Aging Cell welcome submissions in the following areas: -Genetics and functional genomics: mutations affecting longevity; gene homologies; organismal and cellular aging; gene manipulation. -Signaling and gene expression: mechanisms linking age-associated changes with phenotypes and physiology; intracellular signaling; interactions between cells and tissues; hormonal, immune, and inflammatory systems. -Cell proliferation, aging and death: replicative senescence; apoptosis; telomere biology and other intrinsic and extrinsic influences; chronological cellular aging; phenotypes of aging cells. -Cell stress and damage: extrinsic and intrinsic influences of free radicals on cells and tissues; free radical defense and damage; free radicals as signaling molecules; stress and aging. -Stem cells and aging: effects of age on stem cell generation; migration and homeostasis; stem cell-niche interactions; regulatory mechanisms. -Integrative physiology: outcomes of aging processes at organismal, cellular and molecular levels. -Biodemography and comparative studies: population and cross-species comparative studies. -New theories of aging and longevity: discussion at the broadest level of established and novel theories of aging and longevity.
Erik B. van den Akker, Willemijn M. Passtoors, Rick Jansen, Erik W. van Zwet, Jelle J. Goeman, Marc Hulsman, Valur Emilsson, Markus Perola, Gonneke Willemsen, Brenda W.J.H. Penninx, Bas Heijmans, Andrea B. Maier, Dorret I. Boomsma, Joost N. Kok, P. Eline Slagboom, Marcel J. T. Reinders, Marian Beekman
SummaryThe bodily decline that occurs with advancing age strongly impacts on the prospects for future health and life expectancy. Despite the profound role of age in disease etiology, knowledge about the molecular mechanisms driving the process of aging in humans is limited. Here, we used an integrative network‐based approach for combining multiple large‐scale expression studies in blood (2539 individuals) with protein–protein Interaction (PPI) data for the detection of consistently coexpressed PPI modules that may reflect key processes that change throughout the course of normative aging. Module detection followed by a meta‐analysis on chronological age identified fifteen consistently coexpressed PPI modules associated with chronological age, including a highly significant module (P =3.5 × 10−38) enriched for ‘T‐cell activation’ marking age‐associated shifts in lymphocyte blood cell counts (R2 = 0.603; P =1.9 × 10−10). Adjusting the analysis in the compendium for the ‘T‐cell activation’ module showed five consistently coexpressed PPI modules that robustly associated with chronological age and included modules enriched for ‘Translational elongation’, ‘Cytolysis’ and ‘DNA metabolic process’. In an independent study of 3535 individuals, four of five modules consistently associated with chronological age, underpinning the robustness of the approach. We found three of five modules to be significantly enriched with aging‐related genes, as defined by the GenAge database, and association with prospective survival at high ages for one of the modules including ASF1A. The hereby‐detected age‐associated and consistently coexpressed PPI modules therefore may provide a molecular basis for future research into mechanisms underlying human aging.
Malene Hansen, Stefan Taubert, Douglas K. Crawford, Nataliya Libina, Seung‐Jae Lee, Cynthia Kenyon
SummaryMany conditions that shift cells from states of nutrient utilization and growth to states of cell maintenance extend lifespan. We have carried out a systematic lifespan analysis of conditions that inhibit protein synthesis. We find that reducing the levels of ribosomal proteins, ribosomal‐protein S6 kinase or translation‐initiation factors increases the lifespan of Caenorhabditis elegans. These perturbations, as well as inhibition of the nutrient sensor target of rapamycin (TOR), which is known to increase lifespan, all increase thermal‐stress resistance. Thus inhibiting translation may extend lifespan by shifting cells to physiological states that favor maintenance and repair. Interestingly, different types of translation inhibition lead to one of two mutually exclusive outputs, one that increases lifespan and stress resistance through the transcription factor DAF‐16/FOXO, and one that increases lifespan and stress resistance independently of DAF‐16. Our findings link TOR, but not sir‐2.1, to the longevity response induced by dietary restriction (DR) in C. elegans, and they suggest that neither TOR inhibition nor DR extends lifespan simply by reducing protein synthesis.
Alice C. Holly, David Melzer, Luke C. Pilling, William Henley, Dena Hernandez, Andrew Singleton, Stefania Bandinelli, Jack M. Guralnik, Luigi Ferrucci, Lorna W. Harries
SummaryWe have previously described a statistical model capable of distinguishing young (age <65 years) from old (age ≥75 years) individuals. Here we studied the performance of a modified model in three populations and determined whether individuals predicted to be biologically younger than their chronological age had biochemical and functional measures consistent with a younger biological age. Those with ‘younger’ gene expression patterns demonstrated higher muscle strength and serum albumin, and lower interleukin‐6 and blood urea concentrations relative to ‘biologically older’ individuals (odds ratios 2.09, 1.64, 0.74, 0.74; P = 2.4 × 10−2, 3.5 × 10−4, 1.8 × 10−2, 1.5 × 10−2, respectively). We conclude that our expression signature of age is robust across three populations and may have utility for estimation of biological age.
Marco De Cecco, Steven W. Criscione, Edward Peckham, Sara Hillenmeyer, Eliza A. Hamm, Jayameenakshi Manivannan, Adam Peterson, Jill A. Kreiling, Nicola Neretti, John M. Sedivy
SummaryReplicative cellular senescence is an important tumor suppression mechanism and also contributes to aging. Progression of both cancer and aging include significant epigenetic components, but the chromatin changes that take place during cellular senescence are not known. We used formaldehyde assisted isolation of regulatory elements (FAIRE) to map genome‐wide chromatin conformations. In contrast to growing cells, whose genomes are rich with features of both open and closed chromatin, FAIRE profiles of senescent cells are significantly smoothened. This is due to FAIRE signal loss in promoters and enhancers of active genes, and FAIRE signal gain in heterochromatic gene‐poor regions. Chromatin of major retrotransposon classes, Alu, SVA and L1, becomes relatively more open in senescent cells, affecting most strongly the evolutionarily recent elements, and leads to an increase in their transcription and ultimately transposition. Constitutive heterochromatin in centromeric and peri‐centromeric regions also becomes relatively more open, and the transcription of satellite sequences increases. The peripheral heterochromatic compartment (PHC) becomes less prominent, and centromere structure becomes notably enlarged. These epigenetic changes progress slowly after the onset of senescence, with some, such as mobilization of retrotransposable elements becoming prominent only at late times. Many of these changes have also been noted in cancer cells.
Benjamin P. Lee, Luke C. Pilling, Florence Emond, Kevin Flurkey, David Harrison, Rong Yuan, Luanne L. Peters, George A. Kuchel, Luigi Ferrucci, David Melzer, Lorna W. Harries
Christopher D. Wiley, James M. Flynn, Christapher S. Morrissey, Ronald Lebofsky, Joe Shuga, Xiao Dong, Marc Unger, Jan Vijg, Simon Melov, Judith Campisi
SummarySenescent cells play important roles in both physiological and pathological processes, including cancer and aging. In all cases, however, senescent cells comprise only a small fraction of tissues. Senescent phenotypes have been studied largely in relatively homogeneous populations of cultured cells. In vivo, senescent cells are generally identified by a small number of markers, but whether and how these markers vary among individual cells is unknown. We therefore utilized a combination of single‐cell isolation and a nanofluidic PCR platform to determine the contributions of individual cells to the overall gene expression profile of senescent human fibroblast populations. Individual senescent cells were surprisingly heterogeneous in their gene expression signatures. This cell‐to‐cell variability resulted in a loss of correlation among the expression of several senescence‐associated genes. Many genes encoding senescence‐associated secretory phenotype (SASP) factors, a major contributor to the effects of senescent cells in vivo, showed marked variability with a subset of highly induced genes accounting for the increases observed at the population level. Inflammatory genes in clustered genomic loci showed a greater correlation with senescence compared to nonclustered loci, suggesting that these genes are coregulated by genomic location. Together, these data offer new insights into how genes are regulated in senescent cells and suggest that single markers are inadequate to identify senescent cells in vivo.
