Simple gangliosides co-localize with amyloid plaques and increase with age in a transgenic mouse model of Alzheimer’s disease

doi:10.21203/rs.3.rs-5182325/v1

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Simple gangliosides co-localize with amyloid plaques and increase with age in a transgenic mouse model of Alzheimer’s disease

https://doi.org/10.21203/rs.3.rs-5182325/v1

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Alzheimer’s disease (AD) is a progressive neurodegenerative disease accounting for two-thirds of all dementia cases, and age is the strongest risk factor. Beyond the amyloid hypothesis, lipid dysregulation is now recognized as a core component of AD pathology. Gangliosides are a class of membrane lipids of the glycosphingolipid family and are enriched in the central nervous system (CNS). Ganglioside dysregulation has been implicated in various neurodegenerative diseases, including AD, but the spatial distribution with respect to amyloid-beta (Aβ) deposition is not well understood. To address this gap, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) was employed to investigate the age-dependent expression profile of A-series ganglioside species GD1a, GM1, GM2, and GM3 in the APP/PS1 transgenic mouse model of AD that develops age-dependent amyloid-beta (Aβ) plaques. This study utilized a dual resolution approach combining whole brain imaging for comprehensive detection of ganglioside expression across neuroanatomical regions with high-resolution imaging of the cerebral cortex and hippocampus to interrogate plaque-associated ganglioside alterations. Results showed age-dependent changes in the complex gangliosides GM1 and GD1a across white and grey matter regions in both wildtype and APP/PS1 mice. Significantly higher levels of simple gangliosides GM2 and GM3 were observed in transgenic mice at 12 and 18 months compared to age-matched controls in the cortex and dentate gyrus of the hippocampus. Accumulation of GM3 co-localized with Aβ plaques in the aged APP/PS1 mice, and correlated with Hexa gene expression supporting ganglioside degradation as a mechanism for the accumulation of GM3 This work is the first to demonstrate that age-related ganglioside dysregulation is spatiotemporally associated with Aβ plaques using sophisticated MSI and reveals novel mechanistic insights underlying lipid regulation in AD.

Analytical Biochemistry

Cellular & Molecular Neuroscience

Nearly 50 million people live with dementia worldwide, with Alzheimer’s disease (AD) being the leading cause (Leng and Edison, 2020). AD is a debilitating and irreversible neurodegenerative disease and accounts for two-thirds of all dementia diagnoses (Leng and Edison, 2020). Patients with AD present with progressive memory loss and cognitive decline, and to date, there are no disease-modifying treatments available. Aging poses the greatest risk for AD, with AD prevalence doubling every 5 years past age 65 (Jorm and Jolley, 1998). The irreversible and debilitating nature of AD calls for an in-depth investigation into the pre-clinical stage prior to symptom onset to identify potential therapeutic targets to halt disease progression. Abnormal protein accumulation of beta-amyloid (Aβ) plaques is a key neuropathological hallmark of AD and in addition to neurofibrillary tangles, is required for post-mortem clinical diagnosis of AD (Knopman et al., 2021). The amyloid hypothesis, postulating that Aβ is the main cause of neurodegeneration in AD, has dominated research efforts for more than 25 years (Selkoe and Hardy, 2016). However, compelling clinical evidence of Aβ plaque accumulation in non-AD patients post-mortem (Nelson et al., 2009; Villemagne et al., 2011) and the lack of effective therapeutics to halt cognitive impairment calls for a need to better understand other aspects of brain vulnerability in AD. Lipid dysregulation is now widely accepted as a critical component of AD pathology, following the first observation of “lipoid granules” in the brain by Alois Alzheimer in 1907 (Di Paolo and Kim, 2011; Foley, 2010). Lipids constitute the bulk of the brain dry mass, are essential components of all brain cell membranes, and can dynamically adapt their composition in response to internal and external cellular environments (Hamilton et al., 2007). Disruption in lipid metabolism has been implicated with a multitude of age-related neurodegenerative diseases (Di Paolo and Kim, 2011); thus, lipids present an understudied and intriguing target to investigate in the context of AD.

