Extracellular Vesicles Biomarkers Research Articles

Biochemical Characterization of Human Salivary Extracellular Vesicles as a Valuable Source of Biomarkers.

Extracellular vesicles (EVs) are natural nanoparticles secreted under physiological and pathological conditions. Thanks to their diagnostic potential, EVs are increasingly being studied as biomarkers of a variety of diseases, including neurological disorders. To date, most studies on EV biomarkers use blood as the source, despite different disadvantages that may cause an impure isolation of the EVs. In the present article, we propose the use of saliva as a valuable source of EVs that could be studied as biomarkers in an easily accessible biofluid. Using a comparable protocol for the isolation of EVs from both liquid biopsies, salivary EVs showed greater purity in terms of co-isolates (evaluated by nanoparticle tracking analysis and Conan test). In addition, Raman spectroscopy was used for the identification of the overall biochemical composition of EVs coming from the two different biofluids. Even considering the limited amount of EVs that can be isolated from saliva, the use of Raman spectroscopy was not hampered, and it was able to provide a comprehensive characterization of EVs in a high throughput and repeatable manner. Raman spectroscopy can thus represent a turning point in the application of salivary EVs in clinics, taking advantage of the simple method of collection of the liquid biopsy and of the quick, sensitive and label-free biophotonics-based approach.

Plasma derived extracellular vesicle biomarkers of microglia activation in an experimental stroke model

Chronic microglia activation post-stroke is associated with worse neurological and cognitive outcomes. However, measurement of microglia activation in vivo is currently limited. Plasma derived extracellular vesicles (EVs) are cell-specific indicators that may allow for non-invasive measurement of microglia phenotype. The aim of this study was to identify activation-state specific microglia EVs (MEVs) in vitro followed by validation in an experimental stroke model. Following pro-inflammatory activation, MEVs contain the microglia protein TMEM119 alongside increased expression of the Toll-like receptor 4 co-receptor CD14. Immunoprecipitation followed by fluorescent nanoparticle tracking analysis (ONI Nanoimager) was used to confirm the isolation of TMEM119+/CD14+ EVs from rat plasma. Electron microscopy confirmed that TMEM119 and CD14 localize to the MEV membrane. To model ischemia, plasma was collected from 3-month wildtype Fischer344 rats prior to, 7 and 28 days after endothelin-1 or saline injection into the dorsal right striatum. Fluorescently labelled MEVs were directly measured in the plasma using nanoflow cytometry (Apogee A60 Microplus). We report a significant increase in circulating TMEM119+/CD14+ EVs 28-days post-stroke in comparison to baseline levels and saline-injected rats, which correlated weakly with stroke volume. TMEM119+/MHC-II+ EVs were also increased post-stroke in comparison to baseline and saline-injected animals. This study is the first to describe an EV biomarker of activated microglia detected directly in plasma following stroke and represents a future tool for the measurement of microglia activity in vivo.

Nanomaterials for Molecular Detection and Analysis of Extracellular Vesicles.

Extracellular vesicles (EVs) have emerged as a novel resource of biomarkers for cancer and certain other diseases. Probing EVs in body fluids has become of major interest in the past decade in the development of a new-generation liquid biopsy for cancer diagnosis and monitoring. However, sensitive and specific molecular detection and analysis are challenging, due to the small size of EVs, low amount of antigens on individual EVs, and the complex biofluid matrix. Nanomaterials have been widely used in the technological development of protein and nucleic acid-based EV detection and analysis, owing to the unique structure and functional properties of materials at the nanometer scale. In this review, we summarize various nanomaterial-based analytical technologies for molecular EV detection and analysis. We discuss these technologies based on the major types of nanomaterials, including plasmonic, fluorescent, magnetic, organic, carbon-based, and certain other nanostructures. For each type of nanomaterial, functional properties are briefly described, followed by the applications of the nanomaterials for EV biomarker detection, profiling, and analysis in terms of detection mechanisms.

