Literature DB >> 28353150

Gene methylation parallelisms between peripheral blood cells and oral mucosa samples in relation to overweight.

Rodrigo San-Cristobal1, Santiago Navas-Carretero2,3, Fermín I Milagro2,3,4, J Ignacio Riezu-Boj2,4, Elizabeth Guruceaga4,5, Carlos Celis-Morales6, Katherine M Livingstone6, Lorraine Brennan7, Julie A Lovegrove8, Hannelore Daniel9, Wim H Saris10, Iwonna Traczyk11, Yannis Manios12, Eileen R Gibney7, Michael J Gibney7, John C Mathers6, J Alfredo Martinez2,3,4,13.   

Abstract

Epigenetics has an important role in the regulation of metabolic adaptation to environmental modifications. In this sense, the determination of epigenetic changes in non-invasive samples during the development of metabolic diseases could play an important role in the procedures in primary healthcare practice. To help translate the knowledge of epigenetics to public health practice, the present study aims to explore the parallelism of methylation levels between white blood cells and buccal samples in relation to obesity and associated disorders. Blood and buccal swap samples were collected from a subsample of the Spanish cohort of the Food4Me study. Infinium HumanMethylation450 DNA Analysis was carried out for the determination of methylation levels. Standard deviation for β values method and concordance correlation analysis were used to select those CpG which showed best parallelism between samples. A total of 277 CpGs met the criteria and were selected for an enrichment analysis and a correlation analysis with anthropometrical and clinical parameters. From those selected CpGs, four presented high associations with BMI (cg01055691 in GAP43; r = -0.92 and rho = -0.84 for blood; r = -0.89 and rho = -0.83 for buccal sample), HOMA-IR (cg00095677 in ATP2A3; r = 0.82 and rho = -0.84 for blood; r = -0.8 and rho = -0.83 for buccal sample) and leptin (cg14464133 in ADARB2; r = -0.9182 and rho = -0.94 for blood; r = -0.893 and rho = -0.79 for buccal sample). These findings demonstrate the potential application of non-invasive buccal samples in the identification of surrogate epigenetic biomarkers and identify methylation sites in GAP43, ATP2A3 and ADARB2 genes as potential targets in relation to overweight management and insulin sensibility.

Entities:  

Keywords:  Methylation; Mirror tissues; Obesity; Parallelism; Surrogate tissues

Mesh:

Year:  2017        PMID: 28353150     DOI: 10.1007/s13105-017-0560-6

Source DB:  PubMed          Journal:  J Physiol Biochem        ISSN: 1138-7548            Impact factor:   4.158


  57 in total

1.  Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation.

Authors:  Nizar Touleimat; Jörg Tost
Journal:  Epigenomics       Date:  2012-06       Impact factor: 4.778

2.  Variation, patterns, and temporal stability of DNA methylation: considerations for epigenetic epidemiology.

Authors:  Rudolf P Talens; Dorret I Boomsma; Elmar W Tobi; Dennis Kremer; J Wouter Jukema; Gonneke Willemsen; Hein Putter; P Eline Slagboom; Bastiaan T Heijmans
Journal:  FASEB J       Date:  2010-04-12       Impact factor: 5.191

3.  Adipose tissue transcriptomics and epigenomics in low birthweight men and controls: role of high-fat overfeeding.

Authors:  Linn Gillberg; Alexander Perfilyev; Charlotte Brøns; Martin Thomasen; Louise G Grunnet; Petr Volkov; Fredrik Rosqvist; David Iggman; Ingrid Dahlman; Ulf Risérus; Tina Rönn; Emma Nilsson; Allan Vaag; Charlotte Ling
Journal:  Diabetologia       Date:  2016-01-11       Impact factor: 10.122

4.  Epigenome-wide profiling of DNA methylation in paired samples of adipose tissue and blood.

Authors:  Yen-Tsung Huang; Su Chu; Eric B Loucks; Chien-Ling Lin; Charles B Eaton; Stephen L Buka; Karl T Kelsey
Journal:  Epigenetics       Date:  2016-02-18       Impact factor: 4.528

5.  A concordance correlation coefficient to evaluate reproducibility.

Authors:  L I Lin
Journal:  Biometrics       Date:  1989-03       Impact factor: 2.571

6.  Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.

