Extended Data Fig. 2: Schematic of the study design in the multi-trait genome-wide association meta-analysis for dietary intake in 282,271 individuals.

The genome-wide association meta-analysis of dietary intake comprised data from 191,157 participants from the UK Biobank and 91,114 participants from the CHARGE Consortium. Single-trait macronutrient GWAS from the UK Biobank and CHARGE Consortium were meta-analyzed using METAL and then combined into a multi-trait GWAS using the multi-trait CPASSOC method. Downstream in silico analyses were conducted to identify biological features of identified loci including functional annotation, tissue and pathway enrichment, and single-cell RNA expression analyses. The Bayesian nonnegative matrix factorization clustering algorithm was used to classify dietary intake genetic loci into subgroups based on potential functional and clinical similarities. Cluster-based polygenic risk scores were built to investigate patterns of metabolic risk.