An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.

Liuyang Wang, Thomas J Balmat, Alejandro L Antonia, Florica J Constantine, Ricardo Henao, Thomas W Burke, Andy Ingham, Micah T McClain, Ephraim L Tsalik, Emily R Ko, Geoffrey S Ginsburg, Mark R DeLong, Xiling Shen, Christopher W Woods, Elizabeth R Hauser, Dennis C Ko
Author Information
  1. Liuyang Wang: Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA.
  2. Thomas J Balmat: Duke Research Computing, Duke University, Durham, NC, 27710, USA.
  3. Alejandro L Antonia: Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA.
  4. Florica J Constantine: Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA.
  5. Ricardo Henao: Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA.
  6. Thomas W Burke: Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA.
  7. Andy Ingham: Duke Research Computing, Duke University, Durham, NC, 27710, USA.
  8. Micah T McClain: Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA.
  9. Ephraim L Tsalik: Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA.
  10. Emily R Ko: Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA.
  11. Geoffrey S Ginsburg: Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA.
  12. Mark R DeLong: Duke Research Computing, Duke University, Durham, NC, 27710, USA.
  13. Xiling Shen: Department of Biomedical Engineering, Woo Center for Big Data and Precision Health, Duke University, Durham, NC, 27710, USA.
  14. Christopher W Woods: Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA.
  15. Elizabeth R Hauser: Duke Molecular Physiology Institute and Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, 27710, USA.
  16. Dennis C Ko: Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA. dennis.ko@duke.edu. ORCID

Abstract

BACKGROUND: While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.
RESULTS: Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.
CONCLUSIONS: Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

