Prenatal and postnatal challenges affect the hypothalamic molecular pathways that regulate hormonal levels

Sandra L Rodriguez-Zas; Nicole L Southey; Laurie Rund; Adrienne M Antonson; Romana A Nowak; Rodney W Johnson

doi:10.1371/journal.pone.0292952

. 2023 Oct 18;18(10):e0292952. doi: 10.1371/journal.pone.0292952

Prenatal and postnatal challenges affect the hypothalamic molecular pathways that regulate hormonal levels

Sandra L Rodriguez-Zas ^1,^2,^3,^4,^5,^*, Nicole L Southey ⁶, Laurie Rund ¹, Adrienne M Antonson ^1,^3,⁵, Romana A Nowak ^1,⁵, Rodney W Johnson ^1,^2,³

Editor: Dragan Hrncic⁷

PMCID: PMC10584192 PMID: 37851674

Abstract

This study aimed to improve our understanding of how the hypothalamus mediates the effects of prenatal and postnatal challenges on behavior and sensitivity to stimuli. A pig model of virally initiated maternal immune activation (MIA) was used to investigate potential interactions of the prenatal challenge both with sex and with postnatal nursing withdrawal. The hypothalami of 72 females and males were profiled for the effects of MIA and nursing withdrawal using RNA-sequencing. Significant differential expression (FDR-adjusted p value < 0.05) was detected in the profile of 222 genes. Genes involved in the Gene Ontology biological process of regulation of hormone levels tended to be over-expressed in individuals exposed to both challenges relative to individuals exposed to either one challenge, and most of these genes were over-expressed in MIA females relative to males across nursing levels. Differentially expressed genes included Fshb, Ttr, Agrp, Gata3, Foxa2, Tfap2b, Gh1, En2, Cga, Msx1, and Npy. The study also found that prenatal and postnatal challenges, as well as sex, impacted the regulation of neurotransmitter activity and immune effector processes in the hypothalamus. In particular, the olfactory transduction pathway genes were over-expressed in weaned MIA males, and several transcription factors were potentially found to target the differentially expressed genes. Overall, these results highlight how multiple environmental challenges can interact and affect the molecular mechanisms of the hypothalamus, including hormonal, immune response, and neurotransmitter processes.

Introduction

Inflammatory signals elicited by infection or other immune challenges can alter molecular mechanisms in the brain associated with behavioral disorders and pain sensitivity. Maternal immune activation (MIA) during gestation is associated with neurodevelopmental pathologies in the offspring, including schizophrenia and autism spectrum disorders and sensory processing sensitivity. In rodent and pig models of MIA, offspring display an increased incidence of autism and schizophrenia-like phenotypes, social deficit, and modified activity levels [1–4]. Likewise, postnatal immune challenges, including inflammatory agents and environmental stressors, can cause behavioral and allodynia alterations [5, 6].

Infection and environmental stressors can alter the balance of inflammatory factors impacting the hypothalamic mechanisms that modulate the pituitary and adrenal gland function in the hypothalamic-pituitary-adrenal (HPA) axis [7]. The impact of the previous factors can have multiple consequences because the hypothalamus regulates various processes, including the endocrine and autonomic nervous systems, hormone release and activity cycles, circadian rhythm, and feeding and social behaviors. In turn, the hypothalamus also participates in the modulation of stress hormones and the response to stressors.

Hyperactivity of the HPA axis, typically detected by high peripheral cortisol, has been associated with MIA-related behavioral disorders, including autism and schizophrenia spectrum disorder, anxiety, depression, hypersensitivity to pain, hyperalgesia, and allodynia [7, 8]. The link between the hypothalamic and behavioral disruption was reported in NIH Swiss mice exposed to PolyI:C-induced MIA, which presented behavioral disruptions and lower levels of hypothalamic vasopressin receptor 1a (Avpr1a) gene expression [9]. Also, P85 male mice exposed to PolyI:C-induced MIA displayed increased pain sensitivity and hypothalamic over-expression of the KiSS-1 metastasis suppressor (Kiss1) gene, while no significant changes were detected in females [7].

Postnatal maternal care has long-lasting effects on offspring development in the biomedical rodent and pig models. The stress elicited by weaning offspring, including withdrawal from nursing, the mother, and littermates, can impact the HPA axis activity. Weaning stress increased the peripheral cortisol level and lowered the hypothalamic expression of the corticotropin releasing hormone (Crh) gene in 28-day-old male pigs [10]. Also, early weaning at P21 (relative to P28) increased the hypothalamic density of the oxytocin receptor in male but not in female mice [11].

Studies about the impact of MIA or nursing withdrawal on the hypothalamus have focused on one of the challenges and profiled genes and gene products that had established relationships with stress or inflammatory responses [7, 12]. This study aimed to understand the simultaneous impact of prenatal and postnatal challenges in the transcriptome of the hypothalamus within and across sexes, considering the multiple signals and physiological and behavioral processes regulated by this structure. Gene pathway reconstruction advanced the understanding of the simultaneous effects of MIA and a second stress on the interconnected molecular mechanisms underlying the processes modulated by the hypothalamus.

Materials and methods

Published protocols were followed for all experimental procedures [13]. Animal studies were approved by the Illinois Institutional Animal Care and Use Committee (IACUC) and abide by the United States Department of Agriculture Animal Welfare Act and the National Institutes of Health (NIH) Public Health Service Policy on the Humane Care and Use of Animals. Gestating female pigs (Camborough breed) were separately housed in disease containment chambers, exposed to a 12-hour light/dark cycle, and fed a diet that met gestational requirements and ad libitum water availability [14]. Porcine respiratory and reproductive virus (PRRSV; strain P129-BV) diluted in sterile Dulbecco’s modified Eagle medium was inoculated to eight gilts, offering MIA challenge to the developing offspring. Another set of eight gilts was inoculated with the medium and was studied as a control. Infection status was confirmed 7 days after inoculation using a PCR test. Virally inoculated gilts had lower feed consumption and higher body temperature for 14 days relative to control gilts, and feed availability was adjusted to match intake between gilt groups [1].

On gestation day 113, farrowing was induced, and all pigs were nursed and remained with their mothers fed a diet that satisfied lactation requirements [13]. At three weeks of age, approximately half of each litter continued nursing, and the remaining pigs were withdrawn from the litter and nursing. The weaned pigs were housed in groups of four per room and received a diet that satisfied growing requirements and ad libitum water, and the experiment concluded one day later.

Altogether, 72 females and males from two prenatal inflammation groups (MIA and control) assigned to one of two postnatal challenges (nursing and nursing withdrawn) were studied. A diagram depicting the experimental design is available in S1 Fig. The pigs were anesthetized using a dose of 0.03 mL/kg body weight of 4.4 mg/kg Telazol (100 mg/mL, Zoetis, Parsippany, NJ, USA), 2.5 mL of ketamine (100 g/L) and 2.5 mL of xylazine (100 g/L) [15]. The anesthesia was applied intramuscularly, followed by an intracardiac injection of Fatal Plus (Vortech Pharmaceuticals, MI, USA) sodium pentobarbital (86 mg/kg body weight). The hypothalamus of the 22-day-old pigs was extracted, flash-frozen on dry ice, and maintained at −80°C using published protocols [16]. The hypothalamic RNA was isolated with the EZNA isolation kit (Omega Biotek, Norcross, GA, USA) per the manufacturer’s instructions. All samples reached an RNA integrity number above 7.4, which indicates low degradation. The Roy J. Carver Biotechnology Center (Urbana, IL, USA) processed the RNA-seq libraries using TruSeq Stranded mRNAseq Sample Prep kit (Illumina Inc, San Diego, CA, USA), which were subsequently quantified by qPCR, and the fragments were sequenced from both ends on two lanes on a NovaSeq 6000 sequencer for 151 cycles using NovaSeq 6000 reagent kit. The sequences were demultiplexed and compiled into FASTQ files using the bcl2fastq v2.20 routine. The average and median number of reads per sample were 259.9 million and 254.5 million, respectively. The experiment identifier GSE227725 in the public Gene Expression Omnibus repository includes the raw sequencing files corresponding to the 72 samples [17].

Read trimming was unnecessary because all read positions’ quality was above a Phred score > 36. The Sus scrofa transcriptome v. 11.1 was used as the reference to align the paired-end reads, and transcript levels were quantified using kallisto v. 0.43.0 and default specifications. The levels of the gene expression were measured as sequence reads couns and were adjusted for library size and gene length. Genes with fewer than 5 reads and lower that 1 adjusted count per pig group were removed from subsequent analysis. The logarithm base 2 ransformed gene expression values were analyzed using a generalized linear model to test the effects of prenatal inflammation, nursing withdrawal, sex, and interactions on 18,295 genes analysis using the software edgeR v. 3.14.0 in the R v. 3.3.3 environment. The p values are adjusted for multiple testing using the False Discovery Rate (FDR) method [18].

Over-representation of gene ontology (GO) biological processes (BP) [19] and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [20] were studied [21]. Sus scrofa was the reference genome used, and the enrichment analyses were performed using the hypergeometric over-representation analysis (ORA) [22] and the gene set enrichment analysis (GSEA) [16, 23]. While the ORA analysis considered genes differentially expressed at FDR p-value < 0.1, GSEA accounted for the log₂(fold change) between factor groups to detect enrichment among the over- or under-expressed genes. The ORA enrichment ratio (ER), GSEA normalized enrichment score (NES), and FDR-adjusted p-value (based on 1000 permutations) were considered in identifying enriched functional categories.

Further understanding of the effects of MIA and nursing withdrawal on the hypothalamus molecular pathways was gathered by integrating gene coexpression networks with gene differential expression profiles. The relationships among genes annotated to statistical and biologically significant enriched categories were obtained from the STRING database v. 11.5 of functional associations [24] and visualized in the Cytoscape v. 3.9.1 platform [25] following published approaches [16]. The nodes represent genes, and the edges represent the protein relationships in STRING experimental, coexpression, text mining, and repositories [24]. The red-to-yellow-to-green color scheme of the nodes denotes the transition from under-expression to equal and over-expression in the first treatment group relative to the second treatment group in the comparison portrayed by the network. While there are no protein profiles to confirm the expression and co-expression patterns, statistical robust findings rely on the consideration of orthogonal contrasts among the 72 pigs distributed across 8 groups application of an stringent thresthold of FDR-adjusted p-value < 0.05 for differential expression, results and interpretation focus on consistency across categories, approaches, and benchmarked against published annotation.

Regulatory mechanisms shared by target genes presenting differential expression associated with MIA, nursing withdrawal, and sex were detected using the iRegulon software v. 1.3, build 1024 [26]. This analysis identified enriched regulatory transcription factor binding motifs and genomic tracks using the area under the cumulative recovery curve (AUC). The AUCs, estimated in the top 3% of the homotypic motif clusters across 10 vertebrate species, were standardized in the iRegulon NES. The NES > 3 threshold that corresponds to a 0.03 < FDR p-value < 0.09 were applied in the present study [26, 27].

Results

Among the 18,295 genes analyzed, at FDR-adjusted p value < 0.05, significant effects were identified on 39 genes for virally induced MIA, 16 genes for nursing withdrawal, 61 genes for sex, 27 genes for MIA-by-nursing withdrawal, 42 genes for MIA-by-sex, and 37 genes for sex-by-nursing withdrawal effect (S1 Table). Focusing on the genes that were impacted by the factors studied, Fig 1 depicts the distribution of the differential expression (log₂(fold change)) among the genes presenting significant (FDR-adjusted p value < 0.1) main effects of MIA, nursing withdrawal, or sex, divided into over- and under-expressed genes within effect. The majority of the genes impacted by the factors studied were over-expressed in MIA relative to control, over-expressed in withdrawal relative to nursing, and in males relative to females.

Hypothalamic biological processes and genes networks associated with challenges and sex effects

The enriched GO biological processes including at least 10 genes differentially expressed (FDR-adjusted p value < 0.05) across MIA, nursing withdrawal, sex, and interactions effects identified by ORA, are presented in Table 1. An extended list of biological processes including at least 5 genes differentially expressed (FDR-adjusted p value < 0.05) across the factors studied is available in S2 Table. The enriched biological processes share endogenous signaling mechanisms, where G protein-coupled receptors are membrane receptors of steroid hormones. Estrogen receptors link estrogen signaling to promoter-related RNA polymerase II and transcription mechanisms, evidenced in the detected positive regulation transcription by RNA polymerase II category (GO:0045944) (Table 1).

Table 1. Enriched Gene Ontology (GO) biological processes, including at least 10 genes differentially expressed (False Discovery Rate FDR-adjusted p value < 0.05) in response to maternal immune activation, nursing withdrawal, sex, or interactions.

GO Identifier	Description	Gene count	Enrichment ¹	p value	FDR p value
GO:0010817	regulation of hormone levels	11	7.9	8.8x10^-08	7.9 x10^-04
GO:0010469	regulation of signaling receptor activity	10	6.7	1.6x10^-06	5.5x10^-03
GO:0071495	cellular response to endogenous stimulus	13	3.5	3.7x10^-05	5.6x10^-02
GO:0045944	positive regulation transcription by RNA polymerase II	11	3.4	2.1x10^-04	1.2x10^-01
GO:0007186	G protein-coupled receptor signaling pathway	11	3.1	4.9x10^-04	1.8x10^-01

Open in a new tab

¹ Over-representation analysis enrichment ratio.

