Signatures of life course socioeconomic conditions in brain anatomy

Socioeconomic status (SES) plays a significant role in health and disease. At the same time, early-life conditions affect neural function and structure, suggesting the brain may be a conduit for the biological embedding of SES. Here, we investigate the brain anatomy signatures of SES in a large-scale population cohort aged 45–85 years. We assess both gray matter morphometry and tissue properties indicative of myelin content. Higher life course SES is associated with increased volume in several brain regions, including postcentral and temporal gyri, cuneus, and cerebellum. We observe more widespread volume differences and higher myelin content in the sensorimotor network but lower myelin content in the temporal lobe associated with childhood SES. Crucially, childhood SES differences persisted in adult brains even after controlling for adult SES, highlighting the unique contribution of early-life conditions to brain anatomy, independent of later changes in SES. These findings inform on the biological underpinnings of social inequality, particularly as they pertain to early-life conditions.

The Inequality of Neural Destiny: Signatures of Lifecourse Socioeconomic Conditions in Markers of Brain Tissue Myelination and Volume

Bogdan Draganski, Leyla Loued-Khenissi, Maria del Carmen Sandi Perez

Socioeconomic status (SES) plays a significant role in health and disease. At the same time, early-life conditions affect neural function and structure, suggesting the brain may be a conduit for the biological embedding of SES. Here, we investigate the neural signatures of SES in a large-scale population cohort aged 45 to 85 years. We assess both grey matter volume (GMV) and magnetization transfer (MT) saturation, indicative of myelin content. Higher SES in childhood and adulthood associated with more GMV in several brain regions, including postcentral and temporal gyri, cuneus, and cerebellum, while low SES correlated with larger entorhinal cortex volume. High childhood SES was linked to more widespread GMV differences and higher myelin content in the sensorimotor network while low SES correlated to myelin content in the temporal lobe. Crucially, childhood SES differences in adult brains persisted even after controlling for adult SES, highlighting the unique contribution of early-life conditions to neural status in older age, independent of later changes in SES. These findings inform on the biological underpinnings of social inequality, particularly as it pertains to early-life conditions.

2020

Whole-brain structural connectivity in temporal lobe epilepsy: a Diffusion Spectrum Imaging study

Alessandro Daducci, Alessandra Griffa, François Lazeyras, Alia Lemkaddem, Jean-Philippe Thiran

Introduction: Medial Temporal Lobe Epilepsy (mTLE) with hippocampal sclerosis is the most frequent cause of drug-resistant focal epilepsy in adults. These patients suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor Imaging and functional MRI studies. Diffusion spectrum imaging (DSI) is a new diffusion imaging technique with high angular resolution for improving the mapping of white matter tracts [1]. In this study, we used DSI to investigate the whole brain effect of TLE as reflected by topological measures of the structural connectivity network. Methods: Eight patients with right-sided mTLE and hippocampal sclerosis and 25 controls underwent our DSI protocol at 3T using a 32 channel coil: DSI (voxel size 2.2x2.2x3mm; 44 slices, 257 diffusion directions; max b-value = 6400 s/mm2), 3D T1-weighted MPRAGE and 3D T2-weighted images. The analysis was performed using the Connectome Mapper. The cortical and subcortical grey matters were parcellated into 86 Regions of Interest (ROI) with anatomical landmarks using Freesurfer 5.0. The ROIs were coregistered to the diffusion data by using a nonlinear registration between T1 and T2, then T2 to the diffusion space. The Diffusion Tool Kit was used for the reconstruction of the diffusion Orientation Distribution Function in each voxel. Streamline fibre-tracking was then performed from each voxel in the white matter areas using an in-house streamline-based algorithm. Two scalar maps, the Fractional Anisotropy and the Generalized Fractional Anisotropy were calculated. For each patient, the connectivity between every region pair was estimated was used to construct a connectivity matrix (the adjacency matrix of the structural network). Finally we used topological measures in order to reduce the data and obtain whole-brain characteristics of the network [2]: characteristic Path Length (L), Clustering Coefficient (C) and Small Worldness (S) where S=(C/Crand)/(L/ Lrand) with Crand and Lrand are computed for a random network. Significant differences between the mTLE and control groups were assessed using a Wilcoxon rank-sum test. Results: In patients, we found a higher characteristic path length (0.0288), with a lower clustering coefficient (0.0079) and reduced small-worldness (p=0.000058) compared to controls. Network nodes that contributed significantly to these alterations were located within as well as outside the temporal lobe in both hemispheres, although with a predominance for the ipsilateral hemisphere and bilateral limbic structures. The pattern of significant nodes showed concordance with brain regions known to be involved in epileptic networks in patients with mTLE. Conclusions: Our results show a reduced efficiency of structural brain networks and altered connectivity patterns that are concordant with the mapping of functional epileptic networks [3] and altered functional connectivity [4] in patients with mTLE. Therefore, the network in mTLE is less segregated than in controls with reduced global interactions between the nodes and reduced specialised communities. Further studies are needed to establish the relevance of these findings with respect to the propagation of epileptic activity, cognitive deficits in mTLE and outcome of epilepsy surgery in individual patients.

