# Metabolic disorders exacerbate the formation of glial scar after stroke

Julien Clain, David Couret, Matthieu Bringart, Arnaud Lecadieu, Olivier

Meilhac, Christian Lefebvre d'Hellencourt, Nicolas Diotel

► To cite this version:

Julien Clain, David Couret, Matthieu Bringart, Arnaud Lecadieu, Olivier Meilhac, et al. Metabolic disorders exacerbate the formation of glial scar after stroke. European Journal of Neuroscience, 2024, 59 (11), pp.3009 - 3029. 10.1111/ejn.16325. hal-05482973

HAL Id: hal-05482973

https://hal.science/hal-05482973v1

Submitted on 29 Jan 2026

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
# Metabolic disorders exacerbate the formation of glial scar after stroke

Julien Clain<fnref n="1" />

David Couret<fnref n="1" />,<fnref n="2" />

Matthieu Bringart<fnref n="1" />

Arnaud Lecadieu<fnref n="1" />,<fnref n="2" />

Olivier Meilhac<fnref n="1" />,<fnref n="2" />

Christian Lefebvre d'Hellencourt<fnref n="1" />

Nicolas Diotel<fnref n="1" />

## Correspondence

Christian Lefebvre d'Hellencourt and Nicolas Diotel, Université de la Réunion, INSERM, UMR 1188 Diabète Athérothrombose Thérapies Réunion Océan Indien (DéTROI), 97410 Saint-Pierre, France.

Email: christian.lefebvre-d-hellencourt@univ-reunion.fr; nicolas.diotel@univ-reunion.fr

## Funding information

This study is funded by European Regional Development Funds (RE0022527) (ZEBRATOX [EU-Région Réunion-French State national counterpart]) and University of Reunion Island.

Edited by: Nathan Smith

## Abstract

Metabolic disorders are risk factors for stroke exacerbating subsequent complications. Rapidly after brain injury, a glial scar forms, preventing excessive inflammation and limiting axonal regeneration. Despite the growing interest in wound healing following brain injury, the formation of a glial scar in the context of metabolic disorders is poorly documented. In this study, we used db/db mice to investigate the impact of metabolic perturbations on brain repair mechanisms, with a focus on glial scarring. First, we confirmed the development of obesity, poor glucose regulation, hyperglycaemia and liver steatosis in these mice. Then, we observed that 3 days after a 30-min middle cerebral artery occlusion (MCAO), db/db mice had larger infarct area compared with their control counterparts. We next investigated reactive gliosis and glial scar formation in db/+ and db/db mice. We demonstrated that astrogliosis and microgliosis were exacerbated 3 days after stroke in db/db mice. Furthermore, we also showed that the synthesis of extracellular matrix (ECM) proteins (i.e., chondroitin sulphate proteoglycan, collagen IV and tenascin C) was increased in db/db mice. Consequently, we demonstrated for the first time that metabolic disorders impair reactive gliosis post-stroke and increase ECM deposition. Given that the damage size is known to influence glial scar, this study now raises the question of the direct impact of hyperglycaemia/obesity on reactive gliosis and glia scar. It paves the way to promote the development of new therapies targeting glial scar formation to improve functional recovery after stroke in the context of metabolic disorders.

**Abbreviations:** ACA, anterior cerebral artery; AUC, area under the curve; BBB, blood-brain barrier; BSA, bovine serum albumin; Casp 3, caspase 3; ColIV, collagen IV; CSPG, chondroitin sulphate proteoglycan; DAPI, 4',6'-diamidino-2-phenylindole; ECM, extracellular matrix; GFAP, glial fibrillary acidic protein; HFD, high-fat diet; hpl, hour post lesion; Iba1, ionized calcium-binding adapter molecule 1; IgG, immunoglobulin G; MAP 2, microtubule-associated protein 2; MCA, middle cerebral artery; MCAO, middle cerebral artery occlusion; OGTT, oral glucose tolerance test; Olig2, oligodendrocyte transcription factor 2; PBS, phosphate-buffered saline; PBT, PBS containing .2% Triton X-100; PFA, paraformaldehyde; pHH3, phosphohistone H3; rtPA, recombinant tissue plasminogen activator; Ten-C, tenascin C; VCH, volume of the contralateral hemisphere; VIH, volume of the ipsilateral hemisphere.

Christian Lefebvre d'Hellencourt and Nicolas Diotel equally contributed to this work.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

© 2024 The Authors. *European Journal of Neuroscience* published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

<footnote n="1">¹Université de la Réunion, INSERM, UMR 1188 Diabète Athérothrombose Thérapies Réunion Océan Indien (DéTROI), Saint-Pierre, France</footnote>

<footnote n="2">²CHU de La Réunion, Saint-Denis, France</footnote>
KEYWORDS

astrogliosis, CSPG, db/db mice, extracellular matrix, glial scar, gliosis, MCAO, microgliosis

# 1 | INTRODUCTION

Metabolic disorders are a constellation of conditions including among others hypertension, high fasting blood glucose, insulin resistance, excess body fat, elevated cholesterol and/or triglyceride levels. They increased the risk of cardiac- and cerebro-vascular diseases and are the gateway to the development of non-communicable diseases, including diabetes and obesity, which lead to the death of around 41 million of people each year (70% of all deaths) (Fahed et al., 2022; WHO, 2021). The prevalence of diabetes and obesity in the world is in constant increase, with 463 million people suffering from diabetes in 2019 and increasing to 537 million in 2021 (Feigin et al., 2021; Magliano et al., 2021). Both pathologies are tightly linked with 80% of diabetic people being overweight and/or obese (Nianogo & Arah, 2022). Also, it is well admitted that both diabetes and obesity are primary risk factors for stroke (Sajdak et al., 2019; Wolf et al., 2022).

Between 2010 and 2020, the prevalence of stroke rose, including in people with diabetes. Stroke represents the second-leading cause of death (≈11.6%) and the third-leading cause of death and disability combined (≈5.7%) in 2019 (Feigin et al., 2021; Magliano et al., 2021). It is characterized by a sudden interruption of the blood flow in the brain either by a clot (ischaemic stroke) or by a rupture of a blood vessel (haemorrhagic stroke). In both types of strokes, a region of the brain is no longer supplied with oxygen, glucose and nutriments. It results in increased oxidative stress, local inflammation and neurological death leading to disabilities and/or death. The clinical deficits appear to reflect the extent of tissue damage (Campbell & Khatri, 2020). In addition, post-stroke interventions are very limited. For ischaemic stroke, only mechanical thrombectomy and injection of recombinant tissue plasminogen activator (rtPA) are available for a small proportion of patients, and there is no therapeutic treatment to limit the consequences of stroke.

In the first few hours after ischaemic stroke, astrocytes and microglia are activated and recruited to the injured area in a process known as reactive gliosis (Zamanian et al., 2012). This physiological process is a key event involved in the formation of the glial scar around the damaged area (Sofroniew, 2005; Zhang, 2019). Initially, glial scarring shows beneficial effects by preventing exacerbated oedema, reducing brain damage and promoting restoration of the blood-brain

barrier (BBB) (Adams & Gallo, 2018; Sofroniew, 2009). However, it also appears to be a detrimental phenomenon in the later stages, when reactive astrocytes synthesize collagen IV (ColIV), a basement membrane component and extracellular matrix (ECM) proteins such as tenascin C (Ten-C) and chondroitin sulphate proteoglycans (CSPGs) (Pearson et al., 2018; Sami et al., 2020). Indeed, CSPGs have been shown to be the main compound inhibiting axonal growth in the ischaemic core (McKeon et al., 1991; Sami et al., 2020). Also, the inhibition of reactive gliosis and glial scarring after stroke increased the infarct area and the neurological deficit (Adya et al., 2012; Liu et al., 2014). To date, the role of the glial scar is dual and controversial after brain injury (Buscemi et al., 2019; Ghaddar et al., 2021; Yang et al., 2020). Based on these previous studies, modulation of the glial scar appears to be a promising therapy to improve brain plasticity and limit subsequent disability (Zhang et al., 2020).

Interestingly, diabetes doubles the risk of ischaemic stroke and worsens post-stroke outcomes (Mosenzon et al., 2023). In various ischaemic models performed in hyperglycaemic mice, the infarct size and the neurological score are aggravated compared with their respective littermates (Couret et al., 2018; Grisotto et al., 2021; MacDougall & Muir, 2011). However, the mechanism by which diabetes worsens the consequences of stroke is poorly understood. Based on these data, we hypothesized that metabolic disorders (diabetes/obesity) might interfere with the formation of the glial scar, exacerbating subsequent damage. The purpose of this study was to highlight the impact of metabolic disorders on glial scarring occurring 3 days after stroke. To this aim, we performed a 30-min brain ischaemia using the middle cerebral artery occlusion (MCAO) protocol in a classical model of diabetic and obese mice (db/db) and their control littermates (db/+). We evaluated the size of the infarct area, reactive gliosis (astrogliosis and microgliosis), the expression of ECM proteins and neurological outcomes.

