A new large-scale genetic mapping study traces links between DNA variations and thousands of blood proteins in people of both European and African ancestry. The work was led by researchers at the Johns Hopkins Bloomberg School of Public Health. It could help researchers better understand the molecular causes of diseases and identify proteins that could be targeted to treat these diseases.
The study included more than 9,000 U.S. subjects and generated maps of DNA-to-protein links for both those of European or African ancestry. The study is thought to be the first of its kind to include two large and ancestrally distinct population cohorts.
The study appears this week in Nature Genetics and the senior author is Nilanjan Chatterjee, PhD, Bloomberg Distinguished Professor in the Department of Biostatistics at the Bloomberg School.
Researchers have been mapping the molecular roots of human diseases for decades through genetic mapping studies such as genome-wide association study (GWAS). But most of the disease-linked DNA variants identified by GWAS analysis do not lie within protein-coding genes. It was therefore assumed that many disease-linked DNA variants affect proteins indirectly, by regulating one or more steps in the gene-to-protein production process, thereby altering protein levels.
By linking diseases directly to proteins, researchers should be able to better understand the roots of disease, and also identify protein targets for disease prevention and treatments.
“This relatively new kind of mapping study provides a wealth of information that will allow researchers to test for potential links of proteins on various types of health outcomes—risk of cancers, heart disease, severe COVID—and help to develop or repurpose therapeutic drugs,” says Chatterjee.
Using DNA Data to Repurpose a Drug
To demonstrate the DNA-protein mapping’s application, the researchers used it to determine whether an existing rheumatoid arthritis drug (anakinra) is a plausible new treatment for gout.
The study was a collaboration between Chatterjee’s team and the research group of Josef Coresh, MD, George W. Comstock Professor in the Bloomberg School’s Department of Epidemiology, and other colleagues.
The analysis covered 7,213 Americans of European ancestry and 1,871 African Americans in the long-running Atherosclerosis Risk in Communities (ARIC) study, headed by Coresh. It also included 467 African Americans from the African American Study of Kidney Disease and Hypertension (AASK). In both of these studies, the research teams had sequenced the genomes of the participants and recorded bloodstream levels of thousands of distinct proteins.
For this mapping study, the team analyzed the ARIC and AASK genomic data to identify more than two thousand common DNA variations that lie close to the genes encoding many of these proteins and correlate with the proteins’ bloodstream levels.
“The value of knowing about these DNA variants that predict certain protein levels is that we can then examine much larger GWAS datasets to see if those same DNA variants are linked to disease risks,” Chatterjee says.
Having data from both white and Black Americans allowed the researchers to map protein-linked DNA variants more finely than if they had been restricted to one or the other. The African-ancestry models generated in the study will allow future analyses of how different populations’ genetic backgrounds might contribute to differences in disease rates. There is increasing evidence that using diverse populations helps genetic studies generate more accurate results.