Chorioamnionitis-exposure alters serum cytokine trends in premature neonates

Chorioamnionitis-exposure alters serum cytokine trends in premature neonates | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Chorioamnionitis-exposure alters serum cytokine trends in premature neonates Gretchen Stepanovich, Cole Chapman, Krista Meserve, Julie Sturza, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1766505/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Dec, 2022 Read the published version in Journal of Perinatology → Version 1 posted 9 You are reading this latest preprint version Abstract Objective: Determine the duration of chorioamnionitis-induced altered immune responses in preterm neonates. Study Design: A 7-plex immunoassay measured levels of IL-1b, IL-6, IL-8, IL-10, TNF-a, CCL2 and CCL3 longitudinally in residual serum samples from chorioamnionitis-exposed and unexposed preterm neonates less than 33 weeks’ gestation. Results: Chorioamnionitis-exposed and unexposed preterm neonates demonstrated differences in the trends of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 over the first month of life. The unexposed neonates demonstrated elevated levels of these inflammatory markers in the first one to two weeks of life with a decrease to baseline levels by the third week of life, while the chorioamnionitis-exposed neonates demonstrated differences over time without a predictable pattern. Chorioamnionitis-exposed and unexposed neonates demonstrated altered IL-10 and TNF-a trajectories over the first twelve weeks of life. Conclusion: Chorioamnionitis induces a state of immune dysregulation that persists for at least twelve weeks following delivery in preterm neonates. Figures Figure 1 Figure 2 Figure 3 Introduction: Blood stream infections are a significant cause of morbidity and mortality for preterm infants in Neonatal Intensive Care Units (NICUs) worldwide. Preterm birth, defined as delivery that occurs prior to 37 weeks’ gestation, complicates approximately 11% of births globally ( 1 ). Those neonates born very preterm, prior to 32 weeks of completed gestation, are at risk for numerous morbidities during their hospitalization including an increased risk for sepsis. Up to 5% of very preterm neonates develop culture positive sepsis during their initial NICU stay compared to only 0.1% of term neonates ( 2 ). Infection risk is often attributed to immaturity of the preterm immune system, particularly the innate immune system. The innate immune system includes primitive barriers such as skin, gastric acidity and cilia within the pulmonary tract, as well as non-specific cells and molecules within the immune system such as neutrophils, monocytes, macrophages and natural killer cells. The immune system cellular response is directed by cytokines and chemokines, which are peptides or proteins that participate in cell signaling. Appropriate cytokines and chemokine responses are necessary for the defense against pathogens. The natural evolution of these responses in premature neonates is poorly understood. Many strategies have been implemented in NICUs to reduce the likelihood of developing sepsis, including central catheter bundles, earlier removal of indwelling devices, use of breast milk, administration of probiotics and strict hand-washing protocols ( 3 , 4 ). Early sepsis detection and prompt initiation of antibiotic therapy significantly improves outcomes in neonatal sepsis ( 5 ). In practice, early sepsis detection is difficult as signs of infection in the neonatal population are often non-specific. The gold standard test to diagnose a blood stream infection is a blood culture that demonstrates growth of a pathogenic organism, however this often takes at least 24 hours to result ( 6 ). Several biomarkers are commonly used to support or refute the presence of infection, including C-reactive protein, procalcitonin and the presence of many immature forms of neutrophils ( 7 ). These biomarkers are non-specific, and are often more useful to rule infection out rather than diagnose it. Several cytokines have been proposed as useful biomarkers to diagnose neonatal sepsis, including IL-1b, IL-6, IL-8, IL-10 and TNF-a ( 8 – 11 ). While cytokines hold great promise as biomarkers to diagnose neonatal sepsis, they often take days to result and lack normal reference ranges for neonates, particularly preterm neonates. These factors contribute to the continued difficulty in prompt diagnosis and treatment of neonatal sepsis, leading to unacceptable mortality rates. The period around labor and delivery is a highly inflammatory process, with elevated maternal levels of IL-1b, IL-6 and TNF-a ( 12 – 14 ). Elevated levels of these same cytokines have also been demonstrated in neonatal samples following delivery ( 14 , 15 ). It is unclear how these cytokine levels change over time in neonates, and whether values should be considered based upon gestational age or chronological age in preterm neonates. Several studies have begun to address these knowledge gaps. Matoba et al reported 12 umbilical cord blood cytokine levels to be increased, five to be decreased and 10 to be unchanged between infants born prematurely and those born at term ( 16 ). Subsequently, Lusyati et al reported levels of 25 cytokines to be stable throughout the first seven days of life, with infants born before 36 weeks’ gestation expressing lower levels of 14 of these cytokines compared to infants born at term ( 17 ). These decreased cytokine responses are thought to contribute to a preterm neonate’s heightened susceptibility to infection as appropriate cytokine responses are necessary to guide the clearance of microorganisms ( 18 ). Preterm delivery is often complicated and may even be stimulated by intrauterine inflammation and/or infection, termed chorioamnionitis ( 1 ). Chorioamnionitis is present in up to 70% of very preterm deliveries and leads to an initial fetal pro-inflammatory response, including increased expression of the pro-inflammatory cytokines IL-1b, IL-6, IL-8 and TNF-a ( 19 , 20 ). This fetal inflammatory response alters the developing immune system, resulting in decreased pro-inflammatory cytokine expression when umbilical cord blood monocytes from chorioamnionitis-exposed neonates undergo a secondary challenge with either LPS or Staphylococcus epidermidis ( 21 , 22 ). Chorioamnionitis exposure is known to increase the risk of developing both early and late onset neonatal sepsis, which may be at least partially due to these dampened monocyte responses ( 23 , 24 ). It is currently unclear how long this chorioamnionitis-induced immune hypo-responsiveness persists, which could impact susceptibility to infection outside of the immediate neonatal period and may have long-term immune phenotype implications for the development of chronic disease. To better understand how inflammatory mediators change over time in preterm neonates, we performed longitudinal cytokine and chemokine profiling. To investigate the impact of chorioamnionitis exposure on these inflammatory markers, we differentiated and compared these inflammatory markers between preterm neonates exposed to maternal chorioamnionitis and those that were unexposed. For this study, we developed a 7-plex cytokine and chemokine assay to measure concentrations of CCL2, CCL3, IL-1β, IL-6, IL-8, IL-10, and TNF-α in neonatal serum samples. Using less than 200 µL of residual serum from clinically indicated routine blood tests, we compared cytokine and chemokine levels throughout an neonate’s NICU course in an effort to establish baseline levels, evaluate changes over time, and examine the impact of exposure to maternal chorioamnionitis. Methods: Patient Recruitment and Blood Collection This study was approved by the University of Michigan IRB. This study was performed in accordance with the Declaration of Helsinki. After informed written parental consent was obtained, residual serum was collected prospectively from clinically indicated lab draws of neonates born at less than 33 weeks’ gestational age. Serum samples were collected from 61 patients from birth through 42 weeks’ postmenstrual age, death or discharge, whichever occurred first. This cohort included 27 chorioamnionitis-exposed and 34 unexposed preterm infants. Sample collection occurred from April, 2019 through April, 2021. Histopathologic examination of the placenta was used to diagnose chorioamnionitis ( 22 , 25 ). The blood volume collected with each sample varied, as the serum available for testing was what remained after all clinically ordered testing was performed. As 200 µL was required for performance of the cytokine assay, samples were pooled if collected within three days of one another and the subject had no significant change in clinical status. A total of 397 residual serum samples were collected. Samples were excluded from data evaluation if the subject had a suspected or confirmed infection and was being treated with antibiotics at the time of sample collection (sepsis, urinary tract infection, pneumonia, necrotizing enterocolitis or spontaneous intestinal perforation), excluding 100 samples from analysis. A total of 297 serum samples were included in the final analysis. Samples were frozen and stored in a -80° C freezer prior to use. Reagents and Buffers Dulbecco’s phosphate buffered saline (PBS, catalog # D5573), bovine serum albumin (BSA, catalog # A2153), and (3-Aminopropyl) triethoxysilane (catalog # 440140) were purchased from Millipore Sigma (St. Louis, MO USA). Glycerol (catalog # BP229), bis(sulfosuccinimidyl)suberate (catalog # A39266), starting block blocking buffer (catalog # 37538), Pierce high sensitivity streptavidin-HRP (SA-HRP, catalog # 21130), and 4-chloronaphthol (4-CN, catalog # 34012) were purchased from Thermo Fisher Scientific (Waltham, MA USA). Drycoat assay stabilizer (catalog # AG066) was obtained from Virusys Corporation (Taneytown, MD USA). Vendors and catalog numbers for antibodies for all multiplexed assay components are summarized in Supplementary Table 1 . Running buffer for all assays was 0.5% BSA in 1X PBS, pH 7.4. Multiplexed Immunoassays Microring resonator immunoassays were validated and performed on the Maverick M1 and Matchbox systems (San Diego, CA USA), respectively, as previously described ( 26 – 28 ). The Maverick instruments use microfluidic systems for automated reagent handling. The M1 uses reusable cartridge devices and the Matchbox uses disposable, injection-molded, plug-and-play devices ( 28 ). Microring chips were functionalized with capture antibodies using an amine-reactive, homobifunctional crosslinker to create a 7-plex cytokine and chemokine capture array. Each capture antibody spanned two clusters of four microring sensors in each of the two microfluidic channels, giving n = 8 technical replicates of each target cytokine or chemokine per channel. After introducing the sample to the chip surface, a mixture of all tracer antibodies was flowed across the chip, followed by streptavidin-tagged enzymes and a signal amplification reagent. Assays were performed at a 30 µl/min flow rate for all steps. There was an initial rinse of 5 minutes with the running buffer to ensure equilibration of the chip prior to sample analysis. The assay included steps as follows: 1) running buffer (2 min); 2) sample (7 min); 3) running buffer rinse (2 min); 4) biotinylated tracer antibodies (7 min); 5) running buffer rinse (2 min); 6) SA-HRP (7 min); 7) running buffer rinse (2 min); 8) 4-CN (7 min); 9) running buffer rinse (2 min). The total assay time was 38 minutes ( Supplementary Fig. 1A ). Immunoassay Calibrations The 7-plex immunoassay was simultaneously calibrated for all analytes in a multiplexed format, as described previously.