1. Neuroscience

Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivity

  1. Florence Authier
  2. Asad Jan
  3. Islam Faress
  4. Christian Stald Skoven
  5. Iria Esperon-Abril
  6. Shagana Tharmakulasingam Balasubramaniam
  7. Kévin-Sébastien Coquelin
  8. Jens R Nyengaard
  9. Carsten Scavenius
  10. Benedetta Attianese
  11. Oscar G Sevillano-Quispe
  12. Simon Fristed Eskildsen
  13. Jesper Skovhus Thomsen
  14. Brian Hansen
  15. Daan MF van Aalten  Is a corresponding author
  1. Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Denmark
  2. Core Center for Molecular Morphology, Department of Clinical Medicine, Aarhus University, Denmark
  3. CFIN, Aarhus Hospital, Denmark
  4. Department of Biomedicine, Aarhus University, Denmark
  5. Division of Cell and Developmental Biology, School of Life Sciences, University of Dundee, United Kingdom
https://doi.org/10.7554/eLife.107170.3
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Cite this article
  1. Florence Authier
  2. Asad Jan
  3. Islam Faress
  4. Christian Stald Skoven
  5. Iria Esperon-Abril
  6. Shagana Tharmakulasingam Balasubramaniam
  7. Kévin-Sébastien Coquelin
  8. Jens R Nyengaard
  9. Carsten Scavenius
  10. Benedetta Attianese
  11. Oscar G Sevillano-Quispe
  12. Simon Fristed Eskildsen
  13. Jesper Skovhus Thomsen
  14. Brian Hansen
  15. Daan MF van Aalten
(2026)
Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivity
eLife 14:RP107170.
https://doi.org/10.7554/eLife.107170.3
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eLife Assessment

This is an important study that takes a key step towards understanding developmental disorders linked to mutations in the O-GlcNAc transferase enzyme by generating a mouse model harboring the C921Y mutation. While the mechanisms remain open, the study thoroughly examines behavioral and anatomical differences in these mice and provides convincing evidence for behavioral hyperactivity and learning/memory deficits, as well as phenotypic differences in skull and brain formation. This study will be of interest to those studying neurodevelopmental disorders and associated mechanisms.

https://doi.org/10.7554/eLife.107170.3.sa0

Abstract

Missense variants in the O-GlcNAc transferase (OGT) gene have recently been shown to segregate with a syndromic form of intellectual disability (OGT-ID), underscoring the importance of protein O-GlcNAcylation in brain function. However, the underlying pathophysiological mechanisms linking ID to potential OGT malfunction—whether developmental, neurophysiological, or both – remain unclear. Here, we present comprehensive analyses encompassing behaviour and brain architecture of a rodent model carrying the pathogenic C921Y OGT-ID variant. These mice show a range of behavioural deficits, including hyperactivity, impulsivity, and associative learning phenotypes. Structural studies, using micro-computed tomography and magnetic resonance imaging, revealed reduced skull size, microcephaly, reduced cortical thickness and hypoplastic corpus callosum. Detailed histological analyses revealed dysplastic changes in the neocortex, predominantly affecting the superficial layers of the cingulate cortex. Mechanistically, quantitative proteomic analyses revealed O-GlcNAc dyshomeostasis associated with distinct perturbed molecular pathways involved in brain development. Taken together, these data reveal neurodevelopmental defects associated with O-GlcNAc dyshomeostasis and provide a platform for dissecting mechanism and treatments of OGT-ID.

Introduction

Intellectual disability (ID) is a prevalent neurodevelopmental condition estimated to affect 1–3% of the global population and is characterised by a significant impairment in cognitive function, along with compromised adaptive and social behaviour (Tassé et al., 2016). Developmental anomalies in the human cerebral cortex, particularly the neocortex, are common causes of ID (Barkovich et al., 2012; Kurabayashi et al., 2023). A recently reported syndromic form of ID is associated with missense variants in the OGT gene, which resides on chromosome Xq13.1, and encodes the O-linked N-acetylglucosamine transferase (OGT). This enzyme facilitates the covalent attachment of O-linked b-N-acetylglucosamine (O-GlcNAc) to the hydroxyl groups of serine and threonine (Ser/Thr) residues on nuclear, cytoplasmic, and mitochondrial proteins (Torres and Hart, 1984; Wulff-Fuentes et al., 2021). O-GlcNAcylation is a dynamic and highly conserved modification governed solely by two enzymes, OGT for attachment (Gao et al., 2001; Fujiki et al., 2011) and O-GlcNAcase (OGA) for removal (Park et al., 2010). This sets O-GlcNAcylation apart from other post-translational modifications, such as phosphorylation and ubiquitination, that rely on hundreds of ‘writer’ and ‘eraser’ enzymes, associated with specific sets of ‘reader’ proteins (Levine et al., 2018; Meek et al., 2021). O-GlcNAcylation regulates cellular functions, such as transcriptional activation (Fujiki et al., 2011), gene expression (Constable et al., 2017), stress response (Dikic et al., 2009), and proteostasis (Fujiki et al., 2011), in response to physiological changes. Structural studies of OGT have demonstrated that the enzyme is composed of an N-terminal tetratricopeptide repeat (TPR) domain, involved in substrate recognition and binding of OGT interactors (Levine et al., 2018; Meek et al., 2021), and a catalytic glycosyltransferase domain. In addition to catalysing O-GlcNAcylation, the catalytic domain is involved in the proteolytic activation of the transcriptional coregulator Host Cell Factor 1 (HCF-1), itself an ID-associated protein (Capotosti et al., 2011; Lazarus et al., 2013).

OGT and OGA are notably abundant in the brain, with particularly enrichment in hippocampal formation and related structures (O’Donnell et al., 2004). Thus, O-GlcNAcylation plays a critical role in neuronal survival, development, and synaptic function. For instance, pan-neuronal knockout of OGT results in severe neurodevelopmental defects and early neurodegeneration (Lee et al., 2020; Su and Schwarz, 2017). Moreover, deletion of OGT in the dopaminergic neurons of substantia nigra or peripheral neurons in the dorsal root ganglion induces widespread apoptosis (Cole and Hart, 2001; Lagerlöf et al., 2017). At the synapse, OGT and OGA display distinct localisation patterns: OGA is absent from the post-synaptic density, whereas OGT is distributed evenly between pre- and post-synaptic compartments in excitatory synapses (Vosseller et al., 2006; Trinidad et al., 2012). In this context, synaptosome mass spectrometry (MS) data have revealed that nearly 20% of synaptic proteins, including ankyrin G, CaMKIV, and GluA2, are modified by O-GlcNAc, which dynamically regulates excitability and transmission (Vaidyanathan et al., 2017; Willems et al., 2017).

To date, 17 pathogenic missense variants in the OGT gene have been identified as causal for a newly described syndromic form of ID, termed OGT-ID, also known as O-GlcNAc transferase congenital disorder of glycosylation (OGT-CDG) (Willems et al., 2017; Pravata et al., 2019; Pravata et al., 2020a). This syndrome is frequently comorbid with neurological and psychiatric disorders such as epilepsy and autism spectrum disorder (ASD), both of which are associated with focal cortical dysplasia (FCD) (Taylor et al., 1971; Casanova et al., 2013; Omelková et al., 2023). In addition to ID and maladaptive behaviour, OGT-ID patients exhibit a plethora of muscular, facial, and neurological abnormalities, such as hypotonia, craniofacial dysmorphia, microcephaly, fifth finger clinodactyly, and developmental delay (Willems et al., 2017; Selvan et al., 2018). Missense and exon-skipping variants in OGT have been found across both functional domains (i.e. TPR and catalytic), with affected patients exhibiting similar clinical features. These observations hint towards pathogenic mechanisms whereby the OGT variants affect neurodevelopmental processes and/or brain function leading to intellectual disability. Nevertheless, understanding the potential impact of OGT-ID variants on brain development has remained challenging, primarily due to the lack of viable vertebrate models since germline knockout (KO) of Ogt in mice leads to embryonic lethality (Shafi et al., 2000).

Among OGT-ID variants, the catalytically impaired C921Y variant has been the most extensively studied. It was identified in three affected brothers born to a healthy, non-consanguineous couple in Denmark. The affected individuals exhibit developmental delay, autistic features, dysmorphic traits, osteoporosis, and seizures (Omelková et al., 2023). Functional studies have shown that the OGTC921Y variant has decreased glycosyltransferase activity, both in vitro and in mouse embryonic stem cells (mESCs). In OGTC921Y mESCs, the mutation reduces O-GlcNAcylation and decreases expression of stem cell markers Oct4, Sox2, and alkaline phosphatase (ALP; Omelková et al., 2023), suggesting that OGT plays a critical role in embryonic stem cell self-renewal and pluripotency (Omelková et al., 2023). In Drosophila melanogaster models, the OGTC921Y mutation has been shown to reduce O-GlcNAcylation during development (Czajewski et al., 2024), a defect that can be rescued by genetic or pharmacological inhibition of OGA. This mutation disrupts larval neuromuscular junction development and shortens sleep bout duration, with both effects being partially reversible through OGA inhibition. These findings suggest that certain aspects of OGT-ID pathology are developmental in origin, while others may be reversible. Although these studies indicate that early differentiation and development are affected, a vertebrate model is required to dissect the developmental and brain-wide effects of OGT-ID variants, as the precise mechanisms remain unknown.

Here, we use an OGTC921Y mouse model of OGT-ID to reveal a range of behavioural deficits, including hyperactivity, impulsivity, and associative learning phenotypes. Structural studies, using micro-computed tomography (MicroCT) and magnetic resonance imaging (MRI), revealed reduced skull size, microcephaly, reduced cortical thickness, and hypoplastic corpus callosum. Detailed histological analyses uncovered nodular cortical dysplasia, predominantly affecting the superficial layers of cingulate cortex. Mechanistically, quantitative proteomic analyses suggested perturbed regulation of distinct perturbed molecular pathways involved in brain development in the presence of O-GlcNAc dyshomeostasis. Taken together, these data reveal neurodevelopmental defects associated with O-GlcNAc dyshomeostasis and provide a platform for dissecting mechanism and treatments of OGT-ID.