# 2 | MATERIALS AND METHODS

## 2.1 | Animals and ethics

BKS(D)-Lepr db/+ and BKS(D)-Lepr db/db mice (6 weeks old, male, 25 g) were purchased from Janvier Labs
(Saint-Berthevin, France). They were maintained under standard conditions of light (12-h light/12-h dark cycle), temperature and humidity with free access to water and standard chow diet during 2 weeks of acclimatization. All experiments were conducted on 8-week-old mice in accordance with the French and European community Guidelines for the Use of Animals in Research, approved by the local Ethics Committee for animal experimentation (APAFIS #32634_2021052612229123_v5).

## 2.2 | Measurement of metabolic parameters

Bodyweight and glycaemia were monitored the week before MCAO. A glucose tolerance test was performed using a 30% oral glucose solution challenge after 6 h of fasting followed by tail blood sampling at 15-, 30-, 45-, 60-, 90- and 120-min post gavage. Blood glucose levels were monitored using a standard glucometer (OneTouch®). The area under the curve (AUC) (blood glucose vs. time post gavage) was calculated.

## 2.3 | MCAO procedure

As previously described, brain ischaemia was performed on 24 mice (Couret et al., 2018). Briefly, all mice were anaesthetized with isoflurane (IsoFlo® Centravet, Paris, France), and the body temperature was maintained on a heating pad to prevent hypothermia. A 7-0 silicon rubber-coated monofilament (702056PK5, Scholz Group, Doccol Corporation, Sharon, MA, USA) was inserted through the right common carotid at the bifurcation of the right middle cerebral artery (MCA) and the right anterior cerebral artery (ACA) (Couret et al., 2018). This MCAO was performed to induce brain ischaemia during 30 min. Then, the monofilament was removed in order to allow brain reperfusion, and all mice were replaced to home cage. During the 3 days following the surgery, soft pellet of food and easy access to water was provided post-operatively. Mice were euthanized 72 h post ischaemia. All brains were dissected rapidly and processed for further analyses.

## 2.4 | Neurological evaluation

Neurological evaluation was performed after stroke using Bederson's neurological deficit scale at 24-, 48 and 72 h post stroke (Bederson et al., 1986). The following quantification was used: 0 for no deficit, 1 for mild forelimb weakness, 2 for severe forelimb weakness and

consistently spins to the side of deficit when lifted by the tail, 3 for mandatory spinning, 4 for unconsciousness and 5 for death.

## 2.5 | Tissue preparation

After anaesthesia, mice were euthanized by cardiac puncture of the left ventricle and intracardially perfused with phosphate-buffered saline (PBS) containing 4% paraformaldehyde (PBS-PFA, pH 7.4). Brains were next immediately removed and cut into 12-µm-thick coronal slices after being fixed overnight at 4°C. For cryostat embedding, brains were cryoprotected with PBS containing 30% sucrose for 24 h at 4°C. After this step, brains were embedded in Tissue-TEK® OCT (KMA-0100-00A, Newtown, United Kingdom) and frozen at -80°C. Finally, coronal sections (12-µm thickness) were obtained using a cryostat (Leica CM 15 20, Wetzlar, Germany).

## 2.6 | Immunohistofluorescence

First, cryostat sections were dried on a warming plate and rehydrated in PBS. Antigen retrieval was performed (only for CD31, haemoglobin and phosphohistone H3 [pHH3] labelling) in sodium citrate (10 mM, pH 6.0) using a microwave as previously described (Clain et al., 2022). Sections were then washed in PBS containing .2% Triton X-100 (PBT), and non-specific binding was blocked in PBT containing 2% bovine serum albumin (BSA) for 1 h. Finally, brain sections were incubated overnight at room temperature in .5% BSA-PBT with the respective primary antibodies (Table 1): polyclonal goat anti-glial fibrillary acidic protein (GFAP) (1:1000, abcam, ab53554, RRID:AB_880202), polyclonal goat anti-ionized calcium-binding adapter molecule 1 (Iba1) (1:250, abcam, ab5076, RRID:AB_2224402), polyclonal rabbit anti-ColIV (1:500, abcam, ab19808, RRID:AB_445160), monoclonal mouse anti-chondroitin sulphate CS-56 (1:200, abcam, ab11570, RRID:AB_298176), monoclonal rabbit anti-Ten-C (1:100, abcam, ab108930, RRID:AB_10865908), polyclonal rabbit anti-activated caspase 3 (Casp 3) (1:200, abcam, ab13847, RRID:AB_445160), polyclonal mouse monoclonal anti-pHH3 (1:1000, Santa-Cruz, sc-374669, RRID:AB_11150094), to label astrocytes (GFAP), microglia (Iba1), ColIV, chondroitin sulphate (CSPGs), Ten-C, activated Casp 3 and proliferative cells (pHH3), respectively. Note that for immunoglobulin G (IgG) immunobelling, incubation with Alexa Fluor 594 anti-mouse IgG were used as previously described (Couret et al., 2021).

The next day, slides were washed in PBT and incubated for 1 h 30 min at room temperature with the
<table><caption>TABLE 1 Primary antibodies.</caption><thead><tr><td>Antibodies</td><td>Host</td><td>Type</td><td>Reference</td><td>RRID</td></tr></thead><tbody><tr><td>Caspase 3</td><td>Rabbit</td><td>Polyclonal</td><td>ab13847</td><td>AB_445160</td></tr><tr><td>CD31<sup>a</sup></td><td>Rabbit</td><td>Polyclonal</td><td>ab28364</td><td>AB_726362</td></tr><tr><td>ColIV</td><td>Rabbit</td><td>Polyclonal</td><td>ab19808</td><td>AB_445160</td></tr><tr><td>CSPG</td><td>Mouse</td><td>Monoclonal</td><td>ab11570</td><td>AB_298176</td></tr><tr><td>GFAP</td><td>Goat</td><td>Polyclonal</td><td>ab53554</td><td>AB_880202</td></tr><tr><td>Haemoglobin<sup>a</sup></td><td>Rabbit</td><td>Polyclonal</td><td>ab191183</td><td>AB_2650996</td></tr><tr><td>Iba1</td><td>Goat</td><td>Polyclonal</td><td>ab5076</td><td>AB_2224402</td></tr><tr><td>MAP 2</td><td>Mouse</td><td>Monoclonal</td><td>mab3418</td><td>AB_11212326</td></tr><tr><td>Neutrophil</td><td>Rat</td><td>Monoclonal</td><td>ab2557</td><td>AB_303154</td></tr><tr><td>Olig2</td><td>Rabbit</td><td>Polyclonal</td><td>ab9610</td><td>AB_570666</td></tr><tr><td>Ten-C</td><td>Rabbit</td><td>Monoclonal</td><td>ab108930</td><td>AB_10865908</td></tr><tr><td>pHH3<sup>a</sup></td><td>Mouse</td><td>Monoclonal</td><td>sc-374669</td><td>AB_11150094</td></tr></tbody></table>

<table><caption>TABLE 2 Secondary antibodies.</caption><thead><tr><td>Antibodies</td><td>Reference</td><td>RRID</td></tr></thead><tbody><tr><td>Goat anti-rat Alexa Fluor 488</td><td>ab150165</td><td>AB_2650997</td></tr><tr><td>Donkey anti-goat Alexa Fluor 488</td><td>ab150129</td><td>AB_2687506</td></tr><tr><td>Donkey anti-mouse Alexa Fluor 488</td><td>ab150105</td><td>AB_2732856</td></tr><tr><td>Donkey anti-mouse Alexa Fluor 594</td><td>ab150108</td><td>AB_2732073</td></tr><tr><td>Donkey anti-rabbit Alexa Fluor 488</td><td>ab150073</td><td>AB_2636877</td></tr></tbody></table>

respective secondary antibodies (Table 2). Sections were then washed with PBT and mounted with Ibidi mounting medium (REF: 50001, Ibidi, Gräfelfing, Germany). A nuclear counterstaining was performed using 4',6'-diamidino-2-phenylindole (DAPI).

The specificity of the staining was assessed by morphological analysis of the labelled cells corresponding to what was expected, as well as by the absence of any staining when the first antibody was omitted (see Figure S1). In addition, the various antibodies used had already been used in previously published studies (see the manufacturer's website).

## 2.7 | Brain oedema

The effect of a 30-min MCAO on brain oedema was performed in both groups. As previously described (Couret et al., 2021), the augmentation or the reduction (Δ) of the volume of the ipsilateral hemisphere (VIH) was

compared with the contralateral one (volume of the contralateral hemisphere [VCH]). The results are the mean of 3Δ from three sections for each brain. It should be noted that the Δ has been calculated using the following formula: $\Delta = \frac{(VIH-VCH)+100}{VCH}$.

## 2.8 | Oil Red O (ORO) staining

ORO staining was performed on liver cryostat sections of db/+ and db/db mice. Slides were washed twice in PBS for 5 min each and then rinsed in 60% isopropanol. The staining steps were performed exposing the sections to the ORO solution for 40 min, and then, slides were rinsed in 60% isopropanol. All nuclei were also stained using a haematoxylin solution. Sections were then mounted with an Ibidi mounting medium (50001, Gräfelding, Germany).

