Meta-Analysis

. 2015 Oct 22:6:8570.

doi: 10.1038/ncomms9570.

The transcriptional landscape of age in human peripheral blood

Marjolein J Peters¹, Roby Joehanes^{2

3}, Luke C Pilling⁴, Claudia Schurmann^{5

6}, Karen N Conneely⁷, Joseph Powell^{8

9}, Eva Reinmaa¹⁰, George L Sutphin¹¹, Alexandra Zhernakova¹², Katharina Schramm^{13

14}, Yana A Wilson¹⁵, Sayuko Kobes¹⁶, Taru Tukiainen^{17

18}; NABEC/UKBEC Consortium; Yolande F Ramos¹⁹, Harald H H Göring²⁰, Myriam Fornage^{21

22}, Yongmei Liu²³, Sina A Gharib²⁴, Barbara E Stranger²⁵, Philip L De Jager²⁶, Abraham Aviv²⁷, Daniel Levy^{2

3}, Joanne M Murabito^{2

28}, Peter J Munson²⁹, Tianxiao Huan^{2

3}, Albert Hofman³⁰, André G Uitterlinden^{1

30}, Fernando Rivadeneira^{1

30}, Jeroen van Rooij¹, Lisette Stolk¹, Linda Broer¹, Michael M P J Verbiest¹, Mila Jhamai¹, Pascal Arp¹, Andres Metspalu¹⁰, Liina Tserel³¹, Lili Milani¹⁰, Nilesh J Samani^{32

33}, Pärt Peterson³¹, Silva Kasela³⁴, Veryan Codd^{32

33}, Annette Peters^{35

36}, Cavin K Ward-Caviness³⁵, Christian Herder³⁷, Melanie Waldenberger^{35

36}, Michael Roden^{37

38}, Paula Singmann^{35

36}, Sonja Zeilinger^{35

36}, Thomas Illig³⁹, Georg Homuth⁵, Hans-Jörgen Grabe⁴⁰, Henry Völzke⁴¹, Leif Steil⁵, Thomas Kocher⁴², Anna Murray⁴, David Melzer⁴, Hanieh Yaghootkar⁴³, Stefania Bandinelli⁴⁴, Eric K Moses⁴⁵, Jack W Kent²⁰, Joanne E Curran²⁰, Matthew P Johnson²⁰, Sarah Williams-Blangero²⁰, Harm-Jan Westra^{12

46

47

48}, Allan F McRae^{49

50}, Jennifer A Smith⁵¹, Sharon L R Kardia⁵¹, Iiris Hovatta^{52

53}, Markus Perola^{10

17

18}, Samuli Ripatti^{17

18

54

55}, Veikko Salomaa¹⁸, Anjali K Henders⁹, Nicholas G Martin⁵⁶, Alicia K Smith⁵⁷, Divya Mehta⁵⁸, Elisabeth B Binder⁵⁸, K Maria Nylocks⁵⁷, Elizabeth M Kennedy⁷, Torsten Klengel⁵⁸, Jingzhong Ding⁵⁹, Astrid M Suchy-Dicey⁶⁰, Daniel A Enquobahrie⁶⁰, Jennifer Brody⁶¹, Jerome I Rotter⁶², Yii-Der I Chen⁶², Jeanine Houwing-Duistermaat⁶³, Margreet Kloppenburg^{64

65}, P Eline Slagboom¹⁹, Quinta Helmer⁶³, Wouter den Hollander¹⁹, Shannon Bean¹¹, Towfique Raj⁶⁶, Noman Bakhshi¹⁵, Qiao Ping Wang¹⁵, Lisa J Oyston¹⁵, Bruce M Psaty^{67

68

69

70}, Russell P Tracy⁷¹, Grant W Montgomery⁵⁶, Stephen T Turner⁷², John Blangero²⁰, Ingrid Meulenbelt¹⁹, Kerry J Ressler⁵⁷, Jian Yang^{49

