Genome-wide Association Studies of Missing Metabolite Measures: Results From Two Population-based Studies

Abstract

Metabolomic studies are increasingly used for both etiological and predictive research, but frequently report missing values. We hypothesized that interindividual genetic variation may account for part of this missingness. Therefore, we performed a GWAS of missingness in measured metabolite levels using an untargeted mass spectrometry-based platform in the Netherlands Epidemiology of Obesity Study (N=594) and the Rhineland Study (N=4,165). We considered metabolites missing in 10%-90% of individuals in both cohorts (N=224). GWAS meta-analyses of these metabolites' probability of missingness revealed 55 metabolome-wide significant associations, including 42 novel ones (p<1.58x10-10), involving 28 metabolites and 41 lead SNPs. Despite considerable pleiotropy, the majority of identified SNP-"missing metabolite" associations were biologically plausible, relating to beta-oxidation, bile acids, steroids, and xenobiotics metabolism. These findings suggest that missing values in metabolomics are nonrandom and partly reflect genetic variation, accounting for which is important for both clinical and epidemiological studies, especially nutritional and pharmacogenetics studies.