The transcriptional landscape of age in human peripheral blood

Nature Communications - Tập 6 Số 1
Marjolein J. Peters1, Roby Joehanes2, Luke C. Pilling3, Claudia Schurmann4, Karen N. Conneely5, Joseph E. Powell6, Eva Reinmaa7, George L. Sutphin8, Alexandra Zhernakova9, Katharina Schramm10, Yana A. Wilson11, Sayuko Kobes12, Taru Tukiainen13, Michael A. Nalls14, Dena Hernández14, Mark Cookson14, J. Raphael Gibbs14, John Hardy15, Adaikalavan Ramasamy15, Alan B. Zonderman16, Allissa Dillman14, Bryan J. Traynor14, Colin Smith17, Dan L. Longo18, Daniah Trabzuni15, Juan C. Troncoso19, Marcel van der Brug14, Michael E. Weale20, Richard M. O’Brien19, Robert Johnson21, Robert Walker17, Ronald H. Zielke21, Henk W. Berendse14, Mina Ryten15, Andrew Singleton14, Y.F. Ramos22, Harald H.H. Göring23, Myriam Fornage24, Yongmei Liu25, Sina A. Gharib26, Barbara E. Stranger27, Philip L. De Jager28, Abraham Aviv29, Daniel Levy30, Joanne M. Murabito2, Peter J. Munson31, Tianxiao Huan30, Albert Hofman32, André G. Uitterlinden32, Fernando Rivadeneira32, Jeroen van Rooij1, Lise Tarnow1, Linda Broer1, Michaël Verbiest1, Mila Jhamai1, Pascal P. Arp1, Andres Metspalu7, Liina Tserel33, Lili Milani7, Nilesh J. Samani34, Pärt Peterson33, Silva Kasela35, Veryan Codd34, Annette Peters36, Cavin Ward‐Caviness36, Christian Herder37, Mélanie Waldenberger36, Michael Roden37, Paula Singmann36, Sonja Kunze36, Thomas Illig38, Georg Homuth4, Hans J. Grabe39, Henry Völzke40, Leif Steil4, Thomas Kocher41, Anna Murray3, David Melzer3, Hanieh Yaghootkar42, Stefania Bandinelli43, Eric K. Moses44, Jack W. Kent23, Joanne E. Curran23, Matthew P. Johnson23, Sarah Williams‐Blangero23, Harm-Jan Westra45, Allan F. McRae46, Jennifer A. Smith47, Sharon L. R. Kardia47, Iiris Hovatta48, Markus Perola49, Samuli Ripatti49, Veikko Salomaa49, Anjali K. Henders50, Nicholas G. Martin51, Alicia K. Smith52, Divya Mehta53, Elisabeth B. Binder53, K. Maria Nylocks52, Elizabeth M. Kennedy5, Torsten Klengel53, Jingzhong Ding54, Astrid Suchy‐Dicey55, Daniel A. Enquobahrie55, Jennifer A. Brody56, Jerome I. Rotter57, Nicole Soranzo57, Jeanine J. Houwing‐Duistermaat58, M. Kloppenburg59, P. Eline Slagboom22, Quinta Helmer58, Wouter den Hollander22, Shannon Bean8, Towfique Raj60, Noman Bakhshi11, Qiao‐Ping Wang11, Lisa J. Oyston11, Bruce M. Psaty61, Russell P. Tracy62, Grant W. Montgomery51, Stephen T. Turner63, John Blangero23, Ingrid B. Borecki22, Kerry J. Ressler52, Jian Yang64, Lude Franke9, Johannes Kettunen65, Peter M. Visscher64, G. Gregory Neely11, Ron Korstanje8, Robert L. Hanson12, Holger Prokisch66, Luigi Ferrucci67, Tõnu Esko68, Alexander Teumer4, Joyce B. J. van Meurs1, Andrew D. Johnson30
1Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam, 3000CA, The Netherlands
2The National Heart, Lung, and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, 01702, Massachusetts, USA
3Epidemiology and Public Health, University of Exeter Medical School, Exeter, EX4 1DB, UK
4Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17493, Germany
5Department of Human Genetics, School of Medicine, Emory University, Atlanta, 30301, Georgia, USA
6Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, St Lucia, 4000, Brisbane, Queensland, Australia
7Estonian Genome Center, University of Tartu, Tartu, 0794, Estonia
8Nathan Shock Center of Excellence in the Basic Biology of Aging, The Jackson Laboratory, Bar Harbor, 04609, Maine, USA
9Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, 9700RB, The Netherlands
10Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
11Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, 2006, New South Wales, Australia
12Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, 85001, Arizona, USA
13Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, 00131, Finland
14Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, 20817, Maryland, USA
15Reta Lila Weston Institute and Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
16Research Resources Branch, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, 20817, USA
17Department of Neuropathology, MRC Sudden Death Brain Bank Project, University of Edinburgh, Edinburgh, EH13, UK
18Lymphocyte Cell Biology Unit, Laboratory of Immunology, National Institute on Aging, National Institutes of Health, Baltimore, 20817, Maryland, USA
19Brain Resource Center, Johns Hopkins University, Baltimore, 20817, Maryland, USA
20Department of Medical and Molecular Genetics, King’s College London, Guy’s Hospital, London SE1 9RT, UK
