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Development of Multiplex Genotyping Method of Polymorphic Markers of Genes Associated with Cognitive Abilities

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Abstract

A developed method of multiplex genotyping of polymorphic markers of genes associated with cognitive abilities and neuropsychiatric diseases is based on multilocus PCR and MALDI-TOF mass spectrometry of DNA molecules. The frequencies of 32 single-nucleotide markers localized in 24 genes are analyzed in a sample of elderly people from the Russian population of Tomsk. The data obtained are compared with data for populations from the 1000 Genomes Project.

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References

  1. Lezak, M.D., Neuropsyhology Assessment, New York: New York University Press, 1983.

    Google Scholar 

  2. Zakharov, V.V., Evolution of cognitive deficits: mild and moderate cognitive impairment, Nevrol., Neiropsikhiatr., Psikhosomatika, 2012, no. 2, pp. 16–21.

    Google Scholar 

  3. Zakharov, V.V., Principles of managing patients with cognitive impairment without dementia, Russ. Med. Zh., 2008, vol. 16, no. 12, pp. 1645–1649.

    Google Scholar 

  4. Kognitivnaya psikhologiya: uchebnik dlya vuzov (Cognitive Psychology: Guidebook), Druzhinin, V.N. and Ushakov, D.V., Eds., Moscow: PER SE, 2002.

  5. 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., 2013, vol. 47, no. 6, pp. 852–862. doi 10.1134/S0026893313060149

    Article  CAS  Google Scholar 

  6. Stepanov, V.A., Vagajceva, K.V., Bocharova, A.V., et al., Development of multiplex genotyping method of polymorphic markers for genes involved in human adaptation to cold climate, Sci. Evol., 2016, vol. 1, no. 2, pp. 92–101. doi 10.21603/2500–1418–2016–1–2–92–101

    Article  Google Scholar 

  7. Stepanov, V., Vagaitseva, K., Kharkov, V., et al., Forensic and population genetic characteristics of 62 X chromosome SNPs revealed by multiplex PCR and MALDI-TOF mass spectrometry genotyping in 4 North Eurasian populations, Leg. Med. (Tokyo), 2016, no. 18, pp. 66–71. doi 10.1016/j.legalmed.2015.12.008

    Article  CAS  Google Scholar 

  8. Stepanov, V.A., Vagaitseva, K.V., Kharkov, V.N., et al., Panel of X-linked single-nucleotide polymorphic markers for DNA identification (XSNPID) based on multiplex genotyping by multilocus PCR and MALDITOF mass spectrometry, Mol. Biol. (Moscow), 2016, vol. 50, no. 3, pp. 387–397. doi 10.1134/S0026893316030158

    Article  CAS  Google Scholar 

  9. Ramanan, V.K., Risacher, S.L., Nho, K., et al., APOE and BCHE as modulators of cerebral amyloid deposition: a florbetapir PET genome-wide association study, Mol. Psychiatry, 2014, vol. 19, no. 3, pp. 351–357. doi 10.1038/mp.2013.19

    Article  PubMed  CAS  Google Scholar 

  10. Kim, S., Swaminathan, S., Shen, L., et al., Genomewide association study of CSF biomarkers Abeta1-42, t-tau, and p-tau181p in the ADNI cohort, Neurology, 2011, vol. 76, no. 1, pp. 69–79. doi 10.1212/WNL. 0b013e318204a397

    Article  PubMed  CAS  Google Scholar 

  11. Zhang, C. and Pierce, B.L., Genetic susceptibility to accelerated cognitive decline in the US Health and Retirement Study, Neurobiol. Aging, 2014, vol. 35, no. 6, p. 1512.e11-8. doi 10.1016/j.neurobiolaging. 2013.12.021

    Article  PubMed  Google Scholar 

  12. Cruchaga, C., Kauwe, J.S., Harari, O., et al., GWAS of cerebrospinal fluid tau levels identifies risk variants for Alzheimer’s disease, Neuron, 2013, vol. 78, no. 2, pp. 256–268. doi 10.1016/j.neuron.2013.02.026

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Service, S.K., Verweij, K.J., Lahti, J., et al., A genomewide meta-analysis of association studies of Cloninger’s Temperament Scales, Transl. Psychiatry, 2012, no. 2. e116. doi 10.1038/tp.2012.37

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Davies, G., Armstrong, N., Bis, J.C., et al., Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N = 53949), Mol. Psychiatry, 2015, vol. 20, no. 2, pp. 183–192. doi 10.1038/mp. 2014.188

