Literature DB >> 33436844

Gene expression in blood reflects smoking exposure among cancer-free women in the Norwegian Women and Cancer (NOWAC) postgenome cohort.

Nikita Baiju1, Torkjel M Sandanger2, Pål Sætrom3,4,5,6, Therese H Nøst2,6.   

Abstract

Active smoking has been linked to modulated gene expression in blood. However, there is a need for a more thorough understanding of how quantitative measures of smoking exposure relate to differentially expressed genes (DEGs) in whole-blood among ever smokers. This study analysed microarray-based gene expression profiles from whole-blood samples according to smoking status and quantitative measures of smoking exposure among cancer-free women (n = 1708) in the Norwegian Women and Cancer postgenome cohort. When compared with never smokers and former smokers, current smokers had 911 and 1082 DEGs, respectively and their biological functions could indicate systemic impacts of smoking. LRRN3 was associated with smoking status with the lowest FDR-adjusted p-value. When never smokers and all former smokers were compared, no DEGs were observed, but LRRN3 was differentially expressed when never smokers were compared with former smokers who quit smoking ≤ 10 years ago. Further, LRRN3 was positively associated with smoking intensity, pack-years, and comprehensive smoking index score among current smokers; and negatively associated with time since cessation among former smokers. Consequently, LRRN3 expression in whole-blood is a molecular signal of smoking exposure that could supplant self-reported smoking data in further research targeting blood-based markers related to the health effects of smoking.

Entities:  

Year:  2021        PMID: 33436844      PMCID: PMC7803754          DOI: 10.1038/s41598-020-80158-8

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  42 in total

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Journal:  Toxicol Lett       Date:  2014-11-13       Impact factor: 4.372

Review 5.  Neutrophils in cancer.

Authors:  Louise W Treffers; Ida H Hiemstra; Taco W Kuijpers; Timo K van den Berg; Hanke L Matlung
Journal:  Immunol Rev       Date:  2016-09       Impact factor: 12.988

6.  limma powers differential expression analyses for RNA-sequencing and microarray studies.

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Journal:  Nucleic Acids Res       Date:  2015-01-20       Impact factor: 16.971

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Authors:  P Silverstein
Journal:  Am J Med       Date:  1992-07-15       Impact factor: 4.965

Review 9.  Ten years of pathway analysis: current approaches and outstanding challenges.

Authors:  Purvesh Khatri; Marina Sirota; Atul J Butte
Journal:  PLoS Comput Biol       Date:  2012-02-23       Impact factor: 4.475

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Journal:  Nat Methods       Date:  2015-03-30       Impact factor: 28.547

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  1 in total

1.  The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort.

Authors:  Mie Jareid; Igor Snapkov; Marit Holden; Lill-Tove Rasmussen Busund; Eiliv Lund; Therese Haugdahl Nøst
Journal:  PLoS One       Date:  2021-08-27       Impact factor: 3.240

  1 in total

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