MicroRNA Predictors of Longevity in
Neither genetic nor environmental factors fully account for variability in individual longevity:
genetically identical invertebrates in homogenous environments often experience no less variability in lifespan than outbred human populations. Such variability is often assumed to result from stochasticity in damage accumulation over time; however, the identification of early-life gene expression states that predict future longevity would suggest that lifespan is least in part epigenetically determined. Such “biomarkers of aging,” genetic or otherwise, nevertheless remain rare. In this work, we sought early-life differences in organismal robustness in unperturbed individuals and examined the utility of microRNAs, known regulators of lifespan, development, and robustness, as aging biomarkers. We quantitatively examined Caenorhabditis elegans reared individually in a novel apparatus and observed throughout their lives. Early-to-mid–adulthood measures of homeostatic ability jointly predict 62% of longevity variability. Though correlated, markers of growth/muscle maintenance and of metabolic by-products (“age pigments”) report independently on lifespan, suggesting that graceful aging is not a single process. We further identified three microRNAs in which early-adulthood expression patterns individually predict up to 47% of lifespan differences. Though expression of each increases throughout this time, mir-71 and mir-246 correlate with lifespan, while mir-239 anti-correlates. Two of these three microRNA “biomarkers of aging” act upstream in insulin/IGF-1–like signaling (IIS) and other known longevity pathways, thus we infer that these microRNAs not only report on but also likely determine longevity. Thus, fluctuations in early-life IIS, due to variation in these microRNAs and from other causes, may determine individual lifespan.
Vyšlo v časopise:
MicroRNA Predictors of Longevity in. PLoS Genet 7(9): e32767. doi:10.1371/journal.pgen.1002306
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pgen.1002306
Souhrn
Neither genetic nor environmental factors fully account for variability in individual longevity:
genetically identical invertebrates in homogenous environments often experience no less variability in lifespan than outbred human populations. Such variability is often assumed to result from stochasticity in damage accumulation over time; however, the identification of early-life gene expression states that predict future longevity would suggest that lifespan is least in part epigenetically determined. Such “biomarkers of aging,” genetic or otherwise, nevertheless remain rare. In this work, we sought early-life differences in organismal robustness in unperturbed individuals and examined the utility of microRNAs, known regulators of lifespan, development, and robustness, as aging biomarkers. We quantitatively examined Caenorhabditis elegans reared individually in a novel apparatus and observed throughout their lives. Early-to-mid–adulthood measures of homeostatic ability jointly predict 62% of longevity variability. Though correlated, markers of growth/muscle maintenance and of metabolic by-products (“age pigments”) report independently on lifespan, suggesting that graceful aging is not a single process. We further identified three microRNAs in which early-adulthood expression patterns individually predict up to 47% of lifespan differences. Though expression of each increases throughout this time, mir-71 and mir-246 correlate with lifespan, while mir-239 anti-correlates. Two of these three microRNA “biomarkers of aging” act upstream in insulin/IGF-1–like signaling (IIS) and other known longevity pathways, thus we infer that these microRNAs not only report on but also likely determine longevity. Thus, fluctuations in early-life IIS, due to variation in these microRNAs and from other causes, may determine individual lifespan.
