An integrated transcriptomic and epigenomic analysis identifies CD44 gene as a potential biomarker for weight loss within an energy-restricted program View Full Text


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Article Info

DATE

2018-06-14

AUTHORS

Mirian Samblas, Maria Luisa Mansego, Maria Angeles Zulet, Fermín I. Milagro, J. Alfredo Martinez

ABSTRACT

PURPOSE: The interindividual variable response to weight-loss treatments requires the search for new predictive biomarkers for improving the success of weight-loss programs. The aim of this study is to identify novel genes that distinguish individual responses to a weight-loss dietary treatment by using the integrative analysis of mRNA expression and DNA methylation arrays. METHODS: Subjects from Metabolic Syndrome Reduction in Navarra (RESMENA) project were classified as low (LR) or high (HR) responders depending on their weight loss. Transcriptomic (n = 24) and epigenomic (n = 47) patterns were determined by array-based genome-wide technologies in human white blood cells at the baseline of the treatment period. CD44 expression was validated by qRT-PCR and methylation degree of CpGs of the gene was validated by MassARRAY® EpiTYPER™ in a subsample of 47 subjects. CD44 protein levels were measured by ELISA in human plasma. RESULTS: Different expression and DNA methylation profiles were identified in LR in comparison to HR. The integrative analysis of both array data identified four genes: CD44, ITPR1, MTSS1 and FBXW5 that were differently methylated and expressed between groups. CD44 showed higher expression and lower DNA methylation levels in LR than in HR. Although differences in CD44 protein levels between LR and HR were not statistically significant, a positive association was observed between CD44 mRNA expression and protein levels. CONCLUSIONS: In summary, the combination of a genome-wide methylation and expression array dataset can be a useful strategy to identify novel genes that might be considered as predictors of the dietary response. CD44 gene transcription and methylation may be a possible candidate biomarker for weight-loss prediction. More... »

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1-10

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    Turtle is a human-readable linked data format.

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