2Department of Obstetrics & Gynaecology, Komfo Anokye Teaching Hospital, Kumasi, Ghana
2School of Medical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
3Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, Ghana
Methods: A total of 165 pregnant women comprising of 110 women with PE and 55 pregnant women without PE (controls) were recruited from the Obstetrics and Gynaecology department at the Komfo Anokye Teaching Hospital (KATH). Blood samples were collected and assayed for Placental Growth Factor (PIGF), soluble fms-like tyrosine kinase 1 (sFlt-1) and 8-epi-Prostaglandin F2alpha (8-epi-PGF2α) levels using ELISA kits whilst total antioxidant capacity (T-AOC), urea, creatinine and uric acid were measured spectrophotometrically.
Results: Levels of PIGF, T-AOC, PIGF/sFlt-1 ratio, PIGF/8-epiPGF2α, and sFlt-1/8-epiPGF2α were significantly reduced in early onset PE whilst sFlt-1, 8-epi-PGF2α, sFlt-1/PIGF ratio, 8-epiPGF2α/PIGF, 8-epiPGF2α/sFlt-1, spot urine protein/creatinine (Cr) ratio and Uric Acid (UA) were significantly increased in early-onset PE compared to late-onset PE (p < 0.05). In descending order, the most specific and sensitive biomarker for early onset PE were PIGF/sFlt-1 ratio (0.81; 75.0% and 97.0%; p < 0.0001) followed by 8-epiPGF2α/PIGF (0.73; 60.0% and 81.0%; p = 0.0020), sFlt-1/PIGF ratio (0.79; 55.0% and 81.0%; p < 0.0001), PIGF/8-epiPGF2α (0.71; 60.0% and 78.0%; p = 0.0010) and UA (0.70; 50% and 79.0%; p = 0.0340). At the various diagnostic cut-off of the markers, levels of PIGF, PIGF/sFlt-1, and PIGF/8-epiPGF2α were reduced whilst elevated level of sFlt-1, sFlt-1/PIGF, and 8-epiPGF2α/PIGF were significant predictors of early onset preeclampsia.
Conclusion: PIGF/sFlt-1 is a better diagnostic and predictive marker for early onset PE. Both early and late onsets PE were associated with alterations in various biochemical markers. Measurement of PIGF/sFlt-1 ratio should be included in pre-natal screening tests.
Keywords: Early-onset preeclampsia, diagnosis, biochemical markers, hypertension, proteinuria
Routine diagnosis of PE is based on measurement of Blood Pressure (BP) and urine protein analysis coupled with clinical symptoms [4]. These measurements however, have not proven to be sufficient in diagnosing the condition in its early stage due to its low specificity with respect to prediction of the course of the disease as well as maternal and perinatal outcomes [4]. Uric acid (UA), has been found to promotes endothelial dysfunction and usually correlates well with the severity of the PE [5]. However, it is not a consistent predictive marker for early detection of PE, but generally increases once the disease manifest [5]. The diagnostic accuracy of spot urine protein and Creatinine (Cr) ratio and 24 hour urine protein excretion as a measure of proteinuria in PE have also been challenged [6,7]. Most studies [7,8] recommended the former over the latter whilst results from other studies are [9] inconsistent .
Increasing evidence suggest that imbalances in angiogenic factors and oxidative stress biomarkers may be the underlying cause of PE due to its involvement in placental development [10]. Endothelial dysfunction, the hallmark of PE originates from a reduced levels of Placental Growth Factors (PIGF) with corresponding increased Vascular Endothelium Growth Factor Receptor-1 (VEGF-R1) and pro-oxidants and thus may be used as diagnostic markers in predicting PE [10,11]. We have previously established that imbalance in the levels of angiogenic regulators and oxidative stress biomarkers correlates with adverse pregnancy outcomes among PE subjects. Hence, early identification of these imbalance would alert health care givers in anticipation of adverse pregnancy outcome and thus increased surveillance during pregnancy and parturition to ameliorate the adverse outcome [12].
Currently, there is no published data on the combined diagnostic accuracy of angiogenic factors and oxidative stress markers although some studies [13,14] explored the diagnostic performance of the individual biomarkers. The need to identify highly specific and sensitive biochemical markers is essential to aid in the diagnosis of early onset PE. It is against this background that this study evaluated the individual and the combine diagnostic accuracy of angiogenic factors and oxidative stress biomarkers as well as spot urine protein: creatinine ratio and uric acid for diagnosis of early onset PE.
Serum levels of sFlt-1, PIGF and 8-epi-PGF2α were measured in duplicate using commercially available ELISA kits from R&D System Inc. (Minneapolis, MN USA). The optical density was measured at 450 nm using microplate ELISA reader (Mindray MR- 96A; Shenzhen Mindray Bio-medical electronics Co., Ltd, China). The plasma level of each factor was calculated using standard curves derived from a known concentration of the respective recombinant factors. Total Antioxidant Capacity (TAOC) reagents was obtained from Green stone Swiss Co., Ltd, China and serum levels were estimated spectrophotometrically (Mindray BA-88A; Shenzhen Bio-medical electronics Co., Ltd, China) at 593nm. This assay was measured based on the Ferric Reducing Ability of Plasma (FRAP) method as described by Benzie and Strain, (1999). All samples were analyzed in triplicate. Serum levels of urea, Creatinine (Cr), Blood Urea Nitrogen (BUN) and Uric Acid (UA) were measured spectrophotometrically using automated analyser (Mindray BA-88A; Shenzhen Bio-medical electronics Co., Ltd, China). PIGF/sFlt-1, sFlt-1/PIGF, 8-epiPGF2α/PIGF, 8-epiPGF2α/sFlt-1, PIGF/8-epiPGF2α, sFlt-1/8-epiPGF2α and Spot urine protein: Cr ratios were calculated.
As shown in Figure 1, Participants with PE had significantly elevated levels of sFlt-1(p < 0.0001), sFlt-1/PIGF ratio (p < 0.0001) and 8-epi-PGF2α (p < 0.0001) and a reduced levels of PIGF (p < 0.0001), PIGF/sFlt-1 ratio (p < 0.0001) and T-AOC (p < 0.0001) compared to controls Figure 1.
Levels of angiogenic and oxidative stress markers in early and late onset PE are shown in Figure 2. There were elevated levels of sFlt-1 (p = 0.0421), sFlt-1/PIGF ratio (p = 0.0485) and 8-epi- PGF2α (p = 0.0121) and a reduced levels of PIGF (p < 0.0001), PIGF/sFlt-1 ratio (p = 0.0071) and T-AOC (p = 0.0471) in early onset PE compared to late onset Figure 2.
As shown in Figure 3, levels of uric acid (p = 0.0590), spot urine protein: Cr ratio (p = 0.1363), 8-epiPGF2α/PIGF (p = 0.0190), and 8-epiPGF2α/sFlt-1 (p = 0.0590) were higher while PIGF/8- epiPGF2α (p = 0.0695), and sFlt-1/8-epiPGF2α (p = 0.0942) were lower in early onset compared to late onset PE Figure 3.
Analysis on Spearman rho moment correlation indicated that a statistically significant (p < 0.05) negative correlation of BP (SBP and DBP), UA, spot urine protein: Cr, parity and BMI was observed with PIGF, T-AOC and PIGF/sFlt-1 ratio compared while a statistically significant positive correlation was observed with sFlt-1, 8-epi-PGF2α, and sFlt-1/PIGF ratio (p < 0.05). The correlations of angiogenic factors and oxidative stress markers with BP (SBP and DBP) and spot urine protein: Cr ratio was significant (p < 0.05) after adjusting for age, BMI and parity. (Table 2) UA correlated significantly with oxidative stress biomarkers after adjusting for age, BMI and parity not angiogenic factors Table 2. Figure 4, Figure 5, Figure 6.
