1,721,113 research outputs found
Relationship between cognitive abilities and mental health as represented by cognitive abilities at the neural and genetic levels of analysis
Full text linkCognitive abilities are closely tied to mental health from early childhood. This study explores how neurobiological units of analysis of cognitive abilities—multimodal neuroimaging and polygenic scores (PGS)—represent this connection. Using data from over 11,000 children (ages 9–10) in the Adolescent Brain Cognitive Development (ABCD) Study, we applied multivariate models to predict cognitive abilities from mental health, neuroimaging, PGS, and environmental factors. Neuroimaging included 45 MRI-derived features (e.g. task/resting-state fMRI, structural MRI, diffusion imaging). Environmental factors encompassed socio-demographics (e.g. parental income/education), lifestyle (e.g. sleep, extracurricular activities), and developmental adverse events (e.g. parental use of alcohol/tobacco, pregnancy complications). Cognitive abilities were predicted by mental health (r = 0.36), neuroimaging (r = 0.54), PGS (r = 0.25), and environmental factors (r = 0.49). Commonality analyses showed that neuroimaging (66%) and PGS (21%) explained most of the cognitive–mental health link. Environmental factors accounted for 63% of the cognitive–mental health link, with neuroimaging and PGS explaining 58% and 21% of this environmental contribution, respectively. These patterns remained consistent over two years. Findings highlight the importance of neurobiological units of analysis for cognitive abilities in understanding the cognitive–mental health connection and its overlap with environmental factors
Whole brain imaging of learning, memory, and plasticity
No full textEven in adulthood, experience can have a lasting impact on the brain. The processes of learning and memory formation engage disparate neural circuits and result in many structural and functional changes in the brain. This plasticity occurs at multiple scales, from changes in synaptic strength, to shifts in dendritic spine density, to cell genesis, and to mesoscopic changes in the size or shape of different brain regions. A major challenge has been visualizing this plasticity across the whole brain. Chapters 3 and 4 of this thesis present approaches to visualize neural activity, markers of synaptic plasticity, and mesoscopic structural plasticity across the entire mouse brain. These approaches are then used to investigate the behavioural requirements and cellular pathways driving a particular form of structural plasticity: changes in brain structure volume. Chapter 5 and 6 ask whether changes in brain anatomy induced by learning and experience require long-term memory formation and/or CREB-dependent transcription. Chapter 6 also characterizes the time course of these volume changes and shows that even two days of environmental enrichment can induce structural changes in the brain. Finally, chapter 7 uses hierarchical Bayesian modelling to perform a meta-analysis of several different studies of experience-dependent plasticity. This chapter shows that maze training, exercise, and environmental enrichment each have distinct and increasingly large effects on hippocampal volume. In summary, this thesis presents methods for visualizing plasticity at multiple scales and shows that MRI can be used to image subtle structural plasticity induced by learning and experience.Ph.D
Implementation of Co-clinical Autism Trials in Mice and Humans
Full text linkDespite promise in animal models, novel therapeutics consistently fail in clinical trials of autism. Due to the heterogeneous nature of autism, treatment will likely only ameliorate symptoms in a subset of patients. There is a need to simultaneously test promising new compounds while understanding and predicting which patients will respond to each therapy. To determine what might contribute to response susceptibility, the implementation of co-clinical trials in autism is proposed.
Here, the implementation of multiple co-clinical trials is discussed, including how changes to the protocols were expanded and adapted as the projects proceeded. The first studies set the groundwork for the methodology, first in a study of high throughput characterization of behavioural and neuroanatomical measures in mouse models, then in a study of oxytocin in mouse models of autism. Next, the first true co-clinical trial of tideglusib was investigated in mouse models of autism, followed by an investigation of arbaclofen that deviated due to treatment side effects.
A high-throughput protocol for mouse models of autism is discussed, which encompasses chronic treatment over development, multiple magnetic resonance imaging time-points, and behavioural tests before, during, and after treatment. Human subjects also follow an extensive phenotyping protocol, including behavioural testing, as well as genetics and imaging assessments. This multi-modal, multi-species approach is designed to be a rigorous method of assessing treatment effect, with the intention of stratification by response susceptibility.
