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\begin{document}

\title{Neonatal inflammation, stress and growth factors after vaginal delivery,
pre-labour, and in-labour caesarean section: a retrospective cohort
study}



\author[1]{Pia Kiilerich}%
\author[1]{Rikke Cortes}%
\author[2]{Ulrik LAUSTEN-THOMSEN }%
\author[1]{Nis  BORBYE-LORENZEN}%
\author[1]{Kristin Skogstrand}%
\affil[1]{Statens Serum Institut}%
\affil[2]{Rigshospitalet}%


\vspace{-1em}



  
  \date{May 23, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Objective To explore the effect of different delivery modes, vaginal
delivery compared to caesarean section with or without initiation of
labour, on the immune system and brain of the infants. Further, we aimed
to elucidate gender and gestational ages' effect on these biomarkers.
Design Retrospective case control study Setting Dried blood spots from
new-born screening biobank drawn 2-4 days after birth Population or
Sample Mature new-borns divided into delivery by pre-labour (n=714),
in-labour caesarean section (n=655), and vaginally (n=5897). Method The
samples were analysed for inflammatory markers (IL-18, MCP-1, CRP, sTNF
RI), stress- (HSP-70), growth- (EGF, VEGF-A), and neurotrophic factors
(BDNF, NT-3, S100B). Main Outcome Measures Delivery by caesarean section
with or without initiation of labour Results The neonatal levels of
inflammatory and stress-markers were significantly lower, while the
levels of growth factors were higher after pre-labour caesarean section
compared to vaginal delivery. The biomarker levels were similar after
in-labour caesarean section and vaginal delivery. Males had generally
higher levels of inflammation and lower levels of growth and
neurotrophic factors. Overall, the levels of inflammatory markers
increased, and the growth factors decreased with increasing gestational
age. Conclusion The biomarker levels indicates that the labour process
has an important effect on the foetal immune system and level of stress,
regardless if the delivery ends with caesarean section or vaginal birth.
Funding ''L\selectlanguage{ngerman}æge Sofus Carl Emil Friis og hustru Olga Doris Friis' legat''
and ''Fonden til Lægevidenskabens Fremme''. Keywords Inflammation;
brain; CODIBINE; caesarean section; dried blood spot samples%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\textbf{Objective}

To explore the effect of different delivery modes, vaginal delivery
compared to caesarean section with or without initiation of labour, on
the immune system and brain of the infants. Further, we aimed to
elucidate gender and gestational ages' effect on these biomarkers.

\textbf{Design}

Retrospective case control study

\textbf{Setting}

Dried blood spots from new-born screening biobank drawn 2-4 days after
birth

\textbf{Population or Sample}

Mature new-borns divided into delivery by pre-labour (n=714), in-labour
caesarean section (n=655), and vaginally (n=5897).

\textbf{Method}

The samples were analysed for inflammatory markers (IL-18, MCP-1, CRP,
sTNF RI), stress- (HSP-70), growth- (EGF, VEGF-A), and neurotrophic
factors (BDNF, NT-3, S100B).

\textbf{Main Outcome Measures}

Delivery by caesarean section with or without initiation of labour

\textbf{Results}

The neonatal levels of inflammatory and stress-markers were
significantly lower, while the levels of growth factors were higher
after pre-labour caesarean section compared to vaginal delivery. The
biomarker levels were similar after in-labour caesarean section and
vaginal delivery. Males had generally higher levels of inflammation and
lower levels of growth and neurotrophic factors. Overall, the levels of
inflammatory markers increased, and the growth factors decreased with
increasing gestational age.

\textbf{Conclusion}

The biomarker levels indicates that the labour process has an important
effect on the foetal immune system and level of stress, regardless if
the delivery ends with caesarean section or vaginal birth.

\textbf{Funding}

''L\selectlanguage{ngerman}æge Sofus Carl Emil Friis og hustru Olga Doris Friis' legat'' and
''Fonden til Lægevidenskabens Fremme''.

\textbf{Keywords}

Inflammation; brain; CODIBINE; caesarean section; dried blood spot
samples

\textbf{Tweetable abstract:} Pre-labour C-section leads to altered
biomarkers in new-borns compared to in-labour C-section or vaginal
delivery



\section*{Introduction}

{\label{introduction}}

Caesarean section (CS) is a well-known and potentially life-saving
surgical procedure. The global rate of deliveries by CS has increased
from 12.1\% in 2000 to 21.1\% of deliveries in 2015 (1). It is estimated
that 9-19\% of CSs can be justified by medical indications (2, 3), and
the World Health Organization currently recommends CS for up to 15\% of
deliveries(4). Yet, national frequencies varies greatly and range from
0.6\% in South Sudan (1) to 55-65\% in Brazil (5).