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Ibrahim-Verbaas, C.A., Bressler, J., Debette, S., et al., GWAS for executive function and processing speed suggests involvement of the CADM2 gene, Mol. Psychiatry, 2016, vol. 21, no. 2, pp. 189–197. doi 10.1038/mp. 2014.188

    Article  PubMed  CAS  Google Scholar 

  16. Debette, S., Ibrahim Verbaas, C.A., Bressler, J., et al., Genome-wide studies of verbal declarative memory in nondemented older people: the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, Biol. Psychiatry, 2015, vol. 77, no. 8, pp. 749–763. doi 10.1016/j.biopsych.2014.08.027

    Article  PubMed  Google Scholar 

  17. Jun, G., Ibrahim-Verbaas, C.A., Vronskaya, M., et al., A novel Alzheimer disease locus located near the gene encoding tau protein, Mol. Psychiatry, 2016, vol. 21, no. 1, pp. 108–117. doi 10.1038/mp.2015.23

    Article  PubMed  CAS  Google Scholar 

  18. Lambert, J.C., Heath, S., Even, G., et al., Genomewide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease, Nat. Genet., 2009, vol. 41, no. 10, pp. 1094–1099. doi 10.1038/ng. 439

    Article  PubMed  CAS  Google Scholar 

  19. Schizophrenia Working Group of the Psychiatric Genomics Consortium, Biological insights from 108 schizophrenia-associated genetic loci, Nature, 2014, vol. 511, no. 7510, pp. 421–427. doi 10.1038/nature13595

    Google Scholar 

  20. Loo, S.K., Shtir, C., Doyle, A.E., et al., Genome-wide association study of intelligence: additive effects ofnovel brain expressed genes, J. Am. Acad. Child Adolesc. Psychiatry, 2012, vol. 51, no. 4, pp. 432–440. e2. doi 10.1016/j.jaac.2012.01.006

    Article  PubMed  Google Scholar 

  21. Hollingworth, P., Harold, D., Sims, R., et al., Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease, Nat. Genet., 2011, vol. 43, no. 5, pp. 429–435. doi 10.1038/ng.803

    PubMed  CAS  Google Scholar 

  22. Lambert, J.C., Ibrahim-Verbaas, C.A., Harold, D., et al., Meta-analysis of 74046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease, Nat. Genet., 2013, vol. 45, no. 12, pp. 1452–1458. doi 10.1038/ng.2802

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. 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. doi 10.1038/ejhg.2010.2

    Article  PubMed  PubMed Central  Google Scholar 

  24. Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium, Genome-wide association study identifies five new schizophrenia loci, Nat. Genet., 2011, vol. 43, no. 10, pp. 969–976. doi 10.1038/ng.940

    Google Scholar 

  25. Cross-Disorder Group of the Psychiatric Genomics Consortium, Identification of risk loci with shared effects on five major psychiatric disorders: a genomewide analysis, Lancet, 2013, vol. 381, no. 9875, pp. 1371–1379. doi 10.1016/S0140-6736(12)62129-1

    Google Scholar 

  26. Furney, S.J., Simmons, A., Breen, G., et al., Genomewide association with MRI atrophy measures as a quantitative trait locus for Alzheimer’s disease, Mol. Psychiatry, 2011, vol. 16, no. 11, pp. 1130–1138. doi 10.1038/mp.2010.123

    Article  PubMed  CAS  Google Scholar 

  27. 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. doi 10.1093/hmg/ddp413

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Rietveld, C.A., Esko, T., Davies, G., et al., Common genetic variants associated with cognitive performance identified using the proxy-phenotype method, Proc. Natl. Acad. Sci. U.S.A., 2014, vol. 111, no. 38, pp. 13790–13794. doi 10.1073/pnas.1404623111

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. 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. doi 10.1111/j.1469-1809.2012.00721.x

    Article  PubMed  PubMed Central  Google Scholar 

  30. Calboli, F.C., Tozzi, F., Galwey, N.W., et al., A genome-wide association study of neuroticism in a population-based sample, PLoS One, 2010, vol. 5, no. 7. e11504. doi 10.1371/journal.pone.0011504

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Beecham, G.W., Hamilton, K., Naj, A.C., et al., Genome-wide association meta-analysis of neuropathologic features of Alzheimer’s disease and related dementias, PLoS Genet., 2014, vol. 10, no. 9. e1004606. doi 10.1371/journal.pgen.1004606

