| Literature DB >> 30860258 |
Amy S Tsai1, Kacey Berry2,3, Maxime M Beneyto1, Dyani Gaudilliere4, Edward A Ganio1, Anthony Culos1, Mohammad S Ghaemi1, Benjamin Choisy1, Karim Djebali1, Jakob F Einhaus1, Basile Bertrand1, Athena Tanada1, Natalie Stanley1, Ramin Fallahzadeh1, Quentin Baca1, Lisa N Quach2,3, Elizabeth Osborn2,3, Lauren Drag3, Maarten G Lansberg2,3, Martin S Angst1, Brice Gaudilliere1, Marion S Buckwalter2,3,5, Nima Aghaeepour1.
Abstract
Stroke is a leading cause of cognitive impairment and dementia, but the mechanisms that underlie post-stroke cognitive decline are not well understood. Stroke produces profound local and systemic immune responses that engage all major innate and adaptive immune compartments. However, whether the systemic immune response to stroke contributes to long-term disability remains ill-defined. We used a single-cell mass cytometry approach to comprehensively and functionally characterize the systemic immune response to stroke in longitudinal blood samples from 24 patients over the course of 1 year and correlated the immune response with changes in cognitive functioning between 90 and 365 days post-stroke. Using elastic net regularized regression modelling, we identified key elements of a robust and prolonged systemic immune response to ischaemic stroke that occurs in three phases: an acute phase (Day 2) characterized by increased signal transducer and activator of transcription 3 (STAT3) signalling responses in innate immune cell types, an intermediate phase (Day 5) characterized by increased cAMP response element-binding protein (CREB) signalling responses in adaptive immune cell types, and a late phase (Day 90) by persistent elevation of neutrophils, and immunoglobulin M+ (IgM+) B cells. By Day 365 there was no detectable difference between these samples and those from an age- and gender-matched patient cohort without stroke. When regressed against the change in the Montreal Cognitive Assessment scores between Days 90 and 365 after stroke, the acute inflammatory phase Elastic Net model correlated with post-stroke cognitive trajectories (r = -0.692, Bonferroni-corrected P = 0.039). The results demonstrate the utility of a deep immune profiling approach with mass cytometry for the identification of clinically relevant immune correlates of long-term cognitive trajectories.Entities:
Keywords: cognitive outcomes; machine learning; mass cytometry; stroke; systemic immunology
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Year: 2019 PMID: 30860258 PMCID: PMC6933508 DOI: 10.1093/brain/awz022
Source DB: PubMed Journal: Brain ISSN: 0006-8950 Impact factor: 13.501