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Record W4225136998 · doi:10.1101/2022.04.27.22273667

Fibroblast Growth Factor-23 and Risk of Cardiovascular Diseases: a Mendelian Randomisation study

2022· preprint· en· W4225136998 on OpenAlexaff
Killian Donovan, William G. Herrington, Guillaume Paré, Marie Pigeyre, Richard Haynes, Rebecca J. Sardell, Adam S. Butterworth, Lasse Folkersen, Stefan Gustafsson, Qin Wang, Colin Baigent, Anders Mälarstig, Michael V. Holmes, Natalie Staplin

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersUniversity of OxfordKidney Research UKBritish Heart FoundationMedical Research CouncilNational Institute for Health and Care Research
KeywordsMedicineConfoundingMendelian randomizationOdds ratioInternal medicineCoronary artery diseaseRisk factorConfidence intervalCardiologyDiseaseCase-control studyEpidemiologyGenotypeGeneticsBiologyGenetic variants

Abstract

fetched live from OpenAlex

Abstract Fibroblast growth factor 23 (FGF-23) is associated with a range of cardiovascular and non-cardiovascular diseases in conventional epidemiological studies, but substantial residual confounding may exist. Mendelian randomisation approaches can help control for such confounding. SCALLOP consortium data on 19,195 participants were used to generate an FGF-23 genetic score. Data from 337,448 UK Biobank participants were used to estimate associations between higher genetically-predicted FGF-23 concentration and the odds of any atherosclerotic cardiovascular disease (n=26,266 events), of any non-atherosclerotic cardiovascular disease (n=12,652), and of non-cardiovascular diseases previously linked to FGF-23. Measurements of carotid intima-media thickness (CIMT) and left ventricular mass (LVM) were available in a subset. Associations with cardiovascular outcomes were also tested in three large case-control consortia: CARDIOGRAMplusC4D (coronary artery disease, n=181,249 cases), MEGASTROKE (stroke, n=34,217), and HERMES (heart failure, n=47,309). We identified 34 independent variants for circulating FGF-23 which formed a validated genetic score. There were no associations between genetically-predicted FGF-23 and any of the cardiovascular or non-cardiovascular outcomes. In UK Biobank, the odds ratio for any atherosclerotic cardiovascular disease per 1-SD higher genetically-predicted logFGF-23 was 1.03 (95% confidence interval [CI] 0.98-1.08), and for any non-atherosclerotic cardiovascular disease was 1.01 (0.94-1.09). The odds ratios in the case-control consortia were 1.00 (0.97-1.03) for coronary artery disease, 1.01 (0.95-1.07) for stroke, and 1.00 (0.95-1.05) for heart failure. In those with imaging, logFGF-23 was not associated with CIMT or LVM index. This suggests that previously reported observational associations of FGF-23 with risk of atherosclerotic and non-atherosclerotic cardiovascular diseases are unlikely to be causal.

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)0.015
metaresearch head score (Gemma)0.031
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 score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.267
Teacher spread0.250 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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