The log₂(fold change) of genes differentially expressed (FDR-adjusted p value < 0.05) for the effects of MIA, nursing withdrawal, sex, and interactions annotated to the enriched GO biological processes (Table 1) are summarized in Table 2. The differentially expressed genes include follicle-stimulating hormone beta polypeptide (Fshb), transthyretin (Ttr), agouti-related neuropeptide (Agrp), GATA binding protein 3 (Gata3), forkhead box A4 (Foxa2), transcription factor AP-2 beta (Tfap2b), growth hormone 1 (Gh1), glycoprotein hormones, engrailed homeobox 2 (En2), alpha polypeptide (Cga), MSH homeobox 1 (Msx1), neuropeptide Y (Npy), neuromedin U (Nmu), prolactin (Prl), POU class 4 homeobox 1 (Pou4f1), nuclear receptor subfamily 5 group A member 2 (Nr5a2), paired box 3 (Pax3), KiSS-1 metastasis-suppressor (Kiss1), thyroid stimulating hormone receptor (Tshr), luteinizing hormone beta polypeptide (Lhb), aldehyde dehydrogenase 1 family member A1(Aldh1a1), C-X-C motif chemokine ligand 9 (Cxcl9), and eukaryotic translation initiation factor 1A, Y-linked (Eif1ay). Significant interactions between MIA and the remaining factors indicate that the impact of MIA on gene expression depends on the nursing status and sex of the individual. Likewise, a significant interaction between nursing withdrawal and sex indicates that the impact of such stressor depends on the sex of the individual.

Table 2. Log₂(fold change) of the differentially (False Discovery Rate FDR-adjusted p value < 0.05) expressed genes (^#) for the effects of maternal immune activation (MIA), nursing withdrawal (Nur), sex, and interactions (-) annotated to enriched Gene Ontology biological processes (BP).

Gene	Enriched BP¹	MIA-Nur	Nur-Sex	Sex-MIA	MIA	Nur	Sex
Agrp	R,S,G	-2.86^#	-3.79^#	-2.43	-2.98^#	2.71^#	2.54^#
Aldh1a1	H	0.26	3.03^#	1.46	0.41	-1.41	-0.95
Cga	H,R,T,G	-5.66^#	-3.86^#	-2.36	-6.64^#	0.02	3.62^#
Cxcl9	R,G	1.81	4.78^#	2.87	-1.84	-1.26	-1.08
En2	T	-3.22^#	6.25^#	0.14	-2.40^#	-1.27	-2.59^#
Foxa2	H,T	-1.59	4.43^#	2.17	1.01	-0.52	-3.94^#
Fshb	H,R,S,T,G	-3.48^#	-0.94	0.53	-3.25^#	0.95	0.85
Gata3	H,S,T	-2.64^#	2.13	2.00	-0.33	0.26	-2.46^#
Gh1	R,S	0.50	3.87^#	5.99^#	0.49	-0.76	-2.61^#
Gnrh2	R,G	1.14	1.45	1.96	1.91	-1.45	-1.96^#
Kiss1	H,G	-2.20	-2.71^#	-2.52	-2.65^#	1.50	1.77^#
Lhb	H,R,S,G	-2.06	-0.17	1.25	-2.34^#	-0.70	0.48
Msx1	S,T	-1.57	-0.61	0.36	-1.98^#	-0.16	0.42
Nmu	H,G	-1.76	-2.91^#	-1.52	-1.76	1.44	1.69
Npy	R,G	-2.21	-2.86^#	-2.01	-2.10^#	2.31^#	1.84^#
Nr5a2	S,T	-2.10	-2.84^#	-0.94	-1.15	1.51	1.45
Pax3	T	-0.85	1.54	2.71^#	0.93	-0.04	-1.78^#
Pou4f1	S,T	-3.39^#	5.37^#	2.84^#	-0.57	-0.66	-3.15^#
Prl	R,S,T	1.71	0.86	6.16^#	-0.07	0.03	-0.25
Tfap2b	H,S,T	-1.15	0.49	3.11^#	0.68	0.34	-1.55
Tshr	S,G	-1.13	-2.54^#	-0.86	-1.09	0.92	1.49
Ttr	H,R	3.32^#	-0.65	-0.63	1.80	-1.23	1.53

Open in a new tab

¹ Enriched biological process: H = regulation of hormone levels; R = regulation of signaling receptor activity; S = cellular response to endogenous stimulus; T = positive regulation of transcription by RNA polymerase II; G = G protein-coupled receptor signaling pathway.

² Sign of log₂(fold change) for main effects: +(-) over- (under)-expression in control relative to MIA group, nursing withdrawal relative to the nursing group, or males relative to females; for interactions: +(-) over- (under-) expression in withdrawn nursing males, withdrawn nursing control, and control males relative to other groups.

Most genes in the enriched endocrine signaling processes (Table 1) presented a negative log₂(fold change) for the MIA-by-nursing interaction indicating. This profile suggests that genes tended to be over-expressed in individuals exposed to both challenges (MIA and nursing withdrawal) relative to individuals exposed to either one challenge across the sexes (Table 2). A positive log₂(fold change) trend was observed for the sex-by-MIA interaction, indicating that most genes were over-expressed in MIA females relative to MIA males across nursing levels. While the distribution of log₂(fold change) signs was even for the nursing-by-sex interaction, the most extreme values had a positive sign indicating that these genes were over-expressed in nursing-withdrawn males relative to females.

Considering the main effect of MIA among the genes in Table 2, the most differentially expressed genes had a negative log₂(fold change), which marks predominant over-expression in MIA relative to control pigs. Considering the main effect of sex, most extreme log₂(fold change) had a negative sign corresponding to over-expression in females relative to males. The positive log₂(fold change) of two genes presenting extreme postnatal stressor effect corresponds to over-expression in nursing withdrawn relative to individuals that remained with the mother nursing (Table 2).

The combined study of the expression profiles across MIA-nursing-sex groups and molecular interactions among the genes in the regulation of hormone levels process (GO:0010817) enabled additional characterization of the hypothalamic dysregulation. The visualization of the network of genes in the hormonal regulation pathway was selected for visualization across 12 contrasts because of the significant enrichment, and also because it includes genes from other enriched pathways including regulation of transcription by RNA polymerase II, G-protein-coupled receptor signaling pathway, cellular response to endogenous stimulus, regulation of signaling receptor activity. Fig 2 depicts the relationship between genes in the regulation of hormone levels process in the STRING database while comparing groups that differ in the MIA level or sex within a nursing group. Fig 3 depicts the relationship between genes in the regulation of hormone levels process while comparing groups that differ in the nursing status or sex within a MIA level. The genes annotated to the process regulation of hormone levels include Aldh1a1, Cga, Foxa2, Fshb, Gata3, Kiss1, Lhb, Nmu, Tfap2b, and Ttr. The gene Esr1 was added to the network to facilitate the depiction of connections between the genes in the process. The color scheme ranges from red or under-expressed in the first group, to yellow (equally expressed), and green or over-expressed in the first group relative to the second group of the contrast. The log₂(fold changes) represented by the color scheme are listed in S4 Table.

Fig 2 networks c and d depict a predominance of genes over-expressed in nursed MIA relative to control pigs across sexes, whereas the profile tended to revert in nursing withdrawn pigs (Fig 2A and 2B). Fig 3 networks a and b depict a predominance of genes under-expressed in MIA withdrawn relative to nursing pigs, whereas the profile became less extreme and reverted in control pigs (Fig 3C and 3D). Notably, the gene expression differences between sexes were more extreme in pigs not exposed to challenges (Fig 2F) and weaker in pigs exposed to both challenges (Fig 2E). Gene estrogen receptor 1 (Esr1) is a hub gene presenting the highest network radiality, closeness centrality, and betweenness centrality among all genes in the network. As a hub, gene Esr1 presented weak changes in gene expression across prenatal or postnatal challenges or sexes.

Gene set and regulatory enrichment analysis of differentially expressed genes in the hypothalamus

Enrichment results from the GSEA approach enabled the characterization of the MIA, nursing, and sex effects on KEGG pathways and GO biological processes among genes presenting extreme differential expression. Table 3 summarizes the KEGG pathways and GO biological processes enriched at FDR-adjusted p value < 0.05 in at least two experimental factors. An extended list of all enriched KEGG pathways and GO biological processes identified by GSEA at FDR-adjusted p value < 0.05 is available in S3 Table.

Table 3. Normalized enrichment score of KEGG pathways and GO biological processes (BP) enriched at False Discovery Rate FDR-adjusted p value < 0.05 among genes with profiles impacted by at least two experimental factors including maternal immune activation (MIA), nursing (Nur), sex, or interactions (-).

KEGG or BP	Description	MIA-Nur	Nur-Sex	MIA-Sex	MIA	Nur	Sex
Pathway
ssc05330	Allograft rejection		2.49		-2.28	-2.29	-2.16
ssc04612	Antigen processing and presentation	2.95	2.64	2.67		-2.79	-2.45
ssc04514	Cell adhesion molecules (CAMs)	2.31		2.44
ssc00260	Glycine, serine and threonine metabolism		2.25				-1.82
ssc05332	Graft-versus-host disease		2.36		-2.14	-2.31	-2.26
ssc05168	Herpes simplex infection					-2.17	-1.94
ssc05164	Influenza A	2.30		2.49
ssc04672	Intestinal immune network for IgA production	2.47	2.23	2.46	-1.99
ssc05140	Leishmaniasis	2.29	2.33	2.41
ssc04740	Olfactory transduction	-2.28	-2.07	-2.59		2.17	2.39
ssc05012	Parkinson disease	2.44				-2.67
ssc04145	Phagosome	2.32		2.44
ssc03010	Ribosome		2.28		-2.11	-2.77
ssc05150	Staphylococcus aureus infection	2.96		2.60	-2.16	-2.59	-1.88
ssc04658	Th1 and Th2 cell differentiation			2.39			-1.87
ssc04940	Type I diabetes mellitus	2.69	2.32	2.41	-2.12	-2.28	-2.12
ssc05416	Viral myocarditis		2.17		-2.16		-1.81
Process
GO:0051186	cofactor metabolic process	1.97				-1.82
GO:0002252	immune effector process			2.18		-1.93
GO:0006839	mitochondrial transport	2.13				-2.36
GO:0006836	neurotransmitter transport	2.41				-1.81
GO:2001057	reactive nitrogen species metabolic process	2.20		2.03
GO:0031099	regeneration	1.89				-2.16
GO:0001505	regulation of neurotransmitter levels	2.54		2.16

Open in a new tab

² Sign of the normalized enrichment score NES for main effects: +(-) over- (under)-expression in control relative to MIA group, nursing withdrawal relative to the nursing group, or males relative to females; for interactions: +(-) over- (under-) expression in withdrawn nursing males, withdrawn nursing control, and control males relative to other groups.

The predominance of inflammatory response and neurotransmitter functional categories in Table 3 highlights the complementary understanding of the molecular mechanisms impacted by MIA, nursing withdrawal, and sex offered by GSEA. Inflammatory response categories associated with the virally induced MIA studied include the viral diseases pathways Influenza A (ssc05164) and Herpes simplex infection (ssc05168) and the GO immune effector process (GO:0002252) and reactive nitrogen species metabolic process (GO:2001057). Examples of enriched neuronal signaling categories include the cell adhesion molecules (ssc04514) and regulation of neurotransmitter levels (GO:0001505).

The sign of the NES is consistent across enriched inflammatory response and neurotransmitter categories and indicates over-expression in nursed MIA females relative to other groups. The consistent profile of the mitochondrial transport process (GO:0006839) corresponds to neuroinflammation impairment of axonal mitochondrial transportation. Contrary to the previous trend, the NES sign of the olfactory transduction pathway (ssc04740) indicates that the genes in this pathway were predominantly over-expressed in nursing-withdrawn, control males.

The analysis of regulatory motifs and genomic tracks encompassing transcription factor binding sites among the differentially expressed genes (FDR-adjusted p value < 0.05) highlighted shared modulatory mechanisms. Overall, 71 motifs and 9 tracks annotated to 57 transcription factors were enriched at approximate FDR-adjusted p-value < 0.05, normalized enrichment score > 3 among the target genes impacted by the effects of MIA, nursing withdrawal, and sex. Table 4 lists the motifs or tracks for the transcription factors presenting normalized enrichment score > 4. An extended list of motifs, tracks, and transcription factors is available in S5 Table. Enriched transcription factors listed in Table 4 and Fig 4 include ALX homeobox 4 (ALX4), C-terminal binding protein 2 (CTBP2), FOXA2, forkhead box B1 (FOXB1), PROP paired-like homeobox 1 (PROP1), sirtuin 6 (SIRT6), SUZ12 polycomb repressive complex 2 subunit (SUZ12), transcription factor 12 (TCF12), AT-rich interaction domain 3A (ARID3A), forkhead box K1 (FOXK1), nuclear transcription factor Y subunit gamma (NFYC), PBX homeobox 1 (PBX1), paired box 3 (PAX3), RAR related orphan receptor C (RORC), SP100 nuclear antigen (SP100), serum response factor (SRF), transcription factor 7 like 1 (TCF7L1), and tumor protein p53 (TP53).

Table 4. Top enriched motif or genomic track (normalized enrichment score NES > 4) within transcription factor and the number of differentially expressed target genes (False Discovery Rate-adjusted p value < 0.05) for the effects of maternal immune activation, nursing withdrawal, sex, and interactions.

Transcription factor(s) ¹	Motif/track	AUC²	NES	Genes
SUZ12/FOXA2	wgEncodeSydhTfbsNt2d1Suz12UcdPk.narrowPeak.gz	0.18	10.65	17
CTBP2/PAX3	wgEncodeSydhTfbsH1hescCtbp2UcdPk.narrowPeak.gz	0.16	9.25	13
TCF12/FOXA2	wgEncodeHaibTfbsA549Tcf12V0422111Etoh02PkRep2.broadPeak.gz	0.09	4.81	11
PROP1	taipale-TAATYNAATTA-PROP1-DBD	0.13	4.81	32
ALX4	homer-M00250	0.12	4.29	45
FOXB1	taipale-WNWGTMAATATTRACWNW-FOXB1-DBD	0.12	4.24	11
SIRT6	transfac_pro-M01797	0.12	4.23	11

Open in a new tab

¹ Regulatory region or track in the iRegulon database encompassing one or multiple genes.

² Area Under the cumulative Recovery Curve.

A bimodality can be observed among transcription factors with target genes in the process regulation of hormone levels. Approximately half of the transcription factors have multiple target genes (e.g., FOXK1, TP53 RORC, TCF7L1, ARID3A), whereas most of the remaining transcription factors have two to three target genes. (PBX1, SRF, NFYC, and TCF12). Most differentially expressed target genes had multiple regulatory transcription factors. Several differentially expressed genes have transcription factor functions, including Gata3, Foxa2, and Tfap2b.

Discussion

Studies of targeted gene expression profiles indicate that the hypothalamus mediates the effects of prenatal inflammatory challenges on social, food intake, reproductive behaviors, and sensitivity to environmental stimuli [7]. Postnatal conditions such as stressors and sex contribute to variations in the effects of MIA on the hypothalamus. Mice exposed to PolyI:C-elicited MIA presented changes in pain sensitivity and reproduction behavior, and Gnrh1 was over-expressed in the hypothalamus of MIA males while under-expressed in MIA females [7]. Likewise, PRRSV-elicited MIA in pigs was associated with changes in physical activity, social behaviors, and amygdala transcriptome [1, 3, 28]. A study of the genes and pathways in the pig hypothalamus impacted by MIA and the stress of nursing withdrawal across sexes advance the understanding of how this brain structure can mediate the effects of prenatal and postnatal challenges on behavior and sensitivity to stimuli.

Among the 18,295 genes analyzed, changes in the profile of 222 genes (FDR-adjusted p value < 0.05) were associated with the effects of MIA, nursing withdrawal, sex, and interactions (S1 Table). Four-fold was the average fold change among the genes presenting sex or nursing effects alone or in interactions, and the profile was characterized by over-expression in pigs withdrawn from nursing and in males relative to nursed pigs or females. The observed over-expression of hypothalamic genes in response to the stress of weaning is consistent with reports of associated increases in the level of plasma cortisol and expression of genes Fos proto-oncogene, AP-1 transcription factor subunit, and Crh in the hypothalamus of 28-day-old pigs weaned relative to nursed [10]. The hypothalamus produces CRH that signals the pituitary gland to release adrenocorticotropin hormone (ACTH), which signals the adrenal glands to secrete cortisol hormones into the blood. In the present study, nursing withdrawal was associated with a 1.4 fold increase in the expression of Crh, and the level of cortisol was significantly higher in the blood of 21-day-old weaned relative to nursed pigs [29].

The fold change of genes differentially expressed in the MIA relative to the control group was, on average 6.5 units, indicating that prenatal inflammatory signals are associated with long-lasting gene over-expression in the hypothalamus. Consistent with these findings, most genes in the terpenoid biosynthesis pathway were over-expressed in the hippocampus of nursed male pigs exposed to PRRSV-elicited MIA, and terpenoids have anti-inflammatory effects [16]. The prenatal stressor of maternal anxiety during gestation was associated with enhanced HPA axis activity (characterized by high plasma cortisol levels) and depression symptoms in the offspring during adolescence [30]. Also, adult male guinea pigs born to females exposed to prenatal stress of strobe light during the rapid fetal brain growth phase presented higher basal plasma cortisol levels [31].

In the present study, MIA-exposed males had higher (albeit non-significant) expression of the cortisol-release precursor Crh relative to other groups. Prenatal immune activation interacting with the remaining factors studied, or alone, accounted for 103 genes. Similarly, nursing withdrawal interacting with MIA and sex or alone accounted for 85 differentially expressed genes. These results highlight the importance of studying the effects of prenatal and postnatal challenges in both sexes.

Hypothalamic biological processes and genes networks associated with challenges and sex effects

Many differentially expressed genes in the study are annotated to processes related to the regulation of hormone levels (GO:0010817) (Table 1). This result is supported by the enrichment of processes related to G protein-coupled receptor signaling and activity and response to endogenous stimulus (GO:0007186, GO:0010469, and GO:0071495, respectively). Aligned with our results, a study of transcriptome profiles in patients diagnosed with bipolar disorder, a MIA-associated phenotype, reported enrichment of the regulation of hormone levels process [32]. Also, the levels of transcript isoforms of the thyrotropin-releasing hormone were impacted by PRRSV-elicited MIA in the hippocampus of pigs [14]. The enrichment of positive regulation transcription by RNA polymerase II (GO:0045944) is consistent with reports that hormones modulate RNA polymerase II density patterns in the promoter and gene regions [33]. Growth, thyroid, and estrogen hormones have been associated with the recruitment of RNA polymerase II to regulatory regions [34].

Many genes annotated to the enriched hormone level and receptor signaling regulation processes shared profiles in response to MIA, nursing withdrawal, and sex effects (Table 2). These patterns included over-expression in the hypothalamus of pigs exposed to both challenges relative to a single challenge, and this profile was observed in Agrp, Cga, En2, Fshb, Gata3, Pou4f1, and Ttr. Another pattern is over-expression in MIA females relative to males, and this pattern was observed in genes including Gh1, Pax3, Pou4f1, Prl, and Tfap2b. Genes over-expressed in nursing withdrawn males relative to females included Aldh1a1, Cxcl9, En2, Foxa2, Gh1, Pou4f1, whereas the opposite pattern was detected for Agrp, Cga, Kiss1, Nmu, Npy, Nr5a2, and Tshr. The modification of the previous gene profiles can impact physiological processes because, for example, changes in the hypothalamic expression patterns of glucocorticoid receptors such as Nr5a2 and Ttr can influence the modulation of the HPA axis. The under-expression of glucocorticoid receptor genes may disrupt the response to glucocorticoids, leading to increased ACTH release, production of adrenal steroids, and corticoid activity, influencing physiological processes such as puberty [7].

The detected profiles of genes associated with prenatal and postnatal challenge alone or in combination are aligned with published reports. Consistent with the over-expression of Fshb in the hypothalamus of pigs exposed to prenatal and postnatal challenges, over-expression of Fshb, gonadotropin-releasing hormone receptor (Gnrhr), and Prl was detected in the cerebellum of adult male mice that were neonatally inoculated with Thimerosal, an inflammatory agent associated with neurodevelopmental disorders [35]. The correlated profile of Fshb and Lhb observed in the present study is aligned with the inflammatory response to intraperitoneal LPS response in adult male mice that were associated with activation of the hypothalamus, disruption of the HPA axis, and elevated blood levels of FSH and LH [36]. The higher level of Nmu in MIA and nursing withdrawal groups agrees with the known physiological role of endogenous NMU in adaptation to environmental stimulus, inducing stress response after central administration [37]. Also, Nmu knockout mice have lower plasma corticosterone levels and lower stress indicators than wild-type mice [38].

Consistent with the observed under-expression of Aldh1a1 in animals exposed to either challenge, this gene was under-expressed in the amygdala of neonatal rats exposed to early-life trauma modeled using odor-shock conditioning [39]. Likewise, Aldh1a1 was under-expressed in the amygdala of 21-day-old pigs exposed to PRRSV-induced MIA [28]. The lower expression of Aldh1a1 in the prenatal brain of mice exposed to MIA elicited by influenza, PolyI:C, and interleukin-6 has suggested that this gene is associated with aberrant neural development [40]. Also, decreased expression of Aldh1a1 in the ventral tegmental area of the mice at PD22 was associated with repeated early exposure to social stress [41].

The higher level of Gata3 in the hypothalamus of pigs exposed to MIA and postnatal stress agrees with the higher abundance of the protein GATA3 in the brain of a mouse line that models autism spectrum disorder phenotypes [42]. A study of the effects of postnatal stress reported that the hypothalamus of female macaques exposed to housing in a novel room with unfamiliar conspecifics had increased expression levels of Kiss1 relative to controls [43].

The sex-dependent effects of prenatal inflammation and nursing withdrawal on several genes detected in the present study are supported by previous findings. For example, the level of FSHB in the pituitary gland in response to chronic stress exposure modeled by regular handling was higher in males relative to female mice [44]. The hypothalamus of mice exposed to PolyI:C-caused MIA had increased expression of Kiss1 relative to control mice, and the differential expression at P32 was higher in males than in females [7]. The previous finding led to the hypothesis of the peripubertal control that Kiss1 exerts on abnormal brain function after prenatal immune challenge. The significant sex-dependent MIA effect characterized by under-expression of Tfap2b in the hypothalamus of MIA males relative to females is consistent with reports of under-expression in the cerebellum of male offspring of PolyI:C-treated female mice during gestation [45]. Also, male mice from a Tfap2b knockout line had increased susceptibility to stress [46].

The comparison of the hypothalamic gene networks from females and males exposed to prenatal inflammation relative to controls in the absence of a postnatal stressor indicates the over-expression of many interconnected genes (e.g., Lhb, Fshb, Cga) annotated to the regulation of hormone levels process (Fig 2). On the other hand, exposure to nursing withdrawal challenge reverted the profiles, and many genes were under-expressed in animals exposed to MIA relative to controls (e.g., Gata3, Tfap2b). The previous Cga pattern follows reports that LPS-elicited inflammation increases the expression of hypothalamic Cga in mice [47]. The over-expression of Tfap2b in male nursing pigs exposed to MIA was also reported in a brain transcriptomic study of mice offspring of dams exposed to the stressor of predator scent during gestation [48].

The network of genes that participates in the regulation of the hormone level process, many of which are also annotated to other enriched processes such as regulation of transcription by RNA polymerase II and G-protein-coupled receptor signaling pathway, highlighted the under-expression of many interacting genes in the withdrawn relative to nursing groups in offspring exposed to MIA (e.g., Gata3, Lhb, Fshb, Cga) (Fig 3). No predominant profile was detected in response to postnatal stress among control individuals not exposed to MIA. Consistent with the observed patterns of extreme under-expression of Lhb in nursing withdrawal relative to nursing groups exposed to MIA, neonatal LPS-induced inflammation furthers the suppression of luteinizing hormone pulse in adult rats [49]. The under-expression of Lhb is withdrawn relative to the nursing group was consistent across prenatal conditions and sexes, whereas Fshb was over-expressed in nursing withdrawal conditions in control females and males. The Fshb pattern is aligned with reports that the postnatal stress of social isolation is associated with lower LH and higher FSH secretion in rats [50].

The pattern of Ttr is characterized by under-expression in the hypothalamus of pigs exposed to either one challenge in the absence of the other challenge. The previous patterns are aligned with the under-expression of Ttr in the amygdala of 21-day-old pigs exposed to PRRSV -induced MIA [28] and in mice exposed to PolyI:C-induced MIA, both in the nucleus accumbens of [51] and the hippocampus [52]. The detection of sex effects and sex-dependent prenatal and postnatal challenge effects on the patterns of genes annotated to the regulation of hormone levels process has been previously reported. In mice, LPS-induced MIA was associated with deceleration of the migration of GnRH neurons to the forebrain in mice [4]. The previous findings supported the conclusion that LPS-initiated MIA can modulate the synthesis of GnRH and LH, leading to distinct abnormalities in testicular and ovarian development [53]. Also, LPS-initiated MIA in rats was associated with impaired sexual behavior in male offspring [2].

Gene set and regulatory enrichment analysis of differentially expressed genes in the hypothalamus

The individualized GSEA study of the KEGG pathways and GO biological processes enriched for MIA, nursing withdrawal, or sex effects offered a complementary understanding of the specific mechanisms impacted by each factor.The over-representation of genes annotated to the neurotransmitter and inflammatory response categories was characterized by gene over-expression in individuals that experienced the prenatal or postnatal challenge. The prolonged disruption of the expression profile of genes associated with prenatal exposure to inflammatory signals and interaction with the postnatal stress of nursing withdrawal detected for the Influenza A and Staphylococcus aureus infection pathways (Table 3) can exemplify the double-hit hypothesis scenario [54].

The predominance of MIA-impacted genes that are annotated to immune response KEGG pathways such as influenza, allograft rejection, and antigen processing and presentation is consistent with reports of the enrichment of related functional categories in the amygdala of pigs and brains of mice exposed to viral and viral mimetic-elicited MIA [55, 56]. Likewise, the enrichment of immune-related functional categories among genes presenting sex-dependent MIA effects was reported in the hippocampus of pigs born to mothers exposed to virally-induced MIA and in the fetal cortex of mice exposed to PolyI:C-induced MIA during gestation [16, 57].

The over-representation of genes annotated to neurotransmitter regulation and transport processes that are affected by prenatal challenge interacting with postnatal challenge and sex is aligned with reports that MIA disrupts the development of neurotransmission in dopaminergic pathways underlying schizophrenia spectrum disorder phenotypes [58]. Neurotransmitters are commonly found in neurons alongside neuropeptides [59] and differential expression of neuropeptide genes was detected in the hippocampus of 60-day-old pigs exposed to PRRSV-elicited MIA [27]. Also aligned with the present findings, a study of MIA in mice detected a higher inhibitory synaptic tone of males and females, whereas changes in the excitatory synapse transmission were only detected in females relative to controls [60]. The between-sex differences in the prenatal inflammation effect further suggest the existence of sexual dimorphism in the synaptic pruning and neuronal disruption associated with MIA.

