| Literature DB >> 33986412 |
Lennard Ostendorf1, Philipp Dittert2,3,4, Robert Biesen3, Ankelien Duchow5,6, Victoria Stiglbauer2, Klemens Ruprecht6,7, Judith Bellmann-Strobl5,6,8,7, Dominik Seelow9,10, Werner Stenzel2, Raluca A Niesner4,11, Anja E Hauser3,4, Friedemann Paul5,6,8,7, Helena Radbruch12.
Abstract
We aimed to evaluate SIGLEC1 (CD169) as a biomarker in multiple sclerosis (MS) and Neuromyelitis optica spectrum disorder (NMOSD) and to evaluate the presence of SIGLEC1+ myeloid cells in demyelinating diseases. We performed flow cytometry-based measurements of SIGLEC1 expression on monocytes in 86 MS patients, 41 NMOSD patients and 31 healthy controls. Additionally, we histologically evaluated the presence of SIGLEC1+ myeloid cells in acute and chronic MS brain lesions as well as other neurological diseases. We found elevated SIGLEC1 expression in 16/86 (18.6%) MS patients and 4/41 (9.8%) NMOSD patients. Almost all MS patients with high SIGLEC1 levels received exogenous interferon beta as an immunomodulatory treatment and only a small fraction of MS patients without interferon treatment had increased SIGLEC1 expression. In our cohort, SIGLEC1 expression on monocytes was-apart from those patients receiving interferon treatment-not significantly increased in patients with MS and NMOSD, nor were levels associated with more severe disease. SIGLEC1+ myeloid cells were abundantly present in active MS lesions as well as in a range of acute infectious and malignant diseases of the central nervous system, but not chronic MS lesions. The presence of SIGLEC1+ myeloid cells in brain lesions could be used to investigate the activity in an inflammatory CNS lesion.Entities:
Year: 2021 PMID: 33986412 PMCID: PMC8119413 DOI: 10.1038/s41598-021-89786-0
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1(a) Representative histograms of SIGLEC1 fluorescence on CD14high monocytes, FMO: fluorescence minus one control. (b) Cross-sectional analysis of SIGLEC1 expression on CD14high monocytes of 31 healthy controls, 86 MS patients and 41 NMOSD patients. If multiple samples of the same individual were analysed, the mean of the measurements is displayed. (c) Longitudinal analysis of SIGLEC1 expression of 52 individuals with up to five measurements. (d) Comparison of SIGLEC1 expression in MS patients, receiving no immunomodulatory treatment (n = 24), interferon beta (n = 13) or a non-interferon treatment (n = 49). Treatment with interferon with significantly associated with higher levels of SIGLEC1 expression: Kruskal–Wallis test with Dunn’s correction, **p < 0.01, ****p < 0.0001. (e) Comparison of SIGLEC1 expression in patients with RRMS (n = 63), SPMS (n = 15) and PPMS (n = 5). Red symbols indicate interferon treatment. (f) Scatter plot of the EDSS disability score against SIGLEC1 expression, no significant correlation was detected.
Figure 2(a) Representative immunohistochemical stainings of CD68, HLA-DR and SIGLEC1 (CD169) in brain tissue from a patient with active inflammatory multiple sclerosis lesion, a chronic lesion from a patient with secondary-progressive multiple sclerosis (SPMS) and a control patient who died of cardiovascular disease (CVD). Both RRMS and SPMS show infiltrates with CD68+ and HLA-DR+ myeloid cells, but only in the active lesion, these express SIGLEC1. Nuclei are stained blue and the respective marker antigens in brown. The scale bar indicates 100 µm. These results are representative of 4 RRMS, 5 SPMS and 7 control samples that were examined. (b) Immunohistochemical stainings of SIGLEC1 in brain tissue from patients with Herpes simplex viral encephalitis (n = 2), cerebral infarction with inflammatory changes (n = 2), cerebral toxoplasmosis (n = 1), cerebral abscess (n = 2), glioblastoma (n = 2) and post-transplant lymphoproliferative disease (PTLD, n = 1). Infiltrates of SIGLEC1+ myeloid cells were observed in all samples.
Epidemiological data.
| Healthy controls | MS patients | NMOSD patients | |
|---|---|---|---|
| Number of individuals | 31 | 86 | 41 |
| Age (median, IQR) | 31 (27–34) | 45 (34–52) | 57 (45–64) |
| Sex (n female) | 15 (48.4%) | 53 (61.6%) | 37 (90.2%) |
| Subtype (n) | – | RRMS: 63 (73.3%) SPMS: 15 (17.4%) PPMS: 5 (5.9%) | AQP4+: 23 (56.1%) MOG+: 7 (17.1%) Seronegative: 3 (7.3%) Unknown: 8 (19.5%) |
| Additional immune-mediated diseases (n) | Autoimmune thyroiditis (2), asthma bronchiale (1) | Autoimmune thyroiditis (10), asthma bronchiale (2), psoriasis (1), idiopathic myocarditis (1), celiac disease (1) | Autoimmune thyroiditis (3), myasthenia gravis (1), Sjögren syndrome (1), MCTD (1) |
| Immunosuppressive medication (n) | – | None: 24 (27.9%) Dimethyl fumarate: 15 (17.4%), glatiramer acetate: 14 (16.3%), interferon beta: 13 (15.1%), fingolimod: 7 (8.1%), teriflunomide: 5 (5.8%), methylprednisolone: 2 (2.3%), daclizumab: 2 (2.3%), rituximab: 1 (1.2%), ocrelizumab: 1 (1.2%), natalizumab 1 (1.2%) | Rituximab: 19 (46.3%) Azathioprine: 9 (22.0%) None: 6 (14.6%) Prednisolone: 3 (7.3%) Mycophenolate: 2 (4.9%) Glatiramer acetate: 1 (2.4%) Unknown: 1 (2.4%) |
IQR interquartile range, RRMS relapse-remitting multiple sclerosis, SPMS secondary progressive multiple sclerosis, PPMS primary progressive multiple sclerosis, AQP4+ aquaporin-4 antibody positive, MOG+ myelin oligodendrocyte glycoprotein antibody positive, MCTD mixed connective tissue disease).