Results

OGTC921Y mice display postnatal growth development delay and hyperactivity

In patients, OGT-ID variants associate with balance difficulties, ataxia, and hypotonia, suggesting possible locomotor defects in addition to ID and behavioural deficits (Pravata et al., 2020b). To investigate whether the OGTC921Y variant phenocopies such deficits in mice, we first assessed a range of behavioural traits, including locomotion, anxiety, compulsivity, learning and memory in a mouse line carrying this variant, the generation of which was recently been reported (Authier et al., 2024). As part of our overall behavioural screening, animal body weight was monitored weekly. During the initial period after weaning (3–8 weeks old), no difference in body weight was observed between OGTWT and OGTC921Y mice suggesting similar developmental trajectories between both genotypes. However, we observed statistically significant lower gain in body weight in the OGTC921Y mice from 9 to 20 weeks old compared to the WT mice (time x genotype, p = <0.0001, two-way ANOVA; Figure 1A), suggesting that OGTC921Y mice show postnatal growth development delay.

Figure 1 with 1 supplement see all
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OGTC921Y mice show postnatal growth development delay and increased spontaneous activity.

Significance is shown as *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001. Connecting line graphs are shown as mean ± SEM. (A) Body weight of male OGTWT (n=15) and OGTC921Y (n=16) mice from 3 to 20 weeks old. Two-way ANOVA (α=0.05) followed by Tukey’s column comparisons. (B) Line chart representing the cumulative locomotion index (x-axis, days) for 75 days. Two-way ANOVA (α=0.05) followed by Tukey’s column comparisons (OGTWT, n=10 housed in 5 cages; OGTC921Y, n=10 housed in 5 cages). (C) Line chart representing the cumulative locomotion index with light (6 am–6 pm) and dark (6 pm–6 am) periods in DVC cages over a longitudinal period up to 75 days (x-axis showing time in hours, 24 hr format). The arrows indicate increased nocturnal activity by OGTC921Y mice compared to WT littermates. (D) Heat maps representation of the cumulative locomotion index with light and dark periods in DVC cages for 75 days (x-axis showing time in hours over 24 hr period each day, y-axis showing days with Day 31 as the starting point on top). The arrow indicates increased nocturnal activity by OGTC921Y mice compared to WT littermates. (E) Representative tracking plot over three consecutive days of a male OGTWT and male OGTC921Y mice in the open field arena. (F) Distance travelled over 3 consecutive days of male OGTWT (n=15) and male OGTC921Y (n=16) mice in the open field arena. Two-way ANOVA (α=0.05) followed by Tukey’s column comparisons. (G) Maximal speed displayed by male OGTWT (n=15) and male OGTC921Y (n=16) mice in the open field arena. Two-way ANOVA (α=0.05) followed by Tukey’s column comparisons.

Shortly after weaning, we placed the animals in digitally ventilated cages (DVCs) to continuously monitor the patterns of spontaneous activity in a non-invasive manner (Piilgaard et al., 2023). For this purpose, we tracked animal activity longitudinally, starting at postnatal day 30 until 105 days of age (data collected over 75 consecutive days; n=10 per group, housed in five separate cages). These experiments revealed hyperactive patterns of home cage activity by the OGTC921Y mice, compared to the WT littermates, as early as day 35 (p = <0.0001, two-way ANOVA; Figure 1B). Intriguingly, this period (postnatal 9–20 weeks) also marks the stage reflecting the observed postnatal growth development delay in the OGTC921Y mice (Figure 1A). Evaluation of daily rhythms and home cage activity during light/dark periods revealed that the OGTC921Y mice exhibited frequent periods of hyperactivity during the dark phase (night time, active time for rodents), compared to the WT (Figure 1C and D). However, the resting time (light phase, day time) was similar between the genotypes (Figure 1C and D) ruling out potential disturbances in circadian rhythms, which otherwise could affect their normal day/night patterns of home cage activity.

We next investigated general locomotor activity in an open field arena. Mice were placed in open arenas and allowed to explore for 10 min on 3 consecutive days to evaluate both exploration of and habituation to an unfamiliar environment. Over the total 3-day period, OGTC921Y mice showed an increase in activity in the arena as reflected by an increase in total distance travelled (Day 1, p=0.0011; Day 2, p ≤0.0001; Day 3, p=<0.0001, two-way ANOVA) and maximum speed (Day 1, p=0.0013; Day 2, p=0.001; Day 3, p ≤0.0001, two-way ANOVA) compared to WT mice (Figure 1E–G). To assess whether this hyperactivity was due to higher anxiety levels in OGTC921Y mice, we evaluated the fraction of time spent in the periphery versus centre of the arena. Over the 3 days of testing, OGTC921Y mice demonstrated thigmotaxic behaviour and increased distance travelled in both periphery (Day 1, p=0.0004; Day 2, p ≤0.0001; Day 3, p ≤ 0.0001, two-way ANOVA) and centre areas (Day 1, p=0.014; Day 2, p=0.0012; Day 3, p=0.0193, two-way ANOVA), but no preference for the periphery of the arena compared to WT, as shown by similar time spent in the periphery (Day 1, p=0.1771; Day 2, p=0.2657; Day 3, p=0.8885, two-way ANOVA) and centre areas (Day 1, p=0.1785; Day 2, p=0.2543; Day 3, p=0.8849, two-way ANOVA) between both genotypes (Figure 1—figure supplement 1A–D). During elevated-plus maze (EPM), a test to assess elevated and open space anxiety, OGTC921Y mice covered more distance (p ≤ 0.0001, t-test) and performed a higher number of entries in the centre (p ≤ 0.0001, t-test) resulting in an increase in open/close time ratio (p=0.0063, t-test; Figure 1—figure supplement 1E–H). Similarly, OGTC921Y mice travelled more distance (0–5 min, p=0.009; 5–10 min, p ≤ 0.0001, two-way ANOVA) and displayed frequent light-dark transitions compared to WT mice during the dark-light paradigm test (0–5 min, p=0.001; 5–10 min, p=0.3374, two-way ANOVA), with no difference in time spent in the light compartment between both genotypes (0–5 min, p=0.0926; 5–10 min, p=0.0608, two-way ANOVA; Figure 1—figure supplement 1I–L). These findings potentially rule out anxiety-like behaviour in both the OGTC921Y and the WT mice.

We also assessed motor skills, including sensorimotor coordination and balance. No differences were observed in mean speed (p=0.9056, t-test) or time spent on the rotarod (p=0.814, t-test) between WT and OGTC921Y mice (Figure 2—figure supplement 1A and B). In the pole test, both OGTC921Y and WT mice were able to perform a t-turn and reach the ground with similar scores (p=0.1523, Mann-Whitney test; Figure 2—figure supplement 1C). During static rod tests, OGTC921Y mice spent more time than their WT littermates to complete the required t-turn (35 mm, p=0.0018; 28 mm, p=0.0003; 22 mm, p=0.1201; 15 mm, p=0.0005; 10 mm, p ≤ 0.0001, two-way ANOVA), although all mice reached the goal platform (Figure 2A–C). Taken together these data rule out gross defects in motor coordination and balance in the OGTC921Y animals, while revealing a degree of hyperactivity and stereotypy.

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Motor, digging, and burying activity.

Significance is shown as *p<0.05, **p<0.01, and ***p<0.001. Bar graphs are shown as mean ± SD. Student t test was used for statistics. (A) Representative image of experimental set-up for the static rods test. (B) Time to t-turn of male OGTWT (n=15) and OGTC921Y (n=16) during the static rods test. (C) Delta time defined as (total time – time to turn) of male OGTWT (n=15) and OGTC921Y (n=16) during the static rods test. (D) Representative images of the marble test at 0 min (T0) and 30 min (T30). (E) Number of buried marbles by male OGTWT (n=15) and OGTC921Y (n=16) during the marble test. (F) Representative image of the litter burrowing test. (G) Percentage of litter removed by male OGTWT (n=15) and OGTC921Y (n=16) during the litter burrowing test. (H) Number of digging events by male OGTWT (n=15) and OGTC921Y (n=16) during 3 min observation. (I) Time spent digging by male OGTWT (n=15) and OGTC921Y (n=16) during 3 min observation. (J) Number of rearing events by male OGTWT (n=15) and OGTC921Y (n=16) during 3 min observation. (K) Time spent rearing by male OGTWT (n=15) and OGTC921Y (n=16) during 3 min observation.

OGTC921Y mice exhibit reduced digging behaviour

In order to further characterise the stereotypic phenotypes that could reflect ASD features observed in some OGT-ID patients (Pravata et al., 2020b), we assessed compulsive and repetitive behaviour. The OGTC921Y showed a reduced number of buried marbles in a marble burying test (p=0.0002, t-test; Figure 2D and E) and a reduction in litter displacement in a burrowing test (p=0.0107, t-test; Figure 2F and G) compared to WT mice. To investigate whether the reduction in burying/burrowing activity was due to reduced digging behaviour, WT and OGTC921Y were individually placed in cages containing 5 cm deep litter. The number of digging events and time spent digging during 3 min were measured. The OGTC921Y mice exhibit both reduced number of digging events (p=0.0004, t-test) and digging time (p=0.0003, t-test) compared to WT mice (Figure 2H and I). These findings were not due to lower activity of the OGTC921Y mice, but rather to an increase in rearing events (p=0.1978, t-test) and time spent rearing (p=0.0317, t-test) compared to WT mice (Figure 2J and K). The number of self-grooming events (p=0.7421, t-test) and time spent self-grooming (p=0.3785, t-test) were similar between the two genotypes (Figure 2—figure supplement 1D and E). In addition, OGTC921Y mice removed the same amount of material as WT mice during the nesting test (p=0.9774, t-test; Figure 2—figure supplement 1F).

OGTC921Y mice manifest features of impulsive behaviour and enhanced long-term memory recall

We next investigated the effect of the OGTC921Y variant on memory. First, we evaluated spontaneous alternation using a T-maze test as a measure of working spatial memory. The mice were placed in a T-shape maze and allowed to choose freely between right (R) and left (L) arms for seven successive trials (Figure 3A). Both OGTC921Y and WT mice show similar percentage of spontaneous alternation (p=0.2347, t-test; Figure 3B), suggesting intact short-term spatial working memory in the OGTC921Y mice. Nevertheless, the OGTC921Y mice display a significantly reduced latency of choice (p=0.0175, Mann-Whitney test) compared to WT mice (Figure 3C), suggesting possible impulsive behaviour.

Figure 3
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OGTC921Y show impulsivity, enhanced long-term memory and delayed aversive associated learning.

