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Comparison of Polygenic Risk for Schizophrenia between European and Korean Populations

유럽인 자료로 산출된 조현병 다유전자 위험도 점수의 한국인 조현병 환자를 대상으로 한 적용

  • Lee, Jinyoung (Department of Psychiatry, Sungkyunkwan University School of Medicine, Samsung Medical Center) ;
  • Lee, Dongbin (Department of Psychiatry, Sungkyunkwan University School of Medicine, Samsung Medical Center) ;
  • Cho, Eun Young (Samsung Biomedical Research Institute, Center for Clinical Medicine) ;
  • Baek, Ji Hyun (Department of Psychiatry, Sungkyunkwan University School of Medicine, Samsung Medical Center) ;
  • Hong, Kyung Sue (Department of Psychiatry, Sungkyunkwan University School of Medicine, Samsung Medical Center)
  • 이진영 (성균관대학교 의과대학 삼성서울병원 정신건강의학교실) ;
  • 이동빈 (성균관대학교 의과대학 삼성서울병원 정신건강의학교실) ;
  • 조은영 (삼성생명과학연구소 임상의학연구센터) ;
  • 백지현 (성균관대학교 의과대학 삼성서울병원 정신건강의학교실) ;
  • 홍경수 (성균관대학교 의과대학 삼성서울병원 정신건강의학교실)
  • Received : 2020.07.13
  • Accepted : 2020.09.15
  • Published : 2020.10.30

Abstract

Objectives: This study aimed to explore whether common genetic variants that confer the risk of schizophrenia have similar effects between Korean and European ancestries using the polygenic risk score (PRS) analysis. Methods: Study subjects included 713 Korean patients with schizophrenia and 497 healthy controls. The Korea Biobank array was used for genotyping. Summary statistics of the most recent genome-wide association study (GWAS) of the European population were used as baseline data to calculate PRS. Logistic regression was conducted to determine the association between calculated PRS of European patients with schizophrenia and clinical diagnosis of schizophrenia in the Korean population. Results: Schizophrenia PRS was significantly higher in patients with schizophrenia than in healthy controls. The PRS at the p-value threshold of 0.5 best explained the variance of schizophrenia (R2=0.028, p=4.4×10-6). The association was significant after adjusting for age and sex (odds ratio=1.34, 95% confidence interval=1.19-1.51, p=1.1×10-6). The pattern of the association remained similar across different p-value thresholds (0.01-1). Conclusion: Schizophrenia PRS calculated using the European GWAS data showed a significant association with the clinical diagnosis of schizophrenia in the Korean population. Results suggest overlapping genetic risk variants between the two populations.

Keywords

Acknowledgement

이 연구는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행되었음(No. 2019R1A2C1005346).

