Anti-angiogenic mechanisms and serotonergic dysfunction in the Rgs2 knockout model for the study of psycho-obstetric risk

Serena B Gumusoglu; Michaela D Kiel; Aleigha Gugel; Brandon M Schickling; Kaylee R Weaver; Marisol C Lauffer; Hannah R Sullivan; Kaylie J Coulter; Brianna M Blaine; Mushroor Kamal; Yuping Zhang; Eric J Devor; Donna A Santillan; Stephanie C Gantz; Mark K Santillan

doi:10.1038/s41386-023-01749-3

. 2023 Oct 17;49(5):864–875. doi: 10.1038/s41386-023-01749-3

Anti-angiogenic mechanisms and serotonergic dysfunction in the Rgs2 knockout model for the study of psycho-obstetric risk

Serena B Gumusoglu ^1,², Michaela D Kiel ¹, Aleigha Gugel ^2,³, Brandon M Schickling ¹, Kaylee R Weaver ¹, Marisol C Lauffer ^2,⁴, Hannah R Sullivan ¹, Kaylie J Coulter ¹, Brianna M Blaine ¹, Mushroor Kamal ¹, Yuping Zhang ¹, Eric J Devor ¹, Donna A Santillan ¹, Stephanie C Gantz ^2,³, Mark K Santillan ^1,^✉

PMCID: PMC10948883 PMID: 37848733

Abstract

Psychiatric and obstetric diseases are growing threats to public health and share high rates of co-morbidity. G protein-coupled receptor signaling (e.g., vasopressin, serotonin) may be a convergent psycho-obstetric risk mechanism. Regulator of G Protein Signaling 2 (RGS2) mutations increase risk for both the gestational disease preeclampsia and for depression. We previously found preeclampsia-like, anti-angiogenic obstetric phenotypes with reduced placental Rgs2 expression in mice. Here, we extend this to test whether conserved cerebrovascular and serotonergic mechanisms are also associated with risk for neurobiological phenotypes in the Rgs2 KO mouse. Rgs2 KO exhibited anxiety-, depression-, and hedonic-like behaviors. Cortical vascular density and vessel length decreased in Rgs2 KO; cortical and white matter thickness and cell densities were unchanged. In Rgs2 KO, serotonergic gene expression was sex-specifically changed (e.g., cortical Htr2a, Maoa increased in females but all serotonin targets unchanged or decreased in males); redox-related expression increased in paraventricular nucleus and aorta; and angiogenic gene expression was changed in male but not female cortex. Whole-cell recordings from dorsal raphe serotonin neurons revealed altered 5-HT1A receptor-dependent inhibitory postsynaptic currents (5-HT1A-IPSCs) in female but not male KO neurons. Additionally, serotonin transporter blockade by the SSRI sertraline increased the amplitude and time-to-peak of 5-HT1A-IPSCs in KO neurons to a greater extent than in WT neurons in females only. These results demonstrate behavioral, cerebrovascular, and sertraline hypersensitivity phenotypes in Rgs2 KOs, some of which are sex-specific. Disruptions may be driven by vascular and cell stress mechanisms linking the shared pathogenesis of psychiatric and obstetric disease to reveal future targets.

Subject terms: Neuroscience, Physiology

Introduction

Perinatal mood and psychiatric disorders are a significant and growing public health concern. Rates of new-onset major depressive disorder in pregnancy increased seven-fold in the last two decades to approximately 1:7 [1–3], and suicide is the leading cause of postpartum death in the United States [4, 5]. Risk factors influencing this precipitous rise include increased awareness/diagnosis, poor social supports, sociodemographic and maternal stress, and increased maternal morbidity; many of these were exacerbated during the COVID-19 pandemic [6–9]. Pregnancy-specific mechanisms of depression remain unclear, however, limiting clinical treatment and prevention.

Insights into psychiatric mechanisms may be gleaned from the pregnancy literature. For instance, epidemiologic reports find that gestational diseases such as preeclampsia and perinatal psychiatric disease share high rates of co-morbidity [10]. The pregnancy disease preeclampsia, a dangerous and common hypertensive disorder of pregnancy, is associated with increased risk for mood and anxiety disorders [11, 12]. Mood and anxiety disorders also increase preeclampsia risk up to three-fold [13]. This bi-directional risk suggests shared mechanisms that may reveal insights into novel treatment targets [14].

Many risk factors shared by both preeclampsia and psychiatric disease involve G-protein coupled receptor (GPCR) dysfunction. For example, preeclampsia is associated with serotonin signaling deficits across multiple receptor subtypes [15], impaired vascular reactivity to serotonin [16–18], and immunologic perturbation [19]. Many of these mechanisms are shared in psychiatric diseases such as major depressive disorder. Similarly, the GPCR signaling molecule arginine vasopressin (AVP) is increased as early as the first trimester in preeclamptic pregnancies [20, 21] and in postpartum depression [22], causing altered AVP receptor expression across tissues [23] and cardiovascular risk throughout the lifespan [24, 25]. Neuropeptides such as AVP interact with monoaminergic systems including serotonin in the brain and periphery, influencing the impacts of serotonin-selective reuptake inhibitors (SSRIs) on neurochemical and biobehavioral phenotypes [26].

One GPCR signaling factor that regulates serotonergic and vasopressin signaling is the Regulator of G protein Signaling 2 (RGS2). RGS2 is disrupted in preeclampsia and depression [27–29], and RGS2 polymorphisms are linked to preeclampsia [30–32]; RGS2 is down-regulated in preeclamptic placenta [33]. Our prior work reveals that decreased Rgs2 in placenta is sufficient to recapitulate preeclampsia-like phenotypes such as gestation-onset hypertension and placental anti-angiogenesis in mice [29, 33]. Rgs2 KO mice also exhibit uterine artery deficits and GPCR-mediated vasoconstriction [34, 35].

In addition to serving as a vascular risk gene for preeclampsia, neuropsychopharmacology studies reveal that RGS2 dysfunction contributes to animal behaviors relevant to anxiety and depression [28, 36–42], possibly via impacts on serotonergic systems. Rgs2 KO mice have decreased (mRNA) Htr1a and Htr1b expression in the dorsal raphe [43], and disrupted monoamine signaling in hippocampus which is related to sex-specific learning and memory phenotypes [44, 45].

RGS2 influences SSRI efficacy for the treatment of psychiatric disorders. For example, select RGS2 polymorphisms are predictive of substantial clinical benefit from sertraline in individuals with social anxiety disorder [36]. Here, we evaluate the impact of the most prescribed SSRI [46], sertraline, on mouse Rgs2 KO dorsal raphe serotonergic neurons using brain slice electrophysiology. Sertraline was selected given prior clinical data suggesting its significance in the mediation of preeclampsia features including hypertension and pro-inflammation [10, 47, 48], interaction with RGS2 [36], and its exceptionally high affinity for the serotonin transporter (SERT) relative to other neurotransmitter transporters [49].

Given prior work on RGS2 in obstetric disease reveals a critical role in anti-angiogenesis and vascular dysfunction [29, 33, 35], we had the goal here of extending these findings to the brain. We hypothesized that similar vascular mechanisms might also drive behavioral phenotypes in Rgs2 KO mice. We examined conserved regulators of cellular stress and angiogenesis to find that Rgs2-mediated mechanisms disrupt both cerebrovascular structure and brain function more broadly. These results implicate Rgs2-serotonin mechanisms in neurobiological risk and highlight the relevance of GPCR signaling for cerebrovascular health.

Materials and methods

Mice

Mice harboring a null Rgs2 allele (KOs) were recovered from cryopreservation (B6.129P2-RGS2tm1Dgen/Mmnc, MMRRC:011639-UNC), as described previously [33], and backcrossed (12 generations) against C57BL/6 J (Jax) animals. Adult homozygous Rgs2^−/− (KO) and Rgs2^+/+ wildtype (WT) littermate controls were used. Procedures were approved by the University of Iowa Office of the Institutional Animal Care and Use Committee. For additional details, see the Supplementary Materials and Methods.

Behavioral assessments

Adult offspring (12+ weeks of age) were assessed on one task daily during the light cycle, as previously [50–52]. For additional details, see the Supplementary Materials and Methods.

Elevated plus maze

Mice were placed in the center of an elevated plus maze (San Diego Instruments), facing one of the closed arms. The maze was lit to ~210 lux in open arms/center. They were allowed to freely explore the maze for five minutes. Time spent in the open and closed arms and center of the maze were measured and compared to assess anxiety-like behavior, as previously [53].

Open field test

Mice were placed in the center of an open field arena (16 × 16.5 × 12 in, black acrylic, ~110 lux in center) and allowed to freely explore for 30 min. Distance traveled (cm/s) was assessed as a measure of locomotion in five-minute time bins. Anxiety-like behavior was assessed by measuring the time spent in the center versus the periphery of the field (each defined to include 50% of surface area), as previously [51–53].

Y maze

Mice freely explored the three-armed apparatus (San Diego Instruments; 150 lux) for five minutes, as previously [53]. Spontaneous alternations through the maze center were quantified using EthoVision XT software (Noldus). For additional details, see the Supplementary Materials and Methods.

Three-chamber social preference and social novelty preference

As previously [54–57], mice were first habituated (10 min) to the three-chamber social apparatus (10 × 20.5 × 9 in field) under dim lighting conditions (~5 lux) to promote social exploration. For social preference testing, an object (Lego Duplo) was placed into one cup and a sex-, size-, and age-matched “stranger” mouse was placed into the other. Experimental mice were allowed to freely explore for 10 min. Social preference was calculated as social cup exploration: non-social cup exploration time.

For social novelty preference testing, a new stranger mouse in a cup was placed into the chamber that previously contained the original stranger, and the original stranger was moved to the previously nonsocial cup. The experimental mouse was allowed to freely explore for 10 min. Social novelty preference was calculated as novel stranger cup exploration: total social interaction time. For additional details, see the Supplementary Materials and Methods.

Sucrose preference test

Sucrose preference testing followed standard protocols [58]. Mice were moved into static housing and single-housed 48 hours prior to sucrose preference testing. They were given water via a 25 mL serological pipette (gradations every 0.2 mL) modified with a sipper tube for these 48 h. After 48 h, an additional pipette containing 2% sucrose solution was added to the other side of the cage (counterbalanced across mice). Consumption of water and sucrose was measured twice daily for 48 h.

Tail suspension test

Following standard protocols [59], mice were suspended by the tail approximately 20 inches above a table for six minutes. Struggle or mobile time was defined as movement of any limbs or trunk for at least 0.5 s. For additional details, see the Supplementary Materials and Methods.

Tissue collection

Mice were euthanized via CO2 overdose and rapid decapitation. Brains were dissected and hemisectioned; one half was fixed (4% PFA) then cryopreserved (20% sucrose) for coronal cryosectioning at 20 μm (Leica) for immunohistochemistry and the other half was coronally sectioned at 100μm using a plexiglass mold for tissue punches. Punches were taken of isocortex (somatomotor areas), hypothalamic paraventricular nucleus (PVN), midbrain (at the dorsal raphe nucleus), and hindbrain (medulla) [49]. Aortas were dissected fresh, cleaned of adventitia, and flash frozen for molecular studies. For additional details, see the Supplementary Materials and Methods.

Quantitative polymerase chain reaction (qPCR)

Brain punches and aortas were processed for total mRNA (RNeasy Kit, Qiagen). RNA concentration was determined (Nanodrop Spectrophotometer, Thermofisher) and 1 μg reverse transcribed (Super Script IV Reverse transcriptase kit, Thermo Fisher). Reactions were run in triplicate (QuantStudio 5 Real-Time PCR System, Applied Biosystems) and gene expression was calculated from average Ct values normalized to 18 S rRNA as the housekeeping gene [formula: 2(−ΔCt)] (QuantStudio, Thermofisher). SYBR Green primers were used (Supplementary Table 1) for targets related to cell stress/redox (Tgfβ, HIF1α, Ho1, Nox4, Nox2, Nrf2, Nos2, Sod1, Gpx1), angiogenesis (Pdgfrb, Vegfr1, Angpt, Mmp9), and GPCR signaling and serotonin (Htr1a, Htr2a, Maoa, Avpr1a, Ido, Slc6a4, Tph1, Fgf2).

Immunohistochemistry

As previously described [51–53], sections were immunostained with NEUN monoclonal primary antibody (1:300; 24307S, catalog number NC1593317, Cell Signaling Technology) and secondary polyclonal antibody (1:500; DyLight 633, catalog number NBP1-75633, Novus Biologicals). Cerebrovasculature was labeled using Isolectin GS-IB4 (IB4) conjugated to Alexa Fluor 488 (1:1000; I21411, Invitrogen). Slides were coverslipped with DAPI mounting medium (H200010, Vector Laboratories). For additional details, see the Supplementary Materials and Methods.

Stereology

Neuronal, cellular, and cerebrovascular imaging was performed on an Olympus IX3 scanning fluorescent microscope with CellSens (Olympus Life Science) software. Assessments were performed by the same blinded experimenter utilizing CellSense imaging software and ImageJ. For additional details, see the Supplementary Materials and Methods.

Cerebrovascular assessments

As previously described [53], 20 μm coronal brain sections were side mounted, blocked, and vessels stained with IB4 lectin. For each animal, 2 neocortical images (1920 × 1200 pixels) per section were pseudo-randomly taken at 20x magnification across 3–6 coronal sections at intervals of 200 μm. Freehand draw in ImageJ was used to manually trace IB4 lectin+ vessels. Approximately 10 vessels were traced per image. Care was taken to exclude cellular structures (e.g., with DAPI+ nucleus), as IB4 lectin also labels microglia which often lie near microvessels in the brain [60, 61]. The length and diameter at the widest point of all vessel traces was calculated in ImageJ (measure command) per image then averaged across images (minimum 3) for each animal. To determine vessel branching, the number of branches or junctions on a given vessel trace was tabulated and averaged over length of the root vessel, as has been done in anti-angiogenic genetic modeling previously [62].

Enzyme-linked immunoassay (ELISA)

Trunk blood was collected upon animal sacrifice into a heparin-coated tube and frozen (−80 °C). Platelet-free plasma serotonin (5-HT) was measured by ELISA (ab133053, Abcam), per manufacturer protocols. Samples were assayed within two weeks of collection.

Tail-cuff plethysmography

Blood pressure was assessed in a separate cohort (n = 3–7/genotype/sex) by tail-cuff plethysmography on a high throughput non-invasive blood pressure monitoring system (CODA, Kent Scientific), as previously [63]. Briefly, mice were restrained in plexiglass tubes and acclimated to 30 min periods of restraint for 2 weeks prior to testing. Blood pressures were then averaged over 2 days of testing.

Evans blue blood-brain barrier permeability assay

Following established protocols [64], female brains were tested for presence of Evans blue (EB) dye 30 min after i.v. administration. For additional details, see the Supplementary Materials and Methods.

Brain slice preparation and electrophysiological recordings

Brain slices and electrophysiological recordings were made as previously described [65]. All recordings were made with the investigator blinded to genotype. In brief, WT and homozygous Rgs2 KO mice were deeply anesthetized with isoflurane and euthanized by decapitation. Brains were extracted and placed in warmed and bubbled (95/5% O₂/CO₂) modified Krebs’ buffer containing (in mM): 126 NaCl, 2.5 KCl, 1.2 MgCl₂, 1.2 CaCl₂, 1.2 NaH₂PO₄, 21.5 NaHCO₃, and 11 D-glucose. To increase slice viability and limit excitotoxicity, 5 µM of MK-801 was added to the buffer solution. Coronal dorsal raphe slices (240 µm) were collected using a vibrating microtome (Leica VT 1000 S). Slices were then incubated in the same buffer solution at 28 °C for at least 30 min before recording.

Electrophysiological recordings were made at 35 °C from dorsal raphe serotonin neurons, identified based on location relative to the cerebral aqueduct and firing broad action potentials (>1 ms half-width) under 40 Hz to somatic current injection [65, 66] with Multiclamp 200B and 700B amplifiers (Molecular Devices), Digidata 1550B A/D converters (Molecular Devices), and Clampex software (Molecular Devices) with borosilicate glass electrodes (World Precision Instruments) wrapped with Parafilm to reduce pipette capacitance. Pipette resistances were 2.8 to 4.4 MΩ when filled with an internal solution containing: (in mM) 104.56 K-methylsulfate, 3.73 KCl, 5.3 NaCl, 4.06 MgCl₂, 4.06 CaCl₂, 7.07 HEPES (K), 3.25 BAPTA (K4), 0.26 GTP (sodium salt), 4.87 ATP (sodium salt), 4.59 creatine phosphate (sodium salt), pH 7.24 with KOH, mOsm ~274, for whole-cell patch-clamp recordings. Series resistance was monitored throughout the experiment. A liquid junction potential of −8 mV between the internal and external solution was used to correct all reported voltages. Brief pulses (0.5 ms, 60 Hz) of electrical stimulation were delivered to the brain slice in 60 s intervals via a borosilicate glass monopolar stimulating electrode (World Precision Instruments) inserted within 200 µm of the recorded neuron to evoke synaptic currents. To isolate the 5-HT1A-IPSC, synaptic currents were evoked in the presence of GluN (MK-801, Tocris), GluA/GluK (NBQX, 3 μM, Tocris), GABA_A (picrotoxin, 100 μM, Sigma-Aldrich), and α1-adrenergic (prazosin, 100 nM, Tocris) receptor blockers. Drugs were applied to brain slices via bath application.

Statistical analyses

Based on our work in similar models [20, 51–53, 63, 67], sample sizes were selected to achieve 94–100% power to detect a respective change in sensitivity and specificity from 0.5 to 0.9. Normality (by Shapiro–Wilk test) and equal variance (by Brown-Forsythe test) were confirmed before performing two-way ANOVAs to test for sex, genotype, and interaction effects. As appropriate, post hoc pairwise multiple comparisons were performed via the Student-Newman-Keuls (SNK) Method. If either the assumption of normality or equal variance was violated, a nonparametric ANOVA on Ranks (Kruskal-Wallis) test was used, followed by Holm-Sidak corrected multiple comparisons. Normally distributed gene expression data were tested via one-sample t-test; non-normally distributed data were tested by the one sample Wilcoxon test. Associations were interrogated by linear regression on grouped male and female data to reveal underlying, associative mechanisms. Outliers (greater than two standard deviations from the mean) were excluded.

Dorsal raphe serotonin neuron recordings were analyzed using Clampfit 11.1. τ-decay were determined by fitting the 5-HT1A-IPSCs from the peak to the return to 0 current with a single exponential. Unless stated otherwise, n=number of cells. Significant differences were determined by Mann-Whitney U tests.

For all tests, P values < 0.05 were considered significant. All plotted averages depict means ± S.E.M. Statistical analyses were completed in SigmaPlot v12.3 (Systat Software, Inc.) or GraphPad Prism 9 and displayed using GraphPad Prism 9 (GraphPad Software, Inc.).

Results

Sex-specific behavioral alterations in the Rgs2 knockout mouse

To test sex-specific brain function changes relevant to psychiatry, we assessed male and female KO and WT behaviors (n = 8–12/sex/genotype). There was also no difference in distance traveled by epoch in males (two-way repeated measures ANOVA interaction: F[5,90] = 1.808, p = 0.12, main effect [ME] genotype: F[1,18] = 0.7327, p = 0.40) nor females (interaction: F[5,50] = 0.8042, p = 0.55, ME genotype: F[1,10] = 0.008, p = 0.93), though both animals habituated with diminished locomotion (p < 0.0001 ME time, males: F[2.978,53.60] = 38.34; females: F[3.432,34.32] = 28.09; Fig. 1A, B). Time spent in the center versus periphery of the open field test was unchanged by group (H[3] = 2.003, p = 0.57 by ANOVA on Ranks; Fig. 1C). Working memory, as measured by spontaneous alternation ratio on the Y-maze, was unchanged by genotype or sex (two-way ANOVA interaction: F[1,38] = 0.9654, p = 0.33; ME sex: F[1,38] = 1.560, p = 0.2193; ME genotype: F[1,38] = 0.09088, p = 0.76), and alternations were elevated beyond chance in all groups (males: WT: 0.57 ± 0.03, p = 0.02 by one sample t test, KO: 0.56 ± 0.02, p = 0.02; females: WT: 0.58 ± 0.03, p = 0.03, KO: 0.32 ± 0.03, p = 0.001; Fig. 1D). We found male-specific exploratory deficits on the Y-maze (latency to enter first arm, two-way ANOVA interaction: F[37] = 10.32, p = 0.003; ME sex: F[1,35] = 1.709, p = 0.20; ME genotype: F[1,35] = 0.8820, p = 0.35; post hoc genotype difference by Student-Newman-Keuls (SNK) method in males p = 0.008; Fig. 1E). Social preference was significantly increased above chance for males (WT: p = 0.0003, KO p = 0.0005) and females (WT p = 0.008, KO p = 0.0009) by single sample t-test, but unchanged by group (H[3] = 5.182, p = 0.16 by ANOVA on Ranks; Fig. 1F). Social novelty preference was increased above chance by single sample t-test only among WT males (p = 0.03; KO females: p = 0.09; KO males: p = 0.09; WT females: p = 0.88), but unchanged by group (two-way ANOVA interaction: F[1,38] = 0.3868, p = 0.54; ME sex: F[1,38] = 2.282, p = 0.14; ME genotype: F[1,38] = 0.7122, p = 0.40; Fig. 1G). Time spent on the open versus closed arms of the elevated plus maze was significantly decreased in KOs (two-way ANOVA, ME genotype: F[36] = 4.87, p = 0.03), driven by females (p = 0.02 by post hoc SNK; Fig. 1H). Sucrose consumption was significantly increased in KOs (two-way ANOVA, ME genotype: F[1,35] = 16.90, p = 0.0002; post hoc SNK males: p = 0.03, females: p = 0.001; Fig. 1I). We further found decreased struggle behavior on the tail suspension test in KOs (two-way ANOVA, ME genotype: F[1,37] = 5.752, p = 0.02; no significant post hoc SNK; Fig. 1J). Struggle time per bout was unchanged (two-way ANOVA interaction: F[1,37] = 0.062, p = 0.81; ME sex: F[1,37] = 0.9019, p = 0.35; ME genotype: F[1,37] = 0.7897, p = 0.38; Fig. 1K).

Fig. 1 — On the open field, A KO males exhibited no locomotor differences by genotype across the full 30 min task (two-way repeated measures ANOVA interaction: F[5,90] = 1.808, p = 0.12, main effect [ME] genotype: F[1,18] = 0.7327, p = 0.40), though they did down-regulate locomotor behavior across the task (p < 0.0001 ME of time: F[2.978,53.60] = 38.34). B Females also exhibited no significant difference in distance traveled by genotype across the full open field task (two-way repeated measures ANOVA interaction: F[5,50] = 0.8042, p = 0.55, ME genotype: F[1,10] = 0.008, p = 0.93) while down-regulating locomotor behavior across the task (p < 0.0001 main effect of time: F[3.432,34.32] = 28.09). C Center time relative to peripheral zone time on the open field was unchanged by genotype (H[3] = 2.003, p = 0.57 by ANOVA on Ranks). D Working memory, as assessed by spontaneous alternations on the Y maze, was unchanged by genotype or sex (two-way ANOVA interaction: F[1,38] = 0.9654, p = 0.33; ME sex: F[1,38] = 1.560, p = 0.2193; ME genotype: F[1,38] = 0.09088, p = 0.76). Spontaneous alternation rates were elevated beyond chance (dashed line, 50%) in all groups by one-sample t-test (males: WT: 0.57 ± 0.03, p = 0.02, KO: 0.56 ± 0.02, p = 0.02; females: WT: 0.58 ± 0.03, p = 0.03, KO: 0.32 ± 0.03, p = 0.001). E Male-specific latency to explore any arm when first placed into the Y maze was significantly increased in KOs (two-way ANOVA interaction: F[37] = 10.32, p = 0.003; ME sex: F[1,35] = 1.709, p = 0.20; ME genotype: F[1,35] = 0.8820, p = 0.35; post hoc genotype difference by Student-Newman–Keuls (SNK) method in males p = 0.008). F Social preference for a novel stranger mouse versus a non-social stimulus (cylinder containing object) was significantly increased above chance (dashed line, 1) for males (WT: p = 0.0003, KO p = 0.0005) and females (WT p = 0.008, KO p = 0.0009) by single sample t-test, but unchanged by group (H[3] = 5.182, p = 0.16 by ANOVA on Ranks. G Social novelty preference was increased above chance (dashed line, 1) by single sample t-test only among WT males (p = 0.03; KO females: p = 0.09; KO males: p = 0.09; WT females: p = 0.88), but unchanged by group (two-way ANOVA interaction: F[1,38] = 0.3868, p = 0.54; ME sex: F[1,38] = 2.282, p = 0.14; ME genotype: F[1,38] = 0.7122, p = 0.40). H KO mice exhibited decreased time on the open relative to the closed arm and center of the elevated plus maze (two-way ANOVA, ME genotype: F[36] = 4.87, p = 0.03), which was driven by females (p = 0.02 by post hoc SNK) indicating an anxiety-like phenotype. I Hedonic behavior, as assessed by the sucrose preference test, was significantly increased in KOs (two-way ANOVA, ME genotype: F[1,35] = 16.90, p = 0.0002; post hoc SNK males: p = 0.03, females: p = 0.001). J The tail suspension test revealed decreased KO struggle behavior (two-way ANOVA, ME genotype: F[1,37] = 5.752, p = 0.02; no significant post hoc SNK) but K) unchanged struggle time per bout (two-way ANOVA interaction: F[1,37] = 0.062, p = 0.81; ME sex: F[1,37] = 0.9019, p = 0.35; ME genotype: F[1,37] = 0.7897, p = 0.38). All p values calculated by ANOVA (two-way or on Ranks, as noted) and by post hoc SNK. Data are displayed as mean ± SEM.

Cortical vessel density and length but not cell numbers are diminished in Rgs2 KO mice

We next conducted histological assessments of brain morphology, including of cerebrovasculature (n = 3–6/sex/genotype), which is changed in multiple models of obstetric and psychiatric disease and is associated with behavioral alternations including anxiety-like, hedonic, and depression-like behaviors [6, 68, 69]. These revealed significant reductions in cortical vascular density in KOs (two-way ANOVA, main effect genotype: F[1,19] = 30.75, p < 0.001; males and females p < 0.001 by SNK; Fig. 2A). Vessel length in KOs was also decreased (H[3] = 17.225, p < 0.001; post hoc Dunn’s Method WT vs KO males p = 0.005, WT vs KO females p = 0.10; Fig. 2B). Vessel elaboration (genotype: F[1,20] = 0.0009, p = 0.98; sex: F[1,20] = 0.9801, p = 0.33; Fig. 2C) and luminal diameter (genotype: F[1,21] = 0.0059, p = 0.94; sex: F[1,21] = 0.0087, p = 0.93; Fig. 2D) were unchanged. Vessels appeared more diffuse and fragmented in KO tissues (Fig. 2E). Cortical thickness (Fig. 2E) across regions of cerebral cortex was unchanged (ANOVA on ranks p < 0.001; no significant post hoc differences by region; Fig. 2F), nor was white matter thickness at the corpus callosum (interaction: F[1,8] = 0.05929, p = 0.81; ME genotype: F[1,8] = 0.1990, p = 0.67; ME sex: F[1,8] = 0.004360, p = 0.95; Fig. 2G).

Neocortical density of all cells (interaction: F[1,15] = 1.088, p = 0.31; ME genotype: F[1,15] = 0.4907, p = 0.49, ME sex: F[1,15] = 0.1454, p = 0.71; Fig. 2H), of neurons (interaction: F[1,15] = 1.594, p = 0.23; ME genotype: F[1,15] = 0.1047, p = 0.75; ME sex: F[1,15] = 0.00043, p = 0.98; Fig. 2I), and ratio of neurons to glia (interaction: F[1,15] = 1.174, p = 0.30; ME genotype: F[1,15] = 0.2252, p = 0.64; ME sex: F[1,15] = 0.01520, p = 0.90; Fig. 2J) were unchanged.

Sex-specific abnormalities in angiogenesis, G protein signaling, and redox related gene expression in Rgs2 KO mice

Given the known role of Rgs2 in cerebrovascular biology and mood and anxiety-related behaviors, we next assessed whether expression of angiogenic genes and those involved in regulation of signaling pathways dependent on Rgs2 (e.g., 5HT, AVP, etc.) were disrupted. Given large cerebrovascular deficits in this model, we also assessed angiogenic targets (Fig. 3). P values reference comparison of KO fold change (relative to WT) by one-sample Shapiro–Wilk t test (if normally distributed) or by one-sample Wilcoxon test (if non-normally distributed).

In neocortex (Fig. 3A, B), redox-related targets Hif1a and Ho1 were decreased in males (Hif1a: 7.75% of controls, p = 0.03; Ho1: 45.30% of controls, p = 0.0002), while only Hif1a was decreased in females (62.25% of controls, p = 0.02). Tgfβ was decreased in males only (42.8% of controls, p < 0.0001) and Nox4 expression was unchanged by genotype across sexes. Expression of angiogenesis-related genes including Pdgtrb and Angpt was unchanged; Mmp9 was decreased (58.70% of controls, p = 0.03) and Vegfr1 was increased (613%, p = 0.008) in males only. In terms of cortical GPCR-related signaling, there were female-specific elevations in Htr2a (378.4% of controls, p = 0.02) and Maoa (237.6% of controls, p = 0.045) expression, while Slc6a4 (males: 13.86% of controls, p = 0.03; females: 51.01% of controls, p = 0.01) and Tph1 (males: 25.05% of controls, p = 0.03; females: 27.56% of controls, p = 0.0006) were decreased in both sexes. Fgf2 (14.16% of controls, p = 0.03), Ido (13.02%, p = 0.03), and Avpr1a (4.89% of controls, p = 0.03) were both down-regulated in male KOs, while only Avpr1a was down-regulated in female KOs (70.07% of controls, p = 0.04). Together, these data suggest female increases in serotonin systems gene expression, including receptors (Htr2a) and metabolic machinery (e.g., Maoa), possibly as compensation for a lack of Rgs2 mediation of GPCR signaling. Cell stress and hypoxia-related genes may be dysregulated as a result of aberrant signaling in Rgs2 KO cells.

