Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction

Alison K Wright; Tianyi Huang; Matthew J Carr; Arjun D Premdayal; Sushant Saluja; Hassan S Dashti; Simon G Anderson; David W Ray; Samuel E Jones; Andrew R Wood; Timothy M Frayling; Michael N Weedon; Jacqueline M Lane; Richa Saxena; Junxi Liu; Jack Bowden; Deborah A Lawlor; Susan Redline; Martin K Rutter

doi:10.1007/s00125-025-06503-6

Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction

Alison K Wright, Tianyi Huang, Matthew J Carr, Arjun D Premdayal, Sushant Saluja, Hassan S Dashti, Simon G Anderson, David W Ray, Samuel E Jones, Andrew R Wood, Timothy M Frayling, Michael N Weedon, Jacqueline M Lane, Richa Saxena, Junxi Liu, Jack Bowden, Deborah A Lawlor, Susan Redline, Martin K Rutter

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Journal	Diabetologia
DOIs	https://doi.org/10.1007/s00125-025-06503-6
Publication status	E-pub ahead of print - 2 Aug 2025

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10.1007/s00125-025-06503-6

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Wright, A. K., Huang, T., Carr, M. J., Premdayal, A. D., Saluja, S., Dashti, H. S., Anderson, S. G., Ray, D. W., Jones, S. E., Wood, A. R., Frayling, T. M., Weedon, M. N., Lane, J. M., Saxena, R., Liu, J., Bowden, J., Lawlor, D. A., Redline, S., & Rutter, M. K. (2025). Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction. Diabetologia. Advance online publication. https://doi.org/10.1007/s00125-025-06503-6

@article{ead66fc31919422084b2622d58bb63aa,

title = "Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction",

abstract = "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.",

author = "Wright, \{Alison K\} and Tianyi Huang and Carr, \{Matthew J\} and Premdayal, \{Arjun D\} and Sushant Saluja and Dashti, \{Hassan S\} and Anderson, \{Simon G\} and Ray, \{David W\} and Jones, \{Samuel E\} and Wood, \{Andrew R\} and Frayling, \{Timothy M\} and Weedon, \{Michael N\} and Lane, \{Jacqueline M\} and Richa Saxena and Junxi Liu and Jack Bowden and Lawlor, \{Deborah A\} and Susan Redline and Rutter, \{Martin K\}",

note = "{\textcopyright} 2025. The Author(s).",

year = "2025",

month = aug,

day = "2",

doi = "10.1007/s00125-025-06503-6",

language = "English",

journal = "Diabetologia",

issn = "0012-186X",

publisher = "Springer Nature",

}

Wright, AK, Huang, T, Carr, MJ, Premdayal, AD, Saluja, S, Dashti, HS, Anderson, SG , Ray, DW, Jones, SE, Wood, AR, Frayling, TM, Weedon, MN, Lane, JM, Saxena, R, Liu, J, Bowden, J, Lawlor, DA, Redline, S & Rutter, MK 2025, 'Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction', Diabetologia. https://doi.org/10.1007/s00125-025-06503-6

TY - JOUR

T1 - Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction

AU - Wright, Alison K

AU - Huang, Tianyi

AU - Carr, Matthew J

AU - Premdayal, Arjun D

AU - Saluja, Sushant

AU - Dashti, Hassan S

AU - Anderson, Simon G

AU - Ray, David W

AU - Jones, Samuel E

AU - Wood, Andrew R

AU - Frayling, Timothy M

AU - Weedon, Michael N

AU - Lane, Jacqueline M

AU - Saxena, Richa

AU - Liu, Junxi

AU - Bowden, Jack

AU - Lawlor, Deborah A

AU - Redline, Susan

AU - Rutter, Martin K

PY - 2025/8/2

Y1 - 2025/8/2

N2 - 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.

AB - 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.

U2 - 10.1007/s00125-025-06503-6

DO - 10.1007/s00125-025-06503-6

M3 - Article

C2 - 40753283

SN - 0012-186X

JO - Diabetologia

JF - Diabetologia

ER -

Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction

Abstract

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