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. 2021 Sep 4;144(8):2349-2360.
doi: 10.1093/brain/awab110.

Astrocytic glycogen accumulation drives the pathophysiology of neurodegeneration in Lafora disease

Jordi Duran  1   2 , Arnau Hervera  3   4   5   6 , Kia H Markussen  7 , Olga Varea  1 , Iliana López-Soldado  1 , Ramon C Sun  8 , Jose Antonio Del Río  3   4   5   6 , Matthew S Gentry  7 , Joan J Guinovart  1   2   9
Affiliations

Astrocytic glycogen accumulation drives the pathophysiology of neurodegeneration in Lafora disease

Jordi Duran et al. Brain. .

Abstract

The hallmark of Lafora disease, a fatal neurodegenerative disorder, is the accumulation of intracellular glycogen aggregates called Lafora bodies. Until recently, it was widely believed that brain Lafora bodies were present exclusively in neurons and thus that Lafora disease pathology derived from their accumulation in this cell population. However, recent evidence indicates that Lafora bodies are also present in astrocytes. To define the role of astrocytic Lafora bodies in Lafora disease pathology, we deleted glycogen synthase specifically from astrocytes in a mouse model of the disease (malinKO). Strikingly, blocking glycogen synthesis in astrocytes-thus impeding Lafora bodies accumulation in this cell type-prevented the increase in neurodegeneration markers, autophagy impairment, and metabolic changes characteristic of the malinKO model. Conversely, mice that over-accumulate glycogen in astrocytes showed an increase in these markers. These results unveil the deleterious consequences of the deregulation of glycogen metabolism in astrocytes and change the perspective that Lafora disease is caused solely by alterations in neurons.

Keywords: Lafora disease; epilepsy; glycogen; neurodegeneration; neuroinflammation.

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Figures

Figure 1
Figure 1
Accumulation of glycogen in the brains of 3-month-old mice. Lafora bodies are abundant in malinKO hippocampi but greatly diminished in malinKO+MGSGfap-KO hippocampi. (A) Low and high power photomicrographs illustrating the distribution of Lafora bodies after periodic acid-Schiff (PAS) staining and MGS immunostaining of the hippocampi of 3-month-old littermates from the different groups. Scale bar = 100 μm. (B) Glycogen content of total brain. Control (n = 7), malinKO (n = 7), malinKO+MGSGfap-KO (n = 6). Data are expressed as mean ± SEM. ****P < 0.0001.
Figure 2
Figure 2
MalinKO+MGSGfap-KO brains contain nLBs but not CAL. MGS immunostainings of the CA3-CA2 region of the hippocampus (top), the cortex (middle) and the cerebellum (bottom) of 3-month-old mice. Scale bar = 100 μm.
Figure 3
Figure 3
Accumulation of proteins is prevented in malinKO+MGSGfap-KO brains. Western blotting for MGS, laforin and p62 of total brain homogenates of 3-month-old mice. (A) Representative blots. (B) Quantification of the bands normalized to Revert. Data are expressed as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; n.s. = non-significant. n = 4 animals per group. Revert was used as loading control.
Figure 4
Figure 4
Analysis of brain damage in malinKO+MGSGfap-KO mice. Neuroinflammation markers are increased in the brains of old malinKO mice but normalized in malinKO+MGSGfap-KO mice. (A) GFAP and Iba1 immunostainings of hippocampi from the different groups. (B) Quantification of hippocampal area of the immunostainings. Data are expressed as mean ± SEM of percentage of positive pixels [control (n = 5), malinKO (n = 7), malinKO+MGSGfap-KO (n = 7)]. (C) Quantitative PCR analysis of genes involved in the inflammatory response. Data are expressed as mean ± SEM of 2ΔΔCt in relative units for each genotype analysed [control (n = 5), malinKO (n = 5), malinKO+MGSGfap-KO (n = 6)]. **P < 0.01; ***P < 0.001; ****P < 0.0001; n.s. = non-significant.
Figure 5
Figure 5
Accumulation of glycogen in 9A-MGSGfap mice. (A) PAS staining and MGS immunostaining of 9A-MGSGfap in consecutive serial coronal sections. (B) Glycogen content of total brain (n = 6 animals per group). Data are expressed as mean ± SEM. ****P < 0.0001. (C) Western blotting for MGS, laforin and p62 of total brain homogenates. Revert was used as loading control.
Figure 6
Figure 6
Analysis of brain damage in 9A-MGSGfap mice. Neuroinflammation markers are increased in the brains of 9A-MGSGfap mice. (A) GFAP and Iba1 immunostainings of hippocampi. (B) Quantification of the hippocampal area of the immunostainings. Data are expressed as mean ± SEM of percentage of positive pixels [control (n = 5), 9A-MGSGfap (n = 6)]. (C) Quantitative PCR analysis of genes involved in the inflammatory response. Data are expressed as mean ± SEM of 2ΔΔCt in relative units for each genotype analysed (n = 6 animals per group). **P < 0.01. ***P < 0.001. ****P < 0.0001.
Figure 7
Figure 7
Study of kainate-induced epilepsy. Eleven-month-old mice were subjected to three kainate injections (8 mg/kg every 30 min), and epileptic responses were analysed for 180 min after the first injection. (A) Percentage of mice reaching seizure Stages I to VI and kainate-induced mortality. (B) Percentage of time spent in each stage during the course of the experiment. Data are expressed as average ± SEM. n = 6 mice/group. Two-way ANOVA P-values display post hoc Bonferroni differences. (C) Number of seizures experienced per animal divided by time segments after the first, second and third kainate injections. Data are expressed as average ± SEM. n = 6 animals per group. Two-way ANOVA P-values display post hoc Bonferroni differences.
Figure 8
Figure 8
Metabolic profiles. (A) Sparse partial least squares-discriminant analysis (sPLS-DA) multivariate analysis of control (red), malinKO (blue) and malinKO+MGSGfap-KO (green) brains. (B) Heat map clustering showing the 10 most affected metabolites from sPLS-DA multivariate analysis.
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