Table 3 shows the sensitivity and specificity pattern of angiogenic factors, oxidative stress biomarkers, UA and spot urine protein: Cr ratio. The diagnostic thresholds were 14.30pg/ ml for PIGF, 838.5pg/ml for sFlt-1, 404.3 0pg/ml for 8-epiPGF2α, 0.38 mmol/l for T-AOC, 18.00 for sFlt-1/PIGF ratio, 0.60 for PIGF/ sFlt-1 ratio, 7.2 for 8-epiPGF2α/PIGF, 0.48 for 8-epiPGF2α/sFlt- 1, 0.14 for PIGF/8-epiPGF2α, 1.13 for sFlt-1/8-epiPGF2α , 11.60 for spot-urine protein: Cr and 440.00umol/l for UA. However, the most accurate, specific and sensitive marker was PIGF/sFlt-1 ratio (0.81; 75.0% and 97.0%; p < 0.0001) followed by sFlt-1/ PIGF ratio (0.79; 81.0% and 55.0%; p < 0.0001), 8-epiPGF2α/
Variables |
Total (n=165) |
Controls (n=55) |
PE (n=110) |
p-value |
Age (years) |
29.78 ± 0.40 |
29.99 ± 0.44 |
29.85 ± 0.53 |
0.710 |
Gestational age (weeks) |
36.12 ± 0.71 |
38.09 ± 0.37 |
36.02 ± 0.27 |
<0.0001 |
Parity |
0.9455 |
|||
Nulliparous |
80 (48.5%) |
25(45.5%) |
55(50.0%) |
|
Primiparous |
32 (19.4%) |
12(21.8%) |
20(18.2%) |
|
Multiparous |
53 (32.1%) |
18(32.7%) |
35(31.9%) |
|
Gravidity |
0.0041 |
|||
Primigravida |
60 (36.4%) |
12(21.8%) |
48(43.6%) |
|
Secundigravida |
57 (34.5%) |
17(30.9%) |
40(36.4%) |
|
Multigravida |
48 (29.0%) |
26(47.3%) |
22(20.0%) |
|
Economic income (GHS) |
|
|
|
0.0013 |
<500 GHS (low income) |
134(81.2%) |
33(60.0%) |
101(91.8%) |
|
500-1000 GHS (middle income) |
26(15.8%) |
18(32.7%) |
8(7.3%) |
|
>1000 (high income) |
5(3.0%) |
4(7.3%) |
1(0.9%) |
|
Family history of HTN |
|
|||
Yes |
28 (16.9%) |
1(1.8%) |
27(24.5%) |
<0.0001 |
Previous Caesarean section |
|
|||
Yes |
30 (18.2%) |
6(10.9%) |
24(21.8%) |
0.0484 |
Early gestation BMI (Kg/m2) |
23.49 ± 5.52 |
21.07 ± 7.53 |
25.90 ± 6.51 |
0.0181 |
SBP (mmHg) |
139.75 ± 1.32 |
114.30 ± 0.99 |
165.20 ± 1.64 |
<0.0001 |
DBP (mmHg) |
88.97 ± 1.04 |
69.33 ± 0.96 |
108.60 ± 1.12 |
<0.0001 |
Urea (mmol/L) |
4.03 ± 0.40 |
1.99 ± 0.11 |
6.07 ± 0.69 |
< 0.0001 |
Cr (umol/l) |
84.48 ± 10.53 |
54.77 ± 1.77 |
114.2 ± 19.30 |
0.0284 |
BUN/Cr |
17.67 ± 0.78 |
11.25 ± 0.23 |
24.08 ± 1.32 |
< 0.0001 |
Uric acid (umol/l) |
352.3 ± 0.11 |
303.0 ± 7.37 |
401.7 ± 9.85 |
< 0.0001 |
Spot urine protein (g/l) |
1.03 ± 0.06 |
0.01 ± 0.00 |
2.05 ± 0.11 |
<0.0001 |
PIGF |
sFlt-1 |
8-epi-PGF2α |
T-AOC |
sFlt-1/PIGF |
PIGF/sFlt-1 |
