ES2586034T3 - Micro-ARN como marcador de actividad de las plaquetas - Google Patents

Micro-ARN como marcador de actividad de las plaquetas Download PDF

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ES2586034T3
ES2586034T3 ES12788630.7T ES12788630T ES2586034T3 ES 2586034 T3 ES2586034 T3 ES 2586034T3 ES 12788630 T ES12788630 T ES 12788630T ES 2586034 T3 ES2586034 T3 ES 2586034T3
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Manuel Mayr
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    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

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Abstract

Un método para determinar la actividad de las plaquetas en un individuo que comprende determinar en una muestra de plasma o suero obtenida de un individuo el nivel de al menos un microARN seleccionado del grupo que consiste en miR-126, miR-197, miR-223, miR-24 y miR -21.

Description

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5. D'Alessandra Y, Devanna P, Limana F, Straino S, Di Carlo A, Brambilla PG, Rubino M, Carena MC, Spazzafumo L, De Simone M, Micheli B, Biglioli P, Achilli F, Martelli F, Maggiolini S, Marenzi G, Pompilio G, y Capogrossi MC. Circulating microRNAs are new and sensitive biomarkers of myocardial infarction. Eur Heart J 31: 2765-2773, 2010.
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miR-126 regulates angiogenic signaling and vascular integrity. Dev Cell 15: 272-284, 2008. 15
9. Friedewald WT, Levy RI, y Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 18: 499-502, 1972.
10. Goeman JJ. L1 penalized estimation in the Cox proportional hazards model. Biom J 52: 70-84, 2010. 20
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IHD Register: Report of the Fifth Working Group. Copenhagen DWHO ROfE. 1971.
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Inui M, Martello G, y Piccolo S. MicroRNA control of signal transduction. Nat Rev Mol Cell Biol 11: 252-263, 2010.
25 13. Johnnidis JB, Harris MH, Wheeler RT, Stehling-Sun S, Lam MH, Kirak O, Brummelkamp TR, Fleming MD, y Camargo FD. Regulation of progenitor cell proliferation and granulocyte function by microRNA-223. Nature 451: 1125-1129, 2008.
14. Kiddle SJ, Windram OP, McHattie S, Mead A, Beynon J, Buchanan-Wollaston V, Denby KJ, y Mukherjee S.
30 Temporal clustering by affinity propagation reveals transcriptional modules in Arabidopsis thaliana. Bioinformatics 26: 355-362,2010.
15. Kiechl S, Lorenz E, Reindl M, Wiedermann CJ, Oberhollenzer F, Bonora E, Willeit J, y Schwartz DA. Toll-like
receptor 4 polymorphisms and atherogenesis. N Engl J Med 347: 185-192, 2002. 35
16. Latronico MV, Catalucci D, y Condorelli G. Emerging role of microRNAs in cardiovascular biology. Circ Res 101: 1225-1236, 2007.
17. Lehmann U, Streichert T, Otto B, Albat C, Hasemeier B, Christgen H, Schipper E, Hille U, Kreipe HH, y Langer F. 40 Identification of differentially expressed microRNAs in human male breast cancer. BMC Cancer 10: 109, 2010.
18. Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM, Castle J, Bartel DP, Linsley PS, y Johnson JM. Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 433: 769773, 2005.
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Liu N, y Olson EN. MicroRNA regulatory networks in cardiovascular development. Dev Cell 18: 510-525, 2010.
20.
Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O'Briant KC, Allen A, Lin DW, Urban N, Drescher CW, Knudsen BS, Stirewalt DL, Gentleman R, Vessella RL, Nelson
50 PS, Martin DB, y Tewari M. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci U S A 105: 10513-10518, 2008.
21. Patrick DM, Montgomery RL, Qi X, Obad S, Kauppinen S, Hill JA, van Rooij E, y Olson EN. Stress-dependent
cardiac remodeling occurs in the absence of microRNA-21 in mice. J Clin Invest 120: 3912-3916, 2010. 55
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Pillai RS, Bhattacharyya SN, y Filipowicz W. Repression of protein synthesis by miRNAs: how many mechanisms? Trends Cell Biol 17: 118-126, 2007.
23.
Prokopi M, Pula G, Mayr U, Devue C, Gallagher J, Xiao Q, Boulanger CM, Westwood N, Urbich C, Willeit J,
60 Steiner M, Breuss J, Xu Q, Kiechl S, y Mayr M. Proteomic analysis reveals presence of platelet microparticles in endothelial progenitor cell cultures. Blood 114: 723-732, 2009.
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24. Pulikkan JA. Cell-cycle regulator E2F1 and microRNA-223 comprise an autoregulatory negative feedback loop in acute myeloid leukemia. Blood 115: 1768-1778, 2010.
5 25. Rautou PE, Vion AC, Amabile N, Chironi G, Simon A, Tedgui A, y Boulanger CM. Microparticles, vascular function, and atherothrombosis. Circ Res 109: 593-606, 2011.
26. Scapoli L, Palmieri A, Lo Muzio L, Pezzetti F, Rubini C, Girardi A, Farinella F, Mazzotta M, y Carinci F. MicroRNA
expression profiling of oral carcinoma identifies new markers of tumor progression. Int J Immunopathol Pharmacol 10 23: 1229-1234,2010.
27. Sun W, Shen W, Yang S, Hu F, Li H, y Zhu TH. miR-223 and miR-142 attenuate hematopoietic cell proliferation, and miR-223 positively regulates miR-142 through LMO2 isoforms and CEBP-beta. Cell Res 20: 1158-1169, 2010.
15 28. Thum T, Gross C, Fiedler J, Fischer T, Kissler S, Bussen M, Galuppo P, Just S, Rottbauer W, Frantz S, Castoldi M, Soutschek J, Koteliansky V, Rosenwald A, Basson MA, Licht JD, Pena JT, Rouhanifard SH, Muckenthaler MU, Tuschl T, Martin GR, Bauersachs J, y Engelhardt S. MicroRNA-21 contributes to myocardial disease by stimulating MAP kinase signalling in fibroblasts. Nature 456: 980-984, 2008.
20 29. Tijsen AJ, Creemers EE, Moerland PD, de Windt LJ, van der Wal AC, Kok WE, y Pinto YM. MiR423-5p as a circulating biomarker for heart failure. Circ Res 106: 1035-1039, 2010.
30. Wang GK, Zhu JQ, Zhang JT, Li Q, Li Y, He J, Qin YW, y Jing Q. Circulating microRNA: a novel potential
biomarker for early diagnosis of acute myocardial infarction in humans. Eur Heart J 31: 659-666, 2010. 25
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Wang K, Zhang S, Marzolf B, Troisch P, Brightman A, Hu Z, Hood LE, y Galas DJ. Circulating microRNAs, potential biomarkers for drug-induced liver injury. Proc Natl Acad Sci U S A 106: 4402-4407, 2009.
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Zampetaki A, Kiechl S, Drozdov I, Willeit P, Mayr U, Prokopi M, Mayr A, Weger S, Oberhollenzer F, Bonora E,
30 Shah A, Willeit J, y Mayr M. Plasma microRNA profiling reveals loss of endothelial miR-126 and other microRNAs in type 2 diabetes. Circ Res 107: 810-817, 2010.
33.
Kloosterman WP, Plasterk RH. Dev Cell. 2006 Oct;11(4):441-50. 35 34. Stefani G, Slack FJ. Nat Rev Mol Cell Biol. 2008 Mar;9(3):219-30.
