBM, kg, X±SD 58.66 ± 9.70 56.00 ± 11.99 51.88 ± 14.19 <0.05 Creatinine, µmol/l, X±SD 82.65 ± 18.51 93.90 ± 59.73 87.35 ± 59.73 NS eGFR, ml/min/m2, X±SD 74.84 ± 13.61 68.12 ± 19.63 65.38 ± 16.46 <0.05 WBC, x 10 9 /l, X±SD 7.39 ± 2.0 7.37 ± 2.38 8.21 ± 2.13 NS RBC, mln/µl, X±SD 4.72 ± 0.51 4.53 ± 0.54 4.35 ± 0.56 <0.001 Hematocrit, %, X±SD 42.56 ± 3.76 40.75 ± 3.85 38.98 ± 4.98 <0.001 Hemoglobin, g/dl, X±SD 14.32 ± 1.32 13.51 ± 1.42 12.83 ± 1.78 <0.001 PLT, x 10 9 /l, X±SD 209.62 ± 51.09 218.97 ± 66.30 227.91 ± 51.97 NS PEF, L/min, X±SD 369.23 ± 129.42 314.80 ± 138.66 247.46 ± 114.15 <0.001 FEV1, L, X±SD 2.10 ± 0.59 1.85 ± 0.66 1.58 ± 0.54 <0.001 Table legend: BMI – body mass index, FFBM – fat-free body mass, eGFR – estimated glomerular filtration rate, WBC – white blood cells, RBC – red blood cells, PLT – platelets, PEF – peak expiratory flow, FEV1 – forced expiratory flow in 1 second f. Severity of frailty and mRNA21 The median mRNA-21 concentration in the entire group was 0.0477 (0.0352-0.0658). The lowest value recorded was 0.0124 in the frail group, and the highest was 0.6141 in the pre-frail group. Concentration values are presented in Fig. 1. A statistically significant difference in mRNA-21 values (p<0.001) was observed between the groups, with the lowest values in the frail group. Multiple comparisons of p-values between groups revealed statistically significant differences between the frail and pre-frail groups (p = 0.000009) and the frail and robust groups (p = 0.000002). There are no differences between the pre-frail and robust groups in mRNA-21 values. g. Components of the frailty definition The most frequently observed trait of frailty syndrome was exhaustion (41% of patients) and decreased muscle strength (30% of patients). The strongest statistically significant differences in mRNA-21 concentration between groups with and without a specific frailty feature were observed for decreased muscle strength and decreased walking speed (p < 0.001). In the case of each trait, patients with the presence of the trait were characterized by lower miRNA-21 levels than those without the trait. The miRNA-21 serum levels, depending on individual frailty features, are presented in Table 2. Table 2. mRNA-21 concentration depending on the presence or absence of individual traits for the diagnosis of frailty syndrome Frailty trait Patients with specific frailty trait vs. all other patients Median, IQR Exhaustion 108 vs. 155 0.0472 (0.0253-0.0511) vs. 0.0477 (0.0428-0.0511) <0.05 Weight loss 48 vs. 215 0.0351 (0.0204-0.0477) vs. 0.0477 (0.0428-0.0511) <0.001 Decrease in walking speed 34 vs. 227 0.0253 (0.0188-0.0477) vs. 0.0477 (0.0428-0.0511) <0.001 Decrease in muscle strength 79 vs. 182 0.0467 (0.0253-0.0511) vs. 0.0477 (0.0428-0.0511) <0.05 Decrease in physical activity 33 vs. 228 0.0319 (0.0221-0.0477) vs. 0.0477 (0.0428-0.0511) <0.05 h. Comorbidities In the whole study group, the most common comorbidities were hypertension and hyperlipidemia (both 217 cases), diabetes (112 cases), and previous cancer (88 cases). Most patients had not undergone percutaneous coronary intervention during previous hospitalizations (132 people vs. 127 people). No differences in mRNA-21 concentrations were observed between patients with specific comorbidities and other patients. The list of comorbidities and respective miRNA-21 serum levels is presented in the table below (Table 3). Table 3. mRNA-21 concentration depending on the presence or absence of analyzed comorbidities Patients with specific comorbidity vs. all other patients Median, IQR P Hypertension 42 vs. 217 0.0467 (0.0351-0.0511) vs. 0.0477 (0.0352-0.0511) NS Diabetes 146 vs. 112 0.0477 (0.0351-0.0511) vs. 0.0477 (0.0352-0.0494) NS Hyperlipidemia 42 vs. 217 0.0477 (0.0253-0.0526) vs. 0.0477 (0.0412-0.0511) NS Stroke/TIA 231 vs. 27 0.0477 (0.0418-0.0511) vs. 0.0477 (0.0221-0.0526) NS Peripheral artery disease 217 vs. 39 0.0477 (0.0417-0.0511) vs. 0.0467 (0.0253-0.0477) NS Atrial fibrillation 188 vs. 70 0.0477 (0.0351- 0.0511) vs. 0.0477 (0.0417-0.0511) NS COPD 241 vs. 18 0.0477 (0.0351- 0.0511) vs. 0.0477 (0.0253-0.0526) NS Asthma 240 vs. 19 0.0477 (0.0351-0.0511) vs. 0.0477 (0.0253-0.0511) NS Renal failure 232 vs. 27 0.0477 (0.0351-0.0511) vs. 0.0467 (0.0253-0.0511) NS Malignancy 225 vs. 34 0.0477 (0.0423-0.0511) vs. 0.0466 (0.0253-0.0511) NS Smoking 171 vs. 88 0.0477 (0.0351-0.0511) vs. 0.0477 (0.0417-0.0511) NS AMI 177 vs. 82 0.0477 (0.0379-0.0511) vs. 0.0467 (0.0319- 0.0511) NS PCI 132 vs. 127 0.0477 (0.0351-0.0511) vs. 0.0477 (0.0351-0.0511) NS CABG 220 vs. 39 0.0477 (0.0351-0.0511) vs. 0.0477 (0.0428- 0.0477) NS Table legend: TIA – transient ischemic attack, COPD – chronic obstructive pulmonary disease, AMI – history of acute myocardial infarction, PCI – history of percutaneous coronary intervention, CABG – history of coronary artery bypass grafting i. Correlations of mRNA-21 with quantitative variables To assess the relationship between the serum level of miRNA-21 and other factors, we calculated the correlation between its level and quantitative variables in the entire enrolled population. Significant positive correlations were found for weight, fat-free body mass, hemoglobin concentration, peak expiratory flow, and forced expiratory flow in one second (Table 4) Table 4. Correlations of mRNA-21 with quantitative variables N Spearman R P Age 261 -0.05 NS Weight 261 0.12 <0.05 Height 261 0.10 NS BMI 261 0.11 NS FFBM 261 0.19 <0.05 Creatinine 259 0.02 NS eGFR 257 0.06 NS Hematocrit 259 0.10 NS Hemoglobin 259 0.12 <0.05 PEF 256 0.17 <0.05 FEV1 256 0.14 <0.05 Table legend: BMI – body mass index, fat-free body mass, eGFR – estimated glomerular filtration rate, PEF – peak expiratory flow, FEV1 – forced expiratory flow in one second Discussion We have found in our study that frail patients with cardiovascular diseases have significantly lower levels of circulating miRNA-21 in their blood compared to their non-frail counterparts. The analysis indicated that the miRNA-21 level is substantially lower in patients with an individual phenotype characterized by frailty, in contrast to all other patients. However, the comorbidities do not impact the level of miRNA-21 in our patient population. To our knowledge, previously published papers on miRNA-21 have not addressed the issue of frailty, but they provide insightful information on its role in human pathology. Olivieri et al. have reported that miRNA-21 levels increase with advancing age ( 18 ). Other studies have also shown that post-acute coronary syndrome (ACS) patients have increased values of miRNA-21 ( 15 ). It rises more sharply in cases of acute myocardial infarction than in chronic coronary syndrome. In our study, no such relationship was found. A meta-analysis by Xin et al. demonstrated that patients with hypertension exhibit elevated levels of miRNA-21 ( 19 ). Animal models suggest this may be linked to the proliferation of vascular smooth muscle cells ( 20 ). In the present study, no association was found between miRNA-21 levels and a diagnosis of diabetes, although molecular studies suggest increased miRNA-21 expression in beta cells exposed to pro-inflammatory cytokines, leading to dysfunction in insulin secretion ( 21 ). Additionally, miRNA-21 may play a role in modulating the Phosphatase and Tensin Homolog in insulin-sensitive skeletal muscles, potentially resulting in improved glucose tolerance ( 22 ). Studies by Seyhan et al. ( 23 ) found a correlation between elevated serum miRNA-21 levels and diabetes diagnosis, as well as glucose intolerance and prediabetes. Similarly, other researchers observed higher circulating miRNA2-1 levels in patients with type 2 diabetes ( 24 , 25 ). In contrast, Ghorbani et al. ( 26 ) found no such correlation, suggesting instead that lower serum miRNA-21 levels are associated with hyperinsulinemia and insulin resistance. Galenko et al. associated reduced miRNA-21 levels with atrial fibrillation but found no differences based on the type of the condition (paroxysmal or persistent) or recurrence status. The study noted a higher incidence of atrial fibrillation in individuals with hypertension, who would typically exhibit increased miRNA-21 levels ( 27 ). Conversely, McManus et al. confirmed a link between lower miRNA-21 levels in both tissues and serum among patients with atrial fibrillation, with significantly lower miRNA-21 levels in persistent versus paroxysmal atrial fibrillation ( 28 ). Other studies, including animal models, suggest that decreased atrial miRNA-21 expression is associated with a lower risk of fibrosis and atrial fibrillation, particularly after myocardial infarction or cardiac surgery ( 29 – 31 ). This effect may be due to miRNA-21 inhibiting sprouty homologue 1 (Sprouty1 or Spry1), a negative regulator of the ERK/mitogen-activated protein kinase pathway. Reduced Sprouty1 levels result in hyperphosphorylation of ERK and p38 mitogen-activated protein kinases, leading to increased procollagen expression. This positions miRNA21 as a potential therapeutic target in atrial fibrillation treatment ( 29 ). In Yang et al.‘s research, a positive correlation was observed between blood miRNA21 levels and obesity, measured by body mass index (BMI), waist circumference, hip circumference, and waist-to-hip ratio ( 32 ). Another study found no significant difference in miRNA-21 levels between obese and non-obese patients, although miRNA-21 levels were positively correlated with body fat percentage ( 33 ). Anti-miRNA21 treatments were found to be effective in reducing body weight in a murine model ( 34 ). Although this study did not directly assess obesity using these metrics, Spearman’s analysis revealed a significant association between body weight and miRNA21 levels, alongside a correlation between reduced lean body mass (but not increased fat mass) and miRNA21, potentially linked to sarcopenia associated with frailty syndrome ( 35 ). Atherosclerosis and its complications have drawn considerable interest among researchers studying miRNA-21. Evidence suggests that miRNA-21 may contribute to the development of atherosclerosis ( 36 , 37 ), with elevated levels observed in patients with atherosclerosis. In patients with well-controlled hypertension, low miRNA-21 levels in peripheral blood mononuclear cells are associated with reduced arterial stiffness ( 38 ). miRNA-21 appears particularly relevant in acute myocardial infarction (AMI). miRNA-21 shows increased expression in the infarct border zone ( 39 ). Research by Zhang et al. indicated that serum miRNA-21 levels are significantly higher in AMI patients compared to healthy individuals or those with angina pectoris, with miRNA-21 levels correlating with classic myocardial infarction markers—creatine kinase (CK), creatine kinase-MB (CK-MB), and troponin I (cTnI) ( 15 ). The study also highlighted concerns over the release of miRNA-21 from various organs, potentially compromising biomarker specificity. Wang et al.’s meta-analysis found that circulating miRNA-21 levels in diagnosing AMI had a general sensitivity and specificity of 0.83 and 0.81, respectively, and noted its early appearance in peripheral blood compared to traditional AMI markers ( 40 ). miRNA-21 levels also rise in acute ischemic stroke ( 41 ). Patients meeting frailty criteria had significantly lower PEF and FEV1 values compared to other patients. Respiratory disorders in frailty patients have been reported in earlier studies, with respiratory diseases (asthma and COPD) also predisposing individuals to frailty ( 42 , 43 ). This study further identified a correlation between miRNA-21 levels and respiratory dysfunction (PEF and FEV1 reduction), although no association was found with asthma or COPD diagnoses, possibly due to unconfirmed diagnoses or alternative causes of respiratory impairment. Previous studies have demonstrated a positive correlation between miRNA-21 levels and asthma ( 44 , 45 ). The association between COPD and miRNA-21 levels requires further research; however, animal models suggest that elevated miRNA-21 expression may mediate pulmonary vascular remodeling under prolonged hypoxia ( 46 ). No association was found between miRNA-21 levels and renal failure diagnosis in this study, nor did miRNA-21 predict renal events post-coronary angiography, despite significant pre-procedure eGFR differences among robust, pre-frail, and frail groups, and marginal differences in