Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk

Abstract

Background: Understanding genetic-metabolite associations has translational implications for informing cardiovascular risk assessment. Interrogating functional genetic variants enhances our understanding of disease pathogenesis and the development and optimization of targeted interventions.

Methods: In this study, a total of 187 plasma metabolite levels were profiled in 4974 individuals of European ancestry of the GCAT| Genomes for Life cohort. Results of genetic analyses were meta-analysed with additional datasets, resulting in up to approximately 40,000 European individuals. Results of meta-analyses were integrated with reference gene expression panels from 58 tissues and cell types to identify predicted gene expression associated with metabolite levels. This approach was also performed for cardiovascular outcomes in three independent large European studies (N = 700,000) to identify predicted gene expression additionally associated with cardiovascular risk. Finally, genetically informed mediation analysis was performed to infer causal mediation in the relationship between gene expression, metabolite levels and cardiovascular risk.

Results: A total of 44 genetic loci were associated with 124 metabolites. Lead genetic variants included 11 non-synonymous variants. Predicted expression of 53 fine-mapped genes was associated with 108 metabolite levels; while predicted expression of 6 of these genes was also associated with cardiovascular outcomes, highlighting a new role for regulatory gene HCG27. Additionally, we found that atherogenic metabolite levels mediate the associations between gene expression and cardiovascular risk. Some of these genes showed stronger associations in immune tissues, providing further evidence of the role of immune cells in increasing cardiovascular risk.

Conclusions: These findings propose new gene targets that could be potential candidates for drug development aimed at lowering the risk of cardiovascular events through the modulation of blood atherogenic metabolite levels.

Keywords: Cardiovascular risk; Genome-wide association analysis; Immune tissue expression; Mendelian randomization; Metabolite levels; Transcriptome-wide association analysis.

Fig. 1

Graphical abstract of the performed analyses and main results. GWAS: Genome-wide association study. TWAS: Transcriptome-wide association study. MR: Mendelian randomization

Fig. 2

Genome-wide associated variants for 190 metabolites. A Summary of the GWAS results. B 3D Manhattan plot of significant SNPs according to thresholds in meta-analyses and mashr approaches. C Significant loci per metabolite class

Fig. 3

Transcription-wide associated genes for 190 metabolites. A 3D Manhattan plot of the 2537 gene-metabolite associations in the overall multi-tissue meta-analysis. B Summary of the fine-mapped 53 genes for metabolites. C Upset plot of the 53 fine-mapped gene-metabolite associations per metabolite class. D Distribution of the 53 fine-mapped genes among metabolite classes and specific cell type categories

Fig. 4

Transcription-wide associated genes for cardiovascular outcomes. A Upset plot of the 15 gene-cardiovascular phenotypes associations per tissue category and summary of the 6 replicated genes. B Summary of the genetically informed mediation inference analysis among the 6 genes, metabolite levels and cardiovascular risk