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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Human Physiology</journal-id><journal-title-group><journal-title xml:lang="en">Human Physiology</journal-title><trans-title-group xml:lang="ru"><trans-title>Физиология человека</trans-title></trans-title-group></journal-title-group><issn publication-format="print">0131-1646</issn><issn publication-format="electronic">3034-6150</issn><publisher><publisher-name xml:lang="en">The Russian Academy of Sciences</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">663984</article-id><article-id pub-id-type="doi">10.31857/S0131164624020024</article-id><article-id pub-id-type="edn">VLCPMR</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Articles</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Статьи</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Sex Differences in the Effect of Brain-derived Neurotrophic Factor (BDNF) Val66Met Polymorphism on Baseline EEG Connectivity</article-title><trans-title-group xml:lang="ru"><trans-title>Половые различия в эффекте полиморфизма Val66Met мозгового нейротрофического фактора (BDNF) в отношении показателей базовой ЭЭГ-коннективности</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Privodnova</surname><given-names>E. Yu.</given-names></name><name xml:lang="ru"><surname>Приводнова</surname><given-names>Е. Ю.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>privodnovaeu@neuronm.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Volf</surname><given-names>N. V.</given-names></name><name xml:lang="ru"><surname>Вольф</surname><given-names>Н. В.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>privodnovaeu@neuronm.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Scientific Research Institute of Neurosciences and Medicine</institution></aff><aff><institution xml:lang="ru">ФГБНУ Научно-исследовательский институт нейронаук и медицины</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Novosibirsk State University</institution></aff><aff><institution xml:lang="ru">Новосибирский государственный университет</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2024-07-24" publication-format="electronic"><day>24</day><month>07</month><year>2024</year></pub-date><volume>50</volume><issue>2</issue><fpage>20</fpage><lpage>31</lpage><history><date date-type="received" iso-8601-date="2025-02-25"><day>25</day><month>02</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2024, Russian Academy of Sciences</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2024, Российская академия наук</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="en">Russian Academy of Sciences</copyright-holder><copyright-holder xml:lang="ru">Российская академия наук</copyright-holder></permissions><self-uri xlink:href="https://journals.eco-vector.com/0131-1646/article/view/663984">https://journals.eco-vector.com/0131-1646/article/view/663984</self-uri><abstract xml:lang="en"><p>Dependent on Val66Met polymorphism in BDNF gene secretion of neurotrophin affects morphological and functional changes in the developing and mature nervous system, in particular, may contribute to associated with white matter degradation changes in connectivity observed with aging. It was also shown that the associated with Val66Met polymorphism differences in connectivity between cortical structures are moderated by the sex of the subjects. However, there are no studies examining the effect of polymorphism on connectivity, taking into account age and gender differences. In this regard, the present study examined the associations of the Val66Met polymorphism of the BDNF gene with the characteristics of delayed phase synchronization based on EEG data in 223 younger (from 18 to 35 years old) and 134 older (over 55 years old) men and women. The analysis included connections between 84 cortical areas, identified on the basis of 42 Brodmann areas located in the left and right hemispheres. A