Background
Increasing evidence highlights the involvement of immune dysfunction in the complex mental diseases, such as schizophrenia and autism spectrum disorder, in which genetic predisposition(s) requires additional environmental impact(s) to determine the progression of pathophysiology [
1,
2]. Maternal immune activation has been shown to induce neuroinflammation and schizophrenic/autistic phenotypes in both humans and other species [
3-
8]. Accumulating genetic evidence has recently also provided support on the association of immune genes with psychiatric diseases [
1,
9]. Among the major disease manifestations, social deficit is a core symptom that negatively influences the lives of psychiatric patients. In fact, social behavior has been intimately associated with infections and inflammatory diseases in human evolution [
10-
12].
In animal research, a handful of studies have revealed the association of immune activation and immune genes with social and emotional behaviors [
13-
16]. For instance, triggering immune defenses in pregnant monkeys can lead to social problems in their offspring [
17]. Recently, microglia as a major source of immune genes in the brain has been extensively reported to regulate the brain functional connectivity and behavior [
18-
21]. Moreover, immune-related genes, such as the major histocompatibility complex (MHC) molecules, complements and their receptors, are known to be expressed in the brain and regulate brain structural and functional plasticity, either directly or indirectly by controlling microglial or immune activation [
22-
24]. Therefore, the potential association of social behavior with immune genes in the brain becomes an outstanding question. However, although a few immune genes have been discovered, it is predictable that a complex social behavior is associated with not only a singular, but rather a network of different genes that may have a relatively weak effect size individually. In this respect, addressing how various immune genes may jointly regulate sociability is of upmost relevance and importance but has not been fully investigated so far.
Due to ethical and empirical limitations in clinical studies, rodent models have proven to be highly useful in characterizing the mechanisms of psychiatric diseases. Multiple genetically different inbred mouse strains exist and many exhibit clear and reliable differences in learning and memory [
25], sensorimotor gating [
26], and anxiety [
25,
27,
28], resembling the neuropsychiatric endophenotypes [
28-
30]. Such strain differences offer clues to decipher genetic and gene × environmental influences on behaviors. In this regard, we have recently used such strategy to characterize the association of microglial activation with anxiety [
28]. Deficit in sociability may also represent a key feature among some of these inbred strains. However, approaches used to study social behaviors and results on inbred mouse strains are still very limited. A previous study suggested less significant sociability and social novelty preference of the male DBA/2 J strain than the C57BL/6 J strain [
31]. Similarly, we recently found that female DBA/2 J mice were significantly less active in social interaction, as compared to C57BL/6 J female mice, but we had not explored male mice in that study [
32]. It is therefore necessary to more fully characterize the differences in social behaviors of inbred strains and to explore further the usefulness of this strategy to discover the underlying mechanisms.
To more elaborately address the immune-mediated mechanisms in social deficiency, we took an unbiased evidence-driven strategy by analyzing the publicly available genotypic and phenotypic data of several male inbred mouse strains with bioinformatics approaches. We first made the gene expression profiling by using online brain DNA microarray data and selected candidate genes for functional clustering analysis. To predict the association of the interested genes with the brain development and behaviors, we aligned their expression data with the online behavioral data. Lastly, we examined the C57BL/6 J and DBA/2 J mouse strains that displayed significant differences in social behaviors to validate the expression of the major candidate genes and their association with social behaviors.
Materials and methods
Animals
Seven-week-old male mice from two inbred strains, C57BL/6 J (n = 8) and DBA/2 J (n = 8), were purchased from a single supplier, Harlan Laboratories (The Netherlands), to avoid a possible source of variation. The mice were single-housed in standard cages with aspen chips bedding and nesting materials, food, and water available ad libitum and under a 12-h light/dark cycle (lights on 6.00 to 18.00). Animals were acclimated to the environment for 3 weeks before experiments. The research was performed with permission by the National Animal Experiment Board of Finland.
Resident-intruder test
For assessment of reciprocal social behavior, tested animals (residents) were in their home cages. An unfamiliar intruder mouse of the same strain, gender, and age (Harlan Laboratories) was placed into the resident’s cage, and mice interaction was recorded by a video camera for 5 min. Time spent by the resident in social behavior (sniffing, chasing, following, and heterogrooming) was evaluated.