( 26 ) Serial dilutions from a mixed saturating analyte sample of all multiplexed targets were used to construct eight-point calibration curves correlating net sensor shifts to target concentrations. To quantify, the signal before the enhancement step (t = 29 min) was subtracted from the signal after the final assay rinse step (t = 38 min). These net resonance wavelength shifts (∆pm) were plotted as a function of standard concentration and fit to a four-parametric logistic function ( Supplementary Fig. 1B ). Limits of detection (LOD) and quantification (LOQ) were defined as the blank signal plus 3 times and 10 times the standard deviation of the blank, respectively ( Supplementary Table 2 ). Each calibration was performed at least in triplicate for each sample dilution as measured with 8 sensors per technical replicate. Sample Evaluation All samples contained at least 200 µL of residual serum. Neonatal residual serum samples were analyzed at two dilutions (0.5X and 0.1X) in running buffer using the same steps highlighted in Supplementary Fig. 1A . To quantify, the net shift surrounding the amplification step for each target was correlated to concentration using the corresponding standard calibration curve, 50% serum or 10% serum, matching the serum content of the residual serum dilution. The most appropriate dilution to use for statistical analysis was selected by choosing the dilution with the relative shift closest to the inflection point of the respective calibration curve. Statistical Analysis Basic statistical analysis was performed in GraphPad Prism 8. Data normality was evaluated using the Shapiro-Wilk test. Study group characteristics were compared using the student’s t-test for quantitative parametric data, the Mann-Whitney test for nonparametric data and the Chi-square test for categorical variables. p-values of < 0.05 were considered significant. Cytokine and chemokine levels were compared between the first and second weeks of life in the same subject using the Wilcoxon matched-pairs signed rank test. If there was more than one data point within these time frames, the data points were averaged to create a single mean level for each week. p-values < 0.05 was considered significant for this analysis method. General Estimating Equations were used in SPSS 28.0.1.0 to evaluate for changes in cytokine trends over the first four weeks of life in the chorioamnionitis-exposed and unexposed groups as the data was longitudinal, paired and non-parametric with missing data points for some subjects. The General Estimating Equations used a robust covariance matrix, an unstructured working correlation matrix and a Tweedie with log link model. If there was more than one data point within each time frame, the data points were averaged to create a single mean level for each week. p-values < 0.05 was considered significant for the comparison of overall trends within each exposure group. However, when individual timepoints were compared within exposure groups, p-values < 0.01 were considered significant to correct for multiple comparisons. Subjects were then separated into those exposed to maternal chorioamnionitis and those who were unexposed and cytokine and chemokine levels from each subject were compared over time by week-of-life (chronologic age). When there was more than one data point in a week, all points within that week were averaged to create a single mean cytokine level. Univariate statistics showed that the cytokines were not normally distributed and were largely right skewed, with many zeros, representing cytokine levels below the limit of detection. To transform the data to approximate a normal distribution more appropriate for modeling, the natural log of (cytokine level + x, where x is a positive value that varies based on the cytokine in question) was used. SAS Proc Mixed was used to perform repeated measures regression to look at the effect of chorioamnionitis status on the trajectory of cytokines over time while controlling for gestational age, ethnicity, and birth via C-section, all of which were found to be statistically different between exposure groups. Analyses were restricted to the first twelve weeks of life as the chorioamnionitis-exposed group had no data points beyond the first twelve weeks of life. Autoregressive covariance structure was selected based upon a) a conceptual understanding of the data (measurements close in time would be expected to more strongly correlated than measurements which are farther away from one another) and b) lower Akaike information criteria (AIC) in comparison to other covariance structures. The interaction term between week of life and chorioamnionitis status indicated whether or not the cytokine trajectories differed. Least square mean values from SAS Proc Mixed were graphed to allow for a clearer understanding of trajectory differences. p-values of < 0.05 were considered significant. Results: Characteristics of Study Subjects A total of 61 preterm neonates were enrolled in this study, including 27 exposed to chorioamnionitis and 34 unexposed. Subjects ranged from 22 to 32 weeks’ gestational age at birth and were followed to 42 weeks’ postmenstrual age, discharge or death, whichever came first. Table 1 describes characteristics of the two study groups. Chorioamnionitis-exposed preterm neonates were younger, more likely to be African American and more likely to be born by vaginal delivery than unexposed preterm neonates. Table 1 Study group characteristics. Chorioamnionitis-exposed Preterm Neonates (n = 27) Unexposed Preterm Neonates (n = 34) p-value Birth gestational age in weeks (mean ± SD) 27.03 ± 2.7 28.69 ± 2.99 0.028* Birth weight in grams (mean ± SD) 1051 ± 363 1181 ± 544 0.44 Male sex 10 (37%) 20 (59%) 0.09 Ethnicity - Caucasian - African American - Other 16 (59%) 7 (26%) 4 (15%) 27 (79%) 1 (3%) 6 (18%) 0.09 0.008* 0.77 C-section 19 (70%) 32 (94%) 0.01* Antenatal steroids at least 12 hours prior to delivery 23 (85%) 23 (68%) 0.11 Multiple gestation 16 (59%) 20 (59%) 0.97 Early onset sepsis (blood culture positive within 72 hours of birth) 4 (15%) 1 (3%) 0.09 Late onset sepsis (blood culture positive after 72 hours of life) 4 (15%) 5 (15%) 0.99 Ventilator associated pneumonia 3 (11%) 4 (12%) 0.94 Urinary tract infection 2 (7%) 7 (21%) 0.15 Necrotizing enterocolitis (Bell’s stage II or greater) 2 (7%) 5 (15%) 0.37 Spontaneous intestinal perforation 3 (11%) 2 (6%) 0.46 *p < 0.05. Quantitative variables were compared using the student’s t-test for parametric data, the Mann-Whitney test for nonparametric data and categorical variables were compared using the Chi-square test. Cytokine and Chemokine Measurements During Initial Two Weeks of Life Levels of 7 cytokines and chemokines known to be important in innate immunity were measured in residual neonatal serum (Table 2 ). We first sought to investigate the change in cytokine and chemokine levels from the first week of life to the second in all of the preterm neonates regardless of chorioamnionitis exposure. We directly compared all cytokine and chemokine levels from each infant averaged over the first week of life to its average levels in the second week of life using a matched comparison, with each infant compared to itself at two different points in time. Levels from the first week of life were significantly higher than those in week two for the following cytokines and chemokines: IL-6, IL-8, CCL2 and CCL3 (Fig. 1 ). Table 2 Characteristics of the seven cytokines and chemokines included in the study. Cytokine/ Chemokine Produced By Pro- or Anti-Inflammatory Function IL-1β Macrophages, fibroblasts, epithelial cells, endothelial cells Pro Involved in cell proliferation and differentiation; important to the acute phase response to assist in the clearance of microorganisms (29) IL-6 Macrophages, T cells, B cells, fibroblasts, epithelial cells, endothelial cells Both Secreted by macrophages; important to the acute phase response to assist in the clearance of microorganisms (29, 30) IL-10 T regulatory cells, CD4 Th2 cells Anti A CD4 + regulatory cytokine; important for immune homeostasis, suppresses autoinflammation (31) IL-8 Macrophages, endothelial cells, epithelial cells and airways smooth muscle cells Pro Induces chemotaxis in granulocytes, causing them to migrate toward the site of infection; stimulates bacterial phagocytosis (32) TNF-α Macrophages, Th1 cells, Th2 cells Both Involved in signaling via TNFR1 and TNFR2; has both pro- and anti-inflammatory effects; important to the acute phase response to assist in the clearance of microorganisms (29) CCL2 Monocytes, dendritic cells, endothelial cells Pro Recruits monocytes macrophages and neutrophils to local sites of infection and are necessary for prominent signaling pathways in the neonatal immune system (33) CCL3 Macrophages, osteoblasts Pro Recruits monocytes macrophages and neutrophils to local sites of infection and are necessary for prominent signaling pathways in the neonatal immune system (33) Cytokine and Chemokine Trends Over the First Month of Life We then stratified the preterm neonates into chorioamnionitis-exposed or unexposed based on histoplacental pathology and compared the levels of serum cytokines and chemokines by time post birth. The following epochs were compared between the same subject: week 1 (day of life 1–7), week 2 (day of life 8–14), week 3 (day of life 15–21), week 4 (day of life 22–28) and beyond 4 weeks (29 + days of life). General Estimating Equations were used to evaluate for changes in cytokine trends over the first four weeks of life in the different exposure groups as the data was longitudinal, paired and non-parametric with missing data points for some subjects. Unexposed and chorioamnionitis-exposed preterm neonates demonstrated changes in IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 during the first month of life (Fig. 2 A-F). Chorioamnionitis-exposed preterm neonates demonstrated changes in CCL3 over the first month of life but unexposed preterm neonates did not (Fig. 2 G). In general, unexposed preterm neonates demonstrated elevated levels of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 in the first one to two weeks of life with a decrease to what appears to be baseline levels by the third week of life (Fig. 2 ). This is in contrast to chorioamnionitis-exposed