Given redox-related changes in cortex, a slightly expanded subset of redox genes was next evaluated in paraventricular nucleus (PVN; Fig. 3C–F), a region critical to GPCR-related functions including vasopressin and oxytocin signaling. We hypothesized that redox-related genes may have been abnormal in KO animals given disinhibited intracellular signaling. Most patterns of gene expression in PVN remained consistent between male and female Rgs2 KO animals. In both sexes, redox-related Nos2 (males: 1.11% of controls, p < 0.0001; females: 1.36% of controls, p < 0.0001), Ho1 (males: 19.30% of controls, p < 0.0001; females: 42.06% of controls, p = 0.0008), Nox4 (males: 5.88% of controls, p < 0.0001; females: 8.86% of controls, p < 0.0001), and Nox2 (males: 2.83% of controls, p < 0.0001; females: 4.76% of controls, p < 0.0001) were down-regulated in KOs, while Sod1 (males: 7567% of controls, p < 0.0001; females: 12930% of controls, p = 0.0001) and Gpx1 (males: 3147% of controls, p = 0.0003; females: 6303% of controls, p < 0.0001) were strongly up-regulated. In KO females only, Nrf2 was significantly up-regulated (150% of controls, p = 0.04). In contrast to cortex, angiogenesis-related Hif1a was strongly up-regulated in both male (756.8% of controls, p = 0.004) and female KO PVN (1427% of controls, p = 0.0010). A subset of GPCR signaling genes were down-regulated in both male and female KO PVN: Avpr1a (males: 25.20% of controls, p = 0.002; females: 39.49% of controls, p = 0.002), Ido (males: 8.69% of controls, p < 0.0001; females: 0.67% of controls, p < 0.0001), Slc6a4 (males: 0.92% of controls, p < 0.0001; females: 9.68% of controls, p < 0.0001), and Tph1 (males: 3.65% of controls, p = 0.03; females: 1.46% of controls, p < 0.0001). Only in female KO PVN was serotonin-related target HTR1A down-regulated (35.30% of controls, p < 0.0001) and Maoa up-regulated (290.8% of controls, p = 0.03).

Given GPCR-related changes in gene expression in cortex and hypothalamic PVN, we next sought to examine gene expression in the serotonergic dorsal raphe nucleus of the midbrain (Fig. 3G, H). In both male and female KO midbrain, there was pan-suppression of most serotonergic and GPCR-related targets: Htr1a (males: 32.54% of controls, p = 0.0069; females: 37.39% of controls, p = 0.010), Avpr1a (males: 8.69% of controls, p < 0.0001; females: 0.67% of controls, p < 0.0001), Ido (males: 2.73% of controls, p < 0.0001; females: 5.18% of controls, p = 0.03), Slc6a4 (males: 3.64% of controls, p < 0.0001; females: 0.88% of controls, p < 0.0001), and Tph1 (males: 1.01% of controls, p < 0.0001; females: 3.48% of controls, p < 0.0001). In male KOs only, there was decreased Htr2a (43.35% of controls, p = 0.02), while in female KOs there was increased Maoa (290.8% of controls, p = 0.008).

Finally, we measured expression of serotonin-related genes in hindbrain (Fig. 3I, J) to determine specificity of serotonin system changes. Of Htr1a, Htr2a, and Maoa, which were changed in the other brain regions in a sex-specific manner, only Htr1a was down-regulated in both male (23.51%, p < 0.0001) and female (23.44%, p = 0.0005) KO hindbrain. Htr2a was modestly down-regulated (48.89%, p = 0.03) in male KOs only.

Broadly, changes across brain regions in the Rgs2 KO mouse suggest sex-specific impacts on serotonin, redox, and angiogenic genes across the brain (Fig. 3K). Pan-suppression of serotonin systems in male cortex was contrasted by up-regulation of select targets (e.g., Htr2a, Maoa) in females, which may be compensatory. Angiogenic and redox-related gene expression was also disrupted, with particularly pronounced up-regulation in PVN, where GPCR-related signaling (e.g., AVP, OXT) is prominent.

Behavior and cerebrovasculature changes are associated with brain serotonin and angiogenesis-related gene expression in a sex- and genotype-specific manner in the Rgs2 KO mouse

To interrogate molecular pathways in Rgs2-dispruted endophenotypes, we tested correlations between gross somatomotor cortex output (locomotor behavior) and expression of key serotonin and angiogenesis-related genes in the brain: Ido, Tgfβ, Slc6a4, Angpt. These genes regulate immune/cell stress (Tgfβ), serotonin signaling (Slc6a4), and angiogenic mechanisms (Angpt). Tgfβr2 and Angpt are differentially expressed in placenta with reduced Rgs2, and Slc6a4 (encodes SERT) [33] is a critical regulator of serotonergic neurotransmission, which is altered with variation in RGS2 [36, 43, 70, 71]. Vascular density in the cortex was significantly and positively correlated with depressive behavior (tail suspension test) across all animals, regardless of genotype (linear regression: r(9) = 0.67, p = 0.03).

IDO is a rate-limiting antioxidant enzyme in the kynurenine pathway, which, when activated, depletes tryptophan to produce kynurenine and downstream metabolites. IDO is activated by immune and cellular stress mechanisms; activated IDO depletes tryptophan available for serotonin synthesis and leads to depression-like phenotypes [72–75]. Given this central role for IDO in tryptophan/serotonin metabolism and its response to cellular stress, we tested whether Ido expression was correlated with vascular deficits in Rgs2 KO versus WT control brain (Fig. 4A, B). Ido was positively correlated with vascular density in KO (linear regression: r[10] = 0.70, p = 0.02) but not WT brain (r[11] = 0.08, p = 0.80), suggesting a protective role for Ido expression in preventing angiogenic deficits.

Next, we tested whether a cell stress/immune response in cortex might be related to cortically-mediated locomotor behavior in Rgs2 KO animals (Fig. 4C, D). Locomotor behavior is a gross output of the somatomotor cortex and therefore may reveal broad, cortical function deficits. Expression of Tgfβ, which encodes a pleiotropic cytokine with a wide variety of immune regulatory and cytostatic functions, was inversely correlated with locomotor behavior on the open field test in WT (r[11] = −0.74, p = 0.006) but not KO (r[10] = −0.18, p = 0.59) animals.

We next tested whether serotonin signaling might also be related to cerebrovascular density in a sex-specific manner (Fig. 4E, F). We found a positive, significant correlation between cerebrovascular density and cortical Slc6a4 in females (r[10] = 0.75, p = 0.008) but not in males (r[11] = −0.43, p = 0.17), suggestive of a female-specific protective role for SERT in cerebrovascular health.

Finally, we tested the role of angiogenic mechanisms in regulation of cortical function, as measured by locomotor output, in Rgs2 KO animals (Fig. 4G, H). In WT (r[11] = −0.73, p = 0.007) but not KO (r[10] = −0.30, p = 0.37) mice, cortical Angpt was inversely correlated with total distance traveled (Fig. 4G, H).

In separate cohorts, we found no disruptions in blood pressure by tail-cuff plethysmography (Fig. S1A–C), circulating 5-HT (Fig. S1D), or blood-brain barrier permeability in females only. We also measured cellular stress/redox-, fibrosis-, and angiogenesis-related gene expression in aortas of WT and KO animals (N = 3/sex/condition) (Fig. S1E, F): Angpt and Nox2 were down-regulated and Nox4 was up-regulated in female KOs. In male KOs, only fibrosis-related Mmp9 was down-regulated. For additional details, see Supplementary Results.

Serotonin synaptic transmission is altered and sensitivity to sertraline increased in female Rgs2 KO mice

Next, to determine whether deletion of Rgs2 alters serotonin synaptic transmission, we performed whole-cell electrophysiological recordings from dorsal raphe serotonin neurons in acute brain slices.

In the dorsal raphe, 5-HT release produces 5-HT1A receptor-mediated inhibitory postsynaptic currents (5-HT1A-IPSC) via activation of G protein-coupled inwardly rectifying potassium (GIRK) channels [76]. 5-HT release was evoked once every 60 s by a train of electrical stimuli (5 pulses, 0.5 ms, 60 Hz) delivered to the brain slice via a monopolar stimulating electrode. 5-HT1A-IPSCs were isolated by the presence of GluN, GluA/GluK, GABA_A, and α1-adrenergic receptor blockers in the external solution (Fig. 5A). In control conditions using brain slices from female mice, there were no differences in the amplitude (WT: 89.0 ± 19.0 pA, n = 21; KO: 77.3 ± 13.1 pA, n = 14; p = 0.96) and time-to-peak (WT: 390.7 ± 23.3 ms, n = 20; KO: 375.5 ± 21.1 ms, n = 14; p = 0.82) of the 5-HT1A-IPSC between WT and Rgs2 KO neurons. However, there was a significant difference in the rate of decay (τ-decay) of the 5-HT1A-IPSC, such that the 5-HT1A-IPSC was faster in KO neurons (442.3 ± 36.9 ms, n = 14) when compared with WT neurons (533.7 ± 32.0 ms, n = 20, p = 0.047, Fig. 5B). Parallel studies done using brain slices from males revealed no differences in the 5-HT1A-IPSC between WT and Rgs2 KO (see Supplementary Results, Fig. S2).

Fig. 5 — A Representative traces of whole-cell voltage-clamp recordings of the 5-HT1A-IPSC in control conditions and after acute application of sertraline (sert., 300 nM, the presence of 5-HT1B receptor antagonist SB-216641) in WT and *Rgs2* KO dorsal raphe serotonin neurons from female mice. B Plot of the rate of decay of the 5-HT1A-IPSC in control conditions in WT and *Rgs2* KO serotonin neurons from female mice. C-E) Sertraline had a greater effect in *Rgs2* KO neurons when compared with WT, increasing the C amplitude and D time-to-peak (ttp) of the 5-HT1A-IPSC. Sertraline substantially prolonged the E) rate of decay of the 5-HT1A-IPSC, but to a similar extent between WT and *Rgs2* KO neurons from female mice. B–E statistical significance determined by two-tailed Mann-Whitney tests. Data are displayed as representative traces or in scatter plots and bar graphs (mean ± SEM), where individual cells are represented as points. F Overall model describing mechanism by which *Rgs2* may interact with vascular dysfunction and cellular stress to increase psycho-obstetric risk. Environmental (e.g., stress [82], adverse childhood experiences and abuse [83]), genetic (e.g., *Rgs2* [29, 33, 43], *HTR* mutations [15, 19]), and biologic (e.g., hypertension, obesity [84, 85]) risk factors interact to interrupt *Rgs2*-mediated serotonin signaling pathways. These disruptions in turn increase cellular stress [78] and downstream redox and inflammatory factor production [79, 80], thereby impairing angiogenic processes and vascular health, leading to increased risk for depression via cerebrovascular dysfunction [112] and increased risk for preeclampsia via placental and peripheral vascular dysfunction [84]. Made using BioRender.

The amplitude and time course of the 5-HT1A-IPSC in the dorsal raphe is limited by efficient clearance of extracellular serotonin by reuptake via SERT [77]. In WT and Rgs2 KO neurons from female mice, application of sertraline (300 nM) in the presence of 5-HT1B and α2-adrenergic receptor antagonists (SB-216641:1 μM, [77] and idazoxan: 1 µM), increased the amplitude and slowed the time-to-peak of the 5-HT1A-IPSC (Fig. 5A, C). However, the augmentation of the 5-HT1A-IPSC amplitude by sertraline was significantly greater in Rgs2 KO neurons (~160%) when compared with WT (~125%, p = 0.009, Fig. 5A, C). In addition, sertraline had a greater effect on the time-to-peak of the 5-HT1A-IPSC in KO neurons than WT (p = 0.03, Fig. 5A, D). Sertraline slowed the rate of decay dramatically, prolonging the 5-HT1A-IPSC by seconds in both WT and KO neurons (p = 0.46, Fig. 5A, E). In WT and Rgs2 KO neurons from male mice, sertraline had similar effects on the amplitude, time-to-peak, and rate of decay of the 5-HT1A-IPSC (see Supplementary Results and Fig. S2). The data revealed that increased sensitivity to sertraline was a female-specific consequence of the loss of Rgs2 (two-way ANOVA interaction: F[1,29] = 4.88, p = 0.035; Sidak’s multiple comparison test WT vs. KO: male: p = 0.09; female: p = 0.023; see Supplementary Results). These data suggest altered serotonin 5-HT1A receptor-dependent synaptic transmission between dorsal raphe nucleus serotonin neurons in female Rgs2 KO animals and increased sensitivity to sertraline. We propose that multiple risk factors converge on Rgs2-serotonin signaling mechanisms to alter neurobiology (Fig. 5F).

Discussion

In this study, we sought to determine whether vascular, function, and electrophysiologic features of brain health are disrupted with loss of Rgs2. Our prior work demonstrates that decreased placental Rgs2 is sufficient to drive obstetric risk phenotypes in a mouse model via vascular mechanisms [29, 33]. Here, we extended this obstetric modeling work to test whether RGS2-mediated vascular pathology in the brain is also implicated and associated with changes in GPCR signaling more broadly (e.g., serotonergic systems) and with cell stress and redox dysfunction. Overall, our findings demonstrate that altered serotonin signaling occurs in the Rgs2 KO [78–80], as does vascular and anti-angiogenic dysfunction in the brain and periphery. These results may suggest a central mechanism underlying both obstetric and psychiatric risk (Fig. 5F).

These studies were based on prior work linking Rgs2 to neurobiological and behavioral phenotypes in humans and in preclinical models [36, 81]. A variety of predisposing risk factors including environmental (e.g., stress [82], childhood abuse [83]), genetic (e.g., RGS2 [29, 33, 43], HTR mutations [15, 19]), and biologic (e.g., hypertension, obesity [84, 85]) factors interact to interrupt RGS2-mediated serotonin signaling pathways. Genetic mutations spanning RGS2 are associated with childhood behavioral inhibition, social anxiety, agoraphobia, PTSD, and limbic hyperactivation, as well as with anxiety-like phenotypes in mice [28, 36–40]. The RGS2 SNP rs4606 is associated with a doubling of risk for generalized anxiety disorder [86]. C alleles in the rs4606 RGS2 SNP are each associated with 5.59-fold increase in risk for suicidal ideation in a cohort of individuals exposed to natural disaster stress [42]. Postmortem work finds reduced RGS2 in the brains of female (but not male) individuals with depression [41].

In mice, we previously reported that diminished Rgs2 in placenta is sufficient to cause vascular, obstetric phenotypes [33]. RGS2 promotes vascular relaxation and adaptation by selectively inhibiting Gq signaling [87] and endothelial G(i/o) activity [88]. Despite significant interest in RGS2 function in the peripheral vasculature [34, 35, 89], no prior studies have evaluated its role in cerebrovasculature. Here, we found significant decreases in cortical vascular density and vessel length in Rgs2 KO mice despite no gross abnormalities in grey or white matter or in neuronal, glial, or total cell density. These gross neuroanatomical and cell density findings confirm one prior report in this model [45]. Redox mechanisms may also play a role in vascular vulnerability in the periphery, as our results in aorta suggest, though future studies will need to directly assess redox processes and reactive oxygen species production. Unlike RGS5, RGS2 effects on cerebrovasculature and behavior appeared independent of hypertension [90].

In addition to cerebrovasculature, we also examined serotonin systems functioning in this risk model. Prior clinical and pre-clinical work implicates RGS2 in serotonin systems functioning [29, 36, 39, 70]. We found female-specific vulnerabilities in serotonin signaling and metabolism, as well as broad disruptions to expression of redox-related, inflammatory, and angiogenesis/vascular function genes in Rgs2 KOs. Finally, we confirmed that molecular disruptions in Rgs2 KO result in female-specific alterations to serotonin synaptic transmission between dorsal raphe serotonin neurons and increased sensitivity to the SSRI sertraline.

Prior work reveals behavioral abnormalities in the Rgs2 KO mouse similar to those we report here, including anxiety and depressive-like behaviors [27, 41, 43–45, 71, 91]. We find aspects of anxiety (e.g., increased latency to explore arms of the Y maze in males, decreased EMP open arm time in both males and females), depressive-like behavior (decreased struggle time on the TST), and increased hedonic behavior (sucrose preference) in KOs. Prior work finds that sociability may be particularly sensitive to stress in this model and may depend on RGS2 in the nucleus accumbens [41]. Our use of the three-chamber social task, which is limited in its ethological validity and ability to detect animal emotional cognition [68], may have limited our ability to detect social differences here. Future studies should utilize more reciprocal models (e.g., free-moving interaction) or refined approaches (e.g., social microstructure assessment).

