Mapping Genetic Influence on Brain Structure

Neuroimaging is playing an increasingly crucial role in delineating pathological conditions that cannot be typically defined by non-specific clinical symptom. The goal of this thesis was to characterize the genetic influence on grey and white matter indices and evaluate their potential as a reliable “structural MRI signatures”. We first assessed the effects of spatial resolution and smoothing on heritability estimation (Chapter 3). We then investigated heritability patterns of MRI measures of grey and white matter (Chapters 4-5). We then performed a cross-sectional evaluation of how heritability changes over the lifespan for both grey and white matter (Chapter 6). Finally, multivariate structural equation modeling was used to investigate the genetic correlation between grey matter structure and white matter connectivity (Chapter 7), in the default mode network (DMN). Our results show that several key brain structures were moderate to highly heritable and that this heritability was both spatially and temporally heterogeneous. At a network level, the DMN was found to have distinct genetic factors that modulated the grey matter regions and white matter tracts separately. We conclude that the spatial and temporal heterogeneity are likely to reflect gene expression patterns that are related to the developmental of specific brain regions and circuits over time

Regional Brain Differences in Cortical Thickness, Surface Area and Subcortical Volume in Individuals with Williams Syndrome

Williams syndrome (WS) is a rare genetic neurodevelopmental disorder characterized by increased non-social anxiety, sensitivity to sounds and hypersociability. Previous studies have reported contradictory findings with regard to regional brain variation in WS, relying on only one type of morphological measure (usually volume) in each study. The present study aims to contribute to this body of literature and perhaps elucidate some of these discrepancies by examining concurrent measures of cortical thickness, surface area and subcortical volume between WS subjects and typically-developing (TD) controls. High resolution MRI scans were obtained on 31 WS subjects and 50 typically developing control subjects. We derived quantitative regional estimates of cortical thickness, cortical surface area, and subcortical volume using FreeSurfer software. We evaluated between-group ROI differences while controlling for total intracranial volume. In post-hoc exploratory analyses within the WS group, we tested for correlations between regional brain variation and Beck Anxiety Inventory scores. Consistent with our hypothesis, we detected complex patterns of between-group cortical variation, which included lower surface area in combination with greater thickness in the following cortical regions: post central gyrus, cuneus, lateral orbitofrontal cortex and lingual gyrus. Additional cortical regions showed between-group differences in one (but not both) morphological measures. Subcortical volume was lower in the basal ganglia and the hippocampus in WS versus TD controls. Exploratory correlations revealed that anxiety scores were negatively correlated with gray matter surface area in insula, OFC, rostral middle frontal, superior temporal and lingual gyrus. Our results were consistent with previous reports showing structural alterations in regions supporting the socio-affective and visuospatial impairments in WS. However, we also were able to effectively capture novel and complex patterns of cortical differences using both surface area and thickness. In addition, correlation results implicate specific brain regions in levels of anxiety in WS, consistent with previous reports investigating general anxiety disorders in the general population

Structural abnormalities in cortical volume, thickness, and surface area in 22q11.2 microdeletion syndrome: Relationship with psychotic symptoms.

Introduction22q11.2 deletion syndrome (22q11DS) represents one of the largest known genetic risk factors for psychosis, yet the neurobiological mechanisms underlying symptom development are not well understood. Here we conducted a cross-sectional study of 22q11DS to decompose cortical volume into its constituent parts, cortical thickness (CT) and surface area (SA), which are believed to have distinct neurodevelopmental origins.MethodsHigh-resolution T1-weighted scans were collected on 65 participants (31 22q11DS, 34 demographically comparable typically developing controls, 10-25 years old). Measures of cortical volume, CT, and SA were extracted from regions of interest using the FreeSurfer image analysis suite. Group differences and age-related trajectories in these structures, as well as their association with psychotic symptomatology, were assessed.ResultsRelative to controls, 22q11DS participants showed bilateral volumetric reductions in the inferior temporal cortex, fusiform gyrus, anterior cingulate, superior parietal cortex, and cuneus, which were driven by decreased SA in these regions. 22q11DS participants also had increased volumes, driven by increased CT, in bilateral insula regions. 22q11DS youth had increased CT in frontal regions, particularly middle frontal and medial orbitofrontal cortices. A pattern of age-associated cortical thinning was observed in typically developing controls in brain regions associated with visual and sensory information-processing (i.e., left pericalcarine cortex and fusiform gyrus, right lingual and postcentral cortices). However, this relationship was disrupted in 22q11DS participants. Finally, correlational analyses revealed that increased CT in right medial orbitofrontal cortex was associated with increased positive symptom severity in 22q11DS.ConclusionDifferential disruptions of CT and SA in distinct cortical regions in 22q11DS may indicate abnormalities in distinct developmental neural processes. Further, neuroanatomic abnormalities in medial frontal brain structures disproportionately affected in idiopathic schizophrenia were associated with psychotic symptom severity in 22q11DS youth, suggesting that disrupted biological processes in these cortical regions may underlie development of psychotic symptoms, both in 22q11DS and in the broader population

Imaging genetics : Methodological approaches to overcoming high dimensional barriers

Imaging genetics is still a quite novel area of research which attempts to discover how genetic factors affect brain structures and functions. In this thesis, using a various methodological approaches I showed how it can contribute to our understanding of the complex genetic architecture of the human brain

