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Characterization of cerebrovascular changes in Alzheimer’s disease mice by photoacoustic imaging

Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya 572025, P. R. China

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Zhongyang Zhang

Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya 572025, P. R. China

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Hua Shi

Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya 572025, P. R. China

E-mail Address: huashi@hainanu.edu.cn

Corresponding author.

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, and

Feifan Zhou

https://orcid.org/0000-0001-8213-507X

Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya 572025, P. R. China

E-mail Address: zhouff@hainanu.edu.cn

Corresponding author.

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https://doi.org/10.1142/S179354582450007XCited by:0 (Source: Crossref)

Abstract

The cerebral vasculature plays a significant role in the development of Alzheimer’s disease (AD), however, the specific association between them remains unclear. In this paper, based on the benefits of photoacoustic imaging (PAI), including label-free, high-resolution, in vivo imaging of vessels, we investigated the structural changes of cerebral vascular in wild-type (WT) mice and AD mice at different ages, analyzed the characteristics of the vascular in different brain regions, and correlated vascular characteristics with cognitive behaviors. The results showed that vascular density and vascular branching index in the cortical and frontal regions of both WT and AD mice decreased with age. Meanwhile, vascular lacunarity increased with age, and the changes in vascular structure were more pronounced in AD mice. The trend of vascular dysfunction aligns with the worsening cognitive dysfunction as the disease progresses. Here, we utilized in vivo PAI to analyze the changes in vascular structure during the progression of AD, elucidating the spatial and temporal correlation with cognitive impairment, which will provide more intuitive data for the study of the correlation between cerebrovascular and the development of AD.

Keywords:

1. Introduction

Alzheimer’s disease (AD) is the most common type of dementia, a neurodegenerative disease, with patients experiencing progressive impairment of thinking, memory, judgment, and independence, which in turn affects the quality of life and even leads to death.¹ The World Alzheimer’s Disease 2018 Report indicated a global count of no less than 50 million dementia patients, projected to escalate to 152 million by 2050, with about 60–70% of them suffering from AD.² As there is currently no treatment to stop, slow, or reverse the disease process, AD and related dementia diseases have become the seventh leading cause of death worldwide. The average clinical duration of AD is 8–10 years,³ and there are currently about 9.83 million people with AD in China,⁴ imposing a heavy medical, caregiving, and economic burden on families and society. Therefore, strengthening the prevention, diagnosis, and treatment of AD, and reducing the burden on society and families are urgent public health problems.

The underlying causes of AD remain unclear, and the traditional amyloid hypothesis has been overturned. Epidemiological statistics have shown that cardiovascular disease is an important factor in AD development. Vascular risk factors such as diabetes mellitus, hypertension, and vascular aging are positively associated with the onset of AD.^5,6 However, the causal effect of these vascular risk factors on the onset of AD is still unknown. Zhang et al.⁷ reported the first high-precision mapping of the entire cerebral vascular network in AD mice (male APP/PS1 transgenic mice) using micro-optical sectioning tomography (MOST). By quantitative analysis of cerebrovascular network in AD and wild-type (WT) mice, they found that the vascular system of the hippocampal region of the brain was significantly impaired in the AD model mice. Jullienne et al.⁸ conducted 18F-deoxyglucose positron emission tomography (PET) scans on AD mice (5xFAD transgenic mice) at various ages and discovered significant impairment in the vascular system of the hippocampal region with age, accompanied by the increase in vessel length, vessel density, and connection density on the cortical surface. These studies indicate that the significance of vascular injury in the pathological process of AD has not been fully recognized.

