Decoding the sleep enigma: a proteomic mediation analysis linking healthy sleep patterns to lung cancer risk

The biological link between sleep patterns and lung cancer remains an enigma. This study aims to explore how healthy sleep patterns modulate lung cancer risk through proteomic mediation and develop a sleep-related biomarker panel.

This study utilized data from the UK Biobank, comprising 34 881 participants. We used a composite sleep score that considered the following five sleep behaviors: sleep duration, chronotype, insomnia, snoring, and daytime sleepiness (0-5 scores). Proteomic profiling measured 2862 proteins, which were then used to build proteomic signatures through logistic regression to identify significant proteins, followed by LASSO regression to select representative biomarkers for forming weighted signatures. Cox proportional hazards models and mediation analysis were employed to evaluate associations between sleep patterns, proteins, and lung cancer risk.

Higher healthy sleep scores were significantly associated with reduced lung cancer risk, with hazard ratios (HR = 0.589, p = .046) for a score of 3 and (HR = 0.516, p = .013) for a score of 4. Similar trends were observed in non-small cell lung cancer and lung adenocarcinoma. Proteomic signature analysis revealed that protein signatures associated with healthy sleep scores had a protective effect against lung cancer (HR = 0.865, p < .001) and non-small cell lung cancer (HR = 0.863, p < .001). Additionally, mediation analysis identified 18 proteins with mediation proportions exceeding 10 per cent in the relationship between healthy sleep scores and lung cancer, with CXCL17 showing the highest mediation proportion.

This study reveals a potential association between healthy sleep patterns and reduced lung cancer risk.