Horvath's development of the DNA methylation based age estimation method known as epigenetic clock was featured in Nature magazine.[3]
In 2011, Horvath co-authored the first article that described an age estimation method based on DNA methylation levels from saliva.[5] In 2013 Horvath published a single author article on a multi-tissue age estimation method that applies to all nucleated cells, tissues, and organs.[6][3] This discovery, known as the Horvath clock, was unexpected because cell types differ in terms of their DNA methylation patterns and age related DNA methylation changes tend to be tissue specific.[3] In his article, he demonstrated that estimated age, also referred to as DNA methylation age, has the following properties: it is close to zero for embryonic and induced pluripotent stem cells, it correlates with cell passage number; it gives rise to a highly heritable measure of age acceleration; and it is applicable to chimpanzees.[6]
Since the Horvath clock allows one to contrast the ages of different tissues from the same individuals, it can be used to identify tissues that show evidence of increased or decreased age.[7]
Horvath published the first article demonstrating that trisomy 21 (Down syndrome) is associated with strong epigenetic age acceleration effects in both blood and brain tissue.[19]
Using genome-wide association studies, Horvath's team identified the first genetic markers (SNPs) that exhibit genome-wide significant associations with epigenetic aging rates[20][21] – in particular, the first genome-wide significant genetic loci associated with epigenetic aging rates in blood notably the telomerase reverse transcriptase gene (TERT) locus.[22]
As part of this work, his team uncovered a paradoxical relationship: genetic variants associated with longer leukocyte telomere length in the TERT gene paradoxically confer higher epigenetic age acceleration in blood.[22]
Work in biodemographyedit
Horvath proposed that slower epigenetic aging rates could explain the mortality advantage of women and the Hispanic mortality paradox.[23]
Lifestyle factors and nutritionedit
Horvath published the first large scale study of the effect of lifestyle factors on epigenetic aging rates.[24]
These cross sectional of epigenetic aging rates in blood confirm the conventional wisdom regarding the benefits of education, eating a high plant diet with lean meats, moderate alcohol consumption, physical activity and the risks associated with metabolic syndrome.
Epigenetic clock theory of agingedit
Horvath and Raj proposed an epigenetic clock theory of aging[25] which views biological aging as an unintended consequence of both developmental programs and maintenance program, the molecular footprints of which give rise to DNA methylation age estimators. DNAm age is viewed as a proximal readout of a collection of innate ageing processes that conspire with other, independent root causes of aging, to the detriment of tissue function.[25]
^ abHorvath, S (2013). "DNA methylation age of human tissues and cell types". Genome Biology. 14 (10): R115. doi:10.1186/gb-2013-14-10-r115. PMC4015143. PMID 24138928.
^Horvath, S; Mah, V; Lu, AT; Woo, JS; Choi, OW; Jasinska, AJ; Riancho, JA; Tung, S; Coles, NS; Braun, J; Vinters, HV; Coles, LS (2015). "The cerebellum ages slowly according to the epigenetic clock" (PDF). Aging. 7 (5): 294–306. doi:10.18632/aging.100742. PMC4468311. PMID 26000617. Archived from the original (PDF) on 2015-05-25. Retrieved 2017-06-23.
^Horvath, S (2015). "Decreased epigenetic age of PBMCs from Italian semi-supercentenarians and their offspring". Aging. 7 (Dec): 1159–70. doi:10.18632/aging.100861. PMC4712339. PMID 26678252.
^Chen, B; Marioni, ME (2016). "DNA methylation-based measures of biological age: meta-analysis predicting time to death". Aging. 8 (9): 1844–1865. doi:10.18632/aging.101020. PMC5076441. PMID 27690265.
^Horvath, S; Erhart, W; Brosch, M; Ammerpohl, O; von Schoenfels, W; Ahrens, M; Heits, N; Bell, JT; Tsai, PC; Spector, TD; Deloukas, P; Siebert, R; Sipos, B; Becker, T; Roecken, C; Schafmayer, C; Hampe, J (2014). "Obesity accelerates epigenetic aging of human liver". Proc Natl Acad Sci U S A. 111 (43): 15538–43. Bibcode:2014PNAS..11115538H. doi:10.1073/pnas.1412759111. PMC4217403. PMID 25313081.
^Horvath, S; Levine, AJ (2015). "HIV-1 infection accelerates age according to the epigenetic clock". J Infect Dis. 212 (10): 1563–73. doi:10.1093/infdis/jiv277. PMC4621253. PMID 25969563.
^Levine, M (2015). "Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer's disease related cognitive functioning". Aging. 7 (Dec): 1198–211. doi:10.18632/aging.100864. PMC4712342. PMID 26684672.
^Marioni, R; Shah, S; McRae, A; Ritchie, S; Muniz-Terrera, GH; SE; Gibson, J; Redmond, P; SR, C; Pattie, A; Corley, J; Taylor, A; Murphy, L; Starr, J; Horvath, S; Visscher, P; Wray, N; Deary, I (2015). "The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936". International Journal of Epidemiology. 44 (4): 1388–1396. doi:10.1093/ije/dyu277. PMC4588858. PMID 25617346.
^Horvath, S (2015). "Increased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients". Aging. 7 (12): 1130–42. doi:10.18632/aging.100859. PMC4712337. PMID 26655927.
^Horvath, S (2016). "Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels". Aging. 8 (7): 1485–512. doi:10.18632/aging.101005. PMC4993344. PMID 27479945.