50}, Lude Franke¹², Johannes Kettunen^{17

18

73}, Peter M Visscher^{49

50}, G Gregory Neely¹⁵, Ron Korstanje¹¹, Robert L Hanson¹⁶, Holger Prokisch^{13

14}, Luigi Ferrucci⁷⁴, Tonu Esko^{10

46

75

76}, Alexander Teumer⁵, Joyce B J van Meurs¹, Andrew D Johnson^{2

3}

Collaborators, Affiliations

Collaborators

Affiliations

¹ Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands.
² The National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts 01702, USA.
³ Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20817, USA.
⁴ Epidemiology and Public Health, University of Exeter Medical School, Exeter EX4 1DB, UK.
⁵ Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17493, Germany.
⁶ The Charles Bronfman Institute for Personalized Medicine, Genetics of Obesity &Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York 10029, USA.
⁷ Department of Human Genetics, School of Medicine, Emory University, Atlanta, Georgia 30301, USA.
⁸ Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, St Lucia, Brisbane, Queensland 4000, Australia.
⁹ The Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4000, Australia.
¹⁰ Estonian Genome Center, University of Tartu, Tartu 0794, Estonia.
¹¹ Nathan Shock Center of Excellence in the Basic Biology of Aging, The Jackson Laboratory, Bar Harbor, Maine 04609, USA.
¹² Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9700RB, The Netherlands.
¹³ Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany.
¹⁴ Institute of Human Genetics, Technical University Munich, Munich 85540, Germany.
¹⁵ Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, New South Wales 2006, Australia.
¹⁶ Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona 85001, USA.
¹⁷ Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki 00131, Finland.
¹⁸ Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00131, Finland.
¹⁹ Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
²⁰ Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78201, USA.
²¹ Division of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Sciences, Center at Houston, Texas 77001, USA.
²² Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, Texas 77001, USA.
²³ Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina 27101, USA.
²⁴ Computational Medicine Core, Center for Lung Biology, University of Washington, Seattle, Washington 98101, USA.
²⁵ Section of Genetic Medicine, Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois 60290, USA.
²⁶ Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02108, USA.
²⁷ Center of Human Development and Aging, New Jersey Medical School, Newark 07101, USA.
²⁸ General Internal Medicine Section, Boston University, Boston, Massachusetts 02108, USA.
²⁹ The Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20817, USA.
³⁰ Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000CA, The Netherlands.
³¹ Molecular Pathology, Institute of Biomedicine, University of Tartu, Tartu 0794, Estonia.
³² Department of Cardiovascular Sciences, University of Leicester, Leicester LE1, UK.
³³ National Institute for Health Research Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE1, UK.
³⁴ Institute of Molecular and Cell Biology, Estonian Genome Center, University of Tartu, Tartu 0794, Estonia.
³⁵ Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.
³⁶ Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.
³⁷ Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf 40593, Germany.
³⁸ Division of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf 40593, Germany.
³⁹ Hannover Unified Biobank, Hannover Medical School, Hannover 30519, Germany.
⁴⁰ Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, University Medicine Greifswald, Greifswald 17489, Germany.
⁴¹ Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany.
⁴² Unit of Periodontology, Department of Restorative Dentistry, Periodontology and Endodontology, University Medicine Greifswald, Greifswald 17489, Germany.
⁴³ Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK.
⁴⁴ Geriatric Unit, Azienda Sanitaria di Firenze, Florence 50123, Italy.
⁴⁵ Centre for Genetic Origins of Health and Disease, The University of Western Australia, and Faculty of Health Sciences, Curtin University, Perth, Western Australia 9011, Australia.
⁴⁶ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge 02138, USA.
⁴⁷ Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02108, USA.
⁴⁸ Partners Center for Personalized Genetic Medicine, Boston, Massachusetts 02108, USA.
⁴⁹ The Queensland Brain Institute, University of Queensland, Brisbane, Queensland 4000, Australia.
⁵⁰ University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4000, Australia.
⁵¹ Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48103, USA.
⁵² Department of Biosciences, University of Helsinki, Helsinki 00100, Finland.
⁵³ Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki 00100, Finland.
⁵⁴ Wellcome Trust Sanger Institute, Hinxton, Cambridge CB4, UK.
⁵⁵ Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki 00100, Finland.
⁵⁶ QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4000, Australia.
⁵⁷ Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia 30301, USA.
⁵⁸ Max-Planck Institute of Psychiatry, Munich 80331, Germany.
⁵⁹ Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27101, USA.
⁶⁰ Department of Epidemiology, University of Washington, Seattle, Washington 98101, USA.
⁶¹ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington 98101, USA.
⁶² Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90501, USA.
⁶³ Department of Medical Statistics, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
⁶⁴ Department of Rheumatology, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
⁶⁵ Department of Clinical Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
⁶⁶ Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts 02138, USA.
⁶⁷ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington 98195, USA.
⁶⁸ Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA.
⁶⁹ Cardiovascular Health Research Unit, Department of Health Services, University of Washington, Seattle, Washington 98195, USA.
⁷⁰ Group Health Research Institute, Group Health Cooperative, Seattle, Washington 98195, USA.
⁷¹ Department of Pathology, University of Vermont College of Medicine, Colchester, Vermont 98195, USA.
⁷² Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, Minnesota 55901, USA.
⁷³ Computational Medicine, Institute of Health Sciences, Faculty of Medicine, University of Oulu, Oulu 90570, Finland.
⁷⁴ Clinical Research Branch, National Institute on Aging, Baltimore, Maryland 21218, USA.
⁷⁵ Division of Endocrinology, Children's Hospital Boston, Boston, Massachusetts 02108, USA.
⁷⁶ Department of Genetics, Harvard Medical School, Boston, Massachusetts 02108, USA.

PMID: 26490707
PMCID: PMC4639797
DOI: 10.1038/ncomms9570

Meta-Analysis

The transcriptional landscape of age in human peripheral blood

Marjolein J Peters et al. Nat Commun. 2015.

. 2015 Oct 22:6:8570.

doi: 10.1038/ncomms9570.

Authors

Collaborators

Affiliations

¹ Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands.
² The National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts 01702, USA.
³ Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20817, USA.
⁴ Epidemiology and Public Health, University of Exeter Medical School, Exeter EX4 1DB, UK.
⁵ Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17493, Germany.
⁶ The Charles Bronfman Institute for Personalized Medicine, Genetics of Obesity &Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York 10029, USA.
⁷ Department of Human Genetics, School of Medicine, Emory University, Atlanta, Georgia 30301, USA.
⁸ Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, St Lucia, Brisbane, Queensland 4000, Australia.
⁹ The Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4000, Australia.
¹⁰ Estonian Genome Center, University of Tartu, Tartu 0794, Estonia.
¹¹ Nathan Shock Center of Excellence in the Basic Biology of Aging, The Jackson Laboratory, Bar Harbor, Maine 04609, USA.
¹² Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9700RB, The Netherlands.
¹³ Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany.
¹⁴ Institute of Human Genetics, Technical University Munich, Munich 85540, Germany.
¹⁵ Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, New South Wales 2006, Australia.
¹⁶ Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona 85001, USA.
¹⁷ Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki 00131, Finland.
¹⁸ Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00131, Finland.
¹⁹ Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
²⁰ Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78201, USA.
²¹ Division of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Sciences, Center at Houston, Texas 77001, USA.
²² Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, Texas 77001, USA.
²³ Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina 27101, USA.
²⁴ Computational Medicine Core, Center for Lung Biology, University of Washington, Seattle, Washington 98101, USA.
²⁵ Section of Genetic Medicine, Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois 60290, USA.
²⁶ Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02108, USA.
²⁷ Center of Human Development and Aging, New Jersey Medical School, Newark 07101, USA.
²⁸ General Internal Medicine Section, Boston University, Boston, Massachusetts 02108, USA.
²⁹ The Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20817, USA.
³⁰ Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000CA, The Netherlands.
³¹ Molecular Pathology, Institute of Biomedicine, University of Tartu, Tartu 0794, Estonia.
³² Department of Cardiovascular Sciences, University of Leicester, Leicester LE1, UK.
³³ National Institute for Health Research Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE1, UK.
³⁴ Institute of Molecular and Cell Biology, Estonian Genome Center, University of Tartu, Tartu 0794, Estonia.
³⁵ Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.
³⁶ Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.
³⁷ Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf 40593, Germany.
³⁸ Division of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf 40593, Germany.
³⁹ Hannover Unified Biobank, Hannover Medical School, Hannover 30519, Germany.
⁴⁰ Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, University Medicine Greifswald, Greifswald 17489, Germany.
⁴¹ Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany.
⁴² Unit of Periodontology, Department of Restorative Dentistry, Periodontology and Endodontology, University Medicine Greifswald, Greifswald 17489, Germany.
⁴³ Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK.
⁴⁴ Geriatric Unit, Azienda Sanitaria di Firenze, Florence 50123, Italy.
⁴⁵ Centre for Genetic Origins of Health and Disease, The University of Western Australia, and Faculty of Health Sciences, Curtin University, Perth, Western Australia 9011, Australia.
⁴⁶ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge 02138, USA.
⁴⁷ Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02108, USA.
⁴⁸ Partners Center for Personalized Genetic Medicine, Boston, Massachusetts 02108, USA.
⁴⁹ The Queensland Brain Institute, University of Queensland, Brisbane, Queensland 4000, Australia.
⁵⁰ University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4000, Australia.
⁵¹ Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48103, USA.
⁵² Department of Biosciences, University of Helsinki, Helsinki 00100, Finland.
⁵³ Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki 00100, Finland.
⁵⁴ Wellcome Trust Sanger Institute, Hinxton, Cambridge CB4, UK.
⁵⁵ Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki 00100, Finland.
⁵⁶ QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4000, Australia.
⁵⁷ Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia 30301, USA.
⁵⁸ Max-Planck Institute of Psychiatry, Munich 80331, Germany.
⁵⁹ Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27101, USA.
⁶⁰ Department of Epidemiology, University of Washington, Seattle, Washington 98101, USA.
⁶¹ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington 98101, USA.
⁶² Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90501, USA.
⁶³ Department of Medical Statistics, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
⁶⁴ Department of Rheumatology, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
⁶⁵ Department of Clinical Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands.
⁶⁶ Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts 02138, USA.
⁶⁷ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington 98195, USA.
⁶⁸ Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA.
⁶⁹ Cardiovascular Health Research Unit, Department of Health Services, University of Washington, Seattle, Washington 98195, USA.
⁷⁰ Group Health Research Institute, Group Health Cooperative, Seattle, Washington 98195, USA.
⁷¹ Department of Pathology, University of Vermont College of Medicine, Colchester, Vermont 98195, USA.
⁷² Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, Minnesota 55901, USA.
⁷³ Computational Medicine, Institute of Health Sciences, Faculty of Medicine, University of Oulu, Oulu 90570, Finland.
⁷⁴ Clinical Research Branch, National Institute on Aging, Baltimore, Maryland 21218, USA.
⁷⁵ Division of Endocrinology, Children's Hospital Boston, Boston, Massachusetts 02108, USA.
⁷⁶ Department of Genetics, Harvard Medical School, Boston, Massachusetts 02108, USA.

