NEW YORK – Using genetic data for more than 1 million individuals of European ancestry, a large international team has identified about 2,100 blood pressure-associated loci, including more than 100 novel loci, which the team folded into polygenic risk scores (PRS) for blood pressure traits.
"Our study found additional genomic locations that together explain a much larger part of the genetic differences in people's blood pressure," co-first author Jacob Keaton, a precision health informatics section researcher with the National Human Genome Research Institute, said in a statement. "Knowing a person's risk for developing hypertension could lead to tailored treatments, which are more likely to be effective."
As they reported in Nature Genetics on Tuesday, Keaton and colleagues from Vanderbilt University Medical Center, the University of Groningen in the Netherlands, Queen Mary University of London, and other centers performed a blood pressure trait GWAS meta-analysis involving up to almost 1.03 million European individuals.
Along with genetic and summary statistic data for UK Biobank, International Consortium for Blood Pressure, and Million Veteran Program participants profiled for a past blood pressure study, the team also considered new de-identified medical record and genetic data for 50,000 individuals participating in the Vanderbilt University biorepository (BioVU).
"Our goals were to identify novel [blood pressure] variants, reveal new biology underlying [blood pressure], and generate a new [blood pressure] PRS," the authors explained.
Based on data spanning nearly 7.6 million SNPs, the researchers tracked down 2,103 blood pressure trait-linked loci, including 1,495 loci associated with systolic blood pressure, 1,504 diastolic blood pressure-related sites, and 1,318 loci with ties to pulse pressure. The collection encompassed 113 previously unappreciated loci that were linked to one or more of the blood pressure traits.
By bringing in linkage disequilibrium, predicted gene expression, functional mapping, and other data, the team took a closer look at the loci, genes, pathways, and regulatory variants contributing to the association signals detected, highlighting processes such as iron metabolism, iron overload, and iron absorption and genes expressed in cardiovascular, blood, and central nervous system tissues.
The researchers also incorporated transcriptomic data to track down possible drug targets implicated by these blood pressure-related SNPs. They uncovered more than three dozen possible gene targets, including a handful of genes already targeted by approved drugs used to treat blood pressure or other conditions, suggesting potential treatment strategies.
"Future studies should also continue to evaluate associations with genetically predicted gene expression to stimulate other avenues of investigation," the authors concluded. "These goals, if accomplished, will provide researchers with translational knowledge to mitigate disparities and reduce the global impact of health outcomes for which hypertension is a highly common risk factor."
The collection of blood pressure trait-associated SNPs also made it possible to come up with PRS for systolic blood pressure, diastolic blood pressure, and pulse pressure. The addition of these scores improved hypertension prediction models tested in both individuals of European and non-European ancestry.
Using data from the All of Us research project, for example, the team found that PRS established in European participants correlated with blood pressure and hypertension in a group of more than 21,800 African American individuals.
Even so, the authors emphasized the need for additional studies that bring together data from diverse ancestry groups from large biobank and cohort collections to better understand the biology of blood pressure and its cardiovascular consequences.
"We do show a significant association of our European-derived PRS with [blood pressure] and hypertension in an African-American sample," they wrote. "However, the nominal [predictive increases] when adding the PRS into hypertension-prediction models in African-American individuals show that substantial studies that include individuals of non-European ancestry, or alternative methodological approaches, are essential to understand ancestrally related disparities in hypertension, observations that mirror those for other complex traits."