35. Latronico MV, Catalucci D, Condorelli G. Circ Res. 2007 Dic 7;101(12):1225-36.
36.
van Rooij E, Marshall WS, Olson EN. Circ Res. 2008 Oct 24;103(9):919-28. 40
37. Kuehbacher A, Urbich C, Zeiher AM, Dimmeler S. Circ Res. 2007 Jul 6;101(1):59-68.
38.
Tanaka M et al. PLoS One. 2009;4(5):e5532. 45 39. Laterza OF et al. Clin Chem. 2009 Nov;55(11):1977-83.
40. Ji X, Takahashi R, Hiura Y, Hirokawa G, Fukushima Y, Iwai N. Clin Chem. 2009 Nov;55(11):1944-9.
41.
Hoak JC. Platelet and atherosclerosis. Semin. Thromb. Hemost. 1988; 14: 202-5. 50
42.
Rabbani LE, Loscalzo J. Atherosclerosis 1994; 105: 1-7.
43.
White JG. Platelets and atherosclerosis. Eur. J. Clin. Invest. 1994; 24 (Supl 1): 25-9.
55 44. Falk E, Fernandez-Ortiz A. Role of thrombosis in atherosclerosis and its complications. Am. J. Cardiol. 1995; 75:3B-11B.
45. Nash GF, Turner LF, Scully MF, Kakkar AK: Platelets and cancer. Lancet Oncol 2002, 3(7):425-430.
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Tabla 2A. Análisis de interacción de la asociación entre miARN selectivos e infarto de miocardio (IM).
Subgrupos
Razón de riesgo (IC 95%) para infarto de miocardio por 1 incremento DT de loge miRNA*
MiR-126
MiR-197 MiR-223
Diagnóstico de diabetes
Si
0 ,23 (0 ,09-0 ,61) 1 ,06 (0 ,36-3 ,14) 1 ,46 (0 ,61-3 ,51)
No
0 ,43 (0 ,23-0 ,79) 1 ,86 (1 ,04-3 ,34) 2 ,31 (1 ,31-4 ,07)
Pinteracción=0 ,131
Pinteracción=0 ,268 Pinteracción=0 ,286
Sexo
Varón
0 ,39 (0 ,21-0 ,73) 1 ,57 (0 ,86-2 ,89) 1 ,95 (1 ,05-3 ,63)
Mujer
0 ,42 (0 ,20-0 ,90) 2 ,50 (1 ,14-5 ,51) 2 ,68 (1 ,30-5 ,53)
Pinteracción= 0 ,814
Pinteracción=0 ,209 Pinteracción=0-392
Historial de enfermedad cardiovascular
Si
0 ,41 (0 ,22-0 ,76) 2 ,02 (1 ,10-3 ,70) 2 ,29 (1 ,28-4 ,08)
No
0 ,30 (0 ,12-0 ,79) 1 ,19 (0 ,53-2 ,70) 1 ,83 (0 ,74-4 ,54)
Pinteracción=0 ,486
Pinteracción=0 ,189 Pinteracción=0 ,624
* Todos los modelos de Cox incluían un término de interacción de diabetes, sexo o historial de enfermedad cardiovascular con el miRNA de interés, más las variables de edad, sexo, condición de fumador (fumador vs , no fumador), presión arterial sistólica, colesterol LDL, diabetes, historial de enfermedad cardiovascular, miR-126, miR-197 y miR-223.
Tabla 2B. Análisis de interacción de la asociación entre los miARN seleccionados e incidentes de infarto de miocardio (IM).
Subgrupos
Razón de riesgo (IC 95%) para infarto de miocardio por 1 incremento DT de loge miRNA*
Núm. de eventos de IM
Tasa de incidencia (por1000 personasaño) MiR-126 MiR-197 MiR-223
Diagnostico de diabetes
Si
6 7,9 (3,6-17,6) 4,07(1,63-10,13) 0,85 (0,32-2,25) 0,70(0,26-1,85)
No
41 5,2 (3,8-7,0) 2,35 (1,28-4,30) 0,55 (0,32-0,94) 0,47(0,29-0,75)
Pinteracción=0,174
Pinteracción=0,337 Pinteracción=0,405
Sexo
Varón
30 7,2 (5,0-10,3) 2,61 (1,40-4,88) 0,64 (0,36-1,12) 0,52(0,31-0,88)
Mujer
17 3,7 (2,3-6,0) 2,36 (1,12-4,96) 0,42(0,21-0,85) 0,42(0,23-0,77)
Pinteracción=0,755
Pinteracción=0,206 Pinteracción=0,491
Historial de enfermedad cardiovascular
Si
12 25,0 (14,2-44 0) 2,45 (1,34-4 47) 0,81(0,37-1,80) 0,47(0,29-0,76)
No
35 4,3 (3,1-5,9) 3,25 (1,28-8,25) 0,52 (0,30-0,90) 0,55(0,24-1,23)
Pinteracción=0,490
Pinteracción=0,252 Pinteracción=0,711
* Todos los modelos de Cox incluían un término de interacción de diabetes, sexo o historial de enfermedad cardiovascular con el miRNA de interés, más las variables de edad, sexo, condición de fumador (fumador vs. no fumador), presión arterial sistólica, colesterol LDL, diabetes, historial de enfermedad cardiovascular, miR-126, miR197 y miR-223. (modelo multivariable 2).
15
imagen12
-
Tabla 4. Correlación entre concentración de dímero D y niveles de expresión de miRNA seleccionados*
imagen13
D-Dímero / miR126 D-Dímero / miR197 D-Dímero / miR223 D-Dímero / miR24 D-Dímero / miR130a D-Dímero / miR433 D-Dímero / let7d
Momento inicial
0,8096 (0,015) 0,7024 (0,052) 0,9078 (0,002) 0,8482 (0,008) 0,8436 (0,009) 0,7612 (0,028) 0,7870 (0,021)
10 min
0,7733 (0,024) 0,2085 (0,620) 0,7552 (0,030) 0,6824 (0,062) 0,7265 (0,041) 0,7047 (0,051) 0,6959 (0,055)
1 h
-0,2399 (0,604) -0,5388 (0,212) -0,433 (0,333) -0,491 (0,263) -0,2685 (0,560) 0,1468 (0,754) -0,3104 (0,498)
5 h
0,0876 (0,852) -0,1272 (0,786) 0,0668 (0,887) 0,0999 (0,831) 0,1120 (0,811) 0,0381 (0,935) 0,0932 (0,842)
2 d
0,1816 (0,667) 0,0298 (0,944) 0,0491 (0,908) 0,1393 (0,742) 0,4683 (0,242) 0,4249 (0,294) 0,4663 (0,244)
7 d
0,2535 (0,511) -0,0237 (0,952) 0,1219 (0,755) 0,2483 (0,519) 0,1791 (0,645) 0,2990 (0,434) 0,2952 (0,441)
* Los números son los coeficientes de correlación parcial ajustados a la edad y el sexo (valores P).
imagen14
Tabla 5
Combinaciones MiR
AIC Cambio índice C NRI IDI
MiR-24, -126, -197
564,9772949 0,0308 (-0,0290, 0,0907) 16,54 (-2,32, 35,40) 0,0555 (0,0076, 0,1034)
MiR-24, -126, -150
566,5112915 0,0217 (-0,0424, 0,0857) 17,24 (-2,05, 36,53) 0,0515 (0,0089, 0,0941)
MiR-126, -197, -223
565,0547485 0,0366 (-0,0158, 0,0889) 16,86 (-1,99, 35,71) 0,0473 (0,0050, 0,0896)
MiR-3423p, -24, -126
567,0376587 0,0238 (-0,0326, 0,0802) 19,37 (0,54, 38,19) 0,0470 (0,0094, 0,0845)
MiR-24, -126, -146b
566,605957 0,0188 (-0,0381, 0,0757) 16,70 (-1,18, 34,58) 0,0447 (0,0073, 0,0822)
MiR-320, -24, -126
565,9118652 0,0226 (-0,0325, 0,0777) 17,08 (-1,29, 35,45) 0,0434 (0,0095, 0,0773)
MiR-191, -24, -126
567,0245972 0,0195 (-0,0357, 0,0747) 14,26 (-3,13, 31,64) 0,0430 (0,0075, 0,0785)
MiR-283p, -24, -126
566,0445557 0,0213 (-0,0333, 0,0760) 13,78 (-3,59, 31,15) 0,0427 (0,0077, 0,0778)
MiR-25, -24, -126
567,6636963 0,0182 (-0,0381, 0,0746) 13,14 (-4,25, 30,54) 0,0419 (0,0050, 0,0788)
let7e, miR-24, -126
566,3652344 0,0212 (-0,0327, 0,0752) 11,81 (-5,07, 28,69) 0,0415 (0,0075, 0,0756)
MiR-486, -24, -126
566,9111938 0,0209 (-0,0324, 0,0741) 11,33 (-5,54, 28,21) 0,0410 (0,0055, 0,0766)
MiR-24, -126, -454
567,1853027 0,0197 (-0,0354, 0,0749) 13,62 (-3,77, 31,01) 0,0407 (0,0058, 0,0755)
MiR-140, -24, -126
567,2825928 0,0202 (-0,0346, 0,0750) 13,78 (-3,60, 31,16) 0,0406 (0,0060, 0,0752)
MiR-24, -126, -223
567,4731445 0,0188 (-0,0355, 0,0732) 16,07 (-1,81, 33,94) 0,0404 (0,0059, 0,0749)
MiR-122, -24, -126
567,4348755 0,0199 (-0,0350, 0,0748) 13,46 (-3,92, 30,84) 0,0402 (0,0055, 0,0749)
MiR-93, -24, -126
567,1271362 0,0198 (-0,0348, 0,0744) 13,62 (-3,77, 31,01) 0,0401 (0,0058, 0,0745)
let7b, miR-24, -126
567,6226196 0,0215 (-0,0332, 0,0763) 13,94 (-3,44, 31,32) 0,0398 (0,0062, 0,0734)
MiR-21, -126, -197
565,9361572 0,0373 (-0,0160, 0,0905) 15,37 (-2,03, 32,77) 0,0394 (-0,0003, 0,0791)
MiR-93, -126, -197
564,0219116 0,0448 (-0,0055, 0,0951) 16,54 (-1,34, 34,43) 0,0392 (0,0020, 0,0764)
MiR-320, -126, -223
567,2560425 0,0211 (-0,0220, 0,0642) 20,32 (2,44, 38,21) 0,0310 (0,0069, 0,0551)
18

