Replication Study of GWAS-Associated Variants in the TUFM, SH2B1, ZNF638, NEGR1, ATP2A1, EXOC4, and CSE1L Genes and Cognitive Abilities

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

To date, a large number of genome-wide association analyses (GWAS) of cognitive abilities (i.e. intelligence, educational level, executive functions, etc.) have been conducted in European populations. A replication analysis of GWAS-associated variants of the general factor of intelligence in the development of spatial (3D) abilities in the individuals from Russia is relevant. In order to estimate the main effect of the most significant GWAS loci on spatial abilities in the Russian cohort (N = 1011, 18–25 years old) a set of seven “top” SNPs (p < 10–13) was formed: TUFM rs7187776, SH2B1 rs7198606, ZNF638 rs2287326, NEGR1 rs12128707, ATP2A1 rs8055138, EXOC4 rs1362739, and CSE1L rs6063353. Statistically significant differences (р < 0.05) in genotype frequencies distribution of ATP2A1 rs8055138, NEGR1 rs12128707, and ZNF638 rs2287326 between Russians, Tatars, and Udmurts have been observed. As a result of analysis of genotype-by-environment interactions we revealed ethnicity-specific character of associations: in Russians maternal age at delivery (βST = 0.84, p = 0.005) and in Tatars bilingual/unilingual rearing (βST = 0.44, р = 0.020) modulated association of ZNF638 rs2287326 with spatial abilities. Moreover, urban/rural residency in childhood modulated association of TUFM rs7187776 with 3D abilities (βST = 0.41, р = 0.009). The data obtained indicate the involvement of the ZNF638, TUFM, SH2B1, and EXOC4 genes, which are responsible for adipogenesis, in the manifestation of cognitive abilities, and, therefore, confirms the relationship between cognitive and metabolic disorders. Nevertheless, ethnicity-specific character of demonstrated associations and differences in genotype frequencies of analyzed GWAS-SNPs point to the specific pattern of associated genetic loci characteristic for the Russian cohort and to the complexity of replication of data reported for the combined samples of Europeans.

About the authors

A. V. Kazantseva

Institute of Biochemistry and Genetics – Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences

Author for correspondence.
Email: Kazantsa@mail.ru
Russia, 450054, Ufa

Yu. D. Davydova

Institute of Biochemistry and Genetics – Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences

Email: Kazantsa@mail.ru
Russia, 450054, Ufa

R. F. Enikeeva

Institute of Biochemistry and Genetics – Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences

Email: Kazantsa@mail.ru
Russia, 450054, Ufa

Z. R. Takhirova

Bashkir State University, Laboratory of Neurocognitive Genetics, Department of Genetics and Fundamental Medicine

Email: Kazantsa@mail.ru
Russia, 450076, Ufa

R. N. Mustafin

Bashkir State Medical University, Department of Medical Genetics and Fundamental Medicine

Email: Kazantsa@mail.ru
Russia, 450008, Ufa

M. M. Lobaskova

Psychological Institute of Russian Academy of Education

Email: Kazantsa@mail.ru
Russia, 125009, Moscow

S. B. Malykh

Psychological Institute of Russian Academy of Education; Lomonosov Moscow State University

Email: Kazantsa@mail.ru
Russia, 125009, Moscow; Russia, 119991, Moscow

E. K. Khusnutdinova

Institute of Biochemistry and Genetics – Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences; Bashkir State University, Laboratory of Neurocognitive Genetics, Department of Genetics and Fundamental Medicine; Lomonosov Moscow State University

Email: Kazantsa@mail.ru
Russia, 450054, Ufa; Russia, 450076, Ufa; Russia, 119991, Moscow

