Biology subjects

Sled, J. G.

Publications and source records attributed to Sled, J. G..

7 recordsLinked to original sources

bioRxiv2026

Brain structural and genetic correlates of motor coordination and learning behaviours: modelling developmental coordination disorder

Developmental coordination disorder (DCD) is a common neurodevelopmental condition characterized by impaired motor coordination and learning, yet its neurobiological and genetic bases remain poorly understood. Here, we leverage the BXD recombinant inbred mouse panel to model the polygenic architecture of DCD and link behaviour, brain structure, and genotype. High-resolution ex vivo MRI across 14 strains revealed that DCD-like mice have modestly reduced total brain volume, with a distinct neuroanatomical profile characterized by enlarged cortical regions alongside reduced cerebellar, thalamic, and other subcortical volumes. These structural differences closely mirror findings reported in human DCD. Across strains, variation in brain structure strongly correlated with motor behaviours, with coordinated patterns linking increased cortical and decreased subcortical volumes to poorer motor coordination, while more focal associations were observed for motor learning. Multivariate analysis identified a dominant brain-behaviour axis capturing this cortical-subcortical trade-off. Quantitative trait locus (QTL) mapping revealed multiple loci influencing regional brain volumes, including a prominent locus on chromosome 12 regulating cerebellar structures, but did not identify single loci driving the main multivariate brain-behaviour relationships, consistent with a distributed genetic architecture. Together, these findings demonstrate that DCD-like motor impairments arise from coordinated alterations across distributed brain systems under polygenic control. This work establishes a translational framework linking genetic variation to brain organization and motor function, and suggests that DCD reflects the extreme of a continuous spectrum of neurobiological variation rather than a discrete condition.

neuroscience↗

bioRxiv2026

Chronic Stress Exacerbates Long-term Microvascular Network Dysfunction Following Brain Trauma

BackgroundPreexisting factors are among the strongest predictors of recovery following traumatic brain injury (TBI), with chronic stress closely associated with permanent disability and worse long-term outcomes. While chronic cerebrovascular dysfunction is linked to these poor trajectories, as impaired blood flow regulation drives secondary disease progression, the mechanisms regulating this vascular failure remain incompletely understood. Crucially, how premorbid chronic stress and TBI disrupt the fundamental coordination of the cerebrovascular network post-injury remains unknown. MethodsTo elucidate this coordination at rest and in response to increased neuronal activity, we used a model of three repeated moderate closed cortical impacts comorbid with chronic stress induced by social isolation (SI) post-weaning. Our previously developed vascular analysis pipeline (NOVAS3D) was employed to estimate changes in vascular radii across cerebrovasculature proximal to neuronal activation. Arteries and veins were annotated in the imaged volumes to allow for blood flow simulations. ResultsUsing graph-based network analysis, we demonstrate that TBI, when compounded with chronic stress, critically disrupts the long-range coordination of the capillary network. Specifically, the functional coordination of radius changes between nearby, non-adjacent capillaries was reduced by 40{+/-}20% in TBI+SI mice relative to controls. Consequently, simulations estimated that the vascular networks in TBI+SI mice experienced a 68{+/-}7% reduction in arterial red blood cell velocity (VRBC) responses to neuronal activation. These network-wide impairments were fundamentally driven by severely blunted vessel reactivity, including a 28{+/-}7% decrease in the magnitude of arteriolar dilations and a 47{+/-}7% decrease in the magnitude of arteriolar constrictions. ConclusionThese findings provide a mechanistic foundation for worse clinical outcomes seen in TBI patients with comorbid chronic stress, identifying arteriolar reactivity and long-range capillary coordination as critical therapeutic targets to mitigate secondary injury and improve long-term recovery.

neuroscience↗

bioRxiv2023

A new mouse model of ATR-X syndrome carrying a common patient mutation exhibits neurological and morphological defects

ATRX is a chromatin remodelling ATPase that is involved in transcriptional regulation, DNA damage repair and heterochromatin maintenance. It has been widely studied for its role in ALT-positive cancers, but its role in neurological function remains elusive. Hypomorphic mutations in the X-linked ATRX gene cause a rare form of intellectual disability combined with alpha-thalassemia called ATR-X syndrome in hemizygous males. Patients also have facial dysmorphism, microcephaly, musculoskeletal defects and genital abnormalities. Since complete deletion of ATRX in mice results in early embryonic lethality, the field has largely relied on conditional knockout models to assess the role of ATRX in multiple tissues. Given that null alleles are not found in patients, a more patient-relevant model was needed. Here, we have produced and characterised the first patient mutation knock-in model of ATR-X syndrome, carrying the most common patient mutation, R246C. This is one of a cluster of missense mutations located in the chromatin interaction domain that disrupts its function. The knock-in mice recapitulate several aspects of the patient disorder, including craniofacial defects, microcephaly and impaired neurological function. They provide a powerful model for understanding the molecular mechanisms underlying ATR-X syndrome and for testing potential therapeutic strategies.

neuroscience↗

bioRxiv2021

Age related susceptibility to grey matter demyelination and neurodegeneration is associated with meningeal neutrophil accumulation in an animal model of Multiple Sclerosis

