Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

Abstract

The study of metabolomics and disease has enabled the discovery of new risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular importance. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid. Here, we present a metabolome-wide association study (MWAS), which uses genetic and metabolomic data to impute metabolites into large samples with genome-wide association summary statistics. We conduct a metabolome-wide, genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations (metabolite quantitative trait loci, or mQTLs). We then build prediction models for all available CSF metabolites and test for associations with 27 neurological and psychiatric phenotypes, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the feasibility of MWAS to study omic data in scarce sample types.

Fig. 1. Genome-wide association study (GWAS) meta-analysis of the CSF metabolome.

a Manhattan plot of the meta-analysis across all 338 metabolites tested, with the significant SNPs colored by the metabolic pathway of the associated metabolite (n = 291 meta-analyzed CSF samples). Age at CSF sample, sex, genotyping batch (WADRC only), and the first five principal components were controlled for in each individual GWAS. The top SNP of each locus is labeled with the nearest gene. The horizontal lines represent the genome-wide (5 × 10⁻⁸, black) and Bonferroni-corrected significance thresholds (1.48 × 10⁻¹⁰, red). Data points with P < 1 × 10⁻⁵⁰ for N6-methyllysine are not shown. b Q–Q plot based on the meta-analysis across all metabolites. c Forest plot of the top SNPs from each significant locus across the discovery, replication, and meta-analysis ordered by chromosome and BP position. The blue point represents the discovery GWAS, green the replication GWAS, and beige the meta-analysis. The effect size refers to the GWAS beta-effect estimate.

Fig. 2. Metabolite prediction model performance.

The prediction performance of the best model for each metabolite is shown arranged in order of decreasing R². Metabolites with a significant locus from the genome-wide association study (GWAS) meta-analysis are denoted with an asterisk.