Biology subjects

Ball, G.

Publications and source records attributed to Ball, G..

10 recordsLinked to original sources

bioRxiv2018

Quantifying individual differences in brain morphometry underlying symptom severity in Autism Spectrum Disorders

The neurobiology of heterogeneous neurodevelopmental disorders such as autism spectrum disorders (ASD) are still unclear. Despite extensive efforts, most findings are difficult to reproduce due to high levels of individual variance in phenotypic expression. To quantify individual differences in brain morphometry in ASD, we implemented a novel subject-level, distance-based method on subject-specific attributes. In a large multi-cohort sample, each subject with ASD (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.58) was strictly matched to a control participant (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.70). Intrapair Euclidean distance of MRI brain morphometry and symptom severity measures were entered into a regularised machine learning pipeline for feature selection, with rigorous out-of-sample validation and bootstrapped permutation testing. Subject-specific structural morphometry features significantly predicted individual variation in ASD symptom severity (19 cortical thickness features, p=0.01, n=5000 permutations; 10 surface area features, p=0.006, n=5000 permutations). Findings remained robust across subjects and were replicated in validation samples. Identified cortical regions implicate key hubs of the salience and default mode networks as neuroanatomical features of social impairment in ASD. Present results highlight the importance of subject-level markers in ASD, and offer an important step forward in understanding the neurobiology of heterogeneous disorders.

neuroscience↗

bioRxiv2018

Individual variation in longitudinal postnatal development of the primate brain

Quantifying individual variation in postnatal brain development can provide insight into cognitive diversity within a population and the aetiology of common neuropsychiatric and neurodevelopmental disorders that are associated with adverse conditions in early life. Non-invasive studies of the non-human primate can aid understanding of human brain development, facilitating longitudinal analysis during early postnatal development when comparative human populations are difficult to sample.\n\nIn this study, we perform analysis of a longitudinal MRI dataset of 32 macaques, each with up to five magnetic resonance imaging (MRI) scans acquired between 1 and 36 months of age. Using nonlinear mixed effects model we derive growth trajectories for whole brain, cortical and subcortical grey matter, cerebral white matter and cerebellar volume. We then test the association between individual variation in postnatal tissue volumes and birth weight.\n\nWe report nonlinear growth models for all tissue compartments, as well as significant variation in total intracranial volume between individuals. We also demonstrate that subcortical grey matter varies both in total volume and rate of change between individuals and is associated with differences in birth weight. This supports evidence that subcortical grey matter is specifically vulnerable to adverse conditions in utero and highlights the importance of longitudinal MRI analysis in developmental studies.

neuroscience↗

bioRxiv2018

Genes associated with neuropsychiatric disease increase vulnerability to abnormal deep grey matter development

1.BackgroundNeuropsychiatric disease has polygenic determinants but is often precipitated by environmental pressures, including adverse perinatal events. However, the way in which genetic vulnerability and early-life adversity interact remains obscure. Preterm birth is associated with abnormal brain development and psychiatric disease. We hypothesised that the extreme environmental stress of premature extra-uterine life could contribute to neuroanatomic abnormality in genetically vulnerable individuals.\n\nMethodsWe combined Magnetic Resonance Imaging (MRI) and genome-wide single nucleotide polymorphism (SNP) data from 194 infants, born before 33 weeks of gestation, to test the prediction that: the characteristic deep grey matter abnormalities seen in preterm infants are associated with polygenic risk for psychiatric illness. Summary statistics from a meta-analysis of SNP data for five psychiatric disorders were used to compute individual polygenic risk scores (PRS). The variance explained by the PRS in the relative volumes of four deep grey matter structures (caudate nucleus, thalamus, subthalamic nucleus and lentiform nucleus) was estimated using linear regression both for the full, mixed-ancestral, cohort and a subsample of European infants.\n\nResultsThe PRS was negatively associated with: lentiform volume in the full cohort ({beta}=-0.24, p=8x10-4) and the European subsample ({beta}=-0.24, p=8x10-3); and with subthalamic nuclear volume in the full cohort ({beta}=-0.18, p=0.01) and the European subsample ({beta}=-0.26, p=3x10-3).\n\nConclusionsGenetic variants associated with neuropsychiatric disease increase vulnerability to abnormal deep grey matter development and are associated with neuroanatomic changes in the perinatal period. This suggests a mechanism by which perinatal adversity leads to later neuropsychiatric disease in genetically predisposed individuals.

neuroscience↗

bioRxiv2018

Loss of the Wnt/β-catenin pathway in microglia of the developing brain drives pro-inflammatory activation leading to white matter injury

Microglia of the developing brain have unique functional properties but how their activation states is regulated is poorly understood. Inflammatory activation of microglia in the still-developing brain of preterm born infants is associated with permanent neurological sequelae in 9 million infants every year. Investigating the regulators of microglial activation in the developing brain with multiple models of neuroinflammation-mediated injury and primary human microglia we found that a reduction in Wnt/{beta}-catenin signalling is necessary and sufficient to drive an oligodendrocyte-injurious microglial phenotype. We validated in a cohort of preterm born infants that genomic variation in the WNT pathway is associated with the levels of connectivity found in their brains. Using a Wnt agonist delivered by a BBB penetrant microglia-specific targeting nanocarrier we prevented in our animal model the pro-inflammatory microglial activation, white matter injury and behavioural deficits. Collectively, these data validate that the Wnt pathway regulates microglial activation, is critical in the evolution of an important form of human brain injury and is a viable therapeutic target.

immunology↗

bioRxiv2017

Age, sex, and puberty related development of the corpus callosum: a multi-technique diffusion MRI study

PurposeThe corpus callosum is integral to the central nervous system, and continually develops with age by virtue of increasing axon diameter and ongoing myelination. Magnetic resonance imaging (MRI) techniques offer a means to disentangle these two aspects of white matter development. We investigate the profile of microstructural metrics across the corpus callosum, and assess the impact of age, sex and pubertal development on these processes.\n\nMethodsThis study made use of two independent paediatric populations. Multi-shell diffusion MRI data were analysed to produce a suite of diffusion tensor imaging (DTI), neurite orientation density and dispersion imaging (NODDI), and apparent fibre density (AFD) metrics. A multivariate profile analysis was performed for each diffusion metric across 10 subdivisions of the corpus callosum.\n\nResultsAll diffusion metrics significantly varied across the length of the corpus callosum. AFD exhibited a strong relationship with age across the corpus callosum (partial{eta} 2 = .65), particularly in the posterior body of the corpus callosum (partial{eta} 2 = .72). In addition, females had significantly higher AFD compared with males, most markedly in the anterior splenium (partial{eta} 2 = .14) and posterior genu (partial{eta} 2 = .13). Age-matched pubertal group differences were localised to the splenium.\n\nConclusionWe present evidence of a strong relationship between apparent fibre density and age, sex, and puberty during development. These results are consistent with ex vivo studies of fibre morphology, providing insights into the dynamics of axonal development in childhood and adolescence using diffusion MRI.\n\nTarget journalsBrain Structure & Function; HBM; NeuroImage; Developmental Cognitive Neuroscience

neuroscience↗

bioRxiv2017

An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems

We introduce a new conceptual framework and a model-based interventional calculus to steer, manipulate, and reconstruct the dynamics and generating mechanisms of non-linear dynamical systems from partial and disordered observations based on the contributions of each of the systems, by exploiting first principles from the theory of computability and algorithmic information. This calculus entails finding and applying controlled interventions to an evolving object to estimate how its algorithmic information content is affected in terms of positive or negative shifts towards and away from randomness in connection to causation. The approach is an alternative to statistical approaches for inferring causal relationships and formulating theoretical expectations from perturbation analysis. We find that the algorithmic information landscape of a system runs parallel to its dynamic attractor landscape, affording an avenue for moving systems on one plane so they can be controlled on the other plane. Based on these methods, we advance tools for reprogramming a system that do not require full knowledge or access to the systems actual kinetic equations or to probability distributions. This new approach yields a suite of universal parameter-free algorithms of wide applicability, ranging from the discovery of causality, dimension reduction, feature selection, model generation, a maximal algorithmic-randomness principle and a systems (re)programmability index. We apply these methods to static (e.coli Transcription Factor network) and to evolving genetic regulatory networks (differentiating naive from Th17 cells, and the CellNet database). We highlight their ability to pinpoint key elements (genes) related to cell function and cell development, conforming to biological knowledge from experimentally validated data and the literature, and demonstrate how the method can reshape a systems dynamics in a controlled manner through algorithmic causal mechanisms.

systems biology↗

bioRxiv2017

Pseudopaline, a staphylopine-like metallophore involved in zinc and nickel uptake in Pseudomonas aeruginosa