Significance is shown as *p<0.05, **p<0.01, and ***p<0.001. Bar graphs are shown as mean ± SD. (A) Schematic of the T-maze paradigm. Mice are free to explore both arms for seven additional trials. Each choice and latency were recorded. (B) Percentage of correct alternation (L-R/R-L sequences) of OGTWT (n=15) and OGTC921Y (n=16) during the T-maze test. Student t test was used for statistics. (C) Latency of arm entry of OGTWT (n=15) and OGTC921Y (n=16) during the T-maze test. Student t test was used for statistics. (D) Representative image of the Novel Object Recognition (NOR) test. During the familiarisation phase, mice are free to explore an arena with two identical objects. During the test phase, mice were free to explore the same arena where one of the familiar objects has been replaced by a novel object to assess short (90 min) and long (24 hr) memory. (E) Discrimination index of OGTWT (n=15) and OGTC921Y (n=16) during the short-term (90 min) NOR test. Student t test was used for statistics. (F) Discrimination index of OGTWT (n=15) and OGTC921Y (n=16) during the long-term (24 hr) NOR test. Student t test was used for statistics. (G) Diagram showing the behavioural paradigm (top), tone, conditioned stimulus (CS), trace period, and unconditioned stimulus, foot shock (US) lengths (bottom). (H) Freezing behaviour of OGTWT and OGTC921Y (n=9 per group) during the acquisition session of the aversive conditioning. ITI, Intertrial interval. Two-way ANOVA time x genotype interaction p<0.0001, F(11,176) = 5.572. (I) Locomotor activity of OGTWT and OGTC921Y (n=9 per group) evoked by the US. The data represent the 3 s bin following the foot shock. Two-way ANOVA time x genotype interaction p=0.3323, F(3,48) = 1.166. (J) Freezing behaviour of OGTWT and OGTC921Y (n=9 per group) in the recall session where the CS were presented without US. The trace period refers to the 25 s following the CS presentation. Two-way ANOVA time x genotype interaction p=0.5337, F(11,176) = 0.9082.

We also investigated novelty-associated memory using the Novel Object Recognition (NOR) paradigm. We used two different sets of objects to assess both short- (90 min) and long-term (24 hr) memory. During the familiarisation phase, the mice were placed in an open field arena with two identical objects for 10 min. After 90 min or 24 hr, mice were placed in the same arena containing one familiar object and one novel object (Figure 3D). Time spent exploring each object was recorded allowing 20 s total exploration of both objects. Discrimination indexes were approached by calculating (tnovel – tfamiliar)/ttotal. After a 90 min interval, OGTC921Y mice showed a similar discrimination index as WT mice (p=0.1482, t-test), suggesting normal short-term memory function in this assay (Figure 3E). However, while both WT and OGTC921Y show discrimination indices greater than 0.2 after 24 hr, OGTC921Y mice showed significantly greater discrimination index compared to WT mice (p=0.0434, t-test), potentially indicating enhanced long-term memory recall (Figure 3F).

OGTC921Y mice exhibit impaired plasticity during associative learning

To assess learning and memory function, we subjected OGTC921Y mice and WT littermates to aversive Pavlovian trace conditioning – an established hippocampus- and cortex-dependent learning and memory paradigm where mice learn to associate a neutral tone with an aversive foot shock in a non-contiguous manner. Learning involves the presentation of a tone as the conditioned stimulus (CS), followed by a trace period, after which a foot shock is delivered as the unconditioned stimulus (US; Figure 3G). We used freezing, defined as the complete cessation of movement (except for breathing), as the conditioned response (CR) and a surrogate measure of short-term adaptation and aversive learning. Freezing behaviour was monitored during the acquisition phase and again 24 hr later during a recall session (Figure 3G). We observed that OGTC921Y mice exhibited significant learning deficits, as indicated by a delay in freezing behaviour compared to WT littermates (time x genotype, p ≤ 0.0001, two-way ANOVA; Figure 3H). This learning deficit cannot be attributed to somatosensory anomalies, as both genotypes displayed comparable responses to the US, as indicated by locomotor activity evoked by the foot shock (time x genotype, p=0.3323, two-way ANOVA; Figure 3I). Furthermore, mutant mice reached the same CR levels as WT mice by the fourth CS-tone presentation (Figure 3H), suggesting unimpaired auditory function. During the 24 hr recall, there were no differences in freezing behaviour in OGTC921Y mice compared to WT mice (time x genotype, p=0.5337, two-way ANOVA; Figure 3J), suggesting an impaired plasticity during the acquisition phase. Taken together, these data suggest that OGTC921Y exhibit impaired plasticity during associative learning.

OGTC921Y mice exhibit reduced skull size and shape deformation

OGT-ID is often associated with microcephaly or craniofacial deformities, which were also recapitulated in our initial report using a small cohort (n<5) of 2-month-old OGTC921Y mice (Authier et al., 2024). Here we aimed for a comprehensive skull shape analysis using MicroCT in larger cohorts of older (5 month) mice (WT, n=14; OGTC921Y, n=16). Average skull shapes were superimposed for OGTWT and OGTC921Y mice and skull shape differences between the two groups were analysed. The OGTC921Y skulls were smaller in both the anterior and posterior areas, whereas the top of the skull appeared more curved compared to the WT skulls (Figure 4A). We performed similar analyses on the previously reported MicroCT data collected from 2-month-old animals (Authier et al., 2024) to detect possible temporal aspects to these defects. The 2-month-old OGTC921Y mice show similar but more prominent shape differences than the 5-month-old OGTC921Y mice, suggesting an age-dependent convergence of skull shapes (Figure 4A). Next, surface landmarks were used to perform principal component analysis (PCA) allowing comparison of skull shape independently of size differences (Figure 4—figure supplement 1A). Skulls from 5-month-old OGTWT and OGTC921Y mice were separated along the first principal component (PC1) with a higher dispersion in the OGTC921Y group suggesting heterogeneity in skull shape deformation phenotype penetrance. More than 63% of the OGTC921Y skulls display a positive PC1 value, whereas 93% of the WT skulls display a negative PC1 value. The skull of the OGTC921Y mice has a shorter and rounder shape than the average WT mice (Figure 4B). We performed Euclidean Distance Matrix Analysis (EDMA) using 45 relevant landmarks from the Richtsmeier laboratory resource (https://getahead.la.psu.edu) to identify the key regions contributing to the shape differences (Figure 4—figure supplement 1A). At 5 months of age, 55% of the distances were at least 2% shorter in the OGTC921Y skulls than in WT skulls, with the largest differences affecting the cranial base length (Figure 4—figure supplement 1B). Similarly, in skulls from 2-month-old animals, distances that are shorter than 5% in the OGTC921Y skulls were predominantly located at the base of the skull (Figure 4—figure supplement 1B). The main bone contributing to the cranial base length is the sphenoid, and shortening in the sphenoid bone determines the curvature of the cranial vault postnatally (Adasooriya et al., 2023). This may indicate that defects in the postnatal development of the skull could cause the observed phenotype in the OGTC921Y mice. Similar skull shape deformities have been reported in mouse models of Fragile X syndrome (Heulens et al., 2013) and skeletal defect syndromes, such as osteogenesis imperfecta (Husain et al., 2024).

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Micro-computed tomography of OGT-ID mouse skulls indicates a reduced endocast volume and shorter skull length.

Significance is shown as *p<0.05, **p<0.01, and ***p<0.001. Bar graphs are shown as mean ± SD. (A) Heatmaps obtained of the average OGTC921Y skull (n=16) to the average OGTWT skull (n=14). Red and blue regions indicate that the average OGTC921Y skull is smaller or larger respectively than the average OGTWT in those areas. (B) PCA biplot of PC1 and PC2 of the surface landmarks of 20 weeks old male OGTWT and OGTC921Y skulls (top). Percentages in the axis indicate the explained variance. Deformations in PC1 showing shape differences across this axis are shown (bottom). (C) Volume of the skulls of 8 weeks and 20 weeks old male OGTWT and OGTC921Y mice. Student t test was used for statistics. (D) Volume of the extracted endocranial cavity of 8 weeks and 20 weeks old male OGTWT and OGTC921Y mice. Student t test was used for statistics.

At both ages (i.e. 2 and 5 months old), the reduction in cranial base distances and overall reduction in skull size in the OGTC921Y mice were obvious (2 months, p=0.0016; 5 months, p=0.0101, two-way ANOVA; Figure 4C). From 3D reconstruction of the skulls, we determined the endocranial cavity volume as an indirect measure of the brain volume. At both ages tested, OGTC921Y mice had a smaller internal cranial volume compared to their WT littermates (2 months, p=0.013; 5 months, p<0.0001, two-way ANOVA; Figure 4D), suggesting a smaller brain volume. Taken together, these findings indicate that the OGTC921Y mice exhibit antero-posterior skull growth defects leading to reduced skull size and shape deformation, suggesting dysmorphic features and reduced brain size.

OGTC921Y display reduced cortical thickness and hypoplastic changes in brain structures

Neocortex hypoplasia, changes in cortical thickness and white matter integrity defects have been reported in mouse models of neurodevelopment disorders including ASD (Fenlon et al., 2015), CHARGE (Donovan et al., 2023), and Rett (Allemang-Grand et al., 2017) syndromes. To assess whether the reduction in brain size is general or localised to specific brain regions, we employed MRI. Specifically, we performed volumetry analysis of anatomically well-defined brain regions based on high-resolution MRIs of 50 µm isotropic resolution, covering both the grey and white matter. The OGTC921Y mice showed a reduced total brain volume compared to WT (Figure 5A). Regional volumetric analyses showed a reduction in absolute volumes in most brain regions (Figure 5—figure supplement 1). When expressed as regional relative volume (RRV) variation, the OGTC921Y mice showed significantly reduced (group median) volumes of several brain regions including the frontal lobe of the cerebral cortex, corpus callosum, basal forebrain, globus pallidus, internal capsule, and stria terminalis (Figure 5C, Figure 5—figure supplement 2). In contrast, RRV was increased in the lateral septum, medulla, hippocampus, and hypothalamus regions of the OGTC921Y mice compared to WT mice (Figure 5C, Figure 5—figure supplement 2). Cortical thickness analysis revealed significantly thinner cortex bilaterally in posterior regions in the OGTC921Y mice compared to WT mice, with differences on the order of 100 µm (Figure 5B).

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OGTC921Y mice show changes in regional brain volume and reduced cortical thickness.

