Predicting environmental chemical factors associated with disease-related gene expression data

We have developed a scalable and statistical method to identify possible environmental associations with disease using publicly available data and have validated some of the associations in the literature

Chirag J Patel

2010

Scholarcy highlights

  • Many common diseases arise from an interaction between environmental and genetic factors
  • Predicting Environmental Factors Associated with Diseaserelated Gene Expression Data Sets: Prostate, Lung, and Breast Cancer We found previously measured cancer gene expression datasets to identify potential environmental associations with cancer
  • We implemented a method to predict a list of environmental factors associated with differentially expressed genes
  • We determine whether the differentially expressed genes are associated to a chemical by assessing if the expressed genes are enriched for a chemical-gene set, or contain more genes from the chemical-gene set than expected at random using the hypergeometric test
  • We applied this method in two phases, the first a verification phase in which we sought to rediscover known exposures applied to samples, and a query phase, in which we sought to find factors associated with cancer gene expression datasets
  • We found predicted chemicals such as sodium arsenite in its association with prostate and lung cancers, estrogenic compounds such as bisphenol A and estradiol with prostate and breast cancers, and dimethylnitrosamine with lung cancer
  • We have developed a scalable and statistical method to identify possible environmental associations with disease using publicly available data and have validated some of the associations in the literature

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