Factor de necrosis tumoral alfa en pacientes con preeclampsia a término y pretérmino(Tumor necrosis factor alpha in term and pre-term preeclamptic patients)Eduardo Reyna-Villasmil 1 , Jorly Mejia-Montilla 1, Nadia Reyna-Villasmil 1, Duly Torres-Cepeda 1, Joel Santos-Bolívar 1, Jhoan Aragón-Charry 11 Servicio de Obstetricia y Ginecología, Maternidad “Dr. Nerio Belloso”, Hospital “Dr. Urquinaona”, Maracaibo - Venezuela.[ARTICULO ORIGINAL]Recibido: 03 de Mayo de 2012. Aceptado: 17 de Julio de 2012.ResumenEl objetivo de la investigación fue identificar y comparar las concentraciones de factor de necrosis tumoral alfa en pacientes con preeclampsia a término y pre-término. Se seleccionó un total de 50 pacientes. Se incluyeron a 20 pacientes preeclámpticas pre-término (grupo A) y 30 preeclámpticas a término (grupo B). Las muestras de sangre para la determinación de factor de necrosis tumoral alfa se recolectaron en todas las pacientes antes del parto e inmediatamente después del diagnóstico de preeclampsia. No se encontraron diferencias significativas con relación a la edad materna e Índice de masa corporal al momento de la toma de la muestra. Se observaron diferencias estadísticamente significativas entre los grupos con respecto a la edad gestacional (p < 0,0001). El valor promedio de la presión arterial sistólica en el grupo A fue de 149,4 ± 11,3 mmHg mientras que en las pacientes del grupo B fue de 148,1 ± 12,3 mmHg (p = 0,7071) y el valor promedio de presión arterial diastólica en el grupo A fue de 103,8 ± 8,6 mmHg y en el grupo B fue de 102,7 ± 7,9 mmHg (p = 0,6436). Las concentraciones de factor de necrosis tumoral alfa fueron similares en el grupo de preeclámpticas pre-término (98,2 ± 45,1 pg/mL) comparado con el grupo de preeclámpticas a término (96,6 ± 48,7 pg/mL; p = 0,9072). Al realizar la correlación entre los valores de factor de necrosis tumoral alfa con los valores de presión arterial se observó que no existía correlación con la presión arterial sistólica (r = 0,129; p = 0,374) ni con la de presión arterial diastólica (r = 0,158, p = 0,273). Se concluye que las concentraciones sanguíneas del factor de necrosis tumoral alfa resultaron similares en las pacientes preeclámpticas con embarazo pretérmino y a término. La correlación de las concentraciones de factor de necrosis tumoral alfa con los valores de presión arterial sistólica y diastólica resultó no significativa.Palabras claveFactor de necrosis tumoral alfa, preeclampsia, citokinas.AbstractThe objective of research was to know and compare concentrations of tumor necrosis factor alpha in term and pre-term preeclamptic patients. Fifty patients were selected. Twenty pre-term preeclamptic patients (group A) and thirty term preeclamptic patients (group B) were selected. Blood samples for tumor necrosis factor alpha was collected in all patients before labor and immediately after diagnosis of preeclampsia. There were not significant differences related to a maternal age and body mass index at the moment of collecting samples. There were significant differences between groups in gestational age (p < 0,00001). Mean value of systolic blood pressure in group A was 149.4 ± 11.3 mmHg while in patients of group B was 148.1 ± 12.3 mmHg (p = 0.7071) and mean value od diastolic blood pressure in group A was 103.8 ± 8,6 mmHg and in group B was 102.7 ± 7.9 mmHg (p = 0,6436). Tumor necrosis factor alpha concentrations were similar in study group A (98.2 ± 45.1 pg/mL) compared with group B (96.6 ± 48.7 pg/mL; p = 0.9072). When correlation was calculated between values of necrosis tumor factor alpha with values of blood pressure there was observed that there was no correlation with systolic blood pressure (r = 0.129; p = 0.374) nor diastolic blood pressure (r = 0.158; p = 0.273). It is concluded that blood concentrations of tumor necrosis factor alfa were similar in preeclamptic patients wit pre-term and term pregnacy. Correlation of tumor necrosis factor alfa with values of systolic and diastolic