Gangliosides are glycosphingolipids that are ubiquitously expressed throughout the body but are particularly enriched in the central nervous system (CNS). They are major constituents of CNS cell membranes and play a pivotal role in maintaining normal brain function (Kolter, 2012). Alterations in ganglioside expression have been implicated in aging(Caughlin et al., 2017a; Kracun et al., 1992; Segler Stahl et al., 1983), neurodegenerative diseases (Desplats et al., 2007; Dodge et al., 2015; Maglione et al., 2010; Svennerholm and Gottfries, 1994; Wu et al., 2012), and CNS injury (Caughlin et al., 2019, 2015; Ramirez et al., 2003; Whitehead et al., 2011). Gangliosides account for 80% of all glycans and more than 75% of sialic acid residues present in the brain, demonstrating their involvement in membrane organization, cellular communication, and signal transduction (Sipione et al., 2020; Sonnino and Prinetti, 2010). Structurally, gangliosides are composed of a hydrophobic sphingosine base chain embedded within the membrane, and a hydrophilic head group containing oligosaccharides and linked sialic acid(s). Thus, ganglioside species can be identified based on the composition and structure of their oligosaccharide head group and dictate unique biological functions and interactions (Kolter, 2012). A-series gangliosides consist of structurally simple species GM3 and GM2, as well as complex species GM1 and GD1a. Complex gangliosides represent the predominant form in the adult brain, while simple gangliosides are expressed in low abundance (Kolter, 2012). Importantly, the complex ganglioside GM1 exerts neuroprotective and neurotrophic effects (Chiricozzi et al., 2020); in contrast, the accumulation of GM2 and GM3 is associated with neurotoxicity and neurodegeneration (Caughlin et al., 2015; Dufresne et al., 2017). The intricate homeostatic balance of gangliosides is required for normal CNS function and thus tightly regulated through complex intracellular trafficking and metabolic pathways. Further, loss-of-function genetic mutations in ganglioside biosynthesis and degradation enzymes have been shown to be causative factors in severe neurological disorders such as Hereditary Spastic Paraplegia, Parkinson’s disease, and Tay Sachs disease (Boukhris et al., 2013; Harlalka et al., 2013; Regier et al., 2016; Schneider, 2018). However, current understandings of ganglioside alterations in AD remain descriptive and lack mechanistic insight, partly limited by molecular biology techniques compatible for spatial membrane lipid analysis (Wang and Whitehead, 2020).

Advanced age presents the greatest risk factor for AD and ganglioside dysregulation has been independently identified in both aging and AD (Kolter, 2012). Importantly, the homeostatic balance between complex and simple gangliosides may be perturbed in AD. Post-mortem studies showed elevated simple gangliosides GM2 and GM3 and decreased complex gangliosides GM1 and GD1a within the frontal cortex of dementia patients compared to healthy controls (Kracun et al., 1992). In animal models, brain region-specific accumulation of simple gangliosides was observed with aging (Caughlin et al., 2018), suggesting a pathological shift in ganglioside homeostasis during aging that is exacerbated in transgenic rats (Caughlin et al., 2018). GM2 and GM3 accumulation has been observed in the cortex of transgenic mouse models of AD (Barrier et al., 2007) and post-mortem brains from patients diagnosed with AD in the entorhinal cortex, forebrain, and surrounding cerebral blood vessels (Chan et al., 2012). Increased expression of GM2 and GM3 has also been detected in a comorbid model of Aβ pathology and stroke within the stroke-induced infarct region (Caughlin et al., 2015), demonstrating differences in vulnerability to altered lipid metabolism in the AD brain. Furthermore, recent studies have shown that ganglioside accumulation colocalizes with Aβ plaques in both post-mortem brain tissue from confirmed AD diagnosis and animal models of AD (Kaya et al., 2017b; Michno et al., 2024; Ollen-Bittle et al., 2024). This growing body of literature demonstrates that aging, neuroanatomy, and Aβ pathology all play a role in ganglioside dysregulation. A comprehensive understanding of how these temporal- and anatomical-specific ganglioside alterations influences the neurodegenerative process in AD remains to be elucidated.

Our current knowledge of ganglioside alterations during AD has been limited by approaches that are compatible for brain lipid analyses lacking neuroanatomical specificity. To overcome this challenge, we employed matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), in combination with traditional brain histology and molecular analysis of ganglioside metabolic pathways to detect and measure gangliosides directly within brain tissue. The present study used the APP/PS1 transgenic mouse model to interrogate 1) neuroanatomical regions vulnerable to ganglioside dysregulation, 2) the positional relationship between ganglioside alterations and Aβ plaque accumulation, and 3) metabolic alterations driving ganglioside perturbations. We hypothesized that ganglioside dysregulation in regions of age-dependent Aβ pathology is denoted by a shift to increased simple gangliosides in the APP/PS1 AD mouse model. Work in this study reveals novel mechanistic insights underlying the role of ganglioside dysregulation in AD pathogenesis.

2.1. Animal Model.

All procedures involving live animals were per the guidelines of the Canadian Council on Animal Care and approved by the University of Western Ontario Animal Use Committee (Protocol 2022-137). Wildtype C57BL/6J and transgenic APP/PS1 mice were bred in-house. The APP/PS1 double transgenic mice express a chimeric mouse/human amyloid precursor protein (Mo/HuAPP6905swe; APP Swedish mutation) and a mutant human presenilin 1 (PS1-dE9) on the C57BL/6J-congenic background. APP/PS1 mice expressed Aβ plaque deposition as early as 2 months withinthe cortex and 4 months within the hippocampus (Gengler et al., 2010). Both male and female APP/PS1 mice and aged-matched littermate WT controls were euthanized by carbon dioxide inhalation at 4, 8, 12, or 18 months old (Fig. 1A) to capture aging from early adulthood to old age, with n = 4 per group. Brain tissue was isolated by decapitation and fresh-frozen extraction on dry ice and stored at −80 °C until processed for MALDI MSI.

