Acute liver damage generates age independent microglia morphology changes in mice

Abstract

Non-alcoholic fatty liver disease (NAFLD) has emerged as a silent global epidemic, frequently contributing to systemic inflammation. As the primary immune cells of the central nervous system (CNS), microglia undergo morphological changes that serve as critical indicators of CNS health. In this study, we aimed to quantify alterations in microglial morphology within the cortex of young and aged mice with liver damage. Our results demonstrated that hepatic dysfunction leads to a significant increase in total branch length in both young (285.79±68.23 μm) and aged animals (268.67±69.06 μm), compared to their respective controls (164.07±33.05 μm and 140.96±27.18 μm) (p<0.0001). Additionally, aged animals with liver damage exhibited a mean branch length of 5.84±0.66 μm, higher than 2.63±0.19 μm observed in those without liver injury. The number of primary branches in aged mice with liver damage decreased from 6.6±1.2 branches to 3.1±1.5 (p<0.0001). In addition, we have shown a decrease in the number of secondary branches in aged animals with liver damage. This suggests that microglia not only respond to CNS-specific injuries but also to chronic systemic pathologies like NAFLD. These findings highlight the importance of better understanding the liver–brain axis in order to better understand the neuroimmune consequences of systemic diseases.

Introduction

Microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in preserving homeostasis by reacting to any change in the brain parenchyma [1, 2, 3]. This function is supported by a continuous stretching and retraction of their processes, making microglia morphology one of the most dynamic cellular structures in the human body [4].

Besides their physiological role in synaptic pruning [5, 6], microglia are known to actively scan their environment [7, 8, 9]. The microglia reaction to acute events is well documented in both focal ischemia [10, 11, 12] and global hypoxia [13], where significant alterations can occur within just a few minutes up to 10 days, with a progressive reversal of their morphology [14, 15]. Furthermore, dozens of reports have identified microglia as the local source of inflammatory mediators in chronic neurodegenerative diseases [16, 17, 18, 19]. This inherent dynamic not only underlines their role in maintaining local microenvironment under physiological conditions, but also in pathologies that directly affect the nervous system, with recent investigations detecting changes in microglia population in chronic pathologies that do not directly affect the brain, such as chronic liver damage [20, 21, 22].

Given the indiscriminatory response of microglia to the local imbalance in homeostasis, this is far from surprising, as the accumulation of cytotoxic factors, such as proinflammatory systemic cytokines, can impact the brain [23]. With microglia reversing to a scanning phenotype being somewhat variable, the observation that systemic activation of microglia can occur, highlights the importance of microglial functions across lifespan and raises critical questions regarding their overarching impact not only on the healthy brain, but also the impact of other chronic systemic entities on the brain.

Aim

While understanding microglia morphology has proven to be an accurate tool in our understanding of their roles in CNS pathology, here we are attempting to objectify changes in microglia morphology in the cortex of wild type mice with chronic liver damage. This might prove crucial for developing therapeutic strategies aimed to modulate microglial activity in various systemic disorders, ultimately addressing the pressing need for novel interventions in contemporary research.

Materials and Methods

Experimental animals

The study was performed on young [16–18-weeks-old (n=6)] and aged [70–72-weeks-old (n=6)] male C57BL/6N mice, housed in individual ventilated cages under a 12-hour light/dark cycle and constant temperature (20°C). The mice were obtained from the Animal Facility of the University of Medicine and Pharmacy of Craiova, Romania. All experimental protocols and animal care were approved by the Committee for Experimental Animals Wellbeing of the University of Medicine and Pharmacy of Craiova (Approval No. 2.1 from 10.11.2022) and by the Sanitary, Veterinary and Food Safety Directorates (Approval No. 27/18.10.2024).

Non-alcoholic fatty liver disease/non-alcoholic steatohepatitis induction

The non-alcoholic fatty liver disease (NAFLD)/non-alcoholic steatohepatitis [24] was induced by replacing the normal food pellets with ones lacking methionine/choline (MCD) (MP Biomedicals, Germany). All animals consumed the MCD diet ad libitum for four weeks, while the controls received normal food pellets.

Abdominal ultrasonography

Hepatic ultrasound assessments were conducted using an S12-4 plane probe and a Philips CX50 Ultrasound Machine (Philips Healthcare, Netherlands). During the procedure, the animals were anesthetized via inhalation with a mixture of 1.5% Isoflurane, 49% oxygen (O2), and 49% nitrous oxide (N2O). The severity score was determined based on parenchymal echotexture, the presence of nodules, and the surface appearance of the liver border [21, 22]. The body weight of the mice was assessed weekly throughout the experiment.

