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Perspectives of osteoarthritis prevention and therapy personification based on the analysis of comorbid background, genetic polymorphisms and microelement status

https://doi.org/10.17749/2070-4909/farmakoekonomika.2021.077

Abstract

Objective: analysis of the osteoarthritis (OA) comorbidity taking into account the microelement status and genetic polymorphisms of the examined patients, determination of the prospects for the OA prevention and therapy.

Material and methods. A cross-sectional study of a multiethnic cohort (n=655, mean age 43±14 years, 95% CI 29–70) formed on the basis of the Institute of Microelements database, was carried out. For all participants, the content of the 62 elements of the Element Periodic Table profile in hair was identified and variants of 120 nucleotide polymorphisms associated with various pathologies were defined

Results. The study found that 18 of the 27 ICD-10 diagnoses examined were comorbid with OA. Osteoarthritis was comorbid with pathologies with a pronounced component of inflammation (ulcerative colitis, atherosclerosis, unspecified encephalopathy, obesity, diabetes mellitus, essential (primary) hypertension, urine calculus, acute myocardial infarction, cholelithiasis, etc.). The core of OA comorbidity was established, which included following pathologies: chronic cerebral ischemia, diabetes mellitus, thrombophlebitis, atherosclerosis, cholelithiasis. Seven profiles of the most frequent combinations of these diagnoses were identified. The presence of 2 out of 5 of these pathologies was recorded in 92% of patients with OA (n=50) and only in 2% of control patients (n=600), which corresponded to an extreme increase in the risk of OA (OR 56.3, 95% CI 17.4–181.6, p<10–20). Analysis of the 62 elements profile of the Element Periodic Table content in hair showed that reduced levels of silicon, molybdenum, vanadium and calcium are significantly associated with OA. As a result of studying data on 120 nucleotide polymorphisms, OA was significantly associated with the LPL Ser447Stop CC, LPL N291S AA, NOS3 E298D GG, and MTHFR 677 CC genotypes, which regulate lipid metabolism and inflammation.

Conclusion. Based on the obtained results the prospects for the use of chondroitin sulfate and glucosamine sulfate in patients with an increased risk of OA development are shown.

About the Authors

I. Yu. Torshin
Institute of Pharmacoinformatics, Federal Research Center “Informatics and Management”, Russian Academy of Sciences; Big Data Storage and Analysis Center, Lomonosov Moscow State University
Russian Federation

Ivan Yu. Torshin – PhD (Phys. Math.), PhD (Chem.), Senior Researcher, Institute of Pharmacoinformatics, Federal Research Center “Informatics and Management”, Russian Academy of Sciences; Big Data Storage and Analysis Center, Lomonosov Moscow State University. Scopus Author ID: 7003300274; ResearcherID: C-7683-2018; RSCI SPIN-code: 1375-1114

4 Vavilov Str., Moscow 2119333
1 Leninskie Gory, Moscow 119991



A. M. Lila
Nasonov Research Institute of Rheumatology; Russian Medical Academy of Continuing Professional Education
Russian Federation

Aleksandr M. Lila – Dr. Med. Sc., Professor, Director, Nasonova Research Institute of Rheumatology; Chief of Chair of Rheumatology, Russian Medical Academy of Continuing Professional Education. Scopus Author ID: 6602550827; ResearcherID: W-3334-2017; RSCI SPIN-code: 7287-855534А

Kashirskoye Shosse, Moscow 115522
2/1bld1 Barrikadnaya Str., Moscow 125993



A. V. Naumov
Russian Gerontological Research and Clinical Center, Pirogov Russian National Research Medical University
Russian Federation

Anton V. Naumov – Dr. Med. Sc., Professor, Head of Laboratory of Musculoskeletal System Diseases. RSCI SPIN-code: 4763-9738

