MétaCan
Menu
← Back to cohort
Record W2803189008 · doi:10.1101/329052

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in <i>PCSK9</i>

2018· preprint· en· W2803189008 on OpenAlexaff
Amand F. Schmidt, Michael V. Holmes, David Preiss, Daniel I. Swerdlow, Spiros Denaxas, Ghazaleh Fatemifar, Rupert Faraway, Chris Finan, Tom Lumbers, Albert Henry, Dennis Valentine, Zammy Fairhurst-Hunter, Fernando Pires Hartwig, Bernardo Lessa Horta, Elina Hyppönen, Christine Power, Max Moldovan, Erik Van Iperen, Kees Hovingh, Ilja Demuth, Kristina Norman, Elisabeth Steinhagen‐Thiessen, Juri Demuth, Lars Bertram, Christina M. Lill, Stefan Coassin, Johann Willeit, Stefan Kiechl, Karin Willeit, Dan Mason, John Wright, Richard Morris, Goya Wanamethee, Peter H. Whincup, Yoav Ben‐Shlomo, Stela McLachlan, Jackie F. Price, Mika Kivimäki, Catherine Welch, Adelaida Sánchez-Gálvez, Pedro Marques‐Vidal, Andrew Nicolaides, Andrie G. Panayiotou, N. Charlotte Onland‐Moret, Yvonne T. van der Schouw, Giuseppe Matullo, Giovanni Fiorito, Simonetta Guarrera, Carlotta Sacerdote, Nicholas J. Wareham, Claudia Langenberg, Robert A. Scott, Jian’an Luan, Martin Bobák, Sofia Malyutina, Andrzej Pająk, Růžena Kubínová, Abdonas Tamošiūnas, Hynek Pikhart, Niels Grarup, Oluf Pedersen, Torben Hansen, Allan Linneberg, Tine Jess, Jackie A. Cooper, Steve E. Humphries, Murray H. Brilliant, Terrie Kitchner, Håkon Håkonarson, David Carrell, Catherine A. McCarty, Kirchner H. Lester, Eric B. Larson, David R. Crosslin, Mariza de Andrade, Dan M. Roden, Joshua C. Denny, Cara L. Carty, Stephen Hancock, John Attia, Elizabeth Holliday, Rodney J. Scott, Peter W. Schofield, Martin O’Donnell, Salim Yusuf, Michael Chong, Guillaume Paré, Pim van der Harst, M. Abdullah Said, Ruben N. Eppinga, Niek Verweij, Harold Snieder, Tim Christen, Dennis O. Mook‐Kanamori, Stefan Gustafsson, Lars Lind, Erik Ingelsson, Raha Pazoki, Oscar H. Franco, Albert Hofman, André G. Uitterlinden, Abbas Dehghan, Alexander Teumer, Sebastian E. Baumeister, Marcus Dörr, Markus M. Lerch, Uwe Völker, Henry Völzke, Joey Ward, Jill P. Pell, Tom Meade, Ingrid E. Christophersen, Anke H. Maitland‐van der Zee, E.V. Baranova, Robin Young, Ian Ford, Archie Campbell, Sandosh Padmanabhan, Michiel L. Bots, Diederick E. Grobbee, Philippe Froguel, Dorothée Thuillier, Ronan Roussel, Amélie Bonnefond, Bertrand Cariou, Melissa Smart, Yanchun Bao, Meena Kumari, Anubha Mahajan, Jemma C. Hopewell, Sudha Seshadri, Caroline Dale, Rui Providencia E. Costa, Paul M. Ridker, Daniel I. Chasman, Alex P. Reiner, Marylyn D. Ritchie, Leslie A. Lange, Alex J. Cornish, Sara E. Dobbins, Kari Hemminki, Ben Kinnersley, Marc Sanson, Karim Labrèche, Matthias Simon, Melissa L. Bondy, Philip Law, Helen E. Speedy, James M. Allan, Li Ni, Molly Went, Niels Weinhold, Gareth J. Morgan, Pieter Sonneveld, Björn Nilsson, Hartmut Goldschmidt, Amit Sud, Andreas Engert, Markus Hansson, Harry Hemingway, Folkert W. Asselbergs, Riyaz Patel, Brendan J. Keating, Naveed Sattar, Richard S. Houlston, Juan P. Casas, Aroon D. Hingorani

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsPopulation Health Research Institute
FundersMedical Research CouncilBlood Cancer UKRosetrees TrustNational Institute for Health and Care ResearchBritish Heart FoundationWellcome Trust
KeywordsPCSK9Internal medicineMedicineMendelian randomizationOdds ratioSingle-nucleotide polymorphismPlaceboDiabetes mellitusType 2 diabetesOncologyCholesterolEndocrinologyGenotypeGeneticsBiologyLipoproteinGenetic variantsLDL receptorPathologyGene

Abstract

fetched live from OpenAlex

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). Fourteen 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. Apparent discordance between genetic associations and trial outcome for T2DM might be explained lack by a of statistical precision, or differences in the nature and duration of genetic versus pharmacological perturbation of PCSK9. Funding This research was funded by the British Heart Foundation (SP/13/6/30554, RG/10/12/28456, FS/18/23/33512), UCL Hospitals NIHR Biomedical Research Centre, by the Rosetrees and Stoneygate Trusts. Condensed abstract Evidence on the long-term efficacy and safety of therapeutic inhibition of PCSK9 is lacking. To explore potential long-term effects of PCSK9 inhibition, we characterised the phenotypic consequence of LDL-cholesterol lowering variants at the PCSK9 locus. A PCSK9 gene score comprising 4 SNPs recapitulated the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and risk of myocardial infarction, and was associated with an increased risk of type 2 diabetes. No associations with safety outcomes such as cancer, COPD, Alzheimer’s disease or atrial fibrillation were identified. Our findings suggest PCSK9 inhibition may be safe and effective during prolonged use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.228
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicLipoproteins and Cardiovascular Health→French-language works237,207→