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A genome-wide association study reveals a substantial genetic basis underlying the Ebbinghaus illusion

Journal of Human Genetics volume 66, pages 261–271 (2021)Cite this article

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Abstract

The Ebbinghaus illusion (EI) is an optical illusion of relative size perception that reflects the contextual integration ability in the visual modality. The current study investigated the genetic basis of two subtypes of EI, EI overestimation, and EI underestimation in humans, using quantitative genomic analyses. A total of 2825 Chinese adults were tested on their magnitudes of EI overestimation and underestimation using the method of adjustment, a standard psychophysical protocol. Heritability estimation based on common single nucleotide polymorphisms (SNPs) revealed a moderate heritability (34.3%) of EI overestimation but a nonsignificant heritability of EI underestimation. A meta-analysis of two phases (phase 1: n = 1986, phase 2: n = 839) of genome-wide association study (GWAS) discovered 1969 and 58 SNPs reaching genome-wide significance for EI overestimation and EI underestimation, respectively. Among these SNPs, 55 linkage-disequilibrium-independent SNPs were associated with EI overestimation in phase 1 with genome-wide significance and their associations could be confirmed in phase 2 cohort. Gene-based analyses found seven genes to be associated with EI overestimation at the genome-wide level, two from meta-analysis, and five from classical two-stage analysis. Overall, this study provided consistent evidence for a substantial genetic basis of the Ebbinghaus illusion.

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References

  1. Boelte S, Holtmann M, Poustka F, Scheurich A, Schmidt L. Gestalt perception and local-global processing in high-functioning autism. J Autism Dev Disord. 2007;37:1493–504.

    Article  Google Scholar 

  2. Dakin S, Frith U. Vagaries of visual perception in autism. Neuron. 2005;48:497–507.

    Article  CAS  PubMed  Google Scholar 

  3. Manning C, Morgan MJ, Allen CTW, Pellicano E. Susceptibility to Ebbinghaus and Muller-Lyer illusions in autistic children: a comparison of three different methods. Mol Autism. 2017;8:16.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Uhlhaas PJ, Phillips WA, Mitchell G, Silverstein SM. Perceptual grouping in disorganized schizophrenia. Psychiatry Res. 2006;145:105–17.

    Article  PubMed  Google Scholar 

  5. Bressan P, Kramer P. The relation between cognitive-perceptual schizotypal traits and the Ebbinghaus size-illusion is mediated by judgment time. Front Psychol. 2013;4:343.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Doherty MJ, Campbell NM, Tsuji H, Phillips WA. The Ebbinghaus illusion deceives adults but not young children. Dev Sci. 2010;13:714–21.

    Article  PubMed  Google Scholar 

  7. Bremner AJ, Doherty MJ, Caparos S, de Fockert J, Linnell KJ, Davidoff J. Effects of culture and the urban environment on the development of the Ebbinghaus Illusion. Child Dev. 2016;87:962–81.

    Article  PubMed  Google Scholar 

  8. Yamazaki Y, Otsuka Y, Kanazawa S, Yamaguchi MK. Perception of the Ebbinghaus illusion in 5-to 8-month-old infants. Jpn Psychol Res. 2010;52:33–40.

    Article  Google Scholar 

  9. Coren S, Porac C. Heritability in visual-geometric illusions: a family study. Perception. 1979;8:303–9.

    Article  CAS  PubMed  Google Scholar 

  10. Schwarzkopf DS, Song C, Rees G. The surface area of human V1 predicts the subjective experience of object size. Nat Neurosci. 2011;14:28–30.

    Article  CAS  PubMed  Google Scholar 

  11. Chen CH, Peng Q, Schork AJ, Lo MT, Fan CC, Wang Y, et al. Large-scale genomics unveil polygenic architecture of human cortical surface area. Nat Commun. 2015;6:7.

    Google Scholar 

  12. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88:76–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Chen B, Zhu Z, Na R, Fang W, Zhang W, Zhou Q, et al. Genomic analyses of visual cognition: perceptual rivalry and top-down control. J Neurosci. 2018;38:9668–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Zhu Z, Chen B, Na R, Fang W, Zhang W, Zhou Q, et al. Heritability of human visual contour integration-an integrated genomic study. Eur J Hum Genet. 2019;27:1867–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.

