Blood test can help predict susceptibility to placebo effect

The Matrix / Warner Bros. Pictures, 1999

A proteomic blood test will help determine how a patient will respond to placebo treatment, it says in a study published in the journal PLoS ONE… Biologists analyzed the protein composition of the blood of patients who received placebo treatment and those who did not. They found a difference in the content of proteins of the complement system in these groups and based on this data they created a predictive model.

Placebo Is any simulation of the patient’s treatment that is carried out without his knowledge. This can be the use of tablets without the active ingredient, injections of saline solution, or imitation of medical procedures. It is known that such a “fake” treatment can lead to real physiological improvements.

Despite the fact that many studies have been devoted to placebo and it is actively used in clinical trials (eg, COVID-19 vaccine), the mechanism of the placebo effect is still not fully understood. Most of the research on this topic is based on the neurophysiology and neurochemistry of patients: known, for example, that neurotransmitters, which are endogenous opioids, are involved in the mechanisms of the placebo effect of pain suppression.

Researchers from the University of Munich, led by Karin Meissner, decided to investigate the relationship between the placebo effect and the protein composition of the blood. To do this, they rocked 100 healthy patients in special chairs to make people nauseous. The patients were divided into three groups: 60 people were “treated” with placebo, 10 with real drugs for nausea, and 30 were not treated at all. Real treatment was only needed so that the researchers who dispensed the drugs to the patients did not know what they were dispensing. This approach is called a double-blind study and is almost always used when using a placebo.

All patients were rocked for 20 minutes, after which they rested an equal amount, and some received treatment or placebo. The researchers took plasma from patients for analysis, and the subjects told the researchers how severe they were. Subsequently, the changes were recorded according to the degree of nausea, difficulty in movement and intestinal activity.

Of the 60 patients in the placebo group, 39 showed an improvement in the treatment of nausea, and only 5 out of 30 in the untreated group. The differences between these groups were significant (p < 0.01). Чтобы исследовать состав плазмы крови пациентов, исследователи использовали метод mass spectrometry… For this, all molecules in the plasma solution were ionized and dispersed in a mass spectrometer. A detector in the device senses moving particles and determines the ratio of charge to mass. Knowing the charge after ionization, it is possible to determine the mass of each molecule in solution.

A total of 711 proteins were found, of which 74 differed significantly between the groups with and without placebo. To investigate the mechanisms of the placebo effect, scientists conducted a bioinformatic analysis of all proteins and found that their genes belong to a functional group of the complement system – enzymes that perform a protective function in the blood and are involved in the immune response.

Based on this data, the scientists created a bioinformatic model that was able to predict the response to placebo based on the content of proteins in the blood. For nausea, the prediction accuracy was AUC = 0.86 – this estimate shows the coincidence of the prediction and the actual result from 0 to 1, where 0.5 or less means a coincidence.

So researchers from Munich showed the molecular basis of the placebo effect and developed a system for predicting exposure to it. It is quite convenient to conduct blood tests of patients – therefore, such a system can be useful for clinical trials that include placebo.

A few years ago, scientists discovered the area of ​​the brain responsible for the response to placebo. In an experiment, the activity of this region and its neural connections helped to reliably predict in which patients placebo would be effective, as well as the magnitude of this effect.

Anya Muravyova

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