Using NGS-methylation profiling to understand the molecular pathogenesis of young MI patients who have subsequent cardiac events.
Methylation
RRBS
biomarkers
cardiac
myocardial infarction
next-generation sequencing
young
Journal
Epigenetics
ISSN: 1559-2308
Titre abrégé: Epigenetics
Pays: United States
ID NLM: 101265293
Informations de publication
Date de publication:
06 2019
06 2019
Historique:
pubmed:
12
4
2019
medline:
29
5
2020
entrez:
12
4
2019
Statut:
ppublish
Résumé
Globally, ischaemic heart disease is a major contributor to premature morbidity and mortality. A significant number of young Myocardial Infarction (MI) patients (aged <55 y) have subsequent cardiac events within a year of their index event. This study used Next Generation Sequencing (NGS) methylation to understand the pathogenesis in this subset of young MI patients, comparing them to a cohort of patients without recurrent events. Cases and controls were matched for age, gender, ethnicity, and comorbidities. Differential methylation analyses were performed on Reduced Representation Bisulphite Sequencing (RRBS) data. Across the group and within case-control pairs' variation were analysed. Pairwise comparisons across each matched case-control pair resulted in a list of genes that were consistently significantly differentially methylated between all 16 matched pairs. This gene list was input into pathway analysis databases. Of particular relevance to cardiac pathology the following pathways were identified as over-represented in the patients with recurrent events; cell adhesion, transcription regulation and cardiac electrical conduction, specifically relating to calcium channel activity. This study looked at methylation differences between two populations of young MI patients. There were significantly different methylation profiles between the two groups studied; key pathways were identified as specifically affected in the patients with recurrent cardiac events. Matched pairwise comparisons and detailed interpretations of DNA methylation data may help to elucidate complex pathogeneses within and between clinical subtypes. Further analysis will determine whether these epigenomic differences can be useful as predictive biomarkers of clinical progression.
Identifiants
pubmed: 30971167
doi: 10.1080/15592294.2019.1605815
pmc: PMC6557607
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
536-544Références
BMC Bioinformatics. 2009 Feb 03;10:48
pubmed: 19192299
PLoS Genet. 2009 Aug;5(8):e1000591
pubmed: 19662162
J Biomed Biotechnol. 2012;2012:741542
pubmed: 23193365
PLoS One. 2013 Aug 21;8(8):e72278
pubmed: 23991079
Arch Biochem Biophys. 2013 Dec;540(1-2):82-93
pubmed: 24103691
Nucleic Acids Res. 2014 Apr;42(6):3515-28
pubmed: 24445802
Bioinformatics. 2014 Jul 1;30(13):1814-22
pubmed: 24608764
Expert Rev Cardiovasc Ther. 2014 Sep;12(9):1087-98
pubmed: 25047512
Clin Epigenetics. 2015 Mar 25;7:33
pubmed: 25861393
Epigenomics. 2015;7(8):1287-302
pubmed: 26192535
Epidemiology. 2016 Jul;27(4):602-11
pubmed: 26928707
Heart Lung Circ. 2016 Oct;25(10):955-60
pubmed: 27265644
Eur Heart J. 2016 Nov 14;37(43):3267-3278
pubmed: 27655226
Heart Lung Circ. 2017 Jun;26(6):566-571
pubmed: 28089789
Hum Mol Genet. 2016 Nov 1;25(21):4739-4748
pubmed: 28172975
Thromb Res. 2017 Apr;152:14-19
pubmed: 28213102
Nat Rev Genet. 2017 Jun;18(6):331-344
pubmed: 28286336
Eur Rev Med Pharmacol Sci. 2017 Apr;21(8):1828-1836
pubmed: 28485796
Biomed Rep. 2017 Jul;7(1):3-5
pubmed: 28685051
Sci Rep. 2017 Aug 18;7(1):8719
pubmed: 28821809
Medicine (Baltimore). 2017 Oct;96(42):e7741
pubmed: 29049183
Nucleic Acids Res. 2018 Jan 4;46(D1):D649-D655
pubmed: 29145629
Dev Biol. 2018 Feb 1;434(1):108-120
pubmed: 29229250
Science. 2018 Mar 2;359(6379):1047-1050
pubmed: 29371428
J Mol Cell Cardiol. 2018 Sep;122:1-10
pubmed: 30063898
Biomed Rep. 2018 Nov;9(5):383-404
pubmed: 30402224
J Cell Mol Med. 2019 Feb;23(2):1137-1151
pubmed: 30516028
F1000Res. 2018 Nov 27;7:
pubmed: 30542613