The transcriptional landscape of age in human peripheral blood
Open accessAbstract
Disease 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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A gene-expression study on whole-blood RNA from a large population cohort in Europe and the USA found immune response and inflammation were the most highly upregulated pathways associated with ageing.
“A gene-expression study conducted on whole-blood RNA samples from a large population cohort in Europe and the USA revealed that immune response and inflammation were the most highly upregulated pathways in association with ageing39.”
From Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty (2018) · cites this paper as [39]
The transcriptomic clock was found to have associations with some biomarkers and risk factors, including smoking status, and a unique association with systolic blood pressure that was not detected by the Horvath and Hannum clocks.
“However, the transcriptomic clock was found to have associations with some biomarkers and risk factors, including smoking status, and a unique association with systolic blood pressure that was not detected by the Horvath and Hannum clocks.”
From Measuring biological age using omics data (2022) · cites this paper as [81]
The Peters et al. transcriptomic clock had highly variable age prediction accuracy across cohorts and was significantly less accurate in chronological age prediction than epigenetic clocks in all tested cohorts.
“The transcriptomic clock had highly variable age prediction accuracy across cohorts and was significantly less accurate in chronological age prediction than epigenetic clocks in all tested cohorts.”
From Measuring biological age using omics data (2022) · cites this paper as [81]
Peters et al.'s transcriptomic age gap correlated with different biological ageing measures than the Horvath and Hannum clocks.
“Peters et al.’s transcriptomic age gap correlated with different biological ageing measures to those of the Horvath and Hannum clocks81;”
From Measuring biological age using omics data (2022) · cites this paper as [81]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models
Sobel, M. E. (1982) · Sociological Methodology · doi:10.2307/270723 · Cited by 12,810 · see citing works
DNA methylation age of human tissues and cell types
Horvath, S. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r115 · Cited by 7,075 · see citing works
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368 · see citing works
Self-citationFunctions of DNA methylation: islands, start sites, gene bodies and beyond
Jones, P. A. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3230 · Cited by 6,061 · see citing works
Two subsets of memory T lymphocytes with distinct homing potentials and effector functions
Sallusto, F., Lenig, D., Förster, R., Lipp, M., & Lanzavecchia, A. (1999) · Nature · doi:10.1038/44385 · Cited by 5,846 · see citing works
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205 · see citing works
Human DNA methylomes at base resolution show widespread epigenomic differences
Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., Tonti-Filippini, J., Nery, J. R., Lee, L., Ye, Z., Ngo, Q.-M., et al. (2009) · Nature · doi:10.1038/nature08514 · Cited by 4,673 · see citing works
Genome-wide methylation profiles reveal quantitative views of human aging rates
Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J.-B., Gao, Y., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2012.10.016 · Cited by 4,270 · see citing works
Mapping and analysis of chromatin state dynamics in nine human cell types
Ernst, J., Kheradpour, P., Mikkelsen, T. S., Shoresh, N., Ward, L. D., Epstein, C. B., Zhang, X., Wang, L., Issner, R., Coyne, M., et al. (2011) · Nature · doi:10.1038/nature09906 · Cited by 2,898 · see citing works
Kenyon, C. J. (2010) · Nature · doi:10.1038/nature08980 · Cited by 2,739 · see citing works
The NHGRI GWAS Catalog, a curated resource of SNP-trait associations
Welter, D., MacArthur, J., Morales, J., Burdett, T., Hall, P., Junkins, H., Klemm, A., Flicek, P., Manolio, T., Hindorff, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1229 · Cited by 2,707 · see citing works
Oxidative damage and mitochondrial decay in aging.
Shigenaga, M. K., Hagen, T. M., & Ames, B. N. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.23.10771 · Cited by 2,055 · see citing works
Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Yang, J., DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Ferreira, T., Morris, A. P., Medland, S. E., Madden, P. A. F., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2012) · Nature Genetics · doi:10.1038/ng.2213 · Cited by 1,712 · see citing works
Self-citationDecline in skeletal muscle mitochondrial function with aging in humans
Short, K. R., Bigelow, M. L., Kahl, J., Singh, R., Coenen-Schimke, J., Raghavakaimal, S., & Nair, K. S. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0501559102 · Cited by 1,333 · see citing works
Genetic associations with human longevity at the APOE and ACE loci
Schächter, F., Faure-Delanef, L., Guénot, F., Rouger, H., Froguel, P., Lesueur-Ginot, L., & Cohen, D. (1994) · Nature Genetics · doi:10.1038/ng0194-29 · Cited by 1,095 · see citing works
The role of mitochondria in aging
Bratic, A., & Larsson, N.-G. (2013) · Journal of Clinical Investigation · doi:10.1172/jci64125 · Cited by 1,087 · see citing works
Mitonuclear protein imbalance as a conserved longevity mechanism
Houtkooper, R. H., Mouchiroud, L., Ryu, D., Moullan, N., Katsyuba, E., Knott, G., Williams, R. W., & Auwerx, J. (2013) · Nature · doi:10.1038/nature12188 · Cited by 1,035 · see citing works
FOXO3A genotype is strongly associated with human longevity
Willcox, B. J., Donlon, T. A., He, Q., Chen, R., Grove, J. S., Yano, K., Masaki, K. H., Willcox, D. C., Rodriguez, B., & Curb, J. D. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801030105 · Cited by 983 · see citing works
Meta-analysis of age-related gene expression profiles identifies common signatures of aging
de Magalhães, J. P., Curado, J., & Church, G. M. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp073 · Cited by 737 · see citing works
Optimal Full Matching and Related Designs via Network Flows
Hansen, B. B., & Klopfer, S. O. (2006) · Journal of Computational and Graphical Statistics · doi:10.1198/106186006x137047 · Cited by 703 · see citing works
The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster
Jin, W., Riley-Berger, R., Wolfinger, R. D., White, K. P., Passador-Gurgel, G., & Gibson, G. C. (2001) · Nature Genetics · doi:10.1038/ng766 · Cited by 644 · see citing works
Taylor, K. R., & Gallo, R. L. (2006) · The FASEB Journal · doi:10.1096/fj.05-4682rev · Cited by 639 · see citing works
Rera, M., Clark, R. I., & Walker, D. W. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1215849110 · Cited by 619 · see citing works