16 Pervaya Leonov Str., Moscow 129226



I. S. Sardaryan
Saint Petersburg State Pediatric Medical University
Russian Federation

Ivan S. Sardaryan – MD, PhD, Associate Professor, Chair of Pharmacology with a Course in Clinical Pharmacology and Pharmacoeconomics. Scopus Author ID: 572006721; RSCI SPIN-code: 9522-9761

2 Litovskaya Str., Saint Petersburg 194100



T. E. Bogacheva
Ivanovo State Medical Academy
Russian Federation

Tatyana E. Bogacheva – MD, PhD, Assistant Professor, Chair of Pharmacology. Scopus Author ID: 57188826213; RSCI SPIN-code: 8970-6270

8 Sheremetevskiy Prospect, Ivanovo 153012



T. R. Grishina
Ivanovo State Medical Academy
Russian Federation

Tatyana R. Grishina – Dr. Med. Sc., Professor, Chief of Chair of Pharmacology. RSCI SPIN-code: 1241-0701

8 Sheremetevskiy Prospect, Ivanovo 153012



I. V. Gogoleva
Ivanovo State Medical Academy
Russian Federation

Irina V. Gogoleva – MD, PhD, Associate Professor, Chair of Pharmacology. Scopus Author ID: 35773149200; RSCI SPIN-code: 6599-7955

8 Sheremetevskiy Prospect, Ivanovo 153012



O. A. Limanova
Ivanovo State Medical Academy
Russian Federation

Olga A. Limanova – MD, PhD, Associate Professor, Chair of Pharmacology

8 Sheremetevskiy Prospect, Ivanovo 153012



O. A. Gromova
Institute of Pharmacoinformatics, Federal Research Center “Informatics and Management”, Russian Academy of Sciences; Big Data Storage and Analysis Center, Lomonosov Moscow State University
Russian Federation

Olga A. Gromova – Dr. Med. Sc., Professor, Research Supervisor, Institute of Pharmacoinformatics, Federal Research Center “Informatics and Management”, Russian Academy of Sciences; Leading Researcher, Big Data Storage and Analysis Center, Lomonosov Moscow State University. Scopus Author ID: 7003589812; ResearcherID: J-4946-2017; RSCI SPIN-code: 6317-9833

4 Vavilov Str., Moscow 2119333
1 Leninskie Gory, Moscow 119991



References

1. Hootman J.M., Helmick C.G., Barbour K.E., et al. Updated projected prevalence of self-reported doctor-diagnosed arthritis and arthritisattributable activity limitation among US adults, 2015–2040. Arthritis Rheumatol. 2016; 68 (7): 1582–7. https://doi.org/10.1002/art.39692.

2. Puenpatom R.A., Victor T.W. Increased prevalence of metabolic syndrome in individuals with osteoarthritis: an analysis of NHANES III data. Postgrad Med. 2009; 121 (6): 9–20. https://doi.org/10.3810/pgm.2009.11.2073.

3. Naumov A.V., Shamuilova M.M., Kotselapova A.U. Osteoarthritis in modern clinical practice: analysis of factors and recommendations. Therapist. 2009; 11: 4–15 (in Russ.).

4. Scherzer Z.A., Alvarez C., Renner J.B., et al. Effects of comorbid cardiovascular disease and diabetes on hand osteoarthritis, pain, and functional state transitions: the Johnston county osteoarthritis project. J Rheumatol. 2020; 47 (10): 1541–9. https://doi.org/10.3899/jrheum.191075.

5. Alvarez C., Cleveland R.J., Schwartz T.A., et al. Comorbid conditions and the transition among states of hip osteoarthritis and symptoms in a community-based study: a multi-state time-to-event model approach. Arthritis Res Ther. 2020; 22 (1): 12. https://doi.org/10.1186/s13075-020-2101-x.

6. Bastick A.N., Runhaar J., Belo J.N., Bierma-Zeinstra S.M. Prognostic factors for progression of clinical osteoarthritis of the knee: a systematic review of observational studies. Arthritis Res Ther. 2015; 17 (1): 152. https://doi.org/10.1186/s13075-015-0670-x.

7. Lila A.M., Torshin I.Yu., Gromova O.A. Is it worthwhile rethinking the positive experience of the last 50 years of using chondroitin sulfates against atherosclerosis? FARMAKOEKONOMIKA. Modern Pharmacoeconomics and Pharmacoepidemiology. 2020; 13 (2): 184–91 (in Russ.). https://doi.org/10.17749/2070-4909/farmakoekonomika.2020.043.

8. Berenbaum F., Walker C. Osteoarthritis and inflammation: a serious disease with overlapping phenotypic patterns. Postgrad Med. 2020; 132 (4): 377–84. https://doi.org/10.1080/00325481.2020.1730669.

9. de Munter W., Blom A.B., Helsen M.M., et al. Cholesterol accumulation caused by low density lipoprotein receptor deficiency or a cholesterol-rich diet results in ectopic bone formation during experimental osteoarthritis. Arthritis Res Ther. 2013; 15 (6): R178. https://doi.org/10.1186/ar4367.

10. Torshin I.Yu., Gromova O.A. Expert data analysis in molecular pharmacology. Moscow; 2012 (in Russ.).

11. Trewick A.L., Moustafa J.S., de Smith A.J., et al. Accurate singlenucleotide polymorphism allele assignment in trisomic or duplicated regions by using a single base-extension assay with MALDI-TOF mass spectrometry. Clin Chem. 2011; 57 (8): 1188–95. https://doi.org/10.1373/clinchem.2010.159558.

12. Torshin I.Yu. Sensing the change: from molecular genetics to personalized medicine. N.Y.: Nova Biomedical Books; 2009.

13. Torshin I.Yu., Rudakov K.V. On the application of the combinatorial theory of solvability to the analysis of chemographs: Part 2. Local completeness of invariants of chemographs in view of the combinatorial theory of solvability. Pattern Recognit Image Anal. 2014; 24: 196–208. https://doi.org/10.1134/S1054661814020151.

14. Torshin I.Yu., Rudakov K.V. On the theoretical basis of metric analysis of poorly formalized problems of recognition and classification. Pattern Recognit Image Anal. 2015; 25: 577–87. https://doi.org/10.1134/S1054661815040252.

15. Torshin I.Yu., Limanova O.A., Sardaryan I.S., et al. Provision of vitamin D in children and adolescents aged 7 to 14 years and the relationship of deficiency of vitamin D with violations of children’s health: the analysis of a large-scale sample of patients by means of data mining. Journal "Pediatria" named after G.N. Speransky. 2015; 94(2): 175–84 (in Russ.).

16. Limanova O.A., Torshin I.Yu., Sardaryan I.S., et al. Micronutrient provision and women's health: intellectual analysis of clinicoepidemiological data. Gynecology, Obstetrics and Perinatology. 2014; 13 (2): 5–15 (in Russ.).

17. Wearing J., Konings P., de Bie R.A., et al. Prevalence of probable sarcopenia in community-dwelling older Swiss people – a cross-sectional study. BMC Geriatr. 2020; 20: 307. https://doi.org/10.1186/s12877-020-01718-1.

18. Shimo-Nakanishi Y., Urabe T., Hattori N., et al. Polymorphism of the lipoprotein lipase gene and risk of atherothrombotic cerebral infarction in the Japanese. Stroke. 2001; 32 (7): 1481–6. https://doi.org/10.1161/01.str.32.7.1481.

19. Sobstyl J., Dzida G., Puzniak A., et al. Analiza zwiazku polimorfizmu genu śródbłonkowej syntetazy tlenku azotu z zawałem mieśnia sercowego [Analysis of association of human endothelial nitric oxide synthase gene polymorphism with myocardial infraction]. Pol Merkur Lekarski. 2002; 13 (73): 10–3 (in Polish).

20. Canavy I., Henry M., Morange P.E., et al. Genetic polymorphisms and coronary artery disease in the south of France. Thromb Haemost. 2000; 83 (2): 212–6.

21. Kim R.J., Becker R.C. Association between factor V Leiden, prothrombin G20210A, and methylenetetrahydrofolate reductase C677T mutations and events of the arterial circulatory system: a meta-analysis of published studies. Am Heart J. 2003; 146 (6): 948–57. https://doi.org/10.1016/S0002-8703(03)00519-2.

22. Inanir A., Yigit S., Tural S., et al. MTHFR gene C677T mutation and ACE gene I/D polymorphism in Turkish patients with osteoarthritis. Dis Markers. 2013; 34 (1): 17–22. https://doi.org/10.3233/DMA-2012-00939.

23. Yamada S., Sugahara K. Potential therapeutic application of chondroitin sulfate/dermatan sulfate. Curr Drug Discov Technol. 2008; 5 (4): 289–301. https://doi.org/10.2174/157016308786733564.

24. Torshin I.Yu., Lila A.M., Gromova O.A., et al. On the anticoagulant and antiaggregatory properties of a glucosamine sulfate molecule. Sovremennaya revmatologiya (Modern Rheumatology). 2019; 13 (3): 135–41 (in Russ.). https://doi.org/10.14412.1996-7012-2019-3-135-141.

25. Gromova O.A., Torshin I.Yu., Lila A.M., et al. On the safety of glucosamine sulfate in patients with insulin resistance. Consilium Medicum. 2019; 21 (4): 75–83 (in Russ.). https://doi.org/10.26442/20751753.2019.4.190309.

26. Lila A.M., Gromova O.A., Torshin I.Yu., et al. Molecular effects of chondrogard in osteoarthritis and herniated discs. Neurology, Neuropsychiatry, Psychosomatics. 2017; 9 (3): 88–97 (in Russ.). https://doi.org/10.14412/2074-2711-2017-3-88-97.

27. Martín Arias L.H., Martín González A., Sanz Fadrique R., Vazquez E.S. Cardiovascular risk of nonsteroidal anti-inflammatory drugs and classical and selective cyclooxygenase-2 inhibitors: a meta-analysis of observational studies. J Clin Pharmacol. 2019; 59 (1): 55–73. https://doi.org/10.1002/jcph.1302.

28. Martel-Pelletier J., Farran A., Montell E., et al. Discrepancies in composition and biological effects of different formulations of chondroitin sulfate. Molecules. 2015; 20 (3): 4277−89. https://doi.org/10.3390/molecules20034277.

29. Zolotovskaya I.A., Davydkin I.L., Poverennova I.E. Therapy for nonspecific lower back pain in patients with high cardiovascular risk. S.S. Korsakov Journal of Neurology and Psychiatry. 2019; 119 (8): 18−23 (in Russ.). https://doi.org/10.17116/jnevro201911908118.

30. Torshin I.Yu., Lila A.M., Naumov A.V., et al. Meta-analysis of clinical trials of osteoarthritis treatment effectiveness with Chondroguard. FARMAKOEKONOMIKA. Sovremennaya farmakoekonomika i farmakoepidemiologiya / FARMAKOEKONOMIKA. Modern Pharmacoeconomics and Pharmacoepidemiology. 2020; 13 (4): 18–29 (in Russ.). https://doi.org/10.17749/2070-4909/farmakoekonomika.2020.066.


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For citations:


Torshin I.Yu., Lila A.M., Naumov A.V., Sardaryan I.S., Bogacheva T.E., Grishina T.R., Gogoleva I.V., Limanova O.A., Gromova O.A. Perspectives of osteoarthritis prevention and therapy personification based on the analysis of comorbid background, genetic polymorphisms and microelement status. FARMAKOEKONOMIKA. Modern Pharmacoeconomics and Pharmacoepidemiology. 2021;14(1):28-39. (In Russ.) https://doi.org/10.17749/2070-4909/farmakoekonomika.2021.077

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