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Record W4416243543 · doi:10.1093/bjd/ljaf463

Sleep patterns and the risk of psoriatic disease: genetic predisposition and metabonomics

2025· article· en· W4416243543 on OpenAlexaff
Ziyu Guo, Zehao Luo, Shiyu Zhang, Yao Yu, Tzu-Hua Wu, Y.Y. Chen, Yuming Sun, Furong Zeng, Lin Shi, Guowei Zhou, Lixia Lü, Guangtong Deng

Bibliographic record

VenueBritish Journal of Dermatology · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsSKiN Health
FundersFundamental Research Funds for Central Universities of the Central South UniversityHuxiang Youth Talent Support ProgramNational Natural Science Foundation of China
KeywordsGenetic predispositionSleep (system call)Sleep patternsRisk factorAssociation (psychology)PsoriasisGenetic association

Abstract

fetched live from OpenAlex

BACKGROUND: The longitudinal impact of comprehensive sleep patterns on incident psoriatic disease (PsD) and the potential mediating effects are unclear. OBJECTIVES: To investigate the associations of sleep patterns with PsD risk, alongside the role of genetic predisposition and the potential mediating effects of serum metabolites. METHODS: This prospective cohort study included 399 912 participants without PsD registered in UK Biobank. Cox proportional hazard models were used to examine the association between sleep patterns, genetic risk of PsD and the overall risk of PsD. Cross-product interaction terms between polygenic risk score (PRS) categories and sleep patterns were incorporated into the fully adjusted models, and the relative excess risk due to interaction (RERI) was calculated to examine additive interaction. Mediation analyses were used to identify specific metabolites as potential mediators of PsD. RESULTS: During a mean follow-up of 14.7 years, 4001 new cases of PsD were identified. Compared with those with high PRS and low sleep scores, participants with low PRS and high sleep scores had the lowest risk of PsD [hazard ratio 0.35, 95% confidence interval (CI) 0.28-0.43]. Although no significant interaction between PRS and sleep score was initially detected (P = 0.08), subsequent analyses using a median-dichotomized PRS revealed multiplicative (P = 0.003) and additive interactions (RERI 0.36, 95% CI 0.17-0.55; P < 0.001). Mediation analyses identified glycoprotein acetylation, the ratio of polyunsaturated fatty acids to monounsaturated fatty acids and alkaline phosphatase as partial mediators of the sleep-PsD association. CONCLUSIONS: Unfavourable sleep patterns significantly increase the risk of PsD, especially in people with a high genetic predisposition to PsD. This association is partially mediated by inflammatory and metabolic biomarkers, highlighting sleep optimization as a modifiable lifestyle factor for mitigating PsD risk.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.223
Teacher spread0.220 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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