1.Research progress of sulfation modification of chondroitin sulfate and chondroitin sulfate preparation in Kashin-Beck disease and osteoarthritis
Yizhen LYU ; Huan DENG ; Ziwei GUO ; Jiaxin LIU ; Yan ZHAO ; Lichun QIAO ; Xiang XIAO ; Yang SHEN ; Xuan LIU ; Jing HAN
Chinese Journal of Endemiology 2021;40(11):942-946
Chondroitin sulfate (CS) is a sulfurated glycosaminoglycan, a major component of the extracellular matrix, widely distributed in skin, cartilage and vascular tissue. CS plays an important role in the physiological state regulation of articular cartilage, which affects tensile strength and elasticity of tissues by influencing aggrecan. Previous studies have shown that CS sulfate modification may be related to the growth and development disorders of cartilage tissue and the occurrence of osteoarticular diseases. At the same time, CS is also a common joint supplement, often used in the treatment of osteoarthritis and Kashin-Beck disease. In this paper, the research progress of CS sulfate modification characteristics in Kashin-Beck disease and osteoarthritis and the application of the preparation in the treatment of Kashin-Beck disease and osteoarthritis are reviewed, aiming to provide help for the investigation of the etiology of Kashin-Beck disease and the treatment of osteoarthritis and Kashin-Beck disease.
2.gwasfilter: an R script to filter genome-wide association study
Songchun YANG ; Chongyang LI ; Yizhen HU ; Qiufen SUN ; Jianqiao PAN ; Dianjianyi SUN ; Baoshan MA ; Jun LYU ; Liming LI
Chinese Journal of Epidemiology 2021;42(10):1876-1881
Objective:To develop an R script that can efficiently and accurately filter genome-wide association studies (GWASs) from the GWAS Catalog Website.Methods:The selection principles of GWASs were established based on previous studies. The process of manual filtering in the GWAS Catalog was abstracted as standard algorithms. The R script (gwasfilter.R) was written by two programmers and tested many times.Results:It takes six steps for gwasfilter.R to filter GWASs. There are five main self-defined functions among this R script. GWASs can be filtered based on "whether the GWAS has been replicated" "sample size" "ethnicity of the study population" and other conditions. It takes no more than 1 second for this script to filter GWASs of a single trait.Conclusions:This R script (gwasfilter.R) is user-friendly and provides an efficient and standard process to filter GWASs flexibly. The source code is available at github ( https://github.com/lab319/gwas_filter).