Literature DB >> 28952191

Weighted Gene Co-Expression Network Analysis Identifies Gender Specific Modules and Hub Genes Related to Metabolism and Inflammation in Response to an Acute Lipid Challenge.

Attia Fatima1,2, Ruth M Connaughton1,3, Anna Weiser1,4, Aoife M Murphy1,3, Colm O'Grada1, Miriam Ryan3, Lorraine Brennan3, Peadar O'Gaora5, Helen M Roche1,3.   

Abstract

SCOPE: Inflammation is characteristic of diet-related diseases including obesity and type 2 diabetes (T2D). However, biomarkers of inflammation that reflect the early stage metabolic derangements are not optimally sensitive. Lipid challenges elicit postprandial inflammatory and metabolic responses. Gender-specific transcriptomic networks of the peripheral blood mononuclear cell (PBMC) were constructed in response to a lipid challenge. METHODS AND
RESULTS: Eighty-six adult males and females of comparable age, anthropometric, and biochemical profiles completed an oral lipid tolerance test (OLTT). PBMC transcriptome was profiled following OLTT. Weighted gene coexpression networks were constructed separately for males and females. Functional ontology analysis of network modules was performed and hub genes identified. Two modules of interest were identified in females-an "inflammatory" module and an "energy metabolism" module. NLRP3, which plays a central role in inflammation and STARD3 that is involved in cholesterol metabolism, were identified as hub genes for the respective modules.
CONCLUSION: The OLTT induced some gender-specific correlations of gene coexpression network modules. In females, biological processes relating to energy metabolism and inflammation pathways were evident. This suggests a gender specific link between inflammation and energy metabolism in response to lipids. In contrast, G-protein coupled receptor protein signaling pathway was common to both genders.
© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  metabolic-inflammation; modules; nutrigenomics; nutritional biomarkers; weighted gene coexpression network analysis (WGCNA)

Mesh:

Substances:

Year:  2017        PMID: 28952191     DOI: 10.1002/mnfr.201700388

Source DB:  PubMed          Journal:  Mol Nutr Food Res        ISSN: 1613-4125            Impact factor:   5.914


  3 in total

1.  Identification and evaluation of hub mRNAs and long non-coding RNAs in neutrophils during sepsis.

Authors:  Jiamin Huang; Ran Sun; Bingwei Sun
Journal:  Inflamm Res       Date:  2020-02-05       Impact factor: 4.575

2.  Multiomics Integrated Analysis Identifies SLC24A2 as a Potential Link between Type 2 Diabetes and Cancer.

Authors:  Qin Bian; Haijun Li; Xiaoyi Wang; Tingting Liang; Kai Zhang
Journal:  J Diabetes Res       Date:  2022-05-13       Impact factor: 4.061

3.  Discriminating Dietary Responses by Combining Transcriptomics and Metabolomics Data in Nutrition Intervention Studies.

Authors:  Kathryn J Burton-Pimentel; Grégory Pimentel; Maria Hughes; Charlotte Cjr Michielsen; Attia Fatima; Nathalie Vionnet; Lydia A Afman; Helen M Roche; Lorraine Brennan; Mark Ibberson; Guy Vergères
Journal:  Mol Nutr Food Res       Date:  2021-01-29       Impact factor: 5.914

  3 in total

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