2.2. MALDI MSI.

Brain tissue was sectioned coronally on a cryostat (Thermo Fisher Scientific CryoStar NX50) at a thickness of 10 μm and thaw-mounted onto electrically conductive Indium-Tin-Oxide (ITO) slides (Hudson Surface Technology Inc.). MALDI MSI detection of gangliosides from fresh frozen brain tissue was previously optimized using 1,5-diaminonapthalene (DAN) matrix to facilitate negative ionization of gangliosides upon laser application (Fig.1B). Tissue slides were coated in a thin layer of 1,5-Diaminonapthalene (DAN) matrix (Sigma-Aldrich) by sublimation at 140 °C and incubated overnight at −20 °C for tissue rehydration and desiccated at room temperature before imaging, as previously described (Caughlin et al., 2017b). A 5-peptide Mass Standard Kit for Calibration (Sciex) was spotted adjacent to tissue sections for instrument calibration to achieve a mass tolerance of 50 ppm. MS images were acquired using a Sciex MALDI 5800 TOF/TOF instrument in the negative ion reflectron mode in the 1100-2000 m/z mass range, at 70 μm spatial resolution for whole brain imaging or 40 μm for cortex and hippocampus imaging.

2.3. Ganglioside Quantification

Neuroanatomical regions of interest (ROIs) were selected for quantification based on the mouse brain atlas by Paxinos & Franklin (Paxinos and Franklin, 2019). To assess neuroanatomical-specific ganglioside changes, coronal sections were imaged to capture the cortex and hippocampal subregions CA1, dentate gyrus molecular layer, and granular layer (Fig. 1C,D). Additional ROIs including subcortical structures (striatum, lateral septal nucleus) and white matter tracts (corpus callosum, internal capsule, fimbria) from Bregma 0.98 mm and -1.94 mm were quantified and included in the supplemental figures 1-5. MALDI MSI molecular images were analyzed using TissueView software (version 2, Sciex). A total of 2 tissue sections per brain were used to isolate discrete anatomical regions to quantify the 9 regions of interest, for a total of 128 images (64 mice x 2 sections) and 576 total datasets (64 mice x 9 ROIs). Peaks corresponding to the 18-carbon species (d18:1) for the major a-series gangliosides GM1, GM2, GM3, and GD1a, as well as the d20:1 species for GM1, were identified based on the mass-to-charge ratio, as validated by previous studies(Caughlin et al., 2018) and the Lipidmaps database (www.lipidmaps.org). Ganglioside abundance was extracted from the averaged mass spectrum for each ROI by performing area under the curve (AUC) analysis of the largest three monoisotopic peaks at the corresponding m/z for each species (Fig. 1E). Data normalization was performed by dividing the AUC of each species by the total mass spectrum AUC, expressed as percentage (%) signal intensity to reduce error produced by variability in sample preparation between group comparisons, as previously described (Caughlin et al., 2018).

2.4. Thioflavin S Staining

Following MSI, some ITO slides were washed with 100% methanol to remove all remaining DAN matrix, and the fresh-frozen tissue sections were post-fixed in 3% formaldehyde (Sigma-Aldrich) for 15 min followed by 1x 10 mM PBS for 15 min. Slides were incubated in filtered 1% aqueous Thioflavin S (Sigma-Aldrich) for 10 min and protected from light throughout. Slides were washed 5 x for 3 min in 50% ethanol, 3 x for 3 min in 75% ethanol, and 3 x 5 min in distilled water before being air dried and coverslipped with DAPI mounting medium (Sigma-Aldrich). Slides were visualized using fluorescent microscopy (Nikon Eclipse Ni-E, Nikon Qi2 fluorescent camera, NIS Elements Imaging) and images were captured using 10x and 20x objectives. CorelDraw (version 22.1.0) software was utilized for alignment and overlay of MSI and fluorescent images of the same tissue section. Briefly, high-resolution MSI images were converted to red- or blue- transparency and overlayed upon fluorescent images by aligning the tissue border and anatomical landmarks of the hippocampus. ROI selection of plaque regions and adjacent regions for ganglioside quantification were performed using the TissueView software as defined by Thioflavin S positive and negative staining, respectively.

2.5. RNA extraction

Cortex and hippocampus were dissected from frozen brain tissues and processed on ice to prevent thawing. Tissue samples (~ 50 mg) were manually homogenized in 600 μL TRIzol (Life Technologies) followed by the addition of 120 μL chloroform and vigorously mixed in 1.5 mL Eppendorf tubes (Thermo Fisher Scientific). Homogenized tissue samples were incubated at room temperature for 2-3 min then centrifuged at 12,000×g for 15 min at 4 °C for phase separation. The aqueous phase was isolated and mixed with an equal volume of isopropyl alcohol, followed by a 30-min incubation at − 20 °C for RNA precipitation. Samples were centrifuged at 12,000×g for 10 min at 4 °C and the supernatant was removed. The resulting pellet was washed twice with 75% ethanol and centrifuged at 7,500×g for 5 min at 4 °C to remove the leftover ethanol. The RNA pellet was resuspended in 20 μL RNase-free water after air drying. Following extraction, RNA concentrations were determined using a Nanodrop One spectrophotometer (Thermo Fisher Scientific). The integrity of RNA samples was monitored using A260/A280 ratio.

2.6. Quantitative real time PCR (qPCR):

cDNA was synthesized using 2 μg of RNA from each tissue sample using M-MMLV Reverse Transcriptase (Invitrogen). Target gene amplification was performed with specific forward and reverse primers designed using the NCBI primer design tool. Primer sequences are provided in Supplemental Table 1. cDNA was combined with forward and reverse primers and SsoAdvanced Universal SYBR Green Mix (Bio-Rad). Rpl13α was used as an endogenous housekeeping control with all gene expression levels normalized to this value. Comparison of gene expression levels was performed using the ΔΔCT method (Livak and Schmittgen, 2001).

