A meta-analysis of genome-wide association studies of epigenetic age acceleration

Autoři: Jude Gibson aff001;  Tom C. Russ aff001;  Toni-Kim Clarke aff001;  David M. Howard aff001;  Robert F. Hillary aff005;  Kathryn L. Evans aff004;  Rosie M. Walker aff004;  Mairead L. Bermingham aff005;  Stewart W. Morris aff005;  Archie Campbell aff005;  Caroline Hayward aff007;  Alison D. Murray aff008;  David J. Porteous aff004;  Steve Horvath aff009;  Ake T. Lu aff009;  Andrew M. McIntosh aff001;  Heather C. Whalley aff001;  Riccardo E. Marioni aff004
Působiště autorů: Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom aff001;  Centre for Dementia Prevention, University of Edinburgh, Edinburgh, United Kingdom aff002;  Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom aff003;  Centre for Cognitive Ageing & Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom aff004;  Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom aff005;  Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom aff006;  MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom aff007;  Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, United Kingdom aff008;  Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, United States of America aff009;  Department of Biostatistics, School of Public Health, University of California-Los Angeles, Los Angeles, CA, United States of America aff010
Vyšlo v časopise: A meta-analysis of genome-wide association studies of epigenetic age acceleration. PLoS Genet 15(11): e32767. doi:10.1371/journal.pgen.1008104
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008104


'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father’s age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.

Klíčová slova:

DNA methylation – Epigenetics – Gene expression – Gene regulation – Genetic loci – Genome-wide association studies – Molecular genetics


1. Niccoli T, Partridge L. Ageing as a Risk Factor for Disease. Curr Biol [Internet]. 2012 Sep 11 [cited 2018 Jun 4];22(17):R741–52. Available from: https://www.sciencedirect.com/science/article/pii/S0960982212008159?via%3Dihub doi: 10.1016/j.cub.2012.07.024 22975005

2. Rode L, Nordestgaard BG, Bojesen SE. Peripheral Blood Leukocyte Telomere Length and Mortality Among 64 637 Individuals From the General Population. JNCI J Natl Cancer Inst [Internet]. 2015 Jun 1 [cited 2018 Sep 25];107(6). Available from: https://academic.oup.com/jnci/article-lookup/doi/10.1093/jnci/djv074

3. Beck S, Rakyan VK. The methylome: approaches for global DNA methylation profiling. Trends Genet [Internet]. 2008 May 1 [cited 2018 May 14];24(5):231–7. Available from: https://www.sciencedirect.com/science/article/pii/S0168952508000577?via%3Dihub doi: 10.1016/j.tig.2008.01.006 18325624

4. Bollati V, Schwartz J, Wright R, Litonjua A, Tarantini L, Suh H, et al. Decline in genomic DNA methylation through aging in a cohort of elderly subjects. Mech Ageing Dev [Internet]. 2009 Apr [cited 2018 May 14];130(4):234–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19150625 doi: 10.1016/j.mad.2008.12.003 19150625

5. Christensen BC, Houseman EA, Marsit CJ, Zheng S, Wrensch MR, Wiemels JL, et al. Aging and Environmental Exposures Alter Tissue-Specific DNA Methylation Dependent upon CpG Island Context. Schübeler D, editor. PLoS Genet [Internet]. 2009 Aug 14 [cited 2018 May 14];5(8):e1000602. Available from: doi: 10.1371/journal.pgen.1000602 19680444

6. Shah S, McRae AF, Marioni RE, Harris SE, Gibson J, Henders AK, et al. Genetic and environmental exposures constrain epigenetic drift over the human life course. Genome Res [Internet]. 2014 Nov 1 [cited 2018 May 14];24(11):1725–33. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25249537 doi: 10.1101/gr.176933.114 25249537

7. Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell [Internet]. 2013 Jan 24 [cited 2018 May 14];49(2):359–67. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23177740 doi: 10.1016/j.molcel.2012.10.016 23177740

8. Horvath S. DNA methylation age of human tissues and cell types. Genome Biol [Internet]. 2013 Dec 10 [cited 2018 May 14];14(10):R115. Available from: http://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-10-r115 doi: 10.1186/gb-2013-14-10-r115 24138928

9. Marioni RE, Shah S, McRae AF, Ritchie SJ, Muniz-Terrera G, Harris SE, et al. The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936. Int J Epidemiol [Internet]. 2015 Aug 1 [cited 2018 May 14];44(4):1388–96. Available from: https://academic.oup.com/ije/article-lookup/doi/10.1093/ije/dyu277 25617346

10. Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai P-C, et al. DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging (Albany NY) [Internet]. 2016 Sep 28 [cited 2018 May 14];8(9):1844–65. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27690265

11. Marioni RE, Suderman M, Chen BH, Horvath S, Bandinelli S, Morris T, et al. Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data. J Gerontol A Biol Sci Med Sci [Internet]. 2019 Jan 1 [cited 2019 Jan 21];74(1):57–61. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29718110 doi: 10.1093/gerona/gly060 29718110

12. Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE, et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol [Internet]. 2015 Jan 30 [cited 2018 May 14];16(1):25. Available from: http://genomebiology.com/2015/16/1/25

13. Fagnoni FF, Vescovini R, Passeri G, Bologna G, Pedrazzoni M, Lavagetto G, et al. Shortage of circulating naive CD8(+) T cells provides new insights on immunodeficiency in aging. Blood [Internet]. 2000 May 1 [cited 2019 Jan 21];95(9):2860–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/10779432 10779432

14. Miller RA. The aging immune system: primer and prospectus. Science [Internet]. 1996 Jul 5 [cited 2019 Jan 21];273(5271):70–4. Available from: http://www.ncbi.nlm.nih.gov/pubmed/8658199 doi: 10.1126/science.273.5271.70 8658199

15. Quach A, Levine ME, Tanaka T, Lu AT, Chen BH, Ferrucci L, et al. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging (Albany NY) [Internet]. 2017 Feb 14 [cited 2018 May 14];9(2):419–46. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28198702

16. Levine ME, Lu AT, Bennett DA, Horvath S. Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer’s disease related cognitive functioning. Aging (Albany NY) [Internet]. 2015 Dec [cited 2018 May 14];7(12):1198–211. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26684672

17. Levine ME, Lu AT, Chen BH, Hernandez DG, Singleton AB, Ferrucci L, et al. Menopause accelerates biological aging. Proc Natl Acad Sci U S A [Internet]. 2016 Aug 16 [cited 2018 May 14];113(33):9327–32. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27457926 doi: 10.1073/pnas.1604558113 27457926

18. Horvath S, Ritz BR. Increased epigenetic age and granulocyte counts in the blood of Parkinson’s disease patients. Aging (Albany NY) [Internet]. 2015 Dec [cited 2018 May 14];7(12):1130–42. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26655927

19. McCartney DL, Stevenson AJ, Walker RM, Gibson J, Morris SW, Campbell A, et al. DNA methylation age acceleration and risk factors for Alzheimer’s disease. bioRxiv [Internet]. 2018 Mar 8 [cited 2018 Jun 12];278945. Available from: https://www.biorxiv.org/content/early/2018/03/08/278945

20. Lu AT, Xue L, Salfati EL, Chen BH, Ferrucci L, Levy D, et al. GWAS of epigenetic aging rates in blood reveals a critical role for TERT. Nat Commun [Internet]. 2018 Dec 26 [cited 2018 May 14];9(1):387. Available from: http://www.nature.com/articles/s41467-017-02697-5 doi: 10.1038/s41467-017-02697-5 29374233

21. Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics [Internet]. 2010 Sep 15 [cited 2018 May 15];26(18):2336–7. Available from: https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btq419 20634204

22. Twine NA, Harkness L, Kassem M, Wilkins MR. Transcription factor ZNF25 is associated with osteoblast differentiation of human skeletal stem cells. BMC Genomics [Internet]. 2016 [cited 2018 Nov 5];17(1):872. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27814695 doi: 10.1186/s12864-016-3214-0 27814695

23. Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol [Internet]. 2011 Jan 20 [cited 2019 Jun 15];12(1):R10. Available from: http://genomebiology.biomedcentral.com/articles/10.1186/gb-2011-12-1-r10 21251332

24. Gibbs JR, van der Brug MP, Hernandez DG, Traynor BJ, Nalls MA, Lai S-L, et al. Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain. Flint J, editor. PLoS Genet [Internet]. 2010 May 13 [cited 2019 Jun 15];6(5):e1000952. Available from: https://dx.plos.org/10.1371/journal.pgen.1000952 20485568

25. Gaunt TR, Shihab HA, Hemani G, Min JL, Woodward G, Lyttleton O, et al. Systematic identification of genetic influences on methylation across the human life course. Genome Biol [Internet]. 2016 Dec 31 [cited 2019 Jun 15];17(1):61. Available from: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0926-z

26. Bulik-Sullivan BK, Loh P-R, Finucane HK, Ripke S, Yang J, Patterson N, et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet [Internet]. 2015 Feb 2 [cited 2018 May 14];47(3):291–5. Available from: http://www.nature.com/doifinder/10.1038/ng.3211 25642630

27. Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun [Internet]. 2017 Dec 28 [cited 2018 May 14];8(1):1826. Available from: http://www.nature.com/articles/s41467-017-01261-5 doi: 10.1038/s41467-017-01261-5 29184056

28. Kircher M, Witten DM, Jain P, O’Roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet [Internet]. 2014 Mar 2 [cited 2018 May 14];46(3):310–5. Available from: http://www.nature.com/articles/ng.2892 doi: 10.1038/ng.2892 24487276

29. Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res [Internet]. 2012 Sep [cited 2018 May 14];22(9):1790–7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22955989 doi: 10.1101/gr.137323.112 22955989

30. Aguet F, Brown AA, Castel SE, Davis JR, He Y, Jo B, et al. Genetic effects on gene expression across human tissues. Nature [Internet]. 2017 Oct 11 [cited 2018 May 15];550(7675):204–13. Available from: http://www.nature.com/doifinder/10.1038/nature24277 29022597

31. Saheki Y, Bian X, Schauder CM, Sawaki Y, Surma MA, Klose C, et al. Control of plasma membrane lipid homeostasis by the extended synaptotagmins. Nat Cell Biol [Internet]. 2016 May 11 [cited 2018 Jun 11];18(5):504–15. Available from: http://www.nature.com/articles/ncb3339 doi: 10.1038/ncb3339 27065097

32. Belinky F, Nativ N, Stelzer G, Zimmerman S, Iny Stein T, Safran M, et al. PathCards: multi-source consolidation of human biological pathways. Database (Oxford) [Internet]. 2015 [cited 2018 Jun 12];2015. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25725062

33. Segura MF, Sole C, Pascual M, Moubarak RS, Jose Perez-Garcia M, Gozzelino R, et al. The Long Form of Fas Apoptotic Inhibitory Molecule Is Expressed Specifically in Neurons and Protects Them against Death Receptor-Triggered Apoptosis. J Neurosci [Internet]. 2007 Oct 17 [cited 2018 Jun 12];27(42):11228–41. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17942717 doi: 10.1523/JNEUROSCI.3462-07.2007 17942717

34. Krasilnikov MA. Phosphatidylinositol-3 kinase dependent pathways: the role in control of cell growth, survival, and malignant transformation. Biochemistry (Mosc) [Internet]. 2000 Jan [cited 2018 Jun 12];65(1):59–67. Available from: http://www.ncbi.nlm.nih.gov/pubmed/10702641

35. Castaing-Berthou A, Malet N, Radojkovic C, Cabou C, Gayral S, Martinez LO, et al. PI3Kβ Plays a Key Role in Apolipoprotein A-I-Induced Endothelial Cell Proliferation Through Activation of the Ecto-F1-ATPase/P2Y1 Receptors. Cell Physiol Biochem [Internet]. 2017 [cited 2018 Jun 11];42(2):579–93. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28578353 doi: 10.1159/000477607 28578353

36. Couarch P, Vernia S, Gourfinkel-An I, Lesca G, Gataullina S, Fedirko E, et al. Lafora progressive myoclonus epilepsy: NHLRC1 mutations affect glycogen metabolism. J Mol Med (Berl) [Internet]. 2011 Sep [cited 2018 Jun 11];89(9):915–25. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21505799

37. Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet [Internet]. 2014 May [cited 2019 Jul 5];10(5):e1004383. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24830394 doi: 10.1371/journal.pgen.1004383 24830394

38. Võsa U, Claringbould A, Westra H-J, Bonder MJ, Deelen P, Zeng B, et al. Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis. bioRxiv [Internet]. 2018 Oct 19 [cited 2019 Jul 5];447367. Available from: https://www.biorxiv.org/content/10.1101/447367v1

39. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol [Internet]. 2015 Apr [cited 2018 May 15];11(4):e1004219. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25885710 doi: 10.1371/journal.pcbi.1004219 25885710

40. Krynetski EY, Evans WE. Genetic polymorphism of thiopurine S-methyltransferase: molecular mechanisms and clinical importance. Pharmacology [Internet]. 2000 Sep [cited 2018 Jun 11];61(3):136–46. Available from: http://www.ncbi.nlm.nih.gov/pubmed/10971199 doi: 10.1159/000028394 10971199