Three-chambered sociability test
The inbred mice were individually tested in a three-chambered apparatus as described previously [
33]. The test apparatus consisted of three rectangular chambers (18 × 35 × 18 cm) divided by Plexiglas walls with openings (6 × 5 cm) allowing the animal to move between chambers. Both side chambers contained an empty transparent Plexiglas holder (8 cm in diameter, 10 cm high, with small holes allowing snout contact but not biting or fighting between the animals). A test mouse was first released in the central chamber and was allowed to habituate to the apparatus for 10 min. An unfamiliar gender- and age-matched stranger mouse of the FVB strain (Harlan Laboratories) was then placed in one of the holders. Location of the stranger mouse in either of the two holders (the social chamber) varied systematically between trials. The test mouse was allowed to explore the whole apparatus for 10 min. Time spent in sniffing of each holder was recorded by a video camera.
Inbred mice brain microarray data processing and differential expression analysis
Whole brain microarray datasets of 10 ~ 12-week old male mice of eight inbred strains (129S1/SvImJ:
n = 5, A/J:
n = 4, BALB/cByJ:
n = 5, C3H/HeJ:
n = 5, C57BL/6 J:
n = 5, DBA/2 J:
n = 5, FVB/NJ:
n = 5, and SJL/J:
n = 4), which were produced in an Affymetrix 3’ 430_2.0 platform [
34], were selected from the PhenoGen Informatics Database (University of Colorado and Denver Health Sciences Center, Denver, CO, USA) after quality control of their integrities. Arrays were grouped according to the strains and normalized by the RMA method. Differential expression was done by using the analytical tool in PhenoGen Informatics. Probes in the dataset were first filtered through the MSA5 absolute call filter, and those present in at least 75% of the samples were kept. One-way analysis of variance (ANOVA) was used for statistical evaluation.
P values were further adjusted with the Benjamini and Hochberg method for multiple test
post hoc correction with FDR
= 1E − 7. A list of differentially expressed genes and their statistical data were finally downloaded from Phenogen Informatics for further bioinformatics analyses.
Functional annotation clustering of differentially expressed brain genes and protein-protein interaction network analysis
Differentially expressed genes were imported into the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources [
35] and analyzed by the functional annotation tool therein to get the most significant gene clusters according to their gene ontology terms (GO_biological process, cellular component, and molecular function). Clustering of annotated genes was done with the medium classification stringency and under the default statistical settings. Twenty-three top innate immune genes were further analyzed for their direct and indirect protein-protein interaction networks by the STRING v9.1 [
36] and for their phenotypic correlations in the Mouse Phenome Database (MPD) [
37].
Online correlational analysis of immune genes with mice behaviors and brain morphology
Mean expression values of the brain immune genes across the eight inbred mouse strains were fed into MPD’s correlational analysis tool (Pearson’s), to be aligned with the data on mouse psychiatry-related behaviors, including anxiety-related, exploratory, fear conditioning, learning and social behaviors, and on brain morphologies. Pearson’s co-efficients were set at |
r| ≥ 0.7,
P < 0.05. Behavioral and brain morphological data on the eight inbred strains were then retrieved from the MPD with the corresponding registration numbers (MPD #118 for anxiety, #108 for brain morphology, #94 for exploratory behavior, #468 for fear conditioning) [
38-
43].
Total RNA isolation and real-time qPCR
The mice were deeply anesthetized with pentobarbital (Orion Pharma, Helsinki, Finland) for about 5 min, and the prefrontal cortex (PFC), hypothalamus, and hippocampus were dissected after intra-cardiac perfusion, immediately frozen in liquid nitrogen, and kept at −80°C. Total RNAs from the tissues were extracted by using GeneJET RNA Purification Kit (Thermo Scientific (Inc.), Helsinki, Finland) and reversely transcribed (1 μg) with RevertAid First Strand cDNA Synthesis Kit (Thermo Scientific). RT-qPCR was performed by using corresponding primers and Maxima SYBR Green Master Mixes (Thermo Scientific) on a CFX384 Real-Time PCR Detection System (Bio-Rad, Helsinki, Finland) according to the manufacturer’s instructions. The forward and reverse primers used for target genes were listed below. Relative fold change was calculated by first normalization with the reference gene Gapdh and then against the level in C57BL/6 J and presented as 2-ΔΔCT. No strain difference in Gapdh and another reference gene Actb was observed (data not shown).
Gene Primers
Tnfsf13b For: 5′-GAC TGT CTG CAG CTG ATT GC-3′
Rev: 5′-CCT CCA AGG CAT TTC CTC TT-3′
C1qb For: 5′-TCT GGG AAT CCA CTG CTG TC-3′
Rev: 5′-AGA CCT CAC CCC ACT GTG TC-3′
H2-d1 For: 5′-GATGCAGAGCATTACAGGGC-3′
Rev: 5′-GCCAGGTCAGGGCAATGTC-3′
Polr3b For: 5′-AGACAAATTCAGCAGTCGCC-3′
Rev: 5′-GGGTTCATTATGATGTCGGG-3′
Gapdh For: 5′-TGT TCC TAC CCC CAA TGT GT-3′
Rev: 5′-TGT GAG GGA GAT GCT CAG TG-3′
Statistical analysis
Normality was evaluated by the D’Agostino and Pearson omnibus test. Student’s t test was used for analysis of the resident-intruder and three-chambered test data. qPCR data for immune genes were analyzed by two-way analysis of variance (ANOVA) with Bonferroni’s post hoc test. Correlations of the candidate gene mRNA levels with the percentages of social time in the resident-intruder and three-chambered tests were analyzed by Pearson’s method. Results are presented as mean ± SEM. P < 0.05 was considered to be significant.
Discussion
In this study, we combined unbiased bioinformatics with targeted experimental approaches to address what and how immune genes may affect social behaviors in inbred mice, and we discovered several candidate immune genes, such as H2-d1, C1qb, Polr3b, and Tnfsf13b, and the gene networks that they represent. Our data implied the possible involvement of these immune genes in regulating social behavior; the deficit of which is a core symptom of several neuropsychiatric diseases, such as schizophrenia and autism spectrum disorder.
Inbred mouse strains have been extensively used for behavioral research and represent a valid model for studying social behaviors relevant to human neuropsychiatric diseases. We speculated that various immune genes in the brains of different inbred mouse strains may contribute to differences in their behaviors, such as the ability of making social interactions. To test this hypothesis, we started with an analysis of the whole brain Affymetrix microarray data on these strains provided by Phenogen Informatics. Such strategy is based on the notion that gene functions are closely associated with their expression levels. Next, by predicting the association of gene expression with brain morphology and behaviors from the online database, we targeted six differentially expressed immune genes, and we later validated them in the brain regions of the male DBA/2 J and C57BL/6 J mice by RT-qPCR. Out of the six genes, C1qb, H2-d1, Polr3b
, and Tnfsf13b were validated. In particular, we found that H2-d1 was significantly decreased in all of the tested brain regions - PFC, hippocampus, and hypothalamus - of DBA/2 J mice, while C1qb, Polr3b and Tnfsf13b may play region-specific roles in the brain.
We further examined the associations of these immune genes with social behaviors among the C57BL/6 J and DBA/2 J mice. Of particular note, the C1qb gene was significantly positively associated with the sociability in the DBA/2 J mice, not in the C57BL/6 J mice. This strain-dependent association may be due to the lower expression of C1qb in the hippocampus of DBA/2 J than in C57BL/6 J, as the higher threshold of C1qb expression in the C57BL/6 J mice may disrupt the linear relationship between gene expression and behavioral output in this strain. Additionally, the average expression of H2-d1 in the three brain regions was also significantly correlated with sociability in combined strains, but not in separate groups. It should be noted, however, that some of these genes may manifest only a weak effect on the complicate social behavior individually, and therefore, a network of related immune genes may be more relevant to have a joint impact, highlighting the importance of using unbiased approaches to systemically evaluate genetic association with a certain disease feature.
The most significant finding in our study was a cluster of MHCI genes,
H2-d1 in particular, which were differentially expressed in the brains and associated with animal behaviors. Classical MHCI α-chains are encoded by three genes in humans, denoted HLA-A, −B, and -C. In mice, these genes are H2-K, −D, and -L. MHCI molecules are found in an isoform- and region-specific manner throughout the brain [
45]. During the past decade, researchers have provided convincing evidence that, as the classical “immune” proteins, MHCI molecules regulate establishment and function of cortical connections, activity-dependent synaptic refinement and pattern formation, long-term depression and motor learning, and homeostatic plasticity by restriction of immune response [
24,
46,
47]. More importantly, the association of MHCI loci with schizophrenia has been confirmed by several cohorts of GWAS data [
1,
9,
46]. These are corroborated by our findings and support the validation of our approach to find out immune-related genetic mechanisms of social deficit in animal models. However, a detailed investigation is warranted to further examine our data.
