Genome-wide association studies of coffee intake in UK/US participants of European ancestry uncover cohort-specific genetic associations

Abstract

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N = 130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across hundreds of biomarkers, health, and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from the UK Biobank (UKB; N = 334,659). We observed consistent positive genetic correlations with substance use and obesity in both cohorts. Other genetic correlations were discrepant, including positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in the UKB, and genetic correlations with cognition that were negative in 23andMe but positive in the UKB. Phenome-wide association study using polygenic scores of coffee intake derived from 23andMe or UKB summary statistics also revealed consistent associations with increased odds of obesity- and red blood cell-related traits, but all other associations were cohort-specific. Our study shows that the genetics of coffee intake associate with substance use and obesity across cohorts, but also that GWAS performed in different populations could capture cultural differences in the relationship between behavior and genetics.

Fig. 1. GWAS and secondary analyses of coffee intake from the 23andMe cohort.

A Manhattan plot displays seven genome-wide significant loci associated with coffee intake in the 23andMe cohort (N = 130,153). The horizontal line represents the threshold for significance (p = 5.00E−08). Nearest protein-coding genes (<1 Mb) to significant loci are labeled. Quantile-quantile plot shown in upper left corner. For more details, see Table 1 and Supplementary Table 6. B Overlap of genes identified by MAGMA, H-MAGMA, S-PrediXcan, and S-MultiXcan. Genes identified by all four methods are displayed. C Genes implicated in coffee intake by S-PrediXcan according to brain regions. Upregulated genes are shown in red, downregulated shown in blue.

Fig. 2. Genetic and phenotypic associations with genetic disposition to coffee intake in US and UK cohorts.

A Comparison of genetic correlations across psychiatric (light gray), anthropologic (medium gray), and health (dark gray) traits between 23andMe (lanes 1 and 2) and UKB (lanes 3 and 4). Lanes 1 and 3 show r_g values calculated by LDSC, and lanes 2 and 4 show FDR-corrected p values. Only traits for which at least one cohort was FDR-significant are displayed. For a full list of correlations and trait names, see Supplementary Table 16. Most signals persisted after conditioning for dietary sugar, cigarettes per day, and Alcohol Use Disorder Identification (AUDIT) Consumption scores using mtCOJO [113] (Supplementary Tables 17, 18 and Supplementary Figs. 13, 14). Genetic correlations that could not be calculated are grayed out; * denotes reverse coding. B Phenomic associations (panel 1: PheWAS [p < 3.62E−05], panel 2: LabWAS [p < 1.57E−04]) identified from PGS of coffee intake from 23andMe and UKB summary statistics. Only traits for which at least one cohort was FDR-significant are displayed (saturated bars = FDR significant; desaturated bars = FDR non-significant). Category abbreviations: neurological (neuro.), genitourinary (gen.), neoplasms (neopl.), sense organs (sense), dermatologic (derma.), immune (imm.). For full trait names and more detail, see Supplementary Tables 19 and 20.