Metal uptake is vital for all living organisms. In metal scarce conditions, a common bacterial strategy consists in the biosynthesis of metallophores, their export in the extracellular medium and the recovery of a metal-metallophore complex through dedicated membrane transporters. Staphylopine is a recently described metallophore distantly related to plant nicotianamine that contributes to the broad-spectrum metal uptake capabilities of Staphylococcus aureus. Here, we characterize a four genes operon (PA4837-PA4834) in Pseudomonas aeruginosa involved in the biosynthesis and trafficking of a staphylopine-like metallophore named pseudopaline. Pseudopaline differs from staphylopine with regard to the stereochemistry of its histidine moiety associated to an alpha ketoglutarate moiety instead of pyruvate. In vivo, the pseudopaline operon is regulated by zinc through the Zur repressor. The metal-uptake property of the pseudopaline system appears different from that of staphylopine with a predominant effect on nickel uptake, and on zinc uptake in metal scarce conditions mimicking a chelating environment, thus reconciling the regulation of the cnt operon by zinc with its function as a zinc importer under metal scarce conditions.\n\nAUTHOR SUMMARYZinc is an essential micronutrients for bacteria, particularly important at the host-pathogen interface where the host tends to sequester metals in a so called nutritional immunity framework, and the pathogenic bacterium increases its metal uptake efforts in order to keep up with its metal requirements. Here we reveal a novel metallophore, named pseudopaline, which is synthesized and exported by Pseudomonas aeruginosa and serves for the uptake of nickel in metal poor media, and for the uptake of zinc in metal scarce conditions that mimic the chelating environment that presumably prevails within a host.

microbiology↗

bioRxiv2017

Modelling Neuroanatomical Variation Due To Age And Sex During Childhood And Adolescence

Brain development is a dynamic process that follows a choreographed trajectory during childhood and adolescence with tissue-specific alterations that reflect complex and ongoing biological processes. Accurate identification and modelling of these anatomical processes in vivo with MRI may provide clinically useful imaging markers of individual variability in development. In this study, we build a model of age- and sex-related anatomical variation using multimodal imaging measures and manifold learning.\n\nUsing publicly-available data from two large, independent developmental cohorts (n=768 and 862), we apply a multimodal machine learning approach combining measures of tissue volume, cortical area and cortical thickness into a low-dimensional data representation.\n\nWe find that neuroanatomical variation due to age and sex can be captured by two orthogonal patterns of brain development and we use this model to predict age with a mean error of 1.6-2 years and sex with an accuracy of 80-84%.\n\nWe present a framework for modelling anatomical development during childhood using low-dimensional data representations. This model accurately predicts age and sex based on image-derived markers of cerebral morphology and generalises well to independent populations.

neuroscience↗

bioRxiv2017

Network component analysis reveals developmental trajectories of structural connectivity and specific alterations in autism spectrum disorder

The structural organisation of the brain can be characterised as a hierarchical ensemble of segregated modules linked by densely interconnected hub regions that facilitate distributed functional interactions. Disturbances to this network may be an important marker of abnormal development. Recently, several neurodevelopmental disorders, including autism spectrum disorder (ASD), have been framed as disorders of connectivity but the full nature and timing of these disturbances remain unclear.\n\nIn this study, we use non-negative matrix factorisation, a data-driven, multivariate approach, to model the structural network architecture of the brain as a set of superposed subnetworks, or network components.\n\nIn an openly available dataset of 196 subjects scanned between 5 to 85 years we identify a set of robust and reliable subnetworks that develop in tandem with age and reflect both anatomically local and long-range, network hub connections. In a second experiment, we compare network components in a cohort of 51 high-functioning ASD adolescents to a group of age-matched controls. We identify a specific subnetwork representing an increase in local connection strength in the cingulate cortex in ASD (t=3.44, p<0.001).\n\nThis work highlights possible long-term implications of alterations to the developmental trajectories of specific cortical subnetworks.

neuroscience↗

bioRxiv2017

Integrative genomics study of microglial transcriptome reveals effect of DLG4 (PSD95) on white matter in preterm infants.

Preterm birth places newborn infants in an adverse environment that leads to brain injury linked to neuroinflammation. To characterise this pathology, we present a translational bioinformatics investigation, with integration of human and mouse molecular and neuroimaging datasets to provide a deeper understanding of the role of microglia in preterm white matter damage. We examined preterm neuroinflammation in a mouse model of encephalopathy of prematurity induced by IL1B exposure, carrying out a gene network analysis of the cell-specific transcriptomic response to injury, which we extended to analysis of protein-protein interactions, transcription factors, and human brain gene expression, including translation to preterm infants by means of imaging-genetics approaches in the brain. We identified the endogenous synthesis of DLG4 (PSD95) protein by microglia in mouse and human, modulated by inflammation and development. Systemic genetic variation in DLG4 was associated with structural features in the preterm infant brain, suggesting that genetic variation in DLG4 may also impact white matter development and inter-individual susceptibility to injury.\n\nPreterm birth accounts for 11% of all births 1, and is the leading global cause of deaths under 5 years of age 2. Over 30% of survivors experience motor and/or cognitive problems from birth 3, 4, which last into adulthood 5. These problems include a 3-8 fold increased risk of symptoms and disorders associated with anxiety, inattention and social and communication problems compared to term-born infants 6. Prematurity is associated with a 4-12 fold increase in the prevalence of Autism Spectrum Disorders (ASD) compared to the general population 7, as well as a risk ratio of 7.4 for bipolar affective disorder among infants born below 32 weeks of gestation 8.\n\nThe characteristic brain injury observed in contemporary cohorts of preterm born infants includes changes to the grey and white matter tissues, that specifically include oligodendrocyte maturation arrest, hypomyelination and cortical changes visualised as decreases in fractional anisotropy 9-13. Exposure of the fetus and postnatal infant to systemic inflammation is an important contributing factor to brain injury in preterm born infants 12, 14, 15, and the persistence of inflammation is associated with poorer neurological outcome 16. Sources of systemic inflammation include maternal/fetal infections such as chorioamnionitis (which it is estimated affects a large number of women at a sub-clinical level), with the effect of systemic inflammation in the brain being mediated predominantly by the microglial response 17.\n\nMicroglia are unique yolk-sac derived resident phagocytes of the brain 18, 19, found preferentially within the developing white matter as a matter of normal developmental migration 12. Microglial products associated with white matter injury include pro-inflammatory cytokines, such as interleukin-1{beta} (IL1B) and tumour necrosis factor (TNF-)20, which can lead to a sub-clinical inflammatory situation associated with unfavourable outcomes 21. In addition to being key effector cells in brain inflammation, they are critical for normal brain development in processes such as axonal growth and synapse formation 22, 23. The role of microglia in neuroinflammation is dynamic and complex, reflected in their mutable phenotypes including both pro-inflammatory and restorative functions 24. Despite their important neurobiological role, the time course and nature of the microglial responses in preterm birth are currently largely unknown, and the interplay of inflammatory and developmental processes is also unclear. We, and others, believe that a better understanding of the molecular mechanisms underlying microglial function could harness their beneficial effects and mitigate the brain injury of prematurity and other states of brain inflammation25, 26\n\nA clinically relevant experimental mouse model of IL1B-induced systemic inflammation has been developed to study the changes occurring in the preterm human brain 27, 28. This model recapitulates the hallmarks of encephalopathy of prematurity including oligodendrocyte maturation delay with consequent dysmyelination, associated magnetic resonance imaging (MRI) phenotypes and behavioural deficits. Here, we take advantage of this model system to characterise the molecular underpinnings of the microglial response to IL1B-driven systemic inflammation and investigate its role in concurrent development.\n\nIn preterm infants MRI is used extensively to provide in-vivo correlates of white and grey matter pathology, allowing clinical assessment and prognostication. Diffusion MRI (d-MRI) measures the displacement of water molecules in the brain, and provides insight into the underlying tissue structure. Various d-MRI measures of white matter have been associated with developmental outcome in children born preterm 29-32, with up to 60% of inter-individual variability in structural and functional features attributable to genetic factors 33, 34. White matter abnormalities are linked to associated grey matter changes at both the imaging and cellular level 10, 35, 36, with functional and structural consequences lasting into adulthood 37, 38. Tract Based Statistics (TBSS) allows quantitative whole-brain white matter analysis of d-MRI data at the voxel level while avoiding problems due to contamination by signals arising from grey matter 39. This permits voxel-wise statistical testing and inferences to be made about group differences or associations with greater statistical power. TBSS has been shown to be an effective tool for studying white matter development and injury in the preterm brain 40, providing a macroscopic in vivo quantitative measure of white matter integrity that is associated with cognitive, fine motor, and gross motor outcome 11, 41, 42.\n\nIn this work we take a translational systems biology approach to investigate the role of microglia in preterm neuroinflammation and brain injury. We integrate microglial cell-type specific data from a mouse model of perinatal neuroinflammatory brain injury with experimental ex vivo and in vitro validation, translation to the human brain across the lifespan including analysis of human microglia, and assessment of the impact of genetic variation on structure of the preterm brain. We add to the understanding of the neurobiology of prematurity by: a) revealing the endogenous expression of DLG4 (PSD95) by microglia in early development, which is modulated by developmental stage and inflammation; and b) finding an association between systemic genetic variability in DLG4 and white matter structure in the preterm neonatal brain.

genomics↗