PMID: 26490707
PMCID: PMC4639797
DOI: 10.1038/ncomms9570

Abstract

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.

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Figures

**Figure 1. Pathway analysis on the clusters of co-expressed genes.**
We ran a co-functionality network analysis on 897 downregulated genes with age (negative effect direction) and 600 upregulated genes with age (positive effect direction) using GeneNetwork. With a correlation threshold of 0.7, we selected all clusters bigger than four genes and ran per-cluster pathway analyses using KEGG, Reactome, and GO-terms in WEBGESTALT. Benjamini & Hochberg FDR was used for multiple testing corrections. The significant threshold 0.05 after correction for multiple testing was applied. (a) Three clusters of downregulated genes with age and (b) four clusters of genes upregulated with age were enriched for functional pathways in KEGG, Reactome, and GO terms; the specific pathways are mentioned next to the (sub)cluster names.

**Figure 2. Age-associated genes are enriched for the presence of potentially functional methylation sites.**
(a) Quantile–quantile (QQ) plot of the observed P-values (−log10P) for the methylation–age associations. The plot in black shows pvalues from the 1,497 significant age-associated genes, whereas the plot in red shows pvalues for 1,497 random genes. We do not see enrichment for the 1,497 age-associated genes. (b) QQ plot of the observed P-values (−log10P) for the expression–methylation associations. The plot in black shows P values from the 1,497 significant age-associated genes, whereas the plot in blue shows pvalues for 1,497 random genes. The age-associated genes are enriched for CpG methylation sites that associate with gene expression levels.

**Figure 3. Transcriptomic age versus chronological age.**
This figure represents the correlations between chronological age (x axis) and transcriptomic age (y axis) in eight different cohorts: (a) RS-III, (b) DILGOM, (c) KORA, (d) InCHIANTI, (e) SHIP-TREND, (f) FHS-OFFSPRING, (g) NIDDK/PHOENIX and (h) EGCUT. Transcriptomic age was calculated using a cohort-specific prediction formula and the measured gene expression levels of 11,908 genes. The correlation between chronological age and transcriptomic age was significant in all cohorts (P<2E−29).

**Figure 4. The added value of the transcriptomic predictor.**
To show the added value of the transcriptomic predictor, we choose one biological ageing phenotype systolic blood pressure (SBP), and plotted its correlation with chronological age (a), delta age (b) and the transcriptomic age (c) in the Rotterdam Study (n=597 samples with SBP data available). Delta age represents the difference between chronological age and transcriptomic age. SBP was plotted on the y axis, and the age-related values were plotted on the x axes. SBP was significantly associated with chronological age (P=4.0E−04), but SBP was even stronger associated with transcriptomic age (calculated with a cohort-specific prediction formula based on gene expression levels) (P=8.7E−09), Therefore, the transcriptomic predictor adds value over chronological age alone. Other biological ageing phenotypes showed the same pattern.

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The transcriptional landscape of age in human peripheral blood

Collaborators

Affiliations

The transcriptional landscape of age in human peripheral blood

Authors

Collaborators

Affiliations

Abstract

Figures

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical