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Abstract

During our analysis of gene expression in monocytes/whole blood of women in spontaneous preterm labor (Paquette et al1Paquette A.G. Shynlova O. Kibschull M. Price N.D. Lye S.J. Comparative analysis of gene expression in maternal peripheral blood and monocytes during spontaneous preterm labor.Am J Obstet Gynecol. 2018; 218: 345.e1-345.e30Abstract Full Text Full Text PDF Scopus (38) Google Scholar) it became apparent that glucocorticoid (GC) treatment was a confounding variable that could not be corrected for using standard statistical analyses. Therefore, we utilized the publicly available data in Gene Expression Omnibus dataset GSE61880 to screen for genes that are affected by GC in vitro. While not ideal, we considered this an important analysis. Jubb et al2Jubb A.W. Hofer T.P. Hume D.A. Ziegler-Heitbrock L. The preterm labor associated ADAMTS2 gene is induced by glucocorticoids.Am J Obstet Gynecol. 2018; 219: 122-123Scopus (1) Google Scholar make valid comments regarding GC signaling in monocytes, including the identification of dose-/time-dependent increases in ADAMTS2 expression in CD14++ monocytes treated in vitro with methylprednisolone for 5 days.3Hofer T.P.J. Frankenberger M. Mages J. et al.Tissue-specific induction of ADAMTS2 in monocytes and macrophages by glucocorticoids.J Mol Med. 2008; 86: 323-332Crossref PubMed Scopus (32) Google Scholar This work, and our own analysis of later time points in GSE61880, suggest that ADAMTS2 is induced by GC in monocyte-derived macrophages and might account for the elevated ADAMTS2 expression found in our study. We addressed this in the “Limitations” section of our article (lines 790-798). In the “Discussion” section, we described several studies in which matrix metalloproteinases (MMP) (eg, MMP8, MMP9) have been used clinically as biomarkers. As a member of this family and as potential biomarker of preterm labor we noted (lines 724-726) that ADAMTS2 would need validation in a separate cohort and with proteomics data. The authors highlight other known GC-responsive genes in their data set (FKBP5 and ADORA3) that were characterized as “non-responders” in our analysis, using statistical cutoffs commonly used in bioinformatics. They state that 41% or 16/39 genes presented in Figure 1, C (line 56 of the letter)2Jubb A.W. Hofer T.P. Hume D.A. Ziegler-Heitbrock L. The preterm labor associated ADAMTS2 gene is induced by glucocorticoids.Am J Obstet Gynecol. 2018; 219: 122-123Scopus (1) Google Scholar are GC-responsive. It is important to note that this only represents those 39 labor-associated genes whose expression was common to both monocytes and whole blood. When one considers all labor-associated genes expressed in either monocytes or whole blood (n = 403, line 491) the percentage of “GC-responsive” genes is only 14%, ie, 86% of genes we identified as being differentially expressed between patients in PTL and in gestational aged-matched controls, are not GC-responsive. Overall, it is apparent that much more work must be done to disentangle the influence of GC signaling from that of PTL on blood cells. In our data set, women were administered GC at a very wide range (6 hours-34 days), with 7/13 women in this study treated 6-24 hours before blood collection (lines 431-439). Thus, neither GSE8608 nor GSE61880 data sets published by the authors of the letter can truly capture the range of GC exposure present within our study. This is important because the half-life of GC in the blood of pregnant women ranges between 3-9 hours contingent upon the steroid used. The preterm labor associated ADAMTS2 gene is induced by glucocorticoidsAmerican Journal of Obstetrics & GynecologyVol. 219Issue 1PreviewIn their study of the maternal blood leukocyte transcriptome at the time of preterm labor, Paquette et al1 report on a 5-fold increase of the ADAMTS2 transcripts as compared to term labor and go on to suggest it may be a clinically useful biomarker for this condition. The authors considered the possible impact of glucocorticoids (GC), which are given before preterm but not term delivery and they addressed this by analyzing the GSE61881 GEO data set, which we published alongside an article on the response of macrophages to GC. Full-Text PDF