Keywords

References

  1. Lancet Respir Med. 2020 Aug;8(8):807-815 [PMID: 32422178]
  2. Nat Commun. 2015 May 13;6:7041 [PMID: 25967671]
  3. Am J Hum Genet. 2017 Jan 5;100(1):40-50 [PMID: 27989323]
  4. Cell Chem Biol. 2018 Mar 15;25(3):262-267.e5 [PMID: 29396289]
  5. Pulm Med. 2020 Aug 10;2020:6175964 [PMID: 32850151]
  6. Nat Genet. 2018 Nov;50(11):1593-1599 [PMID: 30349118]
  7. PLoS Genet. 2013 May;9(5):e1003509 [PMID: 23717212]
  8. Am J Hum Genet. 2017 Jul 6;101(1):5-22 [PMID: 28686856]
  9. Cell Host Microbe. 2018 Aug 8;24(2):308-323.e6 [PMID: 30092202]
  10. N Engl J Med. 2020 Oct 15;383(16):1522-1534 [PMID: 32558485]
  11. Nature. 2012 Sep 20;489(7416):443-6 [PMID: 22895189]
  12. Bioinformatics. 2018 May 1;34(9):1600-1602 [PMID: 29069305]
  13. PLoS Genet. 2015 Sep 09;11(9):e1005487 [PMID: 26352407]
  14. Clin Infect Dis. 2021 Jul 15;73(2):328-331 [PMID: 32750119]
  15. PLoS One. 2018 Mar 1;13(3):e0193256 [PMID: 29494641]
  16. Hum Mol Genet. 2011 Oct 15;20(20):4056-68 [PMID: 21768215]
  17. PLoS Genet. 2018 Jan 30;14(1):e1007172 [PMID: 29381699]
  18. Ann Rheum Dis. 2017 May;76(5):869-877 [PMID: 27899376]
  19. Front Genet. 2019 Apr 26;10:334 [PMID: 31080455]
  20. Nat Genet. 2014 Jun;46(6):543-550 [PMID: 24816252]
  21. BMC Med Genomics. 2011 Jan 26;4:13 [PMID: 21269473]
  22. Nat Commun. 2021 Feb 17;12(1):1079 [PMID: 33597532]
  23. Rheumatology (Oxford). 2012 Apr;51(4):715-20 [PMID: 22179738]
  24. Nat Genet. 2019 Oct;51(10):1459-1474 [PMID: 31578528]
  25. Ann Rheum Dis. 2016 Apr;75(4):652-9 [PMID: 25646370]
  26. Nat Genet. 2015 Mar;47(3):291-5 [PMID: 25642630]
  27. Nat Genet. 2015 Nov;47(11):1236-41 [PMID: 26414676]
  28. Glycobiology. 2021 Feb 9;31(2):82-88 [PMID: 32521004]
  29. Nat Genet. 2012 Mar 04;44(4):430-4, S1-2 [PMID: 22387998]
  30. Bioinformatics. 2010 May 1;26(9):1205-10 [PMID: 20335276]
  31. Gigascience. 2015 Feb 25;4:7 [PMID: 25722852]
  32. Nat Genet. 2013 Jun;45(6):613-20 [PMID: 23583980]
  33. PLoS Genet. 2014 May 15;10(5):e1004383 [PMID: 24830394]
  34. Am J Hum Genet. 2019 Jan 3;104(1):65-75 [PMID: 30595370]
  35. Nucleic Acids Res. 2015 Apr 20;43(7):e47 [PMID: 25605792]
  36. Nat Commun. 2015 Jul 15;6:7754 [PMID: 26174136]
  37. Ann Rheum Dis. 2020 May;79(5):657-665 [PMID: 32238385]
  38. Lancet Infect Dis. 2020 Apr;20(4):425-434 [PMID: 32105637]
  39. Hum Mol Genet. 2011 Dec 15;20(24):5000-11 [PMID: 21908519]
  40. Nat Genet. 2009 Sep;41(9):986-90 [PMID: 19648918]
  41. Hum Genet. 2012 May;131(5):747-56 [PMID: 22143225]
  42. Nature. 2013 Mar 14;495(7440):251-4 [PMID: 23486063]
  43. Nat Commun. 2017 Feb 27;8:14357 [PMID: 28240269]
  44. Bioinformatics. 2014 Oct;30(19):2811-2 [PMID: 24930139]
  45. Nat Commun. 2015 Aug 14;6:7975 [PMID: 26272126]
  46. Cell. 2016 Nov 17;167(5):1415-1429.e19 [PMID: 27863252]
  47. Nature. 2021 Mar;591(7848):92-98 [PMID: 33307546]
  48. Nat Commun. 2019 Nov 15;10(1):5175 [PMID: 31729369]
  49. Genome Biol. 2010;11(3):R25 [PMID: 20196867]
  50. Pathobiology. 2021;88(1):15-27 [PMID: 33049751]
  51. Hum Mol Genet. 2013 Jun 15;22(12):2529-38 [PMID: 23446634]
  52. Immunity. 2020 Jul 14;53(1):19-25 [PMID: 32610079]
  53. N Engl J Med. 2019 Oct 10;381(15):1422-1433 [PMID: 31509666]
