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      Epigenetic Predictor of Age

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          Abstract

          From the moment of conception, we begin to age. A decay of cellular structures, gene regulation, and DNA sequence ages cells and organisms. DNA methylation patterns change with increasing age and contribute to age related disease. Here we identify 88 sites in or near 80 genes for which the degree of cytosine methylation is significantly correlated with age in saliva of 34 male identical twin pairs between 21 and 55 years of age. Furthermore, we validated sites in the promoters of three genes and replicated our results in a general population sample of 31 males and 29 females between 18 and 70 years of age. The methylation of three sites—in the promoters of the EDARADD, TOM1L1, and NPTX2 genes—is linear with age over a range of five decades. Using just two cytosines from these loci, we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years. In forensic science, such a model could estimate the age of a person, based on a biological sample alone. Furthermore, a measurement of relevant sites in the genome could be a tool in routine medical screening to predict the risk of age-related diseases and to tailor interventions based on the epigenetic bio-age instead of the chronological age.

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          Most cited references11

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          Genome-wide association analysis by lasso penalized logistic regression.

          In ordinary regression, imposition of a lasso penalty makes continuous model selection straightforward. Lasso penalized regression is particularly advantageous when the number of predictors far exceeds the number of observations. The present article evaluates the performance of lasso penalized logistic regression in case-control disease gene mapping with a large number of SNPs (single nucleotide polymorphisms) predictors. The strength of the lasso penalty can be tuned to select a predetermined number of the most relevant SNPs and other predictors. For a given value of the tuning constant, the penalized likelihood is quickly maximized by cyclic coordinate ascent. Once the most potent marginal predictors are identified, their two-way and higher order interactions can also be examined by lasso penalized logistic regression. This strategy is tested on both simulated and real data. Our findings on coeliac disease replicate the previous SNP results and shed light on possible interactions among the SNPs. The software discussed is available in Mendel 9.0 at the UCLA Human Genetics web site. Supplementary data are available at Bioinformatics online.
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            Dimethyl sulfoxide to vorinostat: development of this histone deacetylase inhibitor as an anticancer drug.

            In our quest to understand why dimethyl sulfoxide (DMSO) can cause growth arrest and terminal differentiation of transformed cells, we followed a path that led us to discover suberoylanilide hydroxamic acid (SAHA; vorinostat (Zolinza)), which is a histone deacetylase inhibitor. SAHA reacts with and blocks the catalytic site of these enzymes. Extensive structure-activity studies were done along the path from DMSO to SAHA. SAHA can cause growth arrest and death of a broad variety of transformed cells both in vitro and in tumor-bearing animals at concentrations not toxic to normal cells. SAHA has many protein targets whose structure and function are altered by acetylation, including chromatin-associated histones, nonhistone gene transcription factors and proteins involved in regulation of cell proliferation, migration and death. In clinical trials, SAHA has shown significant anticancer activity against both hematologic and solid tumors at doses well tolerated by patients. A new drug application was approved by the US Food and Drug Administration for vorinostat for treatment of cutaneous T-cell lymphoma. More potent analogs of SAHA have shown unacceptable toxicity.
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              Widespread and tissue specific age-related DNA methylation changes in mice.

              Aberrant methylation of promoter CpG islands in cancer is associated with silencing of tumor-suppressor genes, and age-dependent hypermethylation in normal appearing mucosa may be a risk factor for human colon cancer. It is not known whether this age-related DNA methylation phenomenon is specific to human tissues. We performed comprehensive DNA methylation profiling of promoter regions in aging mouse intestine using methylated CpG island amplification in combination with microarray analysis. By comparing C57BL/6 mice at 3-mo-old versus 35-mo-old for 3627 detectable autosomal genes, we found 774 (21%) that showed increased methylation and 466 (13%) that showed decreased methylation. We used pyrosequencing to quantitatively validate the microarray data and confirmed linear age-related methylation changes for all 12 genomic regions examined. We then examined 11 changed genomic loci for age-related methylation in other tissues. Of these, three of 11 showed similar changes in lung, seven of 11 changed in liver, and six of 11 changed in spleen, though to a lower degree than the changes seen in colon. There was partial conservation between age-related hypermethylation in human and mouse intestines, and Polycomb targets in embryonic stem cells were enriched among the hypermethylated genes. Our findings demonstrate a surprisingly high rate of hyper- and hypomethylation as a function of age in normal mouse small intestine tissues and a strong tissue-specificity to the process. We conclude that epigenetic deregulation is a common feature of aging in mammals.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                22 June 2011
                : 6
                : 6
                : e14821
                Affiliations
                [1 ]Department of Human Genetics, University of California Los Angeles, Los Angeles, California, United States of America
                [2 ]Department of Biostatistics, University of California Los Angeles, Los Angeles, California, United States of America
                [3 ]Department of Medicine, University of California Los Angeles, Los Angeles, California, United States of America
                [4 ]Department of Biomathematics, University of California Los Angeles, Los Angeles, California, United States of America
                [5 ]Center for Society and Genetics, University of California Los Angeles, Los Angeles, California, United States of America
                University of Insubria, Italy
                Author notes

                Conceived and designed the experiments: SB EV. Performed the experiments: SB. Analyzed the data: SB WL MS JS SH EV. Contributed reagents/materials/analysis tools: SB FS JS SH. Wrote the paper: SB SH EV. Helped revise manuscript: FS.

                Article
                11-PONE-RA-21777
                10.1371/journal.pone.0014821
                3120753
                21731603
                de818cff-970d-4fe2-9b41-f241cdc968d9
                Bocklandt et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 11 March 2011
                : 11 May 2011
                Page count
                Pages: 6
                Categories
                Research Article
                Developmental Biology/Aging
                Genetics and Genomics/Epigenetics
                Molecular Biology/DNA Methylation
                Genetics and Genomics/Epigenetics

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                Uncategorized

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