Genome-wide association studies have identified >
3500 associated single nucleotide polymorphisms and over 1000 independent loci associated with hypertension. These individually have small effect sizes, and few associated loci have been experimentally tested for causal roles in hypertension using animal models or in humans. Thus, methods to prioritize and maximize the relevance of identified single nucleotide polymorphisms and associated loci are critical to determine their importance in hypertension. We propose several approaches to aid in these efforts, including: (1) integration of genome-wide association study data with multiomic data sets, including proteomics, transcriptomics, and epigenomics, (2) utilizing linked clinical and genetic data sets to determine genetic contributions to hypertension subphenotypes with distinct drivers, and (3) performing whole exome/genome sequencing on cohorts of individuals with severe hypertension to enrich for rare variants with larger effect sizes. Rather than creating longer lists of hypertension-associated single nucleotide polymorphisms, these approaches are needed to identify key mediators of hypertension pathophysiology.