blood pressure were not significant.KeywordsTumor necrosis factor alpha, preeclampsia, cytokines.IntroducciónLa preeclampsia es una enfermedad multisistémica caracterizada por una alteración endotelial difusa, incremento de la resistencia vascular periférica, alteraciones de la coagulación, estrés oxidativo, dislipidemia y aumento de las citokinas producidas por los leucocitos (1).Se han propuesto diferentes hipótesis para explicar la fisiopatología de la preeclampsia: isquemia placentaria, alteraciones de las lipoproteínas plasmáticas, mala adaptación inmune y factores genéticos (2). La hipótesis de la mala adaptación inmune sugiere que la preeclampsia es causada por la inadecuada regulación de la respuesta inmune Th2 materna, lo cual lleva a un aumento de la dañina inmunidad Th1 (3,4). La disfunción endotelial observada en la preeclampsia puede ser parte de una activación incontrolada y excesiva de la respuesta inflamatoria materna al embarazo. Se ha encontrado una respuesta inmune generalizada en las preeclámpticas y se ha especulado que puede ser secundaria al aumento de las concentraciones de citokinas circulantes (5).Las citokinas son mediadores proteicos solubles involucrados en la respuesta inmune, reacciones inflamatorias, control de la respuesta inmune materna y desarrollo fetoplacentario (6). El factor de necrosis tumoral (FNT) alfa, inicialmente llamado caquectina, es un inmunoestimulante y mediador de la inflamación, capaz de promover algunos factores de crecimiento. Lo producen los macrófagos, las células T citotóxicas, la placenta y los tejidos deciduales (7). Es capaz de ejercer alguna función en la implantación y la modulación de la invasión del trofoblasto al útero. También puede inhibir in vitro la síntesis de ácido desoxiribonucleíco y la proliferación celular del trofoblasto (8-10). El FNT alfa se puede detectar en el laboratorio por inmunotinciones en los extremos proliferativos de las vellosidades, en el citotrofoblasto intersticial (aunque no en las células gigantes multinucleadas) y en el trofoblasto que penetra a las arterias espirales (11). Además, está involucrado en el mecanismo del parto (12).Su concentración plasmática en las embarazadas muestra importantes variaciones interindividuales las cuales pueden depender de la edad gestacional. Al respecto, se ha descrito un aumento paralelo de su concentración sanguínea en el segundo trimestre y luego disminuye (13). Diferentes datos sugieren que el FNT alfa contribuye a las alteraciones endoteliales y a la dislipidemia que caracterizan la fisiopatología de la preeclampsia.El objetivo de la investigación fue identificar y comparar las concentraciones de FNT en pacientes con preeclampsia a término y pre-término.MetodologíaSe realizó un estudio comparativo, transversal y prospectivo en el que se determinó la concentración de FNT, en un total de 50 pacientes preeclámpticas primigestas con diferentes edades gestacionales; 20 preeclámpticas pretérmino (grupo A) y 30 preeclámpticas a término (grupo B). Todas las pacientes eran primigestas. Se definió preeclampsia a la presencia de presión arterial mayor o igual a 140/90 mmHg, en dos tomas separadas por 6 o más horas, y proteinuria de 24 horas mayor o igual a 300 mg, o 1-2 cruces de proteinuria en un examen cualitativo, en gestaciones mayor o igual a 20 semanas. La investigación fue aprobada por el Comité de Ética de la Institución y se obtuvo consentimiento por escrito de todas las pacientes.Los criterios de exclusión fueron antecedentes de enfermedad hipertensiva preexistente (<20 semanas), hábito tabáquico, enfermedad cardiaca o renal, diabetes mellitus, embarazo múltiple y tratamiento con medicamentos que puedan alterar el metabolismo del FNT-alfa.Las muestras de sangre (10 mL), obtenidas de la vena antecubital, se recolectaron en todas las pacientes antes del parto e inmediatamente después del diagnóstico, y se las dejó coagular a temperatura ambiente. Posteriormente, a los 30 minutos de tomada la muestra, fueron