|
SBP |
r= -0.688; p<0.0001 |
r= 0.644; p<0.0001 |
r= 0.627; p<0.0001 |
r= -0.660; p<0.0001 |
r= 0.702; p<0.0001 |
r= -0.451; p<0.0001 |
r= -0.690; p<0.0001 |
r= 0.628; p<0.0001 |
r= 0.534; p<0.0001 |
r= -0.674; p<0.0001 |
r= 0.352; p<0.0001 |
r= -0.448; p<0.0001 |
|
|
|
|
|
|
|
|
DBP |
r= -0.694; p<0.0001 |
r= 0.647; p<0.0001 |
r= 0.677; p<0.0001 |
r= -0.684; p<0.0001 |
r= 0.709; p<0.0001 |
r= -0.459; p<0.0001 |
r= -0.708; p<0.0001 |
r= 0.635; p<0.0001 |
r= 0.575; p<0.0001 |
r= -0.699; p<0.0001 |
r= 0.367; p<0.0001 |
r= -0.453; p<0.0001 |
|
|
|
|
|
|
|
|
UA |
r= -0.132; p= 0.107 |
r= 0.208; p=0.011 |
r= 0.390; p= 0.005 |
r= -0.249; p=0.034 |
r= 0.174; p=0.0330 |
r= -0.116; p=0.0330 |
|
r= -0.140; p= 0.088 |
r= 0.111; p=0.050 |
r= 0.277; p= 0.021 |
r= -0.266; p=0.024 |
r= 0.417; p=0.073 |
r= -0.120; p=0.1440 |
|
|
|
|
|
|
|
Spot urine protein/Cr |
r= -0.219; p= 0.007 |
r= 0.226; p=0.010 |
r= 0.139; p= 0.019 |
r= -0.190; p=0.016 |
r= 0.336; p=0.011 |
r= -0.426; p=0.001 |
|
r= -0.307; p= 0.008 |
r= 0.231; p=0.030 |
r= 0.163; p= 0.047 |
r= -0.209; p=0.021 |
r= 0.322; p=0.035 |
r= -0.393; p=0.017 |
|
|
|
|
|
|
|
Parity |
r= 0.021; p= 0.794 |
r= -0.021; p= 0.794 |
r= -0.081; p=0.3250 |
r= 0.080; p=0.330 |
r= -0.005; p=0.949 |
r= 0.037; p=0.651 |
|
|
|
|
|
|
|
BMI |
r= -0.327; p<0.0001 |
r= 0.299; p<0.0001 |
r= 0.271; p=0.001 |
r= -0.303; p<0.0001 |
r= 0.332; p<0.0001 |
r= -0.221; p=0.0070 |
|
|
|
|
|
|
|
AGE
|
r= -0.205; p= 0.0371 |
r= 0.319; p= 0.0038 |
r= 0.279; p= 0.0150 |
r= -0.226; p= 0.0193 |
r= 0.397; p= 0.0026 |
r= -0.146; p= 0.0497 |
Table 4 shows the logistic regression of biomarkers for early onset preeclampsia. After adjusting for age, early gestation BMI and parity, PIGF levels <14.3 pg/ml was significantly (p = 0.0135) associated with 7 times increase odds, sFlt-1 levels >838.5 pg/ ml was significantly (p = 0.0309) associated 1.61 times increase odds, sFlt-1/PIGF ratio > 18.0 was significantly (p = 0.002) associated with 2.96 times increase odds, PIGF/sFlt-1 ratio <0.60 was significantly (p < 0.0001) associated with 35.08 times increase odds, 8-epiPGF2α/PIGF ratio >7.2 was significantly (p = 0.009) associated with 1.74 times increase odds, and PIGF/8- epiPGF2α ratio <0.14 was significantly (p = 0.0212) associated with 1.61 times increase odds for early onset PE Table 4.
