About: DNA methylation in ELOVL2 and C1orf132 correctly predicted chronological age of individuals from three disease groups

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About: DNA methylation in ELOVL2 and C1orf132 correctly predicted chronological age of individuals from three disease groups Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	DNA methylation in ELOVL2 and C1orf132 correctly predicted chronological age of individuals from three disease groups
Creator	Branicki, Wojciech Barcikowska, & Bednarczuk, & Gasperowicz, & Karłowska-Pik, J Makowska, & Pepłońska, B Pięta, & Pośpiech, E Płoski, & Spólnicka, M Wężyk, & Zbieć-Piekarska, & Ziemkiewicz, &
source	PMC
abstract	Improving accuracy of the available predictive DNA methods is important for their wider use in routine forensic work. Information on age in the process of identification of an unknown individual may provide important hints that can speed up the process of investigation. DNA methylation markers have been demonstrated to provide accurate age estimation in forensics, but there is growing evidence that DNA methylation can be modified by various factors including diseases. We analyzed DNA methylation profile in five markers from five different genes (ELOVL2, C1orf132, KLF14, FHL2, and TRIM59) used for forensic age prediction in three groups of individuals with diagnosed medical conditions. The obtained results showed that the selected age-related CpG sites have unchanged age prediction capacity in the group of late onset Alzheimer’s disease patients. Aberrant hypermethylation and decreased prediction accuracy were found for TRIM59 and KLF14 markers in the group of early onset Alzheimer’s disease suggesting accelerated aging of patients. In the Graves’ disease patients, altered DNA methylation profile and modified age prediction accuracy were noted for TRIM59 and FHL2 with aberrant hypermethylation observed for the former and aberrant hypomethylation for the latter. Our work emphasizes high utility of the ELOVL2 and C1orf132 markers for prediction of chronological age in forensics by showing unchanged prediction accuracy in individuals affected by three diseases. The study also demonstrates that artificial neural networks could be a convenient alternative for the forensic predictive DNA analyses.
has issue date	2017-07-19(xsd:dateTime)
bibo:doi	10.1007/s00414-017-1636-0
bibo:pmid	28725932
has license	no-cc
sha1sum (hex)	2f9b92ef995e9147727d0adacedaf6a0de4246c6
schema:url	https://doi.org/10.1007/s00414-017-1636-0
resource representing a document's title	DNA methylation in ELOVL2 and C1orf132 correctly predicted chronological age of individuals from three disease groups
has PubMed Central identifier	PMC5748441
has PubMed identifier	28725932
schema:publication	Int J Legal Med
resource representing a document's body	covid:2f9b92ef995e9147727d0adacedaf6a0de4246c6#body_text
is schema:about of	named entity 'patients' named entity 'FHL2' named entity 'individuals' named entity 'patients' named entity 'process' named entity 'speed' named entity 'NOTED' named entity 'BUT' named entity 'HYPERMETHYLATION' named entity 'USED' named entity 'EARLY ONSET' named entity 'USE' named entity 'ANALYZED' named entity 'ALZHEIMER' named entity 'individual' named entity 'aberrant' named entity 'Alzheimer' named entity 'hypermethylation' named entity 'The' named entity 'study' named entity 'demonstrated' named entity 'alternative' named entity 'prediction' named entity 'modified' named entity 'group' named entity 'predictive' named entity 'early onset Alzheimer's disease' named entity 'forensic' named entity 'FHL2' named entity 'forensic' named entity 'Graves' disease' named entity 'DNA methylation' named entity 'DNA analyses' named entity 'hints' named entity 'DNA methylation' named entity 'HSCT' named entity 'forensic investigations' named entity 'biological age' named entity 'thyrotropin receptor' named entity 'IBM SPSS Statistics' named entity 'FHL2' named entity 'thyroid hormone' named entity 'KLF14' named entity 'hepatocellular carcinoma' named entity 'telomeres' named entity 'post-mitotic' named entity 'tumor suppressor' named entity 'passaging' named entity 'linear regression' named entity 'age-related' named entity 'hypermethylation' named entity 'gene' named entity 'analysis of DNA' named entity 'DNA methylation' named entity 'centrosome' named entity 'MAE' named entity 'IBM SPSS Statistics' named entity 'multilayer perceptron' named entity 'epigenomics' named entity 'DNA methylation' named entity 'physical activity' named entity 'FHL2' named entity 'forensics' named entity 'genetic factors' named entity 'ANN' named entity 'IBM SPSS Statistics' named entity '5.8' named entity 'Student's t test'

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