Androgen Concentrations in Umbilical Cord Blood and Their Association with Maternal, Fetal and Obstetric Factors

The aim of this study was to measure umbilical blood androgen concentrations in a birth cohort using a highly specific liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay and assesses the effects of sex, labor, and gestational age on fetal androgen levels at birth. We performed a prospective cohort study of androgen concentrations in mixed arterial and venous umbilical cord serum from 803 unselected singleton pregnancies from a general obstetric population in Western Australia. Total testosterone (TT), Delta 4-androstenedione, and dehydroepiandrosterone were extracted from archived cord serum samples and measured using LC-MS/MS. SHBG was measured by ELISA; free testosterone (FT) and bioavailable testosterone (BioT) values were also calculated. Median values for all three androgens were generally lower than previously published values. Levels of TT, FT, BioT, and SHBG were significantly higher in male verses female neonates (P<0.0001), while dehydroepiandrosterone levels were higher in females (P<0.0001). Labor was associated with a significant (similar to 15-26%) decrease in median cord blood TT and FT levels (both sexes combined), but a modest (similar to 16-31%) increase in SHBG, Delta 4-androstenedione, and dehydroepiandrosterone concentrations. TT and FT were significantly negatively correlated with gestational age at delivery, while SHBG, Delta 4-androstenedione, and dehydroepiandrosterone were positively correlated. Antenatal glucocorticoid administration also had a significant effect in the multiple regression models. This is the first study to report umbilical cord androgen levels in a large unselected population of neonates using LC-MS/MS. Our findings suggest that previous studies have over-estimated cord androgen levels, and that fetal, maternal, and obstetric factors influence cord androgen levels differentially. Caution should be exercised when interpreting previously-published data that have not taken all of these factors into account.