Recently, increasing evidence has shown that birth delivery mode has an
impact on child health (6). CS is associated to early complications such
as birth asphyxia, respiratory disturbances (7), soft tissue injury (8),
and to neurological and psychological complications such as autism
spectrum disorders (9), ADHD (10), psychosis (11), anxiety, depression,
and sleep disturbances (12). Notable CS-associated late-term
complications for the child includes implications of the immune system:
systemic connective tissue disorders, juvenile arthritis (13),
inflammatory bowel disease, immune deficiencies, asthma (14, 15), sepsis
(16), type 1 diabetes (14), celiac disease (17), and autoimmune diseases
(12).

Compared to infants delivered vaginally, a delivery by CS is thought to
alter the short-term immune response in new-borns by variation of
bacterial colonization of the intestinal tract, due to lack of exposure
to the vaginal and anal microbiota during delivery (18, 19). Further,
the level of foetal stress during CS is lower compared to vaginal
delivery (VD), as both the initiation of birth and the contractions
during VD may trigger many biological effects (20). Pre-labour CS, i.e.
CS before the onset of labour, are more often associated with several of
the above mentioned complications compared with in-labour CS (7, 11, 13,
14, 17), suggesting that important endocrine, physiological and
biochemical processes in the infant are initiated by labour. Most
biomarker studies reported regarding CS versus VD have excluded cases
with in-labour CS, thus the studies cannot explain if the differences
found are due to the surgery or the lack of labour.

Infant males are known to be more fragile due to yet unknown biological
mechanisms (21); they are more often prematurely spontaneously aborted
(22), born premature or late, stillborn, have a higher infant mortality,
and are also more often delivered by CS (23).

Accordingly, we aimed to explore the delivery mode's effects on the
immune system and brain per se of the infants, by measuring
inflammatory, stress, growth, and neurotrophic biomarkers in more than
7000 neonatal dried blood spot samples (DBSS). Further, we wanted to
elucidate potential gender- and gestational age-dependent differences of
the biomarker levels.

\section*{Materials and Methods}

{\label{materials-and-methods}}

\emph{Sample selection}

The CODIBINE cohort comprises all new-borns born with gestational age
(GA)\textless{}37 weeks (n=7946) in Denmark between March 2009-March
2011, and maturely born controls with GA\selectlanguage{english}[?]37 weeks (n=7946) matched by
birth hospital and day. The blood samples were drawn from a heel prick
as DBSS for routine new-born screening. Samples are shipped by mail and
stored at the Danish New-born Screening Biobank, Statens Serum Institut,
at -24degC after screening (24). Our cohort is linked with data from the
Danish Medical Birth Register (MBR) (25) using the Danish Civil
Registration System (26). This is the first of a series of papers from
the project called CODIBINE, Correlations and Diagnoses for Biomarkers
in~New-borns, aiming to explore biomarkers in new-borns correlated to
birth, complications and diagnoses later in life.

In the present study, we reduced the cohort to include mature births,
with samples drawn 2-4 days after birth, in total 7266 individuals: 714
delivered by pre-labour CS, i.e. CS before onset of labour, 655 by
in-labour CS, i.e. CS after initiation of labour, and 5897. Table 1
shows the demographic data for the mothers and new-borns.

Exclusion criteria were: active dissent to participation in scientific
studies (as registered in the Danish national register for use of
biological tissue, ``Vaevsanvendelsesregisteret''), lack of or
insufficient sample material, incomplete civil registration number, and
non-participation in the National New-born Screening Program.

The study was supported by ''Laege Sofus Carl Emil Friis og hustru Olga
Doris Friis' legat'' and ''Fonden til Laegevidenskabens Fremme''. The
warded grant did not include external peer review for scientific quality
or priority assessment. The funders were not involved in conducting
research and writing the paper.