Volumetry and cortical thickness from high resolution T1-weighted magnetic resonance (MR) images. (A) Total brain volume of 20 weeks old male OGTWT and OGTC921Y mice. Groupwise total brain volume where each dot represents one subject. The horizontal lines correspond to group extrema and median. Asterisks (*) mark significance (p<0.05) based on permutation tests (1 M permutations) of either the mean (green asterisk) or median (red asterisk) of the two groups. (B) Heatmaps of group differences in cortical thickness between male OGTWT and OGTC921Y mice. Maps are effect sizes (top row), p-values of significant differences both uncorrected for multiple comparisons (middle row) and corrected with family-wise error (FWE). N=15 per genotype. One mutant was not perfused correctly and removed from analysis. (C) Regional brain volumes represented as percentage of whole brain volume of male OGTWT and OGTC921Y mice. Asterisks (*) indicate uncorrected significance (p<0.05), based on permutation tests (100 k permutations for each region). Pound symbols (#) indicate significance below >α (0.05) divided by total number regions tested (40) for mean (green) and median (red), respectively. Section signs (§) indicate significance (p<0.05) with p-values adjusted for false discovery rate (Benjamini-Hochsberg, BH). Y-axes are scaled to individual ROIs to highlight group variation and difference.

We next assessed potential local brain microstructural defects using diffusion kurtosis imaging (DKI; Jensen et al., 2005; Hansen et al., 2013; Hansen et al., 2016; Hansen and Jespersen, 2017), which provides sensitive indices of water mobility (mean diffusivity, MD) and diffusion directionality (fractional anisotropy, FA) in tissue as well as markers of tissue complexity (mean kurtosis, MK). Collectively, the MRI markers employed here are known to be sensitive to subtle tissue alterations in both rodent (Qvist et al., 2018; Ardalan et al., 2022; Khan et al., 2016; Chuhutin et al., 2020; Joseph et al., 2023; Lindhardt et al., 2024) and human brain (Vukovic et al., 2021; Tietze et al., 2015; Lohmeier et al., 2024; Thaler et al., 2021). We observed no difference in these DKI metrics between OGTC921Y and WT mice in any of the 20 automatically segmented regions including neocortex (Figure 5—figure supplements 3–6). Taking together, these MRI data suggest that OGTC921Y show preserved brain microstructure at the resolution (150 × 150 × 250 µm) of the DKI experiments yet reduced cortical thickness.

OGTC921Y mice exhibit dysmorphic features in superficial cortical layers, predominantly affecting the cingulate

Previous studies indicate that congenital dysplasia in cortical organisation manifests as a range of malformations including disrupted cortical laminar organisation, neuronal heterotopia in the subcortical white matter, misplaced neurons in cortical lamina I, clustering of neurons in the grey matter, and the presence of dysmorphic neurons (Fauser et al., 2006; Tassi et al., 2002; Blümcke et al., 2011). To evaluate cortical cytoarchitecture at the microscopic level and for detecting any features suggestive of FCD in OGTC921Y mice, we subjected the brain sections to histological analyses using H&E (for cells), cresyl violet (for neurons), and luxol fast (for white matter) staining (Figure 6, Figure 6—figure supplement 1). In the H&E analyses, we observed an overall normal six-layered cortical organisation across the regions involved in primary sensorimotor modalities, including the somatomotor cortex M1/M2, primary somatosensory cortex S1/S2, auditory cortex and primary visual cortex V1 (Figure 6—figure supplements 1 and 2). Intriguingly, part of the cingulate (retrosplenial Area 29/Area 30, according to Paxinos and Franklin) found within the paramedian portion (sagittal section, interaural 0.36) showed FCD in five out of six animals in the OGTC921Y cohort (Figure 6A–C, compared to WT). The most conspicuous microscopic finding suggestive of FCD was seen in the form of pseudosulcus formation in the cingulate, such that the superficial cortical layers (I–III) appeared to be displaced inwards (Figure 6B–C, black arrow), and resembled polymicrogyria similar to those observed in other congenital brain malformations (Paprocka et al., 2021; Squier and Jansen, 2014). In two extreme cases, nodular arrangements of cells within the superficial layers (II/III bordering IV), with a central halo containing loosely arranged eosinophilic tissue, were observed (Figure 6B–C, yellow arrow). Having ruled out gross structural alterations (except in the cingulate cortex), we next assessed cortical cell density, which would reveal hypo or hyperproliferative neurodevelopmental anomalies. Total cell density analyses in the neocortical regions (H&E stained serial sections, reflecting both neuronal and non-neuronal cells) did not indicate drastic differences between the two groups in the major cortical regions examined (Figure 6D). Staining analyses using cresyl violet indicated that the nodular collections in the layers II/III bordering IV were predominantly neuronal cell bodies (Figure 6E). In luxol fast-stained sections, these malformations contained collections of ectopic white matter, which populated the centre of nodular malformations (Figure 6F) and/or found as patchy deposits in the vicinity of superficial layers (II–IV; Figure 6C). To further establish the cell identity in the cortical malformations, we performed immunofluorescence analyses using neuronal nuclei marker (NeuN) and astroglial marker glial acidic fibrillary protein (GFAP). These analyses further corroborated the notion that the foci of FDC in the cingulate of OGTC921Y mice were predominantly populated by neuronal cells and were devoid of astrocytes, which otherwise would indicate reactive astrogliosis seen in states of brain trauma (Figure 6G–H, compare WT in Figure 6G to OGTC921Y in Figure 6H). Furthermore, normal localisation of astroglial cells in the subcortical white matter was evident in the WT and OGTC921Y cohorts (Figure 6G–H, merged images in the panels on right). In parallel, multiplex IHC analyses confirmed that the nodular cortical malformations predominantly affected layers II-V, as indicated by the distribution of neuronal markers Reelin and POU class 3 homeobox 2 (POU3F2), and were populated by neurons and oligodendrocytes in the vicinity (Figure 6—figure supplement 3). Taken in conjunction with the MRI (reduced cortical thickness), the cortical dysplasia in revealed by the histology analyses suggest a neurodevelopmental component to OGT-ID affecting the cortical superficial layers, which in OGTC921Y mice predominantly affects the cingulate.

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Pseudosulcus formation, cortical dysplasia, and ectopic white matter in the cingulate cortex of OGTC921Y mice.

(A–B) Representative low magnification (10 X) sagittal views of WT (in A) and OGTC921Y mice (in B), showing cortical malformations in the cingulate cortex of the latter by H&E staining. The black arrow points to instances of pseudosulcus formation and the yellow arrow points to instances of cortical dysplasia observed in the layers II–IV (scale bar = 500 µm). (C) Representative high-magnification (×40) views extracted from the insets in A except one marked with *, which is depicting nodular arrangement of cells in a brain section from a different OGTC921Y animal (scale bar = 100 µm). (D) Regional cell density assessed in ×10 views (H&E staining) of two-serial sections from WT and OGTC921Y mice. Error bars indicate mean ± SEM (n=6/group; Mann-Whitney test, none significant). Regions examined include: (coronal sections) primary motor cortex M1/M2, primary somatosensory cortex S1/S2, auditory cortex (A); (sagittal sections) visual cortex V1 and cingulate cortex (C). Also see Figure 6—figure supplement 1 depicting coordinates and region demarcations (dashed rectangles) used in the cell density analyses. (E–F) Representative low-magnification (×10) sagittal views showing cresyl violet staining for neuronal cell bodies (in E) and myelin staining by luxol fast (in F). Notice the instances of ectopic white matter (red arrows) in the cingulate cortex of OGTC921Y mice (scale bar = 200 µm) in 6 F.

Quantitative proteomics analyses revealed distinctly perturbed molecular pathways in the prefrontal cortex of the OGTC921Y mice

In order to decipher the molecular phenotypes that could be associated with the cortical defects in the OGT-ID mutant strain, we performed proteome analysis on the prefrontal cortex (PFC) of male OGTC921Y and WT mice using label-free quantification. A total of 5488 proteins were identified with a 1% false discovery rate which we then ranked as the top 50 most affected (and potentially revealing) factors. This ranking was based on defined cut-off criteria for both the up-regulated (p-value ≤0.05; log-2 fold change ≥1.45) and down-regulated proteins (p-value ≤0.05, log-2 fold change ≤–1.33). Then we performed pathways enrichment and downstream analyses using the built-in tools of the STRING database (Figure 7A and B). To begin with, the expression of OGA was significantly down-regulated in the cortex of OGTC921Y (Figure 7B) in the MS analyses, as well as in western blotting analyses of the cortex (p=0.0223, t-test; Figure 7—figure supplement 1A and C) as we have reported previously (Authier et al., 2024). Although no significant changes in the expression of OGT were observed in the OGTC921Y cortex (p=0.788, t-test; Figure 7—figure supplement 1A and D), there was a significant increase in the OGT/OGA protein ratio in OGTC921Y mice (p<0.0001, t-test; Figure 7—figure supplement 1E), which is driven by the reduction in OGA levels to compensate for reduced OGT activity. Despite this compensatory mechanism, global O-GlcNAcylation of proteins in the brain was drastically impaired in OGTC921Y brain compared to WT (p=0.0018, t-test; Figure 7—figure supplement 1O and Q). The perturbed regulation of Ogt/Oga ratio (Oga mRNA, p=0.0087; Ogt mRNA, p=0.0894; Ogt/Oga ratio, p<0.0001, t-test) was further confirmed at the transcriptional level by RT-PCR (Figure 7—figure supplement 2A–C). Of note, similar O-GlcNAc dyshomeostasis at protein/mRNA levels was observed in other brain regions analysed except for OGT protein levels that were found reduced in both hippocampus and cerebellum (Figure 7—figure supplements 1 and 2), suggesting brain region specific effect of the OGTC921Y mutation. In the PFC region, gene ontology analyses in the STRING database pointed to significant upregulation in the pathways regulating cellular processes (GO:0009987), cellular metabolic pathways (GO:0044237), nervous system development (GO:0007399), protein catabolic process (GO:0030163), and lysosomal transport (GO:0007041; Figure 7C). Among the top up-regulated proteins identified in our dataset (Figure 7A), 35 proteins belong to neurodevelopmental pathways, including proteins involved in neuronal migration (PLXND1, FAT3, ASTN2, NEUROD1), neurogenesis (NEUROD1, RBBP5, RBBP6), and synaptic function (CLCN3, SORCS3, AP3B1).

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Quantitative proteomics analyses revealed distinctly perturbed molecular pathways in the prefrontal cortex of the OGTC921Y mice.

(A) List of top 50 proteins up-regulated (cut-off criteria p value 0.05, log-2 change 1.45). (B) List of top 50 proteins down-regulated (cut-off criteria p value 0.05, log-2 change –1.33). (C) Up-regulated biological pathways enrichment in the STRING database. (D) Down-regulated biological pathways enrichment in the STRING database.

Intriguingly, we also identified significant downregulation in the pathways regulating small molecule metabolic process (GO: 0044281), carbohydrate derivative biosynthetic process (GO: 1901137), cellular respiration (GO: 0045333), ATP metabolic process (GO: 00046034), and mitochondrial acetyl-CoA biosynthetic process from pyruvate (GO:0061732; Figure 7D). Moreover, the perturbed proteomic signatures in the PFC corresponded to distinct Monarch enrichment profiles (Putman et al., 2024) in the STRING database including abnormal CNS myelination (HP:0011400), agenesis of corpus callosum (HP: 0001274), upper motor neuron dysfunction (HP: 0002493), and abnormal muscle physiology and function (HP: 0011804; HP: 0003808; HP: 0001252; HP: 0001319; HP 0003394; Figure 7—figure supplement 3A and B).

Taken together, these data suggest that perturbations in protein O-GlcNAcylation in the brain of OGTC921Y are associated with distinct alterations in molecular pathways that potentially impact brain development.

Discussion

Although several OGT variants linked to ID have been reported, the mechanisms underlying the disorder remain unknown. Potential mechanisms that have been proposed (Pravata et al., 2020b) include loss of O-GlcNAcylation on OGT substrates important for brain function and development (Pravata et al., 2020b; Authier et al., 2024), OGT aggregation due to reduced OGT stability (Pravata et al., 2020b), impaired OGT interactome (Mayfield et al., 2024), misprocessing of HCF115, or loss of OGA (Pravata et al., 2019; Pravata et al., 2020a; Authier et al., 2024), a common feature observed in models of OGT-ID. Lastly, O-GlcNAc dyshomeostasis has been recently suggested as a common mechanism in OGT-ID variants and has been proposed as a biomarker to identify new pathogenic variants using a stem cell reporter line (Yuan et al., 2025). Furthermore, these hypotheses are not mutually exclusive and can individually or in combination account for the cognitive dysfunction due to impaired brain development, defects in synaptogenesis/synaptic pruning and/or neural transmission impairment . Vertebrate models are a key step towards deciphering the mechanisms linked to the disease, and here we have described a detailed characterisation of a mouse model of one OGT-ID variant (OGTC921Y).

The OGTC921Y variant is found in a Danish family with three affected male siblings that inherited the variant through their affected mother. The male siblings exhibit dysmorphic features, ID with poor language skills and late onset epilepsy. Autistic features including repetitive mannerisms and hyperactivity have also been reported (Omelková et al., 2023). Mild hyperactivity has also been reported in a patient carrying another OGT-ID variant (Pravata et al., 2020a). The OGTC921Y mice recapitulate features of impaired cognitive function, impulsive behaviour, and increased spontaneous activity (or hyperactivity) both in their home cage and in the open field arena. These phenotypes (hyperactivity and impulsivity) are often observed in mouse models recapitulating human ID and autism disorders. For instance, Fmr1Ko mice exhibit hyperactivity in open field assays and increased exploratory behaviour as seen by an increased number of light-dark transitions in the dark-light paradigm similarly to our observations in the OGTC921Y mice (Ding et al., 2014; Peier et al., 2000; Huynh et al., 2015). Moreover, hyperactivity and impulsivity behaviours present in a haploinsufficiency mouse model of Kdm6b were rescued with methylphenidate, a neurostimulant used to alleviate attention deficit and hyperactivity in individuals with ADHD (Gao et al., 2022). In addition, the stereotypy and increased rearing activity observed in the OGTC921Y mice suggest locomotor compulsive behaviour similar to that reported in the individuals carrying the C921Y variant (Omelková et al., 2023). We have observed that, unlike the WT mice, the locomotor activity of the OGTC921Y mice remained unaffected during repeated measurements in the open field test, which could suggest an impairment in spatial habituation learning. Interestingly, defects in habituation learning were also observed in Drosophila models carrying OGT-ID variants during a light-off jump habituation test (Fenckova et al., 2022). As habituation corresponds to the simplest form of learning (Rankin et al., 2009), these data hint towards some learning and memory defects in OGTC921Y mice. This is further indicated by a delay in freezing behaviour during acquisition compared to WT littermates during the aversive Pavlovian paradigm, a well-established hippocampus- and cortex-dependent learning and memory.

Reduction of brain size has been reported in OGT-ID patients, including microcephaly and brain atrophy (Pravata et al., 2020b). In the present study, both the shape and morphology of the skulls of the OGTC921Y mice were affected. The morphological alteration of the skulls reduced the endocast volume (as an estimate of brain volume) significantly in both 2-month-old and 5-month-old OGTC921Y mice compared to their WT littermates. MRI brain structural analyses indicate that redistribution of regional volumes rather than overall reduction underpins the lower total brain volume in the OGTC921Y mice. The frontal lobes of the cerebral cortex were prominently affected and associated with bilateral reduced cortical thickness suggesting overall reduction of cortical grey matter. Reduced brain volume, in particular the PFC region, has also been associated with several neurodevelopment disorders in humans including ADHD (Spencer et al., 2006; Kolk and Rakic, 2022) and associated rodent models (Russell et al., 2005). Moreover, reduced brain volume and grey matter density in cerebellum and cortical regions are observed in adolescents with ASD associated with intellectual deficits (Spencer et al., 2006).

While the MRI data suggest an overall reduction in the size of the PFC, histological analyses revealed FCD and pseudosulci formation in areas of the cingulate (retrosplenial) cortex in the OGTC921Y mice with patchy distribution of ectopic white matter in the vicinity of these cortical malformations. These features are reminiscent of cortical polymicrogyria seen in some types of CDG disorders such as muscular dystrophy-dystroglycanopathy syndromes (Paprocka et al., 2021; Squier and Jansen, 2014), and in some inborn errors of metabolism characterised by defective neural migration (Schiller et al., 2020). Given that OGTC921Y mice exhibit considerable reduction in cortical protein O-GlcNAcylation, it is plausible to postulate that these forms of cortical dysplasia (pseudosulci) arise as neurodevelopmental sequelae to the perturbed O-GlcNAcome. FCD has been linked to cognitive impairment in certain X-linked intellectual disabilities, such as Fragile X syndrome (Reynolds et al., 2020). FCD arises from localised malformations in the cortex caused by disruptions in neuronal proliferation, differentiation, and migration during corticogenesis (Raymond et al., 1995; Barkovich et al., 1996; Barkovich et al., 2005). However, some studies suggest that similar disruptions in the organisation of cortical layers may also arise due to disorders of post-migrational development of neural progenitors and not solely due to defects in proliferation or migration (Judkins et al., 2011). Therefore, it remains to be determined whether the features of cortical malformation (microcephaly and disturbed cytoarchitecture in cingulate) in the OGTC921Y mice pertain to these categories. Behavioural and neuroimaging studies indicate that distinct regions within the cingulate participate in complex cognitive tasks involving affective response and decision making (Leech and Sharp, 2014; Kolling et al., 2016). Meta-analyses of neuroimaging studies in human subjects with psychiatric disease (major depressive disorder, bipolar disorder, schizophrenia, anxiety, and addiction) purport grey matter loss in the dorsal anterior cingulate as a frequent finding (Goodkind et al., 2015; Opel et al., 2020). Taken together, these suggest a link between the cortical structure defects and the behavioural deficits observed in the OGTC921Y mice. However, further systemic interventions (e.g. optogenetic manipulations) will be needed to investigate whether the behavioural phenotypes of OGTC921Y mice solely arise from cortical dysplasia in the cingulate cortex.

There is a significant dearth of information on possible cortical malformations in patients with OGT-ID. This is largely due to the lack of clinical data available as brain imaging has only been reported in a few cases, or that the defects are beyond the limits of detection/resolution in routine clinical MRI scans. Nevertheless, defects in white matter composition have been reported in patients with OGT-ID including thin corpus callosum and periventricular leukomalacia (Pravata et al., 2020b). Both defects have previously been associated with learning difficulties and ID (Spencer et al., 2006; Choi et al., 2016). Changes in white matter structures have also been found in neuroimaging analysis of neurodevelopment disorders such as Fragile-X90, developmental delay (Cascio et al., 2006; Pujol et al., 2004), and ADHD (Ishii et al., 2015). Together, these observations suggest that changes in white matter structures could underline learning and behavioural deficits in neurodevelopment disorders. Interestingly, the OGTC921Y mice also showed reduced volumes of several white matter structures including corpus callosum, internal capsule, cerebral peduncle, corticospinal tracts, and stria terminalis. These observations could guide future studies in investigating whether OGT-ID variants cause impaired myelination processes leading to cognitive impairment.

Our proteomics analyses revealed a number of perturbed molecular pathways in the PFC of the OGTC921Y mice. Interestingly, some of the deregulated proteins are associated with brain malformation including progressive microcephaly (ARSA, CHMP1A, QARS1; Doherty et al., 2019; Coulter et al., 2018; Chan et al., 2022), cortical dysplasia (RALGAPB, PACS2; Barnea-Goraly et al., 2003; Levine et al., 2018), myelination defects (ARSA, CHMP1A, GABRA2, HEXA, RMND1; Doherty et al., 2019; He et al., 2023; Feng et al., 2022; Lv et al., 2024; Gupta et al., 2016; Cesani et al., 2016), and agenesis of the corpus callosum (EFNB1, TUBA8, CLCN3, PLXND1; Gürsoy et al., 2021; Abdollahi et al., 2009; Duncan et al., 2021; Tomas-Roca et al., 2015), providing potential candidates underlying the brain defects identified in the OGTC921Y mice. In addition, the RHO GTPase cycle pathway (HAS-9012999) was significantly up-regulated from the Reactome database. RHO GTPase family are involved in cell migration, division, and polarity and play crucial roles in neurodevelopment (Govek et al., 2005). While a detailed description of all the top 50 up-regulated proteins is beyond the scope of this Discussion, the ubiquitin ligase RB binding protein 6 (RBBP6) promotes ubiquitination of the Y box protein 1 (YBX1) followed by its degradation by the proteosome. YBX1 is a nucleic acid-binding protein required for forebrain specification, cell proliferation, and neuronal differentiation through the suppression of RNA polymerase II-mediated transcription (Evans et al., 2020). Interestingly, while RBBP6 was found up-regulated, its target YBX1 was identified as significantly down-regulated in our dataset, suggesting a role of the RBB6P/YBX1 axis in the brain structural defects observed in the OGTC921Y mice. Future studies at early timepoints during brain development will be needed to explore these candidate conveyors of OGT-ID.