You‐Mie Kim, Hae‐Ok Byun, Byul A Jee, Hyunwoo Cho, Yonghak Seo, You‐Sun Kim, Min Hi Park, Hae‐Young Chung, Hyun Goo Woo, Gyesoon Yoon
SummaryAlthough senescence has long been implicated in aging‐associated pathologies, it is not clearly understood how senescent cells are linked to these diseases. To address this knowledge gap, we profiled cellular senescence phenotypes and mRNA expression patterns during replicative senescence in human diploid fibroblasts. We identified a sequential order of gain‐of‐senescence phenotypes: low levels of reactive oxygen species, cell mass/size increases with delayed cell growth, high levels of reactive oxygen species with increases in senescence‐associated β‐galactosidase activity (SA‐β‐gal), and high levels of SA‐β‐gal activity. Gene expression profiling revealed four distinct modules in which genes were prominently expressed at certain stages of senescence, allowing us to divide the process into four stages: early, middle, advanced, and very advanced. Interestingly, the gene expression modules governing each stage supported the development of the associated senescence phenotypes. Senescence‐associated secretory phenotype–related genes also displayed a stage‐specific expression pattern with three unique features during senescence: differential expression of interleukin isoforms, differential expression of interleukins and their receptors, and differential expression of matrix metalloproteinases and their inhibitory proteins. We validated these phenomena at the protein level using human diploid fibroblasts and aging Sprague‐Dawley rat skin tissues. Finally, disease‐association analysis of the modular genes also revealed stage‐specific patterns. Taken together, our results reflect a detailed process of cellular senescence and provide diverse genome‐wide information of cellular backgrounds for senescence.
Wilson C. Fok, Alex Bokov, Jonathan Gelfond, Zhentao Yu, Yiqiang Zhang, Mark Doderer, Yidong Chen, Martin A. Javors, William H. Wood, Yongqing Zhang, Kevin G. Becker, Arlan Richardson, Viviana Pérez
SummaryRapamycin (Rapa) and dietary restriction (DR) have consistently been shown to increase lifespan. To investigate whether Rapa and DR affect similar pathways in mice, we compared the effects of feeding mice ad libitum (AL), Rapa, DR, or a combination of Rapa and DR (Rapa + DR) on the transcriptome and metabolome of the liver. The principal component analysis shows that Rapa and DR are distinct groups. Over 2500 genes are significantly changed with either Rapa or DR when compared with mice fed AL; more than 80% are unique to DR or Rapa. A similar observation was made when genes were grouped into pathways; two‐thirds of the pathways were uniquely changed by DR or Rapa. The metabolome shows an even greater difference between Rapa and DR; no metabolites in Rapa‐treated mice were changed significantly from AL mice, whereas 173 metabolites were changed in the DR mice. Interestingly, the number of genes significantly changed by Rapa + DR when compared with AL is twice as large as the number of genes significantly altered by either DR or Rapa alone. In summary, the global effects of DR or Rapa on the liver are quite different and a combination of Rapa and DR results in alterations in a large number of genes and metabolites that are not significantly changed by either manipulation alone, suggesting that a combination of DR and Rapa would be more effective in extending longevity than either treatment alone.
SummaryThe concept that mutations cause aging phenotypes could not be directly tested previously due to inability to identify age‐related mutations in somatic cells and determine their impact on organismal aging. Here, we subjected Saccharomyces cerevisiae to multiple rounds of replicative aging and assessed de novo mutations in daughters of mothers of different age. Mutations did increase with age, but their low numbers, < 1 per lifespan, excluded their causal role in aging. Structural genome changes also had no role. A mutant lacking thiol peroxidases had the mutation rate well above that of wild‐type cells, but this did not correspond to the aging pattern, as old wild‐type cells with few or no mutations were dying, whereas young mutant cells with many more mutations continued dividing. In addition, wild‐type cells lost mitochondrial DNA during aging, whereas shorter‐lived mutant cells preserved it, excluding a causal role of mitochondrial mutations in aging. Thus, DNA mutations do not cause aging in yeast. These findings may apply to other damage types, suggesting a causal role of cumulative damage, as opposed to individual damage types, in organismal aging.
Chỉ số ảnh hưởng
Total publication
3
Total citation
566
Avg. Citation
188.67
Impact Factor
0
H-index
3
H-index (5 years)
3
i10
2
i10-index (5 years)
0
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