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Contract number
074-02-2018-330, 075-15-2019-871 (1), 075-15-2021-639
Time span of the project
2018-2022

As of 01.11.2022

61
Number of staff members
47
scientific publications
6
Objects of intellectual property
General information

Name of the project: Digital personalized aging medicine: network analysis of Big multi-omic data for the search of new diagnostics, forecasting and therapeutics.

Goals and objectives

Research directions: Clinical medicine, geriatrics and gerontology

Project objective: Search for new medical strategies for ensuring healthy aging, increasing life expectancy of the population and, as a result, increasing quality of live.

The practical value of the study

Scientific results:

The project «Digital personalized medicine of healthy aging» is aimed at studying new strategies to ensure healthy aging, increase life expectancy and its quality. The research implies searching for a combination of specific cellular and molecular changes and pathways determining and responsible for changes in the phenotypes of elderly people from healthy physiological aging to clinically evident pathologies. As a result, markers for early diagnostics of pathology in analyses of blood  and other fluids of the organism should be determined, allowing to diagnose conditions long before other symptoms manifest themselves. The main idea of the project is to use the existing and newly developed biological concepts as well as mathematical and computational methods of data analysis: methods of machine learning, network analysis and artificial intelligence, which should overcome the barrier of existing medical big data and discover complex biomarkers and risk factors and to protect accelerated or decelerated aging, as well as to find new forecasting and therapeutic targets. At the same time, we set the task to explain the observed changes using models of systemic medicine, relying on various network, dynamic and mathematical models.

Reviewing the four years of implementation of the project, it is possible to briefly list the following main academic results: we have initiated the accumulation of a biobank for the research of the processes of aging and age-related diseases in the population of Russia, for the fist time we have conducted an assessment of the acceleration of the epigenetic age in the population of Russia, we have obtained new immunological markers of human aging, on the basis of those we developed immunological biological clock, studied the epigenetic markers of a number of age-related diseases and syndromes, determined promising protection variants of mitochondrial DNA, demonstrated the population heterogeneity of the speed of the epigenetic clock, researched mathematical models of neuron-glial interactions in the context of the development of aging, researched the relation of chronic sleep deprivation and the physiological and cognitive state of model animals.

During the implementation of the research plan, the main efforts were focused on several directions. The following main results have been achieved:

  1. Research of the epigenetics of the aging of the population of Russia. Data accumulation and analysis.
  2. We have researched open problems of the acceleration of the epigenetic age in the Russian cohort compared to the European one, as well as differentially methylated regions that are specific to the population. An analysis of four most common epigenetic clocks did not indicate a statistically significant difference in the acceleration of epigenetic aging. A differential analysis of methylation showed insignificant differences in 57 genes, some of which are related to diseases that are most common in developing countries. Our researchers described an extended biobank, characterized the accumulated samples and conducted research, including epigenetic studies

  3. Research of chronic inflammatory processes in people with normal and accelerated aging.
  4. We have researched epigenetic and immunological or inflammatory biomarkers of age in patients with chronic kidney disease. Aging and age-related diseases have common basic principles that are, to a significant degree, reduced to inflammation. An important risk of the aging of the immune system is chronic kidney disease – a widespread and irreversible pathology. Chronic kidney disease progressing to the terminal stage is considered a serious problem of public healthcare. In periods between hemodialysis sessions patients remain in a state of severe intoxication, as kidneys of patients lose the detoxification function. It was demonstrated that the majority of epigenetic clocks, in particular, DNAmPhenoAge and GrimAge, show the age acceleration in a group of patients. We also demonstrated that the external acceleration of epigenetic aging dies not differ between groups, which testifies to the fact that immune aging is not the main trigger of aging in a group of patients. The phenotypic age shows a more pronounced acceleration of aging in patients with chronic kidney disease. We identified 18 plasma proteins with significantly different levels in patients with chronic kidney disease and in healthy individuals. This data show that a significant number of cytokines of the immune system are related both to age and to chronic kidney disease, according to the theory of inflammation[1].

  5. Research of the genetics, epigenetics and proteomics of aging.
  6. The Laboratory has conducted a network analysis of the epigenetics of individuals with the Down syndrome. Parenclitic networks are a powerful approach to determining hidden relations between covariants. Applying such analysis to families with children suffering from the Down syndrome allowed to find remote jointly regulated genes associated with the pathology. We found biological processes and signaling pathways characteristic not only of patients with the Down syndrome, but also linked to age-related changes in the organism. We demonstrated the relationship between network characteristics and accelerated aging and compared the results with acceleration computed on the basis of the Horvath clock [3]. Even though the method provides good opportunities for data analysis, a necessary part is assessing the stability of results. As a consequence of such assessment, we demonstrated that during cross-validation the sample sat remains the same for 87 per cent. Such a high level of stability confirms the correctness of the selected set of genes and CpG sites. However, we also found weak relationships that are excluded using the standard method. To subsequently solve this problem, we have developed and tested a new synological method, as well as performed a comparison of this method with standard machine learning algorithms [2].
    We have reviewed the generally available datasets of methylated DNAs of four regions of the brain (the temporal lobe, the frontal lobe, the entorhinal cortex and the cerebellum) in healthy adults and patients with the Alzheimer’s disease (AD) and conducted a meta-analysis to determine gender-, age- and AD-related  epigenetic profiles. AD is characterized by specific changes in the patterns of DNA methylation in the brain. It is known that age and gender, two main risk factors in AD, significantly affect the epigenetic profiles in the brain, but their contribution to changes in the DNA related to AD are not well-studied. As a result of the analysis, we demonstrated that differences in DNA methylation between men and women are usually characteristic of four regions of the brain, while the effect of the aging of regions of the cortex are different compared to the cerebellum. The differences between men and women generally are maintained with age. The epigenetic modifications related to AD are significantly enriched with probes whose DNA methylation changes with age, and there is correspondence between the direction of changes (hyper- of hypomethylation) during aging and the Alzheimer’s disease, which confirms accelerated epigenetic aging in the disease. Therefore, the results demonstrate that age-related patterns of DNA methylation coincide with the epigenetic deregulation observed in AD, which provides an understanding of the way elderly age contributes to neurodegeneration [4].
    Our researchers have conducted a comparative analysis of age-related biomarkers obtained using epigenetics for various tissues (whole blood, the prefrontal cortex and the liver) with biomarkers obtained from plasma proteins to determine similarities between various types of data. Identifying such signatures can help to understand the mechanisms of the aging of the organism in the context of gender dimorphism. At the intersection of all the sources (including proteomics), we found 18 genes, specific to gender and related to age. The determined genes are significantly enriched with biological processes related to activity of neurons, which changes with age and can differ in men and women. These genes are also related to such chronic diseases as atherosclerosis, schizophrenia, the Parkinson’s disease, leprosy, which are age-related and pose various risks in men and women.
    We have studied co-mutations of mitochondrial DNA as factors of defense under extreme conditions. Networks are a powerful basis for understanding and forecasting the behavior of many large-scale complex systems. While conducting this analysis, we, for the first time, reviewed network motifs, the main building blocks of networks, to describe the possible role of simultaneous emergence of genome variations in the basis of adaptation to highlands in the Asian population. Variations of mitochondrial DNA are recognized as one of the key players in the understanding of the biological mechanisms of adaptation to extreme conditions. An analysis of motifs using clusterization uncovered the difference between lowland and highland regions. Moreover, we found that the ancestral variant «RSRS50» 10398 is found only at high altitudes, which confirms the fact that at such altitude a separate colonization path could take place. As a whole, the analysis revealed the presence of collateral interactions of high latitude at the level of the whole genome [6].
    An analysis of samples of human mitochondrial genome collected across five continents using the model of a co-mutation network to study models of the evolution of the human uncovered richer co-mutating regions of mitochondrial DNA, which points at the presence of epistasis. In particular, we found that the majority of СОХ enzymes co-mutate in Asian and American populations, while in Africa, European and Oceanic populations a greater shift of co-mutations in hypervariable regions is observed.  Moreover, an analysis based on an ancestral sequence has demonstrated that the mutations are predominantly concentrated in known mitochondrial haplogroups. Nucleotides of the mitochondrial genome of the modern human are most reminiscent of the ancestral state, and very few of them turned out to be the ancestral variants. As a whole, these results demonstrated that co-mutations at the level of a subpopulation can contribute to epistasis that is specific to the mitochondrial genome [5].

  7. Research of the heterogeneity of the process of aging.
  8. On the basis of open longitudinal data we have researched the heterogeneity of the process of aging. We determined the nature of the intrapopulation variability of the mitochondrial DNA [7] and the variability of the biological age of the subjects of the same chronological age. We have analyzed individual longitudinal trajectories of charges of epigenetic age obtained using four most widely known DNA methylation clocks. As a result of this research, we demonstrated that there exist considerable differences in changes of the biological age of humans, be it a constant difference between the epigenetic and the chronological age or gradual divergence over the course of the whole life. The obtained results confirm the existence of individual aging trajectories

  9. Research of multi-dimensional biomarkers of aging and age-related diseases.
  10. A multi-dimensional immunological/inflammatory biomarkers of age in patients with chronic kidney disease has been determined. Inflammation clocks are a part of a large family of biomarkers of aging. Multiple researchers have shown that the process of aging and the onset of age-related syndromes and diseases is accompanied by epigenetic changes in the DNA and can be under the influence of external factors, such as alcohol smoking, the microbiome profile, the region of residence, and nutrition. Recent research demonstrated the relationship between the epigenetic clock and the kidney disease, but it did not include patients with the terminal stage of chronic kidney disease. We developed inflammatory/immunological clocks that evaluate the chronological age of healthy individuals and evaluate the influence of inflammation on the acceleration of aging. The implementation of machine learning algorithms allowed to select significant immunological biomarkers and build a model of the ipAGE clock that accounts for complex relationships and the redundancy of the cytokine network. The mean absolute error of the clock is about 6 years, which can compete with the ipAGE epigenetic clock in terms of precision. ipAGE successfully determines the acceleration of aging in patients with chronic kidney disease [1].

  11. Research of processes of neurodegeneration and inflammation.

    We have conducted experiments to determine the influence of chronic sleep deprivation on cognitive indicators of experimental animals with a model of the family form of the Alzheimer’s disease (5хFAD mouse line) in two age groups (7–9 and 12 months) [8]. We modified methodologies for modeling chronic sleep deprivation, since mice of the 5хFAD line aged 7–-9 months and older cannot withstand 10 hours of sleep deprivation. We assessed training and reconsolidation of spatial memory in the «Morris water maze», evaluated the psycho-emotional status and general motor activity of animals after modeling chronic sleep deprivation in the «Open field» test, determined morphological changes after deprivation in animals with the family form of the Alzheimer’s disease in two age groups. We researched the general level of DNA methylation in the blood of experimental animals after chronic sleep deprivation is modeled

  12. Mathematical modeling of inflammatory aging of the brain. Research of intercellular network signaling in astrocyte-neuron networks of the brain.

    Using mathematical modeling methods, we have researched the concept of «inflammatory» aging in brain tissues. We reviewed the way the process of aging induces suppressing anti-inflammatory cells and, therefore, transition of various types of cells to the inflammatory phenotype (decreasing heterogeneity of cells and clonal expansions), which leads to the propagation of a senescent wave [9]. We developed a model of the propagation of inflammatory aging in the brain [10]. The model describes the relation between the sleep regime and the dynamics of the concentration of «metabolic trash» in the extracellular environment of the brain, intercellular interactions between healthy and aging glial cells. The research of the impact of the reviewed biophysical mechanisms on the rate of aging,, as well as dynamic modes of the development of the process of aging was conducted using numerical modeling methods. Our research demonstrated that sleep deprivation leads to an increase in the concentration of metabolic trash and, as  a consequence, to pathologically active work of microglia leading to the aging of cells. 

Implemented results of research:

One of the results of the implementation of the project is the development of the web application «Cognitive age calculator». The main goal of the calculator is to evaluate the cognitive status of an individual with the use of maximally simple and easily scalable techniques.
The research that allowed us to create the «Cognitive age calculator», which is based on an analysis of the results of cognitive tests, biochemical blood analyses and epigenetic markers of 118 individuals. Using artificial intelligence and machine learning, we have built a model for assessing cognitive age on the basis of three cognitive tests: campimetry and two sensorimotor tests. The produced model has a detection accuracy of 8 years for chronological age and 6 years for biological age on the basis of epigenetic markers.
Cognitive online calculator based on artificial intelligence with a precision of 8 years determines the «age of mind» as a result of three tasks performed by the respondent. The tasks were aimed at evaluating attentiveness, speed of reaction and visual acuity. To complete the test, the subject only needs a computer, a mouse and ten minutes of free time. The model of the calculator was designed for people aged from 18 to 90, but we are planning to modify the algorithm so it can be used by people of any age. 

Education and career development: 

The leading scientist and the key members of the research team of the Laboratory organized 4 topical conferences and scientific schools, we are delivering lectures and supervising students and young researchers in their research in mathematics, information systems, bioinformatics, genetics and psychology. It is worth noting that the Laboratory has experience in fulfilling commercial agreements to perform research and evaluation of biological age on the basis of biochemical blood analysis.

During the implementation of the project, we compiled and implemented the following education programs:
  1. Residency program: 31.08.49 «Therapy», authors: Maria V. Vedunova, Nadezhda A. Lobanova,  implemented at Nizhniy Novgorod State University, 2021.
  2. Residency program: 31.08.09 «Radiology», authors: Maria V. Vedunova, Nadezhda A. Lobanova, implemented at Nizhniy Novgorod State University, 2021.
We have organized internships at the University of Bologna (Italy) for two undergraduate students, 2 postgraduate students and 3 young researchers.

Scientific schools and conference were held:
  1. International conference in neurosciences «Volga Neuroscience Meeting 2018l. As part of the conference we conducted the symposium «System biology and age-related diseases.
  2. 72nd All-Russian school-conference with international participation for young researchers «Biosystems: organization, behavior, control», 2020, devoted to the topic of the project.
  3. 73rd All-Russian school-conference with international participation for young researchers «Biosystems: organization, behavior, control», 2021.
  4. International conference «Volga neuroscience meeting 2021». As part of the conference we conducted the workshop on the topic of the project «Molecular mechanisms of aging».
A Candidate of Sciences dissertation has been prepared on the topic «Research of features of immune response in immunogenic cell death». 

Organizational and structural changes:

On the basis of Nizhniy Novgorod State University we have organized the Center for Healthy Aging, the primary goal of which is to conduct pioneering research in the domain of the epigenetics of the aging of the Russian population. Moreover, in 2022 in Nizhniy Novgorod State University a new division, the Institute for Research on Aging was created. The main objectives of the institute are: fundamental aspects of aging, artificial intelligence and computational biology, cancer and age, cellular stress, senescence and disease, metabolism (exercise and nutrition ), neurodegeneration and resetting regeneration. 

Collaborations:
  • University of Bologna (Italy), University College London (United Kingdom), Rey Juan Carlos University (Spain): joint research.
  • The Laboratory also cooperates with the Ufa Federal Scientific Center of the Russian Academy of Sciences, Samara State Medical University, the Komi Scientific Center of the Ural Branch of the Russian Academy of Sciences, Voronezh State University of Engineering Technology (Russia), some Nizhniy Novgorod city hospitals.

