The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.

Summary Human genetics studies have implicated GALNT2, encoding GalNAc-T2, as a novel regulator of high-density lipoprotein cholesterol (HDL-C) metabolism, but the mechanisms relating GALNT2 to HDL-C remain unclear. We investigated the impact of homozygous GALNT2 deficiency on HDL-C in humans and mammalian models. We identified two humans homozygous for loss-of-function mutations in GALNT2 who demonstrated low HDL-C. We also found that GALNT2 loss-of-function in mice, rats, and nonhuman primates decreased HDL-C. O-glycoproteomics studies of a human GALNT2 deficient subject validated ANGPTL3 and ApoC-III as GalNAc-T2 targets. Additional glycoproteomics in rodents identified targets influencing HDL-C, including phospholipid transfer protein (PLTP). GALNT2 deficiency reduced plasma PLTP activity in humans and rodents, and in mice this was rescued by reconstitution of hepatic Galnt2. We also found that GALNT2 GWAS SNPs associated with reduced HDL-C also correlate with lower hepatic GALNT2 expression. These results posit GALNT2 as a direct modulator of HDL metabolism across mammals.

Large-scale genomic and transcriptomic initiatives offer unprecedented insight into complex traits, but clinical translation remains limited by variant-level associations without biological context and lack of analytic resources. Our resource, PhenomeXcan, synthesizes 8.87 million variants from genome-wide association study summary statistics on 4091 traits with transcriptomic data from 49 tissues in Genotype-Tissue Expression v8 into a gene-based, queryable platform including 22,515 genes. We developed a novel Bayesian colocalization method, fast enrichment estimation aided colocalization analysis (fastENLOC), to prioritize likely causal gene-trait associations. We successfully replicate associations from the phenome-wide association studies (PheWAS) catalog Online Mendelian Inheritance in Man, and an evidence-based curated gene list. Using PhenomeXcan results, we provide examples of novel and underreported genome-to-phenome associations, complex gene-trait clusters, shared causal genes between common and rare diseases via further integration of PhenomeXcan with ClinVar, and potential therapeutic targets. PhenomeXcan (phenomexcan.org) provides broad, user-friendly access to complex data for translational researchers.