C1QB is known to mediate the classical complement cascade for synaptic elimination [
22,
47]. It has been previously demonstrated that retinal C1q expression primes microglia-mediated synaptic pruning during the visual system development [
48]. Recently, C1q was found to mediate the elimination of synapses in the hippocampus in multiple sclerosis, leading to memory impairment in patients [
49]. Here, we found that
C1qb was significantly down-regulated in the hippocampus of the DBA/2 J mice, as compared to the C57BL/6 J mice. Additionally,
C1qb was positively associated with sociability in the DBA/2 J mice. Our data suggests that
C1qb-mediated synaptic pruning may be less effective in the brains of the DBA/2 J mice, which may further result in the lessened sociability of the DBA/2 J mice.
Another target gene in our study was
Polr3b, which was significantly up-regulated in the hippocampus of the DBA/2 J mice. Interestingly, mutations of
POLR3A or
POLR3B are known to be associated with the neurodegenerative hypomyelinating leukodystrophy spectrum disorders in humans [
50-
52]. Besides,
POLR3B was reported to disturb the purine metabolism and contribute to Alzheimer’s disease [
53]. The association of the
Polr3b and its family with social activity of animals has however been unknown so far.
When summarizing the correlated brain structures with various immune genes, we found that one of the most prevalent associations is the length of CC, a key feature of structural abnormality in schizophrenia and autism spectrum disorder. Other inbred mouse strains that show schizophrenia/autism-like endophenotypes, such as 129 and BTBR, are also known to have small or totally absent CC, and have been used to map quantitative trait loci that affect CC size. BTBR strain in particular shows total absence of the CC [
54]. Furthermore, the gene disrupted in schizophrenia 1 (
Disc1) is homozygously inactivated in all 129 mouse substrains, and this genetic mutation may be causally linked to hypo-genesis of CC in these animals [
55]. Our predictions that immune genes are associated with brain morphology could provide valuable information to be validated in the future.
In our analysis, the length of CC is negatively associated with
Tnfsf13b. TNFSF13b (BAFF) is a TNF superfamily member, which acts as a potent B-lymphocyte activator in immune response [
56]. Of note, a recent genetic association study, which collected so far the largest cohort of schizophrenic patients and healthy controls, has discovered a significant association of immune genes other than the MHCI loci with schizophrenia and revealed a particular enrichment of genes of B-lymphocyte lineage [
1]. Association of B-cell activation-related immune genes with schizophrenia, major depression, and bipolar disorder was also observed in another most recent genetic study [
9]. Moreover, a gene involved in B-cell receptor signaling pathway (
PPP3CC) was suggested to mediate antidepressant response in another pharmacogenetic study [
57].
Previous to our work, several immune genes in the brain have been shown to regulate emotional and/or social behaviors of animals. The cytokine interleukin-6 was found to be a critical mediator for the maldevelopment of the fetal brain and the social deficits in the offspring of maternally immune-challenged mice [
14], while interleukin-1β was not involved in a similar paradigm [
15]. CD38, a transmembrane glycoprotein involved in immune response, has been demonstrated to mediate abnormal oxytocin secretion, maternal nurturing, and social behavior in autism [
16]. Another previous study has described a distinct compulsive behavioral phenotype caused by a mutant gene
Hoxb8 that exclusively labels microglia in the brain [
21].The results that we provide here help extend the knowledge on the immune-mediated mechanisms of social behavior.
However, our study has several limitations to be considered. Firstly, although we found significant correlations of several immune genes with social behaviors, correlation does not imply causation. Therefore, cautions are called for the interpretation of our data, and more stringent researches to examine the roles of these candidate immune genes are needed. Secondly, some discrepancy between the microarray and RT-qPCR data existed here. For example, we failed to validate the expressions of
Cx3cl1 and
H2-k1. This may be due to that RT-qPCR is generally more sensitive than microarray but at the same time may cause polymerization bias. And the probes utilized in microarray assay are different from those in RT-qPCR. Moreover, gene expression in the whole brain as detected by microarray may not necessarily parallel with that in the separate brain regions as detected by qPCR in this study. Thirdly, most researches on C57BL/6 and DBA/2 strains focus on male mice, and so did ours. There have been few studies on female mice so far. But gender-specific effect of immune genes on behaviors could exist [
58] and is needed to be addressed in the future.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
LM performed the experiments, analyzed and interpreted the data, and drafted the manuscript. LT designed the study, carried out the bioinformatics analysis, and drafted the manuscript. SP performed the behavioral experiments. NK helped design the behavioral tests. HR supported the project and proofread the manuscript. All authors read and approved the final manuscript.