Mitotic Misregulation and Human Aging
Ly, D. H., Lockhart, D. J., Lerner, R. A., & Schultz, P. G. (2000) · Science · doi:10.1126/science.287.5462.2486 · Cited by 599 · see citing works
Genetics and Beyond – The Transcriptome of Human Monocytes and Disease Susceptibility
Zeller, T., Wild, P. S., Szymczak, S., Rotival, M., Schillert, A., Castagné, R., Maouche, S., Germain, M., Lackner, K. J., Rossmann, H., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010693 · Cited by 584 · see citing works
Genome-Wide Transcript Profiles in Aging and Calorically Restricted Drosophila melanogaster
Pletcher, S. D., Macdonald, S. J., Marguerie, R., Certa, U., Stearns, S. C., Goldstein, D. B., & Partridge, L. (2002) · Current Biology · doi:10.1016/s0960-9822(02)00808-4 · Cited by 568 · see citing works
mTOR Inhibition Alleviates Mitochondrial Disease in a Mouse Model of Leigh Syndrome
Johnson, S. C., Yanos, M. E., Kayser, E., Quintana, A., Sangesland, M., Castanza, A. S., Uhde, L., Hui, J., Wall, V., Gagnidze, A., et al. (2013) · Science · doi:10.1126/science.1244360 · Cited by 520 · see citing works
Price, E. M., Cotton, A. M., Lam, L., Farré, P., Emberly, E., Brown, C. J., Robinson, W., & Kobor, M. (2013) · Epigenetics & Chromatin · doi:10.1186/1756-8935-6-4 · Cited by 491 · see citing works
Genetic signatures of exceptional longevity in humans
Sebastiani, P., Solovieff, N., DeWan, A. T., Walsh, K. M., Puca, A., Hartley, S. W., Melista, E., Andersen, S., Dworkis, D. A., Wilk, J. B., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0029848 · Cited by 464 · see citing works
McCarroll, S. A., Murphy, C. T., Zou, S., Pletcher, S. D., Chin, C.-S., Jan, Y. N., Kenyon, C., Bargmann, C. I., & Li, H. (2004) · Nature Genetics · doi:10.1038/ng1291 · Cited by 454 · see citing works
AGEMAP: A Gene Expression Database for Aging in Mice
Zahn, J. M., Poosala, S., Owen, A. B., Ingram, D. K., Lustig, A., Carter, A., Weeraratna, A. T., Taub, D. D., Gorospe, M., Mazan-Mamczarz, K., et al. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030201 · Cited by 431 · see citing works
Self-citationSimilar gene expression patterns characterize aging and oxidative stress in Drosophila melanogaster
Landis, G. N., Abdueva, D. A., Skvortsov, D., Yang, J., Rabin, B. E., Carrick, J., Tavaré, S., & Tower, J. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307605101 · Cited by 384 · see citing works
Self-citationThe first long-lived mutants: discovery of the insulin/IGF-1 pathway for ageing
Kenyon, C. (2011) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2010.0276 · Cited by 376 · see citing works
Liver mitochondrial respiratory functions decline with age
Yen, T., Chen, Y.-S., King, K.-L., Yeh, S.-H., & Wei, Y. (1989) · Biochemical and Biophysical Research Communications · doi:10.1016/0006-291x(89)92701-0 · Cited by 323 · see citing works
Self-citationAssociation of the FOXO3A Locus with Extreme Longevity in a Southern Italian Centenarian Study
Anselmi, C. V., Malovini, A. L., Roncarati, R., Novelli, V., Villa, F., Condorelli, G., Bellazzi, R., & Puca, A. A. (2009) · Rejuvenation Research · doi:10.1089/rej.2008.0827 · Cited by 298 · see citing works
Gene expression changes with age in skin, adipose tissue, blood and brain
Glass, D., Viñuela, A., Davies, M. N., Ramasamy, A., Parts, L., Knowles, D. A., Brown, A. A., Hedman, Å. K., Small, K. S., Buil, A., et al. (2013) · Genome biology · doi:10.1186/gb-2013-14-7-r75 · Cited by 281 · see citing works
Self-citationGWAS of Longevity in CHARGE Consortium Confirms APOE and FOXO3 Candidacy
Broer, L., Buchman, A. S., Deelen, J., Evans, D. S., Faul, J. D., Lunetta, K. L., Paola Sebastiani, B., Smith, J. A., Smith, A. V., Tanaka, T., et al. (2014) · The Journals of Gerontology Series A · doi:10.1093/gerona/glu166 · Cited by 279 · see citing works
Self-citationHarries, L. W., Hernandez, D. G., Henley, W., Wood, A. R., Holly, A. C., Bradley-Smith, R. M., Yaghootkar, H., Dutta, A., Murray, A., Frayling, T. M., et al. (2011) · Aging Cell · doi:10.1111/j.1474-9726.2011.00726.x · Cited by 273 · see citing works
Self-citationMicroarray Profiling of Gene Expression in Aging and Its Alteration by Caloric Restriction in Mice
Weindruch, R. H., Kayo, T., Lee, C., & Prolla, T. A. (2001) · Journal of Nutrition · doi:10.1093/jn/131.3.918s · Cited by 261 · see citing works
Jones, S. J. M., Riddle, D. L., Pouzyrev, A. T., Velculescu, V. E., Hillier, L., Eddy, S. R., Stricklin, S. L., Baillie, D. L., Waterston, R., & Marra, M. A. (2001) · Genome Research · doi:10.1101/gr.184401 · Cited by 227 · see citing works
Lysosomal Function and Dysfunction: Mechanism and Disease
Boya, P. (2011) · Antioxidants and Redox Signaling · doi:10.1089/ars.2011.4405 · Cited by 211 · see citing works
The evidence for functional non-CpG methylation in mammalian cells
Patil, V., Ward, R. L., & Hesson, L. B. (2014) · Epigenetics · doi:10.4161/epi.28741 · Cited by 203 · see citing works
Nebel, A., Kleindorp, R., Caliebe, A., Nothnagel, M., Blanché, H., Junge, O., Wittig, M., Ellinghaus, D., Flachsbart, F., Wichmann, H. ‐., et al. (2011) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2011.06.008 · Cited by 201 · see citing works
Soerensen, M., Dato, S., Christensen, K., McGue, M. K., Stevnsner, T., Bohr, V. A., & Christiansen, L. (2010) · Aging Cell · doi:10.1111/j.1474-9726.2010.00627.x · Cited by 167 · see citing works
Genetic and epigenetic regulation of gene expression in fetal and adult human livers
Bonder, M. J., Kasela, S., Kals, M., Tamm, R., Lokk, K., Barragán, I., Buurman, W. A., Deelen, P., Greve, J.-W. M., Ivanov, M., et al. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-860 · Cited by 164 · see citing works
Self-citationMitochondrial respiratory chain activity in the human brain as a function of age
Ojaimi, J., Masters, C. L., Opeskin, K., McKelvie, P. A., & Byrne, E. (1999) · Mechanisms of Ageing and Development · doi:10.1016/s0047-6374(99)00071-8 · Cited by 157 · see citing works
A genome-wide association study of aging
Walter, S., Atzmon, G., Demerath, E. W., Garcia, M. E., Kaplan, R. C., Meena Kumari, B., Lunetta, K. L., Milaneschi, Y., Tanaka, T., Tranah, G. J., et al. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.05.026 · Cited by 152 · see citing works
Self-citationThe role of DNA damage repair in aging of adult stem cells
Kenyon, J. D., & Gerson, S. L. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm1064 · Cited by 152 · see citing works
GRASP v2.0: an update on the Genome-Wide Repository of Associations between SNPs and phenotypes
Eicher, J. D., Landowski, C., Stackhouse, B., Sloan, A. A., Chen, W., Jensen, N., Lien, J.-P., Leslie, R., & Johnson, A. D. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1202 · Cited by 148 · see citing works
