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词条 Steve Horvath
释义

  1. Background

  2. Work on the epigenetic clock

     Age related conditions and phenotypes  Genetics of aging  Work in biodemography  Lifestyle factors and nutrition  Epigenetic clock theory of aging 

  3. Weighted correlation network analysis

  4. References

  5. External links

{{Autobiography|date=December 2018}}{{Infobox person
| name = Steve Horvath
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| known_for = developing the epigenetic clock (Horvath clock) and weighted correlation network analysis.
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Steve Horvath is a UCLA professor known for developing the Horvath aging clock, which is a highly accurate molecular biomarker of aging, and for developing weighted correlation network analysis.

The recipient of several research awards, including an Allen Distinguished Investigator award,[1] he has studied genomic biomarkers of aging, the aging process, and many age related diseases/conditions.

Background

{{BLP sources section|date=January 2018}}

Horvath was born in Frankfurt, Germany. He received his Ph.D. in mathematics at the University of North Carolina in 1995 and his Sc.D. in biostatistics at Harvard in 2000. In 2000 Horvath joined the faculty of the University of California, Los Angeles, where he is a Professor of human genetics at the David Geffen School of Medicine at UCLA and of biostatistics at the UCLA Fielding School of Public Health.

Work on the epigenetic clock

Horvath's development of the DNA methylation based age estimation method known as epigenetic clock was featured in Nature magazine.[2]

In 2011 Horvath co-authored the first article that described an age estimation method based on DNA methylation levels from saliva. In 2013 Horvath published a single author article on a multi-tissue age estimation method that applies to all nucleated cells, tissues, and organs.[4] This discovery, known as the Horvath clock, was unexpected because cell types differ in terms of the their DNA methylation patterns and age related DNA methylation changes tend to be tissue specific. 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.[4]

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.[6]

Age related conditions and phenotypes

Horvath co-authored the first articles demonstrating that DNA methylation age predicts life-expectancy [7][8][9] and is positively associated with obesity,[10] HIV infection,[11] Alzheimer's disease,[12] cognitive decline,[13] Parkinson's disease,[1] Huntington's disease,[15] early menopause,[16] Werner syndrome.[17]

Genetics of aging

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.[18]

Using genome-wide association studies, Horvath's team identified the first genetic markers (SNPs) that exhibit genome-wide significant associations with epigenetic aging rates.[19][20]

In particular, the first genome-wide significant genetic loci associated with epigenetic aging rates in blood notably the telomerase reverse transcriptase gene (TERT) locus

.[2]

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.[2]

Work in biodemography

Horvath proposed that slower epigenetic aging rates could explain the mortality advantage of women and the Hispanic mortality paradox.[3]

Lifestyle factors and nutrition

Horvath published the first large scale study of the effect of lifestyle factors on epigenetic aging rates.[4]

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 aging

Horvath and his collaborator Kenneth Raj [5]

proposed an epigenetic clock theory of aging 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.

Weighted correlation network analysis

Horvath and members of his lab developed a widely used systems biological data mining technique known as weighted correlation network analysis.[26][27][28] He published a book on weighted network analysis and genomic applications.[29]

References

1. ^{{cite journal | last1 = Horvath | first1 = S | year = 2015 | title = Increased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients.| url = http://www.impactaging.com/papers/v7/n12/full/100859.html| journal = Aging | volume=7| issue =| pages = 1130–42| doi = 10.18632/aging.100859| pmid= 26655927 | pmc=4712337}}
2. ^1 Lu AT., & Xue L., & Chen BH., et al., Horvath S. (2018). [https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/29374233/GWAS of epigenetic aging rates in blood reveals a critical role for TERT]. Nat Comm{{ doi|10.1038/s41467-017-02697-5}}
3. ^{{Cite journal| title = An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease.| journal = Genome Biol| volume =17 | issue = 1| year = 2016| pmid = 27511193 |pmc= 4980791|vauthors= Horvath S, Gurven M, Levine ME, Trumble BC, Kaplan H, Allayee H, Ritz BR, Chen B, Lu AT, Rickabaugh TM, Jamieson BD, Sun D, Li S, Chen W, Quintana-Murci L, Fagny M, Kobor MS, Tsao PS, Reiner AP, Edlefsen KL, Absher D, Assimes TL | doi=10.1186/s13059-016-1030-0| pages=171}}
4. ^Quach A., & Levine ME., & Tanaka T.,…., & Horvath S. (2018). [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5361673/Epigenetic clock analysis of diet, exercise, education, and lifestyle factors.]. Aging (Albany NY){{ doi|10.18632/aging.101168}}
5. ^Horvath, S., & Raj, K. (2018). [https://www.nature.com/articles/s41576-018-0004-3 DNA methylation-based biomarkers and the epigenetic clock theory of ageing]. Nature Reviews Genetics, {{doi|10.1038/s41576-018-0004-3}}
6. ^1 2 {{cite journal | last1 = Horvath | first1 = S | year = 2013 | title = DNA methylation age of human tissues and cell types | url = | journal = Genome Biology | volume = 14| page = R115 | doi = 10.1186/gb-2013-14-10-r115 | pmid=24138928 | pmc=4015143}}
7. ^1 {{cite journal | last1 = Horvath | first1 = S | date = 2015 | title = Decreased epigenetic age of PBMCs from Italian semi-supercentenarians and their offspring.| url =http://www.impactaging.com/papers/v7/n12/full/100861.html| journal = Aging | volume = | issue = Dec| pages =| }}
8. ^1 {{cite journal | last1 = Horvath | first1 = S | last2 = Mah | first2 = V | last3 = Lu | first3 = AT | last4 = Woo | first4 = JS | last5 = Choi | first5 = OW | last6 = Jasinska | first6 = AJ | last7 = Riancho | first7 = JA | last8 = Tung | first8 = S | last9 = Coles | first9 = NS | last10 = Braun | first10 = J | last11 = Vinters | first11 = HV | last12 = Coles | first12 = LS | year = 2015 | title = The cerebellum ages slowly according to the epigenetic clock | url = http://www.impactaging.com/papers/v7/n5/pdf/100742.pdf | journal = Aging | volume = 7 | issue = 5| pages = 294–306| pmid = 26000617 | doi=10.18632/aging.100742 | pmc=4468311}}
9. ^1 {{cite journal | last1 = Horvath | first1 = S | last2 = Erhart | first2 = W | last3 = Brosch | first3 = M | last4 = Ammerpohl | first4 = O | last5 = von Schoenfels | first5 = W | last6 = Ahrens | first6 = M | last7 = Heits | first7 = N | last8 = Bell | first8 = JT | last9 = Tsai | first9 = PC | last10 = Spector | first10 = TD | last11 = Deloukas | first11 = P | last12 = Siebert | first12 = R | last13 = Sipos | first13 = B | last14 = Becker | first14 = T | last15 = Roecken | first15 = C | last16 = Schafmayer | first16 = C | last17 = Hampe | first17 = J | year = 2014 | title = Obesity accelerates epigenetic aging of human liver | journal = Proc Natl Acad Sci U S A | volume = 111| issue = | pages = 15538–43| doi = 10.1073/pnas.1412759111 | pmid = 25313081 | pmc=4217403}}
10. ^1 {{cite journal | last1 = Gibbs | first1 = WT | year = 2014 | title = Biomarkers and ageing: The clock-watcher | url = | journal = Nature | volume = 508 | issue = | pages = 168–170 | doi = 10.1038/508168a | pmid=24717494}}
