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Maternal immune activation during pregnancy impacts on resting state functional connectivity in the adult offspring
Silke Kreitz1, Alice Zambon2, Marianne Ronovsky2, Lubos Budinsky3, Thomas Helbich3, Spyros Sideromenos2, Claudiu Ivan1, Laura Christina Konerth1, Isabel Wank1, Angelika Berger4, Arnold Pollak4, Andreas Hess1, and Daniela D. Pollak2

1Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich Alexander University Erlangen-Nuremberg, Erlangen, Germany, 2Department of Neurophysiology and Neuropharmacology, Medical University of Vienna, Vienna, Austria, 3Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria, 44Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria

Synopsis

The infection of the pregnant female and the ensuing induction of maternal immune activation affect fetal development with long-lasting consequences for health and disease. Specifically aberrant neural wiring may contribute in the manifestation of psychiatric disorders such as depression. Here, we investigated altered resting state functional connectivity using fMRI in adult mice after prenatal immune activation. While the overall flow of information was intact, especially the cortico-limbic connectivity was disrupted in resting state networks of adult offspring. We propose that these altered connectivity patterns may lead to behavioral and emotional abnormalities with relevance for neuropsychiatric disorders.

Introduction

Gestational infection constitutes a risk factor for the occurrence of psychiatric disorders in offsprings1. Activation of the maternal immune system with subsequent impact on the development of the fetal brain is considered to form the neurobiological basis for aberrant neural wiring and the psychiatric manifestations later in offspring life2. Here we used a validated animal model to investigate the impact of maternal immune activation (MIA) particularly on adult offspring resting state functional connectivity.

Methods

Pregnant C57Bl6/N mice were injected intraperitoneally at embryonic day 12.5 either with Poly(I:C) (= polyriboinosinic-polyribocytidilic acid), a synthetic analog of virus-specific double-stranded RNA, to induce MIA or with 0.9% NaCl (Saline) as vehicle control. Functional connectivity was assessed with resting state functional MRI (RS-fMRI) in the 3 month old offspring. RS-fMRI data were acquired with a T2*-weighted single-shot gradient echo-based Echo Planar Imaging sequence (GE-EPI) covering 22 axial slices of the brain in 2 seconds (600 volumes, total time 10 minutes, TEef=15 ms, TR=2000 ms, matrix 94x64, FOV 15x15 mm, slice thickness 0.5 mm). The measured matrix was reconstructed by zero filling to 128x128 pixels resulting in a final resolution of 117x117x500 µm. Standard preprocessing was performed including inter-slice time and motion correction, spatial gaussian smoothing (FWHM 0.58 mm), low pass filtering at 0.1 Hz and regression of the global mean. Brain voxels were labeled individually for each animal as belonging to 211 pain related brain structures based on the mouse atlas from Franklin and Paxinos3. For RS data analysis the average time course of each seed region was correlated with every voxel in the brain. After defining the FDR corrected significant correlation voxels an asymmetric correlation matrix was created for each subject using for each seed region the mean significant correlation values of all brain structures (MSRA)4. Resulting group average networks were thresholded at K=10 (resulting in same density, on average 10 connections per node). Group average network communities were detected using a heuristic method based on modularity optimization5. Additionally, on those networks small world index σ6 and the node specific graph-theoretical parameters degree, clustering coefficient, average shortest path length7,and hub score8 were calculated per animal. To assess group specific effects a two factor ANOVA (treatment, brain structures) with interaction was performed on node specific graph-theoretical parameters. Differences in connectivity strength between groups were calculated using network based statistics (NBS)9.

Results

First, it appears that the overall effectiveness of information flow in Poly(I:C) mice was intact. We did not observe differences in σ, and also the hub functionality was similar between both groups. However, analysis of node specific community association (Fig. 1) and connectivity strength (Fig. 2) revealed significant differences. Significant increases in connectivity strength could be found mainly in limbic circuits (amygdala, habenulae/septum, basal ganglia, and hypothalamus), brainstem-cerebellum connections, and between visual/auditory cortex and structures of the posterior association as well as somatosensory cortex. However, the thalamic connections, especially to the cortex, and somatosensory to cerebellum were significantly weakened in MIA offspring (Fig. 2). These changes strongly suggest a weakening in cortico-limbic connectivity. Referring to resting state networks derived from ICA analysis known especially from human10 but also from rodent11 studies, dominant connectivity modulation could be observed within the saliency, the sensorimotor and the default mode network (Fig. 2A). ANOVA on node specific graph-theoretical parameters revealed a treatment effect only in average shortest path length and only degree showed significant interactions (Table 1). Therefore, clustering coefficient and hub score did not account for group differences between RS of Poly(I:C) offspring and control animals. Degree was enhanced in olfactory input, brain stem, amygdala, nucleus accumbens, and in thalamus and decreased in paraventricular thalamus, primary somatosensory cortex, insula, parietal association and retrosplenial cortex (Fig. 3A). Path length was especially enhanced in structures of brain stem (medulla) and sensory cortex indicating enhanced segregation of these brain areas. In general dorsal thalamic structures showed increased and ventral decreased path length (Fig. 3B). Again, all these findings point towards higher segregation of cortical-limbic functional connectivity due to MIA.

Discussion

The remarkable dysfunction in cortical-limbic connectivity circuits in Poly(I:C) mice is particularly noteworthy in light of the well-documented alterations in the cortical-limbic mood-regulating circuitry in patients suffering from mood disorders12,13. The observed hyper-connectivity within limbic circuits, encompassing the amygdala, habenulae/septum, basal ganglia, and hypothalamus in Poly(I:C) mice may be considered a result of deficient top-down inhibition by cortical areas resulting from the aberrant cortico-limbic connectivity. The strengthened brainstem-cerebellum, intra-brainstem and intra-cortical connections could reflect adaptive responses indicating functional rearrangements in response to the neurodevelopmental insult of MIA.

Acknowledgements

This work was supported by the Austrian Science Fund (stand-alone project P 27520 to D.D.P), BMBF NeuroRad (02NUK034D) and BMBF NeuroImpa (01EC1403C) to A.H. and “Verein unser Kind” to A.B. We thank Johannes Kaesser, Jutta Prade and Sandra John for their excellent technical support.

References

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Figures

Fig. 1: Forced based plot of average resting-state networks with an average node degree (K) of 10 of animals treated with saline or Poly(I:C). Communities of connected brain areas are indicated with outlines (solid outlines: hierarchy level 1, dashed outlines: hierarchy level 0). Node sizes represent their degree (i.e. the number of connections).

Fig. 2: Significantly altered connections due to treatment with Poly(I:C). A) Significant NBS component (a=0.05, whole component p=0.023), overlaid on the forced based plot of the average control RS network. Node size encodes degree. Bold lines depict intrinsic RS networks. B) Schematic representation of the NBS component with individual structures grouped to functional groups and their accordingly summed connections. Node size codes strength, i.e. sum of all correlation values of connections between functional groups. Line thickness codes connectivity weights, i.e. sum of all correlation values of connections between (lines) and within functional groups (semi circles).

Table 1: ANOVA results for resting state network node parameters.

1 Since degree and hub score are normalized to the same mean for both experimental groups, treatment effect F-value is 0.

* significance p<0.05, highlighted bold



Fig. 3: Significant modulated (ANOVA, see Table 1) graph-theoretical node parameters degree and average path length for RS networks of the offspring of dams treated either with Poly(I:C) or saline. A) spider charts, B) significantly modulated brain structures and their contralateral counterparts (post-hoc t-test, p<0.05, uncorrected).

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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