centrifugadas a 4500 g por 10 minutos y almacenadas a -80°C. Se utilizó una prueba de inmunoabsorción ligada a la enzima para la medición cuantitativa del FNT-alfa en cada muestra. Todas las mediciones fueron hechas por duplicado y el promedio de las dos mediciones fue el resultado final. La sensibilidad del método fue de 3,5 pg/mL. El coeficiente de variación intra e inter-ensayo fue menor a 5%.Los valores obtenidos se presentaron como promedio ± desviación estándar. Se utilizó la prueba t de Student para muestras no relacionadas para el análisis de los grupos y la comparación de las variables continuas. Los coeficientes de correlación entre el FNT-alfa y la presión arterial sistólica y diastólica se evaluaron usando la prueba de Pearson. Se consideró un valor p< 0,05 como estadísticamente significativo.69ResultadosLas características generales de los dos grupos de pacientes se muestran en la tabla 1. No se encontraron diferencias significativas con relación a la edad materna e Índice de masa corporal. Se observaron diferencias estadísticamente significativas entre los grupos con respecto a la edad gestacional (p < 0,0001). El valor promedio de la presión arterial sistólica en el grupo A fue de 149,4 ± 11,3 mmHg mientras que en las pacientes del grupo B fue de 148,1 ± 12,3 mmHg (p = 0,7071) y el valor promedio de presión arterial diastólica en el grupo A fue de 103,8 ± 8,6 mmHg y en el grupo B fue de 102,7 ± 7,9 mmHg (p = 0,6436).Figura 1. Concentración sanguínea del factor de necrosis tumoral alfa en 20 pacientes preeclámpticas con embarazo pre-término (grupo a) y 30 mujeres preeclámpticas con embarazo a término (grupo b).No hubo diferencias estadísticamente significativa en las concentraciones de FNT-alfa entre las pacientes en el grupo de preeclámpticas de pretérmino (grupo A: 98,2 ± 45,1 pg/mL) y las preeclámpticas de término (grupo B: 96,6 ± 48,7 pg/mL; p =0,9072; Figura 1). Al realizar la correlación entre los valores de FNT-alfa con los valores de presión arterial se observó que no existía correlación con la presión arterial sistólica (r = 0,129; p = 0,374) ni con la presión arterial diastólica (r = 0,158, p = 0,273).Discusión70En el presente estudio, no se encontraron diferencias significativas en las concentraciones de FNT-alfa en las pacientes con preeclampsia a término comparado con las pacientes con preeclampsia pretérmino. Tampoco se demostraron correlaciones significativas con los valores de presión arterial sistólica y diastólica.La elevación de FNT alfa tiene un papel fundamental en el desarrollo de ciertas condiciones del embarazo como el aborto, parto pretérmino y la restricción del crecimiento intrauterino (11,12). En mujeres sanas, se piensa que el FNT alfa modula el crecimiento e invasión del trofoblasto en las arterias espirales (8). Este factor puede contribuir a la invasión placentaria anormal, daño de las células endoteliales y estrés oxidativo (4,10,14). Puede estimular la producción del interleucina (IL)-6, debido a que esta inhibe la liberación del FNT alfa (15). Tabla 1. Características generales de las 50 preeclámpticas.VariableGrupo APreeclámpticaspre-término(n = 20)Grupo BPreeclámpticasa término(n = 30)Valor de pEdad materna (años)21,7 ± 2,422,8 ± 2,60,1375Edad gestacional (semanas)35,0 ± 0,738,3 ± 1,1< 0,0001Índice de masa corporal (Kg/m2)27,4 ± 1,527,9 ± 1,80,3099Presión arterial sistólica (mmHg)149,4 ± 11,3148,1 ± 12,30,7071Presión arterial diastólica (mmHg)103,8 ± 8,6102,7 ± 7,90,6436Hasta el momento se desconoce de alguna investigación que compare en forma clara las concentraciones de factor de necrosis tumoral alfa en preeclámpticas pretérmino con aquellas que han alcanzado el término del embarazo a término El hallazgo de la presente investigación de concentraciones similares de FNT alfa en ambos grupos de pacientes sugiere que la preeclampsia puede estar asociada con activación de monocitos o linfocitos desde una fase temprana del síndrome (3). Existen varios reportes que informan de activación