## 2.9 | Microscopy and image analyses

Pictures were captured with a nanozoomer S60 (Hamamatsu, France, Massy) and processed for brightness and contrast adjustment in Adobe Photoshop CS7 similarly between db/+ and db/db. To ensure unbiased sampling and analysis, brain sections and cross-sectional regions were identified and selected for each mouse before being processed for image analysis as follows. For each brain, at least three consecutive sections were analysed: the positively stained area was quantified at the level of the regions of interest using ImageJ. A specific threshold for each immunostaining was defined and applied using ImageJ, leading to binarization of the

<footnote><sup>a</sup>The antigen retrieval was performed.</footnote>
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /><figcaption>FIGURE 1 Legend on next page.</figcaption></figure>
FIGURE 1 Characterization of metabolic parameters in db/+ and db/db mice. (a) Body weight, (b) blood glucose levels and (c) fasting blood glucose levels are significantly higher in db/db than db/+ mice. (d,e) Oral glucose tolerance test (OGTT) showing a disrupted glucose regulation with time at 15, 30, 45, 60, 90 and 120 min post gavage and higher area under the curve (AUC) in db/db mice compared with db/+ mice. Asterisks show the significant differences compared with basal levels (T0) of the respective groups. (f) Representative Oil Red O staining in db/+ and db/db mice liver indicating lipid accumulation in db/db mice. \*p < .05, \*\*\*p < .001. Scale bar = 2 mm (low magnification) and 50 µm (high magnification).

pictures and enabling ImageJ to provide the positively stained area through an 'analyze particles' plugin. In the end, the stained area obtained for a brain corresponds to the average of at least three sections. Note that minor adjustments in the threshold can be made in some image subsets if required (e.g., background and light reflection). Also, some of the results obtained were confirmed by an independent experimenter, defining its own threshold and analyses and resulting in similar results.

For Casp 3 and oligodendrocyte transcription factor 2 (Olig2) immunostainings, a cell counting was manually performed in regions of interest from three consecutive sections for each brain. A similar process was done for the counting of ramified (multiple processes observed), intermediate (elongated shape with only one or two processes) or ameboid microglia (rounded microglia).

Each dot on the graphs corresponds to the average of the counting (cell number or positive area) performed in different sections from one animal.

## 2.10 | Statistical analysis

Statistics were performed using GraphPad Prism. Comparisons between two groups were performed using a statistical Student's *t* test and comparisons between more than two groups were performed using ANOVA multiple testing. All data are expressed as mean ± SEM, and *n* values correspond to the number of animals. A *p* value <.05 was considered as statistically significant. \*p < .05; \*\*p < .01; \*\*\*p < .001 and \*\*\*\*p < .0001.

# 3 | RESULTS

## 3.1 | Metabolic parameters of db/db mice

Metabolic parameters of 8-week-old db/db and db/+ were first investigated. As expected, we observed that body weight, non-fasting blood glucose and fasting blood glucose levels were significantly higher in db/db mice than in db/+ mice (Figure 1a-c). We also performed an oral glucose tolerance test (OGTT) using a 30% glucose solution to evaluate impaired glucose tolerance. As

shown in Figure 1, blood glucose levels and its respective AUC were significantly higher in db/db in our experimental conditions (Figure 1d,e). Liver steatosis through ORO lipid staining in both groups was also investigated. Stronger hepatic ORO staining was observed in db/db mice compared with their control littermates (Figure 1f).

Together, these results confirm the expected metabolic dysfunctions of db/db mice characterized by impaired glucose regulation, hyperglycaemia, overweight and liver steatosis that are among main features of metabolic syndrome.

## 3.2 | Metabolic disorders worsen brain damage and neuronal death after MCAO

In the following experiments, we aimed to characterize the impact of the db/db condition (diabetes and obesity) after brain ischaemia on several parameters including cell death, neurological score, BBB leakage, reactive gliosis (astrogliosis and microgliosis) and glial scarring.

To this aim, we performed a 30-min MCAO in db/+ and db/db mice, and we collected the brains 3 days post injury. First, microtubule-associated protein 2 (MAP 2) staining was done to label neurons, and the negative area was quantified as a reflection of the ischaemic core as previously shown (Buscemi et al., 2019). In parallel, the area surrounded by GFAP-positive astrocytes was also measured as a reflection of the damage area (Buscemi et al., 2019; Shimada et al., 2012). We observed that both ischaemic core and injured region were significantly higher in db/db mice compared with db/+ (Figure 2a,b, respectively). In agreement, the number of apoptotic cells (Casp 3 positive) was higher in db/db mice (Figure 2c). Of interest, db/db mice also displayed a significant marked oedema (+6.44% compared with the contralateral hemisphere, *p* = .034, *n* = 9) while no oedema was observed in db/+ mice (−.81%, not significant from the contralateral hemisphere, *p* = .61, *n* = 10). The comparison between the oedema calculation of db/db versus db/+ is significant (*p* = .0146; *n* = 9–10). Finally, we carried out a neurological assay using the Bederson score. The neurological score was higher in db/db compared with controls, 24 h after MCAO, indicating stronger disabilities. From 48 to 72 h post ischaemia, no difference was observed between db/+ and db/db mice.
<figure><img src="image_9.png" /></figure>

0 = no deficit

1 = forelimb flexion

2 = decreased resistance to grip test

3 = spontaneous movements in all directions

4 = contralateral circling

5 = death

<caption>FIGURE 2 Legend on next page.</caption>
FIGURE 2 Brain damage and cell death are aggravated in db/db mice after stroke. (a) Ischaemic core determined by the absence of MAP 2 staining in the ipsilateral hemisphere (MAP 2-negative region, see blue line). (b) Area surrounded by GFAP staining showing the damaged area including the ischaemic core (GFAP-negative region, see blue line). Both ischaemic core and damaged area are significantly higher in db/db than in db/+ mice. (c) Number of activated caspase 3-positive cells and representative staining in the ipsilateral hemisphere. The brain schematic shows the location of the regions of interest studied (black squares) in the contralateral and ipsilateral parts of the db/+ and db/db. (d) Neurological score using Bederson's deficit scale showing a significantly higher deficit in db/db mice compared with db/+ at 24 h post lesion (hpl). *p < .05, **p < .01, ****p < .001.

In conclusion, all these results indicated that the metabolic condition of db/db mice worsens brain damage, cell death and transiently exacerbates the neurological score after MCAO.

## 3.3 | Metabolic disorders exacerbate BBB leakage, haemorrhagic transformation, neutrophil infiltration and angiogenesis after MCAO

In physiological conditions, plasma proteins such as IgG are not detected in brain parenchyma. After brain damage, they can reach the cerebral parenchyma reflecting BBB leakage. In the present study, brain sections were stained and the IgG-positive area was significantly higher in the brain of db/db mice (Figure 3a). Haemorrhagic transformation also evidencing the disruption of the BBB disruption was investigated, showing a stronger haemoglobin labelling in the brain of db/db mice compared with control littermates (Figure 3b). Similarly, neutrophil infiltration was increased in the injured hemisphere of db/db mice (Figure 3c).

Finally, after brain injury, regenerative angiogenesis occurs and can be followed using the CD31 endothelial cell marker. The CD31-positive area and staining intensity were higher in the db/db brain compared with control mice, correlated to a stronger ischaemic area (Figure 3d). The co-labelling of CD31 with the pHH3 as a proliferative marker well demonstrated the presence of CD31/pHH3-double positive cells within the ischaemic core and consequently ascertaining regenerative neurogenesis (Figure 3d).

These experiments showed that db/db exhibited stronger BBB leakage, haemorrhagic transformation, neutrophil infiltration and injury-induced angiogenesis.

## 3.4 | Metabolic disorders impair reactive gliosis

After any brain damage, astrocytes and microglia become reactive, a process characterized by their recruitment to the damage site, their proliferation, their hypertrophy

and the overexpression of cell specific markers such as GFAP and Iba1 for astrocytes and microglia, respectively (Pekny & Pekna, 2014; Sofroniew, 2009). Astrocytes and microglia are known to be key players in glial scarring (Qin et al., 2019; Sofroniew, 2005; Wang et al., 2018).

To study astrogliosis, we performed GFAP immunostaining 3 days after stroke and we investigated the dorsal part of the ischaemic area boundary (Figure 4a, Region 1). In both groups, GFAP-positive area was significantly higher in the ipsilateral hemisphere compared with the respective contralateral region (Figure 4b). The astrocytic activation ratio measurement (ipsilateral/contralateral) was significantly higher in db/db mice (Figure 4b), demonstrating a higher rate of astrogliosis after cerebral ischaemia in obese/diabetic mice. In another oligaemia region (Figure 4a, Region 2), similar results were obtained (data not shown). In addition, at the vicinity of the damaged area, astrocytes appeared more hypertrophic in db/db (Figure 4c). In contrast, the processes and the ‘soma’ of astrocytes appear thinner in db/+ mice. Similarly, the quantification of the GFAP staining at higher magnification in the close vicinity of the damaged area was higher in diabetic mice (Figure 4d), demonstrating the stronger activation of astrocytes in this disrupted metabolic context.