  54. PLoS One. 2015 Aug 05;10(8):e0132626 [PMID: 26244499]
  55. J Biol Chem. 2018 Dec 7;293(49):18864-18878 [PMID: 30291141]
  56. Nucleic Acids Res. 2019 Jan 8;47(D1):D1005-D1012 [PMID: 30445434]
  57. Sci Rep. 2018 Feb 16;8(1):3137 [PMID: 29453348]
  58. Nat Commun. 2020 Jan 9;11(1):163 [PMID: 31919418]
  59. Cell. 2020 Sep 3;182(5):1198-1213.e14 [PMID: 32888493]
  60. Nat Chem Biol. 2017 Jan;13(1):46-53 [PMID: 27820798]
  61. Nat Commun. 2019 Dec 16;10(1):5732 [PMID: 31844061]
  62. J Clin Pathol. 2020 Jun;73(6):347-349 [PMID: 31662441]
  63. Bioinformatics. 2016 Oct 15;32(20):3207-3209 [PMID: 27318201]
  64. Semin Arthritis Rheum. 2020 Oct;50(5):1089-1100 [PMID: 32916560]
  65. J Thromb Haemost. 2018 Jun 11;: [PMID: 29888865]
  66. PLoS Genet. 2007 Nov;3(11):e194 [PMID: 17997608]
  67. Nature. 2018 Oct;562(7726):203-209 [PMID: 30305743]
  68. Expert Opin Ther Pat. 2019 Nov;29(11):871-879 [PMID: 31593642]
  69. Bioinformatics. 2013 Jan 1;29(1):15-21 [PMID: 23104886]
  70. Vox Sang. 1995;68(4):236-40 [PMID: 7660643]
  71. Ann Rheum Dis. 2016 Jun;75(6):1219-27 [PMID: 26174021]
  72. Nature. 2015 Oct 1;526(7571):68-74 [PMID: 26432245]
  73. PLoS Genet. 2010 Dec 23;6(12):e1001256 [PMID: 21203500]
  74. PLoS Genet. 2011 Nov;7(11):e1002355 [PMID: 22072984]
  75. Nat Genet. 2011 Oct 09;43(11):1127-30 [PMID: 21983786]
  76. Blood. 2008 Apr 1;111(7):3540-5 [PMID: 18245665]
  77. Nat Genet. 2009 Jun;41(6):657-65 [PMID: 19465909]
  78. Nat Genet. 2008 Apr;40(4):430-6 [PMID: 18327256]
  79. Bioinformatics. 2014 Jun 15;30(12):i185-94 [PMID: 24931982]
  80. J Biol Chem. 1979 Nov 10;254(21):10754-60 [PMID: 315409]
  81. Nat Genet. 2010 Mar;42(3):210-5 [PMID: 20139978]
  82. Nat Genet. 2017 Apr;49(4):559-567 [PMID: 28250457]
  83. Clin Proteomics. 2019 Sep 07;16:35 [PMID: 31516400]
  84. Nature. 2015 Oct 8;526(7572):253-7 [PMID: 26416757]
  85. Sci Rep. 2019 Mar 21;9(1):4981 [PMID: 30899057]
  86. Nat Genet. 2009 Aug;41(8):926-30 [PMID: 19561606]
  87. J Biol Chem. 1992 May 5;267(13):8723-31 [PMID: 1577715]
  88. Genome Biol. 2015 Sep 15;16:190 [PMID: 26374098]
  89. Science. 2015 May 8;348(6235):648-60 [PMID: 25954001]
  90. Lancet. 2008 Dec 6;372(9654):1953-61 [PMID: 18834626]
  91. Hum Mol Genet. 2020 Apr 15;29(6):923-943 [PMID: 31985003]
  92. Hum Mol Genet. 2019 Jun 15;28(12):2062-2077 [PMID: 31163085]
  93. PLoS Pathog. 2016 Jul 21;12(7):e1005680 [PMID: 27442518]
  94. J Thromb Haemost. 2016 May;14(5):953-63 [PMID: 26875505]
  95. Med Hypotheses. 2020 Nov;144:110005 [PMID: 32575019]
  96. Bioinformatics. 2012 Oct 1;28(19):2540-2 [PMID: 22843982]
  97. Am J Respir Crit Care Med. 2020 Mar 1;201(5):564-574 [PMID: 31710517]
  98. Nat Genet. 2013 Feb;45(2):145-54 [PMID: 23263486]
  99. Eur J Clin Pharmacol. 2020 Nov;76(11):1615-1618 [PMID: 32594204]

Grants

  1. R01 AI118903/NIAID NIH HHS
  2. R21 AI133305/NIAID NIH HHS
  3. T32 GM145449/NIGMS NIH HHS
  4. UM1 AI104681/NIAID NIH HHS

MeSH Term

COVID-19
Databases, Nucleic Acid
Genetic Predisposition to Disease
Genome-Wide Association Study
Humans
Linkage Disequilibrium
Multifactorial Inheritance
Polymorphism, Single Nucleotide
SARS-CoV-2

Links to CNCB-NGDC Resources

Database Commons: DBC007602 (iCPAGdb)

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