Self-citationLandis, G. N., Shen, J., & Tower, J. (2012) · Aging · doi:10.18632/aging.100499 · Cited by 142 · see citing works
The Epidemiology of Longevity and Exceptional Survival
Newman, A. B., & Murabito, J. M. (2013) · Epidemiologic Reviews · doi:10.1093/epirev/mxs013 · Cited by 128 · see citing works
Self-citationActin Dynamics Affect Mitochondrial Quality Control and Aging in Budding Yeast
Higuchi‐Sanabria, R., Vevea, J., Swayne, T. C., Chojnowski, R., Hill, V. M., Boldogh, I. R., & Pon, L. A. (2013) · Current Biology · doi:10.1016/j.cub.2013.10.022 · Cited by 127 · see citing works
Allum, F., Shao, X., Guénard, F., Simon, M.-M., Busche, S., Caron, M., Lambourne, J. J., Lessard, J., Tandre, K., Hedman, Å. K., et al. (2015) · Nature Communications · doi:10.1038/ncomms8211 · Cited by 114 · see citing works
The signaling hubs at the crossroad of longevity and age-related disease networks
Wolfson, M., Budovsky, A., Tăcutu, R., & Fraifeld, V. E. (2008) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2008.08.026 · Cited by 101 · see citing works
Age-related effects on hippocampal precursor cell subpopulations and neurogenesis
Walter, J., Keiner, S., Witte, O. W., & Redecker, C. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2009.11.011 · Cited by 100 · see citing works
The evolution of the ribosome biogenesis pathway from a yeast perspective
Ebersberger, I., Simm, S., Leisegang, M. S., Schmitzberger, P., Mirus, O., von Haeseler, A., Bohnsack, M. T., & Schleiff, E. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1137 · Cited by 99 · see citing works
Unchecked CD70 Expression on T Cells Lowers Threshold for T Cell Activation in Rheumatoid Arthritis
Lee, W., Yang, Z., Li, G., Weyand, C. M., & Goronzy, J. J. (2007) · The Journal of Immunology · doi:10.4049/jimmunol.179.4.2609 · Cited by 91 · see citing works
A role for actin in aging and apoptosis
Gourlay, C. W., & Ayscough, K. R. (2005) · Biochemical Society Transactions · doi:10.1042/bst0331260 · Cited by 90 · see citing works
Molecular Mechanisms Involved in the Aging of the T-cell Immune Response
Moro‐García, M. A., Alonso‐Arias, R., & López‐Larrea, C. (2012) · Current Genomics · doi:10.2174/138920212803759749 · Cited by 85 · see citing works
Altered rate of DNA replication in ageing human fibroblast cultures
Petes, T. D., Farber, R. A., TARRANT, G. M., & Holliday, R. (1974) · Nature · doi:10.1038/251434a0 · Cited by 80 · see citing works
Accelerated Aging in HIV/AIDS: Novel Biomarkers of Senescent Human CD8+ T Cells
Chou, J. P., Ramirez, C. M., Wu, J. E., & Effros, R. B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064702 · Cited by 78 · see citing works
Landis, G. N., Bhole, D., & Tower, J. (2003) · Genome biology · doi:10.1186/gb-2003-4-2-r8 · Cited by 71 · see citing works
ArhGAP15, a novel human RacGAP protein with GTPase binding property 1
Seoh, M. L., Ng, C. H., Yong, J., Lim, L., & LEUNG, T. K. C. (2003) · FEBS Letters · doi:10.1016/s0014-5793(03)00213-8 · Cited by 67 · see citing works
Genetic Studies Reveal the Role of the Endocrine and Metabolic Systems in Aging
Barzilai, N., & Gabriely, I. (2010) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2010-0859 · Cited by 62 · see citing works
Harries, L. W., Fellows, A. D., Pilling, L. C., Hernandez, D. G., Singleton, A., Bandinelli, S., Guralnik, J. M., Powell, J., Ferrucci, L., & Melzer, D. R. (2012) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2012.07.003 · Cited by 61 · see citing works
Self-citationTranscriptional Profiling of Human Familial Longevity Indicates a Role for ASF1A and IL7R
Passtoors, W. M., Boer, J. M., Goeman, J. J., van den Akker, E. B., Deelen, J., Zwaan, B. J., Scarborough, A., van der Breggen, R., Vossen, R. H. A. M., Houwing‐Duistermaat, J. J., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0027759 · Cited by 47 · see citing works
Self-citationvan den Akker, E. B., Passtoors, W. M., Jansen, R., van Zwet, E. W., Goeman, J. J., Hulsman, M., Emilsson, V., Perola, M., Willemsen, G. A. H. M., Penninx, B. W. J. H., et al. (2013) · Aging Cell · doi:10.1111/acel.12160 · Cited by 44 · see citing works
Self-citationEffect of Aging on Wound Healing
Pittman, J. A. (2007) · Journal of Wound Ostomy and Continence Nursing · doi:10.1097/01.won.0000281658.71072.e6 · Cited by 43 · see citing works
Landis, G. N., Bhole, D., Lu, L., & Tower, J. (2001) · Genetics · doi:10.1093/genetics/158.3.1167 · Cited by 40 · see citing works
Ganna, A., Rivadeneira, F., Albert Hofman, D., Uitterlinden, A. G., Magnusson, P. K. E., Pedersen, N. L., Ingelsson, E., & Tiemeier, H. W. (2013) · Human Genetics · doi:10.1007/s00439-013-1267-6 · Cited by 39 · see citing works
Self-citationGenetic dissection of gene expression observed in whole blood samples of elderly Danish twins
Tan, Q., Christensen, K., Christiansen, L., Frederiksen, H., Bathum, L., Dahlgaard, J., & Kruse, T. A. (2005) · Human Genetics · doi:10.1007/s00439-005-1308-x · Cited by 37 · see citing works
Major aging-associated RNA expressions change at two distinct age-positions
Gheorghe, M., Snoeck, M. M. J., Emmerich, M., Bäck, T., Goeman, J. J., & Raz, V. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-132 · Cited by 31 · see citing works
Liu, Y., Lu, W., Brummel, T. J., Yuh, C., Lin, P., Kao, T., Li, F., Liao, P., Benzer, S., & Wang, H. (2009) · Aging Cell · doi:10.1111/j.1474-9726.2009.00471.x · Cited by 31 · see citing works
Self-citationGenotype×age interaction in human transcriptional ageing
Kent, J. W., Göring, H. H. H., Charlesworth, J., Drigalenko, E. I., Diego, V. P., Curran, J. E., Johnson, M. P., Dyer, T. D., Cole, S. A., Jowett, J. B. M., et al. (2012) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2012.07.005 · Cited by 29 · see citing works
Self-citationDidsbury, A. J., Wang, C., Verdon, D. J., Sewell, M. A., McIntosh, J. D., & Taylor, J. A. (2011) · Virology Journal · doi:10.1186/1743-422x-8-551 · Cited by 28 · see citing works
Loegel, T. N., Trombley, J. D., Taylor, R. T., & Danielson, N. D. (2012) · Analytica Chimica Acta · doi:10.1016/j.aca.2012.09.019 · Cited by 20 · see citing works
Park, J., Jo, Y. H., Cho, C. H., Choe, W., Kang, I., Baik, H. H., & Yoon, K. (2012) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2012.11.040 · Cited by 18 · see citing works
Luo, Y., Mitrpant, C., Johnsen, R. D., Fabian, V. A., Fletcher, S., Mastaglia, F. L., & Wilton, S. D. (2013) · Europe PMC (PubMed Central) · Cited by 14 · see citing works
Nascent-polypeptide-associated Complex: A Bridge between Ribosome and CytosolPreprint
Lauring, B. P., Wang, S., Sakai, H., Davis, T. A., Wiedmann, B., Kreibich, G., & Wiedmann, M. (1995) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.1995.060.01.008 · Cited by 14 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Sobel M. E. Sociological Methodology Vol. 13, 290– 312 (1982).