preterm neonates, who demonstrated differences in cytokine levels over the first month of life but without a predictable pattern (Fig. 2 ). Direct comparisons between the different time points are detailed in Supplementary Table 3 . Cytokine and Chemokine Trajectories Between Chorioamnionitis-exposed and unexposed preterm neonates Repeated measures of regression were then performed to look at the effect of chorioamnionitis status on the trajectory of cytokines over the 12 weeks following birth. This analysis controlled for gestational age, race/ethnicity and mode of delivery, as all of these variables were found to differ between exposure groups on univariate analysis. The trajectories of IL-10 and TNF-a differed between chorioamnionitis-exposed and unexposed neonates, while there were no differences in the trajectories of IL-1b, IL-6, IL-8, CCL2 or CCL3 between groups (Fig. 3 ). Discussion: Neonatal infections are a cause of significant morbidity and mortality in preterm neonates during their hospitalization in the NICU ( 2 ). It is known that preterm neonates exposed to chorioamnionitis have an increased risk of developing early-onset sepsis (blood stream infection that occurs within the first 72 hours of life) ( 21 , 24 , 34 ). It is unclear if this infection risk is due to a common pathogen causing both conditions or alterations in the neonatal immune response following chorioamnionitis exposure, or both. Multiple studies have shown that exposure to chorioamnionitis impacts the neonatal immune system by altering gene transcription and innate immune responses ( 20 – 22 ). These altered immune responses include dampened pro-inflammatory cytokine expression when a second pathogen is encountered ( 21 , 22 ). Appropriate pro-inflammatory cytokine expression is necessary for the clearance of microorganisms, so these chorioamnionitis-induced changes to neonatal immune responses are thought to be at least partially responsible for this increased risk of infection. However, it is unclear how long chorioamnionitis-induced dampened cytokine expression persists, as studies are conflicting about whether chorioamnionitis exposure protects against or increases the risk for developing late onset sepsis (blood stream infection that presents after 72 hours of life) ( 24 , 35 – 37 ). To assess the persistence of chorioamnionitis-induced dampened pro-inflammatory cytokine expression in preterm neonates, we performed longitudinal cytokine and chemokine profiling in very preterm neonates from birth to NICU discharge. We chose a panel of cytokines and chemokines known to be significant contributors to neonatal immune responses. Neonates primarily rely upon the innate immune system early in life to protect against infections due to limited antigen exposure in utero and major deficiencies in adaptive immune responses ( 38 , 39 ). Innate immune cells, including monocytes, macrophages and neutrophils, require signaling from cellular messengers such as cytokines and chemokines in order to mount a coordinated response to an infectious pathogen ( 40 ). CCL2 and CCL3 are chemokines that recruits monocytes, macrophages and neutrophils to local sites of infection and are necessary for prominent signaling pathways in the neonatal immune system ( 33 ). IL-8 shows similar chemotactic affinity for neutrophils and stimulates bacterial phagocytosis ( 32 ). IL-6, IL-1b and TNF-a are pro-inflammatory cytokines important to the acute phase response necessary to assist in the clearance of microorganisms ( 29 , 30 ). IL-10 is an immunoregulatory cytokine important for immune homeostasis that also suppresses autoinflammation ( 31 ). We believe this panel of cytokines and chemokines provides a broad overview of neonatal innate immune reactivity. In this study, we used a novel method of cytokine and chemokine evaluation, using each preterm neonate as its own matched control to compare levels at different chronologic ages. While this method has previously been used to demonstrate a significant decline in IL-1b, IL-6 and TNF-a from DOL 1 to DOL 40 in term neonates, we are the first to use it to evaluate changes in cytokine and chemokine levels over time in preterm neonates ( 13 , 14 ). We found that in our population of preterm neonates, levels of IL-6, IL-8, CCL2 and CCL3 decreased between the first and second weeks of life. Non-chorioamnionitis exposed preterm neonates had a consistent decrease in levels of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 over the first month of life, reaching what appeared to be baseline levels around three weeks after birth. This is in contrast to chorioamnionitis-exposed preterm neonates, whose cytokine and chemokine levels demonstrated differences over the first month of life without a consistent pattern based on chronologic age. We additionally found that the trajectory of IL-10 and TNF-a serum levels differed between chorioamnionitis-exposed and unexposed preterm neonates. These findings are important as most of these cytokines and chemokines have been proposed as biomarkers to diagnose or predict prematurity-based complications, including sepsis, necrotizing enterocolitis and bronchopulmonary dysplasia ( 8 – 11 , 41 , 42 ). Our findings suggest that chronologic age and chorioamnionitis-exposure should be taken into consideration when using cytokines and chemokines as biomarkers in premature neonates. The altered cytokine and chemokine responses seen in the chorioamnionitis-exposed preterm neonates is in line with previous reports demonstrating altered cytokine responses from chorioamnionitis-exposed umbilical cord blood monocytes following stimulation with either LPS or Staphylococcus epidermidis ( 21 , 22 ). This chorioamnionitis-induced immune dysregulation may provide insight into immune-related complications experienced by chorioamnionitis-exposed neonates, including late onset sepsis, persistent wheezing and asthma ( 37 , 43 ). These findings suggest that exposure to early life inflammation has long-lasting consequences for preterm neonates that increases their risk for immune-related diseases well beyond the neonatal period. Our 7-plex cytokine microring resonator assay was robustly validated for all targets simultaneously to ensure reproducible results across all samples analyzed. Each assay was 38 minutes to result, creating a quick method for analyzing important clinical samples. Using this multiplexed immunoassay, we were able to collect large amounts of immunological data quickly and with little starting sample volume. This technology has the potential to provide clinically relevant information quickly for the most vulnerable patients, which could impact bedside patient care. This study has several limitations. All samples were collected from clinically indicated laboratory tests, so the timing of sample collection varied between patients and was not standardized. There were differences between the exposure groups, and chorioamnionitis-exposed subjects were more likely to be born earlier, African American and by vaginal delivery than unexposed subjects. It is unclear if these differences impacted cytokine and chemokine expression. Degree of prematurity and mode of delivery have been shown to impact immune responses in prior studies, so these factors were accounted for in out statistical evaluation ( 44 – 46 ). Samples were excluded from subjects who had a suspected or confirmed infection and were receiving antibiotics at the time of sample collection. However, samples were included from these patients later during their NICU course once the infection was treated. It is unclear if the suspected or confirmed infections influenced future cytokine and chemokine expression. Furthermore, corrections were not made for clinical differences such as mode of respiratory support, presence of BPD, steroid administration, or PDA treatment. Consistent with previous reports, chorioamnionitis-exposed preterm neonates in this study had an increased incidence of early onset sepsis ( 21 , 24 , 34 ). It is unclear what impact this had on subsequent cytokine or chemokine responses and if the presence of early onset sepsis further compounded dampened cytokine and chemokine expression. The numbers in this study are not large enough to directly address this, but future studies containing more subjects would be of benefit. Conclusions: This study demonstrated that healthy preterm neonates had a consistent decrease in levels of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 over the first month of life, reaching what appeared to be baseline levels around three weeks after birth. This same pattern of changes was not present in chorioamnionitis-exposed preterm neonates, which may reflect immune system dysregulation. The altered cytokine and chemokine trends in chorioamnionitis-exposed very preterm neonates may explain their increased risk for immune-mediated complications outside of the immediate neonatal period, including late onset sepsis, persistent wheezing and asthma. Declarations: Conflict of Interest Statement: The authors declare no competing financial interests. Funding: This project was funded through philanthropic funds from the Korneffel family and by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health AI141673. Author Contributions: GES made substantial contributions to the acquisition, analysis and interpretation of the data and wrote the initial draft of the manuscript. CAC and KLM made substantial contributions to the acquisition, analysis and interpretation of the data and critically revised the manuscript. JMS made substantial contributions to the analysis and interpretation of the data and critically revised the manuscript. LAE made substantial contributions to the design of the work, analysis and interpretation of the data and critically revised the manuscript. 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Romero R, Chaemsaithong P, Docheva N, Korzeniewski SJ, Tarca AL, Bhatti G, et al. Clinical chorioamnionitis at term V: umbilical cord plasma cytokine profile in the context of a systemic maternal inflammatory response. J Perinat Med. 2016; 44: 53–76. de Jong E, Hancock DG, Wells C, Richmond P, Simmer K, Burgner D, et al. Exposure to chorioamnionitis alters the monocyte transcriptional response to the neonatal pathogen Staphylococcus epidermidis. Immunol Cell Biol. 2018; 96: 792–804. Bermick J, Gallagher K, denDekker A, Kunkel S, Lukacs N, Schaller M. Chorioamnionitis exposure remodels the unique histone modification landscape of neonatal monocytes and alters the expression of immune pathway genes. FEBS J. 2019; 286: 82–109. Schrag SJ, Hadler JL, Arnold KE, Martell-Cleary P, Reingold A, Schuchat A. Risk factors for invasive, early-onset Escherichia coli infections in the era of widespread intrapartum antibiotic use. Pediatrics. 2006; 118: 570–576. Garcia-Munoz Rodrigo F, Galan Henriquez G, Figueras Aloy J, Garcia-Alix Perez A. Outcomes of very-low-birth-weight infants exposed to maternal clinical chorioamnionitis: a multicentre study. Neonatology. 2014; 106: 229–234. Redline RW, Faye-Petersen O, Heller D, Qureshi F, Savell V, Vogler C, et al. Amniotic infection syndrome: nosology and reproducibility of placental reaction patterns. Pediatr Dev Pathol. 2003; 6: 435–448. Robison HM, Bailey RC. A Guide to Quantitative Biomarker Assay Development using Whispering Gallery Mode Biosensors. Curr Protoc Chem Biol. 2017; 9: 158–173. Robison HM, Escalante P, Valera E, Erskine CL, Auvil L, Sasieta HC, et al. Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification. Integr Biol (Camb). 2019; 11: 16–25. Mudumba S, de Alba S, Romero R, Cherwien C, Wu A, Wang J, et al. Photonic ring resonance is a versatile platform for performing multiplex immunoassays in real time. J Immunol Methods. 2017; 448: 34–43. de Bont ES, Martens A, van Raan J, Samson G, Fetter WP, Okken A, et al. Tumor necrosis factor-alpha, interleukin-1 beta, and interleukin-6 plasma levels in neonatal sepsis. Pediatr Res. 1993; 33: 380–383. Dulay AT, Buhimschi IA, Zhao G, Bahtiyar MO, Thung SF, Cackovic M, et al. Compartmentalization of acute phase reactants Interleukin-6, C-Reactive Protein and Procalcitonin as biomarkers of intra-amniotic infection and chorioamnionitis. Cytokine. 2015; 76: 236–243. Ye Q, Du LZ, Shao WX, Shang SQ. Utility of cytokines to predict neonatal sepsis. Pediatr Res. 2017; 81: 616–621. Franz AR, Steinbach G, Kron M, Pohlandt F. Interleukin-8: a valuable tool to restrict antibiotic therapy in newborn infants. Acta Paediatr. 2001; 90: 1025–1032. Kinjo T, Ohga S, Ochiai M, Honjo S, Tanaka T, Takahata Y, et al. Serum chemokine levels and developmental outcome in preterm infants. Early Hum Dev. 2011; 87: 439–443. Ofman G, Vasco N, Cantey JB. Risk of Early-Onset Sepsis following Preterm, Prolonged Rupture of Membranes with or without Chorioamnionitis. Am J Perinatol. 2016; 33: 339–342. Strunk T, Doherty D, Jacques A, Simmer K, Richmond P, Kohan R, et al. Histologic chorioamnionitis is associated with reduced risk of late-onset sepsis in preterm infants. Pediatrics. 2012; 129: e134-41. Puri K, Taft DH, Ambalavanan N, Schibler KR, Morrow AL, Kallapur SG. Association of Chorioamnionitis with Aberrant Neonatal Gut Colonization and Adverse Clinical Outcomes. PLoS One. 2016; 11: e0162734. Villamor-Martinez E, Lubach GA, Rahim OM, Degraeuwe P, Zimmermann LJ, Kramer BW, et al. Association of Histological and Clinical Chorioamnionitis With Neonatal Sepsis Among Preterm Infants: A Systematic Review, Meta-Analysis, and Meta-Regression. Front Immunol. 2020; 11: 972. Canto E, Rodriguez-Sanchez JL, Vidal S. Distinctive response of naive lymphocytes from cord blood to primary activation via TCR. J Leukoc Biol. 2003; 74: 998–1007. Marodi L. Down-regulation of Th1 responses in human neonates. Clin Exp Immunol. 2002; 128: 1–2. Iroh Tam PY, Bendel CM. Diagnostics for neonatal sepsis: current approaches and future directions. Pediatr Res. 2017; 82: 574–583. Maheshwari A, Schelonka RL, Dimmitt RA, Carlo WA, Munoz-Hernandez B, Das A, et al. Cytokines associated with necrotizing enterocolitis in extremely-low-birth-weight infants. Pediatr Res. 2014; 76: 100–108. Sahni M, Yeboah B, Das P, Shah D, Ponnalagu D, Singh H, et al. Novel biomarkers of bronchopulmonary dysplasia and bronchopulmonary dysplasia-associated pulmonary hypertension. J Perinatol. 2020; 40: 1634–1643. Kumar R, Yu Y, Story RE, Pongracic JA, Gupta R, Pearson C, et al. Prematurity, chorioamnionitis, and the development of recurrent wheezing: a prospective birth cohort study. J Allergy Clin Immunol. 2008; 121: 878–884 e6. Sharma AA, Jen R, Kan B, Sharma A, Marchant E, Tang A, et al. Impaired NLRP3 inflammasome activity during fetal development regulates IL-1beta production in human monocytes. Eur J Immunol. 2015; 45: 238–249. Strunk T, Prosser A, Levy O, Philbin V, Simmer K, Doherty D, et al. Responsiveness of human monocytes to the commensal bacterium Staphylococcus epidermidis develops late in gestation. Pediatr Res. 2012; 72: 10–18. Jakobsson HE, Abrahamsson TR, Jenmalm MC, Harris K, Quince C, Jernberg C, et al. Decreased gut microbiota diversity, delayed Bacteroidetes colonisation and reduced Th1 responses in infants delivered by caesarean section. Gut. 2014; 63: 559–566. Additional Declarations There is NO conflict of interest to disclose. Supplementary Files CytokineSupportingTables.docx SupplementaryFig1.tif Cite Share Download PDF Status: Published Journal Publication published 20 Dec, 2022 Read the published version in Journal of Perinatology → Version 1 posted Editorial decision: revise 26 Jul, 2022 Review # 2 received at journal 23 Jul, 2022 Review # 1 received at journal 05 Jul, 2022 Reviewer # 2 agreed at journal 26 Jun, 2022 Reviewer # 1 agreed at journal 20 Jun, 2022 Reviewers invited by journal 20 Jun, 2022 Submission checks completed at journal 17 Jun, 2022 Editor assigned by journal 16 Jun, 2022 First submitted to journal 16 Jun, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1766505","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":115041766,"identity":"27eb0a3a-e045-4efc-aa0e-050d2a88f70a","order_by":0,"name":"Gretchen Stepanovich","email":"","orcid":"","institution":"University of Michigan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gretchen","middleName":"","lastName":"Stepanovich","suffix":""},{"id":115041767,"identity":"573591b5-db06-48d3-bd05-c074c5b8cc4e","order_by":1,"name":"Cole Chapman","email":"","orcid":"","institution":"University of Michigan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cole","middleName":"","lastName":"Chapman","suffix":""},{"id":115041768,"identity":"17097809-37c4-48e3-8b57-582cad8d186b","order_by":2,"name":"Krista Meserve","email":"","orcid":"https://orcid.org/0000-0002-9398-9158","institution":"University of Michigan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Krista","middleName":"","lastName":"Meserve","suffix":""},{"id":115041769,"identity":"6d008856-85e6-4e8a-a385-fc47c99e7e1f","order_by":3,"name":"Julie Sturza","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Julie","middleName":"","lastName":"Sturza","suffix":""},{"id":115041770,"identity":"35db0da0-f670-4a31-b2be-e6718d17328f","order_by":4,"name":"Lindsay Ellsworth","email":"","orcid":"https://orcid.org/0000-0002-6395-7550","institution":"University of Michigan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lindsay","middleName":"","lastName":"Ellsworth","suffix":""},{"id":115041771,"identity":"3f2a70f0-5a8f-49f5-93fb-56e15f651683","order_by":5,"name":"Ryan Bailey","email":"","orcid":"","institution":"University of Michigan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ryan","middleName":"","lastName":"Bailey","suffix":""},{"id":115041772,"identity":"76893ead-4754-46df-8d9a-bd6562ff4fd2","order_by":6,"name":"Jennifer Bermick","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIie3Rv0rEMBzA8Z8UnMq5ptzhvcKvBAJCqa+SUrhbIucDCFcpXBf/rBUHX8FHKAhxKc4ZW251UpAb/Jd4WBwSXR3yHQJN+iFpA+Dz/cN2Cj3wRA/EPCLg3nZO1/xGZj9IVPxBtg1EIxzedJCgOpddx5MFjEv5pI5TSlV+ug5PYH+kuP1gZw9z5Hx2UExkfi0wZ0xlJQ0l0MhFasFItrnDQyVoILBJNFmNxS5kty5y88gI5x8IZPH8RWhtyDssnaQODWk0EYEhDIkmRyvg6PwWYUiOMJHmYDklbV/StwsSX7WdlcRVy6INT1H/sXUgXtP4spr3ff2STEf39l3iwjo9XJOlqXPF5/P5fN99Aj3YXF/xJNcuAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-0245-946X","institution":"University of Iowa","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jennifer","middleName":"","lastName":"Bermick","suffix":""}],"badges":[],"createdAt":"2022-06-16 23:00:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1766505/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1766505/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41372-022-01584-2","type":"published","date":"2022-12-20T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":22966467,"identity":"232a5e79-3a7b-4032-9790-df4aafa46903","added_by":"auto","created_at":"2022-06-22 19:56:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":510318,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of cytokines and chemokines obtained in the first and second weeks of life in preterm neonates. Serum protein levels were measured and compared between the same subject during the first and second weeks of life. If more than one serum level was obtained during each week, then the average level was used for comparison. Serum protein levels are demonstrated for A) IL-1b, B) IL-6, C) IL-8, D) IL-10, E) TNF-a, F) CCL2 and G) CCL3. First week n=37, second week n=37. Wilcoxon test used to determine statistical significance. *p\u0026lt;0.05, **p\u0026lt;0.01, ****p\u0026lt;0.0001. Mean ± standard error of the mean for each protein level shown below each x-axis label.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1766505/v1/92a1589ba54a978956bab61d.png"},{"id":22966297,"identity":"bddf69e7-5a17-4ebc-9c7b-f854c3d4b62c","added_by":"auto","created_at":"2022-06-22 19:51:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":549627,"visible":true,"origin":"","legend":"\u003cp\u003eLongitudinal cytokine and chemokine trends over time in chorioamnionitis-exposed and unexposed preterm neonates. Serum protein levels were measured and compared between the same subject during day of life (DOL) 1-7, 8-14, 15-21, 22-28 and 29 and beyond. If more than one serum level was obtained during each timeframe, then the average level was used for comparison. Serum protein levels are demonstrated in chorioamnionitis-exposed (white circles) and unexposed (black circles) preterm neonates for A) IL-1b, B) IL-6, C) IL-8, D) IL-10, E) TNF-a, F) CCL2 and G) CCL3. Unexposed n=28, chorioamnionitis-exposed n=17. General Estimating Equations were used to determine statistical significance. Circles represent mean levels and error bars represent standard error of the mean. p-values for differences in trends over time are shown.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1766505/v1/8e8a8c51198149b89b6ba1ac.png"},{"id":22966300,"identity":"9c704e53-78d2-4f00-8e0b-1655237481b9","added_by":"auto","created_at":"2022-06-22 19:51:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":579747,"visible":true,"origin":"","legend":"\u003cp\u003eLongitudinal cytokine and chemokine trajectories over time in chorioamnionitis-exposed and unexposed preterm neonates.\u0026nbsp;If more than one serum level was obtained for a patient during each timeframe, then the average level was used for comparison. The lsmean of serum protein levels are demonstrated in chorioamnionitis-exposed (white circles) and unexposed (black circles) preterm neonates for A) IL-1b, B) IL-6, C) IL-8, D) IL-10, E) TNF-a, F) CCL2 and G) CCL3.\u0026nbsp;Unexposed n=34, chorioamnionitis-exposed n=27. \u0026nbsp;\u0026nbsp;SAS Proc Mixed was used to perform repeated measures of regression to look at the effect of chorioamnionitis status on the trajectory of cytokines over time, while controlling for gestational age, ethnicity, and mode of delivery.