Identification of tRNA-derived Fragments and Their Potential Roles in Atherosclerosis  

作　　者：Jian WANG Pei-kang DONG Xiu-feng XU Tao HUANG Shuai MAO Qing-guo WANG Jie HAO Xiao-hong LIU Xiao-dong SUN Kai KANG Quan ZHANG Jing-tian LI Tao WANG 

机构地区：[1]Department of Cardiology,Affiliated Hospital of Weifang Medical University,Weifang,261031,China [2]Department of Neurology,Affiliated Hospital of Weifang Medical University,Weifang,261031,China [3]Department of Endocrinology,Affiliated Hospital of Weifang Medical University,Weifang,261031,China

出　　处：《Current Medical Science》2021年第4期712-721,共10页当代医学科学（英文）

基　　金：supported by grants from the National Natural Science Foundation of China(No.82000441);Shandong Provincial Natural Science Foundation,China(No.ZR201911090321);Medicine and Health Science Technology Development Program of Shandong Province(No.2018WS050);Shandong Province Traditional Chinese Medicine Science and Technology Development Plan of Shandong Province(No.2019-0426);Shandong Province Higher Educational Science and Technology Program for Youth Innovation(No.2020KJL004).

摘　　要：Objective Atherosclerosis(AS),a chronic inflammatory disease,is the basis of cardiovascular disease(CVD).Although the treatment has been greatly improved,AS still imposes a large burden on human health and the medical system,and we still need to further study its pathogenesis.As a novel biomolecule,transfer RNA-derived fragments(tRFs)play a key role in the progression of various disease.However,whether tRFs contribute to atherosclerosis pathogenesis remains unexplored.Methods With deep sequencing technology,the change of tRFs expression profiles in patients with AS compared to healthy control group was identified.The accuracy of the sequencing data was validated using RT qPCR.Subsequently,we predicted the potential target genes of tRFs by online miRNA target prediction algorithms.The potential functions of tRFs were evaluated with Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses.Results There were 13 tRFs differentially expressed between patients with AS and healthy controls,of which 2 were up-regulated and 11 were down-regulated.Validation by RT-qPCR analysis confirmed the sequencing results,and tRF-Gly-GCC-009 was highly up-regulated in the AS group based on the results of sequencing which was confirmed by RT-qPCR analysis.Furthermore,GO enrichment and KEGG pathway analyses indicated that 10 signaling pathways were related to tRF-Gly-GCC-009.These pathways might be physiopathological fundamentals of AS,mainly involving in Apelin signaling,Notch signaling and calcium signaling.Conclusion The results of our study provide important novel insight into the underlying pathogenesis and demonstrate that tRFs might be potential biomarkers and therapeutic targets for AS in the future.

关 键 词：ATHEROSCLEROSIS noncoding RNAs transfer RNA-derived fragments bioinformatic prediction 

分 类 号：R73[医药卫生—肿瘤]