41. Nagaoka K, Hino S, Sakamoto A, Anan K, Takase R, Umehara T, et al. Lysine-specific demethylase 2 suppresses lipid influx and metabolism in hepatic cells. Mol Cell Biol [Internet]. 2015 Apr [cited 2018 Jun 11];35(7):1068–80. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25624347 doi: 10.1128/MCB.01404-14 25624347

42. Ozato K, Shin D-M, Chang T-H, Morse HC. TRIM family proteins and their emerging roles in innate immunity. Nat Rev Immunol [Internet]. 2008 Nov 1 [cited 2018 Jun 11];8(11):849–60. Available from: http://www.nature.com/articles/nri2413 doi: 10.1038/nri2413 18836477

43. Yang J, Lu C, Wei J, Guo Y, Liu W, Luo L, et al. Inhibition of KPNA4 attenuates prostate cancer metastasis. Oncogene [Internet]. 2017 [cited 2018 Jun 11];36(20):2868–78. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27941876 doi: 10.1038/onc.2016.440 27941876

44. Jakob S, Haendeler J. Molecular mechanisms involved in endothelial cell aging: role of telomerase reverse transcriptase. Z Gerontol Geriatr [Internet]. 2007 Oct [cited 2018 Jun 11];40(5):334–8. Available from: http://link.springer.com/10.1007/s00391-007-0482-y 17943236

45. Mattson MP, Klapper W. Emerging roles for telomerase in neuronal development and apoptosis. J Neurosci Res [Internet]. 2001 Jan 1 [cited 2018 Jun 11];63(1):1–9. Available from: http://doi.wiley.com/10.1002/1097-4547%2820010101%2963%3A1%3C1%3A%3AAID-JNR1%3E3.0.CO%3B2-I doi: 10.1002/1097-4547(20010101)63:1<1::AID-JNR1>3.0.CO;2-I 11169608

46. Tajima H, Niikura T, Hashimoto Y, Ito Y, Kita Y, Terashita K, et al. Evidence for in vivo production of Humanin peptide, a neuroprotective factor against Alzheimer’s disease-related insults. Neurosci Lett [Internet]. 2002 May 24 [cited 2018 Jun 11];324(3):227–31. Available from: https://www.sciencedirect.com/science/article/pii/S0304394002001994?via%3Dihub doi: 10.1016/s0304-3940(02)00199-4 12009529

47. Guo B, Zhai D, Cabezas E, Welsh K, Nouraini S, Satterthwait AC, et al. Humanin peptide suppresses apoptosis by interfering with Bax activation. Nature [Internet]. 2003 May 4 [cited 2018 Jun 11];423(6938):456–61. Available from: http://www.nature.com/articles/nature01627 doi: 10.1038/nature01627 12732850

48. Agrawal B, Krantz MJ, Parker J, Longenecker BM. Expression of MUC1 mucin on activated human T cells: implications for a role of MUC1 in normal immune regulation. Cancer Res [Internet]. 1998 Sep 15 [cited 2018 Jun 11];58(18):4079–81. Available from: http://www.ncbi.nlm.nih.gov/pubmed/9751614 9751614

49. Shi Y, Yuan B, Zhu W, Zhang R, Li L, Hao X, et al. Ube2D3 and Ube2N are essential for RIG-I-mediated MAVS aggregation in antiviral innate immunity. Nat Commun [Internet]. 2017 May 4 [cited 2018 Jun 12];8:15138. Available from: http://www.nature.com/doifinder/10.1038/ncomms15138 28469175

50. Chen Y-F, Wu C-Y, Kirby R, Kao C-H, Tsai T-F. A role for the CISD2 gene in lifespan control and human disease. Ann N Y Acad Sci [Internet]. 2010 Jul [cited 2018 Jun 12];1201(1):58–64. Available from: http://doi.wiley.com/10.1111/j.1749-6632.2010.05619.x

51. Wang C-H, Kao C-H, Chen Y-F, Wei Y-H, Tsai T-F. Cisd2 mediates lifespan: is there an interconnection among Ca 2+ homeostasis, autophagy, and lifespan? Free Radic Res [Internet]. 2014 Sep 29 [cited 2018 Jun 12];48(9):1109–14. Available from: http://www.tandfonline.com/doi/full/10.3109/10715762.2014.936431 24974737

52. Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh P-R, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet [Internet]. 2015 Nov 28 [cited 2018 May 15];47(11):1236–41. Available from: http://www.nature.com/articles/ng.3406 doi: 10.1038/ng.3406 26414676

