Preterm birth (birth before 37 weeks of gestation) complicates many pregnancies and has for decades been strongly associated with increased risk of neonatal morbidity and mortality.1 Long-term complications seen in relation to preterm birth include cerebral palsy, respiratory disease, blindness, and deafness. In many countries the incidence of preterm birth has increased in recent years. In Denmark in 2004 it complicated 6.3% of all pregnancies, an increase of 22% since 1995.2 The cause of preterm birth appears to be multifactorial, with maternal stress, genetic predisposition, multiple pregnancies, in vitro fertilization, and exposure to alcohol and smoking during pregnancy being well-known risk factors. It also is generally accepted that inflammation in pregnancy plays an important role, and several studies have shown a correlation between intrauterine inflammation and preterm birth.3–5 Increased levels of inflammatory markers have been shown in connection with preterm birth in maternal plasma,6 amniotic and cervical fluid,7 umbilical venous plasma,8 and cord blood,9,10 and in vitro in lipopolysaccharide (LPS)-stimulated placental11 and fetal12 membranes. Nelson et al have found elevated levels of interleukin (IL)-8 and decreased levels of brain-derived neurotrophic factor, neurotrophin-3, and neurotrophin-4 in dried blood spots samples drawn 1.2±0.9 days after birth from infants born preterm compared with dried blood spots samples drawn 2.6±2.2 days after birth from infants born at term.13
It is not known whether inflammation that may trigger preterm birth is of fetal, placental, or maternal origin.14 Whether inflammation is a cause of preterm birth or a consequence also has been discussed.15 Vaginal infections do not always develop into ascending intrauterine infections, and the presence of bacteria in the fetal membranes does not always lead to preterm birth.16 The explanation for this is not known; it is most likely a combination of genetic susceptibility and time of exposure.4 Because of various methods of defining infection in different studies of infection and birth outcome, the findings are contradictory.17 Further, culture of microorganisms may be difficult, and a negative bacterial culture is not always conclusive.18 If inflammation and not bacterial invasion, per se, is a cause of preterm birth, it is relevant to look at specific inflammatory markers in the mother and in the neonate. The aim of the current study is to investigate fetal/neonatal inflammatory patterns based on 25 inflammatory markers in neonatal dried blood spots samples from infants born preterm and term, collected several days after birth, when all measured markers are considered to be of infant origin. The 25 inflammatory markers were selected to provide a broad picture of the immune response, with Th1, Th2, Th3, Th17, acute inflammatory proteins, and neurotrophins represented.
MATERIALS AND METHODS
The current study was based on data collected as part of a pilot study assessing biomarkers and risk factors for cerebral palsy using a case-control design and archived blood specimens. The case group consisted of children with spastic cerebral palsy, and the control group consisted of children without developmental problems. Information on only those children in the control group was used in this analysis. For the pilot study, the children in the control group were randomly selected from the Danish Medical Birth Register,19 which collects data on all live births and stillbirths in Denmark. The same number of children were selected for the control and case groups by year of birth (1982–1990) within three gestational age strata (very preterm: less than 32 weeks of gestation; preterm: 32–36 weeks of gestation; and term: 37 or more weeks of gestation). No lower limit for gestational age was set, but it was required that the children be liveborn and alive at age 5 years. Selected children from the control group were excluded if they had a history of developmental disorders in the Danish National Hospital Register.20 Thus, children in this study had no reported adverse developmental sequelae regardless of gestational age at birth. For the pilot study, the target sample size was 100 children in the case group and 100 children in the control group in each gestational age stratum. All selected individuals were invited to participate, and active refusals were excluded from the study. Included in this study were the final 160 participants from the control group born from 1982 through 1990 from singleton pregnancies, with available medical records, and with adequate residual dried blood spots samples for analysis. Seventy-eight infants were born at less than 37 weeks of gestation (26 very preterm and 52 preterm), and 82 infants were born at term. All risk factor data (Table 1) were abstracted from maternal obstetric and neonatal medical records. The presence of a specific condition was based on a clinical diagnosis (eg, premature rupture of membranes) or a notation of quantitative information (eg, maternal temperature) as recorded in the medical record. Gestational age for each birth was based on last menstrual period dates, early ultrasound, or newborn examination. The study was approved by the Danish Data Protection Agency and the Ethical Committee in Vejle and Funen Counties, Denmark (Ref. no.: 19990258).
The samples from all the study participants were retrieved from the Danish biological specimen bank of residual newborn screening dried blood spots samples21 and prepared for biomarker analysis. All samples were drawn before 10 days of age; samples drawn later than 10 days of age were excluded (20 born preterm and one born at term) to get comparable times for sample collection. The mean age of sample collection was 6 days (95% confidence interval [CI] 5–7 days) for very preterm infants, 5 days (95% CI 5–6 days) for preterm infants, and 5 days (95% CI 5–5 days) for infants born at term. We performed the dried blood spots samples analysis with Luminex xMAP technology (Austin, TX) as described in Skogstrand et al22 for 25 inflammatory markers: (interleukin-1β [IL-1β]; -2; -4; -5; -6; -8; -10; -12; -17; -18; tumor necrosis factor-α (TNF-α); -β (TNF-β); soluble IL-6 receptor-α (sIL-6rα); interferon-γ (IFN-γ); granulocyte-macrophage colony–stimulating factor; transforming growth factor-β1 (TGF-β1); monocyte chemoattractant protein-1; macrophage inflammatory protein-1α (MIP-1α) and -1β; neurotrophin-4; brain-derived neurotrophic factor; regulated upon activation, normal T cell expressed and presumably secreted; C-reactive protein (CRP); matrix metalloproteinase (MMP-9); and triggering receptor expressed on myeloid cells.
Statistical analyses were performed with SAS System 8.2 (SAS, Cary, NC) and GraphPad Prism 5 (GraphPad Software, Inc., San Diego, CA). The samples were divided into the three sampling strata based on gestational age. Medians and interquartile ranges were used to describe the different biomarker levels, and the Kruskal-Wallis nonparametric analysis of variance and Dunn's test for pairwise comparisons23 were used for comparisons of the groups (very preterm, preterm, and very preterm plus preterm with term). The Maentel-Haenszel trend test24 was used for comparison over the gestational age categories (3×4 tables). Further, based on biomarker levels in neonates born at term, cut-points corresponding to the 10th, 25th, 75th, and 90th percentiles were established and levels were dichotomized for less than the 10th, less than the 25th, greater than the 75th, and greater than the 90th percentile. Odds ratios (ORs) and 95% CIs were calculated using logistic regression comparing very preterm infants, preterm infants, and very preterm plus preterm infants with infants born at term for each analyte. Statistically significant differences in any comparisons based on the dichotomized biomarker levels were selected for further multivariable logistic regression analyses, including other risk factors. Two different multivariable models were performed based on inclusion of maternal or neonatal risk factors. All variables presented in Table 1 were considered for the two models. The final models, including either maternal or neonatal factors that had the best fit based on likelihood ratios and Hosmer-Lemeshow goodness-of-fit tests, were: 1. Maternal factors: previous preterm birth, smoking, premature rupture of membranes (PROM) more than 48 hours before birth, and maternal infections 2. Neonatal factors: Apgar score at 1 minute of less than 7 and resuscitation (any kind) at delivery.
A combination of the two models with both maternal and fetal factors was not performed because of the relatively few children in the study and because of the fact that the observed immune response was considered of fetal origin. A P<.05 was considered statistically significant.
As seen in Table 1, maternal smoking (preterm and very preterm plus preterm versus infants born at term), PROM (more than 48 hours) (preterm and very preterm plus preterm versus infants born at term), previous preterm birth (preterm and very preterm plus preterm versus infants born at term), cesarean delivery (preterm and very preterm plus preterm versus infants born at term), Apgar score 1 minute after birth of less than 7 (very preterm, preterm, and very preterm plus preterm versus infants born at term), and resuscitation at delivery (very preterm, preterm, and very preterm plus preterm versus infants born at term) were significantly associated with being born preterm. Previous spontaneous abortions or stillbirth, previous induced abortions, sex, placental infarct, maternal autoimmune disease, fever (higher than 38.5°C) in pregnancy, maternal infections, maternal age older than 35 years, and maternal body mass index were not associated with preterm birth, nor were they associated with any reported adverse long-term developmental problems. There were two cases of neonatal infections, only one case of preeclampsia, and no cases of chorioamnionitis or intracranial bleedings.
