ГоловнаArchive of numbers2023Volume 31, issue 2 (115)Comparative mathematical analysis based on the data history of nonhereditary risk and anti-risk factors between patients with sporadic and familial forms of multiple sclerosis
Title of the article | Comparative mathematical analysis based on the data history of nonhereditary risk and anti-risk factors between patients with sporadic and familial forms of multiple sclerosis | ||||
Authors |
Negreba Tetiana Voloshyna Natalia Kirzhner Valery Chernenko Maksym PogulyaevaTetiana Nikishkova Iryna Voloshyn-Gaponov Ivan Kutikov Damir Gaponov Petro |
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In the section | MECHANISMS OF FORMATION AND MODERN PRINCIPLES OF TREATMENT OF NEUROLOGICAL DISORDERS | ||||
Year | 2023 | Issue | Volume 31, issue 2 (115) | Pages | 16-23 |
Type of article | Scientific article | Index UDK | 616.832-004.12:615.07 | Index BBK | - |
Abstract | Objective. To identify nonhereditary risk and anti-risk factors in the development of multiple
sclerosis (MS) according to premorbid history and lifestyle in patients with sporadic and familial
forms of the disease using mathematical analysis.
Methods of the study. questionnaire; methods of mathematical statistics (mean values, confidence
interval); permutation test to quantify significant differences between the indicators in the study
groups; odds ratio (OR) to determine the strength of the relationship between patients with dif-
ferent forms of MS and premorbid history and lifestyle data.
Results of the study. The study included 97 patients with MS: sporadic form — 55 (8 men and
47 women) with an average age of 47.8 years and disease duration of 15.7 years; familial form —
42 (10 men and 32 women) with an average age of 46.3 years and disease duration of 16.6 years.
A comparative analysis was conducted between patients with sporadic (55) and familial (42) forms
of MS; with relapsing-remitting (RR) in sporadic (31) and familial (20) forms; with progressive-type
(PtP) in sporadic (24) and familial (22) forms.
A comparative analysis of premorbid history and lifestyle indicators revealed their significant
differences in different types of course in patients with sporadic and familial forms of MS. The high
level of reliability of the indicators in the study groups allowed us to consider them as condi-
tional risk factors (RF) and anti-risk factors (ARF) in the development of MS. In the general group
of patients with sporadic form, multiorgan somatic pathology, allergic reactions and endocrine
disorders prevailed; in the general group of familial form, cardiovascular diseases, chronic pathology
of the ENT organs and viral infections were prevalent. In sporadic PTP, in contrast to RP, a signifi-
cant variety of indicators was found, including somatic and infectious diseases, poor tolerance
to hot weather, and lifestyle characteristics. In the familial form, in contrast to the sporadic form,
lifestyle indicators prevailed in RP, while in PTP, viral and bacterial infections played a leading role.
In the sporadic form, in contrast to the familial form, conditional ARF was obtained, indicating
a healthy lifestyle in this category of patients. A significant prevalence of mean OR values for
lifestyle indicators was obtained compared with the premorbid anamnesis: in the familial form
of RP in the form of RF (insufficient intake of vitamins and minerals, diet with a predominance
of meat and dairy foods, excessive coffee consumption); in the sporadic form in all study groups
in the form of ARF (systematic exercise, balanced diet, sufficient intake of vitamins and mine-
rals). mathematical studies, reliable indicators of premorbid history and lifestyle formed different
structures of conditional
Conclusions. Thus, according to the results of the clinical and RF and ARF, taking into account
the form and type of MS course. This position is supported by the selective and differentiated
distribution of conditional RF in RP and PTP in patients with familial forms, which opens up new
therapeutic possibilities at different stages of the disease. Depending on the type of course,
the treatment algorithm for pancreatic cancer in the familial form should be aimed at correcting
lifestyle-related factors, while in PTP — at timely prevention and treatment of bacterial and viral
infections. The presence of lifestyle indicators in the form of conditional ARF only in sporadic form
indicates that the pathogenetic impact of nonhereditary ARF in familial MS is mainly controlled
by genetic mechanisms responsible for the development of MS. The increase in the level of mean
OR values for lifestyle indicators, in contrast to premorbid history, has important diagnostic
and prognostic significance for this category of RF and ARF in the two forms of MS. |
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Key words | multiple sclerosis, risk factors, anti-risk factors, mathematical analysis | ||||
Access to full text version of the article pdf | download | ||||
Bibliography | 1. Gusev E. I., Zavalishin I. A., Boyko A. N. Rasseyannyy
skleroz : klinicheskoye rukovodstvo. Moskva : Real Tayms, 2011.