creatinine and eGFR post-procedure. These findings contrast with prior animal studies, which have shown elevated miRNA-21 levels in renal tissue in various renal diseases, including chronic kidney disease and diabetic nephropathy ( 47 ). Murine studies suggest miRNA-21’s role in kidney disease may involve promoting renal fibrosis through pathways related to fatty acid and lipid oxidation ( 48 ) and regulation of metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) ( 49 ), highlighting miRNA-21 inhibition as a potential therapeutic target for kidney diseases ( 47 , 50 ). Previous research has reported increased miRNA-21 expression in tumor tissues and serum; however, further studies are needed to assess miRNA-21 levels post-recovery ( 51 – 53 ). In this study, 57% of CAD patients were classified as pre-frail, and 13% were frail. Pre-frail patients have approximately a 23% chance of regaining fitness, a 58% chance of remaining pre-frail, and an 18% chance of progressing to frailty. Frail patients, however, have only a 3% chance of regaining fitness and a 40% chance of improving to pre-frail status ( 54 ). Despite the absence of miRNA-21 differences, there is an urgent need to focus on pre-frail patients as well. Limitations of the study and a future perspective We present a cross-sectional single-time point analysis of the serum level of miRNA-21 in relation to clinical, morphological, and laboratory features of patients classified according to the phenotype frailty scale. The single-time-point approach has the lowest power to infer a cause-and-effect association. We need to determine how the serum level of miRNA-21 changes over time during longitudinal observation. The question to be answered in a specifically designed research study is: What is the impact of the baseline miRNA-21 level on cardiovascular outcomes? These are obligatory prerequisites to use miRNA-21 as a specific biomarker. Declarations Conflict of interest The authors declare no conflict of interest. Funding A.R.T. has received grants BNW-1-171/K/3/K, and PCN-1-235/K/2/K from the Medical University of Silesia J.C. has received grant 58/TALENTYJUTRA_E1/2022 from Empiria i Wiedza Foundation. Author Contribution J.C., S.W., M.K., M.J., M.S., and P.W. enrolled patients, performed morphometric analyses, completed the database, and assisted with miRNA-21 assessment. D.H. and J.S. performed, analyzed, and interpreted the miRNA-21 assessment. B.P.C. and M.M. edited the manuscript. A.R.T. conceived, directed, and sponsored the work throughout all levels of development. J.C. and A.R.T. drafted the manuscript. All the authors discussed the results and approved the manuscript. Data Availability The datasets analyzed during the current study are available from the corresponding author on reasonable request References Fried, L. P. et al. Frailty in older adults: evidence for a phenotype. J. Gerontol. Biol. Sci. Med. Sci. 56 (3), M146–M156 (2001). Epub 2001/03/17. PubMed PMID: 11253156. Rockwood, K. et al. A global clinical measure of fitness and frailty in elderly people. CMAJ 173 (5), 489–495. 10.1503/cmaj.050051 (2005). PubMed PMID: 16129869; PubMed Central PMCID: PMC1188185. Gu, S. Z. et al. Coronary artery lesion phenotype in frail older patients with non-ST-elevation acute coronary syndrome undergoing invasive care. EuroIntervention 15 (3), e261–e8. 10.4244/eij-d-18-00848 (2019). Kanenawa, K. et al. Frailty and Bleeding After Percutaneous Coronary Intervention. Am J Cardiol. ;148:22 – 9. Epub 20210303. (2021). 10.1016/j.amjcard.2021.02 .041. PubMed PMID: 33667444. Kwok, C. S. et al. Relation of Frailty to Outcomes in Percutaneous Coronary Intervention. Cardiovasc. Revasc Med. 21 (7), 811–818 (2020). PubMed PMID: 31761641. Christensen, D. M. et al. Frailty, Treatments, and Outcomes in Older Patients With Myocardial Infarction: A Nationwide Registry‐Based Study. J. Am. Heart Association . 12 (14), e030561. 10.1161/JAHA.123.030561 (2023). Ekerstad, N. et al. Frailty is independently associated with short-term outcomes for elderly patients with non-ST-segment elevation myocardial infarction. Circulation 124 (22), 2397–2404. 10.1161/CIRCULATIONAHA.111.025452 (2011). Epub 20111107. Murali-Krishnan, R. et al. Impact of frailty on outcomes after percutaneous coronary intervention: a prospective cohort study. Open. Heart . 2 (1), e000294. 10.1136/openhrt-2015-000294 (2015). Ratcovich, H. et al. Prevalence and Impact of Frailty in Patients ≥ 70 Years Old with Acute Coronary Syndrome Referred for Coronary Angiography. Cardiology 149 (1), 1–13 (2024). Epub 20231110. doi: 10.1159/000535116. PubMed PMID: 37952523; PubMed Central PMCID: PMC10836927. Afilalo, J. et al. Frailty Assessment in the Cardiovascular Care of Older Adults. J. Am. Coll. Cardiol. 63 (8), 747–762. https://doi.org/10.1016/j.jacc.2013.09.070 (2014). Cacciatore, S. et al. Management of Coronary Artery Disease in Older Adults: Recent Advances and Gaps in Evidence. J Clin Med. ;12(16). Epub 20230811. (2023). 10.3390/jcm12165233 . PubMed PMID: 37629275; PubMed Central PMCID: PMC10455820. García-Giménez, J. L. et al. Implementing Precision Medicine in Human Frailty through Epigenetic Biomarkers. Int J Environ Res Public Health. ;18(4). Epub 20210215. (2021). 10.3390/ijerph18041883 . PubMed PMID: 33672064; PubMed Central PMCID: PMC7919465. Wawrzyniak, S. et al. Epigenetic Biomarkers of Cardiovascular Risk in Frail Patients—A Scope Review. Curr. Issues. Mol. Biol. 47 (6), 422. 10.3390/cimb47060422 (2025). PubMed PMID:. Ramos, J. et al. Circulating miRNAs are associated with frailty and ST-elevation myocardial infarction pathways. Arch. Gerontol. Geriatr. 106 , 104870. 10.1016/j.archger.2022.104870 (2023). Epub 20221119. Zhang, Y., Liu, Y. J., Liu, T., Zhang, H. & Yang, S. J. Plasma microRNA-21 is a potential diagnostic biomarker of acute myocardial infarction. Eur. Rev. Med. Pharmacol. Sci. 20 (2), 323–329 (2016). PubMed PMID: 26875904. Woloszyn-Horak, E. et al. Frailty syndrome in daily practice of interventional cardiology ward-rationale and design of the FRAPICA trial: A STROBE-compliant prospective observational study. Med. (Baltim). 99 (5), e18935 (2020). 0000000000018935. PubMed PMID: 32000408; PubMed Central PMCID: PMC7004665. Jackson, A. S. & Pollock, M. L. Practical Assessment of Body Composition. Physician Sportsmed. 13 (5), 76–90 (1985). 11708790. PubMed PMID: 27463295. Olivieri, F. et al. Age-related differences in the expression of circulating microRNAs: miR-21 as a new circulating marker of inflammaging. Mech. Ageing Dev. 133 (11–12), 675–685. 10.1016/j.mad.2012.09 (2012). Epub 20121002. Xin, C., He, W., Sun, X., Li, M. & Wang, H. The Association of Micro-RNA 21 and Hypertension: A Meta-Analysis. Global Heart . 10.5334/gh.1325 (2024). Ji, R. et al. MicroRNA expression signature and antisense-mediated depletion reveal an essential role of MicroRNA in vascular neointimal lesion formation. Circul. Res. 100 (11), 1579–1588. 10.1161/circresaha.106.141986 (2007). Epub 20070503. Roggli, E. et al. Involvement of microRNAs in the cytotoxic effects exerted by proinflammatory cytokines on pancreatic beta-cells. Diabetes 59 (4), 978–986. 10.2337/db09-0881 (2010). Epub 20100119. Lawan, A. et al. Skeletal Muscle-Specific Deletion of MKP-1 Reveals a p38 MAPK/JNK/Akt Signaling Node That Regulates Obesity-Induced Insulin Resistance. Diabetes ; 67 (4):624–635. (2018). Epub 20180109. doi: 10.2337/db17-0826 . PubMed PMID: 29317435; PubMed Central PMCID: PMC5860856. Seyhan, A. A. et al. Pancreas-enriched miRNAs are altered in the circulation of subjects with diabetes: a pilot cross-sectional study. Sci. Rep. 6 , 31479. 10.1038/srep31479 (2016). Epub 20160825. Nunez Lopez, Y. O., Garufi, G. & Seyhan, A. A. Altered levels of circulating cytokines and microRNAs in lean and obese individuals with prediabetes and type 2 diabetes. Mol Biosyst. ;13(1):106 – 21. (2016). 10.1039/c6mb00596a . PubMed PMID: 27869909. Olivieri, F. et al. MiR-21-5p and miR-126a-3p levels in plasma and circulating angiogenic cells: relationship with type 2 diabetes complications. Oncotarget 6 (34), 35372–35382. 10.18632/oncotarget.6164 (2015). PubMed PMID: 26498351; PubMed Central PMCID: PMC4742111. Ghorbani, S. et al. Decreased serum microRNA-21 level is associated with obesity in healthy and type 2 diabetic subjects. Arch. Physiol. Biochem. 124 (4), 300–305 (2018). PubMed PMID: 29113498. Galenko, O. et al. The role of microRNAs in the development, regulation, and treatment of atrial fibrillation. Journal of interventional cardiac electrophysiology: an international journal of arrhythmias and pacing. ;55(3):297–305. Epub 20190103. (2019). 10.1007/s10840-018-0495-z . PubMed PMID: 30607665. McManus, D. D. et al. Plasma microRNAs are associated with atrial fibrillation and change after catheter ablation (the miRhythm study). Heart rhythm: official J. Heart Rhythm Soc. 12 (1), 3–10 (2015). PubMed PMID: 25257092; PubMed Central PMCID: PMC4277933. Cardin, S. et al. Role for MicroRNA-21 in atrial profibrillatory fibrotic remodeling associated with experimental postinfarction heart failure. Circ. Arrhythm. Electrophysiol. 5 (5), 1027–1035. 10.1161/circep.112.973214 (2012). Epub 20120826. He, X. et al. Rapid atrial pacing induces myocardial fibrosis by down-regulating Smad7 via microRNA-21 in rabbit. Heart vessels . 31 (10), 1696–1708. 10.1007/s00380-016-0808-z (2016). Epub 20160311. Huang, Z. et al. Signal Transducer and Activator of Transcription 3/MicroRNA-21 Feedback Loop Contributes to Atrial Fibrillation by Promoting Atrial Fibrosis in a Rat Sterile Pericarditis Model. Circ. Arrhythm. Electrophysiol. 9 (7), e003396. 10.1161/circep.115.003396 (2016). PubMed PMID: 27406600; PubMed Central PMCID: PMC4956678. Yang, P., Dong, X. & Zhang, Y. MicroRNA profiles in plasma samples from young metabolically healthy obese patients and miRNA-21 are associated with diastolic dysfunction via TGF-β1/Smad pathway. J. Clin. Lab. Anal. 34 (6), e23246. 10.1002/jcla.23246 (2020). Epub 20200228. Fontanella, R. A. et al. Adiponectin Related Vascular and Cardiac Benefits in Obesity: Is There a Role for an Epigenetically Regulated Mechanism? Front. Cardiovasc. Med. 8 , 768026 (2021). PubMed PMID: 34869683; PubMed Central PMCID: PMC8639875. Seeger, T., Fischer, A., Muhly-Reinholz, M., Zeiher, A. M. & Dimmeler, S. Long-term inhibition of miR-21 leads to reduction of obesity in db/db mice. Obes. (Silver Spring Md) . 22 (11), 2352–2360. 10.1002/oby.20852 (2014). Epub 20140820. Korzonek-Szlacheta, I. et al. The Association between Circulating Cytokines and Body Composition in Frail Patients with Cardiovascular Disease. Nutrients 16 (8), 1227. 10.3390/nu16081227 (2024). PubMed PMID:. Zhu, J. et al. Exosomes from nicotine-stimulated macrophages accelerate atherosclerosis through miR-21-3p/PTEN-mediated VSMC migration and proliferation. Theranostics 9 (23), 6901–6919. 10.7150/thno.37357 (2019). Epub 20190921. Zhang, J. Y. et al. Circulating MiRNA biomarkers serve as a fingerprint for diabetic atherosclerosis. Am. J. Transl Res. 8 (6), 2650–2658 (2016). Epub 20160615. PubMed PMID: 27398148; PubMed Central PMCID: PMC4931159. Parthenakis, F. et al. Low Levels of MicroRNA-21 Are a Marker of Reduced Arterial Stiffness in Well-Controlled Hypertension. J. Clin. Hypertens. (Greenwich) . 19 (3), 235–240. 10.1111/jch.12900 (2017). Epub 20160822. van Rooij, E. et al. Dysregulation of microRNAs after myocardial infarction reveals a role of miR-29 in cardiac fibrosis. Proc. Natl. Acad. Sci. U.S.A. 105 (35), 13027–13032. 10.1073/pnas.0805038105 (2008). Epub 20080822. Wang, K., Li, K., Li, Z. & Yan, X. Circulating miRNA-21 as early potential diagnostic biomarker for acute myocardial infarction: a meta-analysis. Front. Cardiovasc. Med. 11 , 1330884. 10.3389/fcvm.2024.1330884 (2024). Epub 20240822. Mohammed, A. et al. Long non-coding RNA NBAT1, TUG1, miRNA-335, and miRNA-21 as potential biomarkers for acute ischemic stroke and their possible correlation to thyroid hormones. Front. Mol. Biosci. 9 , 914506 (2022). PubMed PMID: 36250025; PubMed Central PMCID: PMC9565477. Qu, J. et al. Causal relationship between frailty and chronic obstructive pulmonary disease or asthma: A two sample bidirectional Mendelian randomization study. Arch. Gerontol. Geriatr. 118 , 105310. 10.1016/j.archger.2023.105310 (2024). Epub 20231212. Verduri, A., Clini, E., Carter, B. & Hewitt, J. Impact of Frailty on Symptom Burden in Chronic Obstructive Pulmonary Disease. J Clin Med. ;13(4). Epub 20240208. (2024). 10.3390/jcm13040984 . PubMed PMID: 38398298; PubMed Central PMCID: PMC10889165. ElKashef, S., Ahmad, S. E., Soliman, Y. M. A. & Mostafa, M. S. Role of microRNA-21 and microRNA-155 as biomarkers for bronchial asthma. Innate Immun. 27 (1), 61–69 (2021). Epub 20200127. doi: 10.1177/1753425920901563. PubMed PMID: 31986951; PubMed Central PMCID: PMC7780351. Lu, L., Zheng, G. & Lin, Y. Blood miR-21 and miR-26 tailor a good diagnostic model for childhood asthma. Cell Mol Biol (Noisy-le-grand). ; 69 (12):33–37. Epub 20231130. (2023). 10.14715/cmb/2023.69 .12.6. PubMed PMID: 38063121. Yang, S. et al. miR-21 regulates chronic hypoxia-induced pulmonary vascular remodeling. Am. J. Physiol. Lung Cell. Mol. Physiol. 302 (6), L521–L529. 10.1152/ajplung.00316.2011 (2012). Epub 20120106. Lv, W. et al. Therapeutic potential of microRNAs for the treatment of renal fibrosis and CKD. Physiol. Genomics . 50 (1), 20–34. 10.1152/physiolgenomics.00039.2017 (2018). Epub 20171110. Chau, B. N. et al. MicroRNA-21 promotes fibrosis of the kidney by silencing metabolic pathways. Sci. Transl Med. 4 (121), 121ra18. 10.1126/scitranslmed.3003205 (2012). PubMed PMID: 22344686; PubMed Central PMCID: PMC3672221. Wang, J. et al. Effect of miR-21 on renal fibrosis by regulating MMP-9 and TIMP1 in kk-ay diabetic nephropathy mice. Cell. Biochem. Biophys. 67 (2), 537–546. 10.1007/s12013-013-9539-2 (2013). PubMed PMID: 23443810. Zhong, X. et al. miR-21 is a key therapeutic target for renal injury in a mouse model of type 2 diabetes. Diabetologia. ;56(3):663 – 74. Epub 20130105. (2013). 10.1007/s00125-012-2804-x . PubMed PMID: 23292313. Markou, A., Zavridou, M. & Lianidou, E. S. miRNA-21 as a novel therapeutic target in lung cancer. Lung Cancer (Auckl) . 7 , 19–27 (2016). Epub 20160302. doi: 10.2147/lctt.S60341. PubMed PMID: 28210157; PubMed Central PMCID: PMC5310696. Resnick, K. E. et al. The detection of differentially expressed microRNAs from the serum of ovarian cancer patients using a novel real-time PCR platform. Gynecol. Oncol. 112 (1), 55–59 (2009). 036. PubMed PMID: 18954897. Sales, A. C. V. et al. Mirna21 Expression in the Breast Cancer Tumor Tissue is Independent of Neoadjuvant Chemotherapy. Breast Cancer (Dove Med. Press) . 12 , 141–151. 10.2147/bctt.S269519 (2020). Epub 20201008. Kojima, G., Taniguchi, Y., Iliffe, S., Jivraj, S. & Walters, K. Transitions between frailty states among community-dwelling older people: A systematic review and meta-analysis. Ageing Res Rev. ;50:81 – 8. Epub 20190116. (2019). 10.1016/j.arr.2019.01.010 . PubMed PMID: 30659942. Additional Declarations No competing interests reported. Supplementary Files Onlinefloatimage1.png Visual abstract Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 10 Feb, 2026 Reviews received at journal 29 Jan, 2026 Reviewers agreed at journal 16 Jan, 2026 Reviewers invited by journal 16 Jan, 2026 Editor assigned by journal 18 Nov, 2025 Editor invited by journal 31 Jul, 2025 Submission checks completed at journal 26 Jul, 2025 First submitted to journal 26 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7133943","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":546773413,"identity":"9b69d1d8-bf1b-4944-8c20-d26ffcfc5a31","order_by":0,"name":"Julia Cieśla","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Cieśla","suffix":""},{"id":546773414,"identity":"37b7e046-4fbc-4db0-8f82-e929fe1c497b","order_by":1,"name":"Stanisław Wawrzyniak","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Stanisław","middleName":"","lastName":"Wawrzyniak","suffix":""},{"id":546773415,"identity":"26e134bc-494c-4bc0-b24b-3dd90b9e4646","order_by":2,"name":"Michał Krawiec","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Michał","middleName":"","lastName":"Krawiec","suffix":""},{"id":546773416,"identity":"87ab0369-e58d-49e9-91f8-c4fa0ee2056d","order_by":3,"name":"Michał Janik","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Michał","middleName":"","lastName":"Janik","suffix":""},{"id":546773417,"identity":"a14ffa43-6a5b-4292-b12d-ebdaa185cd54","order_by":4,"name":"Marcin Schulz","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Marcin","middleName":"","lastName":"Schulz","suffix":""},{"id":546773418,"identity":"732a2184-0f9c-4ccd-b65f-7a68df403385","order_by":5,"name":"Paweł Wojciechowski","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Paweł","middleName":"","lastName":"Wojciechowski","suffix":""},{"id":546773419,"identity":"73cc4d83-c129-4418-a83e-35dfa8c0001b","order_by":6,"name":"Brygida Przywara-Chowaniec","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Brygida","middleName":"","lastName":"Przywara-Chowaniec","suffix":""},{"id":546773420,"identity":"d731e32f-7ddc-4224-b401-3b3920981d28","order_by":7,"name":"Dorota Hudy","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Dorota","middleName":"","lastName":"Hudy","suffix":""},{"id":546773421,"identity":"6d3a093e-2419-4fa3-a2a2-e9cb6ead94b1","order_by":8,"name":"Joanna Katarzyna Strzelczyk","email":"","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":false,"prefix":"","firstName":"Joanna","middleName":"Katarzyna","lastName":"Strzelczyk","suffix":""},{"id":546773422,"identity":"80b33a17-5d02-48d3-957f-80d02f4a85b5","order_by":9,"name":"Michał M. Masternak","email":"","orcid":"","institution":"University of Central Florida","correspondingAuthor":false,"prefix":"","firstName":"Michał","middleName":"M.","lastName":"Masternak","suffix":""},{"id":546773423,"identity":"7bdbc34e-da09-459e-bf0d-368595eef7cb","order_by":10,"name":"Andrzej R. Tomasik","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYPACCQN+CIMZhBvwK2aDapFsgGthJEoLg4HBAWK18M9vPrrhxx8LY+PzZ0w3MFRYJzZIN+LXInGMLe1mb5uEmdmNHLMbDGfSExtkDhJw2DEesxu8DRI2ZjeADMa2w4kNEon4tcgDtdz880fCxrj/DFDLPyK0GAC13OZhkzAzYAA6jLGBCC2Gx9LSbsu2SRhL3Egru5FwLN24jZBf5A4fPnbzzZ86w/7+w9tufKixlu2Xbj6AVwsqSABiNgkSNEABGVpGwSgYBaNgeAMARgdJB0iEm7EAAAAASUVORK5CYII=","orcid":"","institution":"Medical University of Silesia","correspondingAuthor":true,"prefix":"","firstName":"Andrzej","middleName":"R.","lastName":"Tomasik","suffix":""}],"badges":[],"createdAt":"2025-07-15 20:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7133943/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7133943/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96288348,"identity":"8dd40ff6-5df6-4d2a-82da-47a342a07051","added_by":"auto","created_at":"2025-11-19 12:11:38","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1687100,"visible":true,"origin":"","legend":"","description":"","filename":"mRNA21revisionV1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/57c76cb92b24c2c371451dbf.docx"},{"id":96364199,"identity":"b88f0c5d-9d49-48b6-b398-0c8d0ad10ca5","added_by":"auto","created_at":"2025-11-20 10:09:01","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11245,"visible":true,"origin":"","legend":"","description":"","filename":"8c7c1b5ac025402c9052c2df5d43a416.json","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/ab49abbb1b3b47931d479825.json"},{"id":96365055,"identity":"25047ca4-55e2-4f79-a693-44925de62c23","added_by":"auto","created_at":"2025-11-20 10:09:57","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":139811,"visible":true,"origin":"","legend":"","description":"","filename":"8c7c1b5ac025402c9052c2df5d43a4161enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/2fcc84773d1663c17d184703.xml"},{"id":96288349,"identity":"470bba35-9e94-46ac-b9fb-61e696688e77","added_by":"auto","created_at":"2025-11-19 12:11:38","extension":"jpeg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":165768,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/42cb4e0056bcf2b6b3ed70b4.jpeg"},{"id":96288345,"identity":"42d7d99c-733f-4c79-94d0-6667c2b68abc","added_by":"auto","created_at":"2025-11-19 12:11:38","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84753,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/71abaac6e2ca51182a335aef.png"},{"id":96288350,"identity":"7d3fa2c1-60b9-4368-9ad4-4b7d45a38bd1","added_by":"auto","created_at":"2025-11-19 12:11:38","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":137460,"visible":true,"origin":"","legend":"","description":"","filename":"8c7c1b5ac025402c9052c2df5d43a4161structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/83863070714a6d64b2ddf3d4.xml"},{"id":96288351,"identity":"32169838-3407-4c59-adc6-512a356fbf3c","added_by":"auto","created_at":"2025-11-19 12:11:38","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152930,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/a3480ac166d0ab674a0e64e9.html"},{"id":96288343,"identity":"63dffdf2-9c17-4cfd-ae00-26422c3de1d1","added_by":"auto","created_at":"2025-11-19 12:11:38","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":362365,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/01b828812a109766027049b0.jpeg"},{"id":96369228,"identity":"0067a83f-ae90-4c06-80ea-a86018541f03","added_by":"auto","created_at":"2025-11-20 10:20:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1466405,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/6defbe62-dab3-4e0d-b9ce-8216744cbade.pdf"},{"id":96288346,"identity":"693f71d8-0314-4343-8bba-b4041e9ffb74","added_by":"auto","created_at":"2025-11-19 12:11:38","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33142,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisual abstract\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7133943/v1/159e6669beb8939a07e9f954.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Lower serum level of miRNA-21 may be considered as a comorbidity-independent characteristic of frailty in cardiovascular patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFrailty syndrome is a clinical condition characterized by a decline in physiological reserves, increased vulnerability to stressors, and an increased risk of adverse health outcomes. Fried et al. have described frailty as the presence of at least three out of five key criteria: exhaustion, weakness, slowness, unintentional weight loss, and low physical activity (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). These features reflect a progressive deterioration in physical and functional capacities, often leading to disability, hospitalization, and mortality (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe incidence of cardiovascular diseases (CVD) increases with the progression from robust to frail status, characterized by the development of frailty (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Frail CVD patients have a significantly higher comorbid burden, angiographic disease severity, and more frequently observed highly vulnerable thin cap fibroatheroma in intravascular ultrasound examination (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). These features translate into increased risk and worse procedural outcomes. Frail patients treated with percutaneous coronary intervention, irrespective of primary diagnosis, e.g., acute or chronic coronary syndrome, have an increased periprocedural bleeding risk (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), vascular injury risk (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), increased risk of stroke or transient ischemic attack (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), and increased short-, medium-, and long-term mortality risk (\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Just over half of frail patients with acute myocardial infarction are scheduled for angiography and percutaneous coronary intervention (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFollowing Afilalo et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), we lack optimized resource allocation, which would enable frail patients to avoid costly but futile interventions. Eventually, frailty should not be viewed as a reason to withhold care, but rather to deliver it in a more patient-oriented manner (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). To overcome the challenge of frailty, an individualized patient approach involves implementing precision medicine by utilizing biological biomarkers to enhance diagnostic accuracy and optimize management. Identifying biomarkers would allow cardiologists to predict the functional trajectories of older adults at preclinical stages (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Precision medicine was defined by the National Research Council\u0026rsquo;s Toward Precision Medicine in 2008 as: \u0026ldquo;The tailoring of medical treatment to the individual characteristics of each patient \u0026hellip; to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment. Preventive and therapeutic interventions can then be concentrated on those patients who will benefit, sparing expense and side effects for those who will not\u0026rdquo;. Our recent literature search identified the GrimAge epigenetic clock, miRNA-146a, and miRNA-21 as potential biomarkers of frailty (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). miRNA-21 regulates pathways involved in inflammation and fibrosis, which are exacerbated in conditions such as coronary artery disease and myocardial infarction (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Given the overlap between inflammatory pathways in frailty and cardiovascular disease, miRNA21 may serve as a valuable marker for assessing the severity of frailty and predicting patient outcomes, particularly in invasive cardiovascular treatments. The elevated levels of miRNA21 seen after acute MI, combined with its role in inflammation and fibrosis, suggest that it could be a valuable marker for both frailty and cardiovascular disease severity (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This could help guide treatment decisions and improve patient outcomes, particularly in cases requiring more aggressive interventions.\u003c/p\u003e\u003cp\u003eThe study aimed to assess serum levels of miRNA-21 in frail patients, compare them to those in pre-frail and robust counterparts, and evaluate miRNA-21 levels in relation to comorbidities and phenotypic frailty features.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003ea.\u0026nbsp; \u0026nbsp;Study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is the ancillary sub-study of the FRAPICA trial (ClinicalTrials.gov NCT04035486,\u0026nbsp;\u003cstrong\u003eregistered 06/07/20217\u003c/strong\u003e). The design and rationale of the FRAPICA study have been described previously (16). In brief, the study\u0026apos;s inclusion criteria were age 65 years or older and informed consent to participate in the project. We enrolled 261 consecutive eligible patients in this analysis, who were admitted to the 2nd Department of Cardiology in Zabrze between February 2023 and December 2023. Patients were assessed for the severity of frailty syndrome according to the Fried phenotype criteria (1). Respiratory parameters like peak expiratory flow (PEF) and forced expiratory volume in 1 second (FEV1) were measured using an Asmaplan 1 peak flow meter (Vitalograph, Ireland). Patients\u0026rsquo; height and weight were measured with a Seca 287 measuring station (Seca, Hamburg, Germany). Fat-free body mass (FFBM) was measured using Harpenden\u0026rsquo;s skinfold caliper and Baty\u0026rsquo;s body assessment software v. 17 (Baty International Ltd., Burgess Hill, UK) with a three-site Jackson/Pollock algorithm (17). For practical purposes, we have cross-checked the aforementioned method with Seca mBCA 528 bioimpedance analysis in 20 subjects (10 volunteers and 10 FRAPICA patients) aged 22\u0026ndash;82 years. The Bland-Altman analysis revealed a mean difference of -0.062 kg; all results fell within the 95% confidence intervals (data not shown). Patients were drawn for fasting blood, and serum was prepared. Serum samples were stored at -81℃ until analysis. Clinical and laboratory data were retrieved from patients\u0026rsquo; electronic medical records. The study was conducted under the Declaration of Helsinki and approved by the Ethics Committee of the Medical University of Silesia (3 Oct 2017 (KNW/0022/KB1/39/I/17)); (8 Feb 2022 (PCN/CBN/0022/KB1/39/II/17/22)). Informed consent was obtained from all the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u0026nbsp; \u0026nbsp;Frailty syndrome evaluation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo diagnose the degree of frailty, each patient was assessed using the Frailty Phenotype Score using the following criteria:\u003c/p\u003e\n\u003cp\u003e\u0026middot; Slowness\u0026mdash;reduced gait speed at a distance of 5m at the usual pace.\u0026nbsp;The patient must repeat the test three times, and the results are averaged. If a patient walks for more than 6 seconds, the criterion is positive.\u003c/p\u003e\n\u003cp\u003e\u0026middot; Weakness is assessed with a maximal handgrip strength test. It is carried out in the dominant arm. We use an electronic hand dynamometer EH101 (VETEK AB, Sweden). A patient must repeat the measurement three times, and the maximal value is recorded. The test is positive for frailty when strength is lower than 20 kg for women and 30 kg for men.\u003c/p\u003e\n\u003cp\u003e\u0026middot; The Minnesota Leisure Time Activity questionnaire assesses low physical activity. The result is positive when calorie expenditure per week is lower than 270 kcal/week in women and \u0026lt;383 kcal/week in men. We have prepared a Microsoft Excel-based template for rapid questioning and easy calculation of all activities and respective calorie expenditures. We are assessing physical activity from the past 12 months.\u003c/p\u003e\n\u003cp\u003e\u0026middot; Exhaustion\u0026mdash;self-reported by a patient. It is evaluated by the answer to 2 questions from the Center for Epidemiologic Studies Depression Scale Revised (CESD-R) scale. The patient has to answer the following questions: \u0026ldquo;How often in the past week did you feel like everything you did was an effort? How often did you feel like you could not get going in the past week?\u0026rdquo; The possible answers are \u0026ldquo;often\u0026rdquo; (\u0026ge;3 days) or \u0026ldquo;not often\u0026rdquo; when the feeling is present in 0 to 2 days. A positive answer is when the patient says \u0026ldquo;often.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u0026middot; Weight loss exceeding 10 pounds (approximately 4.5 kg) unintentionally in the past year.\u003c/p\u003e\n\u003cp\u003eWe recognize frailty if three or more out of five features are met. Patients with 1 or 2 traits present are classified as pre-frail. Patients who did not meet any of the requirements are marked as robust.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec.\u0026nbsp; \u0026nbsp;MiRNA-21 assays\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study used hsa-miR-21-5p miREIA (BioVendor, Czech Republic) - an enzyme immunoassay for the quantitative measurement of human microRNA-21-5p. The samples were analyzed in parallel using a cel-miR-39-3p miREIA assay kit (BioVendor, Czech Republic), and then miRNA-21 expression was normalized with the extraction coefficient. \u0026nbsp;Cell-free miRNA from serum was isolated with RNA Isolation Kit Plasma/Serum (BioVendor, Czech Republic). After lysis, the spike-in from the cel-miR-39-3p miREIA assay kit was added to each sample, with a final concentration of spike-in of 1000 amol/\u0026mu;l. All samples were kept at -81℃ until further analysis. For cel-miR39-3p measurements, 20 \u0026mu;l of 50x diluted RNA sample was used and for hsa-miR-21-5p 20 \u0026mu;l of undiluted RNA sample was used. The miRNA-21 levels analyzed and presented are the normalized values.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed.\u0026nbsp; \u0026nbsp;Statistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter analyzing the data for normality of distribution and equality of variances (Shapiro-Wilk test), we employed both parametric and non-parametric statistical methods for comparing the robust, prefrail, and frail groups. We have used ANOVA for multiple group comparisons of normally distributed quantitative data. Any significances disclosed in the analysis of variance were checked with Student\u0026rsquo;s t-test. We have used the Kruskal-Wallis ANOVA to compare the levels of miRNA-21 across multiple groups, and the Mann-Whitney U test to compare two groups. The Chi-squared test with Yates\u0026apos; correction for comparing frequency data. We have presented data as means and standard deviations, as medians and interquartile ranges, or as frequency data. Quantitative variables were correlated using the Spearman test. Statistical significance was considered at p-values \u0026lt; 0.05.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ee. \u0026nbsp; Demographic and medical data\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 261 patients recruited to the study, the majority were pre-frail patients (50%), followed by the robust patients \u0026nbsp;(36%), while 14% of patients were frail. The percentage of women increased from 23.6% (robust) to 48.6% (frail, P\u0026lt;0.01). The groups differed in terms of age, height, and lean body mass. Frail patients had the lowest height and FFBM values, as well as the highest mean age. There were no differences between the groups in terms of total body mass.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering eGFR, statistically significant differences were observed between the groups before coronary angiography, with the lowest values in patients with frailty. Considering the values of red blood cell count, hematocrit, and hemoglobin, statistically significant differences (p \u0026lt; 0.001) were noted, with the lowest values observed in patients with frailty. Strong statistical significance (p \u0026lt; 0.01) was also noted for respiratory parameters, including FEV1 and PEF. Clinical characteristics are presented in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 1. Patient demographics and clinical presentation.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRobust (n=93)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-frail (n=131)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrail (n=37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSignificance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71.24\u0026nbsp;\u0026plusmn;\u0026nbsp;5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73.52\u0026nbsp;\u0026plusmn;\u0026nbsp;5.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.00\u0026nbsp;\u0026plusmn;\u0026nbsp;6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen/women, n/n\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78/53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19/18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight, kg, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.33\u0026nbsp;\u0026plusmn;\u0026nbsp;14.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81.50\u0026nbsp;\u0026plusmn;\u0026nbsp;17.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.35\u0026nbsp;\u0026plusmn;\u0026nbsp;22.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight, cm, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e170.25 \u0026plusmn; 7.16\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e167.25 \u0026plusmn; 9.51\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e162.19\u0026nbsp;\u0026plusmn;\u0026nbsp;16.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI, kg/m2, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.10\u0026nbsp;\u0026plusmn;\u0026nbsp;4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.11 \u0026plusmn; 5.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.63\u0026nbsp;\u0026plusmn;\u0026nbsp;6.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFFBM, kg, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.66\u0026nbsp;\u0026plusmn;\u0026nbsp;9.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.00\u0026nbsp;\u0026plusmn;\u0026nbsp;11.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51.88\u0026nbsp;\u0026plusmn;\u0026nbsp;14.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine, \u0026micro;mol/l, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.65\u0026nbsp;\u0026plusmn;\u0026nbsp;18.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e93.90 \u0026plusmn; 59.73\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e87.35\u0026nbsp;\u0026plusmn;\u0026nbsp;59.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eeGFR, ml/min/m2, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e74.84\u0026nbsp;\u0026plusmn;\u0026nbsp;13.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68.12\u0026nbsp;\u0026plusmn;\u0026nbsp;19.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.38 \u0026plusmn; 16.46\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWBC, x 10\u003csup\u003e9\u003c/sup\u003e/l, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.39 \u0026plusmn; 2.