statistically significant effect, including the factor of polymorphism, was the SEX × GENOTYPE interaction when considering associations at the frequency of the α<sub>1</sub>-rhythm: in Val/Met men, the strength of thirty-three connections was higher compared to Val/Val. Strengthening of connections was observed mainly between the parahippocampal regions of different hemispheres. At the frequency of the gamma rhythm, associated with the genotype differences in connectivity depended on gender and age. In young subjects, the scores of connectivity in Val/Val women were lower in comparison with men, however, no differences between Val/Val and Met carriers were found in any age group. The combined effect of sex and BDNF genotype on the baseline EEG parameters of brain connectivity may be a background for further study of the role of these factors in the formation of basic characteristics of brain activity.</p></abstract><trans-abstract xml:lang="ru"><p>Зависимая от генотипа по полиморфизму <italic>Val66Met</italic> гена <italic>BDNF</italic> секреция нейротрофина влияет на морфологические и функциональные изменения в развивающейся и зрелой нервной системе, в частности, может вносить вклад в связанные с деградацией белого вещества изменения коннективности, наблюдаемые при старении. Также показано, что ассоциированные с <italic>Val66Met</italic> полиморфизмом различия в коннективности между корковыми структурами опосредованы полом испытуемых. Однако работы, в которых эффекты полиморфизма в отношении коннективности рассматриваются с учетом возрастных и половых различий отсутствуют. В связи с этим в настоящем исследовании рассмотрены ассоциации полиморфизма <italic>Val66Met</italic> гена <italic>BDNF </italic>с характеристиками отставленной фазовой синхронизации на основе данных электроэнцефалограммы (ЭЭГ) у 223 молодых (от 18 до 35 лет) и 134 пожилых (старше 55 лет) мужчин и женщин. В анализ вошли связи между 84 корковыми областями, выделенными на основе 42 областей Бродмана, расположенных в левом и правом полушарии. Статистически значимым эффектом, включающим фактор полиморфизма, было взаимодействие ПОЛ × ГЕНОТИП при рассмотрении связей на частоте α<sub>1</sub>-ритма: у мужчин <italic>Val</italic>/<italic>Met</italic> сила тридцати трех связей выше по сравнению с мужчинами <italic>Val</italic>/<italic>Val</italic> генотипа. Усиление связей наблюдалось преимущественно между парагиппокампальными областями разных полушарий. На частоте γ-ритма ассоциированные с генотипом особенности коннективности различались в зависимости от пола и возраста. У молодых испытуемых значение коннективности у женщин <italic>Val</italic>/<italic>Val</italic> было меньше по сравнению с мужчинами, однако различий между <italic>Val</italic>/<italic>Val</italic> и <italic>Met-</italic>носителями не было выявлено ни в одной возрастной группе. Обнаруженное совместное влияние пола и генотипа <italic>BDNF</italic> на показатели фоновой ЭЭГ-коннективности мозга является предпосылкой для дальнейшего изучения роли этих факторов в формировании базовых характеристик активности мозга.</p></trans-abstract><kwd-group xml:lang="en"><kwd>brain-derived neurotrophic factor</kwd><kwd>BDNF Val66Met polymorphism</kwd><kwd>connectivity</kwd><kwd>background EEG</kwd><kwd>lagged phase synchronization</kwd><kwd>sex differences</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>нейротрофический фактор мозга</kwd><kwd>BDNF Val66Met полиморфизм</kwd><kwd>коннективность</kwd><kwd>фоновая ЭЭГ</kwd><kwd>отставленная фазовая синхронизация</kwd><kwd>половые различия</kwd></kwd-group><funding-group><award-group><funding-source><institution-wrap><institution xml:lang="ru">Правительство РФ</institution></institution-wrap><institution-wrap><institution xml:lang="en">Government of the Russian Federation</institution></institution-wrap></funding-source><award-id>122042700001-9</award-id></award-group></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Anastasia A., Deinhardt K., Chao M.V. et al. Val66Met polymorphism of BDNF alters prodomain structure to induce neuronal growth cone retraction // Nat. Commun. 