Skip to main content
SpringerLink
Log in

Genetic Diversity of North Eurasia Populations by Genetic Markers Associated with Diseases Impairing Human Cognitive Functions

Russian Journal of Genetics volume 57, pages 1082–1091 (2021)Cite this article

Abstract

The genetic diversity of sixteen native populations of North Eurasia is investigated using a panel of genetic markers in genes associated, according to the data of genome-wide association studies, with diseases that lead to impaired human cognitive functions (schizophrenia, Alzheimer’s disease, and their cognitive endophenotypes). There is a decrease in genetic diversity in the geographic space from west to east. The highest level of genetic diversity was shown in Caucasoid populations. There are two groups of SNPs that predominate in Caucasians or Mongoloids. The location of sixteen populations in the space of the principle components demonstrates their geographic localization. Clusterization of populations in accordance with their affiliation to four geographic regions was observed. In general, the analysis of within- and between-population genetic diversity for 28 markers in 16 populations replicates the patterns of the Northern Eurasia gene pool structure, which are described using other marker systems.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1.
Fig. 2.

REFERENCES

  1. Yakhno, N.N., Zakharov, V.V., Lokshina, A.B., et al., Dementsii: rukovodstvo dlya vrachei (Dementia: Guidance for Doctors), Moscow: MEDpress-inform, 2011.

  2. Zakharov, V.V. and Yakhno, N.N., Kognitivnye rasstroistva v pozhilom i starcheskom vozraste: metodicheskoe posobie dlya vrachei (Cognitive Disorders in Old and Senile Age: A Methodological Guide for Physicians), Moscow, 2005.

  3. Alzheimer’s Association, Alzheimer’s disease facts and figures, Alzheimers Dement., 2019, vol. 15, no. 3, pp. 321—387.

    Article  Google Scholar 

  4. Heinrichs, R.W. and Zakzanis, K.K., Neurocognitive deficit in schizophrenia: a quantitative review of the evidence, Neuropsychology, 1998, vol. 12, no. 3, pp. 426—445. https://doi.org/10.1037//0894-4105.12.3.426

    Article  CAS  PubMed  Google Scholar 

  5. Kontaxaki, M.I., Kattoulas, E., Smyrnis, N., and Stefanis, N.C., Cognitive impairments and psychopathological parameters in patients of the schizophrenic spectrum, Psychiatriki, 2014, vol. 25, no. 1, pp. 27—38.

    PubMed  Google Scholar 

  6. Logue, M.W., Schu, M., Vardarajan, B.N., et al., Multi-institutional research on Alzheimer genetic epidemiology (MIRAGE) study group: a comprehensive genetic association study of Alzheimer disease in African Americans, Arch. Neurol., 2011, vol. 68, no. 12, pp. 1569—1579. https://doi.org/10.1001/archneurol.2011.646

    Article  PubMed  PubMed Central  Google Scholar 

  7. Seshadri, S., Fitzpatrick, A.L., Ikram, M.A., et al., Genome-wide analysis of genetic loci associated with Alzheimer disease, JAMA, 2010, vol. 303, no. 18, pp. 1832—1840. https://doi.org/10.1001/jama.2010.574

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Shi, Y., Li, Z., Xu, Q., et al., Common variants on 8p12 and 1q24.2 confer risk of schizophrenia, Nat. Genet., 2011, vol. 43, no. 12, pp. 1224—1227.

    Article  CAS  Google Scholar 

  9. Kirov, G., Zaharieva, I., Georgieva, L., et al., A genome-wide association study in 574 schizophrenia trios using DNA pooling, Mol. Psychiatry, 2009, vol. 14, no. 8, pp. 796—803. https://doi.org/10.1038/mp.2008.33

    Article  CAS  PubMed  Google Scholar 

  10. Ripke, S., Sanders, A.R., Kendler, K.S., et al., Genome-wide association study identifies five new schizophrenia loci, Nat. Genet., 2011, vol. 43, no. 10, pp. 969—976.

    Article  CAS  Google Scholar 

  11. Loo, S.K., Shtir, C., Doyle, A.E., et al., Genome-wide association study of intelligence: additive effects of novel brain expressed genes, J. Am. Acad. Child Adolesc. Psychiatry, 2012, vol. 51, no. 4, pp. 432—440. https://doi.org/10.1016/j.jaac.2012.01.006

    Article  PubMed  Google Scholar 

  12. Aberg, K.A., Liu, Y., Bukszár, J., et al., A comprehensive family-based replication study of schizophrenia genes, JAMA Psychiatry, 2013, vol. 70, no. 6, pp. 573—581. https://doi.org/10.1001/jamapsychiatry.2013.288

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Stefansson, H., Ophoff, R.A., Steinberg, S., et al., Common variants conferring risk of schizophrenia, Nature, 2009, vol. 6, no. 460, no. 7256, pp. 744—747. https://doi.org/10.1038/nature08186

  14. Børglum, A.D., Demontis, D., Grove, J., et al., Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci, Mol. Psychiatry, 2014, vol. 19, no. 3, pp. 325—333. https://doi.org/10.1038/mp.2013.2

    Article  CAS  PubMed  Google Scholar 

  15. Hu, X., Pickering, E., Liu, Y.C., et al., Meta-analysis for genome-wide association study identifies multiple variants at the BIN1 locus associated with late-onset Alzheimer’s disease, PLoS One, 2011, vol. 24, no. 6(2). e16616. https://doi.org/10.1371/journal.pone.0016616

  16. O’Donovan, M.C., Craddock, N., Norton, N., et al., Identification of loci associated with schizophrenia by genome-wide association and follow-up, Nat. Genet., 2008, vol. 40, no. 9, pp. 1053—1055. https://doi.org/10.1038/ng.201

    Article  CAS  PubMed  Google Scholar 

  17. Kamboh, M.I., Barmada, M.M., Demirci, F.Y., et al., Genome-wide association analysis of age-at-onset in Alzheimer’s disease, Mol. Psychiatry, 2012, vol. 17, no. 12, pp. 1340—1346.

    Article  CAS  Google Scholar 

  18. Naj, A.C., Jun, G., Beecham, G.W., et al., Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease, Nat. Genet., 2011, vol. 43, no. 5, pp. 436—441. https://doi.org/10.1038/ng.801

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Yue, W.H., Wang, H.F., Sun, L.D., et al., Genome-wide association study identifies a susceptibility locus for schizophrenia in Han Chinese at 11p11.2, Nat. Genet., 2011, vol. 43, no. 12, pp. 1228—1231. https://doi.org/10.1038/ng.979

    Article  CAS  PubMed  Google Scholar 

  20. Sullivan, P.F., Lin, D., Tzeng, J.Y., et al., Genomewide association for schizophrenia in the CATIE study: results of stage 1, Mol. Psychiatry, 2008, vol. 13, no. 6, pp. 570—584. https://doi.org/10.1038/mp.2008.25

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Purcell, S.M., Wray, N.R., Stone, J.L., et al., Common polygenic variation contributes to risk of schizophrenia and bipolar disorder, Nature, 2009, vol. 460, no. 7256, pp. 748—752.

    Article  CAS  Google Scholar 

  22. Bergen, S.E., O’Dushlaine, C.T., Ripke, S., et al., Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder, Mol. Psychiatry, 2012, vol. 17, no. 9, pp. 880—886. https://doi.org/10.1038/mp.2012.73

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Need, A.C., Attix, D.K., McEvoy, J.M., et al., A genome-wide study of common SNPs and CNVs in cognitive performance in the CANTAB, Hum. Mol. Genet., 2009, vol. 18, no. 23, pp. 4650—4661. https://doi.org/10.1093/hmg/ddp413

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Cirulli, E.T., Kasperaviciūte, D., Attix, D.K., et al., Common genetic variation and performance on standardized cognitive tests, Eur. J. Hum. Genet., 2010, vol. 18, no. 7, pp. 815—820. https://doi.org/10.1038/ejhg.2010.2

    Article  PubMed  PubMed Central  Google Scholar 

  25. Bertram, L., Lange, C., Mullin, K., et al., Genome-wide association analysis reveals putative Alzheimer’s disease susceptibility loci in addition to APOE, Am. J. Hum. Genet., 2008, vol. 83, no. 5, pp. 623—632. https://doi.org/10.1016/j.ajhg.2008.10.008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Athanasiu, L., Mattingsdal, M., Kähler, A.K., et al., Gene variants associated with schizophrenia in a Norwegian genome-wide study are replicated in a large European cohort, J. Psychiatr. Res., 2010, vol. 44, no. 12, pp. 748—753. https://doi.org/10.1016/j.jpsychires.2010.02.002

    Article  PubMed  PubMed Central  Google Scholar 

  27. Cummings, A.C., Jiang, L., Velez Edwards, D.R., et al., Genome-wide association and linkage study in the Amish detects a novel candidate late-onset Alzheimer disease gene, Ann. Hum. Genet., 2012, vol. 76, no. 5, pp. 342—351. https://doi.org/10.1111/j.1469-1809.2012.00721.x

    Article  PubMed  PubMed Central  Google Scholar 

  28. Shifman, S., Johannesson, M., Bronstein, M., et al., Genome-wide association identifies a common variant in the reelin gene that increases the risk of schizophrenia only in women, PLoS Genet., 2008, vol. 4, no. 2. e28. https://doi.org/10.1371/journal.pgen.0040028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Moreno-Grau, S., de Rojas, I., Hernández, I., et al., Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer’s disease and three causality networks: the GR@ACE project2019, Alzheimers Dement., 2019, vol. 15, no. 10, pp. 1333—1347. https://doi.org/10.1016/j.jalz.2019.06.4950

    Article  PubMed  Google Scholar 

  30. Mathew, C.G., The isolation of high molecular weight eukaryotic DNA, Methods Mol. Biol., 1985, vol. 2, pp. 31—34.

    CAS  PubMed  Google Scholar 

  31. Vagaitseva, K.V., Bocharova, A.V., Marusin, A.V., et al., Development of multiplex genotyping method of polymorphic markers of genes associated with cognitive abilities, Russ. J. Genet., 2018, vol. 54, no. 6, pp. 740—745. https://doi.org/10.1134/S1022795418060121

    Article  CAS  Google Scholar 

  32. Stepanov, V.A. and Trifonova, E.A., Multiplex SNP genotyping by MALDITOF mass spectrometry: frequencies of 56 immune response gene SNPs in human populations, Mol. Biol. (Moscow), 2013, vol. 47, no. 6, pp. 852—862. https://doi.org/10.1134/S0026893313060149

    Article  CAS  Google Scholar 

  33. Trifonova, E.A., Popovich, A.A., Vagaitseva, K.V., et al., The multiplex genotyping method for single-nucleotide polymorphisms of genes associated with obesity and body mass index, Russ. J. Genet., 2019, vol. 55, no. 10, pp. 1282—1293. https://doi.org/10.1134/S1022795419100144

    Article  CAS  Google Scholar 

  34. Nei, M., Molecular Population Genetics and Evolution, New York: Columbia Univ. Press, 1987.

    Book  Google Scholar 

  35. Excoffier, L., Laval, G., and Schneider, S., Arlequin ver. 3.0: an integrated software package for population genetics data analysis, Evol. Bioinf. Online, 2005, vol. 1, pp. 47—50. https://doi.org/10.1177/117693430500100003

    Article  CAS  Google Scholar 

  36. Stepanov, V.A., Khar’kov, V.N., Trifonova, E.A., and Marusin, A.V., Metody statisticheskogo analiza v populyatsionnoi i evolyutsionnoi genetike cheloveka (nasledstvennost’ i zdorov’e): uchebno-metodicheskoe posobie (Methods of Statistical Analysis in Human Population and Evolutionary Genetics: Study Guide), Puzyrev, V.P., Ed., Tomsk: Pechatnaya Manufaktura, 2014.

    Google Scholar 

  37. Vagaitseva, K.V., Genetic diversity of North Eurasian populations by the X chromosome STR and SNP markers and their DNA identification potential, Cand. Sci. (Biol.) Dissertation, Tomsk: Research Institute of Medical Genetics, Siberian Branch of the Russian Academy of Medical Sciences, 2015.

  38. Khar’kov, V.N., Gene pool structure and phylogeography of indigenous population of Siberia inferred from Y-chromosome markers, Doctoral (Biol.) Dissertation, Tomsk: Research Institute of Medical Genetics, Siberian Branch of the Russian Academy of Medical Sciences, 2012.

  39. Stepanov, V.A., Khar’kov, V.N., Puzyrev, V.P., and Spiridonova, M.G., Genetic diversity of Y-chromosome lines among the peoples of Siberia, in Genofond naseleniya Sibiri (The Gene Pool of the Population of Siberia), Novosibirsk: Inst. Arkheol. Etographii Sib. Otd. Ross. Akad. Nauk, 2003, pp. 147—152.

  40. Golubenko, M.V., Eremina, E.R., Tadinova, V.N., et al., Territorial gene pool differentiation among population of Siberia and Central Asia relative to restriction polymorphism of mitochondrial DNA, Med. Genet., 2002, vol. 1, no. 3, pp. 124—128.

    Google Scholar 

Download references

Funding

The present study was supported by the Russian Foundation for Basic Research (project no. 18-29-13045).

Author information

Authors and Affiliations

  1. Research Institute of Medical Genetics, Tomsk National Research Medical Center, Russian Academy of Sciences, 634050, Tomsk, Russia

    A. V. Bocharova & V. A. Stepanov

Authors
  1. A. V. Bocharova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. A. Stepanov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. V. Bocharova.

Ethics declarations

Conflict of interest. The authors declare no conflict of interest.

Statement of compliance with standards of research involving humans as subjects. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants involved in the study.

Additional information

Translated by A. Kazantseva

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bocharova, A.V., Stepanov, V.A. Genetic Diversity of North Eurasia Populations by Genetic Markers Associated with Diseases Impairing Human Cognitive Functions. Russ J Genet 57, 1082–1091 (2021). https://doi.org/10.1134/S1022795421080020

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1022795421080020

Keywords:

search

Navigation