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Biomarked for Death—Four Blood Proteins Can Predict Early Demise

While you may appear to be healthy, you may be frailer than you know. You may even be at risk of death—from one disease or another—within the next five years. Would you want to know? You may now have the choice, thanks to researchers at the Estonian Genome Cen

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While you may appear to be healthy, you may be frailer than you know. You may even be at risk of death—from one disease or another—within the next five years. Would you want to know? You may now have the choice, thanks to researchers at the Estonian Genome Center and the Institute for Molecular Medicine, Finland.

These researchers have developed a screening technology. It looks for four biomarkers that have been associated with a risk of dying from any disease in the near future. Ordinarily, biomarkers are used to assess an individual’s risk of developing a specific condition. The new screening technology, however, is used to reveal general frailty, even in apparently healthy people. It reflects the risk for dying, whatever the ultimate cause—heart disease, cancer, or any other condition.

The biomarkers identified by the researchers are albumin, alpha-1-acid glycoprotein, citrate, and the size of very-low-density lipoprotein particles. Of these, albumin was the only one previously linked with mortality. All these molecules are normally present in everyone’s blood—the amounts of these molecules are what matter. To assess the degree to which an individual’s biomarkers are imbalanced, the researchers found a way to compile a biomarker score.

The researchers found that individuals with a biomarker score in the top 20% had a risk of dying within five years that was 19 times greater than that of individuals with a score in the bottom 20% (288 versus 15 deaths). In addition, biomarker scores were still predictive of early death—that is, a death within the next five years—independent of well-known risk factors such as age, smoking, drinking, obesity, blood pressure, and cholesterol.

The researchers detailed their results February 25 in PLOS Medicine, in an article entitled “Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons.” To carry out their study, the researchers relied on technology that allowed them to screen blood samples for a wide range of blood biomarkers.

This technology, nuclear magnetic resonance (NMR) spectroscopy, screened for over 100 potential biomarkers in two cohorts of healthy people. The first cohort, investigated by Estonian members of the research team, consisted of 9,842 people. So astonished by what they found, the Estonian scientists asked their Finnish colleagues to repeat the experiment. The Finnish cohort, consisting of 7,503 people, produced the same result: Just four biomarkers are predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases.

While the researchers emphasized that more studies would be needed before their findings could be implemented in clinical practice, they expressed optimism that their work could alert seemingly healthy people to the need for medical intervention. One of the study’s Finnish authors, Johnannes Kettunen, said, “We believe that in the future these measures can be used to identify people who appear healthy but in fact have serious underlying illnesses and guide them to proper treatment.”

In discussing their results, the authors of the PLOS Medicine story wrote, “In spite of [this study’s] limitations, the fact that the same four biomarkers are associated with a short-term risk of death from a variety of diseases does suggest that similar underlying mechanisms are taking place. This observation points to some potentially valuable areas of research to understand precisely what’s contributing to the increased risk.”

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Related questions

01How stable is the antibody?

A crucial question often addressed during preclinical development focuses on the in vivo stability of therapeutic antibodies. Increasing the half-life of a therapeutic antibody has several benefits ranging from higher treatment efficacy to increased advantages for the patients who will have a fewer number of therapy sessions and a reduced cost. Given these compelling benefits, following the identification of therapeutic antibodies with the desired specificity, developers usually subject them to a refinement step to increase their stability. This process is often hindered by the lack of reliable experimental tools to predict the half-life of antibodies in patients. The major hurdle of using mouse models to predict antibody stability in the serum lies in the way immunoglobulin proteins are processed by the organism. In mammals, most proteins circulating in the serum undergo constant uptake by endothelial cells and are routed through the endosomes to the lysosomal compartment for degradation. In the endosomes, immunoglobulin G (IgG) proteins are recognized and bound by a transmembrane protein, called the neonatal Fc receptor (FcRn), which mediates their recycling to the plasma membrane and subsequent release back into the serum. As a result, the half-life of IgGs are significantly extended by this mechanism. Since most therapeutic antibodies belong to the IgG class, this recycling system is very relevant for their relative stability in the body. Remarkably, the relative affinity between IgGs and FcRn is extremely disparate between different species, with the mouse receptor showing a much higher affinity than its human counterpart.

Source: www.genengnews.com ↗
02Undruggable or unscreenable?

Another obstacle to discovering new PPI inhibitors is the lack of libraries designed to hunt for them, points out Philippe Roche, PhD, senior scientist at the Integrative Structural and Chemical Biology team at the Cancer Research Center of Marseilles, France. “If you screen PPIs using libraries that were designed for kinases or GPCRs, that’s why you don’t get a lot of good results,” he says. To that end, his group began assembling a library focused on orthosteric inhibitors of PPIs. The result was 2P2Idb, a hand-curated, structural database cataloguing orthosteric inhibitors of PPIs for which the interface had been 3D characterized. From analyzing these known PPI inhibitors, and what structures they had in common, Roche and his colleagues developed a model to predict whether compounds would likely inhibit PPIs. Using this method, 2P2Idb creates an enriched screening library that dramatically increases the hit rate compared to standard libraries. Having proven their success with a small library of 1600 compounds, they are in the process of expanding the library to 10,000 compounds. Once that’s published, “the idea is to make this library available to labs around the world,” Roche says. “We will provide the library free of charge for people to be able to screen PPI targets.”

Source: www.genengnews.com ↗
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Peptide Therapy Guide Editorial Team

Editorial team for Peptide Therapy Guide.

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