Cited by
Sorted by citations
Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty
Ferrucci, L., & Fabbri, E. (2018) · Nature Reviews Cardiology · doi:10.1038/s41569-018-0064-2 · Cited by 3,690 · see citing works
Self-citationFacing up to the global challenges of ageing
Partridge, L., Deelen, J., & Slagboom, P. E. (2018) · Nature · doi:10.1038/s41586-018-0457-8 · Cited by 1,475 · see citing works
Self-citationJylhävä, J., Pedersen, N. L., & Hägg, S. (2017) · EBioMedicine · doi:10.1016/j.ebiom.2017.03.046 · Cited by 1,240 · see citing works
DNA methylation-based measures of biological age: meta-analysis predicting time to death
Chen, B. H., Marioni, R. E., Colicino, E., Peters, M. J., Ward-Caviness, C. K., Tsai, P.-C., Roetker, N. S., Just, A. C., Demerath, E. W., Guan, W., et al. (2016) · Aging · doi:10.18632/aging.101020 · Cited by 1,126 · see citing works
Self-citationDNA methylation aging clocks: challenges and recommendations
Bell, C. G., Lowe, R., Adams, P. D., Baccarelli, A. A., Beck, S., Bell, J. T., Christensen, B. C., Gladyshev, V. N., Heijmans, B. T., Horvath, S., et al. (2019) · Genome Biology · doi:10.1186/s13059-019-1824-y · Cited by 1,025 · see citing works
Metabolic Control of Longevity
López-Otín, C., Galluzzi, L., Freije, J. M. P., Madeo, F., & Kroemer, G. (2016) · Cell · doi:10.1016/j.cell.2016.07.031 · Cited by 753 · see citing works
Single-cell transcriptomic profiling of the aging mouse brain
Ximerakis, M., Lipnick, S. L., Innes, B. T., Simmons, S. K., Adiconis, X., Dionne, D., Mayweather, B. A., Nguyen, L., Niziolek, Z., Ozek, C., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0491-3 · Cited by 736 · see citing works
Biomarkers of aging for the identification and evaluation of longevity interventions
Moqri, M., Herzog, C. M. S., Poganik, J. R., Justice, J. N., Belsky, D. W., Higgins‐Chen, A., Moskalev, A., Fuellen, G., Cohen, A. A., Bautmans, I., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.003 · Cited by 697 · see citing works
Self-citationSexual-dimorphism in human immune system aging
Márquez, E. J., Chung, C.-H., Marches, R., Rossi, R. J., Nehar-Belaid, D., Eroglu, A., Mellert, D. J., Kuchel, G. A., Banchereau, J., & Ucar, D. (2020) · Nature Communications · doi:10.1038/s41467-020-14396-9 · Cited by 584 · see citing works
Measuring biological age using omics data
Rutledge, J., Oh, H., & Wyss-Coray, T. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00511-7 · Cited by 570 · see citing works
Radzikowska, U., Ding, M., Tan, G., Zhakparov, D., Peng, Y., Wawrzyniak, P., Wang, M., Li, S., Morita, H., Altunbulakli, C., et al. (2020) · Allergy · doi:10.1111/all.14429 · Cited by 542 · see citing works
Universal DNA methylation age across mammalian tissues
Lu, A. T.-H., Fei, Z., Haghani, A., Robeck, T. R., Zoller, J. A., Li, C. Z., Lowe, R., Yan, Q. J., Zhang, J., Vu, H., et al. (2023) · Nature Aging · doi:10.1038/s43587-023-00462-6 · Cited by 495 · see citing works
Zhang, Q., Vallerga, C. L., Walker, R. M., Lin, T., Henders, A. K., Montgomery, G. W., He, J., Fan, D., Fowdar, J., Kennedy, M., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0667-1 · Cited by 487 · see citing works
Self-citationAging Hallmarks and the Role of Oxidative Stress
Maldonado, E., Morales-Pison, S., Urbina, F., & Solari, A. (2023) · Antioxidants · doi:10.3390/antiox12030651 · Cited by 421 · see citing works
Cai, Y., Song, W., Li, J., Jing, Y., Liang, C., Zhang, L., Zhang, X., Zhang, W., Liu, B., An, Y., et al. (2022) · Science China Life Sciences · doi:10.1007/s11427-022-2161-3 · Cited by 436 · see citing works
Self-citationThe Rotterdam Study: 2018 update on objectives, design and main results
Ikram, M. A., Brusselle, G., Murad, S. D., van Duijn, C. M., Franco, O. H., Goedegebure, A., Klaver, C. C. W., Nijsten, T. E. C., Peeters, R. P., Stricker, B. H. C., et al. (2017) · European Journal of Epidemiology · doi:10.1007/s10654-017-0321-4 · Cited by 431 · see citing works
Self-citationAging, inflammation and the environment
Bektas, A., Schurman, S. H., Sen, R., & Ferrucci, L. (2017) · Experimental Gerontology · doi:10.1016/j.exger.2017.12.015 · Cited by 431 · see citing works
Self-citationthe BIOS Consortium, van Iterson, M., van Zwet, E. W., & Heijmans, B. T. (2017) · Genome biology · doi:10.1186/s13059-016-1131-9 · Cited by 421 · see citing works
Self-citationAge-Related Change in Mobility: Perspectives From Life Course Epidemiology and Geroscience
Ferrucci, L., Cooper, R., Shardell, M. D., Simonsick, E. M., Schrack, J. A., & Kuh, D. J. (2016) · The Journals of Gerontology Series A · doi:10.1093/gerona/glw043 · Cited by 418 · see citing works
Self-citationPersonal aging markers and ageotypes revealed by deep longitudinal profiling
Ahadi, S., Zhou, W., Schüssler-Fiorenza Rose, S. M., Sailani, M. R., Contrepois, K., Avina, M., Ashland, M., Brunet, A., & Snyder, M. (2020) · Nature Medicine · doi:10.1038/s41591-019-0719-5 · Cited by 408 · see citing works
Bao, H., Cao, J., Chen, M., Min, C., Chen, W., Chen, X., Chen, Y., Chen, Y., Chen, Y., Chen, Z., et al. (2023) · Science China Life Sciences · doi:10.1007/s11427-023-2305-0 · Cited by 389 · see citing works
Self-citationDeep biomarkers of human aging: Application of deep neural networks to biomarker development
Putin, E., Mamoshina, P., Aliper, A. M., Korzinkin, M., Moskalev, A., Kolosov, A., Ostrovskiy, A., Cantor, C. R., Vijg, J., & Zhavoronkov, A. A. (2016) · Aging · doi:10.18632/aging.100968 · Cited by 373 · see citing works
Single-cell transcriptomics reveals expansion of cytotoxic CD4 T cells in supercentenarians