Few studies have assessed sex-specificity of Rgs2 KO behavior, which we do not find is particularly pronounced here. However, those that have report learning [44], addiction and reward-seeking [81, 92, 93], but generally not mood-related phenotypes as we assess here. Further, we found that cortical Slc6a4 was correlated with vascular density in female but not male animals, suggesting a sex-specific role for serotonin dysregulation in this model. Future studies should evaluate the role of the serotonin transporter, either directly or by SSRI modulation, in the Rgs2 KO model to determine whether SERT underlies mood-related phenotypes with and without pregnancy.

Molecular profiling of the brain by qPCR in Rgs2 KOs revealed some increased serotonin-related gene expression in female cortex (e.g., Htr2a, Maoa) but decreases in males; increased redox- and angiogenesis-related gene expression in paraventricular nucleus of the hypothalamus (e.g., Sod1, Gpx1, Sod1, Hif1α); and sex-specific serotonin system dysregulation across midbrain and hindbrain. For example, Hif1α, Mmp9, and Fgf2 are known positive regulators of angiogenesis [94], and were all down-regulated in male cortex, while only Hif1α was down-regulated in females. Prior work finds that Mmp9 expression is influenced by estrogen, which is protective against matrix degradation and vascular disease in some settings [94]. Sod1 and Gpx1 were both strongly up-regulated in paraventricular nucleus of the hypothalamus (PVN), suggesting increased oxidative stress resistance [95, 96]. Sod1 expression is increased under oxidative conditions in the brain [97, 98].

The PVN was selected for additional molecular analyses given its functional dependence on RGS2 [99], regulation of affective and mood-related phenotypes [100, 101], reciprocal connections with dorsal raphe and other monoamine systems [102–104], and high expression of vasopressin GPCRs [99, 103], which are disrupted in both preeclampsia and depression [105–108]. In contrast to the cortex, angiogenesis-related Hif1α was strongly up-regulated in both male and female KO PVN. A subset of GPCR signaling genes were down-regulated in both male and female KO PVN: Avpr1a, Ido, Slc6a4, and Tph1. Only in female KO PVN were serotonin signaling targets Htr1a and Maoa up-regulated. This echoes prior reports that serotonin systems are particularly sensitive to perturbation in females [109, 110]. Interestingly, however, Rgs2 deletion in the PVN causes PVN neuronal death and hyper-consumptive behavior in males and females, echoing the increased sucrose preference we report across sexes here [99]. PVN Rgs2 should be assessed in future studies to determine the role of RGS2 in these neurons and in their broader networks, including serotonin networks (PVN has reciprocal connections to the dorsal raphe).

Future studies should extend our results by examining neurotransmission and brain function in pregnancy, with and without Rgs2. Given its known role in pregnancy-specific stress responses and anxiety phenotypes [27], future studies should evaluate the interaction between Rgs2 genotype and pregnancy in terms of the phenotypes described here. Complementary overexpression studies may also reveal whether Rgs2 is sufficient to drive phenotypes in the brain, placenta, and elsewhere, or may be protective.

Given high rates of co-occurrence of psychiatric and obstetric disorders, it is important to identify conserved molecular mechanisms [48, 111]. Together with prior work, we reveal a protective role for Rgs2-serotonin signaling in vascular dysfunction underlying shared psycho-obstetric risk mechanisms. Overall, our findings indicate that loss of Rgs2 leads to behavioral abnormalities, altered serotonergic gene expression and SSRI response in the brain, and central and peripheral vascular dysfunction. Some of these effects are sexually dimorphic. Neurobiological and behavioral disruptions in this model appear to be related to dysregulated cell stress and angiogenesis, which are dysregulated in both anxiety/depression and in preeclampsia. Future work should determine whether pregnancy sets the stage for differential psychiatric risk in the setting of Rgs2-serotonin dysfunction. As conserved mechanisms such as this are examined, it becomes increasingly possible to develop targets for personalized therapies and cures.

Supplementary information

Supplemental Materials and Methods^{(468.1KB, pdf)}

Author contributions

SBG: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; Drafting the work or revising it critically for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. MKS: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. AG: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. BS: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; Drafting the work or revising it critically for important intellectual content; final approval of the version to be published; KW: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. ML: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; Drafting the work or revising it critically for important intellectual content. Hannah Sullivan: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. KC: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. BB: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. MKS: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. YZ: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work. ED: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; and final approval of the version to be published. DAS: Drafting the work or revising it critically for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. SCG: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; Drafting the work or revising it critically for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. MKS: Drafting the work or revising it critically for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Funding

This work was supported by the NIH (5T32HL007121-45 to SBG; HD089940, HD000849, RR024980, 3UL1TR002537, P50HD10355601A1 to MKS; T32 HL007344 to BMS), the American Heart Association (AHA) (18SCG34350001 and 19IPLOI34760288 to MKS; 22POST30908921 to SBG), a startup award from the University of Iowa Carver College of Medicine (SCG), and the Carver College of Medicine and Iowa Neuroscience Institute Carver Trust Early-Stage Investigator award (to SCG).

Competing interests

MKS is a member of the Medical Advisory Board for Comanche Pharmaceuticals and EndPreeclampsia, LLC. DAS is a member of the Medical Advisory Board for EndPreeclampsia, LLC. DAS and MKS hold patents related to the prediction and treatment of preeclampsia: US 293 #9,937,182 (April 10, 2018), EU #2,954,324, and PCT/US2018/027152. All other authors report no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

The online version contains supplementary material available at 10.1038/s41386-023-01749-3.