Considerations that are key to successful implementation of a co-clinical trial are discussed, including behavioural, neuroanatomical, treatment, subject, and data analysis aspects. Recommendations based off lessons-learned are also reviewed, including the design of a third co-clinical trial. All of these considerations are discussed and implemented in a manner that makes use of the heterogeneity of the disorder-- an aspect that historically is ignored-- while also prioritizing translation across species.
The implementation of co-clinical trials is the right "next step" for autism research, where the classic progression of therapeutics has failed. The hope is to introduce the concept of co-clinical trials to the field of autism, creating a shift in our current approach to the treatment of the disorder.Ph.D
Neuroanatomical Correlates of Mouse Social Behaviour
No full textThe environmental and genetic factors modulating social behaviour throughout development are not well understood. In this thesis, mouse social behaviour was measured in the home cage and quantified using information theory. The sociability measures were validated by assessing strains with known sociability deficits, as well as by comparing against the canonical three-chamber sociability assay. Home cage analysis could identify persistent patterns in individualised social behaviours that would be difficult to assess in short-timescale behavioural assays. Obtained using \textit{in vivo} MRI, neuroanatomy was used to assess brain development and spanned a comprehensive timeline from neonatal life to adulthood. A novel registration strategy, as well as both mixed-effects frequentist and bayesian statistics, were used to quantify relationships between neuroanatomy and social behaviour. Several structures in the neonatal mouse brain were found to correlate with social behaviour later displayed by juveniles. This includes structures with known roles in social behaviour such as the prefrontal cortex and crus I. There were also significant sex interactions in structures like the lateral septal complex, known to be associated with female rodent social play. Using the Allen brain institute gene expression dataset, it was found that genes associated with autism tended to have a spatial expression bias towards the neuroanatomical correlates of social behaviour.Ph.D
The Neurobiological Correlates of Structural Covariance Networks
No full textThere exist many studies examining population-level correlations between the cortical thickness or volumes of brain structures. Yet, the reasons for why these correlations—termed structural covariance—form are unclear. Current thoughts on the formation of these correlations can be broadly grouped into two hypotheses. The first hypothesis posits that regions that correlate in their structural properties do so because they are connected by bundles of neurons, and plasticity acting along this structural backbone causes regions to grow or shrink in a coordinated manner. The second hypothesis suggests that regions found to correlate in their structural properties are those that grow together during neurodevelopment.
In this thesis, I examine structural covariance in the mouse brain, with the goal of comparing these two mechanisms. I show that in adult mice, structural covariance networks are associated with both structural connectivity and transcriptomic similarity, and that structural covariance is already present at birth and generally decreases over neurodevelopment. I then specifically focus on the thalamus and its connections to the cortex and show that cortical structural covariance reflects the functional organization of the thalamus, and is sensitive but not specific to structural connectivity. Additionally, I show that plasticity (resulting from exercise) decreases thalamocortical structural covariance. Finally, I show (using multiple models of agenesis of the corpus callosum) that structural covariance is preserved in the absence of structural connectivity.
I end the thesis with a discussion on the plausible mechanisms underlying the formation of structural covariance, and considering all the results presented in this thesis, I make the case that it is the intrinsic coordinated neurodevelopment of structures that results in the main patterns of structural covariance seen in later life.Ph.D.2023-06-28 00:00:0
Genetic and environmental influences on neuroanatomy across the lifespan
No full textAfter centuries of debate, it is acknowledged that the brain is not fixed following development, but is rather a highly dynamic organ that continues to change in structure throughout the lifespan. This neuroanatomical plasticity is driven by the dynamic interplay between genetic and environmental forces that continuously shape the structure of the brain. When these forces are disrupted by genetic mutations or environmental insults, a range of behavioural and neuropsychiatric disorders arise. The aim of this thesis is to investigate the role genes and the environment play in shaping neuroanatomy across the lifespan and in the context of health and disease. In order to understand how these forces influence neuroanatomy, in-vivo and ex-vivo magnetic resonance imaging (MRI) techniques paired with deformation-based morphometry analytical methods were used to detect volumetric changes in the brain. Mice were used as experimental subjects due to the ability to generate inbred, transgenic animals with a level of control that can be used to specifically test genetic and environmental variables. Genetic influences on the brain were studied in the context of two neuropsychiatric disorders, Alzheimer's disease and Rett syndrome. The TgCRND8 mouse model of Alzheimer's disease was scanned