A large-scale transcriptome-wide association study (TWAS) of ten blood cell phenotypes reveals complexities of TWAS fine-mapping

Abstract

Hematological measures are important intermediate clinical phenotypes for many acute and chronic diseases. Hematological measures are highly heritable, and although genome-wide association studies (GWAS) have identified thousands of loci containing trait-associated variants, the causal genes underlying these associations are often uncertain. To better understand the underlying genetic regulatory mechanisms, we performed a transcriptome-wide association study (TWAS) using PrediXcan to systematically investigate the association between genetically-predicted gene expression and hematological measures in 54,542 individuals of European ancestry from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We found 239 significant gene-trait associations with hematological measures. Among this set of 239 associations, we replicated 71 at p < 0.05 with same direction of effect for the blood cell trait in a meta-analysis of TWAS results consisting of up to 35,900 European ancestry individuals from the Women’s Health Initiative (WHI), the Atherosclerosis Risk in Communities Study (ARIC), and BioMe Biobank. We further attempted to refine this list of candidate genes by performing conditional analyses, adjusting for individual variants previously associated with these hematological measures, and performed further fine-mapping of TWAS loci. To assist with the interpretation of TWAS findings, we designed an R Shiny application to interactively visualize TWAS results, one genomic locus at a time, by integrating our TWAS results with additional genetic data sources (GWAS, TWAS from other gene expression reference panels, conditional analyses, known GWAS variants, etc.). Our results and R Shiny application highlight frequently overlooked challenges with TWAS and illustrate the complexity of TWAS fine-mapping efforts.

Transcriptome-wide association study in UK Biobank Europeans identifies associations with blood cell traits

“…Despite the promises of TWAS offering increased interpretability for GWAS results, deciphering the relationship between variant and gene level effects remains challenging. 20,37,38 As a subset of the 557 conditionally significant results, we identify 10 novel loci previously undiscovered even after several large-scale GWAS in both European and transethnic cohorts. In addition, we replicate 3 out of 6 of the novel TWAS loci available for replication in MVP at a nominal significance threshold, and 1 at a Bonferroni adjusted significance threshold.…”

“…Despite the promises of TWAS offering increased interpretability for GWAS results, deciphering the relationship between variant and gene level effects remains challenging. 20, 37, 38…”

“…30,31 We address some challenges with interpreting TWAS loci at the scale of biobanksized analyses through our adapted TWAS fine mapping via FINEMAP and conditional analysis with individual level TWAS data. 20 To our knowledge, all TWAS fine mapping methods and software are currently designed for summary-statistics based TWAS approaches, with limited functionality to input user generated TWAS statistics from individual level data such as those generated by our REGENIE-based approach. 37,39 To overcome this challenge, we substitute the variant-level LD matrix for the predicted expression correlation matrix in our UKB sample in the widely-used FINEMAP software to generate credible sets of genes.…”

“…This methodology has been described in a previous TWAS of blood cell traits from our group. 20 We partitioned the distinct GWAS variants from Vuckovic et al into three phenotype categories: red blood cell (RBC), white blood cell (WBC), and platelet (PLT) traits. 3 We considered all distinct GWAS variants as determined by conditional analysis on individual level data, referred to as conditionally independent variants by Vuckovic et al For a TWAS gene associated with one trait in the above categories, we conditioned on any distinct variant reported as associated with any trait within the corresponding phenotype category on the same chromosome.…”