Objective
We sought to evaluate amniotic fluid brain natriuretic peptide (BNP) levels as a biomarker of recipient twin (RT) cardiomyopathy (RTCM) in twin-twin transfusion syndrome.
Study Design
Amniotic fluid samples were obtained from 157 twin-twin transfusion syndrome RTs and from 6 singletons (controls) from 2007 through 2009. N-terminal prohormone BNP (NT-proBNP) levels were quantified by enzyme-linked immunosorbent assay. RTCM was classified as mild (IIIA), moderate (IIIB), or severe (IIIC) by fetal echocardiography. The relationship between NT-proBNP and RTCM was evaluated using analysis of variance. The ability of NT-proBNP to predict moderate or greater RTCM was evaluated by receiver operating characteristic analysis.
Results
There is a significant positive correlation between NT-proBNP levels and worsening RTCM (r = 0.33; P < .001). NT-proBNP thresholds of 569 fmol/mg and 369 fmol/mg had a sensitivity of 70% and 87%, and specificity of 67% and 42%, respectively, in predicting moderate or greater RTCM.
Conclusion
This is the first large case series that demonstrates a relationship between NT-proBNP and RTCM. This pathophysiologic insight supports ongoing efforts to develop screening biomarkers.
Twin-twin transfusion syndrome (TTTS) is a serious complication in about 10-20% of monozygous twin gestations. TTTS is a progressive disease of unknown etiology but a requirement for interplacental vascular anastomoses leading to functional and structural cardiac changes in the recipient twin (RT). In contrast, in the donor twin, Doppler echocardiographic changes are rare and ventricular function and atrioventricular valve competence is usually preserved.
Specific cardiac changes in the RT may include: unilateral or bilateral ventricular hypertrophy, increased cardiothoracic ratio, ventricular dilation, tricuspid regurgitation and mitral regurgitation, systolic dysfunction, and in some cases right ventricular outflow tract obstruction and pulmonary valve stenosis or atresia. It is suspected that these changes result from either or both RT hypervolemia and systemic hypertension. Evidence of fetal hypertension is based on tricuspid regurgitation jet velocity estimates of right ventricular systolic pressure, which are often elevated to >50 mm Hg; estimates of >100 mm Hg have been observed. Consistent with fetal hypertension in TTTS is the evidence of hormonal and vasoactive adaptive changes including a 2.5-fold increase in RT endothelin (ET)-1 level (a potent vasoconstrictor) and up-regulation of the renin–angiotensin system. Evidence of increased cardiac synthesis and secretion of natriuretic peptides in RT has been described. Bajoria et al demonstrated that RTs in TTTS have higher concentrations of atrial natriuretic peptide, brain natriuretic peptide (BNP), and ET-1 than their donor co-twin or monochorionic-diamniotic twins without TTTS. These cardiovascular changes are a major cause of RT mortality. We have previously shown that cardiac function in the RT can predict survival especially after selective fetoscopic laser photocoagulation (SFLP). Furthermore, RTs with cardiac dysfunction are at increased risk of developing cerebral palsy. The ability to reliably identify RT cardiomyopathy (RTCM) is assuming an increasingly important role in assessment, risk stratification, and counseling in TTTS. Identification of a cardiac biochemical biomarker that reflects the severity of RTCM would be valuable, particularly when detailed fetal echocardiography is not readily available.
In recent years, assay of cardiac serum biomarkers such as BNP or its precursor N-terminal (NT)-prohormone BNP (proBNP) have come to play an important prognostic, diagnostic, as well as therapeutic role in cardiac diseases, especially heart failure.
These natriuretic peptides are endogenous hormones that are released by the heart in response to myocardial stretch, volume overload, hyperosmolality, hypoxia, and vasoconstrictors, such as angiotensin II, vasopressin, and ET-1. Natriuretic peptides regulate blood pressure and body fluid homeostasis through their diuretic, natriuretic, vasorelaxant, and antihypertensive effects as well exerting antiproliferative effects on cardiovascular/mesenchymal tissue. Little information is known about the role of the natriuretic system in TTTS.
