Changes in Cytokine and Cytokine Receptor Levels During Postnatal Development of the Human Dorsolateral Prefrontal Cortex

doi:10.21203/rs.3.rs-1969039/v1

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Changes in Cytokine and Cytokine Receptor Levels During Postnatal Development of the Human Dorsolateral Prefrontal Cortex

https://doi.org/10.21203/rs.3.rs-1969039/v1

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In addition to their traditional roles in immune cell communication, cytokines regulate brain development. Cytokines are known to influence neural cell generation, differentiation, maturation, and survival. However, most work on the role of cytokines in brain development investigates rodents or focuses on prenatal events. Here, we investigate how mRNA and protein levels of key cytokines and cytokine receptors change during postnatal development in the human prefrontal cortex. We find that most cytokine transcripts investigated (IL1B, IL18, IL6, TNF, IL13) are lowest at birth and increase between 2–5 years old. After 5 years old, transcriptional patterns proceeded in one of two directions: decreased expression in teens and young adults (IL1B, p = 0.002; and IL18, p = 0.004) or increased mean expression with maturation, particularly in teenagers (IL6, p = 0.004; TNF, p = 0.002; IL13, p < 0.001). In contrast, cytokine proteins tended to remain elevated after peaking significantly at age 5 (IL1B, p = 0.012; IL18, p = 0.026; IL6, p = 0.039; TNF, p < 0.001), with TNF protein being highest in young adults. Early developmental increases in cytokines were paralleled by increases in their receptor binding subunits, such as IL1R1 (p = 0.033) and IL6R (p < 0.001) transcripts. In contrast, cytokine receptor-associated signaling subunits, IL1RAP and IL6ST, did not change significantly between age groups. Of the two TNF receptors, the ‘pro-death’ TNFRSF1A and ‘pro-survival’ TNFRSF1B, only TNFRSF1B was significantly changed (p = 0.028), increasing first in toddlers and again in young adults. Finally, the cytokine inhibitor, IL13, was elevated first in toddlers (p < 0.001) and again in teenagers (p < 0.001). While the mean expression of interleukin-1 receptor antagonist (IL1RN) was highest in toddlers, this increase was not statistically significant. The fluctuations in cytokine expression reported here support a role for increases in specific cytokines at two different stages of human cortical development. The first is during the toddler/preschool period (IL1B and IL18) and the other at adolescence/young adult maturation (IL6 and TNF).

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IL1B

IL6

TNF

complement

adolescence

Research into the role of immune signals like cytokines in brain development has been partly driven by their association with atypical brain development and with psychiatric disorders. Epidemiological work further suggests that infection during gestation and early childhood is associated with the occurrence of neurodevelopmental disorders (1–17). In particular, inflammation during prenatal and postnatal development is reportedly associated with the development of autism and schizophrenia (14, 18–23). However, activation of cytokine signaling alone, in the absence of infection, can induce pathological changes in the brain (24–26). Additionally, genetic variation in immune-associated signals can alter the expression and function of immune signals independent of pathogen exposure. These were described with the copy number variant of complement component C4 (27). Thus, genetic and epigenetic changes to immune signaling molecules have the potential to disrupt normal patterns of expression and may exhibit heightened responses during episodes of infection-associated and/or sterile inflammation. Furthermore, psychiatric disorders first become evident during postnatal development. Therefore, we aimed to characterize the developmental timing of typical cytokine signaling during the normal postnatal period to determine when immune signaling perturbations would be expected to impact cortical development.

We previously investigated the trajectory of complement pathway members in neurotypical human prefrontal cortex across major periods of post-natal brain development. We found that the peak expression of many complement pathway members was in toddlers 2–5 years old (28). However, this study did not examine whether an increase in pro-inflammatory and anti-inflammatory cytokines occurs in tandem with complement pathway activation or whether the trajectory of cytokine change is distinct. Cytokines serve as intercellular messengers both inside and outside the immune system and regulate pro- and anti-inflammatory activity (29). Complement and cytokines are capable of reciprocal signaling between pathways, wherein cytokines can induce complement expression and vice versa (30–37). Therefore, given this existing association between complement and cytokine induction. We would expect pro-inflammatory cytokines and their associated receptors to coordinately regulated with complement during development.

Low levels of cytokines are detectable under normal conditions in the fetal and postnatal brain, and are believed to facilitate the development of the mammalian cortex. For instance, multiple cytokines can be detected during the first trimester in the human forebrain at the mRNA and protein level, including IL1B, TNF, IFNG, IL6, IL4, IL10, and TGFB1 (38). IL6, TNF, and IL1B have also previously been implicated in some of the crucial processes involved in brain development, such as progenitor cell proliferation (39), neuronal migration (40, 41) and both glial (42, 43) and neuronal (42) differentiation. In addition, transcripts for IL1B, IL6, TNF, and IL18 (44–54), as well as their receptors (52, 53, 55–65) have been identified in the postnatal cortex of rats, mice, and humans. However, the time course of change in cytokine levels across human postnatal brain development remains unclear.

To date, the studies investigating cytokine expression in human postnatal brain have been predominantly restricted to adults. Therefore, there is a gap in our understanding of immune expression in the brain at earlier, more dynamic ages. These include age periods coinciding with the typical age of onset for neurodevelopmental disorders such as autism spectrum disorders (ASD) (66, 67), which is concomitant with a peak cortical expression of the complement pathway (28). Additionally, abnormal cytokine levels have been implicated in ASD (68–70). Aberrant cytokine signaling could disrupt numerous processes during postnatal brain development. These include interneuron migration (71, 72), developmentally programmed cell death (73–76), neuronal maturation (77–80), synaptogenesis (81, 82), synaptic pruning (83–87), and oligodendrocyte maturation/myelination (88–90). Therefore, for the first time, we quantified the normal human cortical expression of an array of pro-inflammatory and anti-inflammatory cytokines implicated in neurodevelopment and characterized their expression trajectory from near birth until early adulthood using both mRNA and protein-based methods. We hypothesized that the mRNA and protein of pro-inflammatory cytokines IL1β, IL6, IL18 and TNF, and their associated receptors, would follow a similar trajectory to that of complement, peaking during early postnatal human brain development. Additionally, we hypothesized that the expression of associated inhibitory cytokines IL1RN, IL10, and IL13 would increase from school-age children through young adult, comparable to complement inhibitors (28).

Subjects

Postmortem samples from Brodmann’s area 46 in the DLPFC were obtained from the University of Maryland Brain and Tissue Bank in conjunction with the National Institute of Child Health and Development (N=65). The individuals in this cohort ranged from 6 weeks old to 25 years old. Subjects (neonates, infants, toddlers, school-age children, teenagers, and young adults) were assigned to one of six age groups based on cognitive development stages in consultation with a pediatrician. These developmental groups roughly correspond with stages of sensory and cognitive development, i.e., visual acuity and grasping (Neonates: birth-3 months old); sitting upright and environmental engagement (Infants: 4 months-1 year old); preoperational, pre-conceptual rapid language development (Toddlers: 1.5-4 years old); concrete operations (School-age children: 5-12 years old); formal operations, reproductive competence and heightened peer interactions (Teenagers: 14-18 years old); social independence and early maturity (Young Adults: around 22 years old). Eight to thirteen samples were selected per developmental group as described: groups were established with care to balance male and female samples as best as possible, and groups were matched for RNA integrity number (RIN), pH, and postmortem interval (PMI) for most groups. However, PMI was significantly longer in neonates and infants than in older ages (ANOVA, F(5,51)=2.881, p=0.023). Age groups analyzed, and their respective demographic and tissue quality information, are reported in Table 1. We have also included several Sudden Infant Death Syndrome (SIDS) samples in our age groups under two years old. A role for inflammation in SIDS has been proposed (91). However, the syndrome remains poorly understood, with much potential for heterogeneous causes of death. We studied ages 25 and under to focus on developmental processes, rather than aging (92) – however, the time at which “aging” begins remains an area of debate (93-96). All subjects were free of neurological and psychiatric symptoms at the time of death. Individual sample information, including age, sex, RIN, pH, PMI, and cause of death, are in Supplementary Table 1.

Table 1. Summary of patient demographics. RIN, pH, and PMI are presented as mean ± standard deviation.

