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      ELOVL2: Not just a biomarker of aging

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          Abstract

          DNA methylation of the ELOVL2 (Elongation Of Very Long Chain Fatty Acids-Like 2) promoter is one of the most robust molecular biomarkers for chronological age, but whether ELOVL2 plays a functional role in aging has not been explored. ELOVL2 encodes a transmembrane protein involved in the synthesis of very long polyunsaturated fatty acids (VLC-PUFAs). These fatty acids play important roles in retinal biology and photoreceptor renewal, key processes implicated in age-related eye diseases such as age-related macular degeneration (AMD). Here, we summarize our work deciphering the role of ELOVL2 in the eye emphasizing the potential functional role of age-related DNA methylation in the pathophysiology of AMD.

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          Methylation of ELOVL2 gene as a new epigenetic marker of age.

          The discovery of biomarkers able to predict biological age of individuals is a crucial goal in aging research. Recently, researchers' attention has turn toward epigenetic markers of aging. Using the Illumina Infinium HumanMethylation450 BeadChip on whole blood DNA from a small cohort of 64 subjects of different ages, we identified 3 regions, the CpG islands of ELOVL2, FHL2, and PENK genes, whose methylation level strongly correlates with age. These results were confirmed by the Sequenom's EpiTYPER assay on a larger cohort of 501 subjects from 9 to 99 years, including 7 cord blood samples. Among the 3 genes, ELOVL2 shows a progressive increase in methylation that begins since the very first stage of life (Spearman's correlation coefficient = 0.92) and appears to be a very promising biomarker of aging. © 2012 The Authors Aging Cell © 2012 Blackwell Publishing Ltd/Anatomical Society of Great Britain and Ireland.
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            Impact of age, BMI and HbA1c levels on the genome-wide DNA methylation and mRNA expression patterns in human adipose tissue and identification of epigenetic biomarkers in blood.

            Increased age, BMI and HbA1c levels are risk factors for several non-communicable diseases. However, the impact of these factors on the genome-wide DNA methylation pattern in human adipose tissue remains unknown. We analyzed the DNA methylation of ∼480 000 sites in human adipose tissue from 96 males and 94 females and related methylation to age, BMI and HbA1c. We also compared epigenetic signatures in adipose tissue and blood. Age was significantly associated with both altered DNA methylation and expression of 1050 genes (e.g. FHL2, NOX4 and PLG). Interestingly, many reported epigenetic biomarkers of aging in blood, including ELOVL2, FHL2, KLF14 and GLRA1, also showed significant correlations between adipose tissue DNA methylation and age in our study. The most significant association between age and adipose tissue DNA methylation was found upstream of ELOVL2. We identified 2825 genes (e.g. FTO, ITIH5, CCL18, MTCH2, IRS1 and SPP1) where both DNA methylation and expression correlated with BMI. Methylation at previously reported HIF3A sites correlated significantly with BMI in females only. HbA1c (range 28-46 mmol/mol) correlated significantly with the methylation of 711 sites, annotated to, for example, RAB37, TICAM1 and HLA-DPB1. Pathway analyses demonstrated that methylation levels associated with age and BMI are overrepresented among genes involved in cancer, type 2 diabetes and cardiovascular disease. Our results highlight the impact of age, BMI and HbA1c on epigenetic variation of candidate genes for obesity, type 2 diabetes and cancer in human adipose tissue. Importantly, we demonstrate that epigenetic biomarkers in blood can mirror age-related epigenetic signatures in target tissues for metabolic diseases such as adipose tissue.
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              Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception

              Background The well-established association of chronological age with changes in DNA methylation is primarily founded on the analysis of large sets of blood samples, while conclusions regarding tissue-specificity are typically based on small number of samples, tissues and CpGs. Here, we systematically investigate the tissue-specific character of age-related DNA methylation changes at the level of the CpG, functional genomic region and nearest gene in a large dataset. Results We assembled a compendium of public data, encompassing genome-wide DNA methylation data (Illumina 450k array) on 8092 samples from 16 different tissues, including 7 tissues with moderate to high sample numbers (Dataset size range 96–1202, N total = 2858). In the 7 tissues (brain, buccal, liver, kidney, subcutaneous fat, monocytes and T-helper cells), we identified 7850 differentially methylated positions that gained (gain-aDMPs; cut-offs: P bonf ≤ 0.05, effect size ≥ 2%/10 years) and 4,287 that lost DNA methylation with age (loss-aDMPs), 92% of which had not previously been reported for whole blood. The majority of all aDMPs identified occurred in one tissue only (gain-aDMPs: 85.2%; loss-aDMPs: 97.4%), an effect independent of statistical power. This striking tissue-specificity extended to both the functional genomic regions (defined by chromatin state segmentation) and the nearest gene. However, aDMPs did accumulate in regions with the same functional annotation across tissues, namely polycomb-repressed CpG islands for gain-aDMPs and regions marked by active histone modifications for loss-aDMPs. Conclusion Our analysis shows that age-related DNA methylation changes are highly tissue-specific. These results may guide the development of improved tissue-specific markers of chronological and, perhaps, biological age. Electronic supplementary material The online version of this article (10.1186/s13072-018-0191-3) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                101752932
                48862
                Transl Med Aging
                Transl Med Aging
                Translational medicine of aging
                2468-5011
                24 September 2020
                30 June 2020
                2020
                08 October 2020
                : 4
                : 78-80
                Affiliations
                [a ]Viterbi Family Department of Ophthalmology, School do Medicine, University of California San Diego, La Jolla, CA, 92093, USA
                [b ]Department of Physiology and Biophysics, Department of Ophthalmology, Center for Translational Vision Research, School of Medicine, University of California Irvine, CA 92697 and Gavin Herbert Eye Institute, University of California, Irvine, CA, 92697, USA
                Author notes
                [* ]Corresponding author. dlchao@ 123456health.ucsd.edu (D.L. Chao), dorotask@ 123456hs.uci.edu (D. Skowronska-Krawczyk).
                Article
                NIHMS1631395
                10.1016/j.tma.2020.06.004
                7544151
                33043173
                172ebbdf-1368-4e18-963c-b60f47e1db38

                This is an open access article under the CC BY-NC-ND license.

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                polyunsaturated fatty acids,aging,membrane structure,macular degeneration

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