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Journal Article

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9

Authors

  1. Amand F. Schmidt
  2. Michael V. Holmes
  3. David Preiss
  4. Daniel I. Swerdlow
  5. Ghazaleh Fatemifar
  6. Rupert Faraway
  7. Chris Finan
  8. Dennis Valentine
  9. Zammy Fairhurst-Hunter
  10. Fernando Pires Hartwig
  11. Bernardo Lessa Horta
  12. Elina Hypponen
  13. Christine Power
  14. Max Moldovan
  15. Erik van Iperen
  16. Kees Hovingh
  17. Ilja Demuth
  18. Kristina Norman
  19. Elisabeth Steinhagen-Thiessen
  20. Juri Demuth
  21. Lars Bertram
  22. Christina M. Lill
  23. Stefan Coassin
  24. Johann Willeit
  25. Stefan Kiechl
  26. Karin Willeit
  27. Dan Mason
  28. John Wright
  29. Richard Morris
  30. Goya Wanamethee
  31. Peter Whincup
  32. Yoav Ben-Shlomo
  33. Stela McLachlan
  34. Jackie F. Price
  35. Mika Kivimaki
  36. Catherine Welch
  37. Adelaida Sanchez-Galvez
  38. Pedro Marques-Vidal
  39. Andrew Nicolaides
  40. Andrie G. Panayiotou
  41. N. Charlotte Onland-Moret
  42. Yvonne T. van der Schouw
  43. Giuseppe Matullo
  44. Giovanni Fiorito
  45. Simonetta Guarrera
  46. Carlotta Sacerdote
  47. Nicholas J. Wareham
  48. Claudia Langenberg
  49. Robert A. Scott
  50. Jian’an Luan
  51. Martin Bobak
  52. Sofia Malyutina
  53. Andrzej Pająk
  54. Ruzena Kubinova
  55. Abdonas Tamosiunas
  56. Hynek Pikhart
  57. Niels Grarup
  58. Oluf Pedersen
  59. Torben Hansen
  60. Allan Linneberg
  61. Tine Jess
  62. Jackie Cooper
  63. Steve E. Humphries
  64. Murray Brilliant
  65. Terrie Kitchner
  66. Hakon Hakonarson
  67. David S. Carrell
  68. Catherine A. McCarty
  69. Kirchner H. Lester
  70. Eric B. Larson
  71. David R. Crosslin
  72. Mariza de Andrade
  73. Dan M. Roden
  74. Joshua C. Denny
  75. Cara Carty
  76. Stephen Hancock
  77. John Attia
  78. Elizabeth Holliday
  79. Rodney Scott
  80. Peter Schofield
  81. Martin O’Donnell
  82. Salim Yusuf
  83. Michael Chong
  84. Guillaume Pare
  85. Pim van der Harst
  86. M. Abdullah Said
  87. Ruben N. Eppinga
  88. Niek Verweij
  89. Harold Snieder
  90. Tim Christen
  91. D.O. Mook-Kanamori
  92. Stefan Gustafsson
  93. Lars Lind
  94. Erik Ingelsson
  95. Raha Pazoki
  96. Oscar Franco
  97. Albert Hofman
  98. Andre Uitterlinden
  99. Abbas Dehghan
  100. Alexander Teumer
  101. Sebastian Baumeister
  102. Marcus Dörr
  103. Markus M. Lerch
  104. Uwe Völker
  105. Henry Völzke
  106. Joey Ward
  107. Jill P. Pell
  108. Tom Meade
  109. Ingrid E. Christophersen
  110. Anke H. Maitland-van der Zee
  111. Ekaterina V. Baranova
  112. Robin Young
  113. Ian Ford
  114. Archie Campbell
  115. Sandosh Padmanabhan
  116. Michiel L. Bots
  117. Diederick E. Grobbee
  118. Philippe Froguel
  119. Dorothée Thuillier
  120. Ronan Roussel
  121. Amélie Bonnefond
  122. Bertrand Cariou
  123. Melissa Smart
  124. Yanchun Bao
  125. Meena Kumari
  126. Anubha Mahajan
  127. Jemma C. Hopewell
  128. Sudha Seshadri
  129. Caroline Dale
  130. Rui Providencia E. Costa
  131. Paul M. Ridker
  132. Daniel I. Chasman
  133. Alex P. Reiner
  134. Marylyn D. Ritchie
  135. Leslie A. Lange
  136. Alex J. Cornish
  137. Sara E. Dobbins
  138. Kari Hemminki
  139. Ben Kinnersley
  140. Marc Sanson
  141. Karim Labreche
  142. Matthias Simon
  143. Melissa Bondy
  144. Philip Law
  145. Helen Speedy
  146. James Allan
  147. Ni Li
  148. Molly Went
  149. Niels Weinhold
  150. Gareth Morgan
  151. Pieter Sonneveld
  152. Björn Nilsson
  153. Hartmut Goldschmidt
  154. Amit Sud
  155. Andreas Engert
  156. Markus Hansson
  157. Harry Hemingway
  158. Folkert W. Asselbergs
  159. Riyaz S. Patel
  160. Brendan J. Keating
  161. Naveed Sattar
  162. Richard Houlston
  163. Juan P. Casas
  164. Aroon D. Hingorani

Publication date

29 Oct 2019

Summary

Background:
We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9.
Methods:
Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration.
Results:
The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer’s disease – outcomes for which large-scale trial data were unavailable.
Conclusions:
Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.

Published in

BMC Cardiovascular Disorders

Volume

19:240

DOI

https://doi.org/10.1186/s12872-019-1187-z

ISSN

16

Subjects

Health, Biology, and Genetics

Notes

Open Access; This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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