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ES12788630.7T 2011-11-11 2012-11-06 Micro-ARN como marcador de actividad de las plaquetas Active ES2586034T3 (es)

Applications Claiming Priority (5)

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GB201119571 2011-11-11
GB201119571A GB201119571D0 (en) 2011-11-11 2011-11-11 Detection method
GB201212539 2012-07-13
GBGB1212539.9A GB201212539D0 (en) 2012-07-13 2012-07-13 Detection method
PCT/GB2012/052754 WO2013068730A1 (en) 2011-11-11 2012-11-06 Micro -rnas as marker for platelet activity

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WO2015091897A1 (en) * 2013-12-19 2015-06-25 Comprehensive Biomarker Center Gmbh Determination of platelet-mirnas
CN110951870A (zh) * 2020-01-03 2020-04-03 中国人民解放军总医院 miRNA表达量在预测氯吡格雷治疗疗效中的应用

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EP2290071B1 (en) * 2004-05-28 2014-12-31 Asuragen, Inc. Methods and compositions involving microRNA
ES2446362T3 (es) * 2006-03-20 2014-03-07 The Ohio State University Research Foundation Huellas de microARN durante megacariocipoyesis humana
AU2011243291A1 (en) * 2010-04-21 2012-11-01 Academisch Medisch Centrum Bij De Universiteit Van Amsterdam Means and methods for determining risk of cardiovascular disease

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