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. 2018 Oct 1;29(9):3712–3724. doi: 10.1093/cercor/bhy251

Gestational Stress Augments Postpartum β-Amyloid Pathology and Cognitive Decline in a Mouse Model of Alzheimer’s Disease

Zahra Jafari 1,2, Jogender Mehla 1, Bryan E Kolb 1,✉, Majid H Mohajerani 1,✉
PMCID: PMC6686749  PMID: 30561536

Abstract

Besides well-known risk factors for Alzheimer’s disease (AD), stress, and in particular noise stress (NS), is a lifestyle risk factor common today. It is known that females are at a significantly greater risk of developing AD than males, and given that stress is a common adversity in females during pregnancy, we hypothesized that gestational noise exposure could exacerbate the postpartum development of the AD-like neuropathological changes during the life span. Pregnant APPNL-G-F/NL-G-F mice were randomly assigned to either the stress condition or control group. The stress group was exposed to the NS on gestational days 12–16, which resulted in a markedly higher hypothalamic–pituitary–adrenal (HPA) axis responsivity during the postpartum stage. Higher amyloid-β (Aβ) deposition and larger Aβ plaque size in the olfactory area were the early onset impacts of the gestational stress (GS) seen at the age of 4 months. This pattern of increased Aβ aggregation and larger plaque size were observed in various brain areas involved in both AD and stress regulation, especially in limbic structures, at the age of 6 months. The GS also produced anxiety-like behavior, deficits in learning and memory, and impaired motor coordination. The findings suggest that environmental stresses during pregnancy pose a potential risk factor in accelerating postpartum cognitive decline and AD-like neuropathological changes in the dams (mothers) later in life.

Keywords: Alzheimer’s disease, Aβ plaque, cognitive impairment, gestational stress, HPA-axis, motor dysfunction, noise, postpartum, prepulse inhibition

Introduction

Dementia is a major worldwide challenge for health and social care in the current century. Alzheimer’s disease (AD) is a progressive neurological disorder that impairs memory and other cognitive abilities in the elderly populations and accounts for 60–80% of dementia cases (Cui and Li 2013; Marcello et al. 2015). AD’s clinical features include the extracellular deposition of amyloid-β (Aβ) peptide, the formation of intracellular neurofibrillary tangles of hyperphosphorylated tau protein, as well as neuronal and synaptic loss in the cerebral cortex and hippocampus (Marcello et al. 2015). Although the complex etiology of AD is not fully understood, the effects of lifestyle characteristics, environmental factors, and sex in the risk of developing AD-like symptoms have been tackled in multiple multidisciplinary studies (Carroll et al. 2010; Cui and Li 2013; Khalsa 2015; Laws et al. 2018). Besides well-known risk factors related to lifestyle for mental disease, dementia, and AD, stress is an inherent component of modern life that has a major contribution in shaping the brain and behavior (Marcello et al. 2015; Belnoue et al. 2016; Jafari, Kolb et al. 2017). Stress causes neurotoxic damages to cells in the hippocampus and other brain areas via the hypothalamic–pituitary–adrenal (HPA) axis hyperactivation (Khalsa 2015). Recent studies also support a causative connection between stress and multiple risk factors for the AD-like neuropathological changes, that is, inflammation, cardiovascular disease, diabetes, depression, anxiety, physical inactivity, sleep deprivation, smoking, hearing loss, less education, social isolation, and obesity (Khalsa 2015; Livingston et al. 2017).

Pregnancy and motherhood is a significant period of a female’s life that is accompanied by many neural and behavioral changes including neuroendocrine, molecular, and physiological adaptations occurring during pregnancy, parturition, and the postpartum period and is correlated with major changes in maternal mood, cognition, and stress regulation (Toufexis et al. 2014; Belnoue et al. 2016). A growing body of laboratory studies suggests that mothers show remarkable plasticity within the brain in areas underlying maternal behavior, such as the hypothalamus and the olfactory bulb, and in areas underlying nonmaternal behaviors, such as the hippocampus, septum, and amygdala (Pawluski et al. 2009; Macbeth and Luine 2010; Reid and Taylor 2015; Belnoue et al. 2016). These neural changes are concomitant with behavioral changes in learning, memory, foraging ability, and anxiety (Byrnes and Bridges 2006; Lemaire et al. 2006; Pawluski, Vanderbyl, et al. 2006; Pawluski, Walker, et al. 2006; Pawluski and Galea 2007). Enhanced memory function, higher resilience to stress, and decreased anxiety have been shown in primiparous (one pregnancy and bout of rearing) and multiparous (multiple pregnancies and bouts of rearing) rats compared with nulliparous (no pregnancy) rats and this experience persists into old age (Lemaire et al. 2006). Studies also have shown the mitigation of aging-related decrements by lower Aβ plaque deposition in the hippocampal formation in the postpartum dams (mothers) (Gatewood et al. 2005). There is also evidence that these neurobehavioral changes are enduring and initiate a more permanent change in mothers (Gatewood et al. 2005; Love et al. 2005; Macbeth et al. 2008). Although research into the neural mechanisms underlying cognitive changes during pregnancy and postpartum is only beginning, some theories including evolutionary, foraging, fertility, and parental care have been advanced (Macbeth and Luine 2010). For instance, central oxytocin (Oxt), (i.e., a hypothalamic neuropeptide with a variety of social and nonsocial activities/behaviors (Yang et al. 2013)), can modulate HPA axis responses to stress through regulating corticotropin-releasing hormone (CRH) secretion and expression in the paraventricular nucleus (Windle et al. 2006; Ochedalski et al. 2007). Other studies, however, have shown that gestational stress (GS) can entirely counteract the advantages of reproduction on postpartum cognitive performance (Lemaire et al. 2006), likely due to the interaction of stress and motherhood-induced changes in several hormonal inputs to the brain, including Oxt (Windle et al. 2006), alternations in ovarian hormone levels (Luine 2014), and hyperactivity of the HPA-axis and subsequent increased sensitivity to external challenges (Toufexis et al. 2014).

