Literature DB >> 28844970

Role of DNA methylation in human age prediction.

Neelam Goel1, Priya Karir2, Vivek Kumar Garg3.   

Abstract

DNA methylation (DNAm) is a fundamental biochemical modification which occurs over the lifespan of an individual and it is a significant component in the aging process. Methylation level of CpG sites plays an important role in finding the age of a person. Different approaches were used to extract age-related CpG (AR-CpG) sites for developing age-prediction models because the level of methylation is directly related to age for some CpG sites. Several age prediction models have been developed over the past few years and most of these models were based on regression techniques. This paper reviews and analyzes age-prediction models developed using methylated data. The first section introduces the problem of aging in humans. In the next section, the concept of DNA methylation is described in detail. Thereafter, DNA methylation based age-prediction methods are discussed. In addition to this, a summary of all these methods is also provided. Finally, some limitations of the current research along with future directions are given.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Aging; Biomarker; CpG site; DNA methylation; Demethylation

Mesh:

Year:  2017        PMID: 28844970     DOI: 10.1016/j.mad.2017.08.012

Source DB:  PubMed          Journal:  Mech Ageing Dev        ISSN: 0047-6374            Impact factor:   5.432


  10 in total

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Authors:  Julia Becker; Nina Sophia Mahlke; A Reckert; S B Eickhoff; S Ritz-Timme
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2.  Accurate age estimation from blood samples of Han Chinese individuals using eight high-performance age-related CpG sites.

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Journal:  Int J Legal Med       Date:  2022-07-11       Impact factor: 2.791

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Review 4.  Insights into the Conserved Regulatory Mechanisms of Human and Yeast Aging.

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6.  Exploring Epigenetic Age in Response to Intensive Relaxing Training: A Pilot Study to Slow Down Biological Age.

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7.  Aging in psoriasis vulgaris: female patients are epigenetically older than healthy controls.

Authors:  Pavel Borsky; Marcela Chmelarova; Zdenek Fiala; Kvetoslava Hamakova; Vladimir Palicka; Jan Krejsek; Ctirad Andrys; Jan Kremlacek; Vit Rehacek; Martin Beranek; Andrea Malkova; Tereza Svadlakova; Drahomira Holmannova; Lenka Borska
Journal:  Immun Ageing       Date:  2021-03-03       Impact factor: 6.400

8.  DNA methylation of the cancer-related genes F2RL3 and AHRR is associated with occupational exposure to polycyclic aromatic hydrocarbons.

Authors:  Ayman Alhamdow; Christian Lindh; Jessika Hagberg; Pål Graff; Håkan Westberg; Annette M Krais; Maria Albin; Per Gustavsson; Håkan Tinnerberg; Karin Broberg
Journal:  Carcinogenesis       Date:  2018-07-03       Impact factor: 4.944

9.  A Blood-Bone-Tooth Model for Age Prediction in Forensic Contexts.

Authors:  Helena Correia Dias; Licínio Manco; Francisco Corte Real; Eugénia Cunha
Journal:  Biology (Basel)       Date:  2021-12-10

10.  DNA Methylation Biomarkers-Based Human Age Prediction Using Machine Learning.

Authors:  Atef Zaguia; Deepak Pandey; Sandeep Painuly; Saurabh Kumar Pal; Vivek Kumar Garg; Neelam Goel
Journal:  Comput Intell Neurosci       Date:  2022-01-24
  10 in total

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