53. Zheng J, Erzurumluoglu AM, Elsworth BL, Kemp JP, Howe L, Haycock PC, et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics [Internet]. 2017 Jan 15 [cited 2018 May 15];33(2):272–9. Available from: https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btw613 27663502

54. Bell JT, Tsai P-C, Yang T-P, Pidsley R, Nisbet J, Glass D, et al. Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genet [Internet]. 2012 [cited 2019 Jun 15];8(4):e1002629. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22532803 doi: 10.1371/journal.pgen.1002629 22532803

55. Kops GJPL, Medema RH, Glassford J, Essers MAG, Dijkers PF, Coffer PJ, et al. Control of cell cycle exit and entry by protein kinase B-regulated forkhead transcription factors. Mol Cell Biol [Internet]. 2002 Apr [cited 2018 May 23];22(7):2025–36. Available from: http://www.ncbi.nlm.nih.gov/pubmed/11884591 doi: 10.1128/MCB.22.7.2025-2036.2002 11884591

56. Bonafè M, Barbieri M, Marchegiani F, Olivieri F, Ragno E, Giampieri C, et al. Polymorphic Variants of Insulin-Like Growth Factor I (IGF-I) Receptor and Phosphoinositide 3-Kinase Genes Affect IGF-I Plasma Levels and Human Longevity: Cues for an Evolutionarily Conserved Mechanism of Life Span Control. J Clin Endocrinol Metab [Internet]. 2003 Jul 1 [cited 2018 May 23];88(7):3299–304. Available from: https://academic.oup.com/jcem/article-lookup/doi/10.1210/jc.2002-021810 12843179

57. Wu C-Y, Chen Y-F, Wang C-H, Kao C-H, Zhuang H-W, Chen C-C, et al. A persistent level of Cisd2 extends healthy lifespan and delays aging in mice. Hum Mol Genet [Internet]. 2012 Sep 15 [cited 2018 May 23];21(18):3956–68. Available from: https://academic.oup.com/hmg/article-lookup/doi/10.1093/hmg/dds210 22661501

58. Chen Y-F, Kao C-H, Chen Y-T, Wang C-H, Wu C-Y, Tsai C-Y, et al. Cisd2 deficiency drives premature aging and causes mitochondria-mediated defects in mice. Genes Dev [Internet]. 2009 May 15 [cited 2018 May 23];23(10):1183–94. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19451219 doi: 10.1101/gad.1779509 19451219

59. Vågerö D, Aronsson V, Modin B. Why is parental lifespan linked to children’s chances of reaching a high age? A transgenerational hypothesis. SSM—Popul Heal [Internet]. 2018 Apr [cited 2018 Nov 5];4:45–54. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29349272

60. Horvath S, Gurven M, Levine ME, Trumble BC, Kaplan H, Allayee H, et al. An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol [Internet]. 2016 Dec 11 [cited 2018 May 14];17(1):171. Available from: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1030-0 27511193

61. Smith BH, Campbell H, Blackwood D, Connell J, Connor M, Deary IJ, et al. Generation Scotland: the Scottish Family Health Study; a new resource for researching genes and heritability. BMC Med Genet [Internet]. 2006 Dec 2 [cited 2018 May 15];7(1):74. Available from: http://bmcmedgenet.biomedcentral.com/articles/10.1186/1471-2350-7-74

62. Smith BH, Campbell A, Linksted P, Fitzpatrick B, Jackson C, Kerr SM, et al. Cohort Profile: Generation Scotland: Scottish Family Health Study (GS:SFHS). The study, its participants and their potential for genetic research on health and illness. Int J Epidemiol [Internet]. 2013 Jun 1 [cited 2018 May 15];42(3):689–700. Available from: https://academic.oup.com/ije/article-lookup/doi/10.1093/ije/dys084 22786799

63. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics [Internet]. 2012 May 8 [cited 2018 Jun 4];13:86. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22568884 doi: 10.1186/1471-2105-13-86 22568884

64. Nagy R, Boutin TS, Marten J, Huffman JE, Kerr SM, Campbell A, et al. Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants. Genome Med [Internet]. 2017 Dec 7 [cited 2018 May 15];9(1):23. Available from: http://genomemedicine.biomedcentral.com/articles/10.1186/s13073-017-0414-4 28270201

65. Yang J, Zaitlen NA, Goddard ME, Visscher PM, Price AL. Advantages and pitfalls in the application of mixed-model association methods. Nat Genet [Internet]. 2014 Feb 1 [cited 2018 May 14];46(2):100–6. Available from: http://www.nature.com/articles/ng.2876 doi: 10.1038/ng.2876 24473328

66. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: A Tool for Genome-wide Complex Trait Analysis. Am J Hum Genet [Internet]. 2011 Jan 7 [cited 2018 May 14];88(1):76–82. Available from: https://www.sciencedirect.com/science/article/pii/S0002929710005987?via%3Dihub doi: 10.1016/j.ajhg.2010.11.011 21167468

67. Zaitlen N, Kraft P, Patterson N, Pasaniuc B, Bhatia G, Pollack S, et al. Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits. Visscher PM, editor. PLoS Genet [Internet]. 2013 May 30 [cited 2018 May 15];9(5):e1003520. Available from: http://dx.plos.org/10.1371/journal.pgen.1003520 23737753

68. Hall LS, Adams MJ, Arnau-Soler A, Clarke T-K, Howard DM, Zeng Y, et al. Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank. Transl Psychiatry [Internet]. 2018 Dec; Available from: https://doi.org/10.1038/s41398-017-0034-1

69. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics [Internet]. 2010 Sep 1 [cited 2018 May 14];26(17):2190–1. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20616382 doi: 10.1093/bioinformatics/btq340 20616382

70. Gibbs RA, Boerwinkle E, Doddapaneni H, Han Y, Korchina V, Kovar C, et al. A global reference for human genetic variation. Nature [Internet]. 2015 Oct 1 [cited 2018 Sep 28];526(7571):68–74. Available from: http://www.nature.com/articles/nature15393 doi: 10.1038/nature15393 26432245

71. Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res [Internet]. 2014 Jan 1 [cited 2018 May 15];42(D1):D1001–6. Available from: https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkt1229

72. MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res [Internet]. 2017 Jan 4 [cited 2018 May 15];45(D1):D896–901. Available from: https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw1133 27899670

73. Consortium T 1000 GP. An integrated map of genetic variation from 1,092 human genomes. Nature [Internet]. 2012 Nov [cited 2018 May 14];491(7422):56–65. Available from: http://www.nature.com/articles/nature11632 doi: 10.1038/nature11632 23128226

74. Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res [Internet]. 2010 Sep 1 [cited 2018 May 14];38(16):e164–e164. Available from: https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkq603 20601685

75. Ernst J, Kellis M. ChromHMM: automating chromatin-state discovery and characterization. Nat Methods [Internet]. 2012 Mar 1 [cited 2018 May 14];9(3):215–6. Available from: http://www.nature.com/articles/nmeth.1906 doi: 10.1038/nmeth.1906 22373907

76. Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, et al. Integrative analysis of 111 reference human epigenomes. Nature [Internet]. 2015 Feb 19 [cited 2018 May 14];518(7539):317–30. Available from: http://www.nature.com/articles/nature14248 doi: 10.1038/nature14248 25693563

77. Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet [Internet]. 2016 May 28 [cited 2018 May 14];48(5):481–7. Available from: http://www.nature.com/articles/ng.3538 doi: 10.1038/ng.3538 27019110

78. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Source J R Stat Soc Ser B [Internet]. 1995 [cited 2018 May 15];57(1):289–300. Available from: http://www.jstor.org/stable/2346101

Genetika Reprodukční medicína

Článek vyšel v časopise

PLOS Genetics

2019 Číslo 11

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Zvyšte si kvalifikaci online z pohodlí domova

Antiseptika a prevence ve stomatologii
nový kurz
Autoři: MUDr. Ladislav Korábek, CSc., MBA

Citikolin v neuroprotekci a neuroregeneraci: od výzkumu do klinické praxe nejen očních lékařů
Autoři: MUDr. Petr Výborný, CSc., FEBO

Zánětlivá bolest zad a axiální spondylartritida – Diagnostika a referenční strategie
Autoři: MUDr. Monika Gregová, Ph.D., MUDr. Kristýna Bubová

Diagnostika a léčba deprese pro ambulantní praxi
Autoři: MUDr. Jan Hubeňák, Ph.D

Význam nemocničního alert systému v době SARS-CoV-2
Autoři: doc. MUDr. Helena Lahoda Brodská, Ph.D., prim. MUDr. Václava Adámková

Všechny kurzy
Kurzy Doporučená témata Časopisy
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.


Nemáte účet?  Registrujte se