References

1.O’Connor E, Rossom RC, Henninger M, Groom HC, Burda BU, Henderson JT, et al. Screening for Depression in Adults: An Updated Systematic Evidence Review for the U.S. Preventive Services Task Force. 2016. [PubMed]
2.Trost SL, Beauregard JL, Smoots AN, Ko JY, Haight SC, Moore Simas TA, et al. Preventing Pregnancy-Related Mental Health Deaths: Insights From 14 US Maternal Mortality Review Committees, 2008-17. Health Aff (Millwood) 2021;40:1551–59. doi: 10.1377/hlthaff.2021.00615. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Shuman CJ, Peahl AF, Pareddy N, Morgan ME, Chiangong J, Veliz PT, et al. Postpartum depression and associated risk factors during the COVID-19 pandemic. BMC Res Notes. 2022;15:102. doi: 10.1186/s13104-022-05991-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Bonari L, Bennett H, Einarson A, Koren G. Risks of untreated depression during pregnancy. Can Fam Physician. 2004;50:37–9. [PMC free article] [PubMed] [Google Scholar]
5.Goldman-Mellor S, Margerison CE. Maternal drug-related death and suicide are leading causes of postpartum death in California. Am J Obstet Gynecol. 2019;221:489e1–89e9. doi: 10.1016/j.ajog.2019.05.045. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Liu X, Jin G, Fan B, Xing Y, Wang L, Wang M, et al. The impact of ALDH2 activation by Alda-1 on the expression of VEGF in the hippocampus of a rat model of post-MI depression. Neurosci Lett. 2018;674:156–61.. doi: 10.1016/j.neulet.2018.03.048. [DOI] [PubMed] [Google Scholar]
7.Marcus SM. Depression during pregnancy: rates, risks and consequences–Motherisk Update 2008. Can J Clin Pharmacol. 2009;16:e15–22. [PubMed] [Google Scholar]
8.Bunevicius R, Kusminskas L, Bunevicius A, Nadisauskiene RJ, Jureniene K, Pop VJ. Psychosocial risk factors for depression during pregnancy. Acta Obstet Gynecol Scand. 2009;88:599–605. doi: 10.1080/00016340902846049. [DOI] [PubMed] [Google Scholar]
9.Silverman ME, Reichenberg A, Savitz DA, Cnattingius S, Lichtenstein P, Hultman CM, et al. The risk factors for postpartum depression: A population-based study. Depress Anxiety. 2017;34:178–87.. doi: 10.1002/da.22597. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Vignato JA, Gumusoglu SB, Davis HA, Scroggins SM, Hamilton WS, Brandt DS, et al. Selective Serotonin Reuptake Inhibitor Use in Pregnancy and Protective Mechanisms in Preeclampsia. Reprod Sci. 2022; 30:701–12 [DOI] [PMC free article] [PubMed]
11.Qiu C, Sanchez SE, Lam N, Garcia P, Williams MA. Associations of depression and depressive symptoms with preeclampsia: results from a Peruvian case-control study. BMC Womens Health. 2007;7:15. doi: 10.1186/1472-6874-7-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Caropreso L, de Azevedo Cardoso T, Eltayebani M, Frey BN. Preeclampsia as a risk factor for postpartum depression and psychosis: a systematic review and meta-analysis. Arch Womens Ment Health. 2020;23:493–505. doi: 10.1007/s00737-019-01010-1. [DOI] [PubMed] [Google Scholar]
13.Palmsten K, Setoguchi S, Margulis AV, Patrick AR, Hernández-Díaz S. Elevated risk of preeclampsia in pregnant women with depression: depression or antidepressants? Am J Epidemiol. 2012;175:988–97. doi: 10.1093/aje/kwr394. [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Srajer A, Johnson JA, Yusuf K. Preeclampsia and postpartum mental health: mechanisms and clinical implications. J Matern Fetal Neonatal Med. 2022;35:8443–49.. doi: 10.1080/14767058.2021.1978067. [DOI] [PubMed] [Google Scholar]
15.Bolte AC, van Geijn HP, Dekker GA. Pathophysiology of preeclampsia and the role of serotonin. Eur J Obstet Gynecol Reprod Biol. 2001;95:12–21. doi: 10.1016/S0301-2115(00)00367-5. [DOI] [PubMed] [Google Scholar]
16.Lang U, Prada J, Clark KE. Systemic and uterine vascular response to serotonin in third trimester pregnant ewes. Eur J Obstet Gynecol Reprod Biol. 1993;51:131–8. doi: 10.1016/0028-2243(93)90025-8. [DOI] [PubMed] [Google Scholar]
17.Bodelsson G, Marsál K, Stjernquist M. Reduced contractile effect of endothelin-1 and noradrenalin in human umbilical artery from pregnancies with abnormal umbilical artery flow velocity waveforms. Early Hum Dev. 1995;42:15–28. doi: 10.1016/0378-3782(95)01636-H. [DOI] [PubMed] [Google Scholar]
18.Feng X, Zhang Y, Tao J, Lu L, Liu J, Zhao M, et al. Comparisons of vascular responses to vasoconstrictors in human placenta in preeclampsia between preterm and later term. Curr Pharm Biotechnol. 2019; 21:727–33 [DOI] [PubMed]
19.Gumusoglu S, Scroggins S, Vignato J, Santillan D, Santillan M. The Serotonin-Immune Axis in Preeclampsia. Curr Hypertens Rep. 2021;23:37. doi: 10.1007/s11906-021-01155-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Santillan MK, Santillan DA, Scroggins SM, Min JY, Sandgren JA, Pearson NA, et al. Vasopressin in preeclampsia: a novel very early human pregnancy biomarker and clinically relevant mouse model. Hypertension. 2014;64:852–9. doi: 10.1161/HYPERTENSIONAHA.114.03848. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Sandgren JA, Scroggins SM, Santillan DA, Devor EJ, Gibson-Corley KN, Pierce GL, et al. Vasopressin: the missing link for preeclampsia? Am J Physiol Regul Integr Comp Physiol. 2015;309:R1062–4. doi: 10.1152/ajpregu.00073.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Kashkouli M, Jahanian Sadatmahalleh S, Ziaei S, Kazemnejad A, Saber A, Darvishnia H, et al. Relationship between postpartum depression and plasma vasopressin level at 6-8 weeks postpartum: a cross-sectional study. Sci Rep. 2023;13:3518. doi: 10.1038/s41598-022-27223-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Gumusoglu S, Davis L, Schickling B, Devor E, Von Tersch L, Santillan M, et al. Effects of maternal hypertension on cord blood Arginine vasopressin receptor expression. Pregnancy Hypertens. 2023;31:1–3. doi: 10.1016/j.preghy.2022.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.McNestry C, Killeen SL, Crowley RK, McAuliffe FM. Pregnancy complications and later life women’s health. Acta Obstet Gynecol Scand. 2023;102:523–31.. doi: 10.1111/aogs.14523. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Szczepanska-Sadowska E. The Heart as a Target of Vasopressin and Other Cardiovascular Peptides in Health and Cardiovascular Diseases. Int J Mol Sci. 2022;23:14414. doi: 10.3390/ijms232214414. [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Golyszny M, Obuchowicz E. Are neuropeptides relevant for the mechanism of action of SSRIs? Neuropeptides. 2019;75:1–17. doi: 10.1016/j.npep.2019.02.002. [DOI] [PubMed] [Google Scholar]
27.Okimoto N, Bosch OJ, Slattery DA, Pflaum K, Matsushita H, Wei FY, et al. RGS2 mediates the anxiolytic effect of oxytocin. Brain Res. 2012;1453:26–33. doi: 10.1016/j.brainres.2012.03.012. [DOI] [PubMed] [Google Scholar]
28.Smoller JW, Paulus MP, Fagerness JA, Purcell S, Yamaki LH, Hirshfeld-Becker D, et al. Influence of RGS2 on anxiety-related temperament, personality, and brain function. Arch Gen Psych. 2008;65:298–308. doi: 10.1001/archgenpsychiatry.2007.48. [DOI] [PubMed] [Google Scholar]
29.Perschbacher KJ, Deng G, Fisher RA, Gibson-Corley KN, Santillan MK, Grobe JL. Regulators of G protein signaling in cardiovascular function during pregnancy. Physiol Genomics. 2018;50:590–604. doi: 10.1152/physiolgenomics.00037.2018. [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Karppanen T, Kaartokallio T, Klemetti MM, Heinonen S, Kajantie E, Kere J, et al. An RGS2 3’UTR polymorphism is associated with preeclampsia in overweight women. BMC Genet. 2016;17:121. doi: 10.1186/s12863-016-0428-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Kvehaugen AS, Melien O, Holmen OL, Laivuori H, Dechend R, Staff AC. Hypertension after preeclampsia and relation to the C1114G polymorphism (rs4606) in RGS2: data from the Norwegian HUNT2 study. BMC Med Genet. 2014;15:28. doi: 10.1186/1471-2350-15-28. [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Kvehaugen AS, Melien O, Holmen OL, Laivuori H, Oian P, Andersgaard AB, et al. Single nucleotide polymorphisms in G protein signaling pathway genes in preeclampsia. Hypertension. 2013;61:655–61. doi: 10.1161/HYPERTENSIONAHA.111.00331. [DOI] [PubMed] [Google Scholar]
33.Perschbacher KJ, Deng G, Sandgren JA, Walsh JW, Witcher PC, Sapouckey SA, et al. Reduced mRNA Expression of RGS2 (Regulator of G Protein Signaling-2) in the Placenta Is Associated With Human Preeclampsia and Sufficient to Cause Features of the Disorder in Mice. Hypertension. 2020;75:569–79. doi: 10.1161/HYPERTENSIONAHA.119.14056. [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Koch JN, Dahlen SA, Owens EA, Osei-Owusu P. Regulator of G Protein Signaling 2 Facilitates Uterine Artery Adaptation During Pregnancy in Mice. J Am Heart Assoc. 2019;8:e010917. doi: 10.1161/JAHA.118.010917. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Jie L, Owens EA, Plante LA, Fang Z, Rensing DT, Moeller KD, et al. RGS2 squelches vascular Gi/o and Gq signaling to modulate myogenic tone and promote uterine blood flow. Physiol Rep. 2016;4:e12692. doi: 10.14814/phy2.12692. [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Stein MB, Keshaviah A, Haddad SA, Van Ameringen M, Simon NM, Pollack MH, et al. Influence of RGS2 on sertraline treatment for social anxiety disorder. Neuropsychopharmacology. 2014;39:1340–6. doi: 10.1038/npp.2013.301. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Leygraf A, Hohoff C, Freitag C, Willis-Owen SA, Krakowitzky P, Fritze J, et al. Rgs 2 gene polymorphisms as modulators of anxiety in humans? J Neural Transm (Vienna) 2006;113:1921–5. doi: 10.1007/s00702-006-0484-8. [DOI] [PubMed] [Google Scholar]
38.Hohoff C, Weber H, Richter J, Domschke K, Zwanzger PM, Ohrmann P, et al. RGS2 ggenetic variation: association analysis with panic disorder and dimensional as well as intermediate phenotypes of anxiety. Am J Med Genet B Neuropsychiatr Genet. 2015;168B:211–22. doi: 10.1002/ajmg.b.32299. [DOI] [PubMed] [Google Scholar]
39.Mouri K, Hishimoto A, Fukutake M, Nishiguchi N, Shirakawa O, Maeda K. Association study of RGS2 gene polymorphisms with panic disorder in Japanese. Kobe J Med Sci. 2010;55:E116–21. [PubMed] [Google Scholar]
40.Amstadter AB, Koenen KC, Ruggiero KJ, Acierno R, Galea S, Kilpatrick DG, et al. Variant in RGS2 moderates posttraumatic stress symptoms following potentially traumatic event exposure. J Anxiety Disord. 2009;23:369–73. doi: 10.1016/j.janxdis.2008.12.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Williams AV, Peña CJ, Ramos-Maciel S, Laman-Maharg A, Ordoñez-Sanchez E, Britton M, et al. Comparative Transcriptional Analyses in the Nucleus Accumbens Identifies RGS2 as a Key Mediator of Depression-Related Behavior. Biol Psych. 2022;92:942–51. doi: 10.1016/j.biopsych.2022.06.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Amstadter AB, Koenen KC, Ruggiero KJ, Acierno R, Galea S, Kilpatrick DG, et al. Variation in RGS2 is associated with suicidal ideation in an epidemiological study of adults exposed to the 2004 Florida hurricanes. Arch Suicide Res. 2009;13:349–57. doi: 10.1080/13811110903266541. [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Lifschytz T, Broner EC, Zozulinsky P, Slonimsky A, Eitan R, Greenbaum L, et al. Relationship between Rgs2 gene expression level and anxiety and depression-like behaviour in a mutant mouse model: serotonergic involvement. Int J Neuropsychopharmacol. 2012;15:1307–18. doi: 10.1017/S1461145711001453. [DOI] [PubMed] [Google Scholar]
44.Raab A, Popp S, Lesch KP, Lohse MJ, Fischer M, Deckert J, et al. Increased fear learning, spatial learning as well as neophobia in Rgs2. Genes Brain Behav. 2018;17:e12420. doi: 10.1111/gbb.12420. [DOI] [PubMed] [Google Scholar]
45.Oliveira-Dos-Santos AJ, Matsumoto G, Snow BE, Bai D, Houston FP, Whishaw IQ, et al. Regulation of T cell activation, anxiety, and male aggression by RGS2. Proc Natl Acad Sci. 2000;97:12272–7. doi: 10.1073/pnas.220414397. [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Luo Y, Kataoka Y, Ostinelli EG, Cipriani A, Furukawa TA. National Prescription Patterns of Antidepressants in the Treatment of Adults With Major Depression in the US Between 1996 and 2015: A Population Representative Survey Based Analysis. Front Psych. 2020;11:35. doi: 10.3389/fpsyt.2020.00035. [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Desaunay P, Eude LG, Dreyfus M, Alexandre C, Fedrizzi S, Alexandre J, et al. Benefits and Risks of Antidepressant Drugs During Pregnancy: A Systematic Review of Meta-analyses. Paediatr Drugs. 2023;25:247–65. doi: 10.1007/s40272-023-00561-2. [DOI] [PubMed] [Google Scholar]
48.Gumusoglu SB, Schickling BM, Vignato JA, Santillan DA, Santillan MK. Selective serotonin reuptake inhibitors and preeclampsia: A quality assessment and meta-analysis. Pregnancy Hypertens. 2022;30:36–43. doi: 10.1016/j.preghy.2022.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Tatsumi M, Groshan K, Blakely RD, Richelson E. Pharmacological profile of antidepressants and related compounds at human monoamine transporters. Eur J Pharmacol. 1997;340:249–58. doi: 10.1016/S0014-2999(97)01393-9. [DOI] [PubMed] [Google Scholar]
50.Gumusoglu SB, Chilukuri ASS, Santillan DA, Santillan MK, Stevens HE. Neurodevelopmental Outcomes of Prenatal Preeclampsia Exposure. Trends Neurosci. 2020;43:253–68. doi: 10.1016/j.tins.2020.02.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Gumusoglu SB, Fine RS, Murray SJ, Bittle JL, Stevens HE. The role of IL-6 in neurodevelopment after prenatal stress. Brain Behav Immun. 2017;65:274–83. doi: 10.1016/j.bbi.2017.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Gumusoglu SB, Hing BWQ, Chilukuri ASS, Dewitt JJ, Scroggins SM, Stevens HE. Chronic maternal interleukin-17 and autism-related cortical gene expression, neurobiology, and behavior. Neuropsychopharmacology. 2020;45:1008–17. doi: 10.1038/s41386-020-0640-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Gumusoglu SB, Chilukuri ASS, Hing BWQ, Scroggins SM, Kundu S, Sandgren JA, et al. Altered offspring neurodevelopment in an arginine vasopressin preeclampsia model. Transl Psych. 2021;11:79. doi: 10.1038/s41398-021-01205-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Fairless AH, Dow HC, Toledo MM, Malkus KA, Edelmann M, Li H, et al. Low sociability is associated with reduced size of the corpus callosum in the BALB/cJ inbred mouse strain. Brain Res. 2008;1230:211–7. doi: 10.1016/j.brainres.2008.07.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Fairless AH, Katz JM, Vijayvargiya N, Dow HC, Kreibich AS, Berrettini WH, et al. Development of home cage social behaviors in BALB/cJ vs. C57BL/6J mice. Behav Brain Res. 2013;237:338–47. doi: 10.1016/j.bbr.2012.08.051. [DOI] [PMC free article] [PubMed] [Google Scholar]
56.Ferri SL, Dow HC, Schoch H, Lee JY, Brodkin ES, Abel T. Age- and sex-specific fear conditioning deficits in mice lacking Pcdh10, an Autism Associated Gene. Neurobiol Learn Mem. 2021;178:107364. doi: 10.1016/j.nlm.2020.107364. [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Ferri SL, Kreibich AS, Torre M, Piccoli CT, Dow H, Pallathra AA, et al. Activation of basolateral amygdala in juvenile C57BL/6J mice during social approach behavior. Neuroscience. 2016;335:184–94. doi: 10.1016/j.neuroscience.2016.08.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Klomp AJ, Plumb A, Mehr JB, Madencioglu DA, Wen H, Williams AJ. Neuronal deletion of Ca(V)1.2 is associated with sex-specific behavioral phenotypes in mice. Sci Rep. 2022;12:22152. doi: 10.1038/s41598-022-26504-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Coryell MW, Wunsch AM, Haenfler JM, Allen JE, Schnizler M, Ziemann AE, et al. Acid-sensing ion channel-1a in the amygdala, a novel therapeutic target in depression-related behavior. J Neurosci. 2009;29:5381–8. doi: 10.1523/JNEUROSCI.0360-09.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Dailey ME, Waite M. Confocal imaging of microglial cell dynamics in hippocampal slice cultures. Methods. 1999;18:222–30. doi: 10.1006/meth.1999.0775. [DOI] [PubMed] [Google Scholar]
61.Grossmann R, Stence N, Carr J, Fuller L, Waite M, Dailey ME. Juxtavascular microglia migrate along brain microvessels following activation during early postnatal development. Glia. 2002;37:229–40. doi: 10.1002/glia.10031. [DOI] [PubMed] [Google Scholar]
62.Luna RL, Kay VR, Ratsep MT, Khalaj K, Bidarimath M, Peterson N, et al. Placental growth factor deficiency is associated with impaired cerebral vascular development in mice. Mol Hum Reprod. 2016;22:130–42. doi: 10.1093/molehr/gav069. [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Sandgren JA, Deng G, Linggonegoro DW, Scroggins SM, Perschbacher KJ, Nair AR, et al. Arginine vasopressin infusion is sufficient to model clinical features of preeclampsia in mice. JCI Insight. 2018;3:e99403. doi: 10.1172/jci.insight.99403. [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Kucuk M, Kaya M, Kalayci R, Cimen V, Kudat H, Arican N, et al. Effects of losartan on the blood-brain barrier permeability in long-term nitric oxide blockade-induced hypertensive rats. Life Sci. 2002;71:937–46. doi: 10.1016/S0024-3205(02)01772-1. [DOI] [PubMed] [Google Scholar]
65.Khamma JK, Copeland DS, Hake HS, Gantz SC. Spatiotemporal Control of Noradrenaline-Dependent Synaptic Transmission in Mouse Dorsal Raphe Serotonin Neurons. J Neurosci. 2022;42:968–79. doi: 10.1523/JNEUROSCI.1176-21.2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Gantz SC, Levitt ES, Llamosas N, Neve KA, Williams JT. Depression of Serotonin Synaptic Transmission by the Dopamine Precursor L-DOPA. Cell Rep. 2015;12:944–54. doi: 10.1016/j.celrep.2015.07.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
67.Santillan MK, Pelham CJ, Ketsawatsomkron P, Santillan DA, Davis DR, Devor EJ, et al. Pregnant mice lacking indoleamine 2,3-dioxygenase exhibit preeclampsia phenotypes. Physiol Rep. 2015;3:e12257. doi: 10.14814/phy2.12257. [DOI] [PMC free article] [PubMed] [Google Scholar]
68.Jabarin R, Netser S, Wagner S. Beyond the three-chamber test: toward a multimodal and objective assessment of social behavior in rodents. Mol Autism. 2022;13:41. doi: 10.1186/s13229-022-00521-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Sideromenos S, Lindtner C, Zambon A, Horvath O, Berger A, Pollak DD. VEGF Treatment Ameliorates Depression-Like Behavior in Adult Offspring After Maternal Immune Activation. Cells. 2020;9:1048. doi: 10.3390/cells9041048. [DOI] [PMC free article] [PubMed] [Google Scholar]
70.Ghavami A, Hunt RA, Olsen MA, Zhang J, Smith DL, Kalgaonkar S, et al. Differential effects of regulator of G protein signaling (RGS) proteins on serotonin 5-HT1A, 5-HT2A, and dopamine D2 receptor-mediated signaling and adenylyl cyclase activity. Cell Signal. 2004;16:711–21. doi: 10.1016/j.cellsig.2003.11.006. [DOI] [PubMed] [Google Scholar]
71.Mark MD, Wollenweber P, Gesk A, Kösters K, Batzke K, Janoschka C, et al. RGS2 drives male aggression in mice via the serotonergic system. Commun Biol. 2019;2:373. doi: 10.1038/s42003-019-0622-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
72.Christmas DM, Potokar J, Davies SJ. A biological pathway linking inflammation and depression: activation of indoleamine 2,3-dioxygenase. Neuropsychiatr Dis Treat. 2011;7:431–9. doi: 10.2147/NDT.S17573. [DOI] [PMC free article] [PubMed] [Google Scholar]
73.Maes M, Leonard BE, Myint AM, Kubera M, Verkerk R. The new ‘5-HT’ hypothesis of depression: cell-mediated immune activation induces indoleamine 2,3-dioxygenase, which leads to lower plasma tryptophan and an increased synthesis of detrimental tryptophan catabolites (TRYCATs), both of which contribute to the onset of depression. Prog Neuropsychopharmacol Biol Psych. 2011;35:702–21. doi: 10.1016/j.pnpbp.2010.12.017. [DOI] [PubMed] [Google Scholar]
74.Muller N, Schwarz MJ. The immune-mediated alteration of serotonin and glutamate: towards an integrated view of depression. Mol Psych. 2007;12:988–1000. doi: 10.1038/sj.mp.4002006. [DOI] [PubMed] [Google Scholar]
75.O’Connor JC, Lawson MA, Andre C, Moreau M, Lestage J, Castanon N, et al. Lipopolysaccharide-induced depressive-like behavior is mediated by indoleamine 2,3-dioxygenase activation in mice. Mol Psych. 2009;14:511–22. doi: 10.1038/sj.mp.4002148. [DOI] [PMC free article] [PubMed] [Google Scholar]
76.Williams JT, Colmers WF, Pan ZZ. Voltage- and ligand-activated inwardly rectifying currents in dorsal raphe neurons in vitro. J Neurosci. 1988;8:3499–506. doi: 10.1523/JNEUROSCI.08-09-03499.1988. [DOI] [PMC free article] [PubMed] [Google Scholar]
77.Courtney NA, Ford CP. Mechanisms of 5-HT1A receptor-mediated transmission in dorsal raphe serotonin neurons. J Physiol. 2016;594:953–65. doi: 10.1113/JP271716. [DOI] [PMC free article] [PubMed] [Google Scholar]
78.Redman CWG, Staff AC, Roberts JM. Syncytiotrophoblast stress in preeclampsia: the convergence point for multiple pathways. Am J Obstet Gynecol. 2022;226:S907–S27. doi: 10.1016/j.ajog.2020.09.047. [DOI] [PubMed] [Google Scholar]
79.Harmon AC, Cornelius DC, Amaral LM, Faulkner JL, Cunningham MW, Jr, Wallace K, et al. The role of inflammation in the pathology of preeclampsia. Clin Sci (Lond) 2016;130:409–19. doi: 10.1042/CS20150702. [DOI] [PMC free article] [PubMed] [Google Scholar]
80.Cornelius DC. Preeclampsia: From Inflammation to Immunoregulation. Clin Med Insights Blood Disord. 2018;11:1179545X17752325. doi: 10.1177/1179545X17752325. [DOI] [PMC free article] [PubMed] [Google Scholar]
81.D’Souza MS, Seeley SL, Emerson N, Rose-Malkamaki MJ, Ho SP, Tsai YC, et al. Attenuation of nicotine-induced rewarding and antidepressant-like effects in male and female mice lacking regulator of G-protein signaling 2. Pharmacol Biochem Behav. 2022;213:173338. doi: 10.1016/j.pbb.2022.173338. [DOI] [PubMed] [Google Scholar]
82.Klonoff-Cohen HS, Cross JL, Pieper CF. Job stress and preeclampsia. Epidemiology. 1996;7:245–9. doi: 10.1097/00001648-199605000-00005. [DOI] [PubMed] [Google Scholar]
83.Roberts AL, Lyall K, Rich-Edwards JW, Ascherio A, Weisskopf MG. Association of maternal exposure to childhood abuse with elevated risk for autism in offspring. JAMA Psych. 2013;70:508–15. doi: 10.1001/jamapsychiatry.2013.447. [DOI] [PMC free article] [PubMed] [Google Scholar]
84.Wang A, Rana S, Karumanchi SA. Preeclampsia: the role of angiogenic factors in its pathogenesis. Physiology (Bethesda) 2009;24:147–58. doi: 10.1152/physiol.00043.2008. [DOI] [PubMed] [Google Scholar]
85.Villa PM, Marttinen P, Gillberg J, Lokki AI, Majander K, Orden MR, et al. Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study. PLoS One. 2017;12:e0174399. doi: 10.1371/journal.pone.0174399. [DOI] [PMC free article] [PubMed] [Google Scholar]
86.Koenen KC, Amstadter AB, Ruggiero KJ, Acierno R, Galea S, Kilpatrick DG, et al. RGS2 and generalized anxiety disorder in an epidemiologic sample of hurricane-exposed adults. Depress Anxiety. 2009;26:309–15. doi: 10.1002/da.20528. [DOI] [PMC free article] [PubMed] [Google Scholar]
87.Heximer SP. RGS2-mediated regulation of Gqalpha. Methods Enzymol. 2004;390:65–82. doi: 10.1016/S0076-6879(04)90005-5. [DOI] [PubMed] [Google Scholar]
88.Osei-Owusu P, Sabharwal R, Kaltenbronn KM, Rhee MH, Chapleau MW, Dietrich HH, et al. Regulator of G protein signaling 2 deficiency causes endothelial dysfunction and impaired endothelium-derived hyperpolarizing factor-mediated relaxation by dysregulating Gi/o signaling. J Biol Chem. 2012;287:12541–9. doi: 10.1074/jbc.M111.332130. [DOI] [PMC free article] [PubMed] [Google Scholar]
89.Tokudome T, Otani K, Mao Y, Jensen LJ, Arai Y, Miyazaki T, et al. Endothelial Natriuretic Peptide Receptor 1 Play Crucial Role for Acute and Chronic Blood Pressure Regulation by Atrial Natriuretic Peptide. Hypertension. 2022;79:1409–22. doi: 10.1161/HYPERTENSIONAHA.121.18114. [DOI] [PubMed] [Google Scholar]
90.D’Souza MS, Luu AN, Guisinger TC, Seeley SL, Waldschmidt RA, Chrissobolis S. Regulator of G-Protein Signaling 5 Protein Deficiency Differentially Influences Blood Pressure, Vascular and Behavioral Effects in Aged Male Mice. J Cardiovasc Pharmacol. 2022;80:305–13. doi: 10.1097/FJC.0000000000001272. [DOI] [PubMed] [Google Scholar]
91.Yalcin B, Willis-Owen SA, Fullerton J, Meesaq A, Deacon RM, Rawlins JN, et al. Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice. Nat Genet. 2004;36:1197–202. doi: 10.1038/ng1450. [DOI] [PubMed] [Google Scholar]
92.Pham H, Sieg J, Seeley SL, D’Souza MS. Differential methamphetamine-induced behavioral effects in male and female mice lacking regulator of G Protein signaling 4. Behav Brain Res. 2022;423:113770. doi: 10.1016/j.bbr.2022.113770. [DOI] [PubMed] [Google Scholar]
93.Rorabaugh BR, Rose MJ, Stoops TS, Stevens AA, Seeley SL, D’Souza MS. Regulators of G-protein signaling 2 and 4 differentially regulate cocaine-induced rewarding effects. Physiol Behav. 2018;195:9–19. doi: 10.1016/j.physbeh.2018.07.016. [DOI] [PubMed] [Google Scholar]
94.Rempe RG, Hartz AMS, Bauer B. Matrix metalloproteinases in the brain and blood-brain barrier: Versatile breakers and makers. J Cereb Blood Flow Metab. 2016;36:1481–507. doi: 10.1177/0271678X16655551. [DOI] [PMC free article] [PubMed] [Google Scholar]
95.Tsang CK, Liu Y, Thomas J, Zhang Y, Zheng XF. Superoxide dismutase 1 acts as a nuclear transcription factor to regulate oxidative stress resistance. Nat Commun. 2014;5:3446. doi: 10.1038/ncomms4446. [DOI] [PMC free article] [PubMed] [Google Scholar]
96.Eleutherio ECA, Silva Magalhaes RS, de Araujo Brasil A, Monteiro Neto JR, de Holanda Paranhos L. SOD1, more than just an antioxidant. Arch Biochem Biophys. 2021;697:108701. doi: 10.1016/j.abb.2020.108701. [DOI] [PubMed] [Google Scholar]
97.Milani P, Amadio M, Laforenza U, Dell’Orco M, Diamanti L, Sardone V, et al. Posttranscriptional regulation of SOD1 gene expression under oxidative stress: Potential role of ELAV proteins in sporadic ALS. Neurobiol Dis. 2013;60:51–60. doi: 10.1016/j.nbd.2013.08.005. [DOI] [PubMed] [Google Scholar]
98.Milani P, Gagliardi S, Cova E, Cereda C. SOD1 Transcriptional and Posttranscriptional Regulation and Its Potential Implications in ALS. Neurol Res Int. 2011;2011:458427. doi: 10.1155/2011/458427. [DOI] [PMC free article] [PubMed] [Google Scholar]
99.Deng Y, Dickey JE, Saito K, Deng G, Singh U, Jiang J, et al. Elucidating the role of Rgs2 expression in the PVN for metabolic homeostasis in mice. Mol Metab. 2022;66:101622. doi: 10.1016/j.molmet.2022.101622. [DOI] [PMC free article] [PubMed] [Google Scholar]
100.Lan N, Hellemans KG, Ellis L, Weinberg J. Exposure to Chronic Mild Stress Differentially Alters Corticotropin-Releasing Hormone and Arginine Vasopressin mRNA Expression in the Stress-Responsive Neurocircuitry of Male and Female Rats Prenatally Exposed to Alcohol. Alcohol Clin Exp Res. 2015;39:2414–21. doi: 10.1111/acer.12916. [DOI] [PMC free article] [PubMed] [Google Scholar]
101.Taylor PV, Veenema AH, Paul MJ, Bredewold R, Isaacs S, de Vries GJ. Sexually dimorphic effects of a prenatal immune challenge on social play and vasopressin expression in juvenile rats. Biol Sex Differ. 2012;3:15. doi: 10.1186/2042-6410-3-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
102.Goel N, Philippe TJ, Chang J, Koblanski ME, Viau V. Cellular and serotonergic correlates of habituated neuroendocrine responses in male and female rats. Psychoneuroendocrinology. 2022;136:105599. doi: 10.1016/j.psyneuen.2021.105599. [DOI] [PubMed] [Google Scholar]
103.Rood BD, Stott RT, You S, Smith CJ, Woodbury ME, De Vries GJ. Site of origin of and sex differences in the vasopressin innervation of the mouse (Mus musculus) brain. J Comp Neurol. 2013;521:2321–58. doi: 10.1002/cne.23288. [DOI] [PubMed] [Google Scholar]
104.de Souza Villa P, Menani JV, de Arruda Camargo GM, de Arruda Camargo LA, Saad WA. Activation of the serotonergic 5-HT1A receptor in the paraventricular nucleus of the hypothalamus inhibits water intake and increases urinary excretion in water-deprived rats. Regul Pept. 2008;150:14–20. doi: 10.1016/j.regpep.2008.05.003. [DOI] [PubMed] [Google Scholar]
105.Issotina Zibrila A, Li Y, Wang Z, Zhao G, Liu H, Leng J, et al. Acetylcholinesterase inhibition with Pyridostigmine attenuates hypertension and neuroinflammation in the paraventricular nucleus in rat model for Preeclampsia. Int Immunopharmacol. 2021;101:108365. doi: 10.1016/j.intimp.2021.108365. [DOI] [PubMed] [Google Scholar]
106.Matsuura T, Shinohara K, Iyonaga T, Hirooka Y, Tsutsui H. Prior exposure to placental ischemia causes increased salt sensitivity of blood pressure via vasopressin production and secretion in postpartum rats. J Hypertens. 2019;37:1657–67. doi: 10.1097/HJH.0000000000002091. [DOI] [PubMed] [Google Scholar]
107.Kato TM, Fujimori-Tonou N, Mizukami H, Ozawa K, Fujisawa S, Kato T. Presynaptic dysregulation of the paraventricular thalamic nucleus causes depression-like behavior. Sci Rep. 2019;9:16506. doi: 10.1038/s41598-019-52984-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
108.Stanton LM, Price AJ, Manning EE. Hypothalamic corticotrophin releasing hormone neurons in stress-induced psychopathology: Revaluation of synaptic contributions. J Neuroendocrinol. 2023;35:e13268. doi: 10.1111/jne.13268. [DOI] [PubMed] [Google Scholar]
109.Oliver DK, Intson K, Sargin D, Power SK, McNabb J, Ramsey AJ, et al. Chronic social isolation exerts opposing sex-specific consequences on serotonin neuronal excitability and behaviour. Neuropharmacology. 2020;168:108015. doi: 10.1016/j.neuropharm.2020.108015. [DOI] [PubMed] [Google Scholar]
110.McEuen JG, Semsar KA, Lim MA, Bale TL. Influence of sex and corticotropin-releasing factor pathways as determinants in serotonin sensitivity. Endocrinology. 2009;150:3709–16. doi: 10.1210/en.2008-1721. [DOI] [PMC free article] [PubMed] [Google Scholar]
111.Murray EJ, Gumusoglu SB, Santillan DA, Santillan MK. Manipulating CD4+ T Cell Pathways to Prevent Preeclampsia. Front Bioeng Biotechnol. 2022;9:811417. doi: 10.3389/fbioe.2021.811417. [DOI] [PMC free article] [PubMed] [Google Scholar]
112.Taylor WD, Aizenstein HJ, Alexopoulos GS. The vascular depression hypothesis: mechanisms linking vascular disease with depression. Mol Psych. 2013;18:963–74. doi: 10.1038/mp.2013.20. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Supplemental Materials and Methods^{(468.1KB, pdf)}