Age Group	Age Range (years)	# Male/Female	RIN	pH	PMI	n
Neonate	0.11-0.24	5/5	7.48±1.36	6.52±0.20	22.3±5.36	10
Infant	0.25-0.91	8/5	7.58±0.59	6.61±0.16	17.46±6.36	13
Toddler	1.58-4.86	5/4	7.02±1.02	6.66±0.26	22.33±9.26	9
School-age	5.39-12.97	4/4	7.33±0.63	6.70±0.17	14.75±4.86	8
Teenager	15-17.82	6/2	7.45±0.71	6.75±0.09	15.5±5.26	8
Young Adult	20.14-25.38	6/3	7.53±0.79	6.67±0.23	13.67±8.26	9
Total	0.11-25.38	34/23	7.41±0.87	6.64±0.20	17.82±7.31	57

RNA extraction and cDNA synthesis

Total RNA was extracted from 30-100 mg of frozen DLPFC tissue using the Trizol (Cat# 15596026, Invitrogen, Thermo Scientific, Waltham, MA, USA) reagent method. A tissue homogenizer (Model PT10/35, Brinkmann Instruments) was used to homogenize frozen tissues on wet ice. Chloroform was used to dissociate nucleoprotein complexes; then, soluble RNA was removed from each sample. RNA was precipitated using isopropyl alcohol and re-suspended in diethyl-pyrocarbonate-treated water (97). The yield and purity of the extracted RNA were determined via spectrophotometer analysis. Following extraction, the RIN was determined for each sample using the Agilent Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). All samples had 260/280 ratios >1.70 and RIN values >6. RNA (1.5 μg)/sample was converted into cDNA using Superscript IV First Strand Synthesis Kit (Cat # 18091200, Thermo Scientific, Waltham, MA, USA) as described (98).

High-throughput quantitative PCR

High-throughput quantitative PCR was run on a Biomark HD (Fluidigm, South San Francisco, CA, USA) using a 96.96 Dynamic IFC high-throughput qPCR chip (Cat# 100-6123, Fluidigm, South San Francisco, CA, USA), enabling simultaneous Taqman gene expression assays on all samples. All probes are included in Supplementary Table 2. The following transcripts passed quality control analysis: IL6, IL1B, IL18, TNF, IL1R1, IL18R1, IL6R, IL6ST, TNFRSF1A, TNFRSF1B. No signal in either the no-template control or the no-RT control exceeded cycle threshold levels. Therefore, no transcripts were excluded from further analysis based on a low expression. ‘Low expression’ here is categorized as having a detectable signal in less than five samples of any given age group or a detectable signal in less than three points of the standard curve.

Single target quantitative RT-PCR

Quantitative PCR was run on an Applied Biosystems 7900HT Fast Real-Time PCR System (Thermo Fisher, Waltham, MA, USA). Taqman gene expression assays were used (Supplementary Table 3). A 1:6 plate cDNA dilution was used for transcripts IL10, IL13, IL1RN, and IL1RAP, which were added for analysis following the high-throughput quantitative PCR. In addition, serial dilutions of pooled cDNA from these samples were used to establish a standard curve, with dilutions 1:1, 1:3, 1:9, 1:27, 1:81, 1:243, and 1:729. No signal in the no-template control or the no-RT control exceeded cycle threshold levels for any qPCR run.

Protein extraction

Total protein was extracted from 30-60 mg of fresh frozen human DLPFC tissue. We used neuronal protein extraction reagent (N-PER) (Fisher Scientific, Hampton, NH, USA, Cat# PI87792) and Halt protease and phosphatase inhibitor cocktail plus 0.5 mM ethylenediaminetetraacetic acid (0.5mM EDTA) (Fisher Scientific, Hampton, NH, USA, Cat# PI78440) at 10 µL N-PER per 1 mg tissue in 1.5mL Axygen centrifuge tubes (Cat# MCT-175-C, Axygen). Tissues were homogenized on wet ice with hand-held Axygen tissue grinders (Fisher Scientific, Hampton, NH, Cat# 14 222 358) for 10 min using continual manual agitation. The homogenate was then incubated on wet ice for an additional ten minutes. Microcentrifuge tubes of homogenate were then centrifuged for 10 min at 10,000g at 4°C to pellet tissue debris and insoluble material. The supernatant was removed and stored in 1.5 ml low-protein binding centrifuge tubes (Fisher Scientific, Hampton, NH, USA, Cat# E925000090) at -80°C. Before use, the protein was quantified by bicinchoninic acid (BCA) assay. All samples were then diluted in N-PER with Halt protease and phosphatase inhibitor cocktail to a concentration of 2 mg/mL.

Multiplex immunoassay

For cytokine protein expression, multiplex immunoassays were performed. Multiplex immunoassays were run on a BioRad BioPlex 200 System (Bio-Rad, Hercules, CA, USA, Cat# 171000201). A custom 4-Plex Human Cytokine Assay Kit, including two 96-well plates, was used. The custom-designed assay targeted human cytokines IL6, IL1B, IL18, and TNF used existing probe antibodies from a 48-plex kit (Bio-Plex Pro Human Cytokine Screening Panel, Bio-Rad, Hercules, CA, USA, Cat #12007283). The assay used the 100-region bead map with a bead count of 50 beads per region. The sample timeout was set to 60 seconds. Multiplex immunoassays were run in the Molecular Core of SUNY Upstate Medical University, following the manufacturer’s protocol. Before running experimental samples, the measurement error (variation in values for repeated measurement of the same sample for each of the cytokines) was estimated. Samples (100 µg) were run in triplicate, and pooled internal controls were included in triplicate on each plate to monitor plate-to-plate variability. The samples used are reported in Supplementary Table 1. The kit provided lyophilized standards that were reconstituted in 250 µL in Standard Diluent HB (Bio-Rad, Hercules, CA, USA). Standards were diluted to ratios of 1:4, 1:16, 1:64, 1:256, 1:1,024, 1:4,096, 1:16,384, 1:65,536, and 1:262,144. The coefficient of variation (% CV) was calculated for triplicate readings of each sample. Samples that exceeded ± 15% CV (30% CV total) had one “outlier replicate” removed, which resulted in <± 15% CV from replicate measures for each sample.

Statistical analysis

Statistical tests of qPCR and multiplex immunoassay results were performed using SPSS statistics (Version 25, OSX, IBM, Armonk, NY, USA). Outliers by age group were identified using the ROUT test for outliers using GraphPad Prism (GraphPad Prism version 9.3.1 for Windows, GraphPad Software, San Diego, CA, USA) and then removed (~ 2 outliers per transcript). For TNF mRNA, 5 out of 11 samples in the neonate and infant groups were below the level of detection. Since the visual inspection of the data suggested the neonates and infants had similar levels of TNF mRNA (when detectable), the neonate and infant groups were combined for this analysis. Outliers were then removed using ROUT analysis. Data were tested for normality using Kolmogorov-Smirnoff testing and for homogeneity of variance using Levene’s test. If the data were non-normally distributed, data were logged, and Cox Box transformed (Real Statistics Excel plug-in, Release 5.4. Copyright 2013 – 2018 Charles Zaiontz. www.real-statistics.com). Data were tested for correlation with pH, RIN, and PMI.

Data without covariates that were normally distributed were analyzed using ANOVA, and non-normally distributed data were analyzed using the Kruskal-Wallis test. Normally distributed data with covariates were analyzed by ANCOVA. Non-normally distributed data with covariates were analyzed using Quade’s ranked test. A significant ANOVA, ANCOVA, Kruskal-Wallis, or Quade’s ranked test was followed by a Fisher’s Least Significant Difference (LSD) posthoc test. Welch’s ANOVA was used for normally distributed data exhibiting non-homogenous variance between groups (99, 100), followed by the Games-Howell posthoc test. Sex differences were analyzed by independent sample 2-tailed t-tests for each transcript but could not be compared between age groups due to sample size limitations. All transcripts were tested for correlation with age under the age of 5 years old using Spearman’s ρ. Statistical significance was set at p≤0.05.

Increases in IL1B mRNA and protein early in life

IL1B mRNA levels (Fig. 1a) were at a nadir just after birth in the neonatal prefrontal cortex and increased during postnatal life (F(5,46) = 4.451,p = 0.002). For IL1B mRNA, levels increased approximately 95% between neonates and infants (p = 0.038) and almost 380% between infants and toddlers (p = 0.006), ultimately peaking with an 830% net increase from the lowest age group (Neonates) to the highest (Toddlers) (Fig. 1a). When examining ages ranging from 2 months to 5 years old more specifically, IL1B mRNA was found to be significantly positively correlated with age (Spearman’s rho, ρ = 0.580, p < 0.001) (Table 2). Mean IL1B mRNA levels were then reduced back to roughly infant levels in school-age children but were still significantly elevated compared to neonates through school-age children (p = 0.022) and adolescence (p = 0.008). IL1B mRNA levels in young adults were intermediate compared to earlier ages and not significantly different from any other age group.

