This was a prospective study conducted at two high-volume academic centers (1st Chair and Department of Cardiology, Medical University of Warsaw, Poland and Department of Interventional Cardiology, Institute of Cardiology, Jagiellonian University Medical College, Krakow, Poland) in collaboration with Amsterdam Vesicle Center, Amsterdam University Medical Centers, the Netherlands. The study protocol, designed in compliance with the Declaration of Helsinki, was approved by the Ethics Committee of Medical University of Warsaw (approval number: KB/105/2021) and the Ethics Committee of Medical Chamber in Krakow (approval number: 304/KBL/OIL/2019).

The study population included patients with chronic coronary syndrome (CCS 1–3), objectively documented myocardial ischemia (i.e. ischemic changes on ECG during chest pain episode; reversible abnormalities in stress myocardial perfusion; reversible abnormalities in contractility on stress echocardiography), absence of significant obstructive coronary artery disease (CAD) (< 50% diameter stenosis in angiography or fractional flow reserve [FFR] > 0.80) and informed consent to participate in the study. Exclusion criteria were (i) indications for coronary angiography other than CAD (i.e. valvular disease, post-cardiac arrest state, left ventricular systolic dysfunction with ejection fraction [EF] < 30%), (ii) detection of at least one significant stenosis in at least one of the major epicardial arteries with a diameter > 2.5 mm (> 50% diameter stenosis and/or FFR < 0.8), (iii) tortuosity or calcifications within the coronary arteries preventing FFR guidewire insertion, (iv) history of PCI with stent implantation, (v) prolonged QTc interval on ECG, (vi) chronic kidney disease (estimated glomerular filtration rate [eGFR] < 30 ml/min/1.73 m2), (vii) severe chronic obstructive pulmonary disease (GOLD 4), (viii) allergy to iodinated contrast agents, (ix) pregnancy and breast-feeding, and (x) lack of patient informed consent to participate in the study.

Coronary angiography was performed in line with the standard of care at the participating hospitals, and coronary function tests were performed as adjunctive procedures. Coronary microvascular function was assessed using CoroFlow™ Software (Coroventis, Uppsala, Sweden) and PressureWire X (Abbott, Illinois, US). A pressure–temperature sensor was inserted into the left anterior descending artery (LAD) territory. In case of severe LAD tortuosity, another epicardial artery which allowed for FFR wire insertion was chosen. Following intracoronary administration of 200 µg of nitroglycerin, FFR, CFR and IMR were measured in real-time at rest and during hyperaemia using thermodilution method. Hyperaemia was achieved by an intravenous infusion of adenosine (140 µg/kg/min). Thermodilution was performed by repeated intracoronary injections of 3 ml of saline. Subsequently, ACh was administered intracoronary in incremental doses according to standardized protocol during continuous 12-leasd ECG monitoring. In case of anginal pain and ischaemic ECG changes allowing to diagnose VSA with the smaller ACh dose, the higher doses were not administered. Following the provocation test, nitroglycerin was administered intracoronary until the resolution of the spasm, anginal pain and/or ECG changes. Based on the coronary function testing results, patients were divided as proposed in the CorMicA trial: patients with INOCA (CMD, VSA or mixed endotype) and patients without INOCA (non-anginal chest pain, i.e. no CMD or VSA).

Venous blood was collected from all patients once, prior to coronary angiography. Blood was collected from antecubital vein into 7.5 mL 0.109 mol/L ethylenediaminetetraacetic acid (EDTA) plastic tubes (S-Monovette, Sarstedt) according to the guidelines to study EVs and processed by trained professionals (P.S., E.F., M.Z) [12]. Within 1 h from blood collection, platelet-depleted plasma was prepared by double centrifugation. The centrifugation parameters were: 2500 g, 15 min, 20 °C, acceleration speed 1, no brake. The first centrifugation step was done with 7.5 mL whole blood collection tubes. Supernatant was collected 10 mm above the buffy coat. The second centrifugation step was done with 3.5 mL plasma in 15 mL polypropylene centrifuge tubes (Greiner Bio-One B.V). Supernatant (platelet-depleted plasma) was collected 5 mm above the buffy coat, transferred into 5 mL polypropylene centrifuge tubes (Greiner Bio-One B.V.), mixed by pipetting, transferred to 1.5 mL low-protein binding Eppendorfs (Thermo Fisher Scientific), and stored at − 80 °C until analysis. Prior to analysis, samples were thawed for 1 min in a water bath (37 °C) to avoid cryoprecipitation.