Biomarkers |
Threshold value |
Sensitivity(95%CI) |
Specificity(95%CI) |
PPV |
NPV |
LR+ |
LR- |
Diagnostic Accuracy |
p-value |
PIGF |
14.30 pg/ml |
0.44(0.28-0.61) |
0.90(0.68-0.98) |
0.88 |
0.50 |
4.38 |
0.63 |
0.62 |
0.0050 |
sFlt-1 |
838.50 pg/ml |
0.50(0.34-0.66) |
0.85(0.63-0.95) |
0.84 |
0.52 |
3.33 |
0.59 |
0.64 |
0.0390 |
8-epiPGF2α |
404.30 pg/ml |
0.50(0.34-0.66) |
0.80(0.58-0.92) |
0.80 |
0.50 |
2.50 |
0.63 |
0.62 |
0.0470 |
T-AOC |
0.38 mmol/l |
0.50(0.33-0.67) |
0.80(0.57-0.92) |
0.79 |
0.52 |
2.50 |
0.63 |
0.62 |
0.1350 |
sFlt-1/PIGF |
18.00 |
0.81(0.64-0.91) |
0.65(0.34-0.74) |
0.78 |
0.71 |
2.15 |
0.06 |
0.79 |
< 0.0001 |
PIGF/sFlt-1 |
0.60 |
0.97(0.82-1.00) |
0.75(0.53-0.89) |
0.84 |
0.92 |
3.25 |
0.25 |
0.81 |
< 0.0001 |
8-epiPGF2α/PIGF |
7.20 |
0.81(0.64-0.91) |
0.60(0.39-0.78) |
0.76 |
0.67 |
2.03 |
0.31 |
0.73 |
0.0020 |
8-epiPGF2α/sFlt-1 |
0.48 |
0.56(0.39-0.72) |
0.75(0.53-0.89) |
0.78 |
0.52 |
2.25 |
0.58 |
0.63 |
0.0690 |
PIGF/8-epiPGF2α |
0.14 |
0.78(0.60-0.89) |
0.60(0.39-0.78) |
0.76 |
0.63 |
1.95 |
0.36 |
0.71 |
0.0010 |
sFlt-1/8-epiPGF2α |
1.13 |
0.91(0.75-0.97) |
0.15(0.05-0.37) |
0.63 |
0.50 |
1.07 |
0.63 |
0.62 |
0.0680 |
Spot-urine protein: Cr |
11.60 |
0.93(0.77-0.99) |
0.16(0.09-0.26) |
0.32 |
0.85 |
1.11 |
0.42 |
0.39 |
0.7260 |
UA |
440.00umol/l |
0.50(0.33-0.67) |
0.79(0.67-0.86) |
0.50 |
0.79 |
2.33 |
0.64 |
0.70 |
0.0340 |
Biomarkers |
Threshold value |
AOR (95% CI) |
p-value |
PIGF |
<14.3 pg/ml |
7.00(1.386 to 35.36) |
0.0135 |
sFlt-1 |
>838.5 pg/ml |
1.61(1.031-2.517) |
0.0309 |
8-epiPGF2α |
>404.3 pg/ml |
0.68 (0.446-1.045) |
0.0792 |
T-AOC |
<0.38 mmol/l |
0.81(0.701-0.984) |
0.0918 |
sFlt-1/PIGF |
>18.0 |
2.69(1.438-5.053) |
0.0020 |
PIGF/sFlt-1 |
<0.60 |
35.08(24.83-42.08) |
<0.0001 |
8-epiPGF2α/PIGF |
>7.2 |
1.74(1.148 - 2.632) |
0.0090 |
8-epiPGF2α/sFlt-1 |
>0.48 |
0.74(0.489-1.105) |
0.1394 |
PIGF/8-epiPGF2α |
<0.14 |
1.61(1.074-2.425) |
0.0212 |
sFlt-1/8-epiPGF2α |
>1.13 |
1.10(0.748 to 1.619) |
0.6240 |
Spot urine protein : Cr ratio |
>1.60 |
0.501(0.325-0.817) |
0.0718 |
UA |
>440 µmol/l |
1.001(0.812-1.215) |
0.0514 |
This case-control study evaluated the diagnostic accuracy of sFlt-1/PIGF in the second and third trimester of pregnancy. This study observed that using sFlt-1/PIGF proved to be sensitive (81.0%) with PPV of 78.0% and NPV of 71.0% but was associated with poor specificity (55.0%). Above the threshold value of 18.0 for sFlt-1/PIGF, PE patients were 2.69 times more likely to develop early onset PE. The current study for the first time identified the ratios of 8-epiPGF2α/PIGF and PIGF/8-epiPGF2α as significant diagnostic markers for early onset PE with sensitivity (81.0% vs 78%), specificity (60.0% vs 60.0%), PPV (76% vs 76%) and NPV (67% vs 63%). At a threshold of 7.2 and above for 8-epiPGF2α/ PIGF ratio and 0.14 and below for PIGF/8-epiPGF2α, PE patient are 1.74 times and 1.61 times respectively more likely to develop early onset PE. 8-epiPGF2α/PIGF ratio gave a better diagnostic value for early onset PE compared to previously known sFlt-1/ PIGF ratio. However, at the threshold value sFlt-1/PIGF ratio was more likely to predict early onset PE compared to 8-epiPGF2α/ PIGF ratio (2.69 times vs 1.74 times). The combine effect of angiogenic factors and oxidative stress biomarkers indicates the synergic role they play in the pathogenesis of PE. Further studies are therefore needed to prove the diagnostic potency of 8-epiPGF2α/PIGF.