11. ^1 {{cite news |author= |title= The Paul G. Allen Frontiers Group Names Five Allen Distinguished Investigators |url= http://www.prnewswire.com/news-releases/the-paul-g-allen-frontiers-group-names-five-allen-distinguished-investigators-300474517.html|work= |location=Cision PR Newswire |date=June 15, 2017 |access-date= }}
12. ^1 {{cite journal | last1 = Horvath | first1 = S | last2 = Garagnani | first2 = P | last3 = Bacalini | first3 = MG | last4 = Pirazzini | first4 = C | last5 = Salvioli | first5 = S | last6 = Gentilini | first6 = D | last7 = Di Blasio | first7 = AM | last8 = Giuliani | first8 = C | last9 = Tung | first9 = S | last10 = Vinters | first10 = HV | last11 = Franceschi | first11 = C | date = Feb 2015 | title = Accelerated epigenetic aging in Down syndrome | journal = Aging Cell | volume = 14| issue = | pages = 491–5| doi = 10.1111/acel.12325 | pmid = 25678027 | pmc=4406678}}
13. ^1 {{cite journal | last1 = Horvath | first1 = S | last2 = Levine | first2 = AJ | year = 2015 | title = HIV-1 infection accelerates age according to the epigenetic clock | journal = J Infect Dis | volume = 212| issue = | pages = 1563–73| doi = 10.1093/infdis/jiv277 | pmid=25969563 | pmc=4621253}}
14. ^1 {{cite journal | last1 = Levine | first1 = M | date = 2016 | title = Menopause accelerates biological aging| url =http://www.pnas.org/content/early/2016/07/20/1604558113.short | journal = Proc Natl Acad Sci USA | volume = 113| issue = | pages =201604558| pmid= 27457926 | pmc= 4995944| doi=10.1073/pnas.1604558113}}
15. ^1 {{cite journal | last1 = Levine | first1 = M | date = 2015 | title = Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer's disease related cognitive functioning| url = http://www.impactaging.com/papers/v7/n12/full/100864.html | journal = Aging | volume = 7| issue = Dec| pages =1198–211| pmid= 26684672 | pmc=4712342}}
16. ^1 {{cite journal | last1 = Lu | first1 =A | date = 2016 | title = Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum.| url = http://www.nature.com/ncomms/2016/160202/ncomms10561/full/ncomms10561.html| journal = Nature Communications | volume =7 | issue = | pages =10561| doi=10.1038/ncomms10561 | pmid=26830004 | pmc=4740877}}
17. ^1 {{cite journal | last1 = Lu | first1 =A | date = 2017 | title =Genetic architecture of epigenetic and neuronal ageing rates in human brain regions.| url = https://www.nature.com/articles/ncomms15353| journal = Nature Communications | volume =8 | issue =15353 | pages =| doi=10.1038/ncomms15353 | pmid=28516910 | pmc=5454371 }}
18. ^1 {{cite journal | last1 = Marioni | first1 = R | last2 = Shah | first2 = S | last3 = McRae | first3 = A | last4 = Chen | first4 = B | last5 = Colicino | first5 = E | last6 = Harris | first6 = S | last7 = Gibson | first7 = J | last8 = Henders | first8 = A | last9 = Redmond | first9 = P | last10 = Cox | first10 = S | last11 = Pattie | first11 = A | last12 = Corley | first12 = J | last13 = Murphy | first13 = L | last14 = Martin | first14 = N | last15 = Montgomery | first15 = G | last16 = Feinberg | first16 = A | last17 = Fallin | first17 = M | last18 = Multhaup | first18 = M | last19 = Jaffe | first19 = A | last20 = Joehanes | first20 = R | last21 = Schwartz | first21 = J | last22 = Just | first22 = A | last23 = Lunetta | first23 = K | last24 = Murabito | first24 = JM | last25 = Starr | first25 = J | last26 = Horvath | first26 = S | last27 = Baccarelli | first27 = A | last28 = Levy | first28 = D | last29 = Visscher | first29 = P | last30 = Wray | first30 = N | last31 = Deary | first31 = I | year = 2015 | title = DNA methylation age of blood predicts all-cause mortality in later life | journal = Genome Biology | volume = 16 | issue = 1| page = 25 | doi = 10.1186/s13059-015-0584-6 | pmid=25633388 | pmc=4350614}}
