Methodology.

a) Illustration of the partial least squares correlation analysis. Starting from two input matrices containing per-subject information of regional cortical thickness measures as well as clinical data (demographic and MetS-related risk factors) a correlation matrix is computed. This is subsequently subjected to singular value decomposition resulting in a set of mutually orthogonal latent variables. Latent variables each consist of a left singular vector (here, clinical covariance pattern), singular value and right singular vector (here, cortical thickness covariance profile). b-d) Contextualization analysis. b) Based on microarray gene expression data, the densities of different cell populations across the cortex were quantified. c) Based on functional and structural group-consensus connectomes based on data from the Human Connectome Project, metrics of functional and structural brain network topology were derived. d) Cell density as well as connectomic measures were related to the bootstrap ratio via spatial correlations. Modified from Petersen et al. and Zeighami et al. [32,76].

Abbreviations: Astro – astrocytes; DWI – diffusion-weighted magnetic resonance imaging; Endo – endothelial cells; Ex – excitatory neuron populations (Ex1-8); In – inhibitory neuron populations (In1-8); Micro – microglia; Oligo – oligodendrocytes; rs-fMRI – resting-state functional magnetic resonance imaging; SVD – singular value decomposition.

Descriptive statistics UKB and HCHS

Partial least squares (PLS) analysis.

a) Explained variance and p-values of latent variables. b) Clinical covariance profile. 95% confidence intervals were calculated via bootstrap resampling. Note that confound removal for age, gender, education and cohort was performed prior to PLS. c) Bootstrap ratio representing the covarying cortical thickness pattern. A high positive or negative bootstrap ratio indicates high contribution of a brain region to the overall covariance pattern. Vertices with a significant bootstrap ratio (> 1.96 or < -1.96) are highlighted by colors. d) Scatter plot relating subject-specific clinical and cortical thickness scores. Higher scores indicate higher adherence to the respective covariance profile. Abbreviations: - Spearman correlation coefficient.

Virtual histology analysis.

The correspondence between MetS effects (bootstrap ratio) and cell type-specific gene expression profiles was examined via an ensemble-based gene category enrichment analysis. a) Barplot displaying spatial correlation results. The bar height displays the significance level. Colors encode the aggregate z-transformed Spearman correlation coefficient relating the Schaefer100-parcellated bootstrap ratio and respective cell population densities. b) Scatter plots illustrating spatial correlations between MetS effects and exemplary cortical gene expression profiles per cell population significantly associated across analyses – i.e., endothelium, microglia and excitatory neurons type 8. Top 5 genes most strongly correlating with the bootstrap ratio map were visualized for each of these cell populations. Icons in the bottom right of each scatter plot indicate the corresponding cell type. A legend explaining the icons is provided at the bottom. First row: endothelium; second row: microglia; third row: excitatory neurons type 8. A corresponding plot illustrating the contextualization of the t-statistic derived from group statistics is shown in supplementary figure S20. Abbreviations: – negative logarithm of the false discovery rate-corrected p-value derived from spatial lag models [38,40]; – Spearman correlation coeffient. – aggregate z-transformed Spearman correlation coefficient.

Brain network contextualization.

Spatial correlation results derived from relating Schaefer400×7-parcellated cortical maps of MetS effects (bootstrap ratio) to network topological indices (red: functional connectivity, blue: structural connectivity). Scatter plots that illustrate the spatial relationship are supplemented by respective surface plots for anatomical localization. The color coding of cortical regions and associated dots corresponds. a) & b) Functional and structural degree centrality rank. c) & d) Functional and structural neighborhood abnormality. e) & f) Intrinsic functional network hierarchy represented by functional connectivity gradients 1 and 2. Complementary results concerning t-statistic maps derived from group comparisons between MetS subjects and controls are presented in supplementary figure S22. Abbreviations: prewire - p-value derived from network rewiring [45]; psmash - p-value derived from brainSMASH surrogates [44]; pspin - p-value derived from spin permutation results [43]; rsp-Spearman correlation coefficient.