Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.
Institut(e)Institute of Translational Genomics (ITG)
FörderungenNHLBI NIH's National Institute of General Medical Sciences NHGRI National Institute of Mental Healthof the NIH NIH's National Human Genome Research Institute (NHGRI) Deutsche Forschungsgemeinschaft Helmholtz Young Investigator grant Marie-Sk1odowska Curie fellowship H2020 grant National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH)