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Laboratory for Statistical Multi-omics and Bio-informatics

Contract number
075-15-2021-595
Time span of the project
2021-2023
Invited researcher

As of 01.11.2022

33
Number of staff members
22
scientific publications
3
Objects of intellectual property
General information

Name of the project: The development of high-performance computational tools for the complex analysis of multi-omics data and the evolvement of personalised medicine

Goals and objectives

The project is aimed at the development of high-productivity computational tools for complex analysis of multi-omics data and the development of personalised medicine. To achieve this, we a planning to create a laboratory for statistical multi-omics at the Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences (IBG UFRC RAS). A high-performance computing cluster and an open online platform for data collection and analysis will also be created. The research will be conducted using existing biological samples and phenotypic data of the IBG UFRC RAS that is a centre for deposition and storage of unique gene banks of the DNAs of   aboriginal inhabitants of various regions of Russia as well as of patients with various diseases and their family members.

We are also planning to expand the biological collection of the IBG UFRC RAS by adding of a deeply phenotyped set. Additionally, the laboratory is planning to conduct a full-genome genotyping for the study of the molecular mechanisms underlying the formation of complex characteristics, including cardiometabolic features, the individual psychological profile (inclination to aggressive behaviour and depression), and sporting characteristics.

To this end, we will use methods of multi-phenotype analysis that were developed under the supervision of Inga Prokopenko and tested using major databases of genotype and clinical data, such as «UK Biobank».

The practical value of the study

Scientific results:

  • The Laboratory created the first version of the freely available library of analytical tools on the ANTE–OMICS platform, developed a system for working with online users (clients), completed the internal configuration of the software products that will be launched online for users.
  • We have created a federated database in SQL and deigned its structure for epidemiological, demographic and climatic data available at the Institute of Biochemistry and Genetics of the Ufa Federal Research Center of the Russian Academy of Sciences (IBS UFRC RAS), harmonized the epidemiological, demographic and climatic data of the collection of biological materials of IBS UFRC RAS for the population of the Volga–Urals region of Russia, the North Caucasus region of Russia, Central Asia, Siberia and the Baltic region; for multifactorial diseases and hereditary diseases, for a sample of healthy individuals belonging to various age cohorts.
  • Questionnaire data has been collected and a sample has been created that consists of about 1000 mentally fit individuals aged 18 to 25 (average age 20,45 ± 2,42 years) of Russian (337 individuals), Tatar (320 individuals), Udmurt (214 individuals) and mixed ethnicity (129 individuals).
  • We are developing new approaches to personalized medicine based on the polygenic assessment of genetic and environmental factors to forecast individual risks of onset of obesity, diabetes, breast cancer, kidney cancer, bronchial asthma, osteoporosis, depression and aggression that allow to conduct timely proactive measures.
  • We are conducting work to generate full-genome data for the collected samples of a sample group of students undergoing training at basic departments of IBS UFRC RAS to conduct research of multifactorial features and diseases, including research of genetic foundations of physical activity. A full-genome genotyping of a DNA sample has been conducted with the use of Illumina biochips on an iScan microchip scanner manufactured by Illumina as part of an agreement with an industrial partner, «Genotech» Ltd.

Implementation of research results:

As a result of the implementation of the project, we have determined informative predictors of cardiometabolic diseases (arterial hypertension, obesity, type 2 diabetes), multiple sclerosis, respiratory system diseases (bronchial asthma, chronic obstructive pulmonary disease), oncological diseases (breast cancer, kidney cancer), osteoporosis. The developed new approaches for personalized medicine relying on the assessment of the polygenic risk can be applied in practice to forecast risks of development of socially significant diseases to prevent their onset and severe course.

Education and retraining of personnel:

  • We have compiled and launched four new education programs implemented by members of the academic team of the laboratory in the domain of the project:
    1. Education program for master’s degree students «Algorithmic bioinformatics», direction of training 09.04.01 «Informatics and computer technology», launched in the academic year 2021–2022 at the Faculty of Informatics and Robotics of Ufa State Aviation Technical University.
    2. Education program for master’s degree students «Genomic medicine», direction of training 06.04.01 «Biology», launched in the academic year 2021-2022 at the Faculty of Biology of Bashkir State University.
    3. Education program for bachelor’s degree students «Genetics», direction of training 06.03.01 «Biology», launched in the academic year at the Faculty of Biology of Bashkir State University.
    4. Education program for master’s degree students «Genomics and bioinformatics», direction of training 06.04.01 «Biology», launched in the academic year 2021–2022 at the Faculty of Biology of Bashkir State University.
  • Members of the academic team of the Laboratory have prepared and defended 5 Candidate of Sciences dissertations and 2 Doctor of Sciences dissertations.
  • We have organized and staged internships on the topic of the project at the leading scientist’s main place of work for two postgraduate students at the Section of Statistical Multi-Omics of the Department of Clinical and Experimental Medicine of the School of Biosciences and Medicine (University of Surrey, Guildford, United Kingdom) with the topic: «Mastering methods of analysis of multi-omics data», for 32 days each.
  • Professor Inga Prokopenko has conducted a lecture course for undergraduate and postgraduate students of Bashkir State University on the following topics:
    1. «Introduction to full-genome research» (4 individuals);
    2. «Lost heritability» in large-scare genetic research» (4 individuals)
    3. «Design of genomic research and genomic technologies» (4 individuals).
  • Members of the academic team of the project have completed advanced training and occupational retraining courses:
    1. 9 members of the research team of the Laboratory have completed the online course «Introduction to the statistical analysis of genome-wide association studies» organized by Inga Prokopenko.
    2. 19 employees of the Laboratory have completed the online course «Polygenic risk score seminar and training» organized and Inga Prokopenko.
    3. On assignment from the head of the project, four members of the academic team have completed training at the online course «Mendelian randomization Course» at Cambridge University (Cambridge, United Kingdom).

