Title |
GWAS of epigenetic aging rates in blood reveals a critical role for TERT
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Published in |
Nature Communications, January 2018
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DOI | 10.1038/s41467-017-02697-5 |
Pubmed ID | |
Authors |
Ake T. Lu, Luting Xue, Elias L. Salfati, Brian H. Chen, Luigi Ferrucci, Daniel Levy, Roby Joehanes, Joanne M. Murabito, Douglas P. Kiel, Pei-Chien Tsai, Idil Yet, Jordana T. Bell, Massimo Mangino, Toshiko Tanaka, Allan F. McRae, Riccardo E. Marioni, Peter M. Visscher, Naomi R. Wray, Ian J. Deary, Morgan E. Levine, Austin Quach, Themistocles Assimes, Philip S. Tsao, Devin Absher, James D. Stewart, Yun Li, Alex P. Reiner, Lifang Hou, Andrea A. Baccarelli, Eric A. Whitsel, Abraham Aviv, Alexia Cardona, Felix R. Day, Nicholas J. Wareham, John R. B. Perry, Ken K. Ong, Kenneth Raj, Kathryn L. Lunetta, Steve Horvath |
Abstract |
DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 individuals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) paradoxically confer higher IEAA (P < 2.7 × 10-11). Causal modeling indicates TERT-specific and independent effects on LTL and IEAA. Experimental hTERT-expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the epigenetic clock, in addition to its established role of compensating for cell replication-dependent telomere shortening. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 10 | 23% |
United Kingdom | 6 | 14% |
Canada | 2 | 5% |
Germany | 2 | 5% |
France | 2 | 5% |
India | 1 | 2% |
Russia | 1 | 2% |
China | 1 | 2% |
Spain | 1 | 2% |
Other | 2 | 5% |
Unknown | 16 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 25 | 57% |
Scientists | 18 | 41% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 303 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 58 | 19% |
Researcher | 58 | 19% |
Student > Master | 26 | 9% |
Student > Bachelor | 24 | 8% |
Other | 18 | 6% |
Other | 48 | 16% |
Unknown | 71 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 87 | 29% |
Agricultural and Biological Sciences | 38 | 13% |
Medicine and Dentistry | 32 | 11% |
Neuroscience | 13 | 4% |
Psychology | 6 | 2% |
Other | 38 | 13% |
Unknown | 89 | 29% |