\emph{Sample analysis}

The samples were analysed using an in-house developed multiplex assay
based on Meso-Scale Discovery (MSD) technolog, targeting 3 biomarkers
for inflammation (Interleukin-18 (IL-18), Monocyte Chemotactic Protein
(MCP-1), C-Reactive Protein (CRP)), 1 anti-inflammatory marker (soluble
Tumor Necrosis Factor 1 (sTNF RI)), 1 biomarker for stress (Heat Shock
Protein-70 (HSP70)), 2 growth factors (Epidermal Growth Factor (EGF),
Vascular Endothelial Growth Factor A (VEGF-A)), and 3 neurotrophic
biomarkers for brain development and/or damage (Brain-Derived
Neurotrophic Factor (BDNF), Neurotrophin-3 (NT-3), and S100 calcium
binding protein B (S100B)).

All antibodies were purchased from RnDsystems, with the exception of
anti-S100B, which was purchased from Sigma-Aldrich (capture) and DAKO
(detection), respectively. The capture antibodies were purchased
biotinylated, except for anti-S100B that was in-house purified using
protein A column, and biotinylated using EZ-Link Sulfo-NHS-LC-Biotin
(ThermoFisher) as per manufacturers instructions. The biotinylated
antibodies were diluted to the concentration 0.1\selectlanguage{greek}µ\selectlanguage{english}g/ml for CRP and
10\selectlanguage{greek}µ\selectlanguage{english}g/ml for the other antibodies, bound to different linkers 1-10 (MSD)
according to manufacturer's instructions, and finally added to each
plate well (50\selectlanguage{greek}µ\selectlanguage{english}l/well, U-plex plates, MSD), and incubated at room
temperature (RT) for 1 hour. After washing with washing buffer (PBS
containing 0.05\% Tween 20), the plates were stored at 4\selectlanguage{ngerman}°C until use.
Calibrators and controls were prepared by recombinant antigens diluted
in diluent 7 (MSD). All detection antibodies were sulfo-tagged using MSD
Gold Sulfo-tag NHS-Ester (MSD) as per manufacturers instructions, and
were mixed together to a final concentration of 0.1\selectlanguage{greek}µ\selectlanguage{english}g/ml of each
antibody.

The DBSS were punched as 2x3.2mm disks in microtiter wells using DBS
Puncher\selectlanguage{ngerman}® instrument (Perkin Elmer), added 130 \selectlanguage{greek}µ\selectlanguage{english}l extraction buffer (PBS
containing proteaseinhibitor, as earlier described (27)) to each well,
sealed and extracted for 1 hour at RT on a shaker set at 450 rpm. After
extraction, 50\selectlanguage{greek}µ\selectlanguage{english}l extract was aspirated from each well and transferred to
the pre-coated plates with a pipetting robot (Biomek 4000, Ramcon)
together with calibrators and controls. The plates were sealed and
incubated on a shaker set at 600 rpm for 2 hours at RT. After washing,
detection antibodies were added to each well followed by 2 hours
incubation at 600 rpm at RT.

Finally, the plates were washed, added 2xRead buffer T (MSD), and
immediately read at the QuickPlex reader (MSD).

Concentrations of the biomarkers were calculated from the calibration
curves with 4 parameter logistic fit using Discovery Workbench 4.0
software (MSD).

Analytical characteristics are shown in table 2. Values measured below
or above the working ranges were set to the lowest or highest measurable
concentration.

\emph{Statistics}

For each of the ten biomarkers the data was log-transformed using the
natural logarithm in order to obtain normal distribution. The mode of
delivery was stratified into three groups; VD, pre-labour CS and
in-labour CS, as classified by obstetrician at the time of birth.
Two-way ANOVA was used to test for overall difference between birth
type, where GA was included in the model as well as the interaction, and
to test for the overall difference between genders, where birth type was
included in the model as well as the interaction. A t-test with
un-pooled variance was used to detect pairwise significant differences
with Holms method (28) to adjust for multiple testing.

One-way ANOVA was used to test for the overall difference of the
biomarkers between gestational age. A pairwise t-test with un-pooled
variance, adjusted for multiple testing using Holms method, was used to
test for differences between the weeks.

Maternal age, BMI, and neonatal birth weight and age at sampling were
initially included in the models, but did not contribute to the
explanation of the variation, and these parameters were therefore
excluded from the final models (data not shown). The birth weight and GA
was lower in the pre-labour CS group. Birth weight was included in the
first calculations, but did not make any differences as long as GA was
included, and thus were excluded in the final calculation.