Whereas structural brain defects suggest a neurodevelopment origin, it is as yet unknown whether the associated cortical dysfunction originates from structural defects during neurodevelopment or neurophysiological defects due to the continuous presence of the catalytically impaired OGTC921Y variant in neurons, their synapses, and glia. Non-invasive monitoring of the OGTC921Y mice activity patterns (in DVC) showed that spontaneous hyperactivity was not detected from weaning but continuously progressed from approximatively 7 weeks of age, coinciding with a delay in postnatal growth. With reasonable caution, this is reminiscent of clinical findings in patients with OGT-ID who generally start developing symptoms in the first two years. From a translational perspective, these features hint towards a progressive postnatal appearance of behaviour and morphological deficits in the OGTC921Y mice, thus potentially offering a therapeutic window for future interventions. It is hoped that cognitive impairment due to prefrontal cortical dysfunction can partly be rescued postnatally even in presence of brain structural defects, with notable examples from research in models of Fragile X and Retts neurodevelopmental syndromes (Allemang-Grand et al., 2017; Kolk and Rakic, 2022; Reynolds et al., 2020).

Conclusions

In conclusion, we report that O-GlcNAc dyshomeostasis in brains of OGTC921Y mice is associated with distinct behavioural phenotypes reflecting hyperactivity, impulsivity, and learning deficits. These phenotypes were accompanied by features consistent with perturbed neurodevelopment including skull deformation, microcephaly, and FCD in the cingulate cortex (Figure 8). Moreover, the glimpse offered by changes in the neocortical proteome of OGTC921Y mice and the observed O-GlcNAc dyshomeostasis will guide future studies in unravelling the pathophysiology of the disorder and hold promise for the development of novel therapeutic interventions in OGT-ID.

Figure 8
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Graphical summary of the neurodevelopmental, structural, and behavioural defects identified in the OGTC921Y mice.

This figure was created using BioRender.com.

Figure 8—source data 1

Labelled original files for western blot analysis displayed in Figure 8.

https://cdn.elifesciences.org/articles/107170/elife-107170-fig8-data1-v1.zip
Figure 8—source data 2

Original files for western blot analysis displayed in Figure 8.

https://cdn.elifesciences.org/articles/107170/elife-107170-fig8-data2-v1.zip

Materials and methods

Animal husbandry

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The OGTC921Y line was previously generated and reported (Authier et al., 2024) and was maintained under C57BL/6 J background (Janvier, France). Animal cohorts were obtained from crossing of male OGTWT with female OGTC921Y/+. Only male mice were used in all experiments. Animals were housed in DVCs (Tecniplast, Italy) with water and food available ad libitum and 12/12 hr light/dark cycles in the Skou animal facility of Aarhus University. All animal studies and breeding were performed in accordance with the ARRIVE guidelines and the European Communities Council Directive (2010/EU) and were approved by the Danish Animal Experiments Inspectorate (Dyreforsøgstilsynet), under Breeding license 2022-15-0202-00135 and Project licenses: 2023-15-0201-01426 and 2020-15-0201-00421.

Non-invasive monitoring of spontaneous activity in home cages (DVC)

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Patterns of locomotion and spontaneous activity were continuously monitored over 24 hr in home cages through a specialised DVCs platform (Tecniplast, Italy) between the age of 30 days and 105 days (termination). This platform is based on electrical capacitance sensing technology, which incorporates a sensor board equipped with an integrated circuit comprising 12 electrodes directly beneath the floor of the cages (Piilgaard et al., 2023). The DVC circuit measures changes in the electrical capacitance signal from each electrode in response to the movement of a water-filled body (animal) close to or away from a given electrode. The measurements, performed approximately 4 times/s, are remotely relayed to the centralised DVC analytics platform (Tecniplast, Italy). In this web-based interface, time-stamped data for each cage can be visualised using in-built tools (e.g. daily rhythms, cumulative activity/locomotion index aggregated per min/hr/day, bedding status, light or dark period activity, heatmaps etc.). In the default setup, the DVC analytics web-interface plots the animal locomotion index as arbitrary units normalised between 0% and 100%, representing the overall activity performed in the cage by the animals, that is the signal is measured for each cage and not each animal.

Behaviour assessment

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Prior to behavioural testing, all animals were handled daily by the experimenter for 1 week. All handling took place in the experimental room with an ambient light setting of 25–30 Lux. All animals were housed in groups of two to three individuals. Animals were 10 weeks old at the start of behavioural testing, reaching 14 weeks old at the end. Before any behavioural test, mice were placed in the experiment room for at least 30 min prior to testing. The data analyses and video quantification were performed blindly with respect to the genotype. The sample size was determined based on previous experience and validated using post-hoc power calculation using ClinCalc online tool (https://clincalc.com/stats/Power.aspx).

Locomotor behaviour and sensorimotor coordination

Open field

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The activity of mice in an open-field maze was recorded using ANY-maze video tracking software (Stoelting Europe, Ireland). Individual animals were placed in a 33.5 × 33.5 × 39 cm opaque box and were allowed to explore for 10 min over 3 consecutive days. Time spent in the centre and periphery and time moving in the periphery were analysed to investigate parameters of locomotion and anxiety.

Rotarod

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Coordination skills were assessed using rotarod apparatus. Mice were placed on a Ugo Basile NB 80534 rotarod with an increase in speed from 4 to 40 rpm and an acceleration time of 2 min (40 rpm/min is reached after 2 min) for maximum 5 min. Latency to fall from the rotarod and speed were measured.

Static rods

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Mice were placed at the extremity of the rod with head facing the void. Time spent by the mouse to perform a t-turn and to reach the goal platform were recorded. If the animal fall <5 s (presumably due to a misplacement), the mouse was tested again. After three consecutive fails or an upside down of a mouse, a 120 s score was reported. Five rod diameters (35, 28, 22, 15, and 10 mm) were used for each animal.

Pole test

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Mice were placed close to the top of a pole (40 cm) with the head of the mouse facing up. Times to perform a t-turn and reach the ground were recorded. The test was performed three times for each mouse. If the mouse succeeded in the three attempts, a score of 3 was reported. For each slide and fail to perform the test within the 120 s cut off, an additional 1 point was incremented in the total score.

Cognitive performance

NOR

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Novelty associated short- and long-term memory were assessed in an open-field maze. During the familiarisation phase, mice are free to explore the maze containing two identical familiar objects for 10 min. After 90 min for short-term and 24 hr for long-term memory, one of the familiar objects is replaced by a novel object and mice are free to explore the maze for 10 min. Time spent exploring objects and number of explorations was measured until reaching a total exploration time of 20 s for each mouse.

Spontaneous alternation

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The spontaneous alternation test was performed in a T-maze and was used to assess spatial working memory. Mice were free to choose left or right arms for seven trials. Each arm entry was recorded to calculate the percentage of spontaneous alternation corresponding to the number of correct Left-Right (L/R) or Right-Left (R/L) sequences. Mice that were able to remember which arms they had entered most recently would choose a different one to explore.

Aversive conditioning and recall

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The apparatus consisted of an open-top cage (24 × 20 × 30 cm) with metal floor bars, placed inside a soundproof cubicle (55 × 60 × 57 cm; Ugo Basile, Italy). Three minutes after being placed in the conditioning chamber, the mice were conditioned using four tone-foot shock (CS-US) pairings (n=9 per group). Each pairing consisted of a 25 s, 7 kHz tone (CS), followed by a 25 s gap (trace period), and then a 1.5 s foot shock (US) at 0.5 mA. After the conditioning session, the animals were isolated for 10–15 min before being returned to their home cage with their littermates. Long-term memory recall was assessed in a novel context 24 hr after conditioning. Following a 3-min acclimatisation period in the novel context, the mice were exposed to four CS presentations without foot shocks. The intertrial interval ranged from 120 to 180 s for both the conditioning and testing sessions. The behavioural responses were recorded using a top-mounted camera and freezing and locomotor activity were automatically scored using ANY-maze software (Stoelting Europe, Ireland). The freezing percentage represents the time the mouse spent freezing during the CS presentation or the total duration of the time bin.

Anxiety behaviour

Elevated-plus maze

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Anxiety-like behaviour was assessed using the EPM paradigm. Mice were placed in the centre of the cross-shaped maze comprised of two open arms (125 Lux) and two closed arms (25 Lux) and allowed to explore the maze for 5 min. Time, distance, and number of entries in each of the open and closed arms were analysed as an approximation for anxiety.

Dark-light paradigm

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Light-like anxiety behaviour was assessed using the dark-light paradigm at 180 Lux. Mice were placed in an arena containing both dark and light compartments. At the start of the test, mice were placed in the dark compartment and were free to explore both compartments for 10 min. Time, distance, and number of entries in the light compartment were analysed to investigate the level of anxiety.

Compulsive behaviour

Marbles

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Before the test, 20 glass marbles (1.6 cm in diameter) were placed on the top of the bedding (in five rows of four marbles) in a cage with 5 cm bedding. At the end of the test, the number of buried marbles (covered by at least 75% of bedding) was counted.

Digging and self-grooming

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Mice were placed in a cage with 5 cm (digging) or 1 cm (self-grooming) bedding for 3 min. Number of digging/self-grooming/rearing events and time spent digging/self-grooming/rearing were recorded.

Nesting

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Mice were placed in a cage with 1 cm bedding in the presence of a cotton pad as nesting material for 1 hr. Cotton pads were weighed before and 24 hr after testing to allow drying. Percentage of material removed was quantified.

Litter burrowing

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Mice were placed in a cage in the presence of a PVC tube filled with 120 g of litter bedding for 30 min. Percentage of litter material removed was quantified.

Brain perfusion for structural analyses

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Brains were perfusion fixed and prepared for in-skull MRI (OGTWT n=15 and OGTC921Y n=16). Perfusion fixation was performed after the mice had been anaesthetised by an intraperitoneal injection of Euthanimal (250 mg/kg, Alfasan, 088672). Then, the brain was fixed by transcardiac perfusion at 125 mmHg, to be close to physiologic brain perfusion as previously reported (Schwarzmaier et al., 2022) using 25 mL heparinised (Heparin, 0.2 mL/100 mL, 5000 IU/mL, Pan Pharma, 482480) Natriumchlorid (9 mg/mL, B Braun, 5/389885/0417) for 3 min 30 s, followed by 25 mL of buffered 10% formalin solution (VWR Qpath Chemicals, 11699404) for 3 min 30 s. After decapitation, the mandible and extracranial tissue were removed from the skull to avoid susceptibility artifacts from air bubbles trapped in fur and cavities during imaging. Hereafter, the in-skull brains were stored in 10% formalin solution for at least 1 week prior to imaging. One WT mouse was excluded due to misperfusion.

