New insights into DNA and protein connections

New insights into DNA and protein connections ...

A new genetic mapping project led by researchers at the Johns Hopkins Bloomberg School of Public Health identifies links between DNA variations and tens of thousands of blood proteins in two large and large populations. These findings should help researchers better understand the molecular implications of diseases and identify proteins that might be used to treat these diseases.

The study included over 9,000 European or African descendants and produced maps of DNA-to-protein links for both groups. Proteins play a critical role in cell function, and changes in protein mechanismsoften can lead to disease. DNA-to-protein mapping might help researchers understand some health disparities.

InNature Genetics, the study appears to be a result of the 2nd of May.

Through so-called genetic mapping studies, researchers have begun mapping human diseases'' molecular roots. The most common is the genome-wide association study (GWAS). Because of its persistence, scientists have identified hundreds or thousands of individuals in the genome sequence who have studied the disease. This study identifies several key genetic variables.

Most of the disease-linked DNA variants identified by GWAS analysis do not belong within 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.

According to a relatively new type of mapping study, scientists will uncover potential proteins connections on a variety of health outcomesrisks of cancers, heart disease, severe COVIDand help to develop or repurpose therapeutic drugs, according to research senior author Nilanjan Chatterjee, PhD, a Bloomberg Distinguished Professor at the Bloomberg School.

The researchers used the DNA-protein mappings technique to identify an existing rheumatoid arthritis medication as a plausible new treatment for the common joint-pain condition known as gout.

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

In the long-running Atherosclerosis Risk in Communities study, led by Coresh, the study covered 7,213 European ancestry and 1,871 African Americans; and 467 African Americans from the African American Study of Kidney Disease and Hypertension (AASK) the research teams had sequenced the genomes of the participants and recorded bloodstream levels.

The Chatterjees team used their ARIC and AASK genomic data to identify more than two thousand common DNA variations that are connected to many of these proteins and correlate with proteins bloodstream levels.

According to Chatterjee, the benefit of being aware of these DNA variants that predict certain protein levels is that we can then investigate much larger GWAS datasets to see if these same DNA variants are linked to disease hazards.

Using a European-American sample, they found that it predicted several proteins whose levels would 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 finding that suggests the existing rheumatoid arthritis medication anakinra, which mimics IL1RN, as a plausible new therapy for gout.

The researchers, who gathered data from both white and black Americans, allowed them to map protein-linked DNA variants more precisely than if they had been restricted to one or the other. The African-ancestry models developed in the study will allow future investigations of how different populations genetic backgrounds might contribute to differences in disease rates.

Prostata cancer risk, for example, is higher in African American men, therefore one might combine prostate cancer GWAS data on African Americans with protein data to identify proteins that contribute to increased prostate cancer risk in the population, according to Chatterjee.

The team has made datasets and protein prediction models available on the Internet, so researchers may use the resource.Chatterjees'' team and collaborators anticipate conducting further research in the ARIC and AASK cohorts, as well as in other diverse cohorts, to obtain information about proteins and other factors that affect the DNA-to-disease chain.

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

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