Literature DB >> 33374448

DNA Methylomes and Epigenetic Age Acceleration Associations with Poor Metabolic Control in T1D.

Raúl F Pérez1, Juan Luis Fernandez-Morera1,2, Judit Romano-Garcia3, Edelmiro Menendez-Torre4,5,6, Elias Delgado-Alvarez4,5,6, Mario F Fraga1,7, Agustin F Fernandez1.   

Abstract

Type 1 diabetes (T1D) is an autoimmune disease that leads to insulin deficiency and hyperglycemia. Little is known about how this metabolic dysfunction, which substantially alters the internal environment, forces cells to adapt through epigenetic mechanisms. Consequently, the purpose of this work was to study what changes occur in the epigenome of T1D patients after the onset of disease and in the context of poor metabolic control. We performed a genome-wide analysis of DNA methylation patterns in blood samples from 18 T1D patients with varying levels of metabolic control. We identified T1D-associated DNA methylation differences on more than 100 genes when compared with healthy controls. Interestingly, only T1D patients displaying poor glycemic control showed epigenetic age acceleration compared to healthy controls. The epigenetic alterations identified in this work make a valuable contribution to improving our understanding of T1D and to ensuring the appropriate management of the disease in relation to maintaining healthy aging.

Entities:  

Keywords:  DNA methylation; PhenoAge; age acceleration; epigenetic aging; metabolic control; type 1 diabetes

Year:  2020        PMID: 33374448      PMCID: PMC7824441          DOI: 10.3390/biomedicines9010013

Source DB:  PubMed          Journal:  Biomedicines        ISSN: 2227-9059


  29 in total

1.  The sva package for removing batch effects and other unwanted variation in high-throughput experiments.

Authors:  Jeffrey T Leek; W Evan Johnson; Hilary S Parker; Andrew E Jaffe; John D Storey
Journal:  Bioinformatics       Date:  2012-01-17       Impact factor: 6.937

2.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

Authors:  Martin J Aryee; Andrew E Jaffe; Hector Corrada-Bravo; Christine Ladd-Acosta; Andrew P Feinberg; Kasper D Hansen; Rafael A Irizarry
Journal:  Bioinformatics       Date:  2014-01-28       Impact factor: 6.937

3.  Allele-specific methylation of type 1 diabetes susceptibility genes.

Authors:  Alida S D Kindt; Rainer W Fuerst; Jan Knoop; Michael Laimighofer; Tanja Telieps; Markus Hippich; Maria A Woerheide; Simone Wahl; Rory Wilson; Eva-Maria Sedlmeier; Angela Hommel; John A Todd; Jan Krumsiek; Anette-G Ziegler; Ezio Bonifacio
Journal:  J Autoimmun       Date:  2017-12-08       Impact factor: 7.094

4.  Evaluating the role of epigenetic histone modifications in the metabolic memory of type 1 diabetes.

Authors:  Feng Miao; Zhuo Chen; Saul Genuth; Andrew Paterson; Lingxiao Zhang; Xiwei Wu; Sierra Min Li; Patricia Cleary; Arthur Riggs; David M Harlan; Gayle Lorenzi; Orville Kolterman; Wanjie Sun; John M Lachin; Rama Natarajan
Journal:  Diabetes       Date:  2014-01-23       Impact factor: 9.461

Review 5.  The "Metabolic Memory" Theory and the Early Treatment of Hyperglycemia in Prevention of Diabetic Complications.

Authors:  Roberto Testa; Anna Rita Bonfigli; Francesco Prattichizzo; Lucia La Sala; Valeria De Nigris; Antonio Ceriello
Journal:  Nutrients       Date:  2017-04-28       Impact factor: 5.717

Review 6.  The Role of Epigenetics in Type 1 Diabetes.

Authors:  Samuel T Jerram; Mary N Dang; R David Leslie
Journal:  Curr Diab Rep       Date:  2017-08-16       Impact factor: 4.810

7.  An epigenetic biomarker of aging for lifespan and healthspan.

Authors:  Morgan E Levine; Ake T Lu; Austin Quach; Brian H Chen; Themistocles L Assimes; Stefania Bandinelli; Lifang Hou; Andrea A Baccarelli; James D Stewart; Yun Li; Eric A Whitsel; James G Wilson; Alex P Reiner; Abraham Aviv; Kurt Lohman; Yongmei Liu; Luigi Ferrucci; Steve Horvath
Journal:  Aging (Albany NY)       Date:  2018-04-18       Impact factor: 5.682

8.  A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.

Authors:  Andrew E Teschendorff; Francesco Marabita; Matthias Lechner; Thomas Bartlett; Jesper Tegner; David Gomez-Cabrero; Stephan Beck
Journal:  Bioinformatics       Date:  2012-11-21       Impact factor: 6.937

9.  Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray.

Authors:  Yi-an Chen; Mathieu Lemire; Sanaa Choufani; Darci T Butcher; Daria Grafodatskaya; Brent W Zanke; Steven Gallinger; Thomas J Hudson; Rosanna Weksberg
Journal:  Epigenetics       Date:  2013-01-11       Impact factor: 4.528

10.  DNA methylation age calculators reveal association with diabetic neuropathy in type 1 diabetes.

Authors:  Delnaz Roshandel; Zhuo Chen; Angelo J Canty; Shelley B Bull; Rama Natarajan; Andrew D Paterson
Journal:  Clin Epigenetics       Date:  2020-04-05       Impact factor: 6.551

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.