2013. V. 4. P. e2490.</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>Szarowicz C.A., Steece-Collier K., Caulfield M.E. New Frontiers in Neurodegeneration and Regeneration Associated with Brain-Derived Neurotrophic Factor and the rs6265 Single Nucleotide Polymorphism // Int. J. Mol. Sci. 2022. V. 23. № 14. P. 8011.</mixed-citation></ref><ref id="B3"><label>3.</label><mixed-citation>Kowiański P., Lietzau G., Czuba E. et al. BDNF: A Key Factor with Multipotent Impact on Brain Signaling and Synaptic Plasticity // Cell. Mol. Neurobiol. 2018. V. 38. № 3. P. 579.</mixed-citation></ref><ref id="B4"><label>4.</label><mixed-citation>Knyazev G.G., Volf N.V., Belousova L.V. Age-related differences in electroencephalogram connectivity and network topology // Neurobiol. Aging. 2015. V. 36. № 5. P. 1849.</mixed-citation></ref><ref id="B5"><label>5.</label><mixed-citation>Varangis E., Habeck C.G., Razlighi Q.R., Stern Y. The Effect of Aging on Resting State Connectivity of Predefined Networks in the Brain // Front. Aging Neurosci. 2019. V. 11. P. 234.</mixed-citation></ref><ref id="B6"><label>6.</label><mixed-citation>Kailainathan S., Piers T.M., Yi J.H. et al. Activation of a synapse weakening pathway by human Val66 but not Met66 pro-brain-derived neurotrophic factor (proBDNF) // Pharmacol. Res. 2016. V. 104. P. 97.</mixed-citation></ref><ref id="B7"><label>7.</label><mixed-citation>Thomason M.E., Yoo D.J., Glover G.H., Gotlib I.H. BDNF genotype modulates resting functional connectivity in children // Front. Hum. Neurosci. 2009. V. 3. P. 55.</mixed-citation></ref><ref id="B8"><label>8.</label><mixed-citation>Wei S.M., Eisenberg D.P., Kohn P.D. et al. Brain-derived neurotrophic factor Val⁶⁶Met polymorphism affects resting regional cerebral blood flow and functional connectivity differentially in women versus men // J. Neurosci. 2012. V. 32. № 20. P. 7074.</mixed-citation></ref><ref id="B9"><label>9.</label><mixed-citation>Yin Y., Hou Z., Wang X. et al. The BDNF Val66Met polymorphism, resting-state hippocampal functional connectivity and cognitive deficits in acute late-onset depression // J. Affect. Disord. 2015. V. 183. P. 22.</mixed-citation></ref><ref id="B10"><label>10.</label><citation-alternatives><mixed-citation xml:lang="en">Toh Y.L., Ng T., Tan M. et al. Impact of brain-derived neurotrophic factor genetic polymorphism on cognition: A systematic review // Brain Behave. 2018. V. 8 № 7. P. e01009.</mixed-citation><mixed-citation xml:lang="ru">Toh Y.L., Ng T., Tan M. et al. Impact of brain-derived neurotrophic factor genetic polymorphism on cognition: A systematic review // Brain Behave. 2018. V. 8. № 7. P. e01009.</mixed-citation></citation-alternatives></ref><ref id="B11"><label>11.</label><mixed-citation>Rodríguez-Rojo I.C., Cuesta P., López M.E. et al. BDNF Val66Met Polymorphism and Gamma Band Disruption in Resting State Brain Functional Connectivity: A Magnetoencephalography Study in Cognitively Intact Older Females // Front. Neurosci. 2018. V. 12. P. 684.</mixed-citation></ref><ref id="B12"><label>12.</label><mixed-citation>Wang C., Zhang Y., Liu B. et al. Dosage effects of BDNF Val66Met polymorphism on cortical surface area and functional connectivity // J. Neurosci. 2014. V. 34. № 7. P. 2645.</mixed-citation></ref><ref id="B13"><label>13.</label><mixed-citation>Jang J.H., Yun J.-Y., Jung W.H. et al. The impact of genetic variation in comt and bdnf on resting-state functional connectivity // Int. J. Imaging Syst. Technol. 2012. V. 22. № 1. P. 97.</mixed-citation></ref><ref id="B14"><label>14.</label><mixed-citation>Colclough G.L., Smith S.M., Nichols T.E. et al. The heritability of multi-modal connectivity in human brain activity // eLife. 2017. V. 6. P. e20178.</mixed-citation></ref><ref id="B15"><label>15.