deCODE genetics: Predicting the probability of death

Rhea-AI Summary

deCODE genetics, a subsidiary of Amgen, has developed a blood-based predictor to estimate time to all-cause death, outperforming traditional risk factors. The research analyzed nearly 5,000 protein measurements from 22,913 Icelanders, revealing a significant correlation between protein profiles and mortality. The predictor effectively identifies individuals at both high and low risk of death within a decade. Key findings include the role of growth/differentiation factor 15 (GDF15) in predicting mortality.

Positive

• Developed a superior predictor of mortality based on protein measurements.
• Identified high-risk and low-risk individuals effectively.
• Utilizes data from a significant sample size of 22,913 participants.

Negative

• None.

REYKJAVIK, Iceland, June 18, 2021 /PRNewswire/ -- Scientists from deCODE genetics have developed a predictor based on protein measurements in blood samples that predicts  the time to all-cause  death better than traditional risk factors.

In a paper published today in Communications Biology, scientists from deCODE genetics, a subsidiary of Amgen, describe how they developed  predictor of how much is left of the life of a person.

Using a dataset of ~5000 protein measurements in 22,913 Icelanders, of whom 7,061 died during the study period, the scientists developed a  predictor of the time to death that can outperform  predictors based on multiple known  risk factors. The predictor can identify the 5% at highest risk in a group of 60-80 year olds, where 88% died within ten years and the 5% at lowest risk where only 1% died within ten years.

The scientists explored how individual proteins associate with mortality and various causes of death and found most causes of death to have similar protein profiles. In particular, they found growth/differentiation factor 15 (GDF15), which has been associated with mortality and ageing before, to be an important predictor of all-cause mortality. Furthermore, they found that, on average, participants predicted at high risk of death within a short period of time had less grip strength and performed worse on an exercise tolerance test and a test of cognitive function than those predicted at lower risk.

"The predictor gives a good estimate of general health from a single blood draw," says Thjodbjorg Eiriksdottir scientist at deCODE genetics and author on the paper.

"This is pretty cool but also scary and hopefully somewhat useful", says  Kari Stefansson a senior author on the paper . "This shows that our general health is reflected in the plasma proteome. Using just one blood sample per person you can easily compare large groups in a standardized way, for example, to estimate treatment effects in clinical trials."

Based in Reykjavik, Iceland, deCODE is a global leader in analyzing and understanding the human genome. Using its unique expertise in human genetics combined with growing expertise in transcriptomics and population proteomics and vast amount of phenotypic data, deCODE has discovered risk factors for dozens of common diseases and provided key insights into their pathogenesis. The purpose of understanding the genetics of disease is to use that information to create new means of diagnosing, treating and preventing disease. deCODE is a wholly-owned subsidiary of Amgen (NASDAQ: AMGN).

Contact:

Thora Kristin Asgeirsdottir
PR and Communications
deCODE genetics 
thoraa@decode.is 
354 894 1909

 

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SOURCE deCODE genetics

FAQ

What is the new predictor developed by deCODE genetics?

deCODE genetics developed a blood-based predictor that estimates time to all-cause death, showing better accuracy than traditional risk factors.

How does the predictor work?

The predictor is based on protein measurements from blood samples, analyzing data from nearly 5,000 proteins.

What company owns deCODE genetics?

deCODE genetics is a wholly-owned subsidiary of Amgen (NASDAQ: AMGN).

How many participants were involved in the study?

The study involved 22,913 Icelanders, with 7,061 deaths occurring during the study period.

What role does GDF15 play in the predictor?

Growth/differentiation factor 15 (GDF15) is identified as an important predictor of all-cause mortality in the study.