References

  1. Тихомирова Т.Н., Малых С.Б., Богомаз С.А. и др. Пространственное мышление и память у старшеклассников с различным уровнем математической беглости // Теоретич. и эксперим. психология. 2013. Т. 6. № 4. С. 99–109.
  2. Канзафарова Р.Ф., Казанцева А.В., Хуснутдинова Э.К. Генетические и средовые аспекты наличия трудностей в обучении математике // Генетика. 2015. Т. 51. № 3. С. 281–289. https://doi.org/10.7868/S0016675815010038
  3. Коногорская С.А. Особенности пространственного мышления и их взаимосвязь с учебной успешностью обучающихся // Научно-педагог. обозрение. 2017. Т. 15. № 1. https://doi.org/10.23951/2307-6127-2017-1-142-152
  4. Тахирова З.Р., Казанцева А.В., Еникеева Р.Ф. и др. Психогенетика пространственных способностей человека // Рос. психол. журн. 2021. Т. 18. № 2. С. 67–93. https://doi.org/10.21702/rpj.2021.2.5
  5. Kazantseva A.V., Enikeeva R.F., Davydova Y.D. et al. The role of the KIBRA and APOE genes in developing spatial abilities in humans // Vavilov. Zh. Genet. Selektsii. 2021. V. 25. № 8. P. 839–846. https://doi.org/10.18699/VJ21.097
  6. Казанцева А.В., Еникеева Р.Ф., Романова А.Р. и др. Взаимосвязь стресс-обусловленного когнитивного функционирования с вариантами генов регуляции синаптической пластичности // Генетика. 2020. Т. 56. № 1. С. 98–106. https://doi.org/10.31857/S0016675820010063
  7. Enikeeva R.F., Kazantseva A.V., Davydova Y.D. et al. The role of inflammatory system genes in individual differences in nonverbal intelligence // Vavilov. Zh. Genet. Selektsii. 2022. V. 26. № 2. P. 179–181. https://doi.org/10.18699/VJGB-22-22
  8. Laukka E.J., Köhncke Y., Papenberg G. et al. Combined genetic influences on episodic memory decline in older adults without dementia // Neuropsychology. 2020. V. 34. № 6. P. 654–666. https://doi.org/10.1037/neu0000637
  9. Ahmetov I.I., Valeeva E.V., Yerdenova M.B. et al. KIBRA gene variant is associated with ability in chess and science // Genes (Basel). 2023. V. 14. № 1. https://doi.org/10.3390/genes14010204
  10. Mustafin R.N., Kazantseva A.V., Enikeeva R.F. et al. Longitudinal genetic studies of cognitive characteristics // Vavilov. Zh. Genet. Selektsii. 2020. V. 24. № 1. P. 87–95. https://doi.org/10.18699/VJ20.599
  11. Bocharova A., Vagaitseva K., Marusin A. et al. Association and gene-gene interactions study of late-onset Alzheimer’s disease in the Russian population // Genes (Basel). 2021. V. 12. № 10. https://doi.org/10.3390/genes12101647
  12. Ortega-Rojas J., Arboleda-Bustos C.E., Guerrero E. et al. Genetic variants and haplotypes of TOMM40, APOE, and APOC1 are related to the age of onset of late-onset Alzheimer disease in a Colombian population // Alzheimer Dis. Assoc. Disord. 2022. V. 36. № 1. P. 29–35. https://doi.org/10.1097/WAD.0000000000000477
  13. Lee J.J., Wedow R., Okbay A. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals // Nat. Genet. 2018. V. 50. № 8. P. 1112–1121. https://doi.org/10.1038/s41588-018-0147-3
  14. Lam M., Trampush J.W., Yu J. et al. Large-scale cognitive GWAS meta-analysis reveals tissue-specific neural expression and potential nootropic drug targets // Cell. Rep. 2017. V. 21. № 9. P. 2597–2613. https://doi.org/10.1016/j.celrep.2017.11.028
  15. Lam M., Chen C.-Y., Li Z. et al. Comparative genetic architectures of schizophrenia in East Asian and European populations // Nat. Genet. 2019. V. 51. № 12. P. 1670–1678. https://doi.org/10.1038/s41588-019-0512-x
  16. Hill W.D., Marioni R.E., Maghzian O. et al. A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence // Mol. Psychiatry. 2019. V. 24. № 2. P. 169–181. https://doi.org/10.1038/s41380-017-0001-5
  17. Savage J.E., Jansen P.R., Stringer S. et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence // Nat. Genet. 2018. V. 50. № 7. P. 912–919. https://doi.org/10.1038/s41588-018-0152-6
  18. Plomin R., Kovas Y. Generalist genes and learning disabilities // Psychol. Bull. 2005. V. 131. № 4. P. 592–617. https://doi.org/10.1037/0033-2909.131.4.592
  19. Brouwer-Brolsma E.M., van de Rest O., Godschalk R. et al. Associations between maternal long-chain polyunsaturated fatty acid concentrations and child cognition at 7 years of age: The MEFAB birth cohort // Prostaglandins Leukot. Essent. Fatty Acids. 2017. V. 126. P. 92–97. https://doi.org/10.1016/j.plefa.2017.09.012
  20. Asnaani A., Richey J.A., Dimaite R. et al. A cross-ethnic comparison of lifetime prevalence rates of anxiety disorders // J. Nerv. Ment. Dis. 2010. V. 198. № 8. P. 551–555. https://doi.org/10.1097/NMD.0b013e3181ea169f
  21. Hao Y., Liu X., Lu X. et al. Genome-wide association study in Han Chinese identifies three novel loci for human height // Hum. Genet. 2013. V. 132. № 6. P. 681–689. https://doi.org/10.1007/s00439-013-1280-9
