| Part 1 Study on the Correlation of Quality of Life in Patients with Axial SpondyloarthritisOBJECTIVEAxial spondyloarthritis(AxSpA)is a group of autoinflammatory diseases that mainly involve the central axis joints causing inflammatory back pain.It includes non-radiographic axial spondyloarthritis(nr-axSpA)and radiographic axial spondyloarthritis(r-axSpA),the latter is also known as ankylosing spondylitis(AS).In order to further improve the quality of life of patients,this study intends to investigate the clinical symptoms,HLA-B27 subtypes and quality of life of axSp A patients in our hospital,and to explore the related factors affecting the quality of life.METHODSIn this study,72 axSpA patients were enrolled in our outpatient or inpatient department between December 2020 and June 2021.A structured questionnaire was first used to record patients’ general information,quality of life assessment(ASQoL),disease assessment scale(PGA,nocturnal back pain VAS,total back pain VAS,BASDAI,BASFI),etc.56 of these axSpA patients completed the HLA-B27 subtype with full informed consent All data were statistically analyzed using SPSS 25.0.Counting data were described by frequency(percentage)and measurements by median(0.25 percentile,0.75 percentile).Non-parametric Mann-Whitney U assays were compared within the cohort,and correlation analysis was performed using Spearman analysis.The significance level of all statistical assays was statistically significant with p<0.05.RESULTS(1)Clinical Symptom Survey:A clinical symptom survey of 72 axSpA patients found that the most common symptoms were lumbar and sacroiliac joint pain(88.89%),followed by morning stiffness(43.06%),Swelling,tenderness,or deformity of peripheral joints(15.28%),heel adhesion inflammation(5.56%),inflammatory bowel disease(2.78%),cervical j oint pain(1.39%),finger(1.39%),uveitis(1.39%).(2)HLA-B27 subtype distribution:48(85.71%),4(7.14%)negative,3(5.36%)other subtypes of HLA-B*27,and 1(1.79%)HLA-B*27:05 subtypes were detected in 56 patients with axSpA.(3)ASQoL results:ASQoL results showed a maximum probability of a No.12 positive "I get tired easily" test of 40.28%.Other options with high positivity rates were,in order of importance,No.17:"My condition gets me down"(29.17%),No.18:"I worried if I am disappointing others"(26.39%),and No.8:"I have to stop what I am doing to rest"(26.39%).The results showed that the areas most affected by axSpA were fatigue,depression and increased workload.(4)ASQoL Correlation Factor Analysis:A Mann-Whitney U-rank sum test was used to validate significant differences between groups.Results showed that ASQoL scores were higher and statistically significant(p<0.05)among female patients across gender groups.The Spearman correlation analysis was used to study age,course of disease,onset age,disease assessment scale(PGA,nocturnal back pain VAS,total back pain VAS,BASDAI,BASFI)and ASQoL,and showed a correlation between disease assessment scale(PGA,nocturnal back pain VAS,total back pain VAS,BASDAI,and total back pain).CONCLUSIONThe study confirmed the association of pain,condition assessment scales and quality of life.Fatigue,psychological problems,and increased workload were also observed in axSpA patients.Therefore,to improve the quality of life of axSpA patients comprehensively,in addition to improving the treatment effect of patients,the joint efforts of medical workers,patients’ families and the patients themselves are also requiredPart II Exploring Common Risk Genes for Ankylosing Spondylitis and Crohn’s Disease Based on Gene Expression Profile and GWASOBJECTIVEThe co-morbidities of ankylosing spondylitis(AS)and Crohn’s disease(CD)pose challenges for gastroenterologists and rheumatologists.To uncover the association between AS and CD,this study used gene expression microarray and GWAS to explore common risk genes for both diseases.METHODSTwo expression spectrum chip datasets,GSE73754(AS vs.HC)and GSE119600(CD vs.HC),were selected from the GEO database and differentially analyzed using GE02R in both disease groups.Subsequently,we obtained co-up-regulated differentially expressed genes(DEGs)and co-down-regulated DEGs for both diseases by Venn analysis,followed by functional enrichment annotation for up-regulated DEGs and down-regulated DEGs using Metascape.Protein-protein interaction networks(PPI)and core gene analysis were performed exclusively for up-regulated DEGs,using STRING online and Cytoscape software,respectively.To explore the enrichment of inflammatory and cytokine pathways in both disease datasets,we used Genset Enrichment Analysis(GSEA)to analyze gene expression in both disease datasets.Finally,overlapping genes were obtained by Venn analysis using DEGs from the two disease-associated genes in the GWAS study and miRNA-mRNA regulatory network analysis of overlapping genes using miRWalk and miRTarBase datasets.RESULTS(1)A total of 149 co-up-regulated DEGs and 82 co-down-regulated DEGs were identified between the two disease groups of AS and CD,and GO/KEGG functional enrichment analysis was performed on the co-up/down-regulated DEGs using Metascape.Seven hub genes were found from the PPI network that DEGs,which were DICERl、RPL9、RPL17、RPL14、EIF3M、EEF1B2、LYAR、RPS4X、RPL10A、RPL12、RPL36AL、RPS15A、FBL、RPS17、PSMA6、TCP1.After their functional enrichment analysis,it was found that these genes were enriched in cellular tissue processing pathways,such as Eukaryotic Translation Elongation,Nop56p-associated pre-rRNA complex,60S ribosomal subunit,cytoplasmic,Formation of the ternary complex,and subsequently,the 43S complex,etc.(2)The GSEA results of the two disease datasets showed that relatively highly expressed genes in AS samples could be enriched to 10 inflammation-related gene sets,and CD samples could be enriched to 24 inflammation-related gene sets.Among them,9 gene sets are enriched gene sets shared by the two disease datasets,including:"GH_PATHWAY","IL7_PATHWAY","PAR1_PATHWAY","IL3_PATHWAY","P38MAPK_PATHWAY","IL6_PATHWAY","TOLL_PATHWAYM","MAPK_PATHWAY","IL2RB_PATHWAY".In addition,AS and CD samples were also significantly enriched in "WP_IL17_SIGNALING_PATHWAY"compared with healthy controls.(3)We searched the GWAS catalog and published literature for common risk genes of AS and CD,and found that 7 genes overlapped with the common up-regulated DEGs,namely ANTXR2,ERAP2,LRRK2,STAT3,TRIB1,HSPA6,and PSMA6.Using the website to predict the miRNAs of these 7 genes,a total of 64 target miRNAs were found to be related to them.The study found that these genes have certain significance in explaining the co-morbidity mechanism ofA S and CD.CONCLUSIONIn this study,through GSEA analysis of the gene expression profiles of AS and CD,a total of 9 inflammation-related pathways were found to be enriched in the disease groups.Based on the gene expression profiling chip data and GWAS,this study also identified 7 common risk genes for AS and CD,providing some clues for the subsequent exploration of the association between AS and IBD.These genes may be targets for diagnosis and treatment in the future. |