Taken together, our results suggest that the db/db condition exacerbates astrogliosis in the injured hemisphere of db/db mice probably linked to the size of the damage area.

Similarly, we studied microgliosis following brain ischaemia in healthy and diabetic conditions by performing Iba1 staining. In both groups, Iba1-positive area was quantified in the same region as GFAP (Region 1) and was shown to be significantly higher in the ipsilateral hemisphere compared with the respective contralateral region (Figure 5a). In contrast to the GFAP analysis, the microglia activation ratio (ipsilateral/contralateral) was significantly lower in the db/db group compared with the control group (Figure 5a). We also investigated microglia activation through their morphological changes (Figure 5b). Resting microglia corresponds to highly branched cells while intermediate microglia correspond to microglia displaying one or two long cytoplasmic processes. In contrast, ameboid/phagocytic microglia have
FIGURE 3 Metabolic disruptions favour BBB leakage, haemorrhagic transformation and neutrophil infiltration after MCAO. (a) Representative pictures and quantification of IgG-positive area in db/+ and db/db mice showing an increased BBB leakage in diabetic mice. The dotted lines correspond to the area of IgG diffusion in the brain after a stroke. (b) Representative pictures and quantification of haemoglobin-positive areas highlighting a significantly higher haemorrhagic transformation in db/db mice. (c) Representative pictures and quantification of neutrophil-positive areas in db/+ and db/db mice showing a higher neutrophil infiltration in the injured hemisphere of db/db mice after MCAO. (d) Representative pictures and quantification of CD31-positive area in db/+ and db/db mice showing a higher density and stronger staining of endothelial cells in the injured hemisphere of diabetic mice after MCAO. Regenerative angiogenesis was ascertained by co-expression of CD31 (green) with the mitosis marker phosphohistone H3 (pHH3) (red) with DAPI counterstaining (blue). The brain schematic shows the location of the regions of interest studied (black squares) in the contralateral and ipsilateral parts of the db/+ and db/db. \*p < .05, \*\*p < .01. Scale bar: 200 µm (b–d) and 1 mm (a).

<figure><img src="image_10.png" /></figure>
<figure><img src="image_11.png" /><figcaption>FIGURE 4 Legend on next page.</figcaption></figure>
FIGURE 4 Reactive astrogliosis is increased in db/db mice after MCAO. (a) Representative pictures of GFAP staining (green) in the contralateral and the ipsilateral hemisphere of db/+ and db/db mice. Note that the squared numbers (1 and 2) correspond to the perilesional regions at the top and the bottom of the damaged area and their respective contralateral regions, used for quantification. As the damage is smaller in db/+, the neuroanatomical region studied is different between db/+ and db/db. (b) GFAP-positive area is significantly higher in the ipsilateral hemisphere compared with the contralateral hemisphere in db/+ and db/db mice. GFAP fold induction (ipsilateral/ contralateral) is higher in db/db mice showing an increased reactive astrogliosis following stroke compared with db/+ mice. (c) Representative pictures of astrocytes (GFAP, green) showing astrocytic hypertrophy in the ipsilateral hemisphere. (d) The quantification of the GFAP-positive area at the close vicinity of the damaged area is higher in db/db mice. The brain schematic shows the location of the regions of interest studied (black squares) in the contralateral and ipsilateral parts of the db/+ and db/db, with the damaged area shown in red. \*p < .05, \*\*\*p < .001. Scale bar: 5, 20 and 100 µm and 1 mm.

been defined as Iba1-positive cells with no or very small processes and a spherical shape as previously described (Leyh et al., 2021). Following brain ischaemia, we observed hypertropia of microglia in both db/+ and db/db. Interestingly, in the ischaemic core, the proportion of ameboid microglia was higher in db/db mice while more intermediate microglia were present in the db/+ group (Figure 5c). Such a difference in the activation of microglia according to the db/+ and db/db condition could be induced either by a difference in cell death and/or also a difference in the kinetic of microglia activation.

Altogether, the db/db condition seems to impair microgliosis by decreasing their recruitment at the vicinity of the damage area and by increasing their activation in the ischaemic core probably in link with higher cell death occurring in the infarct region of db/db mice. It is also interesting to mention that in the contralateral hemisphere, Iba1-positive area was stronger in db/db mice than in db/+ without reaching the significance.

After cerebral lesions, the recruitment and the proliferation of oligodendrocyte precursor cells (OPCs) in the ischaemic area are activated. We used Olig2 antibody to label OPCs and oligodendrocytes and observed that the number of Olig2-positive cells was significantly higher in db/db mice (Figure 6), probably in link with the increased size of the damaged region.

## 3.5 | Metabolic disorders favour ECM synthesis after stroke

During the glial scar process, the ECM is known to play a key role to prevent overwhelming inflammation. However, very few reports documented the effect of diabetes/ obesity on glial scarring. We consequently decided to investigate some of the main ECM proteins involved in the formation of the glial scar including ColIV, Ten-C and CSPG.

Although ColIV-positive area was slightly increased in the damaged region of db/+ mice compared with the

respective contralateral region, there was no significant change 3 days post-stroke (Figure 7a,b). In striking contrast, ColIV-positive area was significantly higher in the damaged region of db/db mice compared with its respective contralateral counterpart (Figure 7a,b). This was further confirmed by the calculation of the ColIV ratio (ipsilateral/contralateral) (Figure 7b).

The same results were obtained for Ten-C staining with a non-significant increase in the damaged region of db/+ mice and a strong and significant overexpression in db/db mice (Figure 7b). In addition, the Ten-C expression ratio (ipsilateral/contralateral) was significantly increased in db/db mice compared with the control group (Figure 7b).

In addition, we decided to explore the expression of CSPG, one important ECM protein family shown to limit axonal growth and regeneration (Zou et al., 2018). As previously shown for ColIV and Ten-C, the CSPG-positive area was increased in the damage region compared with its respective counterpart from the contralateral hemisphere but did not reach a significant value in db/+ mice (Figure 8a,b). In contrast, this increase was stronger and significant in db/db mice with a CSPG ratio (ipsilateral/contralateral) significantly different from db/+ and db/db condition (Figure 8b).

Taken together, these results demonstrated that in db/db mice, the disrupted metabolic condition exacerbates the expression of key ECM proteins at 3 days post stroke.

## 3.6 | Positive correlation between the infarct area and the thickness of the glial scar in db/db mice

During analysis of the immunolabelled pictures, we observed a large heterogeneity regarding the scar among db/db mice. We thus correlated the size of the glial scar to the infarct area. As shown in Figure 9, there is a positive correlation between the size of the infarct area and the thickness of the glial scar.
<figure><img src="image_12.png" /><figcaption>FIGURE 5 Legend on next page.</figcaption></figure>
**FIGURE 5** Reactive microgliosis is impaired in db/db mice after MCAO. (a) Iba1-positive area is significantly higher in the ipsilateral hemisphere compared with the contralateral hemisphere in both groups at the perilesional area. Iba1 fold induction (ipsilateral/ contralateral) is decreased in db/db mice compared with db/+ ones. (b) Representative pictures showing hypertrophic microglia (Iba1 in green) in the ipsilateral hemisphere compared with the contralateral one in both groups. (c) Quantification of the percentage of resting, intermediate and ameboid/phagocytic microglia in the ischaemic core. Note that a decrease in the percentage of intermediate microglia and an increase in ameboid ones are observed in db/db mice. The brain schematic shows the location of the regions of interest studied (black squares) in the contralateral and ipsilateral parts of the db/+ and db/db, with the damaged area shown in red. \*p < .05, \*\*\*p < .001. Scale bar: 40 and 100 µm.

<figure><img src="image_13.png" /></figure>

**FIGURE 6** Oligodendrocyte recruitment is enhanced in db/db mice. Representative pictures of Olig2 staining (red) in the ischaemic core showing higher number of OPC and/or oligodendrocytes in db/db mice. The brain schematic shows the location of the regions of interest studied (black squares) in the contralateral and ipsilateral parts of the db/+ and db/db, with the damaged area shown in red.
\*p < .05. Scale bar: 200 µm.

## 4 | DISCUSSION

The aim of the present study was to investigate the impact of metabolic disorders (hyperglycaemia and obesity) on stroke and in particular on glial scar formation using db/db and control non-obese and non-diabetic db/+ mouse models. In our experimental conditions, the disrupted metabolic context causes larger infarct area, exacerbated astroglial and microglial activation and higher ECM protein synthesis 3 days after stroke, associated with a transient worsening of neurological outcomes.

### 4.1 | Infarct size, cell death, neurological outcomes and BBB leakage after ischaemia

Three days after MCAO, the infarct area and the size of the ischaemic core were significantly larger in db/db mice, associated with an increase in the number of apoptotic cells. This is in agreement with previous works obtained in db/db mice at 3 days after 45 min or a

permanent distal occlusion (Ma et al., 2018; Tureyen et al., 2011). Such an increased cell death is observed as early as a few hours after MCAO in db/db (Li et al., 2016). In high-fat diet (HFD) and acute hyperglycaemic models, the infarct size is also higher compared with their respective controls (Couret et al., 2018; Grisotto et al., 2021; Maysami et al., 2015). These results demonstrated the deleterious impact of the metabolic disruptions on the size of the damaged area following stroke.