References

  1. Stilo SA, Murray RM. The epidemiology of schizophrenia: replacing dogma with knowledge. Dialogues Clin Neurosci 2010;12:305-315. https://doi.org/10.31887/DCNS.2010.12.3/sstilo
  2. Flint J, Munafo M. Schizophrenia: genesis of a complex disease. Nature 2014;511:412-413. https://doi.org/10.1038/nature13645
  3. Cardno AG, Gottesman II. Twin studies of schizophrenia: from bow-and-arrow concordances to star wars Mx and functional genomics. Am J Med Genet 2000;97:12-17. https://doi.org/10.1002/(SICI)1096-8628(200021)97:1<12::AID-AJMG3>3.0.CO;2-U
  4. Sullivan PF, Kendler KS, Neale MC. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry 2003;60:1187-1192. https://doi.org/10.1001/archpsyc.60.12.1187
  5. Burmeister M, McInnis MG, Zollner S. Psychiatric genetics: progress amid controversy. Nat Rev Genet 2008;9:527-540. https://doi.org/10.1038/nrg2381
  6. van Os J, Kapur S. Schizophrenia. Lancet 2009;374:635-645. https://doi.org/10.1016/S0140-6736(09)60995-8
  7. Allen NC, Bagade S, McQueen MB, Ioannidis JP, Kavvoura FK, Khoury MJ, et al. Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nat Genet 2008;40:827. https://doi.org/10.1038/ng.171
  8. Collins AL, Kim Y, Sklar P, O'Donovan MC, Sullivan PF, Consortium IS. Hypothesis-driven candidate genes for schizophrenia compared to genome-wide association results. Psychol Med 2012;42:607. https://doi.org/10.1017/S0033291711001607
  9. Purcell SM, Wray NR, Stone JL, Visscher PM, O'Donovan MC, Sullivan PF, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009;460:748-752. https://doi.org/10.1038/nature08185
  10. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 2014;511:421-427. https://doi.org/10.1038/nature13595
  11. Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB. Rare variants create synthetic genome-wide associations. PLoS Biol 2010;8:e1000294. https://doi.org/10.1371/journal.pbio.1000294
  12. 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;49:1576-1583. https://doi.org/10.1038/ng.3973
  13. Yue WH, Wang HF, Sun LD, Tang FL, Liu ZH, Zhang HX, et al. Genome-wide association study identifies a susceptibility locus for schizophrenia in Han Chinese at 11p11. 2. Nat Genet 2011;43:1228-1231. https://doi.org/10.1038/ng.979
  14. Martin AR, Gignoux CR, Walters RK, Wojcik GL, Neale BM, Gravel S, et al. Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations. Am J Hum Genet 2017;100:635-649. https://doi.org/10.1016/j.ajhg.2017.03.004
  15. Wray NR, Goddard ME, Visscher PM. Prediction of individual genetic risk to disease from genome-wide association studies. Genome Res 2007;17:1520-1528. https://doi.org/10.1101/gr.6665407
  16. Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, et al. 10 years of GWAS discovery: biology, function, and translation. Am J Hum Genet 2017;101:5-22. https://doi.org/10.1016/j.ajhg.2017.06.005
  17. Rammos A, Gonzalez LAN, Weinberger DR, Mitchell KJ, Nicodemus KK. The role of polygenic risk score gene-set analysis in the context of the omnigenic model of schizophrenia. Neuropsychopharmacology 2019;44:1562-1569. https://doi.org/10.1038/s41386-019-0410-z
  18. Morales J, Welter D, Bowler EH, Cerezo M, Harris LW, McMahon AC, et al. A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog. Genome Biol 2018;19:21. https://doi.org/10.1186/s13059-018-1396-2
  19. Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature 2016;538:161-164. https://doi.org/10.1038/538161a
  20. Ikeda M, Takahashi A, Kamatani Y, Momozawa Y, Saito T, Kondo K, et al. Genome-wide association study detected novel susceptibility genes for schizophrenia and shared trans-populations/diseases genetic effect. Schizophr Bull 2019;45:824-834. https://doi.org/10.1093/schbul/sby140
  21. Martin AR, Kanai M, Kamatani Y, Okada Y, Neale BM, Daly MJ. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat Genet 2019;51:584-591. https://doi.org/10.1038/s41588-019-0379-x
  22. Lam M, Chen CY, Li Z, Martin AR, Bryois J, Ma X, et al. Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat Genet 2019;51:1670-1678. https://doi.org/10.1038/s41588-019-0512-x
  23. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, fourth edition, text revision (DSM-IV-TR). Washington, DC: American Psychiatric Association;2000.
  24. Moon S, Kim YJ, Han S, Hwang MY, Shin DM, Park MY, et al. The Korea Biobank Array: design and identification of coding variants associated with blood biochemical traits. Sci Rep 2019;9:1382. https://doi.org/10.1038/s41598-018-37832-9
  25. Choi SW, O'Reilly PF. PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience 2019;8:giz082. https://doi.org/10.1093/gigascience/giz082
  26. Duncan L, Shen H, Gelaye B, Meijsen J, Ressler K, Feldman M, et al. Analysis of polygenic risk score usage and performance in diverse human populations. Nat Commun 2019;10:3328. https://doi.org/10.1038/s41467-019-11112-0
  27. Marnetto D, Parna K, Lall K, Molinaro L, Montinaro F, Haller T, et al. Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals. Nat Commun 2020;11:1-9. https://doi.org/10.1038/s41467-019-13993-7
  28. Talarico F, Santoro M, Ota VK, Gadelha A, Pellegrino R, Hakonarson H, et al. Implications of an admixed Brazilian population in schizophrenia polygenic risk score. Schizophr Res 2019;204:404. https://doi.org/10.1016/j.schres.2018.07.026
  29. Wimberley T, Gasse C, Meier SM, Agerbo E, MacCabe JH, Horsdal HT. Polygenic risk score for schizophrenia and treatment-resistant schizophrenia. Schizophr Bull 2017;43:1064-1069. https://doi.org/10.1093/schbul/sbx007
  30. Zhang JP, Robinson D, Yu J, Gallego J, Fleischhacker WW, Kahn RS, et al. Schizophrenia polygenic risk score as a predictor of anti-psychotic efficacy in first-episode psychosis. Am J Psychiatry 2019;176:21-28. https://doi.org/10.1176/appi.ajp.2018.17121363
  31. Jonas KG, Lencz T, Li K, Malhotra AK, Perlman G, Fochtmann LJ, et al. Schizophrenia polygenic risk score and 20-year course of illness in psychotic disorders. Transl Psychiatry 2019;9:300. https://doi.org/10.1038/s41398-019-0612-5
  32. Musliner KL, Krebs MD, Albinana C, Vilhjalmsson B, Agerbo E, Zandi PP, et al. Polygenic risk and progression to bipolar or psychotic disorders among individuals diagnosed with unipolar depression in early life. Am J Psychiatry 2020:appiajp202019111195.
  33. Perkins DO, Olde Loohuis L, Barbee J, Ford J, Jeffries CD, Addington J, et al. Polygenic risk score contribution to psychosis prediction in a target population of persons at clinical high risk. Am J Psychiatry 2020;177:155-163. https://doi.org/10.1176/appi.ajp.2019.18060721
  34. Curtis D. Polygenic risk score for schizophrenia is more strongly associated with ancestry than with schizophrenia. Psychiatr Genet 2018;28:85-89. https://doi.org/10.1097/YPG.0000000000000206
  35. Fabbri C, Serretti A. Role of 108 schizophrenia-associated loci in modulating psychopathological dimensions in schizophrenia and bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2017;174:757-764. https://doi.org/10.1002/ajmg.b.32577
  36. Mistry S, Harrison JR, Smith DJ, Escott-Price V, Zammit S. The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: a systematic review. J Affect Disord 2018;234:148-155. https://doi.org/10.1016/j.jad.2018.02.005
  37. Vassos E, Di Forti M, Coleman J, Iyegbe C, Prata D, Euesden J, et al. An examination of polygenic score risk prediction in individuals with first-episode psychosis. Biol Psychiatry 2017;81:470-477. https://doi.org/10.1016/j.biopsych.2016.06.028
  38. Gasse C, Wimberley T, Wang Y, Mors O, Borglum A, Als TD, et al. Schizophrenia polygenic risk scores, urbanicity and treatmentresistant schizophrenia. Schizophr Res 2019;212:79-85. https://doi.org/10.1016/j.schres.2019.08.008
  39. Toulopoulou T, Zhang X, Cherny S, Dickinson D, Berman KF, Straub RE, et al. Polygenic risk score increases schizophrenia liability through cognition-relevant pathways. Brain 2019;142:471-485. https://doi.org/10.1093/brain/awy279
  40. Zhang JP, Robinson D, Yu J, Gallego J, Fleischhacker WW, Kahn RS, et al. Schizophrenia polygenic risk score as a predictor of anti-psychotic efficacy in first-episode psychosis. Am J Psychiatry 2019;176:21-28. https://doi.org/10.1176/appi.ajp.2018.17121363