Noise is a common source of stress that is an important environmental concern for humans (Basner et al. 2014) and nonhuman animals (Ristovska et al. 2014; Shannon et al. 2016; Jafari et al. 2018). High levels of noise are markedly stressful and significantly enhance release of stress hormones (i.e., glucocorticoids), leading to impairments in emotional, cognitive, and behavioral functions in the pregnant animal and her offspring (Lemaire et al. 2006; Jafari, Mehla, Kolb et al. 2017; Jafari et al. 2018). Although a large body of evidence indicates that GS increases the risks of psychopathology in offspring (Charil et al. 2010; Weinstock 2017), we were unaware of any study that has tackled the GS influence on brain structure–function in rodents later in life. Recent studies support the noxious effect of noise in inducing AD-like neuropathological changes in laboratory animals (Cuadrado-Tejedor et al. 2012; Baglietto-Vargas et al. 2015; Cui et al. 2015) and increasing the risk of developing AD in humans (Tzivian et al. 2017). Thus, given 1) the greater risk of developing AD-like symptoms in females than males (Carroll et al. 2010; Laws et al. 2018), 2) a reciprocal relationship between the HPA and hypothalamic–pituitary–gonadal (HPG) axes and ample evidence supporting that ovarian hormones actively modulate the function of the HPA axis and vice versa, 3) an increase in the production of ovarian hormones during puberty, ovulation, and pregnancy (Toufexis et al. 2014), 4) the loss of ovarian hormones during menopause that is related to females’ higher vulnerability to AD-like symptomes (Zhao et al. 2015), 5) the long-lasting negative effects of the GS on brain and behavior (Lemaire et al. 2006; Jafari, Faraji et al. 2017; Jafari, Mehla, Afrashteh et al. 2017), and 6) the etiological association of noise exposure with AD-like neuropathological changes in rodents (Cui and Li 2013; Marcello et al. 2015), we hypothesized that the GS could accelerate the Aβ accumulation and cognitive decline in dams (mothers) postpartum. We used a knock-in APPNL-G-F/NL-G-F mouse model of AD that overproduces Aβ42 without overexpressing other APP fragments. This mouse model presents typical Aβ pathology, neuroinflammation, and memory impairment in an age-dependent manner. The cortical deposition specifically starts after 2 months and is almost saturated by 7 months. Subcortical amyloidosis is also shown after 4 months (Saito et al. 2014; Mehla et al. 2018). This characteristic let us focus on the stress effect on Aβ pathology and cognitive impairment by eliminating the impact of other fragments involved in the development of AD-like symptoms.

Material and Methods

Animals

The male and female pairs of AD transgenic mice carrying Swedish (NL), Arctic (G), and Beyreuther/Iberian (F) mutations (APPNL-G-F/NL-G-F, APP: amyloid β-protein precursor) were provided by RIKEN Brain Science Institute, Japan. Then, a colony of APPNL-G-F/NL-G-F mice was maintained at the Canadian Center for Behavioural Neuroscience. Genotyping of all mice was done by polymerase chain reaction using tail snipping method. Thirty-two female APPNL-G-F/NL-G-F mice at 8 weeks of age were individually mated with 32 male APPNL-G-F/NL-G-F mice in standard shoe box cages at 4:00 PM. For the recording of gestational length, a former protocol was followed (Jafari, Faraji, et al. 2017; Jafari, Mehla, Kolb, et al. 2017). All animals were given access to food and water ad libitum and were maintained on a 12:12-h light:dark cycle (on 7:30 AM and off 7:30 PM) under normal light condition (200 Lux) in a temperature-controlled room (21°C) with less than 58 ± 2 dB room noise level. All testing and training were performed during the light phase of the cycle at the same time of day. The experimental procedures were approved by the University of Lethbridge Animal Care Committee in compliance with the standards set out by the Canadian Council for Animal Care.

Experimental Design

Pregnant mice were randomly assigned to 2 groups consisting of one GS group and one control group (CG). The animals were exposed to noise stress (NS) on gestational days (GDs) 12–16 because this timeframe corresponds to the second trimester in human pregnancy when substantial neural development occurs (Clancy et al. 2007).

NS Procedure

The NS paradigm consisted of an intermittent 3000 Hz frequency sound of 90 dB for 1-s duration and 15-s interstimulus interval (ISI) (Haque et al. 2004; Jafari, Faraji, et al. 2017). On GDs 12, 14, and 16, the mice (n = 16) in groups of 2 to 3 in their standard cage were moved to a sound chamber specified for the NS. A speaker which emitted the NS was placed inside the cage. The sound pressure level was monitored daily inside the cage without an animal (Tektronix RM3000, Digital Phosphor Oscilloscope). The mice were exposed to the NS for 24 h starting at 8:00 AM. We used a 3000 Hz frequency tone, since (a) is audible by mice (Heffner and Heffner 2007) and (b) is relatively similar to environmental and traffic noises which are largely made up of low to mid-frequency tones (Chang et al. 2014). We applied an intermittent stimulus intensity to prevent noise-induced hearing loss. Twenty-four-hour rest after every stress exposure will also provide enough time for recovery from possible temporary threshold shifts (White et al. 1998).

Control Group

Pregnant mice (n = 16) on GDs 12, 14, and 16 in groups of 2 to 3 in their standard cage were moved to a sound chamber specified for the CG. A silent speaker was placed inside the cage. The mice were left undisturbed for 24 h starting at 8:00 AM. In the CG, no stress was given.