A noticeable finding is the enrichment of the olfactory transduction pathway, supported by olfactory receptor genes and the profile of most annotated genes opposite to that of the genes in the immune response and neurotransmitter pathways. Genes annotated to the olfactory transduction pathway include olfactory receptors (e.g., 51A4, 52K1, 51S1, 2C1, 51G1, 51G2, and 52R1), which are over-expressed in individuals exposed to MIA, and in particular males and those exposed to nursing withdrawal. The detected participation of olfactory pathway genes agrees with reports that LPS-elicited MIA diminished the olfactory perception of neonatal and adult male and female rats and that these changes were not associated with neuroinflammation or changes in maternal care [61]. Likewise, our finding about the impact of nursing withdrawal stress on olfactory perception-related genes is consistent with reports relating chronic stress to disruption in the prefrontal cortex and hippocampus mechanisms and pathologies of the olfactory neural system [62].

The analysis of genes impacted by the effects of MIA, nursing withdrawal, and sex as targets of transcription regulation identified 80 enriched regulatory motifs and genomic tracks corresponding to 57 unique transcription factors (Table 4). Focusing on the genes related to hormone regulation of levels and signaling demonstrated that approximately half the transcription factors regulate the expression of a few genes, and the remaining factors target multiple genes.

The transcription factor SUZ12 is an example of a regulator of multiple differentially expressed genes in response to prenatal and postnatal stressors. A transcriptome study of the basolateral amygdala of male mice exposed to the chronic stress of repeated housing with an aggressive mouse identified the enrichment of SUZ12 upstream of differentially expressed genes [63]. SUZ12 was also enriched among genes in the hippocampus of 60-day-old pigs exposed to PRRSV-elicited MIA [27]. The present results are aligned with reports that mutations in Suz12 have been associated with MIA-related autism spectrum disorder phenotypes [64]. The association of many differentially expressed genes to TCF7L1 is supported by a meta-analysis of transcriptome experiments that associated this transcription factor with autism spectrum disorder [65].

In addition to differentially expressed genes that are the target of shared transcription factors, several transcription factor genes were differentially expressed in response to MIA, nursing withdrawal, and sex. The transcription factors Gata3, Foxa2, and Tfap2b share the profile of over-expression in single challenge conditions (i.e., MIA or nursing withdrawal) and over-expressed in females exposed to MIA. Many detected transcription factors target genes annotated to inflammatory processes. The enriched transcription factor ALX4 has been associated with the activity of several inflammatory and stress factors, decreasing serotonin availability and increasing neuroinflammation and aberrant neuronal signaling [66]. The enrichment of the transcription factor Sirt6 is associated with differentially expressed genes in immune response pathways and relates to the role of SIRT6 in ameliorating neuroinflammation [67]. Also notable is that the over-represented transcription factor ARID3A inhibits the replication of the PRRSV in vivo and in vitro, and this is the virus used in the present study to elicit maternal inflammation [68].

Among the enriched transcription factors that target differentially expressed genes that participate in hormone regulation and signaling, CTBP2 is involved in suppressing interleukin-2 gene activation in T cells [69], and CTBPs can transactivate proinflammatory genes in the microglia and astrocytes that respond to LPS inflammatory challenge [70]. While the present study detected the enrichment of RORC in association with genes in the hormone signaling process, this transcription factor also participated in immune response processes. The ablation of RORC in mice lowers inflammation in autoimmune encephalomyelitis and lowers Th17 cells in the central nervous system that promote depression-like behaviors [71]. Similarly, depletion of the enriched transcription factor SRF during early life contributes to autism-like deficits in social interaction in adulthood and neurodevelopmental disorders [72]. The enrichment of PBX1, which targets the genes Cga and Prl, can be related to findings that this transcription factor was associated with autism spectrum disorder in a transcriptome study of adult cortical tissue in humans [73].

Conclusions

An investigation of the genes and pathways influenced by MIA and postnatal stress enhanced our knowledge of the hypothalamus’s intermediate role in modulating the impact of the factors studied on behavior and stimuli sensitivity. An unexpected finding is that prenatal and postnatal challenges interacting with sex significantly impacted genes annotated to the regulation of hormone levels and related pathways. The genes in the previous pathways tended to be over-expressed in individuals exposed to both challenges relative to individuals exposed to either challenge. Also, most genes were over-expressed in MIA females relative to males across nursing levels. These gene profiles suggest that environmental challenges before puberty can impact reproduction-related processes.

Notable, network analysis of genes in the regulation of hormone levels detected over-expression in nursed MIA relative to control pigs across sexes and a reversal of this trend within nursing withdrawn pigs. On the other hand, most genes were under-expressed in MIA withdrawn relative to nursing pigs. These findings exemplify the plasticity of the genes to accommodate either one or both challenges studied. In addition to endocrine signaling, neurotransmitter activity, and inflammatory response are molecular mechanisms impacted by prenatal and postnatal challenge and sex. Genes annotated to neurotransmitter and inflammatory response categories were overexpressed in the hypothalamus of pigs exposed to prenatal or postnatal challenges. Opposite to the immune response and neurotransmitter pathway genes, the olfactory transduction pathway genes were characterized by gene over-expression in weaned MIA males relative to other groups. Several transcription factors, including ALX4, FOXA2, SIRT6, and TP53, potentially target the differentially expressed genes and join the effect of the differentially expressed transcription factor genes Gata3, Tfap2b, and Foxa2. Altogether our findings showcase how two challenges or hits can interact in altering the hypothalamus molecular mechanisms associated with hormonal, immune response, and neurotransmitter processes.

Supporting information

S1 Fig. Experimental design scheme.

(XLSX)

Click here for additional data file.^{(68.6KB, xlsx)}

S1 Table. Genes differentially expressed at False Discovery Rate-adjusted p value < 0.05 and log2(fold change) (LFC) across the effects of maternal immune inflammation (MIA), nursing withdrawal (Nur), sex and interactions (-).

(XLSX)

Click here for additional data file.^{(17.7KB, xlsx)}

S2 Table. Enriched Gene Ontology biological processes including at least 5 differentially expressed (False Discovery Rate-adjusted p value < 0.05) genes across MIA, nursing withdrawal, sex, and interactions levels.

(XLSX)

Click here for additional data file.^{(9.9KB, xlsx)}

S3 Table. Gene Ontology biological processes and KEGG pathways enriched at False Discovery Rate-adjusted p value < 0.05 for maternal immune activation (MIA), nursing withdrawal (Nur), sex, and interactions (-).

(XLSX)

Click here for additional data file.^{(14.3KB, xlsx)}

S4 Table. The log2(fold changes) for each contrast between groups depicted in the gene networks.

(XLSX)

Click here for additional data file.^{(11.1KB, xlsx)}

S5 Table. Enriched motifs, tracks, and transcription factors (normalized enrichment scores NES > 3.5) among genes presenting differential expression (False Discovery Rate FDR-adjusted p value < 0.05) for the effects of maternal immune activation, nursing withdrawal, sex, and interaction.

(XLSX)

Click here for additional data file.^{(10.7KB, xlsx)}

Acknowledgments

The contribution of B. Southey in data management, organization, and formatting according to the National Center for Biotechnology Gene Expression Omnibus repository requirements is greatly appreciated.

Data Availability

The data is located in the National Center for Bioinformatics Institute (NCBI), Gene Expression Omnibus (GEO repository, experiment identifier GSE227725. The secure token to allow review is cdyxkkoidjmhhst.