Zdroje
1. GögeleMPattaroCFuchsbergerCMinelliCPramstallerPP 2010 Heritability Analysis of Life Span in a Semi-isolated Population Followed Across Four Centuries Reveals the Presence of Pleiotropy Between Life Span and Reproduction. J Gerontol A Biol Sci Med Sci 705 1 12
2. HerskindAMMcGueMHolmNVSørensenTIHarvaldB 1996 The heritability of human longevity: a population-based study of 2872 Danish twin pairs born 1870–1900. Hum Genet 97 319 323
3. HoriuchiS 2003 Interspecies Differences in the Life Span Distribution: Humans versus Invertebrates. Pop Dev Review 29 127 151
4. VaupelJWCareyJRChristensenKJohnsonTEYashinAI 1998 Biodemographic trajectories of longevity. Science 280 855 860
5. BrooksALithgowGJJohnsonTE 1994 Mortality rates in a genetically heterogeneous population of Caenorhabditis elegans. Science 263 668 671
6. SzewczykNJUdranszkyIAKozakESungaJKimSK 2006 Delayed development and lifespan extension as features of metabolic lifestyle alteration in C. elegans under dietary restriction. J Exp Biol 209 4129 4139
7. KenyonCJ 2010 The genetics of ageing. Nature 464 504 512
8. KirkwoodTBLFederMFinchCEFranceschiCGlobersonA 2005 What accounts for the wide variation in life span of genetically identical organisms reared in a constant environment? Mech Ageing Dev 126 439 443
9. BakerGTSprottRL 1988 Biomarkers of aging. Exp Gerontol 23 223 239
10. PincusZSlackFJ 2010 Developmental biomarkers of aging in Caenorhabditis elegans. Dev Dyn 239 1306 1314
11. HerndonLASchmeissnerPJDudaronekJMBrownPAListnerKM 2002 Stochastic and genetic factors influence tissue-specific decline in ageing C. elegans. Nature 419 808 814
12. HsuA-LFengZHsiehM-YXuXZS 2009 Identification by machine vision of the rate of motor activity decline as a lifespan predictor in C. elegans. Neurobiol Aging 30 1498 1503
13. HuangCXiongCKornfeldK 2004 Measurements of age-related changes of physiological processes that predict lifespan of Caenorhabditis elegans. Proc Natl Acad Sci USA 101 8084 8089
14. HulmeSEShevkoplyasSSMcGuiganAPApfeldJFontanaW 2010 Lifespan-on-a-chip: microfluidic chambers for performing lifelong observation of C. elegans. Lab on a Chip 10 589 597
15. TermanABrunkUT 2006 Oxidative stress, accumulation of biological “garbage”, and aging. Antioxidants & Redox Signaling 8 197 204
16. ClokeyGVJacobsonLA 1986 The autofluorescent “lipofuscin granules” in the intestinal cells of Caenorhabditis elegans are secondary lysosomes. Mech Ageing Dev 35 79 94
17. KlassMR 1977 Aging in the nematode Caenorhabditis elegans: major biological and environmental factors influencing life span. Mech Ageing Dev 6 413 429
18. GariganDHsuA-LFraserAGKamathRSAhringerJ 2002 Genetic analysis of tissue aging in Caenorhabditis elegans: a role for heat-shock factor and bacterial proliferation. Genetics 161 1101 1112
19. GerstbreinBStamatasGKolliasNDriscollM 2005 In vivo spectrofluorimetry reveals endogenous biomarkers that report healthspan and dietary restriction in Caenorhabditis elegans. Aging Cell 4 127 137
20. Sánchez-BlancoAKimSK 2011 Variable Pathogenicity Determines Individual Lifespan in Caenorhabditis elegans. PLoS Genet 7 e1002047 doi:10.1371/journal.pgen.1002047
21. HouthoofdKBraeckmanBPLenaertsIBrysKMatthijssensF 2005 DAF-2 pathway mutations and food restriction in aging Caenorhabditis elegans differentially affect metabolism. Neurobiol Aging 26 689 696
22. LundJTedescoPDukeKWangJKimSK 2002 Transcriptional profile of aging in C. elegans. Curr Biol 12 1566 1573
23. GoldenTRHubbardADandoCHerrenMAMelovS 2008 Age-related behaviors have distinct transcriptional profiles in Caenorhabditis elegans. Aging Cell 7 850 865
24. FortneyKKotlyarMJurisicaI 2010 Inferring the functions of longevity genes with modular subnetwork biomarkers of Caenorhabditis elegans aging. Genome Biol 11 R13
25. ReaSLWuDCypserJRVaupelJWJohnsonTE 2005 A stress-sensitive reporter predicts longevity in isogenic populations of Caenorhabditis elegans. Nat Genet 37 894 898
26. CypserJRJohnsonTE 2002 Multiple stressors in Caenorhabditis elegans induce stress hormesis and extended longevity. J Gerontol A Biol Sci Med Sci 57 B109 114
27. HornsteinEShomronN 2006 Canalization of development by microRNAs. Nat Genet 38 S20 24
28. LiXCassidyJJReinkeCAFischboeckSCarthewRW 2009 A microRNA imparts robustness against environmental fluctuation during development. Cell 137 273 282
29. StarkABrenneckeJBushatiNRussellRBCohenSM 2005 Animal MicroRNAs confer robustness to gene expression and have a significant impact on 3′ UTR evolution. Cell 123 1133 1146
30. Ibáñez-VentosoCDriscollM 2009 MicroRNAs in C. elegans Aging: Molecular Insurance for Robustness? Curr Genomics 10 144 153
31. BoehmMSlackFJ 2005 A developmental timing microRNA and its target regulate life span in C. elegans. Science 310 1954 1957
32. CrawfordDLibinaNKenyonC 2007 Caenorhabditis elegans integrates food and reproductive signals in lifespan determination. Aging Cell 6 715 721
33. DillinACrawfordDKKenyonC 2002 Timing requirements for insulin/IGF-1 signaling in C. elegans. Science 298 830 834
34. LinKDormanJBRodanAKenyonC 1997 daf-16: An HNF-3/forkhead family member that can function to double the life-span of Caenorhabditis elegans. Science 278 1319 1322
35. Ibáñez-VentosoCYangMGuoSRobinsHPadgettRW 2006 Modulated microRNA expression during adult lifespan in Caenorhabditis elegans. Aging Cell 5 235 246
36. de LencastreAPincusZZhouKKatoMLeeSS 2010 MicroRNAs both promote and antagonize longevity in C. elegans. Curr Biol 20 2159 2168
37. YanaiharaNCaplenNBowmanESeikeMKumamotoK 2006 Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9 189 198
38. VoliniaSCalinGALiuC-GAmbsSCimminoA 2006 A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci USA 103 2257 2261
39. SchetterAJLeungSYSohnJJZanettiKABowmanED 2008 MicroRNA expression profiles associated with prognosis and therapeutic outcome in colon adenocarcinoma. JAMA 299 425 436
40. WangYLiangYLuQ 2008 MicroRNA epigenetic alterations: predicting biomarkers and therapeutic targets in human diseases. Clin Genet 74 307 315
41. Noren HootenNAbdelmohsenKGorospeMEjioguNZondermanAB 2010 microRNA expression patterns reveal differential expression of target genes with age. PLoS ONE 5 e10724 doi:10.1371/journal.pone.0010724
42. FabianTJJohnsonTE 1994 Production of age-synchronous mass cultures of Caenorhabditis elegans. J Gerontol A Biol Sci Med Sci 49 B145 156
43. DavisBOAndersonGLDusenberyDB 1982 Total luminescence spectroscopy of fluorescence changes during aging in Caenorhabditis elegans. Biochemistry 21 4089 4095
44. ShamirLWolkowCAGoldbergIG 2009 Quantitative measurement of aging using image texture entropy. Bioinformatics 25 3060 3063
45. JohnstonJIserWBChowDKGoldbergIGWolkowCA 2008 Quantitative image analysis reveals distinct structural transitions during aging in Caenorhabditis elegans tissues. PLoS ONE 3 e2821 doi:10.1371/journal.pone.0002821
46. MiskaEAAlvarez-SaavedraEAbbottALLauNCHellmanAB 2007 Most Caenorhabditis elegans microRNAs are individually not essential for development or viability. PLoS Genet 3 e215 doi:10.1371/journal.pgen.0030215
47. MartinezNJOwMCReece-HoyesJSBarrasaMIAmbrosVR 2008 Genome-scale spatiotemporal analysis of Caenorhabditis elegans microRNA promoter activity. Genome Res 18 2005 2015
48. IsikMKorswagenHCBerezikovE 2010 Expression patterns of intronic microRNAs in Caenorhabditis elegans. Silence 1 5
49. SeewaldAKCypserJMendenhallAJohnsonT 2010 Quantifying phenotypic variation in isogenic Caenorhabditis elegans expressing Phsp-16.2::gfp by clustering 2D expression patterns. PLoS ONE 5 e11426 doi:10.1371/journal.pone.0011426
50. MitchellDHStilesJWSantelliJSanadiDR 1979 Synchronous growth and aging of Caenorhabditis elegans in the presence of fluorodeoxyuridine. J Gerontol 34 28 36
51. SpirtesPGlymourC 1991 An algorithm for fast recovery of sparse causal graphs. Social Science Computer Review 9 62 72
52. YashinAIVaupelJWIachineIA 1994 A duality in aging: the equivalence of mortality models based on radically different concepts. Mech Ageing Dev 74 1 14
53. YashinAICypserJWJohnsonTEMichalskiAIBoykoSI 2002 Heat shock changes the heterogeneity distribution in populations of Caenorhabditis elegans: does it tell us anything about the biological mechanism of stress response? J Gerontol A Biol Sci Med Sci 57 B83 92
54. WuDReaSLYashinAIJohnsonTE 2006 Visualizing hidden heterogeneity in isogenic populations of C. elegans. Exp Gerontol 41 261 270
55. PiperMDWSelmanCMcElweeJJPartridgeL 2008 Separating cause from effect: how does insulin/IGF signalling control lifespan in worms, flies and mice? J Intern Med 263 179 191
56. MurphyCTMcCarrollSABargmannCIFraserAKamathRS 2003 Genes that act downstream of DAF-16 to influence the lifespan of Caenorhabditis elegans. Nature 424 277 283
57. SamuelsonAVCarrCERuvkunG 2007 Gene activities that mediate increased life span of C. elegans insulin-like signaling mutants. Genes Dev 21 2976 2994
58. OlsenAVantipalliMCLithgowGJ 2006 Checkpoint proteins control survival of the postmitotic cells in Caenorhabditis elegans. Science 312 1381 1385
59. YamawakiTMArantes-OliveiraNBermanJRZhangPKenyonC 2008 Distinct activities of the germline and somatic reproductive tissues in the regulation of Caenorhabditis elegans' longevity. Genetics 178 513 526
60. ClarkWR 2004 Reflections on an unsolved problem of biology: the evolution of senescence and death. Adv Gerontol 14 7 20
61. PfisterPMWendlandtMNeuenschwanderPSuterUW 2007 Surface-textured PEG-based hydrogels with adjustable elasticity: Synthesis and characterization. Biomaterials 28 567 575
62. BrennerS 1974 The genetics of Caenorhabditis elegans. Genetics 77 71 94
63. ByerlyLCassadaRCRussellRL 1976 The life cycle of the nematode Caenorhabditis elegans. I. Wild-type growth and reproduction. Dev Biol 51 23 33
64. EdwardsSCharlieNMilfortMBrownBGravlinC 2008 A Novel Molecular Solution for Ultraviolet Light Detection in Caenorhabditis elegans. PLoS Biol 6 e198 doi:10.1371/journal.pbio.0060198
65. WellsWMViolaPAtsumiHNakajimaSKikinisR 1996 Multi-modal volume registration by maximization of mutual information. Med Image Analysis 1 35 51
66. KimKIJungKParkSHKimHJ 2002 Support vector machines for texture classification. IEEE Trans PAMI 24 1542 1550
67. SchölkopfBSmolaAWilliamsonRCBartlettPL 2000 New support vector algorithms. Neural Computation 12 1207 1245
68. ChangC-CLinC-J 2010 LIBSVM: a library for support vector machines. http://www.csie.ntu.edu.tw/~cjlin/libsvm
69. VarmaMZissermanA 2003 Texture classification: are filter banks necessary? Proc IEEE Conf Computer Vision and Pattern Recognition 2 691 698
70. ScottD 1992 Multivariate Density Estimation: Theory, Practice, and Visualization. John Wiley & Sons, New York, Chichester
71. ScheinesRSpirtesPGlymourCMeekC 2010 The TETRAD Project: Causal Models and Statistical Data. http://www.phil.cmu.edu/projects/tetrad/
72. OrrM 1995 Regularization in the selection of radial basis function centers. Neural Computation 7 606 623
Štítky
Genetika Reprodukčná medicínaČlánok vyšiel v časopise
PLOS Genetics
2011 Číslo 9
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