A specific technique of immunolabelling of urinary small extracellular vesicle biomarkers for the diagnostic of renal cancer.

Small extracellular vesicles (EVs) are characterized by the membrane expression of CD63, CD81 and CD9 tetraspanins. Their size is inferior to 200 nm. They share the same characteristics as the native cells and are found in human fluids. Specific membrane protein biomarkers expressed on small EV are useful for the diagnosis of tumoural pathologies. Clear cell renal cell carcinoma (CCRCC) is diagnosed by imaging examinations and/or tissue biopsy. Carbonic anhydrase IX (CAIX) is a powerful biomarker of CCRCC. The detection of CAIX on small EV from the urine of patients could constitute a liquid biopsy for CCRCC. We have set up a specific protocol for the preparation, the immunostaining characterization and the transmission electron microscopy observation of small EVs isolated from the urine of CCRCC patients. The background labelling was significantly reduced. We successfully detected biomarkers on urinary small EVs from CCRCC patients. This technique could be extended with antibodies directed against other EV biomarkers for the detection and the monitoring of cancer diseases.

Acidification of blood plasma facilitates the separation and analysis of extracellular vesicles

BackgroundBlood plasma is available with minimal invasive sampling, it has significant diagnostic utility, and it is a valuable source of extracellular vesicles (EVs). Nevertheless, rich protein content, the presence of lipoproteins (LPs) that share similar biophysical properties, and relatively low abundance of EVs, especially those of rare subpopulations, make any downstream application a very challenging task. The growing evidence of the intricate surface interactome of EVs, and the association of EVs with LPs, impose further challenges during EV purification, detection, and biomarker analyses. ObjectivesIn this study, we tackled the fundamental issues of plasma EV yield and LP co-isolation and their implications in the subsequent marker analyses. MethodsModerate acidification of plasma was combined with size exclusion chromatography (SEC) and/or differential centrifugation (DC) to disrupt LPs and improve recovery of EVs and their subsequent detection by immunoassays and single-particle analysis methods. ResultsOur results demonstrate a surprisingly efficient enrichment of EVs (up to 3.3-fold higher than at pH 7) and partial depletion of LPs (up to 61.2%). Acidification of blood plasma samples enabled a quick single-step isoelectric precipitation of up to 20.4% of EVs directly from plasma, upon short low-speed centrifugation. ConclusionThus, acidification holds potential as a simple and inexpensive methodological step, which improves the efficacy of plasma EV enrichment and may have implications in future biomarker discoveries.

Single-Response Electronic Tongue and Machine Learning Enable the Multidetermination of Extracellular Vesicle Biomarkers for Cancer Diagnostics Without Recognition Elements.

Platforms based on impedimetric electronic tongue (nonselective sensor) and machine learning are promising to bring disease screening biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point-of-care, thus contributing to rationalize and decentralize laboratory tests with social and economic impacts being achieved. By combining a low-cost and scalable electronic tongue with machine learning, in this chapter, we describe the simultaneous determination of two extracellular vesicle (EV) biomarkers, i.e., the concentrations of EV and carried proteins, in mice blood with Ehrlich tumor from a single impedance spectrum without using biorecognizing elements. This tumor shows primary features of mammary tumor cells. Pencil HB core electrodes are integrated into polydimethylsiloxane (PDMS) microfluidic chip. The platform shows the highest throughput in comparison with the methods addressed in the literature to determine EV biomarkers.

Monocrystalline Labeling Enables Stable Plasmonic Enhancement for Isolation‐Free Extracellular Vesicle Analysis (Small 2/2023)

Isolation-Free Extracellular Vesicle Analysis Tony Hu and co-workers develop a rapid in situ copper nanoshell growth protocol using a gold nanorod seed enhanced plasmonic scattering, as the nanorod lattice structure promotes monocrystalline growth to generate geometries with superior plasmonic properties. Correspondingly, they show that a non-disruptive copper nanoshell-enhanced immunoassay (Cu-NEI) for a disease-associated extracellular vesicle biomarker exhibits better diagnostic performance than a gold nanorod-based assay. More details can be found in article number 2204298.

