Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes

Abstract

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes, with nine proteins and five metabolites replicated using independent exposure data. We found causal associations between accumbens volume and plasma protease c1 inhibitor as well as strong association between putamen volume and Agouti signaling protein. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

Keywords: Mendelian randomization; Metabolites; Neurological disorders; Proteome; Subcortical brain volume.

Fig. 1.

Study overview and design for MR analysis. SNP information for exposures and outcomes were extracted from GWAS summary statistics for each feature. B2 is the causal association of interest (Effect of Biomarkers on seven different subcortical brain structure volumes), estimated using B2 =B1/B3. B1 and B3 are the direct associations of the genetic variants on the exposure (biomarkers) and outcomes (subcortical structures) obtained from the GWAS studies. We also assume that the SNP instrument selected acts on the outcome only through exposure and not through any confounders. IVW: Inverse Variance Weighted.

Fig. 2.

Significant causal associations between plasma proteins and subcortical brain structure volumes as uncovered via MR analysis. The Proteins were the exposures and the subcortical structures’ volume as outcomes. The associations were significant after FDR corrections for multiple testing.

Fig. 3.

Significant causal associations between metabolites and subcortical brain structure volumes as uncovered via MR analysis. The metabolites were the exposures and the subcortical structures’ volume as outcomes. The associations were significant after FDR corrections for multiple testing.

Fig. 4.

Enrichment analysis of proteins using the g:Profiler tool. The rectangles correspond to the various enriched Gene Ontology terms and the proteins associated with each term are shown in ellipses.