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)




    Mendelian randomization: potential use of genetics to enable causal inferences regarding HIV-associated biomarkers and outcomes.
  • Author:"He, Weijing;Castiblanco, John;Walter, Elizabeth A;Okulicz, Jason F;Ahuja, Sunil K"

  • Published Year:2010

  • Journal:Current opinion in HIV and AIDS

  • Abstract:"PURPOSE OF REVIEW: It is unknown whether biomarkers simply correlate with or are causal for HIV-associated outcomes. Mendelian randomization is a genetic epidemiologic approach used to disentangle causation from association. Here, we discuss the potential use of Mendelian randomization for differentiating whether biomarkers are correlating with or causal for HIV-associated outcomes. RECENT FINDINGS: Mendelian randomization refers to the random allocation of alleles at the time of gamete formation. In observational epidemiology, this refers to the use of genetic variants to estimate a causal effect between a modifiable risk factor and an outcome of interest. A formal Mendelian randomization study using a genetic marker as a proxy for the biomarker has not been conducted in the HIV field. However, in the postgenomic era, this approach is being used increasingly. Examples are evidence for the causal role of BMI in blood pressure and noncausal role of C-reactive protein in coronary heart disease. We discuss the conceptual framework, uses, and limitations of Mendelian randomization in the context of HIV infection as well as specific biomarkers (IL-6, C-reactive protein) and genetic determinants (e.g., in CCR5, chemokine, and DARC genes) that associate with HIV-related outcomes. SUMMARY: Making the distinction between correlation and causality has particular relevance when a biomarker (e.g., IL-6) is potentially modifiable, in which case a biomarker-guided targeted treatment strategy may be feasible. Although the tenets of Mendelian randomization rest on strong assumptions, and conducting a Mendelian randomization study in HIV infection presents many challenges, it may offer the potential to identify causal biomarkers for HIV-associated outcomes."

  • 10.1097/COH.0b013e32833f2087

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