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)




    Aortic valve sclerosis is a high predictive marker of systemic endothelial dysfunction in hypertensive patients.
  • Author:"Erdogan, T;Cetin, M;Kocaman, S A;Durakoglugil, M E;Ergul, E;Canga, A"

  • Published Year:2013

  • Journal:Herz

  • Abstract:"BACKGROUND: Aortic valve sclerosis (AVS) is closely related to hypertension and is an important predictor of coronary artery disease as well as cardiovascular morbidity and mortality. However, the mechanisms causing AVS have not yet been clarified. Therefore, we planned to investigate the influence of atherosclerosis-related risk factors including C-reactive protein (CRP), epicardial adipose tissue (EAT), carotid intima-media thickness (CIMT), pulse wave velocity (PWV), left ventricular hypertrophy, and the conventional risk parameters as well as endothelial dysfunction in untreated hypertensive patients. METHODS AND RESULTS: Our study was cross-sectional and observational, and included 107 consecutive untreated hypertensive patients. All patients underwent vascular evaluation by CIMT, PWV, flow-mediated dilation (FMD%), as well as echocardiographic examinations. Age (OR = 1.180, p < 0.001), male sex (OR = 3.056, p = 0.019), waist circumference (OR = 1.082, p = 0.004), EAT (OR = 1.419, p = 0.001), smoking status (OR = 3.161, p = 0.014), FMD% (OR = 0.649, p < 0.001), mean CIMT (OR = 2.481, P < 0.001), and carotid plaque (OR = 4.692, P = 0.001) were associated with AVS in univariate analyses. Multivariate analyses revealed only age (OR = 1.144, P = 0.006) and FMD% (OR = 0.691, 0.001) as independent predictors of AVS. The presence of AVS had a high positive predictive value (100 %) but a low negative predictive value (51 %) for endothelial dysfunction (FMD < 12 %) in hypertensive patients. CONCLUSION: Our study supports the theory that systemic endothelial dysfunction has an initial and independent effect on AVS pathogenesis. Moreover, we demonstrated that the presence of AVS in patients with hypertension predicts endothelial dysfunction, with a high positive predictive value. Thus, AVS in hypertensive patients may urge clinicians toward aggressive risk factor modification and intensive treatment."

  • 10.1007/s00059-013-3763-9

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