The objective of this study was to evaluate amniotic fluid NT-proBNP levels as a screening biomarker of RTCM in TTTS.
Materials and Methods
A retrospective study of all patients with TTTS treated with SFLP between 16-26 weeks of gestation was performed. All patients were treated with SFLP either as initial therapy or after a failed trial of serial amnioreduction at the Fetal Care Center of Cincinnati from January 2007 through January 2009. A failed trial of amnioreduction was defined as evidence of progression of fetal echocardiography despite amnioreduction. This study was approved by the institutional review board of Cincinnati Children’s Hospital and Medical Center.
Clinical records including maternal demographics, medical history, and neonatal and fetal survival data were reviewed in all patients. Overall fetal survival was defined as total number of fetuses alive at birth/total number of expected fetuses to be born. Patient evaluation pre- and post-SFLP included fetal echocardiography, magnetic resonance imaging, and comprehensive fetal anatomical survey including Doppler evaluation of ductus venosus, middle cerebral artery, and umbilical vein and artery. Abnormal Doppler flow studies were defined as absent or reverse end-diastolic flow in midcord of the umbilical artery in the absence of fetal or maternal breathing or reversal flow in ductus venosus or pulsatile umbilical venous flow. Fetuses with congenital malformations or chromosomal anomalies were excluded (n = 32). The diagnosis of TTTS was based on a monochorionic-diamniotic twin pregnancy (single placenta, thin dividing membrane, same gender) that was complicated by polyhydramnios in the RT (>8 cm depth of amniotic fluid) and oligohydramnios in the donor (<2 cm depth of amniotic fluid), with the exclusion of other causes for amniotic fluid and growth discrepancy. Staging was assigned using both the Quintero and the Cincinnati TTTS staging system. The Cincinnati TTTS staging system utilizes fetal echocardiography to detect RTCM, and modifies staging based on severity of RT cardiovascular abnormality ( Table 1 ). TTTS cardiomyopathy (CM) is scored as the aggregate impression of the severity of 3 parameters: the presence and severity of atrioventricular valvular regurgitation (AVVR); degree of ventricular wall thickening; and ventricular function as assessed by the myocardial performance index (MPI) ( Table 2 ). The presence or absence of AVVR was assessed by color-flow Doppler interrogation. The severity of AVVR was graded semiquantitatively as mild (narrow jet ≤0.5 atrial length), moderate (narrow jet >0.5 atrial length), or severe (wide jet >0.5 atrial length). The MPI was measured in both the right and left ventricles. The MPI is a Doppler index measuring both systolic and diastolic myocardial function. It is defined as the sum of the isovolumic relaxation and isovolumic contraction time, divided by ejection time, measured from Doppler inflow and outflow spectral profiles. An abnormal MPI was defined as a value >2 SD above the normal mean, which at our institution equals a right ventricular MPI >0.48 and a left ventricular MPI >0.43.
| Stage | Donor | Recipient | Recipient cardiomyopathy |
|---|---|---|---|
| I | Oligohydramnios (DVP <2 cm) | Polyhydramnios (DVP >8 cm) | No |
| II | Absent bladder | Bladder seen | No |
| III | Abnormal Doppler | Abnormal Doppler | None |
| IIIA | Mild | ||
| IIIB | Moderate | ||
| IIIC | Severe | ||
| IV | Hydrops | Hydrops | |
| V | Death | Death |
| Classification | Description | ||
|---|---|---|---|
| Variables/cardiomyopathy | Mild | Moderate | Severe |
| AVVR | Mild | Moderate | Severe |
| RV/LV hypertrophy | Mild | Moderate | Severe |
| MPI a |
|
|
|
a Standards per our institution: left MPI = 0.33 ± 0.05; right MPI = 0.32 ± 0.08.
