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Premature births from inflammation and infection rapidly detected by proteomics technology

A combination of four proteins that result from inflammation and infection and lead to premature birth can be rapidly and accurately detected in the amniotic fluid of pregnant women using proteomics technology, Yale researchers report in two studies in the February issue of British Journal of Obstetrics and Gynecology.

Using proteomics science, the Yale team, in collaboration with two other academic institutions, developed a novel method called MR scoring to discriminate healthy from diseased women in whom preterm delivery is impending and the health of the fetus is in danger. MR scoring relies on identification of a group of proteins that serve as biomarkers characteristic to women who will deliver preterm. The proteins detected are Human neutrophil defensin 1, Human neutrophil defensin 2, Calgranulin C and Calgranulin A.

"We are probably at a turning point in the history of preterm labor diagnosis," said Irina Buhimschi, M.D., research scientist in the Department of Obstetrics & Gynecology and Reproductive Sciences. "While many proteins are present in the amniotic fluid, not all are biomarkers with diagnostic significance."

About 50 percent of women who deliver prematurely have evidence of inflammation in the amniotic fluid. In the current study, Buhimschi and co-authors analyzed stored samples of amniotic fluid from 107 women, some diagnosed with rupture of the membranes or twins and eventually delivered prematurely. The sensitivity and specificity of the MR score in identifying women who had infection and inflammation and delivered earlier reached 100 percent. The four biomarkers are necessary and sufficient to separate between sick and healthy patients.

Buhimschi said the current "gold standard" for infection consists of amniotic fluid culture, which takes days to obtain results. A proteomic diagnostic test for infection and inflammation could probably be performed much faster than the current available laboratory tests. Other cu
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Contact: Karen N. Peart
karen.peart@yale.edu
203-432-1326
Yale University
4-Feb-2005


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