Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure

Carregando...
Imagem de Miniatura
Citações na Scopus
5
Tipo de produção
article
Data de publicação
2023
Título da Revista
ISSN da Revista
Título do Volume
Editora
NATURE PORTFOLIO
Autores
RASOOLY, Danielle
PELOSO, Gina M.
DASHTI, Hesam
GIAMBARTOLOMEI, Claudia
WHEELER, Eleanor
AUNG, Nay
FEROLITO, Brian R.
PIETZNER, Maik
FARBER-EGER, Eric H.
Citação
NATURE COMMUNICATIONS, v.14, n.1, 2023
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure. Here, the authors perform a large-scale meta-analysis of genome-wide association studies and cis-MR proteomics to identify protein biomarkers and drug targets for heart failure.
Palavras-chave
Referências
  1. Aung N, 2019, CIRCULATION, V140, P1318, DOI 10.1161/CIRCULATIONAHA.119.041161
  2. Bai WJ, 2018, J CARDIOVASC MAGN R, V20, DOI 10.1186/s12968-018-0471-x
  3. Beauverger P, 2020, CARDIOVASC RES, V116, P329, DOI 10.1093/cvr/cvz097
  4. Brown KK, 2018, MEDCHEMCOMM, V9, P606, DOI 10.1039/c7md00633k
  5. Bulik-Sullivan BK, 2015, NAT GENET, V47, P291, DOI 10.1038/ng.3211
  6. Burgess S, 2017, EUR J EPIDEMIOL, V32, P377, DOI 10.1007/s10654-017-0255-x
  7. Chen EY, 2013, BMC BIOINFORMATICS, V14, DOI 10.1186/1471-2105-14-128
  8. Chong M, 2019, CIRCULATION, V140, P819, DOI 10.1161/CIRCULATIONAHA.119.040180
  9. Di Angelantonio E, 2009, JAMA-J AM MED ASSOC, V302, P1993, DOI 10.1001/jama.2009.1619
  10. Esan O, 2020, DRUG DES DEV THER, V14, P2623, DOI 10.2147/DDDT.S224771
  11. Evangelou E, 2018, NAT GENET, V50, P1412, DOI 10.1038/s41588-018-0205-x
  12. Fahey ME, 2011, BMC BIOINFORMATICS, V12, DOI 10.1186/1471-2105-12-298
  13. Fielitz J, 2008, P NATL ACAD SCI USA, V105, P3059, DOI 10.1073/pnas.0712265105
  14. Gallagher MD, 2018, AM J HUM GENET, V102, P717, DOI 10.1016/j.ajhg.2018.04.002
  15. Ge T, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09718-5
  16. Giambartolomei C, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004383
  17. Graham SE, 2021, NATURE, V600, P675, DOI 10.1038/s41586-021-04064-3
  18. Hemani G, 2018, ELIFE, V7, DOI 10.7554/eLife.34408
  19. Hemani G, 2017, PLOS GENET, V13, DOI 10.1371/journal.pgen.1007081
  20. Hoffmann TJ, 2018, GENETICS, V210, P499, DOI 10.1534/genetics.118.301479
  21. Jain M, 2009, CIRCULATION, V119, P2058, DOI 10.1161/CIRCULATIONAHA.108.837286
  22. Joseph J, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-35323-0
  23. Karczewski Konrad J, 2022, Cell Genom, V2, P100168, DOI 10.1016/j.xgen.2022.100168
  24. Karlsson T, 2019, NAT MED, V25, P1390, DOI 10.1038/s41591-019-0563-7
  25. Kehat I, 2011, CIRC RES, V108, P176, DOI 10.1161/CIRCRESAHA.110.231514
  26. Kuleshov MV, 2016, NUCLEIC ACIDS RES, V44, pW90, DOI 10.1093/nar/gkw377
  27. Levin MG, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-34216-6