2.7. Data and Statistical Analyses

All statistical analysis was performed using GraphPad Prism (version 10) software. Group comparisons were performed using Two-Way ANOVAs to assess age and genotype effects, followed by Tukey’s post-hoc test for ganglioside quantification or Šídák's post-hoc test for gene expression analysis. Statistical significance was determined with ⍺ = 0.05, and all data were presented as mean values with error bars indicating standard error of the mean (SEM). Methodology schematic were generated using BioRender (Biorender.com), and figures were created using CorelDraw (version 22.1.0).

3.1. Global age-dependent increase in complex gangliosides

We first sought to identify neuroanatomical regions of altered ganglioside expression during aging in both WT and APP/PS1 mice. To measure brain region specific changes in gangliosides, MALDI MSI was performed on coronal brain sections from mice at 4-, 8-, 12- and 18-month-old WT and APP/PS1 mice. Imaging showed that GD1a was predominantly expressed within the grey matter (Fig. 2A) and represented 0.2 to 0.6% of the total mass spectrometry signal intensity. GD1a expression showed a significant increase based on age within the cortex (Fig. 2B), hippocampal regions CA1 (Fig. 2C), and the dentate gyrus (DG) molecular layer (Fig. 2D) for both WT and APP/PS1 mice. GD1a did not change during aging within the DG granular layer in either WT or APP/PS1 mice (Fig. 2E). In the lateral septal nucleus region (LSN), GD1a expression was higher in APP/PS1 compared to WT mice independent of age, while no changes were observed in white matter regions (Supplemental Fig. 1).

GM1 displayed the highest signal intensity on the molecular image and was predominantly expressed in the cortex and white matter (Fig. 2F). Across the anatomical regions studied, GM1 represented 2-3% of the total signal at 4 m, followed by a dramatic increase to 15-25% by 18 m of age. GM1 levels showed an age-dependent increase that was consistently observed within the cortex (Fig. 2G), hippocampus (Fig. 2H-J), subcortical regions, and white matter (Supplemental Fig. 2). The signals of GM1 were comparable between WT and APP/PS1 mice throughout aging, with no significant transgene differences in any anatomical regions. GM1 d20:1 was also measured based on reports showing an increased d20:1/d18:1 ratio during normal aging in the hippocampal layers (Caughlin et al., 2017a) and its selective enrichment in the DG molecular layer allowed delineation of hippocampal subregions upon ROI selection. The d20:1 species for GD1a, GM2, and GM3 remained below levels of detection and were therefore not quantified. In this study, GM1 d20:1 expression was high in the dentate gyrus molecular layer and showed similar patterns of increased expression with aging as GM1 d18:1 (Supplemental Fig. 3). Altogether, our analyses revealed a global enrichment of the complex gangliosides during aging that is independent of genotype.

3.2. Age-dependent increase in simple gangliosides within the cortex and hippocampus of APP/PS1 mice.

An increased proportion of simple gangliosides has been previously reported with advanced age in an Aβ plaque negative rat model of AD (Caughlin et al., 2018); however, it’s likely that Aβ deposition affects the distribution of gangliosides in the brain (Kaya et al., 2017b). In this study, there was a significant age-related increase in GM2 expression within the CA1 (Fig. 2m) and the DG granular layer (Fig. 2O) of the hippocampus. Notably, both age and transgene effects in GM2 expression were observed in the cortex (Fig. 2L) and the DG molecular layer of the hippocampus (Fig. 2N). In the cortex (Fig. 2L), GM2 expression was significantly elevated at 12 m and returned to baseline by 18 m in WT mice, whereas in APP/PS1 mice GM2 was elevated at 12 m and remained elevated at 18 m compared to 4 m of age. Similar changes were observed in the DG molecular layer, except no age-dependent increase was observed in WT mice (Fig. 2N). Significant transgene effects were observed at 12 and 18 m in the cortex and DG molecular layer, with elevated GM2 levels in APP/PS1 mice compared to the age-matched WT controls. Transgene effects were not observed in other hippocampus subregions CA1 and DG granular layer, subcortical regions, and white matter regions (Supplemental Fig. 4).

A higher expression of GM3 was observed within the hippocampus (Fig. 2P). An age-dependent increase in GM3 levels was detected in grey matter regions but not the white matter, with enriched expression levels within the LSN and the hippocampus (Supplemental Fig. 5). Significant age- and transgene-related increases in GM3 expression were observed in the cortex (Fig. 2Q), DG molecular layer (Fig. 2S) and granular layer (Fig. 2T), while the CA1 of the hippocampus (Fig. 2r) only demonstrated significant age effects. In APP/PS1 mice, GM3 increased across age and became significantly elevated at 12 m and 18 m compared to 4 m in the cortex (Fig. 2Q) and DG molecular layer (Fig. 2S), and by 18 m in the DG granular layer (Fig. 2T). In contrast, GM3 levels did not change with age in WT mice in these brain regions. Similarly, GM3 was significantly elevated in APP/PS1 compared to age-matched WT controls at 12 m and 18 m in the cortex and DG molecular layer, and at 18 m in the DG granular layer (Fig. 2T). Overall, significant transgene effects were observed in the expression of simple gangliosides GM2 and GM3, where they accumulate within the cortex and dentate gyrus in APP/PS1 mice past 12 m of age.

