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dc.contributor.authorCharlesworth, J.
dc.contributor.authorCurran, J.
dc.contributor.authorJohnson, M.
dc.contributor.authorGöring, H.
dc.contributor.authorDyer, T.
dc.contributor.authorDiego, V.
dc.contributor.authorKent, J.
dc.contributor.authorMahaney, M.
dc.contributor.authorAlmasy, L.
dc.contributor.authorMacCluer, J.
dc.contributor.authorMoses, Eric
dc.contributor.authorBlangero, J.
dc.date.accessioned2017-01-30T10:51:18Z
dc.date.available2017-01-30T10:51:18Z
dc.date.created2016-09-12T08:37:04Z
dc.date.issued2010
dc.identifier.citationCharlesworth, J. and Curran, J. and Johnson, M. and Göring, H. and Dyer, T. and Diego, V. and Kent, J. et al. 2010. Transcriptomic epidemiology of smoking: The effect of smoking on gene expression in lymphocytes. BMC Medical Genomics. 3.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/6204
dc.identifier.doi10.1186/1755-8794-3-29
dc.description.abstract

Background. This investigation offers insights into system-wide pathological processes induced in response to cigarette smoke exposure by determining its influences at the gene expression level. Methods. We obtained genome-wide quantitative transcriptional profiles from 1,240 individuals from the San Antonio Family Heart Study, including 297 current smokers. Using lymphocyte samples, we identified 20,413 transcripts with significantly detectable expression levels, including both known and predicted genes. Correlation between smoking and gene expression levels was determined using a regression model that allows for residual genetic effects. Results. With a conservative false-discovery rate of 5% we identified 323 unique genes (342 transcripts) whose expression levels were significantly correlated with smoking behavior. These genes showed significant over-representation within a range of functional categories that correspond well with known smoking-related pathologies, including immune response, cell death, cancer, natural killer cell signaling and xenobiotic metabolism. Conclusions. Our results indicate that not only individual genes but entire networks of gene interaction are influenced by cigarette smoking. This is the largest in vivo transcriptomic epidemiological study of smoking to date and reveals the significant and comprehensive influence of cigarette smoke, as an environmental variable, on the expression of genes. The central importance of this manuscript is to provide a summary of the relationships between gene expression and smoking in this exceptionally large cross-sectional data set. © 2010 Charlesworth et al; licensee BioMed Central Ltd.

dc.titleTranscriptomic epidemiology of smoking: The effect of smoking on gene expression in lymphocytes
dc.typeJournal Article
dcterms.source.volume3
dcterms.source.titleBMC Medical Genomics
curtin.departmentSchool of Biomedical Sciences
curtin.accessStatusOpen access via publisher


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