Composite sleep score and risk of psychiatric disorders via proteomic features in preclinical obesity: a prospective cohort study from the UK Biobank.

AIMS: Sleep disturbances are linked to psychiatric disorders, and obesity is associated with a higher risk of several psychiatric disorders. However, evidence is lacking on how a composite sleep score relates to psychiatric disorder risk in preclinical obesity and on the proteomic pathways that mediate this relationship. Our study aimed to investigate the association of composite sleep score and the risk of multiple specific psychiatric disorders in participants with preclinical obesity.

METHODS

The prospective cohort study from the UK Biobank included 91,380 participants with preclinical obesity. Six groups were categorized according to sleep scores. Hazard ratios (HRs) for the incidence risk of psychiatric disorders were estimated using multiple Cox proportional hazards regression analysis. Mediation analysis of plasma proteomics in this association was conducted in a subset of participants (n = 9,486).

RESULTS

After a mean follow-up period of 12.9 years, a total of 8,992 incident cases of psychiatric disorders were observed. Using Group 1 as the reference, the risk of psychiatric disorders decreased significantly across Groups 2-6 with increasing sleep score, reaching the lowest in Group 6 (fully adjusted HR = 0.47, 95% CI: 0.33-0.67). Analyses of specific psychiatric disorders revealed that the inverse associations remained significant after full adjustment, with the most notable effect observed for attention deficit hyperactivity disorder (HR = 0.24, 95% CI: 0.08-0.72). Mediation analysis further identified 16 plasma proteins that exerted significant partial mediating effects in this association.

CONCLUSIONS

Our findings underscore that better sleep quality is associated with a lower risk of psychiatric disorders among individuals with preclinical obesity. The identification of proteomic mediators may provide further insight into the underlying biological mechanisms, highlighting the clinical significance of integrating sleep-related assessment and intervention.