longitudinally over the time course of pathological onset using a manganese-enhanced MRI sequence. An additional diffusion-weighted sequence was used to gain neuroanatomical images of the developing brain. Mouse models of Rett syndrome were studied using ex-vivo and in-vivo imaging techniques to determine whether neuroanatomical phenotypes that arise early in life could be rescued following the reactivation of Mecp2 in adulthood, the genetic determinant which drives this neurodevelopmental disorder. The effects of the environment on the brain was investigated using in-vivo imaging to track the spatial and temporal changes that occur in the brain following exposure to an enriched housing environment. These studies demonstrate that the structure of the brain is influenced by genes that play important roles in development and maturation and is highly responsive to environmental challenges in adulthood.Ph.D
The Structural and Functional Connectivity of the Cerebellum in Autism Spectrum Disorder
Full text linkThe cerebellum coordinates motor, cognitive, and affective function in the brain, largely via its connectivity to the cerebral cortex. Perinatal injury to the cerebellum and mutations to genes integral for cerebellar development are strongly associated with Autism Spectrum Disorder (ASD), a highly prevalent neurodevelopmental disorder with an unclear etiology and heterogeneous behaviour presentation. Disrupted cerebellar development results in changes to its coordinated growth and neurophysiological activity with other brain regions, heretofore referred to as structural and functional connectivity. Recurrent patterns in cerebellar-cerebral connectivity in the context of atypical neurodevelopment have been observed. However, much is still unknown regarding the extent to which these patterns correspond to particular ASD-related behaviours and genetic mutations. In chapter 2, behaviour-correlated functional connectivity profiles - measured using resting-state functional magnetic resonance imaging (MRI) - were identified using a neurodevelopmental disorder (NDD) imaging and behaviour dataset. The findings were then assessed for replication using an independent dataset from a second consortium. Two functional connectivity components were observed in the original and replication dataset: a first component maximally correlated to obsessive-compulsive behaviour and a second component characterized by social communication deficit contrasted against attention deficit. Statistically stable features of these components mainly included nodes pertaining to the attentional, central executive, and default mode networks. Having identified functional connectivity profiles correlated to ASD-related behaviours, structural connectivity profiles were then characterized and compared to those of clustered mouse models, where each model bore a genetic mutation associated with ASD. Structural connectivity was defined as correlations between regional brain volumes measured via MRI. Two mouse model clusters were significantly similar to human clusters following False Discovery Rate correction: the cluster with elevated protein product expression in the cerebellum versus the cerebrum, and the cluster with genes implicated mTOR pathway biomolecule synthesis. Structural correlations were most similar between mice and humans for correlations between cerebellar Crus II or vermal lobule VI and all cerebral regions. Similar to the findings of chapter 2, large structural correlation differences mainly involved regions pertaining to the attentional, central executive, and default-mode networks.Ph.D
Neuroanatomical Correlates of Mouse Social Behaviour
Full text linkThe environmental and genetic factors modulating social behaviour throughout development are not well understood. In this thesis, mouse social behaviour was measured in the home cage and quantified using information theory. The sociability measures were validated by assessing strains with known sociability deficits, as well as by comparing against the canonical three-chamber sociability assay. Home cage analysis could identify persistent patterns in individualised social behaviours that would be difficult to assess in short-timescale behavioural assays. Obtained using \textit{in vivo} MRI, neuroanatomy was used to assess brain development and spanned a comprehensive timeline from neonatal life to adulthood. A novel registration strategy, as well as both mixed-effects frequentist and bayesian statistics, were used to quantify relationships between neuroanatomy and social behaviour. Several structures in the neonatal mouse brain were found to correlate with social behaviour later displayed by juveniles. This includes structures with known roles in social behaviour such as the prefrontal cortex and crus I. There were also significant sex interactions in structures like the lateral septal complex, known to be associated with female rodent social play. Using the Allen brain institute gene expression dataset, it was found that genes associated with autism tended to have a spatial expression bias towards the neuroanatomical correlates of social behaviour.Ph.D
Mapping Mouse and Human Brains using Spatial Gene Expression Patterns
No full textThe use of mouse models is ubiquitous in neuroscience, both in the context of under- standing the fundamental principles of nervous system organization, and in the context of modelling human clinical conditions to investigate their underlying physiology. Yet even as the use of mice in the field has increased exponentially and the tools for study- ing the nervous system have become increasingly sophisticated, methods for establishing correspondences between the mouse and human brain have seemingly lagged behind.