19. ^1 {{cite journal | last1 = Marioni | first1 = R | last2 = Shah | first2 = S | last3 = McRae | first3 = A | last4 = Ritchie | first4 = S | last5 = Muniz-Terrera | first5 = GH | last6 = SE | first6 = | last7 = Gibson | first7 = J | last8 = Redmond | first8 = P | last9 = SR | first9 = C | last10 = Pattie | first10 = A | last11 = Corley | first11 = J | last12 = Taylor | first12 = A | last13 = Murphy | first13 = L | last14 = Starr | first14 = J | last15 = Horvath | first15 = S | last16 = Visscher | first16 = P | last17 = Wray | first17 = N | last18 = Deary | first18 = I | year = 2015 | title = The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936 | journal = International Journal of Epidemiology | volume = 44| issue = | pages = 1388–1396| doi = 10.1093/ije/dyu277 | pmid = 25617346 | pmc=4588858}}
20. ^1 {{cite journal | last1 = Chen | first1 = B | last2 = Marioni | first2 = ME| year = 2016 | title = DNA methylation-based measures of biological age: meta-analysis predicting time to death. | journal = Aging | volume = 8 | issue =9 | pages = 1844–1865 | doi= 10.18632/aging.101020 | pmid = 27690265 | pmc=5076441}}
21. ^1 {{cite journal | last1 =Horvath | first1 = S | date = 2016 | title = Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels| url =http://www.aging-us.com/article/no9ssRw2iNbWETXwP/text | journal = Aging| volume =8 | issue = 7| pages =1485–512 | pmid= 27479945 | pmc= 4993344| doi=10.18632/aging.101005}}
22. ^1 {{cite journal | last1 =Maierhofer | first1 = A | date = 2017 | title = Accelerated epigenetic aging in Werner syndrome.| journal = Aging| volume =9 | issue = 4| pages =1143–1152| pmid=28377537| pmc= 5425119 | doi=10.18632/aging.101217}}
23. ^1 Zhang B, Horvath S (2005) A General Framework for Weighted Gene Co-Expression Network Analysis", Statistical Applications in Genetics and Molecular Biology: Vol. 4: No. 1, Article 17 {{PMID|16646834}}  
24. ^1 {{cite journal | last1 = Horvath | first1 = S | last2 = Zhang | first2 = B | last3 = Carlson | first3 = M | last4 = Lu | first4 = KV | last5 = Zhu | first5 = S | last6 = Felciano | first6 = RM | last7 = Laurance | first7 = MF | last8 = Zhao | first8 = W | last9 = Shu | first9 = Q | last10 = Lee | first10 = Y | last11 = Scheck | first11 = AC | last12 = Liau | first12 = LM | last13 = Wu | first13 = H | last14 = Geschwind | first14 = DH | last15 = Febbo | first15 = PG | last16 = Kornblum | first16 = HI | last17 = Cloughesy | first17 = TF | last18 = Nelson | first18 = SF | last19 = Mischel | first19 = PS |authorlink17=Timothy Cloughesy|authorlink19=Paul S. Mischel | year = 2006 | title = Analysis of Oncogenic Signaling Networks in Glioblastoma Identifies ASPM as a Novel Molecular Target | url = | journal = PNAS | volume = 103 | issue = 46| pages = 17402–17407 | doi=10.1073/pnas.0608396103| pmc = 1635024 }}
25. ^1 Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008, 9:559 {{PMID|19114008}} {{PMC|2631488}} BMC Bioinformatics {{open access}}
26. ^1 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}} [https://www.springer.com/new+&+forthcoming+titles+(default)/book/978-1-4419-8818-8?changeHeader|Springer website]
[6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]
}}

External links

{{Authority control}}{{DEFAULTSORT:Horvath, Steve}}

7 : 1967 births|Educators from California|University of California, Los Angeles faculty|Biogerontologists|Harvard School of Public Health alumni|Living people|University of North Carolina alumni
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