No difference was found in the use of anaesthetics between pre-labour
and in-labour CS (data not shown), thus we did not correct for this in
the analysis. The analysis was re-run excluding the cases with
pre-labour rupture of the membranes (PROM). No difference in the result
was found (data not shown). Only 0.8\% of the infants were registered
with an infection the first 4 days after birth, thus this was not
adjusted for in the statistics.

All statistical analyses and figures were performed using the dplyr (29)
and ggplot2 (30) packages in R software version 3.5.2.

\section*{Results}

{\label{results}}

Infants born by pre-labour CS had significantly decreased levels of the
inflammatory markers (CRP, MCP-1, IL-18) and the stress-marker HSP70,
and significantly increased levels of the growth factors (VEGF and EGF)
compared to infants born by VD. Comparing pre-labour CS with in-labour
CS showed a similar pattern: CRP, MCP-1 and HSP70 were significantly
decreased, and VEGF was increased, in infants born by pre-labour CS
compared to infants born by in-labour CS. When comparing in-labour CS to
VD, only CRP was significantly different. We found no delivery form
depending differences in neonatal levels of the neurotrophic factors
(S100B, BDNF and NT-3), or the anti-inflammatory marker sTNF RI (Figure
1).

Most biomarkers were different between genders: males had significantly
lower levels than females of the anti-inflammatory marker sTNF RI, the
growth factors (EGF and VEGF), and the neurotrophic factor BDNF. The
inflammatory markers CRP and MCP-1 were higher in males compared to
females. Delivery form has an overall effect on S100B and IL-18 in
males, but not in females. The gender differences were generally more
significant after VD (CRP, MCP-1, sTNF RI, EGF, BDNF, VEGF), than after
in-labour (CRP, BDNF) and pre-labour CS (CRP, VEGF) (Figure 2).

We saw an overall increase of the inflammatory markers CRP, IL-18, and
MCP-1 from GA 37-42, and a decrease of the anti-inflammatory marker sTNF
RI. The stress-marker HSP70 decreased from GA 38-40. The growth factors
EGF and VEGF, and the neurotrophic factor S100B, decreased overall in
samples from GA 37 to 42, while no overall significant difference was
found for the neurotrophic factors BDNF and NT-3 (Figure 3).

There was a significant difference in infants' birth weight between
delivery forms, where the heaviest infants are born by in-labour CS and
the lightest by pre-labour CS (table 1). Birth weight was included in
the first calculations, but did not make any differences as long as GA
was included in the final model, and thus were excluded in the final
calculation. The maternal BMI was higher for mothers in the CS group (no
matter type) compared to VD, and the maternal age was higher in the
pre-labour CS group compared to the other groups. Neither of the factors
could explain any of the differences found in the biomarkers. The age at
sampling could not explain the differences observed in biomarkers
between the different delivery forms, neither could it explain the
differences in males and females. There were significantly more cases of
PROM before in-labour CS and VD. Removing all cases with PROM did not
change the results.

\section*{Discussion}

{\label{discussion}}

\emph{Main findings:}

In this study, the neonatal levels of inflammatory and stress-markers
were generally lower, and the levels of growth factors were higher after
pre-labour CS compared to after VD or in-labour CS. The differences in
biomarkers could not be explained by the higher incidence of PROM before
in-labour CS and VD. Accordingly, the data suggests that the labour
process has an important physiological effect on the foetal immune
system and level of stress, regardless if the delivery ends with
caesarean section or vaginal birth.

\emph{Strengths and limitations:}

The strengths of this study are the study size, and the unbiased and
random selection of the participants from all of Denmark, meaning that
there was no selection for social status, income, race etc. All samples
were handled in the same way, and analyzed in the same labouratory, thus
minimizing analytic variance. We were not able to account for lifestyle
factors associated with maternal request for CS or factors increasing
the risk of CS. Further, we did not have any information regarding
length of labour.

\emph{Interpretation}

Decreased levels of inflammatory markers in cord blood and neonatal
serum after CS compared with VD has been described before (31, 32), but
most previous studies did not stratify for the type of CS (pre-labour or
in-labour). A few studies regarding CRP have been described, that found
similar differences in new-born levels depending on birth form as we
describe (33, 34). In a study among teenagers, whose mothers had entered
the active phase of labour before CS, spontaneous and toll-like
receptor-stimulated cytokine release was increased, compared to controls
born by pre-labour CS (35). This concurs with another study showing that
the risk for early childhood infections are higher in children born by
pre-labour CS compared to children born by in-labour CS or VD (1, 36).
One of the common explanations for the immunological differences after
CS and VD has been microbial transmission from mother to child, either
by transmission during vaginal birth or by microbial invasion of the
amniotic cavity after PROM (32, 36). However, in our study, the
exclusion of all cases with PROM did not make any difference in the
significance of the biomarker levels. Following national guidelines,
prophylactic antibiotics are given during or after both pre- and
in-labour CS in Denmark (37), and the hospital stay afterwards are the
same (in contrast to after VD where the woman and infant often leaves
the hospital a few hours after birth). The explanation for the observed
differences in our study is thus more likely to be the influences of
stress hormones and/or the physical pressure from the labour process.
During VD, cortisol and other stress hormones increase. Elevated
cortisol at birth is a known indicator of hypothalamic-pituitary-adrenal
axis activation, which is important for regulation of stress and many
other body processes (38). The observed sustained inflammatory response
2-4 days after birth in our study after in-labour CS or VD may thus be
protective for the foetus later in life, and could possible even explain
some of the increased risk for autoimmune and inflammatory disorders
after pre-labour CS.

The intracellular inducible HSP70 are one of the major HSPs involved in
numerous cellular functions, such as cytoprotection, anti-apoptosis, and
immune regulatory effects (39). Increased temperature, exposure to
oxidative stress, such as hypoxia, viral infection, and
ischemia-reperfusion injury, can induce the expression (39). The fact
that HSP70 had similar infant levels after in-labour CS and VD may
indicate that the stress effect is the same provided the labour have
been initiated, regardless if the delivery ends with CS or VD.

Animal studies have shown that mouse brains have increased contents of
norepinephrine, dopamine, serotonin and metabolites of dopamine and
serotonin after vaginal deliveries compared to mice delivered by CS. The
turnover ratios of the neurotransmitters were also higher in the mouse
brains after vaginal delivery, and the later adult mice showed different
behavioural patterns (40). We have recently found significantly lower
neonatal levels of BDNF in new-borns later diagnosed with autism
spectrum disorders (41). In the current study, we did not see any
correlation with the neurotrophic markers BDNF, NT-3, and S100B, and the
delivery form. This might indicate that neurodevelopment are not
dependent on delivery form.

VEGF is a growth factor that stimulates vasculogenesis and angiogenesis
after stress, and it is an essential factor for placental development
(42). VEGF is expressed at sites of injury and inhibits the activity of
nitric oxide synthase, preventing inflammation (43), and it is present
at high levels in the central nervous system (44). VEGF is a potent
stimulator of angiogenesis in asthma (45), and both VEGF and EGF are
stimulators of mucins in the respiratory tract, which concentrations
have been reported as positively correlated with asthma disease severity
(46, 47). We are not aware of any other studies regarding delivery forms
and growth factors. The increased levels after pre-labour CS could
indicate that the mechanisms for the increased risk for asthma have been
initiated already 2-4 days after birth, but this needs to be more
thoroughly investigated in further studies using asthma as an outcome.

Higher concentrations of CRP in neonatal males compared to females has
been described before (48). This may be due to hormonal differences, as
estradiol (which is highest in females) decreases the production of CRP
(49, 50), and increases the gene expression of BDNF (51). Although these
early-life differences may simply be an epiphenomenon, it might be the
precursors to later in life higher frequencies of different disorders in
males, but this needs further investigation. Circumcision is rarely
performed in Denmark (52), thus this cannot explain any of the gender
biomarker differences (52).

The overall increasing levels of inflammation biomarkers from GA 37-42
concurs with a study showing that the leucocyte count increases with GA
up to week 40 (53). The levels of HSP70 decreases until week 40, but
then increases in week 41 and 42. This may support the ongoing
discussion about earlier deliveries of foetuses after GA week 40 due to
increased risk for the overdue foetus (54). The growth factors and S100B
decreased for each week of GA, while the neurotrophic factors did not
depend on GA. Low GA at birth is a well-known risk factor for later
cognitive impairment (55). This effect appears to persist even when born
at term, and a study has reported that there are significantly more
children receiving special education the lower the gestational age they
were born, even up to GA week 39 compared to week 40 (56). We did not
see any differences in the neurotrophic markers that could explain this,
but the higher levels of growth factors and S100B could indicate a less
mature body and brain.

\emph{Conclusion}

The results indicate that the labour process is an important and
necessary part of delivery for the infants' immune system, and also add
to the growing body of evidence suggesting an unnecessary
``overproduction'' of CS leading to not only maternal and socioeconomic,
but certainly also neonatal consequences. The long-term outcome, after
pre-labour and in-labour CS, on the developing immune system in the
children in this study, remains to be investigated. When the children in
the CODIBINE cohort gets older, and thus have obtained an age where more
diagnoses have been set, we plan to make a full study on several
disorders and birth complications.

\section*{Acknowledgements}

{\label{acknowledgements}}

Thanks to Malene Billsten Zent, Lisette Jensen, Karin Skaarup, and
Karina Liebmann Madsen for skilful laboratory analysis.

\section*{Disclosure of interests}

{\label{disclosure-of-interests}}

The authors have no conflicts of interests.

\section*{Author contributions}

{\label{author-contributions}}

PK: analysing and writing up the work

RC: analysing and writing up the work

ULT: analysing and writing up the work

NBL: analysing and writing up the work

KS: Conception, planning, carrying out, analysing and writing up the
work

\section*{Details of Ethics Approval}

{\label{details-of-ethics-approval}}

The study was approved by the Danish Ethical Committee (VEK), Project-ID
H-6-2014-078 and H-6-2014-079.

\section*{Funding}

{\label{funding}}

The study was supported by ''L\selectlanguage{ngerman}æge Sofus Carl Emil Friis og hustru Olga
Doris Friis' legat'' and ''Fonden til Lægevidenskabens Fremme''.

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\textbf{Table 1. Maternal and neonatal demographic data}\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
\textbf{Type of birth} & \textbf{Type of birth} & \textbf{Type of birth}
& \textbf{Pre-labor cesarean section} & \textbf{Pre-labor cesarean
section} & \textbf{In-labor cesarean section} & \textbf{In-labor
cesarean section} & \textbf{Vaginal delivery} & \textbf{Vaginal
delivery}\tabularnewline
\midrule
\endhead
Gender & Gender & Gender & Male & Female & Male & Female & Male &
Female\tabularnewline
& Number (\%) (n=7266) & Number (\%) (n=7266) & 379 (5.2\%) & 355
(4.6\%) & 389 (5.4\%) & 266 (3.7\%) & 3132 (43.1\%) & 2765
(38.1\%)\tabularnewline
Birth weight & Birth weight & Birth weight & & & & & &\tabularnewline
& Mean (95\% CI) & Mean (95\% CI) & 3543 (3491-3594) & 3326 (3271-3381)
& 3683 (3629-3737) & 3571 (3508-3634) & 3613 (3597-3630) & 3499
(3482-3516)\tabularnewline
Maternal BMI & Maternal BMI & & & & & & &\tabularnewline
& Mean (95\% CI) & Mean (95\% CI) & 25.5 (24.9-26.1) & 25.4 (24.7-26.1)
& 25.4 (24.8-26.0) & 25.8 (25.1-26.4) & 24.0 (23.9-24.2) & 24.1
(23.9-24.3)\tabularnewline
Maternal age & Maternal age & Maternal age & & & & & &\tabularnewline
& Mean (95\% CI) & Mean (95\% CI) & 32.6 (32.2-33.1) & 31.9 (31.4-32.4)
& 30.1 (29.6-30.6) & 30.8 (30.2-31.4) & 30.2 (30.0-30.4) & 30.4
(30.2-30.6)\tabularnewline
Gestational age (weeks) & Gestational age (weeks) & Gestational age
(weeks) & & & & & &\tabularnewline
& 37 & 37 & 52 (7.3\%) & 50 (7.0\%) & 28 (4.3\%) & 17 (2.6\%) & 155
(2.6\%) & 138 (2.3\%)\tabularnewline
& 38 & 38 & 159 (22.3\%) & 150 (21.0\%) & 49 (7.5\%) & 40 (6.1\%) & 388
(6.6\%) & 294 (5.0\%)\tabularnewline
& 39 & 39 & 139 (19.5\%) & 120 (16.8\%) & 70 (10.7\%) & 51 (7.8\%) & 695
(11.8\%) & 602 (10.2\%)\tabularnewline
& 40 & 40 & 21 (2.9\%) & 7 (1.0\%) & 91 (13.9\%) & 65 (9.9\%) & 1041
(17.7\%) & 935 (15.9\%)\tabularnewline
& 41 & 41 & 6 (0.8\%) & 6 (0.8\%) & 99 (15.1\%) & 64 (9.8\%) & 661
(11.2\%) & 637 (10.8\%)\tabularnewline
& 42 & 42 & 2 (0.3\%) & 2 (0.3\%) & 52 (7.9\%) & 29 (4.4\%) & 192
(3.3\%) & 159 (2.7\%)\tabularnewline
Age at sampling (days) & Age at sampling (days) & Age at sampling (days)
& & & & & &\tabularnewline
& 2 & 2 & 270 (37.8\%) & 234 (32.8\%) & 184 (25.4\%) & 132 (18.2\%) &
1656 (28.1\%) & 1405 (23.8\%)\tabularnewline
& 3 & 3 & 105 (14.7\%) & 98 (13.7\%) & 195 (26.9\%) & 125 (17.3\%) &
1406 (23.8\%) & 1307 (22.2\%)\tabularnewline
& 4 & 4 & 4 (0.6\%) & 3 (0.4\%) & 10 (1.4\%) & 9 (1.2\%) & 70 (1.2\%) &
53 (0.9\%)\tabularnewline
PROM & PROM & PROM & 2 (0.5\%) & 4 (1.1\%) & 48 (12.3\%) & 39 (14.7\%) &
221 (7.1\%) & 188 (6.8\%)\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2. Analytical characteristics}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
& \textbf{working range pg/ml} & \textbf{working range pg/ml} &
\textbf{inter assay}\tabularnewline
\midrule
\endhead
\textbf{Analyte} & \textbf{low} & \textbf{high} &
\textbf{CV\%}\tabularnewline
\textbf{BDNF} & 61.5 & 40000 & 28.7\tabularnewline
\textbf{CRP} & 43.6 & 10000000 & 47.3\tabularnewline
\textbf{EGF} & 2.5 & 5000 & 12.2\tabularnewline
\textbf{HSP70} & 246.1 & 5000000 & 17.8\tabularnewline
\textbf{IL-18} & 0.2 & 5000 & 13.8\tabularnewline
\textbf{MCP-1} & 4.4 & 50000 & 22.4\tabularnewline
\textbf{NT-3} & 2.0 & 5000 & 16.9\tabularnewline
\textbf{S100B} & 28.8 & 50000 & 24.6\tabularnewline
\textbf{sTNF-R1} & 16.9 & 100000 & 11.9\tabularnewline
\textbf{VEGF} & 3.0 & 5000 & 9.5\tabularnewline
\bottomrule
\end{longtable}



\section*{Table/Figure Caption List}

{\label{tablefigure-caption-list}}

\textbf{Table 2. Analytical characteristics}

The lowest concentrations in the working range was calculated as the
concentrations 2.5 standard deviations above the lowest points on the
calibration curves, and the highest points was set as the highest
calibration points.

Inter assay CV\% was calculated from controls present on all the plates,
in total 211 plates.

\textbf{Figure 1. Biomarker levels depending on gestational age and
delivery form}

The biomarkers are shown as mean with 95\% confidence interval, divided
into gestational age and pre-labour, in-labour caesarean section and
vaginal delivery, respectively. *statistical significance between
pre-labour caesarean section and vaginal delivery, \#statistical
significance between pre-labour and in-labour caesarean section for the
specific week. The p-values are calculated as an overall difference.

\textbf{Figure 2. Gender differences in biomarker levels depending on
birth form}

The biomarkers are divided into gender and grouped into pre-labour,
in-labour caesarean section and vaginal delivery. The data is shown as
mean concentrations with 95\% confidence interval. *there is a
significant difference between gender. P-values are calculated as an
overall difference comparing males and females irrespective of delivery
form.

\textbf{Figure 3. Biomarker levels depending on gestational age on
delivery}

The figure shows the concentrations of the different biomarkers divided
into gestational age, combined for all delivery forms. The data is
plotted as the group mean with the 95\% confidence interval as the
whiskers. Data points with no letters in common are significantly
different on a 5\% level.\selectlanguage{english}
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\end{figure}\selectlanguage{english}
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\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-3/Figure-3}

\end{center}
\end{figure}

\selectlanguage{english}
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