Message Board

Respected readers, authors and reviewers, you can add comments to this page on any questions about the contribution, review,        editing and publication of this journal. We will give you an answer as soon as possible. Thank you for your support!

Name
E-mail
Phone
Title
Content
Verification Code
x Close Forever Close
Volume 36 Issue 3
. 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Pharmaceutical Practice and Service  > 2018  >  36(3): 198-203

LIU Shiyu, ZHAO Liang, CHEN Jun, ZHANG Guoqing. Research progress in depression related biomarkers based on omics technology[J]. Journal of Pharmaceutical Practice and Service, 2018, 36(3): 198-203. doi: 10.3969/j.issn.1006-0111.2018.03.002
Citation: LIU Shiyu, ZHAO Liang, CHEN Jun, ZHANG Guoqing. Research progress in depression related biomarkers based on omics technology[J]. Journal of Pharmaceutical Practice and Service, 2018, 36(3): 198-203. doi: 10.3969/j.issn.1006-0111.2018.03.002
shu

Research progress in depression related biomarkers based on omics technology

doi: 10.3969/j.issn.1006-0111.2018.03.002

  • Department of Pharmacy, Third Hospital Affiliated to Second Military Medical University, Shanghai 200438, China

  • Received Date: 2017-11-18
  • Rev Recd Date: 2018-04-10
  • In recent years,the incidences of depression increased year by year due to increased social pressure,which do serious harm to human being both physically and mentally.Studies have shown that the pathogenesis of depression is complicated,mainly related to body's inflammation,neurotrophic and metabolic processes.There were no sufficient objective bases for the clinical diagnosis of depression.The drug treatment result was not satisfactory.Therefore,biomarkers become more and more important in disease risk prediction,classification,diagnosis and prognosis.The rapid developments in genomics,transcriptomics,proteomics,metabolomics and their applications in the diagnosis make it possible to further screen for depression related biomarkers.This article reviewed the research progresses in depression related biomarkers with omics technologies.
  • [1] 李爱玲,宋健.生物标志物分类及其在临床医学中的应用[J].中国药理学与毒理学杂志,2015,29(1):7-13.
    [2] 王睿, 黄树明.抑郁症发病机制研究进展[J].医学研究生学报, 2015, 27(12):1332-1336.
    [3] 虞萌,黄家恺,巴俊强,等. 生物标志物的筛查方法及研究进展[J]. 医学综述,2017,23(05):867-871.
    [4] 苑杰. 抑郁症生物标志物研究进展[J]. 国际精神病学杂志,2015, 6(02):103-107.
    [5] 朱立静,孙冰婷,宗阳,等. 抑郁症组学生物标志物的研究进展[J]. 中国医院药学杂志,2016,36(23):2131-2134.
    [6] Watanabe SY, Iga J, Ishii K, et al. Biological tests for major depressive disorder that involve leukocyte gene expression assays[J]. J Psychiatr Res,2015,66-67:1-6.
    [7] Fuchikami M, Morinobu S, Segawa M, et al. DNA methylation profiles of the brain-derived neurotrophic dactor (BDNF) gene as a potent diagnostic biomarker in major depression[J]. PLoS ONE,2011,6(8):e23881.
    [8] Fan HM, Sun XY, Guo W, et al. Differential expression of microRNA in peripheral blood mononuclear cells as specific biomarker for major depressive disorder patients[J]. J Psychiatr Res,2014,59:45-52.
    [9] Cui X, Sun X, Niu W, et al. Long non-coding RNA:potential diagnostic and therapeutic biomarker for major depressive disorder[J]. Med Sci Monit,2016,22:5240-5248.
    [10] Gururajan A, Naughton ME, Scott KA, et al. MicroRNAs as biomarkers for major depression:a role for let-7b and let-7c[J]. Transl Psychiatry,2016,6(8):e862.
    [11] Powell TR, Mcguffin P, D'Souza UM, et al. Putative transcriptomic biomarkers in the inflammatory cytokine pathway differentiate major depressive disorder patients from control subjects and bipolar disorder patients[J]. PLoS One,2014,9(3):e91076.
    [12] Herve M, Bergon A, Le Guisquet AM, et al. Translational identification of transcriptional signatures of major depression and antidepressant response[J]. Front Mol Neurosci,2017,10:248.
    [13] Hennings JM, Uhr M, Klengel T, et al. RNA expression profiling in depressed patients suggests retinoid-related orphan receptor alpha as a biomarker for antidepressant response[J]. Transl Psychiatry,2015,5(3):e538.
    [14] 李林蔚,丁德馨,李广悦,等. 蛋白质组学技术在筛选生物标志物方面的应用研究进展[J]. 中南医学科学杂志,2015,43(03):322-325.
    [15] Bot M, Chan MK, Jansen R, et al. Serum proteomic profiling of major depressive disorder[J]. Transl Psychiatry,2015,5(7):e599.
    [16] 宋轶任. 双相Ⅱ型情感障碍患者与抑郁症患者的血浆比较蛋白质组学研究[D].重庆:重庆医科大学,2016.
    [17] 曹莉莎,张芳,罗文,等. 抑郁大鼠海马组织的比较蛋白质组学研究[J]. 中国药理学通报,2016,32(5):697-702.
    [18] 詹远. 基于iTRAQ技术的卒中后抑郁症患者血浆蛋白质组学研究[D].重庆:重庆医科大学,2014.
    [19] Zhan Y, Yang YT, You HM, et al. Plasma-based proteomics reveals lipid metabolic and immunoregulatory dysregulation in post-stroke depression[J]. European Psychiatry,2014(29):307-315.
    [20] Lee MY, Eun YK, Kim SH, et al. Discovery of serum protein biomarkers in drug-free patients with major depressive disorder[J]. Biological Psychiatry,2016(69):60-68.
    [21] 陈宇. 基于蛋白芯片技术筛选抑郁症血浆的诊断标志物[D].重庆:重庆医科大学,2014.
    [22] 徐红波. 基于iTRAQ技术筛选抑郁症相关血浆蛋白和氨基酸的初步研究[D].重庆:重庆医科大学,2012.
    [23] 胡永波,周健,刘海朋,等. 抑郁模型大鼠海马突触的差异蛋白质组学分析[J]. 世界科技研究与发展,2011,31(2):305-310.
    [24] 颜因,曹莉莎,李敏,等. 氟西汀作用于慢性温和不可预见性应激大鼠海马组织前后的差异蛋白质组学研究[J]. 川北医学院学报,2016,31(3):336-341.
    [25] 武冬. 基于代谢组学的抑郁症患者粪便研究[D].重庆:重庆医科大学,2016.
    [26] 夏小涛、孙宁、刘彩春. 基于1H NMR代谢组学的抑郁症生物标志物发现及帕罗西汀干预作用[J]. 药学学报,2016,51(4):595-599.
    [27] 和昱辰. 抑郁症患者血清代谢物及组学的初步研究[D].重庆:第三军医大学,2014.
    [28] 田俊生,史碧云,冯光明,等.慢性温和不可预知应激抑郁模型大鼠粪便1H-NMR代谢组学研究[J]. 中草药,2013,44(22):3170-3176.
    [29] 马致洁,张祎,董捷鸣,等. 基于代谢组学方法的姜黄素抗抑郁作用生物标志物初步筛查[J]. 中国中药杂志,2017,42(18):3596-3601.
    [30] 杜红丽. 知母百合协同抗抑郁的代谢组学研究[D].上海:第二军医大学,2016.
    [31] 赵思俊,赵晓喆,向欢,等. 基于代谢通路调控的沙棘籽油抗抑郁作用机制研究[J]. 中草药,2017,48(13):2682-2690.
    [32] 刘彩春. 逍遥散临床治疗抑郁症的血浆代谢组学研究[D].太原:山西大学,2016.
    [33] 陈建军.筛选抑郁症性别差异性诊断标志物[D].重庆:重庆医科大学,2016.
    [34] 冯光明. 逍遥散治疗抑郁症的临床观察及1H-NMR代谢组学研究[D].太原:山西大学,2014.
    [35] 周新雨. 儿童青少年抑郁症的临床治疗及血浆代谢组学研究[D].重庆:重庆医科大学,2016.
    [36] 郑姝宁. 抗抑郁药物氟西汀和活性化合物油酰胺作用机制的代谢组学研究[D].沈阳:沈阳药科大学,2011.
    [37] 郭晓擎. 复方柴归方抗抑郁有效组分筛选及其药效学评价研究[D].太原:山西大学,2013.
    [38] 彭国茳. 基于尿液代谢组学的逍遥散抗抑郁临床疗效分析[D].太原:山西大学,2015.
    [39] 康雷,江涛,葛新星,等. 荷瘤抑郁样模型小鼠的血清代谢组学研究[J]. 现代生物医学进展,2014,14,(1):42-46.
    [40] 彭扬. 抑郁症患者尿液比较蛋白质组学研究[D].重庆:重庆医科大学,2013.
    [41] 吴玉. 抑郁模型小鼠前额叶的代谢组学研究[D].重庆:重庆医科大学,2016.
    [42] 提喀斯木·尼扎,木丁麦合苏木·艾克木,买吾拉尼江·依孜布拉,等. 基于代谢组学方法研究异常黑胆质成熟剂对抑郁症大鼠血浆代谢的影响[J]. 新疆医科大学学报,2014,39(1):1-6
    [43] 田俊生,左亚妹,孙海峰,等. GC-MS代谢组学分析逍遥散干预抑郁模型大鼠盲肠代谢物组的变化规律[J]. 中草药,2015,46(13):1931-1936.
    [44] 陈磊,郑晓芬,高晓霞,等. 代谢组学研究复方柴归方超临界CO2提取物抗抑郁作用及其机制[J]. 中国中药杂志,2014,39(14):2744-2750.
    [45] 金志国,刘炜. 四逆散干预抑郁症大鼠的生物标志物筛查与代谢通路分析[J]. 中药药理与临床,2017,33(4):10-13.
    [46] 郭秉荣,杨岚,刘佳丽,等. 慢性不可预知温和应激配合孤养抑郁模型大鼠海马的代谢组学研究[J]. 中国药学杂志,2013(14):1160-1164.
    [47] 于牡丹,肖云峰,王玉华.代谢组学在中药复方研究中的应用进展[J]. 中南药学,2016,121(2):182-185.
    [48] 杨中良. 代谢组学在中医中药领域的应用进展[J].中国科技核心期刊,2015,35(1):204-206
    [49] 曹蓓. 代谢组学在临床研究中的应用及进展[J].生命科学,2010,22(8):761-771.
    [50] 陈文才,高燕红,杨杏芬. 代谢组学中生物标志物确认方法研究进展[J]. 中国职业医学,2015,42(4):446-450.
    [51] 杨钦焱,周敏,罗春琼,等. 抑郁症的诊断研究进展[J]. 国际精神病学杂志,2014,41(2):100-102.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Get Citation
PDF
XML

Article Metrics

Article views(3897) PDF downloads(658) Cited by()

Related
Proportional views

Research progress in depression related biomarkers based on omics technology

doi: 10.3969/j.issn.1006-0111.2018.03.002
  • Department of Pharmacy, Third Hospital Affiliated to Second Military Medical University, Shanghai 200438, China
  • Received Date: 2017-11-18
  • Rev Recd Date: 2018-04-10

Abstract: In recent years,the incidences of depression increased year by year due to increased social pressure,which do serious harm to human being both physically and mentally.Studies have shown that the pathogenesis of depression is complicated,mainly related to body's inflammation,neurotrophic and metabolic processes.There were no sufficient objective bases for the clinical diagnosis of depression.The drug treatment result was not satisfactory.Therefore,biomarkers become more and more important in disease risk prediction,classification,diagnosis and prognosis.The rapid developments in genomics,transcriptomics,proteomics,metabolomics and their applications in the diagnosis make it possible to further screen for depression related biomarkers.This article reviewed the research progresses in depression related biomarkers with omics technologies.

LIU Shiyu, ZHAO Liang, CHEN Jun, ZHANG Guoqing. Research progress in depression related biomarkers based on omics technology[J]. Journal of Pharmaceutical Practice and Service, 2018, 36(3): 198-203. doi: 10.3969/j.issn.1006-0111.2018.03.002
Citation: LIU Shiyu, ZHAO Liang, CHEN Jun, ZHANG Guoqing. Research progress in depression related biomarkers based on omics technology[J]. Journal of Pharmaceutical Practice and Service, 2018, 36(3): 198-203. doi: 10.3969/j.issn.1006-0111.2018.03.002
shu

    HTML

Reference (51)

Catalog

    版权所有：《药学实践与服务》编辑委员会

    Supervisor & Sponsors: Address: No 325 Guohe Road, ShanghaiPost Code: 200433

    Tel: （021）81871324,81871397 E-mail: yxsjzzs@163.com

    网站备案号 沪ICP备05003363号-1

    Supported by: Beijing Renhe Information Technology Co., Ltd.  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return