3.3. Simple ganglioside accumulation is spatially associated with Aβ plaque deposition in APP/PS1 mice.

Evaluating regional differences using MSI showed that simple gangliosides were enriched exclusively in the cortex and dentate gyrus of the hippocampus in APP/PS1 mice. Notably, given that both the cortex and hippocampus are known to be regions that accumulate Aβ deposition, we next measured the positional relationship between Aβ plaque deposition and simple ganglioside accumulation. To do this, we performed high-resolution MSI of the cortex and hippocampus in APP/PS1 mice across age. Molecular images demonstrated that the distribution pattern of GD1a (Fig. 3A) and GM1 (Fig. 3B) remained relatively consistent from 4 to 18 m. In contrast, GM2 (Fig. 3C) and GM3 (Fig. 3D) signal was largely absent at 4 m and appeared in a more punctate-like pattern that can be observed in the cortex and hippocampus from 8 m. GM3 expression was more enriched compared to GM2 and showed a dramatic increase in both abundance and intensity from 8 m to 18 m. Notably, the punctate-like accumulation of GM2 and GM3 mirrored the spatial distribution of Aβ plaques, which were also absent at 4 m and progressively accumulate with increased age in APP/PS1 mice (Fig. 3E). Together, high-resolution MALDI MSI revealed that simple ganglioside expression was temporally and spatially associated with plaque deposition in the cortex and hippocampus of APP/PS1 mice.

3.4. GM2 and GM3 expression co-localizes with cortical and hippocampal Aβ plaques.

To further elucidate the spatial relationship between Aβ deposition and simple ganglioside accumulation across age, we performed Thioflavin S (ThioS) staining on the same tissue section following MSI. ThioS staining showed higher abundance of Aβ plaques in the APP/PS1 hippocampus at 18 m compared to 12 m as expected (Yan et al., 2009), while laser spots with 40 µm lateral spacing from MSI could be observed, proving the technical compatibility in this workflow (Fig. 4A). Overlay of MSI and ThioS fluorescent imaging revealed that both GM2 and GM3 signals were co-localized with Aβ plaques in the hippocampus of 18 m APP/PS1 mice (Fig. 4B). To validate the co-localization between simple gangliosides and Aβ plaques, we quantified gangliosides in plaque ROIs (as defined by ThioS+ labeling) as well as adjacent ROIs selected from the cortex and the hippocampus. Across aging, expression of simple gangliosides GM3 (Fig. 4C) and GM2 (Fig. 4D) were significantly enriched in plaque ROIs compared to adjacent ROIs at 18 m. Conversely, expression of the complex ganglioside GM1 (Fig. 4E) was not affected by the presence of plaques at any age. Although Aβ plaques were detectable at 8 m and their abundance increased with age in the APP/PS1 mice, the GM3/GM1 ratio became significantly elevated in plaque ROIs only at 18 m (Fig. 4F). Altogether, we observed plaque-associated enrichment of GM2 and GM3 expression in Aβ plaques compared to adjacent regions by 18 m in the cortex and hippocampus of APP/PS1 mice.

3.5. Elevated Hexa expression is correlated with GM3 accumulation in APP/PS1 mice.

Given that the current understanding of ganglioside perturbation in AD remains descriptive and lacks mechanistic insight, we next interrogated ganglioside metabolic gene expression changes underlying the observed simple ganglioside accumulation. Using the cortical and hippocampal tissue from the same animals following MSI (Fig. 5A), we examined the gene expression of ganglioside biosynthesis and degradation enzymes regulating a-series gangliosides homeostasis (Fig. 5B). In the cortex, Hexa was significantly upregulated in the 18 m APP/PS1 mice compared to the 4 m APP/PS1 mice and their age-matched WT controls (Fig. 5D). No changes were observed for the other degradative gene Glb1 (Fig. 5C), or synthetic genes B3galt4 (Fig. 5E) and B4galnt1 (Fig. 5F). Similarly in the hippocampus, Hexa was upregulated in 18 m APP/PS1 (Fig. 5H), while no changes in Glb1 (Fig. 5G) nor B3galt4 (Fig. 5H) were observed. B4galnt1 was significantly upregulated in the 18 m compared to the 4 m APP/PS1s and age-matched WT controls in the hippocampus (Fig. 5J), but not in the cortex. To determine if changes in ganglioside metabolic gene expression was correlated with altered ganglioside levels, we performed within-subject correlation between significantly altered metabolic genes with GM3 MSI quantification across both age groups. Linear regression analysis showed that Hexa was significantly correlated with GM3 levels in the cortex (Fig. 5K) and hippocampus (Fig. 5M) of APP/PS1 but not WT mice. In contrast, B4galnt1 expression was not correlated with GM3 expression for APP/PS1 and WT in the cortex (Fig. 5L) or hippocampus (Fig. 5N).

Alterations in lipid homeostasis remain understudied in AD pathogenesis due to limitations in technology compatible with studying the complexity of lipid subclasses and subspecies. Recent advancements in MSI have accelerated our understanding of the anatomical specific brain lipidome and demonstrate the role gangliosides play in brain health and disease. In the present study, we employed a novel dual resolution MALDI MSI approach to reveal the regional heterogeneity and plaque-associated ganglioside alterations in an Aβ-depositing mouse model of AD. With advanced age, we observed a global enrichment of complex gangliosides GM1 and GD1a that was independent of genotype; as well as an increase in simple gangliosides GM2 and GM3 in the cortex and hippocampus of APP/PS1 mice compared to age-matched controls. GM2 and GM3 levels were elevated in older mice and were enriched within and surrounding Aβ plaques. Concomitant with elevations in GM2 and GM3, we have shown for the first time that the gene expression of Hexa encoding the β-hexosaminidase enzyme responsible for GM2 degradation was increased in cortical and hippocampal tissue. This study also describes a novel approach combining MSI with histology and molecular biology techniques to uncover mechanistic insights driving ganglioside dysregulation in AD.

4.1. Global increase in complex gangliosides with aging

Recent MALDI MSI studies have demonstrated age-dependent and neuroanatomic-specific alterations in ganglioside expression in patients and prodromal AD models, showing a depletion of complex gangliosides and an accumulation of simple gangliosides (Caughlin et al., 2018; Ollen-Bittle et al., 2024). However, the underlying mechanism driving ganglioside imbalance remained unexplored. Given that advanced age is the greatest risk factor for developing AD, we focused on profiling ganglioside changes throughout aging from early to late adulthood. In the current study, we observed a global age-dependent increase in complex gangliosides for both WT and APP/PS1 mice (Fig. 2a-j). Between the two species, GD1a expression demonstrated a greater degree of anatomical variability, while GM1 was increased across all evaluated brain regions. The lack of transgene differences suggests that elevated GM1 levels may be a protective or compensatory response to age-related pathology. The relationship between the complex gangliosides and AD pathology might be more complex than anticipated. Kracun et al. observed a decrease in major complex gangliosides in the cortex in post-mortem dementia patients (Kracun et al., 1992), whereas Molander-Melin et al. found no changes in ganglioside levels in the frontal cortex of AD patients compared to healthy controls (Molander-Melin et al., 2005), but both studies only captured the end-stage pathology rather than the temporal progression of complex ganglioside changes within the brain. In line with our own findings, Caughlin et al. observed a significant increase in GM1 in the cortex and hippocampus in aged rats and decreased GD1a in the gray matter (Caughlin et al., 2018). In contrast with the present study, Barrier et al. reported decreased GM1 in the cortex in young transgenic mice (Barrier et al., 2007)^.The global age-dependent increase in complex gangliosides shown in this study suggests that Aβ pathology in the APP/PS1 mice does not significantly influence complex ganglioside expression.

4.2.Enhanced vulnerability to simple ganglioside accumulation in the cortex and dentate gyrus of the hippocampus

Ganglioside abundance was measured in the cortex and hippocampus due to their significant role in cognitive and memory impairment in AD, and as regions of initial plaque deposition in the APP/PS1 mice (Gengler et al., 2010). We identified a striking accumulation of simple gangliosides GM2 and GM3 across aging in APP/PS1 mice exclusively in the cortex and dentate gyrus of the hippocampus (Fig. 2k-t), whereas simple ganglioside abundance showed minimal age-dependent changes in wildtype mice. Consistent with our findings, elevated GM3 has been reported in the entorhinal cortex and forebrain in post-mortem AD brains (Chan et al., 2012). Increased simple gangliosides have been observed in the cortex, dentate gyrus, and the striatum in prodromal rat AD models (Caughlin et al., 2018) as well as in regions of ischemic injury in a comorbid model of Aβ and stroke (Caughlin et al., 2015). This suggests that simple ganglioside expression may be selectively elevated in vulnerable brain regions in disease states. Within subregions of the hippocampus, ganglioside alterations were the most apparent in the dentate gyrus, which has been previously reported in AD patients (Hirano-Sakamaki et al., 2015). The dentate gyrus is a critical brain region involved in learning and memory formation and reflects one of the few regions where neurogenesis may occur in the adult brain (Amaral et al., 2007). Preferential enrichment of GM2 and GM3 within the molecular layer may be explained by the distinct cellular architecture of the hippocampus, where the molecular layer is largely composed of dendritic projections from dentate granule cell bodies (Amaral et al., 2007). The perforant pathway acts as the main connection between the cerebral cortex and the hippocampus, terminating in the outer molecular layer, and represents the most vulnerable circuit in the cortex with respect to both aging and AD (Amaral et al., 2007). Therefore, simple ganglioside accumulation in the cortex and dentate gyrus molecular layer in APP/PS1 mice may be associated with pathological changes in the hippocampal circuitry and memory impairments in AD. Additionally, GM2 and GM3 levels in APP/PS1 mice were comparable to wildtype controls in early adulthood and became significantly elevated only at advanced age (12 and 18 m) in the cortex and the hippocampus. Ding et al. showed that brain aging occurred in a region-specific manner, with metabolic alterations in brain regions such as the cortex and hippocampus critically impacted in AD (Ding et al., 2021). Emre et al. also found that the brain lipidome is modified preferentially during aging comparable to Aβ pathology (Emre et al., 2021). Together, the regional- and genotype-specific simple ganglioside accumulation suggest that impaired ganglioside metabolism may result from the synergistic damaging effects of metabolic changes during aging and age-dependent amyloid plaque burden.