2012

Quantitative Susceptibility Mapping in the Human Brain

Diana Khabipova

Magnetic resonance imaging (MRI) offers a good tissue contrast and the ability to visualize many disease related morphologies. The work presented in this thesis investigates the study of underlying structure of the brain using quantitative methods with a special emphasis on quantitative susceptibility mapping (QSM). Magnetic susceptibility reflects the interaction of a material to the magnetic field and measures in biological tissues the magnetic susceptibility of inclusions. The reconstruction of QSM requires further processing steps as the magnetic field produced by the sources needs to be disentangled from the orders of magnitude bigger background field. The produced field also depends not only on the shape and the orientation, but also on the anisotropy of susceptibility and the microstructural compartmentalization of the biological source. For this reason, reconstruction methods need to be capable to calculate accurate values for different brain regions as well as applicable in the everyday clinical diagnosis. Within the framework of the thesis a data acquisition protocol based on a multiple-echo gradient echo sequence as well as a post-processing protocol was implemented. One of the processing steps, the background removal method, was applied to preserve the brain regions close to the cerebrospinal fluid (CSF). This method outperforms state of the art methods in this regions but is computationally intensive. Different brain regions were studied using quantitative methods with special emphasis on the QSM. A new method, modulated closed form solution, with extremely fast computational time is proposed. The comparison with other single orientation methods revealed similar results and the highest correlation to the state-of-the-art method (COSMOS) in the deep gray matter. The R2* maps calculated from the same dataset are also able to distinguish the deep gray matter structures with a similar quality. However, QSM shows a higher sensitivity in early stage multiple sclerosis lesions as well as white matter-gray matter structures. In the human cortex the obtained cortical maps show enhancement of primary sensory cortex, which is known to be highly myelinated, on three evaluated quantitative contrasts R1,R2* and susceptibility. The contrasts based on the relaxation rates, R1 and R2*, show a monotonically decrease from the white matter to the CSF imitating the decrease in iron and myelin. The susceptibility behaviour is more complex as iron and myelin content introduce an opposing sensitivity, allowing to study iron and myelin content when combining the three contrasts. The microstructural organization of white matter influences the R2*, R2 as well as field map from which QSM is calculated. This structure leads to an orientation dependence of the studied contrasts and for QSM the spherical assumption is not valid anymore. Therefore a new QSM method is introduced, which includes the Lorentzian correction in white matter. Main fibres such as forceps major and minor were analysed for the three different quantitative contrasts. The anisotropic component associated with susceptibility is similar for the relaxation rates whereas the isotropic component of R2* shows a higher variability. The resulting deep gray matter structure of the new QSM method remained similar to the state-of-the-art method when comparing the isotropic component but calculates physically meaningful susceptibility maps with improved contrast between known fibre bundles.