  28. Linnér RK, 2019, NAT GENET, V51, P245, DOI 10.1038/s41588-018-0309-3
  29. Liu Y, 2021, BIOINFORMATICS, V37, P1304, DOI 10.1093/bioinformatics/btaa961
  30. Murphy AE, 2021, BIOINFORMATICS, V37, P4593, DOI 10.1093/bioinformatics/btab665
  31. Nielsen JB, 2018, NAT GENET, V50, P1234, DOI 10.1038/s41588-018-0171-3
  32. Nissen SE, 2005, NEW ENGL J MED, V352, P29, DOI 10.1056/NEJMoa042000
  33. Ochoa D, 2021, NUCLEIC ACIDS RES, V49, pD1302, DOI 10.1093/nar/gkaa1027
  34. Pietzner M, 2021, SCIENCE, V374, P839, DOI 10.1126/science.abj1541
  35. Pirruccello JP, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15823-7
  36. Pulit SL, 2019, HUM MOL GENET, V28, P166, DOI 10.1093/hmg/ddy327
  37. Rahimi K, 2021, LANCET, V397, P1625, DOI 10.1016/S0140-6736(21)00590-0
  38. Roden DM, 2008, CLIN PHARMACOL THER, V84, P362, DOI 10.1038/clpt.2008.89
  39. Roger VL, 2021, CIRC RES, V128, P1421, DOI 10.1161/CIRCRESAHA.121.318172
  40. Roth GA, 2020, J AM COLL CARDIOL, V76, P2982, DOI 10.1016/j.jacc.2020.11.010
  41. Santos R, 2017, NAT REV DRUG DISCOV, V16, P19, DOI 10.1038/nrd.2016.230
  42. Schneider M, 2021, NAT REV DRUG DISCOV, V20, P789, DOI 10.1038/s41573-021-00245-x
  43. Shah S, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-019-13690-5
  44. Shaw David R, 2016, Curr Protoc Bioinformatics, V56, DOI 10.1002/cpbi.18
  45. Smith GD, 2004, INT J EPIDEMIOL, V33, P30, DOI 10.1093/ije/dyh132
  46. Stanzick KJ, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-24491-0
  47. Swaminathan PD, 2012, CIRC RES, V110, P1661, DOI 10.1161/CIRCRESAHA.111.243956
  48. Uijl A, 2019, EUR J HEART FAIL, V21, P1197, DOI 10.1002/ejhf.1350
  49. van der Harst P, 2018, CIRC RES, V122, P433, DOI [10.1161/CIRCRESAHA.117.312086, 10.1161/circresaha.117.312086]
  50. Verweij N, 2020, CELL SYST, V11, P229, DOI 10.1016/j.cels.2020.08.005
  51. Votava JA, 2021, CURR OPIN LIPIDOL, V32, P141, DOI 10.1097/MOL.0000000000000742
  52. Watanabe K, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-01261-5
  53. Weeks EM, 2020, medRxiv, DOI [10.1101/2020.09.08.20190561, 10.1101/2020.09.08.20190561, DOI 10.1101/2020.09.08.20190561V1, DOI 10.1101/2020.09.08.20190561]
  54. Willer CJ, 2010, BIOINFORMATICS, V26, P2190, DOI 10.1093/bioinformatics/btq340
  55. Williams SA, 2019, NAT MED, V25, P1851, DOI 10.1038/s41591-019-0665-2
  56. Witztum JL, 2019, NEW ENGL J MED, V381, P531, DOI 10.1056/NEJMoa1715944
  57. Wu K.-H. H., 2021, MEDRXIV, DOI [10.1101/2021.12.06.21267389, DOI 10.1101/2021.12.06.21267389]
  58. Wu TZ, 2021, INNOVATION-AMSTERDAM, V2, DOI 10.1016/j.xinn.2021.100141
  59. Xie Zhuorui, 2021, Curr Protoc, V1, pe90, DOI 10.1002/cpz1.90
  60. Xue A, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04951-w
  61. Yengo L, 2018, HUM MOL GENET, V27, P3641, DOI 10.1093/hmg/ddy271
  62. Zhou Wei, 2022, Cell Genom, V2, P100192, DOI 10.1016/j.xgen.2022.100192