Extracellular vesicles (EVs) are intercellular communicators with key functions in physiological and pathological processes and have recently garnered interest because of their diagnostic and therapeutic potential. The past decade has brought about the development and commercialization of a wide array of methods to isolate EVs from serum. Which subpopulations of EVs are captured strongly depends on the isolation method, which in turn determines how suitable resulting samples are for various downstream applications. To help clinicians and scientists choose the most appropriate approach for their experiments, isolation methods need to be comparatively characterized. Few attempts have been made to comprehensively analyse vesicular microRNAs (miRNAs) in patient biofluids for biomarker studies. To address this discrepancy, we set out to benchmark the performance of several isolation principles for serum EVs in healthy individuals and critically ill patients. Here, we compared five different methods of EV isolation in combination with two RNA extraction methods regarding their suitability for biomarker discovery‐focused miRNA sequencing as well as biological characteristics of captured vesicles. Our findings reveal striking method‐specific differences in both the properties of isolated vesicles and the ability of associated miRNAs to serve in biomarker research. While isolation by precipitation and membrane affinity was highly suitable for miRNA‐based biomarker discovery, methods based on size‐exclusion chromatography failed to separate patients from healthy volunteers. Isolated vesicles differed in size, quantity, purity and composition, indicating that each method captured distinctive populations of EVs as well as additional contaminants. Even though the focus of this work was on transcriptomic profiling of EV‐miRNAs, our insights also apply to additional areas of research. We provide guidance for navigating the multitude of EV isolation methods available today and help researchers and clinicians make an informed choice about which strategy to use for experiments involving critically ill patients.

Rationale:: Myocardial endothelial cells promote cardiomyocyte hypertrophy, possibly through the release of growth factors. The identity of these factors, however, remains largely unknown, and we hypothesized here that the secreted CTRP9 (C1q-tumor necrosis factor–related protein-9) might act as endothelial-derived protein to modulate heart remodeling in response to pressure overload. Objective:: To examine the source of cardiac CTRP9 and its function during pressure overload. Methods and Results:: CTRP9 was mainly derived from myocardial capillary endothelial cells. CTRP9 mRNA expression was enhanced in hypertrophic human hearts and in mouse hearts after transverse aortic constriction (TAC). CTRP9 protein was more abundant in the serum of patients with severe aortic stenosis and in murine hearts after TAC. Interestingly, heterozygous and especially homozygous knock-out C1qtnf9 (CTRP9) gene-deleted mice were protected from the development of cardiac hypertrophy, left ventricular dilatation, and dysfunction during TAC. CTRP9 overexpression, in turn, promoted hypertrophic cardiac remodeling and dysfunction after TAC in mice and induced hypertrophy in isolated adult cardiomyocytes. Mechanistically, CTRP9 knock-out mice showed strongly reduced levels of activated prohypertrophic ERK5 (extracellular signal-regulated kinase 5) during TAC compared with wild-type mice, while CTRP9 overexpression entailed increased ERK5 activation in response to pressure overload. Inhibition of ERK5 by a dominant negative MEK5 mutant or by the ERK5/MEK5 inhibitor BIX02189 blunted CTRP9 triggered hypertrophy in isolated adult cardiomyocytes in vitro and attenuated mouse cardiomyocyte hypertrophy and cardiac dysfunction in vivo, respectively. Downstream of ERK5, we identified the prohypertrophic transcription factor GATA4, which was directly activated through ERK5-dependent phosphorylation. Conclusions:: The upregulation of CTRP9 during hypertrophic heart disease facilitates maladaptive cardiac remodeling and left ventricular dysfunction and might constitute a therapeutic target in the future.

