Assessment of inter‐operator variability in peripheral monocyte subset gating strategy using flow cytometry in patients with suspected acute stroke

Abstract

AbstractBackgroundInnovative tools to reliably identify patients with acute stroke are needed. Peripheral monocyte subsets, that is, classical‐Mon1, intermediate‐Mon2, and non‐classical‐Mon3, with their activation marker expression analyzed using flow‐cytometry (FCM) could be interesting cell biomarker candidates.AimTo assess the inter‐operator variability in a new peripheral monocyte subset gating strategy using FCM in patients with suspected acute stroke.MethodsIn BOOST‐study (“Biomarkers‐algOrithm‐for‐strOke‐diagnoSis‐and Treatment‐resistance‐prediction,” NCT04726839), patients ≥18 years with symptoms suggesting acute stroke within the last 24 h were included. Blood was collected upon admission to emergency unit. FCM analysis was performed using the FACS‐CANTO‐II® flow‐cytometer and Flow‐Jo™‐software. Analyzed markers were CD45/CD91/CD14/CD16 (monocyte backbone) and CD62L/CD11b/HLA‐DR/CD86/CCR2/ICAM‐1/CX3CR1/TF (activation markers). Inter‐operator agreement (starting from raw‐data files) was quantified by the measure distribution and, for each patient, the coefficient of variation (CV).ResultsThree operators analyzed 20 patient blood samples. Median inter‐operator CVs were below the pre‐specified tolerance limits (10% [for Mon1 counts], 20% [Mon2, Mon3 counts], 15% [activation marker median‐fluorescence‐intensities]). We observed a slight, but systematic, inter‐operator effect. Overall, absolute inter‐operator differences in fractions of monocyte subsets were <0.03.ConclusionOur gating strategy allowed monocyte subset gating with an acceptable inter‐operator variability. Although low, the inter‐operator effect should be considered in monocyte data analysis of BOOST‐patients.