New insights into DNA and protein connections

New insights into DNA and protein connections ...

A new genetic mapping study led by researchers at the Johns Hopkins Bloomberg School of Public Health identifies the link between DNA variations and tens of thousands of blood proteins in two large and wide-ranging populations. The results should help researchers better understand the molecular causes of diseases and identify proteins that might be used to treat these diseases.

The study included over 9,000 Americans from Europe or African ancestry and provided maps of DNA-to-protein links for both groups. Proteins play a critical role in cell function, and mutations in protein mechanismsoften can lead to disease. DNA-to-protein mapping might assist researchers understand some health disparities.

The research appears in ThenNature Genetics on May 2nd.

Through so-called genetic mapping studies, scientists have discovered that variations in DNA are linked to disease risk. This study also investigated the DNA of subjectsoften tens or thousands of individuals at a time along with their history of a given disease.

Most of the disease-linked DNA variants identified by the GWAS analysis do not belong in protein-coding genes. Researchers therefore assumed that manyeven mostdisease-linked DNA variations affect proteins indirectly, by regulating one or more steps in the gene-to-protein production process, thereby altering protein levels. Researchers can better understand the roots of disease and also identify protein targets for disease prevention and treatment.

This relatively new type of mapping study provides an awealth of information that will enable researchers to explore potential proteins on various health outcomesrisks of cancers, heart disease, severe COVIDand assist in developing or repurpose therapeutic medications, according to research senior author Nilanjan Chatterjee, PhD, a Bloomberg Distinguished Professor at the Bloomberg School.

The researchers used the DNA mapping technique to identify an existing rheumatoid arthritis medication as a practical new treatment for the common joint-pain disorder known as gout.

The study involved a collaboration between the Chatterjees team and the research group of Josef Coresh, MD, George W. Comstock, a professor in the Bloomberg Schools Department of Epidemiology, and one of the papers co-authors, and colleagues from several institutions.

In the long-running Atherosclerosis Risk in Communities study, led by Coresh, the researchers covered 7,213 Americans of European descent and 1,871 African Americans, and 467 African Americans from the African American Study of Kidney Disease and Hypertension (AASK). In both of these studies, the researchers had sequenced the genomes of the participants and recorded bloodstream levels of tens of thousands of distinct proteins.

The Chatterjees team used ARIC and AASK genomic data to identify more than two thousand common DNA differences that lie close to the genes encoding many of these proteins and correlate with proteins bloodstream levels.

According to Chatterjee, the value of understanding about these DNA variations that predict certain protein levels is that we can then examine much larger GWAS datasets to see if these same DNA variants are linked to disease hazards.

A European-American study demonstrated that it predicted several proteins whose levels might influence the risk of gout or bloodstream levels of the gout-related chemical urate. These proteins included the interleukin 1 receptor antagonist (IL1RN) protein, which appears to lower gout riska findings, suggesting that the existing rheumatoid arthritis drug anakinra, which mimics IL1RN, would be a viable alternative therapy for gout.

Both white and black Americans were able to map protein-linked DNA variants finely than if they had been restricted to one or the other. The African-ancestry models developed in the study will allow future experiments on how different populations'' genetic backgrounds might contribute to differences in disease rates.

According to Chatterjee, prostate cancer risk is higher among African American men, so that in principle, one might combine prostate cancer GWAS data on African Americans with our protein data to identify proteins that raise the risk of prostate cancer in that population.

The researchers can use the dataset and protein prediction models as part of the research. The Chatterjees team and collaborators anticipate doing further research in the ARIC and AASK cohorts, as well as in other diverse cohorts, in order to gather data about proteins and other factors that influence the DNA-to-disease chain.

Proteome-wide association studies were jointly co-authored by Jingning Zhang and Diptavo Dutta, Adrienne Tin, Pascal Schlosser, Morgan Grams, Benjamin Harvey, and the CKDGen Consortium, Bing Yu, Eric Boerwinkle, Josef Coresh, and Nilanjan Chatterjee.

You may also like: