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NX Prenatal Publishes Study on Preterm Birth Biomarkers

NEW YORK (GenomeWeb) – NX Prenatal has published a study in the American Journal of Obstetrics and Gynecology looking at the ability of protein biomarkers extracted from exosomes to predict spontaneous preterm delivery (SPTB).

In the study, portions of which the company presented at last month's Society for Maternal-Fetal Medicine's Annual Pregnancy Meeting in Atlanta, the researchers identified more than 60 proteins that appeared useful in predicting preterm birth and developed a number of three-marker panels that were able to identify women who would go on to spontaneously deliver before 34 weeks with sensitivity and specificity of above 80 percent and area under the curve of above .80 when measured at between 10 and 12 weeks gestation.

The study looked at samples from 25 singleton cases of SPTB occurring at or before 34 weeks, comparing them to 50 normal deliveries. For their proteomic analyses the researchers contracted with Swiss targeted proteomics firm Biognosys, which used multiple-reaction monitoring mass spec on a Thermo Fisher Scientific TSQ Vantange triple quadrupole to measure levels of 132 candidate proteins, 62 of which showed usefulness in detecting SPTB.

Unlike in typical biomarker experiments, these proteins were exosome-bound proteins rather than plasma proteins. Exosomes are membrane-bound particles released by cells that contain molecular content including proteins and nucleic acids from their cell of origin. By focusing their analysis on proteins contained in exosomes, NX Prenatal hopes to reduce the complexity of their sample and up the sensitivity of their analysis.

Taking the 62 potential markers, the researchers applied a differential dependency network analysis, identifying various SPTB-linked co-expression patterns and finding that certain gene ontology categories including inflammation, wound healing, coagulation, and steroid metabolism were overrepresented among these co-expression subnetworks and that these subnetworks consisted of a total of 20 unique proteins.

Using these 20 proteins, the researchers generated a series of two- and three-protein linear models for predicting SPTB. Among the top classifiers were models including the proteins HEMO, KLKB1, A2MG, IC1, and TRFE, all of which "are consistent with known mechanisms of preterm birth and adverse outcomes in pregnancy and parturition," the authors wrote.

The researchers limited their analysis to the two- and three-protein linear models to avoid overfitting, given their relatively small sample size. However, they noted plans to conduct larger studies to test more markers simultaneously, which could further improve performance. In an interview last month with GenomeWeb, NX Prenatal CEO Brian Brohman said he believed that the final version of the test would probably feature somewhere between eight and 12 proteins.