Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

A missense variant in NDUFA6 confers schizophrenia risk by affecting YY1 binding and NAGA expression

Abstract

Genome-wide association studies (GWASs) have revealed that genetic variants at the 22q13.2 risk locus were robustly associated with schizophrenia. However, the causal variants at this risk locus and their roles in schizophrenia remain elusive. Here we identify the risk missense variant rs1801311 (located in the 1st exon of NDUFA6 gene) as likely causal for schizophrenia at 22q13.2 by disrupting binding of YY1, TAF1, and POLR2A. We systematically elucidated the regulatory mechanisms of rs1801311 and validated the regulatory effect of this missense variant. Intriguingly, rs1801311 physically interacted with NAGA (encodes the alpha-N-acetylgalactosaminidase, which is mainly involved in regulating metabolisms of glycoproteins and glycolipids in lysosome) and showed the most significant association with NAGA expression in the human brain, with the risk allele (G) associated with higher NAGA expression. Consistent with eQTL analysis, expression analysis showed that NAGA was significantly upregulated in brains of schizophrenia cases compared with controls, further supporting that rs1801311 may confer schizophrenia risk by regulating NAGA expression. Of note, we found that NAGA regulates important neurodevelopmental processes, including proliferation and differentiation of neural stem cells. Transcriptome analysis corroborated that NAGA regulates pathways associated with neuronal differentiation. Finally, we independently confirmed the association between rs1801311 and schizophrenia in a large Chinese cohort. Our study elucidates the regulatory mechanisms of the missense schizophrenia risk variant rs1801311 and provides mechanistic links between risk variant and schizophrenia etiology. In addition, this study also revealed the novel role of coding variants in gene regulation and schizophrenia risk, i.e., genetic variant in coding region of a specific gene may confer disease risk through regulating distal genes (act as regulatory variant for distal genes).

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

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Reporter gene assays and EMSA validated the regulatory effect of rs1801311.
Fig. 2: rs1801311 showed the most significant association with NAGA expression in human brain.
Fig. 3: YY1 regulates NAGA expression.
Fig. 4: Naga affects proliferation of NSCs.
Fig. 5: Naga affects differentiation of NSCs.
Fig. 6: Naga regulates schizophrenia-associated pathways.
Fig. 7: The working model of rs1801311 in schizophrenia pathogenesis.

Similar content being viewed by others

References

  1. Saha S, Chant D, Welham J, McGrath J. A systematic review of the prevalence of schizophrenia. PLoS Med. 2005;2:e141.

    PubMed  PubMed Central  Google Scholar 

  2. Sullivan PF, Daly MJ, O’Donovan M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet. 2012;13:537–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Schizophrenia Working Group of the Psychiatric Genomics C. Biological insights from 108 schizophrenia-associated genetic loci. Nature 2014;511:421–7.

    Google Scholar 

  4. Pardinas AF, Holmans P, Pocklington AJ, Escott-Price V, Ripke S, Carrera N, et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat Genet. 2018;50:381–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Li ZQ, Chen JH, Yu H, He L, Xu YF, Zhang D, et al. Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia. Nat Genet. 2017;49:1576–83.

    CAS  PubMed  Google Scholar 

  6. Lam M, Chen CY, Li ZQ, Martin AR, Bryois J, Ma X, et al. Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat Genet. 2019;51:1670–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Ding CD, Zhang CL, Kopp R, Kuney L, Meng QT, Wang L, et al. Transcription factor POU3F2 regulates TRIM8 expression contributing to cellular functions implicated in schizophrenia. Mol Psychiatry. 2020. https://doi.org/10.1038/s41380-020-00877-2

    Article  PubMed  PubMed Central  Google Scholar 

  8. Soldner F, Stelzer Y, Shivalila CS, Abraham BJ, Latourelle JC, Barrasa MI, et al. Parkinson-associated risk variant in distal enhancer of alpha-synuclein modulates target gene expression. Nature. 2016;533:95–99.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Montefiori LE, Sobreira DR, Sakabe NJ, Aneas I, Joslin AC, Hansen GT, et al. A promoter interaction map for cardiovascular disease genetics. Elife. 2018;7:e35788.

