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Published in final edited form as: Neurobiol Aging. 2023 Mar 2;126:113–122. doi: 10.1016/j.neurobiolaging.2023.02.012

Characterization of apathy-like behaviors in the 5xFAD mouse model of Alzheimer’s disease

Rachel Keszycki a,b, Guadalupe Rodriguez a, Jeffrey T Dunn a, Andrea Locci a, Hector Orellana a, Isabel Haupfear a, Sky Dominguez a, Daniel W Fisher a,c, Hongxin Dong a,d
PMCID: PMC10106415  NIHMSID: NIHMS1880970  PMID: 36989547

Abstract

Most patients with Alzheimer’s disease (AD) develop neuropsychiatric symptoms (NPS) alongside cognitive decline, and apathy is the one of most common symptoms. Few preclinical studies have investigated the biological substrates underlying NPS in AD. In this study, we used a cross-sectional design to characterize apathy-like behaviors and assess memory in 5xFAD and wildtype control mice at 6, 12, and 16 months of age. Nest building, burrowing, and marble burying were used to test representative behaviors of apathy, and a composite score of apathy-like behavior was generated from these assays. Soluble Aβ42 and plaques were quantified in the prefrontal cortex and hippocampus of the 5xFAD mice with the highest and lowest composite scores using ELISA and histology. Results suggest that 5xFAD mice develop significant apathy-like behaviors starting at 6 months of age that worsen with aging and are positively correlated with soluble Aβ42 and plaques in the prefrontal cortex and hippocampus. Our findings highlight the utility of studying NPS in mouse models of AD to uncover important relationships with underlying neuropathology.

Keywords: Alzheimer’s disease, apathy-like behavior, mouse model, amyloid beta, prefrontal cortex, hippocampus

1. INTRODUCTION

Alzheimer’s disease (AD) is the most common neurodegenerative disease and cause of dementia (Alzheimer’s Association, 2021) and is defined by neuropathological changes including aggregation of amyloid beta (Aβ) into extracellular plaques and hyperphosphorylation of tau into intraneuronal tangles (Beffert and Poirier, 1996). Alzheimer’s dementia is the most commonly associated clinical phenotype and is typically characterized by early amnestic memory impairment followed by progressive cognitive and functional decline (McKhann et al., 2011). Most patients with AD also develop salient changes in personality and behavior known as neuropsychiatric symptoms (NPS) (Geda et al., 2013; Radue et al., 2019). NPS are associated with a steeper decline in daily functioning, reduced patient quality of life, greater caregiver burden, and quicker nursing home placement (Borda et al., 2020; Brodaty et al., 2014; Connors et al., 2020). There is even some evidence that families and caregivers are more attuned to NPS than to cognitive changes as signs of AD (Honjo et al., 2022). Treatment of NPS is limited by a lack of standardization among non-pharmacological and pharmacological approaches. When NPS do not pose a safety risk, non-pharmacological approaches are often recommended as first-line treatment but are limited in their effectiveness and feasibility (Kraus-Schuman et al., 2020; Seitz et al., 2012). Medications commonly prescribed off-label for NPS include a selective serotonin reuptake inhibitor for mood symptoms, a low-dose antipsychotic for agitation/aggression, or a low-dose stimulant for apathy (Wolinsky et al., 2018). However, clinical benefits of these medications can be limited by their side effects, and there are currently no medications approved by the Food and Drug Administration to specifically treat NPS in AD.

Although research in animal models of AD has primarily focused on the neuropathological mechanisms of memory decline, neuropsychiatric-like behaviors are also reported, such as aggression, depression, anxiety, and social withdrawal (Kosel et al., 2020). Apathy is the most common NPS in AD patients (Lyketsos et al., 2011) and is defined clinically as reduced motivation for goal-directed behavior, cognitive activity, and/or socioemotional engagement leading to functional impairment in daily activities (Nobis and Husain, 2018; Robert et al., 2010). In mice, nest building (Deacon, 2006a), marble burying (Deacon, 2006c), and burrowing (Deacon, 2006b) assays are frequently used to evaluate impairments in rodent-typical behaviors akin to impaired activities of daily living in AD (Nichols et al., 2016; Si et al., 2022). Evidence suggests that impaired or “apathy-like” performance on these assays reflects reduced motivation for goal-directed behavior in mice (Baumann et al., 2016; de Brouwer et al., 2019; Jirkof, 2014). Likewise, deficits in fine motor planning and motivation, rather than gross motor impairments observed in some transgenic mouse models of AD, appear to primarily impact performance (Jirkof, 2014). Furthermore, lesions to the hippocampus and prefrontal cortex (PFC)—both implicated in apathy and AD—are associated with poor performance on these tests in C57BL/6J mice (Deacon et al., 2002; Deacon and Rawlins, 2005). Despite these indications, researchers have not yet rigorously characterized apathy-like behaviors using these paradigms in a transgenic mouse model of AD (Kosel et al., 2020).

In this study, we evaluated apathy-like behaviors in 5xFAD mice, one of the most studied transgenic mouse models of AD. The 5xFAD model contains 5 mutations in APP and PSEN1 associated with familial forms of AD, leading to robust Aβ pathology (Oakley et al., 2006). We found that apathy-like behaviors emerged in 5xFAD mice at 6 months of age and worsened in severity with aging. Our results also showed positive associations between the severity of apathy-like behavior and Aβ neuropathology, most notably in the PFC but also in the hippocampus. To our knowledge, this study is the first to systemically characterize relationships between apathy-like behaviors, memory impairment, Aβ pathology, and disease progression in a mouse model of AD.

2. MATERIALS AND METHODS

2.1. Experimental animals

Male and female 5xFAD heterozygous (model name: B6.Cg-Tg (APPSwFlLon, PSEN1*M146L*L286V)6799Vas/Mmjax) and C57BL/6J mouse breeders were purchased from Jackson Laboratories at 8–10 weeks of age. Breeding cages housed one male 5xFAD mouse with two female C57BL/6J mice. At 21–24 days of age, litters underwent genotyping by PCR with hPS1 primers (forward: 5′-GCT TTT TCC AGC TCT CAT TTA CTC-3′; reverse: 5′-AAA AAT GAT GGA ATG CTA ATT GTT-3′). Offspring were housed with 1–4 same-sex littermates in cages with woodchip bedding, a 5 cm2 cotton “nestlet” for enrichment, and food and water accessible ad libitum. Housing facilities maintained a 12-hr light/dark cycle and a temperature of 22 ± 2° C. We tested a total of 263 male and female 5xFAD and WT mice at 6, 12, and 16 months of age (n=9–15 per group, distribution of sexes approximately equal). All care and use of animals took place in accordance with Northwestern University’s Institutional Animal Care and Use Committee guidelines and the NIH Guide for Care and Use of Laboratory Animals.

2.2. Behavioral assays

An experimenter handled the mice once per day for three consecutive days before starting behavioral testing to reduce stress effects. We sanitized test materials with 70% ethanol and deionized water before testing each animal on an apparatus to eliminate scents. Apathy-like behavioral tests were completed in the order depicted in Fig. 1, and all assays were scored by an experimenter blinded to group.

Figure 1. Schematic and ordering of behavioral tests of apathy-like behaviors.

Figure 1.

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(A) Nest building: Mice were housed individually and built nests overnight. (B) Burrowing: After a 24-hr habituation period to burrows in group-housed cages, mice completed the 2-hr burrowing test in individually housed cages and were then permitted to burrow overnight. (C) Marble burying: Mice were placed into individual cages and were given 30 minutes to bury 12 marbles.

2.2.1. Nest building

We performed the nest building assay (Fig. 1A) in home cages located in the animal housing facility, similar to Deacon (2006a). Briefly, mice were placed into individually housed cages overnight with a square “nestlet” of cotton batting (5 cm2). Nests were scored the next morning according Deacon’s criteria, ranging from 1 (lowest nest building quality, highest apathy-like behavior) to 5 with half-point scores for nests falling between categories.

2.2.2. Burrowing

The burrowing test (Fig. 1B) took place in home cages in the animal housing facility using slight modifications from Deacon (2006b). Briefly, we constructed burrows from white PVC pipe (20 cm length, 5.5 cm diameter) with one open and one closed end and adhered the open ends to glass bottles (2.5 cm diameter) to raise them at a slight angle. Mice first underwent a 24-hr habituation in which burrows filled with 200 g of chow were placed into their holding cages. The next day, an experimenter placed mice into individually housed cages with filled burrows. The experimenter weighed the chow burrowed after 2 hr and again 15 hr later (i.e., overnight). Mice that burrowed less (i.e., removed less chow) were deemed as demonstrating greater apathy-like behavior.

2.2.3. Marble burying

We conducted the marble burying assay (Fig. 1C) similarly to Deacon (2006c). Mice acclimated to the testing room for 1 hr to lower stress associated with a novel environment. Then, we placed mice into individual cages with twelve glass marbles (1.5 cm diameter) positioned equidistantly in 3×4 rows atop 5 cm of woodchip bedding. After 30 min, an experimenter counted the marbles buried (i.e., ≤1/3 visible), and fewer marbles buried indicated more severe apathy-like behavior.

2.2.4. Y-maze – Spontaneous alternation

The Y-maze had three arms (5 cm wide × 21 cm long × 15.5 cm high; termed arms ‘A’, ‘B’, and ‘C’) each at a 120° angle from a center zone and containing a distinct spatial cue (i.e., 2D geometric shape) at the end. During testing, we placed the apparatus on a table and illuminated it at 30 lux. Mice started by facing the end of arm ‘A’ and explored freely until they completed 23 arm entries or until 5 min elapsed. We recorded movements from overhead using Any-Maze video software (Stoelting, Wood Dale, IL) and scored entries, defined as all paws within an arm after initially exiting arm A, and spontaneous alternations, defined as three consecutive entries into different arms (i.e., ABC, ACB, BAC, BCA, CAB, and CBA). A mouse entering the same arm twice in a row reset the “spontaneous alternation” criteria. We assessed working memory ability by the percentage of spontaneous alternation: [Total Alternations/(Total Entries–2)]*100. Mice with fewer than one third of the possible number of entries (i.e., ≤7) were excluded.

2.2.5. Composite scores of apathy-like behaviors

We calculated z-scores for nest building, 2-hr burrowing, and marble burying for each mouse relative to the mean and standard deviation (SD) of same-age WT controls so that changes of ±1 z-score unit represented ±1 SD of the control sample’s behavior. To reduce the variance and enhance the reliability of our data (Guilloux et al., 2011), we created composite scores of apathy-like behaviors for each mouse using the following equation: (zi_nest+zi_burrow+zi_marble)/3. We found moderate-to-strong positive correlations between z-scores for nest building, 2-hr burrowing, and marble burying (supplemental Fig. 1), providing further support for using composite scores to indicate overall apathy-like behavior severity. Overnight burrowing was excluded from the composite calculation as it deviated from the normal distribution required for z-scoring and tends to be less sensitive to individual differences due to a ceiling effect (Deacon, 2006b).

2.3. Biochemical analyses

2.3.1. Sample selection

We chose a subset of ‘high-apathy’ and ‘low-apathy’ 5xFAD mice for biochemical analyses, which we defined as having apathy composite scores in the top or bottom third of each age-by-sex group, respectively. High-apathy and low-apathy groups differed by 1.64 SDs on average. Final sample sizes per age were n=6–8 for ELISA (total N=42) and immunohistochemistry (total N=37).

2.3.2. Soluble human Aβ42 quantification using ELISA

Samples from the PFC and hippocampus were prepared by homogenizing the dissected mouse brain tissue with 1x PBS and a protease inhibitor cocktail (Sigma, Cat# P2714). We then used an ELISA kit (Thermo Fisher Scientific, Cat# KHB3441) to detect soluble human Aβ42 according to the manufacturer’s protocol.

2.3.3. Thioflavin-S staining and quantification

Tissue sections (40 μm thick) were stained with thioflavin-S to visualize and quantify fibrillar amyloid plaques (Christensen and Pike, 2020) in contrast to the soluble Aβ42 described above. Briefly, sections containing the PFC (bregma: 2.10 to 1.94 mm) and hippocampus (bregma: −1.22 to −2.54 mm) were washed with 1xPBS, stained for 5 min in 1% thioflavin-S (Sigma, Cat# T1892) aqueous solution, and differentiated for 3 min in 70% alcohol (Franklin and Paxinos, 2008; Guntern et al., 1992). Then, sections were mounted onto slides coated with 2% pig skin gelatin (Sigma, Cat# G1890), coverslipped with Fluorescence Mounting Medium (Abcam, Cat# ab104135), and stored overnight at 4°C. We used a Nikon Eclipse-Ni-E fluorescent microscope to image thioflavin-S-stained plaques in 4 sections of the PFC and dorsal hippocampus per mouse at 10x magnification for quantification. In the PFC, we counted plaques from the rhinal sulcus to the anterior cortex. In the hippocampus, we focused our plaque quantification in the CA1 subregion (from the end of the subiculum to the start of CA2 subregion) given its functional connectivity with the PFC (Li et al., 2015). Using ImageJ Software (v1.53), we determined the mean number and size of Aβ plaques in all PFC and CA1 sections per mouse according to published methods (Locci et al., 2021).

2.4. Experimental design and statistical analysis

Our study followed a cross-sectional design at 6, 12, and 16 months of age. We performed statistical analyses with RStudio Software (v1.1.456, R v4.0.2) packages “lme4” (Bates et al., 2015), “lmerTest” (Kuznetsova et al., 2017), and “emmeans” (Lenth et al., 2022). Outliers beyond the mean ±2 SDs within each group were excluded. Linear models regressed behavioral outcomes on genotype, age, sex, and interactions and biochemical outcomes on apathy-like behavior severity (dichotomous, high-apathy or low-apathy), age, sex, and interactions. Significant results were followed by pairwise comparisons using Tukey’s adjustment for comparing a family of estimates. All graphs depict the mean ± standard error of the mean (S.E.M.).

3. RESULTS

3.1. Apathy-like behaviors emerged in 6-month-old 5xFAD mice and worsened with age

3.1.1. Nest building

Nest building analyses indicated significant effects of genotype (F1,125=73.91, p<0.0001), age (F2,125=4.30, p=0.016), and their interaction (F2,125=11.29, p<0.0001). At 12 and 16 months, but not at 6 months of age, 5xFAD mice had lower nest scores than same-age WT mice (Fig. 2A, both p<0.0001). In 5xFAD mice, nest building was poorer at 12 and 16 months than at 6 months of age (Fig. 2A, both p<0.0001), whereas WT mice obtained slightly higher nest scores with aging. The interaction between age and sex was also significant (F2,125=3.32, p=0.039). At all ages, females tended to have lower nest scores than males overall, and this approached significance at 16 months of age (p=0.0690). In female mice, nest scores were lower at 12 and 16 months than at 6 months of age (Fig. 2A, both p=0.003), an effect that was driven by 5xFAD females. While not significant, nest scores for male 5xFAD mice also tended to decrease with aging.

Figure 2. Apathy-like behaviors in WT and 5xFAD mice.

Figure 2.

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(A) Nest scores were significantly lower in 5xFAD mice at 12 and 16 months of age compared to same-age WT mice. In female mice overall and in 5xFAD mice specifically, nest scores were significantly lower at 12 and 16 months of age compared to 6 months of age. (B) 5xFAD mice burrowed less in 2 hr than WT mice. Among WT mice, 2-hr burrowing was lower in females than in males. In 5xFAD mice, 2-hr burrowing was lower at 12 and 16 months of age than at 6 months of age. (C) In females specifically, overnight burrowing was lower in 5xFAD than in WT mice and was lower at 16 months than at 6 and 12 months of age. In 5xFAD mice specifically, females burrowed less overnight than males across all ages; regardless of genotype, females burrowed less overnight than males at 12 and 16 months of age. (D) 5xFAD mice buried fewer marbles than WT mice. (E) Apathy composite scores were higher for 5xFAD mice than for WT mice. Composite scores were highest for 12-month-old 5xFAD mice; in this group, females scored higher than males. (F) Spontaneous alternation on the Y-maze was lower in 5xFAD than in WT mice, reaching significance at 12 months of age. Linear regression results with Tukey adjustment are shown as mean ± SEM (n=9–15 per group as shown by circles). Symbols denoting significant comparisons are as follows: *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001; a: vs. same-age WTs, b: vs. same-sex 6-month-old mice, c: vs. same-genotype 6-month-old mice, d: vs. same-sex 16-month-old mice, e: vs. same-age males; in 5xFAD mice only, f: vs. same-sex 6-month-old mice (age effect), g: vs. same-sex 16-month-old mice (age effect), and h: vs. same-age males (sex effect).

3.1.2. Burrowing

Two-hour burrowing analyses revealed significant effects of genotype (F1,119=84.15, p<0.0001), age (F2,119=4.72, p=0.011), and sex (F1,119=10.55, p=0.002) for grams of chow burrowed. Analyses also showed significant interactions between genotype and age (F2,119=3.68, p=0.028) and genotype and sex (F1,119=5.07, p=0.026). Burrowing was lower in 5xFAD than in WT mice at all ages (Fig. 2B, 6 months: p<0.001, 12 and 16 months: p<0.0001). 5xFAD mice burrowed less at 12 months (p=0.002) and 16 months (p=0.019) than at 6 months of age (Fig. 2B), whereas 2hr burrowing remained relatively stable with aging in WT mice. Both sexes of 5xFAD mice burrowed less than WT mice (Fig. 2B, both p<0.0001), and female WT mice burrowed less than their male counterparts (Fig. 2B, p<0.001).

Overnight burrowing analyses demonstrated significant effects of genotype (F1,114=12.44, p<0.001), age (F2,114=15.78, p<0.0001), and sex (F1,114=26.07, p<0.0001). The interaction between genotype and sex was significant (F1,114=9.23, p=0.003) with female 5xFAD mice burrowing less overnight than their male and WT counterparts (Fig. 2C, both p<0.0001). The interaction between age and sex was also significant (F2,114=9.63, p<0.001). Regardless of genotype, overnight burrowing was reduced in 16-month-old females compared to 6- and 12-month-old females (Fig. 2C, both p<0.0001), whereas males burrowed similar amounts overnight across age groups. Irrespective of genotype, overnight burrowing was also reduced in females compared to same-age males at 12 months (Fig. 2C, p=0.029) and 16 months of age (Fig. 2C, p<0.0001) but similar between sexes at 6 months of age.

3.1.3. Marble burying

Analyses revealed a significant effect of genotype, but not age or sex, for marbles buried (F1,121=142.62, p<0.0001). Starting at 6 months of age, 5xFAD mice buried fewer marbles than WT mice, and this genotype difference in behavior continued at 12 and 16 months of age (Fig. 2D, p<0.0001).

3.1.4. Composite scores of apathy-like behaviors

Analyses indicated significant effects of genotype (F1,116=294.76, p<0.0001), age (F2,116=11.58, p<0.0001), and sex (F1,116=6.72, p=0.011), a significant interaction between genotype and age (F2,116=11.76, p<0.0001), and a significant 3-way interaction (F2,116=3.09, p=0.049) on composite scores of apathy-like behaviors. Composite scores were higher at all ages and in both sexes of 5xFAD compared to WT mice (Fig. 2E, p<0.001 for 6-month-old females, p<0.0001 for all others). For 12-month-old 5xFAD mice, composite scores were higher than at 6 months (males p=0.002, females p<0.0001) and 16 months of age (males p=0.087, females p=0.026) and were higher in females than in males (Fig. 2E, p=0.019). Female 5xFAD mice also had significantly higher composite scores at 16 months than at 6 months of age (Fig. 2E, p=0.002).

3.2. Working memory deficits appeared in 5xFAD mice starting at 12 months of age

Analyses of spontaneous alternation using the Y-maze test uncovered a significant effect of genotype (F1,113=11.56, p<0.001) and a significant interaction between genotype and age (F2,113=3.31, p=0.040). The percentage of spontaneous alternation was significantly lower in 12-month-old 5xFAD mice compared to same-age WT mice (Fig. 2F, p<0.001) and trended lower in 16-month-old WT mice compared to 12-month-old WT mice (p=0.058). Surprisingly, we did not observe a significant deficit in successful spontaneous alternation percentage in our 5xFAD mice at 16 months of age, so we performed the Morris Water Maze (MWM) (Vorhees and Williams, 2006) followed by linear regression analyses to further assess memory function (supplemental Fig. 2). Compared to same-age WT mice, 16-month-old 5xFAD mice took a significantly longer time to reach the target platform during acquisition and probe trials (both p<0.0001). Swim speed was slower for 5xFAD mice during both learning and memory trials (both p<0.0001) but only significantly predicted performance for the latter (p<0.0001). Covarying for this, probe trial results were no longer significant between genotypes in females but remained significantly impaired in male 5xFAD mice compared to male WT mice (p=0.047).

3.3. Soluble Aβ42 in the PFC and hippocampus of 5xFAD mice was associated with apathy-like behavior and age

The severity of apathy-like behavior was positively correlated with the level of soluble Aβ42 in the PFC (Pearson r=0.392, p=0.011, supplemental Fig. 3). This relationship remained significant when controlling for age and sex in regression analysis (F1,30=4.86, p=0.035) with high-apathy 5xFAD mice showing elevated soluble Aβ42 in the PFC compared to low-apathy mice (p=0.042). The effect of age in the regression was also significant (F2,30=8.64, p=0.001) with a higher level of soluble Aβ42 in the PFC at 12 months (trend, p=0.050) and 16 months (p<0.001) than at 6 months of age (Fig. 3A).

Figure 3. Biochemical analyses in the PFC of low-apathy and high-apathy 5xFAD mice.

Figure 3.

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(A) High-apathy mice had a greater concentration of soluble Aβ42 in the PFC than low-apathy mice. Soluble Aβ42 in the PFC was higher in 5xFADs at 12 and 16 months than at 6 months of age. (B) Females had more Aβ plaques in the PFC than males. (C) Aβ plaques were larger in the PFC at 6 months than at 12 and 16 months of age. (D) PFC sections stained with thioflavin-S to visualize fibrillar Aβ deposits. Images taken at 10x magnification with scale bar indicating 100 μm. Linear regression results with Tukey adjustment are shown as mean ± SEM. Circles denote numbers per group (n=6–8 per age). Symbols denoting significant comparisons are as follows: *p<0.05, ***p<0.001, and ****p<0.0001. i: 6-month-old < 12-month-old mice on average and j: 6-month-old < 16-month-old mice on average.

In the hippocampus, soluble Aβ42 levels did not differ significantly according to the severity of apathy-like behavior. However, the effect of age was significant (F2,30=42.88, p<0.0001) with higher hippocampal Aβ42 at 16 months compared to 6 and 12 months of age (both p<0.0001) and at 12 months compared to 6 months of age (Fig. 4A, p=0.006). Soluble Aβ42 levels in the hippocampus also trended higher in females than in males (Fig. 4A, F1,30=3.21, p=0.083).

Figure 4. Biochemical analyses in the hippocampus of low-apathy and high-apathy 5xFAD mice.

Figure 4.

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(A) Soluble Aβ42 in the hippocampus was higher at 12 and 16 months than at 6 months of age and at 16 months than at 12 months of age but did not substantially differ by apathy-like behavior severity or sex. (B) High-apathy, 12-month-old females had more Aβ plaques in the hippocampal CA1 than low-apathy, 12-month-old females (apathy effect); high-apathy, 12-month-old males (sex effect); and high-apathy, 6-month-old females (age effect). Low-apathy, 12-month-old males had more Aβ plaques in the CA1 than low-apathy, 6-month-old males (age effect). (C) Mean Aβ plaque size in the CA1 did not significantly differ by apathy-like behavior severity, age, or sex. (D) Sections of the hippocampal CA1 subregion stained with thioflavin-S to visualize fibrillar Aβ deposits. Images taken at 10x magnification with scale bar indicating 100 μm. Linear regression results with Tukey adjustment are shown as mean ± SEM. Circles denote numbers per group (n=6–8 per age). Symbols denoting significant comparisons are as follows: *p<0.05, **p<0.01, and ****p<0.0001. i: 6-month-old < 12-month-old mice on average, j: 6-month-old < 16-month-old mice on average, and k: 12-month-old < 16-month-old mice on average.

3.4. Aβ plaques in the PFC and hippocampus of 5xFAD mice correlated with apathy-like behavior severity, age, and sex

The number of Aβ plaques in the PFC was positively correlated with the severity of apathy-like behavior (Pearson r=0.386, p=0.018, supplemental Fig. 3), but this relationship was no longer significant when controlling for age and sex in regression analysis. The effect of sex in the regression was significant (F1,25=10.87, p=0.003) with more PFC plaques in female than in male 5xFAD mice (Fig. 3B, D, p=0.003). Analysis of PFC plaque size suggested a trend for larger plaques in high-apathy compared to low-apathy 5xFAD mice (Fig. 3B, D, F1,24=3.52, p=0.073).

In the hippocampus, the number of Aβ plaques in the CA1 subregion was positively correlated with the severity of apathy-like behavior (Pearson r=0.456, p=0.005, supplemental Fig. 3). Linear regression controlling for age and sex revealed significant relationships between the number of Aβ plaques in this region and the severity of apathy-like behavior (F1,24=5.05, p=0.034), age (F2,24=4.44, p=0.023), and the 3-way interaction (F2,24=3.98, p=0.032). High-apathy 5xFAD mice had more plaques than their low-apathy counterparts, particularly in 12-month-old females (Fig. 4B, D p=0.018). Plaques were also more numerous at 12 months than at 6 months of age in both low-apathy males (p=0.049) and high-apathy females (p=0.014). Among high-apathy 5xFAD mice, females had more Aβ plaques than males at 12 months (p=0.025) and 16 months of age (Fig. 4B, D, trend, p=0.055). Analyses of hippocampal plaque size were not significant for the effects of genotype, age, or sex (Fig. 4C, D).

4. DISCUSSION

In this study, we characterized apathy-like behaviors in 5xFAD mice, a commonly used transgenic mouse model for the study of AD. These behaviors emerged at 6 months of age and worsened with aging at 12 and 16 months. Based on our observations of memory impairment at 12, but not 6, months of age in our 5xFAD mice, apathy may be a prodromal behavioral indicator of AD; however, further confirmation using more sensitive memory tests and in additional mouse models of AD is needed. Importantly, we found an association between greater apathy composite scores and more severe Aβ pathology, most notably a significantly higher level of soluble Aβ42 in the PFC, but also with trends towards larger Aβ plaques in the PFC and more numerous Aβ plaques in the hippocampus. Apathy-like behaviors were also more severe in females than in males, especially in aged groups. To our knowledge, this is the first study to: 1) systematically characterize apathy-like behaviors in a mouse model of AD across ages, sexes, and multiple behavioral assays, 2) to establish associations between apathy-like behavior severity and soluble and insoluble amyloid pathology, and 3) to suggest that apathy-like behavior maybe a prodromal indicator of AD. Overall, our findings highlight the utility of preclinical models to investigate dynamic relationships between NPS, cognitive deficits, and their underlying biological mechanisms in AD.

In this study, our finding that apathy-like behaviors started at 6 months of age in 5xFAD mice on a C57BL/6J background—a timepoint before we could detect memory impairment in this strain—has important implications for NPS as a clinical marker of early AD. Current literature on ‘mild behavioral impairment,’ or the onset of NPS in cognitively normal older adults, implies that NPS often emerge during the prodromal stage of AD (Ismail et al., 2016), and cognitively normal older adults who experience mild changes in mood and behavior may be at a greater risk of dementia (Lyketsos et al., 2011). Apathy-like behaviors also worsened with advancing age and with the onset of memory deficits in our 5xFAD model, further paralleling the course of apathy in AD patients (Lü et al., 2021; Wiels et al., 2021). However, investigations of other mouse models of AD and domains of apathy-like behavior using assays such as the social interaction test (Kosel et al., 2020) are needed to more comprehensively understand relationships between apathy-like behavior and cognition in AD. Establishing animal models that recapitulate the relative timing of NPS and cognitive decline in AD will provide opportunities to investigate their underlying mechanisms, which could aid in developing optimal strategies for early intervention.

The concurrent progression of NPS and cognitive impairment in AD implies that similar biological mechanisms related to accumulating AD neuropathology may underlie both processes (Wingo et al., 2022). In this study, the level of soluble Aβ42 in the PFC was most positively associated with apathy-like behaviors, but this relationship was attenuated in the hippocampus. We also observed relationships between Aβ plaque burden and apathy-like behaviors—albeit to a lesser degree—with larger and more numerous plaques in the PFC and hippocampus, respectfully, of high-apathy 5xFAD mice. In AD, it is hypothesized that Aβ pathology accumulates in the preclinical stage (Sperling et al., 2011) and is initially deposited diffusely in the neocortex followed by the CA1 subregion of the hippocampus and entorhinal cortex (Thal et al., 2002). Prior research has shown strong associations between Aβ burden in the prefrontal cortex and apathy in human patients (Mori et al., 2014), and those having abnormal amyloid retention on positron emission tomography and more severe NPS showing the steepest rates of cognitive decline (Pink et al., 2023). Findings of previous studies suggest that soluble Aβ is more toxic to synaptic function than insoluble fibrils (Lison et al., 2014; Shankar et al., 2007; Shankar et al., 2008) and may contribute to behavioral symptoms in AD through dysregulation of presynaptic neurotransmitter release (Fagiani et al., 2021; Ismail et al., 2016; Lanni et al., 2019). Specifically, pathologic Aβ deposition may impact reward circuitry through reduced acetylcholine-mediated dopamine release in the PFC and hippocampus, leading to apathy (Levy and Dubois, 2006; Marshall et al., 2013; Mori et al., 2014; Preda et al., 2008; Ruggiero et al., 2021). Our results further highlight the role of soluble Aβ42 in promoting AD progression and behavior symptoms. We focused our analyses of soluble Aβ on the Aβ42 isoform as there is evidence that it is more toxic and prone to aggregation than the Aβ40 isoform also commonly implicated in AD (Nirmalraj et al., 2020; Sgourakis et al., 2007). Though beyond the scope of this study, future studies may investigate relationships among soluble Aβ40 and Aβ42, early synaptic dysfunction, and apathy-like behavior in the 5xFAD model. In addition to amyloid-mediated synaptic dysfunction, prior reports indicate significant relationships between NPS and other pathological hallmarks of AD including phosphorylated tau (Kitamura et al., 2018; Malpas et al., 2020; Marshall et al., 2019; Skogseth et al., 2008). While not a model of tau pathology, 5xFAD mice exhibit elevated phosphorylated and total tau (Kanno et al., 2014). Whether this contributes to the salience of apathy-like behavior over the course of disease in this model is an interesting area for future research that may reveal additional relationships between apathy-like behaviors and AD-related neuropathologies.

Variability in memory performance has been widely reported in AD mouse models, and especially in 5xFAD mice (Devi et al., 2015; Kosel et al., 2019; Neuner et al., 2019; O’Leary et al., 2020; Oakley et al., 2006; Porsteinsson et al., 2014; Schneider et al., 2014; Xiao et al., 2015). To highlight group-level heterogeneity in studies of 5xFAD mice, some have reported memory impairment as early as 4–6 months of age on the Y-maze and MWM (Devi et al., 2015; Oakley et al., 2006; Xiao et al., 2015), whereas others have reported a lack of memory deficits even at 15 months of age (O’Leary et al., 2020). In our study, 5xFAD mice showed a significant memory deficit in spontaneous alternation compared to WT mice at 12 months of age, but unexpectedly, spontaneous alternation performance was not significantly different between 5xFAD mice and WT mice at 16 months of age. Further investigation via the MWM demonstrated deficient learning and memory in 16-month-old 5xFAD mice compared to their same-age WT counterparts, although the latter was influenced by genotype differences in swim speed. Several factors may have contributed to these discrepant findings in our 12- and 16-month-old 5xFAD mice. While the severity of apathy-like behaviors generally worsened with aging, composite scores were also less discrepant between genotypes at 16 than at 12 months of age. Normal, age-related brain changes lead to increased rates of certain mood symptoms and memory recall decline in “healthy” aging (Donovan et al., 2015; Koen and Yonelinas, 2016), and similar mechanisms may have contributed to our findings in 5xFAD mice. Given our cross-sectional design, individual differences may have also obfuscated trends of progressive memory impairment that would have otherwise been observable longitudinally (Havas et al., 2011; Kent et al., 2017). Genetics play an important role; a recent seminal study showed that the C57BL/6J background used in our study was “protective” against memory impairment until 15 months of age, including in comparison to the B6SJL background on which the 5xFAD model was created (Neuner et al., 2019). Differences in methodologies between research groups (e.g., Jawhar et al. (2012) vs. our spontaneous alternation paradigm) and in the sensitivity of various learning and memory paradigms may also contribute to this variability (Kosel et al., 2019). Additional considerations include gross motor impairments (Jawhar et al., 2012; O’Leary and Brown, 2022; O’Leary et al., 2020), retinal dysfunction (Lim et al., 2020), and anhedonia (Strekalova et al., 2004). In summary, 5xFAD mice—like many other transgenic AD models (Jankowsky and Zheng, 2017)—display considerable variability in memory performance. Therefore, investigations in additional mouse models of AD and with additional paradigms are needed to fully dissect the dynamic associations between apathy-like behaviors and memory deficits throughout the disease course.

Prior reports have found apathy to be more common in male than in female patients with dementia (Tao et al., 2018; Vik-Mo et al., 2018; Xing et al., 2012; Zuidema et al., 2009); however, apathy-like behaviors tended to be more severe in female than in male mice in the present study. This may be attributed to more robust Aβ pathology in our female 5xFAD mice, namely more plaques in the PFC and a trend for higher soluble Aβ42 in the hippocampus. These findings are expected given the design of the 5xFAD model, which uses the Thy1 promoter containing an estrogen response element to induce overexpression of human APP and potentially exacerbates transgene expression and Aβ pathology in females (Bundy et al., 2019; Sadleir et al., 2015). By contrast, other mouse models of AD, such as APPNLGF knock-in model, develop Aβ pathology without APP overexpression and do not show significant sex differences in behavior at baseline (Auta et al., 2022). Taken together, these findings suggest that alternative mouse models of AD are likely better suited for studies that aim to characterize sex differences in apathy and their underlying mechanisms.

In summary, findings of the present study suggest early and dynamic apathy-like behaviors in the 5xFAD mouse model on a C57BL/6J background. This apathetic phenotype was positively correlated with amyloid pathology in the PFC and hippocampus, most notably with an increased soluble Aβ42 level in the PFC. Our study highlights a potentially shared mechanism of region-specific amyloid pathology in promoting AD progression and behavior symptoms. Our findings in 5xFAD mice support early identification of and intervention in patients with preclinical apathy and elevated Aβ in the PFC. Intervention strategies targeting NPS such as apathy in the earlier stages of AD may help to prevent or slow memory impairment and to improve quality of life in AD patients and caregivers.

Supplementary Material

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Highlights.

  • Six-month-old 5xFAD mice developed apathy-like behaviors that worsened with aging.

  • 5xFAD mice with higher apathy had more soluble Aβ42 in the prefrontal cortex (PFC).

  • Apathy was positively correlated with Aβ plaque burden in the PFC and hippocampus.

  • This investigation indicates early and dynamitic changes of apathy in 5xFAD mice.

  • Findings implicate Aβ in prefrontal-hippocampal circuits in developing apathy.

Funding:

This study was supported by the National Institute of Aging (1R01AG062249; PI: Hongxin Dong) and the National Institute of Neurological Disorders and Stroke (5T32NS047987-14; PI: Ken Paller, Recipient: Rachel Keszycki) of the National Institute of Health.

Footnotes

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Declarations of interest: None

CRediT authorship contribution statement

Rachel Keszycki: Conceptualization, Methodology, Formal Analysis, Investigation, Writing – Original Draft, Writing – Review & Editing, Visualization, Project Administration; Guadalupe Rodriguez: Conceptualization, Investigation, Supervision, Project Administration; Jeffrey T. Dunn: Conceptualization, Writing – Review & Editing, Validation; Andrea Locci: Conceptualization, Methodology, Investigation; Hector Orellana: Investigation; Isabel Haupfear: Investigation; Sky Dominguez: Investigation; Daniel W. Fisher: Conceptualization, Methodology, Writing – Review & Editing, Supervision; Hongxin Dong: Conceptualization, Methodology, Writing – Review & Editing, Supervision, Project Administration, Funding Acquisition

Verification

The co-authors have reviewed and approved of the contents of this manuscript. I can certify that this manuscript is not under review at any other publication. The work contained within this manuscript does not overlap with any other submissions or reports. There are no financial or other relationships that would lead to a perceived conflict of interest.

REFERENCES

  1. Alzheimer’s Association, 2021. 2021 Alzheimer’s disease facts and figures. Alzheimers Dement 17(3), 327–406. [DOI] [PubMed] [Google Scholar]
  2. Auta J, Locci A, Guidotti A, Davis JM, Dong H, 2022. Sex-dependent sensitivity to positive allosteric modulation of GABA action in an APP knock-in mouse model of Alzheimer’s disease: Potential epigenetic regulation. Current Research in Neurobiology 3, 100025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bates D, Mächler M, Bolker B, Walker S, 2015. Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software 67(1), 1 – 48. [Google Scholar]
  4. Baumann A, Moreira CG, Morawska MM, Masneuf S, Baumann CR, Noain D, 2016. Preliminary Evidence of Apathetic-Like Behavior in Aged Vesicular Monoamine Transporter 2 Deficient Mice. Frontiers in Human Neuroscience 10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Beffert U, Poirier J, 1996. Apolipoprotein E, plaques, tangles and cholinergic dysfunction in Alzheimer’s disease. Ann N Y Acad Sci 777, 166–174. [DOI] [PubMed] [Google Scholar]
  6. Borda MG, Aarsland D, Tovar-Rios DA, Giil LM, Ballard C, Gonzalez MC, Brønnick K, Alves G, Oppedal K, Soennesyn H, Vik-Mo AO, 2020. Neuropsychiatric Symptoms and Functional Decline in Alzheimer’s Disease and Lewy Body Dementia. J Am Geriatr Soc 68(10), 2257–2263. [DOI] [PubMed] [Google Scholar]
  7. Brodaty H, Connors MH, Xu J, Woodward M, Ames D, 2014. Predictors of institutionalization in dementia: a three year longitudinal study. J Alzheimers Dis 40(1), 221–226. [DOI] [PubMed] [Google Scholar]
  8. Bundy JL, Vied C, Badger C, Nowakowski RS, 2019. Sex-biased hippocampal pathology in the 5XFAD mouse model of Alzheimer’s disease: A multi-omic analysis. J Comp Neurol 527(2), 462–475. [DOI] [PubMed] [Google Scholar]
  9. Christensen A, Pike CJ, 2020. Staining and Quantification of beta-Amyloid Pathology in Transgenic Mouse Models of Alzheimer’s Disease. Methods Mol Biol 2144, 211–221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Connors MH, Seeher K, Teixeira-Pinto A, Woodward M, Ames D, Brodaty H, 2020. Dementia and caregiver burden: A three-year longitudinal study. Int J Geriatr Psychiatry 35(2), 250–258. [DOI] [PubMed] [Google Scholar]
  11. de Brouwer G, Fick A, Harvey BH, Wolmarans DW, 2019. A critical inquiry into marble-burying as a preclinical screening paradigm of relevance for anxiety and obsessive–compulsive disorder: Mapping the way forward. Cognitive, Affective, & Behavioral Neuroscience 19(1), 1–39. [DOI] [PubMed] [Google Scholar]
  12. Deacon RMJ, 2006a. Assessing nest building in mice. Nature Protocols 1(3), 1117–1119. [DOI] [PubMed] [Google Scholar]
  13. Deacon RMJ, 2006b. Burrowing in rodents: a sensitive method for detecting behavioral dysfunction. Nature Protocols 1(1), 118–121. [DOI] [PubMed] [Google Scholar]
  14. Deacon RMJ, 2006c. Digging and marble burying in mice: simple methods for in vivo identification of biological impacts. Nature Protocols 1(1), 122–124. [DOI] [PubMed] [Google Scholar]
  15. Deacon RMJ, Croucher A, Rawlins JNP, 2002. Hippocampal cytotoxic lesion effects on species-typical behaviours in mice. Behavioural Brain Research 132(2), 203–213. [DOI] [PubMed] [Google Scholar]
  16. Deacon RMJ, Rawlins JNP, 2005. Hippocampal lesions, species-typical behaviours and anxiety in mice. Behavioural Brain Research 156(2), 241–249. [DOI] [PubMed] [Google Scholar]
  17. Devi L, Tang J, Ohno M, 2015. Beneficial effects of the β-secretase inhibitor GRL-8234 in 5XFAD Alzheimer’s transgenic mice lessen during disease progression. Curr Alzheimer Res 12(1), 13–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Donovan NJ, Hsu DC, Dagley AS, Schultz AP, Amariglio RE, Mormino EC, Okereke OI, Rentz DM, Johnson KA, Sperling RA, Marshall GA, 2015. Depressive Symptoms and Biomarkers of Alzheimer’s Disease in Cognitively Normal Older Adults. J Alzheimers Dis 46(1), 63–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Fagiani F, Lanni C, Racchi M, Govoni S, 2021. (Dys)regulation of Synaptic Activity and Neurotransmitter Release by β-Amyloid: A Look Beyond Alzheimer’s Disease Pathogenesis. Front Mol Neurosci 14, 635880–635880. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Franklin K, Paxinos G, 2008. The mouse brain in stereotaxic coordinates, compact Ed 3. Amsterdam [ua]: Elsevier; 1082, 1083. [Google Scholar]
  21. Geda YE, Schneider LS, Gitlin LN, Miller DS, Smith GS, Bell J, Evans J, Lee M, Porsteinsson A, Lanctôt KL, Rosenberg PB, Sultzer DL, Francis PT, Brodaty H, Padala PP, Onyike CU, Ortiz LA, Ancoli-Israel S, Bliwise DL, Martin JL, Vitiello MV, Yaffe K, Zee PC, Herrmann N, Sweet RA, Ballard C, Khin NA, Alfaro C, Murray PS, Schultz S, Lyketsos CG, 2013. Neuropsychiatric symptoms in Alzheimer’s disease: Past progress and anticipation of the future. Alzheimer’s & Dementia 9(5), 602–608. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Guilloux J-P, Seney M, Edgar N, Sibille E, 2011. Integrated behavioral z-scoring increases the sensitivity and reliability of behavioral phenotyping in mice: Relevance to emotionality and sex. Journal of Neuroscience Methods 197(1), 21–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Guntern R, Bouras C, Hof PR, Vallet PG, 1992. An improved thioflavine S method for staining neurofibrillary tangles and senile plaques in Alzheimer’s disease. Experientia 48(1), 8–10. [DOI] [PubMed] [Google Scholar]
  24. Havas D, Hutter-Paier B, Ubhi K, Rockenstein E, Crailsheim K, Masliah E, Windisch M, 2011. A longitudinal study of behavioral deficits in an AβPP transgenic mouse model of Alzheimer’s disease. J Alzheimers Dis 25(2), 231–243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Honjo Y, Ide K, Takechi H, 2022. Most families tend to realize progress of Alzheimer’s disease when behavioural and psychological symptoms are obvious. Psychogeriatrics. [DOI] [PubMed] [Google Scholar]
  26. Ismail Z, Smith EE, Geda Y, Sultzer D, Brodaty H, Smith G, Agüera-Ortiz L, Sweet R, Miller D, Lyketsos CG, Area INSPI, 2016. Neuropsychiatric symptoms as early manifestations of emergent dementia: Provisional diagnostic criteria for mild behavioral impairment. Alzheimer’s & dementia : the journal of the Alzheimer’s Association 12(2), 195–202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Jankowsky JL, Zheng H, 2017. Practical considerations for choosing a mouse model of Alzheimer’s disease. Molecular neurodegeneration 12(1), 89–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Jawhar S, Trawicka A, Jenneckens C, Bayer TA, Wirths O, 2012. Motor deficits, neuron loss, and reduced anxiety coinciding with axonal degeneration and intraneuronal Aβ aggregation in the 5XFAD mouse model of Alzheimer’s disease. Neurobiology of Aging 33(1), 196.e129–196.e140. [DOI] [PubMed] [Google Scholar]
  29. Jirkof P, 2014. Burrowing and nest building behavior as indicators of well-being in mice. Journal of Neuroscience Methods 234, 139–146. [DOI] [PubMed] [Google Scholar]
  30. Kanno T, Tsuchiya A, Nishizaki T, 2014. Hyperphosphorylation of Tau at Ser396 occurs in the much earlier stage than appearance of learning and memory disorders in 5XFAD mice. Behavioural Brain Research 274, 302–306. [DOI] [PubMed] [Google Scholar]
  31. Kent BA, Heath CJ, Kim CH, Ahrens R, Fraser PE, St George-Hyslop P, Bussey TJ, Saksida LM, 2017. Longitudinal evaluation of Tau-P301L transgenic mice reveals no cognitive impairments at 17 months of age. Brain Behav 8(1), e00896–e00896. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Kitamura S, Shimada H, Niwa F, Endo H, Shinotoh H, Takahata K, Kubota M, Takado Y, Hirano S, Kimura Y, Zhang MR, Kuwabara S, Suhara T, Higuchi M, 2018. Tau-induced focal neurotoxicity and network disruption related to apathy in Alzheimer’s disease. J Neurol Neurosurg Psychiatry 89(11), 1208–1214. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Koen JD, Yonelinas AP, 2016. Recollection, not familiarity, decreases in healthy ageing: Converging evidence from four estimation methods. Memory 24(1), 75–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Kosel F, Pelley JMS, Franklin TB, 2020. Behavioural and psychological symptoms of dementia in mouse models of Alzheimer’s disease-related pathology. Neurosci Biobehav Rev 112, 634–647. [DOI] [PubMed] [Google Scholar]
  35. Kosel F, Torres Munoz P, Yang JR, Wong AA, Franklin TB, 2019. Age-related changes in social behaviours in the 5xFAD mouse model of Alzheimer’s disease. Behavioural Brain Research 362, 160–172. [DOI] [PubMed] [Google Scholar]
  36. Kraus-Schuman CA, Sanchez ML, Benson KM, Asghar-Ali AA, 2020. Psychotherapy and Cognitive Disorders. Psychotherapy in Later Life, 139. [Google Scholar]
  37. Kuznetsova A, Brockhoff PB, Christensen RHB, 2017. lmerTest Package: Tests in Linear Mixed Effects Models. Journal of Statistical Software 82(13), 1 – 26. [Google Scholar]
  38. Lanni C, Fagiani F, Racchi M, Preda S, Pascale A, Grilli M, Allegri N, Govoni S, 2019. Beta-amyloid short- and long-term synaptic entanglement. Pharmacol Res 139, 243–260. [DOI] [PubMed] [Google Scholar]
  39. Lenth RV, Buerkner P, Herve M, Love J, Miguez F, Riebl H, Singmann H, 2022. Package ‘emmeans’: Estimated Marginal Means, aka Least-Squares Means, 1.7.2 ed. The Comprehensive R Archive Network. [Google Scholar]
  40. Levy R, Dubois B, 2006. Apathy and the functional anatomy of the prefrontal cortex-basal ganglia circuits. Cereb Cortex 16(7), 916–928. [DOI] [PubMed] [Google Scholar]
  41. Li M, Long C, Yang L, 2015. Hippocampal-prefrontal circuit and disrupted functional connectivity in psychiatric and neurodegenerative disorders. Biomed Res Int 2015, 810548. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Lim JKH, Li Q-X, He Z, Vingrys AJ, Chinnery HR, Mullen J, Bui BV, Nguyen CTO, 2020. Retinal Functional and Structural Changes in the 5xFAD Mouse Model of Alzheimer’s Disease. Front Neurosci 14, 862–862. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Lison H, Happel MFK, Schneider F, Baldauf K, Kerbstat S, Seelbinder B, Schneeberg J, Zappe M, Goldschmidt J, Budinger E, Schröder UH, Ohl FW, Schilling S, Demuth HU, Scheich H, Reymann KG, Rönicke R, 2014. Disrupted cross-laminar cortical processing in β amyloid pathology precedes cell death. Neurobiology of Disease 63, 62–73. [DOI] [PubMed] [Google Scholar]
  44. Locci A, Orellana H, Rodriguez G, Gottliebson M, McClarty B, Dominguez S, Keszycki R, Dong H, 2021. Comparison of memory, affective behavior, and neuropathology in APPNLGF knock-in mice to 5xFAD and APP/PS1 mice. Behavioural Brain Research 404, 113192. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Lü W, Duan J, Zhang W, Yang W, Yu W, 2021. Relationship between neuropsychiatric symptoms and cognitive functions in patients with cognitive impairment. Psychogeriatrics 21(5), 773–782. [DOI] [PubMed] [Google Scholar]
  46. Lyketsos CG, Carrillo MC, Ryan JM, Khachaturian AS, Trzepacz P, Amatniek J, Cedarbaum J, Brashear R, Miller DS, 2011. Neuropsychiatric symptoms in Alzheimer’s disease. Alzheimer’s & Dementia 7(5), 532–539. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Malpas CB, Sharmin S, Kalincik T, 2020. The histopathological staging of tau, but not amyloid, corresponds to antemortem cognitive status, dementia stage, functional abilities and neuropsychiatric symptoms. Int J Neurosci, 1–10. [DOI] [PubMed] [Google Scholar]
  48. Marshall GA, Donovan NJ, Lorius N, Gidicsin CM, Maye J, Pepin LC, Becker JA, Amariglio RE, Rentz DM, Sperling RA, Johnson KA, 2013. Apathy is associated with increased amyloid burden in mild cognitive impairment. J Neuropsychiatry Clin Neurosci 25(4), 302–307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Marshall GA, Gatchel JR, Donovan NJ, Muniz MC, Schultz AP, Becker JA, Chhatwal JP, Hanseeuw BJ, Papp KV, Amariglio RE, Rentz DM, Sperling RA, Johnson KA, 2019. Regional Tau Correlates of Instrumental Activities of Daily Living and Apathy in Mild Cognitive Impairment and Alzheimer’s Disease Dementia. J Alzheimers Dis 67(2), 757–768. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, 2011. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging‐Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia 7(3), 263–269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Mori T, Shimada H, Shinotoh H, Hirano S, Eguchi Y, Yamada M, Fukuhara R, Tanimukai S, Zhang MR, Kuwabara S, Ueno S, Suhara T, 2014. Apathy correlates with prefrontal amyloid beta deposition in Alzheimer’s disease. J Neurol Neurosurg Psychiatry 85(4), 449–455. [DOI] [PubMed] [Google Scholar]
  52. Neuner SM, Heuer SE, Huentelman MJ, O’Connell KMS, Kaczorowski CC, 2019. Harnessing Genetic Complexity to Enhance Translatability of Alzheimer’s Disease Mouse Models: A Path toward Precision Medicine. Neuron 101(3), 399–411.e395. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Nichols JN, Deshane AS, Niedzielko TL, Smith CD, Floyd CL, 2016. Greater neurobehavioral deficits occur in adult mice after repeated, as compared to single, mild traumatic brain injury (mTBI). Behavioural Brain Research 298, 111–124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Nirmalraj PN, List J, Battacharya S, Howe G, Xu L, Thompson D, Mayer M, 2020. Complete aggregation pathway of amyloid beta (1–40) and (1–42) resolved on an atomically clean interface. Sci Adv 6(15), eaaz6014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Nobis L, Husain M, 2018. Apathy in Alzheimer’s disease. Curr Opin Behav Sci 22, 7–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. O’Leary TP, Brown RE, 2022. Visuo-spatial learning and memory impairments in the 5xFAD mouse model of Alzheimer’s disease: Effects of age, sex, albinism, and motor impairments. Genes Brain Behav, e12794. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. O’Leary TP, Mantolino HM, Stover KR, Brown RE, 2020. Age-related deterioration of motor function in male and female 5xFAD mice from 3 to 16 months of age. Genes Brain Behav 19(3), e12538. [DOI] [PubMed] [Google Scholar]
  58. O’Leary TP, Stover KR, Mantolino HM, Darvesh S, Brown RE, 2020. Intact olfactory memory in the 5xFAD mouse model of Alzheimer’s disease from 3 to 15 months of age. Behavioural Brain Research 393, 112731. [DOI] [PubMed] [Google Scholar]
  59. Oakley H, Cole SL, Logan S, Maus E, Shao P, Craft J, Guillozet-Bongaarts A, Ohno M, Disterhoft J, Van Eldik L, Berry R, Vassar R, 2006. Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J Neurosci 26(40), 10129–10140. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Pink A, Krell‐Roesch J, Syrjanen JA, Christenson LR, Lowe VJ, Vemuri P, Fields JA, Stokin GB, Kremers WK, Scharf EL, 2023. Interactions Between Neuropsychiatric Symptoms and Alzheimer’s Disease Neuroimaging Biomarkers in Predicting Longitudinal Cognitive Decline. Psychiatric Research and Clinical Practice. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Porsteinsson AP, Drye LT, Pollock BG, Devanand DP, Frangakis C, Ismail Z, Marano C, Meinert CL, Mintzer JE, Munro CA, Pelton G, Rabins PV, Rosenberg PB, Schneider LS, Shade DM, Weintraub D, Yesavage J, Lyketsos CG, 2014. Effect of Citalopram on Agitation in Alzheimer Disease: The CitAD Randomized Clinical Trial. JAMA 311(7), 682–691. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Preda S, Govoni S, Lanni C, Racchi M, Mura E, Grilli M, Marchi M, 2008. Acute beta-amyloid administration disrupts the cholinergic control of dopamine release in the nucleus accumbens. Neuropsychopharmacology 33(5), 1062–1070. [DOI] [PubMed] [Google Scholar]
  63. Radue R, Walaszek A, Asthana S, 2019. Neuropsychiatric symptoms in dementia. Handb Clin Neurol 167, 437–454. [DOI] [PubMed] [Google Scholar]
  64. Robert PH, Mulin E, Malléa P, David R, 2010. REVIEW: Apathy diagnosis, assessment, and treatment in Alzheimer’s disease. CNS Neurosci Ther 16(5), 263–271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Ruggiero RN, Rossignoli MT, Marques DB, de Sousa BM, Romcy-Pereira RN, Lopes-Aguiar C, Leite JP, 2021. Neuromodulation of Hippocampal-Prefrontal Cortical Synaptic Plasticity and Functional Connectivity: Implications for Neuropsychiatric Disorders. Front Cell Neurosci 15, 732360–732360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Sadleir KR, Eimer WA, Cole SL, Vassar R, 2015. Abeta reduction in BACE1 heterozygous null 5XFAD mice is associated with transgenic APP level. Mol Neurodegener 10, 1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Schneider F, Baldauf K, Wetzel W, Reymann KG, 2014. Behavioral and EEG changes in male 5xFAD mice. Physiology & Behavior 135, 25–33. [DOI] [PubMed] [Google Scholar]
  68. Seitz DP, Brisbin S, Herrmann N, Rapoport MJ, Wilson K, Gill SS, Rines J, Le Clair K, Conn D, 2012. Efficacy and feasibility of nonpharmacological interventions for neuropsychiatric symptoms of dementia in long term care: a systematic review. J Am Med Dir Assoc 13(6), 503–506.e502. [DOI] [PubMed] [Google Scholar]
  69. Sgourakis NG, Yan Y, McCallum SA, Wang C, Garcia AE, 2007. The Alzheimer’s peptides Abeta40 and 42 adopt distinct conformations in water: a combined MD / NMR study. J Mol Biol 368(5), 1448–1457. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Shankar GM, Bloodgood BL, Townsend M, Walsh DM, Selkoe DJ, Sabatini BL, 2007. Natural oligomers of the Alzheimer amyloid-beta protein induce reversible synapse loss by modulating an NMDA-type glutamate receptor-dependent signaling pathway. J Neurosci 27(11), 2866–2875. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Shankar GM, Li S, Mehta TH, Garcia-Munoz A, Shepardson NE, Smith I, Brett FM, Farrell MA, Rowan MJ, Lemere CA, Regan CM, Walsh DM, Sabatini BL, Selkoe DJ, 2008. Amyloid-beta protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory. Nat Med 14(8), 837–842. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Si Y, Guo C, Xiao F, Mei B, Meng B, 2022. Noncognitive species-typical and home-cage behavioral alterations in conditional presenilin 1/presenilin 2 double knockout mice. Behavioural Brain Research 418, 113652. [DOI] [PubMed] [Google Scholar]
  73. Skogseth R, Mulugeta E, Jones E, Ballard C, Rongve A, Nore S, Alves G, Aarsland D, 2008. Neuropsychiatric correlates of cerebrospinal fluid biomarkers in Alzheimer’s disease. Dement Geriatr Cogn Disord 25(6), 559–563. [DOI] [PubMed] [Google Scholar]
  74. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, Iwatsubo T, Jack CR Jr., Kaye J, Montine TJ, Park DC, Reiman EM, Rowe CC, Siemers E, Stern Y, Yaffe K, Carrillo MC, Thies B, Morrison-Bogorad M, Wagster MV, Phelps CH, 2011. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7(3), 280–292. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Strekalova T, Spanagel R, Bartsch D, Henn FA, Gass P, 2004. Stress-induced anhedonia in mice is associated with deficits in forced swimming and exploration. Neuropsychopharmacology 29(11), 2007–2017. [DOI] [PubMed] [Google Scholar]
  76. Tao Y, Peters ME, Drye LT, Devanand DP, Mintzer JE, Pollock BG, Porsteinsson AP, Rosenberg PB, Schneider LS, Shade DM, Weintraub D, Yesavage J, Lyketsos CG, Munro CA, 2018. Sex Differences in the Neuropsychiatric Symptoms of Patients With Alzheimer’s Disease. Am J Alzheimers Dis Other Demen 33(7), 450–457. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Thal DR, Rüb U, Orantes M, Braak H, 2002. Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology 58(12), 1791–1800. [DOI] [PubMed] [Google Scholar]
  78. Vik-Mo AO, Giil LM, Ballard C, Aarsland D, 2018. Course of neuropsychiatric symptoms in dementia: 5-year longitudinal study. Int J Geriatr Psychiatry 33(10), 1361–1369. [DOI] [PubMed] [Google Scholar]
  79. Vorhees CV, Williams MT, 2006. Morris water maze: procedures for assessing spatial and related forms of learning and memory. Nature protocols 1(2), 848–858. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Wiels WA, Wittens MMJ, Zeeuws D, Baeken C, Engelborghs S, 2021. Neuropsychiatric Symptoms in Mild Cognitive Impairment and Dementia Due to AD: Relation With Disease Stage and Cognitive Deficits. Front Psychiatry 12, 707580–707580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Wingo TS, Liu Y, Gerasimov ES, Vattathil SM, Wynne ME, Liu J, Lori A, Faundez V, Bennett DA, Seyfried NT, Levey AI, Wingo AP, 2022. Shared mechanisms across the major psychiatric and neurodegenerative diseases. Nat Commun 13(1), 4314. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Wolinsky D, Drake K, Bostwick J, 2018. Diagnosis and Management of Neuropsychiatric Symptoms in Alzheimer’s Disease. Curr Psychiatry Rep 20(12), 117. [DOI] [PubMed] [Google Scholar]
  83. Xiao N-A, Zhang J, Zhou M, Wei Z, Wu X-L, Dai X-M, Zhu Y-G, Chen X-C, 2015. Reduction of Glucose Metabolism in Olfactory Bulb is an Earlier Alzheimer’s Disease-related Biomarker in 5XFAD Mice. Chinese medical journal 128(16), 2220–2227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Xing Y, Wei C, Chu C, Zhou A, Li F, Wu L, Song H, Zuo X, Wang F, Qin W, Li D, Tang Y, Jia XF, Jia J, 2012. Stage-specific gender differences in cognitive and neuropsychiatric manifestations of vascular dementia. Am J Alzheimers Dis Other Demen 27(6), 433–438. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Zuidema SU, de Jonghe JF, Verhey FR, Koopmans RT, 2009. Predictors of neuropsychiatric symptoms in nursing home patients: influence of gender and dementia severity. Int J Geriatr Psychiatry 24(10), 1079–1086. [DOI] [PubMed] [Google Scholar]

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