4.3. Simple gangliosides GM2 and GM3 are spatially co-localized with amyloid plaques

As extracellular Aβ plaque deposition is one of the major neuropathological hallmarks in AD postulated to drive disease progression, it becomes imperative to understand how Aβ plaque pathology influences ganglioside homeostasis with aging. The APP/PS1 mouse model demonstrates initial Aβ plaque deposition at 2 m in the neocortex and 4 m in the hippocampus (Gengler et al., 2010), providing an effective model for studying ganglioside alterations in plaque-rich environments. In APP/PS1 mice, we observed a significant elevation in GM2 and GM3 expression between 8 and 12 m that remained elevated at 18 m, compared to age-matched controls (Fig. 2). Consistent with our results, Chan et al. found that APP/PS1 mice between 9-12 m of age exhibited a striking accumulation of GM3 in the forebrain, which was also observed in the entorhinal cortex of AD patients (Chan et al., 2012). Another study found elevated GM3 in the cortex of the APPSL/PS1 KI mouse as early as 3 m, which may be due to aggressive Aβ pathology in this mouse model(Barrier et al., 2007). Although GM2 and GM3 are abundant in peripheral tissues, their expression remains low in the healthy adult mammalian brain, and elevated GM3 levels have been shown to lead to neurotoxicity and apoptosis (Prokazova et al., 2009). Further, impaired cognition and Aβ deposition both increase from 6-8 m onwards in the APP/PS1 model (Gengler et al., 2010; Radde et al., 2006), prior to the dramatic increase in simple gangliosides at 12 m observed in our study. Thus, our data suggests that 8-12 m may reflect a “critical period” during aging, marked by the onset of ganglioside dysregulation and exacerbation of other pathological changes in APP/PS1 mice. Given the temporal profile of simple ganglioside accumulation and Aβ plaque deposition in this study, further investigations should consider the assessment of simple gangliosides as a potential biomarker for significant Aβ pathology and underlying cognitive impairments.

Using high-resolution MSI, we observed that the accumulation of simple gangliosides in the cortex and hippocampus is significantly higher surrounding Aβ plaques compared to the adjacent regions, adding to the body of literature identifying lipid species implicated with Aβ plaque pathology. Indeed, Aβ pathology-associated lipid alterations including ceramides, sulfatides, phospholipids, and sphingolipids have previously been characterized in the hippocampus of transgenic mice(Carlred et al., 2016; Kaya et al., 2017a, 2017b). In this study, we found that GM2 and GM3, but not GM1, were co-localized to Aβ plaques in APP/PS1 mice with significantly higher expression in plaque regions compared to adjacent regions at 18 m of age. In support of our findings, Kaya et al. also reported plaque-associated accumulation of GM2 and GM3 in the cortex and hippocampus in the TgArcSwe mouse model, whereas GM1 was not associated with plaques (Kaya et al., 2017b). Recent MALDI MSI analysis of post-mortem AD brains reported an enrichment of GM2 and GM3 surrounding Aβ plaques, as well as GM1 which contrasts with our study (Michno et al., 2024; Ollen-Bittle et al., 2024). This incongruency contributes to the controversial role of GM1 in facilitating Aβ seeding (Kakio et al., 2002), while other studies argue that physiological conformation of GM1 in cells prevents Aβ oligomerization (Cebecauer et al., 2017). While Aβ plaques were detectable at 8 m and their abundance increased across age, elevated GM3/GM1 ratio on plaques was not observed until 18 m (Fig. 4f). Our finding that Aβ plaque deposition preceded simple ganglioside accumulation suggested a causal relationship where the local microenvironment surrounding plaques perturbs the regulatory balance between simple and complex gangliosides. Our results strongly suggest that plaque-associated simple ganglioside accumulation, rather than the depletion of complex gangliosides, may be the main contributing factor in ganglioside dysregulation in AD. Given the observed changes in simple and complex gangliosides, we next investigated the ganglioside degradation pathway as a potential underlying mechanism of lipid dysregulation.