[CR1] 1.O’Connor E, Rossom RC, Henninger M, Groom HC, Burda BU, Henderson JT, et al. Screening for Depression in Adults: An Updated Systematic Evidence Review for the U.S. Preventive Services Task Force. 2016. [PubMed]

[CR2] 2.Trost SL, Beauregard JL, Smoots AN, Ko JY, Haight SC, Moore Simas TA, et al. Preventing Pregnancy-Related Mental Health Deaths: Insights From 14 US Maternal Mortality Review Committees, 2008-17. Health Aff (Millwood) 2021;40:1551–59. doi: 10.1377/hlthaff.2021.00615. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR3] 3.Shuman CJ, Peahl AF, Pareddy N, Morgan ME, Chiangong J, Veliz PT, et al. Postpartum depression and associated risk factors during the COVID-19 pandemic. BMC Res Notes. 2022;15:102. doi: 10.1186/s13104-022-05991-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR4] 4.Bonari L, Bennett H, Einarson A, Koren G. Risks of untreated depression during pregnancy. Can Fam Physician. 2004;50:37–9. [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.Goldman-Mellor S, Margerison CE. Maternal drug-related death and suicide are leading causes of postpartum death in California. Am J Obstet Gynecol. 2019;221:489e1–89e9. doi: 10.1016/j.ajog.2019.05.045. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Liu X, Jin G, Fan B, Xing Y, Wang L, Wang M, et al. The impact of ALDH2 activation by Alda-1 on the expression of VEGF in the hippocampus of a rat model of post-MI depression. Neurosci Lett. 2018;674:156–61.. doi: 10.1016/j.neulet.2018.03.048. [DOI] [PubMed] [Google Scholar]

[CR7] 7.Marcus SM. Depression during pregnancy: rates, risks and consequences–Motherisk Update 2008. Can J Clin Pharmacol. 2009;16:e15–22. [PubMed] [Google Scholar]

[CR8] 8.Bunevicius R, Kusminskas L, Bunevicius A, Nadisauskiene RJ, Jureniene K, Pop VJ. Psychosocial risk factors for depression during pregnancy. Acta Obstet Gynecol Scand. 2009;88:599–605. doi: 10.1080/00016340902846049. [DOI] [PubMed] [Google Scholar]

[CR9] 9.Silverman ME, Reichenberg A, Savitz DA, Cnattingius S, Lichtenstein P, Hultman CM, et al. The risk factors for postpartum depression: A population-based study. Depress Anxiety. 2017;34:178–87.. doi: 10.1002/da.22597. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Vignato JA, Gumusoglu SB, Davis HA, Scroggins SM, Hamilton WS, Brandt DS, et al. Selective Serotonin Reuptake Inhibitor Use in Pregnancy and Protective Mechanisms in Preeclampsia. Reprod Sci. 2022; 30:701–12 [DOI] [PMC free article] [PubMed]

[CR11] 11.Qiu C, Sanchez SE, Lam N, Garcia P, Williams MA. Associations of depression and depressive symptoms with preeclampsia: results from a Peruvian case-control study. BMC Womens Health. 2007;7:15. doi: 10.1186/1472-6874-7-15. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.Caropreso L, de Azevedo Cardoso T, Eltayebani M, Frey BN. Preeclampsia as a risk factor for postpartum depression and psychosis: a systematic review and meta-analysis. Arch Womens Ment Health. 2020;23:493–505. doi: 10.1007/s00737-019-01010-1. [DOI] [PubMed] [Google Scholar]

[CR13] 13.Palmsten K, Setoguchi S, Margulis AV, Patrick AR, Hernández-Díaz S. Elevated risk of preeclampsia in pregnant women with depression: depression or antidepressants? Am J Epidemiol. 2012;175:988–97. doi: 10.1093/aje/kwr394. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR14] 14.Srajer A, Johnson JA, Yusuf K. Preeclampsia and postpartum mental health: mechanisms and clinical implications. J Matern Fetal Neonatal Med. 2022;35:8443–49.. doi: 10.1080/14767058.2021.1978067. [DOI] [PubMed] [Google Scholar]

[CR15] 15.Bolte AC, van Geijn HP, Dekker GA. Pathophysiology of preeclampsia and the role of serotonin. Eur J Obstet Gynecol Reprod Biol. 2001;95:12–21. doi: 10.1016/S0301-2115(00)00367-5. [DOI] [PubMed] [Google Scholar]

[CR16] 16.Lang U, Prada J, Clark KE. Systemic and uterine vascular response to serotonin in third trimester pregnant ewes. Eur J Obstet Gynecol Reprod Biol. 1993;51:131–8. doi: 10.1016/0028-2243(93)90025-8. [DOI] [PubMed] [Google Scholar]

[CR17] 17.Bodelsson G, Marsál K, Stjernquist M. Reduced contractile effect of endothelin-1 and noradrenalin in human umbilical artery from pregnancies with abnormal umbilical artery flow velocity waveforms. Early Hum Dev. 1995;42:15–28. doi: 10.1016/0378-3782(95)01636-H. [DOI] [PubMed] [Google Scholar]

[CR18] 18.Feng X, Zhang Y, Tao J, Lu L, Liu J, Zhao M, et al. Comparisons of vascular responses to vasoconstrictors in human placenta in preeclampsia between preterm and later term. Curr Pharm Biotechnol. 2019; 21:727–33 [DOI] [PubMed]