de los leucocitos en la preeclampsia (4,5). Una acción paracrina del factor de necrosis tumoral alfa puede contribuir a esta activación celular y explicar la respuesta inflamatoria generalizada caracterizada por la alteración en la relación Th1 / Th2 desde antes de la aparición clínica del síndrome (10,11).Existen diferentes investigaciones que han aportado evidencia sobre las concentraciones de FNT alfa en la preeclampsia. Kupferminc y col. (8) han encontrado que los valores plasmáticos de FNT alfa superiores en preeclámpticas que en las embarazadas normales. Durante el parto, las cifras fueron superiores en preeclámpticas, tanto en plasma como en líquido amniótico, pero se igualaron entre las 20 y 24 horas posteriores. Visser y col. (16) reportaron concentraciones elevadas de FNT alfa en el plasma de pacientes preeclámpticas. Schiff y col. (17), por el contrario, no encontraron diferencias significativas en las concentraciones de FNT alfa de pacientes preeclámpticas y controles pero reportaron que los valores inferiores de la citokina tanto en plasma fetal como materno cuando existe restricción intrauterina del crecimiento del feto de causa indeterminada.Se ha descrito la presencia de concentraciones elevadas de FNT alfa en el suero de embarazadas del primer trimestre que, más tarde, desarrollaron cuadro clínico de la hipertensión durante el embarazo (18). Vince y col. (6) reportaron concentraciones altas de IL-6, FNT alfa y sus receptores, las cuales fueron superiores en las pacientes con trombocitopenia. Las concentraciones plasmáticas de los receptores del FNT alfa, pueden ser un marcador clínico mejor que la misma citokina (19).La placenta hipóxica parece ser la fuente de cantidades por encima de lo normal del FNT alfa. En los embarazos normales, es necesario que el trofoblasto extravelloso exprese la proteína antígeno leucocitario humano G, a fin de modular negativamente la formación de esta citokina (20), cuya producción exagerada pudiera conducir al aborto, así como limitar la invasión trofoblástica. En la supresión de la formación del factor, tiene importancia la espermina, que a su vez, requiere de la presencia de fetuína (21). En la preeclampsia, no se expresa la proteína HLA-G en el trofoblasto extravelloso (22), por lo que se puede pensar en la presencia de un incremento del FNT alfa. La hipoxia placentaria, en condiciones experimentales, estimula la secreción de citokinas proinflamatorias. La capacidad de responder a la hipoxia con una mayor secreción de IL-1 y FNT alfa, pertenece principalmente a las vellosidades placentarias.La fuente y el inicio de la producción excesiva de FNT alfa en la preeclampsia, tanto pre-termino como a termino, es desconocida. Su origen puede ser de los monocitos, los neutrófilos o la placenta misma. Ambas clases de monocitos están activados en la preeclampsia (23). Uno de los posibles mecanismos es que en la preeclampsia uno o más factores derivados de la placenta estimulan los monocitos y/o los neutrófilos para producir las alteraciones subyacentes en el síndrome materno. La producción por la placenta puede tener algún papel fisiológico o patológico, porque el sinciciotrofoblasto de la placenta normal contiene ácido ribonucleíco mensajero del FNT alfa y FNT alfa biológicamente activo (6,24). El FNT alfa puede causar daño tisular, mediante la acción de proteasas, colagenasas o fosfolipasa A2, o a través de radicales de oxígeno (25). La afección de las células endoteliales lleva a alteraciones locales del flujo sanguíneo, obstrucción de vasos y aumento de la permeabilidad del endotelio, elementos señalados como característicos de la secreción patológica de esta citokina (25,26). Entre sus acciones también figuran la facilitación de la actividad procoagulante, por inducción del factor tisular de células endoteliales y supresión de la activación de la proteína C, y la liberación de sustancias vasopresoras, como la endotelina-1 (27) y el factor de crecimiento derivado de plaquetas (28). Todas estas