Far and wide: Associations between childhood socio-economic status and brain connectomics

Abstract

Previous studies have identified localized associations between childhood environment - namely their socio-economic status (SES) - and particular neural structures. The primary aim of the current study was to test whether associations between SES and brain structure are widespread or limited to specific neural pathways. We employed advances in whole-brain structural connectomics to address this. Diffusion tensor imaging was used to construct whole-brain connectomes in 113 6-12 year olds. We then applied an adapted multi-block partial-least squares (PLS) regression to explore how connectome organisation is associated with childhood SES (parental income, education levels, and neighbourhood deprivation). The Fractional Anisotropy (FA) connectome was significantly associated with childhood SES and this effect was widespread. We then pursued a secondary aim, and demonstrated that the connectome mediated the relationship between SES and cognitive ability (matrix reasoning and vocabulary). However, the connectome did not significantly mediate SES relationships with academic ability (maths and reading) or internalising and externalising behavior. This multivariate approach is important for advancing our theoretical understanding of how brain development may be shaped by childhood environment, and the role that it plays in predicting key outcomes. We also discuss the limitations with this new methodological approach.

Keywords: Cognitive ability; Diffusion tensor imaging (DTI); Socio-economic status; behaviour; connectomics; educational attainment.

Fig. 1

Overview of the pre-processing steps used to derive the DTI connectome. Reprinted with permission from ‘Whole-brain white matter organization, intelligence, and educational attainment’ by Bathelt et al., 2019.

Fig. 2

Group-average connectome matrix indicating the ROI-by-ROI FA weighted connections, after 60 % consensus thresholding. The ROIs are grouped cortical versus subcortical and hemisphere (L = left hemisphere, R = right hemisphere, BS = brain stem (bilateral)).

Fig. 3

SES and the structural connectome: a topographic and circle plot of the edges that are significantly associated with childhood SES based on the bootstrap of the first PLS component, coloured by the sign of the loading onto the first component (orange, positive; blue, negative). Edges are grouped by brain hemisphere (L/R) and lobe (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

Fig. 4

SES and the structural connectome: the same associations displayed in Fig. 3, but depicted as a network diagram showing the nodes and connections within the white-matter connectome that are significantly associated with childhood SES, as indexed by non-zero 95 % confidence intervals from the bootstrap procedure.

Fig. 5

PLS mediation analysis between the SES measures, the structural connectome and cognitive ability. The significant weights for each dataset are shown, according to bootstrapped confidence intervals. Note that the topographic structural connectome plot shows only the connections found to be reliably associated with the mediation effect. The coefficients for each path correspond to the 95 % confidence intervals from the 3-block bootstrap procedure.

Fig. 6

PLS mediation analysis between the SES measures, the structural connectome and A) academic ability, and B) behavior. The significant weights for each dataset are shown, according to bootstrapped confidence intervals (orange indicates negative loading). The coefficients for each path correspond to the 95 % confidence intervals from the 3-block bootstrap procedure.