4.4. Upregulation of ganglioside degradation as a potential driving mechanism underlying ganglioside dysregulation

Tight metabolic regulation of ganglioside homeostasis is crucial for maintaining healthy CNS function. Defects in ganglioside biosynthetic pathways result in severe epileptic syndromes, while mutations in ganglioside degradation cause lysosomal storage disorders and early-onset neurodegeneration (Sipione et al., 2020). To determine if the plaque-associated simple ganglioside accumulation reflected an underlying metabolic imbalance, we examined the gene expression of four enzymes regulating the synthesis and degradation between a-series ganglioside species. We observed upregulation of the degradative gene Hexa in cortical (Fig. 5d) and hippocampal (Fig. 5h) tissue in aged APP/PS1 mice, compared to young APP/PS1 and aged WT controls. This finding followed a similar pattern as the accumulation of simple gangliosides with aging in APP/PS1 mice only, suggesting that the synergistic effect of aging on the transgenic background may be required to promote ganglioside catabolism. The Hexa gene encodes from the α-subunit of β-Hexosaminidase A, a lysosomal enzyme that is essential for catabolizing the GM2 ganglioside into GM3. Inherited mutations in Hexa lead to Tay-Sachs disease, characterized by abnormal accumulation of GM2 gangliosides in the lysosome and early onset neurodegeneration (Mahuran, 1999). Additionally, linear regression analysis revealed a significant positive correlation between Hexa and GM3 expression in APP/PS1 mice in the cortex (Fig. 5k, R² = 0.68) and hippocampus of (Fig. 5m, R² = 0.70), suggesting that enhanced degradation rather than reduced synthesis may be a driving mechanism promoting local accumulation of simple gangliosides surrounding plaques. In support of this hypothesis, Scoyni et al. reported that Hexa expression in microglia is spatially distributed in the vicinity of Aβ deposits (Scoyni et al., 2023), suggesting that activated microglia surrounding Aβ plaques may play a role in simple ganglioside accumulation. Indeed, GM2 and GM3 accumulation mimics the distribution of activated microglia surrounding Aβ plaques that have been well-characterized in the APP/PS1 mouse model (Lee et al., 2018). Additionally, previous work from our lab has identified elevated levels of simple gangliosides GM2 and GM3 within the infarct region 3 and 7 days following experimental ischemic stroke in vivo, in line with the temporal profile of post-stroke microglia activation and tissue repair (Whitehead et al., 2011). These studies provide preliminary rationale for further interrogating ganglioside alterations, specifically in microglia.

Unexpectedly, we also observed B4galnt1 upregulation along with Hexa in the hippocampus of aged APP/PS1 mice, but not in the cortex (Fig. 5j). B4galnt1 encodes for the GM2 synthase enzyme that plays an essential role in complex ganglioside biosynthesis in the Golgi apparatus (Yamaguchi et al., 2016). The differential expression of ganglioside metabolic genes between both brain regions may originate from differing cell populations between the two regions. RNA databases (The Human Protein Atlas) show that B4galnt1 expression is enriched in excitatory and inhibitory neurons and depleted from glial cells, whereas Hexa is uniformly expressed across CNS cell types. The high proportion of excitatory pyramidal neurons in the CA1 region of the hippocampus (Graves et al., 2012) may selectively upregulate B4galnt1 expression with aging to support complex ganglioside synthesis and neuronal function and may also explain, in our study, why simple ganglioside accumulation was observed in the dentate gyrus but not the CA1 of aged APP/PS1 mice. The difference in ganglioside metabolic gene expression between brain regions demonstrates that further studies are required to examine cell-specific ganglioside alterations in AD pathogenesis. Altogether, we are the first to identify enhanced ganglioside degradation as a potential mechanism driving ganglioside dysregulation in AD and identify Hexa as a potential therapeutic target to restore ganglioside homeostasis.

4.5. Dual resolution MALDI MSI detection of gangliosides in the CNS

This study pioneered a dual resolution MALDI MSI imaging protocol for ganglioside detection across aging, while previous MSI studies either used lower resolution for whole brain detection in rodent models of AD(Caughlin et al., 2018, 2015) or high-resolution analysis of plaque-associated lipid pathology (Kaya et al., 2017a, 2017b). This experimental approach combined the advantage from whole brain imaging to comprehensively sample ganglioside expression in diverse neuroanatomical regions, as well as high-resolution imaging for a focused interrogation of plaque-associated ganglioside dysregulation within the cortex and hippocampus. Our study is the first to combine MSI, histology, and molecular biology to uncover altered regulatory mechanisms that may drive perturbations in ganglioside homeostasis. However, MALDI MSI remains a semi-quantitative and descriptive technique, and the spatial resolution of MSI employed in this study limits investigating ganglioside distribution at a single-cell level. Thus, further in vitro studies are required to elucidate the cell-specific source of ganglioside alterations and the impact of perturbed ganglioside homeostasis on disease pathophysiology. Data from this study supports the development of multiplex data acquisition, incorporating untargeted mass spectrometry imaging approaches with immunohistology and spatial transcriptomics in a digital pathology framework (Ollen-Bittle et al., 2024).

Overall, this work represents critical insight into the onset and development of ganglioside dysregulation in a transgenic mouse of AD, which may shed insight into lipid dysregulation in human AD. Additionally, we show for the first time a potential role for Hexa as a potential molecular mechanism driving ganglioside perturbation in the pathological progression of AD.

CRediT authorship contribution statement: W. Wang: Conceptualization, Investigation, Formal analysis, Visualization, Writing – original draft. S.J. Myers: Writing - review & editing. N. Ollen-Bittle: Writing - review & editing. S.N. Whitehead: Conceptualization, Supervision, Resources, Writing – review & editing, Funding acquisition.

Declaration of Competing Interest: The authors declare no competing interests.

Acknowledgements: Authors received scholarship support from Canadian Institute of Health Research to WW and NOB, Natural Sciences and Engineering Council of Canada to SJM, Natural Sciences and Engineering Council of Canada to SNW.

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The authors declare no competing interests.

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Simple gangliosides co-localize with amyloid plaques and increase with age in a transgenic mouse model of Alzheimer’s disease

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