Plasma Corticosterone Assay

Blood was taken from the submandibular vein at 7:30 to 8:30 AM on GDs 11 and 18, that is, one day before starting stress regimen, and one day after finishing the stress exposure in the NS group, and the corresponding days for the CG. The submandibular bleeding of mice is a single-use lancet method to quickly draw blood without the use of the anesthesia. Approximately 0.1 ml of blood was collected in heparin-coated tubes (Jafari, Mehla, Kolb et al. 2017). The tubes were centrifuged at 6000 rpm at 4 °C for 15 min to collect the plasma. Collected plasma samples then were stored at −80 °C until further analysis. A commercially available enzyme-linked immunosorbent assay (ELISA) kit from Abcam (ab108821) was used to quantify the levels of corticosterone in the plasma (ng/mL). The optical density of corticosterone was read at 450 nm wavelength using a microplate reader (Synergy HT BioTek®). The concentration of corticosterone in samples was calculated using KC4 Bio-Tek® Microplate Data Collection and Analysis software. To reduce intraplate variability, the coefficient of variation for all samples was determined using the same standards and controls across all plates (Jafari et al. 2018).

Behavioral Tests

Several behavioral tests were performed after weaning to measure the effect of GS on cognitive and motor performance of the dams (mothers), at 4 and 6 months. Tests of prepulse inhibition (PPI) of the acoustic startle reflex (ASR), novel object recognition (NOR), rotarod (RR), balance beam test (BBT), and the Morris water task (MWT), including a probe trial, were conducted, respectively, in separate days, with an alternating order of animals, by the same examiner in the mornings at 8:00–11:00 AM (Fig. 1).

Figure 1.

Figure 1.

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Study timeline shows the time of each procedure across age. After testing the PPI of the ASR and MWT, female and male APPNL-G-F/NL-G-F mice at the same age were paired for a timed mice pregnancy. Half of the pregnant mice were exposed to NS during GDs 12–16. Blood was collected on GDs 11 and 18 and also at ages 4 and 6 months before doing a set of behavioral tests including PPI of the ASR, NOR, RR, BBT, and MWT. Animals were sacrificed at two-time steps, a day after finishing behavioral tests. Digital pathology by Nanozoomer was performed to quantify the total number of Aβ plaques, plaque area (%), and the largest plaque size (μm). Aβ, amyloid beta; ASR, acoustic startle reflex; BBT, balance beam test; GDs, gestational days; mo, months, MWT, Morris water task; NOR, novel object recognition; PPI, prepulse inhibition; RR, rotarod.

The PPI of the ASR

Each mouse was placed in a plastic cylinder situated on a plate with a pressure sensor in an acoustic chamber (PANLAB Harvard Apparatus). Any animal motion was detected by the sensor which measured its amplitude and stored data on a computer hard drive. Software generated a sequence of stimulus trials including a startle stimulus, a prepulse stimulus, and a startle stimulus paired with a prepulse stimulus in a white background noise of 65 dB. The ASR stimulus was an 8 kHz tone frequency with 115 dB intensity, 40-ms duration, and a 1-ms rise/fall time. The prepulse stimulus was also an 8 kHz tone frequency with 80 dB intensity, 20-ms duration, and a 1-ms rise/fall time which was presented 100 ms before the startle stimulus. The testing session was started with an acclimation period lasting 3 min. Then animals received 10 startle-only trials in order to habituate their startle responses to a steady-state level. Immediately afterward, 40 trials including 10 “no stimulus,” 10 “pulse stimulus,” 10 “prepulse stimulus,” and 10 “prepulse + pulse stimulus” in pseudorandom order with 30-s ISI were presented. The PANLAB system automatically presented the ASR and PPI (%) in an Excel data spreadsheet. The PPI ratio was calculated by subtracting the ASR amplitude from the PPI amplitude divided by the ASR amplitude ([pulse response – prepulse plus response/pulse response] × 100) (Jafari et al. 2018). Daily calibrations were performed on the chambers to ensure the accuracy of the sound levels (dB) and measurements.

The RR Test

Animals were briefly pretrained on an automated 4-lane RR treadmill (ENV-575M Mouse, Med Association Inc). For the protocol, mice were placed into individual sections of the RR and tested at 2 constant speeds (8 and 16 rpm) and an alternating (4–40 rpm) speed on separate days. Each animal’s performance score in seconds was recorded when the mouse was unable to stay on the RR, trips a plate, and stops the timer. Mice were subjected to 2 trials, with a maximum time of 3 min and a 5-min intertrial test interval. Two trials per animal were averaged (Brooks and Dunnett 2009; Jafari et al. 2018).

The NOR Test

Each mouse was placed in an open-field arena (47 cm width × 50 cm length × 30 cm height) made of white Plexiglass. In the first trial, the mouse was placed in the arena with 2 identical objects and was allowed to explore the field for 5 min. The animal was removed and placed in a transport box for 3 min, and one of the objects was randomly replaced with a new object. The mouse was then returned to the arena, and the animal’s exploration was filmed for 3 min. The time spent with each object (s) was manually recorded only during the second session. The comparison of the percentage of time spent exploring the novel object versus the percentage of time spent exploring the familiar object was performed as well. In addition, behavioral measures including movement time (the time in seconds spent moving in the arena), movement number (the number of movements after the animal remained immobile for more than one second), total distance (the total length of paths traveled by animals, in centimeters), and rest time (the time in seconds spent immobile) during the second session were calculated to determine the locomotor behavior of the animals (Jafari, Faraji et al. 2017; Jafari et al. 2018).

The BBT

The mice were required to traverse an elevated, narrow aluminum beam (1 cm diameter, 100 cm long and 50 cm above a foam pad to cushion falling mice) to reach an enclosed escape box. Mice were first trained (3–4 trials) and were tested (3 trials) on the next day. The mean latency (s), distance traveled (cm), number of foot slips, number of turns, and number of falls across the 3 testing trials were manually scored (Jafari, Faraji et al. 2017; Jafari et al. 2018).

