Integrative structural, functional, and transcriptomic analyses of sex-biased brain organization in humans

Abstract

Humans display reproducible sex differences in cognition and behavior, which may partly reflect intrinsic sex differences in regional brain organization. However, the consistency, causes and consequences of sex differences in the human brain are poorly characterized and hotly debated. In contrast, recent studies in mice-a major model organism for studying neurobiological sex differences-have established: 1) highly consistent sex biases in regional gray matter volume (GMV) involving the cortex and classical subcortical foci, 2) a preponderance of regional GMV sex differences in brain circuits for social and reproductive behavior, and 3) a spatial coupling between regional GMV sex biases and brain expression of sex chromosome genes in adulthood. Here, we directly test translatability of rodent findings to humans. First, using two independent structural-neuroimaging datasets (n > 2,000), we find that the spatial map of sex-biased GMV in humans is highly reproducible (r > 0.8 within and across cohorts). Relative GMV is female biased in prefrontal and superior parietal cortices, and male biased in ventral occipitotemporal, and distributed subcortical regions. Second, through systematic comparison with functional neuroimaging meta-analyses, we establish a statistically significant concentration of human GMV sex differences within brain regions that subserve face processing. Finally, by imaging-transcriptomic analyses, we show that GMV sex differences in human adulthood are specifically and significantly coupled to regional expression of sex-chromosome (vs. autosomal) genes and enriched for distinct cell-type signatures. These findings establish conserved aspects of sex-biased brain development in humans and mice, and shed light on the consistency, candidate causes, and potential functional corollaries of sex-biased brain anatomy in humans.

Trial registration: ClinicalTrials.gov NCT00001246.

Keywords: gray matter volume; imaging-transcriptomics; sex chromosome; sex differences.

Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.

Reproducible regional gray matter volume sex differences in the HCP and UK Biobank datasets. (A) Slice maps and surface projections showing statistically significant male-female differences in GMV after correction for multiple comparisons and controlling for covariates (age and total GMV) in the HCP dataset (full regional list in SI Appendix, Table S2). (B) Scatter and box plot showing cross-voxel spatial correlations for the unthresholded sex-difference t-statistic between 1,000 randomly split-halves of the HCP dataset (averaged Pearson’s r = 0.86, range: 0.75 to 0.90). (C) Density plot showing the observed cross-voxel spatial correlation (red line, Pearson’s r = 0.85) between unthresholded sex-difference t-statistic maps in the HCP dataset and UK Biobank sample (SI Appendix, Fig. S1 A and B) and a null distribution for this correlation statistic (from 1,000 reestimations of the spatial correlations after permutation of sex labels in the HCP dataset, Materials and Methods). The observed correlation lies outside the null distribution (i.e., Pperm < 0.001).

Fig. 2.

Colocalization of gray matter volume sex differences in humans with a distributed brain system that subserves face processing. (A) Reproduction of slice maps and surface projections showing unthresholded (slice maps) and statistically significant (thresholded surface projections) male-female GMV differences in the HCP dataset (compare Fig. 1A). (B) Slice maps and surface projections of the NeuroSynth association statistic in z scores show regions that are more (in warm colors) likely to be activated during tasks related to topic 5, mainly face processing. Pearson’s correlation of the unthresholded maps, with signs, of male-female GMV differences (Left in A) and association statistics of topic 5 (Left in B) is statistically significant (r = 0.32, Pperm < 0.001). (C) A binary conjunction map between cortical regions associated with NeuroSynth topic 5, and cortical regions of significant GMV sex differences. Note that this conjunction is largely composed of regions with male-biased (yellow) as opposed to female-biased (blue) GMV.

Fig. 3.

Spatial coupling between human gray matter volume sex differences and expression of sex-chromosome genes. (A) Schematic of method used to rank genes based on the spatial coupling of brain expression with unthresholded regional sex differences (male-female) in cortical GMV. (B) Schematic showing how relative gene ranking relates to the relationship between gene expression and GMV sex biases. Bold borders denote genes within a set of interest (e.g., sex-linked genes), and the asterisk indicates the median rank for this gene set upon which inferences are made. The polarity of gene rankings is set so that more negative ranks indicate more positive correlation between gene expression and the t-statistic of GMV in males vs. females. This ranking positions sex-linked genes first in a “left-right” reading of C. (C) Point-range plot of the median rank (marked by circle with SD as error bar) of genes on the sex chromosomes and each autosome. Sex chromosomes (X- and Y-linked) genes uniquely showed a statistically significant extreme median rank (relative to the middle line/zero rank, Prand = 0.0014, all chromosome ranks given in SI Appendix, Table S7). The polarity of this rank extremity indicates a positive spatial correlation (marked in red) between sex-chromosome gene expression and male-female differences in GMV (i.e., relative high expression where GMV is greater in males than females and relatively low expression where GMV is greater in females than males). (D) Scatter plot of expression for X- and Y-linked genes ranked at the top 5% of SI Appendix, Table S6 (i.e., those with most extremely positive correlations with the t-statistic map of male-female GMV) vs. their aligned t-values of GMV sex differences (see details in Materials and Methods).

Fig. 4.

Directional enrichment of cell type signatures in transcriptomic correlates of regional gray matter volume sex differences. Using CSEA (38), we identified cell types where genes were significantly overrepresented in the Top Left (A) and Bottom Right (B) 10% of the ranked gene list (SI Appendix, Table S6). CSEA was conducted in the seven cortical cell types (x axis) at specificity index thresholds (pSI) of varying stringency (color coded). Statistical significance is set as −log10. BH FDR-corrected P values in y axis is above the dash line corresponding to BH FDR-corrected P = 0.05.