Hashimoto, K., Kouno, T., Ikawa, T., Hayatsu, N., Miyajima, Y., Yabukami, H., Terooatea, T., Sasaki, T., Suzuki, T., Valentine, M., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1907883116 · Cited by 343 · see citing works
Lopes, K. D. P., Snijders, G. J. L., Humphrey, J., Allan, A., Sneeboer, M. A. M., Navarro, E., Schilder, B. M., Vialle, R. A., Parks, M., Missall, R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00976-y · Cited by 280 · see citing works
Self-citationTimmers, P. R. H. J., Mounier, N., Läll, K., Fischer, K., Zheng, N., Feng, X., Bretherick, A. D., Clark, D. W., Agbessi, M. D. T., Ahsan, H., et al. (2019) · eLife · doi:10.7554/elife.39856 · Cited by 277 · see citing works
Self-citationHuman T cell immunosenescence and inflammation in aging
Bektas, A., Schurman, S. H., Sen, R., & Ferrucci, L. (2017) · Journal of Leukocyte Biology · doi:10.1189/jlb.3ri0716-335r · Cited by 270 · see citing works
Self-citationHuang, Z., Chen, B., Liu, X., Li, H., Xie, L., Gao, Y., Duan, R., Li, Z., Zhang, J., Zheng, Y., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2023216118 · Cited by 247 · see citing works
Cancer and Aging: Two Tightly Interconnected Biological Processes
Berben, L., Floris, G., Wildiers, H. P. M. W., & Hatse, S. (2021) · Cancers · doi:10.3390/cancers13061400 · Cited by 240 · see citing works
Li, P., Marshall, L., Oh, G., Jakubowski, J. L., Groot, D., He, Y., Wang, T., Petronis, A., & Labrie, V. (2019) · Nature Communications · doi:10.1038/s41467-019-10101-7 · Cited by 234 · see citing works
Predicting age from the transcriptome of human dermal fibroblasts
Fleischer, J. G., Schulte, R., Tsai, H. H., Tyagi, S., Ibarra, A., Shokhirev, M. N., Huang, L., Hetzer, M. W., & Navlakha, S. (2018) · Genome Biology · doi:10.1186/s13059-018-1599-6 · Cited by 232 · see citing works
Mamoshina, P., Volosnikova, M., Ozerov, I. V., Lane, E., Skibina, E., Cortese, F., & Zhavoronkov, A. A. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00242 · Cited by 227 · see citing works
Sebastiani, P., Thyagarajan, B., Sun, F., Schupf, N., Newman, A. B., Montano, M., & Perls, T. T. (2017) · Aging Cell · doi:10.1111/acel.12557 · Cited by 222 · see citing works
Piasecka, B., Duffy, D., Urrutia, A., Quach, H., Patin, É., Posseme, C., Bergstedt, J., Charbit, B., Rouilly, V., MacPherson, C. R., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1714765115 · Cited by 212 · see citing works
Slieker, R. C., Relton, C. L., Gaunt, T. R., Slagboom, P. E., & Heijmans, B. T. (2018) · Epigenetics & Chromatin · doi:10.1186/s13072-018-0191-3 · Cited by 207 · see citing works
Self-citationDeterminants of accelerated metabolomic and epigenetic aging in a UK cohort
Robinson, O., Chadeau Hyam, M., Karaman, I., Climaco Pinto, R., Ala-Korpela, M., Handakas, E., Fiorito, G., Gao, H., Heard, A., Jarvelin, M., et al. (2020) · Aging Cell · doi:10.1111/acel.13149 · Cited by 205 · see citing works
A time-resolved proteomic and prognostic map of COVID-19
Demichev, V., Tober-Lau, P., Lemke, O., Nazarenko, T., Thibeault, C., Whitwell, H., Röhl, A., Freiwald, A., Szyrwiel, L., Ludwig, D., et al. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.005 · Cited by 200 · see citing works
Mamoshina, P., Kochetov, K., Lane, E., Cortese, F., Aliper, A. M., Lee, W., Ahn, S., Lee, U., Skjodt, N. M., Kovalchuk, O., et al. (2018) · The Journals of Gerontology Series A · doi:10.1093/gerona/gly005 · Cited by 198 · see citing works
Retinal age gap as a predictive biomarker for mortality risk
Zhu, Z., Shi, D., Guankai, P., Tan, Z., Shang, X., Hu, W., Liao, H., Zhang, X., Huang, Y., Yu, H., et al. (2022) · British Journal of Ophthalmology · doi:10.1136/bjophthalmol-2021-319807 · Cited by 198 · see citing works
Triana, S., Vonficht, D., Jopp-Saile, L., Raffel, S., Lutz, R., Leonce, D., Antes, M., Hernández-Malmierca, P., Ordoñez-Rueda, D., Ramasz, B., et al. (2021) · Nature Immunology · doi:10.1038/s41590-021-01059-0 · Cited by 195 · see citing works
Genetic contributions to autism spectrum disorder
Havdahl, A., Niarchou, M., Starnawska, A., Uddin, M., van der Merwe, C., & Warrier, V. (2021) · Psychological Medicine · doi:10.1017/s0033291721000192 · Cited by 193 · see citing works
Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities
Galkin, F., Mamoshina, P., Aliper, A., de Magalhães, J. P., Gladyshev, V. N., & Zhavoronkov, A. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101050 · Cited by 189 · see citing works
Change in the Rate of Biological Aging in Response to Caloric Restriction: CALERIE Biobank Analysis
Belsky, D. W., Huffman, K. M., Pieper, C. F., Shalev, I., & Kraus, W. E. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx096 · Cited by 189 · see citing works
Methylation-Based Biological Age and Breast Cancer Risk
Kresovich, J. K., Xu, Z., O’Brien, K. M., Weinberg, C. R., Sandler, D. P., & Taylor, J. A. (2019) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djz020 · Cited by 189 · see citing works
Buckley, M. T., Sun, E., George, B. M., Liu, L. A., Schaum, N., Xu, L., Reyes, J. M., Goodell, M. A., Weissman, I. L., Wyss‐Coray, T., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00335-4 · Cited by 189 · see citing works
Molecular and phenotypic biomarkers of aging
Xia, X., Chen, W., McDermott, J., & Han, J.-D. J. (2017) · F1000Research · doi:10.12688/f1000research.10692.1 · Cited by 187 · see citing works
Multi-omic rejuvenation of human cells by maturation phase transient reprogramming
Gill, D., Parry, A., Santos, F., Okkenhaug, H., Todd, C. D., Hernando-Herraez, I., Stubbs, T. M., Milagre, I., & Reik, W. (2022) · eLife · doi:10.7554/elife.71624 · Cited by 185 · see citing works
DNA methylation dynamics in aging: how far are we from understanding the mechanisms?