Systems genomics analysis of complex cognitive traits

The study of the genetic underpinnings of human cognitive traits is deemed an important tool to increase our understanding of molecular processes related to physiological and pathological cognitive functioning. The polygenic architecture of such complex traits implies that multiple naturally occurring genetic variations, each of small effect size, are likely to influence jointly the biological processes underlying cognitive ability. Genetic association results are yet devoid of biological context, thus limiting both the identification and functional interpretation of susceptibility variants. This biological gap can be reduced by the integrative analysis of intermediate molecular traits, as mediators of genomic action. In this thesis, I present results from two such systems genomics analyses, as attempts to identify molecular patterns underlying cognitive trait variability. In the first study, we adopted a system-level approach to investigate the relationship between global age-related patterns of epigenetic variation and cortical thickness, a brain morphometric measure that is linked to cognitive functioning. The integration of both genome-wide methylomic and genetic profiles allowed the identification of a peripheral molecular signature that showed association with both cortical thickness and episodic memory performance. In the second study, we explicitly modeled the interdependencies between local genetic markers and peripherally measured epigenetic variations. We thus generated robust estimators of epigenetic regulation and showed that these estimators resulted in the identification of epigenetic underpinnings of schizophrenia, a common genetically complex disorder. These results underscore the potential of systems genomics approaches, capitalizing on the integration of high-dimensional multi-layered molecular data, for the study of brain- related complex traits

Multimodal brain imaging reveals structural differences in Alzheimer's disease polygenic risk carriers: A study in healthy young adults

Background Recent genome-wide association studies have identified genetic loci that jointly make a considerable contribution to risk of developing Alzheimer’s disease (AD). Because neuropathological features of AD can be present several decades before disease onset, we investigated whether effects of polygenic risk are detectable by neuroimaging in young adults. We hypothesized that higher polygenic risk scores (PRSs) for AD would be associated with reduced volume of the hippocampus and other limbic and paralimbic areas. We further hypothesized that AD PRSs would affect the microstructure of fiber tracts connecting the hippocampus with other brain areas. Methods We analyzed the association between AD PRSs and brain imaging parameters using T1-weighted structural (n = 272) and diffusion-weighted scans (n = 197). Results We found a significant association between AD PRSs and left hippocampal volume, with higher risk associated with lower left hippocampal volume (p = .001). This effect remained when the APOE gene was excluded (p = .031), suggesting that the relationship between hippocampal volume and AD is the result of multiple genetic factors and not exclusively variability in the APOE gene. The diffusion tensor imaging analysis revealed that fractional anisotropy of the right cingulum was inversely correlated with AD PRSs (p = .009). We thus show that polygenic effects of AD risk variants on brain structure can already be detected in young adults. Conclusions This finding paves the way for further investigation of the effects of AD risk variants and may become useful for efforts to combine genotypic and phenotypic data for risk prediction and to enrich future prevention trials of AD

Genetic determinants of cortical structure (thickness, surface area and volumes) among disease free adults in the CHARGE Consortium

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging

Assessment of regional gray matter loss in dementia with Lewy bodies: a surface-based MRI analysis.

OBJECTIVE: To compare magnetic resonance imaging (MRI) patterns of cortical thinning in subjects with dementia with Lewy bodies (DLB), Alzheimer's disease (AD), and normal aging and investigate the relationship between cortical thickness and clinical measures. METHODS: Study participants (31 DLB, 30 AD, and 33 healthy comparison subjects) underwent 3-Tesla T1-weighted MRI and completed clinical and cognitive assessments. We used the FreeSurfer analysis package to measure cortical thickness and investigated the patterns of cortical thinning across groups. RESULTS: Cortical thinning in AD was found predominantly in the temporal and parietal areas extending into the frontal lobes (N = 63, df = 59, t >3.3, p 3.6, p 2.8, p <0.01 uncorrected). CONCLUSION: Cortical thickness may be a sensitive measure for characterising gray matter loss in DLB and highlights important structural imaging differences between the conditions.The study was funded by the Sir Jules Thorn Charitable Trust [grant ref: 05/JTA] and supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre in Ageing and Chronic Disease and Biomedical Research Unit in Lewy Body Dementia based at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University, and the Biomedical Research Centre and Unit in Dementia based at Cambridge University Hospitals NHS Foundation Trust.This is the accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S106474811400219X

Genome-wide significant linkage of schizophrenia-related neuroanatomical trait to 12q24

The insula and medial prefrontal cortex (mPFC) share functional, histological, transcriptional and developmental characteristics and they serve higher cognitive functions of theoretical relevance to schizophrenia and related disorders. Meta-analyses and multivariate analysis of structural magnetic resonance imaging (MRI) scans indicate that gray matter density and volume reductions in schizophrenia are the most consistent and pronounced in a network primarily composed of the insula and mPFC. We used source-based morphometry, a multivariate technique optimized for structural MRI, in a large sample of randomly ascertained pedigrees (N = 887) to derive an insula-mPFC component and to investigate its genetic determinants. Firstly, we replicated the insula-mPFC gray matter component as an independent source of gray matter variation in the general population, and verified its relevance to schizophrenia in an independent case-control sample. Secondly, we showed that the neuroanatomical variation defined by this component is largely determined by additive genetic variation (h2 = 0.59), and genome-wide linkage analysis resulted in a significant linkage peak at 12q24 (LOD = 3.76). This region has been of significant interest to psychiatric genetics as it contains the Darier’s disease locus and other proposed susceptibility genes (e.g. DAO, NOS1), and it has been linked to affective disorders and schizophrenia in multiple populations. Thus, in conjunction with previous clinical studies, our data imply that one or more psychiatric risk variants at 12q24 are co-inherited with reductions in mPFC and insula gray matter concentration