21NICHD Brain and Tissue Bank for Developmental Disorders, University of Maryland Medical School, Baltimore, 2117, Maryland, USA
22Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, 2300RC, The Netherlands
23Department of Genetics, Texas Biomedical Research Institute, San Antonio, 78201, Texas, USA
24Division of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Sciences, Center at Houston, 77001, Texas, USA
25Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, 27101, North Carolina, USA
26Computational Medicine Core, Center for Lung Biology, University of Washington, Seattle, 98101, Washington, USA
27Section of Genetic Medicine, Institute for Genomics and Systems Biology, University of Chicago, Chicago, 60290, Illinois, USA
28Department of Neurology, Program in Translational NeuroPsychiatric Genomics, Brigham and Women’s Hospital, Harvard Medical School, Boston, 02108, Massachusetts, USA
29Center of Human Development and Aging, New Jersey Medical School, Newark, 07101, USA
30Division of Intramural Research, Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, 20817, Maryland, USA
31The Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, 20817, Maryland, USA
32Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3000CA, The Netherlands
33Molecular Pathology, Institute of Biomedicine, University of Tartu, Tartu, 0794, Estonia
34Department of Cardiovascular Sciences, University of Leicester, Leicester, LE1, UK
35Institute of Molecular and Cell Biology, Estonian Genome Center, University of Tartu, Tartu, 0794, Estonia
36Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg, 85764, Germany
37Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, 40593, Germany
38Hannover Unified Biobank, Hannover Medical School, Hannover, 30519, Germany
39Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, University Medicine Greifswald, Greifswald, 17489, Germany
40Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany.
41Department of Restorative Dentistry, Unit of Periodontology, Periodontology and Endodontology, University Medicine Greifswald, Greifswald, 17489, Germany
42Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK
43Geriatric Unit, Azienda Sanitaria di Firenze, Florence, 50123, Italy
44Centre for Genetic Origins of Health and Disease, The University of Western Australia, and Faculty of Health Sciences, Curtin University, Perth, 9011, Western Australia, Australia
45Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02138, USA
46The Queensland Brain Institute, University of Queensland, Brisbane, 4000, Queensland, Australia
47Department of Epidemiology, University of Michigan, Ann Arbor, 48103, Michigan, USA
48Department of Biosciences, University of Helsinki, Helsinki, 00100, Finland
49Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, 00131, Finland
50The Institute for Molecular Bioscience, University of Queensland, Brisbane, 4000, Queensland, Australia
51QIMR Berghofer Medical Research Institute, Brisbane, 4000, Queensland, Australia
52Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, 30301, Georgia, USA
53Max-Planck Institute of Psychiatry, Munich, 80331, Germany
54Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, 27101, North Carolina, USA
55Department of Epidemiology, University of Washington, Seattle, 98101, Washington, USA
56Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, Washington, USA
57Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, 90501, California, USA
58Department of Medical Statistics, Leiden University Medical Center, Leiden, 2300RC, The Netherlands
59Department of Rheumatology, Leiden University Medical Center, Leiden, 2300RC, The Netherlands
60Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, 02138, Massachusetts, USA
61Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, 98195, Washington, USA
62Department of Pathology, University of Vermont College of Medicine, Colchester, 98195, Vermont, USA
63Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, 55901, Minnesota, USA
64University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, 4000, Queensland, Australia
65Computational Medicine, Institute of Health Sciences, Faculty of Medicine, University of Oulu, Oulu, 90570, Finland
66Institute of Human Genetics, Technical University Munich, Munich, 85540, Germany
67Clinical Research Branch, National Institute on Aging, Baltimore, 21218, Maryland, USA
68Division of Endocrinology, Children's Hospital Boston, Boston, 02108, Massachusetts, USA

Tóm tắt

AbstractDisease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age’ of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.

Từ khóa


Tài liệu tham khảo

Eicher, J. D. et al. GRASP v2.0: an update on the Genome-Wide Repository of Associations between SNPs and phenotypes. Nucleic Acids Res. 43, D799–D804 (2014).

Welter, D. et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 42, D1001–D1006 (2014).

Anselmi, C. V. et al. Association of the FOXO3A locus with extreme longevity in a southern Italian centenarian study. Rejuvenation Res. 12, 95–104 (2009).

Broer, L. et al. GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. J. Gerontol. A Biol. Sci. Med. Sci. 70, 110–118 (2014).

Nebel, A. et al. A genome-wide association study confirms APOE as the major gene influencing survival in long-lived individuals. Mech. Ageing Dev. 132, 324–330 (2011).

Schachter, F. et al. Genetic associations with human longevity at the APOE and ACE loci. Nat. Genet. 6, 29–32 (1994).

Soerensen, M. et al. Replication of an association of variation in the FOXO3A gene with human longevity using both case-control and longitudinal data. Aging Cell 9, 1010–1017 (2010).

Walter, S. et al. A genome-wide association study of aging. Neurobiol. Aging 32, 2109 e2115–2109 e2128 (2011).

Willcox, B. J. et al. FOXO3A genotype is strongly associated with human longevity. Proc. Natl Acad. Sci. USA 105, 13987–13992 (2008).

Ganna, A. et al. Genetic determinants of mortality. Can findings from genome-wide association studies explain variation in human mortality? Hum. Genet. 132, 553–561 (2013).

Sebastiani, P. et al. Genetic signatures of exceptional longevity in humans. PLoS ONE 7, e29848 (2012).

Kenyon, C. J. The genetics of ageing. Nature 464, 504–512 (2010).

Jin, W. et al. The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat. Genet. 29, 389–395 (2001).

Jones, S. J. M. et al. Changes in gene expression associated with developmental arrest and longevity in Caenorhabditis elegans. Genome Res. 11, 1346–1352 (2001).

Weindruch, R., Kayo, T., Lee, C. K. & Prolla, T. A. Microarray profiling of gene expression in aging and its alteration by caloric restriction in mice. J. Nutr. 131, 918s–923s (2001).

Ly, D. H., Lockhart, D. J., Lerner, R. A. & Schultz, P. G. Mitotic misregulation and human aging. Science 287, 2486–2492 (2000).

van den Akker, E. B. et al. Meta-analysis on blood transcriptomic studies identifies consistently coexpressed protein-protein interaction modules as robust markers of human aging. Aging Cell 13, 216–225 (2014).

Glass, D. et al. Gene expression changes with age in skin, adipose tissue, blood and brain. Genome Biol. 14, R75 (2013).

Harries, L. W. et al. Human aging is characterized by focused changes in gene expression and deregulation of alternative splicing. Aging Cell 10, 868–878 (2011).

Kent, J. W. et al. Genotype x age interaction in human transcriptional ageing. Mech. Ageing Dev. 133, 581–590 (2012).

Zeller, T. et al. Genetics and beyond—the transcriptome of human monocytes and disease susceptibility. PLoS ONE 5, e10693 (2010).

Tan, Q. et al. Genetic dissection of gene expression observed in whole blood samples of elderly Danish twins. Hum. Genet. 117, 267–274 (2005).

Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol. 14, R115 (2013).

Hannum, G. et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol. Cell 49, 359–367 (2013).

Houtkooper, R. H. et al. Mitonuclear protein imbalance as a conserved longevity mechanism. Nature 497, 451–457 (2013).

McCarroll, S. A. et al. Comparing genomic expression patterns across species identifies shared transcriptional profile in aging. Nat. Genet. 36, 197–204 (2004).