  22. Meruvu S., Hugendubler L., Mueller E. Regulation of adipocyte differentiation by the zinc finger protein ZNF638 // J. Biol. Chem. 2011. V. 286. № 30. P. 26 516–26 523. https://doi.org/10.1074/jbc.M110.212506
  23. Perie L., Verma N., Mueller E. The forkhead box transcription factor FoxP4 regulates thermogenic programs in adipocytes // J. Lipid Res. 2021. V. 62. https://doi.org/10.1016/j.jlr.2021.100102
  24. Snijders Blok L., Vino A., den Hoed J. et al. Heterozygous variants that disturb the transcriptional repressor activity of FOXP4 cause a developmental disorder with speech/language delays and multiple congenital abnormalities // Genet. Med. Off J. Am. Coll. Med. Genet. 2021. V. 23. № 3. P. 534–542. https://doi.org/10.1038/s41436-020-01016-6
  25. Bacon C., Schneider M., Le Magueresse C. et al. Brain-specific Foxp1 deletion impairs neuronal development and causes autistic-like behaviour // Mol. Psychiatry. 2015. V. 20. № 5. P. 632–639. https://doi.org/10.1038/mp.2014
  26. Hamdan F.F., Daoud H., Rochefort D. et al. De novo mutations in FOXP1 in cases with intellectual disability, autism, and language impairment // Am. J. Hum. Genet. 2010. V. 87. № 5. P. 671–678. https://doi.org/10.1016/j.ajhg.2010.09.017
  27. Lai C.S., Fisher S.E., Hurst J.A. et al. A forkhead-domain gene is mutated in a severe speech and language disorder // Nature. 2001. V. 413. № 6855. P. 519–523. https://doi.org/10.1038/35097076
  28. Co M., Anderson A.G., Konopka G. FOXP transcription factors in vertebrate brain development, function, and disorders // Wiley Interdiscip. Rev. Dev. Biol. 2020. V. 9. № 5. https://doi.org/10.1002/wdev.375
  29. Sargolini F., Roullet P., Oliverio A., Mele A. Effects of intra-accumbens focal administrations of glutamate antagonists on object recognition memory in mice // Behav. Brain Res. 2003. V. 138. № 2. P. 153–163. https://doi.org/10.1016/s0166-4328(02)00238-3
  30. Zhong B.-R., Zhou G.-F., Song L. et al. TUFM is involved in Alzheimer’s disease-like pathologies that are associated with ROS // FASEB J. Off. Publ. Fed. Am. Soc. Exp. Biol. 2021. V. 35. № 5. P. e21445. https://doi.org/10.1096/fj.202002461R
  31. Shungin D., Winkler T.W., Croteau-Chonka D.C. et al. New genetic loci link adipose and insulin biology to body fat distribution // Nature. 2015. V. 518. № 7538. P. 187–196. https://doi.org/10.1038/nature14132
  32. Lee D.E., Brown J.L., Rosa M.E. et al. Translational machinery of mitochondrial mRNA is promoted by physical activity in Western diet-induced obese mice // Acta Physiol. (Oxf.). 2016. V. 218. № 3. P. 167–177. https://doi.org/10.1111/apha.12687
  33. Yu X., Xia L., Zhang S. et al. Fluoride exposure and children’s intelligence: Gene-environment interaction based on SNP-set, gene and pathway analysis, using a case-control design based on a cross-sectional study // Environ. Int. 2021. V. 155. https://doi.org/10.1016/j.envint.2021.106681
  34. He K., Guo X., Liu Y. et al. TUFM downregulation induces epithelial-mesenchymal transition and invasion in lung cancer cells via a mechanism involving AMPK-GSK3β signaling // Cell Mol. Life Sci. 2016. V. 73. № 10. P. 2105–2121. https://doi.org/10.1007/s00018-015-2122-9
  35. Dadvand P., Nieuwenhuijsen M.J., Esnaola M. et al. Green spaces and cognitive development in primary schoolchildren // Proc. Natl Acad. Sci. USA. 2015. V. 112. № 26. P. 7937–7942. https://doi.org/10.1073/pnas.1503402112
  36. Dadvand P., Pujol J., Macià D. et al. The association between lifelong greenspace exposure and 3-Dimensional brain magnetic resonance imaging in Barcelona schoolchildren // Environ. Health Perspect. 2018. V. 126. № 2. https://doi.org/10.1289/EHP1876
  37. Rosa M.J., Just A.C., Guerra M.S. et al. Identifying sensitive windows for prenatal particulate air pollution exposure and mitochondrial DNA content in cord blood // Environ. Int. 2017. V. 98. P. 198–203. https://doi.org/10.1016/j.envint.2016.11.007
  38. Казанцева А.В., Давыдова Ю.Д., Еникеева Р.Ф. и др. Индивидуальные вариации длины теломер у здоровых индивидов: эффект полиморфного варианта гена TERT и урбанизации // Генетика. 2022. Т. 58. № 9. С. 1074–1084. https://doi.org/10.31857/S0016675822090107
  39. Pinakhina D., Yermakovich D., Vergasova E. et al. GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis // Front. Genet. 2022. V. 13. https://doi.org/10.3389/fgene.2022.972196

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2.

Download (275KB)
Indexing metadata

Copyright (c) 2023 А.В. Казанцева, Ю.Д. Давыдова, Р.Ф. Еникеева, З.Р. Тахирова, Р.Н. Мустафин, М.М. Лобаскова, С.Б. Малых, Э.К. Хуснутдинова

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies