Strengths and limitations
To our knowledge, this is the first cohort study evaluating the predictive potential of GCF-PLAP concentrations for early-pregnancy risk assessment of PE. These data are consistent with and extend our previous observations99. PLAP concentrations in GCF were significantly greater than those measured in paired plasma samples. In women who subsequently developed PE, GCF-PLAP concentrations were 3- to 6-fold greater than those measured in matched plasma samples. These findings suggest that potential biomarkers of obstetrical diseases can be concentrated in GCF, highlighting the opportunity to use placental biomarkers measured in GCF to improve the performance of prediction models.
Currently, there is considerable debate about the use multivariate algorithms for the prediction of PE, and most obstetric societies do not recommend their use as an screening strategy in routine obstetrical care78,88–94, arguing the lack of solid evidence of external validation and/or randomization of many of such existing models84,128,129. In fact, many societies only recommend the use of maternal risk factors to identify those women who may be at increased risk of PE. Nevertheless, this screening approach based on identification of clinical risk factors has several limitations, especially considering their limited detection capabilities. When only clinical assessment of risk factors is used to identify patients at risk of PE, a minor proportion of PE cases are detected (approximately 30 - 40% of preterm PE and 20 to 35% of late PE cases)130–133, with very high rates of false-positive screening results. In contrast, uterine artery pulsatility index with or without the combination of several maternal risk factors, measured at 11 to 14 weeks of, increases the detection rates of early PE (<34 weeks of gestation) to about 40% to 65% at a fixed false positive rate of 5%, and with an overall sensitivity for early PE of nearly 50%134–152. The most recently developed predictive algorithms, using different combinations of maternal risk factors, biophysical variables like mean maternal blood pressure, uterine artery pulsatility index, and maternal plasmatic biomarkers like placental growth factor and/or pregnancy-associated plasma protein A at 11-14 weeks of gestation, have consistently demonstrated detection rates of preterm PE over nearly 70% at false-positive rates of 10%153–167. The results obtained in this study further support the use of multiparametric algorithms for improving the prediction of PE. Future studies are needed to confirm our results and to address the predictive capabilities of CGF-PLAP concentration alone and/or in combination with more variables and risk factors, such as the uterine artery Doppler value, to further increase the performance of the algorithm.
Regarding the link between periodontal disease and the risk of PE, our study did not confirm the association between periodontal diagnoses and PE that had been previously described in the literature108–112. These results, however, should be interpreted with caution given that the present study was powered to determine the association between GCF-PLAP concentrations and PE but not the association between PE and periodontal diagnosis. Moreover, this link has not been confirmed in all populations120,121. In fact, in a cohort study conducted in 1,562 pregnant women from Argentina122, no significant association between periodontal disease and PE was identified. In addition, in our study, periodontal disease was assessed during early pregnancy. It is known that periodontal disease usually worsens during pregnancy123–125 and that its evaluation at a later stage of pregnancy may be more related to the development of PE.