As seen in Table 2, blood levels of IL-8, sIL-6rα, and TGF-β1 were significantly increased and levels of IL-18 and CRP were decreased in very preterm infants compared with infants born at term. Levels of IL-6 and TGF-β1 were elevated in preterm infants compared with infants born at term, whereas CRP was decreased. In very preterm and preterm infants together compared with infants born at term, blood concentrations of IL-6, IL-8, and TGF-β1 were significantly elevated and concentrations of IL-18 and CRP were decreased. Further, there were statistically significant trends in IL-8, IL-18, TGF-β1, CRP, and brain-derived neurotrophic factor over gestational age based on the three groups (very preterm, preterm, and infants born at term). For IL-8, IL-18, TGF-β1, and CRP, the results remained statistically significant using Dunn's test for multiple comparisons across the three groups.
Results of the subject comparisons based on the dichotomized analyte levels are shown in Table 3 (for space considerations only significant results are shown; remaining data available on request). In unadjusted analysis, IL-8, sIL-6rα, TGF-β1, and MMP-9 were significantly associated with very preterm birth based on the 75th and 90th term percentile cutoff values, whereas IL-18 and CRP were statistically significantly associated with very preterm birth at values below the 25th and the 10th percentiles. The association between MIP-1α and very preterm birth approached significance at values below the 10th percentile. Interleukin-6 was significantly associated with preterm birth based on the 75th term percentile and significantly protective of preterm birth below the 25th percentile. C-reactive protein values were significantly associated with preterm birth below the 25th and 10th term percentiles. Considering very preterm plus preterm combined in comparison with infants born at term, IL-8 and IL-1β were significantly associated with preterm birth at concentrations above the 90th percentile, as were TGF-β1 above both the 75th and 90th percentiles and IL-18 and CRP below the 25th and 10th percentiles. C-reactive protein above the 75th percentile was significantly protective of preterm birth.
Based on the above results, multivariable analyses were performed to calculate adjusted ORs for IL-8, MMP-9, sIL-6rα, TGF-β1, and IL-1β using the 90th percentile cutoff; for IL-18 and IL-6 using the 25th percentile cutoff; and for CRP and MIP-1α using the 10th percentile cutoff. As shown in Table 3, adjusted for maternal factors, IL-8, TGF-β1, and CRP remained statistically significant for the very preterm, preterm, and very preterm plus preterm groups versus infants born at term. Interleukin-18 remained statistically significant for the very preterm and very preterm plus preterm groups versus infants born at term. Matrix metalloproteinase-9, sIL-6rα, and MIP-1α remained statistically significant for the very preterm group versus infants born at term. Adjusting for neonatal factors, CRP remained statistically significantly associated with the very preterm, preterm, and very preterm plus preterm groups versus infants born at term. Soluble IL-6 receptor-α remained statistically significant associated with the very preterm and very preterm plus preterm groups versus infants born at term. Interleukin-18 and MIP-1α remained statistically significant associated with the very preterm group versus infants born at term. Transforming growth factor-β1 remained statistically significant associated with the very preterm plus preterm group versus infants born at term. Lastly, IL-6 remained statistically significant associated with the preterm group versus infants born at term after multivariable adjustment. Excluding the two preterm infants with clinical diagnoses of neonatal infections did not alter the results.
