清华大学玉泉医院(清华大学中西医结合医院)内分泌科,北京 100040
高慧娟,女,34岁,博士,主治医师、助理教授。研究方向:中西医结合防治内分泌代谢病。
冯兴中,E-mail: fengxz9797@sina.com
纸质出版日期:2024-02-25,
收稿日期:2023-05-04,
扫 描 看 全 文
高慧娟,冯兴中.基于血浆蛋白质组学与代谢组学技术探讨2型糖尿病气阴两虚证的生物学基础[J].北京中医药,2024,43(2):133-141.
GAO Hui-juan,FENG Xing-zhong.Study on biological basis of Qi and Yin deficiency syndrome in type 2 diabetes based on plasma proteomics and metabolomics[J]. Beijing Journal of Traditional Chinese Medicine,2024,43(02):133-141.
高慧娟,冯兴中.基于血浆蛋白质组学与代谢组学技术探讨2型糖尿病气阴两虚证的生物学基础[J].北京中医药,2024,43(2):133-141. DOI: 10.16025/j.1674-1307.2024.02.006.
GAO Hui-juan,FENG Xing-zhong.Study on biological basis of Qi and Yin deficiency syndrome in type 2 diabetes based on plasma proteomics and metabolomics[J]. Beijing Journal of Traditional Chinese Medicine,2024,43(02):133-141. DOI: 10.16025/j.1674-1307.2024.02.006.
目的
2
用血浆蛋白质组学与代谢组学技术分析2型糖尿病气阴两虚证的生物学基础。
方法
2
选择2018年5月—2018年9月于首都医科大学附属北京世纪坛医院2型糖尿病气阴两虚证患者30例(Q组),2型糖尿病非气阴两虚证患者30例(F组),健康对照组30例(N组)。用Label free蛋白质组学方法对3组血浆样本进行差异蛋白分析,得到组间差异表达蛋白,采用KEGG pathway、String数据库对差异表达蛋白进行生物信息学分析;采用LC-MS联用技术对3组血浆样本进行差异代谢产物分析,用多维分析和单维分析相结合的方法筛选3组间差异代谢物,通过HMDB数据库进行搜库鉴定,并对筛选出的差异代谢物进行KEGG pathway分析,探索差异代谢物可能参与的代谢途径。
结果
2
血浆蛋白质组学结果:在2型糖尿病组与健康对照组间筛选出差异蛋白119个,其中表达上调的有55个,表达下调的有64个;2型糖尿病气阴两虚证组与非气阴两虚证组间筛选出差异蛋白89个,其中表达上调的有51个,表达下调的有38个;2型糖尿病气阴两虚证组与非气阴两虚证组、健康对照组间筛选出差异表达蛋白18个,其中表达上调的有8个,表达下调的有10个。KEGG pathway分析发现PI3K-AKT信号通路、肾素分泌、IL-17等信号通路与2型糖尿病气阴两虚证的发生发展密切相关。血浆代谢组学结果:在2型糖尿病组与健康对照组间筛选出差异代谢产物32个。KEGG pathway分析发现支链氨基酸(BCAAs)合成与代谢途径、甘油磷脂代谢、丙氨酸、天冬氨酸和谷氨酸代谢途径可能与2型糖尿病的发生发展密切相关。进一步整合蛋白质组学与代谢组学结果发现,BCAAs代谢通路、PI3K-AKT信号通路均与2型糖尿病气阴两虚证密切相关。
结论
2
血浆高水平的BCAAs可能通过抑制PI3K-AKT信号通路导致胰岛素信号通路受损,从而促进2型糖尿病气阴两虚证的发生发展。
Objective
2
To analyze the biological basis of qi and yin deficiency syndrome in type 2 diabetes by using proteomics and metabolomics technology.
Methods
2
From May 2018 to September 2018, 30 cases of type 2 diabetes with qi-yin deficiency syndrome (group Q), 30 cases of type 2 diabetes with non qi-yin deficiency syndrome (group F) and 30 cases of healthy control group (group N) were enrolled in Beijing Shijitan Hospital affiliated to the Capital Medical University. Label free proteomics method was used to analyze the differential proteins of three groups of plasma samples,and the differential expression proteins between groups were obtained. KEGG pathway and String database were used to analyze the bioinformatics of the differential expression proteins. LC-MS combined technology was used to analyze differential metabolites in three groups of plasma samples. A combination of multidimensional analysis and single dimensional analysis was used to screen differential metabolites among the three groups. The HMDB database was searched and identified, and KEGG path analysis was performed on the screened differential metabolites to explore the metabolic pathways in which differential metabolites may participate.
Results
2
The results of plasma proteomics were that 119 differential proteins were screened between the type 2 diabetes group and the healthy control group,of which 55 were up-regulated and 64 were down-regulated;89 differential proteins were screened out between type 2 diabetes with qi-yin deficiency syndrome and non qi-yin deficiency syndrome, among which 51 were up-regulated and 38 were down-regulated;18 differentially expressed proteins were screened out between the type 2 diabetes group with qi and yin deficiency syndrome,the non qi and yin deficiency syndrome group and the healthy control group,of which 8 were up-regulated and 10 were down-regulated. KEGG pathway analysis found that PI3K-AKT signaling pathway, renin secretion, IL-17 and other signaling pathways were closely related to the occurrence and development of qi-yin deficiency syndrome in type 2 diabetes. The results of plasma metabonomics were that 32 differential metabolites were screened out between the type 2 diabetes group and the healthy control group. KEGG pathway analysis found that branched chain amino acid (BCAAs)synthesis and metabolic pathway, glycerol phospholipid metabolism, alanine, aspartic acid and glutamic acid metabolic pathway may be closely related to the occurrence and development of type 2 diabetes. Further integration of proteomics and metabolomics results found that BCAAs were closely related to PI3K-AKT signaling pathway.
Conclusion
2
High levels of BCAAs in plasma may cause damage to insulin signaling pathway by inhibiting PI3K-AKT pathway, leading to the occurrence and development of Qi and Yin deficiency syndrome in type 2 diabetes.
蛋白质组学代谢组学2型糖尿病气阴两虚证
Proteomicsmetabolomicstype 2 diabetesQi and Yin deficiency syndrome
MAGLIANO DJ, ISLAM RM, BARR E, et al. Trends in incidence of total or type 2 diabetes: systematic review[J]. BMJ, 2019,366:l5003.
CHAN J, LIM LL, WAREHAM NJ, et al. The lancet commission on diabetes: using data to transform diabetes care and patient lives[J]. Lancet, 2021,396(10267):2019-2082.
HU RF, SUN XB. Design of new traditional Chinese medicine herbal formulae for treatment of type 2 diabetes mellitus based on network pharmacology[J]. Chin J Nat Med, 2017,15(6):436-441.
NIE C, HE T, ZHANG W, et al. Branched chain amino acids: beyond nutrition metabolism[J]. Int J Mol Sci, 2018,19(4).
王露露, 李冰, 王圳伊,等. 基于“整体观”系统生物学技术在中药研究中的应用进展[J]. 中草药,2020,51(19):5053-5064.
霍梦琪,彭莎,任越,等.基于系统中药学的中药功效标志物发现与应用[J].中国中药杂志,2020,45(14):3245-3250.
WANG T, LIU J, LUO X, et al. Functional metabolomics innovates therapeutic discovery of traditional Chinese medicine derived functional compounds[J]. Pharmacol Ther, 2021,224:107824.
QU T, GAO Y, LI A, et al. Systems biology analysis of the effect and mechanism of total flavonoids of Astragali Radix against cyclophosphamide-induced leucopenia in mice[J]. J Pharm Biomed Anal, 2021,205:114357.
徐欣, 张文华, 罗夏琳,等. 系统生物学驱动的小分子代谢组学策略创新驱动中药现代研究[J]. 世界科学技术-中医药现代化,2019,21(3):333-341.
SEYHAN AA, CARINI C. Are innovation and new technologies in precision medicine paving a new era in patients centric care?[J]. J Transl Med, 2019,17(1):114.
MAUVOISIN D. Circadian rhythms and proteomics: It's all about posttranslational modifications![J]. Wiley Interdiscip Rev Syst Biol Med, 2019,11(5):e1450.
左舒颖, 倪青. 2型糖尿病病证结合治疗体会[J]. 北京中医药,2017,36(6):537-540.
智宇星, 李红梅, 徐安龙. 中西医学视角下对免疫的再认识:基于辨证论治和免疫态的讨论[J]. 中医杂志,2022,63(21):2001-2008.
ZHOU M, SHAO J, WU CY, et al. Targeting BCAA catabolism to treat obesity-associated insulin resistance[J]. Diabetes, 2019,68(9):1730-1746.
BLOOMGARDEN Z. Diabetes and branched-chain amino acids: What is the link[J]. J Diabetes, 2018,10(5):350-352.
CROSSLAND H, SMITH K, IDRIS I, et al. Exploring mechanistic links between extracellular branched-chain amino acids and muscle insulin resistance: an in vitro approach[J]. Am J Physiol Cell Physiol, 2020,319(6):C1151-C1157.
ZONCU R, EFEYAN A, SABATINI DM. mTOR: from growth signal integration to cancer, diabetes and ageing[J]. Nat Rev Mol Cell Biol, 2011,12(1):21-35.
MA X M, BLENIS J. Molecular mechanisms of mTOR-mediated translational control[J]. Nat Rev Mol Cell Biol, 2009,10(5):307-318.
YU Y, YOON S O, POULOGIANNIS G, et al. Phosphoproteomic analysis identifies Grb10 as an mTORC1 substrate that negatively regulates insulin signaling[J]. Science, 2011,332(6035):1322-1326.
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构