In this thesis, I examine how the spatial expression patterns of homologous genes can be used to establish correspondences between the mouse and human brain. I show that a mouse-human common space can be constructed using homologous gene expression and that direct and quantitative comparisons between the brains of the two species can be made in this space. Moreover, I demonstrate how a supervised machine learning ap- proach can improve the level of resolution at which these comparisons are made. These techniques are then applied to a problem in clinical neuroscience: identifying biologically significant subgroups of patients with autism spectrum disorder and related neurodevel- opmental disorders. Using anatomical MRI scans of autism-related mouse models and human patients, I identify neuroanatomically-driven clusters in both species, and evalu- ate the cross-species similarity of these clusters using the transcriptomic common space. Several clusters are found to be significantly matched across species and exhibit congruent patterns of neuroanatomical changes relative to controls. Using the genes associated with the mouse models, the clusters were then augmented with information about molecular pathways, providing insight into the neurobiology driving the human clusters.Ph.D
Cardiac Comorbidities and Their Effect in Autism Spectrum Disorder
Full text linkAutism spectrum disorder (ASD) is characterised by neurodevelopmental and behavioural deficits, while having associated comorbidities, amongst which cardiac are common. ASD and congenital heart disease (CHD) are linked on a functional and genetic level. Most work focuses on CHD-related neurodevelopmental abnormalities; less so on ASD-related cardiac abnormalities. The first aim of this work is the identification of the cardiac phenotype associated with prominent genetic contributors of ASD. The second aim is the interrogation of the association between the cardiac and neuroanatomical phenotypes observed. We hypothesize the existence of cardiac abnormalities and their association to neuroanatomy in the presence of ASD-related genetic abnormalities.ASD presents high etiological and phenotypic heterogeneity. Preclinical studies allow for rigorous experimental design using numerous animal models, which together provide an approximation to the disorder. We firstly reviewed the types of animal models and phenotyping methods employed in preclinical studies, along with the most prominent treatments considered. High variability was documented. Identification of common mechanistic processes, arising from diverse genetic causes, enabling patient stratification, seems essential for future treatment development. For the purposes of this dissertation, mouse models of ASD were used, while high-frequency ultrasound biomicroscopy (UBM) and magnetic resonance imaging (3D ex-vivo structural MRI) were chosen for the cardiac and neuroanatomical phenotyping respectively.
The prevalence of cardiac comorbidities was investigated in 9 ASD-related genetic mouse models (Arid1b(+/-), Chd8(+/-), 16p11.2 (deletion), Sgsh(+/-), Sgsh(-/-), Shank3 Dexon 4-9(+/-), Shank3 Dexon 4-9(-/-), Fmr1(-/-), Vps13b(+/-)), and pooled wild-type littermates (WTs). Mutant groups (MUTs) presented small-scale alterations in cardiac structure and function. Among MUTs there were more cardiac differences, primarily in structural measures, than between MUTs and WTs, recapitulating the characteristic ASD heterogeneity.
The association of the cardiac comorbidities on neuroanatomy was interrogated for 6 of these models (Arid1b(+/-), 16p11.2 (deletion), Sgsh(+/-), Sgsh(-/-), Fmr1(-/-), Vps13b(+/-)), for which brain MRIs were obtained. Using blind source separation (BSS) analysis, we identified three mechanisms driving the heart-brain interactions. The first is the autonomic regulation of the heart by the brain, the second is the effect cardiac function has on the brain through blood flow and the supply of necessary oxygen and nutrients, and the third involves a congenital cardiac malformation impacting lower order brain functions, such as motor regulation. The second and third mechanisms were also identified in the International Mouse Phenotyping Consortium (IMPC) dataset, comprising of a different set of cardiac measures and neuroanatomical information for mouse models of the same type of genetic contributors of ASD (www.mousephenotype.org) (Dickinson et al. 2016), after performing the same analysis, supporting the generalisability of our findings.
Our results shed light on the presence and role of cardiac comorbidities in ASD. Furthermore, they demonstrate the impact of even non-lethal cardiac abnormalities on development, recapitulating already established clinical
observations in non-ASD cases. This dissertation highlights additional potential aetiologies of the observed neuroanatomical particularities in ASD, which, if validated in humans, can have an important clinical impact, in prognosis, prevention and treatment.Ph.D
- …