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Hatemi, P.K., Medland, S.E., Klemmensen, R., et al., Genetic influences on political ideologies: twin analyses of 19 measures of political ideologies from five democracies and genome-wide findings from three populations, Behav. Genet., 2014, vol. 44, no. 3, pp. 282–294. doi 10.1007/s10519-014-9648-8

    Article  PubMed  PubMed Central  Google Scholar 

  33. Rietveld, C.A., Medland, S.E., Derringer, J., et al., GWAS of 126559 individuals identifies genetic variants associated with educational attainment, Science, 2013, vol. 340, no. 6139, pp. 1467–1471. doi 10.1126/science. 1235488

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Ferreira, M.A., O’Donovan, M.C., Meng, Y.A., et al., Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder, Nat. Genet., 2008, vol. 40, no. 9, pp. 1056–1058. doi 10.1038/ng.209

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Mühleisen, T.W., Leber, M., Schulze, T.G., et al., Genome-wide association study reveals two new risk loci for bipolar disorder, Nat. Commun., 2014, vol. 5, p. 3339. doi 10.1038/ncomms4339

    Article  PubMed  CAS  Google Scholar 

  36. Seshadri, S., DeStefano, A.L., Au, R., et al., Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham Study, BMC Med. Genet., 2007, vol. 8, suppl. 1, p. S15. doi 10.1186/1471-2350-8-S1-S15

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Feulner, T.M., Laws, S.M., Friedrich, P., et al., Examination of the current top candidate genes for AD in a genome-wide association study, Mol. Psychiatry, 2010, vol. 15, no. 7, pp. 756–766. doi 10.1038/mp.2008.141

    Article  PubMed  CAS  Google Scholar 

  38. Davies, G., Harris, S.E., Reynolds, C.A., et al., A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing, Mol. Psychiatry, 2014, vol. 19, no. 1, pp. 76–87. doi 10.1038/mp.2012.159

    Article  PubMed  CAS  Google Scholar 

  39. Shen, L., Kim, S., Risacher, S.L., et al., Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: a study of the ADNI cohort, Neuroimage, 2010, vol. 53, no. 3, pp. 1051–1063. doi 10.1016/j.neuroimage. 2010.01.042

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Harold, D., Abraham, R., Hollingworth, P., et al., Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease, Nat. Genet., 2009, vol. 41, no. 10, pp. 1088–1093. doi 10.1038/ng.440

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Heinzen, E.L., Need, A.C., Hayden, K.M., et al., Genome-wide scan of copy number variation in lateonset Alzheimer’s disease, J. Alzheimers Dis., 2010, vol. 19, no. 1, pp. 69–77. doi 10.3233/JAD-2010-1212

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Naj, A.C., Beecham, G.W., Martin, E.R., et al., Dementia revealed: novel chromosome 6 locus for lateonset Alzheimer disease provides genetic evidence for folate-pathway abnormalities, PLoS Genet., 2010, vol. 6, no. 9. e1001130. doi 10.1371/journal.pgen.1001130

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Nelson, P.T., Estus, S., Abner, E.L., et al., ABCC9 gene polymorphism is associated with hippocampal sclerosis of aging pathology, Acta Neuropathol., 2014, vol. 127, no. 6, pp. 825–843. doi 10.1007/s00401-014-1282-2

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Pérez-Palma, E., Bustos, B.I., Villamán, C.F., et al., Overrepresentation of glutamate signaling in Alzheimer’s disease: network-based pathway enrichment using meta-analysis of genome-wide association studies, PLoS One, 2014, vol. 9, no. 4. e95413. doi 10.1371/journal.pone.0095413

    Article  PubMed  PubMed Central  Google Scholar 

  45. Chaste, P., Klei, L., Sanders, S.J., et al., A genomewide association study of autism using the Simons Simplex Collection: does reducing phenotypic heterogeneity in autism increase genetic homogeneity?, Biol. Psychiatry, 2015, vol. 77, no. 9, pp. 775–784. doi 10.1016/j.biopsych.2014.09.017

    Article  PubMed  Google Scholar 

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Correspondence to K. V. Vagaitseva.

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Original Russian Text © K.V. Vagaitseva, A.V. Bocharova, A.V. Marusin, E.A. Kolesnikova, O.A. Makeeva, V.A. Stepanov, 2018, published in Genetika, 2018, Vol. 54, No. 6, pp. 719–726.

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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 54, 740–745 (2018). https://doi.org/10.1134/S1022795418060121

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