Collaborations:

  1. Hannover Medical School, Germany. Joint genetic and genome research of predisposition to breast cancer and ovarian cancer.
  2. University of Surrey, United Kingdom. Joint research, online courses and academic internships of executors of the project at the leading scientist’s main place of work. 
  3. Bashkir State University, Ufa, Russia. Joint bachelor’s and master’s degree programs, developing objects of intellectual property, patents, joint conferences.
  4. Ufa State Aviation Technical University. Joint master’s degree program, joint conferences.

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Escala-Garcia M., Canisius S., Keeman R., …., Bermisheva M.,… Khusnutdinova E., … Bachelot T., Schmidt M. K., kConFab A. I.
Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis // Scientific Reports. ‒ 2021. ‒ T. 11, № 1. ‒ C. 19787. doi: 10.1038/s41598-021-99409-3.
Korytina G. F., Aznabaeva Y. G., Akhmadishina L. Z., Kochetova O. V., Nasibullin T. R., Zagidullin N. S., Zagidullin S. Z., Viktorova T. V.
The relationship between chemokine and chemokine receptor genes polymorphisms and chronic obstructive pulmonary disease susceptibility in Tatar population from Russia: a case control study // Biochemical Genetics. ‒ 2021.10.1007/s10528-021-10087-2. doi: 10.1007/s10528-021-10087-2.
Timasheva Y., Badykov M., Akhmadishina L., Nasibullin T., Badykova E., Pushkareva A., Plechev V., Sagitov I., Zagidullin N.
Genetic predictors of sick sinus syndrome // Molecular Biology Reports. ‒ 2021. ‒ V. 48, № 6. ‒ P. 5355-5362. doi: 10.1007/s11033-021-06517-4.
Balkhiyarova Z, Luciano R, Kaakinen M, Ulrich A, Shmeliov A, Bianchi M, Chioma L, Dallapiccola B, Prokopenko I, Manco M.
Relationship between glucose homeostasis and obesity in early life—a study of Italian children and adolescents // Human molecular genetics. – 2022. – V. 31(5). – P. 816-26. doi: 10.1093/hmg/ddab287.
Dorling L, Carvalho S, Allen J, ... Bermisheva M, Khusnutdinova E, et al.
Breast cancer risks associated with missense variants in breast cancer susceptibility genes // Genome Med. 2022. – V. 14(1):51. doi: 10.1186/s13073-022-01052-8.
Timasheva Y, Nasibullin TR, Tuktarova IA, Erdman VV, Galiullin TR, Zaplakhova OV, Bakhtiiarova KZ.
Multilocus evaluation of genetic predictors of multiple sclerosiss // Gene. – 2022. Jan 30. 809:146008.
Korytina G. F., Aznabaeva Y.G , Akhmadishina L.Z., Kochetova O.V., Nasibullin T.R., Zagidullin N. Sh., Zagidullin Sh. Z., Viktorova T.V.
The relationship between chemokine and chemokine receptor genes polymorphisms and chronic obstructive pulmonary disease susceptibility in Tatar population from Russia: а case control study // Biochemical Genetics. – 2022. – V. 60. P. 54–79 https://doi.org/10.1007/s10528-021-10087-2.
Yalaev B, Tyurin A, Prokopenko I, Karunas A, Khusnutdinova E, Khusainova R.
Using a Polygenic Score to Predict the Risk of Developing Primary Osteoporosis // Int J Mol Sci. - 2022. - V. 23(17). - P. 10021. doi: 10.3390/ijms231710021.
Ivanova E., Gilyazova I., Pavlov V., Izmailov A., Gimalova G., Karunas A., Prokopenko I., Khusnutdinova E.
MicroRNA Processing Pathway-Based Polygenic Score for Clear Cell Renal Cell Carcinoma in the Volga-Ural Region Populations of Eurasian Continent // Genes. – 2022. - V.13. - P.1281. https:// doi.org/10.3390/genes13071281.
Gilyazova I, Ivanova E, Sinelnikov M, Pavlov V, Khusnutdinova E, Gareev I, Beilerli A, Mikhaleva L, Liang Y.
The potential of miR-153 as aggressive prostate cancer biomarker // Noncoding RNA Res. – 2022. – V. 8(1). - P. 53-59. doi: 10.1016/j.ncrna.2022.10.002.
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