Shifts in the subfractional composition of biological fluids of children with neuropsychiatric diseases
ORIGINAL PAPERS
Abstract
Introduction. Dynamic light scattering (laser correlation spectroscopy) is used to measure the average particle diameter and particle diameter distribution in colloidal solutions. These parameters, measured in blood serum, are important characteristics for the diagnosis of some somatic diseases. However, there is very little information on the direction of shifts in serum homeostasis during the development of neuropsychiatric disorders, especially for the pediatric population cohort. The aim of study was to assess the prospects of using the laser correlation spectroscopy method for monitoring metabolic processes in children with disorders of the central nervous system. Materials and methods. Blood serum samples wereobtained during a sanogenetic examination of children aged 8-11 years from correctional classes of general and specialized schools. Based on the results of medical and psychological testing, subgroups with pedagogical neglect (conventional “norm”, n=25), with functional (n=23) or organic (n=23) central nervous system disorders, and a subgroup with psychiatric diagnoses (n=22) were identified. Results. In children with functional disorders of the central nervous system, a shift in the laser correlation spectra towards large-diameter particles was observed compared to the conventionally “normal” spectra, i.e. anabolic-like type of metabolism. In children with mental disorders, an increase in the contribution of small particles to light scattering was noted, i.e. a catabolic-like type of metabolism. In children with organic brain damage, there were no clearly defined peaks: fractions of low- and high-molecular particles made approximately the same contribution to light scattering. Changes in the laser correlation spectra of blood serum and oropharyngeal lavage in children with mental disorders were unidirectional. Conclusion. Laser correlation spectroscopy is a sufficiently sensitive and effective method for measuring variations in the distribution of particle sizes in the blood serum of children with mental retardation of various etiologies and can be a promising auxiliary tool in establishing a diagnosis and assessing the dynamics of a person’s functional state during treatment.
References
1. Макарова Л.В., Параничева Т.М., Тюрина Е.В. Направления здоровьесберегающей деятельности в школе. В 5 ч. Ч. 2. М.: издательство Института возрастной физиологии Российской академии образования. 2023. 16 с.
2. Benitez Ojeda A.B., Carugno P. Special Education. In: Treasure Island (FL): Stat Pearls Publishing. 2025.
3. Grigorenko E.L., Compton D.L., Fuchs L.S., Wagner R.K., Willcutt E.G., Fletcher J.M. Understanding, educating, and supporting children with specific learning disabilities: 50 years of science and practice. Am Psychol. 2020.75(1):37–51. https://doi.org/10.1037/amp0000452.
4. Крыжановский Г.Н., Носкин Л.А., Карганов М.Ю. Полисистемный саногенетический мониторинг: обеспечение функционального здоровья учащихся в ходе модернизации образования. Вопросы современной педиатрии. 2006.5(5 S1):54–58. Edn: Qyukcr.
5. Mavrenkova P., Pankova N., Lebedeva M.. Karganov M. Features of psychomotor coordination in adolescents with neuropsychiatric pathology enrolled in a standard educational. Program Brain Sci. 2022.12(2):245. https://doi.org/10.3390/brainsci12020245.
6. Mavrenkova P.V., Pankova N.B., Lebedeva M.A., Karganov M.Yu. Heart rate variability peculiarities in adolescents with psychopathology in the educational environment. Univers J Public Healt. 2021.9(6):445–453. https://doi.org/10.13189/ujph.2021.090612.
7. Nguyen H.B., Park H., Lim J.E., Nguyen T.T., Kim H.H., Kim K. et al. Evaluation of dynamic light scattering as an effective quality control method for aggregates in radiolabeled antibodies. N J Med Chem. 2025.68(1):555–565. https://doi.org/10.1021/acs.jmedchem.4c02344.
8. Te Nijenhuis L.H., Gangaram Panday N.H., Specht P.A.C., Fine I., Elstein N., Mik E.G. et al. Detection of hemodynamic changes in a porcine lipopolysaccharide model of systemic inflammation using dynamic light scattering measurements of the microcirculation. Front Med (Lausanne). 2025.12:1522630. https://doi.org/10.3389/fmed.2025.1522630.
9. Бажора Ю.И., Носкин Л.А. Лазерная корреляционная спектроскопия в медицине. Одесса: Друк. 2002.
10. Stetefeld J., Mc Kenna S.A., Patel T.R. Dynamic light scattering: a practical guide and applications in biomedical sciences. Biophys Rev. 2016.8(4):409–427. https://doi.org/10.1007/s12551-016-0218-6.
11. Minton A.P. Recent applications of light scattering measurement in the biological and biopharmaceutical sciences. Anal Biochem. 2016.501:4–22. https://doi.org/10.1016/j.ab.2016.02.007.
12. Румянцева Е.И., Ковалев И.Е., Ковалева О.И. Карганов М.Ю. Лазерная корреляционная спектроскопия макромолекулярных комплексов как эффективный метод выявления передозировки инсулина и коррекции инсулинотерапии при сахарном диабете у детей. Доклады Академии наук. 2005.402(3):405–408. Edn: Hsfspv.
13. Weiss J.N., Levy S. Dynamic light scattering spectroscopy of the retina — a non invasive quantitative technique to objectively document visual improvement following ocular stem cell treatment. Stem Cell Investig. 2019.6:8. https://doi.org/10.21037/sci.2019.03.01.
14. Alchinova I., Arkhipova E., Sidnev D., Sanadze A., Dedaev S., Karganov M. A Comparative analysis of the informative value of radioimmunoassay and laser correlation spectroscopy in myasthenia gravis. Isrn Immunology. 2014.718393:5. https://doi.org/10.1155/2014/718393.
15. Ковалева О.И., Ковалева Л.Г., Горбунова Н.А., Карганов М.Ю. Новые возможности ранней диагностики заболеваний системы крови. Гематология и трансфузиология. 2004.49(4):7–13. Edn: Mxubov.
16. Usenko T., Miroshnikova V., Bezrukova A., Basharova K., Landa S., Korobova Z. et al. Fraction of plasma exomeres and low density lipoprotein cholesterol as a predictor of fatal outcome of Covid-19. Plos One. 2023;18(2):e0278083. https://doi.org/10.1371/journal.pone.0278083.
17. Weiss J.N., Eber D. Earlier diagnosis of Alzheimer’s disease by dynamic light scattering spectroscopy. J Alzheimers Dis. 2025.104(3):649–652. https://doi.org/10.1177/1387287725131935.
18. Landa S., Verlov N., Fedorova N., Filatov M., Pantina R., Burdakov V. et al. Extracellular particles as carriers of cholesterol not associated with lipoproteins. Membranes. 2022.12:618. https://doi.org/10.3390/membranes12060618.
19. Ланда С.Б., Аль Шукри С.Х., Горбачев М.И., Егоров В.В., Эмануэль Ю.В., Эмануэль В.Л. Патохимические особенности олигомерных форм белка Тамма–Хорсфалла при уролитиазе. Клиническая лабораторная диагностика. 2016.61(6):335–341. https://doi.org/10.18821/0869-2084-2016-6-335-341.
20. Polysystemic approach to school, sport and environment medicine. M. Karganov, ed. Omics Group Incorporation — e Books. Foster City, Ca, Usa. 2014. 168 p. https://doi.org/10.4172/978-1-63278-000-3-001.
21. Hergenhan S., Holtkamp S., Scheiermann C. Molecular interactions between components of the circadian clock and the immune system. J Mol Biol. 2020.432(12):3700–3713. https://doi.org/10.1016/j.jmb.2019.12.044.
22. Karganov M., Alchinova I., Arkhipova E., Skalny A.V. Laser Correlation Spectroscopy: Nutritional, Ecological and Toxic Aspects. A.N. Misra, ed. In: Biophysics. In Tech. 2012. P. 1–16. https://doi.org/10.5772/35254.
23. Титов В.Н., Карганов М.Ю., Ротенко А.А., Дмитриев В.А., Алчинова И.Б., Архипова Е.Н. Биологические функции и биологические реакции. Лазерная корреляционная спектроскопия в оценке чистоты межклеточной среды — функции эндоэкологии (Лекция). Клиническая лабораторная диагностика. 2009.(6):21–35. EdnN: Kuvgtd.
24. Pedrinia M., Caob B., Nanid J.V.S., Cerqueiraa R.O., Mansurb R.B., Tasice L. et al. Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders. Prog Neuropsychopharmacol Biol Psychiatry. 2019.93:182–188. https://doi.org/10.1016/j.pnpbp.2019.03.010.
25. Shih Pa. Metabolomics Biomarkers for Precision Psychiatry. In: The Role of Bioactive Lipids in Cancer, Inflammation and Related Diseases. K. Honn, D. Zeldin, eds. Advances in Experimental Medicine and Biology. 1161. Springer. Cham. 2019. https://doi.org/10.1007/978-3-030-21735-8_10.
26. Predescu E., Vaidean T., Rapciuc A.M., Sipos R. Metabolomic markers in Attention Deficit/Hyperactivity Disorder (Adhd) among children and adolescents — A systematic review. Int J Mol Sci. 2024.25(8):4385. https://doi.org/10.3390/ijms25084385.
27. Brydges C.R., Bhattacharyya S., Dehkordi S.M., Milaneschi Y., Penninx B., Jansen R. et al. Mood disorders precision medicine consortium. Metabolomic and inflammatory signatures of symptom dimensions in major depression. Brain Behav Immun. 2022.102:42–52. https://doi.org/10.1016/j.bbi.2022.02.003.
28. Rhee S.J., Kim H., Lee Y. et al. The association between serum microbial Dna composition and symptoms of depression and anxiety in mood disorders. Sci Rep. 2021.11(1):13987. https://doi.org/10.1038/s41598-021-93112_z.
29. Мавренкова П.В., Ковалева О.И., Алчинова И.Б., Карганов М.Ю. Лазерная корреляционная спектроскопия выявляет сходные изменения в сыворотке крови пациентов с пограничным расстройством личности и крыс с неонатальным стрессом. Медицинская физика, 2023.(2):72–73. Edn: Bqhcia.