Landis, G., Shen, J. & Tower, J. Gene expression changes in response to aging compared to heat stress, oxidative stress and ionizing radiation in Drosophila melanogaster. Aging (Albany NY) 4, 768–789 (2012).

Landis, G. N. et al. Similar gene expression patterns characterize aging and oxidative stress in Drosophila melanogaster. Proc. Natl Acad. Sci. USA 101, 7663–7668 (2004).

Lauring, B. et al. Nascent-polypeptide-associated complex: a bridge between ribosome and cytosol. Cold Spring Harb. Symp. Quant. Biol. 60, 47–56 (1995).

Johnson, S. C. et al. mTOR inhibition alleviates mitochondrial disease in a mouse model of Leigh syndrome. Science 342, 1524–1528 (2013).

Park, J. et al. ATM-deficient human fibroblast cells are resistant to low levels of DNA double-strand break induced apoptosis and subsequently undergo drug-induced premature senescence. Biochem Biophys. Res. Commun. 430, 429–435 (2013).

Luo, Y. B. et al. Investigation of age-related changes in LMNA splicing and expression of progerin in human skeletal muscles. Int. J. Clin. Exp. Pathol. 6, 2778–2786 (2013).

Bonder, M. J. et al. Genetic and epigenetic regulation of gene expression in fetal and adult human livers. BMC Genomics 15, 860 (2014).

Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

Gheorghe, M. et al. Major aging-associated RNA expressions change at two distinct age-positions. BMC Genomics 15, 132 (2014).

Shigenaga, M. K., Hagen, T. M. & Ames, B. N. Oxidative damage and mitochondrial decay in aging. Proc. Natl Acad. Sci. USA 91, 10771–10778 (1994).

Ojaimi, J., Masters, C. L., Opeskin, K., McKelvie, P. & Byrne, E. Mitochondrial respiratory chain activity in the human brain as a function of age. Mech. Ageing Dev. 111, 39–47 (1999).

Short, K. R. et al. Decline in skeletal muscle mitochondrial function with aging in humans. Proc. Natl Acad. Sci. USA 102, 5618–5623 (2005).

Yen, T. C., Chen, Y. S., King, K. L., Yeh, S. H. & Wei, Y. H. Liver mitochondrial respiratory functions decline with age. Biochem. Biophys. Res. Commun. 165, 944–1003 (1989).

Sallusto, F., Lenig, D., Forster, R., Lipp, M. & Lanzavecchia, A. Two subsets of memory T lymphocytes with distinct homing potentials and effector functions. Nature 401, 708–712 (1999).

Lee, W. W., Yang, Z. Z., Li, G., Weyand, C. M. & Goronzy, J. J. Unchecked CD70 expression on T cells lowers threshold for T cell activation in rheumatoid arthritis. J. Immunol. 179, 2609–2615 (2007).

Moro-Garcia, M. A., Alonso-Arias, R. & Lopez-Larrea, C. Molecular mechanisms involved in the aging of the T-cell immune response. Curr. Genomics 13, 589–602 (2012).

Pletcher, S. D. et al. Genome-wide transcript profiles in aging and calorically restricted Drosophila melanogaster. Curr. Biol. 12, 712–723 (2002).

Rera, M., Clark, R. I. & Walker, D. W. Intestinal barrier dysfunction links metabolic and inflammatory markers of aging to death in Drosophila. Proc. Natl Acad. Sci. USA 109, 21528–21533 (2012).

Landis, G. N., Bhole, D. & Tower, J. A search for doxycycline-dependent mutations that increase Drosophila melanogaster life span identifies the VhaSFD, Sugar baby, filamin, fwd and Cctl genes. Genome Biol. 4, R8 (2003).

Liu, Y. L. et al. Reduced expression of alpha-1,2-mannosidase I extends lifespan in Drosophila melanogaster and Caenorhabditis elegans. Aging Cell 8, 370–379 (2009).

Landis, G., Bhole, D., Lu, L. & Tower, J. High-frequency generation of conditional mutations affecting Drosophila melanogaster development and life span. Genetics 158, 1167–1176 (2001).

Taylor, K. R. & Gallo, R. L. Glycosaminoglycans and their proteoglycans: host-associated molecular patterns for initiation and modulation of inflammation. FASEB J. 20, 9–22 (2006).

Pittman, J. Effect of aging on wound healing: current concepts. J. Wound Ostomy Continence Nurs. 34, 412–415 quiz 416–417 (2007).

