| Ankylosing spondylitis(AS)is a common chronic,systemic,inflammatory disease which belongs to the group of diseases known as the serum-negative spondylarthrosis.This group of disorders refers to a set of diseases with overlapping clinical features and pathogenic mechanisms,yet there are important clinical and outcome differences.Ankylosing spondylitis is characterized by the inflammation of axial and peripheral joints and the attachments of ligaments and entheses and affected more 0.2%-0.45%people in the ethnic Han Chinese population.Patients with ankylosing spondylitis suffered from both physical pain and the dysfunction of joint.The working ability and quality of life of these patients are deeply diminished.The cost and side effect of the long-term treatments of ankylosing spondylitis usually brings even more burden of life.Nowadays,it is widely accepted that ankylosing spondylitis is a complex disease that genetic factors,immune disorder and environment together contribute to its onset.Recently,gut microbiome has been reported to play an important role in the homeostasis of human immune system.Disorder of gut microbiota has been found in multiple disease condition,including type 2 diabetes,inflammatory bowel diseases and atherosclerosis.Recent studies also pointed that gut microbiome is closely related to the pathogenesis of ankylosing spondylitis.Some species of the intestinal flora was identified to participate in triggering the onset of the disease.However,few research has been done to reveal the specific profiles of gut microbiome of ankylosing spondylitis patients.In this study,we conducted a research to investigate the differences of gut microbiome between AS patients and healthy controls by the metagenomics approach.By sequencing the genome of gut microbiota of the enrolled 85 naive AS patients and 63 HCs,we are able to describe the composition of gut microbiota,as well as the functional dysbiosis of AS patients,and to make a step further,to reveal the mechanism underlying.Our study demonstrated that patients with ankylosing spondylitis display a different pattern of composition of gut microbiome with HCs.Gene diversity of gut microbiota is dramatically decreased among patient as well as the abundance of gene counts.Particular species,families and phylum were observed to be enriched in patients’intestine.Bacteroidetes,for instance,is the only phylum enriched in AS patients.Microbiota from healthy controls showed much more diversity compared to AS patients.Both Actinobacteria,Firmicutes,Clostridia and Proteobacteria were enriched in HCs.In family level,we found similar enrichment of Bacteroidaceae,Ruminococcaceae,Porphyromonadaceae in AS patients.KEGG pathway and module analysis gave us an impression of functional gene distribution of gut microbiome of AS patients and HCs,which also showed that they were separated from each other dramatically.Genes of metabolism pathway is greatly enriched in patients,but varies pathways display relatively abundance in HCs.Meanwhile,although they all show abundance in metabolic pathways,the pattern of metabolism they choose for AS and HC were different.Synthesis of LPS,metabolism of amino acid,Vitamins and co-factors pathway and modules were enriched.But pathway of pentose-phosphate metabolism related pathway accompanied with other carbohydrate metabolism pathway and related modules were highlighted in HCs.In addition,we established a diagnosis model according to the mOTU markers we classified in the study.13 mOTU markers were selected to generate the model.The classifier was further adjusted depending on the importance of each mOTU markers and eventually we established the model whose specialty and sensitivity were capable to distinguish AS patients from healthy controls.In conclusion,our research described the differences of microbial phylogenetic structure and function between AS patients and healthy controls.The result of our study revealed that the dysbiosis of gut microbiota was significantly related to the illness and may be used as a marker in diagnosis.Therefore,our findings provide a novel insight of the pathogenesis of AS and the clinical diagnosis methods which may provide a theoretical basis of microecological treatment for AS.Rheumatoid arthritis(RA)is a chronic inflammatory disease which causes severe joints destruction and deformity.RA is characterized with serum autoantibodies as well as extensive lymphocytes infiltration in the synovia,including T and B cells.CD4+ T cells play crucial roles in the pathogenesis of RA.CD4+ T cell is a crucial component of adaptive immune system.One of the most important step in activation of adaptive immune system,is the recognition of antigen and T cell receptor(TCR).The adaptive immune system uses several strategies to generate a repertoire of T cell antigen receptors with sufficient diversity to recognize the universe of potential pathogens.In alpha/beta T cells,which primarily recognize peptide antigens presented by major histocompatibility complex molecules,the diversity of their TCRs lies mostly on the contribution of the third complementarity-determining region(CDR3).Genes of CDR3 regions are consist of noncontiguous variable(V),diversity(D),and joining(J)gene segments.Recombination of these three segments contributes most to the diversity of CDR3.By investigating CDR3 gene sequence,we can understand the recognition pattern of antigen,including autoantigens among patients of autoimmune diseases.In this study,we sequenced the TCR-beta(TCRβ)gene of different subsets of CD4+T cells in patients of rheumatoid arthritis and healthy controls.TCR gene expression and T cell clonity was analyzed.Diversity and length of CDR3 sequences was calculated and recorded.The types and frequency of V-J genes usage was also analyzed.Overlap between subsets of CD4+ T cells was estimated by the Morisita’s overlap index(MOI)and Jaccard similarity coefficient.Relationship of different subsets was showed by Circos.Public clones have been identified.Our result showed the differences of TCR beta gene usage between rheumatoid arthritis patients and healthy controls.Although no significant differences were observed in the diversity of T cell CDR3,we did discover the tendency of reduced diversity in effector memory T cell and regulatory T cell,as well as the relatively increased diversity in naive T cells.Investigation of V-J gene usage showed the reduced diversity of Th17 cell.Further analysis of V-J gene segment usage demonstrates the preference of two clones of TRBV28 and TRBV3-1 in RA patients’ Th17 cells.We found the overlap of TCR clones between CD4+ T cell subsets is most obvious between Tem/Tcm cells and Th17/Treg cells.RA patients Th17 cells and Treg cells displayed a significant similarity with Tem,while HCs showed more similarity with Tcm.We also identified some public clones observed in Tem cells as well as Th17 and Treg cells in different RA patients but not HCs,which indicated their potential to be the pathogenetic autoantigen recognition TCR clones.The correlational analysis of TCR clones and clinical index suggested that RA patients with diseases duration less than 2 year displayed a more abnormal TCR clone compared to HCs,while patients with longer duration had a relatively similar pattern of TCR clones in CD4+ T cell subsets.In a word,our study indicated that the TCR clones of CD4+ T cell subset were different between rheumatoid arthritis patients and healthy controls.Patient display more similarity between Th17 cells and Tem,which may partially explain the inflammatory phenotype of CD4+ T cells in RA patients.Public clones identified in our study also indicates the existence of potential autoreactive T cell clones in patients.Together our study firstly described the TCR repertoire in several different CD4+ T cell subsets,provide a novel insight of the pathogenesis of RA. |
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