    Article  CAS  PubMed  Google Scholar 

  17. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42:565–U131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Visscher PM, Hemani G, Vinkhuyzen AAE, Chen G-B, Lee SH, Wray NR, et al. Statistical power to detect genetic (Co)variance of complex traits using snp data in unrelated samples. Plos Genet. 2014;10:e1004269.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Delaneau O, Marchini J, Zagury J-F. A linear complexity phasing method for thousands of genomes. Nat Methods. 2012;9:179–81.

    Article  CAS  Google Scholar 

  20. Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44:955.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. Plos Genet. 2009;5:e1000529.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet. 2007;39:906–13.

    Article  CAS  PubMed  Google Scholar 

  23. Gauderman WJ, Morrison JM, Morrison W. QUANTO 1.1: a computer program for power and sample size calculations for genetic-epidemiology studies. 2006. https://hydrauscedu/gxe

  24. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26:2190–1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. Plos Comput Biol. 2015;11:e1004219.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Ripke S, Neale BM, Corvin A, Walters JTR, Farh K-H, Holmans PA, et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421.

    Article  CAS  PubMed Central  Google Scholar 

  27. King DJ, Hodgekins J, Chouinard PA, Chouinard V-A, Sperandio I. A review of abnormalities in the perception of visual illusions in schizophrenia. Psychonomic Bull Rev. 2017;24:734–51.

    Article  Google Scholar 

  28. Uhlhaas PJ, Silverstein SM, Phillips WA, Lovell PG. Evidence for impaired visual context processing in schizotypy with thought disorder. Schizophrenia Res. 2004;68:249–60.

    Article  Google Scholar 

  29. Lam M, Chen C-Y, Li Z, Martin AR, Bryois J, Ma X, et al. Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat Genet. 2019;51:1670.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Li Z, Chen J, Yu H, He L, Xu Y, Zhang D, et al. Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia. Nat Genet. 2017;49:1576.

    Article  CAS  PubMed  Google Scholar 

  31. Yu HG, Yan HK, Li JM, Li ZP, Zhang XD, Ma YC, et al. Common variants on 2p16.1, 6p22.1 and 10q24.32 are associated with schizophrenia in Han Chinese population. Mol Psychiatr. 2017;22:954–60.

    Article  CAS  Google Scholar 

  32. Needleman LA, McAllister AK. The major histocompatibility complex and autism spectrum disorder. Dev Neurobiol. 2012;72:1288–301.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Huh GS, Boulanger LM, Du H, Riquelme PA, Brotz TM, Shatz CJ. Functional requirement for class I MHC in CNS development and plasticity. Sci (N. Y, NY). 2000;290:2155–9.

    Article  CAS  Google Scholar 

  34. Higenell V, Ruthazer ES. Layers upon Layers: MHC Class I acts in the retina to influence thalamic segregation. Neuron. 2010;65:439–41.

    Article  CAS  PubMed  Google Scholar 

  35. Lee H, Brott BK, Kirkby LA, Adelson JD, Cheng S, Feller MB, et al. Synapse elimination and learning rules co-regulated by MHC class I H2-D-b. Nature. 2014;509:195.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Braskie MN, Jahanshad N, Stein JL, Barysheva M, Johnson K, McMahon KL, et al. Relationship of a variant in the NTRK1 gene to white matter microstructure in young adults. J Neurosci. 2012;32:5964–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Sawal HA, Ullah MI, Ahmad A, Nasir A, Amar A, Khan EA, et al. Homozygous mutations in NTRK1 gene underlie congenital insensitivity to pain with anhidrosis in Pakistani families. Neurology. Asia. 2016;21:129–36.

    Google Scholar 

  38. Liu Z, Liu J, Liu G, Cao W, Liu S, Chen Y, et al. Phenotypic heterogeneity of intellectual disability in patients with congenital insensitivity to pain with anhidrosis: a case report and literature review. J Int Med Res. 2018;46:2445–57.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Swaminathan S, Kim S, Shen L, Risacher SL, Foroud T, Pankratz N, et al. Genomic copy number analysis in alzheimer’s disease and mild cognitive impairment: an ADNI study. Int J Alzheimer’s Dis. 2011;2011:729478.

    Google Scholar 

  40. Uys GM, Ramburan A, Loos B, Kinnear CJ, Korkie LJ, Mouton J, et al. Myomegalin is a novel A-kinase anchoring protein involved in the phosphorylation of cardiac myosin binding protein C. Bmc Cell Biol. 2011;12:18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Brunetti-Pierri N, Berg JS, Scaglia F, Belmont J, Bacino CA, Sahoo T, et al. Recurrent reciprocal 1q21.1 deletions and duplications associated with microcephaly or macrocephaly and developmental and behavioral abnormalities. Nat Genet. 2008;40:1466–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. McLellan AS, Fischer B, Dveksler G, Hori T, Wynne F, Ball M, et al. Structure and evolution of the mouse pregnancy-specific glycoprotein (Psg) gene locus. BMC Genom. 2005;6:4.

    Article  CAS  Google Scholar 

  43. Shannon RW, Patrick CJ, Jiang Y, Bernat E, He S. Genes contribute to the switching dynamics of bistable perception. J Vis. 2011;11:8, 1-7.

    Article  PubMed  Google Scholar 

  44. Wang Y, Wang L, Xu Q, Liu D, Chen LH, Troje NF, et al. Heritable aspects of biological motion perception and its covariation with autistic traits. Proc Natl Acad Sci USA. 2018;115:1937–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Shakeshaft NG, Plomin R. Genetic specificity of face recognition. Proc Natl Acad Sci USA. 2015;112:12887–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wilmer JB, Germine L, Chabris CF, Chatterjee G, Williams M, Loken E, et al. Human face recognition ability is specific and highly heritable. Proc Natl Acad Sci USA. 2010;107:5238–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Haak KV. Genetic influence on contrast sensitivity in young adults. Acta Ophthalmologica 2019;97:E663–4.

    Article  PubMed  Google Scholar 

  48. Coleman JRI, Lester KJ, Keers R, Munafo MR, Breen G, Eley TC. Genome-wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders. Am J Med Genet Part B-Neuropsychiatr Genet. 2017;174:701–11.

    Article  CAS  Google Scholar 

  49. Warrier V, Grasby KL, Uzefovsky F, Toro R, Smith P, Chakrabarti B, et al. Genome-wide meta-analysis of cognitive empathy: heritability, and correlates with sex, neuropsychiatric conditions and cognition. Mol Psychiatr. 2018;23:1402–9.

    Article  CAS  Google Scholar 

  50. Bosten JM, Goodbourn PT, Lawrance-Owen AJ, Bargary G, Hogg RE, Mollon JD. A population study of binocular function. Vis Res. 2015;110:34–50.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Projects 31930053, 31421003 and 31671168). We are grateful to Zhangyan Guan and Huizhen Yang for help with DNA preparation.

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  1. These authors contributed equally: Zijian Zhu, Biqing Chen, Ren Na

Authors and Affiliations

  1. School of Psychology, Shaanxi Normal University, 710062, Xi’an, China

    Zijian Zhu

  2. PKU-IDG/McGovern Institute for Brain Research, and Peking-Tsinghua Center for Life Sciences, Peking University, 100871, Beijing, China

    Biqing Chen, Ren Na, Wan Fang, Wenxia Zhang, Yi Rao & Fang Fang

  3. Central Laboratory, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, 210029, Nanjing, China

    Biqing Chen

  4. Beijing Innovative Center for Genomics, Peking University School of Life Sciences, and National Institute of Biological Sciences, 102206, Beijing, China

    Wan Fang & Yi Rao

  5. College of Laboratory Medicine, Chongqing Medical University, 400016, Chongqing, China

    Qin Zhou, Han Lei, Ailong Huang & Tingmei Chen

  6. University-Town Hospital of Chongqing Medical University, 401331, Chongqing, China

    Shanbi Zhou

  7. Division of Molecular Nephrology and Creative Training Center for Undergraduates, M.O.E. Key Laboratory of Medical Diagnostics, College of Laboratory Medicine, Chongqing Medical University, 400016, Chongqing, China

    Dongsheng Ni, Yuping Gu & Jianing Liu

  8. School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, 100871, Beijing, China

    Fang Fang

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Zhu, Z., Chen, B., Na, R. et al. A genome-wide association study reveals a substantial genetic basis underlying the Ebbinghaus illusion. J Hum Genet 66, 261–271 (2021). https://doi.org/10.1038/s10038-020-00827-4

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