alteraciones son compatibles con lo que sucede en la preeclampsia. Ejerce acciones sobre la activación plaquetaria que, desde temprano, en fases preclínicas, tiene la preeclampsia. Añadir esta sustancia al plasma rico en plaquetas, antes de la prueba de ADP, resulta en disminución de la agregación en las muestras de no gestantes y de gestantes no complicadas, pero no en las preeclámpticas (29).Los hallazgos de esta investigación son limitados por el número de preeclámpticas seleccionadas. Este estudio demostró valores similares de factor de necrosis tumoral alfa entre los dos grupos de pacientes y no pudo demostrar una relación causa efecto. Un estudio longitudinal con muestras seriadas en mujeres que desarrollan preeclampsia podría suministrar datos más concluyentes sobre la causalidad.En conclusión, las concentraciones sanguíneas del factor de necrosis tumoral alfa resultaron similares en las pacientes preeclámpticas con embarazo pretérmino y a término. La correlación de las concentraciones de factor de necrosis tumoral alfa con los valores de presión arterial sistólica y diastólica resultó no significativa.71ReferenciasSaito S, Shiozaki A, Nakashima A, Sakai M, Sasaki Y. The role of the immune system in preeclampsia. Mol Aspects Med 2007; 28:192-209. [PubMed] [Google Scholar]Ayuk P, Matijevic R. Placental ischaemia is a consequence rather than a cause of pre-eclampsia. Med Hypotheses 2006; 67:792-5. [PubMed] [Google Scholar]Mansouri R, Akbari F, Vodjgani M, Mahboudi F, Kalantar F, Mirahmadian M. Serum cytokines profiles in Iranian patients with preeclampsia. Iran J Immunol 2007; 4:179-85. [PubMed] [Google Scholar]Reyna E, Briceño C, Torres D. Inmunología, inflamación y preeclampsia. Rev Obstet Ginecol Venez 2009; 69:97-110. [Google Scholar]Borzychowski A, Sargent I, Redman C. Inflammation and pre-eclampsia. Semin Fetal Neonatal Med 2006; 11:309-16. [PubMed] [Google Scholar]Vince G, Starkey P, Austgulen R, Kwiatkowski D, Redman C. Interleukin-6, tumour necrosis factor and soluble tumour necrosis factor receptors in women with pre-eclampsia. Br J Obstet Gynaecol 1995; 102:20-5. [PubMed] [Google Scholar]Molina R, Romero T, Ruiz A. Citocinas en la fisiopatología de la preeclampsia. Gac Med Caracas 1999; 107:505-516. [Google Scholar]Kupferminc MJ, Peaceman AM, Wigton TR, Tamura RK, Rehnberg KA, Socol ML. Immunoreactive tumor necrosis factor-alpha is elevated in maternal plasma but undetected in amniotic fluid in the second trimester. Am J Obstet Gynecol 1994; 171:976-9. [PubMed] [Google Scholar]Bowen JM, ChamLey L, Mitchell MD, Keelan JA. Cytokines of the placenta and extra-placental membranes: biosynthesis, secretion and roles in establishment of pregnancy in women. Placenta 2002; 23:239-56. [PubMed] [Google Scholar]Maekawa H, Iwabuchi K, Nagaoka I, Watanabe H, Kamano T, Tsurumaru M. Activated peritoneal macrophages inhibit the proliferation of rat ascites hepatoma AH-130 cells via the production of tumor necrosis factor-alpha and nitric oxide. Inflamm Res 2000; 49:541-7. [PubMed] 72Pijnenborg R, McLaughlin PJ, Vercruysse L, Hanssens M, Johnson PM, Keith JC Jr, Van Assche FA. Immunolocalization of tumour necrosis factor-alpha (TNF-alpha) in the placental bed of normotensive and hypertensive human pregnancies. Placenta 1998; 19:231-9. [PubMed] Figueroa R, Garry D, Elimian A, Patel K, Sehgal P, Tejani N. Evaluation of amniotic fluid cytokines in preterm labor and intact membranes. J Matern Fetal Neonatal Med 2005; 18:241-7. [PubMed] [Google Scholar]Visser W, Beckmann I, Knook MA, Wallenburg HC. Soluble tumor necrosis factor receptor II and soluble cell adhesion molecule 1 as markers of tumor necrosis factor-alpha release in preeclampsia. Acta Obstet Gynecol Scand 2002; 81:713-9. [PubMed] [Google Scholar]Heikkinen J, Möttönen M, Pulkki K, Lassila O, Alanen A. Cytokine levels in midtrimester amniotic fluid in normal pregnancy and in the prediction of pre-eclampsia. Scand J Immunol 2001; 53:310-4. [PubMed] [Google Scholar]Shalaby MR, Waage A, Aarden L, Espevik T. Endotoxin, tumor necrosis factor-alpha and interleukin 1 induce interleukin 6 production in vivo. Clin Immunol Immunopathol 1989; 53:488-98. [PubMed] Visser W, Beckmann I, Bremer HA, Lim HL, Wallenburg HC. Bioactive tumour necrosis factor alpha in pre-eclamptic patients with and without the HELLP syndrome. Br J Obstet Gynaecol 1994; 101:1081-2. [PubMed] [Google Scholar]Schiff E, Friedman SA, Baumann P, Sibai BM, Romero R. Tumor necrosis factor-alpha in pregnancies associated with preeclampsia or small-for-gestational-age newborns. Am J Obstet Gynecol 1994; 170:1224-9. [PubMed] [Google Scholar]Serin IS, Ozçelik B, Basbug M, Kiliç H, Okur D, Erez R. Predictive value of tumor necrosis factor alpha (TNF-alpha) in preeclampsia. Eur J Obstet Gynecol Reprod Biol 2002; 100:143-5. [PubMed] Maymon E, Ghezzi F, Edwin SS, Mazor M, Yoon BH, Gomez R, Romero R. The tumor necrosis factor alpha and its soluble receptor profile in term and preterm parturition. Am J Obstet Gynecol 1999; 181:1142-8. [PubMed] [Google Scholar]Kanai T, Fujii T, Unno N, Yamashita T, Hyodo H, Miki A, Hamai Y, Kozuma S, Taketani Y. Human leukocyte antigen-G-expressing cells differently modulate the release of cytokines from mononuclear cells present in the decidua versus peripheral blood. Am J Reprod Immunol 2001; 45:94-9. [PubMed] [Google Scholar]Wang H, Zhang M, Soda K, Sama A, Tracey KJ. Fetuin protects the fetus from TNF. Lancet 1997; 350:861-2. [PubMed] [Google Scholar]Goldman-Wohl DS, Ariel I, Greenfield C, Hochner-Celnikier D, Cross J, Fisher S, Yagel S. Lack of human leukocyte antigen-G expression in extravillous trophoblasts is associated with pre-eclampsia. Mol Hum Reprod 2000; 6:88-95. [PubMed] [Google Scholar]Greer IA, Haddad NG, Dawes J, Johnston TA, Johnstone FD, Steel JM. Increased neutrophil activation in diabetic pregnancy and in nonpregnant diabetic women. Obstet Gynecol 1989; 74:878-81. [PubMed] [Google Scholar]Haider S, Knöfler M. Human tumour necrosis factor: physiological and pathological roles in placenta and endometrium. Placenta 2009; 30:111-23. [PubMed] [Google Scholar]Dai SM, Nishioka K, Yudoh K. Interleukin (IL) 18 stimulates osteoclast formation through synovial T cells in rheumatoid arthritis: comparison with IL1 beta and tumour necrosis factor alpha. Ann Rheum Dis 2004; 63:1379-86. [PubMed] [Google Scholar]Younes A, Aggarwall BB. Clinical implications of the tumor necrosis factor family in benign and malignant hematologic disorders. Cancer 2003; 98:458-67. [PubMed] [Google Scholar]Vemulapalli S, Chiu P, Rivelli M, Foster CJ, Sybertz EJ. Modulation of circulating endothelin levels in hypertension and endotoxemia in rats. J Cardiovasc Pharmacol 1991; 18:895-903. [PubMed] [Google Scholar]Hajjar KA, Hajjar DP, Silverstein RL, Nachman RL. Tumor necrosis factor-mediated release of platelet-derived growth factor from cultured endothelial cells. J Exp Med 1987; 166:235-45. [PubMed] [Google Scholar]Bar J, Zosmer A, Hod M, Lahav J, Elder MG, Sullivan MH. Changes in the effects of interleukin-1beta and tumor necrosis factor-alpha on platelet activation in early pregnancy. Platelets 2001; 12:453-5. [PubMed]Como citar éste artículo: Reyna-Villasmil E, Mejia-Montilla J, Reyna-Villasmil N, Torres-Cepeda D, Santos-Bolívar J, Aragón-Charry J, Factor de necrosis tumoral alfa en pacientes con preeclampsia a término y pretérmino. Avan Biomed 2012; 1: 68-72 Autor de correspondencia: Dr. Eduardo Reyna-Villasmil, Hospital Central Dr. UrquinaonaFinal Av. El Milagro.Maracaibo, Estado Zulia. VENEZUELA.Teléfono: 584162605233. Correo electronico sippenbauch@gmail.comAvances en BiomedicinaPublicación Oficial del Instituto de Inmunología ClínicaMérida-VenezuelaVolumen 1(2), Jul-Dic 2012, p 68-72Copyright: © ULA 2012Depósito Legal: PPI201102ME3935ISSN: 2244-7881Avan Biomed. 2012; 1(2): 6872.2012; 1(2): 6872. Avan Biomed.TNF en pacientes con preeclampsia. Reyna-Villasmil E y col.Reyna-Villasmil E y col. 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