Analysis of protein also revealed significant increases in IL1B (Fig. 1b) levels across postnatal human life (F(5,52) = 3.265, p = 0.012) and resembled mRNA expression patterns overall. IL1B protein was at its lowest level in neonates and showed an approximate 70% increase in levels between neonates and infants (p = 0.008) (Fig. 1b). IL1B subsequently remained elevated, with toddler (p = 0.002), teenager (p = 0.004), and young adult (p = 0.005) levels of IL1B protein significantly higher than those for neonates. A significant linear increase in IL1B protein was detected in earlier age groups (ages 2 months old-5 years old) (Spearman’s rho, ρ = 0.479, p = 0.006) (Table 2). Overall, the magnitude of changes in protein across age was not as great as those in the mRNA, never exceeding a 140% increase in the mean between any two groups.

Table 2

Correlations with age under 5
Transcript	N	Rho	p-value
IL1β	31	0.551	0.001
IL1R1	31	0.509	0.003
IL18	31	0.58	< 0.001
IL18R	24	0.254	0.232
IL6	26	0.419	0.033
IL6R	32	0.542	0.001
IL6ST	32	0.498	0.004
TNF	21	0.421	0.057
TNFSRF1A	31	0.085	0.648
TNFSRF1B	31	0.208	0.261
IL1RAP	29	0.175	0.363
IL1RN	31	0.343	0.059
IL10	31	0.221	0.233
IL13	30	0.569	0.001
Protein
IL1β	32	0.479	0.006
IL18	31	0.157	0.399
IL6	28	0.474	0.011
TNF-α	32	0.555	< 0.001

Table 2. Correlation of cytokine protein and transcript expression levels with age under 5. Bolded transcripts and proteins are significantly correlated with age under 5.

However, there were some interesting differences in the pattern of change between the IL1B protein and mRNA, in that the plateau seen between ages 5-18 years old in the mRNA seemed to extend in the IL1B protein into the young adult group, whereas the mean IL1B mRNA levels dropped in the young adult group. In fact, the young adult IL1B protein level was still significantly increased by 100% compared to the IL1B protein level in neonates (p=0.005).

IL1R1 transcript, like its ligand IL1B, started with low expression levels, with a sharp increase in toddlers before returning to around neonatal levels during the school-age period (F(5,47) = 2.683, p = 0.033). IL1R1 mRNA levels significantly increased by 90%-100% from neonates and infants to toddlers (Neonates, p = 0.007; infants, p = 0.003) (Fig. 1c). IL1R1 mRNA was significantly correlated with age during the first 5 years of life (Spearman’s rho, ρ = 0.509, p = 0.003) (Table 2); however, IL1R1 mRNA demonstrated a delayed increase compared to IL1B mRNA and was not significantly increased in the first year of life. At later ages, mean IL1R1 mRNA was slightly, but not significantly, elevated to about 60–70% above neonatal levels (School-age children, p = 0.168; teenager, p = 0.131; young adult, p = 0.454). However, the cytoplasmic receptor accessory protein for IL1R, IL1RAP, did not change significantly between age groups (ANCOVA, RIN, pH; F(5,42) = 2.090, p = 0.086) (Fig. 1d). Similarly, IL1RAP did not correlate significantly with age under 5 (Spearman’s rho, ρ = 0.175, p = 0.363).

Increases in IL6 mRNA and protein both early in life and at maturation

Similar to IL1B, IL6 mRNA increased gradually, starting with low levels in neonates, which stabilized in the toddler age group and were sustained later in development. The first significant increase in IL6 mRNA by age group (F(5,52) = 3.265, p = 0.012) was a 380% increase from neonates to toddlers (p = 0.003) (Fig. 2a), and IL6 mRNA was moderately correlated with age within the first 5 years of life (Spearman’s rho, ρ = 0.419, p = 0.033) (Table 2). After this, IL6 mRNA showed an additional significant 410% increase in the expression of teenagers compared to infants (p < 0.019) and a 520% increase compared to neonatal levels. There was a slight subsequent reduction in IL6 mRNA in young adults, which returned the mean expression to intermediate levels, increased by only 140% compared to neonates (p = 0.010).

Like IL6 mRNA, IL6 protein increased gradually early in life before plateauing in toddlers. However, IL6 protein had an overall greater magnitude of mean change than IL6 mRNA. As with IL6 mRNA, IL6 protein was first significantly elevated in the toddler age group (F(5,44) = 2.585, p = 0.039), with an approximately 680% increase from neonatal levels (p = 0.006). Mean IL6 protein levels did start to increase in infants, which is reflected in the positive correlation of IL6 protein with age between 2 months and five years old (Spearman’s rho, ρ = 0.474, p = 0.011) (Table 2). While the early life IL6 mRNA increase was reflected in the IL6 protein level, the second period, where we found the highest mean IL6 mRNA in teenagers, was not. Mean protein level showed no significant difference between school-age children and teenagers (p = 0.514) (Fig. 2b). Thus, the highest IL6 protein levels were detected during the school-age period, which did increase by a large amount, 1200%, compared to neonates (p = 0.004).

IL6R mRNA increased in a steadier fashion after birth (F(5,49) = 6.067, p < 0.001) before peaking in toddlers, then stabilized at relatively elevated levels, similar to IL6 mRNA. When analyzed by age group, IL6R mRNA increased significantly by approximately 160% from neonates to toddlers (p < 0.001) and 90% from infants to toddlers (p < 0.001) (Fig. 2c). IL6R mRNA was significantly correlated with age between 2 months old and 5 years old (Spearman’s rho, ρ = 0.542, p = 0.001) (Table 2). The initial increase in IL6R expression resembles both IL6 mRNA and protein, but this change is of a smaller magnitude. IL6R expression remained elevated compared to both neonates and infants and school-age children (Neonates, p = 0.003; infants, p = 0.015), teenagers (Neonates, p = 0.002; infants, p = 0.010), and young adults (Neonates, p = 0.003; infants, p = 0.018). Furthermore, unlike IL-6 mRNA, we did not find a mean increase in IL6R mRNA in teenagers.

In contrast to IL1R1 and IL6R, IL6ST mRNA did not change significantly across development (F(5,49) = 2.284, p = 0.061) (Fig. 2d). In spite of the modest and non-significant changes in gene expression represented by the group means, IL6ST mRNA was significantly correlated with age under 5 years old, suggesting that there is an early steady increase in expression for all three of the IL1/IL6 receptors studied (ρ = 0.498, p = 0.004) (Table 2).

Increases in IL18 mRNA and protein, but not IL18R, with age

As with IL1B and IL6, IL18 mRNA levels were lowest just after birth in neonates and increased early in postnatal life (F(5,48) = 4.053, p = 0.004) (Fig. 3a). Like IL1B, IL18 mRNA then decreased in school-age children. IL18 mRNA decreased once more in young adults. Thus, IL18 mRNA peaked in toddlers with a significant 200% increase from neonates (p < 0.001), with mean IL18 mRNA levels in infants falling between neonates and toddlers (p = 0.229). IL18 mRNA was also significantly increased in toddlers by 90% when compared to infants (p = 0.001) (Fig. 3a). When focusing on the three youngest developmental groups, a fairly strong linear correlation between age and IL18 mRNA was detected between 2 months old and 5 years old (Spearman’s rho, ρ = 0.580, p < 0.001) (Table 2). The mean level of IL18 mRNA then decreased slightly in school-age children where it was still significantly elevated by 130% compared to neonates (p = 0.025). Mean IL18 mRNA levels were reduced to approximately neonatal levels in the young adult group (p = 0.129).

IL18 protein levels followed a similar pattern as their encoding transcript, increasing during postnatal life (Fig. 3b) (F(5,49) = 2.825, p = 0.026). Unlike IL18 mRNA, IL18 protein remained stably elevated in the teenager and young adult groups compared to neonates and infants (all p > 0.05). IL18 protein was elevated in toddlers by 50% compared to neonates (p = 0.046) and by 130% compared to infants (p = 0.043). There was a slight mean decrease in the school-age group which was not significantly different from any other age group (all p > 0.05).

While mean levels of IL18R1 mRNA appeared to increase over the age period studied, the change in transcript levels did not differ significantly with age (F(5,42) = 1.957, p = 0.105) (Fig. 3c). The levels of IL18R1 mRNA were quite variable at every age. Unlike other cytokines and receptors, IL18R1 mRNA was not significantly correlated with age when only considering those under 5 years old (Spearman’s rho, ρ = 0.254, p = 0.232) (Table 2).

Increases in TNFΑ and TNFR2, but not TNFR1, with age

As with the three other cytokines studied, TNF mRNA levels were lowest earlier in postnatal life and significantly increased during development (F(4,40) = 5.104, p = 0.002) (Fig. 4a). TNF mRNA increased 360% between the neonate + infant group and the toddler group (p = 0.044). When focusing on changes within the first few years of life, no significant correlation was found between TNF mRNA and age (Spearman’s rho, ρ = 0.421, p = 0.057) (Table 2). Similar to IL18, TNF decreased by 64% from toddlers to school-age children, where it was not significantly different from neonatal levels (p = 0.650). Then, in a pattern distinct from all three other cytokines investigated, TNF mRNA increased again in teenagers, exceeding even toddler levels by 100% (Fig. 4a) (p = 0.046).

Levels of TNF protein resembled TNF mRNA levels during post-natal life, increasing significantly in toddlers and remaining elevated into young adulthood (Fig. 4b) (F(5,50) = 7.722, p < 0.001). The fluctuations found in TNF mRNA expression levels between toddlers, school-age children, and teenagers could not be detected in TNF protein levels, but mean levels were elevated in toddlers, school-age children, teenagers, and young adults compared to neonates (All p < 0.001) and infants (Toddler, p = 0.007; school-age children, p = 0.008; teenager, p < 0.001, young adult, p = 0.004) Fig. 4b). When focusing on changes within the first few years of life, a strong positive correlation was found between TNF protein and age (Spearman’s rho, ρ = 0.555, p < 0.001). In agreement with TNF mRNA, mean TNF protein levels peaked in teenagers, which were increased by almost 430% compared to neonates (p < 0.001).

TNFRSF1A mRNA did not show any significant differences when analyzed by age group (F(5,50) = 0.111, p = 0.989)(Fig. 4c). TNFRSF1B mRNA levels were increased beginning in toddlers and remained elevated throughout young adulthood (F(5,48) = 2.763, p = 0.028). TNFRSF1B mRNA levels were increased approximately 60% on average when comparing infants to toddlers (p = 0.045), school-age children (p = 0.023), teenagers (p = 0.019), and young adults (p = 0.002). Neither TNFRSF1A mRNA (Spearman’s rho, ρ = 0.085, p = 0.648) nor TNFRSF1B mRNA (Spearman’s rho, ρ = 0.208, p = 0.261) levels were correlated with age under 5 years old (Table 2). The absence of correlation in TNFRSF1B with age under 5 years old, combined with the age group data, suggests an abrupt increase and peak in expression between 2–5 years old, which persists into young adulthood (Fig. 4d).

‘Anti-inflammatory’ cytokines increased during later stages of brain development

Messenger RNA for IL1RN, the receptor antagonist of IL1B, was not significantly changed between age groups (Welch’s ANOVA, F(5,21.645) = 2.534, p = 0.059) (Fig. 5a), and this was reflected by a lack of a significant correlation with age under 5 (Spearman’s rho, ρ = 0.343, p = 0.059) (Table 2). IL13 mRNA, in contrast, did change significantly between age groups (Welch’s ANOVA, F(5,19.561) = 10.9232, p < 0.001). IL13 mRNA first increased 164% in toddlers relative to neonates (p = 0.006) (Fig. 5b) and was significantly correlated with age under 5 years old (Spearman’s rho, ρ = 0.528, p < 0.001) (Table 2). IL13 mRNA levels peaked in young adults, where it increased by 237% relative to neonates (p = 0.014) and 118% relative to infants (p = 0.036). In contrast, IL10 mRNA was 74% higher in teenagers (Welch’s ANOVA, F(5,22.036) = 3.232, p = 0.024) than it was in young adults (p = 0.049) (Fig. 5c). No clear changes could be detected in IL10 mRNA in earlier age groups, though toddlers had the (statistically non-significant) greatest mean expression level of IL10 mRNA. IL10 mRNA was also not correlated with age under 5 years old (Spearman’s rho, ρ = 0.221, p = 0.233) (Table 2).

In this study, we have characterized changes in mRNA and protein expression of cytokine and cytokine receptors in the developing human prefrontal cortex, with sufficient power to allow a quantitative rather than qualitative analysis. All cytokines studied were expressed in the post-natal human brain as both mRNA and protein (excepting the very little to no expression of TNF mRNA in some neonatal prefrontal cortices). We found that both transcript and protein levels of almost all pro-inflammatory cytokines were characterized by a steady increase under age 5, which was consistent with complement pathway factors previously reported in the same cohort (28). Given what we know about the interplay between complement and cytokines, we interpret that this concomitant increase could mean that these components of the immune system operate together or in a coordinated fashion to regulate normal development. However, following the initial increase in toddlers, the four pro-inflammatory cytokines studied here diverged in expression during brain maturation. IL1B and IL18 decreased in transcription in the school-age children and young adult age groups as predicted, similar to the changes previously seen in complement expression (28). In contrast, IL6 and TNF expression, increased a second time during adolescence. Thus, we saw peaks in cytokine expression during two distinct periods of development.

Previously, we found that complement inhibitor expression increased after complement peaked in toddlers, and that complement expression subsequently decreased (28). In contrast, here we found that the inhibitory cytokines IL1RN or IL10 were not as dynamically expressed across development as the inhibitors of complement we previously characterized. The only cytokine inhibitor to show any change in expression was IL13. As IL13 inhibits proinflammatory cytokines (101–103), the increase in IL13 mRNA in adolescence may represent regulatory pressure on proinflammatory cytokine expression in that age group. However, IL13 can also regulate the effects of complement-mediated lysis in the periphery by inhibiting the downstream effects of the membrane attack complex (104), raising the possibility that elevated IL13 may be more involved in the regulation of complement pathway activity than in IL6 or TNF signaling.

As with cytokines, certain cytokine receptors varied across development. In particular, IL1R1, IL6R and TNFRSF1B expression changed between age groups. Notably, when changes were found in receptor expression, those changes approximated the pattern of their associated cytokine ligand. IL1R1, for instance, increased in toddlers and decreased in older age groups. IL6R and TNFRSF1B, like IL6 and TNF protein and mRNA, increased in toddlers and remained relatively elevated during late development, including adolescence. Other receptors, IL1RAP, IL18R, IL6ST, and TNFRSF1A remained stable throughout the first 2 decades of postnatal life. These results suggest that, like cytokines, the trajectory of cytokine receptor expression across development is not uniform, and that increases in ligand and receptor pairs are more often concomitantly increased when they activate signaling rather than inhibit it.

The evidence presented here suggests that cytokine expression is upregulated during two major periods in human development: early neurodevelopment, when processes such as interneuron migration (71, 72) and synaptogenesis (81, 82) dominate brain development; and late neurodevelopment, which is associated with synaptic pruning (81, 82), myelination (89, 90), and final GABAergic system maturation (105, 106). Cytokines have the potential to affect these processes based on both the timing reported here, and on effects previously reported in the literature. For instance, IL1B has been previously associated with neuronal migration (41) and the survival of differentiating oligodendrocytes (107) in vitro and in vivo. Based on the timing of the peak in IL1B, it is interesting to consider whether IL1B during postnatal development may be associated with maturation from preoligodendrocyte to mature oligodendrocyte, which drops around age 5 in humans (108). Similarly, the adolescent peak in IL6 and TNF mRNAs could be associated with maturation of neurotransmitter systems, i.e. the GABAergic system. The development of GABAergic signaling is a known developmental process that is estimated to extend into adolescence (105, 106). Both IL6 and TNF are known regulators of GABA receptor levels through endocytosis of GABA receptors at the synapse (109, 110). It is interesting to consider whether increased expression in IL6 and/or TNF could contribute to the normal regulation of GABA receptor levels at the synapse in adolescents. We speculate that exaggerated increases in either IL6 or TNF during maturation may throw off normal homeostasis.

The adolescent increase in IL6 and TNF may be significant when considered in light of the age of onset for schizophrenia, which commonly occurs just after adolescence. Notably, increased IL6 mRNA and protein levels are one of the most robust changes found in the brain and blood of people with schizophrenia (111–121). There is increasing evidence of the role of the immune system in neurodevelopmental psychiatric disorders. Epidemiological work in humans suggests that immune activation during gestation and early childhood is associated with the occurrence of neurodevelopmental disorders, in particular the development of ASD, ADHD (Attention-deficit/hyperactivity disorder), and schizophrenia (23, 122–126). Immune activation during development may have short- and long-term impacts on brain development, potentially by disrupting immune factor levels directly during development (127), by inducing changes that affect the systemic response to environmental triggers later in life (e.g. (128–130)), and/or by inducing long-term changes in immune signal expression (50, 113, 128, 131). In this study, we have found evidence that cytokine expression is also active and regulated well after the fetal period in humans, from birth through young adulthood, indicating that cytokines likely have a role in normal postnatal human cortical development. Thus, the dysregulation of cytokine expression during early postnatal life could similarly disrupt brain development through direct or indirect effects on developmental processes. We can use this new knowledge of regulated cytokine expression in the postnatal human prefrontal cortex to expand upon the interaction between cytokine expression, specific brain development processes, and behavioral outcomes using experimental data. In particular, future studies utilizing targeted knockdown, knockout, and/or overexpression of these cytokines with inducible rodent models may allow us to assess the contribution of specific cytokines to development more directly. For instance, by inhibiting a given cytokine during its period of elevated expression reported here, it may be possible to tie normal cytokine activity to particular processes in postnatal development. Characterizing the normal contribution of cytokines to development will help clarify both the effects of abnormal inflammation/cytokine expression on developmental processes, and whether those effects relate to distinct periods of vulnerability.