Funding Statement

This research was funded by United States Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA), Agriculture and Food Research Initiative (AFRI) award number 2018-67015-27413, USDA NIFA University of Illinois at Urbana-Champaign Experiment Station (ILLU) award number 2022-38420-38610, and NIH NIDA award number P30 DA018310. Role the funders: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Antonson AM, Radlowski EC, Lawson MA, Rytych JL, Johnson RW. Maternal viral infection during pregnancy elicits anti-social behavior in neonatal piglet offspring independent of postnatal microglial cell activation. Brain Behav Immun. 2017;59:300–12. doi: 10.1016/j.bbi.2016.09.019 . [DOI] [PubMed] [Google Scholar]
2.Bernardi MM, Kirsten TB, Matsuoka SM, Teodorov E, Habr SF, Penteado SHWN, et al. Prenatal Lipopolysaccharide Exposure Affects Maternal Behavior and Male Offspring Sexual Behavior in Adulthood. Neuroimmunomodulation. 2010;17(1):47–55. doi: 10.1159/000243085 [DOI] [PubMed] [Google Scholar]
3.Rymut HE, Bolt CR, Caputo MP, Houser AK, Antonson AM, Zimmerman JD, et al. Long-lasting impact of maternal immune activation and interaction with a second immune challenge on pig behavior. Frontiers in Veterinary Science. 2020;09. doi: 10.3389/fvets.2020.561151 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Sharova VS, Izvolskaia MS, Zakharova LA. Lipopolysaccharide-Induced Maternal Inflammation Affects the Gonadotropin-Releasing Hormone Neuron Development in Fetal Mice. Neuroimmunomodulation. 2015;22(4):222–32. doi: 10.1159/000365482 [DOI] [PubMed] [Google Scholar]
5.Rodriguez-Zas S, Nixon SE, Lawson MA, McCusker RH, Southey BR, O’Connor JC, et al. Advancing the understanding of behaviors associated with Bacille Calmette GuÃ©rin infection using multivariate analysis. Brain, behavior, and immunity. 2015;44:176–86. doi: 10.1016/j.bbi.2014.09.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Zhang P, Moye LS, Southey BR, Dripps I, Sweedler JV, Pradhan A, et al. Opioid-induced hyperalgesia is associated with dysregulation of circadian rhythm and adaptive immune pathways in the mouse trigeminal ganglia and nucleus accumbens Molecular Neurobiology. 2019. doi: 10.1007/s12035-019-01650-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Zhao X, Erickson M, Mohammed R, Kentner AC. Maternal immune activation accelerates puberty initiation and alters mechanical allodynia in male and female C57BL6/J mice. Developmental Psychobiology. 2022;64(5):e22278. doi: 10.1002/dev.22278 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Rahimi S, Peeri M, Azarbayjani MA, Anoosheh L, Ghasemzadeh E, Khalifeh N, et al. Long-term exercise from adolescence to adulthood reduces anxiety- and depression-like behaviors following maternal immune activation in offspring. Physiology & Behavior. 2020;226:113130. doi: 10.1016/j.physbeh.2020.113130 [DOI] [PubMed] [Google Scholar]
9.Morais LH, Felice D, Golubeva AV, Moloney G, Dinan TG, Cryan JF. Strain differences in the susceptibility to the gut–brain axis and neurobehavioural alterations induced by maternal immune activation in mice. Behavioural Pharmacology. 2018;29(2 and 3):181–98. doi: 10.1097/FBP.0000000000000374 -201804000-00008. [DOI] [PubMed] [Google Scholar]
10.Yu C-H, Chen C-Y, Chang C-C. The immediate effects of weaning stress on the hypothalamus-pituitary-adrenal alteration of newly weaned piglets. Journal of Animal Physiology and Animal Nutrition. 2019;103(4):1218–23. doi: 10.1111/jpn.13104 [DOI] [PubMed] [Google Scholar]
11.Curley JP, Jordan ER, Swaney WT, Izraelit A, Kammel S, Champagne FA. The Meaning of Weaning: Influence of the Weaning Period on Behavioral Development in Mice. Dev Neurosci-Basel. 2009;31(4):318–31. doi: 10.1159/000216543 WOS:000267787200009. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Han VX, Patel S, Jones HF, Dale RC. Maternal immune activation and neuroinflammation in human neurodevelopmental disorders. Nature Reviews Neurology. 2021;17(9):564–79. doi: 10.1038/s41582-021-00530-8 [DOI] [PubMed] [Google Scholar]
13.Rymut HE, Rund LA, Bolt CR, Villamil MB, Bender DE, Southey BR, et al. Biochemistry and Immune Biomarkers Indicate Interacting Effects of Pre- and Postnatal Stressors in Pigs across Sexes. Animals. 2021;11(4):987. doi: 10.3390/ani11040987 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Southey BR, Zhang P, Keever MR, Rymut HE, Johnson RW, Sweedler JV, et al. Effects of maternal immune activation in porcine transcript isoforms of neuropeptide and receptor genes. J Integr Neurosci. 2021;20(1):21–31. doi: 10.31083/j.jin.2021.01.332 . [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Albin DM, Wubben JE, Rowlett JM, Tappenden KA, Nowak RA. Changes in small intestinal nutrient transport and barrier function after lipopolysaccharide exposure in two pig breeds1. Journal of Animal Science. 2007;85(10):2517–23. doi: 10.2527/jas.2006-237 [DOI] [PubMed] [Google Scholar]
16.Rymut HE, Rund LA, Southey BR, Johnson RW, Rodriguez-Zas SL. Terpenoid Backbone Biosynthesis among Pig Hippocampal Pathways Impacted by Stressors. Genes. 2022;13(5):814. doi: 10.3390/genes13050814 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Clough E, Barrett T. The Gene Expression Omnibus Database. In: Mathé E, Davis S, editors. Statistical Genomics: Methods and Protocols. New York, NY: Springer New York; 2016. p. 93–110. [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Reiner A, Yekutieli D, Benjamini Y. Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics. 2003;19(3):368–75. doi: 10.1093/bioinformatics/btf877 [DOI] [PubMed] [Google Scholar]
19.Consortium GO. Gene ontology consortium: going forward. Nucleic acids research. 2015;43(D1):D1049–D56. doi: 10.1093/nar/gku1179 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Research. 2015;44(D1):D457–D62. doi: 10.1093/nar/gkv1070 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Keever-Keigher MR, Zhang P, Bolt CR, Rymut HE, Antonson AM, Corbett MP, et al. Interacting impact of maternal inflammatory response and stress on the amygdala transcriptome of pigs. G3 (Bethesda, Md). 2021. Epub 2021/04/16. doi: 10.1093/g3journal/jkab113 . [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Hahne F, Huber W, Gentleman R, Falcon S, Falcon S, Gentleman R. Hypergeometric testing used for gene set enrichment analysis. Bioconductor case studies. 2008:207–20. [Google Scholar]
23.Subramanian A, Kuehn H, Gould J, Tamayo P, Mesirov JP. GSEA-P: a desktop application for Gene Set Enrichment Analysis. Bioinformatics. 2007;23(23):3251–3. doi: 10.1093/bioinformatics/btm369 [DOI] [PubMed] [Google Scholar]
24.Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research. 2019;47(D1):D607–D13. doi: 10.1093/nar/gky1131 WOS:000462587400085. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Kohl M, Wiese S, Warscheid B. Cytoscape: software for visualization and analysis of biological networks. Methods Mol Biol. 2011;696:291–303. Epub 2010/11/11. doi: 10.1007/978-1-60761-987-1_18 . [DOI] [PubMed] [Google Scholar]
26.Rs Janky, Verfaillie A, Imrichová H, Van de Sande B, Standaert L, Christiaens V, et al. iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections. PLOS Computational Biology. 2014;10(7):e1003731. doi: 10.1371/journal.pcbi.1003731 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Rodriguez-Zas SL, Southey BR, Rymut HE, Rund LA, Johnson RW. Hippocampal Changes Elicited by Metabolic and Inflammatory Stressors following Prenatal Maternal Infection. Genes (Basel). 2022;14(1). Epub 2023/01/22. doi: 10.3390/genes14010077 ; PubMed Central PMCID: PMC9859158. [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Keever MR, Zhang P, Bolt CR, Antonson AM, Rymut HE, Caputo MP, et al. Lasting and Sex-Dependent Impact of Maternal Immune Activation on Molecular Pathways of the Amygdala. Front Neurosci-Switz. 2020;14:774. doi: 10.3389/fnins.2020.00774 WOS:000565353000001. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Rymut HE, Rund LA, Bolt CR, Villamil MB, Southey BR, Johnson RW, et al. The Combined Effect of Weaning Stress and Immune Activation during Pig Gestation on Serum Cytokine and Analyte Concentrations. Animals. 2021;11(8):2274. doi: 10.3390/ani11082274 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Van den Bergh BR, Van Calster B, Smits T, Van Huffel S, Lagae L. Antenatal maternal anxiety is related to HPA-axis dysregulation and self-reported depressive symptoms in adolescence: a prospective study on the fetal origins of depressed mood. Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology. 2008;33(3):536–45. Epub 2007/05/18. doi: 10.1038/sj.npp.1301450 . [DOI] [PubMed] [Google Scholar]
31.Kapoor A, Matthews SG. Short periods of prenatal stress affect growth, behaviour and hypothalamo–pituitary–adrenal axis activity in male guinea pig offspring. The Journal of Physiology. 2005;566(3):967–77. doi: 10.1113/jphysiol.2005.090191 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Zhang Z-Q, Wu W-W, Chen J-D, Zhang G-Y, Lin J-Y, Wu Y-K, et al. Weighted Gene Coexpression Network Analysis Reveals Essential Genes and Pathways in Bipolar Disorder. Frontiers in Psychiatry. 2021;12. doi: 10.3389/fpsyt.2021.553305 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Jonkers I, Lis JT. Getting up to speed with transcription elongation by RNA polymerase II. Nature Reviews Molecular Cell Biology. 2015;16(3):167–77. doi: 10.1038/nrm3953 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Chia DJ, Rotwein P. Defining the Epigenetic Actions of Growth Hormone: Acute Chromatin Changes Accompany GH-Activated Gene Transcription. Molecular Endocrinology. 2010;24(10):2038–49. doi: 10.1210/me.2010-0234 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Li X, Qu F, Xie W, Wang F, Liu H, Song S, et al. Transcriptomic Analyses of Neurotoxic Effects in Mouse Brain After Intermittent Neonatal Administration of Thimerosal. Toxicological Sciences. 2014;139(2):452–65. doi: 10.1093/toxsci/kfu049 [DOI] [PubMed] [Google Scholar]
36.Shen P, Ji S, Li X, Yang Q, Xu B, Wong CKC, et al. LPS-Induced Systemic Inflammation Caused mPOA-FSH/LH Disturbance and Impaired Testicular Function. Frontiers in endocrinology. 2022;13:886085. Epub 2022/07/12. doi: 10.3389/fendo.2022.886085 ; PubMed Central PMCID: PMC9259990. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Hanada R, Nakazato M, Murakami N, Sakihara S, Yoshimatsu H, Toshinai K, et al. A Role for Neuromedin U in Stress Response. Biochemical and Biophysical Research Communications. 2001;289(1):225–8. doi: 10.1006/bbrc.2001.5945 [DOI] [PubMed] [Google Scholar]
38.Nakahara K, Kojima M, Hanada R, Egi Y, Ida T, Miyazato M, et al. Neuromedin U is involved in nociceptive reflexes and adaptation to environmental stimuli in mice. Biochemical and Biophysical Research Communications. 2004;323(2):615–20. doi: 10.1016/j.bbrc.2004.08.136 [DOI] [PubMed] [Google Scholar]
39.Sarro EC, Sullivan RM, Barr G. Unpredictable Neonatal Stress Enhances Adult Anxiety and Alters Amygdala Gene Expression Related to Serotonin and Gaba. Neuroscience. 2014;258:147–61. doi: 10.1016/j.neuroscience.2013.10.064 WOS:000330596900013. [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Garbett KA, Hsiao EY, Kálmán S, Patterson PH, Mirnics K. Effects of maternal immune activation on gene expression patterns in the fetal brain. Translational Psychiatry. 2012;2(4):e98–e. doi: 10.1038/tp.2012.24 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Catale C, Lo Iacono L, Martini A, Heil C, Guatteo E, Mercuri NB, et al. Early Life Social Stress Causes Sex- and Region-Dependent Dopaminergic Changes that Are Prevented by Minocycline. Molecular Neurobiology. 2022;59(6):3913–32. doi: 10.1007/s12035-022-02830-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Uddin MN, Mondal T, Yao Y, Manley K, Lawrence DA. Oxidative stress and neuroimmune proteins in a mouse model of autism. Cell Stress and Chaperones. 2023. doi: 10.1007/s12192-023-01331-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Bethea CL, Kim A, Reddy AP, Chin A, Bethea SC, Cameron JL. Hypothalamic KISS1 expression, gonadotrophin-releasing hormone and neurotransmitter innervation vary with stress and sensitivity in macaques. Journal of neuroendocrinology. 2014;26(5):267–81. Epub 2014/03/13. doi: 10.1111/jne.12146 ; PubMed Central PMCID: PMC4012296. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Nair BB, Khant Aung Z, Porteous R, Prescott M, Glendining KA, Jenkins DE, et al. Impact of chronic variable stress on neuroendocrine hypothalamus and pituitary in male and female C57BL/6J mice. Journal of neuroendocrinology. 2021;33(5):e12972. doi: 10.1111/jne.12972 [DOI] [PubMed] [Google Scholar]
45.Sunwoo J-S, Jeon D, Lee S-T, Moon J, Yu J-S, Park D-K, et al. Maternal immune activation alters brain microRNA expression in mouse offspring. Annals of Clinical and Translational Neurology. 2018;5(10):1264–76. doi: 10.1002/acn3.652 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Hu Y, Korovaichuk A, Astiz M, Schroeder H, Islam R, Barrenetxea J, et al. Functional Divergence of Mammalian TFAP2a and Tfap2b Transcription Factors for Bidirectional Sleep Control. Genetics. 2020;216(3):735–52. doi: 10.1534/genetics.120.303533 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.van Zeijl CJJ, Surovtseva OV, Wiersinga WM, Fliers E, Boelen A. Acute Inflammation Increases Pituitary and Hypothalamic Glycoprotein Hormone Subunit B5 mRNA Expression in Association with Decreased Thyrotrophin Receptor mRNA Expression in Mice. Journal of neuroendocrinology. 2011;23(4):310–9. doi: 10.1111/j.1365-2826.2011.02116.x [DOI] [PubMed] [Google Scholar]
48.Alhassen S, Chen S, Alhassen L, Phan A, Khoudari M, De Silva A, et al. Intergenerational trauma transmission is associated with brain metabotranscriptome remodeling and mitochondrial dysfunction. Communications Biology. 2021;4(1):783. doi: 10.1038/s42003-021-02255-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Li XF, Kinsey-Jones JS, Knox AMI, Wu XQ, Tahsinsoy D, Brain SD, et al. Neonatal Lipopolysaccharide Exposure Exacerbates Stress-Induced Suppression of Luteinizing Hormone Pulse Frequency in Adulthood. Endocrinology. 2007;148(12):5984–90. doi: 10.1210/en.2007-0710 [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Esquifino AI, Chacón F, Jimenez V, Reyes Toso CF, Cardinali DP. 24-hour changes in circulating prolactin, follicle-stimulating hormone, luteinizing hormone and testosterone in male rats subjected to social isolation. Journal of Circadian Rhythms. 2004;2(1):1. doi: 10.1186/1740-3391-2-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Richetto J, Chesters R, Cattaneo A, Labouesse MA, Gutierrez AMC, Wood TC, et al. Genome-Wide Transcriptional Profiling and Structural Magnetic Resonance Imaging in the Maternal Immune Activation Model of Neurodevelopmental Disorders. Cerebral Cortex. 2016;27(6):3397–413. doi: 10.1093/cercor/bhw320 [DOI] [PubMed] [Google Scholar]
52.Ibi D, Nagai T, Kitahara Y, Mizoguchi H, Koike H, Shiraki A, et al. Neonatal polyI:C treatment in mice results in schizophrenia-like behavioral and neurochemical abnormalities in adulthood. Neuroscience Research. 2009;64(3):297–305. doi: 10.1016/j.neures.2009.03.015 [DOI] [PubMed] [Google Scholar]
53.Izvolskaia M, Sharova V, Zakharova L. Perinatal Inflammation Reprograms Neuroendocrine, Immune, and Reproductive Functions: Profile of Cytokine Biomarkers. Inflammation. 2020;43(4):1175–83. doi: 10.1007/s10753-020-01220-1 [DOI] [PubMed] [Google Scholar]
54.Haddad F, Patel S, Schmid S. Maternal immune activation by Poly I: C as a preclinical model for neurodevelopmental disorders: a focus on autism and schizophrenia. Neuroscience & Biobehavioral Reviews. 2020. doi: 10.1016/j.neubiorev.2020.04.012 [DOI] [PubMed] [Google Scholar]
55.Southey BR, Keever-Keigher MR, Rymut HE, Rund LA, Johnson RW, Rodriguez-Zas SL. Disruption of Alternative Splicing in the Amygdala of Pigs Exposed to Maternal Immune Activation. Immuno. 2021;1(4):499–517. doi: 10.3390/immuno1040035 [DOI] [Google Scholar]
56.Tsivion-Visbord H, Kopel E, Feiglin A, Sofer T, Barzilay R, Ben-Zur T, et al. Increased RNA editing in maternal immune activation model of neurodevelopmental disease. Nature Communications. 2020;11(1):5236. doi: 10.1038/s41467-020-19048-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Canales CP, Estes ML, Cichewicz K, Angara K, Aboubechara JP, Cameron S, et al. Sequential perturbations to mouse corticogenesis following in utero maternal immune activation. eLife. 2021;10:e60100. doi: 10.7554/eLife.60100 [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Aguilar-Valles A, Flores C, Luheshi GN. Prenatal inflammation-induced hypoferremia alters dopamine function in the adult offspring in rat: relevance for schizophrenia. PloS one. 2010;5(6):e10967. doi: 10.1371/journal.pone.0010967 [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Hökfelt T, Barde S, Xu Z-QD, Kuteeva E, Rüegg J, Le Maitre E, et al. Neuropeptide and Small Transmitter Coexistence: Fundamental Studies and Relevance to Mental Illness. Frontiers in Neural Circuits. 2018;12. doi: 10.3389/fncir.2018.00106 [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Hui CW, Vecchiarelli HA, Gervais É, Luo X, Michaud F, Scheefhals L, et al. Sex Differences of Microglia and Synapses in the Hippocampal Dentate Gyrus of Adult Mouse Offspring Exposed to Maternal Immune Activation. Frontiers in Cellular Neuroscience. 2020;14(331). doi: 10.3389/fncel.2020.558181 [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Kirsten TB, Chaves GP, Taricano M, Martins DO, Flório JC, de Britto LRG, et al. Prenatal LPS exposure reduces olfactory perception in neonatal and adult rats. Physiology & Behavior. 2011;104(3):417–22. doi: 10.1016/j.physbeh.2011.04.049 [DOI] [PubMed] [Google Scholar]
62.Yuan T-F, Hou G, Arias-Carrion O. Chronic stress impacts on olfactory system. CNS & Neurological Disorders-Drug Targets (Formerly Current Drug Targets-CNS & Neurological Disorders). 2015;14(4):486–91. doi: 10.2174/1871527314666150429111356 [DOI] [PubMed] [Google Scholar]
63.Ayash S, Lingner T, Ryu S, Kalisch R, Schmitt U, Müller MB. Reconceptualising resilience within a translational framework is supported by unique and brain-region specific transcriptional signatures in mice. bioRxiv. 2020:2020.11.15.383489. doi: 10.1101/2020.11.15.383489 [DOI] [Google Scholar]
64.Cyrus SS, Cohen ASA, Agbahovbe R, Avela K, Yeung KS, Chung BHY, et al. Rare SUZ12 variants commonly cause an overgrowth phenotype. American Journal of Medical Genetics Part C: Seminars in Medical Genetics. 2019;181(4):532–47. doi: 10.1002/ajmg.c.31748 [DOI] [PubMed] [Google Scholar]
65.Bristy SA, Islam AMH, Andalib KMS, Khan U, Awal MA, Rahman MH. Determination of molecular signatures and pathways common to brain tissues of autism spectrum disorder: Insights from comprehensive bioinformatics approach. Informatics in Medicine Unlocked. 2022;29:100871. doi: 10.1016/j.imu.2022.100871 [DOI] [Google Scholar]
66.Gadad BS, Raj P, Jha MK, Carmody T, Dozmorov I, Mayes TL, et al. Association of Novel ALX4 Gene Polymorphisms with Antidepressant Treatment Response: Findings from the CO-MED Trial. Complex Psychiatry. 2018;4(1):7–19. doi: 10.1159/000487321 [DOI] [PMC free article] [PubMed] [Google Scholar]
67.He T, Shang J, Gao C, Guan X, Chen Y, Zhu L, et al. A novel SIRT6 activator ameliorates neuroinflammation and ischemic brain injury via EZH2/FOXC1 axis. Acta Pharmaceutica Sinica B. 2021;11(3):708–26. doi: 10.1016/j.apsb.2020.11.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
68.You X, Liu M, Liu Q, Li H, Qu Y, Gao X, et al. miRNA let-7 family regulated by NEAT1 and ARID3A/NF-κB inhibits PRRSV-2 replication in vitro and in vivo. PLOS Pathogens. 2022;18(10):e1010820. doi: 10.1371/journal.ppat.1010820 [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Wang J, Lee S, Teh CE-Y, Bunting K, Ma L, Shannon MF. The transcription repressor, ZEB1, cooperates with CtBP2 and HDAC1 to suppress IL-2 gene activation in T cells. International Immunology. 2009;21(3):227–35. doi: 10.1093/intimm/dxn143 [DOI] [PubMed] [Google Scholar]
70.Li H, Zhang C, Yang C, Blevins M, Norris D, Zhao R, et al. C-terminal binding proteins 1 and 2 in traumatic brain injury-induced inflammation and their inhibition as an approach for anti-inflammatory treatment. International journal of biological sciences. 2020;16(7):1107–20. Epub 2020/03/17. doi: 10.7150/ijbs.42109 ; PubMed Central PMCID: PMC7053329. [DOI] [PMC free article] [PubMed] [Google Scholar]
71.Ivanov II, McKenzie BS, Zhou L, Tadokoro CE, Lepelley A, Lafaille JJ, et al. The orphan nuclear receptor RORgammat directs the differentiation program of proinflammatory IL-17+ T helper cells. Cell. 2006;126(6):1121–33. Epub 2006/09/23. doi: 10.1016/j.cell.2006.07.035 . [DOI] [PubMed] [Google Scholar]
72.Roszkowska M, Krysiak A, Majchrowicz L, Nader K, Beroun A, Michaluk P, et al. SRF depletion in early life contributes to social interaction deficits in the adulthood. Cellular and Molecular Life Sciences. 2022;79(5):278. doi: 10.1007/s00018-022-04291-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
73.Golovina E, Fadason T, Lints TJ, Walker C, Vickers MH, O’Sullivan JM. Understanding the impact of SNPs associated with autism spectrum disorder on biological pathways in the human fetal and adult cortex. Scientific Reports. 2021;11(1):15867. doi: 10.1038/s41598-021-95447-z [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0292952.r001

Decision Letter 0

Dragan Hrncic

5 Sep 2023

PONE-D-23-19245Prenatal and postnatal challenges affect the hypothalamic molecular pathways that regulate hormonal levelsPLOS ONE

Dear Dr. Rodriguez-Zas,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Oct 20 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Prof. Dr. Dragan Hrncic, MD, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please expand the acronym “USDA, NIFA, AFRI, ILLU” (as indicated in your financial disclosure) so that it states the name of your funders in full. This information should be included in your cover letter; we will change the online submission form on your behalf.

3. Thank you for stating the following financial disclosure:

"This research was funded by USDA NIFA AFRI award number 2018-67015-27413, USDA NIFA ILLU award number 2022-38420-38610, and NIH NIDA award number P30 DA018310."

Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

4. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability.

Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

5. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

Additional Editor Comments:

- please do respond in detail to reviewer comments and directions to improve your manuscript

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This work used RNA sequencing to study how prenatal challenge with maternal immune activation (MIA) and postnatal challenge with nursing impact the molecular pathways of hypothalamic pathways, and examine the effects are different among female and male pigs. The main concerns are as follows,

1) Instead of whole-transcriptome sequencing, the work used a target panel of 222 genes. Why? How these genes were chosen? How this limitation will affect the functional analysis of differentially expressed genes (DEGs)?

2) The main result is to present the analysis results of DEGs across three factors, functional significance and the possible regulation mechanism. The current form is hard to follow. The authors may consider to reorganize the results in a more intuitive way.

3) Main result is focused on the hormonal regulation pathway. However, a lot of discussion is on the olfactory transduction pathway while only one enrichment result was presented about the pathway.

4) There is no confirmation from the protein levels on the findings.

Minor points:

1) Figure 1 is hard to digest. Only the DEGs are included and the box-whisker plot seems inappropriate since DEGs are either upregulated (logFC >0) or downregulated (logFC<0). Non-DEGs should have a logFC close to 0.

2) How are the expression levels of 222 genes quantified? Esp in the comparisons between Ctrl and MIA, and between Wea and Nur, the logFCs of DEGs were biased towards the negative side and the positive side, respectively?

3) “Sex” is a different factor from other two. “prenatal challenge with sex” and other similar descriptions are confusing and misleading. The authors may consider rewrite the description on the sex factor.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Oct 18;18(10):e0292952. doi: 10.1371/journal.pone.0292952.r002

Author response to Decision Letter 0

8 Sep 2023

September 7, 2023

Reply to the editorial and reviewers’ recommendations on the manuscript PONE-D-23-19245

Dear Professor Dr. Hrncic and reviewer,

We appreciate for the opportunity to revise our manuscript PONE-D-23-19245. We have modified the submission to address questions and integrate the recommendations offered to us. The suggestions have strengthened our manuscript, and we thank the reviewers for their feedback.

Below is the list of recommendations made by the editorial team and reviewer, and in our point-by-point reply, we describe the manuscript modifications that address the suggestions.

Thank you

Sandra Rodriguez Zas

REPLY. Agree. Clarifications were added in page 6 and in page 15. A whole-transcriptome analysis was undertaken. Please refer to page 5, second paragraph about the “test the effects of prenatal inflammation, nursing withdrawal, sex, and interactions on 18,295 genes”. The reference to 222 genes in the Discussion correspond to the number of genes that presented differential expression at FDR-adjusted p value < 0.05 (page 15 first paragraph).

REPLY. We agree in that the flow of result presentation must be amenable to readers while meeting scientific standards. The order of result presentation follows statistical and biological better practices. Following the logical approach of deductive reasoning, the progress of the result presentation goes from functional categories, corresponding genes and interactions impacted by the factors studied (Tables 1 and 2 and Figs 2-3). Subsequently, the presentation of results focuses up-regulated or down-regulated functional categories (Table 4) and ends with transcription factors. Also consistent with better practices, results within a table were obtained from a common model, method, and specifications.

3) Main result is focused on the hormonal regulation pathway. However, a lot of discussion is on the olfactory transduction pathway while only one enrichment result was presented about the pathway.

REPLY. Agree. Clarifications were added in page 10, and 18. The network of genes in the hormonal regulation pathway was selected for visualization across 12 contrasts because of the significant enrichment, and because it includes genes from other enriched pathways including regulation of transcription by RNA polymerase II, G-protein coupled receptor signaling pathway, cellular response to endogenous stimulus, regulation of signaling receptor activity. Also, the number of genes annotated to the hormonal regulatory pathway is amenable to interpretable visualization. The larger number of genes annotated to the olfactory transduction pathway resulted in a denser network that challenged accessible visualization and interpretation for the 12 group comparisons reported.

4) There is no confirmation from the protein levels on the findings.

REPLY. Agree. A clarification was added in page 6. We agree with the implementation of strategies to minimize false positive results, and in the unbiased validation of results whenever possible. The large number of samples analyzed (72 individuals) and significant genes across effects and contrasts prevents an unbiased confirmation of all group contrasts and 220 genes discussed using protein-based analysis. The replicability of the findings is supported by the conservative criteria in the analysis, and genes and categories selected for interpretation (i.e., simultaneous FDR adjusted p-value < 0.05). Also, genes with low sequence reads in any one group were not reported (Materials and methods section). To convey high degree of robustness in the findings, our discussion highlighted differentially expressed genes that were both supported by enriched functional categories and have been previously associated with maternal immune activation, stress, and sex differences as evidenced by our thorough reference list.

Minor points:

REPLY. Agree. A clarification was added in page 6. We agree that have Fig 1 depicted all 18,295 genes analyzed, the box-whisker plots would have been centered around 0. Fig 1 focuses on the differentially expressed genes and therefore the plots will not necessarily be centered around 0. The plots aim at highlighting that the effects studied do not have a balanced effect in up-regulating some genes and down-regulating in similar magnitude or quantity.

REPLY. Agree. Clarifications were added in pages 5 and 6. We agree that the description of the quantification is important in assessing the findings. A generalized linear model was used to test the effects of prenatal inflammation, nursing withdrawal, sex, and interactions on 18,295 genes analysis. Among these, some genes were differentially expressed at FDR-adjusted p value < 0.05 between MIA and Ctrl and others were differentially expressed between Wea and Nur. Fig 1 demonstrates that most of the impacted genes were over-expressed in individuals exposed to MIA and in individuals exposed to stress.

REPLY. Agree. Clarifications were added in the abstract and in page 8. We agree that while the prenatal and postnatal challenges are distinct in nature to sex differences. Following standard statistical approaches, we tested the effect of each one of the factors (maternal immune activation, stress, and sex) and also their interaction. These interactions aim at identifying whether the effect of maternal immune activation (or stress) depends or varies with sex. In consideration that 79 genes presented significant interaction of either prenatal or postnatal challenge with sex, we favor reporting these interactions in paragraphs proximal to interpretations that focus on the challenges to remind readers of the sex-dependent nature of some of the profiles detected.

Attachment

Submitted filename: PONE-D-23-19245Hypo22ReplytorTviewersPLOSone_sep072023.docx

Click here for additional data file.^{(19.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0292952.r003

Decision Letter 1

Dragan Hrncic

25 Sep 2023

PONE-D-23-19245R1Prenatal and postnatal challenges affect the hypothalamic molecular pathways that regulate hormonal levelsPLOS ONE

Dear Dr. Rodriguez-Zas,

Please submit your revised manuscript by Nov 09 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Prof. Dr. Dragan Hrncic, MD, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: Figure 1 remains the same which requires a change of presentation. The box-whisker plot is inappropriate to present the distribution of two different subsets (up and down DEGs here). It is advised to use two separate box-whisker plots (one for up and one for down) or two separate density plots. The authors may also consider to add a density distribution plot of the normalized counts to explain why the distribution of DEGs are skewed in the first 2 contrasts.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

**********

PLoS One. 2023 Oct 18;18(10):e0292952. doi: 10.1371/journal.pone.0292952.r004

Author response to Decision Letter 1

28 Sep 2023

Sep 27 2023

Reply to the reviewers’ and editorial recommendations on the manuscript PONE-D-23-19245R1

Dear Professor Dr. Hrncic and reviewers,

Once again, we express our appreciation for the opportunity to revise our submission, integrating the recommendations offered to us.

Below is the reply to the feedback.

Thank you

Sandra Rodriguez Zas and co-authors

Review Comments to the Author

REPLY. Agree. Figure 1 has been revised. I apologize for failing to understand the original comment. Following the reviewer’s suggestion, two separate box-whisker plots (one for up and one for down) were created for each effect. Other studies of maternal immune activation are reporting uneven distribution of positive and negative fold changes among the differentially expressed genes (e.g., Kalish, B.T., Kim, E., Finander, B. et al. Maternal immune activation in mice disrupts proteostasis in the fetal brain. Nat Neurosci 24, 204–213 (2021). https://doi.org/10.1038/s41593-020-00762-9; Cesar P CanalesMyka L EstesKarol CichewiczKartik AngaraJohn Paul AboubecharaScott CameronKathryn PrendergastLinda Su-FeherIva ZdilarEllie J KreunEmma C ConnollyJin Myeong SeoJack B GoonKathleen FarrellyTyler W StradleighDeborah van der ListLori HaapanenJudy Van de WaterDaniel VogtA Kimberley McAllisterAlex S Nord (2021) Sequential perturbations to mouse corticogenesis following in utero maternal immune activation eLife 10:e60100); Sarieva, K., Kagermeier, T., Khakipoor, S. et al. Human brain organoid model of maternal immune activation identifies radial glia cells as selectively vulnerable. Mol Psychiatry (2023). https://doi.org/10.1038/s41380-023-01997-1)

PLoS One. doi: 10.1371/journal.pone.0292952.r005

Decision Letter 2

Dragan Hrncic

3 Oct 2023

Prenatal and postnatal challenges affect the hypothalamic molecular pathways that regulate hormonal levels

PONE-D-23-19245R2

Dear Dr. Rodriguez-Zas,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Prof. Dr. Dragan Hrncic, MD, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0292952.r006

Acceptance letter

Dragan Hrncic

8 Oct 2023

PONE-D-23-19245R2

Prenatal and postnatal challenges affect the hypothalamic molecular pathways that regulate hormonal levels

Dear Dr. Rodriguez-Zas:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Dragan Hrncic

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Experimental design scheme.

(XLSX)

Click here for additional data file.^{(68.6KB, xlsx)}

(XLSX)

Click here for additional data file.^{(17.7KB, xlsx)}

(XLSX)

Click here for additional data file.^{(9.9KB, xlsx)}

(XLSX)

Click here for additional data file.^{(14.3KB, xlsx)}

S4 Table. The log2(fold changes) for each contrast between groups depicted in the gene networks.

(XLSX)

Click here for additional data file.^{(11.1KB, xlsx)}

(XLSX)

Click here for additional data file.^{(10.7KB, xlsx)}

Attachment

Submitted filename: PONE-D-23-19245Hypo22ReplytorTviewersPLOSone_sep072023.docx

Click here for additional data file.^{(19.1KB, docx)}

Data Availability Statement

[pone.0292952.ref001] 1.Antonson AM, Radlowski EC, Lawson MA, Rytych JL, Johnson RW. Maternal viral infection during pregnancy elicits anti-social behavior in neonatal piglet offspring independent of postnatal microglial cell activation. Brain Behav Immun. 2017;59:300–12. doi: 10.1016/j.bbi.2016.09.019 . [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref002] 2.Bernardi MM, Kirsten TB, Matsuoka SM, Teodorov E, Habr SF, Penteado SHWN, et al. Prenatal Lipopolysaccharide Exposure Affects Maternal Behavior and Male Offspring Sexual Behavior in Adulthood. Neuroimmunomodulation. 2010;17(1):47–55. doi: 10.1159/000243085 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref003] 3.Rymut HE, Bolt CR, Caputo MP, Houser AK, Antonson AM, Zimmerman JD, et al. Long-lasting impact of maternal immune activation and interaction with a second immune challenge on pig behavior. Frontiers in Veterinary Science. 2020;09. doi: 10.3389/fvets.2020.561151 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref004] 4.Sharova VS, Izvolskaia MS, Zakharova LA. Lipopolysaccharide-Induced Maternal Inflammation Affects the Gonadotropin-Releasing Hormone Neuron Development in Fetal Mice. Neuroimmunomodulation. 2015;22(4):222–32. doi: 10.1159/000365482 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref005] 5.Rodriguez-Zas S, Nixon SE, Lawson MA, McCusker RH, Southey BR, O’Connor JC, et al. Advancing the understanding of behaviors associated with Bacille Calmette GuÃ©rin infection using multivariate analysis. Brain, behavior, and immunity. 2015;44:176–86. doi: 10.1016/j.bbi.2014.09.018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref006] 6.Zhang P, Moye LS, Southey BR, Dripps I, Sweedler JV, Pradhan A, et al. Opioid-induced hyperalgesia is associated with dysregulation of circadian rhythm and adaptive immune pathways in the mouse trigeminal ganglia and nucleus accumbens Molecular Neurobiology. 2019. doi: 10.1007/s12035-019-01650-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref007] 7.Zhao X, Erickson M, Mohammed R, Kentner AC. Maternal immune activation accelerates puberty initiation and alters mechanical allodynia in male and female C57BL6/J mice. Developmental Psychobiology. 2022;64(5):e22278. doi: 10.1002/dev.22278 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref008] 8.Rahimi S, Peeri M, Azarbayjani MA, Anoosheh L, Ghasemzadeh E, Khalifeh N, et al. Long-term exercise from adolescence to adulthood reduces anxiety- and depression-like behaviors following maternal immune activation in offspring. Physiology & Behavior. 2020;226:113130. doi: 10.1016/j.physbeh.2020.113130 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref009] 9.Morais LH, Felice D, Golubeva AV, Moloney G, Dinan TG, Cryan JF. Strain differences in the susceptibility to the gut–brain axis and neurobehavioural alterations induced by maternal immune activation in mice. Behavioural Pharmacology. 2018;29(2 and 3):181–98. doi: 10.1097/FBP.0000000000000374 -201804000-00008. [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref010] 10.Yu C-H, Chen C-Y, Chang C-C. The immediate effects of weaning stress on the hypothalamus-pituitary-adrenal alteration of newly weaned piglets. Journal of Animal Physiology and Animal Nutrition. 2019;103(4):1218–23. doi: 10.1111/jpn.13104 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref011] 11.Curley JP, Jordan ER, Swaney WT, Izraelit A, Kammel S, Champagne FA. The Meaning of Weaning: Influence of the Weaning Period on Behavioral Development in Mice. Dev Neurosci-Basel. 2009;31(4):318–31. doi: 10.1159/000216543 WOS:000267787200009. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref012] 12.Han VX, Patel S, Jones HF, Dale RC. Maternal immune activation and neuroinflammation in human neurodevelopmental disorders. Nature Reviews Neurology. 2021;17(9):564–79. doi: 10.1038/s41582-021-00530-8 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref013] 13.Rymut HE, Rund LA, Bolt CR, Villamil MB, Bender DE, Southey BR, et al. Biochemistry and Immune Biomarkers Indicate Interacting Effects of Pre- and Postnatal Stressors in Pigs across Sexes. Animals. 2021;11(4):987. doi: 10.3390/ani11040987 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref014] 14.Southey BR, Zhang P, Keever MR, Rymut HE, Johnson RW, Sweedler JV, et al. Effects of maternal immune activation in porcine transcript isoforms of neuropeptide and receptor genes. J Integr Neurosci. 2021;20(1):21–31. doi: 10.31083/j.jin.2021.01.332 . [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref015] 15.Albin DM, Wubben JE, Rowlett JM, Tappenden KA, Nowak RA. Changes in small intestinal nutrient transport and barrier function after lipopolysaccharide exposure in two pig breeds1. Journal of Animal Science. 2007;85(10):2517–23. doi: 10.2527/jas.2006-237 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref016] 16.Rymut HE, Rund LA, Southey BR, Johnson RW, Rodriguez-Zas SL. Terpenoid Backbone Biosynthesis among Pig Hippocampal Pathways Impacted by Stressors. Genes. 2022;13(5):814. doi: 10.3390/genes13050814 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref017] 17.Clough E, Barrett T. The Gene Expression Omnibus Database. In: Mathé E, Davis S, editors. Statistical Genomics: Methods and Protocols. New York, NY: Springer New York; 2016. p. 93–110. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref018] 18.Reiner A, Yekutieli D, Benjamini Y. Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics. 2003;19(3):368–75. doi: 10.1093/bioinformatics/btf877 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref019] 19.Consortium GO. Gene ontology consortium: going forward. Nucleic acids research. 2015;43(D1):D1049–D56. doi: 10.1093/nar/gku1179 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref020] 20.Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Research. 2015;44(D1):D457–D62. doi: 10.1093/nar/gkv1070 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref021] 21.Keever-Keigher MR, Zhang P, Bolt CR, Rymut HE, Antonson AM, Corbett MP, et al. Interacting impact of maternal inflammatory response and stress on the amygdala transcriptome of pigs. G3 (Bethesda, Md). 2021. Epub 2021/04/16. doi: 10.1093/g3journal/jkab113 . [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref022] 22.Hahne F, Huber W, Gentleman R, Falcon S, Falcon S, Gentleman R. Hypergeometric testing used for gene set enrichment analysis. Bioconductor case studies. 2008:207–20. [Google Scholar]