[CR19] 19.Gumusoglu S, Scroggins S, Vignato J, Santillan D, Santillan M. The Serotonin-Immune Axis in Preeclampsia. Curr Hypertens Rep. 2021;23:37. doi: 10.1007/s11906-021-01155-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Santillan MK, Santillan DA, Scroggins SM, Min JY, Sandgren JA, Pearson NA, et al. Vasopressin in preeclampsia: a novel very early human pregnancy biomarker and clinically relevant mouse model. Hypertension. 2014;64:852–9. doi: 10.1161/HYPERTENSIONAHA.114.03848. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Sandgren JA, Scroggins SM, Santillan DA, Devor EJ, Gibson-Corley KN, Pierce GL, et al. Vasopressin: the missing link for preeclampsia? Am J Physiol Regul Integr Comp Physiol. 2015;309:R1062–4. doi: 10.1152/ajpregu.00073.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Kashkouli M, Jahanian Sadatmahalleh S, Ziaei S, Kazemnejad A, Saber A, Darvishnia H, et al. Relationship between postpartum depression and plasma vasopressin level at 6-8 weeks postpartum: a cross-sectional study. Sci Rep. 2023;13:3518. doi: 10.1038/s41598-022-27223-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR23] 23.Gumusoglu S, Davis L, Schickling B, Devor E, Von Tersch L, Santillan M, et al. Effects of maternal hypertension on cord blood Arginine vasopressin receptor expression. Pregnancy Hypertens. 2023;31:1–3. doi: 10.1016/j.preghy.2022.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.McNestry C, Killeen SL, Crowley RK, McAuliffe FM. Pregnancy complications and later life women’s health. Acta Obstet Gynecol Scand. 2023;102:523–31.. doi: 10.1111/aogs.14523. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR25] 25.Szczepanska-Sadowska E. The Heart as a Target of Vasopressin and Other Cardiovascular Peptides in Health and Cardiovascular Diseases. Int J Mol Sci. 2022;23:14414. doi: 10.3390/ijms232214414. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR26] 26.Golyszny M, Obuchowicz E. Are neuropeptides relevant for the mechanism of action of SSRIs? Neuropeptides. 2019;75:1–17. doi: 10.1016/j.npep.2019.02.002. [DOI] [PubMed] [Google Scholar]

[CR27] 27.Okimoto N, Bosch OJ, Slattery DA, Pflaum K, Matsushita H, Wei FY, et al. RGS2 mediates the anxiolytic effect of oxytocin. Brain Res. 2012;1453:26–33. doi: 10.1016/j.brainres.2012.03.012. [DOI] [PubMed] [Google Scholar]

[CR28] 28.Smoller JW, Paulus MP, Fagerness JA, Purcell S, Yamaki LH, Hirshfeld-Becker D, et al. Influence of RGS2 on anxiety-related temperament, personality, and brain function. Arch Gen Psych. 2008;65:298–308. doi: 10.1001/archgenpsychiatry.2007.48. [DOI] [PubMed] [Google Scholar]

[CR29] 29.Perschbacher KJ, Deng G, Fisher RA, Gibson-Corley KN, Santillan MK, Grobe JL. Regulators of G protein signaling in cardiovascular function during pregnancy. Physiol Genomics. 2018;50:590–604. doi: 10.1152/physiolgenomics.00037.2018. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR30] 30.Karppanen T, Kaartokallio T, Klemetti MM, Heinonen S, Kajantie E, Kere J, et al. An RGS2 3’UTR polymorphism is associated with preeclampsia in overweight women. BMC Genet. 2016;17:121. doi: 10.1186/s12863-016-0428-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR31] 31.Kvehaugen AS, Melien O, Holmen OL, Laivuori H, Dechend R, Staff AC. Hypertension after preeclampsia and relation to the C1114G polymorphism (rs4606) in RGS2: data from the Norwegian HUNT2 study. BMC Med Genet. 2014;15:28. doi: 10.1186/1471-2350-15-28. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR32] 32.Kvehaugen AS, Melien O, Holmen OL, Laivuori H, Oian P, Andersgaard AB, et al. Single nucleotide polymorphisms in G protein signaling pathway genes in preeclampsia. Hypertension. 2013;61:655–61. doi: 10.1161/HYPERTENSIONAHA.111.00331. [DOI] [PubMed] [Google Scholar]

[CR33] 33.Perschbacher KJ, Deng G, Sandgren JA, Walsh JW, Witcher PC, Sapouckey SA, et al. Reduced mRNA Expression of RGS2 (Regulator of G Protein Signaling-2) in the Placenta Is Associated With Human Preeclampsia and Sufficient to Cause Features of the Disorder in Mice. Hypertension. 2020;75:569–79. doi: 10.1161/HYPERTENSIONAHA.119.14056. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR34] 34.Koch JN, Dahlen SA, Owens EA, Osei-Owusu P. Regulator of G Protein Signaling 2 Facilitates Uterine Artery Adaptation During Pregnancy in Mice. J Am Heart Assoc. 2019;8:e010917. doi: 10.1161/JAHA.118.010917. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Jie L, Owens EA, Plante LA, Fang Z, Rensing DT, Moeller KD, et al. RGS2 squelches vascular Gi/o and Gq signaling to modulate myogenic tone and promote uterine blood flow. Physiol Rep. 2016;4:e12692. doi: 10.14814/phy2.12692. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR36] 36.Stein MB, Keshaviah A, Haddad SA, Van Ameringen M, Simon NM, Pollack MH, et al. Influence of RGS2 on sertraline treatment for social anxiety disorder. Neuropsychopharmacology. 2014;39:1340–6. doi: 10.1038/npp.2013.301. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR37] 37.Leygraf A, Hohoff C, Freitag C, Willis-Owen SA, Krakowitzky P, Fritze J, et al. Rgs 2 gene polymorphisms as modulators of anxiety in humans? J Neural Transm (Vienna) 2006;113:1921–5. doi: 10.1007/s00702-006-0484-8. [DOI] [PubMed] [Google Scholar]

[CR38] 38.Hohoff C, Weber H, Richter J, Domschke K, Zwanzger PM, Ohrmann P, et al. RGS2 ggenetic variation: association analysis with panic disorder and dimensional as well as intermediate phenotypes of anxiety. Am J Med Genet B Neuropsychiatr Genet. 2015;168B:211–22. doi: 10.1002/ajmg.b.32299. [DOI] [PubMed] [Google Scholar]

[CR39] 39.Mouri K, Hishimoto A, Fukutake M, Nishiguchi N, Shirakawa O, Maeda K. Association study of RGS2 gene polymorphisms with panic disorder in Japanese. Kobe J Med Sci. 2010;55:E116–21. [PubMed] [Google Scholar]

[CR40] 40.Amstadter AB, Koenen KC, Ruggiero KJ, Acierno R, Galea S, Kilpatrick DG, et al. Variant in RGS2 moderates posttraumatic stress symptoms following potentially traumatic event exposure. J Anxiety Disord. 2009;23:369–73. doi: 10.1016/j.janxdis.2008.12.005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR41] 41.Williams AV, Peña CJ, Ramos-Maciel S, Laman-Maharg A, Ordoñez-Sanchez E, Britton M, et al. Comparative Transcriptional Analyses in the Nucleus Accumbens Identifies RGS2 as a Key Mediator of Depression-Related Behavior. Biol Psych. 2022;92:942–51. doi: 10.1016/j.biopsych.2022.06.030. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Amstadter AB, Koenen KC, Ruggiero KJ, Acierno R, Galea S, Kilpatrick DG, et al. Variation in RGS2 is associated with suicidal ideation in an epidemiological study of adults exposed to the 2004 Florida hurricanes. Arch Suicide Res. 2009;13:349–57. doi: 10.1080/13811110903266541. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Lifschytz T, Broner EC, Zozulinsky P, Slonimsky A, Eitan R, Greenbaum L, et al. Relationship between Rgs2 gene expression level and anxiety and depression-like behaviour in a mutant mouse model: serotonergic involvement. Int J Neuropsychopharmacol. 2012;15:1307–18. doi: 10.1017/S1461145711001453. [DOI] [PubMed] [Google Scholar]

[CR44] 44.Raab A, Popp S, Lesch KP, Lohse MJ, Fischer M, Deckert J, et al. Increased fear learning, spatial learning as well as neophobia in Rgs2. Genes Brain Behav. 2018;17:e12420. doi: 10.1111/gbb.12420. [DOI] [PubMed] [Google Scholar]

[CR45] 45.Oliveira-Dos-Santos AJ, Matsumoto G, Snow BE, Bai D, Houston FP, Whishaw IQ, et al. Regulation of T cell activation, anxiety, and male aggression by RGS2. Proc Natl Acad Sci. 2000;97:12272–7. doi: 10.1073/pnas.220414397. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR46] 46.Luo Y, Kataoka Y, Ostinelli EG, Cipriani A, Furukawa TA. National Prescription Patterns of Antidepressants in the Treatment of Adults With Major Depression in the US Between 1996 and 2015: A Population Representative Survey Based Analysis. Front Psych. 2020;11:35. doi: 10.3389/fpsyt.2020.00035. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR47] 47.Desaunay P, Eude LG, Dreyfus M, Alexandre C, Fedrizzi S, Alexandre J, et al. Benefits and Risks of Antidepressant Drugs During Pregnancy: A Systematic Review of Meta-analyses. Paediatr Drugs. 2023;25:247–65. doi: 10.1007/s40272-023-00561-2. [DOI] [PubMed] [Google Scholar]

[CR48] 48.Gumusoglu SB, Schickling BM, Vignato JA, Santillan DA, Santillan MK. Selective serotonin reuptake inhibitors and preeclampsia: A quality assessment and meta-analysis. Pregnancy Hypertens. 2022;30:36–43. doi: 10.1016/j.preghy.2022.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR49] 49.Tatsumi M, Groshan K, Blakely RD, Richelson E. Pharmacological profile of antidepressants and related compounds at human monoamine transporters. Eur J Pharmacol. 1997;340:249–58. doi: 10.1016/S0014-2999(97)01393-9. [DOI] [PubMed] [Google Scholar]

[CR50] 50.Gumusoglu SB, Chilukuri ASS, Santillan DA, Santillan MK, Stevens HE. Neurodevelopmental Outcomes of Prenatal Preeclampsia Exposure. Trends Neurosci. 2020;43:253–68. doi: 10.1016/j.tins.2020.02.003. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR51] 51.Gumusoglu SB, Fine RS, Murray SJ, Bittle JL, Stevens HE. The role of IL-6 in neurodevelopment after prenatal stress. Brain Behav Immun. 2017;65:274–83. doi: 10.1016/j.bbi.2017.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR52] 52.Gumusoglu SB, Hing BWQ, Chilukuri ASS, Dewitt JJ, Scroggins SM, Stevens HE. Chronic maternal interleukin-17 and autism-related cortical gene expression, neurobiology, and behavior. Neuropsychopharmacology. 2020;45:1008–17. doi: 10.1038/s41386-020-0640-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR53] 53.Gumusoglu SB, Chilukuri ASS, Hing BWQ, Scroggins SM, Kundu S, Sandgren JA, et al. Altered offspring neurodevelopment in an arginine vasopressin preeclampsia model. Transl Psych. 2021;11:79. doi: 10.1038/s41398-021-01205-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR54] 54.Fairless AH, Dow HC, Toledo MM, Malkus KA, Edelmann M, Li H, et al. Low sociability is associated with reduced size of the corpus callosum in the BALB/cJ inbred mouse strain. Brain Res. 2008;1230:211–7. doi: 10.1016/j.brainres.2008.07.025. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR55] 55.Fairless AH, Katz JM, Vijayvargiya N, Dow HC, Kreibich AS, Berrettini WH, et al. Development of home cage social behaviors in BALB/cJ vs. C57BL/6J mice. Behav Brain Res. 2013;237:338–47. doi: 10.1016/j.bbr.2012.08.051. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR56] 56.Ferri SL, Dow HC, Schoch H, Lee JY, Brodkin ES, Abel T. Age- and sex-specific fear conditioning deficits in mice lacking Pcdh10, an Autism Associated Gene. Neurobiol Learn Mem. 2021;178:107364. doi: 10.1016/j.nlm.2020.107364. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR57] 57.Ferri SL, Kreibich AS, Torre M, Piccoli CT, Dow H, Pallathra AA, et al. Activation of basolateral amygdala in juvenile C57BL/6J mice during social approach behavior. Neuroscience. 2016;335:184–94. doi: 10.1016/j.neuroscience.2016.08.006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR58] 58.Klomp AJ, Plumb A, Mehr JB, Madencioglu DA, Wen H, Williams AJ. Neuronal deletion of Ca(V)1.2 is associated with sex-specific behavioral phenotypes in mice. Sci Rep. 2022;12:22152. doi: 10.1038/s41598-022-26504-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR59] 59.Coryell MW, Wunsch AM, Haenfler JM, Allen JE, Schnizler M, Ziemann AE, et al. Acid-sensing ion channel-1a in the amygdala, a novel therapeutic target in depression-related behavior. J Neurosci. 2009;29:5381–8. doi: 10.1523/JNEUROSCI.0360-09.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR60] 60.Dailey ME, Waite M. Confocal imaging of microglial cell dynamics in hippocampal slice cultures. Methods. 1999;18:222–30. doi: 10.1006/meth.1999.0775. [DOI] [PubMed] [Google Scholar]

[CR61] 61.Grossmann R, Stence N, Carr J, Fuller L, Waite M, Dailey ME. Juxtavascular microglia migrate along brain microvessels following activation during early postnatal development. Glia. 2002;37:229–40. doi: 10.1002/glia.10031. [DOI] [PubMed] [Google Scholar]

[CR62] 62.Luna RL, Kay VR, Ratsep MT, Khalaj K, Bidarimath M, Peterson N, et al. Placental growth factor deficiency is associated with impaired cerebral vascular development in mice. Mol Hum Reprod. 2016;22:130–42. doi: 10.1093/molehr/gav069. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR63] 63.Sandgren JA, Deng G, Linggonegoro DW, Scroggins SM, Perschbacher KJ, Nair AR, et al. Arginine vasopressin infusion is sufficient to model clinical features of preeclampsia in mice. JCI Insight. 2018;3:e99403. doi: 10.1172/jci.insight.99403. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR64] 64.Kucuk M, Kaya M, Kalayci R, Cimen V, Kudat H, Arican N, et al. Effects of losartan on the blood-brain barrier permeability in long-term nitric oxide blockade-induced hypertensive rats. Life Sci. 2002;71:937–46. doi: 10.1016/S0024-3205(02)01772-1. [DOI] [PubMed] [Google Scholar]

[CR65] 65.Khamma JK, Copeland DS, Hake HS, Gantz SC. Spatiotemporal Control of Noradrenaline-Dependent Synaptic Transmission in Mouse Dorsal Raphe Serotonin Neurons. J Neurosci. 2022;42:968–79. doi: 10.1523/JNEUROSCI.1176-21.2021. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR66] 66.Gantz SC, Levitt ES, Llamosas N, Neve KA, Williams JT. Depression of Serotonin Synaptic Transmission by the Dopamine Precursor L-DOPA. Cell Rep. 2015;12:944–54. doi: 10.1016/j.celrep.2015.07.005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR67] 67.Santillan MK, Pelham CJ, Ketsawatsomkron P, Santillan DA, Davis DR, Devor EJ, et al. Pregnant mice lacking indoleamine 2,3-dioxygenase exhibit preeclampsia phenotypes. Physiol Rep. 2015;3:e12257. doi: 10.14814/phy2.12257. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR68] 68.Jabarin R, Netser S, Wagner S. Beyond the three-chamber test: toward a multimodal and objective assessment of social behavior in rodents. Mol Autism. 2022;13:41. doi: 10.1186/s13229-022-00521-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR69] 69.Sideromenos S, Lindtner C, Zambon A, Horvath O, Berger A, Pollak DD. VEGF Treatment Ameliorates Depression-Like Behavior in Adult Offspring After Maternal Immune Activation. Cells. 2020;9:1048. doi: 10.3390/cells9041048. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR70] 70.Ghavami A, Hunt RA, Olsen MA, Zhang J, Smith DL, Kalgaonkar S, et al. Differential effects of regulator of G protein signaling (RGS) proteins on serotonin 5-HT1A, 5-HT2A, and dopamine D2 receptor-mediated signaling and adenylyl cyclase activity. Cell Signal. 2004;16:711–21. doi: 10.1016/j.cellsig.2003.11.006. [DOI] [PubMed] [Google Scholar]

