Sleep Patterns, Plasma Metabolome, and Risk of Incident Type 2 Diabetes Mellitus

Author:

Zhuang Zhenhuang1,Dong Xue1,Jia Jinzhu2,Liu Zhonghua3ORCID,Huang Tao145ORCID,Qi Lu67ORCID

Affiliation:

1. Department of Epidemiology & Biostatistics, School of Public Health, Peking University , Beijing 100191 , China

2. Department of Biostatistics, School of Public Health, Peking University , Beijing 100191 , China

3. Department of Biostatistics, Columbia University , New York, NY 10027-6902 , USA

4. Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education , Beijing 100191 , China

5. Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University , Beijing 100191 , China

6. Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University , New Orleans, LA 70118 , USA

7. Department of Nutrition, Harvard T.H. Chan School of Public Health , Boston, MA 02115 , USA

Abstract

Abstract Context A healthy sleep pattern has been related to a lower risk of type 2 diabetes mellitus (T2DM). Objective We aimed to identify the metabolomic signature for the healthy sleep pattern and assess its potential causality with T2DM. Methods This study included 78 659 participants with complete phenotypic data (sleep information and metabolomic measurements) from the UK Biobank study. Elastic net regularized regression was applied to calculate a metabolomic signature reflecting overall sleep patterns. We also performed genome-wide association analysis of the metabolomic signature and one-sample mendelian randomization (MR) with T2DM risk. Results During a median of 8.8 years of follow-up, we documented 1489 incident T2DM cases. Compared with individuals who had an unhealthy sleep pattern, those with a healthy sleep pattern had a 49% lower risk of T2DM (multivariable-adjusted hazard ratio [HR], 0.51; 95% CI, 0.40-0.63). We further constructed a metabolomic signature using elastic net regularized regressions that comprised 153 metabolites, and robustly correlated with sleep pattern (r = 0.19; P = 3×10−325). In multivariable Cox regressions, the metabolomic signature showed a statistically significant inverse association with T2DM risk (HR per SD increment in the signature, 0.56; 95% CI, 0.52-0.60). Additionally, MR analyses indicated a significant causal relation between the genetically predicted metabolomic signature and incident T2DM (P for trend < .001). Conclusion In this large prospective study, we identified a metabolomic signature for the healthy sleep pattern, and such a signature showed a potential causality with T2DM risk independent of traditional risk factors.

Funder

National Key Research and Development Program of China

Publisher

The Endocrine Society

Subject

Biochemistry (medical),Clinical Biochemistry,Endocrinology,Biochemistry,Endocrinology, Diabetes and Metabolism

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