Photoacoustic imaging (PAI) is a noninvasive in vivo imaging technique that has rapidly developed in recent years.^9,10,11,12 It utilizes endogenous or exogenous molecules within the organism to induce thermoelastic expansion in various tissues in response to light absorption at different wavelengths. This process transforms the light absorption information of tissues into ultrasound signals through vibration and ultimately constructs images using algorithms.^13,14,15,16 Utilizing the photoacoustic effect produced by the light absorption of endogenous hemoglobin at 532nm, in vivo label-free vascular imaging can be achieved for the study of vascular-related diseases, allowing for high-resolution visualization of vascular structure and hemodynamics, presenting anatomical features (such as blood vessels and melanin) and physiological features (such as hemoglobin concentration and blood flow rat).^17,18 Guo et al.¹⁹ developed an ultra-wide field of view arch scanning photoacoustic microscopy (AS-PAM) to analyze the vascular characteristics of the meninges and cortices of early AD mice (male APP/PS1 transgenic mice). They found that the cerebrovascular curvature and branching index were highly sensitive to the pathological progression of AD.¹⁹ In recent years, there has been significant progress in PAI technology for the study of brain diseases, with the application of high-resolution photoacoustic microscopy and wide-field photoacoustic microscopy.

In this study, we utilized in vivo PAI to explore the pathological progression of cerebrovascular in AD mice (5xFAD transgenic mice). By comparing vascular changes in 5xFAD and WT mice at various ages, as well as analyzing the spatial relationship of vascular progression with age in different brain regions, we correlated characteristics of vascular changes with the behavioral of the mice to elucidate the relationship between vascular structural changes and cognitive impairment during AD progression.

2. Materials and Methods

2.1. Mouse strains and breeding

Female C57BL/6J WT mic and B6. Cg-Tg (Appswfllon, PSEN1 * M146L * L286V) 6799Vas/Mmjax (5xFAD, JAX008730) mice were purchased from Cavensbiagle (Suzhou) Model Animal Research Co., Ltd. (Suzhou, China). Mice were fed in free-standing ventilated cages with a 12h light/12h dark cycle (07:00–19:00). All animal experiments were approved by the Experimental Animal Management and Use Committee of Hainan University.

2.2. Novel object location

The novel object location (NOL) experiment has three stages: habituation, training, and testing. The mice were acclimatized to the open field (40cm L×W×H) for 10 min about 24 h before training. During this time, the VisuTrack Systems software (Shanghai Xin Ruan Soft Information Technology Co., Ltd.) was used to calculate the total distance (mm) traveled and the proportion of duration spent in the central area. Throughout the training, the mice were placed in the open field with two identical objects (3cm L×3cm W×5cm H) in opposite corners. Mice had the liberty to roam around for 10min. The object position memory test was conducted about 24h after training using the same procedure, during which one of the objects was relocated to a new position for the test. When the mice came into contact with any of the objects, their exploration of the objects was recorded. The mice were analyzed by recognition index ( $RI = T_{novel} ∕ (T_{novel} + T_{familiar}) \times 100$ %) and discrimination index ( $DI = (T_{novel} - T_{familiar}) ∕ (T_{novel} + T_{familiar})$ ) to characterize their object location memory ability, where $T_{novel}$ and $T_{familiar}$ represent the time of the mice spent in contact with the moved object (new location) and the unmoved object (old location), respectively.

2.3. Photoacoustic imaging

As shown in Fig. 1, in the PAI system (PASONO ANI, Guangdong Photoacoustic Technology Co., Ltd.), the light source is a 532nm laser, with a pulse width of 10ns, and a repetition rate of 10kHz (DTL-314QT, Russia). The laser is output by coupling with a single-mode fiber through an aperture and a fiber coupler (PAF2-7A, Thorlabs, USA), collimated by a fiber collimator (F240FC-532, Thorlabs, USA), and focused to the sample by a $4 \times$ objective lens (GCO-2111, Daheng Optics, China). Optical signal generated in the sample can be detected by a self-focusing transducer (center frequency: 30MHz; $- 6$ dB bandwidth: 80%; the focal length: 8mm; the outer diameter: 8mm; the diameter of the central hole: 3mm. piezoelectric material: polyvinylidene fluoride; silent lens) and converted to photoacoustic signals, which can be amplified by a 50 dB amplifier (LNA-650, RF Bay, USA) and converted to a digital signals by a high-speed data acquisition card (200 MS/s, m4i.4480-x8, Spectrum, Germany). Each laser pulse generates an A-line signal in the imaging depth direction. The continuous A-line signal obtained by two-dimensional transverse scanning constitutes a B-scan image (Fig. 1(b)). The software PAM2.0 (Guangdong Photoacoustic Technology Co., Ltd.) based on C++ and Qt is used to store and reconstruct the collected B-scan image data in real time. AngioTool64 0.6a (https://ccrod.cancer.gov/confluence/display/ROB2/Home) was used to quantitatively analyze the angiogenesis of the obtained photoacoustic images, and to evaluate various vascular morphology and spatial parameters, including vascular length and density, branching index, and lacunarity.²⁰

2.4. Statistical analyses

The data is presented as mean±SEM (Standard Error of the Mean). The analysis of complex comparisons was conducted through a two-way ANOVA complemented by Šídák’s subsequent test. Every level of significance was set at * $p < 0.05$ , ** $p < 0.01$ , and # $p < 0.05$ . Every piece of data underwent analysis through GraphPad Prism 9.3 for graphing.

3. Results

3.1. Motor ability and cognitive memory of mice at different age

To examine the changes in mobility and cognitive behavior of WT and 5xFAD mice with age, the open field test (OFT) was used to assess locomotor activity, exploratory behavior, and anxiety in novel environments,²¹ and the NOL test was used to assess cognitive memory levels.²² The trajectories of the mice in the OFT are depicted in Fig. 2(a), where WT and 5xFAD mice aged 3 months exhibited robust activity, but no notable disparity was observed between WT and 5xFAD mice of identical age. Total distance traveled analyses revealed no significant difference between WT and 5xFAD mice (Fig. 2(b)). Analysis of retention time in the central region revealed no notable disparity between WT and 5xFAD mice (Fig. 2(c)). The results of the OFT revealed no significant difference in locomotor ability and anxiety towards the novel environment between 5xFAD and WT mice of the same age.

Fig. 2. Motor ability and cognitive memory of 5xFAD mice. (a) The representative trajectory of mice in the OFT; (b) The total distance of mice movement; (c) The percentage of time spent in the center of the mice; (d) Representative trajectories of mice in the NOL test; (e) The location recognition index of the NOL test; (f) The discrimination index of the NOL test. For all panels, data were expressed as mean±SEM. * $p < 0.05$ , ** $p < 0.01$ . The number of mice in each group was as follows: 3-month-old WT: $N = 8$ ; 3-month-old AD: $N = 10$ ; 6-month-old WT: $N = 9$ ; 6-month-old AD: $N = 9$ ; 9-month-old WT: $N = 8$ ; 9-month-old AD: $N = 8$ ; 12-month-old WT: $N = 8$ ; 12-month-old AD: $N = 8$ .

Figure 2(d) illustrates the exploration trajectory of the mice in the NOL test. As depicted in Figs. 2(e)–2(f), there was no disparity in location recognition index and discrimination index between 3-month-old 5xFAD mice and WT mice, suggesting that there was no cognitive memory impairment in 3-month-old 5xFAD mice. However, the location recognition index and discrimination index of 5xFAD mice at the ages of 6, 9, and 12 months were markedly less compared to WT mice of identical age. Additionally, the location recognition index and discrimination index of 5xFAD mice decreased with age, indicating that cognitive impairments began to appear in 6-month-old 5xFAD mice and became more severe with age.

3.2. Cerebrovascular changes in mice of different age

Starting from 6 months of age, the spatial cognitive ability of 5xFAD mice was altered, but it was unclear whether their cerebral vasculature changed. Therefore, to further observe the patterns of changes in neurovascular characteristics in AD mice at different stages, photoacoustic microimaging was performed to analyze structural of cerebrovascular.

Figure 3(a) depicts whole-brain meningeal and cortical neurovascular PA images of WT mice and 5xFAD mice at the ages of 3, 6, 9, and 12 months, illustrating distinct vascular networks. Vascular parameters, such as cerebral vascular density, cerebral vascular branching index, and vascular lacunarity, were quantitatively analyzed using AngioTool64 0.6a.²⁰ As shown in Fig. 3(b), the cerebrovascular density of both WT mice and 5xFAD mice decreased with age, but there was no significant difference between WT mice and 5xFAD mice of the same age. The branching index is a parameter marker of neovascularization. Figure 3(c) illustrates a decline in the cerebrovascular branching index with age in both WT and 5xFAD mice, especially, 5xFAD mice exhibit a lower branching index than WT mice of the same age. Vascular lacunarity showed the opposite trend, increasing with age in both 5xFAD and WT mice, and to a greater extent in 5xFAD mice, suggesting that the vascular network of 5xFAD mice is less homogeneous and more porous (Fig. 3(d)). By comparing the changes in vascular parameters in mice of different ages, the results showed that vascular density was significantly reduced in 12-month-old mice compared to that in 3-month-old mice in 5xFAD mice (Fig. 3(e)), however, the reduction in 12-month-old WT mice was not significant. In both 5xFAD and WT mice, the vascular branching index decreased (Fig. 3(f)), and vascular lacunarity increased (Fig. 3(g)) in 12-month-old mice compared to that in 3-month-old mice, but the differences were not statistically significant.

Fig. 3. Changes of cerebrovascular structure in 5xFAD mice. (a) Representative PA images of the cerebral cortex of WT mice and 5xFAD mice, scale: 1mm; Quantitative analysis of vascular density (b), (e), vascular branching index (c), (f), and vascular lacunarity (d), (g) in WT mice and 5xFAD mice. For all panels, the data were expressed as mean±SEM. * $p < 0.05$ , ** $p < 0.01$ . $N = 4$ mice per group.

3.3. Cerebral vascular changes in the parietal cortex of mice at different ages

Despite the characteristic changes in the whole brain meningeal and cortical neurovascular networks in 5xFAD mice of different ages that have been understood, it is still unclear how the neurovascularization of important brain regions related to AD pathological changes. More and more evidence shows that A $β$ is initially accumulated in the medial frontal cortex and medial parietal cortex,²³ both of which are crucial components of the default-mode network,²⁴ essential for brain cognitive function and memory. Clinically, the typical feature of early AD is memory deficits caused by neurodegenerative lesions in the medial temporal lobe. As the disease progresses, it gradually spreads to the frontal and parietal cortex, and finally to most of the cortex.²⁵ Based on whole-brain cortical photoacoustic images, the vascular changes in two significant brain regions, the parietal and frontal cortex, were further analyzed.

The two circled areas depicted in Fig. 4(a) represent the parietal regions of the brain. Additionally, the figure includes vascular PA images of the meninges and cortex in the parietal regions of mice at different ages. Quantitative analysis of the vascular parameters showed that the vascular density (Fig. 4(b)), vascular branching index (Fig. 4(c)), and vascular lacunarity (Fig. 4(e)) in the parietal region of 5xFAD mice and WT mice remained relatively constant with age. When comparing the changes in vascular parameters in the parietal region of mice of different ages, no differences were observed in vascular density (Fig. 4(e)), vascular branching index (Fig. 4(f)), and vascular lacunarity (Fig. 4(g)) between the age groups. These results suggest that the vascular network structure in the parietal region remained unchanged during the pathological progression of AD.

3.4. Cerebral vascular changes in the frontal cortex of mice at different ages

The frontal lobes play a crucial role in integrating nontask-related long-term memory in the brain. Numerous studies have shown that the elderly in the preclinical stage of AD had changes in attention and executive function in the stage of subjective cognitive decline,^26,27 and the performance of attention and executive tasks is closely related to frontal function. At present, few studies have explored the relationship between the vascular structure of the frontal cortex and the pathological process of AD. Therefore, in this study, the cortical blood vessels in the frontal lobe of 5xFAD mice at different stages were analyzed.

The two circular regions depicted in Fig. 5(a) represent the frontal region of the brain, showing PA images of blood vessels in the frontal meninges and cortex of WT and 5xFAD mice of different ages. The analysis showed that the vascular density (Fig. 5(b)) and branching index (Fig. 5(c)) in the frontal region of WT mice and 5xFAD mice decreased with age. 5xFAD mice exhibited lower vascular density and branching index than WT mice of the same age, but there was no significant difference. In contrast, vascular lacunarity increased with age in both WT mice and 5xFAD mice, and to a greater extent in 5xFAD mice. These data suggest that the frontal lobe region of the 5xFAD mice had a more homogeneous vascular network with higher lacunarity (Fig. 5(d)). By comparing the changes in vascular parameters in mice of different ages, the results showed that vascular density was significantly reduced in 12-month-old mice compared to that in 3-month-old mice in 5xFAD mice (Fig. 5(e)). However, the reduction in 12-month-old WT mice was not significant. In both 5xFAD and WT mice, the vascular branching index decreased (Fig. 5(f)), and vascular lacunarity increased (Fig. 5(g)) in 12-month-old mice compared to that in 3-month-old mice, but the differences were not statistically significant. These results suggest that the vascular structure of the frontal cortex shows a progressive trend of damage with age, characterized by a reduction in the number of neovessels and a deterioration in the homogeneity of the vascular network. Furthermore, the trend of vascular changes appears to be more pronounced with age in AD mice.

4. Discussion

Cerebrovascular injury may play an important role in the development of AD, but the association between cerebrovascular and AD progression is still not clear. We conducted noninvasive, using in vivo PAI to analyze the characteristics of the vascular network in the cortical, parietal, and frontal regions of the entire brain in WT and AD mice at varying ages. The data revealed that vascular density and branching index decreased with age in both WT and AD mice in the cortical and frontal regions, while vascular lacunarity increased with age. The vascular changes in the cortical and frontal regions followed a similar trend in both WT and AD mice, but the vascular changes were more pronounced in AD mice with age. However, analysis of vascular characteristics in the parietal region showed no significant changes in vascular density, vascular branching index, or vascular lacunarity with age. When comparing the behavioral and vascular characteristics of mice at 3 and 12 months, no significant changes were observed in the motor ability, cognitive function, and vascular structure of WT mice. However, 5xFAD mice showed a significant decrease in the total distance of movement and cognitive ability at 12 months, as well as a significant decrease in the vascular density of the whole cerebral cortex and the frontal lobe region. The results above indicate that as individuals age, the vasculature in the frontal lobe area gradually experiences a decrease in the number of neovessels and a deterioration in the homogeneity of the vascular network. When AD showed cognitive pathological damage (6 months of age), the trend of vascular damage was more pronounced compared to WT, but there was no significant difference. When the AD pathological process has progressed to a certain point (12 months of age), mice exhibit significantly reduced motor and cognitive abilities, as well as more severe vascular damage in the cerebral cortex and frontal regions.

Studies have assessed the brain volume changes in 5xFAD mice.²⁸ Girard et al. found that there was no volume variance in total forebrain, cerebral cortex, or frontal cortex between WT and 5xFAD mice at ages of 2, 4, and 6 months by magnetic resonance imaging (MRI) analysis.^29,30 In this study, we analyzed the blood vessels on the cortical surface of WT and 5xFAD mice at 3, 6, 9, and 12 months of age. There was no significant difference in vascular parameters between WT and 5xFAD mice. However, when working memory impairment began to occur in 6-month-old 5xFAD mice, the vascular density and vascular branching index showed a downward trend compared with WT mice. To date, most clinical and preclinical studies have reported no change or a slight decrease in vascular density in the presence of AD pathology.³¹ Regarding the effect of aging on vascular density, many studies have shown that vascular density decreases with age in humans^32,33 and rodents,^34,35 which is consistent with our results that vascular density decreases with age in WT and 5xFAD mice. However, there are also some reports of increased vascular density in clinical studies of AD patients^36,37,38 and AD mouse models.^39,40 For these different reports, Fisher et al.³¹ pointed out that different data on vascular density in the AD model may be related to different analysis methods, evaluation indicators, age, gender, and regions of interest.

At present, few studies have used sub-regional fractals to evaluate the complexity of cerebrovascular in AD models. Two studies using in vitro glucose transporter 1 (GLUT1) immunostaining showed that the number of blood vessels in the cerebral cortex and hippocampus of 9-month-old 5xFAD female mice was reduced compared with WT,⁴¹ and the cortical capillary length of 8-month-old 5xFAD female mice was reduced.⁴² We used PAI in vivo vascular imaging to analyze the vascular network characteristics of the whole brain, parietal lobe, and frontal cortex of female WT mice and 5xFAD mice. The results showed that from 6 months, 5xFAD females had increased vascular network complexity in the whole brain and frontal lobe compared with WT. Although more studies are needed to determine the regulation of vascular complexity in different regions of AD progression, regional fractal analysis of cerebrovascular based on noninvasive PAI angiography may help to evaluate vascular dysfunction, and even regional fractal analysis can be used to evaluate AD progression.

The frontal cortex is an important brain region related to executive function⁴³ and working memory.⁴⁴ Studies have shown that executive function is one of the earliest cognitive functions affected by AD patients. Gordon et al.⁴⁵ found that the pathological changes of high levels of tau and phosphorylated tau were significantly correlated with the excessive activation of the brain’s attention control area, indicating that the increased pathological level of the AD brain would lead to early changes in attention and executive control. Therefore, the decrease of attention and executive function in the stage of subjective cognitive decline may be caused by the early pathophysiological changes of the frontal lobe of the brain before the atrophy of the hippocampus.⁴⁶ Research found that damage to the frontal cortex is enough to cause cognitive memory impairments in 5xFAD mice aged 6 months.^29,47 In this study, significant cognitive memory deficits began to appear in 6-month-old transgenic mice. By analyzing the vascular structure characteristics of different brain regions, it was found that the vascular structure of the frontal cortex also changed from 6 months old, and the damage trend was consistent with the cognitive memory decline trend of AD mice, which fully demonstrated the relationship between the vascular structure changes of the frontal cortex and the progression of AD. However, the causal relationship between the changes in the vascular structure of the frontal cortex and the progression of AD needs further study.

5. Conclusions

In this study, the cognitive function of mice at different ages was evaluated by behavior. At the same time, the cortical vascular structure of the whole brain and different brain regions was analyzed by PAI. The spatial relationship of cerebral cortical blood vessels with age was deeply explored, and its behavioral characteristics were associated, to clarify the spatial and temporal correlation between vascular structure changes and cognitive impairment. However, this study only assessed the vasculature on the cortical surface, and the analysis of deeper structures and the association of pathological processes is still lacking. In the future study, we will further explore the characteristics of vascular networks in deeper brain regions and the mechanisms of vascular metabolism in the brain to understand vascular dysfunction in AD.

Acknowledgments

This work was supported by STI2030-Major Projects 2022ZD0212200, Hainan Province Key Area R&D Program (KJRC2023C30, ZDYF2021SHFZ094), and Project of Collaborative Innovation Center of One Health (XTCX2022JKB02). In this work, F. Zhou conceived and designed the experiments. Z. Zhang and X. Li performed the experiments and analyzed the data. X. Li, H. Shi, and F. Zhou wrote the paper. All the authors read and approved the paper. Xi Li and Zhongyang Zhang contributed equally to this work.

Conflicts of Interest

The authors declare no conflict of interest.

ORCID

Feifan Zhou https://orcid.org/0000-0001-8213-507X

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Vol. 17, No. 06

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Received 3 January 2024

Accepted 2 April 2024

Published: 4 May 2024

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