Interestingly, the neurological deficit was higher in db/db mice 24 h after stroke compared with their control littermates, consistent with previous studies (Kurita et al., 2020; Yeung et al., 2010). Nevertheless, db/db mice came back to the same neurological score as db/+ mice at 2 and 3 days post MCAO, whereas other studies have shown that db/db retained a greater deficit up to 3 days after MCAO (Tureyen et al., 2011). These differences could be due to the duration of brain ischaemia (45 vs. 30 min), the resulting lesions and the sample size.

As expected, the leakage of the BBB was increased in db/db as shown by extravasation of IgG. Our study
<figure><img src="image_14.png" /><figcaption>**FIGURE 7** Synthesis of the extracellular matrix proteins is enhanced in db/db mice after MCAO.</figcaption></figure>

(a) Representative pictures of collagen IV staining (ColIV, red) in the contralateral and the ipsilateral hemisphere of db/+ and db/db mice. ColIV-positive area is significantly higher in the ipsilateral hemisphere compared with the contralateral hemisphere in both groups. ColIV fold induction (ipsilateral / contralateral) is higher in the db/db group compared with db/+ mice. (b) Ten-C-positive area is significantly higher in the ipsilateral hemisphere compared with the contralateral hemisphere in both groups. Ten-C fold induction (ipsilateral/ contralateral) is higher in the db/db group compared with db/+ mice. The brain schematic shows the location of the regions of interest studied (black squares) in the contralateral and ipsilateral parts of the db/+ and db/db, with the damaged area shown in red. \*p < .05, \*\*p < .01. Scale bar: 100 µm.
<figure><img src="image_15.png" /><figcaption>**FIGURE 8** Synthesis of the chondroitin sulphate of proteoglycan is enhanced in db/db mice after MCAO. (a) Representative pictures of CSPG staining (green) in the contralateral and the ipsilateral hemisphere of db/+ and db/db mice. (b) In db/db mice, CSPG-positive area is significantly higher in the ipsilateral hemisphere compared with the contralateral hemisphere. CSPG fold induction (ipsilateral/ contralateral) is higher in the db/db group. The brain schematic shows the location of the regions of interest studied (black squares) in the contralateral and ipsilateral parts of the db/+ and db/db, with the damaged area shown in red. \*p < .05, \*\*p < .01. Scale bar: 100 µm.</figcaption></figure>

corroborates and complements previous investigations showing similar results 1 day after a 60-min MCAO in db/db (Kurita et al., 2020) and after a 90-min MCAO in a HFD mouse model displaying decreased expression of ZO-1 (Taïlé et al., 2022). Also, we demonstrated that haemorrhagic transformation was stronger in db/db mice as observed previously in acute hyperglycaemia, HFD and db/db models (Couret et al., 2018; Grisotto et al., 2021; Kumari et al., 2011; Taïlé et al., 2022; Wang et al., 2022). Such increased BBB disruption is associated with increased neutrophil infiltration also observed in different studies (Galea, 2021; Xiang et al., 2021), namely, 1 day after stroke in db/db mice (Kumari et al., 2011, 2020).

Interestingly, cerebral oedema is still present in db/db mice 3 days after stroke, while the volume of the ischaemic hemisphere appears to be slightly but not significantly reduced in db/+ compared with its contralateral counterpart. This difference is probably due to the small infarct size in db/+ that allows a faster resolution of BBB leakage and oedema and a reduced activation of microglia and astrocytes at this stage. We can speculate that in db/db, BBB leakage and persistent reactive gliosis allow cerebral oedema to be maintained while these processes are almost solved in db/+.

Together, we highlighted that metabolic disorders worsen outcomes after stroke by increasing the infarct
<figure><img src="image_16.png" /><figcaption>FIGURE 9 Glial scar thickness is positively correlated with the size of infarct area in db/db mice after MCAO. There is a positive correlation between the infarct area and the thickness of the glial scar in db/db mice. **p < .01.</figcaption></figure>

size and haemorrhagic complications. Hence, these results obtained at distance of the stroke raise the question of the respective roles of obesity versus hyperglycaemia on the cell death mechanism, neurological outcomes and the disruption of the BBB integrity. Interestingly, the study from Couret et al. (2018) demonstrates that acute hyperglycaemia alone is a key player on such endpoints, considering that a single injection of glucose (300 mg/dL) leads to almost similar results on a 30-min MCAO at 1 day post stroke.

## 4.2 | Brain repair mechanisms: Astrogliosis, microgliosis and regenerative angiogenesis

After any type of brain damage, astrogliosis and microgliosis occur to preserve brain homeostasis (Ma et al., 2017; Moulson et al., 2021; Pekny & Pekna, 2014; Qin et al., 2019). These reactive cells enable the formation of the glial scar after injury to the central and peripheral nervous system (Gao et al., 2013; Shinozaki et al., 2017; Yang et al., 2020). As well established, astrocytes undergo various cellular, molecular and metabolic changes after brain injury and become reactive astrocytes characterized by the increased expression of markers such as GFAP (Jurga et al., 2021; Moulson et al., 2021; Sofroniew, 2015; Yang et al., 2020). This activation generally peaks between 2 to 4 days post injury in the injured hemisphere of normal mice (Buscemi et al., 2019; Choudhury & Ding, 2016; Liu et al., 2014; Peterson et al., 2021).

In our experiments, astrocytic activation was higher in db/db mice compared with their control counterparts

in the core of the glial scar and also in the close vicinity of the damaged area. A stronger astrocytic hypertrophy occurs in the ipsilateral hemisphere of db/db mice compared with db/+ . Both the proliferation and recruitment of astrocytes as well as overexpression of astroglia markers could be responsible for the higher GFAP-positive area observed. Depending on the environment, astrocyte response may be different. In vitro, high glucose levels seem to limit astrocyte proliferation and migration during scratch assay (Li et al., 2018). Furthermore, study on deceased patients with hyperglycaemia shows that the density and the activation of GFAP-positive cells were reduced in the hippocampus and the frontal cortex (Sonneville et al., 2012). Such contrasting results are possibly due to different time windows after stroke and the duration of the occlusion between studies and also the metabolic parameters involved in mouse models.

Interestingly, the number of microglia and the expression of their specific marker (Iba1) are increased after stroke (Heindl et al., 2018). In addition, the morphology of microglia switches from a resting/ramified state to an ameboid/phagocytic one (Eldahshan et al., 2019; Heindl et al., 2018; Leyh et al., 2021). In our study, the ratio of Iba1 up-regulation (ipsilateral/contralateral) was significantly reduced in the peri-infarct area of db/db mice. As well, we observed a shift to ameboid stage in the ischaemic core of db/db mice. This is in agreement with other data obtained 3 days after stroke in db/db mice, in which the M2 (anti-inflammatory) profile of microglia decreased in favour of an M1 (pro-inflammatory) profile (Ma et al., 2018). In the literature, hyperglycaemia appears to participate in the transformation of quiescent into activated microglia (Chen et al., 2019) and to promote microglial hyperplasia (Wanrooy et al., 2018). Together, these data highlight the stronger neuroinflammatory state following stroke in db/db mice, raising the question of the respective role of hyperglycaemia, chronic inflammation and oxidative stress as well as obesity on such processes.

## 4.3 | Metabolic disorders and ECM deposits

After brain injury, activated astrocytes and to a lesser extent infiltrated immune cells promoted ECM synthesis that participates in a chemical barrier limiting damages. Such ECM proteins also have an inhibitory effect on axonal regeneration (Moeendarbary et al., 2017; Wang et al., 2018). In db/+ mice, we showed that ColIV expression tends to increase after stroke. This is supported by other studies performed in C57BL/6J male mice 3 days after focal ischaemia (Michalski et al., 2020). Interestingly, this ColIV up-regulation was not shown to be
limited to the brain parenchyma but also involved the neurovascular matrix adhesion zone (Kang & Yao, 2020; Michalski et al., 2020). In db/db mice, we demonstrated the strong and significant up-regulation of ColIV after brain ischaemia. This is in contrast to other data performed in a mouse model of type 1 diabetes, for which ColIV expression around the blood vessel is down-regulated in the injured hemisphere 5 days post stroke (Gliem et al., 2015). The discrepancies between these results could be due to different mice models used (type 1 vs. type 2 diabetes), the obesity/lipid profile aspect and the kinetic time points. We also observed increased expression of CSPG and Ten-C in db/db compared with controls.

Overall, our data seem to indicate that obese/ diabetic conditions disrupt astrogliosis and microgliosis and enhance ECM synthesis contributing to the inhibi- tory environment of the glial scarring. Although it is known that CSPG is increased after stroke (Liu et al., 2014; Liu & Chopp, 2016; Silver & Miller, 2004), data are lacking regarding the effects of metabolic disor- ders (obesity/diabetes) on CSPG synthesis after ischaе- mic stroke. As glial scar formation has been reported to be incomplete 3 days post stroke, further investigations are needed to characterize the impact of hyperglycaemia on the complete formation of the glial scar after ischaе- mic stroke.

## 4.4 | A role for the size of the stroke in exacerbated reactive gliosis and glial scarring observed in db/db

Our results clearly showed that the size of the damaged area is larger in db/db than in control mice. Such data were also encountered in other models of stroke performed in db/db mice and in HFD and acute hyperglycaemic mice (Couret et al., 2018; Grisotto et al., 2021). This raises the question of the respective contribution of obesity versus hyperglycaemia on the infarct size and the subsequent consequences implying reactive gliosis and ECM deposits.

The work from Couret et al. (2018) clearly demonstrated that hyperglycaemia is able, alone, to induce stronger brain damage, associated with increased risk of haemorrhagic transformation. Nevertheless, we could not exclude the deleterious effects of obesity and its associated dyslipidaemia, oxidative stress and inflammation in our db/db models.

Also, as gliosis is known to be dependent on the size of stroke, we could assume that the increase in reactive astrogliosis in db/db is solely due to the larger injured area, given that db/db are known to exhibit larger infarct.

In that case, if we hypothesized that the disrupted metabolism of db/db mice did not impact the reactivity of astrocytes and microglia in response to brain injury, our results would be just an indirect cause of the stroke size. Nevertheless, this would be an interesting new piece of data, as we could also have assumed that hyperglycaemia/obesity might have a negative impact on reactive gliosis and ECM deposition. However, the reactivity of astrocytes at the close vicinity of the damaged area seems to demonstrate a stronger hypertrophic state and a higher number of astrocytes in db/db mice compared with controls in our experimental conditions. We can speculate that the inflammatory micro-environment at the border of the damaged area might be similar between db/+ and db/db. In this case, metabolic status would increase glial reactivity at this acute phase of stroke. Interestingly, the work from Kumari et al. (2007) demonstrated that *Gfap* in situ hybridization results in a delayed activation of astrocytes from 4 to 24 h post ischaemia in db/db compared with db/+ Similarly, the gene expression of the microglial marker *Bfl-1* is detected from 4 h post ischaemia in db/+ and continue to increase until 24 h, while in db/db mice, *Bfl-1* expression appears only from 8 to 12 h post injury and seems to decrease afterwards (Kumari et al., 2007). In our experimental conditions, the kinetic activation of astrocytes and microglia seems to differ between db/+ and db/db mice. Possibly, a decreased initial activation of microglia and astrocytes could also contribute to increased cell death. In order to better understand the direct impact of hyperglycaemia/obesity on reactive gliosis, it would be interesting to study glia scar formation for similar size of infarct in db/+ and db/db mice, meaning nevertheless that the duration of the ischaemia would be longer in db/+ to obtain a similar brain lesion than in db/db.

It will consequently be interesting to perform such studies at 1 and 2 days post MCAO in order to better envision the kinetic of recruitment of microglia and astrocytes following stroke and to homogenize the size of stroke to better understand the respective roles of metabolic disruption versus size of brain damage in glial scarring process.

In conclusion, this work provides data on the possible link between metabolic disorders and worsening outcomes after stroke, not only focusing on stroke size but also providing new insights into regenerative mechanisms involving glial scarring and regenerative angiogenesis. The present study demonstrates that hyperglycaemia/obesity (1) aggravates brain damage after stroke as expected, (2) also exacerbates astrogliosis and microgliosis and (3) promotes ECM deposits known to inhibit axonal growth/regeneration. To our knowledge, this is the first study to open the way to
understanding the indirect and/or direct impact of meta-
bolic dysfunctions on the consequences of stroke, particu-
larly with regard to reactive gliosis and ECM deposits in
its acute phase. In conclusion, this work showed that
hyperglycaemia/obesity impairs glial scar formation at
the acute phase of stroke (3 days post stroke) by modulat-
ing reactive gliosis, leading to worst outcomes in db/db
mice. Further investigations are needed to better charac-
terize the direct effect of metabolic disorders on complete
glial scar formation after stroke.

AUTHOR CONTRIBUTIONS

**Julien Clain:** Conceptualization; data curation; formal analysis; investigation; methodology; resources; validation; visualization; writing—original draft; writing—review and editing.
**David Couret:** Conceptualization; data curation; funding acquisition; investigation; project administration; supervision; validation; writing—original draft; writing—review and editing.
**Matthieu Bringart:** Investigation; methodology; writing—review and editing.
**Arnaud Lecadieu:** Formal analysis; investigation; validation.
**Olivier Meilhac:** Conceptualization; investigation; methodology; writing—review and editing.
**Christian Lefebvre d'Hellencourt:** Conceptualization; data curation; formal analysis; investigation; methodology; project administration; resources; supervision; validation; visualization; writing—original draft; writing—review and editing.
**Nicolas Diotel:** Conceptualization; data curation; formal analysis; funding acquisition; investigation; methodology; project administration; resources; supervision; validation; visualization; writing—original draft; writing—review and editing.

ACKNOWLEDGMENTS

We thank the Région Réunion for its financial support
(J. Clain is a beneficiary of a regional grant) and the
members of the laboratory for their advice.

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no conflict of interest.

PEER REVIEW

The peer review history for this article is available at
https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/ejn.16325.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are avail-
able on request from the corresponding author (N.D.).

ORCID

Nicolas Diotel https://orcid.org/0000-0003-2032-518X

REFERENCES

Adams, K. L., & Gallo, V. (2018). The diversity and disparity of the glial scar. *Nature Neuroscience*, *21*, 9–15. https://doi.org/10.1038/s41593-017-0033-9

Adya, R., Tan, B. K., Chen, J., & Randeva, H. S. (2012). Protective actions of globular and full-length adiponectin on human endothelial cells: Novel insights into adiponectin-induced angiogenesis. *Journal of Vascular Research*, *49*, 534–543.
https://doi.org/10.1159/000338279

Bederson, J. B., Pitts, L. H., Tsuji, M., Nishimura, M. C., Davis, R. L., & Bartkowski, H. (1986). Rat middle cerebral artery occlusion: Evaluation of the model and development of a neurologic examination. *Stroke*, *17*, 472–476. https://doi.org/10.1161/01.STR.17.3.472

Buscemi, L., Price, M., Bezzi, P., & Hirt, L. (2019). Spatio-temporal overview of neuroinflammation in an experimental mouse stroke model. *Scientific Reports*, *9*, 507. https://doi.org/10.1038/s41598-018-36598-4

Campbell, B. C. V., & Khatri, P. (2020). Stroke. *The Lancet*, *396*, 129–142. https://doi.org/10.1016/S0140-6736(20)31179-X

Chen, C., Wu, S., Hong, Z., Chen, X., Shan, X., Fischbach, S., & Xiao, X. (2019). Chronic hyperglycemia regulates microglia polarization through ERK5. *Aging*, *11*, 697–706. https://doi.org/10.18632/aging.101770

Choudhury, G. R., & Ding, S. (2016). Reactive astrocytes and therapeutic potential in focal ischemic stroke. *Neurobiology of Disease*, *85*, 234–244. https://doi.org/10.1016/j.nbd.2015.05.003

Clain, J., Couret, D., Planesse, C., Krejbich-Trotot, P., & Meilhac, O. (2022). Distribution of adiponectin receptors in the brain of adult mouse: Effect of a single dose of the adiponectin receptor agonist, AdipoRON, on ischemic stroke. *Brain Sciences*, *12*(5), 680. https://doi.org/10.3390/brainsci12050680

Couret, D., Bourane, S., Catan, A., Nativel, B., Planesse, C., Dorsemans, A.-C., Ait-Arsa, I., Cournot, M., Rondeau, P., Patche, J., Tran-Dinh, A., Lambert, G., Diotel, N., & Meilhac, O. (2018). A hemorrhagic transformation model of mechanical stroke therapy with acute hyperglycemia in mice. *The Journal of Comparative Neurology*, *526*, 1006–1016. https://doi.org/10.1002/cne.24386

Couret, D., Planesse, C., Patche, J., Diotel, N., Nativel, B., Bourane, S., & Meilhac, O. (2021). Lack of neuroprotective effects of high-density lipoprotein therapy in stroke under acute hyperglycemic conditions. *Molecules*, *26*, 6365. https://doi.org/10.3390/molecules26216365

Eldahshan, W., Fagan, S. C., & Ergul, A. (2019). Inflammation within the neurovascular unit: Focus on microglia for stroke injury and recovery. *Pharmacological Research*, *147*, 104349. https://doi.org/10.1016/j.phrs.2019.104349

Fahed, G., Aoun, L., Bou Zerdan, M., Allam, S., Bou Zerdan, M., Bou ferraa, Y., & Assi, H. I. (2022). Metabolic syndrome: Updates on pathophysiology and management in 2021. *International Journal of Molecular Sciences*, *23*, 786. https://doi.org/10.3390/ijms23020786

Feigin, V. L., Stark, B. A., Johnson, C. O., Roth, G. A., Bisignano, C., Abady, G. G., Abbasifard, M., Abbasi-Kangevari, M., Abd-Allah, F., Abedi, V., Abualhasan, A., Abu-Rmeileh, N. M., Abushouk, A. I., Adebayo, O. M., Agarwal, G., Agasthi, P., Ahinkorah, B. O., Ahmad, S., Ahmadi, S., ... Hamidi, S. (2021). Global, regional, and national burden of
stroke and its risk factors, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. *Lancet Neurology*, 20, 795–820. https://doi.org/10.1016/S1474-4422(21)00252-0

Galea, I. (2021). The blood-brain barrier in systemic infection and inflammation. *Cellular & Molecular Immunology, 18*, 2489–2501. https://doi.org/10.1038/s41423-021-00757-x

Gao, Z., Zhu, Q., Zhang, Y., Zhao, Y., Cai, L., Shields, C. B., & Cai, J. (2013). Reciprocal modulation between microglia and astrocyte in reactive gliosis following the CNS injury. *Molecular Neurobiology, 48*, 690–701. https://doi.org/10.1007/s12035-013-8460-4

Ghaddar, B., Lübke, L., Couret, D., Rastegar, S., & Diotel, N. (2021). Cellular mechanisms participating in brain repair of adult zebrafish and mammals after injury. *Cells, 10*, 391. https://doi.org/10.3390/cells10020391

Gliem, M., Klotz, L., van Rooijen, N., Hartung, H.-P., & Jander, S. (2015). Hyperglycemia and PPARγ antagonistically influence macrophage polarization and infarct healing after ischemic stroke. *Stroke, 46*, 2935–2942.

Grisotto, C., Taïlé, J., Planesse, C., Diotel, N., Gonthier, M.-P., Meilhac, O., & Couret, D. (2021). High-fat diet aggravates cerebral infarct, hemorrhagic transformation and neuroinflammation in a mouse stroke model. *International Journal of Molecular Sciences, 22*, 4571. https://doi.org/10.3390/ijms22094571

Heindl, S., Gesierich, B., Benakis, C., Llovera, G., Duering, M., & Liesz, A. (2018). Automated morphological analysis of microglia after stroke. *Frontiers in Cellular Neuroscience, 12*, 106. https://doi.org/10.3389/fncel.2018.00106

Jurga, A. M., Paleczna, M., Kadluczka, J., & Kuter, K. Z. (2021). Beyond the GFAP-astrocyte protein markers in the brain. *Bio-molecules, 11*, 1361. https://doi.org/10.3390/biom11091361

Kang, M., & Yao, Y. (2020). Basement membrane changes in ischemic stroke. *Stroke, 51*, 1344–1352.

Kumari, R., Bettermann, K., Willing, L., Sinha, K., & Simpson, I. A. (2020). The role of neutrophils in mediating stroke injury in the diabetic db/db mouse brain following hypoxia-ischemia. *Neurochemistry International, 139*, 104790. https://doi.org/10.1016/j.neuint.2020.104790

Kumari, R., Willing, L. B., Krady, J. K., Vannucci, S. J., & Simpson, I. A. (2007). Impaired wound healing after cerebral hypoxia—Ischemia in the diabetic mouse. *Journal of Cerebral Blood Flow and Metabolism, 27*, 710–718. https://doi.org/10.1038/sj.jcbfm.9600382

Kumari, R., Willing, L. B., Patel, S. D., Baskerville, K. A., & Simpson, I. A. (2011). Increased cerebral matrix metalloprotease-9 activity is associated with compromised recovery in the diabetic db/db mouse following a stroke: MMP-9, diabetes and stroke. *Journal of Neurochemistry, 119*, 1029–1040. https://doi.org/10.1111/j.1471-4159.2011.07487.x

Kurita, N., Yamashiro, K., Kuroki, T., Tanaka, R., Urabe, T., Ueno, Y., Miyamoto, N., Takanashi, M., Shimura, H., Inaba, T., Yamashiro, Y., Nomoto, K., Matsumoto, S., Takahashi, T., Tsuji, H., Asahara, T., & Hattori, N. (2020). Metabolic endotoxemia promotes neuroinflammation after focal cerebral ischemia. *Journal of Cerebral Blood Flow and Metabolism, 40*, 2505–2520. https://doi.org/10.1177/0271678X19899577

Leyh, J., Paeschke, S., Mages, B., Michalski, D., Nowicki, M., Bechmann, I., & Winter, K. (2021). Classification of microglial

morphological phenotypes using machine learning. *Frontiers in Cellular Neuroscience, 15*, 701673. https://doi.org/10.3389/fncel.2021.701673

Li, P.-C., Liu, L.-F., Jou, M.-J., & Wang, H.-K. (2016). The GLP-1 receptor agonists exendin-4 and liraglutide alleviate oxidative stress and cognitive and micturition deficits induced by middle cerebral artery occlusion in diabetic mice. *BMC Neuroscience, 17*, 37. https://doi.org/10.1186/s12868-016-0272-9

Li, W., Roy Choudhury, G., Winters, A., Prah, J., Lin, W., Liu, R., & Yang, S.-H. (2018). Hyperglycemia alters astrocyte metabolism and inhibits astrocyte proliferation. *Aging and Disease, 9*, 674–684. https://doi.org/10.14336/AD.2017.1208

Liu, Z., & Chopp, M. (2016). Astrocytes, therapeutic targets for neuroprotection and neurorestoration in ischemic stroke. *Progress in Neurobiology, 144*, 103–120. https://doi.org/10.1016/j.pneurobio.2015.09.008

Liu, Z., Li, Y., Cui, Y., Roberts, C., Lu, M., Wilhelmsson, U., Pekny, M., & Chopp, M. (2014). Beneficial effects of GFAP/vimentin reactive astrocytes for axonal remodeling and motor behavioral recovery in mice after stroke. *Glia, 62*, 2022–2033. https://doi.org/10.1002/glia.22723

Ma, S., Wang, J., Wang, Y., Dai, X., Xu, F., Gao, X., Johnson, J., Xu, N., Leak, R. K., Hu, X., Luo, Y., & Chen, J. (2018). Diabetes mellitus impairs white matter repair and long-term functional deficits after cerebral ischemia. *Stroke, 49*, 2453–2463. https://doi.org/10.1161/STROKEAHA.118.021452

Ma, Y., Wang, J., Wang, Y., & Yang, G.-Y. (2017). The biphasic function of microglia in ischemic stroke. *Progress in Neurobiology, 157*, 247–272. https://doi.org/10.1016/j.pneurobio.2016.01.005

MacDougall, N. J. J., & Muir, K. W. (2011). Hyperglycaemia and infarct size in animal models of middle cerebral artery occlusion: Systematic review and meta-analysis. *Journal of Cerebral Blood Flow and Metabolism, 31*, 807–818. https://doi.org/10.1038/jcbfm.2010.210

Magliano, D. J., Boyko, E. J., & IDF Diabetes Atlas 10th edition scientific committee. (2021). IDF diabetes atlas (10th ed.). International Diabetes Federation.

Maysami, S., Haley, M. J., Gorenkova, N., Krishnan, S., McColl, B. W., & Lawrence, C. B. (2015). Prolonged diet-induced obesity in mice modifies the inflammatory response and leads to worse outcome after stroke. *Journal of Neuroinflammation, 12*, 140. https://doi.org/10.1186/s12974-015-0359-8

McKeon, R., Schreiber, R., Rudge, J., & Silver, J. (1991). Reduction of neurite outgrowth in a model of glial scarring following CNS injury is correlated with the expression of inhibitory molecules on reactive astrocytes. *The Journal of Neuroscience, 11*, 3398–3411. https://doi.org/10.1523/JNEUROSCI.11-11-03398.1991

Michalski, D., Spielvogel, E., Puchta, J., Reimann, W., Barthel, H., Nitzsche, B., Mages, B., Jäger, C., Martens, H., Horn, A. K. E., Schob, S., & Härtig, W. (2020). Increased immunosignals of collagen IV and fibronectin indicate ischemic consequences for the neurovascular matrix adhesion zone in various animal models and human stroke tissue. *Frontiers in Physiology, 11*, 575598. https://doi.org/10.3389/fphys.2020.575598

Moeendarbary, E., Weber, I. P., Sheridan, G. K., Koser, D. E., Soleman, S., Haenzi, B., Bradbury, E. J., Fawcett, J., &
Franze, K. (2017). The soft mechanical signature of glial scars in the central nervous system. *Nature Communications, 8*, 14787. https://doi.org/10.1038/ncomms14787

Mosenzon, O., Cheng, A. Y., Rabinstein, A. A., & Sacco, S. (2023). Diabetes and stroke: What are the connections? *Journal of Stroke*, 25, 26-38. https://doi.org/10.5853/jos.2022.02306

Moulson, A. J., Squair, J. W., Franklin, R. J. M., Tetzlaff, W., & Assinck, P. (2021). Diversity of reactive astrogliosis in CNS pathology: Heterogeneity or plasticity? *Frontiers in Cellular Neuroscience*, 15, 703810. https://doi.org/10.3389/fncel.2021.703810

Nianogo, R. A., & Arah, O. A. (2022). Forecasting obesity and type 2 diabetes incidence and burden: The ViLA-obesity simulation model. *Frontiers in Public Health*, 10, 818816. https://doi.org/10.3389/fpubh.2022.818816