People living with multiple sclerosis (MS) experience episodic central nervous system (CNS) white matter lesions instigated by autoreactive T cells. With age, MS patients show evidence of grey matter demyelination and experience devastating non-remitting symptomology. What drives progression is unclear and has been hampered by the lack of suitable animal models. Here we show that passive experimental autoimmune encephalomyelitis (EAE) induced by an adoptive transfer of young Th17 cells induces a non-remitting clinical phenotype that is associated with persistent leptomeningeal inflammation and cortical pathology in old, but not young SJL/J mice. While the quantity and quality of T cells did not differ in the brains of old vs young EAE mice, an increase in neutrophils and a decrease in B cells was observed in the brains of old mice. Neutrophils were also found in the leptomeninges of a subset of progressive MS patient brains that showed evidence of leptomeningeal inflammation and subpial cortical demyelination. Taken together, our data show that while Th17 cells initiate CNS inflammation, subsequent clinical symptoms and grey matter pathology are dictated by age and associated with other immune cells such as neutrophils.

immunology↗

bioRxiv2021

Genetic Mouse Models of Autism Spectrum Disorder Present Subtle Heterogenous Cardiac Abnormalities.

BackgroundAutism Spectrum Disorder (ASD) and Congenital Heart Disease (CHD) are strongly linked on a functional and genetic level. Most work has been focused on neurodevelopmental abnormalities in CHD. Conversely, cardiac abnormalities in ASD have been less studied. In this work we investigate the prevalence of cardiac comorbidities relative to genetic contributors of ASD. MethodsUsing high frequency ultrasound imaging, we screened 9 mouse models with ASD-related genetic alterations (Arid1b(+/-), Chd8(+/-), 16p11.2 (deletion), Sgsh(+/-), Sgsh(-/-), Shank3 {Delta}exon 4-9(+/-), Shank3 {Delta}exon 4-9(-/-), Fmr1(-/-), Vps13b(+/-)), and pooled wild-type littermates (WT). Using a standardised imaging protocol, we measured heart rate (HR), aorta diameter (AoD), thickness and thickening of the left-ventricular (LV) anterior and posterior walls, LV chamber diameter, fractional shortening, stroke volume and cardiac output, Peak E and A velocity ratio of mitral inflow, Velocity Time Integral (VTI) through the ascending aorta. ResultsMutant groups presented small-scale alterations in cardiac structure and function compared to WTs. A greater number of significant differences was observed among mutant groups than between mutant groups and WTs. Mutant groups differed primarily in measures of structure (LV chamber diameter and anterior wall thickness, HR, AoD). When compared to WTs, they differed in both structure and function (LV anterior wall thickness and thickening, chamber diameter and fractional shortening, HR). The mutant groups with most differences to WTs were 16p11.2 (deletion), Fmrl(-/-), Arid1b(+/-). Among mutant groups, the groups differing most from others were 16p11.2 (deletion), Sgsh(+/-), Fmrl(-/-). Our results broadly recapitulate the associated clinical findings. LimitationsVarious genetically driven cardiac abnormalities occur early in life, so repeating this work in non-adult mice may be valuable. To identify possible sex differences, we must extend this work to female mice. The downsampling procedure used (total correlation calculation) must be verified. Only indirect comparison between our results and clinical literature is possible due to differing study designs. ConclusionsThe characteristic heterogeneity of ASD was recapitulated in the observed cardiac phenotype. The type of measures (morphological, functional) mutant groups differ in can highlight common underlying mechanisms. Clinically, knowledge of cardiac abnormalities in ASD can be essential as even non-lethal cardiac abnormalities can impact normal development.

neuroscience↗

bioRxiv2018

Acute and chronic stage adaptations of vascular architecture and cerebral blood flow in a mouse model of TBI

The 3D organization of cerebral blood vessels determines the overall capacity of the cerebral circulation to meet the metabolic requirements of the brain. This study used Arterial Spin Labeling (ASL) MRI with a hypercapnic challenge and ex vivo Serial Two-Photon Tomography (STPT) to examine the relationship between blood flow and 3D microvascular structure following traumatic brain injury (TBI) in a mouse. Mice were exposed to a controlled cortical impact TBI and allowed to recover for either 1 day or 4 weeks. At each time point, ASL MRI was performed to quantify cerebral perfusion and the brain vasculature was imaged in 3D with STPT. Registration of ASL to STPT enabled flow changes to be related to the underlying microvascular structure in each ASL voxel. Hypoperfusion under rest and hypercapnia was observed both 1 day and 4 weeks post-TBI. Vessel density and vascular volume were reduced 1 day post-TBI, recovering by 4 weeks; however, the reorganized vasculature at the latter time point possessed an abnormal radial pattern. Our findings demonstrate functionally significant long-term changes in the vascular architecture following injury and illustrate why metrics beyond traditional measures of vessel density are required to understand the impact of vascular structure on function.

neuroscience↗

bioRxiv2017

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings.\n\nHere, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed.\n\nWe found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance.

neuroscience↗