</label><mixed-citation>Barber A.D., Hegarty C.E., Lindquist M., Karlsgodt K.H. Heritability of Functional Connectivity in Resting State: Assessment of the Dynamic Mean, Dynamic Variance, and Static Connectivity across Networks // Cereb. Cortex. 2021. V. 31. № 6. P. 2834.</mixed-citation></ref><ref id="B16"><label>16.</label><mixed-citation>Popov T., Tröndle M., Baranczuk-Turska Z. et al. Test-retest reliability of resting-state EEG in young and older adults // Psychophysiology. 2023. V. 60. № 7. P. e14268.</mixed-citation></ref><ref id="B17"><label>17.</label><citation-alternatives><mixed-citation xml:lang="en">Volf N.V., Privodnova E.Y., Bazovkina D.V. [Associations between the efficiency of hemispheric verbal memory processes and the BDNF Val66Met polymorphism in men and women] // Zh. Vyssh. Nerv. Deyat. Im. I.P. Pavlova. 2022. V. 72. № 6. P. 826.</mixed-citation><mixed-citation xml:lang="ru">Вольф Н.В., Приводнова Е.Ю., Базовкина Д.В. Ассоциации между эффективностью полушарных процессов вербальной памяти и BDNF VAL66MET полиморфизмом у мужчин и женщин // Ж. высш. нервн. деят. им. И.П. Павлова. 2022. T. 72. № 6. С. 826.</mixed-citation></citation-alternatives></ref><ref id="B18"><label>18.</label><citation-alternatives><mixed-citation xml:lang="en">Volf N.V., Privodnova E.Y. [Background EEG activity mediates associations between BDNF-VAL66MET polymorphism and memory during aging] // Zh. Vyssh. Nerv. Deyat. Im. I.P. Pavlova. 2023. V. 73. № 3. P. 398.</mixed-citation><mixed-citation xml:lang="ru">Вольф Н.В., Приводнова Е.Ю. Фоновая ЭЭГ активность опосредует ассоциации между BDNF VAL66MET полиморфизмом и памятью // Ж. высш. нервн. деят. им. И.П. Павлова. 2023. Т. 73. № 3. С. 398.</mixed-citation></citation-alternatives></ref><ref id="B19"><label>19.</label><mixed-citation>Annett M. A classification of hand preference by association analysis // Br. J. Psychol. 1970. V. 61. № 3. P. 303.</mixed-citation></ref><ref id="B20"><label>20.</label><mixed-citation>van Diessen E., Numan T., van Dellen E. et al. Opportunities and methodological challenges in EEG and MEG resting state functional brain network research // Clin. Neurophysiol. 2015. V. 126. № 8. P. 1468.</mixed-citation></ref><ref id="B21"><label>21.</label><mixed-citation>Rossini P.M., Di Iorio R., Bentivoglio M. et al. Methods for analysis of brain connectivity: An IFCN-sponsored review // Clin. Neurophysiol. 2019. V. 130. № 10. P. 1833.</mixed-citation></ref><ref id="B22"><label>22.</label><mixed-citation>Pascual-Marqui R.D. Instantaneous and lagged measures of linear and nonlinear dependence between groups of multivariate time series: Frequency decomposition // Int. J. Psychophysiol. 2007. V. 79. P. 55.</mixed-citation></ref><ref id="B23"><label>23.</label><mixed-citation>Chella F., Pizzella V., Zappasodi F., Marzetti L. Impact of the reference choice on scalp EEG-connectivity estimation // J. Neural Eng. 2016. V. 13. № 3. P. e036016.</mixed-citation></ref><ref id="B24"><label>24.</label><mixed-citation>Miljevic A., Bailey N.W., Vila-Rodriguez F. et al. Electroencephalographic Connectivity: A Fundamental Guide and Checklist for Optimal Study Design and Evaluation // Biol. Psychiatry Cogn. Neurosci. Neuroimaging. 2022. V. 7. № 6. P. 546.</mixed-citation></ref><ref id="B25"><label>25.</label><mixed-citation>Scally B., Burke M.R., Bunce D., Delvenne J.F. Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging // Neurobiol. Aging. 2018. V. 71. P. 149.</mixed-citation></ref><ref id="B26"><label>26.</label><mixed-citation>Angelakis E., Lubar J.F., Stathopoulou S., Kounios J. Peak alpha frequency: an electroencephalographic measure of cognitive preparedness // Clin. Neurophysiol. 2004. V. 115. № 4. P. 887.</mixed-citation></ref><ref id="B27"><label>27.</label><mixed-citation>Doppelmayr M., Klimesch W., Pachinger T., Ripper B. Individual differences in brain dynamics: important implications for the calculation of event-related band power // Biol. Cybern. 1998. V. 79. № 1. Р. 49.