Albeit with more and more research focus on the PE prediction in pregnancy, very few serum prediction markers have been successfully implemented in clinical practice. One of the non-negligible hurdles associated with PE was its relatively low prevalence (2–8%), requiring the biomarker tests to be highly sensitive and specific for accurate PE prediction. According to the two recent systemic reviews by De Kat et al. (19) and Mosimann et al. (20), the majority of the previous PE prediction studies, whether focusing solely on serum markers or in combination of other measurements such as maternal characters and ultrasound metrics, were performed as screening studies on the general pregnant population. For instance, even with the NICE guideline study in which 16747 women were screened, only 2.8% of the enrolled patients developed PE (21). In the prediction studies with smaller cohorts and fewer PE positive subjects, the potential pitfall of “data overfitting” was not uncommon in a quality review for first trimester risk-prediction models analysis (22). In the publication for evaluating the PE predictor of sFlt-1/PlGF by Zeisler et al., the authors narrowed down the targeting patients who presented with PE-related clinical and/or laboratory presentations (12). As a result, about 20% of those recruited subjects “with suspected preeclampsia” developed PE within 4 weeks, which significantly increased the incidence rate of PE in the prediction study and generated potentially higher power in the subsequent statistical analysis (12). Similar patient recruiting strategy was adopted in our study and a PE positive rate of 25% (49/196) was observed, with straight focus on the subgroup of pregnancy who were more likely to develop PE.
According to a meta-analysis on the sFlt-1/PlGF ratio which was considered one of the most promising serum markers in PE prediction in the past few years, the authors found this particular ratio marker had an overall sensitivity of 80%, a specificity of 92%, a positive likelihood ratio of 10.5 and a negative likelihood ratio of 0.22 after pooling 15 studies involving 534 cases and 19587 controls (23). With the valuable research accumulation, the 4-week observation window along with the 38 cut-off was applied in the Zeisler’s paper, which showed that the sFlt-1/PlGF ratio could accurately exclude the PE occurrence in the suspicious patients, with the AUC of 0.90 in the ROC analysis, compared to the AUC of 0.67 in our study with follow-up until delivery (12). However, the rest of the markers included in present study, the observation window was not yet defined previously and the delivery remained the mainstream endpoint for most of the PE prediction evaluation studies (19, 20). Interestingly, the average interval between blood sampling and PE occurrence was 7.0 weeks with our prospective cohort, which provided important clinical evidence for future refined validation studies.
The hemostatic factors such as TM and tPAI-C have been found to be related with the incidence and severity of PE decades ago (15, 16, 24). Whether or not they could be useful in PE prediction was not investigated before. In the comparison between PE-diagnosed and healthy controls, we also found the both TM (p = 0.025) and tPAI-C (p < 0.001) to be significantly elevated in the PE group (Supplementary Table 1). However, such difference was not observed in the prospective cohort (Table 2), indicating their limited values in PE predicting.
It has been reported that excessive activation and poor regulation of the complement system at the maternal-fetal interface contributed to the development of PE (25). More importantly, a recently study by Jia et al. showed that the complement factors C1q, B and H were able to differentiate early-onset severe PE with AUCs of 0.81, 0.74 and 0.68 respectively. To further evaluate their potential utility in PE prediction, the circulating levels of complement factors C1q, B and H were determined in present study. Unfortunately, no significant difference was found either in the PE-positive and PE-negative groups comparison (Table 2) or in the PE-diagnosed and healthy control groups comparison (Supplementary Table 1). Future studies about the proper clinical settings in which the complement factors can be applied should be investigated for PE related research.
The two glycoproteins, GlyFn and PAPP-A2 that were included in our testing panel, have been widely studied in preeclampsia. As an abundant protein with a wide spectrum of functions, the serum GlyFn was found to be highly elevated in both early and late pregnancies of the PE patients(14, 26). More interestingly, in a 2020 study by Huhn et al., the GlyFn was reported with a good PE predicting performance in a short term and with an AUC of 0.94 in the ROC analysis, in which a prospective cohort identified with PE-specific high-risk factors was used. In Table 2 and Supplementary Table 1, the GlyFn was significantly increased in the PE-diagnosed patients, but not in the PE-positive group who was not diagnosed with PE at the time of blood sampling but experienced PE development afterwards. This apparent discrepancy may be introduced by the difference of GlyFn measurement reagents as well the patient recruiting criteria. The other glycoprotein PAPP-A2 involved in cleaving insulin-like growth factor binding protein in placenta, was found to be helpful in diagnosing (13) and predicting PE (27). In our study, the PAPP-A2 was one of the only two independent risk factors in the Logistic regression test, indicating its potential importance in PE prediction although further validation should be conducted to refine its optimum cut-off value. Interestingly, the PAPP-A protein with similar biological functions as PAPP-A2, which was a more extensively studied marker for aneuploidies and PE prediction, was found to be decreased in most of the previous PE research works.
As one of the essential criteria for the diagnosis of preeclampsia (3), proteinuria itself was not a sufficient predictor for the occurrence or the adverse outcomes of PE (28). However, the common renal function tests such as BUN, Cre, UA and Cysc were shown to be potential valuable markers for PE diagnosis and/or prediction. For example, the BUN (29) and BUN/Cre ratio (30) were both found increased in the PE patient compared with normal controls. Cysc, the alternative test of Cre used in glomerular filtration rate estimation, was found elevated in PE patients (31) and was able to predict PE in combination of neutrophil gelatinase-associated lipocalin (AUC = 0.88) (32). Moreover, Cysc was reported as a predictor of preterm labor in severe PE, although the physiological increase of Cysc during pregnancy may pose an additional confounding factor in its clinical evaluation (33). In a prospective study with relatively large cohort (n = 9522) by Rezk et al., the serum UA was found to be a useful PE predictor for women at moderate or low risk (34). More interestingly, the elevated UA was later reported to be a risk factor for women with gestational hypertension to develop PE and deliver small-for-gestational-age infants (35). We observed similar findings that all the renal markers included (BUN, Cre, UA and Cysc) were significantly increased in the patients that developed PE before delivery. Of them, the UA, the other independent risk factor in current study, was the most promising predictor with the greatest AUC (0.73) of the ROC analyses (Fig. 2), as well as NPV of 82.1% and PPV of 48.9% (Table 3).
In conclusion, with the prospective cohort that were suspected for PE development and followed up until delivery, a series of serum markers were tested and evaluated. The angiogenic modulators of sFlt-1, PlGF, the renal function tests of BUN, Cre, UA, Cysc, and the glycoprotein PAPP-A2 were statistically changed. The UA was further found to be an independent risk factor or PE development and the most prominent predictor with the greatest AUC in the ROC analyses.