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.37 \u0026plusmn; 2.38\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.21\u0026nbsp;\u0026plusmn;\u0026nbsp;2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC, mln/\u0026micro;l, X\u0026plusmn;SD\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.72\u0026nbsp;\u0026plusmn;\u0026nbsp;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.53 \u0026plusmn; 0.54\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.35 \u0026plusmn; 0.56\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHematocrit, %, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.56\u0026nbsp;\u0026plusmn;\u0026nbsp;3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.75\u0026nbsp;\u0026plusmn;\u0026nbsp;3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38.98\u0026nbsp;\u0026plusmn;\u0026nbsp;4.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemoglobin, g/dl, X\u0026plusmn;SD\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.32\u0026nbsp;\u0026plusmn;\u0026nbsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.51\u0026nbsp;\u0026plusmn;\u0026nbsp;1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.83\u0026nbsp;\u0026plusmn;\u0026nbsp;1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePLT, x 10\u003csup\u003e9\u003c/sup\u003e/l, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e209.62\u0026nbsp;\u0026plusmn;\u0026nbsp;51.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e218.97 \u0026plusmn; 66.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e227.91 \u0026plusmn; 51.97\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePEF, L/min, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e369.23\u0026nbsp;\u0026plusmn;\u0026nbsp;129.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e314.80 \u0026plusmn; 138.66\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e247.46 \u0026plusmn; 114.15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV1, L, X\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.10\u0026nbsp;\u0026plusmn;\u0026nbsp;0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.85 \u0026plusmn; 0.66\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.58\u0026nbsp;\u0026plusmn;\u0026nbsp;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable legend: BMI \u0026ndash; body mass index, FFBM \u0026ndash; fat-free body mass, eGFR \u0026ndash; estimated glomerular filtration rate, WBC \u0026ndash; white blood cells, RBC \u0026ndash; red blood cells, PLT \u0026ndash; platelets, PEF \u0026ndash; peak expiratory flow, FEV1 \u0026ndash; forced expiratory flow in 1 second\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef. \u0026nbsp; \u0026nbsp;Severity of frailty and mRNA21\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The median mRNA-21 concentration in the entire group was 0.0477 (0.0352-0.0658). The lowest value recorded was 0.0124 in the frail group, and the highest was 0.6141 in the pre-frail group. Concentration values are presented in Fig. 1. A statistically significant difference in mRNA-21 values (p\u0026lt;0.001) was observed between the groups, with the lowest values in the frail group. Multiple comparisons of p-values between groups revealed statistically significant differences between the frail and pre-frail groups (p = 0.000009) and the frail and robust groups (p = 0.000002). There are no differences between the pre-frail and robust groups in mRNA-21 values.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg. \u0026nbsp; Components of the frailty definition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most frequently observed trait of frailty syndrome was exhaustion (41% of patients) and decreased muscle strength (30% of patients). The strongest statistically significant differences in mRNA-21 concentration between groups with and without a specific frailty feature were observed for decreased muscle strength and decreased walking speed (p \u0026lt; 0.001). In the case of each trait, patients with the presence of the trait were characterized by lower miRNA-21 levels than those without the trait. The miRNA-21 serum levels, depending on individual frailty features, are presented in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 2. mRNA-21 concentration depending on the presence or absence of individual traits for the diagnosis of frailty syndrome\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"627\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrailty trait\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with specific frailty trait vs. all other patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian, IQR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExhaustion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e108 vs. 155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e0.0472 (0.0253-0.0511) vs. 0.0477 (0.0428-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight loss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e48 vs. 215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e0.0351 (0.0204-0.0477) vs. 0.0477 (0.0428-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecrease in walking speed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34 vs. 227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e0.0253 (0.0188-0.0477) vs. 0.0477 (0.0428-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecrease in muscle strength\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e79 vs. 182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e0.0467 (0.0253-0.0511) vs. 0.0477 (0.0428-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecrease in physical activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e33 vs. 228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003e0.0319 (0.0221-0.0477) vs. 0.0477 (0.0428-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eh. \u0026nbsp; Comorbidities\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the whole study group, the most common comorbidities were hypertension and hyperlipidemia (both 217 cases), diabetes (112 cases), and previous cancer (88 cases). Most patients had not undergone percutaneous coronary intervention during previous hospitalizations (132 people vs. 127 people). No differences in mRNA-21 concentrations were observed between patients with specific comorbidities and other patients. The list of comorbidities and respective miRNA-21 serum levels is presented in the table below (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 3. mRNA-21 concentration depending on the presence or absence of analyzed comorbidities\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with specific comorbidity vs. all other patients\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian, IQR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e42 vs. 217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0467 (0.0351-0.0511) vs. 0.0477 (0.0352-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e146 vs. 112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351-0.0511) vs. 0.0477 (0.0352-0.0494)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHyperlipidemia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e42 vs. 217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0253-0.0526) vs. 0.0477 (0.0412-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke/TIA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e231 vs. 27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0418-0.0511) vs. 0.0477 (0.0221-0.0526)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeripheral artery disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e217 vs. 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0417-0.0511) vs. 0.0467 (0.0253-0.0477)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtrial fibrillation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e188 vs. 70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351- 0.0511) vs. 0.0477 (0.0417-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e241 vs. 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351- 0.0511) vs. 0.0477 (0.0253-0.0526)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsthma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e240 vs. 19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351-0.0511) vs. 0.0477 (0.0253-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRenal failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e232 vs. 27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351-0.0511) vs. 0.0467 (0.0253-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e225 vs. 34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0423-0.0511) vs. 0.0466 (0.0253-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e171 vs. 88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351-0.0511) vs. 0.0477 (0.0417-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e177 vs. 82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0379-0.0511) vs. 0.0467 (0.0319- 0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e132 vs. 127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351-0.0511) vs. 0.0477 (0.0351-0.0511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCABG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e220 vs. 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e0.0477 (0.0351-0.0511) vs. 0.0477 (0.0428- 0.0477)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable legend: TIA \u0026ndash; transient ischemic attack, COPD \u0026ndash; chronic obstructive pulmonary disease, AMI \u0026ndash; history of acute myocardial infarction, PCI \u0026ndash; history of percutaneous coronary intervention, CABG \u0026ndash; history of coronary artery bypass grafting\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ei. \u0026nbsp; \u0026nbsp;Correlations of mRNA-21 with quantitative variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the relationship between the serum level of miRNA-21 and other factors, we calculated the correlation between its level and quantitative variables in the entire enrolled population. Significant positive correlations were found for weight, fat-free body mass, hemoglobin concentration, peak expiratory flow, and forced expiratory flow in one second (Table 4)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 4. Correlations of mRNA-21 with quantitative variables\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpearman R\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFFBM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eeGFR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHematocrit\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemoglobin\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePEF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFEV1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable legend: BMI \u0026ndash; body mass index, fat-free body mass, eGFR \u0026ndash; estimated glomerular filtration rate, PEF \u0026ndash; peak expiratory flow, FEV1 \u0026ndash; forced expiratory flow in one second\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe have found in our study that frail patients with cardiovascular diseases have significantly lower levels of circulating miRNA-21 in their blood compared to their non-frail counterparts. The analysis indicated that the miRNA-21 level is substantially lower in patients with an individual phenotype characterized by frailty, in contrast to all other patients. However, the comorbidities do not impact the level of miRNA-21 in our patient population. To our knowledge, previously published papers on miRNA-21 have not addressed the issue of frailty, but they provide insightful information on its role in human pathology. Olivieri et al. have reported that miRNA-21 levels increase with advancing age (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Other studies have also shown that post-acute coronary syndrome (ACS) patients have increased values of miRNA-21 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). It rises more sharply in cases of acute myocardial infarction than in chronic coronary syndrome. In our study, no such relationship was found.