Amniotic fluid samples used for analysis were obtained at the start of each fetoscopic case immediately following fetoscope insertion. One team of surgeons performed all SFLP procedures using the same mapping protocol and techniques. After the laser procedure, amnioreduction was performed and the RT amniotic fluid volume was reduced such that the deepest vertical pocket was <5 cm. A 5-mL aliquot of amniotic fluid was centrifuged at 2000 g at 4°C. Aliquots acquired from the samples were stored at –80°C. All samples were analyzed in triplicate. Amniotic fluid level of NT-proBNP was measured using enzyme-linked immunosorbent assays (Alpco Diagnostics, Salem, NH) per manufacturer guidelines. Interassay and intraassay variation of NT-proBNP is <5% and 7%, respectively. The lowest detection level of NT-proBNP for this enzyme-linked immunosorbent assay is 5 fmol/mL. The rational for measuring NT-proBNP levels is that BNP is derived from the precursor preproBNP, a 134-amino-acid polypeptide, which is cleaved to the proBNP (108 amino acids) and a signal peptide (26 amino acids). At the time of release under conditions of pressure load, NT-proBNP is cleaved from the precursor peptide proBNP and is cosecreted in quantities directly proportional to its biologically active counterpart BNP and in close correlation with the severity of heart disease. There is excellent clinical and statistical correlation between assays for BNP and NT-proBNP. The longer half-life, better stability, more accurate measurement, and wider dynamic range for NT-proBNP provide an advantage over measuring the active form of BNP. Amniotic fluid level of NT-proBNP was normalized to total protein in the amniotic fluid. Amniotic fluid level of total protein was measured by a colorimetric assay (DC protein assay; Bio-Rad Laboratories, Hercules, CA) as per manufacturer guidelines. Amniotic fluid level of the biomarker was expressed as a ratio of total protein concentrations. Singleton pregnancies that were undergoing amniocentesis for advanced maternal age were consented for inclusion of discarded amniotic fluid as control samples. Only samples from fetuses with normal karyotype and no structural malformations were included in control amniotic fluid samples (n = 6).
Statistical analysis
Statistical analyses for variables with normal distribution were performed using χ 2 or Fisher’s exact test for categorical data and analysis of variance test for continuous variables as appropriate. Otherwise, if not normally distributed then Mann-Whitney test, or Kruskal-Wallis test and Spearman correlation was used as appropriate. Data are presented as mean ± SD or median (and interquartile range) and frequency (percent) as appropriate. All tests were 2-sided and P values < .05 were considered statistically significant. All statistical analyses except receiver operating characteristic (ROC) curve analyses were performed using the software package SPSS (SPSS for Windows, version 17; SPSS Inc, Chicago, IL). SAS (version 9.2; SAS Institute Inc, Cary, NC) was used for ROC analysis.
The ROC curve analysis was performed to assess the ability of NT-proBNP to predict RTCM and to obtain optimal threshold values. For the purpose of calculating sensitivity and specificity, disease state was defined as moderate or greater CM (Cincinnati stage IIIB, IIIC, and IV). The optimal value of NT-proBNP for predicting moderate RTCM and beyond was defined as the concentration with the highest sensitivity and best accuracy. We also evaluated the relationship between NT-proBNP and echocardiographic parameters.
To validate the ROC analysis and the calculation of the area under the curve (AUC), we used 2 interval validation methods: (1) 10-fold cross-validation; and (2) bootstrap validation. The 10-fold validation is an extension of the split-sample validation. Instead of splitting the sample into 2 subsamples (using half to build the model and the other half to test the model), we split the sample into 10 subsamples. Then we used 9 of these subsamples together to build the model, and used the remaining subsample to test the model. We repeated this process 9 times more, effectively using each subsample to test the model once. Finally, we took the average of the 10 AUCs as our cross-validated estimate. In the bootstrap validation, we formed 100 bootstrap samples; each sample was formed by sampling with replacement until we obtained the same size as the original data set. For each of the 100 samples, we built a model, tested the model, and computed the AUC on both the original data set and the bootstrap sample. The difference between the AUC from the original data set and the AUC from the bootstrap sample was recorded. After conducting this process 100 times, we took the mean of the differences in AUC and called this mean the “optimism correction.” Finally, we subtracted this optimism correction from the AUC that was computed using the same original data set to build and test the model. The result is the bootstrap-validated AUC.
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