528 s. (In Russian). 2. Boyko A. N., Gusev E. I. Dostizheniya v izuchenii problem
rasseyannogo skleroza (obzor). Doktor. Ru. Nevrologiya, psikhi-
atriya. 2012. T. 73. No. 5. S. 9—15. (In Russian). 3. Shmidt T. E., Yakhno N. N. Rasseyannyy skleroz : rukovodstvo
dlya vrachey. 5-e izd. Moskva : MEDpress-inform, 2016. 272 s.
ISBN 978-5-00030-337-5. (In Russian). 4. Favorova O. O., Boyko A. N., Kulakova O. G. Rasseyannyy
skleroz kak poligennoye zabolevaniye: sovremennoye sos-
toyaniye problemy. Genetika. 2010. T. 46, No. 3. S. 302—313.
(In Russian). 5. Gandhi R, Laroni A, Weiner HL. Role of the innate immune
system in the pathogenesis of multiple sclerosis. J Neuroimmunol.
2010 Apr 15;221(1-2):7-14. doi: 10.1016/j.jneuroim.2009.10.015.
PMID: 19931190; PMCID: PMC2854189. 6. Antoniuk T. Rozsiianyi skleroz: sytuatsiinyi analiz prob-
lemy v Ukraini: za materialamy obhovorennia rezultativ per-
shoho v Ukraini kompleksnoho doslidzhennia zakhvoriuvanosti
na rozsiianyi skleroz, yii diahnostyky ta likuvannia. NeiroNEWS:
psykhonevrolohiia ta neiropsykhiatriia. 2018. No. 3 (96). S. 6—9.
(In Ukrainian). 7. Korobko D. S. Kliniko-geneticheskoye issledovaniye rasseyan-
nogo skleroza (na primere populyatsii Novosibirskoy oblasti) : av-
toref. dis.na soiskaniye uch. stepeni kand. med.nauk: Spetsialnost
14.01.11 — nervnyye bolezni [abstract dis. for an academic
degree MD, PhD. Sciences Specialty 14.01.11 — nervous dis-
eases]. Novosibirsk. 2014. 33 s. (In Russian). 8. McElroy JP, Oksenberg JR. Multiple sclerosis genetics.
Curr Top Microbiol Immunol. 2008;318:45-72. doi: 10.1007/978-
3-540-73677-6_3. PMID: 18219814. 9. Sych N. S. Patohenetychni aspekty rozsiianoho sklerozu
[Pathogenetic aspects of multiple sclerosis]. Ukrainskyi me-
dychnyi chasopys [Ukrainian medical journal]. 2012. No. 2 (88)
III—IV. https://www.umj.com.ua/article/30152/patogenetichni-
aspekti-rozsiyanogo-sklerozu. (In Ukrainian).
10. Spirin N. N., Kachura D. A., Kachura A. N., Boyko A. N.
Vliyaniye ekologi
cheskikh faktorov na zabolevayemost i raspros-
tranennost rasseyannogo skleroza. Zhurnal nevrologii i psikhiatrii
imeni S. S. Korsakova. 2003. No. 2. S. 111—113. (In Russian). 11. Ebers GC. Environmental factors and multiple sclerosis.
Lancet Neurol. 2008 Mar;7(3):268-77. doi: 10.1016/S1474-
4422(08)70042-5. PMID: 18275928. 12. Balcerac A, Louapre C. Genetics and familial distribu-
tion of multiple sclerosis: A review. Rev Neurol (Paris). 2022
Jun;178(6):512-520. doi: 10.1016/j.neurol.2021.11.009. Epub
2022 Feb 9. PMID: 35148907. 13. Olsson T, Barcellos LF, Alfredsson L. Interactions between
genetic, lifestyle and environmental risk factors for multiple
sclerosis. Nat Rev Neurol. 2017 Jan;13(1):25-36. doi: 10.1038/
nrneurol.2016.187. Epub 2016 Dec 9. PMID: 27934854. 14. RTaan M, Al Ahmad F, Ercksousi MK, Hamza G. Risk
Factors Associated with Multiple Sclerosis: A Case-Control Study
in Damascus, Syria. Mult Scler Int. 2021 Jun 1;2021:8147451. doi:
10.1155/2021/8147451. PMID: 34123428; PMCID: PMC8189778. 15. Venkatesan A, Johnson RT. Infections and multiple scle-
rosis. Handb Clin Neurol. 2014;122:151-71. doi: 10.1016/B978-
0-444-52001-2.00007-8. PMID: 24507517; PMCID: PMC7152154. 16. Venkatesan A. Multiple sclerosis and infections.