Data-independent acquisition mass spectrometry identification of extracellular vesicle biomarkers for gastric adenocarcinoma.

Early diagnosis of gastric adenocarcinoma (GAC) can effectively prevent the progression of the disease and significantly improve patient survival. Currently, protein markers in clinical practice barely meet patient needs; it is therefore imperative to develop new diagnostic biomarkers with high sensitivity and specificity. In this study, we extracted extracellular vesicles (EV) from the sera of 33 patients with GAC and 19 healthy controls, then applied data-independent acquisition (DIA) mass spectrometry to measure protein expression profiles. Differential protein expression analysis identified 23 proteins showing expression patterns across different cancer stages, from which 15 proteins were selected as candidate biomarkers for GAC diagnosis. From this subset of 15 proteins, up to 6 proteins were iteratively selected as features and logistic regression was used to distinguish patients from healthy controls. Furthermore, serum-derived EV from a new cohort of 12 patients with gastric cancer and 18 healthy controls were quantified using the same method. A classification panel consisting of GSN, HP, ORM1, PIGR, and TFRC showed the best performance, with a sensitivity and negative predictive value (NPV) of 0.83 and 0.82. The area under curve (AUC) of the receiver operating characteristic (ROC) is 0.80. Finally, to facilitate the diagnosis of advanced stage GAC, we identified a 3-protein panel consisting of LYZ, SAA1, and F12 that showed reasonably good performance with an AUC of 0.83 in the validation dataset. In conclusion, we identified new protein biomarker panels from serum EVs for early diagnosis of gastric cancer that worth further validation.

Monocrystalline Labeling Enables Stable Plasmonic Enhancement for Isolation-Free Extracellular Vesicle Analysis.

Sensitive detection of extracellular vesicles (EVs) as emerging biomarkers has shown great promises for disease diagnosis. Plasmonic metal nanostructures conjugated with molecules that bind specific biomarker targets are widely used for EVs sensing but involve tradeoffs between particle-size-dependent signal intensity and conjugation efficiency. One solution to this problem would be to induce nucleation on nanoparticles that have successfully bound a target biomarker to permit in situ nanoparticle growth for signal amplification, but approaches that are evaluated to date require harsh conditions or lack nucleation specificity, prohibiting their effective use with most biological specimens. This study describes a one-step in situ strategy to induce monocrystalline copper shell growth on gold nanorod probes without decreasing signal by disrupting probe-target interactions or lipid bilayer integrity to enable EV biomarker detections. This approach increases the detected nanoparticle signal about two orders of magnitude after a 10 min copper nanoshell growth reaction. This has significant implications for improved disease detection, as indicated by the ability of a novel immunoassay using this approach to detect low abundance EVs carrying a pathogen-derived biomarker, after their direct capture from serum, to facilitate the diagnosis of tuberculosis cases in a diagnostically challenging pediatric cohort.

Computational analysis of serum-derived extracellular vesicle miRNAs in juvenile sheep model of single stage Fontan procedure

Patients with single ventricle heart defects requires a series of staged open-heart procedures, termed Fontan palliation. However, while lifesaving, these operations are associated with significant morbidity and early mortality. The attendant complications are thought to arise in response to the abnormal hemodynamics induced by Fontan palliation, although the pathophysiology underlying these physicochemical changes in cardiovascular and other organs remain unknown. Here, we investigated the microRNA (miRNA) content in serum and serum-derived extracellular vesicles (EVs) by sequencing small RNAs from a physiologically relevant sheep model of the Fontan operation. The differential expression analysis identified the enriched miRNA clusters in (1) serum vs. serum-derived EVs and (2) pre-Fontan EVs vs. post-Fontan EVs. Metascape analysis showed that the overexpressed subset of EV miRNAs by Fontan procedure target liver-specific cells, underscoring a potentially important pathway involved in the liver dysfunction that occurs as a consequence of Fontan palliation. We also found that post-Fontan EV miRNAs were associated with senescence and cell death, whereas pre-Fontan EV miRNAs were associated with stem cell maintenance and epithelial-to-mesenchymal transition. This study shows great potential to identify novel circulating EV biomarkers from Fontan sheep serum that may be used for the diagnosis, prognosis, and therapeutics for patients that have undergone Fontan palliation.

Extracellular vesicle biomarkers for cognitive impairment in Parkinson's disease.

Besides motor symptoms, many individuals with Parkinson's disease develop cognitive impairment perhaps due to coexisting α-synuclein and Alzheimer's disease pathologies and impaired brain insulin signalling. Discovering biomarkers for cognitive impairment in Parkinson's disease could help clarify the underlying pathogenic processes and improve Parkinson's disease diagnosis and prognosis. This study used plasma samples from 273 participants: 103 Parkinson's disease individuals with normal cognition, 121 Parkinson's disease individuals with cognitive impairment (81 with mild cognitive impairment, 40 with dementia) and 49 age- and sex-matched controls. Plasma extracellular vesicles enriched for neuronal origin were immunocaptured by targeting the L1 cell adhesion molecule, then biomarkers were quantified using immunoassays. α-Synuclein was lower in Parkinson's disease compared to control individuals (P = 0.004) and in cognitively impaired Parkinson's disease individuals compared to Parkinson's disease with normal cognition (P < 0.001) and control (P < 0.001) individuals. Amyloid-β42 did not differ between groups. Phosphorylated tau (T181) was higher in Parkinson's disease than control individuals (P = 0.003) and in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P < 0.001) and controls (P < 0.001). Total tau was not different between groups. Tyrosine-phosphorylated insulin receptor substrate-1 was lower in Parkinson's disease compared to control individuals (P = 0.03) and in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.02) and controls (P = 0.01), and also decreased with increasing motor symptom severity (P = 0.005); serine312-phosphorylated insulin receptor substrate-1 was not different between groups. Mechanistic target of rapamycin was not different between groups, whereas phosphorylated mechanistic target of rapamycin trended lower in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.05). The ratio of α-synuclein to phosphorylated tau181 was lower in Parkinson's disease compared to controls (P = 0.001), in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P < 0.001) and decreased with increasing motor symptom severity (P < 0.001). The ratio of insulin receptor substrate-1 phosphorylated serine312 to insulin receptor substrate-1 phosphorylated tyrosine was higher in Parkinson's disease compared to control individuals (P = 0.01), in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.02) and increased with increasing motor symptom severity (P = 0.003). α-Synuclein, phosphorylated tau181 and insulin receptor substrate-1 phosphorylated tyrosine contributed in diagnostic classification between groups. These findings suggest that both α-synuclein and tau pathologies and impaired insulin signalling underlie Parkinson's disease with cognitive impairment. Plasma neuronal extracellular vesicles biomarkers may inform cognitive prognosis in Parkinson's disease.

Abstract 5960: Blood-based extracellular vesicle biomarker test for detection of early-stage pancreatic cancer

Abstract Pancreatic cancer is an almost uniformly lethal malignancy, in large part because is it rarely detected in its early, curable stages. We recently conducted a study to evaluate the use of proteins associated with extracellular vesicles (EVs) isolated using an alternating current electrokinetic (ACE) system for the early detection of pancreatic ductal adenocarcinoma. Because earlier detection of pancreatic cancer greatly improves outcomes, we sought to devise a blood-based test with high specificity for detecting early-stage PDAC based on identification of EV-bound biomarkers. EVs were purified from control or stage I-II pancreatic ductal adenocarcinoma (PDAC) patient plasma using an ACE microelectrode array. Following collection of EVs onto the electrodes, contaminating plasma elements were washed away, and the electric field was turned off to release EVs into buffer. The isolated EV/exosome samples were then tested using bead-based multiplex immunoassay kits to determine relative concentrations of biomarkers of interest. Sample cohorts were divided into a training set (controls, N=146; PDAC cases, N=33) to develop a logistic regression-based classification model, and a validation set (controls, N=139; PDAC cases, N=35) to generate a probability-based score for predicting the presence of PDAC. For the training set, the algorithm identified six protein biomarkers associated with the presence of stages I-II cancer in PDAC patient plasma, with a receiver-operating characteristic (AUC) of 0.997 (95% CI: 0.978-1.000) compared to control plasma samples. For the validation set, the algorithm had a sensitivity of 82.9% (95% CI: 67.3% - 91.9%) at a specificity of 99.3% (95% CI: 96.0% - 99.9%), generating an AUC = 0.978 (95% CI=0.954-0.995). The exosomal PDAC assay shows feasibility for developing minimally invasive liquid biopsies that allow low-risk, routine screening of high-risk patients. Those patients identified by the test would be able to undergo additional testing to determine if there is PDAC present. The additional screening and testing of these patients may increase the likelihood of curative treatment. Further work in large datasets is warranted. Citation Format: Juan P. Hinestrosa, Jean M. Lewis, Heath I. Balcer, Razelle Kurzrock, Scott Lippman, Rajaram Krishnan. Blood-based extracellular vesicle biomarker test for detection of early-stage pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5960.

Multiparametric analysis in GBM plasma extracellular vesicles (Evs) and surface marker expression profile.

2038 Background: Glioblastoma (GBM) is the most common malignant brain tumor with poor clinical prognosis. Management of GBM is hampered by the lack of an accurate test that can be used for differential diagnosis of tumor progression from inflammatory pseudoprogression. Plasma extracellular vesicles (EVs) has been shown to be a promising source for biomarker identification. In this project, we aimed to identify GBM plasma EV markers that could serve as the basis of a liquid biopsy. Methods: Sample preparation, assay controls and instrument calibration were performed following MIFlowCyt-EV guideline. Plasma samples were subjected to 2-step centrifugations to remove cell debris and platelets. 10ul of plasma sample was diluted with 90ul filtered PBS, then stained for EV surface markers including CD9, CD31, CD45, CD41a and CD11b, as well as actin phalloidin. Stained plasma samples were purified using IZON qEV1/70nm column, then EV fractions were analyzed using full spectrum Cytek Aurora flow cytometer. Clustering analysis was performed on EV events (CD9 +/ actin phalloidin -) using t-SNE and FlowSOM extensions from FlowJo plugins. Results: Compared to normal donors, GBM plasma EVs were bigger in size (higher SSC value) and expressed higher levels of CD9, CD31, CD45 and CD11b while ND plasma EVs had higher CD41a expression. t-SNE and FlowSOM analysis demonstrated that GBM plasma EVs had a unique surface marker expression profile compared to ND EVs. It also showed 10 EV sub-populations that differed in size as well as various surface marker expression levels. Four of these subpopulations were enriched in GBM EVs, while three of these were enriched in ND EVs. Conclusions: This multiparametric analysis revealed that GBM plasma EVs had a unique surface marker expression profile compared to ND plasma EVs. Further separation and molecular profiling analysis based on each sub population could reveal EV biomarkers that are unique to each sample population.

A plasmonic nanoparticle-embedded polydopamine substrate for fluorescence detection of extracellular vesicle biomarkers in serum and urine from patients with systemic lupus erythematosus

There is an unmet clinical need to develop noninvasive liquid biopsy tools for systemic lupus erythematosus (SLE) diagnosis and therapeutic effect evaluation. Extracellular vesicles (EVs), which are abundant in body fluids, have emerged as a valuable resource for liquid biopsy. Herein, we describe a simple and robust EV detection platform that is based on a plasmonic nanoparticle-embedded polydopamine substrate that is modified with EV-capture molecules and detection probes. We investigated three EV biomarkers, namely, programmed cell death protein-1 (PD-1), microRNA-146a (miRNA-146a) and sialic acid (SA), in serum and urine from SLE patients and healthy controls. This platform prevents complex pretreatment while enabling highly efficient EV capture to the substrate surface, and the multiple functionalization of the detection interface with specific biomarker probes enables simultaneous detection of PD-1, miRNA-146a and SA that are carried by EVs via fluorescence (FL) imaging at the single-vesicle level. Via comparison of EV biomarker profiles, SLE patients can be distinguished from normal controls and classified into treated and untreated groups. Due to its ease of preparation, simplicity and stability, our approach shows good potential in the design of EV-based biosensors for clinical use.

Extracellular vesicle biomarkers for pancreatic cancer diagnosis: a systematic review and meta-analysis

BackgroundExtracellular vesicle (EV) biomarkers have promising diagnosis and screening capacity for several cancers, but the diagnostic value for pancreatic cancer (PC) is controversial. The aim of our study was to review the diagnostic performance of EV biomarkers for PC.MethodsWe performed a systematic review of PubMed, Medline, and Web Of Science databases from inception to 18 Feb 2022. We identified studies reporting the diagnostic performance of EV biomarkers for PC and summarized the information of sensitivity, specificity, area under the curve (AUC), or receiver operator characteristic (ROC) curve) in according to a pre-designed data collection form. Pooled sensitivity and specificity was calculated using a random-effect model.ResultsWe identified 39 studies, including 2037 PC patients and 1632 noncancerous, seven of which were conducted independent validation tests. Seventeen studies emphasized on EV RNAs, sixteen on EV proteins, and sixteen on biomarker panels. MiR-10b, miR-21, and GPC1 were the most frequently reported RNA and protein for PC diagnosis. For individual RNAs and proteins, the pooled sensitivity and specificity were 79% (95% CI: 77–81%) and 87% (95% CI: 85–89%), 72% (95% CI: 69–74%) and 77% (95% CI: 74–80%), respectively. the pooled sensitivity and specificity of EV RNA combined with protein panels were 84% (95% CI: 81–86%) and 89% (95% CI: 86–91%), respectively. Surprisingly, for early stage (stage I and II) PC EV biomarkers showed excellent diagnostic performance with the sensitivity of 90% (95% CI: 87–93%) and the specificity of 94% (95% CI: 92–95%). Both in sensitivity and subgroup analyses, we did not observe notable difference in pooled sensitivity and specificity. Studies might be limited by the isolation and detection techniques of EVs to a certain extent.ConclusionsEV biomarkers showed appealing diagnostic preference for PC, especially for early stage PC. Solving the deficiency of technologies of isolation and detection EVs has important implications for application these novel noninvasive biomarkers in clinical practice.

Realistic biomarkers from plasma extracellular vesicles for detection of beryllium exposure

PurposeExposures related to beryllium (Be) are an enduring concern among workers in the nuclear weapons and other high-tech industries, calling for regular and rigorous biological monitoring. Conventional biomonitoring of Be in urine is not informative of cumulative exposure nor health outcomes. Biomarkers of exposure to Be based on non-invasive biomonitoring could help refine disease risk assessment. In a cohort of workers with Be exposure, we employed blood plasma extracellular vesicles (EVs) to discover novel biomarkers of exposure to Be.MethodsEVs were isolated from plasma using size-exclusion chromatography and subjected to mass spectrometry-based proteomics. A protein-based classifier was developed using LASSO regression and validated by ELISA.ResultsWe discovered a dual biomarker signature comprising zymogen granule protein 16B and putative protein FAM10A4 that differentiated between Be-exposed and -unexposed subjects. ELISA-based quantification of the biomarkers in an independent cohort of samples confirmed higher expression of the signature in the Be-exposed group, displaying high predictive accuracy (AUROC = 0.919). Furthermore, the biomarkers efficiently discriminated high- and low-exposure groups (AUROC = 0.749).ConclusionsThis is the first report of EV biomarkers associated with Be exposure and exposure levels. The biomarkers could be implemented in resource-limited settings for Be exposure assessment.

Circulating micro-RNAs Differentially Expressed in Korean Alzheimer's Patients With Brain Aβ Accumulation Activate Amyloidogenesis.

Roles for extracellular vesicles (EVs) enriched with micro-RNAs (miRNAs) have been proposed in Alzheimer's disease (AD) pathogenesis, leading to the discovery of blood miRNAs as AD biomarkers. However, the diagnostic utility of specific miRNAs is not consistent. This study aimed to discover blood miRNAs that are differentially expressed in Korean AD patients, evaluate their clinical performance, and investigate their role in amyloidogenesis. We discovered miRNAs differentially expressed in AD (N = 8) from cognitively normal participants (CN, N = 7) or Parkinson's disease (PD) patients (N = 8). We evaluated the clinical performance of these miRNAs in plasma of subgroup (N = 99) and in plasma EVs isolated from the total cohort (N = 251). The effects of miRNAs on amyloidogenesis and on the regulation of their target genes were investigated in vitro. Among 17 upregulated and one downregulated miRNAs in AD (>twofold), miR-122-5p, miR-210-3p, and miR-590-5p were differentially expressed compared with CN or PD. However, the diagnostic performance of the selected plasma or EV miRNAs in total participants were limited (area under the curve < 0.8). Nevertheless, levels of 3 miRNAs in plasma or plasma EVs of participants who were amyloid positron emission tomography (Aβ-PET) positive were significantly higher than those from the Aβ-PET negative participants (p < .05). The selected miRNAs induced Aβ production (p < .05) through activation of β-cleavage of amyloid precursor protein (CTF-β; p < .01), and downregulated their target genes (ADAM metallopeptidase domain 10, Brain-derived neurotrophic factor, and Jagged canonical notch ligand 1; p < .05), which was further supported by pathway enrichment analysis of target genes of the miRNAs. In conclusion, despite of the limited diagnostic utility of selected miRNAs as plasma or plasma EV biomarkers, the discovered miRNAs may play a role in amyloidogenesis during AD onset and progression.

The Impact of Intermittent Fasting on Size Profile and Protein Cargo of Circulating Exosomes in High Fat Diet‐Induced Obese Mice

Extracellular vesicles (EVs) have emerged as a key regulator of intercellular and inter‐organ communications, playing an important role in mediating metabolic responses. Dysregulation of exosome secretion and exosome cargo composition has been associated with metabolic diseases. However, how EVs reflect diet‐induced metabolic responses remains unexplored. The objective of the study is to identify changes in the size profile and protein cargoes of circulating exosomes in diet‐induced obesity upon intermittent fasting, as well as to establish EV biomarkers for obesity‐related dietary responses.Male mice (8‐10 weeks of age) were all fed a high‐fat diet (HFD) for 18 weeks prior to being placed either in ad libitum group (HFD‐AL) or intermittent fasting group (HFD‐IF) for an additional 10 weeks. Mice on the normal chow ad libitum (NC‐AL) served as control. The IF group had food available for 10 hours and fasted for 14 hours per day. EVs were isolated from serum and size was measured using Nanoparticle Tracking Analysis. Additionally, quantitative proteomics was conducted to identify EV protein markers and FunRich Analysis Tool was used to identify pathways related to the identified proteins.On a long‐term HFD, the IF significantly altered the size profile of serum exosomes. The HFD‐AL mice had an increasing trend in mean diameter of serum EVs by 24nm compared to the NC‐AL mice. The 10 weeks of IF caused a significant decrease in mean diameter of serum EVs by 47.9nm (P= 0.03) when compared to the HFD‐AL mice. However, neither the HFD nor IF altered the overall particle amount per unit of serum. This suggests that the population composition of EVs may be changed in response to the HFD feeding or IF. To address this question, we analyzed the specific populations of EVs with different ranges of sizes. Intriguingly, we found the HFD altered the population composition of EVs (decreased small EVs and increased large EVs) and the IF was able to reverse these changes. The mean population of EVs/exosomes (30‐150nm in size) were increased in the HFD‐IF group by ~30% (P= 0.02), whereas the populations of larger EVs (200‐350nm) were decreased by ~15% (P= 0.02) when compared to the HFD‐AL mice. Proteomic Analysis of the protein abundance within the isolated EVs showed variance between the experimental groups. Compared to the NC‐AL, the HFD‐AL group had 15 upregulated proteins (involved in pathways such as blood coagulation, immune response, and others) and 18 downregulated proteins (involved in pathways such as cytolysis, classical and alternative pathway complement activation, and others). Between the HFD‐IF and HFD‐AL groups, 43 proteins were found to be significantly different in abundance. Of those 43 proteins, 10 proteins altered by HFD‐AL were reversed by implementing IF. FunRich analysis showed that these 10 proteins belonged to the pathways involving NADP metabolism, immune responses, lipoprotein metabolism, and cholesterol homeostasis.Together, this data suggests intermittent fasting significantly alters the profile and protein cargoes of circulating EVs which may serve as an important mechanism for the metabolic benefits of intermittent fasting in obesity as well as biomarkers for obesity‐related metabolic responses.

Genetic and phenotypic links between obesity and extracellular vesicles.

Obesity has a highly complex genetic architecture, making it difficult to understand the genetic mechanisms, despite the large number of discovered loci via genome-wide association studies (GWAS). Omics techniques have provided a better resolution to view this problem. As a proxy of cell-level biology, extracellular vesicles (EVs) are useful for studying cellular regulation of complex phenotypes such as obesity. Here, in a well-established Scottish cohort, we utilized a novel technology to detect surface proteins across millions of single EVs in each individual's plasma sample. Integrating the results with established obesity GWAS, we inferred 78 types of EVs carrying one or two of 12 surface proteins to be associated with adiposity-related traits such as waist circumference. We then verified that particular EVs' abundance is negatively correlated with body adiposity, while no association with lean body mass. We also revealed that genetic variants associated with protein-specific EVs capture 2-4-fold heritability enrichment for blood cholesterol levels. Our findings provide evidence that EVs with specific surface proteins have phenotypic and genetic links to obesity and blood lipids, respectively, guiding future EV biomarker research.

Men and women display distinct extracellular vesicle biomarker signatures in response to military operational stress.

Extracellular vesicles (EVs) are mediators of physiological changes that occur during physical exertion. This study examined the effects of physical exertion with and without sleep and caloric restriction on EV size, concentration, and surface proteins in men and women. Twenty participants (10 men) completed a 5-day simulated military operational stress protocol with daily physical exertion. Blood was drawn before and immediately after exertion at baseline (D1) and following 48-h of sleep and caloric restriction (D3). EV size and concentration were assessed using nanoparticle tracking analysis. EVs were identified with markers associated with exosomes (CD63), microvesicles (VAMP3), apoptotic bodies (THSD1), and skeletal muscle-derived EVs (SGCA) and quantified using imaging flow cytometry. Interactive and main effects of sex, day, and time on EVs were assessed using three-way ANOVAs. EV concentration declined pre to postexertion in women on D1 and D3 but was stable in men. EV size increased from pre to postexertion and from D1 to D3 in men and women. Physical exertion following sleep and caloric restriction increased CD63+ EV concentration, proportion of total EVs, and CD63 surface protein expression regardless of sex. The proportion of SGCA+ EVs increased in men and women following exertion and from D1 to D3 but was higher in women than in men. No differences were observed in VAMP3+ and THSD1+ EVs. This study identified sexually dimorphic EV profiles in response to various stressors. Further investigations are necessary to determine if dimorphic EV responses affect health and performance outcomes during stress.NEW & NOTEWORTHY Sex is understudied in EV research, and most studies limit EV analysis to single stress conditions such as exercise. Multistress conditions consisting of physical exertion and sleep and caloric restriction are common in real-world settings. We demonstrate that physical exertion results in sex-specific EV signatures and that EV profiles vary according to single versus multistress conditions. Our data highlight important biological and ecological characteristics that should be considered in EV research.