Loegel, T. N., Trombley, J. D., Taylor, R. T. & Danielson, N. D. Capillary electrophoresis of heparin and other glycosaminoglycans using a polyamine running electrolyte. Anal. Chim. Acta 753, 90–96 (2012).

Didsbury, A. et al. Rotavirus NSP4 is secreted from infected cells as an oligomeric lipoprotein and binds to glycosaminoglycans on the surface of non-infected cells. Virol. J. 8, 551 (2011).

Gourlay, C. W. & Ayscough, K. R. A role for actin in aging and apoptosis. Biochem. Soc. Trans 33, 1260–1264 (2005).

Higuchi, R. et al. Actin dynamics affect mitochondrial quality control and aging in budding yeast. Curr. Biol. 23, 2417–2422 (2013).

Bratic, A. & Larsson, N. G. The role of mitochondria in aging. J. Clin. Invest. 123, 951–957 (2013).

Ebersberger, I. et al. The evolution of the ribosome biogenesis pathway from a yeast perspective. Nucleic Acids Res. 42, 1509–1523 (2014).

Kenyon, J. & Gerson, S. L. The role of DNA damage repair in aging of adult stem cells. Nucleic Acids Res. 35, 7557–7565 (2007).

Petes, T. D., Farber, R. A., Tarrant, G. M. & Holliday, R. Altered rate of DNA replication in ageing human fibroblast cultures. Nature 251, 434–436 (1974).

Wolfson, M., Budovsky, A., Tacutu, R. & Fraifeld, V. The signaling hubs at the crossroad of longevity and age-related disease networks. Int. J. Biochem. Cell. Biol. 41, 516–520 (2009).

Boya, P. Lysosomal function and dysfunction: mechanism and disease. Antioxid. Redox Signal. 17, 766–774 (2012).

Seoh, M. L., Ng, C. H., Yong, J., Lim, L. & Leung, T. ArhGAP15, a novel human RacGAP protein with GTPase binding property. FEBS Lett. 539, 131–137 (2003).

Patil, V., Ward, R. L. & Hesson, L. B. The evidence for functional non-CpG methylation in mammalian cells. Epigenetics 9, 823–828 (2014).

Lister, R. et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462, 315–322 (2009).

Allum, F. et al. Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants. Nat. Commun. 6, 7211 (2015).

Jones, P. A. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet. 13, 484–492 (2012).

Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

Price, M. E. et al. Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array. Epigenet. Chromatin 6, 4 (2013).

Sobel, M. E. Sociological Methodology Vol. 13, 290–312 (1982).

Hansen, B. B. & Klopfer, S. O. Optimal full matching and related designs via network flows. J. Comput. Graph. Stat. 15, 609–627 (2006).

Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011).

Barzilai, N. et al. Genetic studies reveal the role of the endocrine and metabolic systems in aging. J. Clin. Endocrinol. Metab. 95, 4493–4500 (2010).

Kenyon, C. The first long-lived mutants: discovery of the insulin/IGF-1 pathway for ageing. Philos. Trans R Soc. Lond. B Biol. Sci. 366, 9–16 (2011).

Newman, A. B. & Murabito, J. M. The epidemiology of longevity and exceptional survival. Epidemiol. Rev. 35, 181–197 (2013).

Harries, L. W. et al. Advancing age is associated with gene expression changes resembling mTOR inhibition: evidence from two human populations. Mech. Ageing Dev. 133, 556–562 (2012).

de Magalhaes, J. P., Curado, J. & Church, G. M. Meta-analysis of age-related gene expression profiles identifies common signatures of aging. Bioinformatics 25, 875–881 (2009).

Passtoors, W. M. et al. Transcriptional profiling of human familial longevity indicates a role for ASF1A and IL7R. PLoS ONE 7, e27759 (2012).

Zahn, J. M. et al. AGEMAP: a gene expression database for aging in mice. PLoS Genet. 3, e201 (2007).

Chou, J. P., Ramirez, C. M., Wu, J. E. & Effros, R. B. Accelerated aging in HIV/AIDS: novel biomarkers of senescent human CD8+ T cells. PLoS ONE 8, e64702 (2013).

Yang, J. et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet. 44, 369–375 S361–363 (2012).