Exploring the relationship between genetic patterns and brain properties using the Allen Human Brain Atlas

Background Imaging transcriptomics is a rapidly developing field that combines neuroimaging with genomics to study mechanisms that influence the organization and activity of the nervous system. Using whole‐brain microarray mRNA expression data from the Allen Human Brain Atlas (AHBA), we examined spatial gradients of gene expression in the brain. We then related these gradients to known spatial patterns of brain function. Method We mapped regional mRNA expression data from more than 21,000 genes to the 200‐parcel Schaeffer atlas. Principle components analysis (PCA) was used to reduce the dimensionality of the data to ten principle components (PCs). This was done for all genes for the whole brain (WBExp) as well as those specific to Alzheimer Disease (ADExp). We additionally mapped eight other properties: functional connectivity gradients (Fig. 2A), myelin, cortical thickness, cerebral blood volume, cerebral blood flow, glucose consumption, and evolutionary expansion (Fig. 2B) to this atlas to explore their relationships with genetic patterns. Region weights from the PCs were predicted from these eight maps. Result The majority of variance for both WBExp (Fig. 1A & 1C) and ADExp (Fig. 1B & 1D) expression was explained by three PCs. Functional connectivity gradients one (β = ‐0.38, β = 0.14), two (β = 0.33, β = ‐0.45), and five (β = ‐0.44, β = 0.32) were moderately related to the first PC of WBExp (Fig. 3A) and ADExp (Fig. 3C) expression patterns (p < 0.05), respectively. Cortical thickness (β = ‐0.32, β = 0.19), cerebral brain volume (β = 0.10, β = ‐0.13), cerebral blood flow (β = 0.42, β = ‐0.52), and evolutionary expansion (β = 0.08, β = ‐0.20) were additionally moderately related to the the WBExp PC1 (Fig. 3B, p < 0.05) and the ADExp PC1 (Fig. 3D, p < 0.05), respectively. Conclusion Our results highlighted that gradients in genetic expressions are related to functional gradients seen using rs‐fMRI as well as biological properties such as cortical thickness, cerebral blood volume, cerebral blood flow, and evolutionary expansion. These findings shed light on mechanisms that influence the structure and function of the brain. Understanding the relationship between genetic patterns and these properties can give insight into healthy and diseased‐brain states such as Alzheimer disease.