3 resultados para T(H)17 CELLS
em Helda - Digital Repository of University of Helsinki
Resumo:
Background: The fecal neutrophil-derived proteins calprotectin and lactoferrin have proven useful surrogate markers of intestinal inflammation. The aim of this study was to compare fecal calprotectin and lactoferrin concentrations to clinically, endoscopically, and histologically assessed Crohn’s disease (CD) activity, and to explore the suitability of these proteins as surrogate markers of mucosal healing during anti-TNFα therapy. Furthermore, we studied changes in the number and expression of effector and regulatory T cells in bowel biopsy specimens during anti-TNFα therapy. Patients and methods: Adult CD patients referred for ileocolonoscopy (n=106 for 77 patients) for various reasons were recruited (Study I). Clinical disease activity was assessed with the Crohn’s disease activity index (CDAI) and endoscopic activity with both the Crohn’s disease index of severity (CDEIS) and the simple endoscopic score for Crohn’s disease (SES-CD). Stool samples for measurements of calprotectin and lactoferrin, and blood samples for CRP were collected. For Study II, biopsy specimens were obtained from the ileum and the colon for histologic activity scoring. In prospective Study III, after baseline ileocolonoscopy, 15 patients received induction with anti-TNFα blocking agents and endoscopic, histologic, and fecal-marker responses to therapy were evaluated at 12 weeks. For detecting changes in the number and expression of effector and regulatory T cells, biopsy specimens were taken from the most severely diseased lesions in the ileum and the colon (Study IV). Results: Endoscopic scores correlated significantly with fecal calprotectin and lactoferrin (p<0.001). Both fecal markers were significantly lower in patients with endoscopically inactive than with active disease (p<0.001). In detecting endoscopically active disease, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for calprotectin ≥200 μg/g were 70%, 92%, 94%, and 61%; for lactoferrin ≥10 μg/g they were 66%, 92%, 94%, and 59%. Accordingly, the sensitivity, specificity, PPV, and NPV for CRP >5 mg/l were 48%, 91%, 91%, and 48%. Fecal markers were significantly higher in active colonic (both p<0.001) or ileocolonic (calprotectin p=0.028, lactoferrin p=0.004) than in ileal disease. In ileocolonic or colonic disease, colon histology score correlated significantly with fecal calprotectin (r=0.563) and lactoferrin (r=0.543). In patients receiving anti-TNFα therapy, median fecal calprotectin decreased from 1173 μg/g (range 88-15326) to 130 μg/g (13-1419) and lactoferrin from 105.0 μg/g (4.2-1258.9) to 2.7 μg/g (0.0-228.5), both p=0.001. The relation of ileal IL-17+ cells to CD4+ cells decreased significantly during anti-TNF treatment (p=0.047). The relation of IL-17+ cells to Foxp3+ cells was higher in the patients’ baseline specimens than in their post-treatment specimens (p=0.038). Conclusions: For evaluation of CD activity, based on endoscopic findings, more sensitive surrogate markers than CDAI and CRP were fecal calprotectin and lactoferrin. Fecal calprotectin and lactoferrin were significantly higher in endoscopically active disease than in endoscopic remission. In both ileocolonic and colonic disease, fecal markers correlated closely with histologic disease activity. In CD, these neutrophil-derived proteins thus seem to be useful surrogate markers of endoscopic activity. During anti-TNFα therapy, fecal calprotectin and lactoferrin decreased significantly. The anti-TNFα treatment was also reflected in a decreased IL-17/Foxp3 cell ratio, which may indicate improved balance between effector and regulatory T cells with treatment.
Resumo:
New blood cells are continuously provided by self-renewing multipotent hematopoietic stem cells (HSC). The capacity of HSCs to regenerate the hematopoietic system is utilized in the treatment of patients with hematological malignancies. HSCs can be enriched using an antibody-based recognition of CD34 or CD133 glycoproteins on the cell surface. The CD133+ and CD34+ cells may have partly different roles in hematopoiesis. Furthermore, each cell has a glycome typical for that cell type. Knowledge of HSC glycobiology can be used to design therapeutic cells with improved cell proliferation or homing properties. The present studies characterize the global gene expression profile of human cord blood-derived CD133+ and CD34+ cells, and demonstrate the differences between CD133+ and CD34+ cell populations that may have an impact in transplantation when CD133+ and CD34+ selected cells are used. In addition, these studies unravel the glycome profile of primitive hematopoietic cells and reveal the transcriptional regulation of N-glycan biosynthesis in CD133+ and CD34+ cells. The gene expression profile of CD133+ cells represents 690 differentially expressed transcripts between CD133+ cells and CD133- cells. CD34+ cells have 620 transcripts differentially expressed when compared to CD34- cells. The integrated CD133+/CD34+ cell gene expression profiles proffer novel transcripts to specify HSCs. Furthermore, the differences between the gene expression profiles of CD133+ and CD34+ cells indicate differences in the transcriptional regulation of CD133+ and CD34+ cells. CD133+ cells express a lower number of hematopoietic lineage differentiation marker genes than CD34+ cells. The expression profiles suggest a more primitive nature of CD133+ cells. Moreover, CD133+ cells have characteristic glycome that differ from the glycome of CD133- cells. High mannose-type and biantennary complex-type N-glycans are enriched in CD133+ cells. N-glycosylation-related gene expression pattern of CD133+ cells identify the key genes regulating the CD133+ cell-specific glycosylation including the overexpression of MGAT2 and underexpression of MGAT4. The putative role of MAN1C1 in the increase of unprocessed high mannose-type N-glycans in CD133+ cells is also discussed. These studies provide new information on the characteristics of HSCs. Improved understanding of HSC biology can be used to design therapeutic cells with improved cell proliferation and homing properties. As a result, HSC engineering could further their clinical use.
Resumo:
Tiivistelmä ReferatAbstract Metabolomics is a rapidly growing research field that studies the response of biological systems to environmental factors, disease states and genetic modifications. It aims at measuring the complete set of endogenous metabolites, i.e. the metabolome, in a biological sample such as plasma or cells. Because metabolites are the intermediates and end products of biochemical reactions, metabolite compositions and metabolite levels in biological samples can provide a wealth of information on on-going processes in a living system. Due to the complexity of the metabolome, metabolomic analysis poses a challenge to analytical chemistry. Adequate sample preparation is critical to accurate and reproducible analysis, and the analytical techniques must have high resolution and sensitivity to allow detection of as many metabolites as possible. Furthermore, as the information contained in the metabolome is immense, the data set collected from metabolomic studies is very large. In order to extract the relevant information from such large data sets, efficient data processing and multivariate data analysis methods are needed. In the research presented in this thesis, metabolomics was used to study mechanisms of polymeric gene delivery to retinal pigment epithelial (RPE) cells. The aim of the study was to detect differences in metabolomic fingerprints between transfected cells and non-transfected controls, and thereafter to identify metabolites responsible for the discrimination. The plasmid pCMV-β was introduced into RPE cells using the vector polyethyleneimine (PEI). The samples were analyzed using high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole (QqQ) mass spectrometer (MS). The software MZmine was used for raw data processing and principal component analysis (PCA) was used in statistical data analysis. The results revealed differences in metabolomic fingerprints between transfected cells and non-transfected controls. However, reliable fingerprinting data could not be obtained because of low analysis repeatability. Therefore, no attempts were made to identify metabolites responsible for discrimination between sample groups. Repeatability and accuracy of analyses can be influenced by protocol optimization. However, in this study, optimization of analytical methods was hindered by the very small number of samples available for analysis. In conclusion, this study demonstrates that obtaining reliable fingerprinting data is technically demanding, and the protocols need to be thoroughly optimized in order to approach the goals of gaining information on mechanisms of gene delivery.