\u003c/p\u003e\u003cp\u003eA meta-analysis by Xin et al. demonstrated that patients with hypertension exhibit elevated levels of miRNA-21 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Animal models suggest this may be linked to the proliferation of vascular smooth muscle cells (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In the present study, no association was found between miRNA-21 levels and a diagnosis of diabetes, although molecular studies suggest increased miRNA-21 expression in beta cells exposed to pro-inflammatory cytokines, leading to dysfunction in insulin secretion (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Additionally, miRNA-21 may play a role in modulating the Phosphatase and Tensin Homolog in insulin-sensitive skeletal muscles, potentially resulting in improved glucose tolerance (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Studies by Seyhan et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) found a correlation between elevated serum miRNA-21 levels and diabetes diagnosis, as well as glucose intolerance and prediabetes. Similarly, other researchers observed higher circulating miRNA2-1 levels in patients with type 2 diabetes (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In contrast, Ghorbani et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) found no such correlation, suggesting instead that lower serum miRNA-21 levels are associated with hyperinsulinemia and insulin resistance.\u003c/p\u003e\u003cp\u003eGalenko et al. associated reduced miRNA-21 levels with atrial fibrillation but found no differences based on the type of the condition (paroxysmal or persistent) or recurrence status. The study noted a higher incidence of atrial fibrillation in individuals with hypertension, who would typically exhibit increased miRNA-21 levels (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Conversely, McManus et al. confirmed a link between lower miRNA-21 levels in both tissues and serum among patients with atrial fibrillation, with significantly lower miRNA-21 levels in persistent versus paroxysmal atrial fibrillation (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Other studies, including animal models, suggest that decreased atrial miRNA-21 expression is associated with a lower risk of fibrosis and atrial fibrillation, particularly after myocardial infarction or cardiac surgery (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This effect may be due to miRNA-21 inhibiting sprouty homologue 1 (Sprouty1 or Spry1), a negative regulator of the ERK/mitogen-activated protein kinase pathway. Reduced Sprouty1 levels result in hyperphosphorylation of ERK and p38 mitogen-activated protein kinases, leading to increased procollagen expression. This positions miRNA21 as a potential therapeutic target in atrial fibrillation treatment (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Yang et al.\u0026lsquo;s research, a positive correlation was observed between blood miRNA21 levels and obesity, measured by body mass index (BMI), waist circumference, hip circumference, and waist-to-hip ratio (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Another study found no significant difference in miRNA-21 levels between obese and non-obese patients, although miRNA-21 levels were positively correlated with body fat percentage (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Anti-miRNA21 treatments were found to be effective in reducing body weight in a murine model (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Although this study did not directly assess obesity using these metrics, Spearman\u0026rsquo;s analysis revealed a significant association between body weight and miRNA21 levels, alongside a correlation between reduced lean body mass (but not increased fat mass) and miRNA21, potentially linked to sarcopenia associated with frailty syndrome (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAtherosclerosis and its complications have drawn considerable interest among researchers studying miRNA-21. Evidence suggests that miRNA-21 may contribute to the development of atherosclerosis (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), with elevated levels observed in patients with atherosclerosis. In patients with well-controlled hypertension, low miRNA-21 levels in peripheral blood mononuclear cells are associated with reduced arterial stiffness (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e\u003cp\u003emiRNA-21 appears particularly relevant in acute myocardial infarction (AMI). miRNA-21 shows increased expression in the infarct border zone (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Research by Zhang et al. indicated that serum miRNA-21 levels are significantly higher in AMI patients compared to healthy individuals or those with angina pectoris, with miRNA-21 levels correlating with classic myocardial infarction markers\u0026mdash;creatine kinase (CK), creatine kinase-MB (CK-MB), and troponin I (cTnI) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The study also highlighted concerns over the release of miRNA-21 from various organs, potentially compromising biomarker specificity. Wang et al.\u0026rsquo;s meta-analysis found that circulating miRNA-21 levels in diagnosing AMI had a general sensitivity and specificity of 0.83 and 0.81, respectively, and noted its early appearance in peripheral blood compared to traditional AMI markers (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). miRNA-21 levels also rise in acute ischemic stroke (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePatients meeting frailty criteria had significantly lower PEF and FEV1 values compared to other patients. Respiratory disorders in frailty patients have been reported in earlier studies, with respiratory diseases (asthma and COPD) also predisposing individuals to frailty (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). This study further identified a correlation between miRNA-21 levels and respiratory dysfunction (PEF and FEV1 reduction), although no association was found with asthma or COPD diagnoses, possibly due to unconfirmed diagnoses or alternative causes of respiratory impairment. Previous studies have demonstrated a positive correlation between miRNA-21 levels and asthma (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). The association between COPD and miRNA-21 levels requires further research; however, animal models suggest that elevated miRNA-21 expression may mediate pulmonary vascular remodeling under prolonged hypoxia (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNo association was found between miRNA-21 levels and renal failure diagnosis in this study, nor did miRNA-21 predict renal events post-coronary angiography, despite significant pre-procedure eGFR differences among robust, pre-frail, and frail groups, and marginal differences in creatinine and eGFR post-procedure. These findings contrast with prior animal studies, which have shown elevated miRNA-21 levels in renal tissue in various renal diseases, including chronic kidney disease and diabetic nephropathy (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Murine studies suggest miRNA-21\u0026rsquo;s role in kidney disease may involve promoting renal fibrosis through pathways related to fatty acid and lipid oxidation (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e) and regulation of metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e), highlighting miRNA-21 inhibition as a potential therapeutic target for kidney diseases (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePrevious research has reported increased miRNA-21 expression in tumor tissues and serum; however, further studies are needed to assess miRNA-21 levels post-recovery (\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, 57% of CAD patients were classified as pre-frail, and 13% were frail. Pre-frail patients have approximately a 23% chance of regaining fitness, a 58% chance of remaining pre-frail, and an 18% chance of progressing to frailty. Frail patients, however, have only a 3% chance of regaining fitness and a 40% chance of improving to pre-frail status (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Despite the absence of miRNA-21 differences, there is an urgent need to focus on pre-frail patients as well.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations of the study and a future perspective\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe present a cross-sectional single-time point analysis of the serum level of miRNA-21 in relation to clinical, morphological, and laboratory features of patients classified according to the phenotype frailty scale. The single-time-point approach has the lowest power to infer a cause-and-effect association. We need to determine how the serum level of miRNA-21 changes over time during longitudinal observation. The question to be answered in a specifically designed research study is: What is the impact of the baseline miRNA-21 level on cardiovascular outcomes? These are obligatory prerequisites to use miRNA-21 as a specific biomarker.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of interest\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eA.R.T. has received grants BNW-1-171/K/3/K, and PCN-1-235/K/2/K from the Medical University of Silesia\u003c/p\u003e\u003cp\u003eJ.C. has received grant 58/TALENTYJUTRA_E1/2022 from Empiria i Wiedza Foundation.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.C., S.W., M.K., M.J., M.S., and P.W. enrolled patients, performed morphometric analyses, completed the database, and assisted with miRNA-21 assessment. D.H. and J.S. performed, analyzed, and interpreted the miRNA-21 assessment. B.P.C. and M.M. edited the manuscript. A.R.T. conceived, directed, and sponsored the work throughout all levels of development. J.C. and A.R.T. drafted the manuscript. All the authors discussed the results and approved the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets analyzed during the current study are available from the corresponding author on reasonable request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFried, L. P. et al. Frailty in older adults: evidence for a phenotype. \u003cem\u003eJ. Gerontol. Biol. Sci. Med. Sci.\u003c/em\u003e \u003cb\u003e56\u003c/b\u003e (3), M146\u0026ndash;M156 (2001). Epub 2001/03/17. PubMed PMID: 11253156.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRockwood, K. et al. A global clinical measure of fitness and frailty in elderly people. \u003cem\u003eCMAJ\u003c/em\u003e \u003cb\u003e173\u003c/b\u003e (5), 489\u0026ndash;495. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1503/cmaj.050051\u003c/span\u003e\u003cspan address=\"10.1503/cmaj.050051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005). PubMed PMID: 16129869; PubMed Central PMCID: PMC1188185.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGu, S. Z. et al. Coronary artery lesion phenotype in frail older patients with non-ST-elevation acute coronary syndrome undergoing invasive care. \u003cem\u003eEuroIntervention\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e (3), e261\u0026ndash;e8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4244/eij-d-18-00848\u003c/span\u003e\u003cspan address=\"10.4244/eij-d-18-00848\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKanenawa, K. et al. Frailty and Bleeding After Percutaneous Coronary Intervention. Am J Cardiol. ;148:22\u0026thinsp;\u0026ndash;\u0026thinsp;9. Epub 20210303. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amjcard.2021.02\u003c/span\u003e\u003cspan address=\"10.1016/j.amjcard.2021.02\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.041. PubMed PMID: 33667444.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKwok, C. S. et al. Relation of Frailty to Outcomes in Percutaneous Coronary Intervention. \u003cem\u003eCardiovasc. Revasc Med.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e (7), 811\u0026ndash;818 (2020). PubMed PMID: 31761641.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChristensen, D. M. et al. Frailty, Treatments, and Outcomes in Older Patients With Myocardial Infarction: A Nationwide Registry‐Based Study. \u003cem\u003eJ. Am. Heart Association\u003c/em\u003e. \u003cb\u003e12\u003c/b\u003e (14), e030561. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/JAHA.123.030561\u003c/span\u003e\u003cspan address=\"10.1161/JAHA.123.030561\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEkerstad, N. et al. Frailty is independently associated with short-term outcomes for elderly patients with non-ST-segment elevation myocardial infarction. \u003cem\u003eCirculation\u003c/em\u003e \u003cb\u003e124\u003c/b\u003e (22), 2397\u0026ndash;2404. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCULATIONAHA.111.025452\u003c/span\u003e\u003cspan address=\"10.1161/CIRCULATIONAHA.111.025452\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011). Epub 20111107.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMurali-Krishnan, R. et al. Impact of frailty on outcomes after percutaneous coronary intervention: a prospective cohort study. \u003cem\u003eOpen. Heart\u003c/em\u003e. \u003cb\u003e2\u003c/b\u003e (1), e000294. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/openhrt-2015-000294\u003c/span\u003e\u003cspan address=\"10.1136/openhrt-2015-000294\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRatcovich, H. et al. Prevalence and Impact of Frailty in Patients\u0026thinsp;\u0026ge;\u0026thinsp;70 Years Old with Acute Coronary Syndrome Referred for Coronary Angiography. \u003cem\u003eCardiology\u003c/em\u003e \u003cb\u003e149\u003c/b\u003e (1), 1\u0026ndash;13 (2024). Epub 20231110. doi: 10.1159/000535116. PubMed PMID: 37952523; PubMed Central PMCID: PMC10836927.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAfilalo, J. et al. Frailty Assessment in the Cardiovascular Care of Older Adults. \u003cem\u003eJ. Am. Coll. Cardiol.\u003c/em\u003e \u003cb\u003e63\u003c/b\u003e (8), 747\u0026ndash;762. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jacc.2013.09.070\u003c/span\u003e\u003cspan address=\"10.1016/j.jacc.2013.09.070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCacciatore, S. et al. Management of Coronary Artery Disease in Older Adults: Recent Advances and Gaps in Evidence. J Clin Med. ;12(16). Epub 20230811. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12165233\u003c/span\u003e\u003cspan address=\"10.3390/jcm12165233\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 37629275; PubMed Central PMCID: PMC10455820.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a-Gim\u0026eacute;nez, J. L. et al. Implementing Precision Medicine in Human Frailty through Epigenetic Biomarkers. Int J Environ Res Public Health. ;18(4). Epub 20210215. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph18041883\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18041883\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 33672064; PubMed Central PMCID: PMC7919465.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWawrzyniak, S. et al. Epigenetic Biomarkers of Cardiovascular Risk in Frail Patients\u0026mdash;A Scope Review. \u003cem\u003eCurr. Issues. Mol. Biol.\u003c/em\u003e \u003cb\u003e47\u003c/b\u003e (6), 422. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cimb47060422\u003c/span\u003e\u003cspan address=\"10.3390/cimb47060422\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025). PubMed PMID:.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamos, J. et al. Circulating miRNAs are associated with frailty and ST-elevation myocardial infarction pathways. \u003cem\u003eArch. Gerontol. Geriatr.\u003c/em\u003e \u003cb\u003e106\u003c/b\u003e, 104870. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2022.104870\u003c/span\u003e\u003cspan address=\"10.1016/j.archger.2022.104870\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023). Epub 20221119.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, Y., Liu, Y. J., Liu, T., Zhang, H. \u0026amp; Yang, S. J. Plasma microRNA-21 is a potential diagnostic biomarker of acute myocardial infarction. \u003cem\u003eEur. Rev. Med. Pharmacol. Sci.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e (2), 323\u0026ndash;329 (2016). PubMed PMID: 26875904.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWoloszyn-Horak, E. et al. Frailty syndrome in daily practice of interventional cardiology ward-rationale and design of the FRAPICA trial: A STROBE-compliant prospective observational study. \u003cem\u003eMed. (Baltim).\u003c/em\u003e \u003cb\u003e99\u003c/b\u003e (5), e18935 (2020). 0000000000018935. PubMed PMID: 32000408; PubMed Central PMCID: PMC7004665.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJackson, A. S. \u0026amp; Pollock, M. L. Practical Assessment of Body Composition. \u003cem\u003ePhysician Sportsmed.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (5), 76\u0026ndash;90 (1985). 11708790. PubMed PMID: 27463295.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlivieri, F. et al. Age-related differences in the expression of circulating microRNAs: miR-21 as a new circulating marker of inflammaging. \u003cem\u003eMech. Ageing Dev.\u003c/em\u003e \u003cb\u003e133\u003c/b\u003e (11\u0026ndash;12), 675\u0026ndash;685. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.mad.2012.09\u003c/span\u003e\u003cspan address=\"10.1016/j.mad.2012.09\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012). Epub 20121002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXin, C., He, W., Sun, X., Li, M. \u0026amp; Wang, H. The Association of Micro-RNA 21 and Hypertension: A Meta-Analysis. \u003cem\u003eGlobal Heart\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5334/gh.1325\u003c/span\u003e\u003cspan address=\"10.5334/gh.1325\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJi, R. et al. MicroRNA expression signature and antisense-mediated depletion reveal an essential role of MicroRNA in vascular neointimal lesion formation. \u003cem\u003eCircul. Res.\u003c/em\u003e \u003cb\u003e100\u003c/b\u003e (11), 1579\u0026ndash;1588. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/circresaha.106.141986\u003c/span\u003e\u003cspan address=\"10.1161/circresaha.106.141986\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007). Epub 20070503.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoggli, E. et al. Involvement of microRNAs in the cytotoxic effects exerted by proinflammatory cytokines on pancreatic beta-cells. \u003cem\u003eDiabetes\u003c/em\u003e \u003cb\u003e59\u003c/b\u003e (4), 978\u0026ndash;986. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/db09-0881\u003c/span\u003e\u003cspan address=\"10.2337/db09-0881\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010). Epub 20100119.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLawan, A. et al. Skeletal Muscle-Specific Deletion of MKP-1 Reveals a p38 MAPK/JNK/Akt Signaling Node That Regulates Obesity-Induced Insulin Resistance. \u003cem\u003eDiabetes\u003c/em\u003e ;\u003cb\u003e67\u003c/b\u003e(4):624\u0026ndash;635. (2018). Epub 20180109. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/db17-0826\u003c/span\u003e\u003cspan address=\"10.2337/db17-0826\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 29317435; PubMed Central PMCID: PMC5860856.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeyhan, A. A. et al. Pancreas-enriched miRNAs are altered in the circulation of subjects with diabetes: a pilot cross-sectional study. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 31479. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/srep31479\u003c/span\u003e\u003cspan address=\"10.1038/srep31479\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016). Epub 20160825.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNunez Lopez, Y. O., Garufi, G. \u0026amp; Seyhan, A. A. Altered levels of circulating cytokines and microRNAs in lean and obese individuals with prediabetes and type 2 diabetes. Mol Biosyst. ;13(1):106\u0026thinsp;\u0026ndash;\u0026thinsp;21. (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1039/c6mb00596a\u003c/span\u003e\u003cspan address=\"10.1039/c6mb00596a\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 27869909.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlivieri, F. et al. MiR-21-5p and miR-126a-3p levels in plasma and circulating angiogenic cells: relationship with type 2 diabetes complications. \u003cem\u003eOncotarget\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e (34), 35372\u0026ndash;35382. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18632/oncotarget.6164\u003c/span\u003e\u003cspan address=\"10.18632/oncotarget.6164\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015). PubMed PMID: 26498351; PubMed Central PMCID: PMC4742111.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhorbani, S. et al. Decreased serum microRNA-21 level is associated with obesity in healthy and type 2 diabetic subjects. \u003cem\u003eArch. Physiol. Biochem.\u003c/em\u003e \u003cb\u003e124\u003c/b\u003e (4), 300\u0026ndash;305 (2018). PubMed PMID: 29113498.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGalenko, O. et al. The role of microRNAs in the development, regulation, and treatment of atrial fibrillation. Journal of interventional cardiac electrophysiology: an international journal of arrhythmias and pacing. ;55(3):297\u0026ndash;305. Epub 20190103. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10840-018-0495-z\u003c/span\u003e\u003cspan address=\"10.1007/s10840-018-0495-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 30607665.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcManus, D. D. et al. Plasma microRNAs are associated with atrial fibrillation and change after catheter ablation (the miRhythm study). \u003cem\u003eHeart rhythm: official J. Heart Rhythm Soc.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e (1), 3\u0026ndash;10 (2015). PubMed PMID: 25257092; PubMed Central PMCID: PMC4277933.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCardin, S. et al. Role for MicroRNA-21 in atrial profibrillatory fibrotic remodeling associated with experimental postinfarction heart failure. \u003cem\u003eCirc. Arrhythm. Electrophysiol.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e (5), 1027\u0026ndash;1035. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/circep.112.973214\u003c/span\u003e\u003cspan address=\"10.1161/circep.112.973214\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012). Epub 20120826.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHe, X. et al. Rapid atrial pacing induces myocardial fibrosis by down-regulating Smad7 via microRNA-21 in rabbit. \u003cem\u003eHeart vessels\u003c/em\u003e. \u003cb\u003e31\u003c/b\u003e (10), 1696\u0026ndash;1708. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00380-016-0808-z\u003c/span\u003e\u003cspan address=\"10.1007/s00380-016-0808-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016). Epub 20160311.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang, Z. et al. Signal Transducer and Activator of Transcription 3/MicroRNA-21 Feedback Loop Contributes to Atrial Fibrillation by Promoting Atrial Fibrosis in a Rat Sterile Pericarditis Model. \u003cem\u003eCirc. Arrhythm. Electrophysiol.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e (7), e003396. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/circep.115.003396\u003c/span\u003e\u003cspan address=\"10.1161/circep.115.003396\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016). PubMed PMID: 27406600; PubMed Central PMCID: PMC4956678.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang, P., Dong, X. \u0026amp; Zhang, Y. MicroRNA profiles in plasma samples from young metabolically healthy obese patients and miRNA-21 are associated with diastolic dysfunction via TGF-β1/Smad pathway. \u003cem\u003eJ. Clin. Lab. Anal.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e (6), e23246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jcla.23246\u003c/span\u003e\u003cspan address=\"10.1002/jcla.23246\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020). Epub 20200228.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFontanella, R. A. et al. Adiponectin Related Vascular and Cardiac Benefits in Obesity: Is There a Role for an Epigenetically Regulated Mechanism? \u003cem\u003eFront. Cardiovasc. Med.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e, 768026 (2021). PubMed PMID: 34869683; PubMed Central PMCID: PMC8639875.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeeger, T., Fischer, A., Muhly-Reinholz, M., Zeiher, A. M. \u0026amp; Dimmeler, S. Long-term inhibition of miR-21 leads to reduction of obesity in db/db mice. \u003cem\u003eObes. (Silver Spring Md)\u003c/em\u003e. \u003cb\u003e22\u003c/b\u003e (11), 2352\u0026ndash;2360. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/oby.20852\u003c/span\u003e\u003cspan address=\"10.1002/oby.20852\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014). Epub 20140820.