Ciccarone, F., Tagliatesta, S., Caiafa, P., & Zampieri, M. (2017) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2017.12.002 · Cited by 184 · see citing works
Simpson, D. J., & Chandra, T. (2021) · Aging Cell · doi:10.1111/acel.13452 · Cited by 182 · see citing works
Gene expression hallmarks of cellular ageing
Frenk, S., & Houseley, J. M. (2018) · Biogerontology · doi:10.1007/s10522-018-9750-z · Cited by 180 · see citing works
Cellular senescence and the tumour microenvironment
Takasugi, M., Yoshida, Y., & Ohtani, N. (2022) · Molecular Oncology · doi:10.1002/1878-0261.13268 · Cited by 178 · see citing works
Age-related accrual of methylomic variability is linked to fundamental ageing mechanisms
Slieker, R. C., van Iterson, M., Luijk, R., Beekman, M., Zhernakova, D. V., Moed, M. H., Mei, H., van Galen, M., Deelen, P., Bonder, M. J., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1053-6 · Cited by 169 · see citing works
Self-citationJohnson, A. A., Shokhirev, M. N., Wyss-Coray, T., & Lehallier, B. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101070 · Cited by 166 · see citing works
Self-citationBiT age: A transcriptome‐based aging clock near the theoretical limit of accuracy
Meyer, D. H., & Schumacher, B. (2021) · Aging Cell · doi:10.1111/acel.13320 · Cited by 165 · see citing works
Antiageing strategy for neurodegenerative diseases: from mechanisms to clinical advances
Jiang, Q., Liu, J., Huang, S., Wang, X.-Y., Chen, X., Liu, G.-H., Ye, K., Song, W., Masters, C. L., Wang, J., et al. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02145-7 · Cited by 165 · see citing works
Huan, T., Chen, G., Liu, C., Bhattacharya, A., Rong, J., Chen, B. H., Seshadri, S. S., Tanrıverdi, K., Freedman, J. E., Larson, M. G., et al. (2017) · Aging Cell · doi:10.1111/acel.12687 · Cited by 165 · see citing works
Self-citationThe Longitudinal Study of Aging in Human Young Adults: Knowledge Gaps and Research Agenda
Moffitt, T. E., Belsky, D. W., Danese, A., Poulton, R., & Caspi, A. (2016) · The Journals of Gerontology Series A · doi:10.1093/gerona/glw191 · Cited by 159 · see citing works
Determination of Biological Age: Geriatric Assessment vs Biological Biomarkers
Diebel, L., & Rockwood, K. J. (2021) · Current Oncology Reports · doi:10.1007/s11912-021-01097-9 · Cited by 155 · see citing works
Potential energy landscapes identify the information-theoretic nature of the epigenome
Jenkinson, G., Pujadas, E., Goutsias, J. I., & Feinberg, A. P. (2017) · Nature Genetics · doi:10.1038/ng.3811 · Cited by 152 · see citing works
Luo, O. J., Lei, W., Zhu, G., Ren, Z., Xu, Y., Xiao, C., Zhang, H., Cai, J., Luo, Z., Gao, L., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00198-9 · Cited by 151 · see citing works
Determining a multimodal aging clock in a cohort of Chinese women
Li, J., Xiong, M., Fu, X.-H., Fan, Y., Dong, C., Sun, X., Zheng, F., Wang, S., Liu, L., Xu, M., et al. (2023) · Med · doi:10.1016/j.medj.2023.06.010 · Cited by 148 · see citing works
Self-citationZhu, H., Chen, J., Liu, K., Gao, L., Wu, H., Ma, L., Zhou, J., Liu, Z., & Han, J. J. (2023) · Science Advances · doi:10.1126/sciadv.abq7599 · Cited by 147 · see citing works
Transcriptional Signatures of Aging
Stegeman, R., & Weake, V. M. (2017) · Journal of Molecular Biology · doi:10.1016/j.jmb.2017.06.019 · Cited by 146 · see citing works
OSCA: a tool for omic-data-based complex trait analysis
Zhang, F., Chen, W., Zhu, Z., Zhang, Q., Nabais, M. F., Qi, T., Deary, I. J., Wray, N. R., Visscher, P. M., McRae, A. F., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1718-z · Cited by 144 · see citing works
Self-citationGoeminne, L. J. E., Vladimirova, A., Eames, A., Tyshkovskiy, A., Argentieri, M. A., Ying, K., Moqri, M., & Gladyshev, V. N. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.10.005 · Cited by 144 · see citing works
Multivariate genomic scan implicates novel loci and haem metabolism in human ageing
Timmers, P. R. H. J., Wilson, J. F., Joshi, P. K., & Deelen, J. (2020) · Nature Communications · doi:10.1038/s41467-020-17312-3 · Cited by 142 · see citing works
Genetic and epigenetic regulation of human aging and longevity
Morris, B. J., Willcox, B. J., & Donlon, T. A. (2019) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2018.08.039 · Cited by 140 · see citing works
Wang, Y., Li, R., Tong, R., Chen, T., Sun, M., Luo, L., Li, Z., Chen, Y., Zhao, Y., Zhang, C., et al. (2025) · Nature Immunology · doi:10.1038/s41590-024-02059-6 · Cited by 139 · see citing works
Self-citationSimplified Assay for Epigenetic Age Estimation in Whole Blood of Adults
Vidal-Bralo, L., Lopez-Golan, Y., & Gonzalez, A. (2016) · Frontiers in Genetics · doi:10.3389/fgene.2016.00126 · Cited by 134 · see citing works
McCartney, D. L., Stevenson, A. J., Walker, R. M., Gibson, J., Morris, S. W., Campbell, A. I., Murray, A. D., Whalley, H. C., Porteous, D. J., McIntosh, A. M., et al. (2018) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2018.05.006 · Cited by 134 · see citing works
Self-citationRibosomal DNA harbors an evolutionarily conserved clock of biological aging
Wang, M., & Lemos, B. (2019) · Genome Research · doi:10.1101/gr.241745.118 · Cited by 131 · see citing works
An integrative study of five biological clocks in somatic and mental health
Jansen, R., Han, L. K., Verhoeven, J. E., Aberg, K. A., van den Oord, E. C., Milaneschi, Y., & Penninx, B. W. (2021) · eLife · doi:10.7554/elife.59479 · Cited by 127 · see citing works
Rhesus macaques as a tractable physiological model of human ageing
Chiou, K. L., Montague, M. J., Goldman, E. A., Watowich, M. M., Sams, S. N., Song, J., Horvath, J. E., Sterner, K. N., Ruiz-Lambides, A. V., Martínez, M. I., et al. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0612 · Cited by 127 · see citing works
Kynurenine emerges from the shadows – Current knowledge on its fate and function
Marszałek‐Grabska, M., Walczak, K., Gaweł, K., Wicha-Komsta, K., Wnorowska, S., Wnorowski, A., & Turski, W. A. (2021) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2021.107845 · Cited by 126 · see citing works
Cellular reprogramming and epigenetic rejuvenation
Simpson, D. J., Olova, N. N., & Chandra, T. (2021) · Clinical Epigenetics · doi:10.1186/s13148-021-01158-7 · Cited by 123 · see citing works
Irizar, P. A., Schäuble, S., Esser, D., Groth, M., Frahm, C., Priebe, S., Baumgart, M., Hartmann, N., Marthandan, S., Menzel, U., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02395-2 · Cited by 122 · see citing works
Revisiting the Hallmarks of Aging to Identify Markers of Biological Age
Guerville, F., Barreto, P. D. S., Ader, I., Andrieu, S., Casteilla, L., Dray, C., Fazilleau, N., Guyonnet, S., Langin, D., Liblau, R., et al. (2020) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2019.50 · Cited by 120 · see citing works
Bongen, E., Lucian, H. J., Khatri, A., Fragiadakis, G. K., Bjornson, Z. B., Nolan, G. P., Utz, P. J., & Khatri, P. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.10.019 · Cited by 115 · see citing works
Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort
Viñuela, A., Brown, A. A., Buil, A., Tsai, P.-C., Davies, M. N., Bell, J. T., Dermitzakis, E. T., Spector, T. D., & Small, K. S. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx424 · Cited by 114 · see citing works
Mouse aging cell atlas analysis reveals global and cell type-specific aging signatures
Zhang, M. J., Pisco, A. O., Darmanis, S., & Zou, J. (2021) · eLife · doi:10.7554/elife.62293 · Cited by 114 · see citing works
Extracting biological age from biomedical data via deep learning: too much of a good thing?
