1.Statins decreases expression of five inflammation-associated microRNAs in the plasma of patients with unstable angina
Jing ZHANG ; Jingyi REN ; Hong CHEN ; Guanping HAN
Journal of Peking University(Health Sciences) 2015;(5):761-768
Objective:To explore the influence of treatment with HMG-CoA reductase inhibitors ( sta-tins) on the expression profile of microRNAs ( miRNAs) in the plasma of patients with unstable angina ( UA) .Methods:The Taqman low-density miRNA array ( TLDA) and significance analysis of microar-rays ( SAM) were used to identify distinct miRNA expression profiles in the plasma of UA patients treated with long-term and regular statins ( UA receiving statins , n=6 ) compared with UA patients who had not received statins therapy before ( UA received no statins , n=6 ) .These differentially expressed miRNAs discovered in the profiling were further validated by real-time PCR in another 20 controls with non-cardiac chest pain , 26 UA patients received no statins , and 19 UA patients received statins .Results: By using TLDA and SAM , significantly decreased expression levels of 21 miRNAs were observed in the UA pa-tients receiving statins compared with those who received no statins ( fold change >3 and false discovery rate<0 .0001%) .The unsupervised hierarchical clustering based on miRNA expression clearly separa-ted the UA patients receiving statins from those who received no statins .Consistent with the profiling da-ta, the levels of 5 inflammation-associated miRNAs (miR-106b, miR-21, miR-25, miR-451, and miR-92a) were down regulated (P<0.05) in the UA patients receiving statins compared with those who re-ceived no statins.Conclusion: A group of inflammation-associated miRNAs, consisting of miR-106b, miR-21, miR-25, miR-451, and miR-92a, could be decreased by treatment with statins and may be used as a novel biomarker for effectiveness of statins therapy in patients with UA .
2.Metformin down-regulates the expression of regulators of G protein signaling in OLETF rats
Zongdong YU ; Jialin SU ; Kang LI ; Xujie ZHOU ; Guanping HAN ; Nana SONG ; Cheng CHEN ; Yumin DUAN ; Xiaohui GUO ; Yong HUO
Chinese Journal of Diabetes 2010;18(1):54-56
Objective To investigate the expression of regulators of G protein signaling(RGS), including RGS2, RGS3 and RGS4 in OLETF rats, as well as the effects of metformin on these expressions. Methods LETO rats were used as control group. Eight-week-old male OLETF rats were assigned to two guoups randomly:model and trial(metfomin dose during 8~(th) to 22~(nd) weeks:300mg kg~(-1)·d~(-1);during 23rd to 28th weeks:400 mg·kg~(-1) ·d~(-1))groups. Expressions of RGS mRNA in aorta and heart werequantified by real-time PCR. Results RGS2, RGS3 and RGS4 mRNA of the thoracic aorta and left ventricle were significantly higher in model group than in control group (P<0.01). Compared with model group, metformin significantly reduced their mRNA in trial group (P<0.01). Conclusions Upregulation of RGS2, RGS3 and RGS4 mRNA expression in the thoracic aorta and left ventricle of OLETF rats is in correlation with cardiovascular lesions; while downregulation of their expression is in correlation with the action of metformin.
3.Establishment and application of big data sharing innovation system of national clinical medical research center
Tingyin CHEN ; Song FENG ; Guanping HAN ; Jun YAN ; Guihu ZHAO ; Zhuozhong WANG ; Hua GUO
Chinese Journal of Hospital Administration 2022;38(5):337-342
In order to effectively integrate scientific research data resources and improve data utilization, the National Clinical Medical Research Center had built a "3321" -integration big data sharing innovation platform. By providing full support to scientific research, sorting out the distribution mechanism of achievements, and formulating authority management norms, the big data platform had solved the weaknesses in data sharing ability, sharing willingness, and sharing security, giving full play to the effectiveness of the clinical research big data platform. By February 2022, the center had collected more than 1.04 million elderly patients data through the big data platform, as well as carried out 75 scientific research projects, and established 10 large population-based clinical research queues. The big data platform had realized full coverage of major diseases in the field of geriatric diseases, promoted the high-quality construction of the national clinical medical research center, and improved the scientific research and innovation ability of the cooperative units.