The transcriptional landscape of age in human peripheral blood
Authors: Peters Marjolein J. , Joehanes Roby , Pilling Luke C. , Schurmann Claudia , Conneely Karen N. , Powell Joseph , Reinmaa Eva , Sutphin George L. , Zhernakova Alexandra , Schramm Katharina , Wilson Yana A. , Kobes Sayuko , Tukiainen Taru ,   NABEC/UKBEC Consortium, Nalls Michael A. , Hernandez Dena G. , Cookson Mark R. , Gibbs Raphael J. , Hardy John , Ramasamy Adaikalavan , Zonderman Alan B. , Dillman Allissa , Traynor Bryan , Smith Colin , Longo Dan L. , Trabzuni Daniah , Troncoso Juan , van der Brug Marcel , Weale Michael E. , O'Brien Richard , Johnson Robert , Walker Robert , Zielke Ronald H. , Arepalli Sampath , Ryten Mina , Singleton Andrew B. , Ramos Yolande F. , Göring Harald H. H. , Fornage Myriam , Liu Yongmei , Gharib Sina A. , Stranger Barbara E. , De Jager Philip L. , Aviv Abraham , Levy Daniel , Murabito Joanne M. , Munson Peter J. , Huan Tianxiao , Hofman Albert , Uitterlinden André G. , Rivadeneira Fernando , van Rooij Jeroen , Stolk Lisette , Broer Linda , Verbiest Michael M. P. J. , Jhamai Mila , Arp Pascal , Metspalu Andres , Tserel Liina , Milani Lili , Samani Nilesh J. , Peterson Pärt , Kasela Silva , Codd Veryan , Peters Annette , Ward-Caviness Cavin K. , Herder Christian , Waldenberger Melanie , Roden Michael , Singmann Paula , Zeilinger Sonja , Illig Thomas , 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. , Williams-Blangero Sarah , Westra Harm-Jan , McRae Allan F. , Smith Jennifer A. , Kardia Sharon L. R. , Hovatta Iiris , Perola Markus , 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 , Suchy-Dicey Astrid M. , Enquobahrie Daniel A. , Brody Jennifer , Rotter Jerome I. , Chen Yii-Der I. , Houwing-Duistermaat Jeanine , Kloppenburg Margreet , Slagboom P. Eline , Helmer Quinta , den Hollander Wouter , Bean Shannon , Raj Towfique , Bakhshi Noman , 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 , Esko Tonu , Teumer Alexander , van Meurs Joyce B. J. , Johnson Andrew D. 
Published: October 2015

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.