Pyrkov, T. V., Slipensky, K., Barg, M., Kondrashin, A., Zhurov, B., Zenin, A., Pyatnitskiy, M., Menshikov, L., Markov, S., & Fedichev, P. O. (2018) · Scientific Reports · doi:10.1038/s41598-018-23534-9 · Cited by 111 · see citing works
Fries, G. R., Zamzow, M. J., Andrews, T., Pink, O., Scaini, G., & Quevedo, J. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.01.035 · Cited by 110 · see citing works
van den Akker, E. B., Trompet, S., Barkey Wolf, J. J. H., Beekman, M., Suchiman, H. E. D., Deelen, J., Asselbergs, F. W., Boersma, E., Cats, D., Elders, P. M., et al. (2020) · Circulation: Genomic and Precision Medicine · doi:10.1161/circgen.119.002610 · Cited by 109 · see citing works
Self-citationPalmer, D. H., Fabris, F., Doherty, A., Freitas, A. A., & de Magalhães, J. P. (2021) · Aging · doi:10.18632/aging.202648 · Cited by 109 · see citing works
Identification and characterization of two functional variants in the human longevity gene FOXO3
Flachsbart, F., Dose, J., Gentschew, L., Geismann, C., Caliebe, A., Knecht, C., Nygaard, M., Badarinarayan, N., ElSharawy, A., May, S., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-02183-y · Cited by 108 · see citing works
Pignolo, R. J. (2018) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2018.10.005 · Cited by 108 · see citing works
Biological age in healthy elderly predicts aging-related diseases including dementia
Wu, J. W., Yaqub, A., Ma, Y., Koudstaal, W., Albert Hofman, D., Ikram, M. A., Ghanbari, M., & Goudsmit, J. (2021) · Scientific Reports · doi:10.1038/s41598-021-95425-5 · Cited by 108 · see citing works
Lehallier, B., Shokhirev, M. N., Wyss‐Coray, T., & Johnson, A. A. (2020) · Aging Cell · doi:10.1111/acel.13256 · Cited by 106 · see citing works
Self-citationBack to the future: Epigenetic clock plasticity towards healthy aging
Declerck, K., & Berghe, W. V. (2018) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2018.01.002 · Cited by 105 · see citing works
Han, L. K. M., Verhoeven, J. E., Tyrka, A. R., Penninx, B. W. J. H., Wolkowitz, O. M., Månsson, K. N. T., Lindqvist, D., Boks, M. P., Révész, D., Mellon, S. H., et al. (2019) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2019.04.004 · Cited by 104 · see citing works
Xia, X., Chen, X., Wu, G., Li, F., Wang, Y., Chen, Y., Chen, M., Wang, X., Chen, W., Xian, B., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-00270-x · Cited by 102 · see citing works
Self-citationKarakaslar, E. O., Katiyar, N., Hasham, M., Youn, A., Sharma, S., Chung, C., Marches, R., Korstanje, R., Banchereau, J., & Ucar, D. (2023) · Aging Cell · doi:10.1111/acel.13792 · Cited by 98 · see citing works
Self-citationThe effect of early discrimination on accelerated aging among African Americans.
Carter, S. E., Ong, M. L., Simons, R. L., Gibbons, F. X., Lei, M., & Beach, S. R. H. (2019) · Health Psychology · doi:10.1037/hea0000788 · Cited by 98 · see citing works
Spatial transcriptomic clocks reveal cell proximity effects in brain ageing
Sun, E., Zhou, O. Y., Hauptschein, M., Rappoport, N., Xu, L., Negredo, P. N., Liu, L. A., Rando, T. A., Zou, J., & Brunet, A. (2024) · Nature · doi:10.1038/s41586-024-08334-8 · Cited by 98 · see citing works
Huang, Z., Whelan, C., Foley, N. M., Jebb, D., Touzalin, F., PETIT, E. J., Puechmaille, S. J., & Teeling, E. C. (2019) · Nature Ecology & Evolution · doi:10.1038/s41559-019-0913-3 · Cited by 97 · see citing works
Janssens, G. E., Lin, X.-X., Millán-Ariño, L., Kavšek, A., Sen, I., Seinstra, R. I., Stroustrup, N., Nollen, E. A. A., & Riedel, C. G. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.03.044 · Cited by 95 · see citing works
Paola Sebastiani, B., Federico, A. N., Morris, M. K., Gurinovich, A., Tanaka, T., Chandler, K. B., Andersen, S. L., Denis, G. V., Costello, C. E., Ferrucci, L., et al. (2019) · Aging Cell · doi:10.1111/acel.13290 · Cited by 95 · see citing works
Self-citationLe-Niculescu, H., Roseberry, K., Gill, S. S., Levey, D. F., Phalen, P. L., Mullen, J., Williams, A., Bhairo, S., Voegtline, T., Davis, H., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01061-w · Cited by 94 · see citing works
Rivero-Segura, N. A., Bello-Chavolla, O. Y., Barrera-Vázquez, O., Gutiérrez-Robledo, L., & Gómez-Verján, J. C. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101164 · Cited by 76 · see citing works
Retinal age gap as a predictive biomarker of future risk of Parkinson’s disease
Hu, W., Wang, W., Wang, Y., Chen, Y., Shang, X., Liao, H., Huang, Y., Bulloch, G., Zhang, S., Kiburg, K., et al. (2022) · Age and Ageing · doi:10.1093/ageing/afac062 · Cited by 94 · see citing works
Self-citationAir pollution, particulate matter composition and methylation-based biologic age
White, A. J., Kresovich, J. K., Keller, J. P., Xu, Z., Kaufman, J. D., Weinberg, C. R., Taylor, J. A., & Sandler, D. P. (2019) · Environment International · doi:10.1016/j.envint.2019.105071 · Cited by 93 · see citing works
- Authors
- Peters, M. J., Joehanes, R., Pilling, L. C., Schurmann, C., Conneely, K. N., Powell, J., Reinmaa, E., Sutphin, G. L., Zhernakova, A., Schramm, K., Wilson, Y. A., Kobes, S., Tukiainen, T., NABEC/UKBEC Consortium, Nalls, M. A., Hernandez, D. G., Cookson, M. R., Gibbs, R. J., Hardy, J., Ramasamy, A., Zonderman, A. B., Dillman, A., Traynor, B., Smith, C., Longo, D. L., Trabzuni, D., Troncoso, J., van der Brug, M., Weale, M. E., O'Brien, R., Johnson, R., Walker, R., Zielke, R. H., Arepalli, S., Ryten, M., Singleton, A. B., Ramos, Y. F., Göring, H. H. H., Fornage, M., Liu, Y., Gharib, S. A., Stranger, B. E., De Jager, P. L., Aviv, A., Levy, D., Murabito, J. M., Munson, P. J., Huan, T., Hofman, A., Uitterlinden, A. G., Rivadeneira, F., van Rooij, J., Stolk, L., Broer, L., Verbiest, M. M. P. J., Jhamai, M., Arp, P., Metspalu, A., Tserel, L., Milani, L., Samani, N. J., Peterson, P., Kasela, S., Codd, V., Peters, A., Ward-Caviness, C. K., Herder, C., Waldenberger, M., Roden, M., Singmann, P., Zeilinger, S., Illig, T., Homuth, G., Grabe, H.-J., Völzke, H., Steil, L., Kocher, T., Murray, A., Melzer, D., Yaghootkar, H., Bandinelli, S., Moses, E. K., Kent, J. W., Curran, J. E., Johnson, M. P., Williams-Blangero, S., Westra, H.-J., McRae, A. F., Smith, J. A., Kardia, S. L. R., Hovatta, I., Perola, M., Ripatti, S., Salomaa, V., Henders, A. K., Martin, N. G., Smith, A. K., Mehta, D., Binder, E. B., Nylocks, K. M., Kennedy, E. M., Klengel, T., Ding, J., Suchy-Dicey, A. M., Enquobahrie, D. A., Brody, J., Rotter, J. I., Chen, Y.-D. I., Houwing-Duistermaat, J., Kloppenburg, M., Slagboom, P. E., Helmer, Q., den Hollander, W., Bean, S., Raj, T., Bakhshi, N., Wang, Q. P., Oyston, L. J., Psaty, B. M., Tracy, R. P., Montgomery, G. W., Turner, S. T., Blangero, J., Meulenbelt, I., Ressler, K. J., Yang, J., Franke, L., Kettunen, J., Visscher, P. M., Neely, G. G., Korstanje, R., Hanson, R. L., Prokisch, H., Ferrucci, L., Esko, T., Teumer, A., van Meurs, J. B. J., & Johnson, A. D.
