Exploring genetic associations between metabolites and atopic dermatitis: insights from bidirectional Mendelian randomization analysis in European population
Bibliographic record
Abstract
Introduction: There is growing evidence indicating a complex interaction between blood metabolites and atopic dermatitis (AD). The objective of this study was to investigate and quantify the potential influence of plasma metabolites on AD through Mendelian randomization (MR) analysis. Methods: Our procedures followed these steps: instrument variable selection, primary analysis, replication analysis, Meta-analysis of results, reverse MR analysis, and multivariate MR (MVMR) analysis. In our study, the exposure factors were derived from the Canadian Longitudinal Study on Aging (CLSA), encompassing 8,299 individuals of European descent and identifying 1,091 plasma metabolites and 309 metabolite ratios. In primary analysis, AD data, was sourced from the GWAS catalog (Accession ID: GCST90244787), comprising 60,653 cases and 804,329 controls. For replication, AD data from the Finnish R10 database included 15,208 cases and 367,046 controls. We primarily utilized the inverse variance weighting method to assess the causal relationship between blood metabolites and AD. Results: Our study identified significant causal relationships between nine genetically predicted blood metabolites and AD. Specifically, 1-palmitoyl-2-stearoyl-GPC (16:0/18:0) (OR = 0.92, 95% CI 0.89-0.94), 1-methylnicotinamide (OR = 0.93, 95% CI 0.89-0.98), linoleoyl-arachidonoyl-glycerol (18:2/20:4) [1] (OR = 0.94, 95% CI 0.92-0.96), and 1-arachidonoyl-GPC (20:4n6) (OR = 0.94, 95% CI 0.92-0.96) were associated with a reduced risk of AD. Conversely, phosphate / linoleoyl-arachidonoyl-glycerol (18:2/20:4) [2] (OR = 1.07, 95% CI 1.04-1.10), docosatrienoate (22:3n3) (OR = 1.07, 95% CI 1.04-1.10), retinol (Vitamin A) / linoleoyl-arachidonoyl-glycerol (18:2/20:4) [2] (OR = 1.08, 95% CI 1.05-1.11), retinol (Vitamin A) / linoleoyl-arachidonoylglycerol (18:2/20:4) [1] (OR = 1.08, 95% CI 1.05-1.12), and phosphate / linoleoyl-arachidonoyl-glycerol (18:2/20:4) [1] (OR = 1.09, 95% CI 1.07-1.12 were associated with an increased risk of AD. No evidence of reverse causality was found in the previously significant results. MVMR analysis further confirmed that 1-palmitoyl-2-stearoyl-GPC (16:0/18:0) and 1-methylnicotinamide are independent and dominant contributors to the development of AD. Conclusion: Our study revealed a causal relationship between genetically predicted blood metabolites and AD. This discovery offers specific targets for drug development in the treatment of AD patients and provides valuable insights for investigating the underlying mechanisms of AD in future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".