Identification of a T cell gene expression clock obtained by exploiting a MZ twin design

Many studies investigated age-related changes in gene expression of different tissues, with scarce agreement due to the high number of affecting factors. Similarly, no consensus has been reached on which genes change expression as a function of age and not because of environment. In this study we analysed gene expression of T lymphocytes from 27 healthy monozygotic twin couples, with ages ranging over whole adult lifespan (22 to 98 years). This unique experimental design allowed us to identify genes involved in normative aging, which expression changes independently from environmental factors. We obtained a transcriptomic signature with 125 genes, from which chronological age can be estimated. This signature has been tested in two datasets of same cell type hybridized over two different platforms, showing a significantly better performance compared to random signatures. Moreover, the same signature was applied on a dataset from a different cell type (human muscle). A lower performance was obtained, indicating the possibility that the signature is T cell-specific. As a whole our results suggest that this approach can be useful to identify age-modulated genes.

[1]  L. Christiansen,et al.  Genetic dissection of gene expression observed in whole blood samples of elderly Danish twins , 2005, Human Genetics.

[2]  Lingli Wang,et al.  A Transcriptional Profile of Aging in the Human Kidney , 2004, PLoS biology.

[3]  James W. Vaupel,et al.  The heritability of human longevity: A population-based study of 2872 Danish twin pairs born 1870–1900 , 1996, Human Genetics.

[4]  T. Ideker,et al.  Genome-wide methylation profiles reveal quantitative views of human aging rates. , 2013, Molecular cell.

[5]  Patrice Godard,et al.  Transcriptomic biomarkers of human ageing in peripheral blood mononuclear cell total RNA , 2010, Experimental Gerontology.

[6]  George C. Williams,et al.  PLEIOTROPY, NATURAL SELECTION, AND THE EVOLUTION OF SENESCENCE , 1957, Science of Aging Knowledge Environment.

[7]  I. Kohane,et al.  Gene regulation and DNA damage in the ageing human brain , 2004, Nature.

[8]  D. Jacobs,et al.  Transcriptomic profiles of aging in purified human immune cells , 2015, BMC Genomics.

[9]  S. Aggarwal,et al.  Increased TNF-alpha-induced apoptosis in lymphocytes from aged humans: changes in TNF-alpha receptor expression and activation of caspases. , 1999, Journal of immunology.

[10]  C. Bouchard,et al.  Molecular Networks of Human Muscle Adaptation to Exercise and Age , 2013, PLoS genetics.

[11]  K. Christensen,et al.  Dissecting complex phenotypes using the genomics of twins , 2010, Functional & Integrative Genomics.

[12]  Kaare Christensen,et al.  Genetic influence on human lifespan and longevity , 2006, Human Genetics.

[13]  S. Horvath DNA methylation age of human tissues and cell types , 2013, Genome Biology.

[14]  Morten Mattingsdal,et al.  DNA Methylation and Gene Expression Changes in Monozygotic Twins Discordant for Psoriasis: Identification of Epigenetically Dysregulated Genes , 2012, PLoS genetics.

[15]  P. Medawar UNSOLVED problem of biology. , 1953, The Medical journal of Australia.

[16]  T. Kirkwood Evolution of ageing , 1977, Nature.

[17]  Leopold Parts,et al.  Gene expression changes with age in skin, adipose tissue, blood and brain , 2013, Genome Biology.

[18]  S. Bandinelli,et al.  Human aging is characterized by focused changes in gene expression and deregulation of alternative splicing , 2011, Aging cell.

[19]  Andres Metspalu,et al.  The transcriptional landscape of age in human peripheral blood , 2015, Nature Communications.

[20]  L. Ferrucci,et al.  Age-associated changes in basal NF-κB function in human CD4+ T lymphocytes via dysregulation of PI3 kinase , 2014, Aging.

[21]  Masao Honda,et al.  Identification of blood biomarkers of aging by transcript profiling of whole blood. , 2012, Biochemical and biophysical research communications.

[22]  Kevin G Becker,et al.  Transcriptional Profiling of Aging in Human Muscle Reveals a Common Aging Signature , 2006, PLoS genetics.

[23]  Cornelia I Bargmann,et al.  Comparing genomic expression patterns across species identifies shared transcriptional profile in aging , 2004, Nature Genetics.

[24]  Ina Hoeschele,et al.  Age-related variations in the methylome associated with gene expression in human monocytes and T cells , 2014, Nature Communications.

[25]  Markus Perola,et al.  Meta-analysis on blood transcriptomic studies identifies consistently coexpressed protein–protein interaction modules as robust markers of human aging , 2013, Aging cell.

[26]  A. Lanzavecchia,et al.  T cells can present antigens such as HIV gp120 targeted to their own surface molecules , 1988, Nature.

[27]  Kyle Duke,et al.  Transcriptional Profile of Aging in C. elegans , 2002, Current Biology.

[28]  R. Beaver,et al.  Temporal linkage between the phenotypic and genomic responses to caloric restriction. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[29]  David B. Goldstein,et al.  Genome-Wide Transcript Profiles in Aging and Calorically Restricted Drosophila melanogaster , 2002, Current Biology.

[30]  M. Blagosklonny,et al.  Growth and aging: a common molecular mechanism , 2009, Aging.

[31]  J. Kaprio,et al.  Global gene expression profiles in skeletal muscle of monozygotic female twins discordant for hormone replacement therapy , 2010, Aging cell.

[32]  Allissa Dillman,et al.  Age-associated changes in gene expression in human brain and isolated neurons , 2013, Neurobiology of Aging.

[33]  Philipp Khaitovich,et al.  Aging and Gene Expression in the Primate Brain , 2005, PLoS biology.

[34]  G. Castellani,et al.  Complex patterns of gene expression in human T cells during in vivo aging. , 2010, Molecular bioSystems.

[35]  L. Christiansen,et al.  Differential and correlation analyses of microarray gene expression data in the CEPH Utah families. , 2008, Genomics.