Histopathology and Immunohistochemistry

Following anesthesia, the animals were subjected to intracardiac perfusion with 5 mL saline and 5 mL of 4% paraformaldehyde (PFA). The brains were kept overnight in 4% PFA at 4°C to reduce microglial activation [13]. All immunohistochemistry was conducted on 35 μm coronal slices obtained by vibratome cut in a 0.1 M phosphate-buffered saline (PBS) solution. Sections were briefly incubated with 0.5% Triton X-100 and 5% horse serum in PBS for one hour at room temperature, followed by an overnight incubation at 4°C with the primary antibodies: rabbit anti-ionized calcium-binding adaptor molecule 1 (Iba1) (Wako, 019-19741, 1:1000). Following washing, slices were incubated for two hours at ambient temperature, in darkness, with secondary antibodies: Alexa Fluor 647 donkey anti-rabbit (Invitrogen, A31573, 1:1000). The stained brain sections were mounted with Fluoromount-G containing 4’,6-Diamidino-2-phenylindole (DAPI) (ThermoScientific, 00-4959-52).

Image analysis

For analysis, Z-stack images of the cortex were captured using a 20× objective on a Zeiss LSM 900 Airyscan 2 confocal microscope and Zen 3.5 software. The cortical Iba1 area for each animal was quantified using Fiji and Image-Pro Plus software. Microglial morphology was quantified using a semi-manual method [25]. Briefly, using each full Z-stack, microglia with complete arborization were manually isolated (Figure 1A,1B). Microglia with processes that extend outside the stack limits were not included in the present study. For each animal, 10 cells were analyzed. After skeletization (Figure 1C, 1D), for each cell the total length of the branch tree, the number of branches, the mean branch length and the number of each branch order were used to assess age differences.

Figure 1.

Schematic overview of techniques: (A) Example of a microglial cell (highlighted within the white square) showing both the soma and fine processes; each cell analyzed in this study was isolated (B), manually traced (C), and subsequently verified (D). Scale bar: 20 μm

Data analysis

The average value for each parameter was entered into GraphPad Prism 10 and/or Microsoft Excel. The differences in means among the groups were evaluated using one- or two-way repetitive analysis of variance (ANOVA) (Tukey’s multiple comparisons test), with Greenhouse–Geisser correction applied. Prior to these analyses, the data set was tested for normality using the Shapiro–Wilk and Kolmogorov–Smirnov tests to ensure the appropriateness of parametric methods. For non-parametric data, the Kruskal–Wallis test was used (Dunn’s multiple comparisons test). For ANOVA test, sessions (weekly results) were used as a within-factor, and diets [normal (WT – wild type) and MCD diet] were considered as a between-factor. For the comparation between young and aged animals, age was used as a within-factor, and diets were considered as a between-factor. In all figures, the mean and standard deviation (SD) are displayed. Statistical significance is depicted as follows: *p<0.05, **p<0.01 and ****p<0.0001.

Results

The MCD diet induces liver injury and leads to a decrease in body weight

Four weeks after the MCD diet, ultrasonography confirmed liver damage in all animals that received the diet (Figure 2A). Regardless of age, the MCD animals developed both micro- and macro-nodules (Figure 2B), with no differences between the groups according to the liver severity scores (p>0.05; Figure 2A), as measured by the Kruskal–Wallis test.

Figure 2.

Assessment of liver damage: (A) US severity scores after four weeks of MCD diet showed no differences between groups; however, the average severity score for mice on the MCD diet was higher compared to those on a normal diet; (B) Example of hepatic US in mice displaying macronodules; (C) Weekly measurements indicated body mass loss in all MCD diet mice. The graphs show mean values ± SD, *p<0.05. MCD: Methionine- and choline-deficient; SD: Standard deviation; US: Ultrasonography; WT: Wild type (normal)

Two-way ANOVA used to assess the animals’ weight, revealed differences between sessions (F1.599,12.79=43.33, p<0.0001). Although no differences were observed in the utilized diets (F3,8=0.9636, p=0.4556), significant interaction was noticed between sessions and diets (F9,24=11.78, p<0.0001). Post-hoc test showed that after four weeks of diet, young MCD mice displayed a reduced weight (19.49±2.32 g), compared to young group without liver damage (27.77±2.10 g) (p=0.0347) (Figure 2C).

Reduced cortical Iba1+ signal indicates microglial inhibition in aged animals with liver damage

One-way ANOVA performed in order to assess the differences in the cortical Iba1+ signal revealed differences between diets (F3,8=4.885, p=0.0324). Aged animals submitted to MCD diet exhibited a decreased Iba1+ area (4183±413.7 μm2), compared to young mice without liver injury (12401±2730 μm2) (p=0.0267) (Figure 3A). Immunohistochemical detection of Iba1-positive microglia in the cortex of both young and aged animals, subjected to either the MCD or a normal diet, is shown in Figure 3B.

Figure 3.

Immunohistochemical analysis of Iba1-positive microglia in (A) cortex revealed a decreased Iba1+ signal in aged animals fed the MCD diet, compared to young mice on a normal diet; (B) Microglia were labeled with Iba1 (green), and cell nuclei were stained with DAPI (blue). The graph presents mean values ± SD, *p<0.05. Scale bar: 50 μm. DAPI: 4’,6-Diamidino-2-phenylindole; Iba1: Ionized calcium-binding adaptor molecule 1; MCD: Methionine- and choline-deficient; SD: Standard deviation; WT: Wild type (normal)

Basic microglia morphology reveals that acute liver damage generates less microglia branches in young mice

By manually tracking individual branches, we were able to evaluate basic morphological characteristics of microglia in young and aged animals fed MCD pellets for four weeks.

The presence of liver damage generated an increase in the total branch length in both young (285.79±68.23 μm) and aged animals (268.67±69.06 μm), compared to their controls (164.07±33.05 μm and 140.96±27.18 μm, respectively) (p<0.0001) (Figure 4A), with two-way ANOVA showing differences between diets (F1,36=55.27, p<0.0001), but not in age (F1,36=1.438, p=0.2382), or their interaction (F1,36=0.031, p=0.8591).

Figure 4.

Microglia arbor morphology: through the systematic tracking of each individual branch, we characterized detailed microglial morphology, beginning with fundamental parameters such as (A) total arbor length, (B) number of branches, and (C) mean branch length; furthermore, a morphological analysis allowed us to identify variations in the number of (D) primary, (E) secondary, (F) tertiary, (G) quaternary, and (H) terminal branches. The graphs show mean values ± SD, *p<0.05, **p<0.01 and ****p<0.0001. MCD: Methionine- and choline-deficient; SD: Standard deviation; WT: Wild type (normal).

Two-way ANOVA revealed differences between diets (F1,36=13.75, p=0.0007) when evaluating the number of branches, and no variances between age (F1,36=0.6665, p=0.4197) and interaction (F1,36=0.0566, p=0.8131). The young animals with liver damage showed less microglia branches (44.9±9.25), compared to WT mice fed normal diet (56.5±9.05) (p=0.0399) (Figure 4B).

When evaluating the mean branch length, both young and aged animals fed MCD pellets presented up to a three-fold increase. Two-way ANOVA revealed significant variances between diets (F1,36=384.4, p<0.0001) and age (F1,36=4.844, p=0.0342), with no differences between interaction (F1,36=0.3145, p=0.5784). The microglia of young MCD fed animals had a mean branch length of 6.3±0.66 μm, compared to 2.91±0.46 μm (p<0.001), while in aged ones the mean length was 5.84±0.66 μm compared to 2.63±0.19 μm in mice fed normal diet (p<0.001) (Figure 4C).

Detailed microglia morphology reveals that acute liver damage generates microglia arbor changes

When evaluating the number of each branch order, we were able to detect a decrease in the number of primary branches in aged animals fed MCD pellets to 3.1±1.5 from 6.6±1.2 branches in aged controls (p<0.0001) (Figure 4D), with two-way ANOVA showing differences between diets (F1,36=21.04, p<0.0001), and interaction (F1,36=8.295, p=0.0067), but not in age (F1,36=0.5575, p=0.4601).

The number of secondary branches were also decreased in MCD mice; however, this was observed for both young and aged animals (Figure 4E), with young animals having a decrease from 11±3.5 to 7.3±1.4 (p=0.0123), while aged ones decreased from 13.1±2.6 to 7.3±1.88 branches (p<0.001). Two-way ANOVA also revealed variances between diets (F1,36=35.15, p<0.0001), but no differences in both age and interaction factors (F1,36=1.717, p=0.1983).

When analyzing the number of tertiary branches, two-way ANOVA showed no differences (p>0.05) (Figure 4F).

While there was no difference between the MCD fed animals and controls when looking at the number of terminals (Figure 4H), the number of quaternary branches decreased for both age brackets when animals were fed MCD pellets from 13.1±3.2 to 7.8±2.8 (p=0.006) in young mice and from 10.7±4.5 to 5.6±2.3 branches in aged animals (p=0.008), with two-way ANOVA showing differences between diets (F1,36=23.92, p<0.0001), and age (F1,36=4.679, p=0.0372), but not in their interaction (F1,36=0.0088, p=0.9256) (Figure 4G).