Neurodegener Dis Manag. 2015;5(6 Suppl):11-4. doi: 10.2217/
nmt.15.64. PMID: 26611265. 17. Lünemann JD, Tintoré M, Messmer B, Strowig T, Rovira A,
Perkal H, Caballero E, Münz C, Montalban X, Comabella M.
Elevated Epstein-Barr virus-encoded nuclear antigen-1 immune
responses predict conversion to multiple sclerosis. Ann Neurol.
2010 Feb;67(2):159-69. doi: 10.1002/ana.21886. PMID: 20225269;
PMCID: PMC2848293. 18. Jaquiéry E, Jilek S, Schluep M, Meylan P, Lysandropoulos A,
Pantaleo G, Du Pasquier RA. Intrathecal immune responses
to EBV in early MS. Eur J Immunol. 2010 Mar;40(3):878-87.
doi: 10.1002/eji.200939761. Erratum in: Eur J Immunol. 2011
May;41(5):1501. PMID: 20017197. 19. TKołtuniuk A, Kazimierska-Zając M, Cisek K, Chojdak-
Łukasiewicz J. The Role of Stress Perception and Coping with
Stress and the Quality of Life Among Multiple Sclerosis Patients.
Psychol Res Behav Manag. 2021 Jun 18;14:805-815. doi: 10.2147/
PRBM.S310664. PMID: 34177278; PMCID: PMC8219305. 20. Kang JH, Lin HC. Increased risk of multiple sclerosis
after traumatic brain injury: a nationwide population-based
study. J Neurotrauma. 2012 Jan 1;29(1):90-5. doi: 10.1089/
neu.2011.1936. Epub 2011 Dec 23. PMID: 22044110. 21. Zhang P, Wang R, Li Z, Wang Y, Gao C, Lv X, Song Y,
Li B. The risk of smoking on multiple sclerosis: a meta-anal-
ysis based on 20,626 cases from case-control and cohort
studies. Peer J. 2016 Mar 15;4:e1797. doi: 10.7717/peerj.1797.
PMID: 27014514; PMCID: PMC4806598. 22. Najafi MR, Shaygannajad V, Mirpourian M, Gholamrezaei A.
Vitamin B(12) Deficiency and Multiple Sclerosis; Is there
Any Association? Int J Prev Med. 2012 Apr;3(4):286-9. PMID:
22624086; PMCID: PMC3354399. 23. Goldsmith JR. Vitamin D as an Immunomodulator: Risks
with Deficiencies and Benefits of Supplementation. Healthcare
(Basel). 2015 Apr 14;3(2):219-32. doi: 10.3390/healthcare3020219.
PMID: 27417758; PMCID: PMC4939543. 24. Waschbisch A, Sanderson N, Krumbholz M, Vlad G, Theil
D, Schwab S, Mäurer M, Derfuss T. Interferon beta and vitamin
D synergize to induce immunoregulatory receptors on periph-
eral blood monocytes of multiple sclerosis patients. PLoS One.
2014 Dec 31;9(12):e115488. doi: 10.1371/journal.pone.0115488.
PMID: 25551576; PMCID: PMC4281069. 25. RRiccio P, Rossano R. Diet, Gut Microbiota, and Vitamins
D + A in Multiple Sclerosis. Neurotherapeutics. 2018 Jan;15(1):75-
91. doi: 10.1007/s13311-017-0581-4. PMID: 29067566; PMCID:
PMC5794694. 26. Nehreba T. V. Klinichna diahnostyka riznykh typiv pere-
bihu rozsiianoho sklerozu. Zbirka anket: Svidotstvo pro avtorske
pravo na naukovyi tvir No. 8675 vid 31.10.2003. (In Ukrainian). 27. Mielke P. W. Permutation Methods: A Distance Function
Approach / P. W. Mielke, K.J. Berry. N.Y.: Springer-Verlag. 2001. 357 p. 28. Moore D. Bootstrap Methods and Permutation Tests.
The Practice of Business Statistics. Ed. T. Hesterberg. N.Y.: Freeman
& Co. 2003. Cap. 14. 70 p. 29. Zaytsev V. M., Liflyandskiy V. G., Marinkin V. I. Prikladnaya
meditsinskaya statistika. SPb. : Foliant, 2003. 428 s. (In Russian). 30. Voloshyna N. P., Vasylovskyi V. V., Chernenko M. E. Vliyaniye
infektsionnogo faktora na sostoyaniye gematoentsefali
cheskogo
baryera u bolnykh rasseyannym sklerozom. Ukrainskyi visnyk
psykhonevrolohii. 2013. No. 21(1). S. 5—7. https://uvnpn.com.
ua/upload/iblock/16e/16e03af2aa8182a7e5cdd8132349976c.
pdf. (In Russian). |