The individual markers of angiogenic factor (PIGF and sFlt- 1) and oxidative stress biomarker (8-epiPGF2α and T-AOC) proved to be highly specific but poorly sensitive (Table 3) thus, their usefulness in early onset PE may be unreliable. The onset threshold levels for sFlt-1 are relatively higher in earlier gestations and begins to deviate from the reference range in preeclamptic patients suggesting their low levels in early onset preeclampsia [19]. Below <14.3 pg/ml of PIGF, PE patients are 7.0 times more likely to develop early onset while sFlt-1 levels >838.5 pg/ml was associated with 1.61 times increase odds. The finding indicates that PIGF can be considered as better predictor for early than sFlt-1. This finding is consistent with a study conducted by Ohkuchi. et al, [20]. This outcome may explain the role PIGF plays in the pathogenic process in the development of preeclampsia. Based on these findings it may be suggested that, sFlt-1 should be considered as a late marker of pre-eclampsia than an early onset marker.
This study also observed that spot urine protein: Cr proved to be highly sensitive (93.0%) but lack specificity (16.0%) with poor diagnostic accuracy (0.39). A recent study by Baba. et al, among normotensive pregnant women showed a significant correlation between the Protein/Cr ratio and 24-h urine protein level [23]. Other previous studies [4,6,8] accredit spot urine protein: Cr to be better marker for identifying proteinuria in PE. However, in this study, spot urine protein: Cr ratio was 50% less likely to predict early onset PE [aOR =0.501(0.325-0.817)]. This result suggest that using spot urine protein: Cr ratio could identify any form of proteinuria related condition but lacks specificity to specific proteinuria condition. Thus incorporating this marker in routine maternal and fetal investigation will only be useful to identify proteinuria and thus not a better marker for early onset PE. However, further studies may be needed to explore it usefulness.
Using UA as a diagnostic tool and predictive factor for the development of pre-eclampsia, at a significant threshold value of 440 μmol/l, the sensitivity, specificity, PPV, NPV and diagnostic accuracy were 50.0%, 79%, 50.0%, 79.0% and 0.70 respectively. However UA may not be a better predictive tool because at levels greater than threshold value it is indecisive [(aOR = 1.001(0.812- 1.215)] to predict early onset PE. Previous study indicates that plasma levels of UA usually increase once the disease manifests and it's more likely to correlate with disease severity. UA correlated significantly with oxidative stress biomarkers but not angiogenic factors indicating that mechanism of elevated UA in PE does not act through the angiogenic pathway.
The main limitation of the current study is the inability to conduct a longitudinal cohort study which could have assessed the changes over time, however, findings from this study will serve as a baseline for further studies to address this interest.
Performed the experiments: Enoch O Anto, William K B A Owiredu, Samuel Asamoah Sakyi, Linda A Fondjo and Cornelius A Turpin.
Analyzed the data: Enoch O Anto, Linda A Fondjo, and Richard K D Ephraim Wrote the first draft of the manuscript: Enoch O Anto, Samuel Asamoah Sakyi, and William K B A Owiredu.
Contributed to the writing of the manuscript: Enoch O Anto, Samuel Asamoah Sakyi, William K B A Owiredu, Cornelius A Turpin and Richard K D Ephraim. Agree with manuscript results and conclusions: Enoch O Anto, Samuel Asamoah Sakyi, Linda A Fondjo, WKBAO and Richard K D Ephraim.
Enrolled Patients: Enoch O Anto, Samuel Asamoah Sakyi, Linda A Fondjo and Cornelius A Turpin. All authors read and approved the final manuscript.
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