Synovial Proteomic Research On Human Knee Osteoarthritis And Meta Analysis Of The Osteoarthritic Epidemiology In China

BackgroundOsteoarthritis is a common diseases of aging, which cause serious damage to physical and mental health of the elderly. Its incidence has obvious characteristics of gender, age, and the geographical distribution, and it is high in China and the other developing countries. Although the results of the study suggest that the onset of osteoarthritis and cartilage degeneration and genetic factors and environmental factors are closely related, but the pathogenesis of osteoarthritis is still unknown. Due to lack of specific molecular biomarkers in early osteoarthritis diagnosis and monitoring, most of the diagnosis in patients with osteoarthritis has been in the middle or late stage. In patients with early osteoarthritis after diagnosis, early intervention, can avoid further joint deterioration, thus reducing the prevalence of middle and late osteoarthritis. So discovering new osteoarthritis molecular biomarkers will help the early diagnosis, treatment and pathogenesis of osteoarthritis.In recent years, the related emerging technologies of proteomics has become effective tools by protein molecular biomarkers researching kinds of clinical chronic disease screening and early diagnosis, as well as provide the reliable technology platform for osteoarthritis specific mechanism of the occurrence and development research. Commonly used proteomic analysis technology is two dimensional gel electrophoresis (2-D GE), but it has shortcomings of the poor sensitivity, specificity and repeatability, and the separation of the small molecular protein, hydrophobic protein and membrane protein has many restrictions. So the higher flux, more accurate quantitative proteomic technology is necessary. Based on stable isotope labeling and reversed-phase liquid chromatography-mass spectrometry, quantitative proteomic technology is one of the proteomics research by the rapid development of technology in the field, including18O stable isotope labeling with relatively simple technology, reagent cheaper, less processing steps and the advantages of easy mass detection, more and more attention on the field of quantitative proteomics research.Osteoarthritic articular cartilage, synovium, and the same origin of the synovial tissue with normal tissue of comparative proteomics research for osteoarthritis provide the most direct and the most reasonable approach of the determination of molecular markers and design of targeted therapy drugs. However, the use of tissue samples in proteomics technology research exist the main obstacle of organization heterogeneity, etc.. Therefore, in order to improve the comparative proteomics technology research, the effectiveness of screening for osteoarthritis molecular markers is necessary to mix as much as possible source of heterogeneity of specimen amount for proteomics research.For isolation and identification of osteoarthritis associated protein molecules, and screening for osteoarthritis molecular targets, this research adopts9patients with osteoarthritis of the knee joint synovial fluid and9cases of normal, the two groups after the amount of mixed by hyaluronidase enzyme solution to reduce viscosity of hyaluronic acid, and then use18O stable isotope to label one of the group after mixing, using reverse phase liquid chromatography-mass spectrometry quantitative proteomic methods to separate identification of differences between the two kinds of synovial fluid protein. Further validation was taken by means of bioinformatics and discussing the differences in protein function correlation and clinical pathological significance. Finally through a systematic review and meta-analysis of osteoarthritis in literature integration analysis of epidemiological cross-sectional study, clinical prevention, control and prognosis estimation of osteoarthritis provide evidence of evidence-based medicine.Chapter1Research on application of isotope labelling and RPLC-MS in knee synovial fluid proteomics of osteoarthritisObjective:To study the radioactive isotope labeling combining upgrade reversed-phase liquid chromatography tandem mass spectrometry (Nano-RPLC-MS/MS) in patients with knee osteoarthritis joint synovial fluid, with the application of knowledge of osteoarthritic synovial joints proteomics differences and exploring the molecular markers in early diagnosis of osteoarthritis.Methods:Apply1D-SDS-PAGE technology for preliminary separation of two samples of total protein, optimization of stable and efficient18O/16O markers, and18O/16O mark of distinction of normal and osteoarthritis knee joint synovial fluid in patients with peptide mixture, apply Nano-RPLC-MS to separate and identify different protein.Results:Through the electrophoretic separation, it functions reaching the peak of protein, and the establishment of a stable and efficient18O markers, a total separation identified25kinds of different proteins. On behalf of the differences in protein are as follows: TTHY_HUMAN (Transthyretin). APOA1_HUMAN (Apolipoprotein A-I)、HEMO_HUMAN (Hemopexin、C03_HUMAN (Complement C3)、PRG4_HUMAN (Proteoglycan4)、VTDB_HUMAN (Vitamin D-binding protein)。Conclusion:The combination of18O stable isotope labeling, RPLC MS quantitative and quantitative proteomic technology can accurately identify osteoarthritis differences in protein. This technology provides new technology and ideas for osteoarthritis in early diagnosis and screening. Chapter2Bioinformatics analysis of differential protein in synovial fluidObjective:To predict the network information such as the function of the difference of protein, and build the knee osteoarthritis joint synovial fluid proteome database.Methods:Use the gene ontology (GO) analyze different proteins from cell components and function of molecules and biological process proportion. Use the STRING v9.1analyze differences between protein interaction networks.Results:According to the different GO analysis from the components of cells, proteins in the plasma lipoprotein particle proportion is the largest, accounting for35%, followed by a very low density lipoprotein, accounted for22%, suggest lipoprotein in synovial fluid play a role in the onset of osteoarthritis. Based on the analysis from molecular function GO differences in protein, serine-type peptides in enzyme inhibitors and the activity of enzyme inhibitors is stronger,15%and14%respectively, suggest enzyme inhibitors are associated with osteoarthritis. Based on the analysis from the biological processes GO difference proteins, acute inflammatory reaction and post-traumatic stress is given priority, suggest osteoarthritis may be associated with local inflammatory response. Differences in protein of STRING analysis show that most proteins have synergy in function or other interactions, except for a few function relatively independent proteins.Conclusions:Bioinformatics technology can be used for the differences in protein function prediction and interaction network analysis. It provides a certain direction and basis for osteoarthritis biomarker research.Chapter3Objective:The prevalence of osteoarthritis (OA) varied in different populations and it appeared to be increasing in the past decades. Recent studies suggest that OA is an independent risk factor for quality of life. However, there has not yet been a systematic analysis and meta-analysis of the prevalence of OA in China.Methods:Epidemiological investigations on OA in China published in journals were identified manually and on-line by using SinoMed, Chongqing VIP database, Wanfang Data and CNKI database. Those Reported in English journals were identified using MEDLINE, Elsevier: ScienceDirect, BIOSIS Previews database. Selected studies had to describe an original study defined by strict screening and diagnostic criteria. The random effects model was employed according to statistical test for homogeneity.Results:Fifty-five studies were selected, the statistical information of which was collected for systematic review and meta-analysis. The results showed that the pooled prevalence of knee OA in male was14.2%(95%CI:11.0%-18.1%), but it was24.4%(95%CI:19.3%-30.3%) in female. It was found that sixty-five years was the risk point age in male and it was fifty-five years in female. The prevalence of male and female in eastern and northern China was significantly higher than southern and western China. OA prevalence of the other joints are as follows, for male: Cervical vertebrae7.1%(95%CI:3.3%-14.8%), Thoracic vertebrae0.3%(95%CI:0.2%-0.5%), Lumbar vertebrae12.8%(95%CI:7.1%-22.0%), Hand3.0%(95%CI:1.1%-8.1%), Hip joint0.8%(95%CI:0.1%-7.4%), Sacroiliac joint0.0%(95%CI:0.0%-0.1%), Ankle joint0.2%(95%CI:0.1%-0.4%), Shoulder joint0.4%(95%CI:0.0%-3.8%), Wrist joints0.3%(95%CI:0.2%-0.6%), Elbow joint0.2%(95%CI:0.0%-2.4%), Foot0.2%(95%CI:0.1%-0.6%); for female:Cervical vertebrae11.1%(95%CI:5.2%-22.1%), Thoracic vertebrae0.5%(95%CI:0.2%-0.8%), Lumbar vertebrae17.3%(95%CI:10.4%-27.4%), Hand6.2%(95%CI:2.7%-13.3%), Hip joint0.6%(95%CI:0.1%-3.0%), Sacroiliac joint0.1%(95%CI:0.0%-0.2%), Ankle joint0.4%(95%CI:0.1%-1.2%), Shoulder joint0.6%(95%CI:0.1%-5.6%), Wrist joints0.6%(95%CI:0.4%-0.9%), Elbow joint0.2%(95%CI:0.0%-2.5%), Foot0.3%(95%CI:0.1%-1.0%).Conclusions:The prevalence of OA is different as the gender, the period of age and the area in China. The prevalence increases in eastern and northern China and it increases after65years in male and55in female.