[pone.0292952.ref023] 23.Subramanian A, Kuehn H, Gould J, Tamayo P, Mesirov JP. GSEA-P: a desktop application for Gene Set Enrichment Analysis. Bioinformatics. 2007;23(23):3251–3. doi: 10.1093/bioinformatics/btm369 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref024] 24.Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research. 2019;47(D1):D607–D13. doi: 10.1093/nar/gky1131 WOS:000462587400085. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref025] 25.Kohl M, Wiese S, Warscheid B. Cytoscape: software for visualization and analysis of biological networks. Methods Mol Biol. 2011;696:291–303. Epub 2010/11/11. doi: 10.1007/978-1-60761-987-1_18 . [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref026] 26.Rs Janky, Verfaillie A, Imrichová H, Van de Sande B, Standaert L, Christiaens V, et al. iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections. PLOS Computational Biology. 2014;10(7):e1003731. doi: 10.1371/journal.pcbi.1003731 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref027] 27.Rodriguez-Zas SL, Southey BR, Rymut HE, Rund LA, Johnson RW. Hippocampal Changes Elicited by Metabolic and Inflammatory Stressors following Prenatal Maternal Infection. Genes (Basel). 2022;14(1). Epub 2023/01/22. doi: 10.3390/genes14010077 ; PubMed Central PMCID: PMC9859158. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref028] 28.Keever MR, Zhang P, Bolt CR, Antonson AM, Rymut HE, Caputo MP, et al. Lasting and Sex-Dependent Impact of Maternal Immune Activation on Molecular Pathways of the Amygdala. Front Neurosci-Switz. 2020;14:774. doi: 10.3389/fnins.2020.00774 WOS:000565353000001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref029] 29.Rymut HE, Rund LA, Bolt CR, Villamil MB, Southey BR, Johnson RW, et al. The Combined Effect of Weaning Stress and Immune Activation during Pig Gestation on Serum Cytokine and Analyte Concentrations. Animals. 2021;11(8):2274. doi: 10.3390/ani11082274 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref030] 30.Van den Bergh BR, Van Calster B, Smits T, Van Huffel S, Lagae L. Antenatal maternal anxiety is related to HPA-axis dysregulation and self-reported depressive symptoms in adolescence: a prospective study on the fetal origins of depressed mood. Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology. 2008;33(3):536–45. Epub 2007/05/18. doi: 10.1038/sj.npp.1301450 . [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref031] 31.Kapoor A, Matthews SG. Short periods of prenatal stress affect growth, behaviour and hypothalamo–pituitary–adrenal axis activity in male guinea pig offspring. The Journal of Physiology. 2005;566(3):967–77. doi: 10.1113/jphysiol.2005.090191 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref032] 32.Zhang Z-Q, Wu W-W, Chen J-D, Zhang G-Y, Lin J-Y, Wu Y-K, et al. Weighted Gene Coexpression Network Analysis Reveals Essential Genes and Pathways in Bipolar Disorder. Frontiers in Psychiatry. 2021;12. doi: 10.3389/fpsyt.2021.553305 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref033] 33.Jonkers I, Lis JT. Getting up to speed with transcription elongation by RNA polymerase II. Nature Reviews Molecular Cell Biology. 2015;16(3):167–77. doi: 10.1038/nrm3953 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref034] 34.Chia DJ, Rotwein P. Defining the Epigenetic Actions of Growth Hormone: Acute Chromatin Changes Accompany GH-Activated Gene Transcription. Molecular Endocrinology. 2010;24(10):2038–49. doi: 10.1210/me.2010-0234 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref035] 35.Li X, Qu F, Xie W, Wang F, Liu H, Song S, et al. Transcriptomic Analyses of Neurotoxic Effects in Mouse Brain After Intermittent Neonatal Administration of Thimerosal. Toxicological Sciences. 2014;139(2):452–65. doi: 10.1093/toxsci/kfu049 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref036] 36.Shen P, Ji S, Li X, Yang Q, Xu B, Wong CKC, et al. LPS-Induced Systemic Inflammation Caused mPOA-FSH/LH Disturbance and Impaired Testicular Function. Frontiers in endocrinology. 2022;13:886085. Epub 2022/07/12. doi: 10.3389/fendo.2022.886085 ; PubMed Central PMCID: PMC9259990. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref037] 37.Hanada R, Nakazato M, Murakami N, Sakihara S, Yoshimatsu H, Toshinai K, et al. A Role for Neuromedin U in Stress Response. Biochemical and Biophysical Research Communications. 2001;289(1):225–8. doi: 10.1006/bbrc.2001.5945 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref038] 38.Nakahara K, Kojima M, Hanada R, Egi Y, Ida T, Miyazato M, et al. Neuromedin U is involved in nociceptive reflexes and adaptation to environmental stimuli in mice. Biochemical and Biophysical Research Communications. 2004;323(2):615–20. doi: 10.1016/j.bbrc.2004.08.136 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref039] 39.Sarro EC, Sullivan RM, Barr G. Unpredictable Neonatal Stress Enhances Adult Anxiety and Alters Amygdala Gene Expression Related to Serotonin and Gaba. Neuroscience. 2014;258:147–61. doi: 10.1016/j.neuroscience.2013.10.064 WOS:000330596900013. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref040] 40.Garbett KA, Hsiao EY, Kálmán S, Patterson PH, Mirnics K. Effects of maternal immune activation on gene expression patterns in the fetal brain. Translational Psychiatry. 2012;2(4):e98–e. doi: 10.1038/tp.2012.24 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref041] 41.Catale C, Lo Iacono L, Martini A, Heil C, Guatteo E, Mercuri NB, et al. Early Life Social Stress Causes Sex- and Region-Dependent Dopaminergic Changes that Are Prevented by Minocycline. Molecular Neurobiology. 2022;59(6):3913–32. doi: 10.1007/s12035-022-02830-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref042] 42.Uddin MN, Mondal T, Yao Y, Manley K, Lawrence DA. Oxidative stress and neuroimmune proteins in a mouse model of autism. Cell Stress and Chaperones. 2023. doi: 10.1007/s12192-023-01331-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref043] 43.Bethea CL, Kim A, Reddy AP, Chin A, Bethea SC, Cameron JL. Hypothalamic KISS1 expression, gonadotrophin-releasing hormone and neurotransmitter innervation vary with stress and sensitivity in macaques. Journal of neuroendocrinology. 2014;26(5):267–81. Epub 2014/03/13. doi: 10.1111/jne.12146 ; PubMed Central PMCID: PMC4012296. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref044] 44.Nair BB, Khant Aung Z, Porteous R, Prescott M, Glendining KA, Jenkins DE, et al. Impact of chronic variable stress on neuroendocrine hypothalamus and pituitary in male and female C57BL/6J mice. Journal of neuroendocrinology. 2021;33(5):e12972. doi: 10.1111/jne.12972 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref045] 45.Sunwoo J-S, Jeon D, Lee S-T, Moon J, Yu J-S, Park D-K, et al. Maternal immune activation alters brain microRNA expression in mouse offspring. Annals of Clinical and Translational Neurology. 2018;5(10):1264–76. doi: 10.1002/acn3.652 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref046] 46.Hu Y, Korovaichuk A, Astiz M, Schroeder H, Islam R, Barrenetxea J, et al. Functional Divergence of Mammalian TFAP2a and Tfap2b Transcription Factors for Bidirectional Sleep Control. Genetics. 2020;216(3):735–52. doi: 10.1534/genetics.120.303533 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref047] 47.van Zeijl CJJ, Surovtseva OV, Wiersinga WM, Fliers E, Boelen A. Acute Inflammation Increases Pituitary and Hypothalamic Glycoprotein Hormone Subunit B5 mRNA Expression in Association with Decreased Thyrotrophin Receptor mRNA Expression in Mice. Journal of neuroendocrinology. 2011;23(4):310–9. doi: 10.1111/j.1365-2826.2011.02116.x [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref048] 48.Alhassen S, Chen S, Alhassen L, Phan A, Khoudari M, De Silva A, et al. Intergenerational trauma transmission is associated with brain metabotranscriptome remodeling and mitochondrial dysfunction. Communications Biology. 2021;4(1):783. doi: 10.1038/s42003-021-02255-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref049] 49.Li XF, Kinsey-Jones JS, Knox AMI, Wu XQ, Tahsinsoy D, Brain SD, et al. Neonatal Lipopolysaccharide Exposure Exacerbates Stress-Induced Suppression of Luteinizing Hormone Pulse Frequency in Adulthood. Endocrinology. 2007;148(12):5984–90. doi: 10.1210/en.2007-0710 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref050] 50.Esquifino AI, Chacón F, Jimenez V, Reyes Toso CF, Cardinali DP. 24-hour changes in circulating prolactin, follicle-stimulating hormone, luteinizing hormone and testosterone in male rats subjected to social isolation. Journal of Circadian Rhythms. 2004;2(1):1. doi: 10.1186/1740-3391-2-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref051] 51.Richetto J, Chesters R, Cattaneo A, Labouesse MA, Gutierrez AMC, Wood TC, et al. Genome-Wide Transcriptional Profiling and Structural Magnetic Resonance Imaging in the Maternal Immune Activation Model of Neurodevelopmental Disorders. Cerebral Cortex. 2016;27(6):3397–413. doi: 10.1093/cercor/bhw320 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref052] 52.Ibi D, Nagai T, Kitahara Y, Mizoguchi H, Koike H, Shiraki A, et al. Neonatal polyI:C treatment in mice results in schizophrenia-like behavioral and neurochemical abnormalities in adulthood. Neuroscience Research. 2009;64(3):297–305. doi: 10.1016/j.neures.2009.03.015 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref053] 53.Izvolskaia M, Sharova V, Zakharova L. Perinatal Inflammation Reprograms Neuroendocrine, Immune, and Reproductive Functions: Profile of Cytokine Biomarkers. Inflammation. 2020;43(4):1175–83. doi: 10.1007/s10753-020-01220-1 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref054] 54.Haddad F, Patel S, Schmid S. Maternal immune activation by Poly I: C as a preclinical model for neurodevelopmental disorders: a focus on autism and schizophrenia. Neuroscience & Biobehavioral Reviews. 2020. doi: 10.1016/j.neubiorev.2020.04.012 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref055] 55.Southey BR, Keever-Keigher MR, Rymut HE, Rund LA, Johnson RW, Rodriguez-Zas SL. Disruption of Alternative Splicing in the Amygdala of Pigs Exposed to Maternal Immune Activation. Immuno. 2021;1(4):499–517. doi: 10.3390/immuno1040035 [DOI] [Google Scholar]

[pone.0292952.ref056] 56.Tsivion-Visbord H, Kopel E, Feiglin A, Sofer T, Barzilay R, Ben-Zur T, et al. Increased RNA editing in maternal immune activation model of neurodevelopmental disease. Nature Communications. 2020;11(1):5236. doi: 10.1038/s41467-020-19048-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref057] 57.Canales CP, Estes ML, Cichewicz K, Angara K, Aboubechara JP, Cameron S, et al. Sequential perturbations to mouse corticogenesis following in utero maternal immune activation. eLife. 2021;10:e60100. doi: 10.7554/eLife.60100 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref058] 58.Aguilar-Valles A, Flores C, Luheshi GN. Prenatal inflammation-induced hypoferremia alters dopamine function in the adult offspring in rat: relevance for schizophrenia. PloS one. 2010;5(6):e10967. doi: 10.1371/journal.pone.0010967 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref059] 59.Hökfelt T, Barde S, Xu Z-QD, Kuteeva E, Rüegg J, Le Maitre E, et al. Neuropeptide and Small Transmitter Coexistence: Fundamental Studies and Relevance to Mental Illness. Frontiers in Neural Circuits. 2018;12. doi: 10.3389/fncir.2018.00106 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref060] 60.Hui CW, Vecchiarelli HA, Gervais É, Luo X, Michaud F, Scheefhals L, et al. Sex Differences of Microglia and Synapses in the Hippocampal Dentate Gyrus of Adult Mouse Offspring Exposed to Maternal Immune Activation. Frontiers in Cellular Neuroscience. 2020;14(331). doi: 10.3389/fncel.2020.558181 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref061] 61.Kirsten TB, Chaves GP, Taricano M, Martins DO, Flório JC, de Britto LRG, et al. Prenatal LPS exposure reduces olfactory perception in neonatal and adult rats. Physiology & Behavior. 2011;104(3):417–22. doi: 10.1016/j.physbeh.2011.04.049 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref062] 62.Yuan T-F, Hou G, Arias-Carrion O. Chronic stress impacts on olfactory system. CNS & Neurological Disorders-Drug Targets (Formerly Current Drug Targets-CNS & Neurological Disorders). 2015;14(4):486–91. doi: 10.2174/1871527314666150429111356 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref063] 63.Ayash S, Lingner T, Ryu S, Kalisch R, Schmitt U, Müller MB. Reconceptualising resilience within a translational framework is supported by unique and brain-region specific transcriptional signatures in mice. bioRxiv. 2020:2020.11.15.383489. doi: 10.1101/2020.11.15.383489 [DOI] [Google Scholar]

[pone.0292952.ref064] 64.Cyrus SS, Cohen ASA, Agbahovbe R, Avela K, Yeung KS, Chung BHY, et al. Rare SUZ12 variants commonly cause an overgrowth phenotype. American Journal of Medical Genetics Part C: Seminars in Medical Genetics. 2019;181(4):532–47. doi: 10.1002/ajmg.c.31748 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref065] 65.Bristy SA, Islam AMH, Andalib KMS, Khan U, Awal MA, Rahman MH. Determination of molecular signatures and pathways common to brain tissues of autism spectrum disorder: Insights from comprehensive bioinformatics approach. Informatics in Medicine Unlocked. 2022;29:100871. doi: 10.1016/j.imu.2022.100871 [DOI] [Google Scholar]

[pone.0292952.ref066] 66.Gadad BS, Raj P, Jha MK, Carmody T, Dozmorov I, Mayes TL, et al. Association of Novel ALX4 Gene Polymorphisms with Antidepressant Treatment Response: Findings from the CO-MED Trial. Complex Psychiatry. 2018;4(1):7–19. doi: 10.1159/000487321 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref067] 67.He T, Shang J, Gao C, Guan X, Chen Y, Zhu L, et al. A novel SIRT6 activator ameliorates neuroinflammation and ischemic brain injury via EZH2/FOXC1 axis. Acta Pharmaceutica Sinica B. 2021;11(3):708–26. doi: 10.1016/j.apsb.2020.11.002 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref068] 68.You X, Liu M, Liu Q, Li H, Qu Y, Gao X, et al. miRNA let-7 family regulated by NEAT1 and ARID3A/NF-κB inhibits PRRSV-2 replication in vitro and in vivo. PLOS Pathogens. 2022;18(10):e1010820. doi: 10.1371/journal.ppat.1010820 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref069] 69.Wang J, Lee S, Teh CE-Y, Bunting K, Ma L, Shannon MF. The transcription repressor, ZEB1, cooperates with CtBP2 and HDAC1 to suppress IL-2 gene activation in T cells. International Immunology. 2009;21(3):227–35. doi: 10.1093/intimm/dxn143 [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref070] 70.Li H, Zhang C, Yang C, Blevins M, Norris D, Zhao R, et al. C-terminal binding proteins 1 and 2 in traumatic brain injury-induced inflammation and their inhibition as an approach for anti-inflammatory treatment. International journal of biological sciences. 2020;16(7):1107–20. Epub 2020/03/17. doi: 10.7150/ijbs.42109 ; PubMed Central PMCID: PMC7053329. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref071] 71.Ivanov II, McKenzie BS, Zhou L, Tadokoro CE, Lepelley A, Lafaille JJ, et al. The orphan nuclear receptor RORgammat directs the differentiation program of proinflammatory IL-17+ T helper cells. Cell. 2006;126(6):1121–33. Epub 2006/09/23. doi: 10.1016/j.cell.2006.07.035 . [DOI] [PubMed] [Google Scholar]

[pone.0292952.ref072] 72.Roszkowska M, Krysiak A, Majchrowicz L, Nader K, Beroun A, Michaluk P, et al. SRF depletion in early life contributes to social interaction deficits in the adulthood. Cellular and Molecular Life Sciences. 2022;79(5):278. doi: 10.1007/s00018-022-04291-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292952.ref073] 73.Golovina E, Fadason T, Lints TJ, Walker C, Vickers MH, O’Sullivan JM. Understanding the impact of SNPs associated with autism spectrum disorder on biological pathways in the human fetal and adult cortex. Scientific Reports. 2021;11(1):15867. doi: 10.1038/s41598-021-95447-z [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Prenatal and postnatal challenges affect the hypothalamic molecular pathways that regulate hormonal levels

Sandra L Rodriguez-Zas

Nicole L Southey

Laurie Rund

Adrienne M Antonson

Romana A Nowak

Rodney W Johnson

Roles

Abstract

Introduction

Materials and methods

Results

Hypothalamic biological processes and genes networks associated with challenges and sex effects

Table 1. Enriched Gene Ontology (GO) biological processes, including at least 10 genes differentially expressed (False Discovery Rate FDR-adjusted p value < 0.05) in response to maternal immune activation, nursing withdrawal, sex, or interactions.

Table 2. Log2(fold change) of the differentially (False Discovery Rate FDR-adjusted p value < 0.05) expressed genes (#) for the effects of maternal immune activation (MIA), nursing withdrawal (Nur), sex, and interactions (-) annotated to enriched Gene Ontology biological processes (BP).

Gene set and regulatory enrichment analysis of differentially expressed genes in the hypothalamus

Fig 4. Relationship between transcription factors (rectangles) and differentially expressed target genes (ellipses) annotated to the enriched (False Discovery Rate FDR-adjusted p value < 0.001) Gene Ontology biological process regulation of hormone levels (GO:0010817).

Discussion

Hypothalamic biological processes and genes networks associated with challenges and sex effects

Gene set and regulatory enrichment analysis of differentially expressed genes in the hypothalamus

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Dragan Hrncic

Roles

Author response to Decision Letter 0

Decision Letter 1

Dragan Hrncic

Roles

Author response to Decision Letter 1

Decision Letter 2

Dragan Hrncic

Roles

Acceptance letter

Dragan Hrncic

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Table 2. Log₂(fold change) of the differentially (False Discovery Rate FDR-adjusted p value < 0.05) expressed genes (^#) for the effects of maternal immune activation (MIA), nursing withdrawal (Nur), sex, and interactions (-) annotated to enriched Gene Ontology biological processes (BP).