We found that infants born preterm (with no subsequently reported developmental problems) have statistically significantly different concentrations of many inflammatory markers in blood drawn several days after birth compared with infants born at term. In general, the degree of association between the levels of inflammatory markers and preterm birth correlated with the degree of prematurity, indicating that an abnormal inflammatory response might be a more prominent feature in very preterm infants. This also has been suggested by others concerning the role of the inflammatory response in causing preterm birth.3
The proinflammatory cytokines IL-8 and IL-6 (and also sIL-6rα, which enhances the effect of IL-6)25,26 were elevated in dried blood spots samples from very preterm newborns, and IL-6 was elevated in dried blood spots samples from preterm newborns. Elevated levels of both IL-6 and IL-8 in amniotic fluid previously have been associated with preterm birth, whereas these markers in maternal serum have not been. Elevated levels of IL-6 also have been described in fetal plasma in association with preterm labor; Romero et al call it the “fetal inflammatory response syndrome.”27 In the latter study, cordocentesis and amniocentesis were performed on women with preterm PROM and on a control group of women between 19 and 42 weeks of gestation. The authors found that the levels of IL-6 in the fetus correlated with the level in amniotic fluid but not in maternal serum when women were in labor. They suggest that the human fetus may play a role in initiating labor but that maternal cooperation must occur, for instance through inflammation in chorioamniotic membranes and decidua. It is believed that fetal inflammatory response syndrome is the fetal response to the hostile intrauterine environment and that cytokines are the signal to start labor.3,16,27
TGF-β1 was elevated in dried blood spots samples from premature newborns in our study and has been shown to increase the fetal membrane production of type-2 cyclooxygenase, prostaglandin E2, and cytosolic phospholipase A2,28 all of which are increased during labor.29 Type-2 cyclooxygenase and cytosolic phospholipase A2 are known to induce the production of prostaglandins30, and prostaglandin E2 to induce uterine contraction and labor.31 Further, TGF-β1 is known to inhibit both the Th1 and Th2 responses, where Th1 differentiation from CD4+ T-cells is skewed to the proinflammatory Th17 differentiation and the production of IL-17.32 TGF-β1 has been described as a cytokine with bipolarity that can both trigger and inhibit the immune system.33 We did not see an increase of IL-17 in blood from premature neonates, but we did see a slight elevation in MMP-9, which is induced by IL-17.32 Matrix metalloproteinase-9 may play a role in membrane rupture and cervical ripening.34,35 We also found an elevated blood concentration of IL-1β associated with preterm birth. Interleukin-1β increases the production of prostaglandins29 and is a proinflammatory cytokine that induces the rest of the immune response.36
We found decreased levels of IL-18 in dried blood spots samples from preterm newborns. A recent animal study has shown that IL-18 gene-disrupted mice have an increased risk of delivering preterm when injected with LPS, as was also the case in mice injected with IL-18 binding protein or an IL-18 antagonist.37 Interleukin-18 synergized with IL-12 is a strong stimulator of the Th1 response, which at first was described to induce IFN-γ but which later has been shown to have a regulatory role in both Th1 and Th2 responses, where IL-18 can shift the immune response in either a Th1 or Th2 direction.38 Th2-type immunity has been connected to a successful pregnancy, whereas Th1-type immunity has been linked to pregnancy failure,39,40 although this is considered an oversimplification by many researchers.3 We saw evidence for a slight shift toward Th2 in the preterm newborns, as IL-6 was elevated (Th2) and IL-18 decreased (Th1), but not with the other classical Th1 and Th2 cytokines measured: IL-2, IL-12, IFN-γ, TNF-β, and IL-4, IL-5, IL-10, respectively.41
Brain-derived neurotrophic factor and CRP were decreased in dried blood spots samples from the neonates born preterm. A decreased level of brain-derived neurotrophic factor previously has been reported in cord blood13 and serum from neonates born preterm42 and has been found to increase with gestational age.43 A possible explanation for the decreased levels of brain-derived neurotrophic factor in preterm newborns may be their less mature nervous and immune systems, along with the fact that brain-derived neurotrophic factor is also secreted by vascular endothelial cells that grow and develop extensively (angiogenesis) in the last period of pregnancy.43 C-reactive protein also was statistically significantly decreased in dried blood spots samples from the preterm newborns in this study. This is in contrast to the well known fact that CRP is elevated in preterm newborns with infection.44–46 However, only two newborns in this study had a diagnosis of neonatal infection, so it is possible that CRP levels in preterm newborns in general are low. The fact that adjustment for neonatal risk factors does not remove the significant association between CRP and preterm birth supports this possibility. Another possible explanation could be polymorphisms in the CRP gene, which have been described to decrease baseline CRP levels.47–49 What influence this may have on the rest of the immune system and preterm birth remains to be investigated.
