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      Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum

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          Abstract

          DNA methylation (DNAm) levels lend themselves for defining an epigenetic biomarker of aging known as the ‘epigenetic clock'. Our genome-wide association study (GWAS) of cerebellar epigenetic age acceleration identifies five significant ( P<5.0 × 10 −8) SNPs in two loci: 2p22.1 (inside gene DHX57) and 16p13.3 near gene MLST8 (a subunit of mTOR complex 1 and 2). We find that the SNP in 16p13.3 has a cis-acting effect on the expression levels of MLST8 ( P=6.9 × 10 −18) in most brain regions. In cerebellar samples, the SNP in 2p22.1 has a cis-effect on DHX57 ( P=4.4 × 10 −5). Gene sets found by our GWAS analysis of cerebellar age acceleration exhibit significant overlap with those of Alzheimer's disease ( P=4.4 × 10 −15), age-related macular degeneration ( P=6.4 × 10 −6), and Parkinson's disease ( P=2.6 × 10 −4). Overall, our results demonstrate the utility of a new paradigm for understanding aging and age-related diseases: it will be fruitful to use epigenetic tissue age as endophenotype in GWAS.

          Abstract

          This genome-wide association study identifies five significant SNPs in two loci which are associated with the epigenetic age of post-mortem cerebellar tissue according to a DNA methylation based biomarker of human aging.

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          DNA methylation age of blood predicts all-cause mortality in later life

          Background DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. Results Here we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. Conclusions DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0584-6) contains supplementary material, which is available to authorized users.
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            Regulation of yeast replicative life span by TOR and Sch9 in response to nutrients.

            Calorie restriction increases life span in many organisms, including the budding yeast Saccharomyces cerevisiae. From a large-scale analysis of 564 single-gene-deletion strains of yeast, we identified 10 gene deletions that increase replicative life span. Six of these correspond to genes encoding components of the nutrient-responsive TOR and Sch9 pathways. Calorie restriction of tor1D or sch9D cells failed to further increase life span and, like calorie restriction, deletion of either SCH9 or TOR1 increased life span independent of the Sir2 histone deacetylase. We propose that the TOR and Sch9 kinases define a primary conduit through which excess nutrient intake limits longevity in yeast.
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              Obesity accelerates epigenetic aging of human liver.

              Because of the dearth of biomarkers of aging, it has been difficult to test the hypothesis that obesity increases tissue age. Here we use a novel epigenetic biomarker of aging (referred to as an "epigenetic clock") to study the relationship between high body mass index (BMI) and the DNA methylation ages of human blood, liver, muscle, and adipose tissue. A significant correlation between BMI and epigenetic age acceleration could only be observed for liver (r = 0.42, P = 6.8 × 10(-4) in dataset 1 and r = 0.42, P = 1.2 × 10(-4) in dataset 2). On average, epigenetic age increased by 3.3 y for each 10 BMI units. The detected age acceleration in liver is not associated with the Nonalcoholic Fatty Liver Disease Activity Score or any of its component traits after adjustment for BMI. The 279 genes that are underexpressed in older liver samples are highly enriched (1.2 × 10(-9)) with nuclear mitochondrial genes that play a role in oxidative phosphorylation and electron transport. The epigenetic age acceleration, which is not reversible in the short term after rapid weight loss induced by bariatric surgery, may play a role in liver-related comorbidities of obesity, such as insulin resistance and liver cancer.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                02 February 2016
                2016
                : 7
                : 10561
                Affiliations
                [1 ]Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles , Los Angeles, California 90095, USA
                [2 ]University of Exeter Medical School, University of Exeter , Exeter EX2 5DW, UK
                [3 ]Department of Genetics and Genomic Sciences, The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai , New York, New York 10029-6574, USA
                [4 ]Davis School of Gerontology, University of Southern California, Ethel Percy Andrus Gerontology Center , 3715 McClintock Avenue, Los Angeles, California 90089-0191, USA
                [5 ]Department of Psychiatry and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai , New York, New York 10029-6574, USA
                [6 ]James J. Peters VA Medical Center , Bronx, New York 10468, USA
                [7 ]Institute of Psychiatry, King's College London , London SE5 8AF, UK
                [8 ]Biostatistics, School of Public Health, University of California Los Angeles , Los Angeles, California 90095, USA
                Author notes
                Article
                ncomms10561
                10.1038/ncomms10561
                4740877
                26830004
                eccec92d-f14c-41f3-bbeb-95370b59e7be
                Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 17 July 2015
                : 29 December 2015
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