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
2020
Article

Résumé

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.

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https://infoscience.epfl.ch/record/278959?ln=fr

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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.

2022

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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.

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The future of human cerebral cartography: a novel approach

Richard Frackowiak, Henry Markram

Cerebral cartography can be understood in a limited, static, neuroanatomical sense. Temporal information from electrical recordings contributes information on regional interactions adding a functional dimension. Selective tagging and imaging of molecules adds biochemical contributions. Cartographic detail can also be correlated with normal or abnormal psychological or behavioural data. Modem cerebral cartography is assimilating all these elements. Cartographers continue to collect ever more precise data in the hope that general principles of organization will emerge. However, even detailed cartographic data cannot generate knowledge without a multi-scale framework making it possible to relate individual observations and discoveries. We propose that, in the next quarter century, advances in cartography will result in progressively more accurate drafts of a data-led, multi-scale model of human brain structure and function. These blueprints will result from analysis of large volumes of neuroscientific and clinical data, by a process of reconstruction, modelling and simulation. This strategy will capitalize on remarkable recent developments in informatics and computer science and on the existence of much existing, addressable data and prior, though fragmented, knowledge. The models will instantiate principles that govern how the brain is organized at different levels and how different spatio-temporal scales relate to each other in an organ-centred context.

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2012