Lymphocyte attention: immune aging base will help create HIV drugs
Scientists have compiled a database of aging immune cells, which in the future will make it possible to test new drugs, including HIV medicines. The specialists covered an unprecedented range - from newborns to long-livers. The oldest person whose information was used in the study is 111 years old. The results of the work make it possible to determine whether the immune status of the patient corresponds to the real age or is greater. Based on the development, they also plan to create software that will help not only to test drugs, but also to see how effective their combinations are.
What T-lymphocytes are responsible for
Specialists of the Center for Mathematical Modeling in Drug Development of Sechenov University together with researchers from the Institute of Computational Mathematics of the Russian Academy of Sciences and foreign colleagues analyzed more than 120 clinical studies aimed at studying the homeostasis (normal state) of T-lymphocytes of people of different ages, and quantitatively characterized the dynamics of aging immune cells. The obtained unique database is planned to be used to build mathematical models of infectious diseases, in particular HIV. They will help drug developers to significantly accelerate the creation of new drugs.
T-lymphocytes are immune cells that can recognize and destroy certain infectious agents or tumor cells. However, as we age, the immune system's ability to fight pathogens decreases. In order to investigate the immunologic status to the fullest extent, it is necessary to evaluate the work of not only the general T-lymphocyte populations, but also their specific subpopulations (subtypes). For example, the number of naive T cells (immune system cells that have not yet encountered an antigen), cells that provide immunologic memory, and effector cells - the main "soldiers" of the immune system.
The resulting database contains measurements of immune cell concentrations not only in the blood, but also in other organs and tissues.
- Each clinical trial that we analyzed has a limited data set - both in terms of the number of participants and their age - said the author of the work, junior researcher at the Center for Mathematical Modeling in Drug Development of Sechenov University Victoria Kulesh. - Applying a systematic approach to collecting and analyzing all available information, we managed to cover not only a huge number of measurements, but also an unprecedented range in age - from newborns to long-livers. The oldest person in our database is 111 years old.
For the first time, scientists applied the methodology of meta-analysis to study the age dynamics of immune cells. This approach made it possible to summarize all available quantitative information on the concentration of various cells and to determine reference values in people within a narrow age range.
Through this description of "healthy" immune aging processes, researchers can improve the diagnosis and determination of the immune status of patients with HIV and other autoimmune or viral chronic diseases, the specialist said. In the future, this will make it possible to personalize therapy based on the number of immune cells a patient has.
Why we need a database of immune cells
Another result of the work scientists called the receipt of an unprecedented database on the work of the immune system, information from which will be used to build mathematical models of immune aging.
For example, experts have found out that memory T-cells and effector cells (immune cells that respond to neural impulses) reach their peak concentration in children from one to five years old. And naive T lymphocytes (cells that have not yet encountered an antigen) - in children under a year old. The study also showed that age-related changes in the concentration of T-lymphocytes in the organs of the lymphatic system do not differ significantly from their content in the blood. This means that blood studies provide an accurate assessment of immunologic status, the scientists said.
The results of the study are planned to be used to develop a system-pharmacological platform for mathematical modeling of infectious diseases, in particular HIV, said Victoria Kulesh. With the help of the base , drug developers will be able to significantly accelerate the creation of new anti-infective drugs, optimize their dose and regimen, determine the optimal targets of their effects and predict the effectiveness of combinations of drugs.
- The results of this work are a starting point for the construction of physiologically based models for infectious and autoimmune diseases (i.e. models reflecting the real development of diseases, functioning of the organism). In the near future, these results will be used to develop a model of the dynamics of HIV infection, - said the expert.
The data will also be used to develop models in systemic lupus erythematosus, dermatomyositis, scleroderma, viral hepatitis and other diseases affecting the immune system.
Thecombination of neural networks, bioinformatics and experimental work can significantly accelerate the process of developing new drugs, said Healthnet STI market expert, Doctor of Pharmaceutical Sciences Tatiana Ryazanova.
- Undoubtedly, creation of such databases is necessary for modeling etiogenesis and pathogenesis of diseases, in particular of infectious nature. In addition, in combination with other methods of virtual drug screening, the platform may be useful for predicting the efficacy of drugs or their combinations," she said," she said.
The more details in such models, the more accurate it is, said Mikhail Bolkov, a researcher at the Institute of Aging Research at the Russian State Research and Clinical Center of the N.I. Pirogov Russian National Research and Clinical Center of the Russian Ministry of Health.
- Fine details allow us to assess how cells inside the body move, exchange signaling molecules, participate in some inflammation or infection. Here we can assess the aging of the organism, and how the range of its capabilities changes in the course of life depending on various factors. Such a factor could be HIV infection, which already aggressively affects the body," he told Izvestia.
In the future, based on this work, it is planned to build a system-pharmacological model of infectious diseases in the form of software, the developers said. Detailed results of the study are published in the scientific journal Frontiers in immunology.
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