Apolipoprotein B as a Protective Factor Against Atopic Dermatitis: Insights Into Lipid Metabolism From a Large Prospective Cohort of 454,974 Individuals
Bibliographic record
Abstract
Abstract: Background: Atopic dermatitis (AD) is a chronic inflammatory skin condition influenced by lipid metabolism. Apolipoprotein B (ApoB), a crucial component of lipid transport, may be linked to AD risk, but this relationship has not been extensively studied in large cohorts. Objectives: To investigate the association between ApoB and the risk of developing AD using data from a large, prospective cohort in the UK Biobank (UKB). Methods: The study analyzed 454,974 participants from the UKB, with ApoB measured via blood biochemistry and nuclear magnetic resonance (NMR) spectroscopy. Cox proportional hazard models were used to evaluate the relationship between ApoB and AD risk, adjusting for demographic, lifestyle, and clinical covariates. Restricted cubic spline (RCS) analysis was employed to assess potential nonlinear relationships. Sensitivity analyses included adjusting for lipid-lowering medication use, comparing apolipoprotein A (ApoA) levels, and repeating analyses with NMR-measured ApoB. Results: Higher ApoB levels were significantly associated with a reduced risk of AD (hazard ratio for continuous ApoB: 0.74, 95% confidence interval: 0.64–0.86, P < 0.001). RCS analysis confirmed a linear inverse relationship between ApoB and AD risk ( P for overall <0.001; P for nonlinear: 0.803). Sensitivity analyses reinforced these findings, showing consistent results across different measures and adjustments, with no significant association found between ApoA levels and AD. Conclusions: This study establishes a significant inverse association between ApoB levels and AD risk, underscoring the role of lipid metabolism in AD pathogenesis in the UKB population. ApoB might be a potential biomarker or therapeutic target for AD prevention, meriting further investigation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".