Unlike mRNA, cytokine proteins circulate freely in the blood serum under physiological conditions. Unfortunately, studies regarding the expression patterns of cytokines in the serum at different developmental ages in humans are somewhat limited. In the case of IL1B, IL6, IL18, and TNF, a comparison of the protein levels detected in this study to serum protein levels reported under physiological conditions during childhood (132) suggests that the contamination of tissue with circulating cytokines would not fully explain the changes in cytokine protein expression seen in this study. The reported pattern of IL18 blood serum protein expression, for instance, found that IL18 was highest between ages 1–7 years old and lowest in samples over 18 years old (132). IL18 brain protein levels were lowest in neonates and infants, so a contribution from the serum would presumably artificially inflate apparent IL18 protein concentrations in this age group. If anything, excluding any serum protein contribution from the results in our study, would emphasize the difference between age groups by decreasing neonate and infant levels to diverge further from teenager and young adult levels. In short, serum protein levels may contribute to the total protein levels reported in this study; however, the patterns of protein expression reported herein were largely consistent with corresponding mRNA expression patterns and did not strongly resemble existing reports of serum cytokine levels during human development.

This work provides a foundation for understanding the normal changes in levels of cytokine, cytokine receptors, and inhibitors from early postnatal neurodevelopment to maturation in the human cortex. Our results suggest that there may be two distinct time windows (toddlers and teenagers) when cytokine signaling takes a more salient role in human cortical development, both of which are associated with an increased incidence of major psychiatric disorders. The increases seen in cytokine expression for IL1B, IL6, IL13, IL18, and TNF between birth and age 5 suggest a significant action around the time of onset of ASD. These results highlight toddlerhood not just as an overall transformative period in the brain but as a period of development strongly tied to immune-associated cytokine signaling as well as complement signaling. Given that late adolescence is considered a period of vulnerability to psychiatric disorders, especially schizophrenia, the role of IL6 and TNF in adolescent cortical development needs further consideration and study. Additionally, since adolescence is normally not associated with increased complement levels but rather is associated with increased complement inhibition, this suggests that increased cytokines may be acting independently of complement at maturation and without associated transcriptional increases in major cytokine inhibitors.

ADHD

attention-deficit/hyperactivity disorder

ASD

Autism Spectrum Disorder

BCA

bicinchoninic acid

EDTA

ethylenediaminetetraacetic acid

N-PER

Neuronal Protein Extraction Reagent

LSD

Least Significant Difference

PMI

post-mortem interval

RIN

RNA integrity number

SIDS

Sudden Infant Death Syndrome

Ethical approval and consent to participate

Experiments involving human tissue were approved by the University of New South Wales Human Research Ethics Committee (HC16441).

Consent for publication

All authors consent to publication.

Availability of data and materials

All data is available upon request.

Competing interests

The authors declare no competing interests.

Funding

The NSW Ministry of Health, Office of Health and Medical Research provided funding for this work. CSW is a recipient of a National Health and Medical Research Council (Australia) Principal Research Fellowship (2009237). SUNY Upstate Medical University provided stipend support (R.E.H.S) and their Hendricks Intramural Pilot Grant (C.S.W.).

Authors’ contributions

Conceptualization, C.S.W., R.E.H.S., M.W., A.K.W., F.M., K.R., M.J.W.; Methodology, R.E.H.S., K.R., K.G., C.S.W., M.J.W.; Investigation, R.E.H.S., K.G., and C.S.W.; Formal analysis, R.E.H.S., C.S.W; Writing – original draft, R.E.H.S.; Writing – review and editing, R.E.H.S., C.S.W., A.K.W., M.W., F.M., K.R., M.J.W.; Funding acquisition, C.S.W.; Resources, C.S.W., M.J.W.; Supervision, C.S.W.

Acknowledgements

We would like to thank the University of Maryland Brain and Tissue Bank, and the families of donors for providing human samples.

Spann MN, Sourander A, Surcel HM, Hinkka-Yli-Salomaki S, Brown AS. Prenatal toxoplasmosis antibody and childhood autism. Autism Res. 2017;10(5):769-77.
Xiao J, Buka SL, Cannon TD, Suzuki Y, Viscidi RP, Torrey EF, et al. Serological pattern consistent with infection with type I Toxoplasma gondii in mothers and risk of psychosis among adult offspring. Microbes Infect. 2009;11(13):1011-8.
Brown AS, Schaefer CA, Quesenberry CP, Jr., Liu L, Babulas VP, Susser ES. Maternal exposure to toxoplasmosis and risk of schizophrenia in adult offspring. Am J Psychiatry. 2005;162(4):767-73.
Brown AS, Begg MD, Gravenstein S, Schaefer CA, Wyatt RJ, Bresnahan M, et al. Serologic evidence of prenatal influenza in the etiology of schizophrenia. Arch Gen Psychiatry. 2004;61(8):774-80.
Brown AS, Cohen P, Harkavy-Friedman J, Babulas V, Malaspina D, Gorman JM, et al. A.E. Bennett Research Award. Prenatal rubella, premorbid abnormalities, and adult schizophrenia. Biol Psychiatry. 2001;49(6):473-86.
Chess S. Follow-up report on autism in congenital rubella. J Autism Child Schizophr. 1977;7(1):69-81.
Chess S, Fernandez P, Korn S. Behavioral consequences of congenital rubella. J Pediatr. 1978;93(4):699-703.
Berger BE, Navar-Boggan AM, Omer SB. Congenital rubella syndrome and autism spectrum disorder prevented by rubella vaccination--United States, 2001-2010. BMC Public Health. 2011;11:340.
Hutton J. Does Rubella Cause Autism: A 2015 Reappraisal? Front Hum Neurosci. 2016;10:25.
Yamashita Y, Fujimoto C, Nakajima E, Isagai T, Matsuishi T. Possible association between congenital cytomegalovirus infection and autistic disorder. J Autism Dev Disord. 2003;33(4):455-9.
Sakamoto A, Moriuchi H, Matsuzaki J, Motoyama K, Moriuchi M. Retrospective diagnosis of congenital cytomegalovirus infection in children with autism spectrum disorder but no other major neurologic deficit. Brain Dev. 2015;37(2):200-5.
Garofoli F, Lombardi G, Orcesi S, Pisoni C, Mazzucchelli I, Angelini M, et al. An Italian Prospective Experience on the Association Between Congenital Cytomegalovirus Infection and Autistic Spectrum Disorder. J Autism Dev Disord. 2017;47(5):1490-5.
Buka SL, Cannon TD, Torrey EF, Yolken RH, Collaborative Study Group on the Perinatal Origins of Severe Psychiatric D. Maternal exposure to herpes simplex virus and risk of psychosis among adult offspring. Biol Psychiatry. 2008;63(8):809-15.
Buka SL, Tsuang MT, Torrey EF, Klebanoff MA, Bernstein D, Yolken RH. Maternal infections and subsequent psychosis among offspring. Arch Gen Psychiatry. 2001;58(11):1032-7.
Mortensen PB, Pedersen CB, Hougaard DM, Norgaard-Petersen B, Mors O, Borglum AD, et al. A Danish National Birth Cohort study of maternal HSV-2 antibodies as a risk factor for schizophrenia in their offspring. Schizophr Res. 2010;122(1-3):257-63.
Mortensen PB, Norgaard-Pedersen B, Waltoft BL, Sorensen TL, Hougaard D, Torrey EF, et al. Toxoplasma gondii as a risk factor for early-onset schizophrenia: analysis of filter paper blood samples obtained at birth. Biol Psychiatry. 2007;61(5):688-93.
Edlow AG, Castro VM, Shook LL, Kaimal AJ, Perlis RH. Neurodevelopmental Outcomes at 1 Year in Infants of Mothers Who Tested Positive for SARS-CoV-2 During Pregnancy. JAMA Netw Open. 2022;5(6):e2215787.
Zhang J, Luo W, Huang P, Peng L, Huang Q. Maternal C-reactive protein and cytokine levels during pregnancy and the risk of selected neuropsychiatric disorders in offspring: A systematic review and meta-analysis. J Psychiatr Res. 2018;105:86-94.
Han VX, Patel S, Jones HF, Dale RC. Maternal immune activation and neuroinflammation in human neurodevelopmental disorders. Nat Rev Neurol. 2021;17(9):564-79.
Han VX, Patel S, Jones HF, Nielsen TC, Mohammad SS, Hofer MJ, et al. Maternal acute and chronic inflammation in pregnancy is associated with common neurodevelopmental disorders: a systematic review. Transl Psychiatry. 2021;11(1):71.
Brown AS, Sourander A, Hinkka-Yli-Salomaki S, McKeague IW, Sundvall J, Surcel HM. Elevated maternal C-reactive protein and autism in a national birth cohort. Mol Psychiatry. 2014;19(2):259-64.
Canetta S, Sourander A, Surcel HM, Hinkka-Yli-Salomaki S, Leiviska J, Kellendonk C, et al. Elevated maternal C-reactive protein and increased risk of schizophrenia in a national birth cohort. Am J Psychiatry. 2014;171(9):960-8.
Khandaker GM, Zimbron J, Dalman C, Lewis G, Jones PB. Childhood infection and adult schizophrenia: a meta-analysis of population-based studies. Schizophr Res. 2012;139(1-3):161-8.
Scola G, Duong A. Prenatal maternal immune activation and brain development with relevance to psychiatric disorders. Neuroscience. 2017;346:403-8.
Solek CM, Farooqi N, Verly M, Lim TK, Ruthazer ES. Maternal immune activation in neurodevelopmental disorders. Dev Dyn. 2018;247(4):588-619.
Bergdolt L, Dunaevsky A. Brain changes in a maternal immune activation model of neurodevelopmental brain disorders. Prog Neurobiol. 2019;175:1-19.
Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, Kamitaki N, et al. Schizophrenia risk from complex variation of complement component 4. Nature. 2016;530(7589):177-83.
Sager REH, Walker AK, Middleton F, Robinson K, Webster MJ, Weickert CS. Trajectory of change in brain complement factors from neonatal to young adult humans. J Neurochem. 2020.
Milkowska P, Popko K, Demkow U, Wolanczyk T. Pro-Inflammatory Cytokines in Psychiatric Disorders in Children and Adolescents: A Review. Adv Exp Med Biol. 2017.
Kawakami Y, Watanabe Y, Yamaguchi M, Sakaguchi H, Kono I, Ueki A. TNF-alpha stimulates the biosynthesis of complement C3 and factor B by human umbilical cord vein endothelial cells. Cancer Lett. 1997;116(1):21-6.
Page MJ, Bester J, Pretorius E. The inflammatory effects of TNF-alpha and complement component 3 on coagulation. Sci Rep. 2018;8(1):1812.
Thomas AM, Gerogianni A, McAdam MB, Floisand Y, Lau C, Espevik T, et al. Complement Component C5 and TLR Molecule CD14 Mediate Heme-Induced Thromboinflammation in Human Blood. J Immunol. 2019;203(6):1571-8.
Sheerin NS, Zhou W, Adler S, Sacks SH. TNF-alpha regulation of C3 gene expression and protein biosynthesis in rat glomerular endothelial cells. Kidney Int. 1997;51(3):703-10.
Sayah S, Ischenko AM, Zhakhov A, Bonnard AS, Fontaine M. Expression of cytokines by human astrocytomas following stimulation by C3a and C5a anaphylatoxins: specific increase in interleukin-6 mRNA expression. J Neurochem. 1999;72(6):2426-36.
Luo C, Chen M, Xu H. Complement gene expression and regulation in mouse retina and retinal pigment epithelium/choroid. Mol Vis. 2011;17:1588-97.
Takabayashi T, Vannier E, Clark BD, Margolis NH, Dinarello CA, Burke JF, et al. A new biologic role for C3a and C3a desArg: regulation of TNF-alpha and IL-1 beta synthesis. J Immunol. 1996;156(9):3455-60.
Schindler R, Gelfand JA, Dinarello CA. Recombinant C5a stimulates transcription rather than translation of interleukin-1 (IL-1) and tumor necrosis factor: translational signal provided by lipopolysaccharide or IL-1 itself. Blood. 1990;76(8):1631-8.
Mousa A, SeigerA, Kjaeldgaard A, Bakhiet M. Human first trimester forebrain cells express genes for inflammatory and anti-inflammatory cytokines. Cytokine. 1999;11(1):55-60.
Yli-Karjanmaa M, Larsen KS, Fenger CD, Kristensen LK, Martin NA, Jensen PT, et al. TNF deficiency causes alterations in the spatial organization of neurogenic zones and alters the number of microglia and neurons in the cerebral cortex. Brain Behav Immun. 2019;82:279-97.
Miller FD, Gauthier AS. Timing is everything: making neurons versus glia in the developing cortex. Neuron. 2007;54(3):357-69.
Ma L, Li XW, Zhang SJ, Yang F, Zhu GM, Yuan XB, et al. Interleukin-1 beta guides the migration of cortical neurons. J Neuroinflammation. 2014;11:114.
Islam O, Gong X, Rose-John S, Heese K. Interleukin-6 and neural stem cells: more than gliogenesis. Mol Biol Cell. 2009;20(1):188-99.
Nakanishi M, Niidome T, Matsuda S, Akaike A, Kihara T, Sugimoto H. Microglia-derived interleukin-6 and leukaemia inhibitory factor promote astrocytic differentiation of neural stem/progenitor cells. Eur J Neurosci. 2007;25(3):649-58.
Pousset F. Developmental expression of cytokine genes in the cortex and hippocampus of the rat central nervous system. Brain Res Dev Brain Res. 1994;81(1):143-6.
Higgins GA, Olschowka JA. Induction of interleukin-1 beta mRNA in adult rat brain. Brain Res Mol Brain Res. 1991;9(1-2):143-8.
Choe W, Stoica G, Lynn W, Wong PK. Neurodegeneration induced by MoMuLV-ts1 and increased expression of Fas and TNF-alpha in the central nervous system. Brain Res. 1998;779(1-2):1-8.
Vitkovic L, Bockaert J, Jacque C. "Inflammatory" cytokines: neuromodulators in normal brain? J Neurochem. 2000;74(2):457-71.
Wesselingh SL, Power C, Glass JD, Tyor WR, McArthur JC, Farber JM, et al. Intracerebral cytokine messenger RNA expression in acquired immunodeficiency syndrome dementia. Ann Neurol. 1993;33(6):576-82.
Culhane AC, Hall MD, Rothwell NJ, Luheshi GN. Cloning of rat brain interleukin-18 cDNA. Mol Psychiatry. 1998;3(4):362-6.
Garay PA, Hsiao EY, Patterson PH, McAllister AK. Maternal immune activation causes age- and region-specific changes in brain cytokines in offspring throughout development. Brain Behav Immun. 2013;31:54-68.
Akerberg BN, Gu F, VanDusen NJ, Zhang X, Dong R, Li K, et al. A reference map of murine cardiac transcription factor chromatin occupancy identifies dynamic and conserved enhancers. Nat Commun. 2019;10(1):4907.
Zhang Y, Chen K, Sloan SA, Bennett ML, Scholze AR, O'Keeffe S, et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J Neurosci. 2014;34(36):11929-47.
Zhang Y, Sloan SA, Clarke LE, Caneda C, Plaza CA, Blumenthal PD, et al. Purification and Characterization of Progenitor and Mature Human Astrocytes Reveals Transcriptional and Functional Differences with Mouse. Neuron. 2016;89(1):37-53.
Wong ML, Bongiorno PB, Gold PW, Licinio J. Localization of interleukin-1 beta converting enzyme mRNA in rat brain vasculature: evidence that the genes encoding the interleukin-1 system are constitutively expressed in brain blood vessels. Pathophysiological implications. Neuroimmunomodulation. 1995;2(3):141-8.
Wong ML, Licinio J. Localization of interleukin 1 type I receptor mRNA in rat brain. Neuroimmunomodulation. 1994;1(2):110-5.
Andre R, Wheeler RD, Collins PD, Luheshi GN, Pickering-Brown S, Kimber I, et al. Identification of a truncated IL-18R beta mRNA: a putative regulator of IL-18 expressed in rat brain. J Neuroimmunol. 2003;145(1-2):40-5.
Ban E, Milon G, Prudhomme N, Fillion G, Haour F. Receptors for interleukin-1 (alpha and beta) in mouse brain: mapping and neuronal localization in hippocampus. Neuroscience. 1991;43(1):21-30.
Farrar WL, Kilian PL, Ruff MR, Hill JM, Pert CB. Visualization and characterization of interleukin 1 receptors in brain. J Immunol. 1987;139(2):459-63.
Cunningham ET, Jr., Wada E, Carter DB, Tracey DE, Battey JF, De Souza EB. In situ histochemical localization of type I interleukin-1 receptor messenger RNA in the central nervous system, pituitary, and adrenal gland of the mouse. J Neurosci. 1992;12(3):1101-14.
Schobitz B, Voorhuis DA, De Kloet ER. Localization of interleukin 6 mRNA and interleukin 6 receptor mRNA in rat brain. Neurosci Lett. 1992;136(2):189-92.
Takao T, Culp SG, Newton RC, De Souza EB. Type I interleukin-1 receptors in the mouse brain-endocrine-immune axis labelled with [125I]recombinant human interleukin-1 receptor antagonist. J Neuroimmunol. 1992;41(1):51-60.
Gadient RA, Otten U. Expression of interleukin-6 (IL-6) and interleukin-6 receptor (IL-6R) mRNAs in rat brain during postnatal development. Brain Res. 1994;637(1-2):10-4.
Ericsson A, Liu C, Hart RP, Sawchenko PE. Type 1 interleukin-1 receptor in the rat brain: distribution, regulation, and relationship to sites of IL-1-induced cellular activation. J Comp Neurol. 1995;361(4):681-98.
Dopp JM, Mackenzie-Graham A, Otero GC, Merrill JE. Differential expression, cytokine modulation, and specific functions of type-1 and type-2 tumor necrosis factor receptors in rat glia. J Neuroimmunol. 1997;75(1-2):104-12.
Tchelingerian JL, Monge M, Le Saux F, Zalc B, Jacque C. Differential oligodendroglial expression of the tumor necrosis factor receptors in vivo and in vitro. J Neurochem. 1995;65(5):2377-80.
Association AP. Diagnostic and statistical manual of psychiatric disorders. 2013.
Bacon EC, Courchesne E, Barnes CC, Cha D, Pence S, Schreibman L, et al. Rethinking the idea of late autism spectrum disorder onset. Dev Psychopathol. 2018;30(2):553-69.
Vargas DL, Nascimbene C, Krishnan C, Zimmerman AW, Pardo CA. Neuroglial activation and neuroinflammation in the brain of patients with autism. Ann Neurol. 2005;57(1):67-81.
Estes ML, McAllister AK. Immune mediators in the brain and peripheral tissues in autism spectrum disorder. Nat Rev Neurosci. 2015;16(8):469-86.
Xu N, Li X, Zhong Y. Inflammatory cytokines: potential biomarkers of immunologic dysfunction in autism spectrum disorders. Mediators Inflamm. 2015;2015:531518.
Paredes MF, James D, Gil-Perotin S, Kim H, Cotter JA, Ng C, et al. Extensive migration of young neurons into the infant human frontal lobe. Science. 2016;354(6308).
Fung SJ, Joshi D, Allen KM, Sivagnanasundaram S, Rothmond DA, Saunders R, et al. Developmental patterns of doublecortin expression and white matter neuron density in the postnatal primate prefrontal cortex and schizophrenia. PLoS One. 2011;6(9):e25194.
Chan WY, Lorke DE, Tiu SC, Yew DT. Proliferation and apoptosis in the developing human neocortex. Anat Rec. 2002;267(4):261-76.
Naruse I, Keino H. Apoptosis in the developing CNS. Prog Neurobiol. 1995;47(2):135-55.
Ferrer I, Serrano T, Soriano E. Naturally occurring cell death in the subicular complex and hippocampus in the rat during development. Neurosci Res. 1990;8(1):60-6.
Ferrer I, Soriano E, del Rio JA, Alcantara S, Auladell C. Cell death and removal in the cerebral cortex during development. Prog Neurobiol. 1992;39(1):1-43.
Peerboom C, Wierenga CJ. The postnatal GABA shift: A developmental perspective. Neurosci Biobehav Rev. 2021;124:179-92.
Kilb W. Development of the GABAergic system from birth to adolescence. Neuroscientist. 2012;18(6):613-30.
Fung SJ, Webster MJ, Sivagnanasundaram S, Duncan C, Elashoff M, Weickert CS. Expression of interneuron markers in the dorsolateral prefrontal cortex of the developing human and in schizophrenia. Am J Psychiatry. 2010;167(12):1479-88.
Xu G, Broadbelt KG, Haynes RL, Folkerth RD, Borenstein NS, Belliveau RA, et al. Late development of the GABAergic system in the human cerebral cortex and white matter. J Neuropathol Exp Neurol. 2011;70(10):841-58.
Huttenlocher PR. Synaptic density in human frontal cortex - developmental changes and effects of aging. Brain Res. 1979;163(2):195-205.
Petanjek Z, Judas M, Simic G, Rasin MR, Uylings HB, Rakic P, et al. Extraordinary neoteny of synaptic spines in the human prefrontal cortex. Proc Natl Acad Sci U S A. 2011;108(32):13281-6.
Stevens B, Allen NJ, Vazquez LE, Howell GR, Christopherson KS, Nouri N, et al. The classical complement cascade mediates CNS synapse elimination. Cell. 2007;131(6):1164-78.
Schafer DP, Lehrman EK, Kautzman AG, Koyama R, Mardinly AR, Yamasaki R, et al. Microglia sculpt postnatal neural circuits in an activity and complement-dependent manner. Neuron. 2012;74(4):691-705.
Paolicelli RC, Bolasco G, Pagani F, Maggi L, Scianni M, Panzanelli P, et al. Synaptic pruning by microglia is necessary for normal brain development. Science. 2011;333(6048):1456-8.
Mallya AP, Wang HD, Lee HNR, Deutch AY. Microglial Pruning of Synapses in the Prefrontal Cortex During Adolescence. Cereb Cortex. 2019;29(4):1634-43.
Attaai A, Neidert N, von Ehr A, Potru PS, Zoller T, Spittau B. Postnatal maturation of microglia is associated with alternative activation and activated TGFbeta signaling. Glia. 2018;66(8):1695-708.
Knuesel I, Chicha L, Britschgi M, Schobel SA, Bodmer M, Hellings JA, et al. Maternal immune activation and abnormal brain development across CNS disorders. Nat Rev Neurol. 2014;10(11):643-60.
Brody BA, Kinney HC, Kloman AS, Gilles FH. Sequence of central nervous system myelination in human infancy. I. An autopsy study of myelination. J Neuropathol Exp Neurol. 1987;46(3):283-301.
Kinney HC, Brody BA, Kloman AS, Gilles FH. Sequence of central nervous system myelination in human infancy. II. Patterns of myelination in autopsied infants. J Neuropathol Exp Neurol. 1988;47(3):217-34.
Blood-Siegfried J. The role of infection and inflammation in sudden infant death syndrome. Immunopharmacol Immunotoxicol. 2009;31(4):516-23.
Franceschi C, Campisi J. Chronic inflammation (inflammaging) and its potential contribution to age-associated diseases. J Gerontol A Biol Sci Med Sci. 2014;69 Suppl 1:S4-9.
Nilsson LG, Sternang O, Ronnlund M, Nyberg L. Challenging the notion of an early-onset of cognitive decline. Neurobiol Aging. 2009;30(4):521-4; discussion 30-3.
Salthouse TA. When does age-related cognitive decline begin? Neurobiol Aging. 2009;30(4):507-14.
Finch CE. The neurobiology of middle-age has arrived. Neurobiol Aging. 2009;30(4):515-20; discussion 30-33.
Schaie KW. "When does age-related cognitive decline begin?" Salthouse again reifies the "cross-sectional fallacy". Neurobiol Aging. 2009;30(4):528-9; discussion 30-33.
Kozlovsky N, Shanon-Weickert C, Tomaskovic-Crook E, Kleinman JE, Belmaker RH, Agam G. Reduced GSK-3beta mRNA levels in postmortem dorsolateral prefrontal cortex of schizophrenic patients. J Neural Transm (Vienna). 2004;111(12):1583-92.
Fillman SG, Sinclair D, Fung SJ, Webster MJ, Shannon Weickert C. Markers of inflammation and stress distinguish subsets of individuals with schizophrenia and bipolar disorder. Transl Psychiatry. 2014;4:e365.
Welch BL. On the Comparison of Several Mean Values: An Alternative Approach. Biometrika. 1951;38:330-6.
Tomarken AJ, and Ronald C. Serlin. Comparison of ANOVA alternatives under variance heterogeneity and specific noncentrality structures. Psychological Bulletin. 1986;99(1):90-9.
de Vries JE. The role of IL-13 and its receptor in allergy and inflammatory responses. J Allergy Clin Immunol. 1998;102(2):165-9.
Hershey GK. IL-13 receptors and signaling pathways: an evolving web. J Allergy Clin Immunol. 2003;111(4):677-90; quiz 91.
de Waal Malefyt R, Abrams J, Bennett B, Figdor CG, de Vries JE. Interleukin 10(IL-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of IL-10 produced by monocytes. J Exp Med. 1991;174(5):1209-20.
Grehan JF, Levay-Young BK, Fogelson JL, Francois-Bongarcon V, Benson BA, Dalmasso AP. IL-4 and IL-13 induce protection of porcine endothelial cells from killing by human complement and from apoptosis through activation of a phosphatidylinositide 3-kinase/Akt pathway. J Immunol. 2005;175(3):1903-10.
Pinto JG, Hornby KR, Jones DG, Murphy KM. Developmental changes in GABAergic mechanisms in human visual cortex across the lifespan. Front Cell Neurosci. 2010;4:16.
Hashimoto T, Nguyen QL, Rotaru D, Keenan T, Arion D, Beneyto M, et al. Protracted developmental trajectories of GABAA receptor alpha1 and alpha2 subunit expression in primate prefrontal cortex. Biol Psychiatry. 2009;65(12):1015-23.
Vela JM, Molina-Holgado E, Arevalo-Martin A, Almazan G, Guaza C. Interleukin-1 regulates proliferation and differentiation of oligodendrocyte progenitor cells. Mol Cell Neurosci. 2002;20(3):489-502.
Yeung MS, Zdunek S, Bergmann O, Bernard S, Salehpour M, Alkass K, et al. Dynamics of oligodendrocyte generation and myelination in the human brain. Cell. 2014;159(4):766-74.
Stellwagen D, Beattie EC, Seo JY, Malenka RC. Differential regulation of AMPA receptor and GABA receptor trafficking by tumor necrosis factor-alpha. J Neurosci. 2005;25(12):3219-28.
Garcia-Oscos F, Salgado H, Hall S, Thomas F, Farmer GE, Bermeo J, et al. The stress-induced cytokine interleukin-6 decreases the inhibition/excitation ratio in the rat temporal cortex via trans-signaling. Biol Psychiatry. 2012;71(7):574-82.
Fillman SG, Cloonan N, Catts VS, Miller LC, Wong J, McCrossin T, et al. Increased inflammatory markers identified in the dorsolateral prefrontal cortex of individuals with schizophrenia. Mol Psychiatry. 2013;18(2):206-14.
Boerrigter D, Weickert TW, Lenroot R, O'Donnell M, Galletly C, Liu D, et al. Using blood cytokine measures to define high inflammatory biotype of schizophrenia and schizoaffective disorder. J Neuroinflammation. 2017;14(1):188.
Purves-Tyson TD, Weber-Stadlbauer U, Richetto J, Rothmond DA, Labouesse MA, Polesel M, et al. Increased levels of midbrain immune-related transcripts in schizophrenia and in murine offspring after maternal immune activation. Mol Psychiatry. 2021;26(3):849-63.
North HF, Weissleder C, Fullerton JM, Sager R, Webster MJ, Weickert CS. A schizophrenia subgroup with elevated inflammation displays reduced microglia, increased peripheral immune cell and altered neurogenesis marker gene expression in the subependymal zone. Transl Psychiatry. 2021;11(1):635.
Purves-Tyson TD, Robinson K, Brown AM, Boerrigter D, Cai HQ, Weissleder C, et al. Increased Macrophages and C1qA, C3, C4 Transcripts in the Midbrain of People With Schizophrenia. Front Immunol. 2020;11:2002.
Catts VS, Wong J, Fillman SG, Fung SJ, Shannon Weickert C. Increased expression of astrocyte markers in schizophrenia: Association with neuroinflammation. Aust N Z J Psychiatry. 2014;48(8):722-34.
Kindler J, Lim CK, Weickert CS, Boerrigter D, Galletly C, Liu D, et al. Dysregulation of kynurenine metabolism is related to proinflammatory cytokines, attention, and prefrontal cortex volume in schizophrenia. Mol Psychiatry. 2020;25(11):2860-72.
Cai HQ, Catts VS, Webster MJ, Galletly C, Liu D, O'Donnell M, et al. Increased macrophages and changed brain endothelial cell gene expression in the frontal cortex of people with schizophrenia displaying inflammation. Mol Psychiatry. 2020;25(4):761-75.
Luo Y, He H, Zhang J, Ou Y, Fan N. Changes in serum TNF-alpha, IL-18, and IL-6 concentrations in patients with chronic schizophrenia at admission and at discharge. Compr Psychiatry. 2019;90:82-7.
Zhou X, Tian B, Han HB. Serum interleukin-6 in schizophrenia: A system review and meta-analysis. Cytokine. 2021;141:155441.
Miller BJ, Buckley P, Seabolt W, Mellor A, Kirkpatrick B. Meta-analysis of cytokine alterations in schizophrenia: clinical status and antipsychotic effects. Biol Psychiatry. 2011;70(7):663-71.
Blomstrom A, Karlsson H, Svensson A, Frisell T, Lee BK, Dal H, et al. Hospital admission with infection during childhood and risk for psychotic illness--a population-based cohort study. Schizophr Bull. 2014;40(6):1518-25.
Johansson Kostenniemi U, Bazan A, Karlsson L, Silfverdal SA. Psychiatric Disabilities and Other Long-term Consequences of Childhood Bacterial Meningitis. Pediatr Infect Dis J. 2021;40(1):26-31.
Khandaker GM, Dalman C, Kappelmann N, Stochl J, Dal H, Kosidou K, et al. Association of Childhood Infection With IQ and Adult Nonaffective Psychosis in Swedish Men: A Population-Based Longitudinal Cohort and Co-relative Study. JAMA Psychiatry. 2018;75(4):356-62.
Green MJ, Watkeys OJ, Whitten T, Thomas C, Kariuki M, Dean K, et al. Increased incidence of childhood mental disorders following exposure to early life infection. Brain Behav Immun. 2021;97:376-82.
Liang W, Chikritzhs T. Early childhood infections and risk of schizophrenia. Psychiatry Res. 2012;200(2-3):214-7.
Urakubo A, Jarskog LF, Lieberman JA, Gilmore JH. Prenatal exposure to maternal infection alters cytokine expression in the placenta, amniotic fluid, and fetal brain. Schizophr Res. 2001;47(1):27-36.
Clark SM, Notarangelo FM, Li X, Chen S, Schwarcz R, Tonelli LH. Maternal immune activation in rats blunts brain cytokine and kynurenine pathway responses to a second immune challenge in early adulthood. Prog Neuropsychopharmacol Biol Psychiatry. 2019;89:286-94.
Gildawie KR, Orso R, Peterzell S, Thompson V, Brenhouse HC. Sex differences in prefrontal cortex microglia morphology: Impact of a two-hit model of adversity throughout development. Neurosci Lett. 2020;738:135381.
Ranaei E, Torshizi S, Amini A, Heidari MH, Namvarpour Z, Fathabady FF, et al. Peripubertal stress following maternal immune activation sex-dependently alters depression-like behaviors in offspring. Behav Brain Res. 2020;393:112800.
Rose DR, Careaga M, Van de Water J, McAllister K, Bauman MD, Ashwood P. Long-term altered immune responses following fetal priming in a non-human primate model of maternal immune activation. Brain Behav Immun. 2017;63:60-70.
Kleiner G, Marcuzzi A, Zanin V, Monasta L, Zauli G. Cytokine levels in the serum of healthy subjects. Mediators Inflamm. 2013;2013:434010.

No competing interests reported.

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Changes in Cytokine and Cytokine Receptor Levels During Postnatal Development of the Human Dorsolateral Prefrontal Cortex

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Abstract

Figures

Introduction

Methods

Subjects

RNA extraction and cDNA synthesis

High-throughput quantitative PCR

Single target quantitative RT-PCR

Protein extraction

Multiplex immunoassay

Statistical analysis

Results

Increases in IL1B mRNA and protein early in life

Increases in IL6 mRNA and protein both early in life and at maturation

Increases in IL18 mRNA and protein, but not IL18R, with age

Increases in TNFΑ and TNFR2, but not TNFR1, with age

Discussion

Conclusion

Abbreviations

Declarations

Tables

Additional Declarations

Supplementary Files

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