Circulating immune cell landscape in patients who had mild ischaemic stroke

Abstract

Introduction: Patients who had a mild ischaemic stroke who present with subtle or resolving symptoms sometimes go undiagnosed, are excluded from treatment and in some cases clinically worsen. Circulating immune cells are potential biomarkers that can assist with diagnosis in ischaemic stroke. Understanding the transcriptomic changes of each cell population caused by ischaemic stroke is critical because they work closely in a complicated relationship. In this study, we investigated peripheral blood mononuclear cells (PBMCs) transcriptomics of patients who had a stroke using a single-cell RNA sequencing to understand peripheral immune response after mild stroke based on the gene expression in an unbiased way.

Methods: Transcriptomes of PBMCsfrom 10 patients who had an acute ischaemic stroke within 24 hours after stroke onset were compared with 9 race-matched/age-matched/gender-matched controls. Individual PBMCs were prepared with ddSeqTM (Illumina-BioRad) and sequenced on the Illumina NovaSeq 6000 platform.

Results: Notable population changes were observed in patients who had a stroke, especially in NK cells and CD14+ monocytes. The number of NK cells was increased, which was further confirmed by flow cytometry. Functional analysis implied that the activity of NK cells also is enhanced in patients who had a stroke. CD14+ monocytes were clustered into two groups; dendritic cell-related CD14+ monocytes and NK cell-related CD14+ monocytes. We found CD14+ monocyte subclusters were dramatically reduced in patients who had a stroke.

Discussion: This is the first study demonstrating the increased number of NK cells and new monocyte subclusters of mild ischaemic stroke based on the transcriptomic analysis. Our findings provide the dynamics of circulating immune response that could assist diagnosis and potential therapeutic development of mild ischaemic stroke.

Trial registration: ClinicalTrials.gov NCT00009243 NCT00001846.

Keywords: inflammatory response; ischaemic attack; stroke; transient.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1

Study design and transcriptome profiling of PBMCs from controls and patients who had a stroke. (A) Schematic picture showing the overall study design; PBMCs were pulled from controls (n=9) and patients who had an acute ischaemic stroke (n=10), and single-cell RNA sequencing was performed. (B) Cell clusters were identified with UMAP projection of 101 481 cells from controls and patients who had a stroke. (C, E) Selected canonical cell markers were used to identify cell clusters. cDC, classical dendritic cell; MK, megakaryocyte; NK, natural killer; PBMC, peripheral blood mononuclear cell; pDC, plasmacytoid dendritic cell; UMAP, uniform manifold approximation and projection.

Figure 2

Differences in NK cell population between controls and patients who had a stroke. (A) Top dot plot shows the total PBMC counts of each subject used in scRNA-seq. The bar plot shows the percentage of cell clusters in each subject. The average percentage of each cell cluster analysed using scRNA-seq (B) and flow cytometry (C) is shown in green for controls and orange for patients who had a stroke. From both scRNA-seq and flow cytometry, it is demonstrated that NK cell cluster is increased in patients who had a stroke. (D) Representative flow cytometry plot shows increased NK cell population in patients who had a stroke. (E) DEGs (adjusted p

Figure 3

Changes of monocytes subclusters in patients who had a stroke. (A) Two CD14+ monocytes clusters were classified into 14 subclusters; CD14+ monocyte cluster A is classified into nine subclusters (0, 2–4 and 6–10), and CD14+ monocyte cluster B is classified into five subclusters (1, 9 and 11–13). (B) Based on the gene expression characteristics, cluster A is named dendritic cell-related CD14+ monocyte cluster (subclusters 0, 2–4, 7 and 8 in a circle in peach) and cluster B is named NK cell-related CD14+ monocyte cluster (subclusters 1, 9 and 11–13 in a circle in cyan). Besides, there is one plasma cell-related cluster (5), one erythrocyte progenitor cell-related cluster (6) and one megakaryocyte-related cluster (10). (C) The violin plot shows specifically expressed genes of each subcluster using classification. (D) The proportion of each subcluster was compared between controls and patients who had a stroke. (E) Individual variations of each subcluster in controls and patients who had a stroke are shown. Horizontal lines represent the average value for the proportion of each subcluster. *Significant differences (p