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKorzonek-Szlacheta, I. et al. The Association between Circulating Cytokines and Body Composition in Frail Patients with Cardiovascular Disease. \u003cem\u003eNutrients\u003c/em\u003e \u003cb\u003e16\u003c/b\u003e (8), 1227. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu16081227\u003c/span\u003e\u003cspan address=\"10.3390/nu16081227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024). PubMed PMID:.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu, J. et al. Exosomes from nicotine-stimulated macrophages accelerate atherosclerosis through miR-21-3p/PTEN-mediated VSMC migration and proliferation. \u003cem\u003eTheranostics\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e (23), 6901\u0026ndash;6919. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7150/thno.37357\u003c/span\u003e\u003cspan address=\"10.7150/thno.37357\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019). Epub 20190921.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, J. Y. et al. Circulating MiRNA biomarkers serve as a fingerprint for diabetic atherosclerosis. \u003cem\u003eAm. J. Transl Res.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e (6), 2650\u0026ndash;2658 (2016). Epub 20160615. PubMed PMID: 27398148; PubMed Central PMCID: PMC4931159.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParthenakis, F. et al. Low Levels of MicroRNA-21 Are a Marker of Reduced Arterial Stiffness in Well-Controlled Hypertension. \u003cem\u003eJ. Clin. Hypertens. (Greenwich)\u003c/em\u003e. \u003cb\u003e19\u003c/b\u003e (3), 235\u0026ndash;240. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jch.12900\u003c/span\u003e\u003cspan address=\"10.1111/jch.12900\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017). Epub 20160822.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Rooij, E. et al. Dysregulation of microRNAs after myocardial infarction reveals a role of miR-29 in cardiac fibrosis. \u003cem\u003eProc. Natl. Acad. Sci. U.S.A.\u003c/em\u003e \u003cb\u003e105\u003c/b\u003e (35), 13027\u0026ndash;13032. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.0805038105\u003c/span\u003e\u003cspan address=\"10.1073/pnas.0805038105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008). Epub 20080822.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, K., Li, K., Li, Z. \u0026amp; Yan, X. Circulating miRNA-21 as early potential diagnostic biomarker for acute myocardial infarction: a meta-analysis. \u003cem\u003eFront. Cardiovasc. Med.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 1330884. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fcvm.2024.1330884\u003c/span\u003e\u003cspan address=\"10.3389/fcvm.2024.1330884\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024). Epub 20240822.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohammed, A. et al. Long non-coding RNA NBAT1, TUG1, miRNA-335, and miRNA-21 as potential biomarkers for acute ischemic stroke and their possible correlation to thyroid hormones. \u003cem\u003eFront. Mol. Biosci.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 914506 (2022). PubMed PMID: 36250025; PubMed Central PMCID: PMC9565477.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQu, J. et al. Causal relationship between frailty and chronic obstructive pulmonary disease or asthma: A two sample bidirectional Mendelian randomization study. \u003cem\u003eArch. Gerontol. Geriatr.\u003c/em\u003e \u003cb\u003e118\u003c/b\u003e, 105310. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2023.105310\u003c/span\u003e\u003cspan address=\"10.1016/j.archger.2023.105310\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024). Epub 20231212.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVerduri, A., Clini, E., Carter, B. \u0026amp; Hewitt, J. Impact of Frailty on Symptom Burden in Chronic Obstructive Pulmonary Disease. J Clin Med. ;13(4). Epub 20240208. (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm13040984\u003c/span\u003e\u003cspan address=\"10.3390/jcm13040984\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 38398298; PubMed Central PMCID: PMC10889165.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElKashef, S., Ahmad, S. E., Soliman, Y. M. A. \u0026amp; Mostafa, M. S. Role of microRNA-21 and microRNA-155 as biomarkers for bronchial asthma. \u003cem\u003eInnate Immun.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (1), 61\u0026ndash;69 (2021). Epub 20200127. doi: 10.1177/1753425920901563. PubMed PMID: 31986951; PubMed Central PMCID: PMC7780351.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLu, L., Zheng, G. \u0026amp; Lin, Y. Blood miR-21 and miR-26 tailor a good diagnostic model for childhood asthma. Cell Mol Biol (Noisy-le-grand). ;\u003cb\u003e69\u003c/b\u003e(12):33\u0026ndash;37. Epub 20231130. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.14715/cmb/2023.69\u003c/span\u003e\u003cspan address=\"10.14715/cmb/2023.69\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.12.6. PubMed PMID: 38063121.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang, S. et al. miR-21 regulates chronic hypoxia-induced pulmonary vascular remodeling. \u003cem\u003eAm. J. Physiol. Lung Cell. Mol. Physiol.\u003c/em\u003e \u003cb\u003e302\u003c/b\u003e (6), L521\u0026ndash;L529. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/ajplung.00316.2011\u003c/span\u003e\u003cspan address=\"10.1152/ajplung.00316.2011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012). Epub 20120106.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLv, W. et al. Therapeutic potential of microRNAs for the treatment of renal fibrosis and CKD. \u003cem\u003ePhysiol. Genomics\u003c/em\u003e. \u003cb\u003e50\u003c/b\u003e (1), 20\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/physiolgenomics.00039.2017\u003c/span\u003e\u003cspan address=\"10.1152/physiolgenomics.00039.2017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018). Epub 20171110.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChau, B. N. et al. MicroRNA-21 promotes fibrosis of the kidney by silencing metabolic pathways. \u003cem\u003eSci. Transl Med.\u003c/em\u003e \u003cb\u003e4\u003c/b\u003e (121), 121ra18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/scitranslmed.3003205\u003c/span\u003e\u003cspan address=\"10.1126/scitranslmed.3003205\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012). PubMed PMID: 22344686; PubMed Central PMCID: PMC3672221.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, J. et al. Effect of miR-21 on renal fibrosis by regulating MMP-9 and TIMP1 in kk-ay diabetic nephropathy mice. \u003cem\u003eCell. Biochem. Biophys.\u003c/em\u003e \u003cb\u003e67\u003c/b\u003e (2), 537\u0026ndash;546. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12013-013-9539-2\u003c/span\u003e\u003cspan address=\"10.1007/s12013-013-9539-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013). PubMed PMID: 23443810.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhong, X. et al. miR-21 is a key therapeutic target for renal injury in a mouse model of type 2 diabetes. Diabetologia. ;56(3):663\u0026thinsp;\u0026ndash;\u0026thinsp;74. Epub 20130105. (2013). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00125-012-2804-x\u003c/span\u003e\u003cspan address=\"10.1007/s00125-012-2804-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 23292313.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarkou, A., Zavridou, M. \u0026amp; Lianidou, E. S. miRNA-21 as a novel therapeutic target in lung cancer. \u003cem\u003eLung Cancer (Auckl)\u003c/em\u003e. \u003cb\u003e7\u003c/b\u003e, 19\u0026ndash;27 (2016). Epub 20160302. doi: 10.2147/lctt.S60341. PubMed PMID: 28210157; PubMed Central PMCID: PMC5310696.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eResnick, K. E. et al. The detection of differentially expressed microRNAs from the serum of ovarian cancer patients using a novel real-time PCR platform. \u003cem\u003eGynecol. Oncol.\u003c/em\u003e \u003cb\u003e112\u003c/b\u003e (1), 55\u0026ndash;59 (2009). 036. PubMed PMID: 18954897.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSales, A. C. V. et al. Mirna21 Expression in the Breast Cancer Tumor Tissue is Independent of Neoadjuvant Chemotherapy. \u003cem\u003eBreast Cancer (Dove Med. Press)\u003c/em\u003e. \u003cb\u003e12\u003c/b\u003e, 141\u0026ndash;151. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/bctt.S269519\u003c/span\u003e\u003cspan address=\"10.2147/bctt.S269519\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020). Epub 20201008.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKojima, G., Taniguchi, Y., Iliffe, S., Jivraj, S. \u0026amp; Walters, K. Transitions between frailty states among community-dwelling older people: A systematic review and meta-analysis. Ageing Res Rev. ;50:81\u0026thinsp;\u0026ndash;\u0026thinsp;8. Epub 20190116. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.arr.2019.01.010\u003c/span\u003e\u003cspan address=\"10.1016/j.arr.2019.01.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PubMed PMID: 30659942.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Frailty syndrome, epigenetics, cardiovascular diseases, comorbidity, microRNA","lastPublishedDoi":"10.21203/rs.3.rs-7133943/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7133943/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe examined the serum level of miRNA-21 in a cohort of frail cardiovascular patients. We have enrolled 261 patients into this ancillary analysis of the FRAPICA trial (ClinicalTrials.org NCT03209414, registered 06/07/20217). The phenotype Fried frailty scale identified 93 robust, 131 pre-frail, and 37 frail patients. The groups differed in terms of demographics, morphology, and clinical characteristics. Frail patients had significantly lower miRNA-21 serum levels (median, 0.022; IQR, 0.0188\u0026ndash;0.0351) compared to pre-frail (0.0477; 0.0467\u0026ndash;0.0511) and robust patients (0.0477; 0.0428\u0026ndash;0.0526), with P\u0026thinsp;\u0026lt;\u0026thinsp;0.001. In the case of each frailty trait, patients with the presence of this trait had lower miRNA-21 levels than patients without the trait. The comorbidities had no impact on the miRNA-21 level. The miRNA-21 level correlated positively with weight, lean body mass, instrumental activities of daily living score, renal excretory function, expiratory pulmonary function, and hemoglobin concentration.\u003c/p\u003e\u003cp\u003eThis finding proposes miR-21 as a potential blood circulating biomarker of frailty, indicating that low levels of this miRNA represent a comorbid-independent characteristic of frailty in cardiovascular patients. Future studies are warranted to investigate the prognostic impact of baseline miRNA-21 levels on cardiovascular outcomes, as well as the longitudinal fluctuations of miRNA-21 serum levels and their clinical implications.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e","manuscriptTitle":"Lower serum level of miRNA-21 may be considered as a comorbidity-independent characteristic of frailty in cardiovascular patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-19 12:11:34","doi":"10.21203/rs.3.rs-7133943/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-10T08:57:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-29T05:21:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184138440889312428519706205587621865250","date":"2026-01-16T13:49:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-16T13:42:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-18T08:01:24+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-31T07:57:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-26T21:38:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-26T18:57:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5111bdf-1ba1-4c4a-a030-27a0b47f85ab","owner":[],"postedDate":"November 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":58165857,"name":"Health sciences/Biomarkers"},{"id":58165858,"name":"Health sciences/Cardiology"},{"id":58165859,"name":"Health sciences/Diseases"},{"id":58165860,"name":"Biological sciences/Genetics"},{"id":58165861,"name":"Health sciences/Medical research"},{"id":58165862,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-02-10T09:09:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-19 12:11:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7133943","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7133943","identity":"rs-7133943","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}