Cell‐free microRNAs (miRNAs) are transferred in disease state including inflammatory lung diseases and are often packed into extracellular vesicles (EVs). To assess their suitability as biomarkers for community‐acquired pneumonia (CAP) and severe secondary complications such as sepsis, we studied patients with CAP (n = 30), sepsis (n = 65) and healthy volunteers (n = 47) subdivided into a training (n = 67) and a validation (n = 75) cohort. After precipitating crude EVs from sera, associated small RNA was profiled by next‐generation sequencing (NGS) and evaluated in multivariate analyses. A subset of the thereby identified biomarker candidates was validated both technically and additionally by reverse transcription quantitative real‐time PCR (RT‐qPCR). Differential gene expression (DGE) analysis revealed 29 differentially expressed miRNAs in CAP patients when compared to volunteers, and 25 miRNAs in patients with CAP, compared to those with sepsis. Sparse partial‐least discriminant analysis separated groups based on 12 miRNAs. Three miRNAs proved as a significant biomarker signature. While expression levels of miR‐1246 showed significant changes with an increase in overall disease severity from volunteers to CAP and to sepsis, miR‐193a‐5p and miR‐542‐3p differentiated patients with an infectious disease (CAP or sepsis) from volunteers. Cell‐free miRNAs are potentially novel biomarkers for CAP and may help to identify patients at risk for progress to sepsis, facilitating early intervention and treatment.

Editor’s Perspective: What We Already Know about This Topic: What This Article Tells Us That Is New: Background: Extracellular vesicles and their microRNA cargo are crucial facilitators of malignant cell communication and could mediate effects of anesthetics on tumor biology during cancer resection. The authors performed a proof-of-concept study to demonstrate that propofol and sevoflurane have differential effects on vesicle-associated microRNAs that influence signaling pathways involved in tumor progression and metastasis. Methods: Circulating vesicles were investigated in a prospective, matched-case pilot study in two cohorts of colorectal cancer patients receiving either propofol (n = 8) or sevoflurane (n = 9), matched for tumor stage and location. Serum was sampled before anesthesia and after tumor resection. Vesicular microRNA profiles were analyzed by next generation sequencing and confirmed by real-time polymerase chain reaction. Next, we assessed perioperative changes in microRNA expression induced by either anesthetic and compared their biologic effects on tumor-relevant pathways. Additionally, vesicles from pre- and postoperative sera were biologic characterized. Results: Postoperative microRNA profiles were shifted in both groups with overlap in the perioperative response. A total of 64 (48 up, range of log₂ fold change 1.07 to 3.76; 16 down, −1.00 to −1.55) and 33 (32 up, 1.02 to 2.98; 1 down, −1.36) microRNAs were significantly regulated (adjusted P value less than 0.05) by propofol and sevoflurane, respectively. Thirty-six (propofol) and five (sevoflurane) microRNAs were specifically responsive to either anesthetic agent. In silico target analyses of microRNA expression patterns indicated an inhibitory effect of propofol on crucial carcinoma-related pathways such as proliferation (z-score, −1.73) and migration (z-score, −1.97), as well as enhanced apoptosis (z-score, 1.19). While size distribution and protein markers of circulating vesicles were not affected by anesthesia, their concentration was reduced after surgery using both anesthetic procedures. Conclusions: This proof-of-concept study provides preliminary evidence that anesthetic agents have specific effects on microRNA profiles in circulating vesicles. These findings could form the basis for larger and mechanistically oriented outcome studies in cancer patients.

