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Epigenetics
Published in Sara C. Zapico, Mechanisms Linking Aging, Diseases and Biological Age Estimation, 2017
Christian Thomas, Sara C. Zapico
As described previously, epigenetic drift is associated with aging. For that reason, over the past few years, researchers have been trying to identify DNA methylation markers that are significantly correlated with age, in order to be used for age-at-death estimation in the forensic sciences. Bocklandt et al. (Bocklandt et al. 2011) found that methylation in the promoter of the EDARADD gene showed a linear correlation with age in saliva samples over a 5-decade period. More recently, EDARADD methylation in blood samples has been reported to be able to predict chronological age with an error of only 3.34 years. Other authors used ELOVL2, finding a good correlation with age in blood samples, although the difference between chronological and predicted age was approximately five years (Garagnani et al. 2013, Zbiec-Piekarska et al. 2015a). Another age prediction model (Weidner et al. 2014) used ASPA, ITG2B and EDARADD genes, finding an accurate age prediction of 5.4 years. A meta-analysis on the association between DNA methylation and age in blood resulted in 44 genes whose methylated levels were highly correlated with age, including EDARADD and ELOVL2 (Bacalini et al. 2015). Zbiec-Piekarska et al. have recently improved their age estimation prediction using ELOVL2, Clorf132, TRIM59, KLF14 and FHL2 to obtain a MAD of 3.9 years (Zbiec-Piekarska et al. 2015b). More recently, Bekaert et al. (Bekaert et al. 2015) evaluated the accuracy of using four age-associated genes ASPA, PDE4C, ELOVL2 and EDARADD for age prediction in blood samples, finding that ELOVL2 showed the highest accuracy with a MAD of 3.75 years. Moreover, the study was extended to samples of teeth, the first of its kind to use this type of sample, and obtained a MAD of 4.86 years. In spite of these previous works, further research is needed in other tissues and samples to improve age-at-death estimation using this valuable and innovative tool.
Aging Epigenetics
Published in Shamim I. Ahmad, Aging: Exploring a Complex Phenomenon, 2017
Vasily V. Ashapkin, Lyudmila I. Kutueva, Boris F. Vanyushin
In a larger-scale investigation using the Illumina HumanMethylation450 BeadChip platform, methylation levels of 485,577 CpG sites were analyzed in blood DNA samples from more than 650 volunteers of 19- to 101-year ages [35]. An age predictive model was built using a set of 71 methylation markers. The mean error of age prediction by this model was ±3.9 years (96% correlation between the passport age and the predicted age). Nearly all markers in the model were located within or near genes with known functions in age-related conditions, such as Alzheimer's disease, cancer, tissue degradation, DNA damage, and oxidative stress. Two sites chosen were within the gene of somatostatin, a regulator of endocrine and nervous system function, and six sites within the gene encoding KLF14, a “master regulator” of obesity and other metabolic diseases. The model was capable not only of predicting the age, but also of revealing the factors that affect the personal rate of aging. For example, the gender was found to affect it very significantly, DNA methylation “aging” in men being approximately 4% faster than in women. The body mass index (BMI) was found not to affect the aging rate of blood, adipose, and muscle cells, whereas age acceleration by approximately 2.2 years per each additional 10 BMI units was observed in the liver [35,36]. When the model was used to estimate the age of tumors, these appeared approximately 40% more aged than respective normal cells of the same person. The age prediction model worked with DNA samples from other organs (breast, lung, kidney, and skin) with the same accuracy as with blood samples, when a linear offset specific for each organ was used. When the epigenetic predictive models were constructed using the same algorithm but based on the age-related methylation data from other organs (breast, lung, and kidney), the main differences were in the sets of the most informative CpG sites chosen. Only two CpGs near ELOVL2, a gene involved in the skin cell aging, appeared to be common. Not only were the methylation levels of age-related CpG sites changing with age, but also the variation limits of these methylation levels between different persons became larger for most sites. For any specific person, the extent of deviation in these values from the population averages seems to be a fairly accurate measure of the individual aging rate.
PLK4: a link between centriole biogenesis and cancer
Published in Expert Opinion on Therapeutic Targets, 2018
Radhika Radha Maniswami, Seema Prashanth, Archana Venkataramana Karanth, Sindhu Koushik, Hemalatha Govindaraj, Ramesh Mullangi, Sriram Rajagopal, Sooriya Kumar Jegatheesan
PLK4 overexpression-associated centrosome amplification is frequently observed in various cancers. This overexpression may occur due to aberrant expression of transcription factors that regulate PLK4 transcription. Guangjian et al. showed that KLF14 played a role in transcriptional repression of PLK4 and prevented centriole duplication in human cancer cells. Loss of KLF14 increased PLK4 expression, induced centrosome amplification and genomic instability in MEFs, while induced spontaneous tumorigenesis in mouse. Moreover, negative correlation between KLF14 and PLK4 levels was observed in various cancers. Thus, KLF14 functions as a tumor suppressor via regulating PLK4 expression [135].
Up-regulation of MiR-145-5p promotes the growth and migration in LPS-treated HUVECs through inducing macrophage polarization to M2
Published in Journal of Receptors and Signal Transduction, 2021
It should be noted that some limitations still existed in our study, for example, the function of miR-145-5p overexpression in protecting the LPS-induced HUVEC injury by switching macrophage phenotype was only supported by in vitro experiments. Additionally, significant regulation of KLF14 by miR-145-5p overexpression observed in the study requires to be further verified. Moreover, the molecular mechanisms of miR-145-5p in regulating macrophage immunophenotype to attenuate of LPS-induced HUVEC injury should be studied in the future.