Authors:  W T Friedewald; R I Levy; D S Fredrickson
Journal:  Clin Chem       Date:  1972-06       Impact factor: 8.327

7.  Weight loss after gastric bypass surgery in human obesity remodels promoter methylation.

Authors:  Romain Barres; Henriette Kirchner; Morten Rasmussen; Jie Yan; Francisc R Kantor; Anna Krook; Erik Näslund; Juleen R Zierath
Journal:  Cell Rep       Date:  2013-04-11       Impact factor: 9.423

8.  TNF-alpha promoter methylation as a predictive biomarker for weight-loss response.

Authors:  Javier Campión; Fermin I Milagro; Estibaliz Goyenechea; J Alfredo Martínez
Journal:  Obesity (Silver Spring)       Date:  2009-02-19       Impact factor: 5.002

9.  Tissue-specific patterns of allelically-skewed DNA methylation.

Authors:  Sarah J Marzi; Emma L Meaburn; Emma L Dempster; Katie Lunnon; Jose L Paya-Cano; Rebecca G Smith; Manuela Volta; Claire Troakes; Leonard C Schalkwyk; Jonathan Mill
Journal:  Epigenetics       Date:  2016-01-19       Impact factor: 4.528

10.  Many obesity-associated SNPs strongly associate with DNA methylation changes at proximal promoters and enhancers.

Authors:  Sarah Voisin; Markus Sällman Almén; Galina Y Zheleznyakova; Lina Lundberg; Sanaz Zarei; Sandra Castillo; Fia Ence Eriksson; Emil K Nilsson; Matthias Blüher; Yvonne Böttcher; Peter Kovacs; Janis Klovins; Mathias Rask-Andersen; Helgi B Schiöth
Journal:  Genome Med       Date:  2015-10-08       Impact factor: 11.117

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  5 in total

Review 1.  Endoplasmic reticulum stress epigenetics is related to adiposity, dyslipidemia, and insulin resistance.

Authors:  Omar Ramos-Lopez; Jose I Riezu-Boj; Fermin I Milagro; Maria J Moreno-Aliaga; J Alfredo Martinez
Journal:  Adipocyte       Date:  2018-03-23       Impact factor: 4.534

Review 2.  DNA methylation markers in obesity, metabolic syndrome, and weight loss.

Authors:  Mirian Samblas; Fermín I Milagro; Alfredo Martínez
Journal:  Epigenetics       Date:  2019-03-27       Impact factor: 4.528

3.  DNA Methylation Signatures of Breastfeeding in Buccal Cells Collected in Mid-Childhood.

Authors:  Veronika V Odintsova; Fiona A Hagenbeek; Matthew Suderman; Doretta Caramaschi; Catharina E M van Beijsterveldt; Noah A Kallsen; Erik A Ehli; Gareth E Davies; Gennady T Sukhikh; Vassilios Fanos; Caroline Relton; Meike Bartels; Dorret I Boomsma; Jenny van Dongen
Journal:  Nutrients       Date:  2019-11-17       Impact factor: 5.717

4.  Dopamine gene methylation patterns are associated with obesity markers and carbohydrate intake.

Authors:  Omar Ramos-Lopez; Jose I Riezu-Boj; Fermin I Milagro; J Alfredo Martinez
Journal:  Brain Behav       Date:  2018-07-11       Impact factor: 2.708

5.  Associations between olfactory pathway gene methylation marks, obesity features and dietary intakes.

Authors:  Omar Ramos-Lopez; Jose I Riezu-Boj; Fermin I Milagro; M Angeles Zulet; Jose L Santos; J Alfredo Martinez
Journal:  Genes Nutr       Date:  2019-04-25       Impact factor: 5.523

  5 in total

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