^Levine, M (2016). "Menopause accelerates biological aging". Proc Natl Acad Sci USA. 113 (33): 9327–9332. Bibcode:2016PNAS..113.9327L. doi:10.1073/pnas.1604558113. PMC4995944. PMID 27457926.
^Maierhofer, A (2017). "Accelerated epigenetic aging in Werner syndrome". Aging. 9 (4): 1143–1152. doi:10.18632/aging.101217. PMC5425119. PMID 28377537.
^Horvath, S; Garagnani, P; Bacalini, MG; Pirazzini, C; Salvioli, S; Gentilini, D; Di Blasio, AM; Giuliani, C; Tung, S; Vinters, HV; Franceschi, C (Feb 2015). "Accelerated epigenetic aging in Down syndrome". Aging Cell. 14 (3): 491–5. doi:10.1111/acel.12325. PMC4406678. PMID 25678027.
^Lu, A (2016). "Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum". Nature Communications. 7: 10561. Bibcode:2016NatCo...710561L. doi:10.1038/ncomms10561. PMC4740877. PMID 26830004.
^Lu, A (2017). "Genetic architecture of epigenetic and neuronal ageing rates in human brain regions". Nature Communications. 8 (15353): 15353. Bibcode:2017NatCo...815353L. doi:10.1038/ncomms15353. PMC5454371. PMID 28516910.
^ abLu, Ake T.; Xue, Luting; Salfati, Elias L.; Chen, Brian H.; Ferrucci, Luigi; Levy, Daniel; Joehanes, Roby; Murabito, Joanne M.; Kiel, Douglas P.; Tsai, Pei-Chien; Yet, Idil; Bell, Jordana T.; Mangino, Massimo; Tanaka, Toshiko; McRae, Allan F.; Marioni, Riccardo E.; Visscher, Peter M.; Wray, Naomi R.; Deary, Ian J.; Levine, Morgan E.; Quach, Austin; Assimes, Themistocles; Tsao, Philip S.; Absher, Devin; Stewart, James D.; Li, Yun; Reiner, Alex P.; Hou, Lifang; Baccarelli, Andrea A.; Whitsel, Eric A.; Aviv, Abraham; Cardona, Alexia; Day, Felix R.; Wareham, Nicholas J.; Perry, John R. B.; Ong, Ken K.; Raj, Kenneth; Lunetta, Kathryn L.; Horvath, Steve (26 January 2018). "GWAS of epigenetic aging rates in blood reveals a critical role for TERT". Nature Communications. 9 (1): 387. Bibcode:2018NatCo...9..387L. doi:10.1038/s41467-017-02697-5. PMC5786029. PMID 29374233.
^Horvath, Steve; Gurven, Michael; Levine, Morgan E.; Trumble, Benjamin C.; Kaplan, Hillard; Allayee, Hooman; Ritz, Beate R.; Chen, Brian; Lu, Ake T.; Rickabaugh, Tammy M.; Jamieson, Beth D.; Sun, Dianjianyi; Li, Shengxu; Chen, Wei; Quintana-Murci, Lluis; Fagny, Maud; Kobor, Michael S.; Tsao, Philip S.; Reiner, Alexander P.; Edlefsen, Kerstin L.; Absher, Devin; Assimes, Themistocles L. (11 August 2016). "An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease". Genome Biology. 17 (1): 171. doi:10.1186/s13059-016-1030-0. PMC4980791. PMID 27511193.
^Quach, Austin; Levine, Morgan E.; Tanaka, Toshiko; Lu, Ake T.; Chen, Brian H.; Ferrucci, Luigi; Ritz, Beate; Bandinelli, Stefania; Neuhouser, Marian L.; Beasley, Jeannette M.; Snetselaar, Linda; Wallace, Robert B.; Tsao, Philip S.; Absher, Devin; Assimes, Themistocles L.; Stewart, James D.; Li, Yun; Hou, Lifang; Baccarelli, Andrea A.; Whitsel, Eric A.; Horvath, Steve (14 February 2017). "Epigenetic clock analysis of diet, exercise, education, and lifestyle factors". Aging. 9 (2): 419–446. doi:10.18632/aging.101168. PMC5361673. PMID 28198702.
^ abHorvath, Steve; Raj, Kenneth (11 April 2018). "DNA methylation-based biomarkers and the epigenetic clock theory of ageing". Nature Reviews Genetics. 19 (6): 371–384. doi:10.1038/s41576-018-0004-3. PMID 29643443. S2CID 4709691.
^Zhang, B; Horvath, S (2005). "A general framework for weighted gene co-expression network analysis" (PDF). Stat Appl Genet Mol Biol. 4: Article17. doi:10.2202/1544-6115.1128. PMID 16646834. S2CID 7756201. Archived from the original (PDF) on 2020-09-28. Retrieved 2017-06-23.
^Langfelder, P; Horvath, S (2008). "WGCNA: an R package for weighted correlation network analysis". BMC Bioinformatics. 9: 559. doi:10.1186/1471-2105-9-559. PMC2631488. PMID 19114008.
^Horvath S (2011). Weighted Network Analysis: Applications in Genomics and Systems Biology. Springer Book. 1st Edition., 2011, XXII, 414 p Hardcover ISBN 978-1-4419-8818-8 website
^"The Paul G. Allen Frontiers Group Names Five Allen Distinguished Investigators". Cision PR Newswire. June 15, 2017.
^"Open Philanthropy award for epigenetic clock research by Steve Horvath". openphilanthropy.org. April 2019.
^"2019 Schober award for Steve Horvath from UCLA". University of Halle (Saale) Germany. September 13, 2019.