The MWT

The water task consisted of a pool (153 cm diameter) filled with water (23–25°C) up to a level of ~15 cm from the top edge of the tank. The water was made opaque by nontoxic white tempera paint. The pool was located in a room rich with distal cues. During all hidden platform trials, the platform was submerged ~1.0 cm under the surface of the water. The tank was divided virtually into 4 quadrants, 1, 2, 3, and 4 using software, with starting points at north, west, east, and south. Animals were trained with 4 trials per day for 8 consecutive days (Water2100 Software vs. 7, 2008). Each trial began with the mouse being placed in the pool in a pseudorandom sequence at one of the 4 cardinal compass positions around the perimeter of the pool. Testing was stopped after the mouse reached the platform or, if the mouse did not find the platform, at the 60-s trial time limit. Data were recorded using an automated tracking system (HVS Image). The swim time (s), swim speed (m/s), and swim distance (m) were calculated for analysis. The probe trial was also carried out on the 9th day, 24 h after the last acquisition trial, in which the platform was removed, and each mouse was allowed to swim freely for 60 s. The time spent in the quadrant where the platform had been located was measured (Jafari, Faraji et al. 2017; Jafari et al. 2018).

Quantification of the Aβ Plaque Area

Methoxy-X04 Injection and Brain Imaging

Methoxy-X04 is a fluorescent dye that selectively binds to β-pleated sheets found in dense core Aβ plaques. It has high specificity in staining Aβ plaques in postmortem sections of AD brain (Hefendehl et al. 2011). The methoxy-X04 solution was prepared by dissolving the methoxy into a solution containing 10% dimethyl sulfoxide (DMSO), 45% propylene glycol, and 45% sodium phosphate-buffered saline (Bisht et al. 2016). Twenty-four hours prior to perfusion, mice were weighed and given an intraperitoneal injection of methoxy-X04 at a dose of 10 mg/kg of body weight. Then they were euthanized via a transcardiac perfusion of 0.9% saline followed by paraformaldehyde (PFA). Brains were removed, and postfixed for 24 h in PFA (Jafari et al. 2018). They were subsequently sliced at 50 μm using a Cryostat, and every second section was mounted on glass slides. Brain sections were automatically imaged in a 40× magnification (resolution: 0.23 μm/pixel) using the Hamamatsu NanoZoomer 2.0-HT Scan System (Hamamatsu Photonics) for quantification of Aβ plaques. The experimenter was blind to the experimental groups.

Brain Sections and Regions of Interests

For each brain, 6 coronal sections (AP ~2.96, 1.94, 0.98, −2.06, −3.08, and −5.34 mm) corresponding with a mouse brain atlas (Paxinos and Franklin 2001) were selected for quantifying total number of Aβ plaques and total plaque area (%) (Saito et al. 2014) (Figs. 4 and 5 and Supplementary Fig. S1). In each brain section, plaque area was also computed for some specific brain regions that studies have shown to be involved in the progression of AD-like symptoms, stress handling, or in regulation of brain-cognitive processes (Sara 2009; Schoenfeld and Gould 2012; Kim et al. 2015; Saar et al. 2015). Studies demonstrated the influence of uncontrollable stress on medial prefrontal cortex (mPFC) (Arnsten 2009), hippocampal region (HR), entorhinal area (EA) (Kim et al. 2007, 2015; Vorhees and Williams 2014), anterior cingulate area (ACA), retrosplenial area (RA) (Maviel et al. 2004), cortical and amygdala areas (Maren 1999; Roozendaal et al. 2004; Oliveira et al. 2012), nucleus accumbens (NA) (Setlow 1997), locus coeruleus (LC) (Sara 2009, 2015), olfactory area (OA) (Belnoue et al. 2016), brainstem structures (Barnum et al. 2012); and the interaction of these brain areas in regulating the glucocorticoid effects on cognitive functions, as well as in the development of AD (Joels et al. 2006; Ueki et al. 2006; Arnsten 2009; Machado et al. 2014; Radley et al. 2015; Hoeijmakers et al. 2018; Jafari et al. 2018).

Figure 4.

Figure 4.

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Aβ plaque quantification in OA at age 4 months. A significant difference between the 2 groups (A1 and A2) in the OA at age 4 months. The GS group showed a significantly higher number of plaques (A3), plaque area (A4), and larger plaque size (A5) compared with the CG (Supplementary Table S5). Results reported as mean ± S.E.M. Asterisks indicate *P < 0.05 or **P < 0.01. Aβ, amyloid beta; CG, control group; GS, gestational stress; OA, olfactory area. Scale bar 0.5 mm.

Figure 5.

Figure 5.

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The Aβ plaque quantification at age 6 months: (A) Six coronal sections (A1-A6: Bregma ~2.96, 1.94, 0.98, -2.06, -3.08, and -5.34 mm) were selected for quantifying the Aβ plaques. (B) Samples of brain sections used in a control (B1) and a stress (B2) animal, and their corresponding distributions of plaque size by total number of plaques (B3: BA1-BA6). (C) The total number of plaques, (D) total plaque area (%), (E) largest plaque size (μm), and (F) plaque area in all specific brain regions (FA1–FA6) were significantly higher in the GS group than the CG (Supplementary Table S5). Aβ, amyloid beta; ACA, anterior cingulate area; CAA, cortical amygdalar area; CG, control group; EA, entorhinal area; GS, gestational stress; HB, hindbrain; HR, hippocampal region; IC, isocortex; LC, locus coeruleus; MB, midbrain; mPFC, medial prefrontal cortex; NA, nucleus accumbens; OA, olfactory area; PPA, posterior parietal area; RA, retrosplenial area; Results reported as mean ± S.E.M. Asterisks indicate *P < 0.05 or **P < 0.01. Scale bar: 1 mm.

The Ilastik 1.1.7 software was used for quantifying the total number of plaques in each brain section. This software automatically presents the number of plaques as well as the plaque size corresponding with each discrete plaque. The number of plaques was also quantified according to the plaque size (less than or more than 4 μm). In line with Hefendehl et al. 2011, 87% of newly generated plaques are small in size having a radius of <4μm. To determine the plaque area, each brain section was uploaded in ImageJ 1.4.3.67 software, and the total plaque area and also plaque area of the regions of interest (ROIs) were measured via using required image processing options under “Edit,” “Image,” “Process,” and “Analyze” tabs. The ROIs were as follows: Isocortex (IC), OA, mPFC, ACA, NA, HR, posterior parietal area (PPA), RA, EA, cortical amygdalar area (CAA), LC, midbrain (MB), and hindbrain (HB). These six coronal sections (A1–A6) were chosen for the Aβ plaque quantification as they provided a good view for differentiating selected ROI’s boundaries.

Statistical Analysis

All statistical analyses were performed using SPSS Statistics 24.0 at a significance level of 0.05 or better. Normally distributed data were analyzed using the Kolmogorov–Smirnov test. Univariate analysis of variance (UANOVA) was conducted to compare the groups regarding different parameters of the corticosterone assay, behavioral tests, and Aβ plaque measurements. A repeated measures ANOVA was used for all comparisons to examine the age effect in each group. The F-values, P-values, estimations of the effect size (partial η2), and observed power were reported for the statistical analyses. Adjustment for multiple comparisons of group means in each measurement was performed with Bonferroni correction.

Results

Impact of the GS on Corticosterone Levels

The corticosterone level was identical in the 2 groups before the GS (P = 0.809). It was significantly higher in the GS group compared with the CG after the NS paradigm and also at ages 4 and 6 months (P ≤ 0.001, Supplementary Table S1). Changes in corticosterone levels across age was significant only in the GS group (P ≤ 0.001, Fig. 2A, Supplementary Table S2).

Figure 2.

Figure 2.

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Results of corticosterone assays and behavioral tests: (A) The corticosterone levels (ng/mL): The corticosterone levels were significantly higher a day after NS and also at ages 4 and 6 months in the GS group compared with the CG. Changes in corticosterone levels were significant across age in the GS group (Supplementary Table S2). The PPI of the ASR test: (B1) The ASR amplitude (%) significantly decreased by age in both groups. (B2) The PPI amplitude (%) significantly reduced by age in the GS group, and the difference with the CG was significant at both 4 and 6 months (Supplementary Table S1). (B3 and B4) The ASR and PPI latencies (ms) increased by age in both groups. The age effect was significant for the PPI latency (Supplementary Table S3), and the difference between the 2 groups was significant at age 6 months. (C) The NOR test: The GS group showed a significantly shorter new object time (s), longer old object time (s), and higher NOR ratio compared with the CG at both ages (Supplementary Table S4). Results were reported as mean ± S.E.M. Asterisks indicate *P < 0.05 or **P < 0.01. ASR, acoustic startle reflex; CG, control group; GS, gestational stress; NOR, novel object recognition; PPI, prepulse inhibition.

Impact of the GS on Cognitive Function and Motor Coordination

The PPI of the ASR

The decrease in ASR amplitude (%) by age was almost identical in the 2 groups (P ≥ 0.707, Fig. 2B1, Supplementary Table S1). The GS group revealed a significant reduction of the PPI amplitude at ages 4 (P = 0.006) and 6 (P = 0.045) months compared with the CG (Fig. 2B2). The ASR latency (ms) increase by age was almost the same in both groups (P ≥ 0.542, Fig. 2B3). The GS group had a significantly higher PPI latency than the CG at age 6 months (P = 0.005, Fig. 2B4).

The ASR amplitude (%) significantly decreased across age in both control (P = 0.009) and GS (P = 0.005) groups (Fig. 2B1, Supplementary Table S3). The CG showed the highest PPI amplitude (%) at age 4 months, whereas the age effect was not significant (P = 0.272). The GS group, however, showed a significant decrease in PPI amplitude by age (P = 0.021, Fig. 2B2). Both groups exhibited a nonsignificant increase in ASR latency (ms) by age (P ≥ 0.117, Fig. 2B3). The trend of increase in PPI latency (ms) was significant in both groups (P ≤ 0.001, Fig. 2B4, Supplementary Table S3).

The NOR Test

The new object time was significantly higher in the CG compared with the GS group (P ≤ 0.038). The GS group took a significantly higher time with the old object (P ≤ 0.024); and a lower ratio of time spent with the novel object versus familiar object than the CG (P ≤ 0.012, Fig. 2C1–C3, Supplementary Table S1). In intragroup analysis, only the CG revealed a significant decrease in both old object time (P = 0.036) and ratio of time spent with the old object (P = 0.010, Supplementary Table S4) by age. No significant difference was observed between the 2 groups in any measures of the locomotion behavior across age (P ≥ 0.213).

The RR Test

The GS group exhibited an impaired performance in all RR speeds, that is, 8 rpm (P ≤ 0.019), 16 rpm (P ≤ 0.041), and the alternate speed (P = 0.043, Supplementary Table S1). The age effect was not significant for both groups (P ≥ 0.081, Fig. 3A1–A3, Supplementary Table S4).

Figure 3.

Figure 3.

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Behavioral tests’ results. (A) The RR test: A shorter time spent on the RR (s) with all low (8 rpm), high (16 rpm), and alternate speeds in the stress group compared with the CG. (B) The BBT: (B1) The GS group spent a significantly longer time (s) to pass across the beam, and (B2) higher number of foot slips compared with the CG (Supplementary Table S1). The number of foot slips decreased by age only in the CG (Supplementary Table S4). (C) The MWT: (C1) Although the swim latency (s) significantly decreased by age due to the practice effect in both groups (Supplementary Table S3), it was significantly longer in the GS group than the CG at both 4 and 6 months. (C2) The average swim latency per training days at 3 ages for both groups. (C3) The probe time (%) was significantly shorter in the GS group compared with the CG at age 6 months. The age effect was only shown in the GS group. Results reported as mean ± S.E.M. Asterisks indicate *P < 0.05 or **P < 0.01. BBT, balance beam test; CG, control group; GS, gestational stress; MWT, Morris water task.

