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Record W2829328274 · doi:10.1016/j.jacc.2018.04.067

Blood CSF1 and CXCL12 as Causal Mediators of Coronary Artery Disease

2018· article· en· W2829328274 on OpenAlexaff
Jennifer Sjaarda, Hertzel C. Gerstein, Michael Chong, Salim Yusuf, David Meyre, Sonia S. Anand, Sibylle Hess, Guillaume Paré

Bibliographic record

VenueJournal of the American College of Cardiology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsThrombosis and Atherosclerosis Research InstituteMcMaster UniversityPopulation Health Research Institute
FundersMedical Research Council
KeywordsMedicineMendelian randomizationCoronary artery diseaseInternal medicineOdds ratioHazard ratioConfoundingConfidence intervalRisk factorBiomarkerOncologyCardiologyGenotypeGenetics

Abstract

fetched live from OpenAlex

Background Identification of biomarkers that cause coronary artery disease (CAD) has led to important advances in prevention and treatment. Epidemiological analyses have identified many biomarker-CAD relationships; however, these associations may arise from reverse causation and/or confounding and therefore may not represent true causal associations. Mendelian randomization (MR) analyses overcome these limitations. Objectives This study sought to identify causal mediators of CAD through a comprehensive screen of 237 biomarkers using MR. Methods MR was performed by identifying genetic determinants of 227 biomarkers in ORIGIN (Outcome Reduction With Initial Glargine Intervention) trial participants (N = 4,147) and combining these with genetic effects on CAD from the CARDIoGRAM consortium (60,801 cases and 123,504 controls). Blood concentrations of novel biomarkers identified by MR were then tested for association with incident major adverse cardiovascular events in ORIGIN. Results Six biomarkers were found to be causally linked to CAD after adjustment for multiple hypothesis testing. The causal role of 4 of these is well documented, whereas macrophage colony-stimulating factor 1 (CSF1) and stromal cell–derived factor 1 (CXCL12) have not previously been reported, to the best of our knowledge. MR analysis predicted an 18% higher risk of CAD per SD increase in CSF1 (odds ratio: 1.18; 95% confidence interval: 1.08 to 1.30; p = 2.1 × 10 −4 ) and epidemiological analysis identified a 16% higher risk of major adverse cardiovascular events per SD (hazard ratio: 1.16; 95% confidence interval: 1.09 to 1.23; p < 0.001). Elevated CXCL12 levels were also identified as a causal risk factor for CAD with consistent epidemiological results. Furthermore, genetically predicted CSF1 and CXCL12 levels were associated with CAD in the UK Biobank (n = 343,735). Conclusions The study identified CSF1 and CXCL12 as causal mediators of CAD in humans. Understanding the mechanism by which these markers mediate CAD will provide novel insights into CAD and could lead to new approaches to prevention. These results support targeting inflammatory processes and macrophages, in particular, to prevent CAD, consistent with the recent CANTOS (Canakinumab Antiinflammatory Thrombosis Outcome Study). (Outcome Reduction With Initial Glargine Intervention [ORIGIN]; NCT00069784 )

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)0.001
metaresearch head score (Gemma)0.002
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.255
Teacher spread0.247 · 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

Citations98
Published2018
Admission routes1
Has abstractno

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