Extracellular vesicles (EVs) play central physiological and pathophysiological roles in intercellular communication. Biomarker studies addressing disorders such as cardiovascular diseases often focus on circulating microRNAs (miRNAs) and may, depending on the type of disease and clinic routine, utilise patient specimens sampled from arterial or venous blood vessels. Thus, it is essential to test whether circulating miRNA profiles depend on the respective sampling site. We assessed potential differences in arterial and venous cell‐free miRNA profiles in a cohort of 20 patients scheduled for cardiac surgery. Prior to surgery, blood was simultaneously sampled from the radial artery and the internal jugular vein. After precipitating crude EVs, we performed small RNA Sequencing, which failed to detect significantly regulated miRNAs using stringent filtering criteria for differential expression analysis. Filtering with less strict criteria, we detected four miRNAs slightly upregulated in arterial samples, one of which could be validated by reverse transcription real‐time PCR. The applicability of these findings to purified arterial and venous EVs was subsequently tested in a subset of the initial study population. While an additional clean‐up step using size‐exclusion chromatography seemed to reduce overall miRNA yield compared to crude EV samples, no miRNAs with differential arteriovenous expression were detected. Unsupervised clustering approaches were unable to correctly classify samples drawn from arteries or veins based on miRNAs in either crude or purified preparations. Particle characterisation of crude preparations as well as characterisation of EV markers in purified EVs resulted in highly similar characteristics for arterial and venous samples. With the exception of specific pathologies (e.g. severe pulmonary disorders), arterial versus venous blood sampling should therefore not represent a likely confounder when studying differentially expressed circulating miRNAs. The use of either arterial or venous serum EV samples should result in highly similar data on miRNA expression profiles for the majority of biomarker studies.Abbreviations ACE inhibitors: Angiotensin‐converting‐enzyme inhibitors; ApoA1: Apolipoprotein A1; CNX: Calnexin; Cv: Coefficient of variation; cDNA: Complementary DNA; CABG: Coronary artery bypass graft; DGE: Differential gene expression; DPBS: Dulbecco's Phosphate Buffered Saline; EVs: Extracellular vesicles; log2FC: Log2 fold change; baseMean: Mean miRNA expression; miRNA: MicroRNA; NTA: Nanoparticle Tracking Analysis; NGS: Next‐Generation Sequencing; RT‐qPCR: Reverse transcription quantitative real‐time PCR; rRNA: Ribosomal RNA; RT: Room temperature; SEC: Size‐exclusion chromatography; snoRNA: Small nucleolar RNA; snRNA: Small nuclear RNA; small RNA‐Seq: Small RNA Sequencing; SD: Standard deviation; tRNA: Transfer RNA; TEM: Transmission electron microscopy; UA: Uranyl acetate.

Background: Progranulin is a widely expressed pleiotropic growth factor with a central regulatory effect during the early immune response in sepsis. Progranulin signaling has not been systematically studied and compared between sepsis, community-acquired pneumonia (CAP), COVID-19 pneumonia and a sterile systemic inflammatory response (SIRS). We delineated molecular networks of progranulin signaling by next-generation sequencing (NGS), determined progranulin plasma concentrations and quantified the diagnostic performance of progranulin to differentiate between the above-mentioned disorders using the established biomarkers procalcitonin (PCT), interleukin-6 (IL-6) and C-reactive protein (CRP) for comparison. Methods: The diagnostic performance of progranulin was operationalized by calculating AUC and ROC statistics for progranulin and established biomarkers in 241 patients with sepsis, 182 patients with SIRS, 53 patients with CAP, 22 patients with COVID-19 pneumonia and 53 healthy volunteers. miRNAs and mRNAs in blood cells from sepsis patients (n = 7) were characterized by NGS and validated by RT-qPCR in an independent cohort (n = 39) to identify canonical gene networks associated with upregulated progranulin at sepsis onset. Results: Plasma concentrations of progranulin (ELISA) in patients with sepsis were 57.5 (42.8–84.9, Q25–Q75) ng/ml and significantly higher than in CAP (38.0, 33.5–41.0 ng/ml, p < 0.001), SIRS (29.0, 25.0–35.0 ng/ml, p < 0.001) and the healthy state (28.7, 25.5–31.7 ng/ml, p < 0.001). Patients with COVID-19 had significantly higher progranulin concentrations than patients with CAP (67.6, 56.6–96.0 vs. 38.0, 33.5–41.0 ng/ml, p < 0.001). The diagnostic performance of progranulin for the differentiation between sepsis vs. SIRS (n = 423) was comparable to that of procalcitonin. AUC was 0.90 (95% CI = 0.87–0.93) for progranulin and 0.92 (CI = 0.88–0.96, p = 0.323) for procalcitonin. Progranulin showed high discriminative power to differentiate bacterial CAP from COVID-19 (sensitivity 0.91, specificity 0.94, AUC 0.91 (CI = 0.8–1.0) and performed significantly better than PCT, IL-6 and CRP. NGS and partial RT-qPCR confirmation revealed a transcriptomic network of immune cells with upregulated progranulin and sortilin transcripts as well as toll-like-receptor 4 and tumor-protein 53, regulated by miR-16 and others. Conclusions: Progranulin signaling is elevated during the early antimicrobial response in sepsis and differs significantly between sepsis, CAP, COVID-19 and SIRS. This suggests that progranulin may serve as a novel indicator for the differentiation between these disorders. Trial registration: Clinicaltrials.gov registration number NCT03280576 Registered November 19, 2015.