Integrated Analys of High‐Fat Challenge‐Induced Changes in Blood Cell Whole‐Genome Gene Expression. Issue 20 (30th September 2019)

• Record Type: Journal Article
• Authors: Matualatupauw, Juri C.; O'Grada, Colm; Hughes, Maria F.; Roche, Helen M.; Afman, Lydia A.; Bouwman, Jildau
• Is Part Of: Molecular nutrition & food research. Volume 63:Issue 20(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-09-30
• Subjects: bioinformatics -- high‐fat challenge -- microarrays -- nutrigenomics -- phenotypic flexibility -- saturated fatty acids; Food -- Biotechnology -- Periodicals; Food -- Microbiology -- Periodicals; Nutrition -- Periodicals; Food -- Toxicology -- Periodicals; Nutrition -- Periodicals; Food Microbiology -- Periodicals; Food Technology -- Periodicals; Molecular Biology -- Periodicals; 664.0705
• DOI: 10.1002/mnfr.201900101
• Languages: English
• ISSNs: 1613-4125

Abstract

Abstract : Scope: Several studies have examined the whole‐genome gene expression response in blood cells to high‐fat challenges with differing results. The study aims to identify consistently up‐ or downregulated genes and pathways in response to a high‐fat challenge using several integration methods. Methods and results: Three studies measuring the gene expression response to a high‐fat challenge in white blood cells are evaluated for common trends using several integration methods. Overlap in differentially expressed genes between separate studies is examined, p ‐values of each separate study are combined, and data are analyzed as one merged dataset. Differentially expressed genes and pathways are compared between these methods. Selecting genes differentially expressed in the three separate studies result in 67 differentially expressed genes, primarily involved in circadian pathways. Using the Fishers p ‐value method and a merged dataset analysis, changes in 1097 and 1182 genes, respectively, are observed. The upregulated genes upon a high‐fat challenge are related to inflammation, whereas downregulated genes are related to unfolded protein response, protein processing, cholesterol biosynthesis, and translation. Conclusion: A general gene expression response to a high‐fat challenge is identified. Compared to separate analyses, integrated analysis provides added value for the discovery of a consistent gene expression response. Abstract : An integrated analysis on microarray datasets from several high‐fat challenge intervention studies is performed. Several integration methods to identify changes in PBMC gene expression upon a high‐fat challenge are used. This integrated analysis is shown to provide added value for the discovery of consistently differentially expressed genes and pathways compared to separate analysis of the studies.