title: Isoflavone effect on gene expression profile and biomarkers of inflammation.
abstract: The use of high throughput techniques to find differences in gene expression profiles between related samples (transcriptomics) that underlie changes in physiological states can be applied in medicine, drug development and nutrition. Transcriptomics can be used to provide novel biomarkers of a future pathologic state and to study how bioactive food compounds or drugs can modulate them in the early stages. In this study, we examine the expression pattern in order to determine the effect of the pathological-inflammatory state on the RAW 264.7 cell model and to ascertain how isoflavones and their active functional metabolites alleviate the inflammatory burst and the extent of gene modulation due to the presence of polyphenols. Results demonstrated that genistein (20 microM) and equol (10 microM) significantly inhibited the overproduction of NO and PGE(2) induced by LPS plus INF-gamma when a pre-treatment was performed or when administered during activation. Daidzein, however, did not exert similar effects. Moreover, both isoflavone treatments regulated gene transcription of cytokines and inflammatory markers, among others. The transcriptomic changes provide clues firstly into defining a differential expression profile in inflammation in order to select putative biomarkers of the inflammatory process, and secondly into understanding the isoflavone action mechanism at the transcriptional level. In conclusion, isoflavone modulates the inflammatory response in activated macrophages by inhibiting NO and PGE(2) and by modulating the expression of key genes defined by transcriptomic profiling.
authors.affiliation: Department of Biochemistry and Biotechnology, Nutrigenomics Research Group, Universitat Rovira i Virgili, Tarragona, Spain.
authors.forename: M
authors.initials: M
authors.lastname: Blay
authors.forename: A E
authors.initials: AE
authors.lastname: Espinel
authors.forename: M A
authors.initials: MA
authors.lastname: Delgado
authors.forename: I
authors.initials: I
authors.lastname: Baiges
authors.forename: C
authors.initials: C
authors.lastname: Bladé
authors.forename: L
authors.initials: L
authors.lastname: Arola
authors.forename: J
authors.initials: J
authors.lastname: Salvadó
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D002460:Cell Line; D002470:Cell Survival / Q000187:drug effects; D015232:Dinoprostone / Q000032:analysis / Q000378:metabolism; D004305:Dose-Response Relationship, Drug; D015870:Gene Expression / Q000187:drug effects; D020869:Gene Expression Profiling; D007249:Inflammation / Q000235:genetics / Q000276:immunology / Q000378:metabolism; D007371:Interferon-gamma / Q000494:pharmacology; D007529:Isoflavones / Q000235:genetics / Q000276:immunology / Q000494:pharmacology; D008070:Lipopolysaccharides / Q000494:pharmacology; D008262:Macrophage Activation / Q000187:drug effects; D008264:Macrophages / Q000187:drug effects* / Q000276:immunology / Q000378:metabolism*; D051379:Mice; D015394:Molecular Structure; D009573:Nitrites / Q000032:analysis / Q000378:metabolism; D013997:Time Factors
chemical_list: D015415:Biomarkers; D007529:Isoflavones; D008070:Lipopolysaccharides; D009573:Nitrites; D007371:Interferon-gamma; D015232:Dinoprostone