A groundbreaking study reveals a blood test capable of predicting an individual's illness trajectory and their potential response to treatment, offering new possibilities for personalised medicine.
A blood test might help predict how one's illness trajectory will proceed and how well they might respond to treatment, according to a study.
The testing method, called 'VeloCD', could predict whether children with acute fever were likely to recover or deteriorate, and whether healthy adults were likely to go on to develop flu or COVID-19 after exposure to the viruses, among other disease trajectories, researchers, led by those from the UK's Imperial College London, said.
Described in a proof-of-concept study and published in the journal Nature Communications, the test measures key markers in the blood -- revealing the levels of gene expression in response to an illness -- to predict the likely trajectory of disease.
Senior author Aubrey Cunnington, head of the department of infectious disease at Imperial College London, said, "We think this type of test could be hugely beneficial for patients and healthcare staff. By offering medics a test which can predict the course of illness it could help them to triage patients much faster, getting the right treatment to the right patient at the right time."
The researchers explained that when one becomes ill, combinations of genes are switched 'on' and 'off' in response, producing RNA markers which can be detected in blood.
Studies have shown that patterns of RNA markers can help identify the cause of one's illness, such as whether a fever is caused by a bacterial or viral infection.
The team used a method called 'RNA velocity', originally developed for studying single cells, but adapted and enhanced to test whole blood samples to find out whether the markers could also indicate prognosis -- whether a patient was likely to get better or worse, and how they would respond to treatment.
The method helped the researchers see which genes were being activated and if their activity was "ramping up or winding down", without having to make repeated measurements over time.
For example, the team could predict whether the changes in the patterns of gene expression in one's blood were becoming more or less like those of individuals with outcomes of interest â for example, severe illness or mild, self-resolving illness.
The results could convey information about a person's future clinical state and the course of their illness, they said.
"We developed VeloCD, a method for quantitative prediction of transitions in clinical state from a single time-point RNA sample," the authors wrote.
"This predicts transcriptomic trajectories and future infection status in influenza A and SARS-CoV-2 controlled human infection studies, which are consistent with trajectories in naturally acquired infections," they said.