BACKGROUND: Intra-amniotic inflammation is associated with poor neonatal outcome independent of prematurity. We applied proteomic technology (SELDI: surface-enhanced laser desorption ionisation) to identify the proteomic profile of intra-amniotic inflammation. DESIGN: One hundred and four samples of amniotic fluid were analysed. In stage 1, samples from patients with symptoms of preterm labour and known outcomes were tested to identify the characteristic profile for inflammation. We extracted the profile using a novel, stepwise logical approach comparing SELDI tracings from patients who delivered preterm and had intra-amniotic inflammation in response to infection to the tracings of patients who had symptoms of preterm labour but delivered at term. In stage 2, we applied the algorithm to samples from pregnancies whose outcomes were unknown to the investigators. SETTING: North-American university in collaboration with Ciphergen field demonstration laboratory. SAMPLE: One hundred and four samples of human amniotic fluid from transabdominal amniocentesis. METHODS: SELDI (surface-enhanced laser desorption ionisation) and Mass Restricted analysis, a novel algorithm for extraction of clinical and biological relevant biomarkers from proteomic SELDI tracings. MAIN OUTCOME MEASURE: Presence of intra-amniotic inflammation and/or infection leading to preterm birth. RESULTS: Patients with intra-amniotic inflammation that deliver preterm have a distinctive amniotic fluid proteomic profile of three or four of the following proteins: neutrophil defensins-1 and -2, and calgranulins A and C. Based on the presence or absence of these biomarkers, we devised the mass restricted (MR) score ranging from 0 (all biomarker peaks absent) to 4 (all biomarker peaks present). In stage 1, MR score > 2 had 92.9% sensitivity (95% CI 76.5-98.9) and 91.8% specificity (95% CI 80.4-97.7) for detection of intra-amniotic inflammation. In blind testing (stage 2), MR score > 2 provided 100% specificity and sensitivity (95% CI 100-100). A MR score > 2 was associated with imminent preterm delivery. CONCLUSION: Proteomic analysis of amniotic fluid reveals the presence of biomarkers characteristic of intrauterine inflammation. This methodology may identify the subgroup of patients that might benefit most from interventions to prevent fetal damage in utero.
BACKGROUND:Intra-amniotic inflammation is associated with poor neonatal outcome independent of prematurity. We applied proteomic technology (SELDI: surface-enhanced laser desorption ionisation) to identify the proteomic profile of intra-amniotic inflammation. DESIGN: One hundred and four samples of amniotic fluid were analysed. In stage 1, samples from patients with symptoms of preterm labour and known outcomes were tested to identify the characteristic profile for inflammation. We extracted the profile using a novel, stepwise logical approach comparing SELDI tracings from patients who delivered preterm and had intra-amniotic inflammation in response to infection to the tracings of patients who had symptoms of preterm labour but delivered at term. In stage 2, we applied the algorithm to samples from pregnancies whose outcomes were unknown to the investigators. SETTING: North-American university in collaboration with Ciphergen field demonstration laboratory. SAMPLE: One hundred and four samples of human amniotic fluid from transabdominal amniocentesis. METHODS: SELDI (surface-enhanced laser desorption ionisation) and Mass Restricted analysis, a novel algorithm for extraction of clinical and biological relevant biomarkers from proteomic SELDI tracings. MAIN OUTCOME MEASURE: Presence of intra-amniotic inflammation and/or infection leading to preterm birth. RESULTS:Patients with intra-amniotic inflammation that deliver preterm have a distinctive amniotic fluid proteomic profile of three or four of the following proteins: neutrophil defensins-1 and -2, and calgranulins A and C. Based on the presence or absence of these biomarkers, we devised the mass restricted (MR) score ranging from 0 (all biomarker peaks absent) to 4 (all biomarker peaks present). In stage 1, MR score > 2 had 92.9% sensitivity (95% CI 76.5-98.9) and 91.8% specificity (95% CI 80.4-97.7) for detection of intra-amniotic inflammation. In blind testing (stage 2), MR score > 2 provided 100% specificity and sensitivity (95% CI 100-100). A MR score > 2 was associated with imminent preterm delivery. CONCLUSION: Proteomic analysis of amniotic fluid reveals the presence of biomarkers characteristic of intrauterine inflammation. This methodology may identify the subgroup of patients that might benefit most from interventions to prevent fetal damage in utero.
Authors: Carl P Weiner; Clifford W Mason; Yafeng Dong; Irina A Buhimschi; Peter W Swaan; Catalin S Buhimschi Journal: Am J Obstet Gynecol Date: 2010-05 Impact factor: 8.661
Authors: Sonya S Abdel-Razeq; Irina A Buhimschi; Mert O Bahtiyar; Victor A Rosenberg; Antonette T Dulay; Christina S Han; Erika F Werner; Stephen Thung; Catalin S Buhimschi Journal: Obstet Gynecol Date: 2010-08 Impact factor: 7.661
Authors: M Sean Esplin; Karen Merrell; Robert Goldenberg; Yinglei Lai; Jay D Iams; Brian Mercer; Catherine Y Spong; Menachem Miodovnik; Hygriv N Simhan; Peter van Dorsten; Mitchell Dombrowski Journal: Am J Obstet Gynecol Date: 2010-11-11 Impact factor: 8.661
Authors: Sarah Y Lee; Irina A Buhimschi; Antonette T Dulay; Unzila A Ali; Guomao Zhao; Sonya S Abdel-Razeq; Mert O Bahtiyar; Stephen F Thung; Edmund F Funai; Catalin S Buhimschi Journal: J Immunol Date: 2011-01-31 Impact factor: 5.422
Authors: Michael G Gravett; Archana Thomas; Kimberly A Schneider; Ashok P Reddy; Surendra Dasari; Thomas Jacob; Xinfang Lu; Matthew Rodland; Leonardo Pereira; Drew W Sadowsky; Charles T Roberts; Miles J Novy; Srinivasa R Nagalla Journal: J Proteome Res Date: 2007-01 Impact factor: 4.466
Authors: Margaret A Baumbusch; Catalin S Buhimschi; Emily A Oliver; Guomao Zhao; Stephen Thung; Kara Rood; Irina A Buhimschi Journal: Cytokine Date: 2016-03-05 Impact factor: 3.861