- Affiliations
- Erasmus MC (NL)
- Boston University (US)
- University of Exeter (GB)
- Universitätsmedizin Greifswald (DE)
- Emory University (US)
- The University of Queensland (AU)
- University of Tartu (EE)
- Jackson Laboratory (US)
- University Medical Center Groningen (NL)
- Helmholtz Munich (DE)
- The University of Sydney (AU)
- National Institutes of Health (US)
- University of Helsinki (FI)
- National Hospital for Neurology and Neurosurgery (GB)
- Guy's Hospital (GB)
- University of Edinburgh (GB)
- King Faisal Specialist Hospital & Research Centre (SA)
- Johns Hopkins University (US)
- University of Maryland, Baltimore (US)
- Leiden University Medical Center (NL)
- Texas Biomedical Research Institute (US)
- The University of Texas Health Science Center at Houston (US)
- Wake Forest University Health Sciences (US)
- University of Washington (US)
- University of Chicago (US)
- Rutgers New Jersey Medical School (US)
- University of Leicester (GB)
- Deutsches Diabetes-Zentrum e.V. (DE)
- Düsseldorf University Hospital (DE)
- Medizinische Hochschule Hannover (DE)
- Azienda Sanitaria di Firenze (IT)
- The University of Western Australia (AU)
- Broad Institute (US)
- University of Michigan (US)
- Finnish Institute for Health and Welfare (FI)
- QIMR Berghofer Medical Research Institute (AU)
- Max Planck Institute of Psychiatry (DE)
- University of California, Los Angeles (US)
- Harvard University (US)
- Group Health Cooperative (US)
- University of Vermont (US)
- Mayo Clinic (US)
- National Institute on Aging (US)
- Corresponding author
- Johnson, Andrew D.
- ORCID
- Peters, Marjolein J.
- Joehanes, Roby
- Pilling, Luke C.
- Schurmann, Claudia
- Conneely, Karen N.
- Powell, Joseph
- Sutphin, George L.
- Zhernakova, Alexandra
- Schramm, Katharina
- Wilson, Yana A.
- Tukiainen, Taru
- Hernandez, Dena G.
- Cookson, Mark R.
- Hardy, John
- Ramasamy, Adaikalavan
- Zonderman, Alan B.
- Dillman, Allissa
- Traynor, Bryan
- Smith, Colin
- Longo, Dan L.
- Trabzuni, Daniah
- Troncoso, Juan
- Weale, Michael E.
- Johnson, Robert
- Walker, Robert
- Ryten, Mina
- Singleton, Andrew B.
- Ramos, Yolande F.
- Göring, Harald H. H.
- Fornage, Myriam
- Gharib, Sina A.
- Stranger, Barbara E.
- Aviv, Abraham
- Levy, Daniel
- Murabito, Joanne M.
- Munson, Peter J.
- Huan, Tianxiao
- Uitterlinden, André G.
- Rivadeneira, Fernando
- Broer, Linda
- Verbiest, Michael M. P. J.
- Metspalu, Andres
- Tserel, Liina
- Milani, Lili
- Samani, Nilesh J.
- Peterson, Pärt
- Kasela, Silva
- Codd, Veryan
- Peters, Annette
- Ward-Caviness, Cavin K.
- Herder, Christian
- Roden, Michael
- Singmann, Paula
- Homuth, Georg
- Grabe, Hans-Jörgen
- Völzke, Henry
- Steil, Leif
- Kocher, Thomas
- Murray, Anna
- Melzer, David
- Yaghootkar, Hanieh
- Bandinelli, Stefania
- Moses, Eric K.
- Kent, Jack W.
- Curran, Joanne E.
- Johnson, Matthew P.
- Westra, Harm-Jan
- McRae, Allan F.
- Smith, Jennifer A.
- Hovatta, Iiris
- Ripatti, Samuli
- Salomaa, Veikko
- Henders, Anjali K.
- Martin, Nicholas G.
- Smith, Alicia K.
- Mehta, Divya
- Binder, Elisabeth B.
- Nylocks, K Maria
- Kennedy, Elizabeth M.
- Klengel, Torsten
- Ding, Jingzhong
- Enquobahrie, Daniel A.
- Brody, Jennifer
- Rotter, Jerome I.
- Chen, Yii-Der I.
- Kloppenburg, Margreet
- Slagboom, P. Eline
- Raj, Towfique
- Wang, Qiao Ping
- Oyston, Lisa J.
- Psaty, Bruce M.
- Tracy, Russell P.
- Montgomery, Grant W.
- Turner, Stephen T.
- Blangero, John
- Meulenbelt, Ingrid
- Ressler, Kerry J.
- Yang, Jian
- Franke, Lude
- Kettunen, Johannes
- Visscher, Peter M.
- Neely, G. Gregory
- Korstanje, Ron
- Hanson, Robert L.
- Prokisch, Holger
- Ferrucci, Luigi
- Teumer, Alexander
- Johnson, Andrew D.
- Venue
- Nature Communications
- Published
- 2015-10-22
- Volume
- 6
- Issue
- 1
- Pages
- 8570-8570
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC4639797
- OpenAlex
- W2173367702
- Cited by
- 725
- References
- 79
- Citations by year
- 2026: 74 · 2025: 82 · 2024: 83 · 2023: 64 · 2022: 81 · 2021: 74 · 2020: 71 · 2019: 60 · 2018: 47 · 2017: 55 · 2016: 29 · 2015: 4
- FWCI
- 17.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (acceptedVersion, other-oa)
- QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by)
- ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley) (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion, cc-by)
- Rutgers University Community Repository (Rutgers University) (submittedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- UWA Profiles and Research Repository (UWA) (submittedVersion, other-oa)
- UNSWorks (UNSW Sydney) (submittedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eSpace (Curtin University) (submittedVersion)
- Figshare (submittedVersion)
- Työväentutkimus Vuosikirja (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Site cant be reached (submittedVersion, cc-by)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- Funders
- National Institute for Health and Care Research (NF-SI-0611-10170)
- European Commission (HEALTH-F2-2008 35627, 201865)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (050.060.810, 911-03-012, 175.010.2005.011, 917103521)
- National Institutes of Health (UL1TR000124)
- National Institute on Aging (R01AG029451, R01AG031277)
- National Heart, Lung, and Blood Institute (R01HL105756)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK063491)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- aging, chronological age, peripheral blood gene expression, CpG methylation, enhancers, insulators, epigenetic clocks, blood pressure, cholesterol, fasting blood glucose, body mass index, European ancestry
- MeSH terms
- Aging, Humans, Biomarkers, DNA Methylation, Gene Expression Profiling, White People, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
