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WCM-Q researchers publish landmark study into proteins

WCM-Q researchers publish landmark study into proteins

Monday, May 13, 2024/ Editor -  


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Doha – May 13, 2024: Researchers at Weill Cornell Medicine-Qatar (WCM-Q) have published a study that marks the introduction to Qatar of some of the world's most advanced analytical tools for discovering the links between genetic variations, proteins and a wide range of diseases.

Using a new tool to measure proteins, WCM-Q researchers Dr. Karsten Suhre and Dr. Frank Schmidt analyzed the blood samples of more than 320 individuals from a multi-ethnic cohort in Qatar. The tool, called the Proteograph Product Suite, allowed the WCM-Q researchers to quantify more than 18,000 different peptides (molecular structures formed of amino acids) from more than 3,000 proteins.

Bringing this new tool, provided by the US-based biotechnology company Seer, to WCM-Q further enhances Qatar's emerging status as a leader in the field of proteomics, which is the large-scale study of proteins, their structures, interactions, functions, and their impact on health.

Lead author Dr. Suhre, Professor of Physiology and Biophysics at WCM-Q, explained the significance of the new tool. He said: 'To understand how genetic diseases function, it is not enough to simply identify the genetic variation that causes the disease. We need to know more, how genes direct which proteins are synthesized by the body, in what quantities, and how they function. So, by analyzing the relationships between the natural genetic variations in the human population and their effects on specific proteins we can obtain a deeper understanding of how organisms function as a whole, and also eventually a greater understanding of how genetic diseases come about and how to treat them. We believe this understanding can provide researchers with targets for the development of new drug therapies to treat complex diseases and alleviate suffering for patients in need.'

Diseases which are linked to genetic variants in proteins that have been addressed by the study include coronary artery disease, type 2 diabetes, amyotrophic lateral sclerosis, and atrial fibrillation. Discovering the complex associations between genetic variants and proteins by merging proteomics and genomics research approaches (known as multiomics) is considered to be an extremely promising avenue for unearthing new therapies for a wide range of diseases, including cardio and metabolic disorders.

The study, published in Nature Communications, a leading scientific journal, provides evidence that the new analytical tool from Seer has enhanced capabilities to perform a process called 'protein quantitative trait loci mapping' (pQTL). This is the identification of links between particular positions on a gene and the presence of a certain amount of a particular protein, which is important because many serious genetic diseases are caused by protein dysregulation. Using the tool, the researchers were able to report in the study that they identified 184 protein-altering variants in 137 genes, which they were also able to associate with corresponding variant peptides, providing extra confirmation of the accuracy of their observations.

The study also showed that the new Seer tool eliminates some of the problems with alternative proteomics analytical tools (called affinity-based tools), which have been used to successfully identify many thousands of pQTLs, but which have a tendency to produce confounding results and can therefore give a confused picture of the presence and function of proteins.

Dr. Schmidt, Associate Professor of Biochemistry and Director of the Proteomics Core at WCM-Q, said: 'To investigate proteins, you need a way to identify and quantify them in samples of human tissue, such as blood. This involves some complicated chemistry and analysis with mass spectrometers, followed by analysis using powerful computers because there is a lot of information to sort through—it is quite technically challenging. Our study shows that the Seer Proteograph platform enables us to do this with an enhanced level of accuracy and in high quantities—we can identify and quantify more proteins and match them more accurately with the genes that code each protein, so we can build up far more comprehensive and accurate pictures of how genetic variations code for particular formations of proteins, including formations that subsequently cause disease.'

He added: 'This new tool quite radically improves our capacity to understand these relationships between genetic variations and protein expression, and helps to build upon Qatar's growing role as a global leader in the exciting and important field of proteomics research.'

It is hoped that the development of enhanced proteomics research capacity at WCM-Q will contribute positively to the college's bid to host the 2026 World Congress of the Human Proteome Organization (HUPO) in Qatar. WCM-Q operates multiple research cores, which can be engaged by other research institutions to perform a number of key research tasks, which has helped establish the college—and Qatar—as the region's leading biomedical research hub.

Dr. Khaled Machaca, Professor of Research in Physiology and Senior Associate Dean for Research, Innovations, and Commercialization at WCM-Q, said: 'Proteomics is an extraordinarily exciting and important area for research, holding huge potential for discoveries with applications in precision medicine, such as the possible development of new therapies for treating inherited genetic diseases, among many other promising avenues. This landmark study by Dr. Suhre and Dr. Schmidt highlights Qatar's global capabilities in proteomics research.'

The study was the result of a collaboration between WCM-Q and Seer, a commercial company. Neither WCM-Q nor any of the WCM-Q faculty listed as authors of the research paper has any financial interest or commercial relationship with Seer, Inc. Dr. Suhre and Dr. Schmidt are supported by the Biomedical Research Fund at WCM-Q, a program supported by Qatar Foundation. Dr. Suhre is also supported by the Qatar National Research Fund (QNRF) grant NPRP11C-0115-180010.

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