Insights from the largest diverse ancestry sex-specific disease map for genetically predicted height.

We performed ancestry and sex specific Phenome Wide Association Studies (PheWAS) to explore disease related outcomes associated with genetically predicted height. This is the largest PheWAS on genetically predicted height involving up to 840,000 individuals of diverse ancestry. We explored European, African, East Asian ancestries and Hispanic population groups.

Association of Genetically Predicted Skipping of COL4A4 Exon 27 with Hematuria and Albuminuria.

Key Points: Using transcriptome-wide association studies, we identified an association between splicing out of exon 27 of COL4A4 and hematuria. We confirmed the presence of COL4A4 exon 27 splicing in an independent cohort. Functional assays revealed that the COL4A4 transcript with exon 27 spliced out affects collagen IV trimer assembly and secretion.

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci.

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI.

GWAS for the composite traits of hematuria and albuminuria.

Our GWAS of hematuria in the UK Biobank identified 6 loci, some of which overlap with loci for albuminuria suggesting pleiotropy. Since clinical syndromes are often defined by combinations of traits, generating a combined phenotype can improve power to detect loci influencing multiple characteristics. Thus the composite trait of hematuria and albuminuria was chosen to enrich for glomerular pathologies.