    PubMed  PubMed Central  Google Scholar 

  10. Birnbaum RY, Clowney EJ, Agamy O, Kim MJ, Zhao J, Yamanaka T, et al. Coding exons function as tissue-specific enhancers of nearby genes. Genome Res. 2012;22:1059–68.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Huo YX, Li SW, Liu JW, Li XY, Luo XJ. Functional genomics reveal gene regulatory mechanisms underlying schizophrenia risk. Nat Commun. 2019;10:670.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Luo XJ, Diao HB, Wang JK, Zhang H, Zhao ZM, Su B. Association of haplotypes spanning PDZ-GEF2, LOC728637 and ACSL6 with schizophrenia in Han Chinese. J Med Genet. 2008;45:818–26.

    CAS  PubMed  Google Scholar 

  13. Ma CG, Li YF, Li XY, Liu JW, Luo XJ. Identification of a functional SNP rs7304782 at schizophrenia risk locus 12q24.31 and validation of its association with schiz ophrenia in Chinese populations. Psychiatry Res. 2020;294:113491.

    CAS  PubMed  Google Scholar 

  14. Li KQ, Li YF, Wang JY, Huo YX, Huang D, Li SW, et al. A functional missense variant in ITIH3 affects protein expression and neurodevelopment and confers schizophrenia risk in the Han Chinese population. J Genet Genomics. 2020;47:233–48.

    PubMed  Google Scholar 

  15. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22:1790–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012;40:D930–934.

    CAS  PubMed  Google Scholar 

  18. Fromer M, Roussos P, Sieberts SK, Johnson JS, Kavanagh DH, Perumal TM, et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci. 2016;19:1442–53.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Jaffe AE, Straub RE, Shin JH, Tao R, Gao Y, Collado-Torres L, et al. Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis. Nat Neurosci. 2018;21:1117–25.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Yang CP, Li XY, Wu Y, Shen QS, Zeng Y, Xiong QX, et al. Comprehensive integrative analyses identify GLT8D1 and CSNK2B as schizophrenia risk genes. Nat Commun. 2018;9:838.

    PubMed  PubMed Central  Google Scholar 

  21. Li SW, Li XY, Liu JW, Huo YX, Li L, Wang JY, et al. Functional variants fine-mapping and gene function characterization provide insights into the role of ZNF323 in schizophrenia pathogenesis. Am J Med Genet B Neuropsychiatr Genet. 2021;186:28–39.

    CAS  PubMed  Google Scholar 

  22. Zhang Y, Li SW, Li XY, Yang YF, Li WQ, Xiao X, et al. Convergent lines of evidence support NOTCH4 as a schizophrenia risk gene. J Med Genet. 2020. https://doi.org/10.1136/jmedgenet-2020-106830

    Article  PubMed  Google Scholar 

  23. Davies G, Marioni RE, Liewald DC, Hill WD, Hagenaars SP, Harris SE, et al. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151). Mol Psychiatry. 2016;21:758–67.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, et al. The genetic architecture of the human cerebral cortex. Science. 2020;367:eaay6690.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Kang HJ, Kawasawa YI, Cheng F, Zhu Y, Xu X, Li M, et al. Spatio-temporal transcriptome of the human brain. Nature. 2011;478:483–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Ma CG, Gu CJ, Huo YX, Li XY, Luo XJ. The integrated landscape of causal genes and pathways in schizophrenia. Transl Psychiatry. 2018;8:67.

    PubMed  PubMed Central  Google Scholar 

  28. Zhong JM, Li SW, Zeng WL, Li XY, Gu CJ, Liu JW, et al. Integration of GWAS and brain eQTL identifies FLOT1 as a risk gene for major depressive disorder. Neuropsychopharmacology. 2019;44:1542–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. GTEx Consortium. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45:580–5.

    Google Scholar 

  30. Võsa U, Claringbould A, Westra H-J, Bonder MJ, Deelen P, Zeng B, et al. Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis. Preprint at https://doi.org/10.1101/447367 (2018).

  31. Gandal MJ, Zhang P, Hadjimichael E, Walker RL, Chen C, Liu S, et al. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 2018;362:eaat8127.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx BW, et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016;48:245–52.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Yang D, Jang I, Choi J, Kim MS, Lee AJ, Kim H, et al. 3DIV: A 3D-genome Interaction Viewer and database. Nucleic Acids Res. 2018;46:D52–D57.

    CAS  PubMed  Google Scholar 

  34. Weinberger DR. Implications of normal brain development for the pathogenesis of schizophrenia. Arch Gen Psychiatry. 1987;44:660–9.

    CAS  PubMed  Google Scholar 

  35. Mao Y, Ge X, Frank CL, Madison JM, Koehler AN, Doud MK, et al. Disrupted in schizophrenia 1 regulates neuronal progenitor proliferation via modulation of GSK3beta/beta-catenin signaling. Cell. 2009;136:1017–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Duan X, Chang JH, Ge S, Faulkner RL, Kim JY, Kitabatake Y, et al. Disrupted-In-Schizophrenia 1 regulates integration of newly generated neurons in the adult brain. Cell. 2007;130:1146–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Tomita K, Kubo K, Ishii K, Nakajima K. Disrupted-in-Schizophrenia-1 (Disc1) is necessary for migration of the pyramidal neurons during mouse hippocampal development. Hum Mol Genet. 2011;20:2834–45.

    CAS  PubMed  Google Scholar 

  38. Ishizuka K, Kamiya A, Oh EC, Kanki H, Seshadri S, Robinson JF, et al. DISC1-dependent switch from progenitor proliferation to migration in the developing cortex. Nature. 2011;473:92–96.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Kirov G, Rujescu D, Ingason A, Collier DA, O’Donovan MC, Owen MJ. Neurexin 1 (NRXN1) deletions in schizophrenia. Schizophr Bull. 2009;35:851–4.

    PubMed  PubMed Central  Google Scholar 

  40. Fromer M, Pocklington AJ, Kavanagh DH, Williams HJ, Dwyer S, Gormley P, et al. De novo mutations in schizophrenia implicate synaptic networks. Nature. 2014;506:179–84.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Maschietto M, Tahira AC, Puga R, Lima L, Mariani D, Paulsen Bda S, et al. Co-expression network of neural-differentiation genes shows specific pattern in schizophrenia. BMC Med Genomics. 2015;8:23.

    PubMed  PubMed Central  Google Scholar 

  42. Cheng YC, Scotting PJ, Hsu LS, Lin SJ, Shih HY, Hsieh FY, et al. Zebrafish rgs4 is essential for motility and axonogenesis mediated by Akt signaling. Cell Mol Life Sci. 2013;70:935–50.

    CAS  PubMed  Google Scholar 

  43. Liu JW, Li M, Luo XJ, Su B. Systems-level analysis of risk genes reveals the modular nature of schizophrenia. Schizophr Res. 2018;201:261–9.

    PubMed  Google Scholar 

  44. Bowie CR, Harvey PD. Cognitive deficits and functional outcome in schizophrenia. Neuropsychiatr Dis Treat. 2006;2:531–6.

    PubMed  PubMed Central  Google Scholar 

  45. Kuperberg G, Heckers S. Schizophrenia and cognitive function. Curr Opin Neurobiol. 2000;10:205–10.

    CAS  PubMed  Google Scholar 

  46. Tollefson GD. Cognitive function in schizophrenic patients. J Clin Psychiatry. 1996;57:31–39.

    PubMed  Google Scholar 

  47. Owen MJ, Sawa A, Mortensen PB. Schizophrenia. Lancet. 2016;388:86–97.

    PubMed  PubMed Central  Google Scholar 

  48. Wang AM, Schindler D, Desnick R. Schindler disease: the molecular lesion in the alpha-N-acetylgalactosaminidase gene that causes an infantile neuroaxonal dystrophy. J Clin Invest. 1990;86:1752–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Saburi E, Tavakolafshari J, Mortazavi Y, Biglari A, Mirzaei SA, Nadri S. shRNA-mediated downregulation of alpha-N-Acetylgalactosaminidase inhibits migration and invasion of cancer cell lines. Iran J Basic Med Sci. 2017;20:1021–8.

    PubMed  PubMed Central  Google Scholar 

  50. Mueller TM, Yates SD, Haroutunian V, Meador-Woodruff JH. Altered fucosyltransferase expression in the superior temporal gyrus of elderly patients with schizophrenia. Schizophr Res. 2016;182:66–73.

    PubMed  PubMed Central  Google Scholar 

  51. Kippe JM, Mueller TM, Haroutunian V, Meador-Woodruff JH. Abnormal N-acetylglucosaminyltransferase expression in prefrontal cortex in schizophrenia. Schizophr Res. 2015;166:219–24.

    PubMed  PubMed Central  Google Scholar 

  52. Mueller TM, Haroutunian V, Meador-Woodruff JH. N-Glycosylation of GABAA receptor subunits is altered in Schizophrenia. Neuropsychopharmacology. 2014;39:528–37.

    CAS  PubMed  Google Scholar 

  53. Tucholski J, Simmons MS, Pinner AL, Haroutunian V, McCullumsmith RE, Meador-Woodruff JH. Abnormal N-linked glycosylation of cortical AMPA receptor subunits in schizophrenia. Schizophr Res. 2013;146:177–83.

    PubMed  PubMed Central  Google Scholar 

  54. Williams SE, Mealer RG, Scolnick EM, Smoller JW, Cummings RD. Aberrant glycosylation in schizophrenia: a review of 25 years of post-mortem brain studies. Mol Psychiatry. 2020;25:3198–207.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Mealer RG, Williams SE, Daly MJ, Scolnick EM, Cummings RD, Smoller JW. Glycobiology and schizophrenia: a biological hypothesis emerging from genomic research. Mol Psychiatry. 2020;25:3129–39.

    PubMed  PubMed Central  Google Scholar 

  56. Mueller TM, Meador-Woodruff JH. Post-translational protein modifications in schizophrenia. NPJ Schizophr. 2020;6:5.

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Licinio J, Wong ML. Advances in schizophrenia research: glycobiology, white matter abnormalities, and their interactions. Mol Psychiatry. 2020;25:3116–8.

    PubMed  PubMed Central  Google Scholar 

  58. Mealer RG, Jenkins BG, Chen CY, Daly MJ, Ge T, Lehoux S, et al. The schizophrenia risk locus in SLC39A8 alters brain metal transport and plasma glycosylation. Sci Rep. 2020;10:13162.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat Genet. 2019;51:63–75.

    CAS  PubMed  Google Scholar 

  60. Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50:668–81.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51:793–803.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study was equally supported by the Distinguished Young Scientists grant of the Yunnan Province (202001AV070006) and Innovative Research Team of Science and Technology department of Yunnan Province (2019HC004) to XJL. Also was supported by the National Nature Science Foundation of China (31970561 to XJL, U1904130 to WQL). One of the brain eQTL datasets used in this study were generated as part of the Common Mind Consortium supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffman-La Roche Ltd, and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, and R37MH057881S1, HHSN271201300031C, AG02219, AG05138, and MH06692. Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer’s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, and the NIMH Human Brain Collection Core. CMC Leadership: Pamela Sklar, Joseph Buxbaum (Icahn School of Medicine at Mount Sinai), Bernie Devlin, David Lewis (University of Pittsburgh), Raquel Gur, Chang-Gyu Hahn (University of Pennsylvania), Keisuke Hirai, HiroyoshiToyoshiba (Takeda Pharmaceuticals Company Limited), Enrico Domenici, Laurent Essioux (F. Hoffman-La Roche Ltd), Lara Mangravite, Mette Peters (Sage Bionetworks), Thomas Lehner, Barbara Lipska (NIMH). The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. We thank Miss. Qian Li for her technical assistance.

Author information

Authors and Affiliations

Authors

Contributions

XJL conceived, designed, and supervised the study. YFL, CGM, JYW, KQL, JL, DH, RC, SWL, and YXL extracted the DNA. YFL performed genotyping assays, reporter gene assays, ChIP-qPCR, knockdown assay, and genome editing. XYL and JWL performed the data analysis. JYW conducted EMSA. YFL and CGM performed proliferation and differentiation of mNSCs assays. YFL wrote the first draft of the manuscript. ML provided critical comments on study design, data interpretation, and manuscript writing. XJL oversaw the project and finalized the manuscript. All authors revised the manuscript critically and approved the final version.

Corresponding author

Correspondence to Xiong-Jian Luo.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Y., Ma, C., Li, W. et al. A missense variant in NDUFA6 confers schizophrenia risk by affecting YY1 binding and NAGA expression. Mol Psychiatry 26, 6896–6911 (2021). https://doi.org/10.1038/s41380-021-01125-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-021-01125-x

This article is cited by

Search

Quick links