Discussions

As the population is aging and medical treatments are improving, the likelihood of a person living with a chronic illness is also growing. While systemic inflammation can dramatically impact the homeostasis of the brain in some cases, such as in the case of septic encephalopathy [26, 27, 28], the long-term changes in the CNS secondary to systemic inflammation are still relatively unknown for both healthy and pathological aging [29, 30]. Recently, extensive investigations have highlighted the bidirectional communication between the liver and the brain, commonly referred to as the “liver–brain axis”. Liver damage, as observed in common conditions like NAFLD, often leads to systemic inflammation. Studies have shown that individuals with liver disease exhibit increased risks of anxiety and depression [31, 32], likely mediated by inflammatory processes that involve immune responses in the brain [20, 21], where microglia play a pivotal role. As researchers have started to investigate the neurological and psychiatric changes observed in individuals with liver damage, there seems to be a need for long-term monitoring of such patients as the precise long-term consequences remain uncertain.

Microglia are known to respond to injuries of the CNS and manage the local inflammatory responses [16, 25, 33, 34, 35]. With their morphology (branching complexity, process length, and cell body shape) varying significantly across lifespan [4], alterations in microglial morphology serve as indicators of the underlying physiological or pathological states of the CNS as their reaction is extremally fast [13]. After a stroke, microglia undergo significant changes that influence the progression of neuroinflammation and tissue repair [36], and microglial activation has been increasingly linked to the pathophysiology of depression [37]. The use of suitable murine models allows for a controlled investigation in response to stroke and post-stroke depression [38], enabling researchers to study the temporal progression of microglial activation and the associated neuroinflammatory pathways. Also, microglial morphology varies significantly depending on the specific anatomical region, exhibiting distinct characteristics in the cortex, hippocampus, and retina [39]. These regional morphological differences can play a crucial role in influencing the progression and outcomes of lesions [40].

In animal models of NAFLD, microglia display changes in their number compared to healthy controls [21]. Using the same model, we were able to show that in animal models of liver damage, microglia exhibit significant morphological changes, indicative of activation, regardless of age. While a major limitation of the present study is the failure to identify if the degree of microglial activation correlates with the severity of liver damage, we were able to show that microglia may serve as a crucial link between peripheral organ damage and CNS dysfunction. This is mainly due to the fact that microglia are constantly surveying their environment and responding to any disturbances [1, 2, 3]. Under physiological conditions, microglia maintain a highly ramified morphology, with long processes extending from the cell body to cover a large area [41, 42]. This morphology is associated with their role in surveillance and maintenance of CNS homeostasis. However, upon detecting injury or inflammation, microglia undergo rapid morphological changes, adopting an amoeboid shape with shortened processes and an enlarged cell body. This transformation facilitates their shift from a monitoring state to an immune active one, allowing them to clear debris, release cytokines, and modulate synaptic function [43, 44]. In the context of liver damage, systemic inflammation appears to be a key driver of microglial activation. Liver injury results in the release of proinflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), which can cross the blood–brain barrier (BBB) and activate microglia [45]. Studies in NAFLD animal models have demonstrated that microglial populations of the animals can be affected [21]. Here, we have shown that microglia of NAFLD animals present significant alterations in their morphology. This suggests that microglia not only respond to CNS-specific injuries but also to systemic pathologies like liver disease. This highlights the need to better understand microglial role in this context and, even more importantly, the long-term impact that such a prolonged activation can have on the function of the CNS. However, the exact relationship between the extent of liver damage and microglial activation remains to be fully elucidated. While the most likely hypothesis suggests that the proinflammatory environment created by liver damage may prime microglia to become more sensitive to stressors, it is possible that the liver damage may impair the integrity of the BBB, as such allowing peripheral inflammatory signals to more easily reach and activate microglia. While morphological analysis of microglia provides valuable insights into their activation state and, as such, their functional role, it is not without challenges. Microglial morphology is highly variable, even within the same region of the brain, and can be influenced by a variety of factors, including age [4, 46], sex [47, 48], and environmental conditions [49].

Given the growing recognition of the liver–brain axis, microglial analysis in liver disease could become an increasingly important tool for understanding the neuro-immune mechanisms underlying liver-related neuro-psychiatric disorders. Future research should focus on establishing standardized protocols for assessing microglial activation in the context of systemic diseases like NAFLD. Additionally, studies should consider the use of both sexes and multiple age groups to account for the variability introduced by these factors. Further investigations are needed to determine whether the observed changes in microglial morphology are directly responsible for the behavioral alterations seen in liver disease models or if they are secondary to other CNS changes. Cellular and molecular studies, including the examination of microglial gene expression and signaling pathways, will be crucial in elucidating the exact role of microglia in mediating the effects of liver damage on the brain.

Conclusions

Microglia serve as the brain’s primary immune cells, and their morphological changes are key indicators of CNS health. In the context of liver damage, we have proven that microglia become activated as seen by morphological alterations observed in all animals with NAFLD. The association between liver damage and microglial activation highlights the importance of better understanding the liver–brain axis. As research continues to uncover the mechanisms behind these interactions, microglial morphology analysis will remain a vital tool for exploring the neuroimmune consequences of systemic diseases.

Conflict of interests

The authors declare that they have no conflict of interests.