Pearson, C. S., Mencio, C. P., Barber, A. C., Martin, K. R., & Geller, H. M. (2018). Identification of a critical sulfation in chondroitin that inhibits axonal regeneration. *eLife*, 7, e37139. https://doi.org/10.7554/eLife.37139

Pekny, M., & Pekna, M. (2014). Astrocyte reactivity and reactive astrogliosis: Costs and benefits. *Physiological Reviews*, 94, 1077-1098. https://doi.org/10.1152/physrev.00041.2013

Peterson, T. C., Lechtenberg, K. J., Piening, B. D., Lucas, T. A., Wei, E., Chaib, H., Dowdell, A. K., Snyder, M., & Buckwalter, M. S. (2021). Obesity drives delayed infarct expansion, inflammation, and distinct gene networks in a mouse stroke model. *Translational Stroke Research*, 12, 331-346. https://doi.org/10.1007/s12975-020-00826-9

Qin, C., Zhou, L.-Q., Ma, X.-T., Hu, Z.-W., Yang, S., Chen, M., Bosco, D. B., Wu, L.-J., & Tian, D.-S. (2019). Dual functions of microglia in ischemic stroke. *Neuroscience Bulletin*, 35, 921-933. https://doi.org/10.1007/s12264-019-00388-3

Sajdak, J., Stepień, D., Werel, P., Czarnowska, A., Kapica-Topczewska, K., & Kulakowska, A. (2019). Does obesity increase the risk of stroke? *Medycyna Ogólna i Nauki o Zdroju*, 25, 204-207. https://doi.org/10.26444/monz/114153

Sami, A., Selzer, M. E., & Li, S. (2020). Advances in the signaling pathways downstream of glial-scar axon growth inhibitors. *Frontiers in Cellular Neuroscience*, 14, 174. https://doi.org/10.3389/fncel.2020.00174

Shimada, I. S., LeComte, M. D., Granger, J. C., Quinlan, N. J., & Spees, J. L. (2012). Self-renewal and differentiation of reactive astrocyte-derived neural stem/progenitor cells isolated from the cortical peri-infarct area after stroke. *The Journal of Neuroscience*, 32, 7926-7940. https://doi.org/10.1523/JNEUROSCI.4303-11.2012

Shinozaki, Y., Shibata, K., Yoshida, K., Shigetomi, E., Gachet, C., Ikenaka, K., Tanaka, K. F., & Koizumi, S. (2017). Transformation of astrocytes to a neuroprotective phenotype by microglia via P2Y1 receptor downregulation. *Cell Reports*, 19, 1151-1164. https://doi.org/10.1016/j.celrep.2017.04.047

Silver, J., & Miller, J. H. (2004). Regeneration beyond the glial scar. *Nature Reviews. Neuroscience*, 5, 146-156. https://doi.org/10.1038/nrn1326

Sofroniew, M. V. (2005). Reactive astrocytes in neural repair and protection. *The Neuroscientist*, 11, 400-407. https://doi.org/10.1177/1073858405278321

Sofroniew, M. V. (2009). Molecular dissection of reactive astrogliosis and glial scar formation. *Trends in Neurosciences*, 32, 638-647. https://doi.org/10.1016/j.tins.2009.08.002

Sofroniew, M. V. (2015). Astrogliosis. *Cold Spring Harbor Perspectives in Biology*, 7, a020420. https://doi.org/10.1101/cshperspect.a020420

Sonneville, R., den Hertog, H. M., Güiza, F., Gunst, J., Derese, I., Wouters, P. J., Brouland, J.-P., Polito, A., Gray, F., Chrétien, F., Charlier, P., Annane, D., Sharshar, T., Van den Berghe, G., & Vanhorebeek, I. (2012). Impact of hyperglycemia on neuropathological alterations during critical illness. *The Journal of Clinical Endocrinology and Metabolism*, 97, 2113-2123. https://doi.org/10.1210/jc.2011-2971

Taïlé, J., Bringart, M., Planesse, C., Patché, J., Rondeau, P., Veeren, B., Clerc, P., Gauvin-Bialecki, A., Bourane, S., Meilhac, O., Couret, D., & Gonthier, M.-P. (2022). Antioxidant polyphenols of *Antirhea borbonica* medicinal plant and caffeic acid reduce cerebrovascular, inflammatory and metabolic disorders aggravated by high-fat diet-induced obesity in a mouse model of stroke. *Antioxidants*, 11, 858. https://doi.org/10.3390/antiox11050858

Tureyen, K., Bowen, K., Liang, J., Dempsey, R. J., & Vemuganti, R. (2011). Exacerbated brain damage, edema and inflammation in type-2 diabetic mice subjected to focal ischemia: Focal ischemia in type-2 diabetes. *Journal of Neurochemistry*, 116, 499-507. https://doi.org/10.1111/j.1471-4159.2010.07127.x

Wang, H., Song, G., Chuang, H., Chiu, C., Abdelmaksoud, A., Ye, Y., & Zhao, L. (2018). Portrait of glial scar in neurological diseases. *International Journal of Immunopathology and Pharmacology*, 31, 205873841880140. https://doi.org/10.1177/2058738418801406

Wang, R., Wang, H., Liu, Y., Chen, D., Wang, Y., Rocha, M., Jadhav, A. P., Smith, A., Ye, Q., Gao, Y., & Zhang, W. (2022). Optimized mouse model of embolic MCAO: From cerebral blood flow to neurological outcomes. *Journal of Cerebral Blood Flow and Metabolism*, 42, 495-509. https://doi.org/10.1177/0271678X20917625

Wanrooy, B. J., Kumar, K. P., Wen, S. W., Qin, C. X., Ritchie, R. H., & Wong, C. H. Y. (2018). Distinct contributions of hyperglycemia and high-fat feeding in metabolic syndrome-induced neuroinflammation. *Journal of Neuroinflammation*, 15, 293. https://doi.org/10.1186/s12974-018-1329-8

WHO. (2021). Non communicable diseases. Available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases

Wolf, V., Abdul, Y., Li, W., & Ergul, A. (2022). Impact of diabetes and ischemic stroke on the cerebrovasculature: A female perspective. *Neurobiology of Disease*, 167, 105667. https://doi.org/10.1016/j.nbd.2022.105667

Xiang, P., Chew, W. S., Seow, W. L., Lam, B. W. S., Ong, W.-Y., & Herr, D. R. (2021). The S1P2 receptor regulates blood-brain barrier integrity and leukocyte extravasation with implications for neurodegenerative disease. *Neurochemistry International*, 146, 105018. https://doi.org/10.1016/j.neuint.2021.105018

Yang, T., Dai, Y., Chen, G., & Cui, S. (2020). Dissecting the dual role of the glial scar and scar-forming astrocytes in spinal cord injury. *Frontiers in Cellular Neuroscience*, 14, 78. https://doi.org/10.3389/fncel.2020.00078

Yeung, C.-M., Lo, A. C. Y., Cheung, A. K. H., Chung, S. S. M., Wong, D., & Chung, S. K. (2010). More severe type 2 diabetes-associated ischemic stroke injury is alleviated in aldose reductase-deficient mice. *Journal of Neuroscience Research*, 88, 2026-2034. https://doi.org/10.1002/jnr.22349
Zamanian, J. L., Xu, L., Foo, L. C., Nouri, N., Zhou, L., Giffard, R. G., & Barres, B. A. (2012). Genomic analysis of reactive astrogliosis. *The Journal of Neuroscience*, **32**, 6391–6410. https://doi.org/10.1523/JNEUROSCI.6221-11.2012

Zhang, L., Lei, Z., Guo, Z., Pei, Z., Chen, Y., Zhang, F., Cai, A., Mok, G., Lee, G., Swaminathan, V., Wang, F., Bai, Y., & Chen, G. (2020). Development of neuroregenerative gene therapy to reverse glial scar tissue back to neuron-enriched tissue. *Frontiers in Cellular Neuroscience*, **14**, 594170. https://doi.org/10.3389/fncel.2020.594170

Zhang, S. (2019). Microglial activation after ischaemic stroke. *Stroke and Vascular Neurology*, 4(2), 71–74. https://doi.org/10.1136/svn-2018-000196

Zou, J.-L., Sun, J.-H., Qiu, S., Chen, S.-H., He, F.-L., Li, J.-C., Mao, H.-Q., Liu, X.-L., Quan, D.-P., Zeng, Y.-S., & Zhu, Q.-T. (2018). Spatial distribution affects the role of CSPGs in nerve regeneration via the actin filament-mediated pathway. *Experimental Neurology*, **307**, 37–44. https://doi.org/10.1016/j.expneurol.2018.05.023

## SUPPORTING INFORMATION

Additional supporting information can be found online in the Supporting Information section at the end of this article.

**How to cite this article:** Clain, J., Couret, D., Bringart, M., Lecadieu, A., Meilhac, O., Lefebvre d'Hellencourt, C., & Diotel, N. (2024). Metabolic disorders exacerbate the formation of glial scar after stroke. *European Journal of Neuroscience*, **59**(11), 3009–3029. https://doi.org/10.1111/ejn.16325