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Yusipov I., Bacalini M.G., Kalyakulina A., Krivonosov M., Pirazzini C., Gensous N., Ravaioli F., Milazzo M, Giuliani C, Vedunova M., Fiorito G., Gagliardi A., Polidoro S, Garagnani P, Ivanchenko M., Franceschi C.
Age-related DNA methylation changes are sex-specific: a comprehensive assessment. Aging (Albany NY), 2020, July, (Vol. 12, no. 23, pp. 24057).
Yusipov, I., Kondakova, E., Kalyakulina, A., Krivonosov, M., Lobanova, N., Bacalini, M. G., Franceschi C., Vedunova M., & Ivanchenko, M.
Accelerated epigenetic aging and inflammatory/immunological profile (ipAGE) in patients with chronic kidney disease. GeroScience, 2022, Apr., (Vol. 44, no. 2, pp. 817-834).
Franceschi, C., Zaikin, A., Gordleeva, S., Ivanchenko, M., Bonifazi, F., Storci, G., & Bonafè, M.
Inflammaging 2018: an update and a model. In Seminars in immunology, 2018, Dec., (Vol. 40, pp. 1-5).
Kalyakulina, A., Iannuzzi, V., Sazzini, M., Garagnani, P., Jalan, S., Franceschi, C., Ivanchenko M. & Giuliani, C.
Investigating mitonuclear genetic interactions through machine learning: A case study on cold adaptation genes in human populations from different european climate regions. Frontiers in physiology, 2020, Nov., (Vol. 11, pp. 1664-042Х)
Whitwell, H. J., Bacalini, M. G., Blyuss, O., Chen, S., Garagnani, P., Gordleeva, S. Y., Jalan S., Ivanchenko M., Kanakov O., KustikovaV., Mariño I.P., Meyerov I., Ullner E., Franceschi C. & Zaikin, A.
The human body as a super network: Digital methods to analyze the propagation of aging. Frontiers in aging neuroscience, 2020, May, (Vol. 12, pp. 136).
Kalyakulina, A. I., Yusipov, I. I., Moskalenko, V. A., Nikolskiy, A. V., Kosonogov, K. A., Osipov, G. V., Zolotykh N.Yu. & Ivanchenko, M. V.
Ludb: a new open-access validation tool for electrocardiogram delineation algorithms. IEEE Access, 2020, Jan., (Vol. 8, pp. 186181-186190).
Pellegrini, C., Pirazzini, C., Sala, C., Sambati, L., Yusipov, I., Kalyakulina, A., Ravaioli F., Kwiatkowska K. M., Durso D. F., Ivanchenko M., Monti D., Lodi R., Franceschi C., Cortelli P., Garagnani P. & Bacalini, M. G.
A meta-analysis of brain DNA methylation across sex, age, and Alzheimer's disease points for accelerated epigenetic aging in neurodegeneration. Frontiers in Aging Neuroscience, 2021, Mar, (Vol. 13, pp. 639428)
Vershinina, O., Bacalini, M. G., Zaikin, A., Franceschi, C., & Ivanchenko, M.
Disentangling age-dependent DNA methylation: deterministic, stochastic, and nonlinear. Scientific reports, 2021, Apr., (Vol. 11, no. 1, pp. 1-12).
Novozhilova, M., Mishchenko, T., Kondakova, E., Lavrova, T., Gavrish, M., Aferova, S., Franceschi C., & Vedunova, M.
Features of age-related response to sleep deprivation: in vivo experimental studies. Aging (Albany NY), 2021, Jul, (Vo. 13, no. 15, pp. 19108).
Krivonosov, M. I., Kondakova, E. V., Bulanov, N. A., Polevaya, S. A., Franceschi, C., Ivanchenko, M. V., & Vedunova, M. V.
A new cognitive clock matching phenotypic and epigenetic ages. Translational psychiatry, 2022, Sep., (Vol. 12, no. 1, pp. 1-9).
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