The BBT

The GS group spent a significantly higher time to pass across the beam (P ≤ 0.041), and a higher number of foot slips (P ≤ 0.043) compared with the CG (Supplementary Table S1). Number of foot slips significantly decreased by age only in the CG (P = 0.038, Fig. 3B1–B2, Supplementary Table S4).

The MWT

Swim latency was significantly longer at ages 4 (P = 0.004) and 6 (P ≤ 0.001) months in the GS group compared with the CG (Fig. 3C1–C2). The same results were obtained in the distance traveled (P ≤ 0.008), whereas the swim speed was similar in both groups across age (P ≥ 0.293). The GS group had a significantly shorter probe time at age 6 months compared with the CG (P = 0.027, Fig. 3C3, Supplementary Table S1). In intragroup analysis (Supplementary Table S3), the latency (P ≤ 0.001) and distance traveled (P ≤ 0.001) revealed a significant reduction by age in both groups. Probe time was significantly reduced only in the GS group at age 6 months (P = 0.023).

Impact of the GS on the Aβ Plaque Area

At age 4 months, the early onset of the Aβ deposition was shown in OA, especially in the glomerular layer of the main olfactory bulb, (Fig. 4A1–A2). The number of plaques (P = 0.024), plaque area (P = 0.004), and the largest plaque size (P = 0.014) in the OA were significantly higher in the GS group than the CG (Fig. 4A3–A5, Supplementary Table S5). In other brain sections, only a small number of plaques was shown in cortical areas, and no significant difference was observed (Supplementary Fig. S1).

At age 6 months, Aβ plaques were observed in all brain sections for both groups (Fig. 5B). Figure 5B3 (BA1–BA6) exhibits a representative distribution of plaque size by total number of plaques in each brain section in a control and a stress animal. The GS caused a significant increase in the number of plaques in all brain sections (P ≤ 0.032). Both number of plaques less than 4 μm (P ≤ 0.042) and more than 4 μm (P ≤ 0.037) were significantly higher in the GS group than the CG (Fig. 5C). Statistical comparisons also indicated a significantly larger plaque size (μm) (P ≤ 0.028, Fig. 5E) and higher total plaque area in all brain sections (P ≤ 0.038, Fig. 5D), and also in specific brain regions (P ≤ 0.041, Fig. 5F: FA1–FA6), in the GS group compared with the CG (Supplementary Table S5).

Correlation between Aβ Plaque Area and Behavioral Findings

Taking into consideration the prominent rule of HR in both special learning and memory and the PPI formation, correlations between the dorsal HR plaque area (%) (Bregma ~−2.06), latency in MWT (s) (the average of latency for each animal during a course of 8-day training), and the PPI response (%) were determined. There was a positive relationship between the plaque area and the latency in MWT (CG: r = 0.794, P = 0.033; GS group: r = 0.621, P = 0.112; Fig. 6A), and a negative relationship between the plaque area and the PPI amplitude (CG: r = −0.762, P = 0.045; GS group: r= −0.693, P = 0.079, Fig. 6B). There was also a negative relationship between the latency in MWT and the PPI response (CG: r = −0.758, P = 0.046; GS group: r = −0.733, P = 0.061, Fig. 6C) in both groups. All correlations were significant in the CG and near to significant in the GS group.

Figure 6.

Figure 6.

Open in a new tab

Relationship between the Aβ plaque area (%) and behavioral measurements at age 6 months: (A) A positive correlation between the plaque area and the latency (s) of the MWT (the “latency of the MWT” refers to the average of latency for each animal during a course of 8-days training); (B) a negative correlation between the plaque area and the PPI of the ASR amplitude (%); and (C) a positive correlation between the latency of the MWT and the PPI of the ASR amplitude. Aβ, amyloid beta; ASR, acoustic startle reflex; HR, hippocampal region; MWT, Morris water task; PPI, prepulse inhibition.

Discussion

The 5 main findings were as follows: 1) the GS markedly increased the corticosterone level across age; 2) GS impaired all cognitive and motor tasks relative to the CG; 3) higher Aβ deposition in the OA was the early onset impact of the GS seen at age 4 months; 4) a significantly higher plaque aggregation and larger plaque size was shown in all brain sections in the GS group compared with CG at age 6 months; and 5) a relationship between the plaque area and behavioral measurements was observed at 6 months. We consider these findings in turn.

The GS Increased Corticosterone Levels

Given that ovarian hormones actively modulate a wide range of neuronal activities such as neural development and survival (McEwen 2002; Simpkins et al. 2005), and estrogen-containing therapy has been remarkably successful in mitigating the risk for the development of AD-like symptoms in females early in menopause (Brinton 2008), current evidence supports the pivotal role of the loss of ovarian hormones on females’ higher vulnerability to AD-like neuropathological changes during life span (Zhao et al. 2015). There is also a mutual relationship between the HPA and HPG axes, and extensive evidence supports ovarian hormones modify the function of the HPA axis and vice versa (Toufexis et al. 2014). Stress during pregnancy elevates corticosterone levels and initiates long-lasting dysfunction of both HPA and HPG axes in the dams (mothers) (Macbeth and Luine 2010; Toufexis et al. 2014). Exposure to high levels of corticosterone downregulates the glucocorticoid receptors (GRs) and increases the responsivity of the HPA axis to stress. This causes a vicious endocrine circle of increased corticosterone levels and increased responsiveness to stress (Jafari et al. 2018). Although, high levels of noise are strongly stressful and elevate the corticosterone level (Jafari, Mehla, Afrashteh et al. 2017), the degree of control during the stressful incidences is a factor that differs among the stressors and modulates the degree of the HPA axis response to stress (Jafari, Faraji et al. 2017). The sense of low/no control over the stressor, such as passively subjecting to noise exposure, can negatively modify the prefrontal cortex regulation of stress hormones as well (Arnsten 2009).

A repeating GS paradigm also has an inhibitory effect upon gonadal hormone secretion and prevents the release of gonadotropin-releasing hormone from the hypothalamus, luteinizing hormone from the pituitary, and 17b-Oestradiol (E2) and progesterone secretion by the ovaries (Chrousos et al. 1998). Higher activation of a sympathetic neural pathway, the sympathetic-adrenal medullary system, originating in the hypothalamus and releasing norepinephrine into the ovaries is the other way that stress regulates HPG activity in females (Mayerhofer et al. 1997; Toufexis et al. 2014). Our markedly higher levels of corticosterone across age in the GS group were concomitant with behavioral impairments and higher Aβ accumulations relative to the CG and support existing evidence regarding enduring neurobehavioral impairments and permanent changes in the dams (mothers) due to GS (Love et al. 2005; Macbeth et al. 2008).

The GS Impaired Cognitive and Motor Performance

Noise is an environmental stressor with many detrimental psychophysiological, mental health, and performance effects involving attention, emotion, and learning and memory in humans (Basner et al. 2014) and nonhuman animals (Kraus et al. 2010; Cui et al. 2012; Marcello et al. 2015; Shannon et al. 2016; Jafari, Faraji et al. 2017; Jafari et al. 2018) The main aim of our study was to examine the role of a NS paradigm during gestation as a risk factor in accelerating the AD-like symptoms in the dams (mothers). The GS group exhibited a significant impairment in all cognitive and motor tasks that were not modified by age. They showed a significant loss in the amplitude and latency of the PPI, which is an index of impairment in sensorimotor gating (Jafari et al. 2018), a decreased tendency to explore the new object, a sign of impaired attention, in part, anxiety-like behavior(Jafari, Faraji, et al. 2017), and a markedly longer latency and shorter probe time in MWT, thus showing a deficit in spatial learning and memory (Cuadrado-Tejedor et al. 2012; Jafari, Mehla, Afrashteh et al. 2017). In our study, the ASR magnitude at 8 KHz was the same between the 2 groups at ages 2, 4, and 6 months, which indicates noise exposure had no hearing risk at this frequency (Turner et al. 2012; Longenecker et al. 2016). In addition, no significant difference was observed between the 2 groups in any measures of the locomotion behavior across age, indicating that increased anxiety-like behavior and decreased PPI might not be caused by hypoactivity due to the impaired motor function of GS group (Jafari et al. 2018). Mice in the stress group, however, might have been habituated to the auditory stimuli by the repeated exposure to the noise exposure during gestation and thus might not normally react to the prepulse of the similar sound level.

The GS also negatively affected balance and motor coordination. There is considerable evidence that hyperactivity of the HPA axis due to stress or glucocorticoid injections can modulate emotion, attention, learning, and memory (Kim et al. 2015), and also temporal and spatial aspects of motor performance in skilled movements, postural adjustments, and balance coordination (Metz 2007; Jafari, Faraji et al. 2017). Higher secretion of both CRH and corticosterone has been shown in females than males in response to various stressful events (Toufexis et al. 2014). In humans, a high level of distress increases the likelihood of developing the AD pathology by 2.7 times relative to those with lower levels of distress resulting in a more rapid progression of the disease (Cui and Li 2013; Marcello et al. 2015). Furthermore, stress-related psychiatric disorders, such as anxiety-like behavior, have been identified as an accelerating risk of developing AD-like symptoms (Marcello et al. 2015).

Both animal studies and meta-analytic evidence of large populations in humans have shown that females are prone to a significantly greater risk of developing the AD-like neuropathological changes than males (Carroll et al. 2010; Laws et al. 2018). Ovarian hormones actively modulate the response of the HPA axis, and hyperactivity of the HPA axis due to stress can also inhibit their secretion (Toufexis et al. 2014). The higher female susceptibility for developing the AD-like symptoms is largely associated with the loss of ovarian sex hormones during menopause (Zhao et al. 2015), which is under the regulation of stress hormones (Toufexis et al. 2014). There is an increase in the production of sex steroid hormones during pregnancy. A repeated GS can markedly suppress this gonadal hormone secretion (Toufexis et al. 2014), and its behavioral effects have been shown to be long-lasting even into old age (Lemaire et al. 2006).

The OA was the First Place of Showing the Adverse Effect of the GS

Animal studies have shown that the NS not only exacerbates cognitive decline but also causes an earlier onset of neurological symptoms in several diverse rodent models of AD (Cuadrado-Tejedor et al. 2012; Cui and Li 2013; Cui et al. 2015; Marcello et al. 2015), that is more likely caused by a CRH-driven increase in Aβ generation (Marcello et al. 2015). In our study, the OA was the first place showing the adverse effect of the GS on Aβ generation, particularly in the glomerular layer of the main olfactory bulb, at age 4 months. Studies have shown that the amyloid is extensively deposited through the olfactory circuits of APP transgenic mice leading to neuronal atrophy, dendritic abnormalities, synaptic loss, and axonal degeneration (Lachen-Montes et al. 2016; Yao et al. 2017). Current studies suggest a relationship between higher deposition of Aβ peptide and dysfunction in olfactory behavioral tests as the primary landmark of identifying the AD in humans (Lafaille-Magnan et al. 2017; Vasavada et al. 2017; Yao et al. 2017). A recent study of the impact of stress during pregnancy on olfactory functions in mice also revealed that the GS alters maternal behavior and prevents both the mothers’ ability to discriminate pup odors and the expected motherhood-induced enhancement in odor memory. They denoted that increased complexity of the dendritic tree of newborn bulbar neurons as a potential mechanism of the enhanced olfactory function in mothers was totally inhibited by GS (Belnoue et al. 2016).

Studies also have shown that changes in cAMP/Ca2+ response element binding protein (CREB)-mediated transcription are correlated with memory impairment (Pugazhenthi et al. 2011). A recent study in rats revealed that intraneuronal Aβ accumulation impairs the CREB-regulated transcription coactivator 1 (CRTC1)-dependent gene expression and cognitive performance at the early stages of the AD-like amyloid pathology before Aβ plaques emerge (Wilson et al. 2017). It is interesting to see how CRTC1-dependent gene expression is modified under stress in future studies.

The GS Markedly Increased the Aβ Deposition

The repeated stress exposure can severely reduce neural plasticity and impair brain structure in various brain regions, especially in limbic structures, that is, the hippocampal formation, mPFC, and amygdala (Czeh et al. 2007; Kim et al. 2015) which is the major neural circuitry mediating stress responses. Although both groups manifested an apparent Aβ deposition in different brain regions at age 6 months, the severity of the Aβ deposition considering both newly generated and existing plaques was significantly higher in the GS group than the CG. It has been shown that the stress-related Aβ aggregation is CRH-driven whereby Aβ raises through corticotrophin-releasing factor receptor 1 (CRFR1)-dependent alterations of γ-secretase localization into lipid rafts and direct actions on γ-secretase, a finding similar to what has been demonstrated in post-traumatic stress disorders (PTSD) (Marcello et al. 2015). The greater Aβ plaque area in cortical, subcortical, and limbic brain regions in our study were aligned with impairments observed in cognitive and motor tasks as well as the relationship between the plaque area and the cognitive behavior (latency in MWT, and the PPI of the ASR amplitude). The limbic structures, particularly the hippocampus, are under the regulation of the 2 classes of corticosteroid receptors including mineralocorticoid receptors and GRs. Certain hippocampal functions such as learning and memory are remarkably mediated by GR activation in response to stress or corticosterone administration. Binding corticosterone to GRs can adversely affect neuronal metabolism, cell survival, physiological functions, and neuronal morphology (Kim et al. 2015).

This study aimed to investigate the negative impacts of a repeated gestational NS paradigm on behavior and development of Aβ plaques in the dams (mothers) postpartum. We did not examine the likely effect of the pregnancy status (primiparous compared with nulliparous mice) in exacerbating the effect of stress on AD-like symptoms on this APPNL-G-F/NL-G-F mouse model. Thus, further research requires a differentiation between the adverse effect of stress during gestation and stress at any time in females, regardless of pregnancy. We also did not measure the CRH level across age, which could provide further support for the dysregulation of the HPA-axis in response to GS. On a cellular level, Aβ, a protein normally found in the healthy brain, is derived from AβPP (amyloid β-protein precursor). AβPP is cleaved first by β-secretase. The carboxyterminal cleavage is then performed by the γ-secretase complex. Depending on where AβPP is cleaved by γ-secretase, one of the 2 Aβ isoforms may be released: Aβ1-40 or Aβ1-42. Aβ1-42 is more prone to oligomerization and is the major component of neuritic plaques in AD brains (Cavanaugh et al. 2014; Muresan and Ladescu Muresan 2015). Deposition of Aβ plaques is also associated with degeneration observed at the synaptic junction and surrounded by reactive astrocytes and activated microglial cells, resulting in localized inflammatory responses (Cavanaugh et al. 2014). In future studies, quantifying the levels of the secretases, isoforms, and also localized inflammatory responses are essential to provide further details of how the GS modifies APP processing in the dams (mothers). Finally, we note that caution is needed as we generalize the findings of AD animal models into prevention, treatment, or health benefits for humans with AD-like symptoms given the imperfect replication of human AD in any other animal species (Cavanaugh et al. 2014).

Conclusion

Although some recent studies have tackled the negative impact of NS as a risk factor in exacerbating AD-like neuropathological changes in transgenic mice, our study was novel in taking into account the outcomes of a gestational NS in accelerating the Aβ pathology and cognitive and motor dysfunction in dams (mothers), a group that is often neglected in stress-associated studies. Early onset of Aβ deposition in the olfactory area at 4 months, a higher Aβ aggregation and larger Aβ size in all brain regions at 6 months, and anxiety-like behavior, learning and memory impairment, and loss of balance and motor coordination in dams postpartum were the major consequences of GS in this study. Our findings are consistent with previous publications (Cui and Li 2013; Marcello et al. 2015) and provide a suggestion as to how nongenetic risk factors contribute to accelerating Aβ deposition and cognitive impairments in the mouse model of the AD.

Supplementary Material

Supplimentary_Data_bhy251
Click here for additional data file. (544.9KB, docx)

Notes

The authors would like to acknowledge Gerlinde A.S. Metz for using her lab equipment for the PPI of the ASR test, Hadil Karem for helping to carry out some behavioral tests, Sean Guy Lacoursiere for helping to use the Ilastik software, Behroo Mirzaagha and Di Shao for animal husbandry, and Takashi Saito and Takaomi Saido from RIKEN Brain Science Institute for providing the AD mice used in this study. Z.J. would like to thank the Iran University of Medical Sciences (IUMS) sabbatical leave committee for their approval of her study leave. Conflict of Interest: None declared.

Authors’ Contributions

Z.J., B.K., and M.H.M. conceived and designed the method, and prepared and reviewed the manuscript, Z.J. performed experimental work and data analysis, Jogender Mehla assisted for the CORT assay, and M.H.M and B.K provided project leadership.

Funding

Canadian Institutes of Health Research (CIHR) (grant # 390930), Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery (grant # 40352), Alberta Innovates (CAIP Chair) (grant # 43568), Alberta Alzheimer Research Program (grant # PAZ15010 and PAZ17010), and Alzheimer Society of Canada (grant # 43674 to M.H.M.); and a Canadian Institute for Advanced Research (grant 33033 to B.K.). This study was a part of a postdoctoral fellowship to Z.J. in the Canadian Center for Behavioural Neuroscience (CCBN) at the University of Lethbridge.

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