1Universitäres Herz- und Gefäßzentrum Hamburg Klinik für Kardiologie Hamburg, Deutschland; 2Harvard Medical School Department of Genetics Boston, USA; 3LMU Klinikum der Universität München Walter-Brendel-Zentrum München, Deutschland; 4University of Alberta Department of Medicine Edmonton, Alberta, Kanada; 5Universitätsklinikum Hamburg-Eppendorf Herzchirurgie Hamburg, Deutschland; 6Duke University Department of Surgery Durham, USA; 7Duke University Department of Pathology Durham, USA
Introduction:
Sarcoidosis is an inflammatory disease that can affect multiple organ systems with unknown etiology. It is defined by the presence of granulomas, which consist of macrophage-derived epithelioid and giant cells, as well as lymphocytes. Cardiac involvement occurs in up to 20% of sarcoid cases and is associated with poor prognosis. Cardiac sarcoidosis associated outcomes include atrial and ventricular arrhythmia, syncope, heart failure, and sudden cardiac death. Current therapy recommendation is based on low-quality observational data due to the lack of controlled trials and an understanding of disease pathogenesis. It consists of immunosuppression, as well as therapy for heart failure and arrhythmia.
Purpose:
To investigate the impact of sarcoid granulomas on the myocardium at a single-nucleus level, aiming to elucidate the pathways contributing to cardiac symptoms and immunologic dysregulation.
Methods:
Single-nucleus RNA sequencing (snRNA Seq) was performed on 25 cardiac samples from various regions of the heart in 18 sarcoid patients, using 10X Chromium V3 chemistry. The sarcoid data were then combined with data from control subjects (32 samples, 12 subjects), dilated cardiomyopathy (DCM) samples (68 samples, 31 subjects), and arrhythmogenic cardiomyopathy (ACM) samples (22 samples, 7 subjects) into a single computational object. DCM and ACM samples were included as comparators due to the phenotypic similarities between these diseases and cardiac sarcoidosis. Bioinformatic analysis was conducted using the R software package Seurat.
Results:
Similar to DCM and ACM, cardiac sarcoidosis resulted in an increased proportion of fibroblasts (sarcoid 24.3%, control 14.5%, p < 0.01) and myeloid cells (sarcoid 13.5%, control 3.5%, p < 0.0001). Additionally, there were sarcoid-specific changes not present in ACM or DCM, including an increase in lymphoid cells (sarcoid 6.0%, control 1.5%, p < 0.01) and a decreased proportion of pericytes (sarcoid 9.8%, control 19.6%, p < 0.0001).
Further analysis revealed a granuloma-specific myeloid cell state, representing epithelioid or giant cells, which exhibits a highly pro-inflammatory gene expression signature. Granulomatous samples also showed an enrichment of pathogenic Th17 cells, previously implicated in autoimmune diseases like multiple sclerosis. Additionally, a specific, highly suppressive IL1R+ regulatory T cell population, previously described only in tumor microenvironments, was observed.
Bioinformatic analysis suggested a cytokinetic dependency between TREM2+ macrophages, traditionally considered to have an immunosuppressive role, and pathogenic Th17 cells in sarcoidosis.
Conclusions:
snRNA-Seq provides a comprehensive insight into cardiac sarcoidosis, offering potential identification of novel therapeutic targets.