</mixed-citation></ref><ref id="B28"><label>28.</label><mixed-citation>Sheikh H.I., Hayden E.P., Kryski K.R. et al. Genotyping the BDNF rs6265 (val66met) polymorphism by one-step amplified refractory mutation system PCR // Psychiatr. Genet. 2010. V. 20. № 3. P. 109.</mixed-citation></ref><ref id="B29"><label>29.</label><mixed-citation>Utoomprurkporn N., Hardy C.J.D., Stott J. et al. “The Dichotic Digit Test” as an Index Indicator for Hearing Problem in Dementia: Systematic Review and Meta-Analysis // J. Am. Acad. Audiol. 2020. V. 31. № 9. P. 646.</mixed-citation></ref><ref id="B30"><label>30.</label><mixed-citation>Zalesky A., Fornito A., Bullmore E.T. Network-based statistic: Identifying differences in brain networks // NeuroImage. 2010. V. 53. № 4. P. 1197.</mixed-citation></ref><ref id="B31"><label>31.</label><mixed-citation>Bullmore E.T., Suckling J., Overmeyer S. et al. Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain // IEEE Trans. Med. Imaging. 1999. V. 18. № 1. P. 32.</mixed-citation></ref><ref id="B32"><label>32.</label><mixed-citation>West S.G., Finch J.F., Curran P.J. Structural equation models with non-normal variables / Structural equation modeling: Concepts, issues and applications // Ed. Hoyle R.H. Thousand Oaks, CA: Sage, 1995. P. 56.</mixed-citation></ref><ref id="B33"><label>33.</label><mixed-citation>Bagit A., Hayward, G.C., MacPherson R.E.K. Exercise and estrogen: common pathways in Alzheimer’s disease pathology // Am. J. Physiol. Endocrinol. Metab. 2021. V. 321. № 1. P. E164.</mixed-citation></ref><ref id="B34"><label>34.</label><mixed-citation>Allen A., McCarson K. Estrogen increases nociception-evoked brain-derived neurotrophic factor gene expression in the female rat // Neuroendocrinology. 2005. V. 81. № 3. P. 193.</mixed-citation></ref><ref id="B35"><label>35.</label><mixed-citation>Barha C.K., Liu-Ambrose T., Best J.R. et al. Sex-dependent effect of the BDNF Val66Met polymorphism on executive functioning and processing speed in older adults: Evidence from the Health ABC study // Neurobiol. Aging. 2018. V. 74. P. 161.</mixed-citation></ref><ref id="B36"><label>36.</label><mixed-citation>Filová B., Ostatníková D., Celec P., Hodosy J. The effect of testosterone on the formation of brain structures // Cells Tissues Organs. 2013. V. 197. № 3. P. 169.</mixed-citation></ref><ref id="B37"><label>37.</label><citation-alternatives><mixed-citation xml:lang="en">Spets D.S., Slotnick S.D. Are there sex differences in brain activity during long-term memory? A systematic review and fMRI activation likelihood estimation meta-analysis // Cogn. Neurosci. 2021. V. 12. № 3-4. P. 163.</mixed-citation><mixed-citation xml:lang="ru">Spets D.S., Slotnick S.D. Are there sex differences in brain activity during long-term memory? A systematic review and fMRI activation likelihood estimation meta-analysis // Cogn. Neurosci. 2021. V. 12. № 3–4. P. 163.</mixed-citation></citation-alternatives></ref><ref id="B38"><label>38.</label><mixed-citation>Luft C.D.B., Zioga I., Thompson N.M. et al. Right temporal alpha oscillations as a neural mechanism for inhibiting obvious associations // Proc. Natl. Acad. Sci. U.S.A. 2018. V. 115. № 52. P. e12144.</mixed-citation></ref><ref id="B39"><label>39.</label><mixed-citation>De Vincenti A.P., Ríos A.S., Paratcha G., Ledda F. Mechanisms That Modulate and Diversify BDNF Functions: Implications for Hippocampal Synaptic Plasticity // Front. Cell. Neurosci. 2019. V. 13. P. e135.</mixed-citation></ref><ref id="B40"><label>40.</label><mixed-citation>Stacho M., Manahan-Vaughan D. The Intriguing Contribution of Hippocampal Long-Term Depression to Spatial Learning and Long-Term Memory // Front. Behave. Neurosci. 2022. V. 16. P. 806356.</mixed-citation></ref><ref id="B41"><label>41.</label><mixed-citation>Matyi M.A., Spielberg J.M. The structural brain network topology of episodic memory // PloS One. 2022. V. 17. № 6. P. e0270592.</mixed-citation></ref></ref-list></back></article>