Magnetic resonance imaging and image analysis

Before imaging, the fixed brain samples were washed in PBS for at least 24 hr to increase MRI signal by removal of excess fixative (Shepherd et al., 2009). For imaging, the samples were subsequently mounted in a 15 mL centrifuge tube filled with a perfluorocarbon-based liquid (Fluorinert, 3 M, PN: FC-770), as is standard (Khan et al., 2016; Chuhutin et al., 2020; Bay et al., 2018; Jespersen et al., 2010; Vestergaard-Poulsen et al., 2011; Knopper et al., 2024).

MRI data collection

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MRI scans were acquired on a 9.4T preclinical system (BioSpec 94/20, Bruker Biospin, Ettlingen, Germany) using a bore-mounted 25 mm quadrature transmit-receive coil. To avoid sample vibrations, the tube containing the sample was secured in a custom polyethylene foam cylinder inside the coil. In-house 3D-printed sample holders ensured consistent positioning of the samples throughout experiments. High-resolution B0 maps were acquired before each sequence, allowing shimming using Bruker’s MAPSHIM. Both DKI data and structural data were acquired for each sample.

Diffusion kurtosis analysis

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DKI data was collected using an eight-segmented diffusion-weighted spin-echo EPI sequence with a 150×150 μm in-plane resolution and 250 μm slice thickness (60 slices for whole-brain coverage). Five unweighted volumes were acquired for signal normalisation followed by 30 isotropically distributed encoding directions at each of three non-zero b-values (0.5, 1.0, 2.0 ms/μm2). Additional scan parameters were time between diffusion gradients (Δ)=15 ms, diffusion gradients duration (δ)=6 ms, 20 averages, effective echo time (TE)=30.0 ms, repetition time (TR)=3500 ms, bandwidth = 278 kHz, resulting in a DKI scan time of 14 hr 46 min 40 s per animal. In addition, a rapid acquisition with relaxation enhancement (RARE) sequence with a 50×50 μm in-plane resolution and 250 μm slice thickness was performed. Here, the 60 slices were positioned identically to the DKI data to allow for precise multi-atlas segmentation (MAS, details below) and regions of interest (ROI)-specific extraction of DKI parameters. The scan parameters used were effective (TE = 10.5 ms, TR = 3000 ms, 30 averages, and RARE factor = 2, with a scan time of 2 hr 28 min 30 s per animal). For the volumetric analysis, we acquired data with an isotropic resolution of 50 μm using a 3D fast low-angle shot (FLASH) sequence. Scan parameters for this were: TR = 88.5 ms, TE = 8.25 ms, matrix size = 360 × 198 × 300, FOV = 18 × 9.9 × 15 mm, and 4 averages, resulting in a scan time of 6 hr 31 min 21 s per animal. For all scan types, data quality was ensured by visual inspection and samples rescanned if needed to ensure consistently high data quality for subsequent analyses. For DKI analysis, all DKI data from all samples were pre-processed in MATLAB (MathWorks Inc, v. 2022 a) for noise floor correction, denoising, and Gibbs ringing removal as described in Knopper et al., 2024; Hansen et al., 2017. After pre-processing, DKI data analysis was performed using inhouse MATLAB scripts as previously described (Ardalan et al., 2022; Hansen et al., 2017) yielding metrics of mean water diffusivity (MD), tissue anisotropy (FA), and the mean kurtosis (MK, an index of tissue microstructure) in each voxel (Hansen et al., 2017).

Multi-atlas segmentation

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To systematically extract regional information from the mouse brain, an MAS Knopper et al., 2024; Ma et al., 2014; Ma et al., 2019 was performed using 10 ex vivo NeAt templates from C57/BL6J mice (Ma et al., 2005; Ma et al., 2008). This followed procedures as described previously (Knopper et al., 2024). Thus, high-resolution labelled images were obtained and then down sampled to match the in-plane resolution of the DKI data allowing extraction of DKI metrics from anatomically well-defined ROIs. Regional voxel values of DKI metrics were filtered for outliers (defined as values exceeding three times the median absolute deviation) and used for statistical analysis.

Volumetric analysis

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The high-resolution FLASH images were processed using an in-house pipeline (Knopper et al., 2024) applying B1 inhomogeneity correction (Sled et al., 1998), denoising (Coupe et al., 2008), and intensity normalisation. Spatial alignment with a high-resolution template of the C57BL/6J mouse (Dorr et al., 2008) was done by manually initializing a linear registration Collins et al., 1994 followed by a non-linear registration (Avants et al., 2014). Neuroanatomical labels from the C57BL/6 J mouse atlas were subsequently transformed and resampled to data native space using the calculated deformation fields and affine transformations for calculation of individual regional volumes. From this, absolute brain volume and regional volumes were calculated. For all brains, RRV (region size as percentage of total brain volume) was calculated to account for total brain size variation.

Statistics

To investigate group differences, permutation tests were performed for either total brain volume (1 M permutations), regional volumes (40 regions, 100 k permutations) or extracted voxelwise DKI metrics for each region (20 regions, 100 k permutations). Uncorrected significance is reported for p-values <0.05 and indicated by asterisks (*). Pound symbols (#) indicate significance below α=0.05 divided by total number regions tested for group mean (green) and group median (red), respectively. Section signs (§) indicate significance (p<0.05) with p values adjusted for false discovery rate (Benjamini-Hochsberg) Benjamini and Hochberg, 1995.

Cortical thickness

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Cortical thickness was calculated as previously described (Lerch et al., 2008). Briefly, Laplace’s equation, with fixed boundary conditions for each of the inner and outer surfaces, was solved. For this, the inner and outer surfaces of the cortex were defined based on the anatomical atlas and transformed to the given mouse. For each point on the cortical surface, the length of a streamline connecting the inside and outside surfaces was used to define the thickness. Cortical thickness was averaged within the bilateral frontal, occipital, and parieto-temporal lobes as well as the entorhinal cortex. Statistical maps of group differences in cortical thickness were generated by fitting a general linear model at each surface vertex (SurfStat, http://www.math.mcgill.ca/keith/surfstat/). Given the multiple comparisons performed, statistical maps were family-wise error (FWE) corrected using random field theory (Worsley et al., 1996) with α=0.001 as cluster defining threshold. All statistical maps were thresholded at p=0.05 (uncorrected and corrected).

Micro-computated tomography (MicroCT)

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Following MRI, the in-skulls brain samples were imaged using MicroCT scanning (vivaCT 80, Scanco Medical AG, Brüttisellen Switzerland). Skulls of 20-week-old mice were placed in the scanner and imaged using 500 projections over 180°, an isotropic voxel size of 39 µm, X-ray voltage of 55 kVp, X-ray current of 105 µA, and an average time of 200 ms. Images were reconstructed and converted to DICOM files that were exported for subsequent analysis in 3D slicer (http://www.slicer.org) and rendered in 3D. Skulls were isolated applying a threshold that separates bone from soft tissue. Segmented skulls and extracted endocasts were exported as 3D models. Furthermore, the coordinates of 45 surface landmarks were registered in a semi-automated fashion: a random skull was chosen as template model and landmarked manually, and these landmarks were automatically applied to the rest of the dataset using the ALPACA module in 3D Slicer. Additionally, the PseudoLMGenerator module was used to obtain a dense network of surface landmarks consisting of 768 points from the skulls and used as input for PCA. The image processing was performed with the operator blinded for the group distribution. For 3D visualisation of differences between WT and OGTC921Y mice by heat maps, models for the average shapes of OGTWT and OGTC921Y skulls were generated from the General Procrustes Analysis (GPA) module, aligned, superimposed, and the model-to-model distance was measured. Skull shape and size differences were assessed by measuring distances between the 45 surface landmarks and performing Euclidean distances matrix analysis. A previously collected cohort of 8-week-old mice skulls were also analysed with this pipeline (Authier et al., 2024). One WT skull was excluded from analysis due to imaging artefact.

Histology and immunofluorescence (IF) microscopy

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Following MicroCT scanning, formalin-fixed and paraffin-embedded brain sections (10 µm thickness) were obtained from the male WT and OGTC921Y mice (n=6 per group). To better characterise the radial and tangential cytoarchitecture in the neocortex, as well as to assess the bilaterality of any incidental findings in brain structure, one hemisphere was cut in sagittal orientation while the opposite hemisphere was cut in coronal orientation. Sections were deparaffinised and stained with haematoxylin and eosin, as described (Robson, 2005). Serial sections were stained with cresyl violet for assessing the cellular arrangement of neurons in cortical layers, and separately with Luxol Fast blue for visualising white matter distribution, including the arrangement of large tracts (Robson, 2005).Then, high-resolution views were obtained with an Olympus VS120 digital slide scanner equipped for bright-field imaging. Slide scans were imported into Qupath (v. 0.5.1; Bankhead et al., 2017), and ROIs were outlined manually guided by the Mouse Brain Atlas (Paxinos and Franklin’s The Mouse Brain in Stereotaxic Coordinates, 4th Edition). ROIs were segmented using the Qupath cell detection on the haematoxylin channel.

Cellular identity was further verified by immunofluorescence (IF) microscopy using the following primary antibodies: anti-NeuN (1:500; ABN78; Sigma-Aldrich) and anti-glial fibrillary acidic protein- GFAP (1:500; ab68428; abcam). For this purpose, sections were deparaffinised and incubated in a blocking buffer comprising 5% normal goat serum in Tris-buffered saline for 1 hr at room temperature. Then, the sections were incubated overnight at 4 °C with the primary antibodies diluted in PBS containing 0.3% Triton-X and 0.5% BSA. IF detection was performed by fluorophore conjugated secondary antibodies: Alexa-Fluor488 goat anti-rabbit (1:1000; A-11034; Thermo Fisher) and Alexa-Fluor594 goat anti-mouse (1:1000; A-11005; Thermo Fisher). Image acquisition was performed on a Leica DM6000 upright microscope equipped with a fluorescence light source. Multiplex IHC analyses were performed in Discovery Ultra automated staining system (Roche Diagnostics) after deparaffinisation and heat-induced antigen retrieval using DISCOVERY CC1 buffer (Roche Diagnostics catalogue # 06414575001) for 32 min at 95 °C. Then, sections were sequentially incubated with the following primary antibodies: anti-NeuN (Rabbit polyclonal, Sigma-Aldrich catalogue # ABN78; dilution, 1:500), anti-Olig2 (clone: EP112; Rabbit monoclonal, Roche Diagnostics catalogue # 07667973001; dilution, 1:500), anti-Reelin (Goat polyclonal, Novus Biologicals catalogue # AF3820, dilution: 1:100), and anti-Pou3F2/BRN2 (Rabbit polyclonal, Proteintech catalogue # 14596–1-AP; dilution, 1:250). Chromogenic detection was performed using Discovery Omnimap Horseradish peroxidase (HRP)-conjugated secondary antibodies with following chromogens: DISCOVERY Teal HRP (for NeuN; Roche Diagnostics catalogue # 08254338001), DISCOVERY ChromoMap DAB (for Olig2: Roche Diagnostics catalogue # 05266645001), DISCOVERY Purple (for Reelin; Roche Diagnostics catalogue # 07053983001), and DISCOVERY yellow HRP (for POU3F2; Roche Diagnostics catalogue # 8502641001). In order to avoid cross-reaction between antibodies, denaturation between chromogenic detection of markers was performed using ULTRA CC2 buffer (Roche Diagnostics catalogue # 05424542001) at 100 °C for 24 min. High-resolution views were obtained with an Olympus VS120 digital slide scanner in bright-field imaging mode.

Tissue collection and dissociation for biochemical analyses

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The PFC was rapidly isolated from whole 16-week-old male mouse brain (n=3 per group), snap frozen, and stored at –80 °C until processing. Tissues were disrupted in PBS two times at 5000 rpm for 30 s with 10 s break using a Precellys 24 Touch homogenizer (Bertin Technologies). Homogenates were split in half for further protein and RNA extractions.

Mass spectrometry and data analysis

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Protein extracts from PFC tissues were prepared for MS using S-Trap micro spin columns (Protifi), including three washes with 50% CHCl₃/50% MeOH. Trypsin digestion (Proteomics grade, Sigma-Aldrich) was performed for 16 hr at 37 °C. The resulting peptides were lyophilised and dissolved in 0.5% formic acid. LC-MS/MS was conducted using an EASY-nLC 1200 system (Thermo Scientific) connected to an Orbitrap Eclipse Tribrid Mass Spectrometer (Thermo Fisher Scientific) with a 2 cm trap column (100 μm i.d.) and a 15 cm analytical column (75 μm i.d.), both packed in-house with ReproSil-Pur C18-AQ 1.9 μm resin (Dr. Maisch GmbH). Peptides were eluted at 250 nL/min using an 80 min gradient from 5% to 44% phase B (0.1% formic acid and 80% acetonitrile), followed by a 30 s gradient to 100% phase B and 5 min at 100% B. Protein identification and quantification were performed using Proteome Discoverer 2.5 (Thermo Scientific). Data were searched against the mouse reference proteome (https://www.uniprot.org/) using the Sequest search engine with the following parameters: MS error tolerance of 10 ppm, MS/MS error tolerance of 0.02 Da, trypsin as the protease with two missed cleavages, and carbamidomethylation as a fixed modification. Variable modifications included HexNAc (ST) and oxidation (M). Label-free quantification was based on precursor ions using unique peptides quantified in at least two out of three replicates. Peptide intensities were normalised to total peptide intensity and scaled using the average of all samples. Protein ratios were based on summed peptide abundances with imputation using replicate-based resampling. Significantly regulated proteins were identified using ANOVA, with adjustments for multiple testing.

Western immunoblotting

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Brain homogenates were lysed using 10 x RIPA buffer (Cell Signaling) as previously described (Authier et al., 2024). For MS, 50 mL of lysates were stored at –80 °C until further processing. For western blot, the rest of the lysates were centrifuged at 14,000 rpm for 20 min at 4 °C, and the protein concentration was determined with Pierce BCA Protein Assay kit (Thermo Fisher Scientific, 23227). Proteins (20 μg) were separated on precast 4–12% NuPAGE Bis–Tris Acrylamide gels (Invitrogen) and transferred to nitrocellulose membrane. Membranes were incubated with primary antibodies in 5% bovine serum albumin in Tris-buffered saline buffer with 0.1% Tween-20 overnight at 4 °C. Anti-OGA (1:1000 dilution; HPA036141; Sigma), anti-O-GlcNAc (RL2) (1:1000 dilution; NB300-524, Novus Biologicals), anti-OGT (F-12) (1:1000 dilution; sc-74546; Santa Cruz), mouse anti-actin (1:5000 dilution; A5441; Merck) antibodies were used. Next, the membranes were incubated with IR680/800-labelled secondary antibodies at room temperature for 1 hr. Blots were imaged using a Li-Cor Odyssey infrared imaging system (Li-Cor), and signals were quantified using Emperia software (Li-Cor). Results were normalised to the mean of each corresponding WT replicates set and represented as a fold change relative to WT.

RT-qPCR

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Total RNA was purified from brain homogenates using RNAeasy Kit (Qiagen) as previously described (Authier et al., 2024). The threshold-crossing value was normalised to internal control transcripts (18 S, Actb, and Pgk1). Results were normalised to the mean of each corresponding WT replicate set and represented as a fold change relative to WT.

Statistics

Statistical analyses were performed with Prism 9 (Graph Pad) unless specified otherwise. D'Agostino & Pearson, Shapiro–Wilk, and Kolmogorov-Smirnov normality tests were performed to verify normality. For data that fulfilled normality requirements, unpaired t tests were used for pairwise comparisons of WT and OGTC921Y data or two-way ANOVA for multiple comparisons were used. For data sets that did not fulfil normality, Mann-Whitney tests were used for pairwise comparisons.

Data availability

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD074604. Behaviour, MicroCT, MRI and histology source data files have been deposited at https://osf.io/b5zqr/overview.

The following data sets were generated
    1. Authier F
    2. Scavenius C
    (2026) PRIDE
    Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivity.
    https://doi.org/10.6019/PXD074604
    1. Authier F
    2. Hansen B
    3. Skoven CS
    4. Eskildsen SF
    (2026) Open Science Framework
    ID b5zqr. Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivity.
    https://osf.io/b5zqr/

References

    1. Collins DL
    2. Neelin P
    3. Peters TM
    4. Evans AC
    (1994)
    Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space
    Journal of Computer Assisted Tomography 18:192–205.
    1. Torres CR
    2. Hart GW
    (1984)
    Topography and polypeptide distribution of terminal N-acetylglucosamine residues on the surfaces of intact lymphocytes: Evidence for O-linked GlcNAc
    The Journal of Biological Chemistry 259:3308–3317.

Article and author information

Author details

  1. Florence Authier

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Conceptualization, Formal analysis, Investigation, Writing – original draft, Writing – review and editing
    Contributed equally with
    Asad Jan
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0965-9165

  2. Asad Jan

    Core Center for Molecular Morphology, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation, Writing – original draft, Writing – review and editing
    Contributed equally with
    Florence Authier
    Competing interests
    No competing interests declared

  3. Islam Faress

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared

  4. Christian Stald Skoven

    CFIN, Aarhus Hospital, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0639-6718

  5. Iria Esperon-Abril

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared

  6. Shagana Tharmakulasingam Balasubramaniam

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  7. Kévin-Sébastien Coquelin

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared

  8. Jens R Nyengaard

    Core Center for Molecular Morphology, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  9. Carsten Scavenius

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared

  10. Benedetta Attianese

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared

  11. Oscar G Sevillano-Quispe

    Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    Contribution
    Visualization
    Competing interests
    No competing interests declared

  12. Simon Fristed Eskildsen

    CFIN, Aarhus Hospital, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4242-9158

  13. Jesper Skovhus Thomsen

    Department of Biomedicine, Aarhus University, Aarhus, Denmark
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9386-6679

  14. Brian Hansen

    CFIN, Aarhus Hospital, Aarhus, Denmark
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared

  15. Daan MF van Aalten

    1. Section for Neurobiology and DANDRITE, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
    2. Division of Cell and Developmental Biology, School of Life Sciences, University of Dundee, Dundee, United Kingdom
    Contribution
    Conceptualization, Writing – original draft, Writing – review and editing
    For correspondence
    daan@mbg.au.dk
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1499-6908

Funding

Wellcome Trust

https://doi.org/10.35802/110061
  • Daan MF van Aalten

Novo Nordisk Fonden (NNF21OC0065969)

  • Daan MF van Aalten

Villum Fonden (00054496)

  • Daan MF van Aalten

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.

Acknowledgements

The authors would like to thank Trine Mikkelesen (JRN lab) for the assistance with the histology workflow, Kristian Graff (Department of Molecular Biology and Genetics, Aarhus University) for the assistance in behaviour equipment build-up and Kamilla Zahll Hornbek (Department of Biomedicine, Aarhus University) for breeding and animal care assistance. This work was funded by a Wellcome Trust Investigator Award (110061), a Novo Nordisk Fonden Laureate award (NNF21OC0065969) and a Villum Fonden Investigator (00054496) to DMFvA. Supported in part by the Danish Research Institute of Translational Neuroscience – DANDRITE of the Nordic-EMBL Partnership for Molecular Medicine and Lundbeckfonden. The Novo Nordisk Foundation is gratefully acknowledged for funding the Scanco µCT equipment as a part of the Aarhus X-ray Imaging Alliance (AXIA).

Ethics

All animal studies and breeding were performed in accordance with the ARRIVE guidelines and the European Communities Council Directive (2010/EU) and were approved by the Danish Animal Experiments Inspectorate (Dyreforsøgstilsynet), under Breeding license 2022-15-0202-00135 and Project licenses: 2023-15-0201-01426 and 2020-15-0201-00421.

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Copyright

© 2025, Authier, Jan et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Florence Authier
  2. Asad Jan
  3. Islam Faress
  4. Christian Stald Skoven
  5. Iria Esperon-Abril
  6. Shagana Tharmakulasingam Balasubramaniam
  7. Kévin-Sébastien Coquelin
  8. Jens R Nyengaard
  9. Carsten Scavenius
  10. Benedetta Attianese
  11. Oscar G Sevillano-Quispe
  12. Simon Fristed Eskildsen
  13. Jesper Skovhus Thomsen
  14. Brian Hansen
  15. Daan MF van Aalten
(2026)
Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivity
eLife 14:RP107170.
https://doi.org/10.7554/eLife.107170.3

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