Several studies have shown that proinflammatory cytokines do not cross the placenta,50,51 which strongly suggests that cytokines present in neonatal dried blood spots samples are not of maternal origin. The ORs adjusted for maternal risk factors in this study, where only the estimate for IL-1β was no longer significant after adjustment, supports this hypothesis. In addition, cytokines have a short half-life in the human body. A study on healthy young volunteers injected with LPS showed that TNF-α had a peak at about 120 minutes and IL-6 at about 150 minutes. TNF-α reached baseline again at 720 minutes (12 hours) and IL-6 at 390 minutes (6.5 hours).52 Thus, the elevated levels of cytokines found as late as 4–6 days after birth are most likely not of placental origin, but from the infant. The ORs adjusted for neonatal risk factors in this study, where the elevated concentrations of IL-8, MMP-9, TGF-β, and IL-1β and decreased concentration of IL-18 were no longer statistically significant after adjustment, support this hypothesis. It has been debated whether infants, and especially preterm infants, are capable of producing an immune response, but recent results show that even very preterm infants can develop a Th1 and Th2 response.53
In our study there is a higher incidence of cesarean delivery among the infants born preterm (cesarean delivery in 11 very preterm, 41 preterm, and 10 infants born at term). Malamitsi-Puchner et al found that vaginal delivery increased the concentration of some cytokines in the term neonate at day 1 and 4 after birth: IL-1β at day 1 and TNF-α at days 1 and 4, whereas IL-4, IL-6, sIL-6rα, IL-8, TNF-α, and regulated upon activation, normal T cell expressed and presumably secreted did not depend on the mode of delivery.54 We did not observe any correlation between cytokine levels and mode of delivery, possibly because most of our samples were drawn later than days 1 and 4. Further, in this study, cesarean delivery was not a significant factor in the multivariable logistic regression models of the associations between biomarkers and preterm birth. Previous preterm birth seemed only to affect the preterm and not the very preterm births in the adjusted models for maternal risk factors, which could support stronger genetic components in preterm than in very preterm births.
The level of degradation of samples over time and assay variations of the measurements of inflammatory markers has been dealt with previously22. There is some degradation of samples over time, but because those in the case and control groups were about the same age, this has less importance. The subjects in this study were randomly selected over the years 1982–1990 and correspond to the initial study cases of cerebral palsy. There were no statistically significant differences in the time from sampling to processing across the three groups (very preterm, preterm and term) among the children from the control group used for this study. Thus, the possibility of any selection bias is considered minimal. The possibility of interaction between biomarkers included in the models should be controlled for in the regression modeling. The main limitation of this study is that we have only one sample from each subject, thus it is not possible to assess patterns of longitudinal change in the neonate. Further, the samples were drawn several days after birth, which means that other inflammatory changes that arise earlier in the inflammatory process around delivery could not be observed, and the inflammation, especially in the very preterm neonates, could be a result from treatment after birth. Controlling for neonatal factors modified some, but not all, cytokine associations with preterm birth and supports the hypothesis that the inflammation was of fetal and/or newborn origin. The samples were drawn between 1 and 10 days of age. Ideally we would draw cord blood at delivery and peripheral blood prospectively after birth to study the longitudinal changes and assess whether inflammation was induced after birth. This could be a follow-up study. For this study we excluded all infants with developmental problems and, therefore, have reduced potential confounding by disease processes associated with adverse long-term developmental outcome that may involve inflammation and/or be a trigger for preterm birth. Further analysis is underway examining the cytokine profiles of children with cerebral palsy versus these children with no long-term developmental problems.
It is possible that a combination of fetal, placental, and maternal inflammation participate in the pathogenesis of preterm birth. Our results of altered cytokine levels in preterm neonates support the hypothesis that the fetus is an important source of inflammation and hence may play a role in the cause(s) of preterm birth.
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