\u0026nbsp;\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1766505/v1/62ac4b9a4896fe4fd94f0c4e.png"},{"id":30610448,"identity":"b3bf4456-9924-453c-b704-33e71ef4425a","added_by":"auto","created_at":"2022-12-21 08:08:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1037772,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1766505/v1/6be0bc27-91f9-43a6-b5d6-bacaae3d8997.pdf"},{"id":22966301,"identity":"960c933b-0a84-4e2b-99fc-604a398951e8","added_by":"auto","created_at":"2022-06-22 19:51:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33329,"visible":true,"origin":"","legend":"","description":"","filename":"CytokineSupportingTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-1766505/v1/39b9309f1ac5ff745cb93a37.docx"},{"id":22966610,"identity":"bdbbfb28-36a1-4d54-a19f-91f4a8d1b48a","added_by":"auto","created_at":"2022-06-22 20:01:33","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1414696,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFig1.tif","url":"https://assets-eu.researchsquare.com/files/rs-1766505/v1/8593973e0c37786eff0d2b55.tif"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Chorioamnionitis-exposure alters serum cytokine trends in premature neonates","fulltext":[{"header":"Introduction:","content":"\u003cp\u003eBlood stream infections are a significant cause of morbidity and mortality for preterm infants in Neonatal Intensive Care Units (NICUs) worldwide. Preterm birth, defined as delivery that occurs prior to 37 weeks\u0026rsquo; gestation, complicates approximately 11% of births globally (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e). Those neonates born very preterm, prior to 32 weeks of completed gestation, are at risk for numerous morbidities during their hospitalization including an increased risk for sepsis. Up to 5% of very preterm neonates develop culture positive sepsis during their initial NICU stay compared to only 0.1% of term neonates (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e). Infection risk is often attributed to immaturity of the preterm immune system, particularly the innate immune system. The innate immune system includes primitive barriers such as skin, gastric acidity and cilia within the pulmonary tract, as well as non-specific cells and molecules within the immune system such as neutrophils, monocytes, macrophages and natural killer cells. The immune system cellular response is directed by cytokines and chemokines, which are peptides or proteins that participate in cell signaling. Appropriate cytokines and chemokine responses are necessary for the defense against pathogens. The natural evolution of these responses in premature neonates is poorly understood.\u003c/p\u003e\n\u003cp\u003eMany strategies have been implemented in NICUs to reduce the likelihood of developing sepsis, including central catheter bundles, earlier removal of indwelling devices, use of breast milk, administration of probiotics and strict hand-washing protocols (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e). Early sepsis detection and prompt initiation of antibiotic therapy significantly improves outcomes in neonatal sepsis (\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e). In practice, early sepsis detection is difficult as signs of infection in the neonatal population are often non-specific. The gold standard test to diagnose a blood stream infection is a blood culture that demonstrates growth of a pathogenic organism, however this often takes at least 24 hours to result (\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e). Several biomarkers are commonly used to support or refute the presence of infection, including C-reactive protein, procalcitonin and the presence of many immature forms of neutrophils (\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e). These biomarkers are non-specific, and are often more useful to rule infection out rather than diagnose it. Several cytokines have been proposed as useful biomarkers to diagnose neonatal sepsis, including IL-1b, IL-6, IL-8, IL-10 and TNF-a (\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e). While cytokines hold great promise as biomarkers to diagnose neonatal sepsis, they often take days to result and lack normal reference ranges for neonates, particularly preterm neonates. These factors contribute to the continued difficulty in prompt diagnosis and treatment of neonatal sepsis, leading to unacceptable mortality rates.\u003c/p\u003e\n\u003cp\u003eThe period around labor and delivery is a highly inflammatory process, with elevated maternal levels of IL-1b, IL-6 and TNF-a (\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e). Elevated levels of these same cytokines have also been demonstrated in neonatal samples following delivery (\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e). It is unclear how these cytokine levels change over time in neonates, and whether values should be considered based upon gestational age or chronological age in preterm neonates. Several studies have begun to address these knowledge gaps. Matoba et al reported 12 umbilical cord blood cytokine levels to be increased, five to be decreased and 10 to be unchanged between infants born prematurely and those born at term (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e). Subsequently, Lusyati et al reported levels of 25 cytokines to be stable throughout the first seven days of life, with infants born before 36 weeks\u0026rsquo; gestation expressing lower levels of 14 of these cytokines compared to infants born at term (\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e). These decreased cytokine responses are thought to contribute to a preterm neonate\u0026rsquo;s heightened susceptibility to infection as appropriate cytokine responses are necessary to guide the clearance of microorganisms (\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePreterm delivery is often complicated and may even be stimulated by intrauterine inflammation and/or infection, termed chorioamnionitis (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e). Chorioamnionitis is present in up to 70% of very preterm deliveries and leads to an initial fetal pro-inflammatory response, including increased expression of the pro-inflammatory cytokines IL-1b, IL-6, IL-8 and TNF-a (\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e). This fetal inflammatory response alters the developing immune system, resulting in decreased pro-inflammatory cytokine expression when umbilical cord blood monocytes from chorioamnionitis-exposed neonates undergo a secondary challenge with either LPS or \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e). Chorioamnionitis exposure is known to increase the risk of developing both early and late onset neonatal sepsis, which may be at least partially due to these dampened monocyte responses (\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e). It is currently unclear how long this chorioamnionitis-induced immune hypo-responsiveness persists, which could impact susceptibility to infection outside of the immediate neonatal period and may have long-term immune phenotype implications for the development of chronic disease.\u003c/p\u003e\n\u003cp\u003eTo better understand how inflammatory mediators change over time in preterm neonates, we performed longitudinal cytokine and chemokine profiling. To investigate the impact of chorioamnionitis exposure on these inflammatory markers, we differentiated and compared these inflammatory markers between preterm neonates exposed to maternal chorioamnionitis and those that were unexposed. For this study, we developed a 7-plex cytokine and chemokine assay to measure concentrations of CCL2, CCL3, IL-1\u0026beta;, IL-6, IL-8, IL-10, and TNF-\u0026alpha; in neonatal serum samples. Using less than 200 \u0026micro;L of residual serum from clinically indicated routine blood tests, we compared cytokine and chemokine levels throughout an neonate\u0026rsquo;s NICU course in an effort to establish baseline levels, evaluate changes over time, and examine the impact of exposure to maternal chorioamnionitis.\u003c/p\u003e"},{"header":"Methods:","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003ePatient Recruitment and Blood Collection\u003c/h2\u003e\n \u003cp\u003eThis study was approved by the University of Michigan IRB. This study was performed in accordance with the Declaration of Helsinki. After informed written parental consent was obtained, residual serum was collected prospectively from clinically indicated lab draws of neonates born at less than 33 weeks\u0026rsquo; gestational age. Serum samples were collected from 61 patients from birth through 42 weeks\u0026rsquo; postmenstrual age, death or discharge, whichever occurred first. This cohort included 27 chorioamnionitis-exposed and 34 unexposed preterm infants. Sample collection occurred from April, 2019 through April, 2021. Histopathologic examination of the placenta was used to diagnose chorioamnionitis (\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e). The blood volume collected with each sample varied, as the serum available for testing was what remained after all clinically ordered testing was performed. As 200 \u0026micro;L was required for performance of the cytokine assay, samples were pooled if collected within three days of one another and the subject had no significant change in clinical status. A total of 397 residual serum samples were collected. Samples were excluded from data evaluation if the subject had a suspected or confirmed infection and was being treated with antibiotics at the time of sample collection (sepsis, urinary tract infection, pneumonia, necrotizing enterocolitis or spontaneous intestinal perforation), excluding 100 samples from analysis. A total of 297 serum samples were included in the final analysis. Samples were frozen and stored in a -80\u0026deg; C freezer prior to use.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eReagents and Buffers\u003c/h2\u003e\n \u003cp\u003eDulbecco\u0026rsquo;s phosphate buffered saline (PBS, catalog # D5573), bovine serum albumin (BSA, catalog # A2153), and (3-Aminopropyl) triethoxysilane (catalog # 440140) were purchased from Millipore Sigma (St. Louis, MO USA). Glycerol (catalog # BP229), bis(sulfosuccinimidyl)suberate (catalog # A39266), starting block blocking buffer (catalog # 37538), Pierce high sensitivity streptavidin-HRP (SA-HRP, catalog # 21130), and 4-chloronaphthol (4-CN, catalog # 34012) were purchased from Thermo Fisher Scientific (Waltham, MA USA). Drycoat assay stabilizer (catalog # AG066) was obtained from Virusys Corporation (Taneytown, MD USA). Vendors and catalog numbers for antibodies for all multiplexed assay components are summarized in \u003cstrong\u003eSupplementary Table\u0026nbsp;1\u003c/strong\u003e. Running buffer for all assays was 0.5% BSA in 1X PBS, pH 7.4.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eMultiplexed Immunoassays\u003c/h2\u003e\n \u003cp\u003eMicroring resonator immunoassays were validated and performed on the Maverick M1 and Matchbox systems (San Diego, CA USA), respectively, as previously described (\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e). The Maverick instruments use microfluidic systems for automated reagent handling. The M1 uses reusable cartridge devices and the Matchbox uses disposable, injection-molded, plug-and-play devices (\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e). Microring chips were functionalized with capture antibodies using an amine-reactive, homobifunctional crosslinker to create a 7-plex cytokine and chemokine capture array. Each capture antibody spanned two clusters of four microring sensors in each of the two microfluidic channels, giving n\u0026thinsp;=\u0026thinsp;8 technical replicates of each target cytokine or chemokine per channel. After introducing the sample to the chip surface, a mixture of all tracer antibodies was flowed across the chip, followed by streptavidin-tagged enzymes and a signal amplification reagent. Assays were performed at a 30 \u0026micro;l/min flow rate for all steps. There was an initial rinse of 5 minutes with the running buffer to ensure equilibration of the chip prior to sample analysis. The assay included steps as follows: 1) running buffer (2 min); 2) sample (7 min); 3) running buffer rinse (2 min); 4) biotinylated tracer antibodies (7 min); 5) running buffer rinse (2 min); 6) SA-HRP (7 min); 7) running buffer rinse (2 min); 8) 4-CN (7 min); 9) running buffer rinse (2 min). The total assay time was 38 minutes (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1A\u003c/strong\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eImmunoassay Calibrations\u003c/h2\u003e\n \u003cp\u003eThe 7-plex immunoassay was simultaneously calibrated for all analytes in a multiplexed format, as described previously.(\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e) Serial dilutions from a mixed saturating analyte sample of all multiplexed targets were used to construct eight-point calibration curves correlating net sensor shifts to target concentrations. To quantify, the signal before the enhancement step (t\u0026thinsp;=\u0026thinsp;29 min) was subtracted from the signal after the final assay rinse step (t\u0026thinsp;=\u0026thinsp;38 min). These net resonance wavelength shifts (∆pm) were plotted as a function of standard concentration and fit to a four-parametric logistic function (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1B\u003c/strong\u003e). Limits of detection (LOD) and quantification (LOQ) were defined as the blank signal plus 3 times and 10 times the standard deviation of the blank, respectively (\u003cstrong\u003eSupplementary Table\u0026nbsp;2\u003c/strong\u003e). Each calibration was performed at least in triplicate for each sample dilution as measured with 8 sensors per technical replicate.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eSample Evaluation\u003c/h2\u003e\n \u003cp\u003eAll samples contained at least 200 \u0026micro;L of residual serum. Neonatal residual serum samples were analyzed at two dilutions (0.5X and 0.1X) in running buffer using the same steps highlighted in \u003cstrong\u003eSupplementary Fig.\u0026nbsp;1A\u003c/strong\u003e. To quantify, the net shift surrounding the amplification step for each target was correlated to concentration using the corresponding standard calibration curve, 50% serum or 10% serum, matching the serum content of the residual serum dilution. The most appropriate dilution to use for statistical analysis was selected by choosing the dilution with the relative shift closest to the inflection point of the respective calibration curve.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eBasic statistical analysis was performed in GraphPad Prism 8. Data normality was evaluated using the Shapiro-Wilk test. Study group characteristics were compared using the student\u0026rsquo;s t-test for quantitative parametric data, the Mann-Whitney test for nonparametric data and the Chi-square test for categorical variables. p-values of \u0026lt;\u0026thinsp;0.05 were considered significant. Cytokine and chemokine levels were compared between the first and second weeks of life in the same subject using the Wilcoxon matched-pairs signed rank test. If there was more than one data point within these time frames, the data points were averaged to create a single mean level for each week. p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant for this analysis method.\u003c/p\u003e\n \u003cp\u003eGeneral Estimating Equations were used in SPSS 28.0.1.0 to evaluate for changes in cytokine trends over the first four weeks of life in the chorioamnionitis-exposed and unexposed groups as the data was longitudinal, paired and non-parametric with missing data points for some subjects. The General Estimating Equations used a robust covariance matrix, an unstructured working correlation matrix and a Tweedie with log link model. If there was more than one data point within each time frame, the data points were averaged to create a single mean level for each week. p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant for the comparison of overall trends within each exposure group. However, when individual timepoints were compared within exposure groups, p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.01 were considered significant to correct for multiple comparisons.\u003c/p\u003e\n \u003cp\u003eSubjects were then separated into those exposed to maternal chorioamnionitis and those who were unexposed and cytokine and chemokine levels from each subject were compared over time by week-of-life (chronologic age). When there was more than one data point in a week, all points within that week were averaged to create a single mean cytokine level. Univariate statistics showed that the cytokines were not normally distributed and were largely right skewed, with many zeros, representing cytokine levels below the limit of detection. To transform the data to approximate a normal distribution more appropriate for modeling, the natural log of (cytokine level\u0026thinsp;+\u0026thinsp;x, where x is a positive value that varies based on the cytokine in question) was used. SAS Proc Mixed was used to perform repeated measures regression to look at the effect of chorioamnionitis status on the trajectory of cytokines over time while controlling for gestational age, ethnicity, and birth via C-section, all of which were found to be statistically different between exposure groups. Analyses were restricted to the first twelve weeks of life as the chorioamnionitis-exposed group had no data points beyond the first twelve weeks of life. Autoregressive covariance structure was selected based upon a) a conceptual understanding of the data (measurements close in time would be expected to more strongly correlated than measurements which are farther away from one another) and b) lower Akaike information criteria (AIC) in comparison to other covariance structures. The interaction term between week of life and chorioamnionitis status indicated whether or not the cytokine trajectories differed. Least square mean values from SAS Proc Mixed were graphed to allow for a clearer understanding of trajectory differences. p-values of \u0026lt;\u0026thinsp;0.05 were considered significant.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results:","content":"\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eCharacteristics of Study Subjects\u003c/h2\u003e\n \u003cp\u003eA total of 61 preterm neonates were enrolled in this study, including 27 exposed to chorioamnionitis and 34 unexposed. Subjects ranged from 22 to 32 weeks\u0026rsquo; gestational age at birth and were followed to 42 weeks\u0026rsquo; postmenstrual age, discharge or death, whichever came first. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e describes characteristics of the two study groups. Chorioamnionitis-exposed preterm neonates were younger, more likely to be African American and more likely to be born by vaginal delivery than unexposed preterm neonates.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eStudy group characteristics.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChorioamnionitis-exposed Preterm Neonates\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnexposed Preterm Neonates\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth gestational age in weeks (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.028*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth weight in grams (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1051\u0026thinsp;\u0026plusmn;\u0026thinsp;363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1181\u0026thinsp;\u0026plusmn;\u0026thinsp;544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale sex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e- \u003cstrong\u003eCaucasian\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e- \u003cstrong\u003eAfrican American\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e- \u003cstrong\u003eOther\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (59%)\u003c/p\u003e\n \u003cp\u003e7 (26%)\u003c/p\u003e\n \u003cp\u003e4 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (79%)\u003c/p\u003e\n \u003cp\u003e1 (3%)\u003c/p\u003e\n \u003cp\u003e6 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-section\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntenatal steroids at least 12 hours prior to delivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultiple gestation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly onset sepsis (blood culture positive within 72 hours of birth)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate onset sepsis (blood culture positive after 72 hours of life)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVentilator associated pneumonia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrinary tract infection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNecrotizing enterocolitis (Bell\u0026rsquo;s stage II or greater)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpontaneous intestinal perforation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Quantitative variables were compared using the student\u0026rsquo;s t-test for parametric data, the Mann-Whitney test for nonparametric data and categorical variables were compared using the Chi-square test.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eCytokine and Chemokine Measurements During Initial Two Weeks of Life\u003c/h2\u003e\n \u003cp\u003eLevels of 7 cytokines and chemokines known to be important in innate immunity were measured in residual neonatal serum (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). We first sought to investigate the change in cytokine and chemokine levels from the first week of life to the second in all of the preterm neonates regardless of chorioamnionitis exposure. We directly compared all cytokine and chemokine levels from each infant averaged over the first week of life to its average levels in the second week of life using a matched comparison, with each infant compared to itself at two different points in time. Levels from the first week of life were significantly higher than those in week two for the following cytokines and chemokines: IL-6, IL-8, CCL2 and CCL3 (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of the seven cytokines and chemokines included in the study.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCytokine/\u003c/p\u003e\n \u003cp\u003eChemokine\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProduced By\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePro- or Anti-Inflammatory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFunction\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIL-1\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMacrophages, fibroblasts, epithelial cells, endothelial cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvolved in cell proliferation and differentiation; important to the acute phase response to assist in the clearance of microorganisms (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMacrophages, T cells, B cells, fibroblasts, epithelial cells, endothelial cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecreted by macrophages; important to the acute phase response to assist in the clearance of microorganisms (29, 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIL-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT regulatory cells, CD4 Th2 cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnti\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA CD4\u0026thinsp;+\u0026thinsp;regulatory cytokine; important for immune homeostasis, suppresses autoinflammation (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIL-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMacrophages, endothelial cells, epithelial cells and airways smooth muscle cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInduces chemotaxis in granulocytes, causing them to migrate toward the site of infection; stimulates bacterial phagocytosis (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTNF-\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMacrophages, Th1 cells, Th2 cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvolved in signaling via TNFR1 and TNFR2; has both pro- and anti-inflammatory effects; important to the acute phase response to assist in the clearance of microorganisms (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonocytes, dendritic cells, endothelial cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecruits monocytes macrophages and neutrophils to local sites of infection and are necessary for prominent signaling pathways in the neonatal immune system (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMacrophages, osteoblasts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecruits monocytes macrophages and neutrophils to local sites of infection and are necessary for prominent signaling pathways in the neonatal immune system (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003eCytokine and Chemokine Trends Over the First Month of Life\u003c/h2\u003e\n \u003cp\u003eWe then stratified the preterm neonates into chorioamnionitis-exposed or unexposed based on histoplacental pathology and compared the levels of serum cytokines and chemokines by time post birth. The following epochs were compared between the same subject: week 1 (day of life 1\u0026ndash;7), week 2 (day of life 8\u0026ndash;14), week 3 (day of life 15\u0026ndash;21), week 4 (day of life 22\u0026ndash;28) and beyond 4 weeks (29\u0026thinsp;+\u0026thinsp;days of life). General Estimating Equations were used to evaluate for changes in cytokine trends over the first four weeks of life in the different exposure groups as the data was longitudinal, paired and non-parametric with missing data points for some subjects. Unexposed and chorioamnionitis-exposed preterm neonates demonstrated changes in IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 during the first month of life (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA-F). Chorioamnionitis-exposed preterm neonates demonstrated changes in CCL3 over the first month of life but unexposed preterm neonates did not (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eG). In general, unexposed preterm neonates demonstrated elevated levels of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 in the first one to two weeks of life with a decrease to what appears to be baseline levels by the third week of life (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). This is in contrast to chorioamnionitis-exposed preterm neonates, who demonstrated differences in cytokine levels over the first month of life but without a predictable pattern (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Direct comparisons between the different time points are detailed in \u003cstrong\u003eSupplementary Table\u0026nbsp;3\u003c/strong\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003eCytokine and Chemokine Trajectories Between Chorioamnionitis-exposed and unexposed preterm neonates\u003c/h2\u003e\n \u003cp\u003eRepeated measures of regression were then performed to look at the effect of chorioamnionitis status on the trajectory of cytokines over the 12 weeks following birth. This analysis controlled for gestational age, race/ethnicity and mode of delivery, as all of these variables were found to differ between exposure groups on univariate analysis. The trajectories of IL-10 and TNF-a differed between chorioamnionitis-exposed and unexposed neonates, while there were no differences in the trajectories of IL-1b, IL-6, IL-8, CCL2 or CCL3 between groups (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion:","content":"\u003cp\u003eNeonatal infections are a cause of significant morbidity and mortality in preterm neonates during their hospitalization in the NICU (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e). It is known that preterm neonates exposed to chorioamnionitis have an increased risk of developing early-onset sepsis (blood stream infection that occurs within the first 72 hours of life) (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e). It is unclear if this infection risk is due to a common pathogen causing both conditions or alterations in the neonatal immune response following chorioamnionitis exposure, or both. Multiple studies have shown that exposure to chorioamnionitis impacts the neonatal immune system by altering gene transcription and innate immune responses (\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e). These altered immune responses include dampened pro-inflammatory cytokine expression when a second pathogen is encountered (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e). Appropriate pro-inflammatory cytokine expression is necessary for the clearance of microorganisms, so these chorioamnionitis-induced changes to neonatal immune responses are thought to be at least partially responsible for this increased risk of infection. However, it is unclear how long chorioamnionitis-induced dampened cytokine expression persists, as studies are conflicting about whether chorioamnionitis exposure protects against or increases the risk for developing late onset sepsis (blood stream infection that presents after 72 hours of life) (\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eTo assess the persistence of chorioamnionitis-induced dampened pro-inflammatory cytokine expression in preterm neonates, we performed longitudinal cytokine and chemokine profiling in very preterm neonates from birth to NICU discharge. We chose a panel of cytokines and chemokines known to be significant contributors to neonatal immune responses. Neonates primarily rely upon the innate immune system early in life to protect against infections due to limited antigen exposure in utero and major deficiencies in adaptive immune responses (\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e). Innate immune cells, including monocytes, macrophages and neutrophils, require signaling from cellular messengers such as cytokines and chemokines in order to mount a coordinated response to an infectious pathogen (\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e). CCL2 and CCL3 are chemokines that recruits monocytes, macrophages and neutrophils to local sites of infection and are necessary for prominent signaling pathways in the neonatal immune system (\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e). IL-8 shows similar chemotactic affinity for neutrophils and stimulates bacterial phagocytosis (\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e). IL-6, IL-1b and TNF-a are pro-inflammatory cytokines important to the acute phase response necessary to assist in the clearance of microorganisms (\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e). IL-10 is an immunoregulatory cytokine important for immune homeostasis that also suppresses autoinflammation (\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e). We believe this panel of cytokines and chemokines provides a broad overview of neonatal innate immune reactivity.\u003c/p\u003e\n\u003cp\u003eIn this study, we used a novel method of cytokine and chemokine evaluation, using each preterm neonate as its own matched control to compare levels at different chronologic ages. While this method has previously been used to demonstrate a significant decline in IL-1b, IL-6 and TNF-a from DOL 1 to DOL 40 in term neonates, we are the first to use it to evaluate changes in cytokine and chemokine levels over time in preterm neonates (\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e). We found that in our population of preterm neonates, levels of IL-6, IL-8, CCL2 and CCL3 decreased between the first and second weeks of life. Non-chorioamnionitis exposed preterm neonates had a consistent decrease in levels of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 over the first month of life, reaching what appeared to be baseline levels around three weeks after birth. This is in contrast to chorioamnionitis-exposed preterm neonates, whose cytokine and chemokine levels demonstrated differences over the first month of life without a consistent pattern based on chronologic age. We additionally found that the trajectory of IL-10 and TNF-a serum levels differed between chorioamnionitis-exposed and unexposed preterm neonates. These findings are important as most of these cytokines and chemokines have been proposed as biomarkers to diagnose or predict prematurity-based complications, including sepsis, necrotizing enterocolitis and bronchopulmonary dysplasia (\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e). Our findings suggest that chronologic age and chorioamnionitis-exposure should be taken into consideration when using cytokines and chemokines as biomarkers in premature neonates.\u003c/p\u003e\n\u003cp\u003eThe altered cytokine and chemokine responses seen in the chorioamnionitis-exposed preterm neonates is in line with previous reports demonstrating altered cytokine responses from chorioamnionitis-exposed umbilical cord blood monocytes following stimulation with either LPS or \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e). This chorioamnionitis-induced immune dysregulation may provide insight into immune-related complications experienced by chorioamnionitis-exposed neonates, including late onset sepsis, persistent wheezing and asthma (\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e). These findings suggest that exposure to early life inflammation has long-lasting consequences for preterm neonates that increases their risk for immune-related diseases well beyond the neonatal period.\u003c/p\u003e\n\u003cp\u003eOur 7-plex cytokine microring resonator assay was robustly validated for all targets simultaneously to ensure reproducible results across all samples analyzed. Each assay was 38 minutes to result, creating a quick method for analyzing important clinical samples. Using this multiplexed immunoassay, we were able to collect large amounts of immunological data quickly and with little starting sample volume. This technology has the potential to provide clinically relevant information quickly for the most vulnerable patients, which could impact bedside patient care.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. All samples were collected from clinically indicated laboratory tests, so the timing of sample collection varied between patients and was not standardized. There were differences between the exposure groups, and chorioamnionitis-exposed subjects were more likely to be born earlier, African American and by vaginal delivery than unexposed subjects. It is unclear if these differences impacted cytokine and chemokine expression. Degree of prematurity and mode of delivery have been shown to impact immune responses in prior studies, so these factors were accounted for in out statistical evaluation (\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e). Samples were excluded from subjects who had a suspected or confirmed infection and were receiving antibiotics at the time of sample collection. However, samples were included from these patients later during their NICU course once the infection was treated. It is unclear if the suspected or confirmed infections influenced future cytokine and chemokine expression. Furthermore, corrections were not made for clinical differences such as mode of respiratory support, presence of BPD, steroid administration, or PDA treatment. Consistent with previous reports, chorioamnionitis-exposed preterm neonates in this study had an increased incidence of early onset sepsis (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e). It is unclear what impact this had on subsequent cytokine or chemokine responses and if the presence of early onset sepsis further compounded dampened cytokine and chemokine expression. The numbers in this study are not large enough to directly address this, but future studies containing more subjects would be of benefit.\u003c/p\u003e"},{"header":"Conclusions:","content":"\u003cp\u003eThis study demonstrated that healthy preterm neonates had a consistent decrease in levels of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 over the first month of life, reaching what appeared to be baseline levels around three weeks after birth. This same pattern of changes was not present in chorioamnionitis-exposed preterm neonates, which may reflect immune system dysregulation. The altered cytokine and chemokine trends in chorioamnionitis-exposed very preterm neonates may explain their increased risk for immune-mediated complications outside of the immediate neonatal period, including late onset sepsis, persistent wheezing and asthma.\u003c/p\u003e"},{"header":"Declarations:","content":"\u003cp\u003eConflict of Interest Statement: The authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003eFunding: This project was funded through philanthropic funds from the Korneffel family and by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health AI141673.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions: GES made substantial contributions to the acquisition, analysis and interpretation of the data and wrote the initial draft of the manuscript. CAC and KLM made substantial contributions to the acquisition, analysis and interpretation of the data and critically revised the manuscript. JMS made substantial contributions to the analysis and interpretation of the data and critically revised the manuscript. LAE made substantial contributions to the design of the work, analysis and interpretation of the data and critically revised the manuscript. RCB and JRB made substantial contributions to the conceptualization and design of the work, acquisition, analysis and interpretation of the data and critically revised the manuscript.\u003c/p\u003e"},{"header":"References:","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eBlencowe H, Cousens S, Oestergaard MZ, Chou D, Moller AB, Narwal R, et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet. 2012; 379: 2162\u0026ndash;2172.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSimonsen KA, Anderson-Berry AL, Delair SF, Davies HD. Early-onset neonatal sepsis. Clin Microbiol Rev. 2014;27: 21\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eRao SC, Athalye-Jape GK, Deshpande GC, Simmer KN, Patole SK. Probiotic Supplementation and Late-Onset Sepsis in Preterm Infants: A Meta-analysis. Pediatrics. 2016; 137: e20153684.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSchmid S, Geffers C, Wagenpfeil G, Simon A. Preventive bundles to reduce catheter-associated bloodstream infections in neonatal intensive care. GMS Hyg Infect Control. 2018; 13: Doc10.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSchmatz M, Srinivasan L, Grundmeier RW, Elci OU, Weiss SL, Masino AJ, et al. Surviving Sepsis in a Referral Neonatal Intensive Care Unit: Association between Time to Antibiotic Administration and In-Hospital Outcomes. J Pediatr. 2020; 217: 59\u0026ndash;65 e1.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eVenkatesh M, Flores A, Luna RA, Versalovic J. Molecular microbiological methods in the diagnosis of neonatal sepsis. Expert Rev Anti Infect Ther. 2010; 8: 1037\u0026ndash;1048.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSharma D, Farahbakhsh N, Shastri S, Sharma P. Biomarkers for diagnosis of neonatal sepsis: a literature review. J Matern Fetal Neonatal Med. 2018; 31: 1646\u0026ndash;1659.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKhaertynov KS, Boichuk SV, Khaiboullina SF, Anokhin VA, Andreeva AA, Lombardi VC, et al. Comparative Assessment of Cytokine Pattern in Early and Late Onset of Neonatal Sepsis. J Immunol Res. 2017; 2017: 8601063.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eReinhart K, Bauer M, Riedemann NC, Hartog CS. New approaches to sepsis: molecular diagnostics and biomarkers. 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Differential patterns of 27 cord blood immune biomarkers across gestational age. Pediatrics. 2009; 123: 1320\u0026ndash;1328.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLusyati S, Hulzebos CV, Zandvoort J, Sauer PJ. Levels of 25 cytokines in the first seven days of life in newborn infants. BMC Res Notes. 2013; 6: 547.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSalio M, Speak AO, Shepherd D, Polzella P, Illarionov PA, Veerapen N, et al. Modulation of human natural killer T cell ligands on TLR-mediated antigen-presenting cell activation. Proc Natl Acad Sci U S A. 2007; 104: 20490\u0026ndash;20495.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePeng CC, Chang JH, Lin HY, Cheng PJ, Su BH. Intrauterine inflammation, infection, or both (Triple I): A new concept for chorioamnionitis. 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Gut. 2014; 63: 559\u0026ndash;566.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-1766505/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1766505/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eObjective:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eDetermine the duration of chorioamnionitis-induced altered immune responses in preterm neonates.\u003cem\u003e \u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy Design:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eA 7-plex immunoassay measured levels of IL-1b, IL-6, IL-8, IL-10, TNF-a, CCL2 and CCL3 longitudinally in residual serum samples from chorioamnionitis-exposed and unexposed preterm neonates less than 33 weeks’ gestation. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResults:\u003c/em\u003e \u003c/strong\u003eChorioamnionitis-exposed and unexposed preterm neonates demonstrated differences in the trends of IL-1b, IL-6, IL-8, IL-10, TNF-a and CCL2 over the first month of life. The unexposed neonates demonstrated elevated levels of these inflammatory markers in the first one to two weeks of life with a decrease to baseline levels by the third week of life, while the chorioamnionitis-exposed neonates demonstrated differences over time without a predictable pattern. Chorioamnionitis-exposed and unexposed neonates demonstrated altered IL-10 and TNF-a trajectories over the first twelve weeks of life.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConclusion:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eChorioamnionitis induces a state of immune dysregulation that persists for at least twelve weeks following delivery in preterm neonates.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Chorioamnionitis-exposure alters serum cytokine trends in premature neonates","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-06-22 19:51:31","doi":"10.21203/rs.3.rs-1766505/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2022-07-26T14:01:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-07-23T23:01:15+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-07-05T20:37:40+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-06-27T01:29:54+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-06-20T18:28:34+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2022-06-20T17:03:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-06-17T11:12:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-06-16T22:56:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Perinatology","date":"2022-06-16T22:56:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b8e7f0f4-9258-4547-b6ce-53a27c2d93ad","owner":[],"postedDate":"June 22nd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2022-12-21T08:07:54+00:00","versionOfRecord":{"articleIdentity":"rs-1766505","link":"https://doi.org/10.1038/s41372-022-01584-2","journal":{"identity":"journal-of-perinatology","isVorOnly":false,"title":"Journal of Perinatology"},"publishedOn":"2022-12-20 05:00:00","publishedOnDateReadable":"December 20th, 2022"},"versionCreatedAt":"2022-06-22 19:51:31","video":"","vorDoi":"10.1038/s41372-022-01584-2","vorDoiUrl":"https://doi.org/10.1038/s41372-022-01584-2","workflowStages":[]},"version":"v1","identity":"rs-1766505","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1766505","identity":"rs-1766505","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}