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Causal effects of genetically determined blood metabolites on asthma: a bidirectional Mendelian randomization study

2024· dataset· en· W6939608208 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMendelian randomizationMetaboliteMetabolomicsGenome-wide association studyPleiotropyGenetic associationMetabolomeAsthmaObservational study

Abstract

The observational association between blood metabolites and asthma has been extensively studied. However, it is still unclear whether this association is causal. In this study, we aimed to investigate the causal relationship between blood metabolites and asthma using a bidirectional Mendelian randomization (MR) analysis. Additionally, we aimed to explore the potential mechanisms underlying this relationship. The study design involved the use of genetic instruments as instrumental variables (IVs) to fulfill the assumptions of MR analysis. The data on 1,091 metabolites and 309 metabolite ratios were obtained from the Canadian Longitudinal Study on Aging (CLSA), while the data on asthma were obtained from the Integrative Epidemiology Unit (IEU) Open GWAS Project. Utilizing the inverse variance-weighted (IVW) method as the primary MR analysis approach, sensitivity tests were conducted to assess the reliability of the findings, which involved employing Cochran’s Q and the MR-Egger intercept. Furthermore, Bayesian weighted MR was used to further test the robustness of the results. Additionally, pathway analysis was conducted to explore the metabolic explanations underlying asthma. In our study, a comprehensive MR Analysis identified 10 metabolites and 6 metabolite ratios significantly associated with the development of asthma (FDR &lt; 0.05). The metabolites included glycerophosphocholines(GPCs), glycerophosphoethanolamines(GPEs), and an unknown metabolite. Of these, 1-arachidonoyl-GPC, 1-myristoyl-2-arachidonoyl-GPC, 1-palmitoyl-2-arachidonoyl-GPC, and 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC were associated with an increased risk of asthma, whereas 1,2-dilinoleoyl-GPC, 1-palmitoyl-2-linoleoyl-GPC, 1,2-dilinoleoyl-GPE, 1 − oleoyl − 2 − linoleoyl − GPE, 1-palmitoyl-2-linoleoyl-GPE, and X-21470 were found to have a protective effect. No heterogeneity and pleiotropy were observed in the significant metabolites (<i>p</i> &gt; 0.05), and each metabolite exhibited a consistent effect direction across all five methods. BWMR analysis results confirmed the significance and direction of effects across exposures, except for Cholesterol to linoleoyl-arachidonoyl-glycerol ratio(<i>p</i> = 0.673). Pathway analysis suggests that glycerophospholipid metabolism may potentially be a mechanism underlying the development of asthma. Our MR findings suggest that the identified metabolites and pathways can serve as biomarkers for clinical asthma screening and prevention, while also providing new insights for future mechanistic exploration and drug target selection.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: about_only · design weight: 3321.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Mendelian randomization study of blood metabolites and asthma; a method is used to answer a biomedical question, not studied.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

It uses Mendelian randomization to study asthma biology, not research practice.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Bidirectional MR of blood metabolites and asthma is domain biomedical etiology, not a study of research practice.

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)0.021
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.018
GPT teacher head0.286
Teacher spread0.268 · 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 designSimulation or modeling
Domainnot available
GenreDataset

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

Citations0
Published2024
Admission routes1
Has abstractyes

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