Laboratory assays were conducted by EVcount (Amsterdam, The Netherlands), a startup company of the Amsterdam University Medical Centers specialized in EV concentration measurements. To determine the concentration of EV subtypes in platelet-depleted plasma, flow cytometry (A60-Micro, Apogee Flow Systems) was used. The reported concentrations describe the number of particles (1) that exceeded the side scattering threshold, corresponding to a side scattering cross section of 10 nm2, (2) with a diameter > 200 nm as determined by the flow cytometry scatter ratio (Flow-SR) [15], (3) having a refractive index < 1.42 to omit false positively labeled chylomicrons [16] and (4) that are positive at the fluorescence detectors corresponding to the used labels, per mL of platelet-depleted plasma. We defined the following EV subtypes: EVs derived from endothelial cells (CD144 + and CD62E +), leucocytes (CD45 +) and platelets (CD61 +). In addition, we defined the total concentration of EVs as the events fulfilling aforementioned criteria 1 to 3. Results are shown as ratio of the concentrations of EV subtypes to total EV concentrations.

To improve the reproducibility of EV flow cytometry experiments, EVcount (i) applied the framework for standardized reporting of EV flow cytometry experiments (MIFlowCyt-EV) [17] (ii) calibrated all detectors, (iii) determined the EV diameter and refractive index by Flow-SR [15] and (iv) applied custom-built software to fully automate data calibration and processing [18]. All relevant details about assay controls, instrument calibration, data acquisition, and EV characterization are included in the Supplementary File.

The primary endpoint was the difference in concentrations of EV subtypes in patients with INOCA and non-anginal chest pain. The secondary endpoint was the difference in concentrations of EV subtypes depending on the INOCA endotype (CMD vs. VSA vs. mixed endotype vs. non-anginal chest pain).

Currently, there is no data regarding the differences in EV concentrations between patients with and without INOCA or with different INOCA endotypes. Hence, the sample size was calculated based on the differences in platelet, leukocyte and endothelial EV concentrations between patients with CAD and healthy individuals, as demonstrated in the recent meta-analysis [19]. Patients with CAD had nominally twofold higher concentrations of the investigated EV subtypes compared to healthy controls. Concurrently, we assumed that the (i) mean difference in EVs concentrations between patients with and without INOCA = 1, (ii) standard deviation (SD) ± 1.0, and (iii) nominal test power = 0.9. Based on these assumptions, each group should include at least 23 patients (a total of 46 patients). Assuming INOCA rate of 50%, at least 92 patients should be enrolled in the study [1].

Statistical analyses were conducted using IBM SPSS Statistics, version 27.0 (IBM, New York, USA). Categorical variables were presented as number and percent and compared using χ2 test. Shapiro–Wilk test was used to assess normal distribution of continuous variables. Continuous variables were presented as mean with standard deviation (SD) or median with interquartile range (IQR). Differences in EV concentrations in patients with and without INOCA were compared using unpaired t-test or U-Mann Whitney, depending on data distribution. Differences in EV concentrations in patients with different INOCA endotypes were compared using Kruskal–Wallis test with Bonferroni correction for multiple comparisons. A chi-square test was used to compare categorical variables. Spearman correlation coefficient was used to evaluate correlations between EVs and echocardiographic parameters and B-type natriuretic peptide (BNP).

The diagnostic value of EVs for INOCA and the cut-offs were calculated using a receiver operating characteristic (ROC) curve. Logistic regression model incorporating EVs and clinical characteristics which differed between patients with and without INOCA were used to determine independent variables associated with the diagnosis of INOCA. The results of multivariable regression analysis are reported as odds ratio (OR) and 95% confidence interval (CI). A two-sided p-value below 0.05 was considered significant.