[CR71] 71.Mark MD, Wollenweber P, Gesk A, Kösters K, Batzke K, Janoschka C, et al. RGS2 drives male aggression in mice via the serotonergic system. Commun Biol. 2019;2:373. doi: 10.1038/s42003-019-0622-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR72] 72.Christmas DM, Potokar J, Davies SJ. A biological pathway linking inflammation and depression: activation of indoleamine 2,3-dioxygenase. Neuropsychiatr Dis Treat. 2011;7:431–9. doi: 10.2147/NDT.S17573. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR73] 73.Maes M, Leonard BE, Myint AM, Kubera M, Verkerk R. The new ‘5-HT’ hypothesis of depression: cell-mediated immune activation induces indoleamine 2,3-dioxygenase, which leads to lower plasma tryptophan and an increased synthesis of detrimental tryptophan catabolites (TRYCATs), both of which contribute to the onset of depression. Prog Neuropsychopharmacol Biol Psych. 2011;35:702–21. doi: 10.1016/j.pnpbp.2010.12.017. [DOI] [PubMed] [Google Scholar]

[CR74] 74.Muller N, Schwarz MJ. The immune-mediated alteration of serotonin and glutamate: towards an integrated view of depression. Mol Psych. 2007;12:988–1000. doi: 10.1038/sj.mp.4002006. [DOI] [PubMed] [Google Scholar]

[CR75] 75.O’Connor JC, Lawson MA, Andre C, Moreau M, Lestage J, Castanon N, et al. Lipopolysaccharide-induced depressive-like behavior is mediated by indoleamine 2,3-dioxygenase activation in mice. Mol Psych. 2009;14:511–22. doi: 10.1038/sj.mp.4002148. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR76] 76.Williams JT, Colmers WF, Pan ZZ. Voltage- and ligand-activated inwardly rectifying currents in dorsal raphe neurons in vitro. J Neurosci. 1988;8:3499–506. doi: 10.1523/JNEUROSCI.08-09-03499.1988. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR77] 77.Courtney NA, Ford CP. Mechanisms of 5-HT1A receptor-mediated transmission in dorsal raphe serotonin neurons. J Physiol. 2016;594:953–65. doi: 10.1113/JP271716. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR78] 78.Redman CWG, Staff AC, Roberts JM. Syncytiotrophoblast stress in preeclampsia: the convergence point for multiple pathways. Am J Obstet Gynecol. 2022;226:S907–S27. doi: 10.1016/j.ajog.2020.09.047. [DOI] [PubMed] [Google Scholar]

[CR79] 79.Harmon AC, Cornelius DC, Amaral LM, Faulkner JL, Cunningham MW, Jr, Wallace K, et al. The role of inflammation in the pathology of preeclampsia. Clin Sci (Lond) 2016;130:409–19. doi: 10.1042/CS20150702. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR80] 80.Cornelius DC. Preeclampsia: From Inflammation to Immunoregulation. Clin Med Insights Blood Disord. 2018;11:1179545X17752325. doi: 10.1177/1179545X17752325. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR81] 81.D’Souza MS, Seeley SL, Emerson N, Rose-Malkamaki MJ, Ho SP, Tsai YC, et al. Attenuation of nicotine-induced rewarding and antidepressant-like effects in male and female mice lacking regulator of G-protein signaling 2. Pharmacol Biochem Behav. 2022;213:173338. doi: 10.1016/j.pbb.2022.173338. [DOI] [PubMed] [Google Scholar]

[CR82] 82.Klonoff-Cohen HS, Cross JL, Pieper CF. Job stress and preeclampsia. Epidemiology. 1996;7:245–9. doi: 10.1097/00001648-199605000-00005. [DOI] [PubMed] [Google Scholar]

[CR83] 83.Roberts AL, Lyall K, Rich-Edwards JW, Ascherio A, Weisskopf MG. Association of maternal exposure to childhood abuse with elevated risk for autism in offspring. JAMA Psych. 2013;70:508–15. doi: 10.1001/jamapsychiatry.2013.447. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR84] 84.Wang A, Rana S, Karumanchi SA. Preeclampsia: the role of angiogenic factors in its pathogenesis. Physiology (Bethesda) 2009;24:147–58. doi: 10.1152/physiol.00043.2008. [DOI] [PubMed] [Google Scholar]

[CR85] 85.Villa PM, Marttinen P, Gillberg J, Lokki AI, Majander K, Orden MR, et al. Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study. PLoS One. 2017;12:e0174399. doi: 10.1371/journal.pone.0174399. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR86] 86.Koenen KC, Amstadter AB, Ruggiero KJ, Acierno R, Galea S, Kilpatrick DG, et al. RGS2 and generalized anxiety disorder in an epidemiologic sample of hurricane-exposed adults. Depress Anxiety. 2009;26:309–15. doi: 10.1002/da.20528. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR87] 87.Heximer SP. RGS2-mediated regulation of Gqalpha. Methods Enzymol. 2004;390:65–82. doi: 10.1016/S0076-6879(04)90005-5. [DOI] [PubMed] [Google Scholar]

[CR88] 88.Osei-Owusu P, Sabharwal R, Kaltenbronn KM, Rhee MH, Chapleau MW, Dietrich HH, et al. Regulator of G protein signaling 2 deficiency causes endothelial dysfunction and impaired endothelium-derived hyperpolarizing factor-mediated relaxation by dysregulating Gi/o signaling. J Biol Chem. 2012;287:12541–9. doi: 10.1074/jbc.M111.332130. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR89] 89.Tokudome T, Otani K, Mao Y, Jensen LJ, Arai Y, Miyazaki T, et al. Endothelial Natriuretic Peptide Receptor 1 Play Crucial Role for Acute and Chronic Blood Pressure Regulation by Atrial Natriuretic Peptide. Hypertension. 2022;79:1409–22. doi: 10.1161/HYPERTENSIONAHA.121.18114. [DOI] [PubMed] [Google Scholar]

[CR90] 90.D’Souza MS, Luu AN, Guisinger TC, Seeley SL, Waldschmidt RA, Chrissobolis S. Regulator of G-Protein Signaling 5 Protein Deficiency Differentially Influences Blood Pressure, Vascular and Behavioral Effects in Aged Male Mice. J Cardiovasc Pharmacol. 2022;80:305–13. doi: 10.1097/FJC.0000000000001272. [DOI] [PubMed] [Google Scholar]

[CR91] 91.Yalcin B, Willis-Owen SA, Fullerton J, Meesaq A, Deacon RM, Rawlins JN, et al. Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice. Nat Genet. 2004;36:1197–202. doi: 10.1038/ng1450. [DOI] [PubMed] [Google Scholar]

[CR92] 92.Pham H, Sieg J, Seeley SL, D’Souza MS. Differential methamphetamine-induced behavioral effects in male and female mice lacking regulator of G Protein signaling 4. Behav Brain Res. 2022;423:113770. doi: 10.1016/j.bbr.2022.113770. [DOI] [PubMed] [Google Scholar]

[CR93] 93.Rorabaugh BR, Rose MJ, Stoops TS, Stevens AA, Seeley SL, D’Souza MS. Regulators of G-protein signaling 2 and 4 differentially regulate cocaine-induced rewarding effects. Physiol Behav. 2018;195:9–19. doi: 10.1016/j.physbeh.2018.07.016. [DOI] [PubMed] [Google Scholar]

[CR94] 94.Rempe RG, Hartz AMS, Bauer B. Matrix metalloproteinases in the brain and blood-brain barrier: Versatile breakers and makers. J Cereb Blood Flow Metab. 2016;36:1481–507. doi: 10.1177/0271678X16655551. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR95] 95.Tsang CK, Liu Y, Thomas J, Zhang Y, Zheng XF. Superoxide dismutase 1 acts as a nuclear transcription factor to regulate oxidative stress resistance. Nat Commun. 2014;5:3446. doi: 10.1038/ncomms4446. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR96] 96.Eleutherio ECA, Silva Magalhaes RS, de Araujo Brasil A, Monteiro Neto JR, de Holanda Paranhos L. SOD1, more than just an antioxidant. Arch Biochem Biophys. 2021;697:108701. doi: 10.1016/j.abb.2020.108701. [DOI] [PubMed] [Google Scholar]

[CR97] 97.Milani P, Amadio M, Laforenza U, Dell’Orco M, Diamanti L, Sardone V, et al. Posttranscriptional regulation of SOD1 gene expression under oxidative stress: Potential role of ELAV proteins in sporadic ALS. Neurobiol Dis. 2013;60:51–60. doi: 10.1016/j.nbd.2013.08.005. [DOI] [PubMed] [Google Scholar]

[CR98] 98.Milani P, Gagliardi S, Cova E, Cereda C. SOD1 Transcriptional and Posttranscriptional Regulation and Its Potential Implications in ALS. Neurol Res Int. 2011;2011:458427. doi: 10.1155/2011/458427. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR99] 99.Deng Y, Dickey JE, Saito K, Deng G, Singh U, Jiang J, et al. Elucidating the role of Rgs2 expression in the PVN for metabolic homeostasis in mice. Mol Metab. 2022;66:101622. doi: 10.1016/j.molmet.2022.101622. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR100] 100.Lan N, Hellemans KG, Ellis L, Weinberg J. Exposure to Chronic Mild Stress Differentially Alters Corticotropin-Releasing Hormone and Arginine Vasopressin mRNA Expression in the Stress-Responsive Neurocircuitry of Male and Female Rats Prenatally Exposed to Alcohol. Alcohol Clin Exp Res. 2015;39:2414–21. doi: 10.1111/acer.12916. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR101] 101.Taylor PV, Veenema AH, Paul MJ, Bredewold R, Isaacs S, de Vries GJ. Sexually dimorphic effects of a prenatal immune challenge on social play and vasopressin expression in juvenile rats. Biol Sex Differ. 2012;3:15. doi: 10.1186/2042-6410-3-15. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR102] 102.Goel N, Philippe TJ, Chang J, Koblanski ME, Viau V. Cellular and serotonergic correlates of habituated neuroendocrine responses in male and female rats. Psychoneuroendocrinology. 2022;136:105599. doi: 10.1016/j.psyneuen.2021.105599. [DOI] [PubMed] [Google Scholar]

[CR103] 103.Rood BD, Stott RT, You S, Smith CJ, Woodbury ME, De Vries GJ. Site of origin of and sex differences in the vasopressin innervation of the mouse (Mus musculus) brain. J Comp Neurol. 2013;521:2321–58. doi: 10.1002/cne.23288. [DOI] [PubMed] [Google Scholar]

[CR104] 104.de Souza Villa P, Menani JV, de Arruda Camargo GM, de Arruda Camargo LA, Saad WA. Activation of the serotonergic 5-HT1A receptor in the paraventricular nucleus of the hypothalamus inhibits water intake and increases urinary excretion in water-deprived rats. Regul Pept. 2008;150:14–20. doi: 10.1016/j.regpep.2008.05.003. [DOI] [PubMed] [Google Scholar]

[CR105] 105.Issotina Zibrila A, Li Y, Wang Z, Zhao G, Liu H, Leng J, et al. Acetylcholinesterase inhibition with Pyridostigmine attenuates hypertension and neuroinflammation in the paraventricular nucleus in rat model for Preeclampsia. Int Immunopharmacol. 2021;101:108365. doi: 10.1016/j.intimp.2021.108365. [DOI] [PubMed] [Google Scholar]

[CR106] 106.Matsuura T, Shinohara K, Iyonaga T, Hirooka Y, Tsutsui H. Prior exposure to placental ischemia causes increased salt sensitivity of blood pressure via vasopressin production and secretion in postpartum rats. J Hypertens. 2019;37:1657–67. doi: 10.1097/HJH.0000000000002091. [DOI] [PubMed] [Google Scholar]

[CR107] 107.Kato TM, Fujimori-Tonou N, Mizukami H, Ozawa K, Fujisawa S, Kato T. Presynaptic dysregulation of the paraventricular thalamic nucleus causes depression-like behavior. Sci Rep. 2019;9:16506. doi: 10.1038/s41598-019-52984-y. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR108] 108.Stanton LM, Price AJ, Manning EE. Hypothalamic corticotrophin releasing hormone neurons in stress-induced psychopathology: Revaluation of synaptic contributions. J Neuroendocrinol. 2023;35:e13268. doi: 10.1111/jne.13268. [DOI] [PubMed] [Google Scholar]

[CR109] 109.Oliver DK, Intson K, Sargin D, Power SK, McNabb J, Ramsey AJ, et al. Chronic social isolation exerts opposing sex-specific consequences on serotonin neuronal excitability and behaviour. Neuropharmacology. 2020;168:108015. doi: 10.1016/j.neuropharm.2020.108015. [DOI] [PubMed] [Google Scholar]

[CR110] 110.McEuen JG, Semsar KA, Lim MA, Bale TL. Influence of sex and corticotropin-releasing factor pathways as determinants in serotonin sensitivity. Endocrinology. 2009;150:3709–16. doi: 10.1210/en.2008-1721. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR111] 111.Murray EJ, Gumusoglu SB, Santillan DA, Santillan MK. Manipulating CD4+ T Cell Pathways to Prevent Preeclampsia. Front Bioeng Biotechnol. 2022;9:811417. doi: 10.3389/fbioe.2021.811417. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR112] 112.Taylor WD, Aizenstein HJ, Alexopoulos GS. The vascular depression hypothesis: mechanisms linking vascular disease with depression. Mol Psych. 2013;18:963–74. doi: 10.1038/mp.2013.20. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Anti-angiogenic mechanisms and serotonergic dysfunction in the Rgs2 knockout model for the study of psycho-obstetric risk

Serena B Gumusoglu

Michaela D Kiel

Aleigha Gugel

Brandon M Schickling

Kaylee R Weaver

Marisol C Lauffer

Hannah R Sullivan

Kaylie J Coulter

Brianna M Blaine

Mushroor Kamal

Yuping Zhang

Eric J Devor

Donna A Santillan

Stephanie C Gantz

Mark K Santillan

Abstract

Introduction

Materials and methods

Mice

Behavioral assessments

Elevated plus maze

Open field test

Y maze

Three-chamber social preference and social novelty preference

Sucrose preference test

Tail suspension test

Tissue collection

Quantitative polymerase chain reaction (qPCR)

Immunohistochemistry

Stereology

Cerebrovascular assessments

Enzyme-linked immunoassay (ELISA)

Tail-cuff plethysmography

Evans blue blood-brain barrier permeability assay

Brain slice preparation and electrophysiological recordings

Statistical analyses

Results

Sex-specific behavioral alterations in the Rgs2 knockout mouse

Fig. 1. Behavioral testing revealed Rgs2 KO sex-specific alterations.

Cortical vessel density and length but not cell numbers are diminished in Rgs2 KO mice

Fig. 2. Cortical vascular density and length is decreased in Rgs2 KO animals, though brain morphology is otherwise intact.

Sex-specific abnormalities in angiogenesis, G protein signaling, and redox related gene expression in Rgs2 KO mice

Fig. 3. qPCR studies of brain (cortex, paraventricular nucleus, midbrain/dorsal raphe, hindbrain) reveal changes in redox-, angiogenesis-, and GPCR-related genes in the Rgs2 KO mouse relative to wildtype (WT) comparators.

Behavior and cerebrovasculature changes are associated with brain serotonin and angiogenesis-related gene expression in a sex- and genotype-specific manner in the Rgs2 KO mouse

Fig. 4. Vascular density and locomotor behavior are respectively related to expression of serotonin and angiogenesis-related genes in the brain in a sex- and genotype-specific manner.

Serotonin synaptic transmission is altered and sensitivity to sertraline increased in female Rgs2 KO mice

Fig. 5. Sertraline augments serotonin synaptic transmission to a greater extent in female Rgs2 KO serotonin neurons.

Discussion

Supplementary information

Author contributions

Funding

Competing interests

Footnotes

Supplementary information

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases