How to Build CHD@ZJU

CHD related Articles were retrieved from Pubmed, by entering keywords "coronary heart disease" and constrict the publish date from 2000/1/1 to now (2013/1/23). As a result, totally 115898 articles were found and their abstracts were downloaded for text mining. Since some articles didn't contain abstracts, only 88396 abstracts remained.
The text-mining process to get CHD related genes could be divided in to 5 following steps:

  • 1) Extracting all keywords from abstracts and ignoring those keywords start with numbers. 101402 keywords were extracted.

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  • 2) Input these keywords into Gene library in ArrayTrack and find possible related genes. 4674 genes were then found.

  • 3) Put these 4674 genes again into pubmed abstracts to find related aticles. Only genes which offical name or there keyword description (such as prolactin for gene PRL) could be found in the abstract would be remained. As a result, 1247 genes were remained.

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  • 4) Manually examined on the 1247 genes to validate it was acutally related to CHD. Some genes would be filtered if it represents other meanings (such as gene CAD, Entrez ID:790, carbamoyl-phosphate synthetase 2, is mostly meant coronary arterial disease in articles). 681 genes were then validated with at least one reference.

  • 5) All genes was compared with 1078 CHD genes in RGD database, and 370 genes were overlapped. These 370 genes were labels as "RGD_Supported" and the other 293 genes were labels as "REFERED". All 663 genes had supported references in CHD@ZJU which were examined by step 4.

    • How To contact Us

    Collaboration Information: Prof. Xiaohui Fan (fanxh@zju.edu.cn)

    Website using assistance : Leihong Wu (11019004@zju.edu.cn)




    Routine assessment of on-clopidogrel platelet reactivity and gene polymorphisms in predicting clinical outcome following drug-eluting stent implantation in patients with stable coronary artery disease.
  • Author:"Viviani Anselmi, Chiara;Briguori, Carlo;Roncarati, Roberta;Papa, Laura;Visconti, Gabriella;Focaccio, Amelia;De Micco, Francesca;Latronico, Michael V G;Pagnotta, Paolo;Condorelli, Gianluigi"

  • Published Year:2013

  • Journal:JACC. Cardiovascular interventions

  • Abstract:"OBJECTIVES: This study sought to assess the usefulness of clopidogrel-pathway genotyping and on-treatment platelet reactivity (OTR) testing in predicting major adverse cardiac events (MACE) in stable coronary artery disease (CAD) patients receiving drug-eluting stents (DES) under dual antiplatelet (clopidogrel plus aspirin) therapy. BACKGROUND: The role of pharmacogenetics and OTR in predicting MACE-death, myocardial infarction, or stent thrombosis-in stable CAD patients scheduled for DES implantation is still debated. METHODS: Patients with stable CAD treated by DES implantation (n = 1,432) were genotyped with a TaqMan OpenArray (Applied Biosystems, Carlsbad, California) and assessed for OTR with the VerifyNow P2Y12 test (Accumetrics Inc., San Diego, California). Genes tested were ABCB1, CYP1A2, CYP2B6*9, CYP2C8*3, CYP2C9*2, CYP2C19, CYP3A4, CYP3A5*3, P2RY12, and PON1CYP2C19. High OTR was defined as P2Y12 reaction units >/=230. The endpoint at 12-month follow-up was MACE occurring during antiplatelet therapy. RESULTS: All groups that were stratified for loss-of-function variants of the cytochrome P450 gene CYP2C19 had significant hazard ratios (HR) for MACE (genotypic HR: 1.41, 95% confidence interval [CI]: 1.06 to 1.89, p = 0.01; allelic HR: 1.56, 95% CI: 2.26 to 1.2, p = 0.01). Variants of other clopidogrel-pathway genes were not significantly associated with MACE. When OTR was assessed, clinical significance was found only in high-risk diabetic (HR: 2.11, 95% CI: 1.29 to 3.45, p < 0.001) and chronic kidney disease (HR: 2.03, 95% CI: 1.03 to 4.02, p = 0.04) patients. CONCLUSIONS: CYP2C19 metabolizer status is an independent predictor of MACE after DES implantation and can be used for prognostication in all stable CAD patients. High OTR, as assessed by the VerifyNow P2Y12 test, is an independent predictor of MACE only for high-risk subsets, that is, patients with diabetes or chronic kidney disease."

  • 10.1016/j.jcin.2013.06.010

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