| Title: |
Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction |
| Authors: |
Wright, Alison K; Huang, Tianyi; Carr, Matthew J; Premdayal, Arjun D; Saluja, Sushant; Dashti, Hassan S; Anderson, Simon G; Ray, David W; Jones, Samuel E; Wood, Andrew R; Frayling, Timothy; Weedon, Michael N; Lane, Jacqueline M; Saxena, Richa; Liu, Junxi; Bowden, Jack; Lawlor, Deborah A; Redline, Susan; Rutter, Martin K |
| Source: |
ISSN: 0012-186X ; Diabetologia, vol. 68, no. 11 (2025) p. 2523-2534. |
| Publication Year: |
2025 |
| Collection: |
Université de Genève: Archive ouverte UNIGE |
| Subject Terms: |
info:eu-repo/classification/ddc/576.5; Insomnia; Prediction; Risk assessment; Sleep deprivation; Type 2 diabetes |
| Description: |
Aims/hypothesis: Suboptimal sleep health is linked to higher risks for incident type 2 diabetes. We aimed to assess the clinical utility of adding self-reported sleep traits to a type 2 diabetes prediction model. Methods: In this cohort study, we used UK Biobank data and Cox proportional hazards models to examine how self-reported sleep duration and insomnia symptoms were associated with incident type 2 diabetes risk. Harrell's C statistic and net reclassification improvement (NRI) were used to assess whether sleep traits improved the incident type 2 diabetes discrimination and predictive utility achieved using QDiabetes variables, with and without including a type 2 diabetes polygenic risk score (PGS). Independent replication was explored in the Nurses' Health Study, the Nurses' Health Study II and the Health Professionals Follow-up Study. Results: Extremes of sleep duration and occasional or frequent insomnia symptoms were associated with higher risks for incident type 2 diabetes. In the UK Biobank and replication cohorts, adding sleep traits to the QDiabetes risk score did not improve type 2 diabetes prediction (C statistic: QDiabetes alone 0.8933; QDiabetes + sleep duration 0.8939; QDiabetes + insomnia 0.8931; QDiabetes + sleep traits 0.8935). The corresponding total NRI values were: 0.08 (95% CI -0.18, 0.33), 0.04 (95% CI -0.08, 0.16) and 0.04 (95% CI -0.10, 0.18). Inclusion of PGS data marginally improved the type 2 diabetes risk prediction achieved using The QDiabetes calculator, with or without the inclusion of sleep traits in the model (QDiabetes + PGS: C statistic 0.8945; total NRI 0.20 [95% CI 0.12, 0.28]; QDiabetes + PGS + sleep traits: C statistic 0.8946; total NRI 0.18 [95% CI 0.09, 0.27]). Conclusions/interpretation: While sleep duration and insomnia symptoms were associated with type 2 diabetes risk, they are not useful for improving type 2 diabetes prediction beyond QDiabetes model performance. Inclusion of a type 2 diabetes PGS marginally improved prediction but lacked clear clinical utility. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/pmid/40753283; unige:189672 |
| Availability: |
https://archive-ouverte.unige.ch/unige:189672 |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.229AAA8B |
| Database: |
BASE |