Published on: 2026-07-13
Source: Novosibirsk State University –
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At 15th International Multiconference “Bioinformatics of Genome Regulation and Structure / Systems Biology” BGRS/SB-2026 a mathematical model is presented that helps assess the risk of sarcopenia in female patients with rheumatoid arthritis. The study on this topic was conducted by an employee of the sector of computer analysis and modeling of biological systems at the Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, a master’s student Faculty of Mechanics and Mathematics of Novosibirsk State University Anastasia Dolmatova. The development is aimed at providing doctors with a convenient screening tool and reducing the burden on expensive equipment.
Rheumatoid arthritis is a common autoimmune disease in which the systemic pathological process is often accompanied by the formation of unfavorable body composition phenotypes that serve as significant predictors of early disability and reduced quality of life. Among these is sarcopenia — an accelerated loss of muscle mass and strength. The standard for diagnosing sarcopenia is dual-energy X-ray absorptiometry in Total body mode, but this method is not available in all clinics, and simpler screening approaches have low sensitivity, missing up to half of the patients with this unfavorable phenotype. According to Dolmatova, this problem was precisely the starting point for the work.
— I used bioinformatics approaches to create a new screening tool, and as a result, it shows risks and early signs of complication development with high accuracy, — she said.
The created model is based on dimensionality reduction algorithms, clustering, and regression models that allow predicting the patient’s body composition based on clinical data. The input includes test results, objective examination indicators, measurements of waist and hip circumference, and other parameters available in routine rheumatologist practice.
The model does not replace hardware diagnostics but helps determine who should be prioritized for dual-energy X-ray absorptiometry.
— We are saying that if the model indicates a risk, such a patient should be referred for further examination, and this can reduce the burden on the scarce equipment, — explained Anastasia Dolmatova.
Sarcopenia is traditionally associated with old age: it increases the tendency to falls, fractures, loss of work capacity, and disability. However, among patients with rheumatoid arthritis, the risk develops earlier and more frequently, regardless of age. Dolmatova emphasizes that sarcopenia remains reversible at early stages. Nutritional correction, increased physical activity, and replenishment of deficiencies (such as vitamin D) can significantly slow muscle mass loss, making early screening especially important.
A website has already been created where existing approaches to sarcopenia risk assessment are implemented; in the future, the new model is planned to be integrated there as well. Access will be possible both from a computer and from a phone. The developed tool is intended for use by doctors, not patients, since its use requires medical data and examination results, as well as the ability to utilize this information. Thus, the model is considered an element of the clinical workflow, not a means for self-treatment.
The project was implemented in collaboration with clinicians from the Research Institute of Clinical and Experimental Lymphology By Vitaly Omelchenko and By Angelina Starshova, who provided patient data and also participated in the model design and discussion of the results. According to Anastasia Dolmatova, doctors show interest in implementing the tool in practice. The development of the model and software implementation took about a year — the work was carried out as part of a diploma project at the Mechanics and Mathematics Faculty of NSU.
The research is currently ongoing. Doctors are forming an additional sample to test the model on a larger number of female patients and to assess its robustness in different clinical scenarios. During the analysis, an interesting subtype has already been identified — young women whose disease started recently, who are mathematically close in parameters to patients with sarcopenia. This profile was noted by rheumatologists as potentially important: it remains to be determined whether these patients truly have a higher risk of developing sarcopenia in the future.
Anastasia Dolmatova does not rule out that similar mathematical approaches could be adapted for other complications of rheumatoid arthritis, but she emphasizes that in the case of sarcopenia, such models did not exist before, and it is this gap that she set out to fill.
The research is supported by the budget project No. FWNR-2025-0018 of the Ministry of Science and Higher Education of the Russian Federation.
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