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Multicenter Study
. 2019 Oct 29;19(1):240.
doi: 10.1186/s12872-019-1187-z.

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

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

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

Amand F Schmidt et al. BMC Cardiovasc Disord. .

Abstract

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.

Keywords: Genetic association studies; LDL-cholesterol; Mendelian randomisation; Phenome-wide association scan.

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Conflict of interest statement

Dr. Holmes has collaborated with Boehringer Ingelheim in research, and in accordance with the policy of the The Clinical Trial Service Unit and Epidemiological Studies Unit (University of Oxford), did not accept any personal payment. David Preiss consulted for Amgen on a single occasion but, in accordance with the policy of the Clinical Trial Service Unit (University of Oxford), did not accept any personal payment. He is an investigator on a clinical trial of the PCSK9 synthesis inhibitor, inclisiran, funded by a grant to the University of Oxford by the Medicines Company, but he receives no personal fees from this grant. Daniel I Swerdlow is an employee of BenevolentAI Ltd. Aroon Hingorani and Harry Hemingway are National Institute for Health Research Senior Investigators. Naveed Sattar consulted for Amgen and Sanofi related to PCSK9 inhibitors; and was an investigator on clinical trials of PCSK9 inhibition funded by Amgen. Naveed Sattar has also consulted for Boehringer Ingelheim, Janssen, Eli-Lilly and NovoNordisk. Daniel Swerdlow has consulted to Pfizer for work unrelated to this paper. Folkert W. Asselbergs is supported by UCL Hospitals NIHR Biomedical Research Centre. Dr. Patel has received honoraria and speaker fees from Sanofi, Amgen and Bayer. Kees Hovingh or his institution (AMC) received honoraria for consultancy, ad boards, and/or conduct of clinical trials from: AMGEN, Aegerion, Pfizer, Astra Zeneca, Sanofi, Regeneron, KOWA, Ionis pharmaceuticals and Cerenis. Bertrand Cariou has received research funding from Pfizer and Sanofi, received honoraria from AstraZeneca, Pierre Fabre, Janssen, Eli-Lilly, MSD Merck & Co., Novo-Nordisk, Sanofi, and Takeda, and has acted as a consultant/advisory panel member for Amgen, Eli Lilly, Novo-Nordisk, Sanofi, and Regeneron. Andrzej Pająk acted as a consultant/advisory pannel member for Amgen. Erik Ingelsson is a scientific advisor for Precision Wellness and Olink Proteomics for work unrelated to this paper. JCH is a scientific advisor to a clinical trial of PCSK9 inhibition. AE Honoraria: Takeda, BMS, Amgen; Consulting: Takeda, BMS, Amgen. SEH acknowledges BHF funding (PG008/08) and support from the UCL BRC. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Lipid and lipoprotein associations of a PCSK9 gene-centric score (GS) compared to placebo-controlled randomized trials of therapeutic inhibition of PCSK9. Footnote: Effect estimates are presented as mean differences, with 95% confidence interval (CI). Trial estimates are presented as percentage change from baseline (during 6 months of follow-up), and GS estimates scaled to a 1 mmol/L lower LDL-C (mmol/L). Results are pooled using a fixed effect model. Trial estimates are based on the systematic review by Schmidt et al 2017 [6, 17]
Fig. 2
Fig. 2
Associations of a PCSK9 gene-centric score with ischemic and non-ischemic cardiovascular endpoints. Footnote: Effect estimates are presented as odds ratios (OR), with 95% confidence interval (CI) scaled to a 1 mmol/L lower LDL-C (mmol/L). Results are pooled using a fixed effect model. The size of the squares are proportional to the inverse of the variance
Fig. 3
Fig. 3
Clinical endpoint associations of the PCSK9 gene-centric score (GS) as compared to placebo-controlled randomized trials of therapeutic inhibition of PCSK9. Footnote: Effect estimates are presented as odds ratios (OR), with 95% confidence interval (CI), for the GS scaled to a 1 mmol/L lower LDL-C (mmol/L). Results are pooled using a fixed effect model. Trial estimates are based on the systematic review by Schmidt et al 2017 [6], with the estimates on ischemic stroke and revascularization solely based on the FOURIER and ODYSSEY OUTCOMES trials
Fig. 4
Fig. 4
Associations of a PCSK9 gene-centric score (GS) with non-cardiovascular events. Footnote: Effect estimates are presented as odds ratios (OR), with 95% confidence interval (CI) scaled to a 1 mmol/L lower LDL-C (mmol/L). Results are pooled using a fixed effect model. The size of the squares are proportional to the inverse of the variance. Note, that all GS estimates are based on 4 SNPs, except for the Alzheimer’s disease estimate which excluded the SNP rs11591147 due to lack of data

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